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Home My WebLink About2019.12.31_CCO.p16_ChemoursCorrectiveActionPlan-AppendixF TR0795 December 2019 APPENDIX F Offsite Human Health Screening Level Exposure Assessment (SLEA) of Table 3+ PFAS OFFSITE HUMAN HEALTH SCREENING LEVEL EXPOSURE ASSESSMENT (SLEA) OF TABLE 3+ PFAS Chemours Fayetteville Works Prepared for The Chemours Company FC, LLC 22828 NC Highway 87 W Fayetteville, NC 28306 Prepared by Geosyntec Consultants of NC, PC 2501 Blue Ridge Road, Suite 430 Raleigh, NC 27607 Geosyntec Project Number TR0795 December 2019 TR0795 ii December 2019 TABLE OF CONTENTS 1 INTRODUCTION ................................................................................................ 1 1.1 SLEA Objectives ......................................................................................... 3 1.2 Overview of HFPO-DA ............................................................................... 4 1.3 Document Organization ............................................................................... 5 2 BACKGROUND .................................................................................................. 6 2.1 Facility Description ..................................................................................... 6 2.2 Facility History ............................................................................................ 6 2.3 Climate......................................................................................................... 6 2.4 Topography .................................................................................................. 7 2.5 Cape Fear River and Tributaries .................................................................. 7 2.6 Table 3+ PFAS and Fate and Transport Considerations ............................. 8 3 CONCEPTUAL EXPOSURE MODEL ............................................................. 10 3.1 Offsite Receptor Populations ..................................................................... 10 3.2 Environmental Exposure Media and Routes ............................................. 11 3.3 Complete Exposure Pathways ................................................................... 13 4 IDENTIFICATION OF OFFSITE EXPOSURE UNITS ................................... 15 5 ENVIRONMENTAL DATASETS AND EPCS ................................................ 17 5.1 Soil ............................................................................................................. 17 Soil Data ........................................................................................ 17 Soil EPCs ...................................................................................... 21 5.2 Well Water ................................................................................................. 22 Well Water Data ............................................................................ 22 Well Water EPCs .......................................................................... 23 5.3 Surface Water ............................................................................................ 23 Surface Water Data ....................................................................... 24 Surface Water EPCs ...................................................................... 26 5.4 Fish ............................................................................................................ 27 Fish Tissue Data ............................................................................ 27 Fish Tissue EPCs .......................................................................... 29 5.5 Homegrown Produce ................................................................................. 29 Homegrown Produce Data ............................................................ 29 TR0795 iii December 2019 TABLE OF CONTENTS (CONTINUED) Homegrown Produce EPCs ........................................................... 29 5.6 Data Quality ............................................................................................... 30 6 INTAKE CHARACTERIZATION .................................................................... 32 6.1 Intake Equations and Inputs ...................................................................... 32 6.2 Intake Characterization Results ................................................................. 32 Upland EUs ................................................................................... 33 Cape Fear River and Pond EUs ..................................................... 34 Surface Water Intake Points .......................................................... 34 7 PROVISIONAL HAZARD CHARACTERIZATION....................................... 35 7.1 HFPO-DA Toxicity Criteria ...................................................................... 35 7.2 Hazard Characterization Methods ............................................................. 36 7.3 Hazard Characterization Results ............................................................... 37 8 UNCERTAINTY ASSESSMENT ..................................................................... 39 8.1 Uncertainty in Laboratory Analytical Data ............................................... 39 Detection Limits ............................................................................ 39 8.2 Uncertainty in Exposure Point Concentrations ......................................... 40 Soil Exposure Point Concentrations ............................................. 40 Produce Exposure Point Concentrations ....................................... 41 Drinking Water Exposure Point Concentrations ........................... 42 Surface Water Exposure Point Concentrations ............................. 42 Fish Tissue Exposure Point Concentrations .................................. 43 8.3 Uncertainty in the Exposure Assessment .................................................. 44 Uncertainty in Exposure Media and Routes ................................. 44 Uncertainty in Exposure Assumptions .......................................... 46 8.4 Uncertainty in the Hazard Characterization .............................................. 46 9 CONCLUSIONS ................................................................................................ 49 10 REFERENCES ................................................................................................... 51 TR0795 iv December 2019 LIST OF TABLES Table 1: Table 3+ Constituents Table 2: Classification of Table 3+ PFAS Table 3: Intake Characterization and Provisional Hazard Characterization Summary Table 4: Supplemental Hazard Characterization LIST OF FIGURES Figure 1: Facility Location Figure 2: Conceptual Exposure Model Figure 3: Exposure Units Figure 4: Sampling Locations Evaluated in the SLEA – Soil Figure 5: Sampling Locations Evaluated in the SLEA – Untreated Well Water Figure 6: River Sampling Diagram Figure 7: Sampling Locations Evaluated in the SLEA – Surface Water and Fish Fillets Figure 8: Offsite HFPO-DA Untreated Well Water Concentrations (2017-2019) LIST OF APPENDICES Appendix A: Consent Order Appendix B: Analytical Data Used in the SLEA Appendix C: ProUCL Output Appendix D: ERM Air Modeling Output Appendix E: Modeled HFPO-DA Concentrations in Homegrown Produce Appendix F: Intake and Hazard Calculations TR0795 v December 2019 LIST OF ABBREVIATIONS % Percent ADI Average Daily Intake BAF Bioaccumulation Factor BCF Bioconcentration Factor bgs Below Ground Surface CFPUA Cape Fear Public Utility Authority CFRW Cape Fear River Watch Chemours The Chemours Company FC, LLC CSM Conceptual Site Model DHHS Department of Health and Human Services DQO Data Quality Objective DuPont E.I. du Pont de Nemours and Company DVM Data Verification Module EIM Environmental Information Management system EPC Exposure Point Concentration EU Exposure Unit °F Degrees Fahrenheit Facility Fayetteville Works facility in Bladen County, North Carolina GI Gastrointestinal HDPE High-Density Polyethylene HFPO-DA Hexafluoropropylene Oxide Dimer Acid km Kilometer Kow Octanol-Water Partition Coefficient Kuraray Kuraray America Inc. ISM Incremental Sampling Methodology mg/kg-day Milligram(s) per Kilogram of Body Weight per Day NC North Carolina NC DEQ North Carolina Department of Environmental Quality TR0795 vi December 2019 LIST OF ABBREVIATIONS (CONTINUED) ng/L Nanograms per Liter NPDES National Pollutant Discharge Elimination System Parsons Parsons of NC (Parsons) PFAS Perfluoroalkyl and Polyfluoroalkyl Substances PFO2HxA Perfluoro(3,5-dioxahexanoic) acid PFO4DA Perfluoro(3,5,7,9-tetraoxadecanoic) acid PFO5DA Perfluoro-3,5,7,9,11-pentaoxadodecanoic acid PFOA Perfluoro-n-octanoic acid PFOS Sodium perfluoro-1-octanesulfonate pKa Acid Dissociation Constant PFMOAA Perfluoro-1-methoxyacetic acid PEPA Perfluoroethoxypropyl carboxylic acid PFESA-BP2 Byproduct 2 PMPA Perfluoromethoxypropyl carboxylic acid PPA Polymer Processing Aid PPARα Peroxisome proliferator-activated receptor alpha PVF Polyvinyl Fluoride QA Quality Assurance QC Quality Control RfDo Oral Reference Dose RM River Mile RPD Relative Percent Difference SLEA Screening Level Exposure Assessment SOP Standard Operating Procedure UCL Upper Confidence Limit on the Mean UF Uncertainty Factor USEPA United States Environmental Protection Agency USGS United States Geological Survey TR0795 vii December 2019 EXECUTIVE SUMMARY Geosyntec has prepared this Offsite Human Health Screening Level Exposure Assessment (SLEA) on behalf of The Chemours Company FC, LLC (Chemours) in support of developing a Corrective Action Plan (CAP) for the Chemours Fayetteville Works Facility in Bladen County, North Carolina (the Facility). The overall goal of the SLEA is to refine understanding of the Facility Conceptual Site Model (CSM) in support of developing the CAP, which is accomplished by quantifying potential human intake and noncarcinogenic human health hazard from assumed exposure to Table 3+ per- and polyfluoroalkyl substances (PFAS) in the vicinity of the Facility. Table 3+ PFAS are the PFAS originating from air emissions and past process water releases at the Facility. The SLEA quantifies potential human exposure to the following media: • offsite soil, drinking well water, and homegrown produce within a 10-kilometer radius of the Facility (subdivided into 12 exposure units); • offsite surface water and fish tissue in the Cape Fear River, extending 10 miles upstream and 55 miles downstream of the Facility (subdivided into five [5] exposure units); • surface water and fish tissue from an onsite Facility pond; and • surface water from a private offsite pond. Central tendency and upper-bound exposure point concentrations (EPCs) for soil, well water, surface water and fish fillets were calculated using empirical data whereas EPCs for produce were calculated using approved United States Environmental Protection Agency (USEPA) models. Exposure to soil, well water, and produce was evaluated for adult and child resident, farmer, and gardener populations. Exposure to surface water and fish tissue was evaluated for adult and child recreationalist populations. Potential PFAS intake from each medium was estimated using standard regulatory risk assessment equations that combine media-specific EPCs with conservative, receptor-specific exposure assumptions recommended by USEPA. Total hexafluoropropylene oxide dimer acid (HFPO-DA) intake calculated for each receptor-exposure scenario was compared to the North Carolina Department of Health and Human Services (NC DHHS) 2017 draft oral reference dose (RfDo) to yield a provisional noncarcinogenic human health hazard estimate. Calculated hazards for HFPO-DA for all receptor-exposure scenarios evaluated in the SLEA are less than 1 which, as defined by USEPA, indicates adverse effects to human receptors are unlikely, including sensitive subpopulations. Untreated well water was identified as the primary source of potential PFAS intake and hazard. Additionally, when TR0795 viii December 2019 the SLEA accounts for the effectiveness of the Chemours-provided drinking water treatment systems that are currently in-place, PFAS intake via well water consumption and associated hazards are substantially reduced and may be as low as zero. While other media were not identified as significantly contributing to overall intake and hazard, human exposure to PFAS in environment media will continue to decrease over time as a result of Facility air emissions reductions. TR0795 1 December 2019 1 INTRODUCTION Geosyntec Consultants of NC, PC (Geosyntec) has prepared this Offsite Human Health Screening Level Exposure Assessment (SLEA) of Table 3+ (per- and polyfluoroalkyl substances) PFAS on behalf of The Chemours Company FC, LLC (Chemours) for the Fayetteville Works facility in Bladen County, North Carolina (Facility)1. Table 3+ PFAS, listed in Table 1, have been historically released from process water and air emissions at the Facility; however, Chemours’ process water is currently sent for offsite disposal and air abatement controls being installed are reducing air emissions by 99 percent (%). The purpose of the SLEA is to estimate potential offsite2 human exposures to current conditions, influenced by historically-released or deposited Table 3+ PFAS and in consideration of control technologies being implemented. SLEA exposure estimates are calculated using regional3 concentrations in environmental media in the vicinity of the Facility. The SLEA focuses on hexafluoropropylene oxide dimer acid (HFPO-DA4) while also estimating human exposures to 19 other PFAS presently capable of being analyzed using the Table 3+ standard operating protocol (SOP) method. The SLEA also presents the results of a provisional human health hazard characterization for HFPO-DA based on intakes quantified herein and the North Carolina Department of Health and Human Services (NC DHHS) 2017 draft oral reference dose (RfDo). The content and findings of the SLEA should be reviewed in consideration of the following: • The SLEA drinking water intake and provisional hazard estimates for residences in the vicinity of the Facility are initially calculated based on untreated well water which, in many cases, is not representative of drinking water conditions. Concentrations detected in groundwater are almost entirely the legacy of prior operations, mostly by Chemours’ predecessor, and abatement and remediation measures already taken by Chemours have addressed and essentially abated releases of PFAS from Chemours’ continuing operations at the Facility. As part of the Consent Order implementation, Chemours is required to offer replacement drinking water (in the form of public water or whole building filtration systems) 1 An Ecological SLEA prepared by Geosyntec is being concurrently submitted with this document. 2 Herein, “onsite” and “offsite” are used to distinguish areas within and outside of the Facility boundaries, respectively, as shown in Figure 1. 3 PFAS concentrations and exposures are characterized herein as “regional” on the basis that they do not represent conditions at a specific point of exposure (e.g., pertinent to an individual or discrete residence or from a specific drinking water well). Rather, the SLEA assesses potential intake on the basis of Exposure Units (EUs) arrayed around and radiating from the approximately center-point of the Facility, as well as conditions in the Cape Fear River, proximal to the Facility. 4 HFPO-DA is also referred to as GenX. TR0795 2 December 2019 when private wells have HFPO-DA detected above 140 nanograms per liter (ng/L). For private drinking water wells, when any individual PFAS listed in Consent Order Attachment C, exceeds 10 ng/L or when total PFAS listed in Consent Order Attachment C exceed 70 ng/L, Chemours is required to offer residents or other persons up to three under-the-sink reverse osmosis drinking water systems. Chemours is required to offer temporary replacement water supplies (i.e., bottled water) to those properties qualifying for a filtration or reverse osmosis system until these systems have been provided. As noted above, the SLEA presents the results of a provisional hazard characterization, limited to HFPO-DA. Under Reasonable Maximum Exposure (RME) conditions, even in the absence of treatment, no receptor-specific, cumulative hazards exceed unity (1). The majority of hazard is associated with consumption of untreated drinking water; however, this exercise may be considered hypothetical, as qualifying residents or other persons (as described above) within the Facility zone of influence are provided with alternate or treated water supplies. All post-treatment drinking well water results are non-detect for all Table 3+ PFAS compounds, resulting in (essentially) zero drinking water-associated hazards. Intake and hazard estimates based on assumed HFPO-DA concentrations of 10 ng/L (the maximum concentration not qualifying for treatment) are up to two orders of magnitude lower than those calculated based on untreated well water reducing hazard estimates from being consistently less than 1 to consistently less than 0.1. • Chemours is acting to reduce air emissions of PFAS from the Facility, including installation of a thermal oxidizer that will dramatically reduce aerial PFAS emissions from the Site, with reduction of aerial HFPO-DA emissions by 99% starting in January 2020 compared to 2017 baseline, and expected comparable reductions for other PFAS. This is relevant since Table 3+ PFAS in offsite media originate from aerial deposition stemming from Facility emissions to air, which are described in the On and Offsite Assessment Report (Geosyntec, 2019c). Based on this, the present concentrations of offsite PFAS are expected to diminish over time through natural attenuation. Current conditions therefore, represent the highest expected concentrations in receiving media with future exposure diminishing over time. With a reduction in air emissions, associated soil and groundwater concentrations will attenuate over time, as will contributions to other receiving media, such as surface water and recreational fish species. Additionally, Chemours’ process water is being sent for offsite disposal, eliminating a pathway that historically contributed PFAS to the river. • The SLEA sampling, analyses, and evaluation methods were developed to provide screening-level estimates of intake and potential human health hazard to offsite populations. Like any regulatory risk assessment, the hazard estimates are not TR0795 3 December 2019 predictive of any health outcome. Rather, the findings are intended to further support refining the existing conceptual site model (CSM) by using measured concentrations of Table 3+ PFAS in the environment to identify sources and transport mechanisms that are the most likely to result in potentially complete exposure pathways for human receptors and rank these pathways based on potential intake. This information can then be used to focus future evaluations on pathways that are relevant to informing risk management decisions and excluding pathways that, albeit complete, are likely insignificant relative to overall exposure. This SLEA considers relevant exposure scenarios under future potential conditions where Consent Order required air emission reduction targets have been achieved. 1.1 SLEA Objectives The objectives of the SLEA are as follows: 1. Develop representative exposure point concentrations (EPCs) for HFPO-DA and other Table 3+ PFAS in offsite environmental media. 2. Develop estimates of average intake of HFPO-DA and other Table 3+ PFAS from relevant exposure pathways for potential human receptor populations in the vicinity of the Facility. 3. Develop estimated ranges of potential associated human health hazard, predicated on intake estimates by pathway and receptor population5. 4. Identify and evaluate uncertainties associated with limitations in environmental data, and exposure assumptions in the context of the results of the SLEA intake and hazard characterizations to support site management decisions. The methodology used in this assessment is consistent with North Carolina risk assessment practices and the United States Environmental Protection Agency’s (USEPA) Guidelines for Exposure Assessment (USEPA, 1992) and Draft Guidelines for Human Exposure Assessment (USEPA, 2016). The SLEA also supports the Groundwater Corrective Action Plan (CAP) required by Paragraph 16 of the executed Consent Order entered into court on February 25, 2019 and 5 The SLEA hazard characterization uses the draft RfDo developed by the NC DHHS (2017), which underpins the State’s provisional health goal for HFPO-DA in drinking water. The SLEA uncertainty assessment evaluates the implications for use of alternative toxicity criteria, such as the probabilistic RfDo developed by Thompson, et al. (2019) and the USEPA’s draft RfDo (USEPA, 2018a). See Section 8.4. TR0795 4 December 2019 signed by Chemours, the North Carolina Department of Environmental Quality (NCDEQ), and the Cape Fear River Watch (CFRW). 1.2 Overview of HFPO-DA HFPO-DA is a human-made chemical produced at the Chemours Fayetteville Works facility in Bladen County, North Carolina. HFPO-DA is a six carbon, branched PFAS containing an ether bond (i.e., an oxygen atom linking two carbon atoms). HFPO-DA6 is a clear, colorless liquid completely miscible with water (i.e., infinite solubility in surface water, groundwater, rainwater, leachate) and low octanol-water partitioning capacity (empirically estimated logKow of 4.24)7. Under normal environmental conditions, HFPO- DA exists as an anionic acid (2.8 acid dissociation constant [pKa])8 (Hoke et al., 2016). Biodegradability test data (DuPont-A080558; Kaplan, 2010) indicate HFPO-DA is not readily biodegradable, with a half-life in soil, water, air, and sediment greater than 6 months (USEPA, 2018a). As such, HFPO-DA is expected to be relatively stable and persistent in the environment, and resistant to photolysis and hydrolysis (undergoing very slow hydroxyl radical catalyzed indirect photolysis). Measured bioconcentration factors (BCFs) and bioaccumulation factors (BAFs) suggest that HFPO-DA has a low potential to bioaccumulate in biota. Multiple fish studies have confirmed BCFs of less than 3 and 30, based on exposure to 200,000 and 20,000 ng/L, and BCFs of 1 for higher concentrations (DuPont-A080560 2009; Hoke et al., 2016; Goodband, 2019). A recent study suggests that HFPO-DA does not have the capacity to bioaccumulate in some benthic fish species, based on treated food consumption over a 21-day exposure period (Hassell et al., 2019). Log BAFs calculated for carp were 0.86 for blood, 0.5 for liver and 0.61 for muscle. Tissue values indicate a BAF of less than 10 (Pan et al., 2017). 6 HFPO-DA is used here to refer to: 2,3,3,3-tetrafluoro-2-(1,1,2,2,3,3,3-heptafluoropropoxy)-propanoic acid (CASN 13252-13-6), which has the chemical formula C6HF11O3. 7 Kow is the octanol-water partitioning coefficient, the ratio of the equilibrium concentration of a dissolved chemical in a two-phase system of n-octanol and water. n-Octanol serves as a surrogate to biota lipids and Kow is used as an indicator of a chemical’s tendency to bioaccumulate in organisms. 8 The pKa predicts that HFPO-DA will be in acid form (as a negative ion, or an anion) at a pH ≥ 2.8. TR0795 5 December 2019 1.3 Document Organization This document is organized as follows: • Section 1, Introduction, presents the objectives of the SLEA and provides an overview of the Table 3+ PFAS. • Section 2, Background, summarizes conditions in offsite areas in the vicinity of the Facility, focusing on those that are relevant to developing a CSM and conceptual exposure model (CEM). • Section 3, Conceptual Exposure Model, identifies potentially complete exposure pathways by which human receptors may come into contact with Table 3+ PFAS in the environment. • Section 4, Identification of Offsite Exposure Units, describes the organization of exposure units evaluated in the SLEA and the rationale for their identification. • Section 5, Environmental Datasets and Exposure Point Concentrations, summarizes the data evaluated in the SLEA, including the sampling and analysis methods for data collection, and describes how data are used in the SLEA to quantify potential human exposure. • Section 6, Intake Characterization, summarizes the methods for quantifying human exposure and compares the calculated intakes by exposure media for relevant populations and associated complete exposure pathways. • Section 7, Provisional Hazard Characterization, presents a description of the methods and toxicological criteria used to derive estimated human health hazard quantitative point estimates for relevant populations and associated complete exposure pathways, related to HFPO-DA. • Section 8, Uncertainty Assessment, identifies key uncertainties in the SLEA. • Section 9, Conclusions, summarizes the findings of the SLEA. • Section 10, References, presents the references used in the development of the SLEA Report. TR0795 6 December 2019 2 BACKGROUND The following section describes the physical setting and operational history of the Facility, as well as fate and transport considerations for HFPO-DA. 2.1 Facility Description The Facility is located within a 2,177-acre property at 22828 NC Highway 87, approximately 15 miles southeast of the city of Fayetteville, NC along the Bladen- Cumberland county line. Figure 1 presents an overview of the Facility location and features. The Facility is bounded by NC Highway 87 to the west, the Cape Fear River to the east, and by undeveloped areas and farmland to the north and south. Willis and Georgia Branch Creeks, which are tributaries of the Cape Fear River, are located near the northern and southern property boundaries respectively, with the Georgia Branch Creek being offsite for its entire course (Geosyntec, 2019a). 2.2 Facility History The Facility property was originally purchased by E.I. du Pont de Nemours and Company (DuPont) in 1970 and the first manufacturing area was constructed shortly thereafter. A former manufacturing area, used to produce nylon strapping and elastomeric tape, was sold in 1992. DuPont sold its Butacite® and SentryGlas® manufacturing units to Kuraray America Inc. (Kuraray) in June 2014 and subsequently spun off its specialty chemicals business into Chemours in July 2015. Presently, the Facility consists of five manufacturing areas used to produce specialty fluorinated monomers, the intermediates and starting materials thereof, fluorinated polymer initiators and processing aids, fluorinated polymer resin, polymer sheeting, and manufactured products. The five manufacturing areas shown in Figure 1 include: Chemours Monomers IXM; Chemours Polymer Processing Aid (PPA); Kuraray Trosifol®; Kuraray SentryGlas®; and DuPont Company polyvinyl fluoride (PVF) resin manufacturing unit. In addition to the manufacturing operations, Chemours operates two natural gas-fired boilers and a wastewater treatment plant, which treatment includes sanitary wastewaters from Chemours, Kuraray, and DuPont and process wastewaters from Kuraray and DuPont (Geosyntec, 2019a). Hazardous waste generated during manufacturing activities are managed at the Hazardous Container and Storage Area prior to shipment offsite for treatment, disposal, or recycling (Parsons, 2014). 2.3 Climate The climate in Bladen County is characterized by relatively mild winters, hot summers, and abundant rainfall. According to the National Weather Service, average monthly temperatures range from a high of 91 degrees Fahrenheit (°F) in July to a low of 33°F in TR0795 7 December 2019 January. Average monthly rainfall ranges from a high of 5.92 inches in July to a low of 2.65 inches in December (Parsons, 2014). 2.4 Topography The developed portion (manufacturing area) of the Facility is located on a relatively flat topographic plateau at an approximate elevation of 145 feet above mean sea level and approximately 70 feet above the Cape Fear River floodplain. Surface topography generally remains flat to the west with a gentle increase of about 5 feet to a topographic divide near NC Highway 87. However, ground surface elevations decrease from the topographic plateau at the manufacturing area towards the Cape Fear River to the east as well as its tributaries, Willis Creek to the north and Georgia Branch Creek to the south. Topographic relief from the main manufacturing area decreases by approximately 100 feet in elevation towards the Cape Fear River bank to the east. Inclined topographic relief combined with overland flow and groundwater seeps have created natural drainage networks into the Cape Fear River (Geosyntec, 2019a). 2.5 Cape Fear River and Tributaries The Cape Fear River and its entire watershed are located in the state of North Carolina. The Cape Fear River drains 9,164 square miles and empties into the Atlantic Ocean near the city of Wilmington, NC. The Facility is situated on the western bank of the Cape Fear River; it draws water from the Cape Fear River and historically returned over 95% of this water via Old Outfall 002 (now discontinued) after being used primarily as non-contact cooling water. Two lock and dam systems with United States Geological Survey (USGS) stream gauges are located downstream of the Facility: (1) W.O. Huske Lock and Dam, located 0.5 river miles downstream from the Facility (USGS 02105500); and (2) Cape Fear Lock and Dam #1, located 55 river miles downstream (USGS 02105769). There are three perennial surface water features that are tributaries to the Cape Fear River at or adjacent to the Facility. To the north of the Facility is Willis Creek. To the south of the Facility is Georgia Branch Creek which confluences with the Cape Fear River approximately 7,500 feet south of the W.O. Huske Dam. Old Outfall 002, which currently conveys only surface water and groundwater to the Cape Fear River, is approximately 1,350 feet south of the W.O. Huske Dam (Geosyntec, 2019a). Additionally, in January 2019 three groundwater seep features were identified on the bluff slope leading from the Facility to the Cape Fear River. These seeps represent groundwater exiting the aquifer and forming channelized flows of water to the Cape Fear River. TR0795 8 December 2019 2.6 Table 3+ PFAS and Fate and Transport Considerations Onsite PFAS were released historically from the Facility from aerial emissions with resulting deposition and from direct process water releases to groundwater. Offsite soil and groundwater PFAS are solely from aerial emission releases based on an analysis of both groundwater flow directions (offsite residential areas are hydraulically isolated or upgradient of process water release areas) and PFAS signatures (Geosyntec, 2019c). In turn, constituents in soil may have contributed to constituents in groundwater through leaching and infiltration of the vadose zone and to vegetation through root uptake. Table 3+ PFAS constituents in surface water may have arisen through aerial deposition, discharge of Facility wastewaters, stormwater/surficial runoff during precipitation events, or discharge from groundwater to receiving surface water bodies at the groundwater- surface water interface. Surface water concentrations may have contributed to fish tissue concentrations through bioconcentration. Table 3+ PFAS, including HFPO-DA, have been detected in soils on- and offsite, in groundwater on- and offsite, in surface water on- and offsite, and in offsite biota. Sources of PFAS for the various environmental media examined in this SLEA are summarized in the table below. Environmental Media Aerial Emissions and Deposition Process Water Releases Cape Fear River   Offsite Soil  -- Offsite Groundwater  -- Offsite Terrestrial Vegetation  -- Offsite Biota (e.g., fish) Uptake and Bioconcentration from Surrounding Media Pursuant to Consent Order Paragraph 27, Chemours funded a study analyzing the fate and transport of identified PFAS originating from the Facility in air, surface water, and groundwater (Geosyntec, 2019d). The findings of the study are summarized below. PFAS are a group of man-made carbon-based chemicals composed of a fully or partially fluorinated chain of carbon atoms (referred to as a “tail”) and a nonfluorinated, polar functional group (referred to as a “head”) at one end of the carbon chain. Fluorination of the carbon chain renders it hydrophobic and lipophobic, while the polar head group is hydrophilic (Mueller and Yingling, 2018). Generally, PFAS vapor pressures are low and water solubilities are high. Most PFAS have one or more negatively charged head groups, TR0795 9 December 2019 so they are likely to be relatively mobile in the subsurface due to the affinity of the head group for water molecules (Mueller and Yingling, 2018). Most Table 3+ PFAS, are fluoroethers: their structure includes two carbons connected by an oxygen atom – an ether bond. PFAS with ether bonds are expected to be less volatile and more soluble than non-ether PFAS of equivalent chain length due to the polar oxygen atoms included in their structures. Table 3+ PFAS contain at least one polar head group and many also contain additional polar head groups. The structural information for the Table 3+ PFAS is provided in Table 2. Generally, Table 3+ PFAS are expected to be mobile in the environment given the presence of charged head groups and ether bonds, but they will experience some retardation. For some Table 3+ PFAS, mobility may be enhanced relative to straight- chain, non-ether PFAS by their branched structure and the presence of two charged head groups. The mobility of the Table 3+ PFAS will be retarded by various chemical processes but will likely have lower retardation than long-chain PFAS without ether bonds. Chemical processes expected to have the most impact on mobility are sorption to organic carbon and, in the unsaturated soil zone, preferential partitioning to the air water interface. The tails of PFAS are made primarily of carbon atoms. They tend to be nonpolar, and so they tend to sorb to organic carbon species in soil and sediment (Higgins and Luthy 2006, Guelfo and Higgins, 2013). Because PFAS tails are also lipophobic, sorption to organic carbon tends to be weaker than that of alkanes. The sorption and retardation of PFAS will increase with increasing fluorinated tail length. For a given soil, sediment, or organic carbon type, the structure of the PFAS tail affects its interactions with organic carbon molecules. Branched isomers tend to have lower sorption affinity than linear isomers of equal chain length (Kärrman et al., 2011). Sorption of PFAS to charged particle surfaces in common soils and sediments is expected to be negligible relative to sorption to particulate organic carbon (Higgins and Luthy, 2006). Current literature indicates that transformation of most PFAS in the environment is negligible. An important observed environmental transformation of PFAS has been the hydrolysis of some polyfluorinated precursors to form perfluorinated compounds (Mueller and Yingling, 2018) and the biotic degradation of trifluoroacetate (e.g., Visscher et al., 1994). Recently, researchers identified an Acidimicrobium microbial species that appears capable of defluorinating select PFAS (Huang and Jaffe, 2019). The ether and carbon-hydrogen bond components of the Table 3+ PFAS may be amenable to transformation reactions that degrade the tails of these compounds (e.g., Weber et al., 2017). TR0795 10 December 2019 3 CONCEPTUAL EXPOSURE MODEL Development of a CEM [conceptual exposure model] is recommended by USEPA (USEPA, 1989) to support interpretation of environmental data and inform site management decisions. The SLEA CEM identifies potentially complete exposure pathways by which human receptors could come in contact with Table 3+ PFAS in environmental media within the offsite Study Area. For an exposure pathway to be complete, the following five elements are necessary: • a source or release from a source; • a mechanism of release and transport; • an exposure medium (i.e., point of contact) for potential receptors; • an exposure route (e.g., ingestion); and, • the presence of a receptor population (e.g., residential adult and child). If an element of the CEM is missing, the exposure pathway is considered incomplete. For the purposes of the SLEA, source and release/transport mechanism(s) for PFAS are presumed to exist. As such, the SLEA focuses on characterizing exposure media, exposure routes, and human receptors for Table 3+ PFAS. Generally, intake of Table 3+ PFAS is only quantified for complete pathways but, in some instances for the purpose of informing site management decisions, intake is also quantified for pathways that are not reasonably anticipated to be complete (e.g., due to current or planned implementation of institutional controls). The human health CEM is diagrammatically presented in Figure 2 and its elements are described below. The CEM reflects the current understanding of fate and transport mechanisms and exposure conditions in the vicinity of the Facility but may be updated as new information becomes available. 3.1 Offsite Receptor Populations The Facility property encompasses 2,177 acres of relatively flat, undeveloped open land and woodland bounded by the Cape Fear River on the east, NC Highway 87 on the west, Willis Creek on the north, and farmland on the south (Figure 1). Based on the current Facility setting, including surrounding land uses, potential receptors for evaluation in the SLEA and the rationale for their inclusion are summarized below: • Residents (Adult and Child). The nearest residence is approximately 1 km north of Facility manufacturing areas. North and northwest of the Facility, several residential neighborhoods occur within 5 km of the Facility. TR0795 11 December 2019 • Farmers (Adult and Child). Farmers were identified as potential receptors based on the predominance of agricultural land use to the east, south, and west of the Facility. • Gardeners (Adult and Child). Residents and farmers may garden on their properties to grow homegrown produce for personal consumption. • Offsite workers (Adults only). Although residential and agricultural land uses predominate the areas surrounding the Facility, some commercial businesses are also present. • Recreationalists (Adult and Child). The Cape Fear River may be used for recreational purposes, including canoeing and swimming. • Recreational anglers (Adult and Child). The Cape Fear River and regional private ponds and lakes may be used for recreational purposes, including fishing. 3.2 Environmental Exposure Media and Routes The SLEA focuses on evaluating the relative potential for intake based on direct and indirect contact with Table 3+ PFAS detected in environmental media from air deposition and from historical process water releases (i.e., via outfall releases and/or via migration of groundwater to Cape Fear River surface water adjacent to and downstream of the Site). This SLEA also considers ongoing and future stack emissions in light of stack control technologies, for instance the Thermal Oxidizer control technology is scheduled to be operational by December 31, 2019. Environmental investigations have detected Table 3+ PFAS in soil, groundwater, surface water, plants (non-edible), and fish in the vicinity of the Facility. Potential exposure media and routes evaluated in the SLEA are summarized below. Unless otherwise noted below, these media-specific complete exposure pathways are quantitatively evaluated herein. It is important to note that these are hypothetical exposure scenarios developed to evaluate the potential for exposure; in reality, some (or all) of these assumed exposure pathways may be incomplete for specific receptor populations. • Offsite Surface Soil. Stack and fugitive process emissions to ambient air have resulted in historically-deposited PFAS in offsite soils, based on dispersion and deposition processes. The projected 99% reduction in Facility-wide air emissions of “GenX compounds” (as defined in the Consent Order) will significantly reduce continuing contribution to offsite surface soil and associated concentrations are expected to attenuate over time. Offsite residents, farmers, gardeners, and workers are assumed to be directly exposed to surface soil via incidental ingestion and dermal contact. As described in Section 8.3.1, dermal absorption studies with HFPO-DA indicate exposure via the dermal pathway is unlikely to be significant TR0795 12 December 2019 (DuPont-25292, 2008); as such, dermal exposure to surface soil is discussed as part of the uncertainty assessment. Soil intake by offsite commercial workers is likely to be lower than that of other offsite populations (e.g., residents, farmers, and gardeners); therefore, offsite worker exposure to soil is qualitatively evaluated in the uncertainty assessment based on the results of receptors with greater exposure potential. • Offsite Subsurface Soil. Table 3+PFAS present in offsite subsurface soils originate from aerial deposition followed by downward infiltration through the vadose zone (unsaturated zone). For most receptors, the potential for direct exposure to subsurface soil is incomplete and, relative to surface soil, would likely be insignificant. Therefore, surface soil conditions are relevant to informing risk management decisions. As such, direct contact with subsurface soil is semi- quantitatively evaluated as component of the SLEA uncertainty assessment. • Offsite Groundwater. Table 3+ PFAS present in offsite groundwater originate from historically-deposited PFAS which have infiltrated from soils to groundwater. Table 3+ PFAS have been detected in groundwater used for drinking water in private wells within the vicinity of the Facility. Offsite residents, farmers, gardeners, and workers using well water for potable purposes are assumed to be exposed to historically-deposited PFAS via ingestion and dermal contact. Due to their limited dermal absorption efficiency (see Section 8.3.1), exposure to PFAS in water via dermal contact is considered an insignificant exposure pathway and, therefore, associated intake is qualitatively evaluated as a component of the uncertainty assessment. Irrigation-related contact represents a significantly lessened degree of exposure when compared to more frequent drinking water use. Thus, irrigation-related exposures are qualitatively evaluated as a component of the uncertainty assessment. • Surface Water. Table 3+ PFAS present in offsite surface water, excluding Willis Creek and the Cape Fear River, stem from offsite aerial deposition, precipitation runoff, and groundwater discharge at the groundwater-surface water interface transporting historically-deposited PFAS to surface water bodies. Willis Creek and the Cape Fear River also include contributions from onsite, direct release sources (e.g., outfalls). Recreationalists have the potential to be exposed to Table 3+ PFAS in surface water (e.g., ponds and creeks near the Facility, Cape Fear River) via incidental ingestion and dermal contact (e.g., swimming, canoeing). Approximately 8 and 55 miles downstream of the Facility, respectively, surface water from the Cape Fear River is withdrawn and treated for use as drinking water at the Bladen Bluffs and Kings Bluff water treatment facilities. Offsite residents, farmers, gardeners, and workers are assumed to use TR0795 13 December 2019 untreated Cape Fear River water collected from the intake points for potable purposes and, therefore, are assumed to be exposed to Table 3+ PFAS via ingestion and dermal contact. As with well water exposure scenarios, dermal contact intakes for surface water as a function of domestic water supply are insignificant and are qualitatively evaluated in the uncertainty assessment. Offsite worker exposure to surface water as drinking water is also qualitatively evaluated. • Terrestrial Biota. Invertebrates and other terrestrial biota may potentially assimilate PFAS from soil or, in the case of plants, from soil, pore water, and wet and dry deposited particulates, by extension. As such, farmers and gardeners are assumed to be indirectly exposed to Table 3+ PFAS via consumption of plants and livestock. The SLEA quantitatively evaluates plant intake using biouptake models from the USEPA (2005); other consumable terrestrial biota (i.e., agricultural livestock and game species) are qualitatively evaluated as part of the uncertainty assessment. • Fish Tissue. Aquatic species in the Cape Fear River and surrounding surface water bodies (e.g., local ponds) may assimilate PFAS from sediment, surface water, or food/prey items. As such, recreational anglers are assumed to be indirectly exposed to Table 3+ PFAS via consumption of fish fillets. 3.3 Complete Exposure Pathways Receptor-exposure scenarios developed for the SLEA to quantitatively evaluate intake of historically-released Table 3+ PFAS from soil, homegrown produce, untreated well water, untreated surface water, and fish tissue are summarized below. For the well water- as-drinking water scenarios, a “current conditions” exposure was also quantified, which considered the requirements of the Consent Order for providing replacement drinking water and treatment systems. As noted above, these exposure pathways are assumed to be complete for the purposes of the SLEA but some or all related exposure pathways may be incomplete for an actual offsite receptor. For example, the SLEA assumes gardeners and farmers only consume fruits and vegetables that are homegrown whereas, in reality, most people also (or exclusively) consume store-brought fruits and vegetables grown in a variety of locations. • Residents (Adult and Child): Surface soil via incidental ingestion; untreated well water as drinking water via ingestion; current conditions well water as drinking water via ingestion; and untreated Cape Fear River surface water from Bladen and Kings Bluff as drinking water via ingestion. Soil and drinking water exposure assumptions for residents are presented in Attachment F, Table F-2-1. TR0795 14 December 2019 • Farmers (Adult and Child): Surface soil via incidental ingestion; untreated well water as drinking water via ingestion; current conditions well water as drinking water via ingestion; and, aboveground leafy vegetables (e.g., lettuce), aboveground fruits (e.g., tomatoes), and belowground vegetables (e.g., carrots) via ingestion. Soil, produce, and drinking water exposure assumptions for farmers are presented in Attachment F, Table F-2-2. • Gardeners (Adult and Child): Surface soil via incidental ingestion; untreated well water as drinking water via ingestion; current conditions well water as drinking water via ingestion; and, aboveground leafy vegetables (e.g., lettuce), aboveground fruits (e.g., tomatoes), and belowground vegetables (e.g., carrots) via ingestion. Soil, produce, and drinking water exposure assumptions for gardeners are presented in Attachment F, Table F-2-3. • Recreationalists (Adult and Child): Untreated surface water via incidental ingestion. Surface water exposure assumptions for recreationalists are presented in Attachment F, Table F-2-4. • Recreational Anglers (Adult and Child): Fish tissue fillets via ingestion. Fish consumption exposure assumptions for Recreational Anglers are presented in Attachment F, Table F-2-5. Additionally, the uncertainty assessment (Section 8.3.1) includes a qualitative or semi- quantitative evaluation of Table 3+ PFAS intake for: (i) direct exposure to subsurface soil by residents, farmers, and gardeners; (ii) use of groundwater as irrigation water by farmers and gardeners; (iii) consumption of livestock by farmers; (iv) direct exposure to surface soil and use of untreated well water and surface water as drinking water by offsite workers; and (v) dermal contact with soil, groundwater, and surface water by relevant receptors. TR0795 15 December 2019 4 IDENTIFICATION OF OFFSITE EXPOSURE UNITS The selection of SLEA exposure units (EUs) was premised on the concept that, based on aerial dispersion and deposition as well as direct discharge of waste and process waters, concentrations of Table 3+ PFAS in environmental media are likely to attenuate with distance from the Facility, particularly for well water and soil which are the primary offsite exposure media of interest. As such, the offsite study area was conceptualized as three concentric circles originating from the approximate center-point of the Facility that correspond to radial distances of 2.5, 5, and 10 km. These concentric circles were then bisected north-to-south and east-to-west to subdivide the offsite study area into northeast, southeast, southwest, and northwest quadrants. Additionally, the northeast direction quadrant corresponds to the dominant wind direction (ERM, 2018) and the EUs that comprise this quadrant (EUs 1, 5, and 9) capture the areas of likely highest historical aerial deposition to soil. Therefore, as shown in Figure 3, the upland EUs evaluated in the SLEA are: • EU1: 2.5-km radius, northeast; • EU2: 2.5-km radius, southeast; • EU3: 2.5-km radius, southwest; • EU4: 2.5-km radius, northwest; • EU5: 5-km radius, northeast; • EU6: 5-km radius, southeast; • EU7: 5-km radius, southwest; • EU8: 5-km radius, northwest; • EU9: 10-km radius, northeast; • EU10: 10-km radius, southeast; • EU11: 10-km radius, southwest; and • EU12: 10-km radius, northwest. The Cape Fear River was also subdivided into multiple EUs, where: • EU13: upstream locations; • EU14: Facility-adjacent locations; • EU15: locations approximately 4 miles downstream of the Facility; TR0795 16 December 2019 • EU16: locations approximately 8 miles downstream of the Facility at Bladen Bluffs; and • EU17: locations approximately 55 miles downstream of the Facility at Kings Bluffs. Additionally, two ponds were designated as EUs: • EU18: Pond 1 located in the northwest corner of the Facility; and • EU19: Pond B located approximately 1 mile east-southeast of the Facility, on the east side of the Cape Fear River. For each upland EU (EU1 through EU12), exposure to surface soil, untreated well water, current conditions well water (i.e., in consideration of the Consent Order requirements for replacement drinking water and treatment systems), and produce is quantitatively evaluated. For each Cape Fear River EU and the two Pond EUs, exposure to surface water is quantitatively evaluated. Fish tissue consumption is quantitatively at the Cape Fear River EUs 13 through 16 and onsite Pond 1 (EU18); fish tissue was not collected at Kings Bluffs (EU17) or offsite Pond B (EU19). Additionally, residential consumption of untreated surface water collected at the public water supply intakes located at Bladen Bluffs and Kings Bluffs, is quantitatively evaluated within the context of the SLEA. TR0795 17 December 2019 5 ENVIRONMENTAL DATASETS AND EPCS This section describes the SLEA datasets and EPC calculation methods. Media-specific EPCs are used to quantify intake as described in Section 7. Analytical datasets evaluated in the SLEA are presented in Appendix B. Datasets for soil and fish tissue consist of samples collected between July and September 2019 per the SLEA Work Plan (Geosyntec 2019e). The dataset for surface water consists of samples collected between September 2017 and October 2019, including data collected per the SLEA Work Plan and downstream data reported by the NCDEQ and CFPUA. The SLEA relies upon well water data collected as part of ongoing offsite monitoring, using recent data collected between 2017 and 2019 to quantify potential intake. EPCs were calculated on an EU-specific basis. When possible, EPCs based on the mean and 95% UCL concentrations are evaluated to provide a range of potential intake estimates where these EPCs are referred to herein as the central tendency exposure (CTE) and reasonable maximum exposure (RME), respectively. The mean and UCL concentrations were calculated using ProUCL Version 5.1; ProUCL outputs are provided as Appendix C. Media-specific considerations for EPC calculation are discussed in the subsections below. 5.1 Soil The SLEA characterizes potential Table 3+ PFAS intake from exposure to offsite soil using data collected between July and September 2019. The goal of the soil sampling investigation was to characterize regional soil conditions in surficial and subsurface depth intervals for each of the 12 EUs, defined in Section 4 (Figure 3). The EUs were arrayed by quadrant and proximity, extending to a distance of 10 km from the approximate center- point of the Facility such that they range in size and include units that are very large (e.g., EUs 9, 10, 11, and 12). Soil datasets are described in Section 5.1.1. Soil EPCs are described in Section 5.1.2. Soil Data Surface soil is defined as 0 to 6 inches below ground surface (bgs). Surface soil sampling was conducted in consideration of ITRC’s incremental sampling methodology (ISM), NCDEQ’s recommendations for collecting composite soil samples from large areas without visible contamination (NCDEQ, 2015), and accessibility. In each EU, 30 discrete soil aliquots were collected and aggregated into a single composite sample submitted for laboratory analysis that is considered representative of the EU. A composite sampling approach was selected because it enables a more complete assessment of a large study area where discrete sampling was impractical (e.g., representativeness, coverage, TR0795 18 December 2019 schedule). The resulting EPC is considered characteristic of regional conditions and exposures within a given EU; however, as discussed further in the uncertainty assessment, it is acknowledged that composite sample EPCs may not be representative of a specific receptor’s exposure. Prior to field mobilization and in consideration of ISM guidance, each EU was gridded via ordinary or area-of-influence kriging to define 30 random sampling locations, or nodes. Areas that the project team knew to be inaccessible were excluded from the grid. Additional modifications to the sampling locations were necessary in the field due to access limitations, including lack of property owner consent, health and safety concerns, and physical barriers to access (e.g., dense vegetation). As a result, most sampling locations were selected in the field. Due to access limitations in the field, the majority of private property-based locations were excluded through potential lack of consent. Chemours was able to secure access to public rights-of-way through the NC Department of Transportation. As a result, some EUs reflect right-of-way-only data sampling locations. Sampling locations were recorded via global positioning system and are shown in Figure 4. Surface soil aliquots were collected from 0 to 6-inches bgs using stainless steel bowls and spoons. Consistent with the SLEA Work Plan, individual surface soil sample aliquots were collected from 30 locations in each EU and were homogenized in the field and composited into a single sample for laboratory analysis, for a total of 12 surface soil samples. Subsurface soil samples were collected from a depth of 4 to 4.5 feet bgs using stainless steel hand augers. One discrete subsurface soil sample was collected from each EU for a total of 12 subsurface soil samples. In EUs 5, 7 and 8, the subsurface sampling location was selected at random from the 30 surface sampling locations. For the remaining EUs, collection of the subsurface soil sample was coordinated with installation of a groundwater monitoring well. For these EUs, the subsurface soil grab sample was preferentially collected from the borehole (and so is not paired with a discrete surface soil aliquot represented in the composite sample). In any case, for each EU, 30 surface soil aliquots were composited into one sample for laboratory analysis and one discrete subsurface soil sample was submitted for laboratory analysis. Although the subsurface soil sample is a discrete grab sample, there are no significant concerns in comparison to the composite-based surface soil sample, on an individual EU basis. Subsurface soil direct contact is not a basis for quantitative evaluation in the exposure assessment, as the potential for direct contact exposure is significantly reduced when compared to surface soil complete exposure pathways. The subsurface soil sample provides an indication of the significance of vadose zone leaching potential but is not a significant line of evidence for use in predicting groundwater concentrations, as direct TR0795 19 December 2019 measurements in groundwater are available. As such, the subsurface soil data are not used to quantitatively assess leaching to groundwater. Field personnel collected quality assurance/quality control (QA/QC) samples (i.e., duplicates, matrix spikes/matrix spike duplicates, and equipment blanks); however, in the interests of performing this SLEA in a timeframe capable of supporting the development of a CAP by December 31, 2019, replicate samples were not collected. Composited surface soil samples and discrete subsurface soil samples were shipped under chain of custody to a TestAmerica analytical laboratory for analysis of Table 3+ PFAS per the SOP. In Figure 4, surface soil sampling locations are shown, grouped by EU and presented in uniform color. Subsurface soil sampling locations are shown in white, irrespective of EU. As discussed above, 30 individual surface soil aliquots were composited into one composite sample for laboratory analysis. In three EUs (EUs 5, 7 and 8), Chemours collected a subsurface soil sample (4-4.5 ft bgs), co-located with a surface soil aliquot; these locations are designated by a crosshatched white circle in Figure 4. For the remaining EUs, Chemours collected a discrete subsurface soil sample (4-4.5 ft bgs), based on access, clearance, and the installation of a groundwater monitoring well. Specific sampling location outcomes are discussed, below: • EU1: 2.5-km radius, Northeast Quadrant. Thirty surface soil aliquots were collected. Based on access restrictions in offsite areas, sampling coverage in EU1 was evenly split between three residential properties adjacent to Marsh Wood Lake and a public access roadway in the eastern portion of the EU. Fifteen surface soil samples were collected in the southeast corner of this EU, along a public roadway. Fifteen additional samples were collected from three private residential yards (five samples per residence) located adjacent to Marsh Wood Lake. A discrete subsurface soil sample (4-4.5 ft bgs) was collected from one of these residences, coincident with the installation of a monitoring well. The predominant air depositional pattern extends from the Facility to the northeast. The three residences adjacent to Marsh Wood Lake occur along this vector. A lower potential for deposition is associated with the sampling points in the southeast corner of EU1, providing a mix of representative soil conditions. The central area of EU1 is not well represented by the existing dataset, owing to access restrictions. A total of 31 soil samples were collected from 31 locations within this EU. • EU2: 2.5-km radius, Southeast Quadrant. Thirty surface soil aliquots were collected. Based on access restrictions in offsite areas, sampling coverage is constrained in EU2 but can be considered complete, extending across the EU. One discrete subsurface soil sample (4-4.5 ft bgs) was collected coincident with a TR0795 20 December 2019 monitoring well installation, located at the approximate midpoint of the EU. A total of 31 samples were collected from 31 locations within this EU. • EU3: 2.5-km radius, Southwest Quadrant. Thirty surface soil aliquots were collected. Targeting public access roadways, sampling coverage in offsite areas is constrained in EU3 but can be considered complete, extending across the EU. One discrete subsurface soil sample (4-4.5 ft bgs) was collected coincident with a monitoring well installation, located in the northwest quadrant of the EU. A total of 31 samples were collected from 31 locations within this EU. • EU4: 2.5-km radius, Northwest Quadrant. Thirty surface soil aliquots were collected. Targeting public access roadways, sampling coverage is in offsite areas is constrained in EU4 but can be considered complete, extending across the EU. One discrete subsurface soil sample (4-4.5 ft bgs) was collected coincident with a monitoring well installation, located in the northeast quadrant of the EU. A total of 31 samples were collected from 31 locations within this EU. • EU5: 5-km radius, Northeast Quadrant. Thirty surface soil aliquots were collected. Targeting public access roadways, sampling coverage is in offsite areas is fairly well distributed across the EU and can be considered complete. One discrete subsurface soil sample (4-4.5 ft bgs) was collected coincident with a surface soil sample aliquot, located on the southern border of the EU. A total of 31 samples were collected from 30 locations within this EU. • EU6: 5-km radius, Southeast Quadrant. Thirty surface soil aliquots were collected. Targeting public access roadways, sampling coverage is in offsite areas is constrained to the eastern and western areas of the EU, with the central area largely unaddressed. Nonetheless, the existing characterization is considered complete, and representative of conditions radiating from the source. One discrete subsurface soil sample (4-4.5 ft bgs) was collected coincident with a monitoring well installation, located in the northwest quadrant of the EU. A total of 31 samples were collected from 31 locations within this EU. • EU7: 5-km radius, Southwest Quadrant. Thirty surface soil aliquots were collected. Targeting public access roadways, sampling coverage is in offsite areas is well distributed and can be considered complete in EU8, extending throughout the EU. One co-located subsurface soil sample (4-4.5 ft bgs) was collected coincident with a surface soil aliquot location, located in the southeast quadrant of the EU. A total of 31 samples were collected from 30 locations within this EU. • EU8: 5-km radius, Northwest Quadrant. Thirty surface soil aliquots were collected. Targeting public access roadways, sampling coverage is in offsite areas is well distributed and can be considered complete in EU7, extending throughout TR0795 21 December 2019 the EU. One co-located subsurface soil sample (4-4.5 ft bgs) was collected coincident with a surface soil aliquot location, located on the southeast border of the EU. A total of 31 samples were collected from 30 locations within this EU. • EU9: 10-km radius, Northeast Quadrant. Thirty surface soil aliquots were collected. Targeting public access roadways, sampling coverage is in offsite areas is fairly well distributed across the EU and can be considered complete. One discrete subsurface soil sample (4-4.5 ft bgs) was collected coincident with a monitoring well installation, located in the northwest quadrant of the EU. A total of 31 samples were collected from 31 locations within this EU. • EU10: 10-km radius, Southeast Quadrant. Thirty surface soil aliquots were collected. Targeting public access roadways, sampling coverage is in offsite areas is fairly well distributed across the EU and can be considered complete. One discrete subsurface soil sample (4-4.5 ft bgs) was collected coincident with a monitoring well installation, located in the central area of the EU. A total of 31 samples were collected from 31 locations within this EU. • EU11: 10-km radius, Southwest Quadrant. Thirty surface soil aliquots were collected. Targeting public access roadways, sampling coverage is in offsite areas is fairly well distributed across the EU and can be considered complete. One discrete subsurface soil sample (4-4.5 ft bgs) was collected coincident with a monitoring well installation, located in the southeast quadrant of the EU. A total of 31 samples were collected from 31 locations within this EU. • EU12: 10-km radius, Northwest Quadrant. Thirty surface soil aliquots were collected. Targeting public access roadways, sampling coverage is in offsite areas is fairly well distributed across the EU and can be considered complete. One discrete subsurface soil sample (4-4.5 ft bgs) was collected coincident with a monitoring well installation, located in the central area of the EU. A total of 31 samples were collected from 31 locations within this EU. Soil EPCs One composite surface soil sample and one discrete subsurface soil sample were collected from each upland EU. Hence, soil CTE and RME EPCs are equivalent to single sample, maximum detected concentrations. Soil EPCs are summarized in Table F-3-1. Of the 20 Table 3+ constituents, only two were detected in soil – HFPO-DA, which was detected in two surface and three subsurface samples, and perfluoro(3,5-dioxahexanoic) acid (PFO2HxA), which was detected in two surface samples and one subsurface sample. TR0795 22 December 2019 As discussed above, subsurface soil data are not used in the intake characterization or provisional hazard characterization. However, potential intake of Table 3+ PFAS in subsurface soil is discussed as part of the uncertainty assessment. 5.2 Well Water The SLEA assesses untreated well water as drinking water, via domestic water usage, based on available data in the upland EUs (i.e., EU1 through EU12). As part of the Consent Order implementation, Chemours is required to offer replacement drinking water (in the form of public water or whole building filtration systems) when private wells have HFPO-DA detected above 140 ng/L. When any individual PFAS listed in Consent Order Attachment C exceeds 10 ng/L or when total PFAS listed in Consent Order Attachment C exceed 70 ng/L, Chemours is required to offer residents or other persons up to three under-the-sink reverse osmosis drinking water systems. Chemours is required to offer temporary replacement water supplies (i.e., bottled water) to residents or other persons qualifying for a filtration or reverse osmosis system until these systems have been provided. Hence, untreated well water data are not representative of current conditions and results in SLEA intake and hazard estimates that are conservative (i.e., health protective). Therefore, the SLEA also includes a “current conditions” evaluation based on drinking water concentrations of 10 ng/L of HFPO-DA and 70 ng/L of total PFAS. These assumed current conditions concentrations represent the maximum concentrations where the Consent Order does not require treatment. However, even this evaluation likely overestimates EU-wide intake and hazard as PFAS are uniformly reported as non-detect in household drinking water where filtration or under-the-sink reverse osmosis drinking water systems have been provided by Chemours. The untreated well water datasets are described in Section 5.2.1. Untreated well water EPCs are described in Section 5.2.2. Well Water Data The SLEA characterizes potential intake of Consent Order Attachment C PFAS9 from drinking water using untreated data collected from offsite private drinking water wells samples (i.e., mid- and post- filtration results were excluded). PFAS analytical groundwater data for evaluation in the SLEA were compiled from the Chemours Locus Environmental Information Management system (EIM), which includes a large dataset 9 Well water samples collected as part of ongoing monitoring are analyzed for the 10 Table 3+ PFAS compounds specified in Attachment C of the Consent Order. Table F-1 identifies the target analytes associated with each SOP. TR0795 23 December 2019 of well data from the offsite study area (over 1,000 wells), particularly for downgradient wells located north of the Facility. Offsite private drinking water wells are screened in both the Surficial and Black Creek Aquifers, based on a review of resident-reported well depths and offsite geological well records retrieved from www.ncwater.org. There were 55 wells with lithology and geophysical data available in the vicinity of the Facility. These wells were sampled for up to 48 PFAS compounds using various analytical laboratories and methods and not all Table 3+ PFAS were analyzed in each sample. Locations of the wells sampled in 2017 and 2019, which were included in the SLEA, are presented in Figure 5. Well Water EPCs For each well, only the most recent sampling data for Table 3+ analytes were evaluated in the SLEA. Where duplicate data exists for a well/analyte pair, the highest concentration result was retained for analysis. Data were segregated by EU prior to EPC calculation. A mean and 95% UCL concentration were calculated to represent the CTE and RME EPCs, respectively, for each EU using ProUCL Version 5.1 (USEPA, 2015a); if ProUCL could not reliably calculate a UCL or the recommended UCL exceeded the maximum detected concentration, the maximum detected concentration was selected as the RME EPC. ProUCL output is provided in Appendix C. Untreated well water EPCs are presented in Appendix F, Table F-3-2. Of the 11 Table 3+ constituents listed on Attachment C and analyzed for in untreated well water, nine (9) were detected in at least one EU. Generally, concentrations in EUs 1 through 4 are higher than those in other EUs, indicating an attenuation of concentrations with distance from the Facility, which is consistent with the CSM. Additional spatial analysis of well data is presented in the Paragraph 19 On and Offsite Assessment Report (Geosyntec, 2019c). 5.3 Surface Water The SLEA characterizes potential PFAS intake from surface water using data collected between 2017 and 2019, as described below. Surface water data were used to calculate EPCs for recreational swimming exposure conditions for four locations in the Cape Fear River, one onsite pond, and one offsite pond. Cape Fear River EPCs were developed for untreated surface water samples collected upstream, adjacent to, and downstream of the Facility, and used to evaluate recreational exposure. Cape Fear River EPCs were also developed for untreated downstream surface water collected from public supply intakes at Bladen Bluffs and Kings Bluffs to conservatively evaluate potable use exposure. EPCs representative of local ponds were developed on a pond-specific basis; only recreational TR0795 24 December 2019 exposures (e.g., fishing, swimming) were evaluated for the ponds. Surface water datasets are described in Section 5.3.1. Surface water EPCs are described in Section 5.3.2. Surface Water Data The SLEA considered surface water data collected from the locations shown in Figure 7 during the following sampling events: • September 2017 Local Program surface water sampling conducted per the Cape Fear River Surface Water Sampling Plan (Parsons, 2017a); • May 2018 Local Program surface water sampling conducted per the Additional Cape Fear River Surface Water Sampling Plan (Geosyntec, 2018a); • June 2018 Regional Program surface water sampling conducted per the Addendum to Additional Cape Fear River Surface Water Sampling Plan (Geosyntec, 2018b); • October and December 2018 Post-Florence surface water sampling conducted per the Post Hurricane Florence Sampling Plan (Geosyntec, 2018c); • Spring (February, May, and June) 2019 surface water sampling conducted per the Seeps and Creeks Investigation Report (Geosyntec, 2019b); and • Summer 2019 SLEA surface water sampling conducted per the SLEA Work Plan (Geosyntec, 2019e). Results of pre-SLEA sampling events were reported in: Cape Fear River Surface Water Sampling Memorandum (Parsons, 2017b); Assessment of the Chemical and Spatial Distribution of PFAS in the Cape Fear River (Geosyntec, 2018d); and Post Hurricane Florence PFAS Characterization Report (Geosyntec, 2018e). A summary of these sampling events is provided below. Local sampling programs conducted by Parsons in September 2017 and May 2018 focused on portions of the Cape Fear River directly upstream, adjacent to, and downstream of the Facility (Geosyntec, 2018d). The associated surface water sampling locations along the Cape Fear River included Cape Fear River-01 (CFR-01) through CFR-09. At each surface water sampling location, four samples were collected along an east-west transect to assess the lateral and vertical concentration distributions in the Cape Rear River (Figure 6)10. Samples collected in the September 2017 and May 2018 events 10 Transect samples are: (i) West, located 25% of the distance across the channel from the west shore, 1-foot below water surface; (ii) Center Top, located in the middle of the channel, 1-foot below water surface; (iii) Center Middle, located in the middle of the channel, halfway between surface and river bottom; and (iv) East, located 25% of the distance across the channel from the east shore, 1-foot below water surface. TR0795 25 December 2019 were analyzed for perfluorinated carboxylic acids, perfluorosulfonic acids, and HFPO-DA (Geosyntec, 2018d). A regional sampling program was performed in June 2018 by Parsons to characterize PFAS distribution from the confluence of the Deep and Haw Rivers [River Mile (RM)- 0] to the Kings Bluff Intake Canal, where the City of Wilmington and the Counties of Pender and Brunswick draw water (RM-132). A total of 16 surface water samples were collected from discrete locations along the Cape Fear River. To the greatest extent practicable, samples were collected from the middle depth of the water column at the thalweg, i.e., the deepest portion of the river channel. The associated sample names indicate the miles from the start of the Cape Fear River and are denoted by RM-X. Samples were analyzed according to Method 8321, Method 537, and Method Table 3 SOP (the Table 3+ method was not yet developed at the time of analysis). Some Regional Program sampling locations are co-located with those from the Local Program sampling locations, for example RM-66/CFR-01 and RM-76/CFR-05 (Geosyntec, 2018d). An assessment was conducted in October and December of 2018 to assess the effect of Hurricane Florence on the distribution of PFAS in the river (Geosyntec, 2018c). As part of the assessment, the following five (5) surface water samples were collected from the middle of the Cape Fear River: three upstream locations (RM-60, CFR-03, RM-76) and two downstream locations (RM-83 and RM-132). Samples were analyzed according to Method 537, Method Table 3 SOP, as well as Method Table 3+ SOP by the Chemours Fluoroproducts Analytical Group. In the spring of 2019, 14 additional samples were collected from the middle of the Cape Fear River at RM-56, RM-68, RM-76, RM-84, and RM-132 (the last two locations correspond to the intakes for Bladen and Kings Bluffs, respectively). Samples were analyzed according to Method 537 Modified and Method Table 3+ SOP. In support of the SLEA, additional surface water samples were collected in July and September 2019 from the Cape Fear River (EU14), an onsite pond (EU18 “Pond 1”), and an offsite pond (EU19 “Pond B”). At CFR-04 and CFR-07, four (4) samples were collected along an east-west transect as described in the SLEA Work Plan (Geosyntec, 2019e). Four (4) surface water samples were collected from onsite “Pond 1” located in the northwest portion of the Facility. Three (3) surface water samples were collected from offsite “Pond B” located 1 mile east of the Facility (east of the Cape Fear River). Surface water samples using a peristaltic pump, new dedicated high-density polyethylene (HDPE) tubing, and dedicated silicone tubing for the pump head at each location. In the Cape Fear River, the tubing was lowered to the Work Plan-specified sampling depth below the water surface using an anchor weight and the tubing positioned to point upwards; in the ponds, the tubing was lowered to the approximate middle depth of the surface water column. Surface water was pumped directly from submerged tubing through a peristaltic pump TR0795 26 December 2019 into new 250-milliliter HDPE bottles. Samples were shipped on ice via chain of custody for analysis via Method Table 3+ SOP (Table 1). Finally, additional untreated (raw) surface water data from public intakes located at Bladen Bluffs and Kings Bluffs were obtained from a NCDEQ website11 and from the Cape Fear Public Utility Authority (CFPUA) website12, respectively. Surface Water EPCs Surface water data were segregated as follows to develop EPCs representative of recreational exposure at the following EUs: • EU13, Cape Fear River Upstream: CFR-01/RM-66, CFR-02, CFR-03, RM-56, RM-60, and RM-68; • EU14, Cape Fear River Facility-adjacent: CFR-04, CFR-05/RM-76, CFR-06, and CFR-07; • EU15, Cape Fear River Downstream (4 Miles): CFR-09; • EU16, Cape Fear River Downstream (8 Miles): RM-84, CFR-BLADEN, and NCDEQ Bladen Bluffs raw (untreated) water data; • EU17, Cape Fear River Downstream (55 Miles): RM-132, CFR-KINGS, and CFPUA Sweeney raw (untreated) water data; • EU18, Pond 1 (onsite): Pond-1-SE, Pond-1-NE, and Pond-1-NW; and • EU19, Pond B (offsite): Pond-B-West, Pond-B-East, and Pond-B-South. Surface water data were segregated as follows to develop EPCs representative of potential potable use: • EU16, Cape Fear River Downstream (8 Miles): NCDEQ Bladen Bluffs raw (untreated) water data; and • EU17, Cape Fear River Downstream (55 Miles): CFPUA Sweeney raw (untreated) water data. The surface water dataset includes samples collected between July 2017 and October 2019. Data were reviewed to identify potential seasonal or annual concentration trends. Concentrations were variable but no trends were apparent. As such, 2017 to 2019 river water data were compiled for each EU to develop recreational use EPCs. Additionally, at Bladen and Kings Bluffs, which correspond to public water supply intake points, water 11 https://deq.nc.gov/news/key-issues/genx-investigation 12 https://www.cfpua.org/692/Drinking-Water-Quality TR0795 27 December 2019 data reported by the NCDEQ for 2017 and CFPUA for 2018 and 2019 were used to develop potable use EPCs. EPCs for the CTE and RME scenarios correspond to mean and 95% UCLs, respectively. Within the available historical datasets, detection limits were often not reported. As such, non-detect results were excluded rather than replaced with a surrogate value (e.g., zero or a more recent RL) to retain the conservative nature of the SLEA. To maintain consistency between EPC calculation methods for surface water, only detected values were used at each EU. Surface water EPCs for the Cape Fear River, onsite pond, and offsite pond sampling locations are presented in Appendix F, Table F-3-4. 5.4 Fish The SLEA characterizes potential intake of Table 3+ PFAS from recreational fish consumption using tissue samples collected between July and September 2019. Fish collection locations are shown in Figure 7 and color-coded by genus. Fish tissue data are described in Section 5.4.1. Fish tissue EPCs are described in Section 5.4.2. Fish Tissue Data In support of the SLEA, fish fillets were collected from five sampling points within the Cape Fear River: (i) 10 miles upstream of the Facility (RM-68) at EU13, which, relative to the distance from the Facility, far exceeds the expected home range for recreational sport fish targeted by local anglers (Lewis and Flickinger, 1967); (ii) adjacent to the Facility (CFR-05 and CFR-06) at EU14, (iii) 4 miles downstream of the Facility (CFR- 09) at EU15, and (iv) 8 miles downstream of the Facility (Bladen Bluffs) at EU16. Fish fillets were also collected from onsite Pond 1 (EU18). Fish were not collected from Kings Bluffs (EU17), which is 55 miles downstream, or offsite Pond B (EU19), which is stocked with fish by the private owner. Fish were collected by traditional rod-and-reel methods. Fish selected for chemical analysis were filleted in the field and fish fillets (i.e., muscle tissue) were preserved on ice and submitted to TestAmerica under chain of custody for analysis of PFAS per the Table 3+ SOP. Species selected for chemical analysis are summarized below by sampling location. • EU13, Cape Fear River Upstream (RM-68). Five (5) fillet samples were collected from the upstream EU. One sample was collected from each of the following specimens: one flathead catfish (Pylodictis olivaris), one channel catfish (Ictalurus punctatus), one blue catfish (Ictalurus furcatus), and two largemouth bass (Micropterus salmoides). HFPO-DA and Table 3+ PFAS were not detected in EU13 fish fillet samples. TR0795 28 December 2019 • EU14, Cape Fear River Facility-adjacent (CFR-06 and CFR-07). Seven (7) fillet samples were collected adjacent to the Facility. One sample was collected from each of the following specimens: one flathead catfish, one channel catfish, four blue catfish, and one largemouth bass. HFPO-DA was not detected at CFR-06 or CFR-07. Table 3+ PFAS were not detected in with the exception of perfluoromethoxypropyl carboxylic acid (PMPA) in three samples and perfluoro(3,5,7,9-tetraoxadecanoic) acid (PFO4DA) in one sample. Relative to the Huske Dam, four (4) specimens were collected upstream and three (3) were collected downstream. Based on these samples, the presence of the dam does not appear to be influencing fillet concentrations; therefore, for the purposes of SLEA EPC calculation, these samples were grouped together. • EU15, Cape Fear River Downstream (CFR-09). Three (3) fillet samples were collected from CFR-09, which is located approximately 4 miles downstream of the Facility. One sample was collected from a largemouth bass and two samples were collected from blue catfish (separate specimens). HFPO-DA was not detected in the CFR-09 samples. PMPA was detected in one sample and PFO4DA was detected in two samples. • EU16, Cape Fear River Downstream, Bladen Bluffs. Eight (8) fillet samples were collected from the Bladen Bluffs EU, which is located approximately 8 miles downstream of the Facility. One sample was collected from each of the following specimens: one bluegill sunfish (Lepomis macrochirus), one channel catfish, one largemouth bass, and five redbreasted sunfish (Lepomis auratus). Target PFAS were detected in six of the eight samples. perfluoro-1-methoxyacetic acid (PFMOAA) was the most frequently detected PFAS, with reported detections in five samples. HFPO-DA was detected in three samples and PFO4DA, perfluoro- 3,5,7,9,11-pentaoxadodecanoic acid (PFO5DA), and R-EVE were detected in one sample each. • EU18, Onsite Pond 1. Three (3) fish fillet samples were collected from onsite Pond 1. These samples were collected from three largemouth bass. HFPO-DA and Table 3+ PFAS were not detected in two of the three samples. In the third sample, PFO4DA and PMPA were detected. In total, six (6) Table 3+ PFAS were detected in fish fillets. Concentrations were reviewed to identify potential concentration trends. Four of the six detected PFAS were only detected in samples collected from Bladen Bluffs, including HFPO-DA. PFO4DA was detected in onsite Pond 1, Facility-adjacent, and downstream samples; the highest concentration was reported at Bladen Bluffs and it exceeded onsite and Facility-adjacent concentrations by two or more orders of magnitude. PMPA was detected in onsite Pond 1, Facility-adjacent, and CFR-09 samples but not Bladen Bluffs samples; no concentration TR0795 29 December 2019 gradient was apparent for the detections. Detections occurred in multiple species and inspection of the data did not indicate a relationship to trophic level. Fish Tissue EPCs EPCs for the CTE and RME scenarios generally correspond to mean and 95% UCL concentrations calculated in ProUCL, respectively. However, based on the limited number of detections, EU-specific UCLs could not be calculated for some PFAS. In these instances, EPCs for the RME scenario correspond to maximum detected concentrations. Fish fillet EPCs for the Cape Fear River and Pond 1 sampling locations are presented in Appendix F, Table F-3-5. 5.5 Homegrown Produce Homegrown Produce Data Due to seasonal limitations, harvest-ready produce could not be collected in the vicinity of the Facility. As such, the SLEA characterizes intake of Table 3+ PFAS from homegrown produce consumption using modeled concentrations in aboveground leafy vegetables (e.g., lettuce), aboveground fruits (e.g., tomatoes), and belowground vegetables (e.g., carrots). Homegrown Produce EPCs Produce EPCs were estimated using equations presented in the USEPA’s 2005 Human Health Risk Assessment Protocol for Hazardous Waste Combustion Facilities (HHRAP). These equations consider bioconcentration of HFPO-DA from surface soil (via root uptake) and air (via particulate deposition and absorption). The produce exposure assessment is limited to HFPO-DA based upon its reliance on physicochemical parameters for modeling plant biouptake and Facility-specific deposition data. The HHRAP equations, inputs, and outputs are presented in Appendix E and discussed below. Study area-specific inputs to the HHRAP equations are limited to surface soil EPCs and particulate emission and deposition rates; otherwise, inputs are based on USEPA recommendations or the primary literature. Surface soil EPCs, which are presented in Table F-4-1, were derived from data collected in September and October 2019 (i.e., per the SLEA Work Plan); soil EPCs were combined with the bioconcentration factors derived in Table E-1 to estimate produce EPCs as a result of root uptake. As with soil, a single EPC is used for the CTE and RME produce exposure estimates (Table F-4-5). Particulate emission and deposition rates were developed from a regional deposition model developed by Chemours for emissions of HFPO-DA from both point and fugitive sources identified at the Facility. The eight (8) sources include the Vinyl Ethers North TR0795 30 December 2019 Division, Vinyl Ethers South, and PPA Process Stacks and associated fugitive emissions, as well as the Polymers Process and Semi-Works Process Stacks. The deposition model used the latest versions of the regulatory dispersion model and supporting programs of AERMOD (version 1621r), AERMAP (version 11103), and BPIP (version 04274), and local meteorological data collected from 2012 through 2016 that was pre-processed for AERMOD by the NCDEQ. Chemours previously presented the deposition modeling results in the 2018 document, Modeling Report: HFPO-DA Atmospheric Deposition and Screening Groundwater Effects, Fayetteville Works Facility, Fayetteville, NC (ERM, 2018). For the purposes of the SLEA and to focus the CAP on future conditions, the model was refined to account for planned stack emissions control measures, including a thermal oxidizer, that will reduce aerial HFPO-DA emissions by 99% starting in January 2020 compared to 2017 baseline, and expected comparable reductions for other PFAS. Wet and dry deposition flux estimates for HFPO-DA were extracted from the refined model for multiple points within each EU. Using these data, an average and maximum flux were calculated (Table E-1 of Appendix E). The average and maximum flux estimates were combined with the projected 2020 Facility-wide emissions rate for HFPO-DA (Table D- 1 of Appendix D). 5.6 Data Quality Analytical data were reviewed using the Data Verification Module (DVM) within the EIM system, which is a commercial software program used to manage data. Following the DVM process, a manual review of the data was conducted. The DVM and manual review results were combined in a data review narrative report for each set of sample results, which is consistent with Stage 2b of the USEPA’s Guidance for Labeling Externally Validated Laboratory Analytical Data for Superfund Use (USEPA, 2009). The narrative report summarizes which samples were qualified (if any), the specific reasons for the qualification, and any potential bias in reported results. The data usability, in view of the project’s data quality objectives (DQOs), was assessed and the data were entered into the EIM system. The data were evaluated by the DVM against the following data usability checks: • Hold time criteria; • Field and laboratory blank contamination; • Completeness of QA/QC samples; • Matrix spike/matrix spike duplicate recoveries and the relative percent differences (RPDs) between these spikes; • Laboratory control sample/control sample duplicate recoveries and the RPD between these spikes; TR0795 31 December 2019 • Surrogate spike recoveries for organic analyses; and • RPD between field duplicate sample pairs. Results are presented in Appendix B with validator flags. The “J” and “UJ” flagged results indicate usable data, which should be considered as quantitatively estimated. In other words, the results are not necessarily within the laboratory’s criteria for accuracy and precision of the test method employed, but in the reviewer’s professional judgment are usable. Laboratory reports and data review narratives for drinking water samples collected prior to the Consent Order were included in reports prepared by Parsons (Parsons, 2017c, 2018 a, b); for samples collected after the Consent Order, the information is submitted electronically to NCDEQ on a routine basis. Laboratory reports and data review narratives for other media are provided as Appendix E to the Ecological SLEA (Geosyntec, 2019f). TR0795 32 December 2019 6 INTAKE CHARACTERIZATION Intake of PFAS was quantified as an average daily intake (ADI), expressed in units of milligrams of constituent per kilogram of body weight per day (mg/kg-day). Intake was calculated for each route and then summed by exposure medium (e.g., soil, drinking water). Total intakes for each receptor from relevant exposure media in a given EU were also calculated. For residents, farmers, gardeners, and recreationalists, two age groups were considered: a child age 0 to 6 years and an aggregated, age-adjusted child/adult receptor, reflective of 0 to 26 years of age. 6.1 Intake Equations and Inputs The equations used to calculate intake are based on USEPA guidance, including the Risk Assessment Guidance for Superfund (USEPA, 1989); and the Regional Screening Levels User’s Guide (USEPA, 2019a). Intake assumptions were developed based on USEPA guidance, including the Human Health Evaluation Manual, Supplemental Guidance: Update of Standard Default Exposure Factors and associated updates (USEPA, 2014; 2015b) and the Exposure Factors Handbook and associated updates (USEPA, 2011; 2017; 2018b, c; 2019b). Receptor-specific inputs and equations are presented in Appendix F, Tables F-2-1 through F-2-5. EPCs are presented in Appendix F, Tables F-3-1 through F-3-5. 6.2 Intake Characterization Results Tables F-4-1 through F-4-10 of Appendix F present the PFAS-specific intake calculations for each receptor-EU combination. Intake of total Table 3+ PFAS (i.e., the sum of detected Table 3+ PFAS) is presented in Table F-5-1 (upland EUs), Table F-5-2 (Cape Fear River and pond EUs), and Table F-5-3 (Cape Fear River surface water intake points). The intakes are summarized below, focusing on the RME exposure scenario. As described in the Section 1 of this SLEA, the results of the intake characterization should be reviewed in consideration of the following: • The SLEA drinking water intake estimates in EU1 through EU12 are initially calculated based on untreated well water which, in many cases, is not representative of current drinking water conditions. While ingestion of untreated well water as drinking water is the most significant complete intake pathway and contributor to hazard, Consent Order Attachment C PFAS are uniformly reported as non-detect in household drinking water where filtration or under-the-sink reverse osmosis drinking water systems have been provided by Chemours. Hence, the SLEA intake estimates based on untreated well water are conservative relative to current conditions. TR0795 33 December 2019 • Chemours is taking action to reduce air emissions of PFAS from the Facility, including installation of a Thermal Oxidizer that will dramatically reduce aerial PFAS emissions from the Site, with reduction of aerial HFPO-DA emissions by 99% starting in January 2020 compared to 2017 baseline, and expected comparable reductions for other PFAS. With a reduction in air emissions, associated soil and groundwater concentrations (and, by extension, well water) will attenuate over time, as will contributions to other receiving media, such as surface water and recreational fish species. Upland EUs The results of the intake characterization for residents, farmers, and gardeners potentially exposed to Table 3+ PFAS in soil, homegrown produce, and untreated drinking water are summarized in Table F-5-1. Across all upland EUs (i.e., EU1 through EU12) for CTE and RME exposure scenarios, drinking water consumption, assuming untreated drinking water, accounted for 97% or more of total intake. The RME range of intake estimates for each exposure medium was as follows: • Untreated Well Water: 6.1E-06 to 4.7E-04 mg/kg-day • Homegrown Produce: 7.7E-16 to 6.2E-06 mg/kg-day • Surface Soil: 1.4E-09 to 6.3E-08 mg/kg-day As discussed throughout this document, the use of untreated well water to calculate domestic use substantially overstates the current potential for exposure on a population and individual basis. The sum of RME EPCs for Table 3+ PFAS listed on Attachment C in untreated well water ranged from approximately 180 ng/L to 9,500 ng/L whereas under current conditions and per the requirements of the Consent Order, concentrations in the monitoring well network are presumed to range from non-detect (i.e., where treatment systems were installed) to 70 ng/L (i.e., the maximum concentration for which a treatment system would not be required by the Consent Order). Table F-5-1 includes an RME intake estimate based on a PFAS concentration of 70 ng/L, which is the maximum EPC for drinking water wells in EU1 through EU12 that is reasonably anticipated under current conditions. The range of intakes under this assumed current conditions scenario was as follows (but may be as low as zero): • Current Conditions Well Water: 2.4E-06 to 3.5E-06 mg/kg-day TR0795 34 December 2019 Cape Fear River and Pond EUs The results of the intake characterization for recreationalists potentially exposed to Table 3+ PFAS in surface water and fish tissue fillets from the Cape Fear River, onsite Pond 1, and offsite Pond B are summarized in Table F-5-2. The lowest intakes were associated with the upstream EU where Table 3+ PFAS were not detected in fish tissue. The highest intakes were associated with consumption of fish caught at Bladen Bluffs. The range of RME intake for Facility-adjacent and near-downstream EUs (i.e., excluding Bladen and Kings Bluff) for each exposure medium was as follows: • Surface Water: 7.3E-08 to 3.1E-06 mg/kg-day • Fish Fillets: 1.1E-07 to 2.1E-06 mg/kg-day The range of RME intake for Bladen and Kings Bluffs for each exposure medium was as follows: • Surface Water: 1.1E-07 to 7.4E-07 mg/kg-day • Fish Fillets (Bladen Bluff): 2.7E-05 to 4.7E-05 mg/kg-day The contribution from fish and surface water to total intake varied by EU, and apparent differences may be attributable to the low number of detections, differences in detection capabilities for surface water and animal tissue, and the exclusion of non-detect results from the surface water EPC calculations (see Section 8.2.4). Surface Water Intake Points The results of the intake characterization for residents potentially exposed to HFPO-DA in untreated surface water at the public supply intake points at Bladen Bluffs (EU16) and Kings Bluffs (EU17) are summarized in Table F-5-3. These data were reported by NCDEQ and CFPUA. Total intake of HFPO-DA from residential consumption of untreated river water from Bladen Bluffs was approximately an order of magnitude higher than intake from Kings Bluffs. Of the Table 3+ compounds, only HFPO-DA was analyzed for at Bladen Bluffs and nine Table 3+ compounds were analyzed for at Kings Bluffs; as such, a total PFAS intake comparison could not be made between the two EUs. The range of RME intakes was as follows: • Bladen Bluffs (HFPO-DA): 1.2E-05 to 1.8E-05 mg/kg-day • Kings Bluffs (HFPO-DA): 6.4E-07 to 9.2E-07 mg/kg-day • Kings Bluffs (Table 3+ PFAS): 3.5E-06 to 5.0E-06 mg/kg-day TR0795 35 December 2019 7 PROVISIONAL HAZARD CHARACTERIZATION The purpose of the SLEA is to assess which complete exposure pathways of Table 3+ PFAS are likely the most significant contributors of overall human exposure on a regional basis. The relative ranking of exposures resulting from the SLEA can be used to inform risk management decisions and exclude pathways that, albeit potentially complete, are insignificant relative to overall exposure potential. In addition to providing a relative ranking of exposure pathways, the estimated intakes of HFPO-DA were also used to calculate provisional quantitative estimates of potential hazard. The hazard characterization is limited to an assessment of HFPO-DA based on the current availability of toxicity criteria, which are described in Section 7.1. The methods used to quantify potential hazard are described Section 7.2. The results of the provisional hazard characterization are presented in Section 7.3. 7.1 HFPO-DA Toxicity Criteria The SLEA provisional hazard characterization is based on the RfDo of 1E-04 mg/kg-day adopted by the NC DHHS. There are other published values available that may better reflect the toxicological profile of HFPO-DA but a detailed evaluation of the uncertainties associated with these values is outside the scope and objectives of the SLEA. Therefore, the SLEA relies upon the determination from the NC DHHS that, in a regulatory context, the RfDo is protective of human health. Because regulatory risk assessment generally “errs on the side of caution,” it must be reiterated that this (or any) RfDo is not predictive of an actual health outcome. The RfDo is described further below. The USEPA defines an RfDo as “An estimate (with uncertainty spanning perhaps an order of magnitude) of a daily oral exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. It can be derived from a [no-observed-adverse-effect level] NOAEL, [low- observed-adverse-effect level] LOAEL, or benchmark dose, with uncertainty factors generally applied to reflect limitations of the data used. Generally used in USEPA’s non- cancer health assessments.” To calculate the RfDo, NC DHHS considered seven repeat oral dose studies in rodents of 28 days or longer that were provided by Chemours/DuPont during the USEPA Toxic Substances Control Act (TSCA) review process (NC DHHS, 2018) in derivation of the RfDo. These repeat oral dose studies are preferred to single-dose studies as they are more likely to be applicable to long-term human exposure; however, they are subchronic whereas chronic studies, generally defined as 6 months to a lifetime, are preferred. The NC DHHS consulted with toxicologists and risk assessors at USEPA, the National Institute of Environmental Health Sciences, and the Agency for Toxic Substances and TR0795 36 December 2019 Disease Registry to identify applicable toxicology information and risk assessment procedures. The NC DHHS utilized a NOAEL of 0.1 mg/kg-day for liver toxicity endpoints from two subchronic studies in mice (a 28-day study and a reproductive screen) as a point of departure (POD) for calculation of the RfDo. These sub-chronic studies were chosen as the critical studies because they demonstrate adverse effects at the lowest doses tested and associations were evident across multiple studies at the same or similar doses. The NC DHHS used default uncertainty factors (UFs) recommended by the USEPA to derive their RfDo from the POD. The NC DHHS did not apply a modifying factor (MF) because NOAELs from multiple studies were identical, or within the same order of magnitude, with similar health endpoints (liver toxicity). Additionally, NC DHHS staff concluded that the UFs discussed below adequately addressed the uncertainties of the database. The following default UFs were applied to the POD to derive the RfDo: • Sub-chronic to chronic uncertainty factor (UFS): A factor of 10 to account for the uncertainty involved in extrapolating from less than chronic NOAELs to chronic NOAELs; • Interspecies uncertainty factor (UFA): A factor of 10 to account for the uncertainty involved in extrapolating from animal data to humans; and, • Intraspecies uncertainty factor (UFH): A factor of 10 to account for the variation in sensitivity among the members of the human population Alternate HFPO-DA RfDo values are available and include a USEPA provisional value and values available from the primary, peer-reviewed literature. Consideration of readily available alternatives and their associated uncertainty are discussed further in Section 8.4. Additionally, per Paragraph 14 of the Consent Order, Chemours is performing studies to provide both human health and ecological toxicity information for select PFAS, including PFMOAA, PMPA, PFO2HxA, perfluoroethoxypropyl carboxylic acid (PEPA) and Byproduct 2 (PFESA-BP2). These studies are described in the Toxicity Study Workplan (Chemours, 2019) and are anticipated to be completed in 2022. 7.2 Hazard Characterization Methods There are presently neither federal nor state regulatory standards for HFPO-DA in water, soil, air, or food. As discussed in above, the provisional hazard characterization is predicated on the current RfDo developed by the NC DHHS of 1E-04 mg/kg-day. Using this RfDo, a hazard quotient (HQ) for HFPO-DA was calculated as follows for each receptor-media-EU combination: 𝐻𝐻𝐻𝐻=𝐴𝐴𝐴𝐴𝐴𝐴÷ 𝑅𝑅𝑅𝑅𝐴𝐴𝑜𝑜 TR0795 37 December 2019 where: • HQ = Hazard quotient (unitless) • ADI = Receptor-specific average daily intake of HFPO-DA (mg/kg-day) • RfDo = Oral reference dose (hazard per mg/kg body weight-day) Total intake of HFPO-DA was summed across relevant media prior to calculating HQs. An HQ greater than 1 was used as the benchmark for identifying potential human health hazard. Consistent with USEPA Region 4 guidance for conducting human health risk assessments, HQs were rounded to one significant figure (USEPA, 2018d). 7.3 Hazard Characterization Results Table F-6-1 presents the preliminary hazard characterization for intake of soil, produce, and untreated drinking water at upland EUs 1 through 12. Calculated HQs were less than 1 for the upland receptor exposure scenarios evaluated in the SLEA, indicating potential HFPO-DA exposure is unlikely to pose a hazard to residents, farmers, or gardeners, even in the absence of drinking water treatment. Outside of EU1, the potential hazard from untreated well water consumption accounted for 96% or more of total hazard for each receptor. At EU1, untreated well water consumption accounted for over 99% of the residential intake but only 84% (CTE) to 92% (RME) of the gardener and farmer intake; consumption of homegrown produce accounted for most of the remainder, with soil intake being insignificant. As stated previously, the use of untreated well water to calculate domestic use substantially overstates the population’s potential exposure, as treatment systems provided by Chemours have substantially reduced PFAS in drinking water. Table F-6-1 also presents HQ estimates based on an assumption of 10 ng/L of HFPO-DA in drinking water, which is the maximum concentration in well water that would not require a treatment system. Total HQs for assumed current conditions range from 0.003 to 0.07 and, hence are more than an order of magnitude below unity (1). This indicates that HFPO-DA in soil, produce, and well water in the vicinity of the Facility do not pose a hazard to resident, farmer, or gardener populations under current conditions. Table F-6-2 presents the preliminary hazard characterization for intake of surface water and fish tissue from the Cape Fear River (10 miles upstream, Facility-adjacent, 4 miles downstream, 8 miles downstream, 55 miles downstream), onsite Pond 1, and offsite Pond B. Calculated HQs were less than 1 for the receptor exposure scenarios evaluated in the SLEA, indicating potential HFPO-DA exposure in the Cape Fear River does not pose a hazard to recreationalist populations. The highest HQs (0.08 to 0.1) are driven by consumption of fish from the downstream EU16 at Bladen Bluffs; otherwise, HQs were TR0795 38 December 2019 less than 0.01, indicating surface water and fish tissue do not pose a hazard to recreationalist populations under current conditions. Table F-6-3 presents the preliminary hazard characterization for domestic use intakes of Cape Fear River untreated surface water collected from the public supply intake points at Bladen Bluffs (EU16) and Kings Bluffs (EU17). Calculated HQs (0.006 to 0.1) were less than 1 for the receptor exposure scenarios evaluated in the SLEA, indicating potential HFPO-DA exposure in untreated surface water at the Bladen Bluffs and Kings Bluff intake points within the Cape Fear River does not pose a hazard to residential consumers under current conditions. Table F-7, which is also duplicated as Table 3 for presentation purposes, presents a summary of Total 3+ PFAS and HFPO-DA intake estimates as well as projected HFPO-DA provisional hazard estimates, by EU under CTE and RME conditions. For the RME scenario, calculated intakes and HQs for upland receptors are presented for untreated well water concentrations as well as assumed current conditions; current conditions incorporate an assumption of 10 ng/L HFPO-DA and 70 ng/L total PFAS in untreated groundwater to address the scenario where no drinking water treatment may have been required. Intake and HQ estimates are only presented for the maximum- exposed receptor which is an offsite child gardener, offsite child recreationalist, or offsite child resident. Utilizing the NC DHHS RfDo, individual HQs are less than 1, even in the absence of drinking water treatment, indicating HFPO-DA does not pose a hazard to offsite populations. The conclusion of no hazard for receptors in the upland EUs is further supported by the current conditions HQs which are more than an order of magnitude less than 1 and may be as low as zero. TR0795 39 December 2019 8 UNCERTAINTY ASSESSMENT This section discusses uncertainties in the SLEA that may materially impact the understanding of exposure, estimates of intake, and quantitative point estimates of hazard for HFPO-DA. Uncertainties are inherent in the process of quantifying exposure (and hazard) due to the use of environmental sampling results, assumptions regarding receptor behavior, and the quantitative representation of chemical toxicity. Therefore, assumptions used in the HH-SLEA aimed to provide additional conservatism where there was significant uncertainty. Analysis of the critical areas of uncertainty in an assessment provides context for interpreting the quantitative results and better informs risk management decisions. 8.1 Uncertainty in Laboratory Analytical Data Detection Limits For groundwater and surface water, the reporting limits (RLs) for Table 3+ PFAS ranged from 2 to 10 ng/L. These concentrations are below the State’s provisional health goal for HFPO-DA in drinking water of 140 ng/L13. Therefore, the method is sufficiently sensitive for this characterization of HFPO-DA drinking water and recreational direct exposure scenarios. Methods for analyzing HFPO-DA are sufficiently sensitive to estimate exposures compared to the NC DHHS HFPO-DA RfDo. While the methods are sensitive enough to evaluate exposures compared to the NC DHHS HFPO-DA RfDo, there are presently neither federal nor state regulatory standards for HFPO-DA in water, soil, air, or food. Hence, there is uncertainty with the ability of laboratory analytical limits to detect PFAS at concentrations that may pose a potential human health hazard. The RLs for Table 3+ PFAS ranged from 500 to 550 ng/kg for Method 537 (HFPO-DA only) and 1,000 to 1,200 ng/kg for the Table 3+ Method (20 PFAS). For fish tissue, RLs for Table 3+ PFAS ranged from 1,000 to 1,200 ng/kg. Based on the maximum RL and default child resident and recreational angler exposure assumptions, the estimated PFAS intake from soil and fish fillets would be 1E-08 and 4E-07 mg/kg-day, respectively. These intake estimates are several orders of magnitude below the NC DHHS RfDo of 1E-04 mg/kg-day. Therefore, the HFPO-DA method is sufficiently sensitive based on the NC DHHS HFPO-DA RfDo. 13 The NC DHHS provisional health goal assumes an individual receives 80% of the acceptable dose (i.e., the RfDo) via other sources, such as food. Hence, the provisional health goal was determined such that intake via drinking water does not exceed 20% of the RfDo. These source contribution estimates are default assumptions and not supported by empirical data. The contribution of HFPO-DA from other sources is likely less than 80% such that concentrations greater than 140 ng/L would also be protective of human health. TR0795 40 December 2019 Although there is not a current expectation that other Table 3+ PFAS could be orders of magnitude more potent than HFPO-DA, uncertainty associated with RLs remains unresolved pending additional toxicological information. 8.2 Uncertainty in Exposure Point Concentrations The SLEA was prepared to provide a screening-level evaluation of intake on a regional basis. As such, the EPCs evaluated herein are not representative of a specific exposure point. Rather, they were calculated on an EU-basis and reflect the variability within a given EU. EPC uncertainty is discussed below by environmental contact medium. For all media evaluated herein, the calculated EPCs are considered conservative, i.e., health- protective, relative to future conditions as attenuation of concentrations in all contact media is expected over time based on the implementation of recent and imminent Facility emissions control technologies. Soil Exposure Point Concentrations Uncertainty associated with soil EPCs is primarily associated with the use of composite samples to characterize Table 3+ PFAS within each EU. Composite samples inherently represent an average concentration across an EU. Although various composite sampling methods were considered in the development of the SLEA Work Plan, a simplified compositing approach was implemented in the interest of time and access limitations. The sampling deviated from typical ISM sampling most significantly in that replicate samples were not collected. Replicate samples provide information about concentration variability and can be combined to develop upper-bound estimates on the mean to support alternate EPCs. Although the current composite samples reflect an average of conditions throughout a given EU, these results may also be considered de facto maximum detected concentrations (in that they are not averaged with replicates). The lack of variability in these data introduces uncertainty to individual intake estimates and it precludes estimation of confidence bounds around an individual’s intake. Although the lack of variability data introduces uncertainty to the SLEA intake estimates, it is unlikely to affect the overall conclusions for the following reasons: (i) the SLEA demonstrates that incidental soil ingestion accounts for less than 1% of total intake of Table 3+ PFAS, and consumptive use of untreated well water accounts for over 90% of total intake; and, (ii) PFAS in groundwater and, subsequently, well water are attributed to leaching from soil and there is likely a correlation in concentration between these media such that, for a given receptor, the ratio of intake from these two sources does not significantly vary. Therefore, uncertainty in soil data does not change the TR0795 41 December 2019 SLEA conclusion that addressing exposure to PFAS via well water consumption meaningfully reduces overall receptor exposure. Because the EU-specific EPCs in soil constitute a regional approach to characterization, and do not reflect conditions at one location or residence, there was consideration of aggregating data among EU groupings to characterize broader regional influence, based on predominant dispersion and deposition patterns. The individual EU approach to EPC development yields the most conservative estimates of projected intake and hazard. Combination of EUs 1, 5 and 9 to characterize a broader northeast quadrant yielded lower EPCs. Since none of the individual EU-based EPCs resulted in significant projected hazards, no additional effort was expended to evaluate EU grouping. Produce Exposure Point Concentrations Empirical produce data were not available. As such, concentrations in homegrown produce were modeled based on uptake from soil, modeled air emissions, and particulate stack emissions deposition rate data. The soil-derived concentrations are subject to the data and EPC uncertainties described above. Additionally, the assumed root uptake factors may under- or over-estimate produce concentrations. Key input parameters for these uptake factors are the octanol- water partition coefficient (Kow) and the organic carbon-water partition coefficient (Koc). The Kow value used was developed by Chemours using empirical, site-specific data. The Koc values used in the SLEA were derived from the primary literature and may or may not be applicable to study area conditions. In future use of site specific Koc values which Chemours is developing would reduce uncertainty in estimates. The deposition-derived concentrations are uncertain due to the combination of multiple models (e.g., AERMOD, AERMAP, and BPIP), which are each inherently uncertain. To evaluate the potential magnitude of uncertainty associated with the homegrown produce EPCs, modeled concentrations were compared to concentrations measured in non-edible grasses collected from the upland EUs to support the Ecological Screening Level Exposure Assessment (Geosyntec, 2019f). Use of the plant uptake models indicated that concentrations in produce due to deposition are insignificant relative to root uptake, with modeled concentrations less than 0.001 ng/kg dry weight (based on 2020 emission and flux estimates). Modeled HFPO-DA concentrations due to root uptake ranged from 49.4 to 357 ng/kg dw in aboveground produce and 2,710 to 19,571 ng/kg dw in belowground produce. Concentrations of HFPO-DA measured in non-edible grass ranged from 1,600 to 171,000 ng/kg dw (Geosyntec, 2019f). It is possible that these grasses represent long-lived species (not annuals) and the measured data in biota represent an artifact of pre-air emission control technology conditions, whereas the modeled air data TR0795 42 December 2019 represent the 2020 reduction goals (a two order-of magnitude improvement). A relationship between soil and vegetation could not be reliably established based on the available data. Given the range of modeled and measured plant concentrations and uncertainty in the relevance of grass concentrations to edible plants, future measured homegrown produce (i.e., fruit and vegetable) concentrations would provide greater certainty in SLEA results. Drinking Water Exposure Point Concentrations Over 1,000 wells have been sampled in the vicinity of the Facility and many wells are sampled regularly as part of ongoing monitoring activities. Thus, the drinking water dataset is robust and calculated statistics (i.e., mean, 95 UCL) are likely reliable. Importantly, the EPCs used herein for the drinking water intake assessment and provisional hazard characterization represent untreated well water. As part of the Consent Order implementation, Chemours is required to offer permanent replacement drinking water (in the form of public water or whole building filtration systems) when private wells have HFPO-DA detected above 140 ng/L. When any individual PFAS listed in Consent Order Attachment C, exceeds 10 ng/L or when total PFAS listed in Consent Order Attachment C exceed 70 ng/L, Chemours is required to offer residents up to three under- the-sink reverse osmosis drinking water systems. Chemours offers temporary replacement water supplies (i.e., bottled water) to residents qualifying for a filtration or reverse osmosis system until these systems have been provided. With the implementation of these systems, post-treatment drinking water (where required for qualifying households) shows no detections of any Table 3+ PFS compounds. With the elimination of pre-treatment well water as the source of domestic drinking water supply, associated hazards are expected to substantially decrease. As summarized in Table 4, the provisional HFPO-DA HQs are substantially lower than those calculated based on untreated well water (i.e., based on current conditions, HFPO-DA HQs are expected to decrease from <1 to <0.1). Surface Water Exposure Point Concentrations The primary source of uncertainty associated with surface water EPCs is the transient nature of surface water such that the samples evaluated in the SLEA represent a “snap shot” of conditions that may change seasonally or annually. However, inclusion of data collected in different years at different times of the year reduces the likelihood that EPCs were underestimated. Unlike other media evaluated in this SLEA, the EPCs for surface water were calculated using only detected concentrations. This approach was selected due to the lack of reporting limits for several historical sample results reported by NCDEQ and CFPUA. In TR0795 43 December 2019 general, exclusion of non-detect results is likely to over-estimate rather than under- estimate EPCs such that the SLEA intake and hazard estimates remain conservative. There is also uncertainty in the total Table 3+ PFAS intake estimates due to inconsistency in target analytes between locations and dates. For example, NCDEQ’s analysis of Bladen Bluffs intake samples was limited to HFPO-DA and the CFPUA’s analysis of Kings Bluffs intake samples was limited to nine Table 3+ PFAS (including HFPO-DA). As a result, total Table 3+ PFAS intake may be underestimated for the hypothetical residential surface water-as-drinking water scenarios. For other EUs and non-potable use scenarios, the potential for underestimating total Table 3+ PFAS intake is mitigated by the fact that at least one sample at each EU was analyzed for the 20 Table 3+ PFAS. One exception is EU15 where no surface water samples were collected; however, the results of the intake characterization for the upstream and downstream EUs support that concentrations at EU15 are unlikely to pose a hazard. Overall, given the low magnitude of the intake estimates (relative to untreated well water) and the NC DHHS RfDo, uncertainties identified above are unlikely to affect the SLEA conclusion that surface water is not a significant source of human exposure for Table 3+ PFAS under current conditions. Fish Tissue Exposure Point Concentrations The primary source of uncertainty associated with the fish tissue EPCs is the small size of the dataset and the fact that these data represent a “snap shot” of conditions, which may change seasonally or annually. From a CSM perspective, the fish tissue data were not particularly informative. No concentration gradient was apparent, and the highest tissue concentrations were measured in samples collected farthest from the Facility, approximately 8 miles downstream at Bladen Bluffs. Given this spatial distribution, it is not possible to draw conclusions about concentrations farther downstream. Future additional fish tissue data from further downstream including near Kings Bluff Intake would refine the assessment of the spatial distribution of these compounds in fish. Due to the limited number of detections in fish fillets a bioconcentration factor for the surface water-to-fish fillet pathway could not be developed. In fish fillets, the most frequently detected Table 3+ PFAS was PFO4DA, which was detected in samples from onsite Pond 1, the Facility-adjacent samples, CFR-09, and Bladen Bluffs, with the highest concentration reported for Bladen Bluffs. Conversely, PFO4DA was reported as non- detect in Bladen Bluffs surface water samples and no relationship between surface water and fish tissue samples was apparent for the other locations where samples were co- located. Based on these data, surface water could not be used as an indicator of fish tissue TR0795 44 December 2019 concentrations and, hence, there is uncertainty associated with the identity of contributing source(s) of PFAS in fish tissue. 8.3 Uncertainty in the Exposure Assessment The SLEA was prepared to provide a screening-level evaluation of intake and to rank exposure media based on potential for intake of Table 3+ PFAS. Like any regulatory exposure or risk assessment, the exposures evaluated herein are hypothetical in that they do not represent any actual receptor nor are they predictive of health outcomes. Uncertainty in Exposure Media and Routes This section discusses the potential effect of including or excluding certain exposure pathways on the results and conclusions of the SLEA. Subsurface soil intake was not quantitively evaluated in the SLEA. Rather, the SLEA focused on exposure to surface soil (0-0.5 ft bgs) because there is a greater potential for exposure to surface soil and, based on the presumed source of PFAS in soil (i.e., deposition from air), contamination is likely to attenuate with depth. Given the limited number of detections of PFAS in soil, it is not possible to draw reliable conclusions about attenuation with depth. The available data do not exhibit a consistent pattern with respect to leaching potential or attenuation with depth. At EU1 (the EU associated with the highest probability of influence, based on dispersion and deposition patterns), HFPO-DA exhibits an almost order-of-magnitude reduction with depth. PFO2HxA also attenuates significantly, from 2,300 ng/kg in surface soil to non-detect in subsurface soil. At EU3, HFPO-DA attenuates from 360 ng/kg in surface soil to non-detect at depth. At EU4, PFO2HxA attenuates from 1,400 ng/kg in surface soil to ND in subsurface soil. At EUs 4 and 8, HFPO-DA is reported as non-detect in surface soil, with low detections registering with depth. At EU4, PFO2HxA is reported as non-detect in surface soil and 2,300 ng/kg in subsurface soil. Given that exposure to subsurface soil is likely to occur infrequently, if at all, it is reasonable to conclude that the intake of subsurface soil is more than an order of magnitude lower than intake associated with surface soil and further characterization of subsurface soil is not useful for informing risk management decisions. It is also worth noting that collection of soil samples was constrained to available public access roads and rights-of-way. Considering the need for routine roadwork, including regrading, excavation and fill, although attenuation with depth is a reasonable expectation, non-detect results in surface soil extending to detected concentration at depth should not be surprising. Worker exposure to environmental media was not quantitatively evaluated given that residential exposures are expected to be greater and, as a result, risk management actions to define remedial goals predicated on residential exposure and potential hazard will also TR0795 45 December 2019 be protective of workers. Based on the provisional hazard characterization, HFPO-DA in surface soil, untreated well water, and untreated surface water is unlikely to pose a hazard to offsite workers. Dermal contact with soil, drinking water, and surface water by relevant receptors was not quantitatively evaluated because no dermal toxicity criteria have been developed at the federal or state level. Exposure studies indicate dermal uptake in animals is undetectable at low doses typical of environmental exposure and human uptake is more than an order of magnitude lower than animal uptake. For human exposures, dermal exposure is expected to be insignificant relative to ingestion exposure. From a relative ranking perspective and based on the chemico-physical properties of PFAS, dermal absorption from water is likely to be greater than that from soil. Hence, inclusion of the dermal pathway would increase the estimated fraction of total intake that is attributable to drinking water. The increase in intake for HFPO-DA could result in provisional HQs for some RME scenarios that exceed 1; however, the marginal increase would not affect the conclusions of this SLEA. Use of groundwater as irrigation water by farmers and gardeners was not quantitatively evaluated in the SLEA. For this type of use scenario, receptors are primarily exposed to the irrigation water via dermal contact. As discussed above, dermal absorption of PFAS is likely to be insignificant. Irrigation-specific intake is likely to be significantly less than consumption-based intake such that risk management actions to address potable use exposure and potential hazard will also be protective of other groundwater uses. Irrigation water could also represent a source of PFAS to produce. In future empirical produce data would further refine the certainty of exposure estimates. Consumption of livestock (pork, beef or chicken muscle tissue or poultry eggs) by farmers was not quantitatively evaluated in the SLEA. Likewise, exposures related to recreational hunting activities (e.g., venison, waterfowl) also were not assessed. Existing studies target either secondary ingestion targets (e.g., liver, rather than muscle tissue) or focus on a different class of compounds (e.g., the ‘C8’ compounds, such as perfluorooctanoic acid [PFOA] and perfluorooctane sulfonate [PFOS]). Since these complete exposure pathways are presumed to occur, future assessments that include these lines of evidence are expected to reduce the uncertainty associated with exposure assessment. Sediment data were not quantitatively evaluated in the SLEA. For human receptors, sediment exposures, if they occur, are primarily associated with recreationalist populations. Generally, sediment exposures can be considered relative to surface soil exposures. While incidental contact (whether ingestion or dermal contact-based) is generally lower than that associated with surface soil, frequency of exposure is more significantly reduced. Residential contact frequency with surface soil is assessed on the TR0795 46 December 2019 basis of 350 days per year spent at the resident’s primary address, while sediment contact for a recreational user is assessed on the basis of 12 events per year. With all other parameter values assumed to be equivalent, sediment contact and intake is related to approximately 3% of that associated with soil. As soil represents only 1% of the total intake for of Table 3+ PFAS for a typical resident (and HIs under the RME condition do not exceed one for any receptor in any EU), sediment exposures are presumed to be below a level of significance capable of eliciting an effect on site or risk management decisions. Based on bioaccumulative potential, sediments are presumed to have a greater impact on fish tissue concentrations and subsequent recreational fish ingestion by humans. Fish tissue concentrations from local ponds and the Cape Fear River represent direct measurements, influenced by dissolved concentrations as well as incidental sediment ingestion by fish. Therefore, the exposure assessment of human consumption of fish inherently accounts for indirect, food chain-related exposures to constituents in sediment. Given the limited potential for direct contact with sediment and the availability of empirical fish tissue data, the lack of sediment data does not present a significant uncertainty in terms of evaluating direct contact human exposures. However, there is uncertainty in how PFAS move through the environment and concentrate in fish tissue, and sediment data may be informative to characterizing this component of the CSM. Uncertainty in Exposure Assumptions Media-specific EPCs were varied for the CTE and RME scenarios evaluated herein but the receptor-specific exposure assumptions were held constant. Exposure assumptions generally corresponded to USEPA default recommended RME values used in the development of USEPA’s Regional Screening Levels. The conservatism of the RME scenario was compounded by combining RME exposure assumptions with the 95% UCL EPC and is more likely to over-estimate, rather than under-estimate, exposure and hazard. The use of RME exposure assumptions in the CTE scenario also likely over-estimates exposure and hazard, such that none of the combinations used herein represent a “true” CTE scenario (i.e., one that combines average EPCs with average intake estimates). However, from a ranking perspective, the lack of a true CTE scenario is unlikely to have affected the conclusions of the SLEA because for the driving receptor-exposure scenario (i.e., untreated well water consumption), the range of intakes is relatively narrow. 8.4 Uncertainty in the Hazard Characterization The hazard characterization was specific to HFPO-DA based on the availability of toxicity criteria (i.e., NC DHHS RfDo). Therefore, cumulative hazards may be underestimated but data are not available to evaluate the overall effect, if any, on the conclusions of the hazard characterization. The lack of toxicity data, however, does not affect the conclusion that untreated drinking water represents the most significant source TR0795 47 December 2019 of potential PFAS exposure and exposures related to drinking water are significantly reduced as a function of Chemours-implemented groundwater treatment measures. The SLEA provisional hazard characterization for HFPO-DA is based on the RfDo of 1E-04 mg/kg-day adopted by the NC DHHS, which is based on liver toxicity endpoints from two subchronic studies in mice. As described below, the use of this value may under or over-estimate potential HFPO-DA. There is inherent uncertainty in the use of animal toxicity data to characterize potential human health hazards, and this uncertainty is accounted for by the use of UFs used to derive the RfDo. Because many research groups are working in this area, the RfDo could potentially change as new information becomes available that would suggest a different animal model for perfluoroalkyls toxicity or impact the selection of UFs underpinning derivation of the RfDo. The toxicological database for PFAS continues to expand and others have used the available data to develop alternative toxicity values. A recent study of HFPO-DA (Thompson, et al., 2019) has proposed an additional, provisional RfDo predicated on chronic studies in rats and benchmark dose modeling using deterministic and probabilistic techniques. Thompson et al. derived a deterministic RfDo of 0.02 mg/kg-day and a more conservative probabilistic RfDo of 0.01 mg/kg-day; by both calculation methods, these RfDo values indicate a lower potency than indicated by the 2017 NC DHHS RfDo. Notably, NC DHHS previously developed an RfDo of 0.01 mg/kg-day, also based on a 2-year chronic rat study. The decrease in the NC DHHS RfDo and divergence from the RfDo values developed by Thompson et al. stems from two key differences: • Study Duration. Thompson et al., 2019 and the 201y6# NC DHHS RfDo were developed from chronic 2-year chronic animal studies whereas the 2017 NC DHHS RfDo was developed from a subchronic, 28-day animal study. Longer- duration animal studies are more relevant to most human exposure and generally given preference when used to develop toxic potency estimates for humans. The need to incorporate an uncertainty factor to address the subchronic basis of the study results in a ten-fold factor lowering of the resultant RfDo. • Study Species. Thompson et al., 2019 and the 201# NC DHHS RfDo were developed based on liver effects observed in rats whereas the 2017 NC DHHS RfDo was developed from liver effects observed in mice. Hepatocellular hypertrophy and an increased liver-to-body weight ratio are common findings in rodents but are considered non-adverse and less relevant to humans when there is evidence for peroxisome proliferator-activated receptor alpha (PPARα) activation (USEPA, 2018a). It is generally agreed that humans and nonhuman primates are refractory, or at least significantly less responsive than rodents, to PPARα- TR0795 48 December 2019 mediated effects (Corton et al., 2014; Klaunig et al., 2003; Maloney and Waxman, 1999). Although mice appear to be the more sensitive species to HFPO-DA based on the observed effect levels, the liver lesions in mice are consistent with PPARα activation and, hence, the observed effects are not relevant to humans. Table 4 presents a comparison of projected RME hazard indices for the maximally- exposed populations for each EU, predicated on use of the NC DHHS and Thompson RfDo values. Table 4 also includes hazards calculated based on the USEPA draft RfDo (developed using methods similar to NC DHHS) that tend to indicate HFPO-DA has a 25% higher potency than the NC DHHS RfDo. It is notable that under each condition, projected hazard indices are equal to or less than 1, indicating no exceedance of available health benchmarks or of USEPA’s threshold for identifying a potential human health hazard, even in the absence of drinking water treatment. There is very little difference between the projected hazard estimates predicated on the NC DHHS and USEPA values, with the USEPA RfDo representing a slightly more conservative value resulting in marginal increases of associated hazard. The Thompson study-based RfDo represents a significant change in associated hazard, with a two order-of-magnitude reduction. If viewed as a bounding estimate along with the NC DHHS-based criterion, it provides for a range of potential hazard to support risk management in consideration of the inherent conservatism incorporated into risk characterization methodologies. Of further note, is the fact that these projected hazard indices represent pre-treatment conditions for drinking water or an assumed concentration of 10 ng/L which is the maximum concentration of HFPO-DA that would not require a treatment system. With the imposition of residential treatment systems in the vicinity of the Facility, PFAS concentrations in well water are substantially reduced such that exposure via the drinking water pathway may be as low as zero. TR0795 49 December 2019 9 CONCLUSIONS This section summarizes the SLEA and its results, which are tabulated in Table 3. The objectives of the SLEA were to develop EPCs for Table 3+ PFAS in offsite environmental media, quantify and rank potential intake from these media for assumed receptor populations, and provide a provisional estimate of potential human health hazard. Based on the existing CSM and to characterize the regional distribution of PFAS in the vicinity of the Facility, the study area was evaluated on an EU-basis, consisting of 12 upland EUs, five Cape Fear River EUs, one onsite pond EU, and one offsite pond EU. The nature and extent of Table 3+ PFAS in the vicinity of the Facility were characterized using air emission rates, soil, untreated well water, untreated surface water, and fish tissue data collected between 2017 and 2019. Additionally, a current conditions drinking water scenario was evaluated based on the treatment requirements of the Consent Order. Based on current use conditions, the SLEA identifies residents, farmers, and gardeners as exposure populations for the upland EUs; recreationalists as exposure populations for the Cape Fear River and ponds; and residential potable water users as exposure populations for untreated surface water from the Cape Fear River collected at public supply intake points (i.e., Bladen and Kings Bluffs). Potential intake was calculated using RME exposure assumptions and a range of EPCs for each environmental/contact medium. Based on available toxicity data, the intake characterization focuses on ingestion pathways. Although the SLEA focuses on potentially complete exposure pathways, it is important to note that the exposure assumptions do not represent an actual receptor; in reality, some (or all) of these assumed exposure pathways may be incomplete for an actual receptor. The SLEA identifies untreated well water as the primary source of potential PFAS intake, and hence, exposure. However, even in the absence of treatment, no hazard was identified for offsite resident, gardener, and farmer populations exposed to soil, well water, and produce in the vicinity of the Facility. For residents, intake of PFAS from direct exposure to soil was insignificant relative to the RfDo and in comparison to domestic use of well water. Residential intake of PFAS from untreated well water accounted for greater than 96% of the total intake and was two or more orders of magnitude greater than intake from soil. For gardeners and farmers, the contribution from soil was also insignificant relative to consumption of untreated well water; however, due to a lack of empirical produce data, there is uncertainty in the total intake estimates for farmers and gardeners and in the relative contributions from homegrown produce and untreated drinking water. The modeled produce concentrations and measured non-edible grass concentrations provide a preliminary indication that produce consumption is unlikely to pose a hazard under TR0795 50 December 2019 current conditions and, due to Facility air emissions reductions, the potential for exposure will further decrease in the future. Finally, regardless of the contribution of homegrown produce to potential intake, replacement drinking water and drinking water filtration systems reduces overall exposures and potential hazard to upland receptors. The SLEA indicated that recreational exposure to surface water and recreational fish consumption is unlikely to be a significant source of PFAS intake and, based on the provisional hazard characterization, HFPO-DA does not pose a human health hazard. The relative contribution of surface water and fish consumption to recreationalists’ total intake estimates varied between EUs; no concentration gradient was apparent based on the fish fillet data, no species-specific relationships were apparent, and no correlation to surface water concentration was apparent. Hence, there is uncertainty associated with the bioconcentration mechanisms for fish. It is also notable that the maximum detected PFAS fish tissue concentrations were measured in fish fillet samples collected from the sample point farthest downstream from the Facility (i.e., Bladen Bluffs), indicating there is uncertainty with respect to the spatial distribution of PFAS in the Cape Fear River and impact on fish fillet data. Under current conditions, no human health hazards from HFPO-DA were identified for consumptive use of untreated surface water from the Bladen and Kings Bluffs public supply intake points. In summary, the SLEA demonstrates that current concentrations of HFPO-DA in the environment in the vicinity of the Facility are unlikely to pose a hazard to human health, even in the absence of groundwater treatment. The Chemours-provided drinking water treatment systems have effectively reduced Table 3+ PFAS concentrations in residential wells (i.e., the primary source of potential PFAS intake) such that in the vicinity of the Facility, the population’s potential for Table 3+ PFAS exposure via domestic water has substantially decreased. Due to Facility air emissions reductions, the potential for exposure to PFAS in environment media will continue to decrease over time. TR0795 51 December 2019 10 REFERENCES Chemours, 2019. Chemours’ Proposed Toxicity Study Work Plan Pursuant to Paragraph 14 of the Consent Order. Chemours Fayetteville Works. March 27, 2019. Corton, JC, ML Cunningham, BT Hummer, C Lau, B Meek, JM Peters, J Popp, L Rhomberg, J See, and JE Klaunig, 2014. 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Environmental Levels and Distribution of Structural Isomers of Perfluoroalkyl Acids After Aqueous Fire- Fighting Foam (AFFF) Contamination. Environmental Chemistry, 8(4): 372-380. Klaunig JE, MA Babich, KP Baetcke, JC Cook, JC Corton, RM David, JG DeLuca, DY Lai, RH McKee, JM Peters, RA Roberts, and PA Fenner-Crisp, 2003. PPARα Agonist- Induced Rodent Tumors: Modes of Action and Human Relevance. Crit Rev Toxicol, 33(6): 655-780. TR0795 53 December 2019 Lewis, WM and S Flickinger, 1967. Home Range Tendency of the Largemouth Bass (Micropterus salmoides). Ecology, 48(6). 1020-23. Maloney EK and DJ Waxman, 1999. trans-Activation of PPARalpha and PPARgamma by Structurally Diverse Environmental Chemicals. Toxicol Appl Pharmacol, 161(2): 209- 18. Mueller R and V Yingling, 2018. Environmental Fate and Transport for Per- and Polyfluoroalkyl Substances. Interstate Technology Regulatory Council. NCDEQ (North Carolina Department of Environmental Quality), 2015. Registered Environmental Consultant Program, Implementation Guidance. October 2015. NCDEQ and NC DHHS, 2018. Secretaries’ Science Advisory Board Review of the North Carolina Drinking Water Provisional Health Goal for GenX, DRAFT. August 29, 2018. NC DHHS (North Carolina Department of Health and Human Services) (2017). DHHS Drinking Water Advisory Decision Matrix. Presented to the NC SAB December 4, 2017. Available at: https://deq.nc.gov/news/hot-topics/genx-investigation/secretaries-science- advisory-board Pan, Y., Zhang, H., Cui, Q., Sheng, N., Yeung, L., Guo, Y., Sun, Y., and Dai, J. (2017). First Report on the Occurrence and Bioaccumulation of Hexafluoropropylene Oxide Trimer Acid: An Emerging Concern. Environ Sci Technol, 51(17): 9553-60. Parsons, 2014. Final RCRA Facility Investigation Report (Rev. 1). February 2014; Revised August 2014. Parsons, 2017a. Technical Memorandum. Cape Fear River Surface Water Sampling Plan. 22 September 2017. Parsons, 2017b. Technical Memorandum. Cape Fear River Surface Water Sampling Memorandum. 3 November 2017. Parsons, 2017c. Residential Drinking Water Well Surveying Memorandum. Fayetteville Works Facility Fayetteville, North Carolina. 7 November 2017. Parsons, 2018a. Comprehensive Residential Sampling Through the End of Phase 2. Fayetteville Works Facility Fayetteville, North Carolina. 29 March 2018. Parsons, May 2018b. Comprehensive Residential Sampling Through March 4, 2018 of Phase 4. Fayetteville Works Facility Fayetteville, North Carolina. May 2018. Thompson, C, S Fitch, C Ring, W Rish, J Cullen, and L Haws, 2019. Development of an Oral Reference Dose for the Perfluorinated Compound GenX. J Appl Toxicol, 39(9): 1267-82. TR0795 54 December 2019 USEPA (United States Environmental Protection Agency), 1989. Risk Assessment Guidance for Superfund, Volume I: Human Health Evaluation Manual (Part A), Interim Final. Office of Emergency and Remedial Response, Washington, DC. EPA/540/1-89/002, December. USEPA, 1992. Guidelines for Exposure Assessment. Risk Assessment Forum, Washington, DC. EPA/600/Z-92/001, May. USEPA, 2004. Risk Assessment Guidance for Superfund, Volume I: Human Health Evaluation Manual (Part E, Supplemental Guidance for Dermal Risk Assessment), Final. Office of Superfund Remediation and Technology Innovation, Washington, DC. EPA/540/R/99/005, OSWER 9285.7-02EP, PB99-963312. July. USEPA, 2005. Human Health Risk Assessment Protocol for Hazardous Waste Combustion Facilities. September. USEPA, 2009. Guidance for Labeling Externally Validated Laboratory Analytical Data for Superfund Use. Office of Solid Waste and Emergency Response, Washington, DC. OSWER No. 9200.1-85, EPA 540-R-08-005. January. USEPA, 2011. Exposure Factors Handbook: 2011 Edition. National Center for Environmental Assessment, Office of Research and Development, Washington, DC. EPA/600/R09/052F, September. USEPA, 2014. Human Health Evaluation Manual, Supplemental Guidance: Update of Standard Default Exposure Factors. Office of Solid Waste and Emergency Response. OSWER Directive 9200.1-120, February. USEPA, 2015a. ProUCL Version 5.1 Technical Guide. Statistical Software for Environmental Applications for Data Sets with and without Nondetect Observations. Prepared by Singh, A. and A.K. Singh. EPA/600/R-07/041, October. USEPA, 2015b. Frequently Asked Questions (FAQs) About Update of Standard Default Exposure Factors. OSWER Directive 9285.6-03, February 24, 2015. USEPA, 2016. Guidelines for Human Exposure Assessment, Peer Review Draft. Risk Assessment Forum. Washington, DC, January 7. USEPA, 2017. Update for Chapter 5 of the Exposure Factors Handbook, Soil and Dust Ingestion. National Center for Environmental Assessment, Office of Research and Development, Washington, DC. EPA/600/R-17/384F, September. USEPA, 2018a. Public Comment Draft, Human Health Toxicity Values for Hexafluoropropylene Oxide (HFPO) Dimer Acid and Its Ammonium Salt (CASRN 13252-13-6 and CASRN 62037-80-3). Office of Water, Washington, DC. EPA-823-P- 18-001, November. TR0795 55 December 2019 USEPA, 2018b. Update for Chapter 9 of the Exposure Factors Handbook, Intake of Fruits and Vegetables. National Center for Environmental Assessment, Office of Research and Development, Washington, DC. EPA/600/R-18/098F, August. USEPA, 2018c. Update for Chapter 11 of the Exposure Factors Handbook, Intake of Meats, Dairy Products, and Fats. National Center for Environmental Assessment, Office of Research and Development, Washington, DC. EPA/600/R-17/485F, April. USEPA, 2018d. Region 4 Human Health Risk Assessment Supplemental Guidance. Scientific Support Section, Superfund Division, EPA Region 4. March 2018. USEPA, 2019a. Regional Screening Levels (RSLs) for Chemical Contaminants at Superfund Sites, November. Available at: https://www.epa.gov/risk/regional- screening-levels-rsls-generic-tables USEPA, 2019b. Update for Chapter 3 of the Exposure Factors Handbook, Ingestion of Water and Other Select Liquids. National Center for Environmental Assessment, Office of Research and Development, Washington, DC. EPA/600/R-18/259F, February. Visscher PT, CW Culbertson, and RS Oremland, 1994. Degradation of Trifluoroacetate in Oxic and Anoxic Sediments. Nature, 369(6483): 729-31. Weber AK, LB Barber, DR LeBlanc, EM Sunderland, and CD Vecitis, 2017. Geochemical and Hydrologic Factors Controlling Subsurface Transport of Poly- and Perfluoroalkyl Substances, Cape Cod, Massachusetts. Environ Sci Technol, 51(8): 4269- 79. TR0795 December 2019 TABLES TABLE 1TABLE 3+PFAS EVALUATED IN THE SLEAChemours Fayetteville Works, North CarolinaGeosyntec Consultants of NC P.C.HFPO-DA Hexafluoropropylene oxide dimer acidC6HF11O3XXPEPA Perfluoroethoxypropyl carboxylic acidC5HF9O3XXPFECA-G Perfluoro-4-isopropoxybutanoic acidC12H9F9O3SXXPFMOAA Perfluoro-2-methoxyaceticacidC3HF5O3XXPFO2HxA Perfluoro(3,5-dioxahexanoic) acidC4HF7O4XXPFO3OA Perfluoro(3,5,7-trioxaoctanoic) acidC5HF9O5XXPFO4DA Perfluoro(3,5,7,9-tetraoxadecanoic) acidC6HF11O6XXPMPA Perfluoromethoxypropyl carboxylic acidC4HF7O3XXHydro-EVE Acid Perfluoroethoxsypropanoic acidC8H2F14O4XEVE Acid Perflouroethoxypropionic acidC8HF13O4XPFECA B Perfluoro-3,6-dioxaheptanoic acidC5HF9O4XR-EVE R-EVEC8H2F12O5XPFO5DA Perfluoro-3,5,7,9,11-pentaoxadodecanoic acid C7HF13O7XXByproduct 4 Byproduct 4C7H2F12O6SXByproduct 6 Byproduct 6C6H2F12O4SXByproduct 5 Byproduct 5C7H3F11O7SXNVHOS Perflouroethoxysulfonic acidC4H2F8O4SXPES Perfluoroethoxyethanesulfonic acidC4HF9O4SXPFESA-BP1 Byproduct 1C7HF13O5SXXPFESA-BP2 Byproduct 2C7H2F14O5SXXNotes:CASN - Chemical Abstract Service NumberSLEA - Screening Level Exposure AssessmentTable 3+ ConstituentChemical AbbreviationChemical Name Chemical FormulaConsent Order ConstituentTR0795December 2019 TABLE 2CLASSIFICATION OF TABLE 3+ PFASChemours Fayetteville Works, North CarolinaGeosyntec Consultants of NC P.C.aR-C=CaaR-CO2HbR-SO3HcHFPO-DAHexafluoropropylene oxide dimer acid13252-13-6C6HF11O3Per 1 Branched ---- --PFECA-GPerfluoro-4-isopropoxybutanoicacid801212-59-9C7H1F13O1Per 1 Branched ---- --PMPAPerfluoromethoxypropylcarboxylic acid13140-29-9C4HF7O3Per 1 Branched ---- --PEPAPerfluoroethoxypropylcarboxylic acid267239-61-2C5HF9O3Per 1 Branched ---- --PFMOAA Perfluoro-2-methoxyacetic acid 674-13-5C3HF5O3Per 1 Linear ---- --PFO2HxA Perfluoro(3,5-dioxahexanoic) acid 39492-88-1C4HF7O4Per 2 Linear ---- --PFECA BPerfluoro-3,6-dioxaheptanoicacid151772-58-6C5HF9O4Per 2 Linear ---- --PFO3OAPerfluoro(3,5,7-trioxaoctanoic)acid39492-89-2C5HF9O5Per 3 Linear ---- --StructurePer- and polyfluoroalkyl ether carboxylic acids (PFECAs)Common Name Chemical NameCAS # FormulaDegree of FluorinationEther BondsIsomer typeFunctional GroupsDiproticdTR0795Page 1 of 3December 2019 TABLE 2CLASSIFICATION OF TABLE 3+ PFASChemours Fayetteville Works, North CarolinaGeosyntec Consultants of NC P.C.aR-C=CaaR-CO2HbR-SO3HcStructureCommon Name Chemical Name CAS # FormulaDegree of FluorinationEther BondsIsomer typeFunctional GroupsDiproticdPFO4DAPerfluoro(3,5,7,9-tetraoxadecanoic)acid39492-90-5C6HF11O6Per 4 Linear ---- --PFO5DAPerfluoro-3,5,7,9,11-pentaoxadodecanoic acid39492-91-6C7HF13O7Per 5 Linear ---- --Hydro-EVEAcidPerfluoroethoxsypropanoicacid773804-62-9C8H2F14O4Poly 2 Branched ---- --EVE AcidPerfluoroethoxypropionicacid69087-46-3C8HF13O4Per 2 Branched-- --R-EVE R-EVE N/AC8H2F12O5Per 1 Branched ----PESPerfluoroethoxyethanesulfonicacid113507-82-7C4HF9O4SPer 1 Linear -- ----NVHOSPerfluoroethoxysulfonicacid1132933-86-8C4H2F8O4SPoly 1 Linear -- ----Byproduct 6 Byproduct 6 N/AC6H2F12O4SPoly 1 Branched -- ----Per- and polyfluoroalkyl ether sulfonic acids (PFESAs)TR0795Page 2 of 3December 2019 TABLE 2CLASSIFICATION OF TABLE 3+ PFASChemours Fayetteville Works, North CarolinaGeosyntec Consultants of NC P.C.aR-C=CaaR-CO2HbR-SO3HcStructureCommon Name Chemical Name CAS # FormulaDegree of FluorinationEther BondsIsomer typeFunctional GroupsDiproticdByproduct 2Byproduct 2749836-20-2C7H2F14O5SPoly 2 Branched -- ----PFESA-BP1 Byproduct 1 29311-67-9C7HF13O5SPer 2 Branched----Byproduct 4 Byproduct 4 N/AC7H2F12O6SPer 1 Branched --Byproduct 5 Byproduct 5 N/AC7H3F11O7SPoly 2 Branched --Notes:d Compound with two acid functional groupsPer- and polyfluoroalkyl ether sulfonic and carboxylic acids (PFES-CAs)a Carbon double bond functional groupb Carboxylic acid functional groupc Sulfonic acid functional groupTR0795Page 3 of 3December 2019 TABLE 3INTAKE CHARACTERIZATION AND PROVISIONAL HAZARD CHARACTERIZATION SUMMARYChemours Fayetteville Works, North CarolinaGeosyntec Consultants of NC P.C.mg/kg-day mg/kg-day mg/kg-day mg/kg-day unitless unitless mg/kg-day mg/kg-day unitlessEU1 2.5 km, Northeast2E-04 5E-04 4E-05 8E-050.40.81E-05 7E-060.07EU2 2.5 km, Southeast3E-04 4E-04 3E-05 6E-050.30.63E-06 5E-07 0.005EU3 2.5 km, Southwest1E-04 2E-04 2E-05 3E-050.20.34E-06 1E-060.01EU4 2.5 km, Northwest4E-05 5E-05 7E-06 1E-050.070.13E-06 5E-07 0.005EU5 5 km, Northeast7E-05 1E-04 2E-05 2E-050.20.24E-06 5E-07 0.005EU6 5 km, Southeast3E-05 5E-05 5E-06 9E-060.050.093E-06 5E-07 0.005EU7 5 km, Southwest5E-05 7E-05 1E-05 2E-050.10.23E-06 5E-07 0.005EU8 5 km, Northwest1E-05 2E-05 3E-06 5E-060.030.053E-06 5E-07 0.005EU9 10 km, Northeast2E-05 3E-05 3E-06 5E-060.030.053E-06 5E-07 0.005EU10 10 km, Southeast1E-05 2E-05 7E-07 1E-06 0.0070.013E-06 5E-07 0.005EU11 10 km, Southwest1E-05 2E-05 2E-06 2E-060.020.023E-06 5E-07 0.005EU12 10 km, Northwest8E-06 9E-06 8E-07 1E-06 0.0080.013E-06 5E-07 0.005EU13 CFR, 10 mi. Upstream1E-07 4E-07 5E-09 5E-09 0.00005 0.00005 n/an/an/aEU14 CFR, Site-Adjacent7E-07 1E-06 2E-08 3E-08 0.0002 0.0003n/an/an/aEU15 CFR, 4 mi. Downstream1E-06 2E-06NDNDNDNDn/an/an/aEU16 CFR, Bladen Bluffs1E-05 5E-05 6E-06 1E-050.060.1n/an/an/aEU17 CFR, Kings Bluffs1E-07 2E-07 2E-08 2E-08 0.0002 0.0002n/an/an/aEU18 Onsite Pond 13E-06 3E-06 7E-07 8E-07 0.007 0.008n/an/an/aEU19 Offsite Pond B1E-06 1E-06 3E-07 3E-07 0.003 0.003n/an/an/aEU16 (Intake Point) CFR, Bladen Bluffs9E-06 2E-050.090.2n/an/an/aEU17 (Intake Point) CFR, Kings Bluffs4E-06 5E-06 8E-07 9E-07 0.008 0.009n/an/an/aNotes:[1] This summary table presents the calculated intakes and HQs for the most sensitive receptor for a given EU scenario.[3] Only HFPO-DA data were available for surface water intake exposure points.Abbreviations:"--" - not available/not calculatedmg/kg-day - milligram(s) of constituent intake per kilogram of body weight per dayn/a - not applicableND - constituent not detectedCFR - Cape Fear RiverRfDo - non-cancer oral reference doseCTE - central tendency exposureRME - reasonable maximum exposureEU - Exposure UnitSW - surface waterHFPO-DA - Hexafluoropropylene oxide dimer acidNC DHHS - North Carolina Department of Health and Human ServicesHQ - hazard quotientRelevant Exposure Media with Untreated Drinking Water Data [2]Relevant Exposure Media with Current Conditions Drinking Water [2]Table 3+ PFAS IntakeHFPO-DA IntakeHFPO-DA HazardTable 3+ PFAS IntakeHFPO-DA IntakeHFPO-DA HazardEU DescriptionReceptor [1]ExposureMedia [2]CTE RME[2] Intake estimates for EU1 through EU12 were calculated using (1) untreated well water data collected between 2017 and 2019 and (2) based on presumed maximum concentrations under current conditions, which correspond to 70 ng/L for total PFAS and 10 ng/L for HFPO-DA. Hazard estimates for EU1 through EU12 were calculated using (1) untreated well water data collected between 2017 and 2019 and (2) based on a presumed maximum concentration of 10 ng/L for HFPO-DA.RME HQOffsite Child Gardener(Age 0-6)• Surface Soil• Homegrown Produce• Well Water as Drinking WaterOffsite Child Recreationalist (Age 0-6)• Surface Water• Fish Tissue FilletsOffsite Child Resident(Age 0-6)• Untreated CFR Surface Water as Drinking WaterNot Available [3]CTE RME CTE HQ RME HQ RME RMEExposureUnit (EU)TR0795December 2019 TABLE 4SUPPLEMENTAL HAZARD CHARACTERIZATION BASED ON ALTERNATIVE RfD VALUESChemours Fayetteville Works, North CarolinaGeosyntec Consultants of NC P.C.USEPA Draft RfDo = NC DHHSRfDo =Thompson et al. RfDo =USEPA Draft RfDo = NC DHHSRfDo =Thompson et al. RfDo =8.00E-05 1.00E-04 1.00E-02 8.00E-05 1.00E-04 1.00E-02EU1 2.5 km, Northeast 8E-05 7E-06 1 0.8 0.008 0.08 0.07 0.0007EU2 2.5 km, Southeast 6E-05 5E-07 0.7 0.6 0.006 0.006 0.005 0.00005EU3 2.5 km, Southwest 3E-05 1E-06 0.4 0.3 0.003 0.02 0.01 0.0001EU4 2.5 km, Northwest1E-055E-070.10.10.001 0.006 0.005 0.00005EU5 5 km, Northeast2E-055E-070.30.20.002 0.006 0.005 0.00005EU6 5 km, Southeast9E-065E-070.10.09 0.0009 0.006 0.005 0.00005EU7 5 km, Southwest2E-055E-070.20.20.002 0.006 0.005 0.00005EU8 5 km, Northwest5E-065E-070.060.05 0.0005 0.006 0.005 0.00005EU9 10 km, Northeast5E-065E-070.070.05 0.0005 0.006 0.005 0.00005EU10 10 km, Southeast1E-065E-070.010.01 0.0001 0.006 0.005 0.00005EU11 10 km, Southwest2E-065E-070.030.02 0.0002 0.006 0.005 0.00005EU12 10 km, Northwest1E-065E-070.010.01 0.0001 0.006 0.005 0.00005EU13 CFR, 10 mi. Upstream5E-09n/a0.00006 0.00005 0.0000005 n/an/an/aEU14 CFR, Site-Adjacent3E-08n/a0.0004 0.0003 0.000003 n/an/an/aEU15 CFR, 4 mi. DownstreamNDn/aNDNDNDn/an/an/aEU16 CFR, Bladen Bluffs1E-05n/a0.20.10.001n/an/an/aEU17 CFR, Kings Bluffs2E-08n/a0.0002 0.0002 0.000002 n/an/an/aEU18 Onsite Pond 18E-07n/a0.010.008 0.00008 n/an/an/aEU19 Offsite Pond B3E-07n/a0.004 0.003 0.00003 n/an/an/aEU16 (Intake Point) CFR, Bladen Bluffs2E-05n/a0.20.20.002n/an/an/aEU17 (Intake Point) CFR, Kings Bluffs9E-07n/a0.010.009 0.00009 n/an/an/aNotes:[1] This summary table presents the calculated intakes and HQs for the most sensitive receptor for a given EU scenario.[3] Intake and hazard estimates based on untreated well water data collected between 2017 and 2019.[4] Current conditions intake and hazard estimates are based on assumed drinking water concentrations of 10 ng/L for HFPO-DA (see Section 7 of the Human Health SLEA Report).[5] HQs are calculated for a range of RfDo values, which are discussed as part of the SLEA uncertainty assessment.Abbreviations:"--" - not available/not calculatedmg/kg-day - milligram(s) of constituent intake per kilogram of body weight per dayn/a - not applicableND - constituent not detectedCFR - Cape Fear RiverRfDo - non-cancer oral reference doseEU - Exposure UnitRME - reasonable maximum exposureHFPO-DA - Hexafluoropropylene oxide dimer acidNC DHHS - North Carolina Department of Health and Human ServicesHQ - hazard quotientUSEPA - United States Environmental Protection AgencyOffsite Child Gardener(Age 0-6)Offsite Child Recreationalist (Age 0-6)Offsite Child Resident(Age 0-6)[2] Intake estimates include HFPO-DA from the following sources: EU1 through EU12 - soil, homegrown produce, and drinking water; EU13 through EU19 - surface water and fish tissue; and EU16 and 17 (Intake Point) - surface water as drinking water.HFPO-DA Intake (mg/kg-day) [2]HFPO-DA HazardExposureUnit (EU)EU DescriptionReceptor [1]Untreated Well Water(RME EPC)Current Conditions(10 ng/L)Untreated Well Water (RME EPC) [3,5]Current Conditions (10 ng/L) [4,5]TR0795December 2019 TR0795 December 2019 FIGURES ") ") ") Willis Creek Old Outfall 002 Pond 1 Cape Fear RiverOutfall 002 W.O. Huske Dam Site River Water Intake NC Highway 87Seep A Seep B Seep C Seep D GBCTributary1GeorgiaBranchCreek Facility Location and Features Figure 1Raleigh 2,000 0 2,0001,000 Feet ³ December 2019 Legend ")Facility Features Site Boundary Nearby Tributary Observed Seep (Natural Drainage) Site Drainage Network Notes:1. The outline of the Cape Fear River shown on this figure is approximate (River outline based on compilation of open data sourcesfrom ArcGIS online service and North Carolina Department of Environmental Quality Online GIS - Major Hydro shapefile).2. Basemap sources: Esri, DigitalGlobe, GeoEye, Earthstar Geographics, CNES/Airbus DS, USDA, USGS, AeroGRID, IGN, and theGIS User Community. Chemours Fayetteville Works, North Carolina Areas at Site Chemours Monomers IXM Former DuPont PMDF Area Wastewater Treatment Plant Kuraray SentryGlas®Leased Area Kuraray Trosifol®Leased Area DuPont Polyvinyl FluorideLeased Area Chemours PolymerProcessing Aid Area Power - Filtered andDemineralized WaterProduction Kuraray Laboratory Path: P:\PRJ\Projects\TR0795\Database and GIS\GIS\SLEA\TR0795_HH_Facility_Location_and_Features_Figure.mxd Last Revised: 11/28/2019 Projection: NAD 1983 StatePlane North Carolina FIPS 3200 Feet; Units in Foot US Exposure Route Notes:[1] The SLEA is specific to offsite receptors. [2] Subsurface soil was qualitatively evaluated in the SLEA. [3] Dermal exposure pathways were qualitatively evaluated in the SLEA. [4] Soil particulates and vapors in ambient air are not evaluated in the SLEA as this pathway is unlikely to be significant. [5] Produce concentrations were estimated from soil data and modeled deposition rate data.[6] Sediment data were qualitatively evaluated in the SLEA. Complete exposure pathway quantitatively evaluated in the SLEA. Potentially complete pathway with limited potential for intake that is qualitatively evaluated in the SLEA. Potentially complete pathway evaluated using a higher-exposure receptor, where: • Worker exposure to soil and drinking water was excluded from quantitative evaluation on the basis that risk management based on residents will be protective of the receptor group. • Recreationalist exposure to soil was excluded from quantitative evaluation on the basis that risk management based on residents will be protective of the receptor group. Incomplete or insignificant exposure pathway; no evaluation or management action is necessary.Raleigh Chemours Fayetteville Works, North Carolina Conceptual Exposure Model for Human Exposure to PFAS Historically Deposited Offsite December 2019 Figure 2Recreationalist (Adult and Child)Impacted Media Secondary Impacted Media Resident(Adult and Child)Farmer(Adult and Child)Gardener(Adult and Child)Commercial Worker (Adult)Potentially Exposed Offsite Human Receptors [1] [7] Intake points for domestic water are located at Bladen and Kings Bluffs. Untreated data were used in the SLEA as aconservative estimate of potential intake. Primary Chemical Source Transport Mechanism Transport Mechanism • Resident, farmer, and gardener fish consumption was excluded from quantitative evaluation on the basis that risk management based on recreationalists will be protective ofthese receptor groups. Manufacturing Facility HistoricalEmissions & Releases Incidental Ingestion Bioaccumulation Aquatic Biota Consumption ConsumptionVegetation [5] Consumption(Raw Well Water) Surface Water [6] Surface Soil [2] (0 to 6" bgs) Groundwater Biouptake Homegrown Meat &Dairy Consumption Dermal Contact [3] Volatilization Dust Emission Outdoor Air Inhalation [4] Inhalation Direct Exposure Volatilization Indoor Air Dermal Contact [3] OffsiteParticulate Deposition;Infiltration with Rain Incidental Ingestion Consumption (Raw Surface Water) Direct Exposure Dermal Contact InhalationVolatilizationIndoor Air Dermal Contact Water Treatment Plant Intake Point [7] EU2 EU6 EU10EU11 EU9EU12 EU5 EU7 EU8 EU3 EU1EU4 EU18 EU19 EU14 EU15 EU13 EU16 5 km 2.5 km 10 km Human Health SLEA Exposure Units Chemours Fayetteville Works, North Carolina Figure 3Raleigh ³Path: P:\PRJ\Projects\TR0795\Database and GIS\GIS\SLEA\TR0795_HH_Exposure_Units_Figure.mxd Last Revised: 12/11/2019 December 2019 Projection: NAD 1983 StatePlane North Carolina FIPS 3200 Feet; Units in Foot US N S W E Notes:EU = Exposure Unitkm = KilometerSLEA = Screening Level Exposure Assessment1. Black lines represent cardinal directions (N, E, S, W).2. Basemap Sources: Esri, HERE, Garmin, Intermap, increment P Corp., GEBCO, USGS, FAO, NPS, NRCAN, GeoBase, IGN, KadasterNL, Ordnance Survey, Esri Japan, METI, Esri China (Hong Kong), (c) OpenStreetMap contributors, and the GIS User Community. Site Boundary EU## EU## Legend Upland EU Surface water EU 3 0 31.5 Kilometers 2 0 21Miles !( !( !(!( !( !( !(!( !( !(!(!(!( !(!( !( !( !(!( !( !( !(!(!( !( !( !(!( !( !( !( !(!( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !(!(!( !( !( !( !( !( !( !( !( !(!(!( !( !(!(!(!(!(!( !( !(!( !(!( !( !(!( !( !( !( !(!(!( !( !(!(!(!( !( !(!( !(!(!( !( !( !( !( !( !( !( !(!( !( !( !( !(!(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !(!( !( !( !( !(!( !( !( !(!(!( !(!( !(!( !(!( !(!( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !(!( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !(!( !( !( !( !(!( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !A !A !A !A !A !A !A !A !A !A !A !A > > > EU2 EU6 EU10EU11 EU9EU12 EU5 EU7 EU8 EU3 EU1EU4 Human Health SLEA Soil Sampling Locations Chemours Fayetteville Works, North Carolina Figure 4Raleigh ³Path: P:\PRJ\Projects\TR0795\Database and GIS\GIS\SLEA\TR0795_HH_Soil_Sample_Locations_Figure.mxd Last Revised: 12/11/2019 December 2019 Projection: NAD 1983 StatePlane North Carolina FIPS 3200 Feet; Units in Foot US N S W E Notes:EU = Exposure UnitISM = Incremental Sampling MethodologySLEA = Screening Level Exposure Assessment1. Each point represents a single ISM subsample which was composited into a single sample for each EU.2. Black lines represent cardinal directions (N, E, S, W).3. Basemap Sources: Esri, HERE, Garmin, Intermap, increment P Corp., GEBCO, USGS, FAO, NPS, NRCAN, GeoBase, IGN, KadasterNL, Ordnance Survey, Esri Japan, METI, Esri China (Hong Kong), (c) OpenStreetMap contributors, and the GIS User Community. Legend >Co-Located Surface/SubsurfaceSoil Location !A Subsurface Discrete SoilLocation Site Boundary !(EU1 (31) !(EU2 (31) !(EU3 (31) !(EU4 (31) !(EU5 (30) !(EU6 (31) !(EU7 (30) !(EU8 (30) !(EU9 (31) !(EU10 (31) !(EU11 (31) !(EU12 (31) EU Surface ISM Soil Location and Increment Counts 3 0 31.5 Kilometers 2 0 21Miles !( !( !( !(!( !( !(!( !( !(!( !(!( !( !( !( !( !( !( !( !(!( !( !(!( !( !(!( !( !( !(!( !(!( !(!( !( !( !( !( !( !( !(!( !( !( !(!( !(!( !( !( !( !(!( !(!(!( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !(!( !(!(!(!(!( !( !( !( !(!( !( !(!( !( !( !( !( !(!(!( !( !( !( !(!(!( !( !( !( !( !( !(!( !( !( !(!( !( !( !(!( !(!(!( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!(!( !( !( !( !( !( !( !(!(!( !( !( !( !( !( !( !( !(!(!( !(!( !(!( !( !( !( !(!( !( !(!( !(!( !(!( !( !(!( !( !(!( !( !( !(!(!( !( !( !( !( !( !( !( !( !( !( !(!( !( !(!( !( !( !(!(!(!(!( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !(!( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !(!( !( !( !( !( !( !(!( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!(!(!( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !(!(!(!( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !(!( !(!( !( !(!( !( !(!( !( !(!( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !(!( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !(!( !( !( !(!( !(!( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!(!(!( !( !( !(!( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !(!( !(!( !(!( !( !( !( !( !( !(!(!( !( !(!( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !(!( !( !( !(!(!(!( !(!( !( !( !( !(!(!(!( !(!( !( !( !(!(!(!( !(!( !( !( !( !(!(!(!(!( !( !(!(!(!(!( !( !( !( !( !( !( !( !( !( !(!(!(!( !( !( !(!( !( !( !( !( !(!(!(!(!(!( !( !(!(!(!( !( !( !( !( !( !( !( !( !( !(!(!( !( !( !(!(!( !( !( !( !( !( !( !( !( !( !(!( !( !(!( !( !(!( !(!(!(!(!( !( !( !( !( !( !(!( !(!( !( !( !( !( !(!(!( !(!( !(!( !( !(!(!( !( !( !(!( !( !(!(!(!( !( !( !( !(!( !( !( !( !( !(!( !(!( !( !( !( !( !(!( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !(!(!(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !(!(!( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !(!(!(!( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !(!( !( !( !( !( !( !( !(!( !(!( !( !( !(!(!( !( !( !( !( !( !( !( !( !( !( !(!(!( !( !(!(!(!(!(!( !( !(!( !( !( !( !( !(!(!(!(!( !( !(!(!(!(!( !( !( !( !(!(!( !( !( !( !( !( !( !(!( !( !(!( !( !( !( !( !( !( !(!(!( !( !( !(!( !( !( !( !(!( !( !(!( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !( !( !(!( !( !(!( !(!(!( !( !( !(!( !( !(!(!( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !(!(!( !( !(!( !(!( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !( !(!( !( !(!( !(!( !( !( !( !( !( !(!( !( !( !(!(!( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !(!( !( !( !( !( !(!( !(!( !(!( !( !( !( !( !(!( !(!( !( !( !( !( !( !( !( !( !(!(!(!(!( !(!( !( !( !( !( !( !(!( !( !(!( !( !( !( !( !( !(!( !( !(!( !( !( !( !( !( !( !( !( !( !(!( !( !( !(!(!(!( !( !(!(!( !( !( !( !( !( !( !( !( !( !( !(!(!(!(!(!( !( !( !( !( !( !(!( !( !(!( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !(!( !(!(!( !( !( !(!( !( !( !( !(!( !( !( !( !( !( !( !( !( !(!(!(!( !(!( !( !( !(!( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !(!(!( !( !(!( !( !( !(!( !( !( !( !( !(!( !(!( !( !( !( !( !( !( !( !( !(!(!( !( !( !( !( !( !(!( !( !(!(!(!( !( !( !( !(!(!( !( !( !( !(!( !( !( !( !( !( !( !( !(!(!( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !( !(!(!(!(!(!(!( !( !( !( !( !( !( !(!( !(!( !(!( !( !( !(!( !( !( !( !( !( !(!( !( !(!(!(!( !( !( !( !( !( !( !( !(!( !(!( !( !(!( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !( !( !( !(!( !(!( !( !( !(!(!( !( !( !( !(!(!(!(!(!(!(!( !( !( !(!( !( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !(!( !( !( !( !( !(!( !(!( !( !( !( !( !(!( !( !( !( !( !( !( !(!( !( !( !(!( !( !( !(!(!( !( !( !( !( !(!(!(!( !( !(!( !( !( !(!( !( !(!( !(!(!( !( !(!( !( !( !( !(!(!(!( !(!( !(!(!(!(!( !( !( !( !(!(!(!(!(!( !(!( !( !( !(!( !( !( !( !( !(!( !( !( !( !( !( !( !( !( !(!( !( !( !( !( !( !(!( !(!( !(!( !(!(!( !(!( !(!(!( !(!(!( !(!(!( !( !( !( !(!(!(!( !( !( !(!(!( !(!(!(!(!( !(!( !(!( !( !( !(!( !(!(!(!(!( !( !(!(!( !( !( !( !(!( !( !(!( !( !( !( !( !( !( !( !( !(!(!(!( !(!(!(!(!( !( !( !( !( !( !(!( !( !( !( !( !( !( !(!(!(!(!(!(!(!( !( !(!(!( !( !( !( !(!(!( !(!(!(!( !( !( 6 mi 4 mi 2 mi EU2 EU6 EU10EU11 EU9EU12 EU5 EU7 EU8 EU3 EU1EU4 Human Health SLEA Untreated Well WaterSampling Locations Chemours Fayetteville Works, North Carolina Figure 5Raleigh ³Path: P:\PRJ\Projects\TR0795\Database and GIS\GIS\SLEA\TR0795_EU_GW_Sample_Locations.mxd Last Revised: 12/11/2019 December 2019 Projection: NAD 1983 StatePlane North Carolina FIPS 3200 Feet; Units in Foot US N S W E Notes:EU = Exposure UnitSLEA = Screening Level Exposure Assessment1. Black lines represent cardinal directions (N, E, S, W).2. Basemap Source: Esri, DigitalGlobe, GeoEye, Earthstar Geographics, CNES/Airbus DS, USDA, USGS, AeroGRID, IGN, andthe GIS User Community. Legend !(Offsite Drinking Water Well Locations Site Boundary 3 0 31.5 Kilometers 2 0 21Miles Cape Fear River Surface Water Sampling Diagram Chemours Fayetteville Works, North Carolina Figure 6RaleighDecember 2019 West (Site side) East Thalweg*, Middle depth *Thalweg: Deepest part of the channel cross section East West East Center Top Center Middle West (Site side) 2018 Regional Program, 2018 Post-Florence, and Spring 2019 Surface Water Sampling 2017-2018 Local Program and 2019 SLEA Surface Water Sampling Sampling Location Selection Rationale: Assess how concentrations differ across cross-section, particularly close to Site Sampling Location Selection Rationale: Assess how concentrations vary along the length of the river. The majority of flow occurs at the thalweg, which is typically the most mixed part of river and expected to be representative of average concentrations. 25 % of river width #* #* #* #* #* #* #* #* !(!(!( !(!(!( !(!(!( !( !( !(!( #*#*#*#* #*#*#* #*#*#*#* #*#*#*#*#* !( !(!(!( !(!(!( !(!( !(!(!( !( Pond-1-NE-072419 DERC-1 LMBDERC-2 LMBDERC-3 LMB Pond-1-NW-072419 Pond-1-SE-072419Pond-1-SE-072419-2 CFR-02 CFR-08 Human Health SLEA Fish Fillet andSurface Water Sampling Locations Chemours Fayetteville Works, North Carolina Figure 7Raleigh 2 0 21 Miles ³Path: P:\PRJ\Projects\TR0795\Database and GIS\GIS\SLEA\TR0795_HH_Fish_SW_Sample_Locations_Figure.mxd; Last Revised: 12/11/2019December 2019 Projection: NAD 1983 StatePlane North Carolina FIPS 3200 Feet; Units in Foot US Legend !(Bluegill !(Catfish !(Largemouth Bass !(Redbreasted Sunfish #*Surface Water #*CFR - Cape Fear River SamplingTransects Site Boundary !(!(!(!(!( MM-68-3 BC MM-68-2 CC MM-68-1 FH MM-68-5 LMB MM-68-4 LMB !( #*#*#* #*#*#*#* #*#*#*#*#* !(!(!( !(!(!( #* #* #* #* #* CFR-07 CFR-06 CFR-04 CFR-03 CFR-05 CFR-04-W-072519 CFR-04-E-072519 CFR-06-1 BCCFR-06-2 BCCFR-06-3 BC CFR-05-1-LMBCFR-05-3 BCCFR-05-4 CCCFR-07-E-072519 CFR-07-E-072519-2CFR-07-CT-072519CFR-07-CM-072519 CFR-07-W-072519 CFR-04-CM-072519CFR-04-CT-072519 POND-B-WEST-091219 POND-B-EAST-091219 POND-B-SOUTH-091219 !(!(!( !(!( !( !(!( CFR Bladen-04-LMB CFR Bladen-03-LMB CFR Bladen-01-Bluegill CFR Bladen-04-Redbreast CFR Bladen-02-LMB CFR Bladen-03-Redbreast CFR Bladen-02-Redbreast CFR Bladen-01-Channel catfish EU13 - Upstream EU14 - Site-Adjacent EU16 - Bladen Bluffs 500 0 500250 Feet 2,000 0 2,0001,000 Feet Notes:CFR = Cape Fear RiverSLEA = Screening Level Exposure Assessment1. Topographic Basemap Source: Esri, HERE, Garmin, Intermap, increment P Corp., GEBCO, USGS, FAO, NPS, NRCAN,GeoBase, IGN, Kadaster NL, Ordnance Survey, Esri Japan, METI, Esri China (Hong Kong), (c) OpenStreetMap contributors,and the GIS User Community. 2,000 0 2,0001,000 Feet !(!(!(#* CFR-09 CFR-09-2 BC CFR-09-1 BC CFR-09-1 LMB EU15 - 4 Miles Downstream 1,000 0 1,000500 Feet EU2 EU6 EU10EU11 EU9EU12 EU5 EU7 EU8 EU3 EU1EU4 5 km 2.5 km 10 km Offsite HFPO-DAGroundwater Concentrations Chemours Fayetteville Works, North Carolina Figure 8Raleigh ³Path: P:\PRJ\Projects\TR0795\Database and GIS\GIS\SLEA\TR0795_HH_Offsite_HFPO_DA_GW_Concentrations_2017_2019_Figure.mxd Last Revised: 12/11/2019 December 2019 Projection: NAD 1983 StatePlane North Carolina FIPS 3200 Feet; Units in Foot US N S W E Notes:ng/L = nanograms per literEU = Exposure Unitkm = kilometer1. Black lines represent cardinal directions (N, E, S, W).2. Basemap Sources: Esri, HERE, Garmin, Intermap, increment P Corp., GEBCO, USGS, FAO, NPS, NRCAN, GeoBase, IGN, KadasterNL, Ordnance Survey, Esri Japan, METI, Esri China (Hong Kong), (c) OpenStreetMap contributors, and the GIS User Community. LegendHFPO-DA Concentration (ng/L) Non-detect <10 10 - 70 70 - 140 140 - 1,400 > 1,400 Site Boundary 3 0 31.5 Kilometers 2 0 21Miles TR0795 December 2019 APPENDIX A Consent Order TR0795 December 2019 APPENDIX B Analytical Data Used in the SLEA Geosyntec Consultants of NC P.C.Table B-1Screening-Level Exposure AssessmentAnalytical Data Used in the SLEASurface and Subsurface SoilExposure Unit [1]Depth(ft bgs)Sample ID [2]Sample Date Units HFPO-DA PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPA PEPA PFESA-BP1 PFESA-BP2 Byproduct 4 Byproduct 5 Byproduct 6 NVHOS EVE AcidHydro-EVE AcidR-EVE PES PFECA B PFECA-GEU-01 0-0.5 EU-1-SOIL-0-.5-091219 9/12/2019 ng/kg2,600<1,0002,300<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU-2 0-0.5 EU2-soil-0-0.57/25/2019 ng/kg<250 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU-3 0-0.5 EU-3-soil-0-0.57/31/2019 ng/kg360 J<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU-4 0-0.5 EU-4-SOIL-0-.5-081919 8/19/2019 ng/kg<250 UJ <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU-5 0-0.5 EU-5-SOIL-0-.5-082319 8/23/2019 ng/kg<250 <1,000 UJ1,400 J<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU-6 0-0.5 EU6-soil-0-0.57/25/2019 ng/kg<250 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU-7 0-0.5 EU-7-SOIL-0-.5-081919 8/19/2019 ng/kg<250 UJ <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU-8 0-0.5 EU-8-SOIL-0-.5-081619 8/16/2019 ng/kg<250 UJ <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU-9 0-0.5 EU-9-SOIL-0-.5-082119 8/21/2019 ng/kg<250 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU-10 0-0.5 EU-10-SOIL-0-.5-082119 8/21/2019 ng/kg<250 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU-11 0-0.5 EU-11-soil-0-0.57/31/2019 ng/kg<250 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU-12 0-0.5 EU-12-SOIL-0-.5-082019 8/20/2019 ng/kg<250 UJ <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU-12 DUP 0-0.5 EU-12-SOIL-0-.5-082019-D[3]8/20/2019 ng/kg<250 UJ <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU-01 4-4.5 EU-1-Soil-4-4.5-081419 8/14/2019 ng/kg430 J<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 UJ <1,000 UJ <1,000 <1,000 <1,000 <1,000 <1,000 UJ <1,000 <1,000 <1,000EU-2 4-4.5 EU-2-SOIL-4-4.5-082219 8/22/2019 ng/kg<250 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 UJ <1,000 UJ <1,000 <1,000 <1,000 <1,000 <1,000 UJ <1,000 <1,000 <1,000EU-3 4-4.5 EU-3-SOIL-4-4.5-082219 8/22/2019 ng/kg<250 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU-4 4-4.5 EU-4-Soil-4-4.5-0813198/13/2019 ng/kg590<1,000 UJ2,300 J<1,000 UJ <1,000 UJ <1,000 UJ <1,000 <1,000 <1,000 <1,000 <1,000 R <1,000 R <1,000 <1,000 <1,000 UJ <1,000 UJ <1,000 R <1,000 <1,000 UJ <1,000 UJEU-5 4-4.5 EU-5-SOIL-4-4.5-081519 8/15/2019 ng/kg<250 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 R <1,000 R <1,000 <1,000 <1,000 <1,000 <1,000 R <1,000 <1,000 <1,000EU-6 4-4.5 EU-6-SOIL-4-4.5-081519 8/15/2019 ng/kg<250 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 UJ <1,000 UJ <1,000 <1,000 <1,000 <1,000 <1,000 R <1,000 <1,000 <1,000EU-7 4-4.5 EU-7-Soil-4-4.5-0814198/14/2019 ng/kg<250 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 R <1,000 R <1,000 <1,000 <1,000 <1,000 <1,000 R <1,000 <1,000 <1,000 UJEU-8 4-4.5 EU-8-Soil-4-4.5-0813198/13/2019 ng/kg260<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 R <1,000 R <1,000 <1,000 <1,000 <1,000 <1,000 R <1,000 <1,000 <1,000EU-8 DUP 4-4.5 EU-8-Soil-4-4.5-081319-D[3]8/13/2019 ng/kg400<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 R <1,000 R <1,000 <1,000 <1,000 <1,000 <1,000 R <1,000 <1,000 <1,000EU-9 4-4.5 EU9-SOIL-4-4.5-082719 8/27/2019 ng/kg<250 UJ <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 UJ <1,000 UJ <1,000 <1,000 <1,000 <1,000 <1,000 UJ <1,000 <1,000 <1,000EU-10 4-4.5 EU10-SOIL-4-4.5-082719 8/27/2019 ng/kg<250 UJ <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 UJ <1,000 UJ <1,000 <1,000 <1,000 <1,000 <1,000 UJ <1,000 <1,000 <1,000EU-11 4-4.5 EU-11-SOIL-4-4.5-081519 8/15/2019 ng/kg<250 <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 R <1,000 R <1,000 <1,000 <1,000 UJ <1,000 UJ <1,000 R <1,000 <1,000 UJ <1,000 UJEU-12 4-4.5 EU-12-SOIL-4-4.5-082219 8/22/2019 ng/kg<250 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 R <1,000 R <1,000 <1,000 <1,000 <1,000 <1,000 R <1,000 <1,000 <1,000Definitions:[1] Exposure Units (EUs) are defined as follows:EU1 - 2.5 kilometer radius, northeastEU5 - 5 kilometer radius, northeastEU9 - 10 kilometer radius, northeastEU2 - 2.5 kilometer radius, southeastEU6 - 5 kilometer radius, southeastEU10 - 10 kilometer radius, southeastEU3 - 2.5 kilometer radius, southwestEU7 - 5 kilometer radius, southwestEU11 - 10 kilometer radius, southwestEU4 - 2.5 kilometer radius, northwestEU8 - 5 kilometer radius, northwestEU12 - 10 kilometer radius, northwest[2] Surface soil (0-0.5 ft bgs) results represent composite samples. Subsurface soil (4-4.5 ft bgs) results represent discrete samples[3] The higher of the duplicate and parent result was used in the SLEA intake and risk characterizationNotes:Bold - Analyte detected above associated reporting limit< - Analyte not detected above associated reporting limit. "--" - Data not availableft bgs = feet below ground surfaceJ - Analyte detected. Reported value may not be accurate or preciseng/kg - nanogram(s) per kilogramDUP - field duplicate sampleR - Result rejected based on quality assurance/quality control criteriaUJ – Analyte not detected. Reporting limit may not be accurate or precise. TR0795Page 1 of 1December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPAEU1 1779/15/2017 9/15/2017 ng/L260 --------------------EU1 1789/15/2017 9/21/2017 ng/L343 --------------------EU1 1769/25/2017 9/25/2017 ng/L1000 --------------------EU1 1759/15/2017 3/14/2018 ng/L530 --------------------EU1 1544/11/2018 4/11/2018 ng/L1.81 --------------------EU1 1749/13/2017 11/7/2017 ng/L26.7 --------------------EU1 1739/6/2017 3/28/2018 ng/L586 --------------------EU1 1733/28/2018 3/28/2018 ng/L313 --------------------EU1 1539/22/2017 12/13/2017 ng/L523<20 <2 <2 <2 <5 <2 <2 <2 <260EU1 1729/6/2017 3/9/2018 ng/L300 --------------------EU1 1719/8/2017 9/8/2017 ng/L820 --------------------EU1 1699/15/2017 9/15/2017 ng/L660 --------------------EU1 1699/18/2017 9/18/2017 ng/L430 --------------------EU1 1688/15/2018 8/15/2018 ng/L840 --------------------EU1 1669/14/2017 9/14/2017 ng/L730 --------------------EU1 1519/14/2017 10/8/2019 ng/L4200 820<2 <277 800 4400 580 120 18 2300EU1 1659/6/2017 11/7/2017 ng/L26.5 --------------------EU1 1649/28/2017 9/3/2019 ng/L1000 400<2 <232 270 870 86 35 13 1400EU1 1639/6/2017 9/11/2019 ng/L1200 370<1.1 <1.128 290 830 86 22 12 1600EU1 1629/28/2017 9/3/2019 ng/L890 370<2 <25 200 510 44 11<21300EU1 1609/6/2017 9/25/2019 ng/L<1.76 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU1 2547/20/2018 7/20/2018 ng/L1000 --------------------EU1 1799/6/2017 9/6/2017 ng/L260 --------------------EU1 1819/20/2017 9/20/2017 ng/L<1.76--------------------EU2 2399/18/2017 9/18/2017 ng/L<2.01--------------------EU2 2409/22/2017 8/28/2019 ng/L1200 780<2 <2130 410 1300 160 60 16 3100EU2 2408/6/2018 8/6/2018 ng/L780 --------------------EU3 2846/15/2018 6/15/2018 ng/L530 --------------------EU3 297 10/17/2017 10/17/2017 ng/L400 --------------------EU3 3022/5/2018 2/5/2018 ng/L240 --------------------EU3 305 10/17/2017 10/17/2017 ng/L390 --------------------EU3 312 10/17/2017 11/7/2017 ng/L442 --------------------EU3 2369/7/2017 9/20/2017 ng/L670 --------------------EU3 2379/19/2017 9/10/2019 ng/L1200 570<2 <227 250 810 160 41<21800EU3 7269/18/2017 10/20/2017 ng/L453 --------------------EU3 391 12/20/2017 5/2/2018 ng/L140 --------------------EU3 6369/18/2019 9/18/2019 ng/L62 55<2 <211 17 20<2 <2 <2310EU3 5739/18/2017 10/23/2017 ng/L176 190<50<50<5074 110<50 <50 <100920EU3 689 10/18/2017 10/18/2017 ng/L350 --------------------EU4 439 10/25/2017 10/25/2017 ng/L360 140<2 <225 88 220 17 4.8<2470EU4 2629/21/2017 7/16/2019 ng/L460 220<2 <233 140 470 38 12<2760EU4 4439/29/2017 10/19/2018 ng/L105 --------------------EU4 44410/5/2017 10/5/2017 ng/L420 --------------------Range ofSampling Dates [2]TR0795Page 1 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU4 450 10/20/2017 10/20/2017 ng/L380 -- -- -- -- -- -- -- -- -- --EU4 462 10/24/2017 10/3/2019 ng/L1100 400<2 <244 270 730 48 10<21600EU4 256 9/15/2017 12/13/2017 ng/L76.9 -- -- -- -- -- -- -- -- -- --EU4 255 9/19/2017 9/19/2017 ng/L440 170<50 <50 <5083 280<50 <50 <100680EU4 261 9/15/2017 12/13/2017 ng/L72.8 -- -- -- -- -- -- -- -- -- --EU4 185 9/7/2017 9/7/2017 ng/L670 310<50 <50 <50170 560 88<50 <1001000EU4 190 9/7/2017 9/7/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU4 189 9/15/2017 9/10/2019 ng/L160 130<2 <25.6 52 120 7.8<2 <2440EU4 186 9/20/2017 9/20/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU4 148 9/7/2017 9/19/2017 ng/L20.8<20 <2 <2 <2 <52.1<2 <2 <237EU4 191 9/8/2017 9/8/2017 ng/L<10-- -- -- -- -- -- -- -- -- --EU4 147 9/13/2017 9/20/2017 ng/L55.2 -- -- -- -- -- -- -- -- -- --EU4 498 12/4/2017 8/13/2019 ng/L190 100<1.1 <1.18.1 62 120 7.8 1.8<1.1410EU4 192 9/15/2017 9/15/2017 ng/L14 -- -- -- -- -- -- -- -- -- --EU4 180 9/18/2017 9/20/2017 ng/L<2.29 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU4 250 9/13/2017 9/18/2017 ng/L30 -- -- -- -- -- -- -- -- -- --EU4 249 9/13/2017 9/18/2017 ng/L78.2 -- -- -- -- -- -- -- -- -- --EU4 248 9/13/2017 9/18/2017 ng/L8.4<20 <2 <2 <26.7 7.6<2 <2 <222EU4 247 9/15/2017 9/15/2017 ng/L0.684<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU4 246 9/19/2017 9/19/2017 ng/L<1.83-- -- -- -- -- -- -- -- -- --EU4 245 9/19/2017 9/19/2017 ng/L7.79 -- -- -- -- -- -- -- -- -- --EU4 244 9/19/2017 9/19/2017 ng/L21.1 -- -- -- -- -- -- -- -- -- --EU4 243 10/31/2018 10/31/2018 ng/L10<20 <2 <2 <2 <5 <2 <2 <2 <233EU4 260 9/15/2017 9/21/2017 ng/L170 -- -- -- -- -- -- -- -- -- --EU4 199 9/20/2017 9/20/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU4 198 9/8/2017 9/8/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU4 196 9/8/2017 10/23/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU4 215 10/6/2017 10/6/2017 ng/L140 -- -- -- -- -- -- -- -- -- --EU4 212 9/8/2017 10/6/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU4 213 10/6/2017 10/6/2017 ng/L19 -- -- -- -- -- -- -- -- -- --EU4 214 7/26/2019 7/26/2019 ng/L21<20 <2 <2 <27.2 14<2 <2 <245EU4 218 9/20/2017 9/20/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <215EU42109/8/201710/10/2017 ng/L150 --------------------EU4 2199/8/2017 7/5/2019 ng/L12<20 <2 <2 <2 <54.4<2 <2 <224EU4 2209/8/2017 10/1/2019 ng/L280 110<2 <213 100 180 21 3.9<2460EU4 2349/13/2017 10/10/2019 ng/L350 140<2 <222 130 320 259<2460EU4 2299/7/2017 9/19/2017 ng/L43--------------------EU4 2299/7/2017 9/7/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU4 2319/19/2017 9/19/2017 ng/L<1.75--------------------EU4 2324/23/2019 4/23/2019 ng/L330 86<2 <210 96 210 20 4.9<2310EU4 2429/7/2017 9/7/2017 ng/L47--------------------EU4 2485[3]1/10/2018 1/10/2018 ng/L0--------------------EU5 700 10/18/2017 10/18/2017 ng/L49 -- -- -- -- -- -- -- -- -- --TR0795Page 2 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU5 989 12/15/2017 12/15/2017 ng/L<5.4 <20 <2 <2 <2 <52.3<2 <2 <211EU5 701 10/25/2017 1/31/2018 ng/L527 -- -- -- -- -- -- -- -- -- --EU5 945 11/30/2017 11/30/2017 ng/L20 -- -- -- -- -- -- -- -- -- --EU5 880 11/29/2017 11/29/2017 ng/L<4 <100 <50 <50 <50 <50 <50 <50 <50 <100 <50EU5 1212 8/14/2018 8/14/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 22792/8/2018 2/8/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 2349 1/31/2018 3/28/2018 ng/L1.87<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 22832/7/2018 2/7/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 2378 1/31/2018 4/30/2018 ng/L151 --------------------EU5 2276 1/30/2018 9/17/2019 ng/L150 80<2 <2 <232 27<2 <2 <2450EU5 3165 6/25/2019 6/25/2019 ng/L110 80<2 <2 <230 27<2 <2 <2460EU5 8259/20/2019 9/20/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 2282 2/19/2018 2/19/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 2281 1/31/2018 1/31/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 2350 1/31/2018 1/31/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 22772/6/2018 2/6/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 23472/8/2018 3/28/2018 ng/L1.85<20 <2 <2 <2 <5 <2 <2 <2 <221EU5 2272 1/31/2018 1/31/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <247EU5 2348 2/20/2018 6/3/2019 ng/L26<20 <2 <2 <2 <5 <2 <2 <2 <2100EU5 2270 1/31/2018 1/31/2018 ng/L190 --------------------EU5 2275 1/31/2018 1/31/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 2269 1/31/2018 1/31/2018 ng/L12<100 <50 <50 <50 <50 <50 <50 <50 <10066EU5 5035/2/2018 11/27/2018 ng/L98--------------------EU5 7659/29/2017 10/17/2017 ng/L132 --------------------EU5 7659/29/2017 10/17/2017 ng/L267 --------------------EU5 7659/29/2017 9/29/2017 ng/L112 --------------------EU5 7665/2/2018 11/27/2018 ng/L150 140<50 <50 <5051 78<50 <50 <100580EU5 826 11/30/2017 11/30/2017 ng/L89--------------------EU5 827 11/30/2017 11/30/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 828 11/30/2017 11/30/2017 ng/L34--------------------EU5 144 10/17/2017 8/6/2019 ng/L290 160<1.1 <1.11.5 59 79 1.8<1.1 <1.1600EU5 144 10/17/2017 10/17/2017 ng/L770 --------------------EU5 138 10/17/2017 8/6/2019 ng/L310 260<1.1 <1.16.7 89 150 6.1<1.1 <1.1840EU5 13912/5/2017 12/5/2017 ng/L260 --------------------EU5 137 10/13/2017 10/26/2018 ng/L2500<1000 <960 <1200 <950 <9502400<880<970<11002500EU5 822 11/22/2017 8/13/2019 ng/L970 660<1.1 <1.119 140 300 18 1.8<1.12800EU5 822 11/22/2017 11/22/2017 ng/L670 --------------------EU5 505 10/27/2017 7/30/2019 ng/L630 240<1.1 <1.141 170 340 18 6.6<1.11100EU5 506 11/22/2017 9/24/2019 ng/L570 400<2 <222 230 430 29 9.2 2.9 1600EU5 512 10/19/2017 8/21/2019 ng/L1800 980<2 <265 380 910 100 285 3500EU5 922 11/29/2017 10/22/2018 ng/L120 --------------------EU5 82912/5/2017 12/5/2017 ng/L280 190<50 <50 <5097 270<50 <50 <100630EU5 915 11/29/2017 9/16/2019 ng/L3400 2400<2 <260 460 2500 170 4.7<29300TR0795Page 3 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU5 515 11/21/2017 8/7/2019 ng/L510 260<1.1 <1.134 170 530 130 28 5.7 1100EU5 516 10/24/2017 8/27/2019 ng/L700 290<2 <270 220 730 150 38 4 1300EU5 830 12/20/2017 7/9/2019 ng/L31<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 1020 2/13/2019 2/13/2019 ng/L17<2 <2 <2 <2 <52.7<2 <2 <228EU5 1000 12/12/2017 12/12/2017 ng/L76 -- -- -- -- -- -- -- -- -- --EU5 2335 2/5/2018 2/5/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 2356 2/7/2018 2/7/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 2327 3/9/2018 11/30/2018 ng/L130 -- -- -- -- -- -- -- -- -- --EU5 2320 2/6/2018 2/6/2018 ng/L49 -- -- -- -- -- -- -- -- -- --EU5 2305 2/6/2018 2/6/2018 ng/L92 -- -- -- -- -- -- -- -- -- --EU5 2304 2/13/2018 2/13/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 832 11/29/2017 11/29/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <214EU5 839 11/29/2017 11/29/2017 ng/L13 -- -- -- -- -- -- -- -- -- --EU5 539 11/27/2017 11/27/2017 ng/L53 -- -- -- -- -- -- -- -- -- --EU5 851 5/29/2019 8/6/2019 ng/L490 280<1.1 <1.112 130 300 14 2.1<1.1770EU5 852 12/15/2017 8/6/2019 ng/L590 290<1.1 <1.113 160 330 18 2.1<1.1880EU5 852 5/1/2018 5/1/2018 ng/L34 -- -- -- -- -- -- -- -- -- --EU5 853 11/29/2017 11/29/2017 ng/L16<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 545 10/18/2017 9/10/2019 ng/L1200 240<2 <266 250 560 16<2 <2700EU5 546 10/27/2017 10/1/2019 ng/L260 170<2 <223 120 330 32 6.8<2590EU5 930 12/14/2017 12/14/2017 ng/L78 -- -- -- -- -- -- -- -- -- --EU5 1021 11/29/2017 11/29/2017 ng/L30 -- -- -- -- -- -- -- -- -- --EU5 548 10/24/2017 6/26/2019 ng/L3.56<20 <2 <1.38 <1.38 <1.38 <1.38 <1.38 <1.38 <2 <10EU5 548 10/24/2017 2/13/2018 ng/L1.85<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 548 10/25/2017 2/13/2018 ng/L1.85<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 1022 11/30/2017 11/30/2017 ng/L53 -- -- -- -- -- -- -- -- -- --EU5 855 11/30/2017 11/30/2017 ng/L17 -- -- -- -- -- -- -- -- -- --EU5 551 10/27/2017 10/27/2017 ng/L370 -- -- -- -- -- -- -- -- -- --EU5 269 9/28/2017 6/26/2019 ng/L<0.647 <20 <2 <1.29 <1.29 <1.29 <1.29 <1.29 <1.29 <2 <10EU5 977 8/2/2019 8/2/2019 ng/L<2.6 <11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.1 <5.3EU5 931 11/29/2017 7/23/2018 ng/L170 -- -- -- -- -- -- -- -- -- --EU5 862 12/19/2017 12/19/2017 ng/L22 -- -- -- -- -- -- -- -- -- --EU5 864 11/29/2017 9/18/2019 ng/L760 220<2 <227 150 830 130 28<2530EU5 865 11/29/2017 9/24/2019 ng/L620 210<2<238110 310 46 13<2610EU5 866 11/30/2017 1/31/2018 ng/L30.2 --------------------EU5 867 12/29/2017 12/29/2017 ng/L480 --------------------EU5 933 11/30/2017 9/26/2019 ng/L1600 160<2 <238 150 690 58 11 2.4 540EU5 86812/7/2017 12/7/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 9347/22/2019 7/22/2019 ng/L1200 290<2 <267 240 870 100 21<2800EU5 935 11/30/2017 1/31/2018 ng/L99--------------------EU5 869 12/14/2017 9/24/2019 ng/L690 180<2 <222 110 290 39 6.4<2670EU5 869 12/14/2017 12/14/2017 ng/L640 --------------------EU5 1173 12/14/2017 10/1/2019 ng/L330 230<2 <234 170 470 57 6.7<2830TR0795Page 4 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU5 936 12/14/2017 12/14/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 628 10/24/2017 10/24/2017 ng/L540 --------------------EU5 628 10/24/2017 10/24/2017 ng/L960 --------------------EU5 628 10/24/2017 10/24/2017 ng/L960 --------------------EU5 628 10/24/2017 10/24/2017 ng/L1500 1100<50 <5057 450 1200 160 55<1003800EU5 628 10/24/2017 10/24/2017 ng/L630 --------------------EU5 628 10/24/2017 10/24/2017 ng/L630 --------------------EU5 628 10/25/2017 10/25/2017 ng/L790 --------------------EU5 787 10/18/2017 12/12/2017 ng/L39--------------------EU5 633 10/20/2017 11/7/2017 ng/L15.5<20 <2 <2 <2 <55.6<2 <2 <242EU5 633 10/20/2017 11/7/2017 ng/L21<20 <2 <2 <2 <56.9<2 <2 <232EU5 905 12/14/2017 12/14/2017 ng/L78<100 <50 <50 <50 <50150<50 <50 <100390EU5 87412/7/2017 12/7/2017 ng/L450 250<50 <50 <50140 370 83<50 <1001100EU5 94412/7/2017 8/28/2019 ng/L210 97<2 <229 120 550 77 30<2300EU5 94312/7/2017 8/28/2019 ng/L410 170<2 <253 170 560 36 19 9.8 820EU5 875 12/13/2017 11/20/2018 ng/L370<10000 <9600 <12000 <9500 <9500 <9200 <8800 <9700 <11000 <8400EU5 876[3]12/13/2017 1/31/2018 ng/L0<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 682 12/13/2017 10/22/2018 ng/L104 --------------------EU5 12341/5/2018 1/5/2018 ng/L12--------------------EU5 12081/5/2018 1/5/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU5 877 12/12/2017 12/12/2017 ng/L230 --------------------EU5 877 12/15/2017 12/15/2017 ng/L5.4<20 <2 <2 <2 <59.9<2 <2 <2 <10EU5 90912/7/2017 12/7/2017 ng/L12<20 <2 <217 16 16 2.1<2 <2110EU5 1184 12/6/2017 12/6/2017 ng/L85--------------------EU6 8793/27/2019 3/27/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU6 15032/1/2018 2/1/2018 ng/L18--------------------EU6 321 11/13/2017 11/13/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU6 88712/6/2017 12/6/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU6 95712/7/2017 12/7/2017 ng/L420 --------------------EU6 1211 12/7/2017 12/7/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU6 35012/7/2017 12/7/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <220EU6 3539/18/2017 7/27/2018 ng/L129 --------------------EU6 3537/27/2018 7/27/2018 ng/L22--------------------EU6 7229/21/2017 10/20/2017 ng/L360 --------------------EU6 723 10/16/2017 10/16/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <226EU6 3643/18/2019 8/28/2019 ng/L270 190<2 <242 170 500 39 11 2.5 650EU6 365 10/18/2017 9/24/2019 ng/L370 250<2 <260 130 350 41 12<2830EU6 377 10/26/2017 7/16/2019 ng/L400 430<2 <272 140 250 8.9 3.7<21500EU6 396 10/20/2017 10/20/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU6 491 10/23/2017 10/23/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU6 491 10/23/2017 10/23/2017 ng/L95--------------------EU6 491 10/23/2017 10/23/2017 ng/L9.2<20 <2 <2 <2 <52.5<2 <2 <2 <10EU6 491 10/23/2017 10/23/2017 ng/L32<20 <2 <2 <2 <5 <2 <2 <2 <2 <10TR0795Page 5 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU6 24585/9/2018 5/9/2018 ng/L36--------------------EU6 10191/4/2018 1/4/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU6 22302/8/2018 2/8/2018 ng/L14--------------------EU6 2419/22/2017 9/22/2017 ng/L250 --------------------EU6 63411/6/2017 11/6/2017 ng/L340 --------------------EU6 1003 12/14/2017 12/14/2017 ng/L78--------------------EU6 90712/5/2017 12/5/2017 ng/L24--------------------EU6 90812/6/2017 12/6/2017 ng/L63--------------------EU6 9833/29/2019 3/29/2019 ng/L37 23<2 <214 20 4782.1<2130EU6 1013 12/5/2017 12/5/2017 ng/L94--------------------EU6 1005 12/5/2017 12/5/2017 ng/L150<100 <50 <50 <50 <5072<50 <50 <100380EU7 271 10/17/2017 10/17/2017 ng/L250<100 <50 <50 <5051 94<50 <50 <100510EU7 276 10/19/2017 10/19/2017 ng/L260 --------------------EU7 27711/9/2017 11/9/2017 ng/L240 --------------------EU7 278 10/19/2017 9/30/2019 ng/L480 290<2 <224 100 190 9.8 2.2<21200EU7 27910/2/2017 10/2/2017 ng/L400 --------------------EU7 282 10/17/2017 4/11/2018 ng/L53.4 --------------------EU7 2599/20/2017 9/20/2017 ng/L280 --------------------EU7 294 10/19/2017 10/19/2017 ng/L21<20 <2 <28.2 8.6 4.1<2 <2 <2150EU7 298 10/19/2017 10/19/2017 ng/L8.5<20 <2 <2 <2 <5 <2 <2 <2 <253EU7 299 10/25/2017 10/25/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <214EU7 301 10/19/2017 10/19/2017 ng/L12<20 <2 <23.7 7.1 172<2 <243EU7 303 10/23/2017 10/23/2017 ng/L39--------------------EU7 304 10/19/2017 10/19/2017 ng/L59--------------------EU7 306 10/24/2017 9/26/2019 ng/L330 190<2 <27.3 53 85 7.5<2 <2750EU7 30810/6/2017 10/6/2017 ng/L230 210<50 <50 <5071 120<50 <50 <1001000EU7 31010/3/2017 10/3/2017 ng/L360 --------------------EU7 313 10/17/2017 10/17/2017 ng/L380 --------------------EU7 315 11/20/2017 11/20/2017 ng/L210 150<50 <5058 87 200<50 <50 <100630EU7 2639/25/2017 9/25/2017 ng/L1100 370<50 <50 <50140 290<50 <50 <1001200EU7101811/30/2017 11/30/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU7 325 10/23/2017 4/11/2019 ng/L4000 770<2 <265 480 1200 130 67<22500EU7 325 10/23/2017 10/23/2017 ng/L98--------------------EU7 327 10/19/2017 8/27/2019 ng/L150 150<2 <25.4 44 63 2.1<2 <2840EU7 3313/27/2018 3/27/2018 ng/L88--------------------EU7 1218 12/12/2017 12/12/2017 ng/L260 200<50 <5059 79 170<50 <50 <100980EU7 15432/7/2018 2/7/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <215EU7 707 10/18/2017 10/18/2017 ng/L86 120<50 <50 <50 <5088<50 <50 <100720EU7 1222 12/12/2017 9/27/2019 ng/L141 54<2 <231 45 87 6.6 3.3<2270EU7 951 12/12/2017 12/12/2017 ng/L25--------------------EU7 349 10/23/2017 10/23/2017 ng/L33--------------------EU7 351 10/23/2017 10/23/2017 ng/L21--------------------EU7 359 10/17/2017 7/9/2019 ng/L690 540<2 <261 98 330 35 5.1<21700TR0795Page 6 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU7 362 10/23/2017 10/23/2017 ng/L19 -- -- -- -- -- -- -- -- -- --EU7 363 10/26/2017 10/26/2017 ng/L99 -- -- -- -- -- -- -- -- -- --EU7 800 10/5/2017 10/5/2017 ng/L370 -- -- -- -- -- -- -- -- -- --EU7 960 11/27/2017 11/27/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU7 961 12/14/2017 12/14/2017 ng/L5.2<20 <2 <2 <2 <5 <2 <2 <2 <212EU7 372 10/30/2017 2/8/2018 ng/L11 -- -- -- -- -- -- -- -- -- --EU7 891 12/7/2017 12/7/2017 ng/L6.8<20 <2 <2 <2 <5 <2 <2 <2 <232EU7 892 12/7/2017 12/7/2017 ng/L7.9<100 <50 <50 <50 <50 <50 <50 <50 <100210EU7 267 9/28/2017 1/10/2018 ng/L32.9 -- -- -- -- -- -- -- -- -- --EU7 267 9/28/2017 1/10/2018 ng/L21.5 25<2 <219 22 19<2 <2 <2280EU7 375 10/17/2017 10/17/2017 ng/L12 20<2 <28.9 10 8.2<2 <2 <2220EU7 729 10/25/2017 10/25/2017 ng/L12 -- -- -- -- -- -- -- -- -- --EU7 376 11/27/2017 11/27/2017 ng/L67 -- -- -- -- -- -- -- -- -- --EU7 378 10/17/2017 12/20/2017 ng/L51.6 -- -- -- -- -- -- -- -- -- --EU7 379 12/1/2017 12/1/2017 ng/L33 -- -- -- -- -- -- -- -- -- --EU7 2412 2/15/2018 2/15/2018 ng/L86 -- -- -- -- -- -- -- -- -- --EU7 2412 2/15/2018 2/15/2018 ng/L200 -- -- -- -- -- -- -- -- -- --EU7 386 10/24/2017 10/24/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <242EU7 388 10/17/2017 10/17/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <240EU7 1509 1/31/2018 1/31/2018 ng/L6.6<20 <2 <2 <29.9 5.3<2 <2 <2150EU7 733 10/18/2017 10/18/2017 ng/L16 30<2 <211 18 17<2 <2 <2320EU7 389 10/18/2017 10/18/2017 ng/L340 -- -- -- -- -- -- -- -- -- --EU7 735 10/24/2017 10/24/2017 ng/L22 -- -- -- -- -- -- -- -- -- --EU7 394 10/26/2017 10/26/2017 ng/L10 24<2 <215<514<2 <2 <2330EU7 897 2/9/2018 2/9/2018 ng/L32 -- -- -- -- -- -- -- -- -- --EU7 2098 1/31/2018 1/31/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU7 811 10/25/2017 1/10/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU7 798 2/13/2018 8/1/2019 ng/L170 130<1.1 <1.136 87 300 35 6.8<1.1690EU7 426 10/18/2017 10/31/2018 ng/L920<10000 <9600 <12000 <9500 <9500 <9200 <8800 <9700 <11000 <8400EU7 495 2/15/2018 11/27/2018 ng/L640<10000 <9600 <12000 <9500 <9500 <9200 <8800 <9700 <11000 <8400EU7 974 12/7/2017 12/7/2017 ng/L31 -- -- -- -- -- -- -- -- -- --EU7 507 10/27/2017 10/27/2017 ng/L16 -- -- -- -- -- -- -- -- -- --EU7 511 10/5/2017 11/6/2018 ng/L350 --------------------EU721172/1/20182/1/2018 ng/L16--------------------EU7 771 10/19/2017 10/19/2017 ng/L250 --------------------EU7 531 10/18/2017 1/28/2019 ng/L122 100<2 <221 40 85 10 2.2<2490EU7 773 10/19/2017 10/19/2017 ng/L18--------------------EU7 550 10/17/2017 1/9/2019 ng/L115<100 <50 <1.2124.4 70.5 82 6.3 1.71<100320EU7 2977 7/19/2019 7/19/2019 ng/L42 21<2 <25.3 29 5062.5<2150EU7 57810/5/2017 10/5/2017 ng/L140 --------------------EU7 603 10/19/2017 9/27/2019 ng/L250 250<2 <214 68 120 11<2 <2760EU7 605 10/20/2017 8/29/2018 ng/L26--------------------EU7 614 10/18/2017 1/28/2019 ng/L100 91<2 <224 49 80 7.6<3.9 <2580TR0795Page 7 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU7 786 10/18/2017 10/18/2017 ng/L180 -- -- -- -- -- -- -- -- -- --EU7 626 10/5/2017 10/5/2017 ng/L430 -- -- -- -- -- -- -- -- -- --EU7 809 10/19/2017 10/19/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU7 631 10/19/2017 10/19/2017 ng/L420 -- -- -- -- -- -- -- -- -- --EU7 635 10/20/2017 10/20/2017 ng/L42 -- -- -- -- -- -- -- -- -- --EU7 789 10/19/2017 10/19/2017 ng/L44<100 <50 <50 <50 <50 <50 <50 <50 <100270EU7 789 10/19/2017 10/19/2017 ng/L31 -- -- -- -- -- -- -- -- -- --EU7 3036 8/8/2019 8/8/2019 ng/L47 55<1.1 <1.110 25 34 2.8<1.1 <1.1340EU7 3036 8/8/2019 8/8/2019 ng/L94 52<1.1 <1.124 53 76 8 4.5<1.1290EU7 252 9/14/2017 9/14/2017 ng/L11 -- -- -- -- -- -- -- -- -- --EU7 794 10/18/2017 10/18/2017 ng/L62 -- -- -- -- -- -- -- -- -- --EU7 674 10/18/2017 10/31/2018 ng/L630<10000 <9600 <12000 <9500 <9500 <9200 <8800 <9700 <11000 <8400EU7 680 10/19/2017 10/19/2017 ng/L250 -- -- -- -- -- -- -- -- -- --EU7 684 10/26/2017 8/6/2019 ng/L230 110<1.1 <1.13.8 51 110 2.2 2<1.1740EU7 795 10/19/2017 10/19/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU7 691 10/19/2017 8/27/2019 ng/L390 290<2 <260 150 530 93 17<2880EU7 693 12/13/2017 11/30/2018 ng/L131 -- -- -- -- -- -- -- -- -- --EU8 222 9/13/2017 10/24/2018 ng/L124 -- -- -- -- -- -- -- -- -- --EU8 221 9/7/2017 8/6/2019 ng/L190 85<1.1 <1.17.4 69 150 3.7<1.1 <1.1380EU8 223 9/7/2017 9/29/2017 ng/L<1.88 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 2415 2/13/2018 7/25/2019 ng/L1.21<20 <2 <2 <2 <5 <2 <2 <2 <211EU8 7797 9/25/2019 9/25/2019 ng/L11<20 <2 <211 30 38 4<2 <2140EU8 8282 10/17/2019 10/17/2019 ng/L6.3<20 <2 <22.2 6.4 3.6<2 <2 <276EU8 7555 8/19/2019 8/19/2019 ng/L13<11 <1.1 <1.19.4 21 24 1.4<1.1 <1.1110EU8 7796 9/26/2019 9/26/2019 ng/L21<20 <2 <29.8 19 28 2.7<2 <2110EU8 8021 9/26/2019 9/26/2019 ng/L7.9<20 <2 <26.6 20 20 2.4<2 <2100EU8 8294 10/8/2019 10/8/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 8296 10/8/2019 10/8/2019 ng/L<2.7 <20 <2 <22.8 8.25<2<2<257EU8 7557 8/19/2019 8/19/2019 ng/L<2.6 <11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.1 <5.3EU8 8298 10/9/2019 10/9/2019 ng/L15<20 <2 <27.6 10 18<2 <2 <2110EU8 8299 10/9/2019 10/9/2019 ng/L10<20 <2 <24.1<52.3<2 <2 <292EU8 2663 7/25/2019 7/25/2019 ng/L40 23<1.1 <1.130 53 110 13 4.8<1.1170EU8 2664 8/15/2019 8/15/2019 ng/L13<11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.1 <5.3EU8 2665 9/11/2019 9/11/2019 ng/L6.9<20 <2 <223 33 120 18 3.4<2150EU8 2666 9/17/2019 9/17/2019 ng/L14<20 <2 <27.9 18 243<2 <284EU8 2669 7/23/2019 7/23/2019 ng/L3.8<20 <2 <22.263.2<2 <2 <249EU8 2670 8/28/2019 8/28/2019 ng/L3.2<20 <2 <2 <26.6<2 <2 <2 <267EU8 2671 8/28/2019 8/28/2019 ng/L<2.8 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 2674 8/28/2019 8/28/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 2474 4/11/2018 4/11/2018 ng/L26.3 --------------------EU8 2676 7/23/2019 7/23/2019 ng/L28<20 <2 <23.6 17 35 3.2<2 <297EU8 26838/8/2019 8/8/2019 ng/L10 15<1.11.5<1.114 11<1.1 <1.1 <1.1110EU8 2391 12/20/2017 12/20/2017 ng/L17.3 --------------------TR0795Page 8 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU8 26899/3/2019 9/3/2019 ng/L13<20 <2 <29.7 31 35<2 <2 <277EU8 2690 8/8/2019 8/8/2019 ng/L19 12<1.1 <1.115 32 50 2.9 1.2<1.173EU8 2465 3/28/2018 3/28/2018 ng/L2.04 -- -- -- -- -- -- -- -- -- --EU8 1228 3/20/2018 3/20/2018 ng/L24 -- -- -- -- -- -- -- -- -- --EU8 2693 7/29/2019 7/29/2019 ng/L36 29<1.1 <1.126 70 91 5<1.1 <1.1200EU8 736 7/2/2019 7/2/2019 ng/L34 21<2 <217 27 40 2.9<2 <2130EU8 2100 5/16/2018 5/16/2018 ng/L41 -- -- -- -- -- -- -- -- -- --EU8 2101 1/31/2018 3/27/2019 ng/L50.3 -- --<1.299.28 50.6 50.7 5.58 1.35 -- --EU8 737 2/13/2018 2/13/2018 ng/L81.2 -- -- -- -- -- -- -- -- -- --EU8 2703 5/29/2019 5/29/2019 ng/L14<20 <2 <220<540 2<2 <276EU8 738 10/16/2017 10/16/2017 ng/L60 -- -- -- -- -- -- -- -- -- --EU8 739 10/19/2017 10/19/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <221EU8 1231 12/20/2017 12/20/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 401 10/26/2017 8/1/2019 ng/L250 72<1.1 <1.118 80 230 20 11<1.1290EU8 402 10/16/2017 10/16/2017 ng/L57 -- -- -- -- -- -- -- -- -- --EU8 2102 2/1/2018 2/1/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 2722 9/11/2019 9/11/2019 ng/L39 26<2 <212 30 48 2.1<2 <2150EU8 2103 1/24/2018 1/24/2018 ng/L18 -- -- -- -- -- -- -- -- -- --EU8 403 10/16/2017 10/16/2017 ng/L77 -- -- -- -- -- -- -- -- -- --EU8 404 10/16/2017 10/16/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 405 10/16/2017 10/16/2017 ng/L50<100 <50 <50 <50 <50 <50 <50 <50 <100140EU8 2728 7/25/2019 7/25/2019 ng/L41 25<2 <27.6 31 55 2.9<2 <2120EU8 2104 1/25/2018 1/25/2018 ng/L12<20 <2 <211 28 39 3.9 2.2<288EU8 406 10/16/2017 10/16/2017 ng/L36 -- -- -- -- -- -- -- -- -- --EU8 407 10/10/2017 10/16/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 920 2/7/2018 2/7/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <222EU8 408 10/10/2017 10/10/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 2105 2/19/2018 2/19/2018 ng/L15<20 <2 <211 25 34 3.4<2<281EU84102/15/2018 2/15/2018 ng/L54--------------------EU8 415 11/10/2017 11/10/2017 ng/L15<20 <2 <2 <2 <53.6<2 <2 <223EU8 2659/28/2017 9/28/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 2107 1/31/2018 8/7/2019 ng/L130 27<2 <1.247.18 39.5 47 6.5 2.17<2150EU8 416 10/24/2017 10/24/2017 ng/L42--------------------EU8 12462/7/2018 2/7/2018 ng/L38--------------------EU8 2108 1/31/2018 1/31/2018 ng/L310 180<50 <50 <5070 200<50 <50 <100760EU8 1247 1/23/2018 1/23/2018 ng/L13<20 <2 <211 27 32<2 <2 <2120EU8 417 10/19/2017 10/19/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 418 10/13/2017 10/13/2017 ng/L16<20 <2 <219 27 45 2.5<2 <2130EU8 419 10/26/2017 6/6/2019 ng/L12<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 420 12/20/2017 9/18/2019 ng/L205 110<2 <219 65 160 9.3 4.8<2310EU8 2109 1/23/2018 8/7/2019 ng/L63----<1.2212.1 57.6 51.6 5.7 2.11 ----EU8 12498/7/2019 8/7/2019 ng/L133 ----<1.255.19 40.8 37.7 2.78<1.25----EU8 421 10/30/2017 10/30/2017 ng/L270 --------------------TR0795Page 9 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU8 422 10/26/2017 10/26/2017 ng/L16 -- -- -- -- -- -- -- -- -- --EU8 423 11/7/2017 11/7/2017 ng/L11 -- -- -- -- -- -- -- -- -- --EU8 741 10/20/2017 10/20/2017 ng/L11 -- -- -- -- -- -- -- -- -- --EU8 427 12/18/2017 12/18/2017 ng/L35 -- -- -- -- -- -- -- -- -- --EU8 428 10/18/2017 10/18/2017 ng/L97 -- -- -- -- -- -- -- -- -- --EU8 258 9/20/2017 9/29/2017 ng/L83.8 -- -- -- -- -- -- -- -- -- --EU8 742 6/13/2019 6/13/2019 ng/L130 110<2 <28 72 150 9<2 <2450EU8 744 10/20/2017 10/20/2017 ng/L13<20 <2 <2 <2 <56.3<2 <2 <236EU8 432 11/15/2017 11/15/2017 ng/L84 -- -- -- -- -- -- -- -- -- --EU8 435 10/17/2017 10/17/2017 ng/L26 -- -- -- -- -- -- -- -- -- --EU8 747 10/17/2017 10/17/2017 ng/L74 -- -- -- -- -- -- -- -- -- --EU8 436 10/26/2017 10/26/2017 ng/L70 -- -- -- -- -- -- -- -- -- --EU8 814 10/26/2017 10/26/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <215EU8 437 10/5/2017 10/5/2017 ng/L170 -- -- -- -- -- -- -- -- -- --EU8 440 10/20/2017 10/20/2017 ng/L60 -- -- -- -- -- -- -- -- -- --EU8 748 10/20/2017 10/20/2017 ng/L16<20 <2 <2 <2917<2 <2 <274EU8 442 1/23/2018 1/23/2018 ng/L18 -- -- -- -- -- -- -- -- -- --EU8 266 9/28/2017 1/28/2019 ng/L130 44<2 <2 <217 57<2 <2 <2280EU8 446 12/28/2017 12/28/2017 ng/L170 -- -- -- -- -- -- -- -- -- --EU8 449 10/17/2017 7/24/2018 ng/L110 -- -- -- -- -- -- -- -- -- --EU8 753 10/17/2017 10/17/2017 ng/L4.4<20 <2 <2 <25.3<2 <2 <2 <274EU8 754 10/30/2017 10/30/2017 ng/L340 -- -- -- -- -- -- -- -- -- --EU8 452 10/17/2017 10/17/2017 ng/L140 -- -- -- -- -- -- -- -- -- --EU8 453 11/16/2018 11/16/2018 ng/L50 -- -- -- -- -- -- -- -- -- --EU8 455 10/10/2017 10/10/2017 ng/L15<20 <2 <2 <26.6 5.9<2 <2 <281EU8 456 10/26/2017 10/26/2017 ng/L89 -- -- -- -- -- -- -- -- -- --EU8 457 10/19/2017 10/19/2017 ng/L140 -- -- -- -- -- -- -- -- -- --EU8 459 10/3/2017 10/27/2017 ng/L8.18<20 <2 <2 <26.6<2 <2 <2 <247EU8 460 10/20/2017 10/20/2017 ng/L13 -- -- -- -- -- -- -- -- -- --EU8 461 10/17/2017 10/17/2017 ng/L33 -- -- -- -- -- -- -- -- -- --EU8 758 10/23/2017 10/23/2017 ng/L10<20 <2 <2 <2 <5 <2 <2 <2 <235EU8 464 10/17/2017 9/5/2018 ng/L36 -- -- -- -- -- -- -- -- -- --EU8 759 10/17/2017 1/28/2019 ng/L120 110<2 <219 45 110 14<3.9 <2520EU8 468 10/16/2017 4/18/2018 ng/L36--------------------EU82579/20/2017 9/20/2017 ng/L43--------------------EU8 1202 1/15/2018 8/21/2019 ng/L<0.567 <20 <2 <1.13 <1.13 <1.13 <1.13 <1.13 <1.13 <2 <10EU8 469 10/24/2017 10/24/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 471 10/16/2017 10/16/2017 ng/L30--------------------EU8 4729/19/2019 9/19/2019 ng/L43 21<2 <2 <216 23<2 <2 <2160EU8 473 11/10/2017 11/10/2017 ng/L<4.3 <20 <2 <2 <2 <5 <2 <2 <2 <213EU8 478 10/16/2017 10/16/2017 ng/L98--------------------EU8 480 10/18/2017 10/18/2017 ng/L15<20 <2 <2 <25.7 12<2 <2 <239EU8 764 10/26/2017 10/26/2017 ng/L87--------------------TR0795Page 10 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU8 48611/9/2017 11/9/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 7583 10/3/2019 10/3/2019 ng/L11<20 <2 <2 <27.9 22 2.2<2 <272EU8 1459/8/2017 9/18/2017 ng/L320 --------------------EU8 7584 8/26/2019 8/26/2019 ng/L98 59<2 <22.8 53 110 17<2 <2280EU8 49710/3/2017 12/13/2017 ng/L5.69<20 <2 <2 <2 <5 <2 <2 <2 <238EU8 2750 6/21/2019 6/21/2019 ng/L7.2<20 <2 <2 <222 16<2 <2 <2180EU8 2752 6/19/2019 6/19/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 1250 2/13/2018 2/13/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 1251 1/24/2018 1/24/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 1252 1/24/2018 1/24/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 12544/2/2019 4/2/2019 ng/L71 48<2 <29.5 17 63 5.7<2 <2190EU8 2171 1/24/2018 1/24/2018 ng/L37--------------------EU8 2173 1/24/2018 1/24/2018 ng/L19--------------------EU8 1255 1/24/2018 1/24/2018 ng/L37--------------------EU8 12562/2/2018 2/2/2018 ng/L50--------------------EU8 2175 2/15/2018 2/15/2018 ng/L18--------------------EU8 12572/7/2018 2/7/2018 ng/L14<20 <2 <24.5 33 41<2 <2 <2140EU8 923 12/14/2017 12/14/2017 ng/L25--------------------EU8 924 12/14/2017 12/14/2017 ng/L13<20 <2 <26.6 18 22<2 <2 <299EU8 831 12/13/2017 12/13/2017 ng/L29--------------------EU8 92512/5/2017 12/5/2017 ng/L62--------------------EU8 878 11/30/2017 11/30/2017 ng/L250 --------------------EU8 835 11/28/2017 11/28/2017 ng/L43--------------------EU8 534 10/30/2017 10/30/2017 ng/L84--------------------EU8 836 11/30/2017 11/30/2017 ng/L47--------------------EU8 837 11/28/2017 11/28/2017 ng/L41<100 <50 <50 <50 <50 <50 <50 <50 <100210EU8 535 10/18/2017 10/18/2017 ng/L200 190<50 <50 <50110 300<50 <50 <100570EU8 84012/4/2017 12/4/2017 ng/L45--------------------EU8 927 11/28/2017 11/28/2017 ng/L17--------------------EU8 842 11/29/2017 11/29/2017 ng/L44--------------------EU8 843 12/14/2017 12/14/2017 ng/L34--------------------EU8 844 12/14/2017 12/14/2017 ng/L36--------------------EU8 845 12/14/2017 12/14/2017 ng/L32--------------------EU8 928 11/29/2017 11/29/2017 ng/L11<20 <2 <2 <258.3<2<2<255EU8 846 11/29/2017 11/29/2017 ng/L20--------------------EU8 847 12/20/2017 12/20/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <219EU8 84812/4/2017 12/4/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <217EU8 540 10/31/2017 7/5/2019 ng/L54 40<2 <229 78 140 5.8<2 <2230EU8 850 11/29/2017 11/29/2017 ng/L4.8<20 <2 <2 <2 <5 <2 <2 <2 <236EU8 5412/19/2018 2/19/2018 ng/L22--------------------EU8 542 10/26/2017 10/26/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 543 11/29/2017 11/29/2017 ng/L45--------------------EU8 5543/18/2019 4/9/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10TR0795Page 11 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU8 5543/18/2019 4/9/2019 ng/L36<20 <2 <2 <29.1 19<2 <2 <2100EU8 85612/1/2017 12/1/2017 ng/L65--------------------EU8 558 11/30/2017 11/30/2017 ng/L61--------------------EU8 5607/10/2019 7/10/2019 ng/L60 38<2 <2 <223 62 3.3<2 <2190EU8 858 11/30/2017 11/30/2017 ng/L52--------------------EU8 565 10/19/2017 10/19/2017 ng/L<4 <20 <2 <2 <2 <52.7<2 <2 <213EU8 566 12/13/2017 11/21/2018 ng/L1300<10000 <9600 <12000 <9500 <9500 <9200 <8800 <9700 <11000 <8400EU8 85912/1/2017 12/1/2017 ng/L350 --------------------EU8 86112/1/2017 12/1/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 567 10/18/2017 8/12/2019 ng/L960 200<1.1 <1.111 83 200 17 3.3<1.1850EU8 568 10/18/2017 10/18/2017 ng/L69--------------------EU8 569 10/24/2017 10/24/2017 ng/L630 380<50 <5063 220 560 66<50 <1001600EU8 570 10/18/2017 10/18/2017 ng/L80--------------------EU8 932 12/13/2017 7/10/2019 ng/L44.4 ----<1.161.19 9.36 7.24<1.16 <1.16----EU8 86312/5/2017 12/5/2017 ng/L380 --------------------EU8 86312/5/2017 12/5/2017 ng/L590 --------------------EU8 2978 7/19/2019 7/19/2019 ng/L37<20 <2 <24.2 23 37 5.1<2 <2120EU8 2981 7/19/2019 7/19/2019 ng/L220 89<2 <211 96 200 23 5.3<2380EU8 2425 3/14/2018 3/14/2018 ng/L82--------------------EU8 2982 9/20/2019 9/20/2019 ng/L61 39<2 <26.6 33 78 13 3.4<2200EU8 778 10/13/2017 10/13/2017 ng/L14<20 <2 <2 <266.2<2 <2 <269EU8 2426 3/14/2018 3/14/2018 ng/L20--------------------EU8 5829/29/2017 1/28/2019 ng/L112 42<2 <224 57 110 7.7 4.1<2220EU8 583 11/21/2017 11/21/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 5843/14/2018 3/14/2018 ng/L1.84 --------------------EU8 2649/22/2017 9/29/2017 ng/L39.2 --------------------EU8 585 10/10/2017 10/10/2017 ng/L170 --------------------EU8 586 10/23/2017 10/23/2017 ng/L25--------------------EU8 589 10/26/2017 10/26/2017 ng/L150 --------------------EU81979/8/20179/29/2017 ng/L<1.8 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 5906/6/2019 6/6/2019 ng/L120 51<2 <225 64 130 14 6.3<2230EU8 591 1/3/2018 1/3/2018 ng/L240 -- -- -- -- -- -- -- -- -- --EU8 195 9/7/2017 9/7/2017 ng/L26 -- -- -- -- -- -- -- -- -- --EU8 201 9/14/2017 9/14/2017 ng/L67 -- -- -- -- -- -- -- -- -- --EU8 594 10/26/2017 10/26/2017 ng/L91 -- -- -- -- -- -- -- -- -- --EU8 194 9/7/2017 9/7/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 202 9/20/2017 9/20/2017 ng/L67 -- -- -- -- -- -- -- -- -- --EU8 595 10/12/2017 10/12/2017 ng/L84 -- -- -- -- -- -- -- -- -- --EU8 205 9/20/2017 11/7/2017 ng/L68.6<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 200 10/5/2017 11/7/2017 ng/L190 -- -- -- -- -- -- -- -- -- --EU8 204 9/14/2017 11/7/2017 ng/L236 -- -- -- -- -- -- -- -- -- --EU8 597 10/12/2017 10/12/2017 ng/L77 -- -- -- -- -- -- -- -- -- --EU8 206 9/7/2017 9/7/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10TR0795Page 12 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU8 598 10/12/2017 10/12/2017 ng/L50 -- -- -- -- -- -- -- -- -- --EU8 207 9/25/2017 9/25/2017 ng/L24 -- -- -- -- -- -- -- -- -- --EU8 599 10/12/2017 10/12/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 208 9/20/2017 9/20/2017 ng/L36 -- -- -- -- -- -- -- -- -- --EU8 209 9/8/2017 10/25/2018 ng/L220<200 <200 <200 <200 <200250<200 <200 <200600EU8 601 10/19/2017 10/19/2017 ng/L28 -- -- -- -- -- -- -- -- -- --EU8 216 9/7/2017 10/3/2017 ng/L41.1 -- -- -- -- -- -- -- -- -- --EU8 602 10/18/2017 10/18/2017 ng/L6.4<20 <2 <2 <2 <54.4<2 <2 <225EU8 604 8/29/2019 8/29/2019 ng/L42 30<2 <29.7 37 58 3.2<2 <2190EU8 780 10/13/2017 10/13/2017 ng/L33 -- -- -- -- -- -- -- -- -- --EU8 2989 7/19/2019 7/19/2019 ng/L8.2<20 <2 <24.7 21 18<2 <2 <292EU8 609 11/28/2017 11/28/2017 ng/L28 -- -- -- -- -- -- -- -- -- --EU8 611 10/27/2017 10/27/2017 ng/L71 -- -- -- -- -- -- -- -- -- --EU8 781 10/13/2017 2/13/2018 ng/L37.6 -- -- -- -- -- -- -- -- -- --EU8 613 10/5/2017 10/22/2018 ng/L101 -- -- -- -- -- -- -- -- -- --EU8 615 10/26/2017 10/26/2017 ng/L24 -- -- -- -- -- -- -- -- -- --EU8 617 12/18/2017 12/18/2017 ng/L84 -- -- -- -- -- -- -- -- -- --EU8 618 10/24/2017 10/24/2017 ng/L18 -- -- -- -- -- -- -- -- -- --EU8 619 10/18/2017 6/13/2018 ng/L15.9<20 <2 <27.4 12 5.6<2 <2 <2110EU8 620 10/18/2017 9/3/2019 ng/L500 210<2 <243 120 300 8.7<2 <2650EU8 7498 8/14/2019 8/14/2019 ng/L30 15<1.1 <1.112 31 50 1.7<1.1 <1.1120EU8 623 10/26/2017 10/26/2017 ng/L7.2<20 <2 <2 <27.1 2.2<2 <2 <263EU8 782 10/16/2017 10/16/2017 ng/L20 -- -- -- -- -- -- -- -- -- --EU8 3002 8/29/2019 8/29/2019 ng/L7.5<20 <2 <26 23 65 3.9<2 <251EU8 625 10/17/2017 10/17/2017 ng/L6<20 <2 <2 <25.7 2.3<2 <2 <268EU8 784 10/17/2017 9/24/2019 ng/L210 87<2 <231 92 150 12 3.1<2420EU8 3003 9/4/2019 9/4/2019 ng/L9<20 <2 <27.9 23 24<2 <2 <2100EU878510/16/2017 10/16/2017 ng/L14--------------------EU8 3004 7/23/2019 7/23/2019 ng/L16<20 <2 <211 17 18<2 <2 <270EU8 2427 3/14/2018 3/14/2018 ng/L9.25 --------------------EU8 2253 1/25/2018 1/25/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 8346 10/9/2019 10/9/2019 ng/L20<20 <2 <212 18 36 2.1<2 <2150EU8 7574 8/26/2019 8/26/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 3006 9/25/2019 9/25/2019 ng/L7.6<20 <2 <28.2 21 7.9<2 <2 <2180EU8 3007 9/26/2019 9/26/2019 ng/L43 32<2 <212 51 130 16 3.1<2160EU8 3008 5/29/2019 8/7/2019 ng/L124 ----<1.333.5 73.8 61.3 3.31<1.3----EU8 22572/1/2018 2/1/2018 ng/L26--------------------EU8 3009 9/17/2019 9/17/2019 ng/L21 24<2 <24.2 24 10<2 <2 <2170EU8 7503 8/15/2019 8/15/2019 ng/L24 19<1.1 <1.17.6 20 25 2.1<1.1 <1.1110EU8 3010 10/4/2019 10/4/2019 ng/L13<20 <2 <212 31 30<2 <2 <2130EU8 7575 10/10/2019 10/10/2019 ng/L42 21<2 <221 25 62 6.1<2 <2180EU8 7494 8/15/2019 8/15/2019 ng/L<2.6 <11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.1 <5.3EU8 2415 2/13/2018 2/13/2018 ng/L17.2 --------------------TR0795Page 13 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU8 6309/23/2019 9/23/2019 ng/L7.3<20 <2 <23.1 13 6.6<2 <2 <2110EU8 22612/1/2018 2/1/2018 ng/L48--------------------EU8 1230 12/18/2017 12/18/2017 ng/L44--------------------EU8 8353 10/7/2019 10/7/2019 ng/L13<20 <2 <215 23 17<2 <2 <2140EU8 30218/8/2019 8/8/2019 ng/L25 15<1.1 <1.112 28 49 5.3 1.4<1.179EU8 1232 12/18/2017 12/18/2017 ng/L63--------------------EU8 87012/4/2017 12/4/2017 ng/L71--------------------EU8 2484 3/28/2018 3/28/2018 ng/L14.9 --------------------EU8 87112/4/2017 12/4/2017 ng/L380 --------------------EU8 1032 12/5/2017 12/5/2017 ng/L31--------------------EU8 1031 12/5/2017 12/5/2017 ng/L420 --------------------EU8 1033 12/5/2017 12/5/2017 ng/L330 --------------------EU8 7551 8/22/2019 8/22/2019 ng/L19<20 <2 <29.1 19 31<2 <2 <261EU8 3024 7/25/2019 7/25/2019 ng/L15<11 <1.1 <1.19.7 27 41<1.11.1<1.167EU8 7552 10/4/2019 10/4/2019 ng/L31<20 <2 <28.2 21 38 2.5<2 <273EU8 7550 8/19/2019 8/19/2019 ng/L33 26<1.1 <1.16.2 20 37 2.5<1.1 <1.186EU8 87212/4/2017 10/8/2019 ng/L570 270<2 <231 200 440 30 8.4<2900EU8 87212/4/2017 12/4/2017 ng/L320 --------------------EU8 3025 7/19/2019 7/19/2019 ng/L29<20 <2 <212 25 433<2 <256EU8 7554 8/26/2019 8/26/2019 ng/L42 44<2 <244 46 60 3.8<2 <2240EU8 8357 10/7/2019 10/7/2019 ng/L42 27<2 <28.9 21 36 3.9<2 <2120EU8 8360 10/10/2019 10/10/2019 ng/L20<20 <2 <27925<2 <2 <278EU8 8362 10/7/2019 10/7/2019 ng/L14<20 <2 <29.3 15 23 2.7<2 <299EU8 3027 5/29/2019 5/29/2019 ng/L44<20<2<216 6.4 747<2 <275EU8 8364 10/10/2019 10/10/2019 ng/L39<20 <2 <212 11 35<2 <2 <290EU8 87312/4/2017 3/14/2018 ng/L163 --------------------EU8 87312/4/2017 12/4/2017 ng/L4<20 <2 <2 <2 <5 <2 <2 <2 <229EU8 87312/4/2017 12/4/2017 ng/L18--------------------EU8 8366 10/18/2019 10/18/2019 ng/L11<20 <2 <28.3 17 26<2 <2 <258EU8 8367 10/9/2019 10/9/2019 ng/L23<20 <2 <29.5 9.8 30 2.5<2 <282EU8 8369 10/9/2019 10/9/2019 ng/L16<20 <2 <26.5<54.4<2 <2 <278EU8 639 10/19/2017 10/19/2017 ng/L16--------------------EU8 640 10/19/2017 7/23/2019 ng/L480 280<2 <249 260 350 25<2 <21300EU8 641 10/20/2017 10/20/2017 ng/L47--------------------EU8 643 10/18/2017 2/13/2018 ng/L89.1 --------------------EU8 6432/13/2018 2/13/2018 ng/L30.3 --------------------EU8 644 10/19/2017 10/19/2017 ng/L430 --------------------EU8 64611/9/2017 11/9/2017 ng/L89--------------------EU8 648 10/20/2017 10/20/2017 ng/L19--------------------EU8 649 10/18/2017 10/18/2017 ng/L78--------------------EU8 650 10/18/2017 10/18/2017 ng/L170 --------------------EU8 651 10/18/2017 10/18/2017 ng/L34--------------------EU8 653 10/18/2017 10/10/2019 ng/L290 120<2 <217 99 260 18 5.7<2450TR0795Page 14 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU8 655 11/21/2018 11/21/2018 ng/L52 -- -- -- -- -- -- -- -- -- --EU8 657 10/19/2017 10/19/2017 ng/L13<20 <2 <2 <28.2 11<2 <2 <246EU8 657 10/19/2017 10/19/2017 ng/L12 -- -- -- -- -- -- -- -- -- --EU8 657 10/19/2017 10/19/2017 ng/L21 -- -- -- -- -- -- -- -- -- --EU8 657 10/19/2017 10/19/2017 ng/L14 -- -- -- -- -- -- -- -- -- --EU8 661 1/10/2018 1/10/2018 ng/L16.7 -- -- -- -- -- -- -- -- -- --EU8 662 10/30/2017 10/30/2017 ng/L17 -- -- -- -- -- -- -- -- -- --EU8 663 12/26/2018 12/26/2018 ng/L16 6.5<2 <2 <25.1 5<2 <2 <274EU8 664 10/24/2017 10/24/2017 ng/L11 -- -- -- -- -- -- -- -- -- --EU8 665 6/13/2019 6/13/2019 ng/L22.8 -- --<1.21 <1.2128.3 33.4 1.46<1.21-- --EU8 791 10/26/2017 10/26/2017 ng/L11<20 <2 <2 <26.52<2 <2 <245EU8 792 10/17/2017 10/17/2017 ng/L14<20 <2 <2 <25.7<2 <2 <2 <252EU8 7490 8/15/2019 8/15/2019 ng/L<2.6 <11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.1 <5.3EU8 6701/12/2018 10/1/2019 ng/L250 130<2 <218 140 430 69 17<2560EU8 3041 9/11/2019 9/11/2019 ng/L4.1<20 <2 <23.3 8.8 5.2<2 <2 <289EU8 3042 7/25/2019 7/25/2019 ng/L81 37<1.1 <1.121 59 130 7.5 1.6<1.1180EU8 3045 7/22/2019 7/22/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <227EU8 2389/8/2017 1/28/2019 ng/L140 63<2 <211 51 120 6.7<2 <2300EU8 2339/13/2017 10/3/2017 ng/L35.5 --------------------EU8 6709/15/2017 9/15/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 3052 7/19/2019 7/19/2019 ng/L5.4<20 <2 <22.3 6.1 8.6<2 <2 <226EU8 3054 7/25/2019 7/25/2019 ng/L3.5<11 <1.1 <1.11.2 10 2.6<1.1 <1.1 <1.198EU8 30558/8/2019 8/8/2019 ng/L37 24<1.1 <1.115 35 88 14 3.5<1.1120EU8 3056 7/19/2019 7/19/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 3057 7/25/2019 7/25/2019 ng/L3.4<11 <1.1 <1.1 <1.14.6<1.1 <1.1 <1.1 <1.194EU830587/19/2019 7/19/2019 ng/L17<20 <2 <26.2 15 28 2.4<2 <260EU8 3059 8/29/2019 8/29/2019 ng/L9.2<20 <2 <23.1 18 15<2 <2 <296EU8 3060 8/28/2019 8/28/2019 ng/L13<20 <2 <26.6 24 41 4.1<2 <283EU8 3061 7/19/2019 7/19/2019 ng/L19<20 <2 <25.8 18 32 2.7<2 <276EU8 30628/9/2019 8/9/2019 ng/L4.8<11 <1.1 <1.11.1 5.1<1.1 <1.1 <1.1 <1.192EU8 2406 1/10/2018 1/10/2018 ng/L31.8 --------------------EU8 3064 7/19/2019 7/19/2019 ng/L8.4<20 <2 <2 <29.2 13<2 <2 <241EU8 3065 7/17/2019 7/17/2019 ng/L5<20 <2 <22.7 6.8 6.3<2 <2 <242EU8 3066 8/19/2019 8/19/2019 ng/L8.9<20 <2 <26.3 21 15<2 <2 <2110EU8 30687/2/2019 7/2/2019 ng/L9.6<20 <2 <2 <211 18 2.7<2 <256EU8 3069 7/23/2019 7/23/2019 ng/L3.5<20 <2 <22.4 6.9 6.9<2 <2 <249EU8 3071 7/24/2019 7/24/2019 ng/L25<20 <2 <25.5 29 618<2 <2110EU8 3072 8/23/2019 8/23/2019 ng/L17<20 <2 <28.8 24 313<2 <2120EU8 3073 8/28/2019 8/28/2019 ng/L7.8<20 <2 <2 <25.9 10<2 <2 <232EU8 3074 7/23/2019 7/23/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 3075 7/23/2019 7/23/2019 ng/L26<20 <2 <25.6 23 50 4.6 2.1<276EU8 30768/9/2019 8/9/2019 ng/L12 13<1.1 <1.13.4 14 14<1.1 <1.1 <1.198EU8 3076 8/23/2019 8/23/2019 ng/L14<20 <2 <27.5 19 18<2 <2 <2110TR0795Page 15 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU8 3077 10/3/2019 10/3/2019 ng/L2.8<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 3078 8/28/2019 8/28/2019 ng/L21<20 <2 <25.8 14 20<2 <2 <2110EU8 30799/3/2019 9/3/2019 ng/L2.9<20 <2 <24.4 15 15<2 <2 <284EU8 3080 7/23/2019 7/23/2019 ng/L3.9<20 <2 <2 <2 <53.7<2 <2 <241EU8 3082 9/17/2019 9/17/2019 ng/L59 22<2 <27 43 78 5.8<2 <2130EU8 2487 10/25/2018 10/25/2018 ng/L9<20 <2 <26.8 16 26 3.4<2 <272EU8 3083 8/23/2019 8/23/2019 ng/L<2.6 <20 <2 <24.4<52.8<2 <2 <232EU8 3084 7/23/2019 7/23/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <222EU8 3085 7/22/2019 7/22/2019 ng/L6.4<20 <2 <25.9 21 14<2 <2 <276EU8 3086 7/22/2019 7/22/2019 ng/L4.5<20 <2 <2 <2 <54<2 <2 <245EU8 3088 7/24/2019 7/24/2019 ng/L58 45<2 <25.5 51 87 5.6<2 <2180EU8 3089 7/29/2019 7/29/2019 ng/L35 35<1.1 <1.19.6 31 86 6.5 1.8<1.1170EU8 2407 1/10/2018 8/28/2019 ng/L5.27<20 <2 <23.2 5 3.5<2 <2 <229EU8 7613 8/28/2019 8/28/2019 ng/L2.7<20 <2 <22 6.4 2.7<2 <2 <247EU8 3091 7/24/2019 7/24/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 3092 7/22/2019 7/22/2019 ng/L59 31<2 <23.5 36 71 6.2<2 <2210EU8 3095 7/24/2019 7/24/2019 ng/L53 43<2 <25.4 47 77 5.2<2 <2180EU8 3096 7/24/2019 7/24/2019 ng/L14<20 <2 <23 15 9.9<2 <2 <2100EU8 2408 1/10/2018 1/10/2018 ng/L5.02 -- -- -- -- -- -- -- -- -- --EU8 3099 7/23/2019 7/23/2019 ng/L6.6<20<2<23.3 9.5 12<2 <2 <252EU8 2409 1/10/2018 8/28/2019 ng/L5.1<20 <2 <24.2<5 <2 <2 <2 <241EU8 2410 1/10/2018 9/4/2019 ng/L<2.6 <20 <2 <22.6<54.6<2 <2 <217EU8 31008/8/2019 8/8/2019 ng/L5.6<11 <1.1 <1.114 20 17<1.1 <1.1 <1.184EU8 3102 7/26/2019 7/26/2019 ng/L5.4<20 <2 <29.5 21 28 2.6<2 <250EU8 3103 7/22/2019 7/22/2019 ng/L15<20 <2 <25.7 9.9 8.4<2 <2 <238EU8 2411 1/10/2018 5/13/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU8 2279/8/2017 9/8/2017 ng/L48--------------------EU8 2269/8/2017 9/8/2017 ng/L39--------------------EU8 2249/13/2017 11/7/2017 ng/L37--------------------EU8 2259/13/2017 9/29/2017 ng/L0.92<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2556 9/12/2019 9/12/2019 ng/L20<20 <2 <2 <272.1<2 <2 <2160EU9 2557 7/26/2019 7/26/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <249EU9 2073 1/23/2018 1/23/2018 ng/L7.4<20 <2 <2 <2 <5 <2 <2 <2 <213EU9 2074 1/24/2018 1/24/2018 ng/L9.4<20 <2 <2 <2 <52<2 <2 <214EU9 20756/3/2019 6/3/2019 ng/L200 120<2 <226 16 200 19<2 <2570EU9 1332 2/13/2018 2/13/2018 ng/L25--------------------EU9 2076 1/23/2018 9/11/2019 ng/L130 75<2 <227 79 130 11 2.5<2450EU9 2076 3/27/2018 3/27/2018 ng/L180 130<50 <50 <5070 170<50 <50 <100610EU9 1315 1/23/2018 10/8/2019 ng/L310 220<2 <231 170 400 59 9.3<2920EU9 1334 1/25/2018 1/25/2018 ng/L15<20 <2 <2 <2 <53.2<2 <2 <233EU9 1317 1/23/2018 8/27/2019 ng/L550 460<2 <232150310 24 5.5<22300EU9 2078 1/25/2018 5/3/2018 ng/L150 --------------------EU9 13183/7/2018 3/7/2018 ng/L11<20 <2 <28.4 22 25 2.3<2 <289TR0795Page 16 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU9 2079 1/23/2018 6/5/2019 ng/L18<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 1300 7/23/2018 7/23/2018 ng/L13--------------------EU9 2080 2/13/2018 2/13/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 13035/7/2018 5/7/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 3153 5/15/2019 5/15/2019 ng/L<0.591----<1.18 <1.18 <1.18 <1.18 <1.18 <1.18----EU9 2091 1/29/2018 1/29/2018 ng/L18--------------------EU9 20929/9/2019 9/9/2019 ng/L25<20 <2 <29.1 26 49 5.4<2 <298EU9 1298 8/31/2018 8/31/2018 ng/L44--------------------EU9 13052/2/2018 2/2/2018 ng/L55--------------------EU9 2095 1/25/2018 1/25/2018 ng/L31--------------------EU9 20962/5/2018 2/5/2018 ng/L45--------------------EU9 2097 2/16/2018 2/16/2018 ng/L39--------------------EU9 8189 10/1/2019 10/1/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2490 12/26/2018 12/26/2018 ng/L53 35<2 <29.3 28 33<2 <2 <2150EU9 2705 6/20/2019 6/20/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <269EU9 2706 6/20/2019 6/20/2019 ng/L56 57<2 <23.5 17 12<2 <2 <2290EU9 2707 7/30/2019 7/30/2019 ng/L<2.6250<1.1 <1.126 190 530 41 156 860EU9 2709 6/20/2019 6/20/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <210EU9 2711 4/10/2019 4/10/2019 ng/L30.1 ----<1.2412.3 32.4 33.4 1.93 1.26 ----EU9 2713 6/20/2019 6/20/2019 ng/L8.7<20 <2 <2 <2 <52.2<2 <2 <291EU9 2715 6/20/2019 6/20/2019 ng/L4.4<20 <2 <2 <2 <5 <2 <2 <2 <278EU9 2491 12/26/2018 12/26/2018 ng/L23 12<2 <28.8 20 36 2.2<2 <289EU9 27218/9/2019 8/9/2019 ng/L<2.6 <11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.143EU9 27268/7/2019 8/7/2019 ng/L4.4<11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.166EU9 8191 10/1/2019 10/1/2019 ng/L13<20 <2 <26.2 16 24<2 <2 <286EU9 2731 7/17/2019 7/17/2019 ng/L9.4<20 <2 <2 <25.2 2.7<2 <2 <2110EU9 24932/6/2019 9/11/2019 ng/L17.6 ----<1.226.36 26.3 22.4<1.22 <1.22----EU922713/2/20183/2/2018 ng/L6<20 <2 <2 <2 <5 <2 <2 <2 <237EU9 2274 3/16/2018 7/10/2019 ng/L1.71<20 <2 <1.14 <1.14 <1.14 <1.14 <1.14 <1.14 <2 <10EU9 22852/7/2018 3/28/2018 ng/L21.9 --------------------EU9 2280 1/31/2018 1/31/2018 ng/L21--------------------EU9 2302 1/30/2018 1/30/2018 ng/L4.9<20 <2 <2 <2 <5 <2 <2 <2 <281EU9 2355 1/30/2018 3/25/2019 ng/L13<20 <2 <2 <25.4<2 <2 <2 <2150EU9 8194 10/1/2019 10/1/2019 ng/L71 44<2 <217 40 81 8.3 3.9<2280EU9 7605 8/26/2019 8/26/2019 ng/L20 23<2 <23.2 18 13<2 <2 <2200EU9 23632/8/2018 2/8/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2325 1/30/2018 1/30/2018 ng/L18<20 <2 <2 <2 <52.2<2 <2 <269EU9 2317 1/30/2018 1/30/2018 ng/L30--------------------EU9 23832/6/2018 2/6/2018 ng/L12--------------------EU9 23072/6/2018 2/6/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2309 1/30/2018 1/30/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <230EU9 23162/6/2018 2/6/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <241EU9 23122/6/2018 2/6/2018 ng/L5.3<20 <2 <2 <2 <5 <2 <2 <2 <232TR0795Page 17 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU9 2315 4/11/2018 4/11/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2311 1/26/2018 1/26/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <244EU9 2360 1/30/2018 1/30/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <231EU9 2314 1/30/2018 1/30/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <224EU9 2313 2/6/2018 2/6/2018 ng/L15 -- -- -- -- -- -- -- -- -- --EU9 2324 2/6/2018 2/6/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2364 2/21/2018 2/21/2018 ng/L41 -- -- -- -- -- -- -- -- -- --EU9 2310 1/30/2018 1/30/2018 ng/L12 -- -- -- -- -- -- -- -- -- --EU9 2310 1/30/2018 1/30/2018 ng/L16 -- -- -- -- -- -- -- -- -- --EU9 2308 1/30/2018 1/30/2018 ng/L14 -- -- -- -- -- -- -- -- -- --EU9 2306 1/30/2018 1/30/2018 ng/L14 -- -- -- -- -- -- -- -- -- --EU9 2382 1/30/2018 1/30/2018 ng/L15 -- -- -- -- -- -- -- -- -- --EU9 2357 4/30/2019 4/30/2019 ng/L67 49<2 <24.4 33 49 2.9<2 <2300EU9 2297 2/6/2018 2/6/2018 ng/L67 -- -- -- -- -- -- -- -- -- --EU9 2298 1/30/2018 1/30/2018 ng/L63<100 <50 <50 <50 <5064<50 <50 <100390EU9 2296 1/30/2018 1/30/2018 ng/L80 -- -- -- -- -- -- -- -- -- --EU9 2291 2/13/2018 6/4/2019 ng/L44<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2289 1/30/2018 1/30/2018 ng/L11<20 <2 <2 <2 <5 <2 <2 <2 <2120EU9 2294 2/7/2018 2/7/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <233EU9 22868/7/2019 8/7/2019 ng/L49 36<1.1 <1.14.4 22 17<1.1 <1.1 <1.1260EU9 22883/9/2018 3/9/2018 ng/L10<20 <2 <2 <25.8 2.1<2 <2 <2110EU9 2293 2/13/2018 2/13/2018 ng/L11<20 <2 <2 <2 <5 <2 <2 <2 <248EU9 2352 2/13/2018 2/13/2018 ng/L4.4<20 <2 <2 <2 <5 <2 <2 <2 <231EU9 2292 1/30/2018 10/19/2018 ng/L130 --------------------EU9 2351 1/30/2018 1/30/2018 ng/L64--------------------EU9 2287 1/31/2018 1/31/2018 ng/L12--------------------EU9 22902/8/2018 7/24/2019 ng/L5.2<20 <2 <1.19 <1.19 <1.19 <1.19 <1.19 <1.19 <2 <10EU9 2284 1/31/2018 1/31/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <219EU9 23372/5/2018 2/5/2018 ng/L87--------------------EU9 23392/5/2018 2/5/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2344 2/15/2018 2/15/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2340 2/14/2018 2/14/2018 ng/L66--------------------EU9 2345 2/14/2018 2/14/2018 ng/L610 --------------------EU9 2343 2/14/2018 2/14/2018 ng/L74--------------------EU9 24142/9/2018 2/9/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2376 2/15/2018 6/3/2019 ng/L27<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU923872/6/20182/6/2018 ng/L85<100 <50 <50 <50 <5084<50 <50 <100420EU9 2334 10/3/2019 10/3/2019 ng/L4.4<20 <2 <2 <2 <57.3<2 <2 <234EU9 23752/1/2018 4/5/2018 ng/L57--------------------EU9 23412/1/2018 2/1/2018 ng/L37--------------------EU9 23902/7/2018 2/7/2018 ng/L12--------------------EU9 8316 10/7/2019 10/7/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2764 7/12/2019 7/12/2019 ng/L150 86<2 <28.8 47 120 8.1<2 <2340TR0795Page 18 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU9 8318 10/7/2019 10/7/2019 ng/L11<20 <2 <214 22 22<2 <2 <2110EU9 2767 7/29/2019 7/29/2019 ng/L52 55<1.1 <1.19.8 30 45 2.6<1.1 <1.1320EU9 2770 7/29/2019 7/29/2019 ng/L52 51<1.1 <1.112 35 51 5 1.1<1.1220EU9 2773 7/30/2019 7/30/2019 ng/L56 46<1.1 <1.117 58 39 2.4<1.1 <1.1210EU9 2775 8/5/2019 8/5/2019 ng/L69 55<1.1 <1.115 35 73 9.8 3<1.1270EU9 8319 10/7/2019 10/7/2019 ng/L52 54<2 <214 38 70 5.9<2 <2220EU9 2780 4/10/2019 4/10/2019 ng/L107 -- --<1.210.4 72 60.1 5.71<1.2-- --EU9 2790 7/11/2019 7/11/2019 ng/L<2.8 <202.3<23.4 10 11<2 <27.7 36EU9 2799 7/29/2019 7/29/2019 ng/L4<11 <1.1 <1.17.7 27 26<1.1 <1.1 <1.1120EU9 2801 7/17/2019 7/17/2019 ng/L63 49<2 <26.8 28 61 6.6<2 <2270EU9 2115 9/9/2019 9/9/2019 ng/L140 65<2 <226 38 88 8.2<2 <2260EU9 2489 12/26/2018 10/2/2019 ng/L180 69<2 <223 66 270 25<2 <2220EU9 2820 7/31/2019 7/31/2019 ng/L33 29<1.1 <1.15.5 26 41<1.1 <1.1 <1.1150EU9 2822 6/19/2019 6/19/2019 ng/L45 25<2 <230 26 91 18 7<2110EU9 2823 7/26/2019 7/26/2019 ng/L59 58<1.1 <1.19 30 47 2.2<1.1 <1.1230EU9 2824 6/19/2019 6/19/2019 ng/L64 57<2 <27.5 23 56 4.1<2 <2230EU9 2826 7/3/2019 7/3/2019 ng/L6.6<20 <2 <2 <2 <5 <2 <2 <2 <230EU9 21192/8/2018 2/8/2018 ng/L27--------------------EU91361 1/31/2018 1/31/2018 ng/L26--------------------EU9 1368 1/31/2018 1/7/2019 ng/L170 77<2 <26.7 73 55 7.1<2 <2350EU9 28418/7/2019 8/7/2019 ng/L<2.6 <11 <1.1 <1.1 <1.16.7 5.4<1.1 <1.1 <1.116EU9 2120 1/31/2018 1/31/2018 ng/L360 --------------------EU9 28448/7/2019 8/7/2019 ng/L17<11 <1.1 <1.19.2 16 35 4.2 1.5<1.146EU9 1369 1/31/2018 1/31/2018 ng/L180 --------------------EU9 1364 1/31/2018 1/31/2018 ng/L26--------------------EU9 2122 1/31/2018 1/31/2018 ng/L87--------------------EU9 8323 10/7/2019 10/7/2019 ng/L46 23<2 <213 27 61 6.5<2 <2100EU9 3163 7/10/2019 7/10/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 3164 7/10/2019 7/10/2019 ng/L20<20 <2 <22.7 15 6.7<2 <2 <294EU9 2124 1/31/2018 11/20/2018 ng/L220<10000 <9600 <12000 <9500 <9500 <9200 <8800 <9700 <11000 <8400EU9 1370 2/16/2018 2/16/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2126 7/18/2019 7/18/2019 ng/L66 55<2 <23.6 26 40 2.8<2 <2280EU9 1310 7/18/2019 7/18/2019 ng/L97 74<2 <26.8 36 554<2 <2330EU9 2856 6/19/2019 6/19/2019 ng/L26<20 <2 <29.1 18 43 6.42<278EU9 2127 1/30/2018 1/30/2018 ng/L65--------------------EU9 1313 1/30/2018 1/30/2018 ng/L79--------------------EU9 2128 1/31/2018 11/28/2018 ng/L170 --------------------EU9 23262/1/2018 2/1/2018 ng/L31--------------------EU9 23332/1/2018 2/1/2018 ng/L15--------------------EU9 21312/1/2018 1/28/2019 ng/L140 48<2 <217 41 98 3.9<2 <2200EU9 13722/6/2018 2/6/2018 ng/L18--------------------EU9 21322/5/2018 2/5/2018 ng/L15--------------------EU9 23322/1/2018 2/1/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10TR0795Page 19 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU9 2133 2/15/2018 11/28/2018 ng/L130 -- -- -- -- -- -- -- -- -- --EU9 1336 2/2/2018 2/2/2018 ng/L22 -- -- -- -- -- -- -- -- -- --EU9 2330 2/2/2018 2/2/2018 ng/L6.2<20 <2 <2 <2 <5 <2 <2 <2 <219EU9 2134 1/26/2018 8/15/2019 ng/L150 180<1.1 <1.121 58 110 7.9 2.5<1.1690EU9 2135 1/26/2018 1/26/2018 ng/L84 -- -- -- -- -- -- -- -- -- --EU9 2136 1/30/2018 1/30/2018 ng/L81 -- -- -- -- -- -- -- -- -- --EU9 2137 1/31/2018 1/31/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2331 2/2/2018 2/2/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 1338 6/19/2019 6/19/2019 ng/L180 110<2 <218 54 130 15 3.9<2480EU9 2365 2/2/2018 2/2/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 1339 2/5/2018 2/5/2018 ng/L33 -- -- -- -- -- -- -- -- -- --EU9 1340 2/13/2018 2/13/2018 ng/L57 -- -- -- -- -- -- -- -- -- --EU9 1341 2/12/2018 2/12/2018 ng/L28 -- -- -- -- -- -- -- -- -- --EU9 2863 6/19/2019 7/30/2019 ng/L8<11 <1.1 <1.17.3 17 18<1.1 <1.1 <1.150EU9 2138 1/30/2018 1/30/2018 ng/L53 -- -- -- -- -- -- -- -- -- --EU9 2139 2/6/2018 4/24/2019 ng/L131 -- --<1.317.2 80.2 50.5 9.16 3.22 -- --EU9 2140 1/30/2018 1/30/2018 ng/L31 -- -- -- -- -- -- -- -- -- --EU9 2141 4/11/2018 4/11/2018 ng/L14.6 -- -- -- -- -- -- -- -- -- --EU9 2143 1/24/2018 1/24/2018 ng/L12 -- -- -- -- -- -- -- -- -- --EU9 2144 1/26/2018 1/26/2018 ng/L65 -- -- -- -- -- -- -- -- -- --EU9 1344 1/26/2018 1/26/2018 ng/L41 -- -- -- -- -- -- -- -- -- --EU9 2145 1/24/2018 1/24/2018 ng/L10 23<2 <22.6 12 12<2 <2 <281EU9 1345 2/5/2018 2/5/2018 ng/L87 -- -- -- -- -- -- -- -- -- --EU9 2146 1/24/2018 1/24/2018 ng/L10<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2146 5/7/2018 5/7/2018 ng/L11<20 <2 <23 14 2.9<2 <2 <2180EU9 2147 1/24/2018 1/24/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2148 2/6/2018 2/6/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2322 1/31/2018 2/5/2018 ng/L18.1 -- -- -- -- -- -- -- -- -- --EU9 2369 2/7/2018 2/7/2018 ng/L12 -- -- -- -- -- -- -- -- -- --EU9 2323 2/2/2018 2/2/2018 ng/L34 -- -- -- -- -- -- -- -- -- --EU9 2367 2/14/2018 2/14/2018 ng/L87 -- -- -- -- -- -- -- -- -- --EU9 2149 1/24/2018 1/24/2018 ng/L58 -- -- -- -- -- -- -- -- -- --EU9 1347 4/23/2019 4/23/2019 ng/L100 65<2 <213 30 47 5.5<2 <2210EU9 2150 2/15/2018 7/16/2018 ng/L160 170<50 <50 <50 <50140<50 <50 <100500EU9 23682/7/2018 2/7/2018 ng/L64--------------------EU91349 9/11/2019 9/11/2019 ng/L99 53<2 <211 54 483<2 <2230EU9 2153 1/30/2018 1/30/2018 ng/L140 --------------------EU9 8195 10/1/2019 10/1/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2154 1/30/2018 1/30/2018 ng/L37--------------------EU9 8183 10/1/2019 10/1/2019 ng/L18<20 <2 <211 20 68 7.1<2 <277EU9 3291 9/13/2019 9/13/2019 ng/L8.6<20 <2 <28.5 19 37 5.3<2 <249EU9 2157 1/30/2018 1/30/2018 ng/L65--------------------EU9 21583/6/2018 3/6/2018 ng/L73--------------------TR0795Page 20 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU9 2159 1/30/2018 1/30/2018 ng/L20 -- -- -- -- -- -- -- -- -- --EU9 2338 2/5/2018 2/5/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2160 2/16/2018 2/16/2018 ng/L20--------------------EU9 2372 2/14/2018 2/14/2018 ng/L78<100 <50 <50 <5054 87<50 <50 <100350EU9 2329 2/12/2018 2/12/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2162 2/15/2018 2/15/2018 ng/L52--------------------EU9 23362/5/2018 8/8/2019 ng/L150 110<1.1 <1.18.7 29 87 10<1.1 <1.1560EU9 2165 3/13/2018 3/13/2018 ng/L28--------------------EU9 2166 9/16/2019 9/16/2019 ng/L22<20 <2 <25.8 15 294<2 <268EU9 3293 8/14/2019 8/14/2019 ng/L<2.6 <11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.1 <5.3EU9 23282/5/2018 2/5/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2342 7/23/2018 9/24/2018 ng/L23--------------------EU9 1351 2/14/2018 2/14/2018 ng/L28--------------------EU9 2169 1/24/2018 1/24/2018 ng/L15<20 <2 <27.4 16 19 2.3<2 <258EU9 7607 8/26/2019 8/26/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 13532/8/2018 2/8/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <211EU9 3295 8/14/2019 8/14/2019 ng/L12<11 <1.1 <1.1 <1.13.2 6.7<1.1 <1.1 <1.125EU9 8338 10/7/2019 10/7/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 7606 8/26/2019 8/26/2019 ng/L45 31<2 <25.5 31 38 2.5<2 <2180EU9 1355 1/25/2018 8/28/2018 ng/L110 --------------------EU9 2884 6/28/2019 6/28/2019 ng/L37 35<2 <214 50 71 6.3<2 <2240EU9 3296 8/14/2019 8/14/2019 ng/L35<20 <2 <25.9 17 44 5.7 2.8<262EU9 3297 8/14/2019 8/14/2019 ng/L32 15<1.1 <1.16.4 18 25 2.5<1.1 <1.183EU9 2895 6/28/2019 6/28/2019 ng/L33<20 <2 <22.3 11 35 4.6 2.4<289EU9 13572/6/2018 6/18/2018 ng/L210 --------------------EU9 5333/27/2019 3/27/2019 ng/L5.24 ----<1.214.07 6.34 8.74<1.21 <1.21----EU9 2910 7/29/2019 7/29/2019 ng/L100 70<1.1 <1.118 49 64 2.7<1.1 <1.1240EU925013/27/2019 3/27/2019 ng/L143 ----<1.369.9 53.2 50.1 4.34<1.36----EU9 2488 11/28/2018 11/28/2018 ng/L146 --------------------EU9 2921 9/23/2019 9/23/2019 ng/L80 47<2 <212 36 46 2.1<2 <2230EU9 2922 7/29/2019 7/29/2019 ng/L180 100<1.1 <1.121 75 180 15<1.1 <1.1320EU9 3299 10/4/2019 10/4/2019 ng/L13<20 <2 <2 <26.1 4.8<2 <2 <2110EU9 29237/8/2019 7/8/2019 ng/L44 33<2 <28.1 24 26<2 <2 <2140EU9 2925 7/22/2019 7/22/2019 ng/L67 31<2 <25.3 26 37<2 <2 <2150EU9 29277/8/2019 7/8/2019 ng/L56 24<2 <26.2 24 22<2 <2 <2140EU9 29297/8/2019 7/22/2019 ng/L59 30<2 <29.9 27 41<2 <2 <2150EU9 2930 7/11/2019 7/11/2019 ng/L15<202.5<281820<2 <28.9 96EU9 29348/7/2019 8/7/2019 ng/L48 19<1.1 <1.15.4 26 66 6.2<1.1 <1.172EU9 29348/7/2019 8/7/2019 ng/L<2.6 <11 <1.1 <1.115 15 12<1.1 <1.1 <1.137EU9 2935 4/10/2019 7/24/2019 ng/L8.2 ----<1.175.01 13.9 11 1.44<1.17----EU9 8344 9/18/2019 9/18/2019 ng/L22.7 --<1.23 <1.235.47 24.7 21.2<1.23 <1.23 <1.23--EU9 2936 4/10/2019 9/25/2019 ng/L270 80<2 <1.2317 161 240 37 2.05<2290EU9 2939 10/17/2019 10/17/2019 ng/L44 47<2 <25.4 35 58 6.6<2 <2260TR0795Page 21 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU9 2940 7/12/2019 7/12/2019 ng/L65 73<2 <25.9 44 94 9.9<2 <2380EU9 2942 8/6/2019 8/6/2019 ng/L63 54<1.1 <1.17.2 42 63 5.5<1.1 <1.1270EU9 1377 2/1/2018 2/1/2018 ng/L12 -- -- -- -- -- -- -- -- -- --EU9 1378 2/26/2018 2/26/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 1380 2/12/2018 2/12/2018 ng/L10<20 <2 <26.8 18 29 2.5<2 <253EU9 2197 2/9/2018 2/9/2018 ng/L13 -- -- -- -- -- -- -- -- -- --EU9 2946 9/19/2019 9/19/2019 ng/L120 67<2 <219 36 100 9.3<2 <2280EU9 860 11/29/2017 11/20/2018 ng/L390<500 <480 <580 <470 <470 <460 <440 <490 <530630EU9 2199 2/1/2018 2/1/2018 ng/L38 -- -- -- -- -- -- -- -- -- --EU9 2203 2/14/2018 2/14/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <212EU9 23192/1/2018 2/1/2018 ng/L16--------------------EU9 2962 6/21/2019 6/21/2019 ng/L9.4<20 <2 <2 <2 <52<2 <2 <2100EU9 13852/1/2018 2/1/2018 ng/L<4 <100 <50 <50 <50 <50 <50 <50 <50 <100 <50EU9 13852/1/2018 2/1/2018 ng/L12<20 <2 <23.4 18 13<2 <2 <2140EU9 13869/4/2019 9/4/2019 ng/L64 53<2 <26.3 50 70 3.7<2 <2270EU9 13882/7/2018 2/7/2018 ng/L21--------------------EU9 2205 4/10/2019 4/10/2019 ng/L<0.648----<1.3 <1.3 <1.3 <1.3 <1.3 <1.3----EU9 2392 1/26/2018 1/26/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2210 2/14/2018 2/14/2018 ng/L24--------------------EU9 23032/1/2018 2/1/2018 ng/L6.4<20 <2 <2 <2 <5 <2 <2 <2 <217EU9 2506 3/27/2019 3/27/2019 ng/L4.31 ----<1.47 <1.47 <1.47 <1.47 <1.47 <1.47----EU9 2507 3/27/2019 7/24/2019 ng/L16.3 ----<1.18 <1.186.98 7.41<1.18 <1.18----EU9 23012/6/2018 2/6/2018 ng/L11--------------------EU9 13942/1/2018 2/1/2018 ng/L14 21<2 <2 <211 8.4<2 <2 <2120EU9 23002/1/2018 2/1/2018 ng/L21--------------------EU9 22242/1/2018 2/1/2018 ng/L12--------------------EU9 22242/1/2018 2/1/2018 ng/L13 23<2 <2 <213 11<2<2<2120EU9 22992/6/2018 2/6/2018 ng/L79--------------------EU9 1320 1/25/2018 1/25/2018 ng/L63--------------------EU9 13952/1/2018 2/1/2018 ng/L25--------------------EU9 2353 1/31/2018 1/31/2018 ng/L61--------------------EU9 2381 1/31/2018 1/31/2018 ng/L14--------------------EU9 23802/1/2018 2/1/2018 ng/L42--------------------EU9 2227 1/30/2018 1/30/2018 ng/L30--------------------EU9 2228 2/12/2018 7/25/2019 ng/L21<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 22292/7/2018 2/7/2018 ng/L42--------------------EU9 22312/6/2018 2/6/2018 ng/L36--------------------EU9 13232/7/2018 6/5/2019 ng/L13<20 <2 <2 <2 <52.2<2 <2 <234EU9 13252/7/2018 2/7/2018 ng/L16--------------------EU9 1396 1/24/2018 1/24/2018 ng/L31--------------------EU9 22422/1/2018 1/28/2019 ng/L180 110<2 <28.9 83 130 11<2 <2450EU9 2247 3/11/2019 3/11/2019 ng/L290 100<2 <218 100 190 26 3.8<2350EU9 1399 1/24/2018 1/24/2018 ng/L220 230<50 <50 <5080 210<50 <50 <100940TR0795Page 22 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU9 24868/1/2018 8/1/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2260 2/22/2018 9/25/2019 ng/L250 180<1.1 <1.119 170 230 25 2.7<1.1780EU9 24595/1/2018 7/23/2018 ng/L180 180<50 <50 <5056 77<50 <50 <100660EU9 2461 4/25/2018 4/25/2018 ng/L8.86 --------------------EU9 22633/5/2018 3/5/2018 ng/L330 --------------------EU9 14002/7/2018 2/7/2018 ng/L16--------------------EU9 22652/9/2018 2/9/2018 ng/L200 --------------------EU9 2266 1/31/2018 1/31/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 2267 2/22/2018 9/25/2019 ng/L200 230<2 <27.8 74 180 14 3.3<2840EU9 14022/1/2018 2/1/2018 ng/L150 --------------------EU9 14042/1/2018 2/1/2018 ng/L29--------------------EU9 24042/1/2018 10/22/2018 ng/L100 --------------------EU9 3037 6/18/2019 6/18/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU9 93812/6/2017 12/6/2017 ng/L91--------------------EU9 2463 4/25/2018 4/25/2018 ng/L1.88 --------------------EU9 2462 4/25/2018 4/25/2018 ng/L80--------------------EU10 1007 12/14/2017 12/14/2017 ng/L21<100 <50 <50 <50 <50 <50 <50 <50 <100230EU10 20833/1/2018 3/1/2018 ng/L14 38<2 <232 16 4.4<2 <2 <2220EU10 15262/7/2018 2/7/2018 ng/L9.9 29<2 <235 27 3.4<2 <2 <2220EU10 8221 10/2/2019 10/2/2019 ng/L8.8 20<2 <218 21 11<2 <2 <2160EU10 8386 10/10/2019 10/10/2019 ng/L12<20 <2 <2 <2 <512<2 <2 <268EU10 910 12/12/2017 12/12/2017 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU10 954 12/15/2017 12/15/2017 ng/L23<100 <50 <50 <50 <50 <50 <50 <50 <100180EU10 972 12/13/2017 12/13/2017 ng/L38<100 <50 <50 <50 <5079<50 <50 <100150EU10 21162/8/2018 2/8/2018 ng/L<4 <20 <2 <26.4 5.5<2 <2 <2 <241EU10 1010 1/24/2018 1/24/2018 ng/L50<100 <50 <50 <5062 98<50 <50 <100580EU10 9111/24/2018 1/24/2018 ng/L15--------------------EU10 2481 4/11/2018 4/11/2018 ng/L1.82 --------------------EU10 9121/24/2018 1/24/2018 ng/L4.5<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU1024963/13/2019 3/13/2019 ng/L76.4 ----<1.2119.1 40.4 32.5 6.91 2.34 ----EU10 2498 9/18/2019 9/18/2019 ng/L0.902 --<1.17 <1.17 <1.17 <1.17 <1.17 <1.17 <1.17 <1.17--EU10 2498 3/13/2019 3/13/2019 ng/L0.866 ----<1.3 <1.3 <1.3 <1.3 <1.3 <1.3----EU10 30168/7/2019 8/7/2019 ng/L59 49<1.1 <1.119 65 230 15<1.1 <1.1250EU10 30188/6/2019 8/6/2019 ng/L<2.6 <11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.15.8EU10 8232 10/2/2019 10/2/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU10 8229 10/2/2019 10/2/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU10 2471 4/25/2018 4/25/2018 ng/L1.79 --------------------EU10 8285 10/4/2019 10/4/2019 ng/L<2.9 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU10 2470 4/25/2018 4/25/2018 ng/L1.79 --------------------EU10 2472 4/25/2018 4/25/2018 ng/L1.79 --------------------EU10 3040 9/23/2019 9/23/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU10 9821/9/2018 1/9/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU10 2480 7/24/2019 7/24/2019 ng/L24.9 ----<1.162.37 5.82 5.2<1.16 <1.16----TR0795Page 23 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU10 Unknown 4/11/2018 4/11/2018 ng/L36.9 -- -- -- -- -- -- -- -- -- --EU10 913 12/11/2017 12/11/2017 ng/L6.3<20 <2 <24.9 7.9 17 4.1<2 <242EU10 913 1/15/2018 1/15/2018 ng/L4.8<20 <2 <2 <2 <53<2 <2 <214EU10 1011 11/30/2017 11/30/2017 ng/L13 -- -- -- -- -- -- -- -- -- --EU10 8238 10/4/2019 10/4/2019 ng/L4.1<20 <2 <25.7 10 7<2 <2 <232EU10 906 11/30/2017 11/30/2017 ng/L8.3 21<2 <218 20 28<2 <2 <2150EU10 2479 4/11/2018 4/11/2018 ng/L1.86 -- -- -- -- -- -- -- -- -- --EU10 3131 8/1/2019 8/1/2019 ng/L31 38<1.1 <1.123 43 130 13 3.4<1.1190EU11 2082 1/30/2018 1/30/2018 ng/L29<100 <50 <50 <50 <50 <50 <50 <50 <100140EU11 1483 1/26/2018 1/26/2018 ng/L14 22<2 <229 24 21<2 <2 <2160EU11 2521 7/26/2019 7/26/2019 ng/L3.3<20 <2 <2 <2 <5 <2 <2 <2 <228EU11 8022 9/27/2019 9/27/2019 ng/L7.7<20 <2 <27.9 8 14<2 <2 <2110EU11 2444 1/29/2018 1/29/2018 ng/L5.53 -- -- -- -- -- -- -- -- -- --EU11 7719 9/20/2019 9/20/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU11 2447 1/29/2018 1/29/2018 ng/L11.9 -- -- -- -- -- -- -- -- -- --EU11 7657 9/19/2019 9/19/2019 ng/L11<20 <2 <23 6.2 8.2<2 <2 <2110EU11 2418 3/7/2018 3/7/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU11 1537 2/7/2018 2/7/2018 ng/L23 -- -- -- -- -- -- -- -- -- --EU11 1521 1/26/2018 1/26/2018 ng/L26 -- -- -- -- -- -- -- -- -- --EU11 1491 1/30/2018 1/28/2019 ng/L170 120<2 <231 34 40<2.9 <3.9 <2570EU11 2430 2/13/2018 2/13/2018 ng/L2.5 --------------------EU11 2431 2/13/2018 2/13/2018 ng/L2.68 --------------------EU11 2530 7/31/2019 7/31/2019 ng/L19 12<1.1 <1.18.3 26 60 3.9 1.7<1.185EU11 2531 7/31/2019 7/31/2019 ng/L<2.6 <11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.15.5EU11 2451 1/29/2018 1/29/2018 ng/L8.25 --------------------EU11 8383 10/7/2019 10/7/2019 ng/L14<20 <2 <24.8 9.6 13<2 <2 <2150EU11 2535 8/29/2019 8/29/2019 ng/L3135<2<28.6 17 22<2 <2 <296EU11 2448 1/29/2018 1/29/2018 ng/L17.6 --------------------EU11 2537 7/31/2019 7/31/2019 ng/L35 18<1.1 <1.16.8 19 26<1.1 <1.1 <1.1110EU11 2432 4/16/2018 4/17/2018 ng/L232 --------------------EU11 2440 1/29/2018 1/29/2018 ng/L22--------------------EU11 14892/6/2018 2/6/2018 ng/L25--------------------EU11 2539 7/26/2019 7/26/2019 ng/L6.1<20 <2 <2 <25.1 2.5<2 <2 <2120EU11 8132 9/30/2019 9/30/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <224EU11 2540 9/16/2019 9/16/2019 ng/L4.4<20 <2 <22.3 11 9.2<2 <2 <252EU11 2541 7/29/2019 7/29/2019 ng/L39 35<1.1 <1.119 35 46 3.8<1.1 <1.1230EU11 15384/9/2018 4/9/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU11 2396 1/30/2018 1/30/2018 ng/L22--------------------EU11 2450 1/29/2018 1/29/2018 ng/L6.07 --------------------EU11 2548 7/30/2019 7/30/2019 ng/L12 16<1.1 <1.14.455.4<1.1 <1.1 <1.192EU11 1204 12/8/2017 12/8/2017 ng/L70--------------------EU11 2088 1/24/2018 6/12/2019 ng/L65<20 <2 <2 <2 <5 <2 <2 <2 <2560EU11 7693 9/20/2019 9/20/2019 ng/L<2.8 <20 <2 <26.6 11<2 <2 <2 <273TR0795Page 24 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU11 7720 9/20/2019 9/20/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU11 2433 2/13/2018 2/13/2018 ng/L5.98 --------------------EU11 15392/7/2018 2/7/2018 ng/L12--------------------EU11 2565 9/16/2019 9/16/2019 ng/L3.5<20 <2 <2514 9.7<2 <2 <269EU11 2394 1/30/2018 1/30/2018 ng/L5.7<20 <2 <22.8<55.3<2 <2 <231EU11 2439[3]1/29/2018 1/29/2018 ng/L0--------------------EU11 889 12/12/2017 12/12/2017 ng/L56 -- -- -- -- -- -- -- -- -- --EU11 2454 1/29/2018 1/29/2018 ng/L16.3 -- -- -- -- -- -- -- -- -- --EU11 2574 7/31/2019 7/31/2019 ng/L8.9 11<1.1 <1.111 24 18<1.1 <1.1 <1.1100EU11 2582 8/1/2019 8/1/2019 ng/L370 200<2 <227 78 210 27 4.6<2550EU11 2464 3/26/2018 3/26/2018 ng/L19.4 -- -- -- -- -- -- -- -- -- --EU11 2446 2/13/2018 2/13/2018 ng/L1.17 -- -- -- -- -- -- -- -- -- --EU11 2469 3/26/2018 3/26/2018 ng/L19.4 -- -- -- -- -- -- -- -- -- --EU11 2456 1/29/2018 1/29/2018 ng/L34.1 -- -- -- -- -- -- -- -- -- --EU11 2434 2/13/2018 2/13/2018 ng/L1.37 -- -- -- -- -- -- -- -- -- --EU11 2441 1/29/2018 6/12/2019 ng/L1.84<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU11 3170 2/13/2018 2/13/2018 ng/L0.742 -- -- -- -- -- -- -- -- -- --EU11 2460 4/23/2018 4/23/2018 ng/L70 -- -- -- -- -- -- -- -- -- --EU11 2460 5/24/2018 5/24/2018 ng/L49.4 -- -- -- -- -- -- -- -- -- --EU11 2077 2/7/2018 7/24/2019 ng/L120 -- --<1.1740 77.6 74.9 8.15 1.89 -- --EU11 2638 8/2/2019 8/2/2019 ng/L14 16<1.1 <1.17.2 9.8 12<1.1 <1.1 <1.1110EU11 2452 2/13/2018 2/13/2018 ng/L20.8 -- -- -- -- -- -- -- -- -- --EU11 2639 7/31/2019 7/31/2019 ng/L13 16<1.1 <1.14.8 15 19<1.1 <1.1 <1.1110EU11 2436[3]2/13/2018 2/13/2018 ng/L0--------------------EU11 2437 2/13/2018 2/13/2018 ng/L0.723 -- -- -- -- -- -- -- -- -- --EU11 9047 10/23/2019 10/23/2019 ng/L40 26<2 <217 22 37 2.6<2 <2140EU11 2653 7/30/2019 7/30/2019 ng/L14 11<1.1 <1.110 23 56 6.5 2.5<1.159EU11 2482 3/26/2018 3/26/2018 ng/L1.82 -- -- -- -- -- -- -- -- -- --EU11 2658 7/30/2019 7/30/2019 ng/L11 11<1.1 <1.111 22 54 6.6 2.4<1.160EU11 2659 9/30/2019 9/30/2019 ng/L8.5<20 <2 <25.9<5 <2 <2 <2 <274EU11 1520 1/26/2018 1/26/2018 ng/L31<100 <50 <50 <50 <50 <50 <50 <50 <100370EU11 2438 2/13/2018 2/13/2018 ng/L1.38 -- -- -- -- -- -- -- -- -- --EU11 2445 1/29/2018 1/29/2018 ng/L3.17 -- -- -- -- -- -- -- -- -- --EU11 2449 1/29/2018 1/29/2018 ng/L41.8 -- -- -- -- -- -- -- -- -- --EU11 7701 9/20/2019 9/20/2019 ng/L5.5<20 <2 <222 14 24<2 <2 <250EU11 1513 1/31/2018 1/31/2018 ng/L28--------------------EU11 2685 9/19/2019 9/19/2019 ng/L5.6<20 <2 <22.2 7.2 6.5<2 <2 <284EU11 1412 1/22/2018 1/22/2018 ng/L44--------------------EU11 8393 10/23/2019 10/23/2019 ng/L8.9<20 <2 <29.7 23 222<2 <2130EU11 2429 1/29/2018 1/29/2018 ng/L7.32 --------------------EU11 2744 7/26/2019 7/26/2019 ng/L<2.7 <20 <2 <2 <25.3<2 <2 <2 <256EU11 1220 12/14/2017 12/14/2017 ng/L46--------------------EU11 1494 1/24/2018 1/24/2018 ng/L12<20 <2 <2 <2 <5 <2 <2 <2 <245TR0795Page 25 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU11 1407 1/22/2018 1/22/2018 ng/L<4 <100 <50 <50 <50 <50 <50 <50 <50 <100 <50EU11 1478 1/26/2018 1/26/2018 ng/L64--------------------EU11 2759 7/31/2019 7/31/2019 ng/L80 67<1.1 <1.110 30 69 3.82<1.1360EU11 15492/6/2018 2/6/2018 ng/L63--------------------EU11 2442 1/29/2018 1/29/2018 ng/L4.38 --------------------EU11 2395 1/30/2018 1/30/2018 ng/L12<20 <2 <25.3<52.7<2 <2 <272EU11 2813 7/29/2019 7/29/2019 ng/L75 57<1.1 <1.181 77 100 2.6<1.1 <1.1290EU11 2475 3/26/2018 3/26/2018 ng/L13.9 --------------------EU11 14792/7/2018 2/7/2018 ng/L31--------------------EU11 8327 10/7/2019 10/7/2019 ng/L11<20 <2 <28.7 22 30<2 <2 <267EU11 14938/7/2019 8/7/2019 ng/L120 53<1.1 <1.114 11 16<1.1 <1.1 <1.1300EU11 14262/6/2018 2/6/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU11 21708/8/2019 8/8/2019 ng/L68 43<1.1 <1.17.2 12 13<1.1 <1.1 <1.1210EU11 2453 1/29/2018 1/29/2018 ng/L14.7 --------------------EU11 1427 2/13/2018 2/13/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU11 21742/8/2018 2/8/2018 ng/L27--------------------EU11 2176 2/12/2018 2/12/2018 ng/L5.2<20 <2 <2 <2 <52.8<2 <2 <2 <10EU11 21832/2/2018 2/2/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU11 2186 1/30/2018 1/30/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU11 21872/2/2018 2/2/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU11 2188 1/22/2018 1/22/2018 ng/L52--------------------EU11 1442 1/22/2018 1/22/2018 ng/L33--------------------EU11 14452/1/2018 2/1/2018 ng/L52--------------------EU11 24002/6/2018 2/6/2018 ng/L90--------------------EU11 29668/1/2019 8/1/2019 ng/L21 13<1.1 <1.13.1 6.3 9.6<1.1 <1.1 <1.165EU11 2207 1/30/2018 1/30/2018 ng/L71--------------------EU11 22092/1/2018 2/1/2018 ng/L83--------------------EU11 22152/2/2018 11/9/2018 ng/L110 --------------------EU11 22172/2/2018 2/2/2018 ng/L67--------------------EU11 1458 1/23/2018 1/23/2018 ng/L270 --------------------EU11 14592/2/2018 2/2/2018 ng/L20--------------------EU11 2219 2/16/2018 2/16/2018 ng/L72--------------------EU11 2476 3/26/2018 3/26/2018 ng/L38.4 --------------------EU11 2984 10/18/2019 10/18/2019 ng/L22 27<2 <28.81419<2 <2 <269EU11 7651 9/19/2019 9/19/2019 ng/L6.3<20 <2 <26.1 5.7<2 <2 <2 <2110EU11 1468 1/23/2018 1/23/2018 ng/L55--------------------EU11 2248 2/14/2018 2/14/2018 ng/L52--------------------EU11 2529 7/29/2019 7/29/2019 ng/L71 79<1.1 <1.127 54 98 11 2.4<1.1430EU11 14972/8/2018 2/8/2018 ng/L34--------------------EU11 3019 7/31/2019 7/31/2019 ng/L16 25<1.1 <1.110 15 16<1.1 <1.1 <1.161EU11 2455 1/29/2018 1/29/2018 ng/L11.6 --------------------EU11 2477 3/26/2018 3/26/2018 ng/L1.84 --------------------EU11 3107 10/18/2019 10/18/2019 ng/L44 37<2 <28.3 15 24<2 <2 <2110TR0795Page 26 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU11 3108 7/29/2019 7/29/2019 ng/L48 55<1.1 <1.121 44 66 5.5<1.1 <1.1330EU11 7699 9/20/2019 9/20/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU11 3108 7/29/2019 7/29/2019 ng/L54 49<1.1 <1.123 46 66 3.3<1.1 <1.1310EU11 2443 1/29/2018 1/29/2018 ng/L7.58 --------------------EU11 3180 8/12/2019 8/12/2019 ng/L3.8<11 <1.1 <1.14.4 5.2 2.4<1.1 <1.1 <1.1120EU11 1481 1/30/2018 1/30/2018 ng/L61<100 <50 <50 <50 <5075<50 <50 <100310EU11 2114 8/7/2018 7/24/2019 ng/L528 -- --<1.16140 685 646 92.8 25.7 -- --EU12 7846 10/3/2019 10/3/2019 ng/L4<20 <2 <22.1 15 3.7<2 <2 <2180EU12 2085 2/2/2018 2/2/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 7849 10/21/2019 10/21/2019 ng/L7.4<20 <2 <2 <26.1<2 <2 <2 <291EU12 1292 1/22/2018 1/22/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2086 1/23/2018 1/23/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 1295 5/2/2018 5/2/2018 ng/L5.7<100 <50 <50 <50 <50 <50 <50 <50 <100 <50EU12 7852 10/3/2019 10/3/2019 ng/L4.4<20 <2 <2 <2 <52.3<2 <2 <252EU12 7616 8/21/2019 8/21/2019 ng/L<0.589-- --<1.18 <1.18 <1.18 <1.18 <1.18 <1.18-- --EU12 8089 9/30/2019 9/30/2019 ng/L<2.9 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 8889 10/21/2019 10/21/2019 ng/L21<20 <2 <2 <27.9 2.1<2 <2 <2210EU12 2551 7/17/2019 7/17/2019 ng/L27 31<2 <22.4 17 11<2 <2 <2220EU12 2554 7/26/2019 7/26/2019 ng/L19 26<2 <2 <28 2.9<2 <2 <2190EU12 8565 10/21/2019 10/21/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 8673 10/21/2019 10/21/2019 ng/L16<20 <2 <22.7 13 12<2 <2 <2110EU12 8115 10/23/2019 10/23/2019 ng/L2.8<20 <2 <28.5 7.3 10<2 <2 <260EU12 3176 6/26/2019 6/26/2019 ng/L3.02 -- --<1.326.84 13.4 11.5<1.32<1.32----EU129357 10/23/2019 10/23/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <222EU12 8098 10/4/2019 10/4/2019 ng/L<2.6 <20 <2 <24.5 158<2 <2 <240EU12 8149 10/1/2019 10/1/2019 ng/L8.7<20 <2 <22.9 9.5 10<2 <2 <257EU12 8092 9/30/2019 9/30/2019 ng/L2.8<20 <2 <25.2 19 13<2 <2 <229EU12 7856 9/25/2019 9/25/2019 ng/L4.8<20 <2 <2 <2 <5 <2 <2 <2 <2110EU12 8097 9/30/2019 9/30/2019 ng/L<2.9 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 9112 10/18/2019 10/18/2019 ng/L8<20 <2 <23.8<52.2<2 <2 <254EU12 9113 10/18/2019 10/18/2019 ng/L6.9<20 <2 <28.3 12 9.8<2 <2 <253EU12 8854 10/18/2019 10/18/2019 ng/L27<20 <2 <24.5<54.3<2 <2 <242EU12 9353 10/18/2019 10/18/2019 ng/L<2.8 <20 <2 <22.3<52.8<2 <2 <216EU12 9120 10/23/2019 10/23/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2466 4/25/2018 4/25/2018 ng/L19.1 --------------------EU12 2577 9/18/2019 9/18/2019 ng/L8.5<20 <2 <2 <2 <57.3<2 <2 <262EU12 2578 9/16/2019 9/16/2019 ng/L16<20 <2 <2 <213 19<2 <2 <2120EU12 8857 10/23/2019 10/23/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2579 8/14/2019 8/14/2019 ng/L11<11 <1.1 <1.1 <1.17.1 7.5<1.1 <1.1 <1.183EU12 8858 10/23/2019 10/23/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <238EU12 8861 9/18/2019 9/18/2019 ng/L29.4 --<1.28 <1.283.13 21.6 19.3<1.28 <1.28 <1.28--EU12 2468 3/28/2018 4/11/2018 ng/L1.88 --------------------EU12 2585 9/16/2019 9/16/2019 ng/L12<20 <2 <2 <26.79<2 <2 <236TR0795Page 27 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU12 25869/9/2019 9/9/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2587 8/22/2019 8/22/2019 ng/L<2.6 <20 <2 <2 <2 <52.2<2 <2 <241EU12 2589 9/20/2019 9/20/2019 ng/L<2.7 <20 <2 <2 <2 <55.1<2 <2 <246EU12 2590 9/13/2019 9/13/2019 ng/L15<20 <2 <2 <2 <55.2<2 <2 <271EU12 8862 10/23/2019 10/23/2019 ng/L27<20 <2 <23.8 6.1 13<2 <2 <285EU12 2592 7/22/2019 7/22/2019 ng/L13<20 <2 <2 <2 <54.6<2 <2 <2150EU12 2593 9/16/2019 9/16/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2595 6/18/2019 6/18/2019 ng/L11<20 <2 <2 <2 <55.6<2 <2 <2140EU12 9122 10/23/2019 10/23/2019 ng/L25 20<2 <25.1 14 27 2.8<2 <2170EU12 2596 10/2/2019 10/2/2019 ng/L4.3<20 <2 <2 <2 <5 <2 <2 <2 <244EU12 25978/8/2019 8/8/2019 ng/L3.4<11 <1.1 <1.1 <1.13.4 5.5<1.1 <1.1 <1.136EU12 3167 6/13/2019 6/13/2019 ng/L26.3 ----<1.21.35 7.24 7.98<1.2 <1.2----EU12 2598 6/21/2019 6/21/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <214EU12 2599 8/14/2019 8/14/2019 ng/L<2.6 <11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.118EU12 2600 9/12/2019 9/12/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2601 9/20/2019 9/20/2019 ng/L3.9<20 <2 <25.1 9.2 12<2 <2 <278EU12 2467 3/28/2018 3/28/2018 ng/L0.844 --------------------EU12 3168 6/13/2019 6/13/2019 ng/L0.749 ----<1.17 <1.17 <1.17 <1.17 <1.17 <1.17----EU12 8122 9/30/2019 9/30/2019 ng/L3.3<20 <2 <22.9<53.4<2 <2 <234EU12 2419 3/14/2018 3/14/2018 ng/L0.773 --------------------EU12 2605 6/18/2019 6/18/2019 ng/L24<20 <2 <2 <2 <518<2 <2 <2230EU12 2606 9/12/2019 9/12/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <231EU12 2607 7/19/2019 7/19/2019 ng/L<2.6 <20 <2 <2 <2 <52.2<2<2<220EU12 2428 3/14/2018 3/14/2018 ng/L29.3 --------------------EU12 2608 6/18/2019 6/18/2019 ng/L15<20 <2 <26.7 27 22<2 <2 <2180EU12 2609 9/11/2019 9/11/2019 ng/L3<20 <2 <23.688.8<2 <2 <275EU12 2610 6/21/2019 6/21/2019 ng/L<4 <20 <2 <2 <2 <53.1<2 <2 <2110EU12 2611 6/18/2019 6/18/2019 ng/L25<20 <2 <2 <2 <517<2 <2 <2200EU12 2612 9/27/2019 9/27/2019 ng/L10<20 <2 <22.1 7.63<2 <2 <2210EU12 2614 7/29/2019 7/29/2019 ng/L<2.6 <11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.127EU12 2615 6/21/2019 6/21/2019 ng/L<4 <20 <2 <2 <2 <53.6<2 <2 <265EU12 2617 7/18/2019 7/18/2019 ng/L<2.9 <20 <2 <2 <2 <5 <2 <2 <2 <222EU12 2620 7/25/2019 7/25/2019 ng/L<2.6 <11 <1.1 <1.12.252.8<1.1 <1.1 <1.118EU12 2624 8/29/2019 8/29/2019 ng/L64 38<2 <28.3 46 99 9.1 2.5<2180EU12 2625 7/25/2019 7/25/2019 ng/L31 27<2 <29.6 35 47 4.1<2 <2150EU12 2417 2/13/2018 2/13/2018 ng/L10.1 --------------------EU12 2628 7/25/2019 7/25/2019 ng/L8.9<20 <2 <23.7 19 14<2 <2 <299EU12 2632 7/24/2019 7/24/2019 ng/L5.1<20 <2 <25.4 13 11<2 <2 <254EU12 8424 10/21/2019 10/21/2019 ng/L38<20 <2 <2 <2 <5 <2 <2 <2 <216EU12 2634 8/19/2019 8/19/2019 ng/L14<20 <2 <26.5 22 27<2 <2 <2130EU12 7861 9/26/2019 9/26/2019 ng/L<2.8 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 8427 10/21/2019 10/21/2019 ng/L5.8<20 <2 <2 <211 9.7<2 <2 <2120EU12 8116 9/30/2019 9/30/2019 ng/L<2.6 <20 <2 <2 <2 <52.1<2 <2 <2 <10TR0795Page 28 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU12 3277 9/25/2019 9/25/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 7865 10/3/2019 10/3/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <274EU12 7867 9/26/2019 9/26/2019 ng/L<2.7 <20 <2 <2 <28.6<2 <2 <2 <2210EU12 7869 9/26/2019 9/26/2019 ng/L<2.9 <20 <2 <2 <26.1 2.3<2 <2 <2130EU12 3278 8/14/2019 8/14/2019 ng/L<2.7 <20 <2 <2 <26.3 2.3<2 <2 <2110EU12 9081 10/18/2019 10/18/2019 ng/L9.4<20 <2 <22.9 40 51 2.2<2 <2160EU12 3175 6/26/2019 6/26/2019 ng/L14.8 -- --<1.24 <1.246.22 6.61<1.24 <1.24-- --EU12 2641 9/17/2019 9/17/2019 ng/L40 33<2 <27.4 32 41 2.4<2 <2240EU12 8288 10/8/2019 10/8/2019 ng/L4<20 <2 <27.5 25 16<2 <2 <2140EU12 8754 10/18/2019 10/18/2019 ng/L3.4<20 <2 <2 <2 <5 <2 <2 <2 <230EU12 7506 8/15/2019 8/15/2019 ng/L<2.6 <11 <1.1 <1.1 <1.1 <2.61.5<1.1 <1.1 <1.118EU12 9181 10/21/2019 10/21/2019 ng/L14<20 <2 <2 <218 15<2 <2 <2160EU12 8806 10/18/2019 10/18/2019 ng/L19<20 <2 <2 <214 9.7<2 <2 <2110EU12 8696 10/23/2019 10/23/2019 ng/L15 30<2 <22.3 33 35<2 <2 <2250EU12 8700 10/23/2019 10/23/2019 ng/L14 22<2 <25.8 31 63 8.7<2 <2220EU12 8920 10/23/2019 10/23/2019 ng/L<2.8 <20 <2 <2 <29.9 2.9<2 <2 <2130EU12 7871 9/25/2019 9/25/2019 ng/L22<20 <2 <22.2 13 51 5.3 2.3<2100EU12 3166 6/13/2019 6/13/2019 ng/L1.16 -- --<1.15 <1.152.61 1.46<1.15 <1.15-- --EU12 9185 10/23/2019 10/23/2019 ng/L16 40<2 <2 <232 38<2 <2 <2260EU12 7497 8/15/2019 8/15/2019 ng/L<2.6 <11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.17.9EU1275788/26/2019 8/26/2019 ng/L10<20 <2 <2 <27.2 5.4<2 <2 <2110EU12 3279 8/14/2019 8/14/2019 ng/L33 24<1.1 <1.11.3 25 79 4.6 2.3<1.1180EU12 7872 10/17/2019 10/17/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 734 10/19/2017 10/22/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 8207 10/2/2019 10/2/2019 ng/L<2.8 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 7873 10/2/2019 10/2/2019 ng/L<2.7 <20 <2 <2 <26.1<2 <2 <2 <276EU12 8867 10/21/2019 10/21/2019 ng/L9.6<20 <2 <24.2 18 313<2 <272EU12 8867 10/21/2019 10/21/2019 ng/L8.8<20 <2 <2418 30 2.2<2 <271EU12 7577 8/26/2019 8/26/2019 ng/L9.6<20 <2 <22.2 25 45 4.2<2 <2100EU12 7874 9/25/2019 9/25/2019 ng/L<2.8 <20 <2 <2 <2 <5 <2 <2 <2 <251EU12 2657 6/19/2019 6/19/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 8118 9/30/2019 9/30/2019 ng/L15<20 <2 <27.2 16 27 2.6<2 <287EU12 8297 10/8/2019 10/8/2019 ng/L18 30<2 <22.7 55 130 15 2.1<2200EU12 8624 10/17/2019 10/17/2019 ng/L<2.6 <20 <2 <2 <26.9 2.8<2 <2 <251EU12 8868 10/21/2019 10/21/2019 ng/L2.8<20 <2 <213 19 36 4.2<2 <259EU12 8625 10/17/2019 10/17/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <215EU12 8627 10/17/2019 10/17/2019 ng/L8.1<20 <2 <22.9 18 19<2 <2 <2110EU12 8628 10/17/2019 10/17/2019 ng/L12<20 <2 <231515<2 <2 <2120EU12 8630 10/17/2019 10/17/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <242EU12 7500 8/15/2019 8/15/2019 ng/L<2.8 <11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.1 <5.3EU12 3280 8/14/2019 8/14/2019 ng/L3.2<11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.175EU12 7580 8/26/2019 8/26/2019 ng/L3<20 <2 <2 <29.2 8.2<2 <2 <278EU12 8632 10/17/2019 10/17/2019 ng/L5.6<20<2<2 <26.2 3.6<2 <2 <293TR0795Page 29 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU12 8633 10/17/2019 10/17/2019 ng/L31 35<2 <24.2 16 9.4<2 <2 <2180EU12 9125 10/21/2019 10/21/2019 ng/L6<20 <2 <2 <2 <513<2 <2 <234EU12 3155 5/8/2019 5/8/2019 ng/L<0.599-- --<1.2 <1.2 <1.2 <1.2 <1.2 <1.2-- --EU12 3179 7/10/2019 7/10/2019 ng/L6.81 -- --<1.18 <1.1825.9 25.8<1.18 <1.18-- --EU12 8377 9/11/2019 9/11/2019 ng/L3.49 -- --<1.2 <1.214.6 15.4 2.2<1.2-- --EU12 8381 9/11/2019 9/11/2019 ng/L8.03 -- --<1.563.1 42.3 42 2.86<1.56-- --EU12 3178 7/10/2019 7/10/2019 ng/L15 -- --<1.181.58 35.8 32.6<1.18 <1.18-- --EU12 7878 9/25/2019 9/25/2019 ng/L<2.8 <20 <2 <2 <2 <5 <2 <2 <2 <211EU12 8205 10/2/2019 10/2/2019 ng/L16<20 <2 <22.1 15 30<2 <2 <291EU12 2684 7/2/2019 7/2/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2499 3/13/2019 3/13/2019 ng/L<0.615-- --<1.23 <1.23 <1.23 <1.23 <1.23 <1.23-- --EU12 2687 9/13/2019 9/13/2019 ng/L7.7<20 <2 <24.1 19 29<2 <2 <2140EU12 7567 8/7/2019 8/7/2019 ng/L<0.603-- --<1.21 <1.21 <1.21 <1.21 <1.21 <1.21-- --EU12 193 10/17/2019 10/17/2019 ng/L1.15 --<1.18 <1.18 <1.182.54 1.27<1.18 <1.18 <1.18--EU12 9222 9/18/2019 9/18/2019 ng/L<0.602--<1.2 <1.2 <1.2 <1.2 <1.2 <1.2 <1.2 <1.2--EU12 2697 5/8/2019 6/19/2019 ng/L19 29<2 <1.26 <1.2610 2<1.26 <1.26 <2190EU12 2509 4/24/2019 4/24/2019 ng/L10.1 -- --<1.315.06 25.5 19.9 3.17 1.76 -- --EU12 2698 8/1/2019 8/1/2019 ng/L<2.6 <11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.1 <5.3EU12 9223 9/18/2019 9/18/2019 ng/L<0.575--<1.15 <1.15 <1.15 <1.15 <1.15 <1.15 <1.15 <1.15--EU12 2714 9/9/2019 9/9/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2717 8/9/2019 8/9/2019 ng/L<2.6 <11 <1.1 <1.1 <1.1 <2.6 <1.1 <1.1 <1.1 <1.1 <5.3EU12 2720 8/28/2019 8/28/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU1227329/12/2019 9/12/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 8917 10/22/2019 10/22/2019 ng/L<2.9 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 3160 5/29/2019 5/29/2019 ng/L<0.61----<1.22 <1.22 <1.22 <1.22 <1.22 <1.22----EU12 7931 10/2/2019 10/2/2019 ng/L<2.9 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 7951 10/4/2019 10/4/2019 ng/L<2.8 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 7956 9/27/2019 9/27/2019 ng/L<2.8 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2881 7/11/2019 7/11/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2900 8/19/2019 8/19/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 8768 10/17/2019 10/17/2019 ng/L<0.674--<1.35 <1.35 <1.35 <1.35 <1.35 <1.35 <1.35 <1.35--EU12 9140 10/23/2019 10/23/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2913 9/30/2019 9/30/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2915 7/11/2019 7/11/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 3300 8/28/2019 8/28/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 8171 10/1/2019 10/1/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2972 7/18/2019 7/24/2019 ng/L<2.5 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 1274 4/24/2018 4/24/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 7970 10/2/2019 10/2/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2996 7/18/2019 7/18/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2997 9/26/2019 9/26/2019 ng/L<2.8 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2998 7/18/2019 7/18/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2999 7/18/2019 7/18/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10TR0795Page 30 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU12 3000 10/7/2019 10/7/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 8111 9/30/2019 9/30/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2256 1/23/2018 1/23/2018 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 22592/5/2018 6/13/2019 ng/L<0.575 <20 <2 <1.15 <1.15 <1.15 <1.15 <1.15 <1.15 <2 <10EU12 7566 8/22/2019 8/22/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 8157 10/1/2019 10/1/2019 ng/L<2.8 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 3120 9/17/2019 9/17/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 3121 6/21/2019 6/21/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 31369/9/2019 9/9/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 3142 7/11/2019 7/11/2019 ng/L<2.8 <20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 2225 8/16/2019 8/16/2019 ng/L270 130<1.1 <1.112 110 190 5.7<1.1 <1.1580EU12 7959 9/30/2019 9/30/2019 ng/L41 55<2 <23.9 28 57 3.3<2 <2570EU12 3149 6/26/2019 8/7/2019 ng/L187 36<2 <1.22 <1.22146 150 7.9 1.57<2220EU12 2832 7/24/2019 7/24/2019 ng/L120 41<2 <27.8 50 290 70 6.7<2140EU12 2755 6/24/2019 6/24/2019 ng/L120 69<2 <22.5 38 81 2.3<2 <5370EU12 2758 6/19/2019 6/19/2019 ng/L120 70<2 <22.8 39 93 8.8<2 <2340EU12 2957 7/19/2019 7/19/2019 ng/L250 63<2 <2 <235 110 20 4.8<2170EU12 2960 7/24/2019 7/24/2019 ng/L220 62<2 <2 <235 120 19 4.2<2190EU12 2951 7/24/2019 7/24/2019 ng/L210 66<2 <2 <234 110 22 5.5<2200EU12 2968 7/19/2019 7/19/2019 ng/L160 51<2 <22.9 39 110 13 2.8<2240EU12 2947 7/15/2019 7/15/2019 ng/L93 53<2 <2436483<2 <2280EU12 7922 10/4/2019 10/4/2019 ng/L65 52<2 <28.6 46 86 4.6<2 <2250EU12 3282 10/9/2019 10/9/2019 ng/L24 35<2 <27.3 33 654<2 <2330EU12 2840 9/13/2019 9/13/2019 ng/L79 55<2 <23.5 23 13<2<2<2320EU12 2976 7/31/2019 7/31/2019 ng/L23 41<1.1 <1.1 <1.137 19<1.1 <1.1 <1.1350EU12 7969 9/25/2019 9/25/2019 ng/L73 49<2 <24.4 25 44 4.2<2 <2270EU12 2240 8/14/2019 8/14/2019 ng/L48 51<2 <27.7 37 38<2 <2 <2280EU12 2969 7/15/2019 7/15/2019 ng/L81 44<2 <242215<2 <2 <2290EU12 3023 7/25/2019 7/25/2019 ng/L22 29<2 <28.7 63 49 2.1<2 <2280EU12 2864 7/15/2019 7/15/2019 ng/L44 39<2 <24.1 43 52<2 <2 <2230EU12 3284 8/14/2019 8/14/2019 ng/L38 30<1.1 <1.14.3 27 47 2.2<1.1 <1.1260EU12 2964 7/19/2019 7/19/2019 ng/L85 38<2 <24.2 30 70 5.3<2 <2170EU12 2112 7/30/2019 7/30/2019 ng/L45 33<1.1 <1.18.8 37 61 1.5<1.1 <1.1180EU12 2772 9/11/2019 9/11/2019 ng/L12 31<2 <22.2 33 68 5.2<2 <2170EU12 2973 7/18/2019 7/18/2019 ng/L18<20 <2 <2 <242 22<2 <2 <2220EU12 8213 10/2/2019 10/2/2019 ng/L11<20 <2 <23.2 42 21<2 <2 <2210EU12 1239 1/23/2018 1/23/2018 ng/L18<20 <2 <210 17 14<2 <2 <2190EU12 2950 7/29/2019 7/29/2019 ng/L20 25<1.1 <1.11.5 21 8.9<1.1 <1.1 <1.1170EU12 8147 10/1/2019 10/1/2019 ng/L33 22<2 <25.5 24 59 5.9<2 <296EU12 8655 10/18/2019 10/18/2019 ng/L35<20 <2 <221715<2 <2 <2170EU12 3301 8/14/2019 8/14/2019 ng/L20 24<1.1 <1.11.1158.2<1.1 <1.1 <1.1170EU12 9017 10/17/2019 10/17/2019 ng/L25<20 <2 <23.2 16 44 6.6 2.3<2140EU12 2959 7/19/2019 7/19/2019 ng/L62<20 <2 <23.3 19 34 2.6<2 <2100TR0795Page 31 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU12 2704 7/22/2019 7/22/2019 ng/L28 23<2 <2 <26.1 2.2<2 <2 <2160EU12 517 8/21/2019 8/21/2019 ng/L17<20 <2 <2 <28 3.3<2 <2 <2190EU12 2828 8/19/2019 8/19/2019 ng/L7.9<20 <2 <29.8 27 89 12 3.6<268EU12 7943 9/25/2019 9/25/2019 ng/L3<20 <2 <22.2 26 14<2 <2 <2170EU12 7911 10/10/2019 10/10/2019 ng/L9.5<20 <2 <23139<2 <2 <2180EU12 3289 8/14/2019 8/14/2019 ng/L4.9<11 <1.1 <1.12.4 32 40 1.3<1.1 <1.1130EU12 2838 9/26/2019 9/26/2019 ng/L10<20 <2 <2 <27.7<2 <2 <2 <2190EU12 2730 7/11/2019 7/11/2019 ng/L19<20 <2 <292832<2 <25 110EU12 7902 10/7/2019 10/7/2019 ng/L12<20 <2 <22.1 19 12<2 <2 <2150EU12 2729 6/24/2019 6/24/2019 ng/L16<20 <2 <2 <2 <519<2 <2 <5160EU12 9130 10/23/2019 10/23/2019 ng/L40<20 <2 <24.8 7.1 13<2 <2 <2130EU12 3147 7/15/2019 7/15/2019 ng/L33<20 <2 <2 <28.6 55 2.2<2 <296EU12 8780 10/17/2019 10/17/2019 ng/L24<20 <2 <241531<2 <2 <2120EU12 7562 8/22/2019 8/22/2019 ng/L7<20 <2 <212 29 32<22<2110EU12 7888 10/10/2019 10/10/2019 ng/L17<20 <2 <26.5 8.9 24 2.2<2 <2130EU12 2850 7/24/2019 7/24/2019 ng/L16 24<2 <27.1 9.9 11<2 <2 <2120EU12 2870 7/31/2019 7/31/2019 ng/L12 19<1.1 <1.11.1 11 13 1.5<1.1<1.1130EU121297 7/11/2018 9/26/2019 ng/L23<20 <2 <2 <29.7<2 <2 <2 <2150EU12 7556 8/19/2019 8/19/2019 ng/L<2.7 <11 <1.1 <1.132411<1.1 <1.1 <1.1140EU12 2967 7/19/2019 7/19/2019 ng/L18<20 <2 <2 <215 13<2 <2 <2130EU12 7953 9/25/2019 9/25/2019 ng/L15<20 <2 <2 <27.9 29<2 <2 <2120EU12 7924 10/17/2019 10/17/2019 ng/L54.9 --<1.29 <1.299.23 50.3 52.6 3.78<1.29 <1.29--EU12 8693 10/22/2019 10/22/2019 ng/L9.4<20 <2 <2 <214 7.4<2 <2 <2140EU12 9215 10/21/2019 10/21/2019 ng/L6.7<20 <2 <2 <216 7.8<2 <2 <2140EU12 3144 7/11/2019 7/11/2019 ng/L5<202.3<22.9 8.4 14<2 <27.7 130EU12 7954 10/2/2019 10/2/2019 ng/L5.9<20 <2 <2 <27.1 23<2 <2 <2130EU12 3288 8/14/2019 8/14/2019 ng/L2.8<11 <1.1 <1.12.1 15 3.7<1.1 <1.1 <1.1140EU12 7919 9/25/2019 9/25/2019 ng/L7.4<20 <2 <24.5 18 13<2 <2 <2120EU12 1276 1/30/2018 1/30/2018 ng/L12<100 <50 <50 <50 <50 <50 <50 <50 <100150EU12 2837 7/29/2019 7/29/2019 ng/L12 15<1.1 <1.17.1 9.2 8.4<1.1 <1.1 <1.1110EU12 3129 10/4/2019 10/4/2019 ng/L20<20 <2 <23.6 5.7 12<2 <2 <2120EU12 7957 9/25/2019 9/25/2019 ng/L6.8<20 <2 <2 <28.1 5.3<2 <2 <2140EU12 8173 10/1/2019 10/1/2019 ng/L27<20 <2 <22.2 12 42 7.8 2.5<266EU12 2835 6/19/2019 6/19/2019 ng/L9.2<20 <2 <2 <2 <5 <2 <2 <2 <2150EU1212381/24/2018 1/24/2018 ng/L9.9<20 <2 <23.3 11 4.9<2 <2 <2130EU12 7947 10/3/2019 10/3/2019 ng/L8.6<20 <2 <2 <211 7.4<2 <2 <2130EU12 8123 10/21/2019 10/21/2019 ng/L14<20 <2 <23.3 13 50 9.8 5.5<258EU12 2914 7/22/2019 7/22/2019 ng/L15<20 <2 <2 <210 29<2 <2 <299EU12 3285 8/19/2019 8/19/2019 ng/L4<11 <1.1 <1.1 <1.17.1 7.6<1.1 <1.1 <1.1130EU12 9066 10/21/2019 10/21/2019 ng/L7.8<20 <2 <22.5 18<2 <2 <2 <2120EU12 7566 8/22/2019 8/22/2019 ng/L<2.7 <20 <2 <25.5 20 12<2 <2 <2110EU12 7504 8/22/2019 8/22/2019 ng/L<2.8 <20 <2 <2 <2205<2 <2 <2120EU12 3143 9/11/2019 9/11/2019 ng/L5.9<20 <2 <23.3 12 23 3.7<2 <295TR0795Page 32 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU12 2847 6/19/2019 6/19/2019 ng/L12<20 <2 <2 <2 <5 <2 <2 <2 <2130EU12 8592 10/21/2019 10/21/2019 ng/L7.5<20 <2 <22.3 9.8<2 <2 <2 <2120EU12 2814 9/13/2019 9/13/2019 ng/L20<20 <2 <24.9 12 21 2<2 <276EU12 2980 9/17/2019 9/17/2019 ng/L11<20 <2 <25.6 11 13<2 <2 <294EU12 8774 10/17/2019 10/17/2019 ng/L9.7<20 <2 <2 <25.4 3<2 <2 <2110EU12 7921 9/27/2019 9/27/2019 ng/L<2.9 <20 <2 <2 <27.4<2 <2 <2 <2120EU12 8656 10/18/2019 10/18/2019 ng/L16<20 <2 <22.4 13 8.8<2 <2 <287EU12 7895 10/3/2019 10/3/2019 ng/L<2.6 <20 <2 <22.8 15 4.4<2 <2 <299EU12 7898 10/2/2019 10/2/2019 ng/L2.8<20 <2 <2 <26.3<2 <2 <2 <2110EU12 1272 1/23/2018 1/23/2018 ng/L7.1 23<2 <28.4 10 13<2 <2 <254EU12 2754 6/19/2019 6/19/2019 ng/L8.8<20 <2 <2 <2 <56.8<2 <2 <299EU12 2164 1/23/2018 1/23/2018 ng/L12 21<2 <2 <25.6 2.8<2 <2 <273EU12 2956 8/8/2019 8/8/2019 ng/L11<11 <1.1 <1.13.6 15 13<1.1 <1.1 <1.171EU12 2834 8/29/2019 8/29/2019 ng/L2.8<20 <2 <2 <2 <5 <2 <2 <2 <2110EU12 2110 1/25/2018 1/25/2018 ng/L13<20 <2 <22.3 8.7<2 <2 <2 <287EU12 8783 10/22/2019 10/22/2019 ng/L5.6<20 <2 <22.4 11 3.5<2 <2 <288EU12 2156 2/14/2018 11/21/2018 ng/L110 -- -- -- -- -- -- -- -- -- --EU12 2262 1/22/2018 1/22/2018 ng/L9.7<20 <2 <2 <2 <5 <2 <2 <2 <2100EU12 8722 10/23/2019 10/23/2019 ng/L2.8<20 <2 <2 <26.5<2 <2 <2 <2100EU12865410/18/2019 10/18/2019 ng/L11<20 <2 <25.1 10 5.7<2 <2 <277EU12 8781 10/23/2019 10/23/2019 ng/L6.1<20 <2 <22.9 7.65<2 <2 <287EU12 9022 10/23/2019 10/23/2019 ng/L6.1<20 <2 <2 <25.3<2 <2 <2 <297EU12 7896 10/2/2019 10/2/2019 ng/L2.7<20 <2 <22.3 15 4.4<2 <2 <283EU12 7894 10/3/2019 10/3/2019 ng/L2.7<20 <2 <2 <25.9<2 <2 <2 <298EU12 7923 10/3/2019 10/3/2019 ng/L13<20 <2 <2 <2 <5 <2 <2 <2 <293EU12 7933 9/25/2019 9/25/2019 ng/L<2.7 <20 <2 <2 <212<2 <2 <2 <294EU12 8658 10/18/2019 10/18/2019 ng/L8.3<20 <2 <22.6 11 11<2 <2 <270EU12 8375 9/11/2019 9/11/2019 ng/L12.9 ----<1.184.4 44.1 40 1.45<1.18----EU12 7938 10/3/2019 10/3/2019 ng/L8.5<20 <2 <2 <2 <5 <2 <2 <2 <293EU12 31407/3/2019 7/3/2019 ng/L<4 <20 <2 <2 <2 <55.4<2 <2 <296EU12 8187 10/4/2019 10/4/2019 ng/L15<20 <2 <22.1 7.6 13 2.1<2 <258EU12 8660 10/18/2019 10/18/2019 ng/L3.7<20 <2 <2 <213 4.1<2 <2 <275EU12 9067 10/21/2019 10/21/2019 ng/L<2.6 <20 <2 <24.2 18<2 <2 <2 <271EU12 31347/3/2019 7/10/2019 ng/L24<20 <2 <2 <2 <514<2 <2 <255EU12 7934 9/26/2019 9/26/2019 ng/L<2.7 <20 <2 <2 <25.2 2.3<2 <2 <285EU12 2974 7/19/2019 7/19/2019 ng/L10<20 <2 <2 <28.2 7.8<2 <2 <265EU12 8665 10/18/2019 10/18/2019 ng/L6<20 <2 <22.5 12 12<2 <2 <258EU12 22552/1/2018 2/1/2018 ng/L89--------------------EU12821 10/21/2019 10/21/2019 ng/L<2.7 <20 <2 <23.6 18<2 <2 <2 <267EU12 8661 10/18/2019 10/18/2019 ng/L10<20 <2 <221115<2 <2 <250EU12 8380 9/11/2019 9/11/2019 ng/L21.7 ----<1.21 <1.2133.4 28.9 2.49<1.21----EU12 2113 1/24/2018 1/24/2018 ng/L5.9<100 <50 <50 <50 <50 <50 <50 <50 <10078EU12 8899 10/22/2019 10/22/2019 ng/L3.3<20 <2 <2 <2 <5 <2 <2 <2 <280TR0795Page 33 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU12 8782 10/22/2019 10/22/2019 ng/L5.5<20 <2 <2 <2 <52.4<2 <2 <275EU12 2249 1/22/2018 1/22/2018 ng/L80 -- -- -- -- -- -- -- -- -- --EU12 7936 9/26/2019 9/26/2019 ng/L<2.7 <20 <2 <2 <2 <52.8<2 <2 <274EU12 8785 10/22/2019 10/22/2019 ng/L3.2<20 <2 <22.8 7.6 3.8<2 <2 <259EU12 2700 7/22/2019 7/22/2019 ng/L6.7<20 <2 <23.6 12 17<2 <2 <237EU12 8379 9/11/2019 9/11/2019 ng/L13.4 -- --<1.274.07 28.6 28.4 1.53<1.27-- --EU12 8382 9/11/2019 9/11/2019 ng/L18.9 -- --<1.343.84 27.8 24.9<1.34 <1.34-- --EU12 8177 10/1/2019 10/1/2019 ng/L6.2<20 <2 <22.2 8.4 6.3<2 <2 <252EU12 8210 10/2/2019 10/2/2019 ng/L3.8<20 <2 <2 <26.7 10<2 <2 <253EU12 8779 10/18/2019 10/18/2019 ng/L5.2<20 <2 <23.4 9.7 17<2 <2 <234EU12 8933 10/17/2019 10/17/2019 ng/L5.1<20 <2 <2 <25 8.7<2 <2 <250EU12 7917 9/25/2019 9/25/2019 ng/L3.1<20 <2 <22.1 8.4 3.1<2 <2 <252EU12 8106 9/30/2019 9/30/2019 ng/L<2.6 <20 <2 <2 <215<2 <2 <2 <253EU12 3152 5/15/2019 5/15/2019 ng/L27.8 -- --<1.212.57 19.6 13.8 1.39<1.21-- --EU12 8663 10/18/2019 10/18/2019 ng/L<2.7 <20 <2 <2 <28.5 6.1<2 <2 <248EU12 7568 8/7/2019 8/7/2019 ng/L10.6 -- --<1.2 <1.223.6 23.4 3.87<1.2-- --EU12 2250 2/1/2018 2/1/2018 ng/L61 -- -- -- -- -- -- -- -- -- --EU12 3151 7/18/2019 7/18/2019 ng/L17<20 <2 <2 <2 <516<2 <2 <228EU12 3138 9/23/2019 9/23/2019 ng/L7.9<20 <2 <2 <2 <56.3<2 <2 <246EU1224213/14/2018 3/14/2018 ng/L60.2 --------------------EU12 8167 10/1/2019 10/1/2019 ng/L6.2<20 <2 <2 <269.7<2 <2 <237EU12 8662 10/18/2019 10/18/2019 ng/L5<20 <2 <2 <26.1<2 <2 <2 <247EU12 9815 10/17/2019 10/17/2019 ng/L8--<1.22 <1.222.52 23.2 23.8<1.22 <1.22 <1.22--EU12 8148 10/1/2019 10/1/2019 ng/L5.8<20 <2 <22.8 7.1 12<2 <2 <229EU12 75698/7/2019 8/7/2019 ng/L8.5 ----<1.17 <1.1723.5 20.4 2.54<1.17----EU12 8667 10/18/2019 10/18/2019 ng/L3.8<20 <2 <2 <26.3 6.1<2 <2 <238EU12 8789 10/23/2019 10/23/2019 ng/L<2.7 <20 <2 <2 <2 <54.1<2 <2 <248EU12 2254 1/23/2018 1/23/2018 ng/L51--------------------EU12 75708/7/2019 8/7/2019 ng/L5.21 ----<1.188.84 18.7 17.6<1.18 <1.18----EU12 2379 1/24/2018 1/24/2018 ng/L47--------------------EU12 3162 5/29/2019 5/29/2019 ng/L10.9 ----<1.181.19 16.6 14<1.18 <1.18----EU12 2723 9/12/2019 9/12/2019 ng/L5.4<20 <2 <2 <2 <55.2<2 <2 <232EU12 8522 10/17/2019 10/17/2019 ng/L2.6<20 <2 <23.7<52.9<2 <2 <233EU12 8188 10/1/2019 10/1/2019 ng/L3<20 <2 <2 <2 <52.5<2 <2 <236EU12 2508 7/10/2019 7/10/2019 ng/L14----<1.181.22 14.2 11.9<1.18 <1.18----EU12 7899 10/2/2019 10/2/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <239EU12 2212 1/30/2018 1/30/2018 ng/L38--------------------EU12 2423 3/14/2018 3/14/2018 ng/L36.4 --------------------EU12 31257/3/2019 7/3/2019 ng/L5.1<20 <2 <2 <2 <54.6<2 <2 <226EU12 7955 10/10/2019 10/10/2019 ng/L<4 <20 <2 <2 <2 <53.3<2<2<232EU12 3287 8/19/2019 8/19/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <232EU12 8376 9/11/2019 9/11/2019 ng/L10.2 ----<1.2 <1.210.6 10.8<1.2 <1.2-- --EU12 2424 3/14/2018 3/14/2018 ng/L31.6 -- -- -- -- -- -- -- -- -- --TR0795Page 34 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU12 8804 10/21/2019 10/21/2019 ng/L<2.6 <20 <2 <2 <26.1 2.3<2 <2 <223EU12 7615 8/21/2019 8/21/2019 ng/L2.02 -- --<1.141.16 14.4 11.8 1.99<1.14-- --EU12 3139 7/22/2019 7/22/2019 ng/L4.1<20 <2 <2 <2 <59.6<2 <2 <217EU12 8787 10/22/2019 10/22/2019 ng/L<2.7 <20 <2 <2 <2 <52.1<2 <2 <228EU12 2920 8/22/2019 8/22/2019 ng/L2.9<20 <2 <2 <2 <55.1<2 <2 <222EU12 2258 1/25/2018 1/25/2018 ng/L30 -- -- -- -- -- -- -- -- -- --EU12 8208 10/2/2019 10/2/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <228EU12 2237 1/22/2018 1/22/2018 ng/L27 -- -- -- -- -- -- -- -- -- --EU12 2908 7/15/2019 7/15/2019 ng/L<2.6 <20 <2 <2 <2 <58.7<2 <2 <218EU12 2422 3/14/2018 3/14/2018 ng/L26.3 -- -- -- -- -- -- -- -- -- --EU12 790 10/22/2019 10/22/2019 ng/L<2.7 <20 <2 <2 <2 <52.2<2 <2 <224EU12 2836 5/8/2019 5/8/2019 ng/L23.8 -- --<1.31.33<1.3 <1.3 <1.3 <1.3-- --EU12 8791 10/22/2019 10/22/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <225EU12 3150 10/2/2019 10/2/2019 ng/L<2.7 <20 <2 <2 <2 <58.6<2 <2 <216EU12 8378 9/11/2019 9/11/2019 ng/L4.17 -- --<1.293.89 8.61 7.79<1.29 <1.29-- --EU12 2422 3/14/2018 3/14/2018 ng/L24.4 -- -- -- -- -- -- -- -- -- --EU12 3154 5/8/2019 5/8/2019 ng/L13.5 -- --<1.281.29 5.48 3.79<1.28 <1.28-- --EU12 8549 10/18/2019 10/18/2019 ng/L<3.1 <20 <2 <2 <2 <5 <2 <2 <2 <224EU12 8144 10/1/2019 10/1/2019 ng/L<2.7 <20 <2 <2 <2 <5 <2 <2 <2 <223EU12 2880 6/21/2019 6/24/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <222EU12 2221 1/25/2018 1/25/2018 ng/L22 -- -- -- -- -- -- -- -- -- --EU12 2246 1/23/2018 1/23/2018 ng/L22 -- -- -- -- -- -- -- -- -- --EU12 1241 1/23/2018 1/23/2018 ng/L22 -- -- -- -- -- -- -- -- -- --EU12 3161 5/29/2019 5/29/2019 ng/L3.36 -- --<1.223.54 7.76 7.24<1.22 <1.22-- --EU12 2251 1/24/2018 1/24/2018 ng/L21 -- -- -- -- -- -- -- -- -- --EU12 2251 1/24/2018 1/24/2018 ng/L21 -- -- -- -- -- -- -- -- -- --EU12 2719 6/18/2019 6/18/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <219EU12848510/17/2019 10/17/2019 ng/L<2.8 <20 <2 <2 <2 <53.8<2 <2 <215EU12 2916 9/27/2019 9/27/2019 ng/L<2.7 <20 <2 <2 <2 <55.4<2 <2 <213EU12 8879 10/23/2019 10/23/2019 ng/L<2.6 <20 <2 <2 <2 <5 <2 <2 <2 <217EU12 2899 6/21/2019 6/21/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <216EU12 75718/7/2019 8/7/2019 ng/L7.47 ----<1.19 <1.194.37 3.4<1.19 <1.19----EU12 2702 6/24/2019 6/24/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <514EU12 3135 7/11/2019 7/11/2019 ng/L<2.7 <20 <2 <2 <2 <52.9<2 <2 <211EU12 2420 3/14/2018 3/14/2018 ng/L12.7 -- -- -- -- -- -- -- -- -- --EU12 3169 6/13/2019 6/13/2019 ng/L10.3 -- --<1.18 <1.181.84<1.18 <1.18 <1.18-- --EU12 2111 1/23/2018 1/23/2018 ng/L12 -- -- -- -- -- -- -- -- -- --EU12 8790 10/22/2019 10/22/2019 ng/L<2.8 <20 <2 <2 <2 <5 <2 <2 <2 <212EU12 2898 6/21/2019 6/21/2019 ng/L<4 <20 <2 <2 <2 <5 <2 <2 <2 <212EU12 2710 7/11/2019 7/11/2019 ng/L<2.7 <202.1<2 <2 <5 <2 <2 <29.7<10EU12 3177 7/10/2019 7/10/2019 ng/L3.57 -- --<1.19 <1.194.53 3.16<1.19 <1.19-- --EU12 2918 7/11/2019 7/24/2019 ng/L<0.598 <202.2<1.2 <1.2 <1.2 <1.2 <1.2 <1.28.4<10TR0795Page 35 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-2Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAUntreated Drinking WaterExposure Unit [1]Residence IDUnits HFPO-DA PEPA PFECA-G PFESA-BP1 PFESA-BP2 PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPARange ofSampling Dates [2]EU12 3148 10/21/2019 10/21/2019 ng/L9.9<20 <2 <2 <2 <5 <2 <2 <2 <2 <10EU12 8090 9/30/2019 9/30/2019 ng/L<2.7 <20 <2 <2 <2 <55.1<2 <2 <2 <10EU12 2909 7/24/2019 7/24/2019 ng/L<2.7 <20 <2 <2 <2 <54<2 <2 <2 <10EU12 3137 7/11/2019 7/11/2019 ng/L<2.7 <20 <2 <2 <2 <52.9<2 <2 <2 <10EU12 7614 8/21/2019 8/21/2019 ng/L0.825 ----<1.19 <1.19 <1.19 <1.19 <1.19 <1.19----Definitions:[1] Exposure Units (EUs) are defined as follows:EU5 - 5 kilometer radius, northeast EU9 - 10 kilometer radius, northeastEU6 - 5 kilometer radius, southeastEU10 - 10 kilometer radius, southeastEU7 - 5 kilometer radius, southwestEU11 - 10 kilometer radius, southwestEU8 - 5 kilometer radius, northwestEU12 - 10 kilometer radius, northwest[2] The analytical results presented in the table represent the maximum concentration reported within the sampling date range. Not all maximums co-occurred such that the sum of maximums at each location is an "artificial composite sample[3] Reporting limits for a limited number of samples with non-detect HFPO-DA results were not available (shown as "0" in the table); these samples were excluded from the statistical summary calculations.Notes:Bold - Analyte detected above associated reporting limit< - Analyte not detected above associated reporting limit. "--" - Data not availableng/L - nanogram(s) per literTR0795Page 36 of 36December 2019 Geosyntec Consultants of NC P.C.Table B-3Screening-Level Exposure AssessmentAnalytical Data Used in the SLEASurface Water DataExposure Unit [1]Sample IDSample Date Units HFPO-DA PEPA PFECA-G PFMOAA PFO2HxA PFO3OA PFO4DA PMPAHydro-EVE AcidEVE Acid PFECA B R-EVE PFO5DA Byproduct 4 Byproduct 5 Byproduct 6 NVHOS PES PFESA-BP1 PFESA-BP2EU13 CFR-01-A05/09/18 ng/L<4--------------------------------------EU13 CFR-01-B05/09/18 ng/L<4--------------------------------------EU13 CFR-01-B405/09/18 ng/L<4--------------------------------------EU13 CFR-01-C05/09/18 ng/L<10--------------------------------------EU13 CFR-MILE-6806/06/18 ng/L<10--------------------------------------EU13 CFR-RM-56-05221905/22/19 ng/L<4 U <20 UJ <2 UJ <5 UJ <2 UJ <2 UJ <2 UJ <10 UJ <2 UJ <2 UJ <2 UJ <2 UJ <2 UJ4 J 12 J<2 UJ2.8 J<2 UJ <2 UJ <2 UJEU13 CFR-RM-56-06071906/07/19 ng/L<4 U <20 U <2 U <5 UJ <2 U <2 U <2 U <10 U <2 U <2 U <2 U <2 U <2 U8.5 J 8.1 J<2 U7.5 <2 U <2 U <2 UEU13 CFR-RM-56-060719-D06/07/19 ng/L<4 U <20 U <2 U <5 UJ <2 U <2 U <2 U <10 U <2 U <2 U <2 U <2 U <2 U8.1 J 4.5 J<2 U7.2 <2 U <2 U <2 UEU13 CFR-RM-68-05221905/22/19 ng/L<4 U <20 UJ <2 UJ <5 UJ2.8 J<2 UJ <2 UJ21 J<2 UJ <2 UJ <2 UJ <2 UJ <2 UJ4.9 J 7.9 J<2 UJ7.6 J<2 UJ <2 UJ <2 UJEU13 CFR-RM-68-06071906/07/19 ng/L5 <20 U <2 U <5 U <2 U <2 U <2 U12 <2 U <2 U <2 U23 J<2 U20 J 320 J<2 U8.2 <2 U <2 U <2 UEU14 CFR-04-A09/26/17 ng/L<10--------------------------------------EU14 CFR-04-A1205/09/18 ng/L<4--------------------------------------EU14 CFR-04-A1305/09/18 ng/L<4--------------------------------------EU14 CFR-04-B09/26/17 ng/L<10--------------------------------------EU14 CFR-04-B1405/09/18 ng/L<4--------------------------------------EU14 CFR-04-B1505/09/18 ng/L4--------------------------------------EU14 CFR-04-B709/26/17 ng/L<10--------------------------------------EU14 CFR-04-B809/26/17 ng/L<10--------------------------------------EU14 CFR-04-C09/26/17 ng/L<10--------------------------------------EU14 CFR-04-C1605/09/18 ng/L<4--------------------------------------EU14 CFR-04-CM-07251907/25/19 ng/L<2 <20 <2 <52.2<2 <2 <10 <2 <2 <22.7<2 <2 <2 <26.2<2 <2 <2EU14 CFR-04-CT-07251907/25/19 ng/L2.1<20 <2 <52.3<2<2<10 <2 <2 <23.8<25.5<2 <26.6<2 <2 <2EU14 CFR-04-E-07251907/25/19 ng/L<2 <20 <2 <52.2<2 <2 <10 <2 <2 <2 <2 <27.6<2 <26.1<2 <2 <2EU14 CFR-04-W-07251907/25/19 ng/L3.4<20 <28.8 4<2 <2 <10 <2 <2 <2 <2 <24.8 2.5<26.6<2 <2 <2EU14 CFR-05-A09/26/17 ng/L160 --------------------------------------EU14 CFR-05-A1705/09/18 ng/L<4--------------------------------------EU14 CFR-05-B09/26/17 ng/L<10--------------------------------------EU14 CFR-05-B1805/09/18 ng/L7.4 --------------------------------------EU14 CFR-05-B1905/09/18 ng/L<4--------------------------------------EU14 CFR-05-B909/26/17 ng/L<10--------------------------------------EU14 CFR-05-C09/26/17 ng/L<10--------------------------------------EU14 CFR-05-C2005/09/18 ng/L49 --------------------------------------EU14 CFR-06-A09/26/17 ng/L43 --------------------------------------EU14 CFR-06-A2105/09/18 ng/L<4--------------------------------------EU14 CFR-06-B09/26/17 ng/L43 --------------------------------------EU14 CFR-06-B1009/26/17 ng/L12 --------------------------------------EU14 CFR-06-B2205/09/18 ng/L5.5 --------------------------------------EU14 CFR-06-B2305/09/18 ng/L<4--------------------------------------EU14 CFR-06-C09/26/17 ng/L<10--------------------------------------EU14 CFR-06-C2405/09/18 ng/L35 --------------------------------------EU14 CFR-07-A09/27/17 ng/L54 --------------------------------------EU14 CFR-07-A2505/10/18 ng/L<10--------------------------------------EU14 CFR-07-B09/27/17 ng/L28 --------------------------------------EU14 CFR-07-B1109/27/17 ng/L27 --------------------------------------EU14 CFR-07-B2605/10/18 ng/L11 --------------------------------------EU14 CFR-07-B2705/10/18 ng/L12 --------------------------------------EU14 CFR-07-C09/26/17 ng/L25 --------------------------------------EU14 CFR-07-C2805/10/18 ng/L19 --------------------------------------EU14 CFR-07-C2905/10/18 ng/L19 --------------------------------------EU14 CFR-07-CM-07251907/25/19 ng/L10<20 <236 13 3.2<213<2 <2 <23.6<25.4 9.6<26.6<2 <2 <2EU14 CFR-07-CT-07251907/25/19 ng/L5.5<20 <221 8.1 2<212<2<2<22.7<28.9 6.6<26.7<2 <2 <2EU14 CFR-07-E-07251907/25/19 ng/L3.7<20 <29.9 4.5<2 <2 <10 <2 <2 <22.9<27.5 3.1<26.8<2 <2 <2EU14 CFR-07-E-072519-207/25/19 ng/L4.3<20 <212 4.9<2 <2 <10 <2 <2 <22.8<26.9 3.1<26<2 <2 <2EU14 CFR-07-W-07251907/25/19 ng/L15<20 <271 25 6.4 2.3 19<2 <2 <23.3<26.5 19<27.2<2 <2 <2TR0795Page 1 of 4December 2019 Geosyntec Consultants of NC P.C.Table B-3Screening-Level Exposure AssessmentAnalytical Data Used in the SLEASurface Water DataExposure Unit [1]Sample IDSample Date Units HFPO-DA PEPA PFECA-G PFMOAA PFO2HxA PFO3OA PFO4DA PMPAHydro-EVE AcidEVE Acid PFECA B R-EVE PFO5DA Byproduct 4 Byproduct 5 Byproduct 6 NVHOS PES PFESA-BP1 PFESA-BP2EU14 CFR-MILE-7606/06/18 ng/L<10--------------------------------------EU14 CFR-MILE-763111/01/18 ng/L<4 <200 <200 <200 <200 <200 <200 <200--------<200----------<200 <200EU14 CFR-MILE-763302/04/19 ng/L2.9<50 <50 <50 <50 <50 <50 <50--------<100----------<50 <50EU14 CFR-RM-76-05221905/22/19 ng/L<4 U <20 UJ <2 UJ <5 UJ3.5 J<2 UJ <2 UJ <10 UJ <2 UJ <2 UJ <2 UJ <2 UJ <2 UJ3.8 J 5.2 J<2 UJ4.1 J<2 UJ <2 UJ <2 UJEU14 CFR-RM-76-06071906/07/19 ng/L6.9 <20 U <2 U <5 U4.4 <2 U <2 U18 <2 U <2 U <2 U4 J<2 U7.9 J 23 J<2 U7.4 <2 U <2 U <2 UEU16 Bladen Bluffs Raw - NCDEQ; EPA[2]06/19/17 ng/L501 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --EU16 Bladen Bluffs Raw - NCDEQ; EPA[2]06/26/17 ng/L31 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --EU16 Bladen Bluffs Raw - NCDEQ; EPA[2]07/03/17 ng/L168 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --EU16 Bladen Bluffs Raw - NCDEQ; EPA[2]07/12/17 ng/L77 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --EU16 Bladen Bluffs Raw - NCDEQ; EPA[2]07/17/17 ng/L54 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --EU16 Bladen Bluffs Raw - NCDEQ; EPA[2]07/24/17 ng/L30.4 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --EU16 Bladen Bluffs Raw - NCDEQ; TA[2]06/19/17 ng/L580 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --EU16 Bladen Bluffs Raw - NCDEQ; TA[2]06/26/17 ng/L36 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --EU16 Bladen Bluffs Raw - NCDEQ; TA[2]07/03/17 ng/L240 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --EU16 Bladen Bluffs Raw - NCDEQ; TA[2]07/12/17 ng/L310 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --EU16 Bladen Bluffs Raw - NCDEQ; TA[2]07/17/17 ng/L70 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --EU16 Bladen Bluffs Raw - NCDEQ; TA[2]07/24/17 ng/L51 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- --EU16 CFR-BLADEN-052219 05/22/19 ng/L28 <20 UJ <2 UJ130 J 40 J 9.9 J 3.5 J 31 J<2 UJ <2 UJ <2 UJ4 J<2 UJ9.6 J 31 J<2 UJ6.1 J<2 UJ <2 UJ <2 UJEU16 CFR-BLADEN-06071906/07/19 ng/L57 <20 U <2 U180 64 16 6.4 55 <2 U <2 U <2 U6.3 J 3.4 19 J 69 J<2 U8.7 <2 U2.4 4.9 EU16 CFR-MILE-8406/06/18 ng/L17 --------------------------------------EU16 CFR-MILE-843211/01/18 ng/L8.6<200 <200 <200 <200 <200 <200 <200--------<200----------<200 <200EU16 CFR-MILE-843402/04/19 ng/L13 50<5056<50 <50 <50 <50--------<100----------<50 <50EU17 CFR-KINGS-05231905/23/19 ng/L17 <20 U <2 U7.8 J 29 7.5 2.4 29 <2 U <2 U <2 U10 J<2 U20 J 7.6 J<2 U6.2 J<2 U <2 U <2 UEU17 CFR-KINGS-052319-D05/23/19 ng/L16 <20 U <2 U8.4 J 29 7.6 2.4 21 <2 U <2 U <2 U <2 U <2 U <2 U8.3 J<2 U <2 U <2 U <2 U <2 UEU17 CFR-KINGS-06071906/07/19 ng/L37 <20 U <2 U230 J 66 20 8.2 35 <2 U <2 U <2 U8.3 J 3.2 19 J 82 J<2 U9 <2 U <2 U5 EU17 CFR-MILE-13211/01/18 ng/L15 ---- 26 13 3.2 -- 16 ------------------------EU17 Sweeney Raw[3]09/12/18 ng/L16.9 7.29ND14.3 13.4 10.9 3.41 4.47 -- -- -- -- -- -- -- -- -- --ND1.7EU17 Sweeney Raw[3]09/14/18 ng/L15.5 2.83ND51.5 43.9 43.4 14.6ND-- -- -- -- -- -- -- -- -- --ND3.29EU17 Sweeney Raw[3]09/15/18 ng/L18.8 5.37ND26.3 25.5 22.4 5.84 5.14 -- -- -- -- -- -- -- -- -- --ND1.85EU17 Sweeney Raw[3]09/16/18 ng/L15.2 9.7ND33.4 28.1 28 8.67ND-- -- -- -- -- -- -- -- -- --ND1.97EU17 Sweeney Raw[3]09/17/18 ng/L33.8 13.8ND13.9 11.2 7.35 3.19 7.61 -- -- -- -- -- -- -- -- -- -- 1.33 2.35EU17 Sweeney Raw[3]09/18/18 ng/L18.6ND ND10.6 9.06 5.66 2.32ND-- -- -- -- -- -- -- -- -- --ND1.34EU17 Sweeney Raw[3]09/19/18 ng/L17.6ND ND9.9 6.94 4.43 2.77ND-- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]09/20/18 ng/L18.9ND ND10.2 8.44 5.14 2.16ND-- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]09/21/18 ng/L12.6ND ND10.7 7.05 5.28 1.67 10.2 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]09/22/18 ng/L8.44ND ND6.82 6.89 5.9 2.09ND-- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]09/23/18 ng/L5.11ND ND5.73 4.59 3.22 1.96ND-- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]09/24/18 ng/L6.32 8.71ND4.05 4.96 2.88ND ND-- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]09/25/18 ng/L8.54ND ND6.7 6.31 3.63 1.25 3.35 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]09/26/18 ng/L15.9 24.8ND13.7 13.4 7.87 2.66 8.6 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]09/27/18 ng/L17.5 21ND16 12.6 5.14 2.05 2.12 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]09/28/18 ng/L27.7ND ND21.2 18.9 9.97 3.95 12.2 -- -- -- -- -- -- -- -- -- --ND1.68EU17 Sweeney Raw[3]09/29/18 ng/L25.1 9.31ND17.5 18.6 8.66 3.46 9.19 -- -- -- -- -- -- -- -- -- --ND1.4EU17 Sweeney Raw[3]09/30/18 ng/L12.4 14.3ND7.53 9.26 4.6 1.69 5.32 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]10/01/18 ng/L10.3 10.3ND8.03 7.05 4.37 1.2 4.82 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]10/02/18 ng/L9.79 17.1ND7.02 4.93ND1.74 5.32 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]10/03/18 ng/L11.7 17.3ND7.19 4.93 3.66 1.3 4.81 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]10/04/18 ng/L10.4 21.7ND6.83 5.45 3.5ND4.15 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]10/05/18 ng/L11 25.3ND8.27 4.23 3.77 2.2 4.59 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]10/06/18 ng/L10.6 23.6ND7.77 5.29 4.74 1.56 4.58 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]10/07/18 ng/L10.2 15.9ND6.17 5.63 4.63 1.22 3.9 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]10/08/18 ng/L11ND ND7.69 5.23ND1.55 4.15 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]10/09/18 ng/L10.2ND ND6.15 5.57 4.49 1.83 4.21 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]10/10/18 ng/L9.94ND ND5.42 4.32ND1.33 4.01 -- -- -- -- -- -- -- -- -- --ND NDTR0795Page 2 of 4December 2019 Geosyntec Consultants of NC P.C.Table B-3Screening-Level Exposure AssessmentAnalytical Data Used in the SLEASurface Water DataExposure Unit [1]Sample IDSample Date Units HFPO-DA PEPA PFECA-G PFMOAA PFO2HxA PFO3OA PFO4DA PMPAHydro-EVE AcidEVE Acid PFECA B R-EVE PFO5DA Byproduct 4 Byproduct 5 Byproduct 6 NVHOS PES PFESA-BP1 PFESA-BP2EU17 Sweeney Raw[3]10/11/18 ng/L9.58ND ND6.27 4.54 4.53 2.02 2.95 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]10/12/18 ng/L10.8ND ND9.81 8.25 4.47 2.29 4.87 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]11/20/18 ng/L3.96ND ND5.21 4.65 3.02ND ND-- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]11/27/18 ng/L12ND ND12.3 6.14 2.59ND5.48 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]12/03/18 ng/L6.93ND ND6.34 4.21ND ND ND-- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]12/10/18 ng/L16 13.6ND15.3 11.7 4.38ND ND-- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]12/17/18 ng/L25.6ND ND15.3 9.33ND1.2 9.99 -- -- -- -- -- -- -- -- -- --ND1.39EU17 Sweeney Raw[3]12/24/18 ng/L5.46ND ND5.98 3.09ND ND ND-- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]12/31/18 ng/L12.8ND ND8.87 6.3ND ND ND-- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]01/07/19 ng/L6.92ND ND6.33 5.58 1.87ND3.38 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]01/14/19 ng/L6.83ND ND8.19 5.59 1.34ND ND-- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]01/21/19 ng/L9.69ND ND11.1 8.39 3.03ND13.1 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]01/28/19 ng/L4.31ND ND5.08 3.69 1.35ND9.74 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]02/04/19 ng/L11.8 6.17ND16.9 10.7 5.46 1.72 4.25 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]02/11/19 ng/L19ND ND17.8 13.6 4.75 1.27 5.96 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]02/18/19 ng/L11.9 7.23ND12.4 7.79 3.73 1.5 4.79 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]02/25/19 ng/L4.08ND ND3.82 2.78ND ND1.61 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]03/04/19 ng/L8.59 3.57ND7.68 6.54 1.61ND5.21 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]03/11/19 ng/L6.75 2.31ND4.69 5.36 1.63ND10.6 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]03/18/19 ng/L7.12 4.04ND7.07 5.29 1.67ND4.26 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]03/25/19 ng/L3.14ND ND4.36 3.08ND ND1.32 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]04/01/19 ng/L7.9 1.72ND12.2 9.98 3.87ND4.09 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]04/08/19 ng/L18.7 6.02ND14.7 13 4.48 1.52 10.6 -- -- -- -- -- -- -- -- -- -- 4.17 1.46EU17 Sweeney Raw[3]04/15/19 ng/L8.39 2.17ND7.2 7.65 2.78ND5.05 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]04/22/19 ng/L18ND ND15.5 11.3 5.84 1.78 12.1 -- -- -- -- -- -- -- -- -- --ND1.48EU17 Sweeney Raw[3]04/29/19 ng/L8.64 4.04ND11.8 8.79 3.83ND6.06 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]05/06/19 ng/L6.79 3.03ND8.19 5.76 2.73ND2.47 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]05/13/19 ng/L12ND ND18.7 14.5 6.09 1.9 4.61 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]05/20/19 ng/L19.6 3.96ND25.2 19.4 7.27 2.57 8.76 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]05/27/19 ng/L23.6 1.82ND29.3 20.3 8.01 2.59 6.78 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]06/03/19 ng/L31.9 6.34ND52.2 43.5 16.7 6.14 14.6 -- -- -- -- -- -- -- -- -- --ND3.51EU17 Sweeney Raw[3]06/10/19 ng/L36.9 8.23ND57 46.8 18.4 7.09 14.7 -- -- -- -- -- -- -- -- -- --ND5.43EU17 Sweeney Raw[3]06/17/19 ng/L9.66 2.4ND8.02 7.7 2.82ND2.07 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]06/24/19 ng/L9.67 2.41ND14.7 13.7 4.13 1.65 5.46 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]07/01/19 ng/L54.8 22.6ND63 57.7 11.3ND64.9 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]07/08/19 ng/L28.6 9.52ND36.2 32.5 9.71 3.88 8.07 -- -- -- -- -- -- -- -- -- --ND3.08EU17 Sweeney Raw[3]07/15/19 ng/L24.8 7.15ND34.9 24.7 7.43 3.31 7.58 -- -- -- -- -- -- -- -- -- --ND2.7EU17 Sweeney Raw[3]07/29/19 ng/L24.8 7.9ND30 25.3 8.85 2.42 6.67 -- -- -- -- -- -- -- -- -- --ND2.1EU17 Sweeney Raw[3]08/12/19 ng/L15.7 5.79ND22.2 15.5 5.1 2.04 5.51 -- -- -- -- -- -- -- -- -- --ND1.57EU17 Sweeney Raw[3]08/26/19 ng/L28.3ND ND38.9 28.7 9.93 3.15 8.3 -- -- -- -- -- -- -- -- -- --ND2.7EU17 Sweeney Raw[3]09/04/19 ng/L11.3 3.24ND14.8 11.5 4.08 1.75 5.97 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]09/05/19 ng/L11.6 6.6ND16.5 12.9 3.91 1.69 7.41 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]09/06/19 ng/L11.1ND ND15.8 12.7 3.69ND6.77 -- -- -- -- -- -- -- -- -- --ND NDEU17 Sweeney Raw[3]09/09/19 ng/L76 16ND52.3 36.1 14.3 7.98 21.7 -- -- -- -- -- -- -- -- -- -- 3.78 6.14EU17 Sweeney Raw[3]09/23/19 ng/L28.4 15.6ND34.2 24.1 8.8 3.2 8.74 -- -- -- -- -- -- -- -- -- --ND2.98EU17 Sweeney Raw[3]10/01/19 ng/L39.4 25.7ND46.8 40.3 14.3 3.74 10.4 -- -- -- -- -- -- -- -- -- --ND3.41EU17 Sweeney Raw[3]10/07/19 ng/L38.8 11ND57.4 50.2 17.5 5.29 15.7 -- -- -- -- -- -- -- -- -- --ND2.91EU18 Pond-1-NE-072419 07/24/19 ng/L940 270<2240 690 91 37 820 3.4<2 <252 9.7 90<2 <25.6<2 <231EU18 Pond-1-NW-072419 07/24/19 ng/L730 280<2250 700 90 38 820 3.4<2 <255 9.9 96<2 <26.1<2 <231EU18 Pond-1-SE-072419 07/24/19 ng/L760 300<2260 720 97 40 850 3.5<2 <258 10 94<2 <26.2<2 <232EU18 Pond-1-SE-072419-2 07/24/19 ng/L770 290<2250 730 95 40 850 3.6<2 <257 10 99<2 <26.3<2 <233TR0795Page 3 of 4December 2019 Geosyntec Consultants of NC P.C.Table B-3Screening-Level Exposure AssessmentAnalytical Data Used in the SLEASurface Water DataExposure Unit [1]Sample IDSample Date Units HFPO-DA PEPA PFECA-G PFMOAA PFO2HxA PFO3OA PFO4DA PMPAHydro-EVE AcidEVE Acid PFECA B R-EVE PFO5DA Byproduct 4 Byproduct 5 Byproduct 6 NVHOS PES PFESA-BP1 PFESA-BP2EU19 POND-B-EAST-09121909/12/19 ng/L310 110<267 220 27 8.9 350<2 <2 <253<2.1140<2 <2 <2 <2 <225EU19 POND-B-SOUTH-091219 09/12/19 ng/L290 110<271 220 26 8.4 350<2 <2 <253 2.1 150<2 <2 <2 <2 <225EU19 POND-B-WEST-091219 09/12/19 ng/L310 100<265 210 26 8.7 340<2 <2 <252<2130<2 <2 <2 <2 <225Notes[1] Exposure Units (EUs) are defined as follows:EU13 - Upstream Cape Fear RiverEU14 - Site-Adjacent Cape Fear RiverEU16 - 8 Miles Downstream, Cape Fear River (Bladen Bluffs)EU17 - 55 Miles Downstream Cape Fear River (Kings Bluffs)EU18 - Onsite Pond 1EU19 - Offsite Pond B[2] https://www.ncwater.org/basins/Cape_Fear/GenXDataspreadsheet.pdf[3] Data were provided by the Cape Fear Public Utility Authority.Definitions:Bold - Analyte detected above associated reporting limit< - Analyte not detected above associated reporting limit-- - No data reportedJ - Analyte detected. Reported value may not be accurate or preciseUJ – Analyte not detected. Reporting limit may not be accurate or precise. ng/L - nanogram(s) per literTR0795Page 4 of 4December 2019 Geosyntec Consultants of NC P.C.Table B-4Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAFish Tissue FilletsExposure Unit [1]Sample ID [2]LocationSpecimen Common NameSpecimen Scientific NameWeight (grams)Length(mm)Sample Date Units HFPO-DA PFMOAA PFO2HxA PFO3OA PFO4DA PFO5DA PMPA PEPA PFESA-BP1 PFESA-BP2EU13 MM-68-1 FHMM-68 Flathead catfishPylodictis olivaris5443 813 8/1/2019 ng/kg<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU13 MM-68-2 CCMM-68 Channel catfishIctalurus punctatus802 457 8/1/2019 ng/kg<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU13 MM-68-3 BCMM-68 Blue catfishIctalurus furcatus4899 660 8/1/2019 ng/kg<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU13 MM-68-4 LMBMM-68 Largemouth bassMicropterus salmoides380 318 8/2/2019 ng/kg<1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJEU13 MM-68-5 LMBMM-68 Largemouth bassMicropterus salmoides976 438 8/1/2019 ng/kg<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU14 CFR-05-1 LMB[3]CFR-06 Largemouth bassMicropterus salmoides631 358 8/1/2019 ng/kg<1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ2,600 J<1,100 UJ370 J<1,100 UJ <1,100 UJ <1,100 UJEU14 CFR-05-2 FH[3]CFR-06 Flathead catfishPylodictis olivaris5262 747 8/1/2019 ng/kg<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU14 CFR-05-3 BC[3]CFR-06 Blue catfishIctalurus furcatus5262 767 8/1/2019 ng/kg<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU14 CFR-05-4 CC[3]CFR-06 Channel catfishIctalurus punctatus607 445 8/1/2019 ng/kg<1,200 UJ <1,200 UJ <1,200 UJ <1,200 UJ <1,200 UJ <1,200 UJ270 J<1,200 UJ <1,200 UJ <1,200 UJEU14 CFR-06-1 BC[4]CFR-07 Blue catfishIctalurus furcatus4899 660 7/31/2019 ng/kg<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU14 CFR-06-2 BC[4]CFR-07 Blue catfishIctalurus furcatus2812 597 7/31/2019 ng/kg<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ280 J<1,000 UJ <1,000 UJ <1,000 UJEU14 CFR-06-3 BC[4]CFR-07 Blue catfishIctalurus furcatus4354 622 7/31/2019 ng/kg<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU15 CFR-09-1 BCCFR-09 Blue catfishIctalurus furcatus12156 914 7/31/2019 ng/kg<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU15 CFR-09-1 LMBCFR-09 Largemouth bassMicropterus salmoides160 226 7/30/2019 ng/kg<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ5,400 J<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU15 CFR-09-2 BCCFR-09 Blue catfishIctalurus furcatus2903 663 7/31/2019 ng/kg<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ1,700 J<1,000 UJ300 J<1,000 UJ <1,000 UJ <1,000 UJEU16 CFR Bladen-01-BluegillBladen Bluffs BluegillLepomis macrochirus76 158 9/26/2019 ng/kg<1,300 UJ6,700 J<1,000 <1,000110,000 J 1,400<1,000 <1,000 <1,000 <1,000EU16 CFR Bladen-01-Channel catfish Bladen Bluffs Channel catfishIctalurus punctatus86 234 9/27/2019 ng/kg<1,300 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU16 CFR Bladen-01-LMBBladen Bluffs Largemouth bassMicropterus salmoides78 191 9/27/2019 ng/kg<4,3004,900 J<1,000 <1,000400310<1,000 <1,000 <1,000 <1,000EU16 CFR Bladen-02-LMBBladen Bluffs Largemouth bassMicropterus salmoides575 356 9/27/2019 ng/kg68,000 1,400 J<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU16 CFR Bladen-02-RedbreastBladen Bluffs Redbreast sunfishLepomis auritus109 196 9/27/2019 ng/kg<1,300 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU16 CFR Bladen-03-LMBBladen Bluffs Largemouth bassMicropterus salmoides835 384 9/27/2019 ng/kg54,000 8,200 J<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU16 CFR Bladen-03-RedbreastBladen Bluffs Redbreast sunfishLepomis auritus138 206 9/27/2019 ng/kg<1,3002,400 J<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU16 CFR Bladen-04-LMBBladen Bluffs Largemouth bassMicropterus salmoides1397 442 9/27/2019 ng/kg24,000 2,300<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU16 CFR Bladen-04-RedbreastBladen Bluffs Redbreast sunfishLepomis auritus145 218 9/27/2019 ng/kg<1,3002,600 J<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000EU18 DERC-1 LMBPond 1 Largemouth bassMicropterus salmoides816 343 7/30/2019 ng/kg<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU18 DERC-2 LMBPond 1 Largemouth bassMicropterus salmoides1270 406 7/30/2019 ng/kg<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJEU18 DERC-3 LMBPond 1 Largemouth bassMicropterus salmoides998 394 7/30/2019 ng/kg<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ270 J<1,000 UJ270 J<1,000 UJ <1,000 UJ <1,000 UJNotes[1] Exposure Units are defined as follows:EU13 - Upstream Cape Fear RiverEU14 - Site-Adjacent Cape Fear RiverEU15 - 4 Miles Downstream, Cape Fear RiverEU16 - 8 Miles Downstream, Cape Fear River (Bladen Bluffs)EU18 - Onsite Pond 1[2] Sample IDs use the following abbreviations to indicate fish species. Only fillet samples were evaluated in the human health SLEA.LMB - Largemouth BassBC - Blue CatfishCC - Channel CatfishFH - Flathead CatfishRedbreast - Redbreasted Sunfish[3] Field staff mistakenly labeled samples collected from CFR-06 as location CFR-05. Coordinates confirmed CFR-06 was correct. [4] Field staff mistakenly labeled samples collected from CFR-07 as location CFR-06. Coordinates confirmed CFR-07 was correct. Definitions:Bold - Analyte detected above associated reporting limit< - Analyte not detected above associated reporting limit-- - No data reportedJ - Analyte detected. Reported value may not be accurate or preciseUJ – Analyte not detected. Reporting limit may not be accurate or precise. ng/kg - nanogram(s) per kilogrammm - millimetersTR0795Page 1 of 2December 2019 Geosyntec Consultants of NC P.C.Table B-4Screening-Level Exposure AssessmentAnalytical Data Used in the SLEAFish Tissue FilletsExposure Unit [1]Sample ID [2]LocationSpecimen Common NameSpecimen Scientific NameWeight (grams)Length(mm)Sample Date UnitsEU13 MM-68-1 FH MM-68 Flathead catfishPylodictis olivaris5443 813 8/1/2019 ng/kgEU13 MM-68-2 CC MM-68 Channel catfishIctalurus punctatus802 457 8/1/2019 ng/kgEU13 MM-68-3 BC MM-68 Blue catfishIctalurus furcatus4899 660 8/1/2019 ng/kgEU13 MM-68-4 LMB MM-68 Largemouth bassMicropterus salmoides380 318 8/2/2019 ng/kgEU13 MM-68-5 LMBMM-68 Largemouth bassMicropterus salmoides976 438 8/1/2019 ng/kgEU14 CFR-05-1 LMB[3]CFR-06 Largemouth bassMicropterus salmoides631 358 8/1/2019 ng/kgEU14 CFR-05-2 FH[3]CFR-06 Flathead catfishPylodictis olivaris5262 747 8/1/2019 ng/kgEU14 CFR-05-3 BC[3]CFR-06 Blue catfishIctalurus furcatus5262 767 8/1/2019 ng/kgEU14 CFR-05-4 CC[3]CFR-06 Channel catfishIctalurus punctatus607 445 8/1/2019 ng/kgEU14 CFR-06-1 BC[4]CFR-07 Blue catfishIctalurus furcatus4899 660 7/31/2019 ng/kgEU14 CFR-06-2 BC[4]CFR-07 Blue catfishIctalurus furcatus2812 597 7/31/2019 ng/kgEU14 CFR-06-3 BC[4]CFR-07 Blue catfishIctalurus furcatus4354 622 7/31/2019 ng/kgEU15 CFR-09-1 BCCFR-09 Blue catfishIctalurus furcatus12156 914 7/31/2019 ng/kgEU15 CFR-09-1 LMBCFR-09 Largemouth bassMicropterus salmoides160 226 7/30/2019 ng/kgEU15 CFR-09-2 BCCFR-09 Blue catfishIctalurus furcatus2903 663 7/31/2019 ng/kgEU16 CFR Bladen-01-BluegillBladen Bluffs BluegillLepomis macrochirus76 158 9/26/2019 ng/kgEU16 CFR Bladen-01-Channel catfish Bladen Bluffs Channel catfishIctalurus punctatus86 234 9/27/2019 ng/kgEU16 CFR Bladen-01-LMBBladen Bluffs Largemouth bassMicropterus salmoides78 191 9/27/2019 ng/kgEU16 CFR Bladen-02-LMBBladen Bluffs Largemouth bassMicropterus salmoides575 356 9/27/2019 ng/kgEU16 CFR Bladen-02-RedbreastBladen Bluffs Redbreast sunfishLepomis auritus109 196 9/27/2019 ng/kgEU16 CFR Bladen-03-LMBBladen Bluffs Largemouth bassMicropterus salmoides835 384 9/27/2019 ng/kgEU16 CFR Bladen-03-RedbreastBladen Bluffs Redbreast sunfishLepomis auritus138 206 9/27/2019 ng/kgEU16 CFR Bladen-04-LMBBladen Bluffs Largemouth bassMicropterus salmoides1397 442 9/27/2019 ng/kgEU16 CFR Bladen-04-RedbreastBladen Bluffs Redbreast sunfishLepomis auritus145 218 9/27/2019 ng/kgEU18 DERC-1 LMBPond 1 Largemouth bassMicropterus salmoides816 343 7/30/2019 ng/kgEU18 DERC-2 LMBPond 1 Largemouth bassMicropterus salmoides1270 406 7/30/2019 ng/kgEU18 DERC-3 LMBPond 1 Largemouth bassMicropterus salmoides998 394 7/30/2019 ng/kgNotes[1] Exposure Units are defined as follows:EU13 - Upstream Cape Fear RiverEU14 - Site-Adjacent Cape Fear RiverEU15 - 4 Miles Downstream, Cape Fear RiverEU16 - 8 Miles Downstream, Cape Fear River (Bladen Bluffs)EU18 - Onsite Pond 1[2] Sample IDs use the following abbreviations to indicate fish species. Only fillet samples were evaluated in the human health SLEA.LMB - Largemouth BassBC - Blue CatfishCC - Channel CatfishFH - Flathead CatfishRedbreast - Redbreasted Sunfish[3] Field staff mistakenly labeled samples collected from CFR-06 as location CFR-05. Coordinates confirmed CFR-06 was correct. [4] Field staff mistakenly labeled samples collected from CFR-07 as location CFR-06. Coordinates confirmed CFR-07 was correct. Definitions:Bold - Analyte detected above associated reporting limit< - Analyte not detected above associated reporting limit-- - No data reportedJ - Analyte detected. Reported value may not be accurate or preciseUJ – Analyte not detected. Reporting limit may not be accurate or precise. ng/kg - nanogram(s) per kilogrammm - millimetersByproduct 4 Byproduct 5 Byproduct 6 NVHOS EVE AcidHydro-EVE AcidR-EVE PES PFECA B PFECA-G<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ<1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ<1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ <1,100 UJ<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ<1,200 UJ <1,200 UJ <1,200 UJ <1,200 UJ <1,200 UJ <1,200 UJ <1,200 UJ <1,200 UJ <1,200 UJ <1,200 UJ<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ<1,000 <1,000 <1,000 <1,000 <1,000 <1,0001,000 J<1,000 <1,000 <1,000 UJ<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000<1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000 <1,000<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ<1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJ <1,000 UJTR0795Page 2 of 2December 2019 TR0795 December 2019 APPENDIX C ProUCL Output Output C-1 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Soil at Exposure Units 1 through 4 General Statistics on Uncensored Data Date/Time of Computation ProUCL 5.112/6/2019 11:41:28 AM User Selected Options From File: WorkSheet.xls From File WorkSheet.xls Full Precision OFF Page 1 of 4 December 2019 Output C-1 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Soil at Exposure Units 1 through 4 0 Min ND Max ND KM Mean KM Var KM SD KM CV General Statistics for Censored Data Set (with NDs) using Kaplan Meier Method Variable NumObs # Missing Num Ds NumNDs % NDs 333.3 DW_EU1_HFPO-DA 24 0 22 2 6 820.4 0.813 8.33% 1.76 1.76 664.3 673003 33.33% N/A 1.235 DW_EU1_PEPA 6 0 4 2 73389 270.9 0 100.00% N/A 100.00% 1.1 2 N/A N/A N/A 1.1 2 N/A N/A N/A DW_EU1_PFECA-G 6 DW_EU1_PFESA-BP1 6 0 0 6 20 20 1.375 2 2 1515 41078 202.7 DW_EU1_PFO2HxA 6 DW_EU1_PFO3OA 6 0 4 2 5 5 261.7 DW_EU1_PFESA-BP2 6 0 4 2 4 2 26.51 1.019 33.33% 2 2 24.33 702.9 33.33% DW_EU1_PFO4DA 6 0 4 2 5 1 41.02 0.789 33.33% 2 2 32 1682 50.00% 133.3 1.09 DW_EU1_PFMOAA 6 0 4 2 71039 266.5 0 33.33% 1.52 33.33% 2 2 1102 2295846 1.282 DW_EU1_PFO5DA 6 0 3 3 41.47 6.44 0 33.33% 0.751 16.67% 10 10 1112 681481 0.743 2.01 2.01 825.5 246316 496.3 DW_EU1_PMPA 6 DW_EU2_HFPO-DA 3 0 2 1 2 2 8.167 N/A DW_EU2_PEPA 1 0 1 0 0 1 N/A N/A 0.00% N/A N/A N/A N/A 100.00% 660.7 N/A N/A DW_EU2_PFECA-G 1 0 0 1 N/A N/A 0 0.00% N/A 100.00% 2 2 N/A N/A N/A N/A N/A N/A N/A N/A DW_EU2_PFESA-BP1 1 DW_EU2_PFESA-BP2 1 0 1 0 2 2 N/A N/A N/A N/A N/A N/A DW_EU2_PFO3OA 1 DW_EU2_PFO4DA 1 0 1 0 N/A N/A N/A DW_EU2_PFMOAA 1 0 1 0 1 0 N/A N/A 0.00% N/A N/A N/A N/A 0.00% DW_EU2_PFO5DA 1 0 1 0 12 0 N/A N/A 0.00% N/A N/A N/A N/A 0.00% N/A N/A DW_EU2_PFO2HxA 1 0 1 0 N/A N/A 0 0.00% N/A 0.00% N/A N/A N/A N/A N/A DW_EU2_PMPA 1 0 1 0 N/A N/A 0 0.00% 0.983 0.00% N/A N/A 421.1 89933 0.712 N/A N/A 299.9 71308 267 DW_EU3_HFPO-DA 12 DW_EU3_PEPA 3 0 3 0 N/A N/A N/A N/A DW_EU3_PFECA-G 3 0 0 3 2 1 N/A N/A 100.00% 2 50 N/A N/A 100.00% 271.7 113.7 N/A DW_EU3_PFESA-BP1 3 0 0 3 N/A N/A 0 0.00% 1.069 33.33% 50 50 19 64 0.421 N/A N/A 8 14752 121.5 DW_EU3_PFESA-BP2 3 DW_EU3_PFMOAA 3 0 3 0 2 50 0.907 2 100 19.5 N/A N/A DW_EU3_PFO4DA 3 DW_EU3_PFO5DA 3 0 0 3 2 50 54.67 DW_EU3_PFO2HxA 3 0 3 0 1 2 432.5 1.362 0.00% N/A N/A 313.3 187033 66.67% DW_EU3_PMPA 3 0 3 0 10 15 749.1 1.565 0.00% N/A N/A 1010 561100 26.67% N/A 1.38 DW_EU3_PFO3OA 3 0 1 2 5548 74.48 0 100.00% N/A 66.67% 2 50 21.5 380.3 0.742 DW_EU4_HFPO-DA 45 0 33 12 47266 217.4 0 100.00% N/A 60.00% 20 20 84.24 9903 1.181 1.1 50 99.52 N/A N/A DW_EU4_PEPA 25 DW_EU4_PFECA-G 25 0 0 25 1.75 10 138.9 8.291 DW_EU4_PFESA-BP1 25 0 0 25 2 0 12 13 N/A 1.373 100.00% 1.1 50 N/A N/A 130.4 N/A DW_EU4_PFESA-BP2 25 0 8 17 129.5 11.38 68.00% 44.00% 1.516 52.00% 5 5 50.8 4585 1.333 2 2 67.71 39084 197.7 DW_EU4_PFMOAA 25 DW_EU4_PFO2HxA 25 0 14 11 N/A 50 19.78 1.586DW_EU4_PFO3OA 25 0 9 16 18 72.00% 8.542 2.923 0.894 64.00% 2 50 12.48 391.4 50 3.27 100.00% 1.1 100 N/A DW_EU4_PFO5DA 25 0 0 25 2DW_EU4_PFO4DA 25 0 7 10 274.2 153135 391.3 1.427 N/A 25 0 16 9 36.00% 10 N/A N/A DW_EU4_PMPA Page 2 of 4 December 2019 Output C-1 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Soil at Exposure Units 1 through 4 N/A Minimum Maximum Mean VarMedianVariable 0.45 724.5 558 723538 850.6 429.9 490 SD MAD/0.675 Skewness CV General Statistics for Raw Data Sets using Detected Data Only NumObs # Missing N/A N/A N/A N/A N/A DW_EU1_PFECA-G 0 DW_EU1_PFESA-BP1 0 0 N/A N/A 385 48600 220.5 DW_EU1_HFPO-DA 22 0 1.81 4200 N/A N/A 3.46 DW_EU1_PFESA-BP2 4 0 5 77 510 4400 1.041 0.708 35.5 30 907 30.12 20.01 390 N/A 1.174 DW_EU1_PEPA 4 0 370 820 22.24 1.976 0 N/A N/A N/A N/A N/A N/A N/A 0.848 DW_EU1_PFMOAA 4 0 200 800 66.72 1.881 0 199 1.28 1653 850 3380958 1839 266.9 1.113 86 64908 1.953 31.13 1.963 DW_EU1_PFO2HxA 4 DW_EU1_PFO3OA 4 0 44 580 280 76200 276 3.215 DW_EU1_PFO4DA 4 0 11 120 60 2300 1.771 0.224 47 28.5 2465 49.65 17.79 14.33 254.8 297 1.056 DW_EU1_PFO5DA 3 0 12 18 1.483 1.545 0 990 0.3 1332 1400 658120 811.2 296.5 0.609 990 88200 -0.883 311.3 N/A DW_EU1_PMPA 5 DW_EU2_HFPO-DA 2 0 780 1200 13 10.33 N/A 130 N/A N/A 0 N/A DW_EU2_PFESA-BP1 0 DW_EU2_PFESA-BP2 1 0 130 130 N/A N/A N/A DW_EU2_PEPA 1 0 780 780 N/A N/A N/A N/A 780 780 N/A N/A 0 N/A DW_EU2_PFMOAA 1 0 410 410 160 160 N/A N/A 410 410 N/A N/A 0 1300 N/A N/A DW_EU2_PFECA-G 0 0 N/A N/A N/A N/A 0 130 N/A N/A N/A N/A N/A N/A N/A DW_EU2_PFO2HxA 1 0 1300 1300 0 N/A 0 60 N/A 160 160 N/A N/A 0 N/A 60 N/A N/A 0 N/A DW_EU2_PFO3OA 1 DW_EU2_PFO4DA 1 0 60 60 1300 N/A N/A N/A DW_EU2_PFO5DA 1 0 16 16 62 1200 N/A N/A 16 16 N/A N/A 0 3100 N/A 267 N/A DW_EU2_PMPA 1 0 3100 3100 0 N/A 0 271.7 0.983 421.1 395 89933 299.9 215 0.712 190 71308 1.617 200.1 1.248 DW_EU3_HFPO-DA 12 DW_EU3_PEPA 3 0 55 570 3100 N/A 0.595 74 14752 N/A 84.51 1.313 DW_EU3_PFESA-BP2 2 DW_EU3_PFMOAA 3 0 17 250 N/A N/A N/A DW_EU3_PFECA-G 0 0 N/A N/A 11 27 N/A N/A N/A N/A N/A N/A N/A N/A DW_EU3_PFO2HxA 3 0 20 810 41 41 1.648 N/A 313.3 110 187033 432.5 133.4 160 121.5 N/A DW_EU3_PFESA-BP1 0 0 N/A N/A N/A N/A 0 113.7 1.069 19 19 128 11.31 11.86 1.38 DW_EU3_PFO3OA 1 0 160 160 0 N/A 0 N/A N/A 41 41 N/A N/A 0 N/A N/A N/A N/A N/A N/A DW_EU3_PFO4DA 1 DW_EU3_PFO5DA 0 0 N/A N/A 160 N/A N/A 238.1 DW_EU3_PMPA 3 0 310 1800 86 400 0.533 1.259 1010 920 561100 749.1 904.4 189.2 N/A N/A 0.742 DW_EU4_HFPO-DA 33 0 0.684 1100 103.5 2.124 0 N/A N/A 180.6 140 10315 101.6 51.89 0.562 N/A N/A 1.432 N/A N/A DW_EU4_PEPA 10 DW_EU4_PFECA-G 0 0 N/A N/A 78.2 56706 181.7 13.48 DW_EU4_PFESA-BP1 0 0 N/A N/A 0 6.7 270 N/A 0.671 N/A N/A N/A N/A N/A N/A DW_EU4_PFESA-BP2 8 0 5.6 44 12.53 0.763 20.09 17.5 0.969 100.4 92 5256 72.5 57.82 0.722 195 50248 224.2DW_EU4_PFO2HxA 14 0 2.1 730 231.3 DW_EU4_PFO3OA 9 0 7.8 88 1 226.8 1.003 DW_EU4_PFMOAA 12 0.284 0.561 30.29 21 639 25.28 19.57 1.702 12 6.629 4.9 13.82 3.718 4.596 DW_EU4_PFO5DA 0 0 N/A N/A 0.835 DW_EU4_PFO4DA 7 0 1.8 N/A N/A N/A N/A N/A 422.9 425 189766 435.6 530 1.393 N/A N/A 1.03DW_EU4_PMPA 16 0 15 1600 Page 3 of 4 December 2019 Output C-1 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Soil at Exposure Units 1 through 4 90%ile 95%ile 99%ile10%ile 20%ile Percentiles using all Detects (Ds) and Non-Detects (NDs) 25%ile(Q1) 50%ile(Q2) 75%ile(Q3) 80%ile 400 0 9.217 166.7 20 Variable NumObs # Missing 107.5 799 260 526.5 852.5 934 1000 3510 370 392.5 1170 610 715 DW_EU1_HFPO-DA 24 DW_EU1_PEPA 6 0 20 74.75 235 285 65.75 545 672.5 DW_EU1_PFESA-BP2 6 DW_EU1_PFMOAA 6 0 5 5 2 2 2 DW_EU1_PFECA-G 6 0 1.55 2 2 2 2 2 2 2 2 2 2 2 DW_EU1_PFO2HxA 6 0 2 2 2 2 3518 555.3 129 670 860 870 2635 12.5 290 2 DW_EU1_PFESA-BP1 6 0 1.55 2 2 2 0 53.75 774.5 2.75 16.5 31 32 54.5 4224 DW_EU1_PFO3OA 6 0 2 2 333 456.5 0 2 17.75 4.25 16.5 31.75 35 77.5 115.8 7 12.75 98.75 15.5 16.75 DW_EU1_PFO4DA 6 DW_EU1_PFO5DA 6 0 2 2 65 86 86 1032 DW_EU1_PMPA 6 0 35 60 780 780 2125 1192 370 1350 1550 1600 1950 391 13 2 2265 DW_EU2_HFPO-DA 3 0 157.6 313.2 1116 1158 0 2 2 780 780 780 780 780 780 2 2 780 2 2 DW_EU2_PEPA 1 DW_EU2_PFECA-G 1 0 2 2 780 990 410 1300 1300 410 1300 1300 DW_EU2_PFMOAA 1 DW_EU2_PFO2HxA 1 0 1300 1300 130 130 130 DW_EU2_PFESA-BP1 1 0 2 2 410 410 2 130 2 2 2 2 2 130 DW_EU2_PFO3OA 1 0 160 160 16 16 160 60 160 160 160 160 160 60 1300 2 DW_EU2_PFESA-BP2 1 0 130 130 130 130 0 1300 1300 410 410 410 410 410 160 DW_EU2_PFO4DA 1 0 60 60 60 60 0 3100 3100 16 16 16 16 16 16 3100 3100 16 3100 3100 DW_EU2_PFO5DA 1 DW_EU2_PMPA 1 0 3100 3100 60 60 60 418 DW_EU3_HFPO-DA 12 0 143.6 188.8 2 2 908.5 562.4 224 395 472.3 514.6 656 122.5 3100 30.8 1142 DW_EU3_PEPA 3 0 82 109 494 532 0 2 49.04 2 2 26 30.8 40.4 49.04 2 26 45.2 40.4 45.2 DW_EU3_PFECA-G 3 DW_EU3_PFESA-BP1 3 0 2 2 190 380 796 50 105 740 138 149 DW_EU3_PFO2HxA 3 DW_EU3_PFO3OA 3 0 11.6 21.2 74 162 179.6 DW_EU3_PFESA-BP2 3 0 14.2 17.4 38 56 47.7 246.5 19 27 38.5 40.8 45.4 45.5 DW_EU3_PFO4DA 3 0 9.8 17.6 432 554 49.1 98.04 21.5 41 45.5 46.4 48.2 2 116 49.54 DW_EU3_PFMOAA 3 0 28.4 39.8 214.8 232.4 0 26 157.8 65 110 460 530 670 49.82 DW_EU3_PFO5DA 3 0 2 2 80.4 90.2 0 4 910.8 615 920 1360 1448 1624 1782 30 170 1712 404 456 DW_EU3_PMPA 3 DW_EU4_HFPO-DA 45 0 4 4 2 51 60.8 2 DW_EU4_PEPA 25 0 20 20 2 2 292 50 20 20 130 140 200 2 290 22.6 378.4 DW_EU4_PFECA-G 25 0 2 2 2 40.4 0 2 50 2 2 2 2 2 50 2 13 40.4 39.6 48.8 DW_EU4_PFESA-BP1 25 DW_EU4_PFESA-BP2 25 0 2 2 2 2 210 232 DW_EU4_PFMOAA 25 0 5 5 0 2 2 164 689.2 5 5 88 96.8 136 246 DW_EU4_PFO2HxA 25 0 2 2 410 542 2 4.4 50 2 2 20 21.8 44 78.88 2 4.8 5.72DW_EU4_PFO4DA 25 0 2 2 2 DW_EU4_PFO5DA 25 0 2 2 49.6 11.2 42.4 DW_EU4_PFO3OA 25 728 952 1456 2 2 2 2 2 80.4 100 33 460 462DW_EU4_PMPA 25 0 10 10 10 Page 4 of 4 December 2019 Output C-2 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Soil at Exposure Units 5 through 8 General Statistics on Uncensored Data Date/Time of Computation ProUCL 5.112/6/2019 11:46:29 AM User Selected Options From File: WorkSheet.xls From File WorkSheet.xls Full Precision OFF Page 1 of 4 December 2019 Output C-2 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Soil at Exposure Units 5 through 8 N/A N/A DW_EU8_PMPA 208 0 166 42 20.19% 5.3 8400 124.2 37952 194.8 1.569 100.00% 1.1 11000 N/A N/A DW_EU8_PFO5DA 208 0 0 208 1.985 DW_EU8_PFO4DA 214 0 25 189 88.32% 1.1 9700 1.525 2.459 1.568 1.028 63.08% 1.1 8800 3.88 59.3 7.7DW_EU8_PFO3OA 214 0 79 135 6144 78.39 DW_EU8_PFMOAA 214 DW_EU8_PFO2HxA 214 0 150 64 29.91% 1.817 32.71% 1.13 9500 22.86 1185 1.506 1.1 9200 43.15 0.0617 DW_EU8_PFESA-BP2 214 0 122 92 83.06 9.114 0 144 70 0.0686 1.3 99.53% 1.1 12000 1.112 0.0047 42.99% 1.1 9500 7.008 DW_EU8_PFESA-BP1 214 0 1 213 34.43 N/A N/A DW_EU8_PEPA 208 DW_EU8_PFECA-G 208 0 0 208 100.00% N/A 74.52% 11 10000 25.12 2279 1.9 1.1 9600 N/A 1.132 DW_EU8_HFPO-DA 357 0 309 48 15588 124.9 0 53 155 508.8 1.978 19.15% 10 8400 449.6 258886 13.45% 0.567 4.3 63.11 DW_EU7_PMPA 47 0 38 9 47.73 N/A N/A DW_EU7_PFO4DA 47 DW_EU7_PFO5DA 47 0 0 47 100.00% N/A 76.60% 1.1 9700 3.821 100.5 2.623 1.1 11000 N/A 1.949 DW_EU7_PFO3OA 47 0 17 30 561.3 23.69 0 11 36 199.7 2.278 38.30% 2 9200 102.5 39875 63.83% 2 8800 10.4 DW_EU7_PFO2HxA 47 0 29 18 10.02 5788 76.08 DW_EU7_PFESA-BP2 47 DW_EU7_PFMOAA 47 0 27 20 42.55% 1.625 48.94% 2 9500 15.59 345.9 1.193 5 9500 46.81 N/A DW_EU7_PFESA-BP1 47 0 0 47 N/A N/A 0 24 23 N/A N/A 100.00% 1.1 9600 N/A N/A 100.00% 1.1 12000 N/A DW_EU7_PFECA-G 47 0 0 47 18.6 22839 151.1 DW_EU7_HFPO-DA 92 DW_EU7_PEPA 47 0 24 23 48.94% 1.423 10.87% 4 4 195.7 200610 2.289 20 10000 106.2 0.0613 DW_EU6_PMPA 16 0 7 9 168933 411 0 82 10 0.125 1.814 93.75% 2 100 2.033 0.0156 56.25% 10 10 226.6 DW_EU6_PFO5DA 16 0 1 15 447.9 10.34 3.215 DW_EU6_PFO3OA 16 DW_EU6_PFO4DA 16 0 4 12 75.00% 0.949 75.00% 2 50 7.927 163.1 1.611 2 50 3.387 1.701 DW_EU6_PFO2HxA 16 0 6 10 21632 147.1 0 4 12 55.42 1.895 75.00% 5 50 32.58 3072 62.50% 2 2 77.59 DW_EU6_PFMOAA 16 0 4 12 12.77 501.6 22.4 DW_EU6_PFESA-BP1 16 DW_EU6_PFESA-BP2 16 0 4 12 75.00% 1.659 100.00% 2 50 N/A N/A N/A 2 50 13.5 1.612 DW_EU6_PFECA-G 16 0 0 16 N/A N/A 0 0 16 114.2 N/A 75.00% 20 100 70.83 13036 100.00% 2 50 N/A DW_EU6_PEPA 16 0 4 12 N/A 19166 138.4 DW_EU5_PMPA 67 DW_EU6_HFPO-DA 30 0 21 9 30.00% 1.279 41.79% 5.3 8400 614.8 1772942 2.166 4 4 108.2 1.741 DW_EU5_PFO5DA 67 0 6 61 2.002 1.415 0 39 28 10.65 0.943 71.64% 1.1 9700 6.117 113.4 91.04% 1.1 11000 1.5 DW_EU5_PFO4DA 67 0 19 48 1332 1870 43.24 DW_EU5_PFO2HxA 67 DW_EU5_PFO3OA 67 0 24 43 64.18% 1.791 47.76% 1.1 9200 252.5 228864 1.895 1.1 8800 24.14 1.468 DW_EU5_PFMOAA 67 0 28 39 11782 108.5 0 35 32 20.48 1.512 65.67% 1.1 9500 13.95 419.5 58.21% 1.29 9500 71.81 DW_EU5_PFESA-BP2 67 0 23 44 478.4 N/A N/A DW_EU5_PFECA-G 67 DW_EU5_PFESA-BP1 67 0 0 67 100.00% N/A 100.00% 1.1 9600 N/A N/A N/A 1.1 12000 N/A 1.668 DW_EU5_PEPA 67 0 27 40 121090 348 0 0 67 519.2 2.245 20.00% 0.647 5.4 311.3 269527 59.70% 2 10000 155 DW_EU5_HFPO-DA 110 0 88 22 N/A General Statistics for Censored Data Set (with NDs) using Kaplan Meier Method Variable NumObs # Missing Num Ds NumNDs % NDs Min ND Max ND KM Mean KM Var KM SD KM CV Page 2 of 4 December 2019 Output C-2 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Soil at Exposure Units 5 through 8 N/A N/A DW_EU8_PMPA 166 0 11 1600 153.5 93 43233 207.9 66.72 4.044 1.354 N/A N/A N/A N/A N/A DW_EU8_PFO5DA 0 0 N/A N/A 1.356 DW_EU8_PFO4DA 25 0 1.1 17 4.169 3.3 12.72 3.567 2.224 2.351 0.855 8.335 4.6 127.8 11.3 2.965 3.932DW_EU8_PFO3OA 79 0 1.4 69 34.32 3.053 DW_EU8_PFMOAA 144 DW_EU8_PFO2HxA 150 0 2 560 60.66 1.45 32.74 21 1451 38.1 17.15 1.163 31.5 7736 87.96 N/A DW_EU8_PFESA-BP2 122 0 1.1 63 5.634 2.443 0 4.6 260 N/A 0.9 1.5 1.5 N/A N/A 0 11.17 8.2 101.1 10.06 DW_EU8_PFESA-BP1 1 0 1.5 1.5 3.344 N/A N/A DW_EU8_PEPA 53 DW_EU8_PFECA-G 0 0 N/A N/A N/A N/A 70.86 39 6130 78.29 26.69 1.105 N/A N/A N/A 1.004 DW_EU8_HFPO-DA 309 0 0.92 1300 31.13 4.857 0 6.5 380 1.849 1.815 519 325 271585 521.1 421.1 72.67 32 17387 131.9 DW_EU7_PMPA 38 0 12 2500 2.157 N/A N/A DW_EU7_PFO4DA 11 DW_EU7_PFO5DA 0 0 N/A N/A N/A N/A 10.39 3.3 371.6 19.28 1.927 1.855 N/A N/A N/A 1.516 DW_EU7_PFO3OA 17 0 2 130 5.041 2.437 0 1.71 67 3.558 1.618 154.1 85 54557 233.6 97.85 22.05 7.6 1273 35.68 DW_EU7_PFO2HxA 29 0 4.1 1200 3.038 41.51 3.862 DW_EU7_PFESA-BP2 24 DW_EU7_PFMOAA 27 0 7.1 480 72.08 1.245 24.96 20 423.9 20.59 16.98 0.825 51 8047 89.71 N/A DW_EU7_PFESA-BP1 0 0 N/A N/A N/A N/A 0 3.7 65 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A DW_EU7_PFECA-G 0 0 N/A N/A 0.945 118.6 1.987 DW_EU7_HFPO-DA 82 DW_EU7_PEPA 24 0 20 770 176.8 1.015 219.1 91 222764 472 117.1 2.154 125 32208 179.5 N/A DW_EU6_PMPA 7 0 20 1500 524.8 1.112 0 5.2 4000 N/A 1.065 2.5 2.5 N/A N/A 0 505.1 380 289598 538.1 DW_EU6_PFO5DA 1 0 2.5 2.5 6.631 6.153 -0.0529 DW_EU6_PFO3OA 4 DW_EU6_PFO4DA 4 0 2.1 12 7.2 0.698 24.23 23.95 332.6 18.24 22.98 0.753 7.35 25.25 5.025 0.57 DW_EU6_PFO2HxA 6 0 2.5 500 202 0.591 0 8 41 -1.589 0.967 115 135 4300 65.57 29.65 203.6 161 38744 196.8 DW_EU6_PFMOAA 4 0 20 170 0.0083 22.24 -0.758 DW_EU6_PFESA-BP1 0 DW_EU6_PFESA-BP2 4 0 14 72 47 0.537 N/A N/A N/A N/A N/A N/A 51 636 25.22 0.752 DW_EU6_PFECA-G 0 0 N/A N/A N/A N/A 0 N/A N/A 0.111 N/A 223.3 220 28222 168 168.3 N/A N/A N/A N/A DW_EU6_PEPA 4 0 23 430 N/A 106.7 0.746 DW_EU5_PMPA 39 DW_EU6_HFPO-DA 21 0 9.2 420 152.9 0.965 1040 610 2659311 1631 726.5 1.568 94 21764 147.5 0.87 DW_EU5_PFO5DA 6 0 2.4 9.8 2.076 1.363 0 11 9300 1.142 0.538 16.71 11 211.4 14.54 13.19 4.967 4.5 7.139 2.672 DW_EU5_PFO4DA 19 0 1.8 55 3.815 46.7 0.755 DW_EU5_PFO2HxA 35 DW_EU5_PFO3OA 24 0 1.8 170 62.13 0.861 475 330 335754 579.4 372.1 1.22 42.5 2864 53.52 0.592 DW_EU5_PFMOAA 28 0 16 460 61.53 1.361 0 2.3 2500 0.28 0.681 35.44 34 440.6 20.99 25.2 164.8 145 12610 112.3 DW_EU5_PFESA-BP2 23 0 1.5 70 2.406 N/A N/A DW_EU5_PFECA-G 0 DW_EU5_PFESA-BP1 0 0 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A 1.434 DW_EU5_PEPA 27 0 80 2400 88.95 3.473 0 N/A N/A 2.914 1.273 388.6 150.5 310506 557.2 204.6 371.4 240 223484 472.7 DW_EU5_HFPO-DA 88 0 1.85 3400 N/A General Statistics for Raw Data Sets using Detected Data Only Variable NumObs # Missing Minimum Maximum Mean Median Var SD MAD/0.675 Skewness CV Page 3 of 4 December 2019 Output C-2 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Soil at Exposure Units 5 through 8 100 DW_EU8_PMPA 208 0 10 11.8 24.5 76 130 160 252 495.5 1272 2 2 2 2 2 2DW_EU8_PFO5DA 208 0 1.1 2 3.1 5.91 DW_EU8_PFO3OA 214 DW_EU8_PFO4DA 214 0 1.265 2 2 50 2 2 3.4 5.14 12.7 68.61 2 2 2 217.4 DW_EU8_PFO2HxA 214 0 2 2 120 200 0 2 2 86.15 438.7 5 13.5 28.23 33 58.58 2 16.5 48.75 58.8 DW_EU8_PFMOAA 214 0 5 5 21.05 19.7 31.88 DW_EU8_PFESA-BP1 214 DW_EU8_PFESA-BP2 214 0 2 2 2 61.31 2 2 2 2 2 50 3.85 9.7 11.4 279.3 DW_EU8_PFECA-G 208 0 1.1 2 2 2 0 1.1 2 116.5 50 20 20 20 25.6 60.2 2 2 2 2 DW_EU8_PEPA 208 0 20 20 2 155.2 274 DW_EU7_PMPA 47 DW_EU8_HFPO-DA 357 0 4 5.4 8.2 578.8 42.5 320 755 872 1400 8400 24 59 73.4 9700 DW_EU7_PFO5DA 47 0 2 2 100 7730 0 10 33.6 6810 11000 2 2 33.5 50 50 2 2 51 100 DW_EU7_PFO4DA 47 0 2 2 6630 67.2 6199 DW_EU7_PFO2HxA 47 DW_EU7_PFO3OA 47 0 2 2 2 8800 2 50 120 186 410 9200 6 50 50 9500 DW_EU7_PFMOAA 47 0 5 5 144 6794 0 2 2 6669 9500 2 14 50 50 60.4 5 44 70.75 85.4 DW_EU7_PFESA-BP2 47 0 2 2 6800 50 8415 DW_EU7_PFECA-G 47 DW_EU7_PFESA-BP1 47 0 1.684 2 2 12000 2 2 26 50 50 9600 2 2 50 1361 DW_EU7_PEPA 47 0 20 20 438 7231 0 2 2 634.5 10000 16 60.5 250 260 399 20 55 170 208 DW_EU7_HFPO-DA 92 0 4.12 12 6735 740 997.5 DW_EU6_PFO5DA 16 DW_EU6_PMPA 16 0 10 10 10 1400 2 2 2 2 2.25 85.38 10 192.5 380 48.65 DW_EU6_PFO4DA 16 0 2 2 11.5 21.5 0 2 2 43.25 44.3 2 2 8.225 8.9 40 2 2 2.5 3.7 DW_EU6_PFO3OA 16 0 2 2 26.88 300 387.5 DW_EU6_PFMOAA 16 DW_EU6_PFO2HxA 16 0 2 2 2 477.5 5 5 27.5 50 135 165.5 2 53.25 72 42.8 DW_EU6_PFESA-BP2 16 0 2 2 55 63 0 5 5 14 70.2 2 2 2 2 2 2 2 21 42 DW_EU6_PFESA-BP1 16 0 2 2 147.5 2 14 DW_EU6_PEPA 16 DW_EU6_PFECA-G 16 0 2 2 2 42.8 20 20 42.25 100 220 403 2 2 2 8706 DW_EU6_HFPO-DA 30 0 4 4 361 386.5 0 20 20 3290 414.2 10 50 735 828 1420 4 34 144.8 254 DW_EU5_PMPA 67 0 10 10 295 100 100 DW_EU5_PFO4DA 67 DW_EU5_PFO5DA 67 0 1.64 2 2 4466 2 2 12 26.6 50 3938 2 2 2.8 4778 DW_EU5_PFO3OA 67 0 2 2 112 157 0 2 2 1113 3573 2 9.9 335 462 770 2 2 50 50 DW_EU5_PFO2HxA 67 0 2 2 50 234 429 DW_EU5_PFESA-BP2 67 DW_EU5_PFMOAA 67 0 5 5 5 3857 2 2 38 50 58.2 3857 5 140 158 3898 DW_EU5_PFESA-BP1 67 0 1.1 2 50 50 0 2 2 50 4872 2 2 2 2 50 2 2 2 2 DW_EU5_PFECA-G 67 0 1.1 2 66.7 1200 334 994 DW_EU5_HFPO-DA 110 DW_EU5_PEPA 67 0 20 20 20 4984 7.05 90.5 472.5 574 772 2437 20 225 248 0 4 4 Percentiles using all Detects (Ds) and Non-Detects (NDs) Variable NumObs # Missing 10%ile 20%ile 25%ile(Q1) 50%ile(Q2) 75%ile(Q3) 80%ile 90%ile 95%ile 99%ile Page 4 of 4 December 2019 Output C-3 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Soil at Exposure Units 9 through 12 From File: WorkSheet.xls General Statistics on Uncensored Data Date/Time of Computation ProUCL 5.112/6/2019 11:52:51 AM User Selected Options From File WorkSheet.xls Full Precision OFF Page 1 of 4 December 2019 Output C-3 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Soil at Exposure Units 9 through 12 DW_EU12_PMPA 315 0 255 60 19.05% 5.3 50 89.19 7368 85.84 0.962 0.576DW_EU12_PFO5DA 322 0 4 318 1.1 50 1.211 98.76% 1.1 100 1.183 DW_EU12_PFO4DA 357 0 16 341 95.52% 0.315 0.561 0.463 84.03% 1.1 50 1.977 18.71 4.325 2.188DW_EU12_PFO3OA 357 0 57 300 0.759 0.642 797.2 28.23 DW_EU12_PFMOAA 357 DW_EU12_PFO2HxA 357 0 231 126 35.29% 1.869 42.58% 1.15 50 11.26 217.5 1.31 1.1 50 15.11 N/A DW_EU12_PFESA-BP2 357 0 138 219 4.734 2.176 61.34% 1.1 0 205 152 N/A 0.928 100.00% 1.1 50 N/A N/A 50 2.346 DW_EU12_PFESA-BP1 357 0 0 357 14.75 0.0113 0.106 DW_EU12_PEPA 315 DW_EU12_PFECA-G 322 0 3 319 99.07% 0.0959 85.40% 11 100 15.69 155.9 0.796 1.1 50 1.11 1.105 DW_EU12_HFPO-DA 384 0 254 130 1015 31.87 0 46 269 141.2 2.05 20.63% 10 50 127.7 19925 33.85% 0.575 4 15.54 DW_EU11_PMPA 63 0 50 13 12.48 N/A N/A DW_EU11_PFO4DA 65 DW_EU11_PFO5DA 63 0 0 63 100.00% N/A 87.69% 1.1 50 1.716 9.897 1.833 1.1 100 N/A 2.57 DW_EU11_PFO3OA 65 0 14 51 137.9 11.74 0 8 57 84 3.173 35.38% 1.1 50 32.68 7056 78.46% 1.1 50 3.701 DW_EU11_PFO2HxA 65 0 42 23 3.146 7110 84.32 DW_EU11_PFESA-BP2 65 DW_EU11_PFMOAA 65 0 41 24 36.92% 3.247 35.38% 1.1 50 11.37 415.9 1.794 2.6 50 25.97 N/A DW_EU11_PFESA-BP1 65 0 0 65 N/A N/A 0 42 23 N/A N/A 100.00% 1.1 50 N/A N/A 100.00% 1.1 50 N/A DW_EU11_PFECA-G 63 0 0 63 20.39 881.5 29.69 DW_EU11_HFPO-DA 126 DW_EU11_PEPA 63 0 25 38 60.32% 1.181 11.90% 2.6 4 37.3 4510 1.8 11 100 25.14 N/A DW_EU10_PMPA 23 0 16 7 17797 133.4 0 111 15 N/A 1.192 100.00% 1.1 100 N/A N/A 30.43% 10 10 111.9 DW_EU10_PFO5DA 24 0 0 24 67.15 0.273 0.523 DW_EU10_PFO3OA 27 DW_EU10_PFO4DA 27 0 2 25 92.59% 0.417 85.19% 1.1 50 2.605 14.15 1.444 1.1 50 1.254 1.375 DW_EU10_PFO2HxA 27 0 14 13 2630 51.28 0 4 23 18.66 2.02 55.56% 1.17 50 13.57 348.3 48.15% 1.1 50 25.39 DW_EU10_PFMOAA 27 0 12 15 3.762 112.5 10.61 DW_EU10_PFESA-BP1 27 DW_EU10_PFESA-BP2 27 0 11 16 59.26% 1.24 100.00% 1.1 50 N/A N/A N/A 1.1 50 8.551 0.649 DW_EU10_PFECA-G 24 0 0 24 N/A N/A 0 0 27 11.54 N/A 73.91% 11 100 17.79 133.2 100.00% 1.1 50 N/A DW_EU10_PEPA 23 0 6 17 N/A 331.3 18.2 DW_EU9_PMPA 167 DW_EU10_HFPO-DA 35 0 27 8 22.86% 1.316 23.95% 5.3 8400 169.1 66300 1.523 2.6 4 13.83 0.985 DW_EU9_PFO5DA 168 0 3 165 0.798 0.893 0 127 40 1.426 0.731 88.83% 1.1 9700 1.448 2.034 98.21% 1.1 11000 1.222 DW_EU9_PFO4DA 179 0 20 159 257.5 54.32 7.37 DW_EU9_PFO2HxA 179 DW_EU9_PFO3OA 179 0 63 116 64.80% 1.76 39.11% 1.1 9200 41.75 5192 1.726 1.1 8800 4.188 1.152 DW_EU9_PFMOAA 179 0 100 79 1089 33 0 109 70 7.096 1.446 51.96% 1.1 9500 6.159 50.36 44.13% 1.14 9500 22.83 DW_EU9_PFESA-BP2 179 0 86 93 72.06 0 2 166 79.21 1.482 17.77% 0.591 4 53.91 6274 62.28% 0.146 N/A N/A DW_EU9_PFECA-G 168 DW_EU9_PFESA-BP1 179 0 0 179 100.00% N/A 98.81% 1.1 9600 1.116 0.0212 0.131 1.1 12000 N/A 11 10000 38.48 DW_EU9_HFPO-DA 287 0 236 51 KM CV General Statistics for Censored Data Set (with NDs) using Kaplan Meier Method Variable NumObs # Missing Num Ds NumNDs 1.469 DW_EU9_PEPA 167 0 63 104 3251 57.01 Min ND Max ND KM Mean KM Var KM SD% NDs Page 2 of 4 December 2019 Output C-3 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Soil at Exposure Units 9 through 12 DW_EU12_PMPA 255 0 7.9 580 68.2 1.929 -0.972 0.257 0.776 7.7 8.05 3.927 1.982 1.483 108.7 94 7121 84.39 DW_EU12_PFO5DA 4 0 5 9.7 1.543 DW_EU12_PFO4DA 16 0 1.57 6.7 3.277 2.5 2.494 1.579 0.919 0.976 0.482 6.342 3.7 95.74 9.785 2.224 5.244DW_EU12_PFO3OA 57 0 1.3 70 12.16 3.973 DW_EU12_PFMOAA 205 DW_EU12_PFO2HxA 231 0 1.27 290 22.63 1.448 18.3 14 260.1 16.13 9.489 0.881 12 1074 32.77 N/A DW_EU12_PFESA-BP2 138 0 1.1 13 1.883 1.286 4.237 3.57 0 1.84 146 N/A 0.593 N/A N/A N/A N/A N/A 6.311 2.512 DW_EU12_PFESA-BP1 0 0 N/A N/A 3.741 0.148 -1.98E-14 DW_EU12_PEPA 46 DW_EU12_PFECA-G 3 0 2.1 2.3 2.2 0.0455 39.22 34 397.6 19.94 14.83 0.508 2.2 0.01 0.1 0.902 DW_EU12_HFPO-DA 254 0 0.749 270 10.38 4.112 0 15 130 1.586 1.61 159.4 110 20661 143.7 69.68 23.03 12 1375 37.08 DW_EU11_PMPA 50 0 5.5 570 2.306 N/A N/A DW_EU11_PFO4DA 8 DW_EU11_PFO5DA 0 0 N/A N/A N/A N/A 5.399 2.4 68.1 8.252 0.675 1.529 N/A N/A N/A 2.065 DW_EU11_PFO3OA 14 0 2 92.8 2.965 3.34 0 1.7 25.7 5.226 1.862 49.31 21.5 10370 101.8 22.61 12.83 4.7 570.3 23.88 DW_EU11_PFO2HxA 42 0 2.4 646 2.764 11.86 6.072 DW_EU11_PFESA-BP2 42 DW_EU11_PFMOAA 41 0 5 685 38.73 2.718 16.31 8.65 576.7 24.02 5.708 1.472 15 11082 105.3 N/A DW_EU11_PFESA-BP1 0 0 N/A N/A N/A N/A 0 2.2 140 N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A N/A DW_EU11_PFECA-G 0 0 N/A N/A 3.98 22.24 2.613 DW_EU11_HFPO-DA 111 DW_EU11_PEPA 25 0 11 200 42.16 0.994 42.11 20.8 4970 70.5 22.68 1.674 27 1755 41.9 N/A DW_EU10_PMPA 16 0 5.8 580 120.1 1.763 0 0.723 528 N/A 0.888 N/A N/A N/A N/A N/A 158.3 155 19739 140.5 DW_EU10_PFO5DA 0 0 N/A N/A 4.496 0.786 N/A DW_EU10_PFO3OA 4 DW_EU10_PFO4DA 2 0 2.34 3.4 2.87 0.261 9.753 9.955 26.04 5.103 5.997 0.523 2.87 0.562 0.75 0.781 DW_EU10_PFO2HxA 14 0 3 230 16.75 1.956 0 4.1 15 0.836 1.403 26.97 20.5 443.2 21.05 20.22 47.18 14.5 4384 66.21 DW_EU10_PFMOAA 12 0 5.5 65 -0.125 17.2 0.286 DW_EU10_PFESA-BP1 0 DW_EU10_PFESA-BP2 11 0 2.37 35 16.68 0.655 N/A N/A N/A N/A N/A N/A 18 119.5 10.93 0.346 DW_EU10_PFECA-G 0 0 N/A N/A N/A N/A 0 N/A N/A 0.275 N/A 32.5 33.5 126.7 11.26 12.6 N/A N/A N/A N/A DW_EU10_PEPA 6 0 20 49 N/A 12.02 1.597 DW_EU9_PMPA 127 DW_EU10_HFPO-DA 27 0 0.866 76.4 17.47 1.124 219.3 120 76533 276.6 131.9 1.262 9.9 385.7 19.64 0.829 DW_EU9_PFO5DA 3 0 6 8.9 1.779 -0.508 0 10 2300 2.446 0.193 3.937 2.9 10.66 3.265 1.334 7.533 7.7 2.123 1.457 DW_EU9_PFO4DA 20 0 1.1 15 4.042 4.744 2.779 DW_EU9_PFO2HxA 109 DW_EU9_PFO3OA 63 0 1.44 59 9.344 1.109 67.03 44 6841 82.71 42.99 1.234 5.9 107.3 10.36 0.647 DW_EU9_PFMOAA 100 0 3.2 190 17.05 2.37 0 2 530 1.209 0.938 11.04 8.8 51.01 7.142 5.041 38.93 27 1333 36.51 DW_EU9_PFESA-BP2 86 0 2.3 32 2.891 0 2.3 2.5 3.111 0.935 65.31 35.5 6928 83.23 35.58 80.65 N/A N/A N/A DW_EU9_PFECA-G 2 DW_EU9_PFESA-BP1 0 0 N/A N/A N/A N/A 2.4 2.4 0.02 0.141 0.148 0.0589 N/A N/A N/A 55 5686 75.4 DW_EU9_HFPO-DA 236 0 1.71 610 Variable NumObs # Missing Minimum Maximum Mean Var SD 1.274 DW_EU9_PEPA 63 0 12 460 35.58 2.688 MAD/0.675 Skewness CVMedian General Statistics for Raw Data Sets using Detected Data Only Page 3 of 4 December 2019 Output C-3 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Soil at Exposure Units 9 through 12 72 130 140DW_EU12_PMPA 315 0 10 12 18.5 190 243 348.6 2 2 2 2 2 2 9.427DW_EU12_PFO5DA 322 0 2 2 2 2 DW_EU12_PFO3OA 357 DW_EU12_PFO4DA 357 0 1.18 2 2 6.028 2 2 2 2 2.916 34.32 2 2 2 52.37 DW_EU12_PFO2HxA 357 0 2 2 44 61.4 2 5 0 1.2 2 39 124.4 5 6.7 15 18.94 31.4 15 21 DW_EU12_PFMOAA 357 0 5 5 5.74 5.28 8.3 DW_EU12_PFESA-BP1 357 DW_EU12_PFESA-BP2 357 0 1.216 2 2 12.44 2 2 2 2 2 2 2 2.9 3.588 95.8 DW_EU12_PFECA-G 322 0 2 2 2 2 0 1.18 2 45.5 2.279 20 20 20 20 30 2 2 2 2 DW_EU12_PEPA 315 0 20 20 2 32.58 61.85 DW_EU11_PMPA 63 DW_EU12_HFPO-DA 384 0 2.6 2.7 2.7 190.9 38 84 140 190 326 563.8 5.9 16 20 50 DW_EU11_PFO5DA 63 0 1.1 1.1 2 90.2 0 10 15.6 45.14 100 1.89 2 2 2 3.34 1.1 2 2 2 DW_EU11_PFO4DA 65 0 1.1 1.1 424 9.86 50 DW_EU11_PFO2HxA 65 DW_EU11_PFO3OA 65 0 1.1 2 2 65.41 2 13 40 50 67.8 367 2 2.6 3.8 102.2 DW_EU11_PFMOAA 65 0 5 5 50 72.4 0 2 2 50 296.5 2 6.6 14 21.2 36.4 5 11 24 30.8 DW_EU11_PFESA-BP2 65 0 2 2 93.4 2 40.4 DW_EU11_PFECA-G 63 DW_EU11_PFESA-BP1 65 0 1.1 1.1 1.1 50 1.1 2 2 2 2 50 2 2 2 345 DW_EU11_PEPA 63 0 13.6 20 76.6 100 0 1.1 1.1 117.5 150.4 5.275 15.35 45.5 54 71.5 20 20 31 40.6 DW_EU11_HFPO-DA 126 0 2.69 4 45.2 228 248 DW_EU10_PFO5DA 24 DW_EU10_PMPA 23 0 10 10 10 507.4 2 2 2 2 100 100 42 185 208 50 DW_EU10_PFO4DA 27 0 1.166 2 50 50 0 1.121 2 50 50 2 2 5.505 11.78 50 2 2 2 2.272 DW_EU10_PFO3OA 27 0 1.248 2 100 86.6 120.4 DW_EU10_PFMOAA 27 DW_EU10_PFO2HxA 27 0 1.72 2 2 204 5 5.82 33.7 42.48 50 64.22 4.4 30.25 46.5 50 DW_EU10_PFESA-BP2 27 0 1.72 2 50 50 0 4.04 5 50 50 1.65 2 2 2 50 2 4.9 21.05 30.2 DW_EU10_PFESA-BP1 27 0 1.136 1.228 58.4 50 50 DW_EU10_PEPA 23 DW_EU10_PFECA-G 24 0 1.121 2 2 50 20 20 38 44.6 100 100 2 2 2 1402 DW_EU10_HFPO-DA 35 0 1.79 2.452 37.56 52.7 0 20 20 651 70.48 13.5 83 235 270 432 2.7 4.8 18 23.38 DW_EU9_PMPA 167 0 10 10 100 2 100 DW_EU9_PFO4DA 179 DW_EU9_PFO5DA 168 0 1.1 2 2 241.9 2 2 2 2 3.236 146.8 2 2 2 475.4 DW_EU9_PFO3OA 179 0 1.412 2 18.2 50 0 1.1 2 201 142.8 2 12 55 64.8 122 2 2 5.5 6.6 DW_EU9_PFO2HxA 179 0 2 2 50 59.6 80.48 DW_EU9_PFESA-BP2 179 DW_EU9_PFMOAA 179 0 5 5 5 251.6 2 3.4 9.85 13 21.4 142.4 15 34 40.4 191.9 DW_EU9_PFESA-BP1 179 0 1.1 1.276 2 50 0 2 2 50 166.6 2 2 2 2 2 2 2 2 2 DW_EU9_PFECA-G 168 0 1.1 2 50 DW_EU9_HFPO-DA 287 DW_EU9_PEPA 167 0 20 364.2 20 53 194 100 180 Variable NumObs # Missing 20 473.6 8.78 24 65 79.8 150 25%ile(Q1) 50%ile(Q2) 75%ile(Q3) 80%ile 57.8 0 4 4.4 20 10%ile 20%ile Percentiles using all Detects (Ds) and Non-Detects (NDs) 90%ile 95%ile 99%ile Page 4 of 4 December 2019 Output C-4 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Water at Exposure Units 13 through 19 (Recreational Use) From File WorkSheet.xls Full Precision OFF General Statistics on Uncensored Full Data Date/Time of Computation ProUCL 5.112/11/2019 12:48:28 PM User Selected Options Page 1 of 4 December 2019 Output C-4 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Water at Exposure Units 13 through 19 (Recreational Use) Minimum Maximum From File: WorkSheet.xls General Statistics for Uncensored Data Sets Variable NumObs # Missing Mean Geo-Mean SD SEM 0 5 5 MAD/0.675 Skewness CV N/A 0 N/A SW_EU13_HFPO-DA 1 SW_EU13_PFO2HxA 1 0 2.8 2.8 2.8 N/A 5 5 N/A N/A 0 N/A 2.8 N/A N/A 0.386 SW_EU13_R-EVE 1 0 23 23 0 N/A 0 4 20 N/A N/A 16.5 15.87 6.364 4.5 6.672 23 23 N/A N/A SW_EU13_PMPA 2 0 12 21 1.728 5.337 2.234 SW_EU13_Byproduct 4 5 SW_EU13_Byproduct 5 5 0 4.5 320 70.5 1.979 9.1 7.696 6.4 2.862 4.744 0.703 16.17 139.5 62.39 0.329 SW_EU14_HFPO-DA 26 0 2.1 160 12.08 3.381 0 8.8 71 -2.079 1.365 6.66 6.235 2.188 0.979 0.445 23.37 12.99 31.92 6.259 SW_EU13_NVHOS 5 0 2.8 8.2 1.634 3.113 2.289 SW_EU14_PFMOAA 6 SW_EU14_PFO2HxA 11 0 2.2 25 6.736 1.015 26.45 19.57 24.08 9.832 10.6 0.91 4.908 6.836 2.061 0.588 SW_EU14_PFO4DA 1 0 2.3 2.3 0 N/A 0 12 19 1.206 N/A 3.867 3.447 2.274 1.313 1.779 2.3 2.3 N/A N/A SW_EU14_PFO3OA 3 0 2 6.4 0 0.593 0.41 SW_EU14_PMPA 4 SW_EU14_R-EVE 8 0 2.7 4 3.225 0.162 15.5 15.2 3.512 1.756 4.448 0.227 3.189 0.523 0.185 0.244 SW_EU14_Byproduct 5 8 0 2.5 23 4.596 1.183 0 4.1 7.4 -0.233 0.868 6.48 6.293 1.58 0.5 1.779 9.013 6.567 7.823 2.766 SW_EU14_Byproduct 4 10 0 3.8 8.9 -1.929 38.55 1.768 SW_EU14_NVHOS 11 SW_EU16_HFPO-DA 17 0 8.6 580 133.6 1.309 6.391 6.326 0.871 0.263 0.593 0.136 64.34 175 42.43 N/A SW_EU16_PFMOAA 3 0 56 180 74.13 -0.568 0 40 64 N/A 0.511 50 50 N/A N/A 0 122 109.4 62.39 36.02 SW_EU16_PEPA 1 0 50 50 N/A 4.522 N/A SW_EU16_PFO2HxA 2 SW_EU16_PFO3OA 2 0 9.9 16 12.95 0.333 52 50.6 16.97 12 17.79 0.326 12.59 4.313 3.05 0.414 SW_EU16_PMPA 2 0 31 55 17.79 N/A 0 4 6.3 N/A 0.395 4.95 4.733 2.051 1.45 2.15 43 41.29 16.97 12 SW_EU16_PFO4DA 2 0 3.5 6.4 N/A 0 N/A SW_EU16_R-EVE 2 SW_EU16_PFO5DA 1 0 3.4 3.4 3.4 N/A 5.15 5.02 1.626 1.15 1.705 0.316 3.4 N/A N/A 0.465 SW_EU16_Byproduct 5 2 0 31 69 28.17 N/A 0 6.1 8.7 N/A 0.537 14.3 13.51 6.647 4.7 6.968 50 46.25 26.87 19 SW_EU16_Byproduct 4 2 0 9.6 19 N/A 0 N/A SW_EU16_NVHOS 2 SW_EU16_PFESA-BP1 1 0 2.4 2.4 2.4 N/A 7.4 7.285 1.838 1.3 1.927 0.248 2.4 N/A N/A N/A SW_EU17_HFPO-DA 79 0 3.14 76 7.265 2.366 0 1.72 25.7 N/A 0.728 4.9 4.9 N/A N/A 0 16.38 13.42 11.92 1.341 SW_EU16_PFESA-BP2 1 0 4.9 4.9 0.796 7.383 5.744 SW_EU17_PEPA 45 SW_EU17_PFMOAA 79 0 3.82 230 19.64 1.425 10.19 7.687 7.302 1.089 7.22 0.717 13.22 27.97 3.147 0.92 SW_EU17_PFO3OA 70 0 1.34 43.4 2.572 3.008 0 1.2 14.6 1.838 0.949 14.81 10.7 13.63 1.534 6.138 7.188 5.43 6.82 0.815 SW_EU17_PFO2HxA 79 0 2.78 66 2.731 3.054 4.041 SW_EU17_PFO4DA 54 SW_EU17_PMPA 65 0 1.32 64.9 8.866 1.051 3.044 2.502 2.44 0.332 0.927 0.802 6.677 9.32 1.156 0.131 SW_EU17_PFO5DA 1 0 3.2 3.2 0 N/A 0 19 20 N/A N/A 9.15 9.11 1.202 0.85 1.26 3.2 3.2 N/A N/A SW_EU17_R-EVE 2 0 8.3 10 N/A 1.038 1.732 SW_EU17_Byproduct 4 2 SW_EU17_Byproduct 5 3 0 7.6 82 32.63 1.31 19.5 19.49 0.707 0.5 0.741 0.0363 17.29 42.75 24.68 0.261 SW_EU17_PFESA-BP1 3 0 1.33 4.17 0.578 -1.608 0 1.34 6.14 N/A 0.498 7.6 7.47 1.98 1.4 2.076 3.093 2.757 1.539 0.889 SW_EU17_NVHOS 2 0 6.2 9 1.282 29.65 1.804 SW_EU17_PFESA-BP2 23 SW_EU18_HFPO-DA 4 0 730 940 800 0.119 2.671 2.405 1.343 0.28 1.156 0.503 796 94.87 47.43 0.0453 0 285 284.8 12.91 6.455 14.83SW_EU18_PEPA 4 0 270 300 Page 2 of 4 December 2019 Output C-4 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Water at Exposure Units 13 through 19 (Recreational Use) SW_EU18_PFMOAA 4 0 240 260 7.413 0 0 690 730 0.0327 250 249.9 8.165 4.082 0 3.706 0.229 SW_EU18_PFO2HxA 4 SW_EU18_PFO3OA 4 0 90 97 93.25 0.0354 710 709.8 18.26 9.129 22.24 0.0257 93.21 3.304 1.652 0.0387 SW_EU18_PMPA 4 0 820 850 22.24 0 0 3.4 3.6 -0.37 0.0207 38.75 38.73 1.5 0.75 1.483 835 834.9 17.32 8.66 SW_EU18_PFO4DA 4 0 37 40 0.855 2.224 -0.864 SW_EU18_Hydro-EVE Acid 4 SW_EU18_R-EVE 4 0 52 58 55.5 0.0477 3.475 3.474 0.0957 0.0479 0.0741 0.0276 55.45 2.646 1.323 0.0143 SW_EU18_Byproduct 4 4 0 90 99 3.706 -0.358 0 5.6 6.3 -1.414 0.0398 9.9 9.899 0.141 0.0707 0.0741 94.75 94.69 3.775 1.887 SW_EU18_PFO5DA 4 0 9.7 10 -1.597 0.741 0.855 SW_EU18_NVHOS 4 SW_EU18_PFESA-BP2 4 0 31 33 31.75 0.0302 6.05 6.044 0.311 0.155 0.148 0.0514 31.74 0.957 0.479 0.0381 SW_EU19_PEPA 3 0 100 110 0 -1.732 0 65 71 -1.732 0.0541 303.3 303.2 11.55 6.667 0 106.7 106.6 5.774 3.333 SW_EU19_HFPO-DA 3 0 290 310 SW_EU19_PFO3OA 3 0 26 27 0.935 0 -1.732 SW_EU19_PFMOAA 3 SW_EU19_PFO2HxA 3 0 210 220 216.7 0.0266 67.67 67.62 3.055 1.764 2.965 0.0451 216.6 5.774 3.333 0.011 346.7 346.6 5.774 3.333 0 0.0167 52.66 0.577 0.333 0.0219 SW_EU19_PFO4DA 3 0 8.4 8.9 0.297 -0.586 0 340 350 1.732 0.029 26.33 26.33 0.577 0.333 0 8.667 8.664 0.252 0.145 0 N/A SW_EU19_PFO5DA 1 0 2.1 2.1 -1.732 0 -1.732 SW_EU19_PMPA 3 SW_EU19_R-EVE 3 0 52 53 52.67 N/A 3 0 25 25 N/A Percentiles for Uncensored Data Sets 25 25 0 0 0SW_EU19_PFESA-BP2 N/A SW_EU19_Byproduct 4 3 0 130 150 140 139.8 10 5.774 14.83 0 0.0714 2.1 2.1 N/A N/A 99%ile SW_EU13_HFPO-DA 1 0 5 5 5 5 0 2.8 2.8 95%ile 5 25%ile(Q1) 50%ile(Q2) 75%ile(Q3) 80%ile 90%ile 5 5 5 5 Variable NumObs # Missing 10%ile 20%ile 2.8 20.1 20.55 SW_EU13_PFO2HxA 1 SW_EU13_PMPA 2 0 12.9 13.8 14.25 20.91 2.8 2.8 2.8 2.8 2.8 2.8 16.5 18.75 19.2 23 SW_EU13_Byproduct 4 5 0 4.36 4.72 15.4 17.7 0 5.86 7.22 23 19.54 23 23 23 23 23 4.9 8.1 8.5 10.8 SW_EU13_R-EVE 1 0 23 23 258.4 7.96 8.08 SW_EU13_Byproduct 5 5 SW_EU13_NVHOS 5 0 4.56 6.32 7.2 8.176 7.9 8.1 12 73.6 196.8 307.7 7.5 7.6 7.72 133.5 SW_EU14_PFMOAA 6 0 9.35 9.9 53.5 62.25 0 2.2 2.3 52.75 69.25 5.5 12 27.75 35 46 10.43 16.5 32.25 36 SW_EU14_HFPO-DA 26 0 3.55 4.3 19 5.76 6.08 SW_EU14_PFO2HxA 11 SW_EU14_PFO3OA 3 0 2.24 2.48 2.6 6.336 2.9 4.4 6.5 8.1 13 23.8 3.2 4.8 5.12 2.3 SW_EU14_PMPA 4 0 12.3 12.6 18.7 18.85 0 2.7 2.74 2.3 18.97 2.3 2.3 2.3 2.3 2.3 12.75 15.5 18.25 18.4 SW_EU14_PFO4DA 1 0 2.3 2.3 3.93 8 8.45 SW_EU14_R-EVE 8 SW_EU14_Byproduct 4 10 0 4.7 5.28 5.425 8.81 2.775 3.1 3.65 3.72 3.86 3.986 6.7 7.575 7.66 22.72 SW_EU14_NVHOS 11 0 6 6.1 7.2 7.3 0 15.4 28.48 21.6 7.38 3.1 5.9 11.95 15.24 20.2 6.15 6.6 6.75 6.8 SW_EU14_Byproduct 5 8 0 2.92 3.1 516.8 50 50 SW_EU16_HFPO-DA 17 SW_EU16_PEPA 1 0 50 50 50 50 30.4 54 168 225.6 386.4 567.4 50 50 50 179 SW_EU16_PFO2HxA 2 0 42.4 44.8 61.6 62.8 0 10.51 11.12 175 63.76 93 130 155 160 170 46 52 58 59.2 SW_EU16_PFMOAA 3 0 70.8 85.6 15.7 6.11 6.255 SW_EU16_PFO3OA 2 SW_EU16_PFO4DA 2 0 3.79 4.08 4.225 6.371 11.43 12.95 14.48 14.78 15.39 15.94 4.95 5.675 5.82 54.76 SW_EU16_R-EVE 2 0 4.23 4.46 6.07 6.185 0 3.4 3.4 53.8 6.277 37 43 49 50.2 52.6 4.575 5.15 5.725 5.84 SW_EU16_PMPA 2 0 33.4 35.8 3.4 18.06 18.53 SW_EU16_PFO5DA 1 SW_EU16_Byproduct 4 2 0 10.54 11.48 11.95 18.91 3.4 3.4 3.4 3.4 3.4 3.4 14.3 16.65 17.12 Page 3 of 4 December 2019 Output C-4 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Water at Exposure Units 13 through 19 (Recreational Use) 68.62 SW_EU16_NVHOS 2 0 6.36 6.62 8.44 8.57 0 2.4 2.4 67.1 8.674 40.5 50 59.5 61.4 65.2 6.75 7.4 8.05 8.18 SW_EU16_Byproduct 5 2 0 34.8 38.6 2.4 4.9 4.9 SW_EU16_PFESA-BP1 1 SW_EU16_PFESA-BP2 1 0 4.9 4.9 4.9 4.9 2.4 2.4 2.4 2.4 2.4 2.4 4.9 4.9 4.9 59.46 SW_EU17_PEPA 45 0 2.404 3.504 22.24 24.56 0 5.93 6.826 37.18 25.52 9.62 12 18.85 24.08 29.26 4.04 7.9 15.6 16.22 SW_EU17_HFPO-DA 79 0 6.782 8.5 52.77 33.22 44.19 SW_EU17_PFMOAA 79 SW_EU17_PFO2HxA 79 0 4.58 5.332 5.585 59.53 7.195 11.8 19.95 26.12 40.48 99.74 9.26 18.75 24.34 32.77 SW_EU17_PFO4DA 54 0 1.309 1.614 6.05 8.057 0 3.362 4.198 19.28 11.46 3.668 4.685 7.975 9.022 14.54 1.69 2.18 3.283 3.572 SW_EU17_PFO3OA 70 0 2.716 3.216 21.56 9.83 9.915 SW_EU17_PMPA 65 SW_EU17_R-EVE 2 0 8.47 8.64 8.725 9.983 4.47 5.96 9.99 10.6 15.3 45.76 9.15 9.575 9.66 3.2 SW_EU17_Byproduct 4 2 0 19.1 19.2 19.9 19.95 0 7.74 7.88 3.2 19.99 3.2 3.2 3.2 3.2 3.2 19.25 19.5 19.75 19.8 SW_EU17_PFO5DA 1 0 3.2 3.2 74.63 8.72 8.86 SW_EU17_Byproduct 5 3 SW_EU17_NVHOS 2 0 6.48 6.76 6.9 8.972 7.95 8.3 45.15 52.52 67.26 80.53 7.6 8.3 8.44 4.162 SW_EU17_PFESA-BP2 23 0 1.412 1.516 4.702 5.387 0 739 748 4.131 5.984 2.555 3.78 3.975 4.014 4.092 1.625 2.35 3.185 3.362 SW_EU17_PFESA-BP1 3 0 1.82 2.31 914.5 297 298.5 SW_EU18_HFPO-DA 4 SW_EU18_PEPA 4 0 273 276 277.5 299.7 752.5 765 812.5 838 889 934.9 285 292.5 294 259.7 SW_EU18_PFO2HxA 4 0 693 696 727 728.5 0 90.3 90.6 258.5 729.7 247.5 250 252.5 254 257 697.5 710 722.5 724 SW_EU18_PFMOAA 4 0 243 246 96.7 40 40 SW_EU18_PFO3OA 4 SW_EU18_PFO4DA 4 0 37.3 37.6 37.75 40 90.75 93 95.5 95.8 96.4 96.94 39 40 40 850 SW_EU18_Hydro-EVE Acid 4 0 3.4 3.4 3.57 3.585 0 52.9 53.8 850 3.597 820 835 850 850 850 3.4 3.45 3.525 3.54 SW_EU18_PMPA 4 0 820 820 57.85 10 10 SW_EU18_R-EVE 4 SW_EU18_PFO5DA 4 0 9.76 9.82 9.85 10 54.25 56 57.25 57.4 57.7 57.97 9.95 10 10 98.91 SW_EU18_NVHOS 4 0 5.75 5.9 6.27 6.285 0 31 31 98.55 6.297 93 95 96.75 97.2 98.1 5.975 6.15 6.225 6.24 SW_EU18_Byproduct 4 4 0 91.2 92.4 32.85 310 310 SW_EU18_PFESA-BP2 4 SW_EU19_HFPO-DA 3 0 294 298 300 310 31 31.5 32.25 32.4 32.7 32.97 310 310 310 110 SW_EU19_PFMOAA 3 0 65.4 65.8 70.2 70.6 0 212 214 110 70.92 105 110 110 110 110 66 67 69 69.4 SW_EU19_PEPA 3 0 102 104 220 26.8 26.9 SW_EU19_PFO2HxA 3 SW_EU19_PFO3OA 3 0 26 26 26 26.98 215 220 220 220 220 220 26 26.5 26.6 8.896 SW_EU19_PMPA 3 0 342 344 350 350 0 52.2 52.4 8.88 350 8.55 8.7 8.8 8.82 8.86 345 350 350 350 SW_EU19_PFO4DA 3 0 8.46 8.52 53 2.1 2.1 SW_EU19_R-EVE 3 SW_EU19_PFO5DA 1 0 2.1 2.1 2.1 2.1 52.5 53 53 53 53 53 2.1 2.1 2.1 149.8 SW_EU19_PFESA-BP2 3 0 25 25 25 25 25 25 25 25 25 135 140 145 146 148 149SW_EU19_Byproduct 4 3 0 132 134 Page 4 of 4 December 2019 Output C-5 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Water at Exposure Units 16 and 17 (Cape Fear River Intake Points) From File WorkSheet.xls Full Precision OFF General Statistics on Uncensored Full Data Date/Time of Computation ProUCL 5.112/11/2019 1:08:57 PM User Selected Options From File: WorkSheet.xls Page 1 of 2 December 2019 Output C-5 Screening-Level Exposure Assessment ProUCL General Statistics Output Surface Water at Exposure Units 16 and 17 (Cape Fear River Intake Points) Minimum Maximum General Statistics for Uncensored Data Sets Variable NumObs # Missing Mean Geo-Mean SD SEM MAD/0.675 Skewness CV 0.744 179 105.2 191.7 55.34 63.45 1.071 13.14 11.99 1.385 1.697 SW_EU17 (Intake Point)_PEPA 45 0 1.72 25.7 1.308 7.22 2.446 SW_EU16 (Intake Point)_HFPO-DA 12 SW_EU17 (Intake Point)_HFPO-DA 75 0 3.14 76 16.12 0 30.4 580 1.816 2.357 3.155 0.717 SW_EU17 (Intake Point)_PFMOAA 75 0 3.82 63 7.383 1.659 0 2.78 57.7 0.796 0.862 10.19 7.687 7.302 1.089 7.22 17.05 12.78 14.7 SW_EU17 (Intake Point)_PFO2HxA 75 SW_EU17 (Intake Point)_PFO3OA 66 0 1.34 43.4 7.043 0.809SW_EU17 (Intake Point)_PFO4DA 51 0 1.2 14.6 0.969 13.77 10.14 12.4 1.432 5.723 0.901 5.314 6.825 0.84 SW_EU17 (Intake Point)_PMPA 61 0 1.32 64.9 7.792 6.137 8.369 1.072 2.861 5.538 1.074 2.968 2.449 2.4 0.336 0.845 2.944 -1.608 0.498 SW_EU17 (Intake Point)_PFESA-BP2 22 0 1.34 6.14 2.565 2.326 1.272 0.271 1.112 1.54 0.496 3.093 2.757 1.539 0.889 0.578SW_EU17 (Intake Point)_PFESA-BP1 3 0 1.33 4.17 0 31.5 39 Percentiles for Uncensored Data Sets Variable NumObs # Missing 10%ile 20%ile 25%ile(Q1) 50%ile(Q2) 75%ile(Q3) 80%ile 90%ile 95%ile 99%ile 571.3 536.6SW_EU16 (Intake Point)_HFPO-DA 12 SW_EU17 (Intake Point)_HFPO-DA 75 0 6.766 8.43 28.52 37.47 0 2.404 3.504 60.31 47.25 73.5 257.5 296 481.9 9.11 11.8 18.85 23.84 58.86 4.04 7.9 15.6 16.22 22.24 25.52 11.8 18.25 25.42 8.85 SW_EU17 (Intake Point)_PFO2HxA 75 0 4.56 5.29 24.56 37.82 52.23 SW_EU17 (Intake Point)_PEPA 45 SW_EU17 (Intake Point)_PFMOAA 75 0 5.83 6.796 7.13 7.535 12.2 14.7 52.15 SW_EU17 (Intake Point)_PFO3OA 66 0 2.66 3.22 14.3 18.18 0 1.3 1.56 43.62 33.39 5.575 8.79 15 19.58 30.98 3.668 4.615 7.975 SW_EU17 (Intake Point)_PFO4DA 51 SW_EU17 (Intake Point)_PMPA 61 0 3.35 4.15 4.26 4.162SW_EU17 (Intake Point)_PFESA-BP1 3 0 1.82 2.31 38.98 1.68 2.09 3.255 3.46 5.84 11.64 5.48 8.76 9.99 SW_EU17 (Intake Point)_PFESA-BP2 22 0 1.406 1.498 1.598 2.225 3.055 3.248 3.5 5.334 5.991 2.555 3.78 3.975 4.014 4.092 4.131 Page 2 of 2 December 2019 Output C-6 Screening-Level Exposure Assessment ProUCL General Statistics Output Fish Fillets General Statistics on Uncensored Data Date/Time of Computation ProUCL 5.112/9/2019 12:51:41 PM User Selected Options From File WorkSheet.xls Full Precision OFF From File: WorkSheet.xls Page 1 of 2 December 2019 Output C-6 Screening-Level Exposure Assessment ProUCL General Statistics Output Fish Fillets 1000 635 1000 1000 1000 1000Filet_EU18_PMPA 3 12 416 562 1000 1000 1000 Filet_EU16_R-EVE 9 1000 1000 1000 1000 1000 1000 1000 1000 Filet_EU18_PFO4DA 3 0 416 562 635 1000 1000 1000 0 1000 1000 66400 101280 Filet_EU16_PFO5DA 9 0 862 1000 1368 1000 1000 1000 1000 22800 1000 1000 1000 1000 1080 1240 Filet_EU16_PFO4DA 9 0 880 1000 62400 7000 7600 Filet_EU16_HFPO-DA 9 8080 1300 1300 24000 36000 56800 66880 Filet_EU16_PFMOAA 9 0 1000 1240 1400 2400 4900 5620 0 1300 1300 5030 5326 Filet_EU15_PMPA 3 0 440 580 1000 1350 1700 3550 3920 4660 650 1000 1000 1000 1000 1000 Filet_EU15_PFO4DA 3 0 1140 1280 2180 1000 1000 Filet_EU14_PFO4DA 7 1000 1000 1000 1100 1160 1760 2516 Filet_EU14_PMPA 7 0 276 298 325 1000 1000 1000 0 1000 1000 Percentiles using all Detects (Ds) and Non-Detects (NDs) Variable NumObs # Missing 10%ile N/A N/A 95%ile 99%ile 0 N/A N/A Filet_EU18_PFO4DA 1 0 270 270 270 20%ile 25%ile(Q1) 50%ile(Q2) 75%ile(Q3) 80%ile 90%ile N/A 0Filet_EU16_R-EVE 1 0 1000 1000 270 N/A N/A Filet_EU16_PFO5DA 2 0 310 1400 855 855 594050 1000 1000 N/A 770.7 808 N/A 0.901 55200 55200 6.006E+9 77499 81245 N/A 1.404Filet_EU16_PFO4DA 2 0 400 110000 -1.008 1779 0.771 Filet_EU16_HFPO-DA 3 0.633 48667 54000 5.053E+8 22480 20756 0.462 Filet_EU16_PFMOAA 7 0 1400 8200 4071 2600 6645714 2578 0 24000 68000 N/A 0.737 Filet_EU15_PMPA 1 0 300 300 N/A 3550 3550 6845000 2616 2743 300 300 N/A N/A 0 N/A Filet_EU15_PFO4DA 2 0 1700 5400 N/A 14.83 1.668 Filet_EU14_PFO4DA 1 0.18 2600 2600 N/A N/A 0 N/A Filet_EU14_PMPA 3 0 270 370 306.7 280 3033 55.08 0 2600 2600 General Statistics for Raw Data Sets using Detected Data Only Variable NumObs # Missing Minimum 0 N/A Skewness CV 0 0 N/A Filet_EU18_PFO4DA 3 0 1 2 66.67% Maximum Mean Median Var SD MAD/0.675 1000 0Filet_EU16_R-EVE 9 0 1 8 1000 1000 270 Filet_EU16_PFO5DA 9 0 2 7 77.78% 1000 1000 88.89% 1000 1000 431.1 117343 342.6 0.795 77.78% 1000 1000 12578 1.186E+9 34444 2.738Filet_EU16_PFO4DA 9 0 2 7 24716 6060988 2462 Filet_EU16_HFPO-DA 9 Filet_EU16_PFMOAA 9 0 7 2 22.22% 1000 1000 3389 0 2 1 0.726 66.67% 1300 4300 17089 6.109E+8 1.446 0 3 6 0 1 6 1930 0.715 Filet_EU15_PMPA 3 0 1 2 N/A 33.33% 1000 1000 2700 3726667 66.67% 1000 1000 300 0 0 Filet_EU15_PFO4DA 3 Variable NumObs # Missing 559.9 2022 44.97 Filet_EU14_PFO4DA 7 0.147 85.71% 1000 1200 1229 313469 0.456 Filet_EU14_PMPA 7 0 3 4 57.14% 1000 1000 306.7 KM Var KM SD KM CVNum Ds NumNDs % NDs Min ND Max ND KM Mean General Statistics for Censored Data Set (with NDs) using Kaplan Meier Method Page 2 of 2 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 From File WorkSheet.xls Full Precision OFF Confidence Coefficient 95% UCL Statistics for Data Sets with Non-Detects User Selected Options Date/Time of Computation ProUCL 5.112/6/2019 11:41:58 AM Number of Bootstrap Operations 2000 Page 1 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs Mean (detects) 724.5 Theta hat (MLE) 834.1 Theta star (bias corrected MLE) 928.3 nu hat (MLE) 38.22 nu star (bias corrected) 34.34 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.869 k star (bias corrected MLE) 0.78 K-S Test Statistic 0.195 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.192 Detected Data Not Gamma Distributed at 5% Significance Level Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.94 Anderson-Darling GOF Test 5% A-D Critical Value 0.777 Detected Data Not Gamma Distributed at 5% Significance Level 97.5% KM Chebyshev UCL 1735 99% KM Chebyshev UCL 2370 95% KM (z) UCL 946.2 95% KM Bootstrap t UCL 1210 90% KM Chebyshev UCL 1179 95% KM Chebyshev UCL 1411 KM SD 820.4 95% KM (BCA) UCL 988.1 95% KM (t) UCL 958.1 95% KM (Percentile Bootstrap) UCL 977.8 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 664.3 KM Standard Error of Mean 171.4 Lilliefors Test Statistic 0.282 Lilliefors GOF Test 5% Lilliefors Critical Value 0.184 Detected Data Not Normal at 5% Significance Level Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.611 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.911 Detected Data Not Normal at 5% Significance Level Mean of Logged Detects 5.91 SD of Logged Detects 1.634 Median Detects 558 CV Detects 1.174 Skewness Detects 3.46 Kurtosis Detects 14.31 Variance Detects 723538 Percent Non-Detects 8.333% Mean Detects 724.5 SD Detects 850.6 Minimum Detect 1.81 Minimum Non-Detect 1.76 Maximum Detect 4200 Maximum Non-Detect 1.76 Number of Detects 22 Number of Non-Detects 2 Number of Distinct Detects 19 Number of Distinct Non-Detects 1 General Statistics Total Number of Observations 24 Number of Distinct Observations 20 DW_EU1_HFPO-DA Page 2 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 KM SD (logged) 2.126 95% Critical H Value (KM-Log) 4.302 KM Standard Error of Mean (logged) 0.444 95% H-UCL (KM -Log) 15222 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 5.464 KM Geo Mean 236.1 95% BCA Bootstrap UCL 1094 95% Bootstrap t UCL 1215 95% H-UCL (Log ROS) 6035 SD in Original Scale 837.1 SD in Log Scale 1.811 95% t UCL (assumes normality of ROS data) 958.3 95% Percentile Bootstrap UCL 957.6 Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 665.4 Mean in Log Scale 5.64 Lilliefors Test Statistic 0.279 Lilliefors GOF Test 5% Lilliefors Critical Value 0.184 Detected Data Not Lognormal at 5% Significance Level Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.778 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.911 Detected Data Not Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 1089 95% Gamma Adjusted KM-UCL (use when n<50) 1129 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (28.87, α) 17.61 Adjusted Chi Square Value (28.87, β) 16.99 80% gamma percentile (KM) 1095 90% gamma percentile (KM) 1727 95% gamma percentile (KM) 2388 99% gamma percentile (KM) 3988 nu hat (KM) 31.48 nu star (KM) 28.87 theta hat (KM) 1013 theta star (KM) 1104 Variance (KM) 673003 SE of Mean (KM) 171.4 k hat (KM) 0.656 k star (KM) 0.602 Estimates of Gamma Parameters using KM Estimates Mean (KM) 664.3 SD (KM) 820.4 Approximate Chi Square Value (19.90, α) 10.77 Adjusted Chi Square Value (19.90, β) 10.3 95% Gamma Approximate UCL (use when n>=50) 1226 95% Gamma Adjusted UCL (use when n<50) 1283 nu hat (MLE) 21.21 nu star (bias corrected) 19.9 Adjusted Level of Significance (β) 0.0392 k hat (MLE) 0.442 k star (bias corrected MLE) 0.415 Theta hat (MLE) 1503 Theta star (bias corrected MLE) 1602 Maximum 4200 Median 526.5 SD 838.1 CV 1.262 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 664.2 GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Page 3 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Lilliefors Test Statistic 0.408 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data Not Normal at 5% Significance Level Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.677 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data Not Normal at 5% Significance Level Note: Sample size is small (e.g., <10), if data are collected using ISM approach, you should use guidance provided in ITRC Tech Reg Guide on ISM (ITRC, 2012) to compute statistics of interest. For example, you may want to use Chebyshev UCL to estimate EPC (ITRC, 2012). Chebyshev UCL can be computed using the Nonparametric and All UCL Options of ProUCL 5.1 Mean of Logged Detects 6.132 SD of Logged Detects 0.387 Median Detects 385 CV Detects 0.45 Skewness Detects 1.976 Kurtosis Detects 3.914 Variance Detects 48600 Percent Non-Detects 33.33% Mean Detects 490 SD Detects 220.5 Minimum Detect 370 Minimum Non-Detect 20 Maximum Detect 820 Maximum Non-Detect 20 Number of Detects 4 Number of Non-Detects 2 Number of Distinct Detects 3 Number of Distinct Non-Detects 1 DW_EU1_PEPA General Statistics Total Number of Observations 6 Number of Distinct Observations 4 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (Chebyshev) UCL 1411 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Data do not follow a Discernible Distribution at 5% Significance Level SD in Original Scale 838.1 SD in Log Scale 2.312 95% t UCL (Assumes normality) 957.4 95% H-Stat UCL 29893 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 664.2 Mean in Log Scale 5.406 KM SD (logged) 2.126 95% Critical H Value (KM-Log) 4.302 KM Standard Error of Mean (logged) 0.444 Page 4 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 nu hat (KM) 18.17 nu star (KM) 10.42 theta hat (KM) 220.2 theta star (KM) 384 Variance (KM) 73389 SE of Mean (KM) 127.7 k hat (KM) 1.514 k star (KM) 0.868 Estimates of Gamma Parameters using KM Estimates Mean (KM) 333.3 SD (KM) 270.9 Approximate Chi Square Value (3.58, α) 0.563 Adjusted Chi Square Value (3.58, β) 0.263 95% Gamma Approximate UCL (use when n>=50) 2163 95% Gamma Adjusted UCL (use when n<50) N/A nu hat (MLE) 4.494 nu star (bias corrected) 3.58 Adjusted Level of Significance (β) 0.0122 k hat (MLE) 0.375 k star (bias corrected MLE) 0.298 Theta hat (MLE) 908.5 Theta star (bias corrected MLE) 1140 Maximum 820 Median 370 SD 289.2 CV 0.85 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 340.3 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Mean (detects) 490 Theta hat (MLE) 59.99 Theta star (bias corrected MLE) 221.9 nu hat (MLE) 65.34 nu star (bias corrected) 17.67 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 8.168 k star (bias corrected MLE) 2.209 K-S Test Statistic 0.421 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.395 Detected Data Not Gamma Distributed at 5% Significance Level Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.804 Anderson-Darling GOF Test 5% A-D Critical Value 0.658 Detected Data Not Gamma Distributed at 5% Significance Level 97.5% KM Chebyshev UCL 1131 99% KM Chebyshev UCL 1604 95% KM (z) UCL 543.4 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL 716.4 95% KM Chebyshev UCL 890 KM SD 270.9 95% KM (BCA) UCL N/A 95% KM (t) UCL 590.7 95% KM (Percentile Bootstrap) UCL N/A Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 333.3 KM Standard Error of Mean 127.7 Page 5 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. 95% KM (BCA) UCL N/A Warning: One or more Recommended UCL(s) not available! Suggested UCL to Use 95% KM (t) UCL 590.7 KM H-UCL 26340 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Data do not follow a Discernible Distribution at 5% Significance Level SD in Original Scale 301 SD in Log Scale 2 95% t UCL (Assumes normality) 577.6 95% H-Stat UCL 930699 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 330 Mean in Log Scale 4.855 KM SD (logged) 1.503 95% Critical H Value (KM-Log) 5.893 KM Standard Error of Mean (logged) 0.709 KM SD (logged) 1.503 95% Critical H Value (KM-Log) 5.893 KM Standard Error of Mean (logged) 0.709 95% H-UCL (KM -Log) 26340 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 5.087 KM Geo Mean 161.8 95% BCA Bootstrap UCL 567.3 95% Bootstrap t UCL 683.5 95% H-UCL (Log ROS) 843 SD in Original Scale 235.5 SD in Log Scale 0.589 95% t UCL (assumes normality of ROS data) 579.6 95% Percentile Bootstrap UCL 535 Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 385.8 Mean in Log Scale 5.811 Lilliefors Test Statistic 0.392 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data Not Lognormal at 5% Significance Level Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.699 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data Not Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 825.9 95% Gamma Adjusted KM-UCL (use when n<50) 1195 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (10.42, α) 4.204 Adjusted Chi Square Value (10.42, β) 2.905 80% gamma percentile (KM) 542.1 90% gamma percentile (KM) 794.6 95% gamma percentile (KM) 1050 99% gamma percentile (KM) 1650 Page 6 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Mean of Logged Detects 3.188 SD of Logged Detects 1.144 Median Detects 30 CV Detects 0.848 Skewness Detects 1.041 Kurtosis Detects 2.039 Variance Detects 907 Percent Non-Detects 33.33% Mean Detects 35.5 SD Detects 30.12 Minimum Detect 5 Minimum Non-Detect 2 Maximum Detect 77 Maximum Non-Detect 2 Number of Detects 4 Number of Non-Detects 2 Number of Distinct Detects 4 Number of Distinct Non-Detects 1 General Statistics Total Number of Observations 6 Number of Distinct Observations 5 The data set for variable DW_EU1_PFESA-BP1 was not processed! DW_EU1_PFESA-BP2 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 6 Number of Distinct Detects 0 Number of Distinct Non-Detects 2 General Statistics Total Number of Observations 6 Number of Distinct Observations 2 The data set for variable DW_EU1_PFECA-G was not processed! DW_EU1_PFESA-BP1 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 6 Number of Distinct Detects 0 Number of Distinct Non-Detects 2 DW_EU1_PFECA-G General Statistics Total Number of Observations 6 Number of Distinct Observations 2 These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Page 7 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 nu hat (MLE) 3.266 nu star (bias corrected) 2.966 k hat (MLE) 0.272 k star (bias corrected MLE) 0.247 Theta hat (MLE) 86.97 Theta star (bias corrected MLE) 95.75 Maximum 77 Median 16.5 SD 29.67 CV 1.253 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 23.67 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Mean (detects) 35.5 Theta hat (MLE) 24.42 Theta star (bias corrected MLE) 66.96 nu hat (MLE) 11.63 nu star (bias corrected) 4.241 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.454 k star (bias corrected MLE) 0.53 K-S Test Statistic 0.254 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.4 Detected data appear Gamma Distributed at 5% Significance Level Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.289 Anderson-Darling GOF Test 5% A-D Critical Value 0.663 Detected data appear Gamma Distributed at 5% Significance Level 97.5% KM Chebyshev UCL 102.4 99% KM Chebyshev UCL 148.7 95% KM (z) UCL 44.89 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL 61.83 95% KM Chebyshev UCL 78.81 KM SD 26.51 95% KM (BCA) UCL N/A 95% KM (t) UCL 49.52 95% KM (Percentile Bootstrap) UCL N/A Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 24.33 KM Standard Error of Mean 12.5 Lilliefors Test Statistic 0.296 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Normal at 5% Significance Level Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.924 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Normal at 5% Significance Level Note: Sample size is small (e.g., <10), if data are collected using ISM approach, you should use guidance provided in ITRC Tech Reg Guide on ISM (ITRC, 2012) to compute statistics of interest. For example, you may want to use Chebyshev UCL to estimate EPC (ITRC, 2012). Chebyshev UCL can be computed using the Nonparametric and All UCL Options of ProUCL 5.1 Page 8 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 DL/2 is not a recommended method, provided for comparisons and historical reasons SD in Original Scale 29.35 SD in Log Scale 1.869 95% t UCL (Assumes normality) 48.15 95% H-Stat UCL 20150 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 24 Mean in Log Scale 2.125 KM SD (logged) 1.427 95% Critical H Value (KM-Log) 5.618 KM Standard Error of Mean (logged) 0.673 KM SD (logged) 1.427 95% Critical H Value (KM-Log) 5.618 KM Standard Error of Mean (logged) 0.673 95% H-UCL (KM -Log) 1055 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.356 KM Geo Mean 10.55 95% BCA Bootstrap UCL 48.15 95% Bootstrap t UCL 65.56 95% H-UCL (Log ROS) 14680 SD in Original Scale 29.26 SD in Log Scale 1.824 95% t UCL (assumes normality of ROS data) 48.17 95% Percentile Bootstrap UCL 44.08 Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 24.1 Mean in Log Scale 2.177 Lilliefors Test Statistic 0.3 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Lognormal at 5% Significance Level Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.921 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 84.42 95% Gamma Adjusted KM-UCL (use when n<50) 142.3 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (6.39, α) 1.841 Adjusted Chi Square Value (6.39, β) 1.093 80% gamma percentile (KM) 40.05 90% gamma percentile (KM) 64.97 95% gamma percentile (KM) 91.41 99% gamma percentile (KM) 156 nu hat (KM) 10.11 nu star (KM) 6.388 theta hat (KM) 28.89 theta star (KM) 45.71 Variance (KM) 702.9 SE of Mean (KM) 12.5 k hat (KM) 0.842 k star (KM) 0.532 Estimates of Gamma Parameters using KM Estimates Mean (KM) 24.33 SD (KM) 26.51 Approximate Chi Square Value (2.97, α) 0.363 Adjusted Chi Square Value (2.97, β) 0.163 95% Gamma Approximate UCL (use when n>=50) 193.7 95% Gamma Adjusted UCL (use when n<50) N/A Adjusted Level of Significance (β) 0.0122 Page 9 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 97.5% KM Chebyshev UCL 1046 99% KM Chebyshev UCL 1512 95% KM (z) UCL 468.3 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL 638.6 95% KM Chebyshev UCL 809.3 KM SD 266.5 95% KM (BCA) UCL N/A 95% KM (t) UCL 514.8 95% KM (Percentile Bootstrap) UCL N/A Detected Data appear Approximate Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 261.7 KM Standard Error of Mean 125.6 Lilliefors Test Statistic 0.391 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data Not Normal at 5% Significance Level Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.756 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Normal at 5% Significance Level Note: Sample size is small (e.g., <10), if data are collected using ISM approach, you should use guidance provided in ITRC Tech Reg Guide on ISM (ITRC, 2012) to compute statistics of interest. For example, you may want to use Chebyshev UCL to estimate EPC (ITRC, 2012). Chebyshev UCL can be computed using the Nonparametric and All UCL Options of ProUCL 5.1 Mean of Logged Detects 5.813 SD of Logged Detects 0.603 Median Detects 280 CV Detects 0.708 Skewness Detects 1.881 Kurtosis Detects 3.647 Variance Detects 76200 Percent Non-Detects 33.33% Mean Detects 390 SD Detects 276 Minimum Detect 200 Minimum Non-Detect 5 Maximum Detect 800 Maximum Non-Detect 5 Number of Detects 4 Number of Non-Detects 2 Number of Distinct Detects 4 Number of Distinct Non-Detects 1 DW_EU1_PFMOAA General Statistics Total Number of Observations 6 Number of Distinct Observations 5 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 49.52 Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level Page 10 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.853 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 833.3 95% Gamma Adjusted KM-UCL (use when n<50) 1351 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (7.12, α) 2.235 Adjusted Chi Square Value (7.12, β) 1.379 80% gamma percentile (KM) 431.3 90% gamma percentile (KM) 682.3 95% gamma percentile (KM) 945.5 99% gamma percentile (KM) 1583 nu hat (KM) 11.57 nu star (KM) 7.116 theta hat (KM) 271.5 theta star (KM) 441.2 Variance (KM) 71039 SE of Mean (KM) 125.6 k hat (KM) 0.964 k star (KM) 0.593 Estimates of Gamma Parameters using KM Estimates Mean (KM) 261.7 SD (KM) 266.5 Approximate Chi Square Value (2.68, α) 0.284 Adjusted Chi Square Value (2.68, β) 0.129 95% Gamma Approximate UCL (use when n>=50) 2451 95% Gamma Adjusted UCL (use when n<50) N/A nu hat (MLE) 2.693 nu star (bias corrected) 2.68 Adjusted Level of Significance (β) 0.0122 k hat (MLE) 0.224 k star (bias corrected MLE) 0.223 Theta hat (MLE) 1159 Theta star (bias corrected MLE) 1164 Maximum 800 Median 235 SD 293.7 CV 1.13 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 260 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Mean (detects) 390 Theta hat (MLE) 114.1 Theta star (bias corrected MLE) 381.9 nu hat (MLE) 27.35 nu star (bias corrected) 8.17 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 3.418 k star (bias corrected MLE) 1.021 K-S Test Statistic 0.382 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.396 Detected data appear Gamma Distributed at 5% Significance Level Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.552 Anderson-Darling GOF Test 5% A-D Critical Value 0.659 Detected data appear Gamma Distributed at 5% Significance Level Page 11 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Number of Detects 4 Number of Non-Detects 2 Number of Distinct Detects 4 Number of Distinct Non-Detects 1 General Statistics Total Number of Observations 6 Number of Distinct Observations 5 Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU1_PFO2HxA When a data set follows an approximate (e.g., normal) distribution passing one of the GOF test When applicable, it is suggested to use a UCL based upon a distribution (e.g., gamma) passing both GOF tests in ProUCL Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Suggested UCL to Use 95% KM (t) UCL 514.8 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Normal Distributed at 5% Significance Level SD in Original Scale 292.9 SD in Log Scale 2.571 95% t UCL (Assumes normality) 501.7 95% H-Stat UCL 1.414E+8 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 260.8 Mean in Log Scale 4.181 KM SD (logged) 2.027 95% Critical H Value (KM-Log) 7.8 KM Standard Error of Mean (logged) 0.955 KM SD (logged) 2.027 95% Critical H Value (KM-Log) 7.8 KM Standard Error of Mean (logged) 0.955 95% H-UCL (KM -Log) 755856 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 4.412 KM Geo Mean 82.41 95% BCA Bootstrap UCL 515 95% Bootstrap t UCL 693.3 95% H-UCL (Log ROS) 1787 SD in Original Scale 271 SD in Log Scale 0.971 95% t UCL (assumes normality of ROS data) 505.7 95% Percentile Bootstrap UCL 461.7 Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 282.8 Mean in Log Scale 5.273 Lilliefors Test Statistic 0.344 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Lognormal at 5% Significance Level Page 12 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs Mean (detects) 1653 Theta hat (MLE) 1136 Theta star (bias corrected MLE) 3116 nu hat (MLE) 11.64 nu star (bias corrected) 4.242 Detected data follow Appr. Gamma Distribution at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.454 k star (bias corrected MLE) 0.53 K-S Test Statistic 0.408 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.4 Detected Data Not Gamma Distributed at 5% Significance Level Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.617 Anderson-Darling GOF Test 5% A-D Critical Value 0.663 Detected data appear Gamma Distributed at 5% Significance Level 97.5% KM Chebyshev UCL 5563 99% KM Chebyshev UCL 8209 95% KM (z) UCL 2277 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL 3245 95% KM Chebyshev UCL 4216 KM SD 1515 95% KM (BCA) UCL N/A 95% KM (t) UCL 2542 95% KM (Percentile Bootstrap) UCL N/A Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 1102 KM Standard Error of Mean 714.3 Lilliefors Test Statistic 0.415 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data Not Normal at 5% Significance Level Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.708 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data Not Normal at 5% Significance Level Note: Sample size is small (e.g., <10), if data are collected using ISM approach, you should use guidance provided in ITRC Tech Reg Guide on ISM (ITRC, 2012) to compute statistics of interest. For example, you may want to use Chebyshev UCL to estimate EPC (ITRC, 2012). Chebyshev UCL can be computed using the Nonparametric and All UCL Options of ProUCL 5.1 Mean of Logged Detects 7.028 SD of Logged Detects 0.939 Median Detects 850 CV Detects 1.113 Skewness Detects 1.953 Kurtosis Detects 3.857 Variance Detects 3380958 Percent Non-Detects 33.33% Mean Detects 1653 SD Detects 1839 Minimum Detect 510 Minimum Non-Detect 2 Maximum Detect 4400 Maximum Non-Detect 2 Page 13 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 KM SD (logged) 3.059 95% Critical H Value (KM-Log) 11.62 KM Standard Error of Mean (logged) 1.442 KM SD (logged) 3.059 95% Critical H Value (KM-Log) 11.62 KM Standard Error of Mean (logged) 1.442 95% H-UCL (KM -Log) 1.183E+11 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 4.917 KM Geo Mean 136.5 95% BCA Bootstrap UCL 2568 95% Bootstrap t UCL 5327 95% H-UCL (Log ROS) 78255 SD in Original Scale 1635 SD in Log Scale 1.5 95% t UCL (assumes normality of ROS data) 2480 95% Percentile Bootstrap UCL 2378 Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 1135 Mean in Log Scale 6.196 Lilliefors Test Statistic 0.359 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Lognormal at 5% Significance Level Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.838 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 5330 95% Gamma Adjusted KM-UCL (use when n<50) 10378 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (4.51, α) 0.932 Adjusted Chi Square Value (4.51, β) 0.479 80% gamma percentile (KM) 1765 90% gamma percentile (KM) 3147 95% gamma percentile (KM) 4680 99% gamma percentile (KM) 8559 nu hat (KM) 6.351 nu star (KM) 4.509 theta hat (KM) 2083 theta star (KM) 2934 Variance (KM) 2295846 SE of Mean (KM) 714.3 k hat (KM) 0.529 k star (KM) 0.376 Estimates of Gamma Parameters using KM Estimates Mean (KM) 1102 SD (KM) 1515 Approximate Chi Square Value (2.49, α) 0.238 Adjusted Chi Square Value (2.49, β) 0.112 95% Gamma Approximate UCL (use when n>=50) 11507 95% Gamma Adjusted UCL (use when n<50) N/A nu hat (MLE) 2.306 nu star (bias corrected) 2.486 Adjusted Level of Significance (β) 0.0122 k hat (MLE) 0.192 k star (bias corrected MLE) 0.207 Theta hat (MLE) 5734 Theta star (bias corrected MLE) 5317 Maximum 4400 Median 670 SD 1660 CV 1.507 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 1102 This is especially true when the sample size is small. Page 14 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Lilliefors Test Statistic 0.421 Lilliefors GOF Test Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.697 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data Not Normal at 5% Significance Level Note: Sample size is small (e.g., <10), if data are collected using ISM approach, you should use guidance provided in ITRC Tech Reg Guide on ISM (ITRC, 2012) to compute statistics of interest. For example, you may want to use Chebyshev UCL to estimate EPC (ITRC, 2012). Chebyshev UCL can be computed using the Nonparametric and All UCL Options of ProUCL 5.1 Mean of Logged Detects 4.764 SD of Logged Detects 1.112 Median Detects 86 CV Detects 1.28 Skewness Detects 1.963 Kurtosis Detects 3.886 Variance Detects 64908 Percent Non-Detects 33.33% Mean Detects 199 SD Detects 254.8 Minimum Detect 44 Minimum Non-Detect 2 Maximum Detect 580 Maximum Non-Detect 2 Number of Detects 4 Number of Non-Detects 2 Number of Distinct Detects 3 Number of Distinct Non-Detects 1 General Statistics Total Number of Observations 6 Number of Distinct Observations 4 Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU1_PFO3OA When a data set follows an approximate (e.g., normal) distribution passing one of the GOF test When applicable, it is suggested to use a UCL based upon a distribution (e.g., gamma) passing both GOF tests in ProUCL Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Suggested UCL to Use 95% KM Bootstrap t UCL N/A 95% Hall's Bootstrap 1.183E+11 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Gamma Distributed at 5% Significance Level SD in Original Scale 1660 SD in Log Scale 3.702 95% t UCL (Assumes normality) 2468 95% H-Stat UCL 1.238E+15 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 1102 Mean in Log Scale 4.686 Page 15 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 nu hat (KM) 5.193 nu star (KM) 3.93 Variance (KM) 41078 SE of Mean (KM) 95.54 k hat (KM) 0.433 k star (KM) 0.328 Estimates of Gamma Parameters using KM Estimates Mean (KM) 133.3 SD (KM) 202.7 Approximate Chi Square Value (2.67, α) 0.282 Adjusted Chi Square Value (2.67, β) 0.128 95% Gamma Approximate UCL (use when n>=50) 1257 95% Gamma Adjusted UCL (use when n<50) N/A nu hat (MLE) 2.674 nu star (bias corrected) 2.67 Adjusted Level of Significance (β) 0.0122 k hat (MLE) 0.223 k star (bias corrected MLE) 0.223 Theta hat (MLE) 595.4 Theta star (bias corrected MLE) 596.2 Maximum 580 Median 65 SD 222.5 CV 1.677 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 132.7 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Mean (detects) 199 Theta hat (MLE) 184.1 Theta star (bias corrected MLE) 455.5 nu hat (MLE) 8.646 nu star (bias corrected) 3.495 Detected data follow Appr. Gamma Distribution at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.081 k star (bias corrected MLE) 0.437 K-S Test Statistic 0.415 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.402 Detected Data Not Gamma Distributed at 5% Significance Level Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.618 Anderson-Darling GOF Test 5% A-D Critical Value 0.666 Detected data appear Gamma Distributed at 5% Significance Level 97.5% KM Chebyshev UCL 730 99% KM Chebyshev UCL 1084 95% KM (z) UCL 290.5 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL 420 95% KM Chebyshev UCL 549.8 KM SD 202.7 95% KM (BCA) UCL N/A 95% KM (t) UCL 325.9 95% KM (Percentile Bootstrap) UCL N/A Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 133.3 KM Standard Error of Mean 95.54 5% Lilliefors Critical Value 0.375 Detected Data Not Normal at 5% Significance Level Page 16 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 When a data set follows an approximate (e.g., normal) distribution passing one of the GOF test When applicable, it is suggested to use a UCL based upon a distribution (e.g., gamma) passing both GOF tests in ProUCL Suggested UCL to Use 95% KM Bootstrap t UCL N/A 95% Hall's Bootstrap 421272 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Gamma Distributed at 5% Significance Level SD in Original Scale 222.3 SD in Log Scale 2.607 95% t UCL (Assumes normality) 315.8 95% H-Stat UCL 77038566 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 133 Mean in Log Scale 3.176 KM SD (logged) 2.074 95% Critical H Value (KM-Log) 7.972 KM Standard Error of Mean (logged) 0.978 KM SD (logged) 2.074 95% Critical H Value (KM-Log) 7.972 KM Standard Error of Mean (logged) 0.978 95% H-UCL (KM -Log) 421272 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 3.407 KM Geo Mean 30.18 95% BCA Bootstrap UCL 388.9 95% Bootstrap t UCL 863.1 95% H-UCL (Log ROS) 50881 SD in Original Scale 220.9 SD in Log Scale 1.778 95% t UCL (assumes normality of ROS data) 316.6 95% Percentile Bootstrap UCL 305.3 Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 134.9 Mean in Log Scale 3.777 Lilliefors Test Statistic 0.36 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Lognormal at 5% Significance Level Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.847 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 754.8 95% Gamma Adjusted KM-UCL (use when n<50) 1559 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (3.93, α) 0.694 Adjusted Chi Square Value (3.93, β) 0.336 80% gamma percentile (KM) 208.5 90% gamma percentile (KM) 388.8 95% gamma percentile (KM) 592.8 99% gamma percentile (KM) 1117 theta hat (KM) 308.1 theta star (KM) 407.1 Page 17 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.268 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.4 Detected data appear Gamma Distributed at 5% Significance Level Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.324 Anderson-Darling GOF Test 5% A-D Critical Value 0.663 Detected data appear Gamma Distributed at 5% Significance Level 97.5% KM Chebyshev UCL 152.7 99% KM Chebyshev UCL 224.4 95% KM (z) UCL 63.8 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL 90.01 95% KM Chebyshev UCL 116.3 KM SD 41.02 95% KM (BCA) UCL N/A 95% KM (t) UCL 70.96 95% KM (Percentile Bootstrap) UCL N/A Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 32 KM Standard Error of Mean 19.34 Lilliefors Test Statistic 0.345 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Normal at 5% Significance Level Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.804 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Normal at 5% Significance Level Note: Sample size is small (e.g., <10), if data are collected using ISM approach, you should use guidance provided in ITRC Tech Reg Guide on ISM (ITRC, 2012) to compute statistics of interest. For example, you may want to use Chebyshev UCL to estimate EPC (ITRC, 2012). Chebyshev UCL can be computed using the Nonparametric and All UCL Options of ProUCL 5.1 Mean of Logged Detects 3.458 SD of Logged Detects 1.006 Median Detects 28.5 CV Detects 1.056 Skewness Detects 1.771 Kurtosis Detects 3.23 Variance Detects 2465 Percent Non-Detects 33.33% Mean Detects 47 SD Detects 49.65 Minimum Detect 11 Minimum Non-Detect 2 Maximum Detect 120 Maximum Non-Detect 2 Number of Detects 4 Number of Non-Detects 2 Number of Distinct Detects 4 Number of Distinct Non-Detects 1 General Statistics Total Number of Observations 6 Number of Distinct Observations 5 Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU1_PFO4DA Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Page 18 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 32 Mean in Log Scale 2.505 Lilliefors Test Statistic 0.211 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Lognormal at 5% Significance Level Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.975 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 139.3 95% Gamma Adjusted KM-UCL (use when n<50) 259.5 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (4.99, α) 1.145 Adjusted Chi Square Value (4.99, β) 0.615 80% gamma percentile (KM) 51.86 90% gamma percentile (KM) 89.77 95% gamma percentile (KM) 131.2 99% gamma percentile (KM) 235 nu hat (KM) 7.304 nu star (KM) 4.985 theta hat (KM) 52.57 theta star (KM) 77.02 Variance (KM) 1682 SE of Mean (KM) 19.34 k hat (KM) 0.609 k star (KM) 0.415 Estimates of Gamma Parameters using KM Estimates Mean (KM) 32 SD (KM) 41.02 Approximate Chi Square Value (2.91, α) 0.347 Adjusted Chi Square Value (2.91, β) 0.156 95% Gamma Approximate UCL (use when n>=50) 262.9 95% Gamma Adjusted UCL (use when n<50) N/A nu hat (MLE) 3.16 nu star (bias corrected) 2.913 Adjusted Level of Significance (β) 0.0122 k hat (MLE) 0.263 k star (bias corrected MLE) 0.243 Theta hat (MLE) 119 Theta star (bias corrected MLE) 129.1 Maximum 120 Median 16.5 SD 45.47 CV 1.451 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 31.34 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Mean (detects) 47 Theta hat (MLE) 33.14 Theta star (bias corrected MLE) 90.16 nu hat (MLE) 11.35 nu star (bias corrected) 4.17 Gamma Statistics on Detected Data Only k hat (MLE) 1.418 k star (bias corrected MLE) 0.521 Page 19 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Warning: Data set has only 3 Detected Values. Mean of Logged Detects 2.647 SD of Logged Detects 0.215 Median Detects 13 CV Detects 0.224 Skewness Detects 1.545 Kurtosis Detects N/A Variance Detects 10.33 Percent Non-Detects 50% Mean Detects 14.33 SD Detects 3.215 Minimum Detect 12 Minimum Non-Detect 2 Maximum Detect 18 Maximum Non-Detect 2 Number of Detects 3 Number of Non-Detects 3 Number of Distinct Detects 3 Number of Distinct Non-Detects 1 DW_EU1_PFO5DA General Statistics Total Number of Observations 6 Number of Distinct Observations 4 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 70.96 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 45.2 SD in Log Scale 1.948 95% t UCL (Assumes normality) 68.85 95% H-Stat UCL 46507 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 31.67 Mean in Log Scale 2.305 KM SD (logged) 1.485 95% Critical H Value (KM-Log) 5.825 KM Standard Error of Mean (logged) 0.7 KM SD (logged) 1.485 95% Critical H Value (KM-Log) 5.825 KM Standard Error of Mean (logged) 0.7 95% H-UCL (KM -Log) 1820 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.536 KM Geo Mean 12.63 95% BCA Bootstrap UCL 75.33 95% Bootstrap t UCL 133.8 95% H-UCL (Log ROS) 7478 SD in Original Scale 44.93 SD in Log Scale 1.693 95% t UCL (assumes normality of ROS data) 68.96 95% Percentile Bootstrap UCL 64.06 Page 20 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 nu hat (MLE) 28.06 nu star (bias corrected) 15.36 Adjusted Level of Significance (β) 0.0122 k hat (MLE) 2.338 k star (bias corrected MLE) 1.28 Theta hat (MLE) 4.048 Theta star (bias corrected MLE) 7.394 Maximum 18 Median 9.542 SD 5.938 CV 0.627 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 1.908 Mean 9.466 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Mean (detects) 14.33 Theta hat (MLE) 0.452 Theta star (bias corrected MLE) N/A nu hat (MLE) 190.3 nu star (bias corrected) N/A Gamma GOF Tests on Detected Observations Only Not Enough Data to Perform GOF Test Gamma Statistics on Detected Data Only k hat (MLE) 31.72 k star (bias corrected MLE) N/A 97.5% KM Chebyshev UCL 28.28 99% KM Chebyshev UCL 40.2 95% KM (z) UCL 13.46 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL 17.83 95% KM Chebyshev UCL 22.2 KM SD 6.44 95% KM (BCA) UCL N/A 95% KM (t) UCL 14.66 95% KM (Percentile Bootstrap) UCL N/A Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 8.167 KM Standard Error of Mean 3.22 Lilliefors Test Statistic 0.328 Lilliefors GOF Test 5% Lilliefors Critical Value 0.425 Detected Data appear Normal at 5% Significance Level Shapiro Wilk Test Statistic 0.871 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.767 Detected Data appear Normal at 5% Significance Level guidance provided in ITRC Tech Reg Guide on ISM (ITRC, 2012) to compute statistics of interest. For example, you may want to use Chebyshev UCL to estimate EPC (ITRC, 2012). Chebyshev UCL can be computed using the Nonparametric and All UCL Options of ProUCL 5.1 Normal GOF Test on Detects Only This is not enough to compute meaningful or reliable statistics and estimates. Note: Sample size is small (e.g., <10), if data are collected using ISM approach, you should use Page 21 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics SD in Original Scale 7.581 SD in Log Scale 1.456 95% t UCL (Assumes normality) 13.9 95% H-Stat UCL 449.9 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 7.667 Mean in Log Scale 1.323 KM SD (logged) 0.985 95% Critical H Value (KM-Log) 4.068 KM Standard Error of Mean (logged) 0.492 KM SD (logged) 0.985 95% Critical H Value (KM-Log) 4.068 KM Standard Error of Mean (logged) 0.492 95% H-UCL (KM -Log) 51.72 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.67 KM Geo Mean 5.312 95% BCA Bootstrap UCL 13.74 95% Bootstrap t UCL 15.62 95% H-UCL (Log ROS) 17.57 SD in Original Scale 4.582 SD in Log Scale 0.433 95% t UCL (assumes normality of ROS data) 14.45 95% Percentile Bootstrap UCL 13.57 Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 10.68 Mean in Log Scale 2.291 Lilliefors Test Statistic 0.315 Lilliefors GOF Test 5% Lilliefors Critical Value 0.425 Detected Data appear Lognormal at 5% Significance Level Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.891 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.767 Detected Data appear Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 19.65 95% Gamma Adjusted KM-UCL (use when n<50) 28.07 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (10.98, α) 4.565 Adjusted Chi Square Value (10.98, β) 3.196 80% gamma percentile (KM) 13.23 90% gamma percentile (KM) 19.22 95% gamma percentile (KM) 25.25 99% gamma percentile (KM) 39.34 nu hat (KM) 19.3 nu star (KM) 10.98 theta hat (KM) 5.078 theta star (KM) 8.923 Variance (KM) 41.47 SE of Mean (KM) 3.22 k hat (KM) 1.608 k star (KM) 0.915 Estimates of Gamma Parameters using KM Estimates Mean (KM) 8.167 SD (KM) 6.44 Approximate Chi Square Value (15.36, α) 7.514 Adjusted Chi Square Value (15.36, β) 5.649 95% Gamma Approximate UCL (use when n>=50) 19.35 95% Gamma Adjusted UCL (use when n<50) N/A Page 22 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Gamma GOF Tests on Detected Observations Only 97.5% KM Chebyshev UCL 3465 99% KM Chebyshev UCL 4861 95% KM (z) UCL 1731 95% KM Bootstrap t UCL 1639 90% KM Chebyshev UCL 2242 95% KM Chebyshev UCL 2754 KM SD 825.5 95% KM (BCA) UCL 1635 95% KM (t) UCL 1871 95% KM (Percentile Bootstrap) UCL 1652 Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 1112 KM Standard Error of Mean 376.8 Lilliefors Test Statistic 0.284 Lilliefors GOF Test 5% Lilliefors Critical Value 0.343 Detected Data appear Normal at 5% Significance Level Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.926 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.762 Detected Data appear Normal at 5% Significance Level Note: Sample size is small (e.g., <10), if data are collected using ISM approach, you should use guidance provided in ITRC Tech Reg Guide on ISM (ITRC, 2012) to compute statistics of interest. For example, you may want to use Chebyshev UCL to estimate EPC (ITRC, 2012). Chebyshev UCL can be computed using the Nonparametric and All UCL Options of ProUCL 5.1 Mean of Logged Detects 6.725 SD of Logged Detects 1.487 Median Detects 1400 CV Detects 0.609 Skewness Detects -0.883 Kurtosis Detects 2.104 Variance Detects 658120 Percent Non-Detects 16.67% Mean Detects 1332 SD Detects 811.2 Minimum Detect 60 Minimum Non-Detect 10 Maximum Detect 2300 Maximum Non-Detect 10 Number of Detects 5 Number of Non-Detects 1 Number of Distinct Detects 5 Number of Distinct Non-Detects 1 DW_EU1_PMPA General Statistics Total Number of Observations 6 Number of Distinct Observations 6 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 14.66 Detected Data appear Normal Distributed at 5% Significance Level Page 23 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Lilliefors Test Statistic 0.418 Lilliefors GOF Test Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.692 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.762 Detected Data Not Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 2529 95% Gamma Adjusted KM-UCL (use when n<50) 3525 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (12.21, α) 5.368 Adjusted Chi Square Value (12.21, β) 3.852 80% gamma percentile (KM) 1787 90% gamma percentile (KM) 2549 95% gamma percentile (KM) 3310 99% gamma percentile (KM) 5074 nu hat (KM) 21.76 nu star (KM) 12.21 theta hat (KM) 613 theta star (KM) 1092 Variance (KM) 681481 SE of Mean (KM) 376.8 k hat (KM) 1.813 k star (KM) 1.018 Estimates of Gamma Parameters using KM Estimates Mean (KM) 1112 SD (KM) 825.5 Approximate Chi Square Value (7.60, α) 2.503 Adjusted Chi Square Value (7.60, β) 1.579 95% Gamma Approximate UCL (use when n>=50) 3472 95% Gamma Adjusted UCL (use when n<50) 5505 nu hat (MLE) 12.53 nu star (bias corrected) 7.596 Adjusted Level of Significance (β) 0.0122 k hat (MLE) 1.044 k star (bias corrected MLE) 0.633 Theta hat (MLE) 1096 Theta star (bias corrected MLE) 1808 Maximum 2300 Median 1350 SD 859 CV 0.751 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 60 Mean 1144 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Mean (detects) 1332 Theta hat (MLE) 1105 Theta star (bias corrected MLE) 2164 nu hat (MLE) 12.05 nu star (bias corrected) 6.155 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.205 k star (bias corrected MLE) 0.616 K-S Test Statistic 0.411 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.363 Detected Data Not Gamma Distributed at 5% Significance Level A-D Test Statistic 0.774 Anderson-Darling GOF Test 5% A-D Critical Value 0.689 Detected Data Not Gamma Distributed at 5% Significance Level Page 24 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Variance Detects 88200 Percent Non-Detects 33.33% Mean Detects 990 SD Detects 297 Minimum Detect 780 Minimum Non-Detect 2.01 Maximum Detect 1200 Maximum Non-Detect 2.01 Number of Detects 2 Number of Non-Detects 1 Number of Distinct Detects 2 Number of Distinct Non-Detects 1 DW_EU2_HFPO-DA General Statistics Total Number of Observations 3 Number of Distinct Observations 3 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 1871 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 905.5 SD in Log Scale 2.476 95% t UCL (Assumes normality) 1856 95% H-Stat UCL 2.693E+8 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 1111 Mean in Log Scale 5.873 KM SD (logged) 2.047 95% Critical H Value (KM-Log) 7.874 KM Standard Error of Mean (logged) 0.934 KM SD (logged) 2.047 95% Critical H Value (KM-Log) 7.874 KM Standard Error of Mean (logged) 0.934 95% H-UCL (KM -Log) 4383294 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 5.988 KM Geo Mean 398.7 95% BCA Bootstrap UCL 1607 95% Bootstrap t UCL 1813 95% H-UCL (Log ROS) 799995 SD in Original Scale 897.1 SD in Log Scale 1.818 95% t UCL (assumes normality of ROS data) 1855 95% Percentile Bootstrap UCL 1660 Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 1117 Mean in Log Scale 6.219 5% Lilliefors Critical Value 0.343 Detected Data Not Lognormal at 5% Significance Level Page 25 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Approximate Chi Square Value (N/A, α) N/A Adjusted Chi Square Value (N/A, β) N/A Gamma Kaplan-Meier (KM) Statistics Adjusted Level of Significance (β) 0.00136 80% gamma percentile (KM) N/A 90% gamma percentile (KM) N/A 95% gamma percentile (KM) N/A 99% gamma percentile (KM) N/A nu hat (KM) 10.63 nu star (KM) N/A theta hat (KM) 372.8 theta star (KM) N/A Variance (KM) 246316 SE of Mean (KM) 405.2 k hat (KM) 1.772 k star (KM) N/A Estimates of Gamma Parameters using KM Estimates Mean (KM) 660.7 SD (KM) 496.3 Mean (detects) 990 Theta hat (MLE) 45.23 Theta star (bias corrected MLE) N/A nu hat (MLE) 87.54 nu star (bias corrected) N/A Gamma GOF Tests on Detected Observations Only Not Enough Data to Perform GOF Test Gamma Statistics on Detected Data Only k hat (MLE) 21.89 k star (bias corrected MLE) N/A 97.5% KM Chebyshev UCL 3191 99% KM Chebyshev UCL 4693 95% KM (z) UCL 1327 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL 1876 95% KM Chebyshev UCL 2427 KM SD 496.3 95% KM (BCA) UCL N/A 95% KM (t) UCL 1844 95% KM (Percentile Bootstrap) UCL N/A Not Enough Data to Perform GOF Test Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 660.7 KM Standard Error of Mean 405.2 guidance provided in ITRC Tech Reg Guide on ISM (ITRC, 2012) to compute statistics of interest. For example, you may want to use Chebyshev UCL to estimate EPC (ITRC, 2012). Chebyshev UCL can be computed using the Nonparametric and All UCL Options of ProUCL 5.1 Normal GOF Test on Detects Only Warning: Data set has only 2 Detected Values. This is not enough to compute meaningful or reliable statistics and estimates. Note: Sample size is small (e.g., <10), if data are collected using ISM approach, you should use Mean of Logged Detects 6.875 SD of Logged Detects 0.305 Median Detects 990 CV Detects 0.3 Skewness Detects N/A Kurtosis Detects N/A Page 26 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 General Statistics Total Number of Observations 1 Number of Distinct Observations 1 However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU2_PEPA Warning: Recommended UCL exceeds the maximum observation Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). 95% KM (BCA) UCL N/A Warning: One or more Recommended UCL(s) not available! Suggested UCL to Use 95% KM (t) UCL 1844 KM H-UCL 1.283E+38 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Data do not follow a Discernible Distribution at 5% Significance Level SD in Original Scale 608.4 SD in Log Scale 3.972 95% t UCL (Assumes normality) 1686 95% H-Stat UCL 6.009E+68 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 660.3 Mean in Log Scale 4.585 KM SD (logged) 2.917 95% Critical H Value (KM-Log) 38.14 KM Standard Error of Mean (logged) 2.382 KM SD (logged) 2.917 95% Critical H Value (KM-Log) 38.14 KM Standard Error of Mean (logged) 2.382 95% H-UCL (KM -Log) 1.283E+38 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 4.816 KM Geo Mean 123.4 95% H-UCL (Log ROS) 24214 95% t UCL (assumes normality of ROS data) 1486 95% Percentile Bootstrap UCL N/A 95% BCA Bootstrap UCL N/A 95% Bootstrap t UCL N/A Mean in Original Scale 781.2 Mean in Log Scale 6.549 SD in Original Scale 418.2 SD in Log Scale 0.605 Lognormal GOF Test on Detected Observations Only Not Enough Data to Perform GOF Test Lognormal ROS Statistics Using Imputed Non-Detects 95% Gamma Approximate KM-UCL (use when n>=50) N/A 95% Gamma Adjusted KM-UCL (use when n<50) N/A Page 27 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 DW_EU2_PFESA-BP2 It is suggested to collect at least 8 to 10 observations before using these statistical methods! If possible, compute and collect Data Quality Objectives (DQO) based sample size and analytical results. Warning: This data set only has 1 observations! Data set is too small to compute reliable and meaningful statistics and estimates! The data set for variable DW_EU2_PFESA-BP1 was not processed! Number of Detects 0 Number of Non-Detects 1 Number of Distinct Detects 0 Number of Distinct Non-Detects 1 General Statistics Total Number of Observations 1 Number of Distinct Observations 1 It is suggested to collect at least 8 to 10 observations before using these statistical methods! If possible, compute and collect Data Quality Objectives (DQO) based sample size and analytical results. DW_EU2_PFESA-BP1 Warning: This data set only has 1 observations! Data set is too small to compute reliable and meaningful statistics and estimates! The data set for variable DW_EU2_PFECA-G was not processed! Number of Detects 0 Number of Non-Detects 1 Number of Distinct Detects 0 Number of Distinct Non-Detects 1 General Statistics Total Number of Observations 1 Number of Distinct Observations 1 If possible, compute and collect Data Quality Objectives (DQO) based sample size and analytical results. DW_EU2_PFECA-G Warning: This data set only has 1 observations! Data set is too small to compute reliable and meaningful statistics and estimates! The data set for variable DW_EU2_PEPA was not processed! It is suggested to collect at least 8 to 10 observations before using these statistical methods! Maximum 780 Median 780 Number of Missing Observations 0 Minimum 780 Mean 780 Page 28 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Warning: This data set only has 1 observations! Data set is too small to compute reliable and meaningful statistics and estimates! The data set for variable DW_EU2_PFO2HxA was not processed! It is suggested to collect at least 8 to 10 observations before using these statistical methods! Maximum 1300 Median 1300 Number of Missing Observations 0 Minimum 1300 Mean 1300 General Statistics Total Number of Observations 1 Number of Distinct Observations 1 If possible, compute and collect Data Quality Objectives (DQO) based sample size and analytical results. DW_EU2_PFO2HxA Warning: This data set only has 1 observations! Data set is too small to compute reliable and meaningful statistics and estimates! The data set for variable DW_EU2_PFMOAA was not processed! It is suggested to collect at least 8 to 10 observations before using these statistical methods! Maximum 410 Median 410 Number of Missing Observations 0 Minimum 410 Mean 410 General Statistics Total Number of Observations 1 Number of Distinct Observations 1 If possible, compute and collect Data Quality Objectives (DQO) based sample size and analytical results. DW_EU2_PFMOAA Warning: This data set only has 1 observations! Data set is too small to compute reliable and meaningful statistics and estimates! The data set for variable DW_EU2_PFESA-BP2 was not processed! It is suggested to collect at least 8 to 10 observations before using these statistical methods! Maximum 130 Median 130 Number of Missing Observations 0 Minimum 130 Mean 130 General Statistics Total Number of Observations 1 Number of Distinct Observations 1 Page 29 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Maximum 16 Median 16 Number of Missing Observations 0 Minimum 16 Mean 16 General Statistics Total Number of Observations 1 Number of Distinct Observations 1 If possible, compute and collect Data Quality Objectives (DQO) based sample size and analytical results. DW_EU2_PFO5DA Warning: This data set only has 1 observations! Data set is too small to compute reliable and meaningful statistics and estimates! The data set for variable DW_EU2_PFO4DA was not processed! It is suggested to collect at least 8 to 10 observations before using these statistical methods! Maximum 60 Median 60 Number of Missing Observations 0 Minimum 60 Mean 60 General Statistics Total Number of Observations 1 Number of Distinct Observations 1 If possible, compute and collect Data Quality Objectives (DQO) based sample size and analytical results. DW_EU2_PFO4DA Warning: This data set only has 1 observations! Data set is too small to compute reliable and meaningful statistics and estimates! The data set for variable DW_EU2_PFO3OA was not processed! It is suggested to collect at least 8 to 10 observations before using these statistical methods! Maximum 160 Median 160 Number of Missing Observations 0 Minimum 160 Mean 160 General Statistics Total Number of Observations 1 Number of Distinct Observations 1 If possible, compute and collect Data Quality Objectives (DQO) based sample size and analytical results. DW_EU2_PFO3OA Page 30 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Data appear Normal at 5% Significance Level Assuming Normal Distribution Lilliefors Test Statistic 0.208 Lilliefors GOF Test 5% Lilliefors Critical Value 0.243 Data appear Normal at 5% Significance Level Normal GOF Test Shapiro Wilk Test Statistic 0.865 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.859 Data appear Normal at 5% Significance Level Coefficient of Variation 0.712 Skewness 1.617 Maximum 1200 Median 395 SD 299.9 Std. Error of Mean 86.57 Number of Missing Observations 0 Minimum 62 Mean 421.1 General Statistics Total Number of Observations 12 Number of Distinct Observations 12 If possible, compute and collect Data Quality Objectives (DQO) based sample size and analytical results. DW_EU3_HFPO-DA Warning: This data set only has 1 observations! Data set is too small to compute reliable and meaningful statistics and estimates! The data set for variable DW_EU2_PMPA was not processed! It is suggested to collect at least 8 to 10 observations before using these statistical methods! Maximum 3100 Median 3100 Number of Missing Observations 0 Minimum 3100 Mean 3100 General Statistics Total Number of Observations 1 Number of Distinct Observations 1 If possible, compute and collect Data Quality Objectives (DQO) based sample size and analytical results. DW_EU2_PMPA Warning: This data set only has 1 observations! Data set is too small to compute reliable and meaningful statistics and estimates! The data set for variable DW_EU2_PFO5DA was not processed! It is suggested to collect at least 8 to 10 observations before using these statistical methods! Page 31 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 95% Hall's Bootstrap UCL 1372 95% Percentile Bootstrap UCL 555.9 95% CLT UCL 563.5 95% Jackknife UCL 576.6 95% Standard Bootstrap UCL 558.5 95% Bootstrap-t UCL 656.5 Nonparametric Distribution Free UCL Statistics Data appear to follow a Discernible Distribution at 5% Significance Level Nonparametric Distribution Free UCLs 95% Chebyshev (MVUE) UCL 880.8 97.5% Chebyshev (MVUE) UCL 1074 99% Chebyshev (MVUE) UCL 1454 Assuming Lognormal Distribution 95% H-UCL 812.4 90% Chebyshev (MVUE) UCL 741.6 Maximum of Logged Data 7.09 SD of logged Data 0.779 Lognormal Statistics Minimum of Logged Data 4.127 Mean of logged Data 5.801 5% Lilliefors Critical Value 0.243 Data appear Lognormal at 5% Significance Level Data appear Lognormal at 5% Significance Level 5% Shapiro Wilk Critical Value 0.859 Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.196 Lilliefors Lognormal GOF Test Lognormal GOF Test Shapiro Wilk Test Statistic 0.955 Shapiro Wilk Lognormal GOF Test Assuming Gamma Distribution 95% Approximate Gamma UCL (use when n>=50)) 630.8 95% Adjusted Gamma UCL (use when n<50) 672.3 Adjusted Level of Significance 0.029 Adjusted Chi Square Value 25.87 MLE Mean (bias corrected) 421.1 MLE Sd (bias corrected) 321 Approximate Chi Square Value (0.05) 27.57 Theta hat (MLE) 189.6 Theta star (bias corrected MLE) 244.7 nu hat (MLE) 53.29 nu star (bias corrected) 41.3 Gamma Statistics k hat (MLE) 2.221 k star (bias corrected MLE) 1.721 5% K-S Critical Value 0.248 Detected data appear Gamma Distributed at 5% Significance Level Detected data appear Gamma Distributed at 5% Significance Level 5% A-D Critical Value 0.741 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.151 Kolmogorov-Smirnov Gamma GOF Test Gamma GOF Test A-D Test Statistic 0.249 Anderson-Darling Gamma GOF Test 95% Student's-t UCL 576.6 95% Adjusted-CLT UCL (Chen-1995) 606.7 95% Modified-t UCL (Johnson-1978) 583.3 95% Normal UCL 95% UCLs (Adjusted for Skewness) Page 32 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Gamma GOF Test Not Enough Data to Perform GOF Test Gamma Statistics k hat (MLE) 1.379 k star (bias corrected MLE) N/A 95% Modified-t UCL (Johnson-1978) 740.4 Assuming Normal Distribution 95% Normal UCL 95% UCLs (Adjusted for Skewness) 95% Student's-t UCL 721.9 95% Adjusted-CLT UCL (Chen-1995) 643.9 5% Lilliefors Critical Value 0.425 Data appear Normal at 5% Significance Level Data appear Normal at 5% Significance Level 5% Shapiro Wilk Critical Value 0.767 Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.287 Lilliefors GOF Test Normal GOF Test Shapiro Wilk Test Statistic 0.93 Shapiro Wilk GOF Test Note: Sample size is small (e.g., <10), if data are collected using ISM approach, you should use guidance provided in ITRC Tech Reg Guide on ISM (ITRC, 2012) to compute statistics of interest. For example, you may want to use Chebyshev UCL to estimate EPC (ITRC, 2012). Chebyshev UCL can be computed using the Nonparametric and All UCL Options of ProUCL 5.1 SD 267 Std. Error of Mean 154.2 Coefficient of Variation 0.983 Skewness 1.248 Minimum 55 Mean 271.7 Maximum 570 Median 190 Total Number of Observations 3 Number of Distinct Observations 3 Number of Missing Observations 0 DW_EU3_PEPA General Statistics Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% Student's-t UCL 576.6 90% Chebyshev(Mean, Sd) UCL 680.8 95% Chebyshev(Mean, Sd) UCL 798.4 97.5% Chebyshev(Mean, Sd) UCL 961.7 99% Chebyshev(Mean, Sd) UCL 1282 95% BCA Bootstrap UCL 605.5 Page 33 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Recommended UCL exceeds the maximum observation Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. Suggested UCL to Use 95% Student's-t UCL 721.9 90% Chebyshev(Mean, Sd) UCL 734.2 95% Chebyshev(Mean, Sd) UCL 943.7 97.5% Chebyshev(Mean, Sd) UCL 1234 99% Chebyshev(Mean, Sd) UCL 1806 95% Hall's Bootstrap UCL N/A 95% Percentile Bootstrap UCL N/A 95% BCA Bootstrap UCL N/A 95% CLT UCL 525.3 95% Jackknife UCL 721.9 95% Standard Bootstrap UCL N/A 95% Bootstrap-t UCL N/A Nonparametric Distribution Free UCL Statistics Data appear to follow a Discernible Distribution at 5% Significance Level Nonparametric Distribution Free UCLs 95% Chebyshev (MVUE) UCL 968.1 97.5% Chebyshev (MVUE) UCL 1269 99% Chebyshev (MVUE) UCL 1859 Assuming Lognormal Distribution 95% H-UCL 1.107E+8 90% Chebyshev (MVUE) UCL 751.7 Maximum of Logged Data 6.346 SD of logged Data 1.17 Lognormal Statistics Minimum of Logged Data 4.007 Mean of logged Data 5.2 5% Lilliefors Critical Value 0.425 Data appear Lognormal at 5% Significance Level Data appear Lognormal at 5% Significance Level 5% Shapiro Wilk Critical Value 0.767 Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.183 Lilliefors Lognormal GOF Test Lognormal GOF Test Shapiro Wilk Test Statistic 0.999 Shapiro Wilk Lognormal GOF Test Assuming Gamma Distribution 95% Approximate Gamma UCL (use when n>=50)) N/A 95% Adjusted Gamma UCL (use when n<50) N/A Adjusted Level of Significance N/A Adjusted Chi Square Value N/A MLE Mean (bias corrected) N/A MLE Sd (bias corrected) N/A Approximate Chi Square Value (0.05) N/A Theta hat (MLE) 197 Theta star (bias corrected MLE) N/A nu hat (MLE) 8.272 nu star (bias corrected) N/A Page 34 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Warning: Data set has only 2 Detected Values. This is not enough to compute meaningful or reliable statistics and estimates. Mean of Logged Detects 2.847 SD of Logged Detects 0.635 Median Detects 19 CV Detects 0.595 Skewness Detects N/A Kurtosis Detects N/A Variance Detects 128 Percent Non-Detects 33.33% Mean Detects 19 SD Detects 11.31 Minimum Detect 11 Minimum Non-Detect 50 Maximum Detect 27 Maximum Non-Detect 50 Number of Detects 2 Number of Non-Detects 1 Number of Distinct Detects 2 Number of Distinct Non-Detects 1 General Statistics Total Number of Observations 3 Number of Distinct Observations 3 The data set for variable DW_EU3_PFESA-BP1 was not processed! DW_EU3_PFESA-BP2 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 3 Number of Distinct Detects 0 Number of Distinct Non-Detects 2 General Statistics Total Number of Observations 3 Number of Distinct Observations 2 The data set for variable DW_EU3_PFECA-G was not processed! DW_EU3_PFESA-BP1 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 3 Number of Distinct Detects 0 Number of Distinct Non-Detects 2 General Statistics Total Number of Observations 3 Number of Distinct Observations 2 DW_EU3_PFECA-G Page 35 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Lognormal GOF Test on Detected Observations Only Not Enough Data to Perform GOF Test Lognormal ROS Statistics Using Imputed Non-Detects Approximate Chi Square Value (N/A, α) N/A Adjusted Chi Square Value (N/A, β) N/A 95% Gamma Approximate KM-UCL (use when n>=50) N/A 95% Gamma Adjusted KM-UCL (use when n<50) N/A Gamma Kaplan-Meier (KM) Statistics Adjusted Level of Significance (β) 0.00136 80% gamma percentile (KM) N/A 90% gamma percentile (KM) N/A 95% gamma percentile (KM) N/A 99% gamma percentile (KM) N/A nu hat (KM) 33.84 nu star (KM) N/A theta hat (KM) 3.368 theta star (KM) N/A Variance (KM) 64 SE of Mean (KM) 8 k hat (KM) 5.641 k star (KM) N/A Estimates of Gamma Parameters using KM Estimates Mean (KM) 19 SD (KM) 8 Mean (detects) 19 Theta hat (MLE) 3.595 Theta star (bias corrected MLE) N/A nu hat (MLE) 21.14 nu star (bias corrected) N/A Gamma GOF Tests on Detected Observations Only Not Enough Data to Perform GOF Test Gamma Statistics on Detected Data Only k hat (MLE) 5.285 k star (bias corrected MLE) N/A 97.5% KM Chebyshev UCL 68.96 99% KM Chebyshev UCL 98.6 95% KM (z) UCL 32.16 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL 43 95% KM Chebyshev UCL 53.87 KM SD 8 95% KM (BCA) UCL N/A 95% KM (t) UCL 42.36 95% KM (Percentile Bootstrap) UCL N/A Not Enough Data to Perform GOF Test Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 19 KM Standard Error of Mean 8 guidance provided in ITRC Tech Reg Guide on ISM (ITRC, 2012) to compute statistics of interest. For example, you may want to use Chebyshev UCL to estimate EPC (ITRC, 2012). Chebyshev UCL can be computed using the Nonparametric and All UCL Options of ProUCL 5.1 Normal GOF Test on Detects Only Note: Sample size is small (e.g., <10), if data are collected using ISM approach, you should use Page 36 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Note: Sample size is small (e.g., <10), if data are collected using ISM approach, you should use guidance provided in ITRC Tech Reg Guide on ISM (ITRC, 2012) to compute statistics of interest. Coefficient of Variation 1.069 Skewness 1.313 Maximum 250 Median 74 SD 121.5 Std. Error of Mean 70.12 Number of Missing Observations 0 Minimum 17 Mean 113.7 General Statistics Total Number of Observations 3 Number of Distinct Observations 3 However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU3_PFMOAA Warning: Recommended UCL exceeds the maximum observation Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). Suggested UCL to Use 95% KM (Chebyshev) UCL 53.87 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Data do not follow a Discernible Distribution at 5% Significance Level SD in Original Scale 8.718 SD in Log Scale 0.498 95% t UCL (Assumes normality) 35.7 95% H-Stat UCL 214.8 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 21 Mean in Log Scale 2.971 KM SD (logged) 0.449 95% Critical H Value (KM-Log) 5.824 KM Standard Error of Mean (logged) 0.449 KM SD (logged) 0.449 95% Critical H Value (KM-Log) 5.824 KM Standard Error of Mean (logged) 0.449 95% H-UCL (KM -Log) 121.1 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.847 KM Geo Mean 17.23 95% H-UCL (Log ROS) 121.1 95% t UCL (assumes normality of ROS data) 32.01 95% Percentile Bootstrap UCL N/A 95% BCA Bootstrap UCL N/A 95% Bootstrap t UCL N/A Mean in Original Scale 18.41 Mean in Log Scale 2.847 SD in Original Scale 8.065 SD in Log Scale 0.449 Page 37 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 95% Chebyshev (MVUE) UCL 439.6 97.5% Chebyshev (MVUE) UCL 579.7 99% Chebyshev (MVUE) UCL 855 Assuming Lognormal Distribution 95% H-UCL 3.138E+9 90% Chebyshev (MVUE) UCL 338.6 Maximum of Logged Data 5.521 SD of logged Data 1.346 Lognormal Statistics Minimum of Logged Data 2.833 Mean of logged Data 4.22 5% Lilliefors Critical Value 0.425 Data appear Lognormal at 5% Significance Level Data appear Lognormal at 5% Significance Level 5% Shapiro Wilk Critical Value 0.767 Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.192 Lilliefors Lognormal GOF Test Lognormal GOF Test Shapiro Wilk Test Statistic 0.997 Shapiro Wilk Lognormal GOF Test Assuming Gamma Distribution 95% Approximate Gamma UCL (use when n>=50)) N/A 95% Adjusted Gamma UCL (use when n<50) N/A Approximate Chi Square Value (0.05) N/A Adjusted Level of Significance N/A Adjusted Chi Square Value N/A nu hat (MLE) 6.662 nu star (bias corrected) N/A MLE Mean (bias corrected) N/A MLE Sd (bias corrected) N/A k hat (MLE) 1.11 k star (bias corrected MLE) N/A Theta hat (MLE) 102.4 Theta star (bias corrected MLE) N/A Gamma GOF Test Not Enough Data to Perform GOF Test Gamma Statistics 95% Student's-t UCL 318.4 95% Adjusted-CLT UCL (Chen-1995) 285.8 95% Modified-t UCL (Johnson-1978) 327.3 Data appear Normal at 5% Significance Level Assuming Normal Distribution 95% Normal UCL 95% UCLs (Adjusted for Skewness) Lilliefors Test Statistic 0.295 Lilliefors GOF Test 5% Lilliefors Critical Value 0.425 Data appear Normal at 5% Significance Level Normal GOF Test Shapiro Wilk Test Statistic 0.92 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.767 Data appear Normal at 5% Significance Level For example, you may want to use Chebyshev UCL to estimate EPC (ITRC, 2012). Chebyshev UCL can be computed using the Nonparametric and All UCL Options of ProUCL 5.1 Page 38 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Data appear Normal at 5% Significance Level Assuming Normal Distribution Lilliefors Test Statistic 0.348 Lilliefors GOF Test 5% Lilliefors Critical Value 0.425 Data appear Normal at 5% Significance Level Normal GOF Test Shapiro Wilk Test Statistic 0.834 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.767 Data appear Normal at 5% Significance Level Note: Sample size is small (e.g., <10), if data are collected using ISM approach, you should use guidance provided in ITRC Tech Reg Guide on ISM (ITRC, 2012) to compute statistics of interest. For example, you may want to use Chebyshev UCL to estimate EPC (ITRC, 2012). Chebyshev UCL can be computed using the Nonparametric and All UCL Options of ProUCL 5.1 Coefficient of Variation 1.38 Skewness 1.648 Maximum 810 Median 110 SD 432.5 Std. Error of Mean 249.7 Number of Missing Observations 0 Minimum 20 Mean 313.3 General Statistics Total Number of Observations 3 Number of Distinct Observations 3 These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU3_PFO2HxA Recommended UCL exceeds the maximum observation Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. Suggested UCL to Use 95% Student's-t UCL 318.4 90% Chebyshev(Mean, Sd) UCL 324 95% Chebyshev(Mean, Sd) UCL 419.3 97.5% Chebyshev(Mean, Sd) UCL 551.6 99% Chebyshev(Mean, Sd) UCL 811.4 95% Hall's Bootstrap UCL N/A 95% Percentile Bootstrap UCL N/A 95% BCA Bootstrap UCL N/A 95% CLT UCL 229 95% Jackknife UCL 318.4 95% Standard Bootstrap UCL N/A 95% Bootstrap-t UCL N/A Nonparametric Distribution Free UCL Statistics Data appear to follow a Discernible Distribution at 5% Significance Level Nonparametric Distribution Free UCLs Page 39 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 90% Chebyshev(Mean, Sd) UCL 1062 95% Chebyshev(Mean, Sd) UCL 1402 97.5% Chebyshev(Mean, Sd) UCL 1873 99% Chebyshev(Mean, Sd) UCL 2798 95% Hall's Bootstrap UCL N/A 95% Percentile Bootstrap UCL N/A 95% BCA Bootstrap UCL N/A 95% CLT UCL 724 95% Jackknife UCL 1042 95% Standard Bootstrap UCL N/A 95% Bootstrap-t UCL N/A Nonparametric Distribution Free UCL Statistics Data appear to follow a Discernible Distribution at 5% Significance Level Nonparametric Distribution Free UCLs 95% Chebyshev (MVUE) UCL 1337 97.5% Chebyshev (MVUE) UCL 1784 99% Chebyshev (MVUE) UCL 2661 Assuming Lognormal Distribution 95% H-UCL 4.009E+16 90% Chebyshev (MVUE) UCL 1015 Maximum of Logged Data 6.697 SD of logged Data 1.853 Lognormal Statistics Minimum of Logged Data 2.996 Mean of logged Data 4.798 5% Lilliefors Critical Value 0.425 Data appear Lognormal at 5% Significance Level Data appear Lognormal at 5% Significance Level 5% Shapiro Wilk Critical Value 0.767 Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.188 Lilliefors Lognormal GOF Test Lognormal GOF Test Shapiro Wilk Test Statistic 0.998 Shapiro Wilk Lognormal GOF Test Assuming Gamma Distribution 95% Approximate Gamma UCL (use when n>=50)) N/A 95% Adjusted Gamma UCL (use when n<50) N/A Approximate Chi Square Value (0.05) N/A Adjusted Level of Significance N/A Adjusted Chi Square Value N/A nu hat (MLE) 3.864 nu star (bias corrected) N/A MLE Mean (bias corrected) N/A MLE Sd (bias corrected) N/A k hat (MLE) 0.644 k star (bias corrected MLE) N/A Theta hat (MLE) 486.5 Theta star (bias corrected MLE) N/A Gamma GOF Test Not Enough Data to Perform GOF Test Gamma Statistics 95% Student's-t UCL 1042 95% Adjusted-CLT UCL (Chen-1995) 977.9 95% Modified-t UCL (Johnson-1978) 1082 95% Normal UCL 95% UCLs (Adjusted for Skewness) Page 40 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! Number of Detects 0 Number of Non-Detects 3 Number of Distinct Detects 0 Number of Distinct Non-Detects 2 DW_EU3_PFO5DA General Statistics Total Number of Observations 3 Number of Distinct Observations 2 Warning: Only one distinct data value was detected! ProUCL (or any other software) should not be used on such a data set! It is suggested to use alternative site specific values determined by the Project Team to estimate environmental parameters (e.g., EPC, BTV). The data set for variable DW_EU3_PFO4DA was not processed! Number of Distinct Detects 1 Number of Distinct Non-Detects 2 Total Number of Observations 3 Number of Distinct Observations 3 Number of Detects 1 Number of Non-Detects 2 DW_EU3_PFO4DA General Statistics Warning: Only one distinct data value was detected! ProUCL (or any other software) should not be used on such a data set! It is suggested to use alternative site specific values determined by the Project Team to estimate environmental parameters (e.g., EPC, BTV). The data set for variable DW_EU3_PFO3OA was not processed! Number of Detects 1 Number of Non-Detects 2 Number of Distinct Detects 1 Number of Distinct Non-Detects 2 General Statistics Total Number of Observations 3 Number of Distinct Observations 3 These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU3_PFO3OA Recommended UCL exceeds the maximum observation Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. Suggested UCL to Use 95% Student's-t UCL 1042 Page 41 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Assuming Gamma Distribution Approximate Chi Square Value (0.05) N/A Adjusted Level of Significance N/A Adjusted Chi Square Value N/A nu hat (MLE) 13.84 nu star (bias corrected) N/A MLE Mean (bias corrected) N/A MLE Sd (bias corrected) N/A k hat (MLE) 2.306 k star (bias corrected MLE) N/A Theta hat (MLE) 438 Theta star (bias corrected MLE) N/A Gamma GOF Test Not Enough Data to Perform GOF Test Gamma Statistics 95% Student's-t UCL 2273 95% Adjusted-CLT UCL (Chen-1995) 1864 95% Modified-t UCL (Johnson-1978) 2295 Data appear Normal at 5% Significance Level Assuming Normal Distribution 95% Normal UCL 95% UCLs (Adjusted for Skewness) Lilliefors Test Statistic 0.214 Lilliefors GOF Test 5% Lilliefors Critical Value 0.425 Data appear Normal at 5% Significance Level Normal GOF Test Shapiro Wilk Test Statistic 0.989 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.767 Data appear Normal at 5% Significance Level Note: Sample size is small (e.g., <10), if data are collected using ISM approach, you should use guidance provided in ITRC Tech Reg Guide on ISM (ITRC, 2012) to compute statistics of interest. For example, you may want to use Chebyshev UCL to estimate EPC (ITRC, 2012). Chebyshev UCL can be computed using the Nonparametric and All UCL Options of ProUCL 5.1 Coefficient of Variation 0.742 Skewness 0.533 Maximum 1800 Median 920 SD 749.1 Std. Error of Mean 432.5 Number of Missing Observations 0 Minimum 310 Mean 1010 General Statistics Total Number of Observations 3 Number of Distinct Observations 3 The data set for variable DW_EU3_PFO5DA was not processed! DW_EU3_PMPA The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Page 42 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Number of Detects 33 Number of Non-Detects 12 Number of Distinct Detects 33 Number of Distinct Non-Detects 5 General Statistics Total Number of Observations 45 Number of Distinct Observations 37 These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU4_HFPO-DA Recommended UCL exceeds the maximum observation Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. Suggested UCL to Use 95% Student's-t UCL 2273 90% Chebyshev(Mean, Sd) UCL 2307 95% Chebyshev(Mean, Sd) UCL 2895 97.5% Chebyshev(Mean, Sd) UCL 3711 99% Chebyshev(Mean, Sd) UCL 5313 95% Hall's Bootstrap UCL N/A 95% Percentile Bootstrap UCL N/A 95% BCA Bootstrap UCL N/A 95% CLT UCL 1721 95% Jackknife UCL 2273 95% Standard Bootstrap UCL N/A 95% Bootstrap-t UCL N/A Nonparametric Distribution Free UCL Statistics Data appear to follow a Discernible Distribution at 5% Significance Level Nonparametric Distribution Free UCLs 95% Chebyshev (MVUE) UCL 3117 97.5% Chebyshev (MVUE) UCL 4021 99% Chebyshev (MVUE) UCL 5799 Assuming Lognormal Distribution 95% H-UCL 1701519 90% Chebyshev (MVUE) UCL 2465 Maximum of Logged Data 7.496 SD of logged Data 0.888 Lognormal Statistics Minimum of Logged Data 5.737 Mean of logged Data 6.685 5% Lilliefors Critical Value 0.425 Data appear Lognormal at 5% Significance Level Data appear Lognormal at 5% Significance Level 5% Shapiro Wilk Critical Value 0.767 Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.229 Lilliefors Lognormal GOF Test Lognormal GOF Test Shapiro Wilk Test Statistic 0.982 Shapiro Wilk Lognormal GOF Test 95% Approximate Gamma UCL (use when n>=50)) N/A 95% Adjusted Gamma UCL (use when n<50) N/A Page 43 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Maximum 1100 Median 30 SD 220 CV 1.586 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 138.7 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Mean (detects) 189.2 Theta hat (MLE) 288.9 Theta star (bias corrected MLE) 307.4 nu hat (MLE) 43.22 nu star (bias corrected) 40.62 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.655 k star (bias corrected MLE) 0.616 K-S Test Statistic 0.109 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.16 Detected data appear Gamma Distributed at 5% Significance Level Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.393 Anderson-Darling GOF Test 5% A-D Critical Value 0.797 Detected data appear Gamma Distributed at 5% Significance Level 97.5% KM Chebyshev UCL 344.5 99% KM Chebyshev UCL 466.4 95% KM (z) UCL 193.1 95% KM Bootstrap t UCL 215.2 90% KM Chebyshev UCL 237.7 95% KM Chebyshev UCL 282.4 KM SD 217.4 95% KM (BCA) UCL 197.6 95% KM (t) UCL 194.2 95% KM (Percentile Bootstrap) UCL 196.5 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 138.9 KM Standard Error of Mean 32.91 Lilliefors Test Statistic 0.214 Lilliefors GOF Test 5% Lilliefors Critical Value 0.152 Detected Data Not Normal at 5% Significance Level Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.757 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.931 Detected Data Not Normal at 5% Significance Level Mean of Logged Detects 4.311 SD of Logged Detects 1.642 Median Detects 78.2 CV Detects 1.259 Skewness Detects 2.124 Kurtosis Detects 5.715 Variance Detects 56706 Percent Non-Detects 26.67% Mean Detects 189.2 SD Detects 238.1 Minimum Detect 0.684 Minimum Non-Detect 1.75 Maximum Detect 1100 Maximum Non-Detect 10 Page 44 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 SD in Original Scale 219.7 SD in Log Scale 2.188 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 139.3 Mean in Log Scale 3.319 KM SD (logged) 2.487 95% Critical H Value (KM-Log) 4.409 KM Standard Error of Mean (logged) 0.377 KM SD (logged) 2.487 95% Critical H Value (KM-Log) 4.409 KM Standard Error of Mean (logged) 0.377 95% H-UCL (KM -Log) 2477 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 3.068 KM Geo Mean 21.5 95% BCA Bootstrap UCL 205.4 95% Bootstrap t UCL 217.8 95% H-UCL (Log ROS) 934 SD in Original Scale 219.5 SD in Log Scale 2.107 95% t UCL (assumes normality of ROS data) 194.5 95% Percentile Bootstrap UCL 194.6 Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 139.5 Mean in Log Scale 3.398 Lilliefors Test Statistic 0.104 Lilliefors GOF Test 5% Lilliefors Critical Value 0.152 Detected Data appear Lognormal at 5% Significance Level Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.953 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.931 Detected Data appear Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 215.5 95% Gamma Adjusted KM-UCL (use when n<50) 218.7 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (35.64, α) 22.98 Adjusted Chi Square Value (35.64, β) 22.64 80% gamma percentile (KM) 224 90% gamma percentile (KM) 393.1 95% gamma percentile (KM) 579.3 99% gamma percentile (KM) 1048 nu hat (KM) 36.76 nu star (KM) 35.64 theta hat (KM) 340.2 theta star (KM) 350.9 Variance (KM) 47266 SE of Mean (KM) 32.91 k hat (KM) 0.408 k star (KM) 0.396 Estimates of Gamma Parameters using KM Estimates Mean (KM) 138.9 SD (KM) 217.4 Approximate Chi Square Value (21.38, α) 11.87 Adjusted Chi Square Value (21.38, β) 11.64 95% Gamma Approximate UCL (use when n>=50) 249.8 95% Gamma Adjusted UCL (use when n<50) 254.9 nu hat (MLE) 21.48 nu star (bias corrected) 21.38 Adjusted Level of Significance (β) 0.0447 k hat (MLE) 0.239 k star (bias corrected MLE) 0.238 Theta hat (MLE) 581.4 Theta star (bias corrected MLE) 584.1 Page 45 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.476 Anderson-Darling GOF Test 97.5% KM Chebyshev UCL 215.3 99% KM Chebyshev UCL 293 95% KM (z) UCL 118.7 95% KM Bootstrap t UCL 129.8 90% KM Chebyshev UCL 147.2 95% KM Chebyshev UCL 175.7 KM SD 99.52 95% KM (BCA) UCL 114.2 95% KM (t) UCL 120.1 95% KM (Percentile Bootstrap) UCL 116.7 Detected Data appear Approximate Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 84.24 KM Standard Error of Mean 20.98 Lilliefors Test Statistic 0.255 Lilliefors GOF Test 5% Lilliefors Critical Value 0.262 Detected Data appear Normal at 5% Significance Level Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.831 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.842 Detected Data Not Normal at 5% Significance Level Mean of Logged Detects 5.077 SD of Logged Detects 0.495 Median Detects 140 CV Detects 0.562 Skewness Detects 1.432 Kurtosis Detects 1.321 Variance Detects 10315 Percent Non-Detects 60% Mean Detects 180.6 SD Detects 101.6 Minimum Detect 86 Minimum Non-Detect 20 Maximum Detect 400 Maximum Non-Detect 20 Number of Detects 10 Number of Non-Detects 15 Number of Distinct Detects 9 Number of Distinct Non-Detects 1 DW_EU4_PEPA General Statistics Total Number of Observations 25 Number of Distinct Observations 10 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use a Adjusted KM-UCL (use when k<=1 and 15 < n < 50 but k<=1) 218.7 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Gamma Distributed at 5% Significance Level 95% t UCL (Assumes normality) 194.3 95% H-Stat UCL 1115 Page 46 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Lilliefors Test Statistic 0.208 Lilliefors GOF Test 5% Lilliefors Critical Value 0.262 Detected Data appear Lognormal at 5% Significance Level Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.934 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.842 Detected Data appear Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 133.4 95% Gamma Adjusted KM-UCL (use when n<50) 137.7 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (32.86, α) 20.76 Adjusted Chi Square Value (32.86, β) 20.1 80% gamma percentile (KM) 138.7 90% gamma percentile (KM) 214.6 95% gamma percentile (KM) 293.3 99% gamma percentile (KM) 482.3 nu hat (KM) 35.83 nu star (KM) 32.86 theta hat (KM) 117.6 theta star (KM) 128.2 Variance (KM) 9903 SE of Mean (KM) 20.98 k hat (KM) 0.717 k star (KM) 0.657 Estimates of Gamma Parameters using KM Estimates Mean (KM) 84.24 SD (KM) 99.52 Approximate Chi Square Value (9.21, α) 3.455 Adjusted Chi Square Value (9.21, β) 3.218 95% Gamma Approximate UCL (use when n>=50) 198.5 95% Gamma Adjusted UCL (use when n<50) 213.2 nu hat (MLE) 8.952 nu star (bias corrected) 9.211 Adjusted Level of Significance (β) 0.0395 k hat (MLE) 0.179 k star (bias corrected MLE) 0.184 Theta hat (MLE) 416 Theta star (bias corrected MLE) 404.3 Maximum 400 Median 3.659 SD 108.4 CV 1.455 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 74.47 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Mean (detects) 180.6 Theta hat (MLE) 41.56 Theta star (bias corrected MLE) 58.1 nu hat (MLE) 86.91 nu star (bias corrected) 62.17 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 4.345 k star (bias corrected MLE) 3.108 K-S Test Statistic 0.235 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.268 Detected data appear Gamma Distributed at 5% Significance Level 5% A-D Critical Value 0.729 Detected data appear Gamma Distributed at 5% Significance Level Page 47 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Number of Detects 0 Number of Non-Detects 25 Number of Distinct Detects 0 Number of Distinct Non-Detects 3 General Statistics Total Number of Observations 25 Number of Distinct Observations 3 Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU4_PFECA-G When a data set follows an approximate (e.g., normal) distribution passing one of the GOF test When applicable, it is suggested to use a UCL based upon a distribution (e.g., gamma) passing both GOF tests in ProUCL Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Suggested UCL to Use 95% KM (t) UCL 120.1 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Normal Distributed at 5% Significance Level SD in Original Scale 105.6 SD in Log Scale 1.42 95% t UCL (Assumes normality) 114.4 95% H-Stat UCL 202.7 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 78.24 Mean in Log Scale 3.412 KM SD (logged) 1.062 95% Critical H Value (KM-Log) 2.575 KM Standard Error of Mean (logged) 0.224 KM SD (logged) 1.062 95% Critical H Value (KM-Log) 2.575 KM Standard Error of Mean (logged) 0.224 95% H-UCL (KM -Log) 141.2 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 3.828 KM Geo Mean 45.98 95% BCA Bootstrap UCL 131.7 95% Bootstrap t UCL 146.7 95% H-UCL (Log ROS) 160.9 SD in Original Scale 96.18 SD in Log Scale 0.982 95% t UCL (assumes normality of ROS data) 127.2 95% Percentile Bootstrap UCL 127.5 Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 94.33 Mean in Log Scale 4.103 Page 48 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 KM SD 11.38 95% KM (BCA) UCL 12.56 95% KM (t) UCL 12.63 95% KM (Percentile Bootstrap) UCL 12.24 Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 8.291 KM Standard Error of Mean 2.537 Lilliefors Test Statistic 0.2 Lilliefors GOF Test 5% Lilliefors Critical Value 0.283 Detected Data appear Normal at 5% Significance Level Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.922 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.818 Detected Data appear Normal at 5% Significance Level Mean of Logged Detects 2.784 SD of Logged Detects 0.725 Median Detects 17.5 CV Detects 0.671 Skewness Detects 0.763 Kurtosis Detects -0.404 Variance Detects 181.7 Percent Non-Detects 68% Mean Detects 20.09 SD Detects 13.48 Minimum Detect 5.6 Minimum Non-Detect 2 Maximum Detect 44 Maximum Non-Detect 50 Number of Detects 8 Number of Non-Detects 17 Number of Distinct Detects 8 Number of Distinct Non-Detects 2 General Statistics Total Number of Observations 25 Number of Distinct Observations 10 The data set for variable DW_EU4_PFESA-BP1 was not processed! DW_EU4_PFESA-BP2 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 25 Number of Distinct Detects 0 Number of Distinct Non-Detects 3 General Statistics Total Number of Observations 25 Number of Distinct Observations 3 The data set for variable DW_EU4_PFECA-G was not processed! DW_EU4_PFESA-BP1 Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Page 49 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 95% Gamma Approximate KM-UCL (use when n>=50) 14.24 95% Gamma Adjusted KM-UCL (use when n<50) 14.79 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (24.69, α) 14.37 Adjusted Chi Square Value (24.69, β) 13.84 80% gamma percentile (KM) 13.61 90% gamma percentile (KM) 22.49 95% gamma percentile (KM) 31.99 99% gamma percentile (KM) 55.39 nu hat (KM) 26.54 nu star (KM) 24.69 theta hat (KM) 15.62 theta star (KM) 16.79 Variance (KM) 129.5 SE of Mean (KM) 2.537 k hat (KM) 0.531 k star (KM) 0.494 Estimates of Gamma Parameters using KM Estimates Mean (KM) 8.291 SD (KM) 11.38 Approximate Chi Square Value (9.88, α) 3.868 Adjusted Chi Square Value (9.88, β) 3.614 95% Gamma Approximate UCL (use when n>=50) 16.81 95% Gamma Adjusted UCL (use when n<50) 17.99 nu hat (MLE) 9.714 nu star (bias corrected) 9.881 Adjusted Level of Significance (β) 0.0395 k hat (MLE) 0.194 k star (bias corrected MLE) 0.198 Theta hat (MLE) 33.86 Theta star (bias corrected MLE) 33.29 Maximum 44 Median 0.01 SD 11.96 CV 1.817 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 6.578 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Mean (detects) 20.09 Theta hat (MLE) 8.137 Theta star (bias corrected MLE) 12.35 nu hat (MLE) 39.5 nu star (bias corrected) 26.02 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 2.469 k star (bias corrected MLE) 1.626 K-S Test Statistic 0.162 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.297 Detected data appear Gamma Distributed at 5% Significance Level Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.229 Anderson-Darling GOF Test 5% A-D Critical Value 0.723 Detected data appear Gamma Distributed at 5% Significance Level 97.5% KM Chebyshev UCL 24.13 99% KM Chebyshev UCL 33.53 95% KM (z) UCL 12.46 95% KM Bootstrap t UCL 14.22 90% KM Chebyshev UCL 15.9 95% KM Chebyshev UCL 19.35 Page 50 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Number of Detects 12 Number of Non-Detects 13 DW_EU4_PFMOAA General Statistics Total Number of Observations 25 Number of Distinct Observations 13 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 12.63 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 12.46 SD in Log Scale 1.492 95% t UCL (Assumes normality) 13.29 95% H-Stat UCL 25.31 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 9.028 Mean in Log Scale 1.148 KM SD (logged) 1.073 95% Critical H Value (KM-Log) 2.589 KM Standard Error of Mean (logged) 0.239 KM SD (logged) 1.073 95% Critical H Value (KM-Log) 2.589 KM Standard Error of Mean (logged) 0.239 95% H-UCL (KM -Log) 12.98 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.42 KM Geo Mean 4.139 95% BCA Bootstrap UCL 12.44 95% Bootstrap t UCL 13.92 95% H-UCL (Log ROS) 23.19 SD in Original Scale 11.33 SD in Log Scale 1.464 95% t UCL (assumes normality of ROS data) 11.73 95% Percentile Bootstrap UCL 11.75 Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 7.856 Mean in Log Scale 1.134 Lilliefors Test Statistic 0.164 Lilliefors GOF Test 5% Lilliefors Critical Value 0.283 Detected Data appear Lognormal at 5% Significance Level Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.963 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.818 Detected Data appear Lognormal at 5% Significance Level Page 51 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Maximum 270 Median 5.614 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 48.43 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Mean (detects) 100.4 Theta hat (MLE) 71.35 Theta star (bias corrected MLE) 90.38 nu hat (MLE) 33.77 nu star (bias corrected) 26.66 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.407 k star (bias corrected MLE) 1.111 K-S Test Statistic 0.194 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.25 Detected data appear Gamma Distributed at 5% Significance Level Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.559 Anderson-Darling GOF Test 5% A-D Critical Value 0.748 Detected data appear Gamma Distributed at 5% Significance Level 97.5% KM Chebyshev UCL 139.1 99% KM Chebyshev UCL 191.5 95% KM (z) UCL 74.06 95% KM Bootstrap t UCL 82.25 90% KM Chebyshev UCL 93.23 95% KM Chebyshev UCL 112.4 KM SD 67.71 95% KM (BCA) UCL 74.42 95% KM (t) UCL 74.99 95% KM (Percentile Bootstrap) UCL 73.83 Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 50.8 KM Standard Error of Mean 14.14 Lilliefors Test Statistic 0.169 Lilliefors GOF Test 5% Lilliefors Critical Value 0.243 Detected Data appear Normal at 5% Significance Level Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.927 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.859 Detected Data appear Normal at 5% Significance Level Mean of Logged Detects 4.214 SD of Logged Detects 1.15 Median Detects 92 CV Detects 0.722 Skewness Detects 1 Kurtosis Detects 1.753 Variance Detects 5256 Percent Non-Detects 52% Mean Detects 100.4 SD Detects 72.5 Minimum Detect 6.7 Minimum Non-Detect 5 Maximum Detect 270 Maximum Non-Detect 5 Number of Distinct Detects 12 Number of Distinct Non-Detects 1 Page 52 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 49.5 Mean in Log Scale 2.499 KM SD (logged) 1.508 95% Critical H Value (KM-Log) 3.207 KM Standard Error of Mean (logged) 0.315 KM SD (logged) 1.508 95% Critical H Value (KM-Log) 3.207 KM Standard Error of Mean (logged) 0.315 95% H-UCL (KM -Log) 146.1 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.859 KM Geo Mean 17.45 95% BCA Bootstrap UCL 78.81 95% Bootstrap t UCL 82.56 95% H-UCL (Log ROS) 287.9 SD in Original Scale 68.94 SD in Log Scale 1.788 95% t UCL (assumes normality of ROS data) 74.73 95% Percentile Bootstrap UCL 74.84 Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 51.14 Mean in Log Scale 2.735 Lilliefors Test Statistic 0.243 Lilliefors GOF Test 5% Lilliefors Critical Value 0.243 Detected Data Not Lognormal at 5% Significance Level Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.816 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.859 Detected Data Not Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 85.78 95% Gamma Adjusted KM-UCL (use when n<50) 88.99 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (26.10, α) 15.45 Adjusted Chi Square Value (26.10, β) 14.9 80% gamma percentile (KM) 83.56 90% gamma percentile (KM) 136.2 95% gamma percentile (KM) 192.2 99% gamma percentile (KM) 329.2 nu hat (KM) 28.14 nu star (KM) 26.1 theta hat (KM) 90.25 theta star (KM) 97.32 Variance (KM) 4585 SE of Mean (KM) 14.14 k hat (KM) 0.563 k star (KM) 0.522 Estimates of Gamma Parameters using KM Estimates Mean (KM) 50.8 SD (KM) 67.71 Approximate Chi Square Value (9.52, α) 3.645 Adjusted Chi Square Value (9.52, β) 3.4 95% Gamma Approximate UCL (use when n>=50) 126.5 95% Gamma Adjusted UCL (use when n<50) 135.6 nu hat (MLE) 9.305 nu star (bias corrected) 9.521 Adjusted Level of Significance (β) 0.0395 k hat (MLE) 0.186 k star (bias corrected MLE) 0.19 Theta hat (MLE) 260.2 Theta star (bias corrected MLE) 254.3 SD 70.77 CV 1.461 Page 53 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Gamma GOF Tests on Detected Observations Only 97.5% KM Chebyshev UCL 386.6 99% KM Chebyshev UCL 538.7 95% KM (z) UCL 197.9 95% KM Bootstrap t UCL 225.6 90% KM Chebyshev UCL 253.5 95% KM Chebyshev UCL 309.3 KM SD 197.7 95% KM (BCA) UCL 202.4 95% KM (t) UCL 200.6 95% KM (Percentile Bootstrap) UCL 200 Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 130.4 KM Standard Error of Mean 41.03 Lilliefors Test Statistic 0.163 Lilliefors GOF Test 5% Lilliefors Critical Value 0.226 Detected Data appear Normal at 5% Significance Level Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.892 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.874 Detected Data appear Normal at 5% Significance Level Mean of Logged Detects 4.491 SD of Logged Detects 1.928 Median Detects 195 CV Detects 0.969 Skewness Detects 1.003 Kurtosis Detects 0.39 Variance Detects 50248 Percent Non-Detects 44% Mean Detects 231.3 SD Detects 224.2 Minimum Detect 2.1 Minimum Non-Detect 2 Maximum Detect 730 Maximum Non-Detect 2 Number of Detects 14 Number of Non-Detects 11 Number of Distinct Detects 13 Number of Distinct Non-Detects 1 DW_EU4_PFO2HxA General Statistics Total Number of Observations 25 Number of Distinct Observations 14 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 74.99 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 70.01 SD in Log Scale 1.853 95% t UCL (Assumes normality) 73.45 95% H-Stat UCL 278.8 Page 54 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Lilliefors Test Statistic 0.275 Lilliefors GOF Test Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.851 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.874 Detected Data Not Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 238.3 95% Gamma Adjusted KM-UCL (use when n<50) 248.7 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (20.48, α) 11.2 Adjusted Chi Square Value (20.48, β) 10.74 80% gamma percentile (KM) 211 90% gamma percentile (KM) 366.8 95% gamma percentile (KM) 537.4 99% gamma percentile (KM) 965.4 nu hat (KM) 21.75 nu star (KM) 20.48 theta hat (KM) 299.7 theta star (KM) 318.4 Variance (KM) 39084 SE of Mean (KM) 41.03 k hat (KM) 0.435 k star (KM) 0.41 Estimates of Gamma Parameters using KM Estimates Mean (KM) 130.4 SD (KM) 197.7 Approximate Chi Square Value (8.91, α) 3.271 Adjusted Chi Square Value (8.91, β) 3.041 95% Gamma Approximate UCL (use when n>=50) 352.7 95% Gamma Adjusted UCL (use when n<50) 379.3 nu hat (MLE) 8.606 nu star (bias corrected) 8.907 Adjusted Level of Significance (β) 0.0395 k hat (MLE) 0.172 k star (bias corrected MLE) 0.178 Theta hat (MLE) 752.5 Theta star (bias corrected MLE) 727.1 Maximum 730 Median 4.4 SD 202.4 CV 1.562 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 129.5 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Mean (detects) 231.3 Theta hat (MLE) 360.1 Theta star (bias corrected MLE) 418.8 nu hat (MLE) 17.98 nu star (bias corrected) 15.46 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.642 k star (bias corrected MLE) 0.552 K-S Test Statistic 0.199 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.239 Detected data appear Gamma Distributed at 5% Significance Level A-D Test Statistic 0.536 Anderson-Darling GOF Test 5% A-D Critical Value 0.78 Detected data appear Gamma Distributed at 5% Significance Level Page 55 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Variance Detects 639 Percent Non-Detects 64% Mean Detects 30.29 SD Detects 25.28 Minimum Detect 7.8 Minimum Non-Detect 2 Maximum Detect 88 Maximum Non-Detect 50 Number of Detects 9 Number of Non-Detects 16 Number of Distinct Detects 8 Number of Distinct Non-Detects 2 DW_EU4_PFO3OA General Statistics Total Number of Observations 25 Number of Distinct Observations 10 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 200.6 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 202.1 SD in Log Scale 2.681 95% t UCL (Assumes normality) 199.1 95% H-Stat UCL 7372 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 130 Mean in Log Scale 2.515 KM SD (logged) 2.342 95% Critical H Value (KM-Log) 4.538 KM Standard Error of Mean (logged) 0.486 KM SD (logged) 2.342 95% Critical H Value (KM-Log) 4.538 KM Standard Error of Mean (logged) 0.486 95% H-UCL (KM -Log) 2283 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.82 KM Geo Mean 16.78 95% BCA Bootstrap UCL 209.9 95% Bootstrap t UCL 222 95% H-UCL (Log ROS) 19881 SD in Original Scale 201.8 SD in Log Scale 2.899 95% t UCL (assumes normality of ROS data) 199.4 95% Percentile Bootstrap UCL 192.4 Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 130.3 Mean in Log Scale 2.457 5% Lilliefors Critical Value 0.226 Detected Data Not Lognormal at 5% Significance Level Page 56 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 nu hat (MLE) 8.9 nu star (bias corrected) 9.165 Adjusted Level of Significance (β) 0.0395 k hat (MLE) 0.178 k star (bias corrected MLE) 0.183 Theta hat (MLE) 61.3 Theta star (bias corrected MLE) 59.52 Maximum 88 Median 0.01 SD 20.81 CV 1.907 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 10.91 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Mean (detects) 30.29 Theta hat (MLE) 15.59 Theta star (bias corrected MLE) 22.12 nu hat (MLE) 34.97 nu star (bias corrected) 24.65 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.943 k star (bias corrected MLE) 1.369 K-S Test Statistic 0.172 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.283 Detected data appear Gamma Distributed at 5% Significance Level Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.287 Anderson-Darling GOF Test 5% A-D Critical Value 0.73 Detected data appear Gamma Distributed at 5% Significance Level 97.5% KM Chebyshev UCL 38.91 99% KM Chebyshev UCL 54.59 95% KM (z) UCL 19.44 95% KM Bootstrap t UCL 23.84 90% KM Chebyshev UCL 25.17 95% KM Chebyshev UCL 30.92 KM SD 19.78 95% KM (BCA) UCL 20.45 95% KM (t) UCL 19.72 95% KM (Percentile Bootstrap) UCL 19.56 Detected Data appear Approximate Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 12.48 KM Standard Error of Mean 4.232 Lilliefors Test Statistic 0.25 Lilliefors GOF Test 5% Lilliefors Critical Value 0.274 Detected Data appear Normal at 5% Significance Level Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.824 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.829 Detected Data Not Normal at 5% Significance Level Mean of Logged Detects 3.132 SD of Logged Detects 0.795 Median Detects 21 CV Detects 0.835 Skewness Detects 1.702 Kurtosis Detects 3.141 Page 57 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics SD in Original Scale 20.51 SD in Log Scale 1.636 95% t UCL (Assumes normality) 19.52 95% H-Stat UCL 41.71 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 12.5 Mean in Log Scale 1.256 KM SD (logged) 1.262 95% Critical H Value (KM-Log) 2.847 KM Standard Error of Mean (logged) 0.272 KM SD (logged) 1.262 95% Critical H Value (KM-Log) 2.847 KM Standard Error of Mean (logged) 0.272 95% H-UCL (KM -Log) 22.94 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.603 KM Geo Mean 4.966 95% BCA Bootstrap UCL 22.04 95% Bootstrap t UCL 25.61 95% H-UCL (Log ROS) 32.86 SD in Original Scale 19.82 SD in Log Scale 1.387 95% t UCL (assumes normality of ROS data) 19.68 95% Percentile Bootstrap UCL 19.8 Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 12.9 Mean in Log Scale 1.672 Lilliefors Test Statistic 0.135 Lilliefors GOF Test 5% Lilliefors Critical Value 0.274 Detected Data appear Lognormal at 5% Significance Level Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.954 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.829 Detected Data appear Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 23.51 95% Gamma Adjusted KM-UCL (use when n<50) 24.59 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (18.84, α) 9.998 Adjusted Chi Square Value (18.84, β) 9.56 80% gamma percentile (KM) 19.98 90% gamma percentile (KM) 35.61 95% gamma percentile (KM) 52.92 99% gamma percentile (KM) 96.74 nu hat (KM) 19.89 nu star (KM) 18.84 theta hat (KM) 31.37 theta star (KM) 33.12 Variance (KM) 391.4 SE of Mean (KM) 4.232 k hat (KM) 0.398 k star (KM) 0.377 Estimates of Gamma Parameters using KM Estimates Mean (KM) 12.48 SD (KM) 19.78 Approximate Chi Square Value (9.16, α) 3.427 Adjusted Chi Square Value (9.16, β) 3.191 95% Gamma Approximate UCL (use when n>=50) 29.18 95% Gamma Adjusted UCL (use when n<50) 31.34 Page 58 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.302 Anderson-Darling GOF Test 5% A-D Critical Value 0.712 Detected data appear Gamma Distributed at 5% Significance Level 97.5% KM Chebyshev UCL 7.38 99% KM Chebyshev UCL 9.819 95% KM (z) UCL 4.352 95% KM Bootstrap t UCL 4.732 90% KM Chebyshev UCL 5.244 95% KM Chebyshev UCL 6.139 KM SD 2.923 95% KM (BCA) UCL 4.639 95% KM (t) UCL 4.396 95% KM (Percentile Bootstrap) UCL 4.405 Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 3.27 KM Standard Error of Mean 0.658 Lilliefors Test Statistic 0.25 Lilliefors GOF Test 5% Lilliefors Critical Value 0.304 Detected Data appear Normal at 5% Significance Level Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.933 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.803 Detected Data appear Normal at 5% Significance Level Mean of Logged Detects 1.727 SD of Logged Detects 0.659 Median Detects 4.9 CV Detects 0.561 Skewness Detects 0.284 Kurtosis Detects -1.462 Variance Detects 13.82 Percent Non-Detects 72% Mean Detects 6.629 SD Detects 3.718 Minimum Detect 1.8 Minimum Non-Detect 2 Maximum Detect 12 Maximum Non-Detect 50 Number of Detects 7 Number of Non-Detects 18 Number of Distinct Detects 7 Number of Distinct Non-Detects 2 General Statistics Total Number of Observations 25 Number of Distinct Observations 9 Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU4_PFO4DA When a data set follows an approximate (e.g., normal) distribution passing one of the GOF test When applicable, it is suggested to use a UCL based upon a distribution (e.g., gamma) passing both GOF tests in ProUCL Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Suggested UCL to Use 95% KM (t) UCL 19.72 Detected Data appear Approximate Normal Distributed at 5% Significance Level Page 59 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.191 Lilliefors GOF Test 5% Lilliefors Critical Value 0.304 Detected Data appear Lognormal at 5% Significance Level Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.93 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.803 Detected Data appear Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 4.594 95% Gamma Adjusted KM-UCL (use when n<50) 4.704 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (56.40, α) 40.14 Adjusted Chi Square Value (56.40, β) 39.2 80% gamma percentile (KM) 5.207 90% gamma percentile (KM) 7.308 95% gamma percentile (KM) 9.389 99% gamma percentile (KM) 14.18 nu hat (KM) 62.57 nu star (KM) 56.4 theta hat (KM) 2.613 theta star (KM) 2.899 Variance (KM) 8.542 SE of Mean (KM) 0.658 k hat (KM) 1.251 k star (KM) 1.128 Estimates of Gamma Parameters using KM Estimates Mean (KM) 3.27 SD (KM) 2.923 Approximate Chi Square Value (18.20, α) 9.535 Adjusted Chi Square Value (18.20, β) 9.108 95% Gamma Approximate UCL (use when n>=50) 5.151 95% Gamma Adjusted UCL (use when n<50) 5.392 nu hat (MLE) 19.17 nu star (bias corrected) 18.2 Adjusted Level of Significance (β) 0.0395 k hat (MLE) 0.383 k star (bias corrected MLE) 0.364 Theta hat (MLE) 7.04 Theta star (bias corrected MLE) 7.414 Maximum 12 Median 1.8 SD 3.336 CV 1.236 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 2.699 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Mean (detects) 6.629 Theta hat (MLE) 2.068 Theta star (bias corrected MLE) 3.441 nu hat (MLE) 44.87 nu star (bias corrected) 26.97 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 3.205 k star (bias corrected MLE) 1.927 K-S Test Statistic 0.205 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.314 Detected data appear Gamma Distributed at 5% Significance Level Page 60 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 The data set for variable DW_EU4_PFO5DA was not processed! Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 25 Number of Distinct Detects 0 Number of Distinct Non-Detects 3 DW_EU4_PFO5DA General Statistics Total Number of Observations 25 Number of Distinct Observations 3 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 4.396 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 6.926 SD in Log Scale 1.127 95% t UCL (Assumes normality) 6.866 95% H-Stat UCL 7.302 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 4.496 Mean in Log Scale 0.741 KM SD (logged) 0.623 95% Critical H Value (KM-Log) 2.07 KM Standard Error of Mean (logged) 0.14 KM SD (logged) 0.623 95% Critical H Value (KM-Log) 2.07 KM Standard Error of Mean (logged) 0.14 95% H-UCL (KM -Log) 4.022 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.935 KM Geo Mean 2.546 95% BCA Bootstrap UCL 4.428 95% Bootstrap t UCL 4.685 95% H-UCL (Log ROS) 4.778 SD in Original Scale 2.991 SD in Log Scale 0.843 95% t UCL (assumes normality of ROS data) 4.208 95% Percentile Bootstrap UCL 4.241 Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 3.185 Mean in Log Scale 0.812 Page 61 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Gamma ROS Statistics using Imputed Non-Detects Mean (detects) 422.9 Theta hat (MLE) 579.2 Theta star (bias corrected MLE) 666 nu hat (MLE) 23.36 nu star (bias corrected) 20.32 Detected data follow Appr. Gamma Distribution at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.73 k star (bias corrected MLE) 0.635 K-S Test Statistic 0.211 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.224 Detected data appear Gamma Distributed at 5% Significance Level Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.835 Anderson-Darling GOF Test 5% A-D Critical Value 0.776 Detected Data Not Gamma Distributed at 5% Significance Level 97.5% KM Chebyshev UCL 779 99% KM Chebyshev UCL 1079 95% KM (z) UCL 407.2 95% KM Bootstrap t UCL 468.6 90% KM Chebyshev UCL 516.7 95% KM Chebyshev UCL 626.6 KM SD 391.3 95% KM (BCA) UCL 418.1 95% KM (t) UCL 412.5 95% KM (Percentile Bootstrap) UCL 420 Detected Data appear Approximate Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 274.2 KM Standard Error of Mean 80.83 Lilliefors Test Statistic 0.207 Lilliefors GOF Test 5% Lilliefors Critical Value 0.213 Detected Data appear Normal at 5% Significance Level Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.842 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.887 Detected Data Not Normal at 5% Significance Level Mean of Logged Detects 5.224 SD of Logged Detects 1.591 Median Detects 425 CV Detects 1.03 Skewness Detects 1.393 Kurtosis Detects 2.358 Variance Detects 189766 Percent Non-Detects 36% Mean Detects 422.9 SD Detects 435.6 Minimum Detect 15 Minimum Non-Detect 10 Maximum Detect 1600 Maximum Non-Detect 10 Number of Detects 16 Number of Non-Detects 9 Number of Distinct Detects 15 Number of Distinct Non-Detects 1 General Statistics Total Number of Observations 25 Number of Distinct Observations 16 DW_EU4_PMPA Page 62 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 KM SD (logged) 1.867 95% Critical H Value (KM-Log) 3.763 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 4.172 KM Geo Mean 64.87 95% BCA Bootstrap UCL 439.2 95% Bootstrap t UCL 496.7 95% H-UCL (Log ROS) 5817 SD in Original Scale 400.3 SD in Log Scale 2.314 95% t UCL (assumes normality of ROS data) 409.9 95% Percentile Bootstrap UCL 406.8 Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 273 Mean in Log Scale 3.872 Lilliefors Test Statistic 0.253 Lilliefors GOF Test 5% Lilliefors Critical Value 0.213 Detected Data Not Lognormal at 5% Significance Level Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.856 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.887 Detected Data Not Lognormal at 5% Significance Level 95% Gamma Approximate KM-UCL (use when n>=50) 482.2 95% Gamma Adjusted KM-UCL (use when n<50) 501.8 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (22.94, α) 13.05 Adjusted Chi Square Value (22.94, β) 12.54 80% gamma percentile (KM) 448.2 90% gamma percentile (KM) 755 95% gamma percentile (KM) 1086 99% gamma percentile (KM) 1907 nu hat (KM) 24.56 nu star (KM) 22.94 theta hat (KM) 558.4 theta star (KM) 597.7 Variance (KM) 153135 SE of Mean (KM) 80.83 k hat (KM) 0.491 k star (KM) 0.459 Estimates of Gamma Parameters using KM Estimates Mean (KM) 274.2 SD (KM) 391.3 Approximate Chi Square Value (9.67, α) 3.738 Adjusted Chi Square Value (9.67, β) 3.49 95% Gamma Approximate UCL (use when n>=50) 700.3 95% Gamma Adjusted UCL (use when n<50) 750.2 nu hat (MLE) 9.477 nu star (bias corrected) 9.673 Adjusted Level of Significance (β) 0.0395 k hat (MLE) 0.19 k star (bias corrected MLE) 0.193 Theta hat (MLE) 1428 Theta star (bias corrected MLE) 1399 Maximum 1600 Median 33 SD 401.9 CV 1.485 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 270.6 GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Page 63 of 64 December 2019 Output C-7 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 1 through 4 Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. When a data set follows an approximate (e.g., normal) distribution passing one of the GOF test When applicable, it is suggested to use a UCL based upon a distribution (e.g., gamma) passing both GOF tests in ProUCL Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Suggested UCL to Use 95% KM (t) UCL 412.5 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Normal Distributed at 5% Significance Level SD in Original Scale 400.6 SD in Log Scale 2.172 95% t UCL (Assumes normality) 409.5 95% H-Stat UCL 3528 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 272.4 Mean in Log Scale 3.923 KM SD (logged) 1.867 95% Critical H Value (KM-Log) 3.763 KM Standard Error of Mean (logged) 0.386 KM Standard Error of Mean (logged) 0.386 95% H-UCL (KM -Log) 1554 Page 64 of 64 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 UCL Statistics for Data Sets with Non-Detects User Selected Options Date/Time of Computation ProUCL 5.112/6/2019 11:46:40 AM From File WorkSheet.xls Full Precision OFF Confidence Coefficient 95% Number of Bootstrap Operations 2000 DW_EU5_HFPO-DA Page 1 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 General Statistics Total Number of Observations 110 Number of Distinct Observations 75 Number of Detects 88 Number of Non-Detects 22 Number of Distinct Detects 72 Number of Distinct Non-Detects 4 557.2 Minimum Detect 1.85 Minimum Non-Detect 0.647 Maximum Detect 3400 Maximum Non-Detect 5.4 2.914 Kurtosis Detects 11.16 Variance Detects 310506 Percent Non-Detects 20% Mean Detects 388.6 SD Detects Mean of Logged Detects 4.867 SD of Logged Detects 1.79 Median Detects 150.5 CV Detects 1.434 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.689 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.244 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0946 Detected Data Not Normal at 5% Significance Level 395.8 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 311.3 KM Standard Error of Mean 49.78 460.6 95% KM Chebyshev UCL 528.3 KM SD 519.2 95% KM (BCA) UCL 394.3 95% KM (t) UCL 393.9 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 622.2 99% KM Chebyshev UCL 806.6 95% KM (z) UCL 393.2 95% KM Bootstrap t UCL 421.6 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.507 Anderson-Darling GOF Test 5% A-D Critical Value 0.812 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.071 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.1 Detected data appear Gamma Distributed at 5% Significance Level 100 nu star (bias corrected) 97.96 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.568 k star (bias corrected MLE) 0.557 Mean (detects) 388.6 Theta hat (MLE) 683.7 Theta star (bias corrected MLE) 698.2 nu hat (MLE) Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs Page 2 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 310.9 This is especially true when the sample size is small. Maximum 3400 Median 90.5 SD 521.7 CV 1.678 k hat (MLE) 0.256 k star (bias corrected MLE) 0.255 Theta hat (MLE) 1216 Theta star (bias corrected MLE) 1220 nu hat (MLE) 56.27 nu star (bias corrected) 56.06 Adjusted Level of Significance (β) 0.0478 Approximate Chi Square Value (56.06, α) 39.86 Adjusted Chi Square Value (56.06, β) 39.67 95% Gamma Approximate UCL (use when n>=50) 437.4 95% Gamma Adjusted UCL (use when n<50) 439.3 Estimates of Gamma Parameters using KM Estimates Mean (KM) 311.3 SD (KM) 519.2 Variance (KM) 269527 SE of Mean (KM) 49.78 k hat (KM) 0.359 k star (KM) 0.356 nu hat (KM) 79.08 nu star (KM) 78.26 theta hat (KM) 865.9 theta star (KM) 875 58.66 80% gamma percentile (KM) 494.2 90% gamma percentile (KM) 896.6 95% gamma percentile (KM) 1346 99% gamma percentile (KM) 2491 95% Gamma Approximate KM-UCL (use when n>=50) 413.7 95% Gamma Adjusted KM-UCL (use when n<50) 415.3 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (78.26, α) 58.88 Adjusted Chi Square Value (78.26, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.944 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.0016 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0941 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0946 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 311.9 Mean in Log Scale 4.149 SD in Original Scale 521.2 SD in Log Scale 2.193 95% t UCL (assumes normality of ROS data) 394.3 95% Percentile Bootstrap UCL 396.7 95% BCA Bootstrap UCL 418.3 95% Bootstrap t UCL 418.5 95% H-UCL (Log ROS) 1479 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 3.986 KM Geo Mean 53.83 KM SD (logged) 2.385 95% Critical H Value (KM-Log) 3.798 KM Standard Error of Mean (logged) 0.233 95% H-UCL (KM -Log) 2204 KM SD (logged) 2.385 95% Critical H Value (KM-Log) 3.798 KM Standard Error of Mean (logged) 0.233 Page 3 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 4.01 393.8 95% H-Stat UCL 2066 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 311.3 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Gamma Distributed at 5% Significance Level SD in Original Scale 521.5 SD in Log Scale 2.356 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM Approximate Gamma UCL 413.7 DW_EU5_PEPA General Statistics Total Number of Observations 67 Number of Distinct Observations 26 Number of Detects 27 Number of Non-Detects 40 Number of Distinct Detects 20 Number of Distinct Non-Detects 6 472.7 Minimum Detect 80 Minimum Non-Detect 2 Maximum Detect 2400 Maximum Non-Detect 10000 3.473 Kurtosis Detects 13.5 Variance Detects 223484 Percent Non-Detects 59.7% Mean Detects 371.4 SD Detects Mean of Logged Detects 5.545 SD of Logged Detects 0.764 Median Detects 240 CV Detects 1.273 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.538 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.923 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.383 Lilliefors GOF Test 5% Lilliefors Critical Value 0.167 Detected Data Not Normal at 5% Significance Level 233.4 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 155 KM Standard Error of Mean 43.74 KM SD 348 95% KM (BCA) UCL 245.8 95% KM (t) UCL 227.9 95% KM (Percentile Bootstrap) UCL 95% KM (z) UCL 226.9 95% KM Bootstrap t UCL 287.1 Page 4 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 286.2 95% KM Chebyshev UCL 345.6 97.5% KM Chebyshev UCL 428.1 99% KM Chebyshev UCL 590.1 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 2.282 Anderson-Darling GOF Test 5% A-D Critical Value 0.763 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.318 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.171 Detected Data Not Gamma Distributed at 5% Significance Level 80.45 nu star (bias corrected) 72.84 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.49 k star (bias corrected MLE) 1.349 Mean (detects) 371.4 Theta hat (MLE) 249.3 Theta star (bias corrected MLE) 275.3 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 149.7 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 2400 Median 0.01 SD 348.9 CV 2.331 k hat (MLE) 0.14 k star (bias corrected MLE) 0.144 Theta hat (MLE) 1065 Theta star (bias corrected MLE) 1038 nu hat (MLE) 18.82 nu star (bias corrected) 19.31 Adjusted Level of Significance (β) 0.0464 Approximate Chi Square Value (19.31, α) 10.35 Adjusted Chi Square Value (19.31, β) 10.2 95% Gamma Approximate UCL (use when n>=50) 279.4 95% Gamma Adjusted UCL (use when n<50) 283.3 Estimates of Gamma Parameters using KM Estimates Mean (KM) 155 SD (KM) 348 Variance (KM) 121090 SE of Mean (KM) 43.74 k hat (KM) 0.198 k star (KM) 0.199 nu hat (KM) 26.58 nu star (KM) 26.72 theta hat (KM) 781.4 theta star (KM) 777.2 15.75 80% gamma percentile (KM) 203.9 90% gamma percentile (KM) 468.7 95% gamma percentile (KM) 799.1 99% gamma percentile (KM) 1709 95% Gamma Approximate KM-UCL (use when n>=50) 259.9 95% Gamma Adjusted KM-UCL (use when n<50) 262.9 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (26.72, α) 15.93 Adjusted Chi Square Value (26.72, β) Page 5 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.887 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.923 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.25 Lilliefors GOF Test 5% Lilliefors Critical Value 0.167 Detected Data Not Lognormal at 5% Significance Level Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 173.8 Mean in Log Scale 4.302 SD in Original Scale 339.3 SD in Log Scale 1.281 95% t UCL (assumes normality of ROS data) 242.9 95% Percentile Bootstrap UCL 247.9 95% BCA Bootstrap UCL 277.4 95% Bootstrap t UCL 323 95% H-UCL (Log ROS) 235.3 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.72 KM Geo Mean 15.18 KM SD (logged) 2.437 95% Critical H Value (KM-Log) 3.118 KM Standard Error of Mean (logged) 0.309 95% H-UCL (KM -Log) 753.8 3.789 KM SD (logged) 2.437 95% Critical H Value (KM-Log) 3.118 KM Standard Error of Mean (logged) 0.309 378.6 95% H-Stat UCL 428.4 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 239 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Data do not follow a Discernible Distribution at 5% Significance Level SD in Original Scale 685 SD in Log Scale 1.819 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (Chebyshev) UCL 345.6 DW_EU5_PFECA-G General Statistics Total Number of Observations 67 Number of Distinct Observations 5 Number of Detects 0 Number of Non-Detects 67 Number of Distinct Detects 0 Number of Distinct Non-Detects 5 Page 6 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 The data set for variable DW_EU5_PFECA-G was not processed! DW_EU5_PFESA-BP1 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). 0 Number of Distinct Non-Detects 7 General Statistics Total Number of Observations 67 Number of Distinct Observations 7 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 67 Number of Distinct Detects General Statistics Total Number of Observations 67 Number of Distinct Observations 27 The data set for variable DW_EU5_PFESA-BP1 was not processed! DW_EU5_PFESA-BP2 Number of Detects 23 Number of Non-Detects 44 Number of Distinct Detects 20 Number of Distinct Non-Detects 7 20.99 Minimum Detect 1.5 Minimum Non-Detect 1.1 Maximum Detect 70 Maximum Non-Detect 9500 0.28 Kurtosis Detects -1.125 Variance Detects 440.6 Percent Non-Detects 65.67% Mean Detects 35.44 SD Detects Mean of Logged Detects 3.308 SD of Logged Detects 0.89 Median Detects 34 CV Detects 0.592 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.939 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.914 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.115 Lilliefors GOF Test 5% Lilliefors Critical Value 0.18 Detected Data appear Normal at 5% Significance Level Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 13.95 KM Standard Error of Mean 2.644 Page 7 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 18.23 21.88 95% KM Chebyshev UCL 25.47 KM SD 20.48 95% KM (BCA) UCL 18.47 95% KM (t) UCL 18.36 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 30.46 99% KM Chebyshev UCL 40.26 95% KM (z) UCL 18.3 95% KM Bootstrap t UCL 19.07 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.394 Anderson-Darling GOF Test 5% A-D Critical Value 0.754 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.106 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.184 Detected data appear Gamma Distributed at 5% Significance Level 95.41 nu star (bias corrected) 84.3 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 2.074 k star (bias corrected MLE) 1.833 Mean (detects) 35.44 Theta hat (MLE) 17.09 Theta star (bias corrected MLE) 19.34 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 14.02 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 70 Median 4.948 SD 20.17 CV 1.438 k hat (MLE) 0.241 k star (bias corrected MLE) 0.24 Theta hat (MLE) 58.15 Theta star (bias corrected MLE) 58.36 nu hat (MLE) 32.32 nu star (bias corrected) 32.2 Adjusted Level of Significance (β) 0.0464 Approximate Chi Square Value (32.20, α) 20.23 Adjusted Chi Square Value (32.20, β) 20.02 95% Gamma Approximate UCL (use when n>=50) 22.32 95% Gamma Adjusted UCL (use when n<50) 22.55 Estimates of Gamma Parameters using KM Estimates Mean (KM) 13.95 SD (KM) 20.48 Variance (KM) 419.5 SE of Mean (KM) 2.644 k hat (KM) 0.464 k star (KM) 0.453 nu hat (KM) 62.14 nu star (KM) 60.69 theta hat (KM) 30.07 theta star (KM) 30.79 80% gamma percentile (KM) 22.78 90% gamma percentile (KM) 38.49 95% gamma percentile (KM) 55.49 99% gamma percentile (KM) 97.68 Gamma Kaplan-Meier (KM) Statistics Page 8 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 43.46 95% Gamma Approximate KM-UCL (use when n>=50) 19.34 95% Gamma Adjusted KM-UCL (use when n<50) 19.48 Approximate Chi Square Value (60.69, α) 43.78 Adjusted Chi Square Value (60.69, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.853 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.914 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.145 Lilliefors GOF Test 5% Lilliefors Critical Value 0.18 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 15.17 Mean in Log Scale 1.931 SD in Original Scale 19.32 SD in Log Scale 1.323 95% t UCL (assumes normality of ROS data) 19.11 95% Percentile Bootstrap UCL 18.99 95% BCA Bootstrap UCL 19.55 95% Bootstrap t UCL 20.07 95% H-UCL (Log ROS) 23.55 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.357 KM Geo Mean 3.884 KM SD (logged) 1.61 95% Critical H Value (KM-Log) 2.508 KM Standard Error of Mean (logged) 0.216 95% H-UCL (KM -Log) 23.33 1.621 KM SD (logged) 1.61 95% Critical H Value (KM-Log) 2.508 KM Standard Error of Mean (logged) 0.216 211.3 95% H-Stat UCL 78.93 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 92.91 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 580.6 SD in Log Scale 2.006 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 18.36 DW_EU5_PFMOAA General Statistics Page 9 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Total Number of Observations 67 Number of Distinct Observations 28 Number of Detects 28 Number of Non-Detects 39 Number of Distinct Detects 21 Number of Distinct Non-Detects 7 112.3 Minimum Detect 16 Minimum Non-Detect 1.29 Maximum Detect 460 Maximum Non-Detect 9500 1.361 Kurtosis Detects 1.866 Variance Detects 12610 Percent Non-Detects 58.21% Mean Detects 164.8 SD Detects Mean of Logged Detects 4.86 SD of Logged Detects 0.779 Median Detects 145 CV Detects 0.681 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.864 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.924 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.231 Lilliefors GOF Test 5% Lilliefors Critical Value 0.164 Detected Data Not Normal at 5% Significance Level 93.27 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 71.81 KM Standard Error of Mean 13.71 112.9 95% KM Chebyshev UCL 131.6 KM SD 108.5 95% KM (BCA) UCL 94.6 95% KM (t) UCL 94.69 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 157.4 99% KM Chebyshev UCL 208.2 95% KM (z) UCL 94.37 95% KM Bootstrap t UCL 98.39 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.489 Anderson-Darling GOF Test 5% A-D Critical Value 0.757 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.143 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.167 Detected data appear Gamma Distributed at 5% Significance Level 123.2 nu star (bias corrected) 111.3 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 2.2 k star (bias corrected MLE) 1.988 Mean (detects) 164.8 Theta hat (MLE) 74.91 Theta star (bias corrected MLE) 82.89 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Page 10 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Minimum 0.01 Mean 70.35 Maximum 460 Median 9.439 SD 108.1 CV 1.536 k hat (MLE) 0.18 k star (bias corrected MLE) 0.182 Theta hat (MLE) 391.3 Theta star (bias corrected MLE) 387.2 nu hat (MLE) 24.09 nu star (bias corrected) 24.35 Adjusted Level of Significance (β) 0.0464 Approximate Chi Square Value (24.35, α) 14.11 Adjusted Chi Square Value (24.35, β) 13.94 95% Gamma Approximate UCL (use when n>=50) 121.4 95% Gamma Adjusted UCL (use when n<50) 122.9 Estimates of Gamma Parameters using KM Estimates Mean (KM) 71.81 SD (KM) 108.5 Variance (KM) 11782 SE of Mean (KM) 13.71 k hat (KM) 0.438 k star (KM) 0.428 nu hat (KM) 58.65 nu star (KM) 57.36 theta hat (KM) 164.1 theta star (KM) 167.8 40.64 80% gamma percentile (KM) 116.7 90% gamma percentile (KM) 200.4 95% gamma percentile (KM) 291.4 99% gamma percentile (KM) 518.8 95% Gamma Approximate KM-UCL (use when n>=50) 100.6 95% Gamma Adjusted KM-UCL (use when n<50) 101.3 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (57.36, α) 40.95 Adjusted Chi Square Value (57.36, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.93 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.924 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.169 Lilliefors GOF Test 5% Lilliefors Critical Value 0.164 Detected Data Not Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 81.39 Mean in Log Scale 3.692 SD in Original Scale 101.6 SD in Log Scale 1.245 95% t UCL (assumes normality of ROS data) 102.1 95% Percentile Bootstrap UCL 101.9 95% BCA Bootstrap UCL 107.7 95% Bootstrap t UCL 108.5 95% H-UCL (Log ROS) 121.1 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.25 KM Geo Mean 9.485 KM SD (logged) 2.333 95% Critical H Value (KM-Log) 3.129 KM Standard Error of Mean (logged) 0.296 95% H-UCL (KM -Log) 354.1 KM SD (logged) 2.333 95% Critical H Value (KM-Log) 3.129 KM Standard Error of Mean (logged) 0.296 DL/2 Statistics Page 11 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 2.81 267.9 95% H-Stat UCL 419.6 DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 149.2 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Gamma Distributed at 5% Significance Level SD in Original Scale 582.6 SD in Log Scale 2.189 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM Approximate Gamma UCL 100.6 95% GROS Approximate Gamma UCL 121.4 DW_EU5_PFO2HxA General Statistics Total Number of Observations 67 Number of Distinct Observations 36 Number of Detects 35 Number of Non-Detects 32 Number of Distinct Detects 30 Number of Distinct Non-Detects 6 579.4 Minimum Detect 2.3 Minimum Non-Detect 1.1 Maximum Detect 2500 Maximum Non-Detect 9200 2.406 Kurtosis Detects 6.476 Variance Detects 335754 Percent Non-Detects 47.76% Mean Detects 475 SD Detects Mean of Logged Detects 5.178 SD of Logged Detects 1.88 Median Detects 330 CV Detects 1.22 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.719 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.934 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.213 Lilliefors GOF Test 5% Lilliefors Critical Value 0.148 Detected Data Not Normal at 5% Significance Level 351.1 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 252.5 KM Standard Error of Mean 59.75 431.7 95% KM Chebyshev UCL 512.9 KM SD 478.4 95% KM (BCA) UCL 363 95% KM (t) UCL 352.1 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 625.6 99% KM Chebyshev UCL 846.9 95% KM (z) UCL 350.7 95% KM Bootstrap t UCL 396.4 90% KM Chebyshev UCL Page 12 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.694 Anderson-Darling GOF Test 5% A-D Critical Value 0.8 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.17 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.156 Detected Data Not Gamma Distributed at 5% Significance Level 43.64 nu star (bias corrected) 41.24 Detected data follow Appr. Gamma Distribution at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.623 k star (bias corrected MLE) 0.589 Mean (detects) 475 Theta hat (MLE) 761.8 Theta star (bias corrected MLE) 806.3 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 248.1 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 2500 Median 2.7 SD 479.7 CV 1.933 k hat (MLE) 0.153 k star (bias corrected MLE) 0.156 Theta hat (MLE) 1622 Theta star (bias corrected MLE) 1589 nu hat (MLE) 20.5 nu star (bias corrected) 20.92 Adjusted Level of Significance (β) 0.0464 Approximate Chi Square Value (20.92, α) 11.53 Adjusted Chi Square Value (20.92, β) 11.38 95% Gamma Approximate UCL (use when n>=50) 450.1 95% Gamma Adjusted UCL (use when n<50) 456.2 Estimates of Gamma Parameters using KM Estimates Mean (KM) 252.5 SD (KM) 478.4 Variance (KM) 228864 SE of Mean (KM) 59.75 k hat (KM) 0.279 k star (KM) 0.276 nu hat (KM) 37.32 nu star (KM) 36.98 theta hat (KM) 906.5 theta star (KM) 914.8 23.83 80% gamma percentile (KM) 378.6 90% gamma percentile (KM) 751.5 95% gamma percentile (KM) 1186 99% gamma percentile (KM) 2327 95% Gamma Approximate KM-UCL (use when n>=50) 388.1 95% Gamma Adjusted KM-UCL (use when n<50) 391.8 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (36.98, α) 24.06 Adjusted Chi Square Value (36.98, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.874 Shapiro Wilk GOF Test Page 13 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 5% Shapiro Wilk Critical Value 0.934 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.246 Lilliefors GOF Test 5% Lilliefors Critical Value 0.148 Detected Data Not Lognormal at 5% Significance Level Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 250.6 Mean in Log Scale 3.149 SD in Original Scale 478.4 SD in Log Scale 2.712 95% t UCL (assumes normality of ROS data) 348.1 95% Percentile Bootstrap UCL 348.4 95% BCA Bootstrap UCL 372.9 95% Bootstrap t UCL 390.7 95% H-UCL (Log ROS) 2787 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.804 KM Geo Mean 16.51 KM SD (logged) 2.866 95% Critical H Value (KM-Log) 3.533 KM Standard Error of Mean (logged) 0.359 95% H-UCL (KM -Log) 3493 KM SD (logged) 2.866 95% Critical H Value (KM-Log) 3.533 KM Standard Error of Mean (logged) 0.359 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 317.9 Mean in Log Scale 2.906 SD in Original Scale 714.6 SD in Log Scale 2.978 95% t UCL (Assumes normality) 463.6 95% H-Stat UCL 6038 Suggested UCL to Use 95% KM Approximate Gamma UCL 388.1 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Gamma Distributed at 5% Significance Level Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU5_PFO3OA When a data set follows an approximate (e.g., normal) distribution passing one of the GOF test When applicable, it is suggested to use a UCL based upon a distribution (e.g., gamma) passing both GOF tests in ProUCL Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. General Statistics Total Number of Observations 67 Number of Distinct Observations 27 Number of Detects 24 Number of Non-Detects 43 Page 14 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Number of Distinct Detects 20 Number of Distinct Non-Detects 7 53.52 Minimum Detect 1.8 Minimum Non-Detect 1.1 Maximum Detect 170 Maximum Non-Detect 8800 0.755 Kurtosis Detects -0.724 Variance Detects 2864 Percent Non-Detects 64.18% Mean Detects 62.13 SD Detects Mean of Logged Detects 3.59 SD of Logged Detects 1.27 Median Detects 42.5 CV Detects 0.861 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.886 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.916 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.167 Lilliefors GOF Test 5% Lilliefors Critical Value 0.177 Detected Data appear Normal at 5% Significance Level 33.29 Detected Data appear Approximate Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 24.14 KM Standard Error of Mean 5.495 40.63 95% KM Chebyshev UCL 48.09 KM SD 43.24 95% KM (BCA) UCL 34.23 95% KM (t) UCL 33.31 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 58.46 99% KM Chebyshev UCL 78.82 95% KM (z) UCL 33.18 95% KM Bootstrap t UCL 36.54 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.29 Anderson-Darling GOF Test 5% A-D Critical Value 0.771 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.0952 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.183 Detected data appear Gamma Distributed at 5% Significance Level 51.04 nu star (bias corrected) 45.99 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.063 k star (bias corrected MLE) 0.958 Mean (detects) 62.13 Theta hat (MLE) 58.43 Theta star (bias corrected MLE) 64.84 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 22.58 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 170 Median 0.01 Page 15 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 SD 43.46 CV 1.925 k hat (MLE) 0.167 k star (bias corrected MLE) 0.169 Theta hat (MLE) 135.3 Theta star (bias corrected MLE) 133.3 nu hat (MLE) 22.36 nu star (bias corrected) 22.69 Adjusted Level of Significance (β) 0.0464 Approximate Chi Square Value (22.69, α) 12.86 Adjusted Chi Square Value (22.69, β) 12.69 95% Gamma Approximate UCL (use when n>=50) 39.85 95% Gamma Adjusted UCL (use when n<50) 40.36 Estimates of Gamma Parameters using KM Estimates Mean (KM) 24.14 SD (KM) 43.24 Variance (KM) 1870 SE of Mean (KM) 5.495 k hat (KM) 0.312 k star (KM) 0.308 nu hat (KM) 41.77 nu star (KM) 41.23 theta hat (KM) 77.45 theta star (KM) 78.45 27.27 80% gamma percentile (KM) 37.25 90% gamma percentile (KM) 70.98 95% gamma percentile (KM) 109.5 99% gamma percentile (KM) 209.4 95% Gamma Approximate KM-UCL (use when n>=50) 36.18 95% Gamma Adjusted KM-UCL (use when n<50) 36.5 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (41.23, α) 27.52 Adjusted Chi Square Value (41.23, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.91 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.916 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.112 Lilliefors GOF Test 5% Lilliefors Critical Value 0.177 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 23.93 Mean in Log Scale 1.506 SD in Original Scale 42.77 SD in Log Scale 2.017 95% t UCL (assumes normality of ROS data) 32.64 95% Percentile Bootstrap UCL 32.85 95% BCA Bootstrap UCL 33.43 95% Bootstrap t UCL 35.11 95% H-UCL (Log ROS) 72.48 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.508 KM Geo Mean 4.517 KM SD (logged) 1.811 95% Critical H Value (KM-Log) 2.743 KM Standard Error of Mean (logged) 0.243 95% H-UCL (KM -Log) 42.88 KM SD (logged) 1.811 95% Critical H Value (KM-Log) 2.743 KM Standard Error of Mean (logged) 0.243 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 96.88 Mean in Log Scale 1.721 Page 16 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 SD in Original Scale 537.8 SD in Log Scale 2.16 95% t UCL (Assumes normality) 206.5 95% H-Stat UCL 130.8 Suggested UCL to Use 95% KM (t) UCL 33.31 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Normal Distributed at 5% Significance Level Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU5_PFO4DA When a data set follows an approximate (e.g., normal) distribution passing one of the GOF test When applicable, it is suggested to use a UCL based upon a distribution (e.g., gamma) passing both GOF tests in ProUCL Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. General Statistics Total Number of Observations 67 Number of Distinct Observations 23 Number of Detects 19 Number of Non-Detects 48 Number of Distinct Detects 16 Number of Distinct Non-Detects 7 14.54 Minimum Detect 1.8 Minimum Non-Detect 1.1 Maximum Detect 55 Maximum Non-Detect 9700 1.142 Kurtosis Detects 1.018 Variance Detects 211.4 Percent Non-Detects 71.64% Mean Detects 16.71 SD Detects Mean of Logged Detects 2.389 SD of Logged Detects 1.029 Median Detects 11 CV Detects 0.87 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.871 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.901 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.18 Lilliefors GOF Test 5% Lilliefors Critical Value 0.197 Detected Data appear Normal at 5% Significance Level 8.521 Detected Data appear Approximate Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 6.117 KM Standard Error of Mean 1.405 10.33 95% KM Chebyshev UCL 12.24 KM SD 10.65 95% KM (BCA) UCL 8.684 95% KM (t) UCL 8.461 95% KM (Percentile Bootstrap) UCL 95% KM (z) UCL 8.428 95% KM Bootstrap t UCL 9.085 90% KM Chebyshev UCL Page 17 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 97.5% KM Chebyshev UCL 14.89 99% KM Chebyshev UCL 20.1 Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.384 Anderson-Darling GOF Test 5% A-D Critical Value 0.762 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.142 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.203 Detected data appear Gamma Distributed at 5% Significance Level 49.93 nu star (bias corrected) 43.38 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.314 k star (bias corrected MLE) 1.142 Mean (detects) 16.71 Theta hat (MLE) 12.71 Theta star (bias corrected MLE) 14.63 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 5.018 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 55 Median 0.01 SD 10.73 CV 2.139 k hat (MLE) 0.19 k star (bias corrected MLE) 0.191 Theta hat (MLE) 26.41 Theta star (bias corrected MLE) 26.21 nu hat (MLE) 25.46 nu star (bias corrected) 25.65 Adjusted Level of Significance (β) 0.0464 Approximate Chi Square Value (25.65, α) 15.11 Adjusted Chi Square Value (25.65, β) 14.93 95% Gamma Approximate UCL (use when n>=50) 8.518 95% Gamma Adjusted UCL (use when n<50) 8.62 Estimates of Gamma Parameters using KM Estimates Mean (KM) 6.117 SD (KM) 10.65 Variance (KM) 113.4 SE of Mean (KM) 1.405 k hat (KM) 0.33 k star (KM) 0.325 nu hat (KM) 44.21 nu star (KM) 43.57 theta hat (KM) 18.54 theta star (KM) 18.81 29.18 80% gamma percentile (KM) 9.552 90% gamma percentile (KM) 17.85 95% gamma percentile (KM) 27.26 99% gamma percentile (KM) 51.46 95% Gamma Approximate KM-UCL (use when n>=50) 9.055 95% Gamma Adjusted KM-UCL (use when n<50) 9.134 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (43.57, α) 29.43 Adjusted Chi Square Value (43.57, β) Lognormal GOF Test on Detected Observations Only Page 18 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Shapiro Wilk Test Statistic 0.941 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.901 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.136 Lilliefors GOF Test 5% Lilliefors Critical Value 0.197 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 5.6 Mean in Log Scale 0.384 SD in Original Scale 10.43 SD in Log Scale 1.705 95% t UCL (assumes normality of ROS data) 7.726 95% Percentile Bootstrap UCL 7.813 95% BCA Bootstrap UCL 8.283 95% Bootstrap t UCL 8.676 95% H-UCL (Log ROS) 10.89 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.878 KM Geo Mean 2.405 KM SD (logged) 1.187 95% Critical H Value (KM-Log) 2.202 KM Standard Error of Mean (logged) 0.166 95% H-UCL (KM -Log) 6.709 KM SD (logged) 1.187 95% Critical H Value (KM-Log) 2.202 KM Standard Error of Mean (logged) 0.166 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 87.17 Mean in Log Scale 1.146 SD in Original Scale 593.7 SD in Log Scale 1.798 95% t UCL (Assumes normality) 208.2 95% H-Stat UCL 28.97 Suggested UCL to Use 95% KM (t) UCL 8.461 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Normal Distributed at 5% Significance Level Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU5_PFO5DA When a data set follows an approximate (e.g., normal) distribution passing one of the GOF test When applicable, it is suggested to use a UCL based upon a distribution (e.g., gamma) passing both GOF tests in ProUCL Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. General Statistics Total Number of Observations 67 Number of Distinct Observations 11 Page 19 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Number of Detects 6 Number of Non-Detects 61 Number of Distinct Detects 6 Number of Distinct Non-Detects 5 2.672 Minimum Detect 2.4 Minimum Non-Detect 1.1 Maximum Detect 9.8 Maximum Non-Detect 11000 1.363 Kurtosis Detects 2.109 Variance Detects 7.139 Percent Non-Detects 91.04% Mean Detects 4.967 SD Detects Mean of Logged Detects 1.493 SD of Logged Detects 0.505 Median Detects 4.5 CV Detects 0.538 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.889 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.788 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.225 Lilliefors GOF Test 5% Lilliefors Critical Value 0.325 Detected Data appear Normal at 5% Significance Level 1.84 Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 1.5 KM Standard Error of Mean 0.204 2.111 95% KM Chebyshev UCL 2.387 KM SD 1.415 95% KM (BCA) UCL 1.855 95% KM (t) UCL 1.84 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 2.771 99% KM Chebyshev UCL 3.525 95% KM (z) UCL 1.835 95% KM Bootstrap t UCL 1.895 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.23 Anderson-Darling GOF Test 5% A-D Critical Value 0.699 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.157 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.333 Detected data appear Gamma Distributed at 5% Significance Level 56.66 nu star (bias corrected) 29.66 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 4.721 k star (bias corrected MLE) 2.472 Mean (detects) 4.967 Theta hat (MLE) 1.052 Theta star (bias corrected MLE) 2.009 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 0.474 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Page 20 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Maximum 9.8 Median 0.01 SD 1.603 CV 3.379 k hat (MLE) 0.228 k star (bias corrected MLE) 0.228 Theta hat (MLE) 2.082 Theta star (bias corrected MLE) 2.084 nu hat (MLE) 30.53 nu star (bias corrected) 30.5 Adjusted Level of Significance (β) 0.0464 Approximate Chi Square Value (30.50, α) 18.88 Adjusted Chi Square Value (30.50, β) 18.68 95% Gamma Approximate UCL (use when n>=50) 0.766 95% Gamma Adjusted UCL (use when n<50) 0.774 Estimates of Gamma Parameters using KM Estimates Mean (KM) 1.5 SD (KM) 1.415 Variance (KM) 2.002 SE of Mean (KM) 0.204 k hat (KM) 1.124 k star (KM) 1.083 nu hat (KM) 150.6 nu star (KM) 145.2 theta hat (KM) 1.335 theta star (KM) 1.384 117.8 80% gamma percentile (KM) 2.398 90% gamma percentile (KM) 3.386 95% gamma percentile (KM) 4.369 99% gamma percentile (KM) 6.636 95% Gamma Approximate KM-UCL (use when n>=50) 1.84 95% Gamma Adjusted KM-UCL (use when n<50) 1.849 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (145.18, α) 118.3 Adjusted Chi Square Value (145.18, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.974 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.788 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.145 Lilliefors GOF Test 5% Lilliefors Critical Value 0.325 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 0.822 Mean in Log Scale -1.25 SD in Original Scale 1.564 SD in Log Scale 1.48 95% t UCL (assumes normality of ROS data) 1.141 95% Percentile Bootstrap UCL 1.152 95% BCA Bootstrap UCL 1.266 95% Bootstrap t UCL 1.333 95% H-UCL (Log ROS) 1.316 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.24 KM Geo Mean 1.271 KM SD (logged) 0.451 95% Critical H Value (KM-Log) 1.836 KM Standard Error of Mean (logged) 0.0648 95% H-UCL (KM -Log) 1.558 KM SD (logged) 0.451 95% Critical H Value (KM-Log) 1.836 KM Standard Error of Mean (logged) 0.0648 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Page 21 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 0.703 234 95% H-Stat UCL 17.12 Mean in Original Scale 96.7 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 673.6 SD in Log Scale 1.763 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 1.84 DW_EU5_PMPA General Statistics Total Number of Observations 67 Number of Distinct Observations 41 Number of Detects 39 Number of Non-Detects 28 Number of Distinct Detects 37 Number of Distinct Non-Detects 4 1631 Minimum Detect 11 Minimum Non-Detect 5.3 Maximum Detect 9300 Maximum Non-Detect 8400 3.815 Kurtosis Detects 17.56 Variance Detects 2659311 Percent Non-Detects 41.79% Mean Detects 1040 SD Detects Mean of Logged Detects 6.016 SD of Logged Detects 1.629 Median Detects 610 CV Detects 1.568 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.575 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.939 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.306 Lilliefors GOF Test 5% Lilliefors Critical Value 0.14 Detected Data Not Normal at 5% Significance Level 904 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 614.8 KM Standard Error of Mean 165.2 1111 95% KM Chebyshev UCL 1335 KM SD 1332 95% KM (BCA) UCL 924.3 95% KM (t) UCL 890.5 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 1647 99% KM Chebyshev UCL 2259 95% KM (z) UCL 886.6 95% KM Bootstrap t UCL 1113 90% KM Chebyshev UCL Page 22 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.935 Anderson-Darling GOF Test 5% A-D Critical Value 0.798 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.143 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.148 Detected data appear Gamma Distributed at 5% Significance Level 51.11 nu star (bias corrected) 48.52 Detected data follow Appr. Gamma Distribution at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.655 k star (bias corrected MLE) 0.622 Mean (detects) 1040 Theta hat (MLE) 1587 Theta star (bias corrected MLE) 1672 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 605.4 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 9300 Median 42 SD 1341 CV 2.215 k hat (MLE) 0.158 k star (bias corrected MLE) 0.161 Theta hat (MLE) 3832 Theta star (bias corrected MLE) 3764 nu hat (MLE) 21.17 nu star (bias corrected) 21.55 Adjusted Level of Significance (β) 0.0464 Approximate Chi Square Value (21.55, α) 12 Adjusted Chi Square Value (21.55, β) 11.85 95% Gamma Approximate UCL (use when n>=50) 1087 95% Gamma Adjusted UCL (use when n<50) 1101 Estimates of Gamma Parameters using KM Estimates Mean (KM) 614.8 SD (KM) 1332 Variance (KM) 1772942 SE of Mean (KM) 165.2 k hat (KM) 0.213 k star (KM) 0.214 nu hat (KM) 28.57 nu star (KM) 28.62 theta hat (KM) 2884 theta star (KM) 2878 17.22 80% gamma percentile (KM) 837.1 90% gamma percentile (KM) 1859 95% gamma percentile (KM) 3113 99% gamma percentile (KM) 6529 95% Gamma Approximate KM-UCL (use when n>=50) 1011 95% Gamma Adjusted KM-UCL (use when n<50) 1022 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (28.62, α) 17.41 Adjusted Chi Square Value (28.62, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.911 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.939 Detected Data Not Lognormal at 5% Significance Level Page 23 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Lilliefors Test Statistic 0.215 Lilliefors GOF Test 5% Lilliefors Critical Value 0.14 Detected Data Not Lognormal at 5% Significance Level Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 613.5 Mean in Log Scale 4.522 SD in Original Scale 1337 SD in Log Scale 2.294 95% t UCL (assumes normality of ROS data) 886.1 95% Percentile Bootstrap UCL 909.6 95% BCA Bootstrap UCL 1046 95% Bootstrap t UCL 1109 95% H-UCL (Log ROS) 3092 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 4.241 KM Geo Mean 69.48 KM SD (logged) 2.465 95% Critical H Value (KM-Log) 3.11 KM Standard Error of Mean (logged) 0.307 95% H-UCL (KM -Log) 3727 KM SD (logged) 2.465 95% Critical H Value (KM-Log) 3.11 KM Standard Error of Mean (logged) 0.307 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 670.4 Mean in Log Scale 4.29 SD in Original Scale 1408 SD in Log Scale 2.538 95% t UCL (Assumes normality) 957.2 95% H-Stat UCL 4858 Suggested UCL to Use 95% KM Approximate Gamma UCL 1011 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Gamma Distributed at 5% Significance Level Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU6_HFPO-DA When a data set follows an approximate (e.g., normal) distribution passing one of the GOF test When applicable, it is suggested to use a UCL based upon a distribution (e.g., gamma) passing both GOF tests in ProUCL Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. General Statistics Total Number of Observations 30 Number of Distinct Observations 22 Number of Detects 21 Number of Non-Detects 9 Number of Distinct Detects 21 Number of Distinct Non-Detects 1 Page 24 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 147.5 Minimum Detect 9.2 Minimum Non-Detect 4 Maximum Detect 420 Maximum Non-Detect 4 0.746 Kurtosis Detects -1.116 Variance Detects 21764 Percent Non-Detects 30% Mean Detects 152.9 SD Detects Mean of Logged Detects 4.425 SD of Logged Detects 1.238 Median Detects 94 CV Detects 0.965 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.829 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.908 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.224 Lilliefors GOF Test 5% Lilliefors Critical Value 0.188 Detected Data Not Normal at 5% Significance Level 152.4 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 108.2 KM Standard Error of Mean 25.9 185.9 95% KM Chebyshev UCL 221.1 KM SD 138.4 95% KM (BCA) UCL 154.4 95% KM (t) UCL 152.2 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 270 99% KM Chebyshev UCL 365.9 95% KM (z) UCL 150.8 95% KM Bootstrap t UCL 159.4 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.633 Anderson-Darling GOF Test 5% A-D Critical Value 0.772 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.157 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.195 Detected data appear Gamma Distributed at 5% Significance Level 40.28 nu star (bias corrected) 35.86 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.959 k star (bias corrected MLE) 0.854 Mean (detects) 152.9 Theta hat (MLE) 159.4 Theta star (bias corrected MLE) 179.1 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 107 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 420 Median 34 SD 141.7 CV 1.324 Page 25 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 k hat (MLE) 0.242 k star (bias corrected MLE) 0.24 Theta hat (MLE) 443.2 Theta star (bias corrected MLE) 446.8 nu hat (MLE) 14.49 nu star (bias corrected) 14.38 Adjusted Level of Significance (β) 0.041 Approximate Chi Square Value (14.38, α) 6.829 Adjusted Chi Square Value (14.38, β) 6.53 95% Gamma Approximate UCL (use when n>=50) 225.3 95% Gamma Adjusted UCL (use when n<50) 235.7 Estimates of Gamma Parameters using KM Estimates Mean (KM) 108.2 SD (KM) 138.4 Variance (KM) 19166 SE of Mean (KM) 25.9 k hat (KM) 0.611 k star (KM) 0.572 nu hat (KM) 36.68 nu star (KM) 34.34 theta hat (KM) 177.1 theta star (KM) 189.1 21.37 80% gamma percentile (KM) 178.4 90% gamma percentile (KM) 284.5 95% gamma percentile (KM) 396.1 99% gamma percentile (KM) 667.3 95% Gamma Approximate KM-UCL (use when n>=50) 169.4 95% Gamma Adjusted KM-UCL (use when n<50) 174 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (34.34, α) 21.94 Adjusted Chi Square Value (34.34, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.93 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.908 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.145 Lilliefors GOF Test 5% Lilliefors Critical Value 0.188 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 108.7 Mean in Log Scale 3.543 SD in Original Scale 140.5 SD in Log Scale 1.761 95% t UCL (assumes normality of ROS data) 152.3 95% Percentile Bootstrap UCL 150.9 95% BCA Bootstrap UCL 156.9 95% Bootstrap t UCL 158.8 95% H-UCL (Log ROS) 522.3 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 3.513 KM Geo Mean 33.56 KM SD (logged) 1.721 95% Critical H Value (KM-Log) 3.498 KM Standard Error of Mean (logged) 0.322 95% H-UCL (KM -Log) 451 3.305 KM SD (logged) 1.721 95% Critical H Value (KM-Log) 3.498 KM Standard Error of Mean (logged) 0.322 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 107.6 Mean in Log Scale SD in Original Scale 141.3 SD in Log Scale 2.02 Page 26 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 151.5 95% H-Stat UCL 930.1 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Gamma Distributed at 5% Significance Level 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use a Adjusted KM-UCL (use when k<=1 and 15 < n < 50 but k<=1) 174 DW_EU6_PEPA General Statistics Total Number of Observations 16 Number of Distinct Observations 6 Number of Detects 4 Number of Non-Detects 12 Number of Distinct Detects 4 Number of Distinct Non-Detects 2 168 Minimum Detect 23 Minimum Non-Detect 20 Maximum Detect 430 Maximum Non-Detect 100 0.111 Kurtosis Detects 0.884 Variance Detects 28222 Percent Non-Detects 75% Mean Detects 223.3 SD Detects Mean of Logged Detects 4.992 SD of Logged Detects 1.283 Median Detects 220 CV Detects 0.752 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.992 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.187 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Normal at 5% Significance Level N/A Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 70.83 KM Standard Error of Mean 32.96 169.7 95% KM Chebyshev UCL 214.5 KM SD 114.2 95% KM (BCA) UCL N/A 95% KM (t) UCL 128.6 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 276.7 99% KM Chebyshev UCL 398.8 95% KM (z) UCL 125 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.349 Anderson-Darling GOF Test Page 27 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 5% A-D Critical Value 0.664 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.295 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.4 Detected data appear Gamma Distributed at 5% Significance Level 10.75 nu star (bias corrected) 4.02 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.343 k star (bias corrected MLE) 0.502 Mean (detects) 223.3 Theta hat (MLE) 166.2 Theta star (bias corrected MLE) 444.3 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 55.82 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 430 Median 0.01 SD 124.9 CV 2.238 k hat (MLE) 0.126 k star (bias corrected MLE) 0.144 Theta hat (MLE) 441.5 Theta star (bias corrected MLE) 386.6 nu hat (MLE) 4.046 nu star (bias corrected) 4.62 Adjusted Level of Significance (β) 0.0335 Approximate Chi Square Value (4.62, α) 0.981 Adjusted Chi Square Value (4.62, β) 0.808 95% Gamma Approximate UCL (use when n>=50) 262.9 95% Gamma Adjusted UCL (use when n<50) N/A Estimates of Gamma Parameters using KM Estimates Mean (KM) 70.83 SD (KM) 114.2 Variance (KM) 13036 SE of Mean (KM) 32.96 k hat (KM) 0.385 k star (KM) 0.354 nu hat (KM) 12.31 nu star (KM) 11.34 theta hat (KM) 184 theta star (KM) 199.9 4.32 80% gamma percentile (KM) 112.4 90% gamma percentile (KM) 204.1 95% gamma percentile (KM) 306.7 99% gamma percentile (KM) 568.1 95% Gamma Approximate KM-UCL (use when n>=50) 167.5 95% Gamma Adjusted KM-UCL (use when n<50) 185.9 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (11.34, α) 4.795 Adjusted Chi Square Value (11.34, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.858 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.329 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Lognormal at 5% Significance Level Page 28 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 58.43 Mean in Log Scale 1.365 SD in Original Scale 123.8 SD in Log Scale 2.733 95% t UCL (assumes normality of ROS data) 112.7 95% Percentile Bootstrap UCL 112.2 95% BCA Bootstrap UCL 129.7 95% Bootstrap t UCL 173.1 95% H-UCL (Log ROS) 10477 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 3.496 KM Geo Mean 32.97 KM SD (logged) 1.027 95% Critical H Value (KM-Log) 2.746 KM Standard Error of Mean (logged) 0.297 95% H-UCL (KM -Log) 115.8 3.076 KM SD (logged) 1.027 95% Critical H Value (KM-Log) 2.746 KM Standard Error of Mean (logged) 0.297 118.7 95% H-Stat UCL 164 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 65.81 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 120.6 SD in Log Scale 1.339 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 128.6 DW_EU6_PFECA-G General Statistics Total Number of Observations 16 Number of Distinct Observations 2 Number of Detects 0 Number of Non-Detects 16 Number of Distinct Detects 0 Number of Distinct Non-Detects 2 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Page 29 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 The data set for variable DW_EU6_PFECA-G was not processed! DW_EU6_PFESA-BP1 0 Number of Distinct Non-Detects 2 General Statistics Total Number of Observations 16 Number of Distinct Observations 2 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 16 Number of Distinct Detects General Statistics Total Number of Observations 16 Number of Distinct Observations 6 The data set for variable DW_EU6_PFESA-BP1 was not processed! DW_EU6_PFESA-BP2 Number of Detects 4 Number of Non-Detects 12 Number of Distinct Detects 4 Number of Distinct Non-Detects 2 25.22 Minimum Detect 14 Minimum Non-Detect 2 Maximum Detect 72 Maximum Non-Detect 50 -0.758 Kurtosis Detects -0.268 Variance Detects 636 Percent Non-Detects 75% Mean Detects 47 SD Detects Mean of Logged Detects 3.687 SD of Logged Detects 0.734 Median Detects 51 CV Detects 0.537 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.964 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.197 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Normal at 5% Significance Level N/A Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 13.5 KM Standard Error of Mean 6.517 33.05 95% KM Chebyshev UCL 41.91 KM SD 22.4 95% KM (BCA) UCL N/A 95% KM (t) UCL 24.92 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 54.2 99% KM Chebyshev UCL 78.34 95% KM (z) UCL 24.22 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL Page 30 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.358 Anderson-Darling GOF Test 5% A-D Critical Value 0.659 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.246 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.396 Detected data appear Gamma Distributed at 5% Significance Level 25.76 nu star (bias corrected) 7.774 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 3.221 k star (bias corrected MLE) 0.972 Mean (detects) 47 Theta hat (MLE) 14.59 Theta star (bias corrected MLE) 48.36 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 12.5 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 72 Median 0.01 SD 23.58 CV 1.887 k hat (MLE) 0.175 k star (bias corrected MLE) 0.184 Theta hat (MLE) 71.31 Theta star (bias corrected MLE) 67.89 nu hat (MLE) 5.608 nu star (bias corrected) 5.889 Adjusted Level of Significance (β) 0.0335 Approximate Chi Square Value (5.89, α) 1.584 Adjusted Chi Square Value (5.89, β) 1.345 95% Gamma Approximate UCL (use when n>=50) 46.47 95% Gamma Adjusted UCL (use when n<50) N/A Estimates of Gamma Parameters using KM Estimates Mean (KM) 13.5 SD (KM) 22.4 Variance (KM) 501.6 SE of Mean (KM) 6.517 k hat (KM) 0.363 k star (KM) 0.337 nu hat (KM) 11.63 nu star (KM) 10.78 theta hat (KM) 37.16 theta star (KM) 40.08 3.981 80% gamma percentile (KM) 21.23 90% gamma percentile (KM) 39.21 95% gamma percentile (KM) 59.46 99% gamma percentile (KM) 111.4 95% Gamma Approximate KM-UCL (use when n>=50) 32.82 95% Gamma Adjusted KM-UCL (use when n<50) 36.55 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (10.78, α) 4.435 Adjusted Chi Square Value (10.78, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.87 Shapiro Wilk GOF Test Page 31 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.278 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 15.59 Mean in Log Scale 1.915 SD in Original Scale 22.1 SD in Log Scale 1.345 95% t UCL (assumes normality of ROS data) 25.28 95% Percentile Bootstrap UCL 24.97 95% BCA Bootstrap UCL 28.11 95% Bootstrap t UCL 34.51 95% H-UCL (Log ROS) 52.19 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.466 KM Geo Mean 4.33 KM SD (logged) 1.345 95% Critical H Value (KM-Log) 3.27 KM Standard Error of Mean (logged) 0.394 95% H-UCL (KM -Log) 33.27 1.123 KM SD (logged) 1.345 95% Critical H Value (KM-Log) 3.27 KM Standard Error of Mean (logged) 0.394 24.27 95% H-Stat UCL 88.05 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 14 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 23.44 SD in Log Scale 1.755 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 24.92 DW_EU6_PFMOAA General Statistics Total Number of Observations 16 Number of Distinct Observations 6 Number of Detects 4 Number of Non-Detects 12 Number of Distinct Detects 4 Number of Distinct Non-Detects 2 Minimum Detect 20 Minimum Non-Detect 5 Maximum Detect 170 Maximum Non-Detect 50 Page 32 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 65.57 -1.589 Kurtosis Detects 2.913 Variance Detects 4300 Percent Non-Detects 75% Mean Detects 115 SD Detects Mean of Logged Detects 4.485 SD of Logged Detects 0.999 Median Detects 135 CV Detects 0.57 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.851 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.34 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Normal at 5% Significance Level N/A Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 32.58 KM Standard Error of Mean 16 80.59 95% KM Chebyshev UCL 102.3 KM SD 55.42 95% KM (BCA) UCL N/A 95% KM (t) UCL 60.63 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 132.5 99% KM Chebyshev UCL 191.8 95% KM (z) UCL 58.9 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.663 Anderson-Darling GOF Test 5% A-D Critical Value 0.66 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.41 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.398 Detected Data Not Gamma Distributed at 5% Significance Level 16.61 nu star (bias corrected) 5.486 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 2.076 k star (bias corrected MLE) 0.686 Mean (detects) 115 Theta hat (MLE) 55.39 Theta star (bias corrected MLE) 167.7 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 29.76 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 170 Median 0.01 SD 58.82 CV 1.977 k hat (MLE) 0.146 k star (bias corrected MLE) 0.161 Theta hat (MLE) 203.1 Theta star (bias corrected MLE) 185.2 Page 33 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 nu hat (MLE) 4.688 nu star (bias corrected) 5.142 Adjusted Level of Significance (β) 0.0335 Approximate Chi Square Value (5.14, α) 1.218 Adjusted Chi Square Value (5.14, β) 1.018 95% Gamma Approximate UCL (use when n>=50) 125.6 95% Gamma Adjusted UCL (use when n<50) N/A Estimates of Gamma Parameters using KM Estimates Mean (KM) 32.58 SD (KM) 55.42 Variance (KM) 3072 SE of Mean (KM) 16 k hat (KM) 0.346 k star (KM) 0.322 nu hat (KM) 11.06 nu star (KM) 10.32 theta hat (KM) 94.29 theta star (KM) 101.1 3.705 80% gamma percentile (KM) 50.79 90% gamma percentile (KM) 95.2 95% gamma percentile (KM) 145.6 99% gamma percentile (KM) 275.4 95% Gamma Approximate KM-UCL (use when n>=50) 81.17 95% Gamma Adjusted KM-UCL (use when n<50) 90.71 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (10.32, α) 4.14 Adjusted Chi Square Value (10.32, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.734 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.399 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data Not Lognormal at 5% Significance Level Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 32.64 Mean in Log Scale 1.893 SD in Original Scale 57.39 SD in Log Scale 1.961 95% t UCL (assumes normality of ROS data) 57.79 95% Percentile Bootstrap UCL 57.72 95% BCA Bootstrap UCL 64.42 95% Bootstrap t UCL 68.9 95% H-UCL (Log ROS) 421.1 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.336 KM Geo Mean 10.34 KM SD (logged) 1.318 95% Critical H Value (KM-Log) 3.225 KM Standard Error of Mean (logged) 0.382 95% H-UCL (KM -Log) 73.83 1.952 KM SD (logged) 1.318 95% Critical H Value (KM-Log) 3.225 KM Standard Error of Mean (logged) 0.382 57.35 95% H-Stat UCL 152 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 32.03 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons SD in Original Scale 57.78 SD in Log Scale 1.675 95% t UCL (Assumes normality) Page 34 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 60.63 DW_EU6_PFO2HxA General Statistics Total Number of Observations 16 Number of Distinct Observations 7 Number of Detects 6 Number of Non-Detects 10 Number of Distinct Detects 6 Number of Distinct Non-Detects 1 196.8 Minimum Detect 2.5 Minimum Non-Detect 2 Maximum Detect 500 Maximum Non-Detect 2 0.591 Kurtosis Detects -1.251 Variance Detects 38744 Percent Non-Detects 62.5% Mean Detects 203.6 SD Detects Mean of Logged Detects 4.44 SD of Logged Detects 1.956 Median Detects 161 CV Detects 0.967 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.913 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.788 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.248 Lilliefors GOF Test 5% Lilliefors Critical Value 0.325 Detected Data appear Normal at 5% Significance Level 143.2 Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 77.59 KM Standard Error of Mean 40.28 198.4 95% KM Chebyshev UCL 253.2 KM SD 147.1 95% KM (BCA) UCL 139.8 95% KM (t) UCL 148.2 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 329.1 99% KM Chebyshev UCL 478.4 95% KM (z) UCL 143.8 95% KM Bootstrap t UCL 175.7 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.276 Anderson-Darling GOF Test 5% A-D Critical Value 0.725 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.218 Kolmogorov-Smirnov GOF Page 35 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 5% K-S Critical Value 0.345 Detected data appear Gamma Distributed at 5% Significance Level 8.289 nu star (bias corrected) 5.478 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.691 k star (bias corrected MLE) 0.456 Mean (detects) 203.6 Theta hat (MLE) 294.7 Theta star (bias corrected MLE) 446 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 76.35 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 500 Median 0.01 SD 152.6 CV 1.998 k hat (MLE) 0.14 k star (bias corrected MLE) 0.155 Theta hat (MLE) 545.7 Theta star (bias corrected MLE) 491.5 nu hat (MLE) 4.477 nu star (bias corrected) 4.971 Adjusted Level of Significance (β) 0.0335 Approximate Chi Square Value (4.97, α) 1.139 Adjusted Chi Square Value (4.97, β) 0.947 95% Gamma Approximate UCL (use when n>=50) 333.3 95% Gamma Adjusted UCL (use when n<50) 400.8 Estimates of Gamma Parameters using KM Estimates Mean (KM) 77.59 SD (KM) 147.1 Variance (KM) 21632 SE of Mean (KM) 40.28 k hat (KM) 0.278 k star (KM) 0.268 nu hat (KM) 8.907 nu star (KM) 8.57 theta hat (KM) 278.8 theta star (KM) 289.7 2.706 80% gamma percentile (KM) 115.3 90% gamma percentile (KM) 231.6 95% gamma percentile (KM) 367.8 99% gamma percentile (KM) 727.1 95% Gamma Approximate KM-UCL (use when n>=50) 216.6 95% Gamma Adjusted KM-UCL (use when n<50) 245.7 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (8.57, α) 3.069 Adjusted Chi Square Value (8.57, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.87 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.788 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.215 Lilliefors GOF Test 5% Lilliefors Critical Value 0.325 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Page 36 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 76.87 Mean in Log Scale 0.659 SD in Original Scale 152.3 SD in Log Scale 3.665 95% t UCL (assumes normality of ROS data) 143.6 95% Percentile Bootstrap UCL 141 95% BCA Bootstrap UCL 168.7 95% Bootstrap t UCL 197.9 95% H-UCL (Log ROS) 2456053 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.098 KM Geo Mean 8.15 KM SD (logged) 2.118 95% Critical H Value (KM-Log) 4.694 KM Standard Error of Mean (logged) 0.58 95% H-UCL (KM -Log) 999.2 1.665 KM SD (logged) 2.118 95% Critical H Value (KM-Log) 4.694 KM Standard Error of Mean (logged) 0.58 143.7 95% H-Stat UCL 3822 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 76.97 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 152.2 SD in Log Scale 2.49 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 148.2 DW_EU6_PFO3OA General Statistics Total Number of Observations 16 Number of Distinct Observations 6 Number of Detects 4 Number of Non-Detects 12 Number of Distinct Detects 4 Number of Distinct Non-Detects 2 18.24 Minimum Detect 8 Minimum Non-Detect 2 Maximum Detect 41 Maximum Non-Detect 50 0.0083 Kurtosis Detects -5.928 Variance Detects 332.6 Percent Non-Detects 75% Mean Detects 24.23 SD Detects Mean of Logged Detects 2.911 SD of Logged Detects 0.9 Median Detects 23.95 CV Detects 0.753 Skewness Detects Page 37 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.77 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.3 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Normal at 5% Significance Level N/A Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 7.927 KM Standard Error of Mean 3.808 19.35 95% KM Chebyshev UCL 24.52 KM SD 12.77 95% KM (BCA) UCL N/A 95% KM (t) UCL 14.6 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 31.71 99% KM Chebyshev UCL 45.81 95% KM (z) UCL 14.19 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.634 Anderson-Darling GOF Test 5% A-D Critical Value 0.661 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.33 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.398 Detected data appear Gamma Distributed at 5% Significance Level 15.66 nu star (bias corrected) 5.247 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.957 k star (bias corrected MLE) 0.656 Mean (detects) 24.23 Theta hat (MLE) 12.38 Theta star (bias corrected MLE) 36.93 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 6.064 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 41 Median 0.01 SD 13.56 CV 2.236 k hat (MLE) 0.167 k star (bias corrected MLE) 0.177 Theta hat (MLE) 36.3 Theta star (bias corrected MLE) 34.18 nu hat (MLE) 5.345 nu star (bias corrected) 5.677 Adjusted Level of Significance (β) 0.0335 Approximate Chi Square Value (5.68, α) 1.477 Adjusted Chi Square Value (5.68, β) 1.248 95% Gamma Approximate UCL (use when n>=50) 23.31 95% Gamma Adjusted UCL (use when n<50) N/A Page 38 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Estimates of Gamma Parameters using KM Estimates Mean (KM) 7.927 SD (KM) 12.77 Variance (KM) 163.1 SE of Mean (KM) 3.808 k hat (KM) 0.385 k star (KM) 0.355 nu hat (KM) 12.33 nu star (KM) 11.35 theta hat (KM) 20.58 theta star (KM) 22.35 4.326 80% gamma percentile (KM) 12.58 90% gamma percentile (KM) 22.84 95% gamma percentile (KM) 34.32 99% gamma percentile (KM) 63.55 95% Gamma Approximate KM-UCL (use when n>=50) 18.74 95% Gamma Adjusted KM-UCL (use when n<50) 20.8 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (11.35, α) 4.801 Adjusted Chi Square Value (11.35, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.774 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.299 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 6.853 Mean in Log Scale 0.282 SD in Original Scale 13.22 SD in Log Scale 2.005 95% t UCL (assumes normality of ROS data) 12.65 95% Percentile Bootstrap UCL 12.26 95% BCA Bootstrap UCL 14.54 95% Bootstrap t UCL 30.95 95% H-UCL (Log ROS) 100.6 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.284 KM Geo Mean 3.613 KM SD (logged) 1.06 95% Critical H Value (KM-Log) 2.797 KM Standard Error of Mean (logged) 0.316 95% H-UCL (KM -Log) 13.62 0.929 KM SD (logged) 1.06 95% Critical H Value (KM-Log) 2.797 KM Standard Error of Mean (logged) 0.316 14.38 95% H-Stat UCL 28.95 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 8.306 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 13.85 SD in Log Scale 1.48 95% t UCL (Assumes normality) Suggested UCL to Use Page 39 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. 95% KM (t) UCL 14.6 DW_EU6_PFO4DA General Statistics Total Number of Observations 16 Number of Distinct Observations 6 Number of Detects 4 Number of Non-Detects 12 Number of Distinct Detects 4 Number of Distinct Non-Detects 2 5.025 Minimum Detect 2.1 Minimum Non-Detect 2 Maximum Detect 12 Maximum Non-Detect 50 -0.0529 Kurtosis Detects -5.311 Variance Detects 25.25 Percent Non-Detects 75% Mean Detects 7.2 SD Detects Mean of Logged Detects 1.733 SD of Logged Detects 0.85 Median Detects 7.35 CV Detects 0.698 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.851 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.275 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Normal at 5% Significance Level N/A Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 3.387 KM Standard Error of Mean 0.959 6.262 95% KM Chebyshev UCL 7.565 KM SD 3.215 95% KM (BCA) UCL N/A 95% KM (t) UCL 5.067 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 9.373 99% KM Chebyshev UCL 12.92 95% KM (z) UCL 4.963 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.433 Anderson-Darling GOF Test 5% A-D Critical Value 0.66 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.315 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.398 Detected data appear Gamma Distributed at 5% Significance Level Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 2.229 k star (bias corrected MLE) 0.724 Page 40 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 17.83 nu star (bias corrected) 5.791 Mean (detects) 7.2 Theta hat (MLE) 3.231 Theta star (bias corrected MLE) 9.947 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 1.808 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 12 Median 0.01 SD 3.923 CV 2.17 k hat (MLE) 0.203 k star (bias corrected MLE) 0.207 Theta hat (MLE) 8.895 Theta star (bias corrected MLE) 8.741 nu hat (MLE) 6.503 nu star (bias corrected) 6.617 Adjusted Level of Significance (β) 0.0335 Approximate Chi Square Value (6.62, α) 1.963 Adjusted Chi Square Value (6.62, β) 1.688 95% Gamma Approximate UCL (use when n>=50) 6.093 95% Gamma Adjusted UCL (use when n<50) N/A Estimates of Gamma Parameters using KM Estimates Mean (KM) 3.387 SD (KM) 3.215 Variance (KM) 10.34 SE of Mean (KM) 0.959 k hat (KM) 1.11 k star (KM) 0.943 nu hat (KM) 35.51 nu star (KM) 30.18 theta hat (KM) 3.052 theta star (KM) 3.591 17.61 80% gamma percentile (KM) 5.476 90% gamma percentile (KM) 7.911 95% gamma percentile (KM) 10.36 99% gamma percentile (KM) 16.06 95% Gamma Approximate KM-UCL (use when n>=50) 5.485 95% Gamma Adjusted KM-UCL (use when n<50) 5.805 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (30.18, α) 18.64 Adjusted Chi Square Value (30.18, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.878 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.283 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 2.061 Mean in Log Scale -0.828 SD in Original Scale 3.812 SD in Log Scale 1.951 95% t UCL (assumes normality of ROS data) 3.732 95% Percentile Bootstrap UCL 3.806 95% BCA Bootstrap UCL 4.282 95% Bootstrap t UCL 7.939 Page 41 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 95% H-UCL (Log ROS) 26.6 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.971 KM Geo Mean 2.639 KM SD (logged) 0.597 95% Critical H Value (KM-Log) 2.156 KM Standard Error of Mean (logged) 0.178 95% H-UCL (KM -Log) 4.397 0.634 KM SD (logged) 0.597 95% Critical H Value (KM-Log) 2.156 KM Standard Error of Mean (logged) 0.178 6.95 95% H-Stat UCL 7.76 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 4.05 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 6.616 SD in Log Scale 1.099 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 5.067 DW_EU6_PFO5DA General Statistics Total Number of Observations 16 Number of Distinct Observations 3 Number of Detects 1 Number of Non-Detects 15 Number of Distinct Detects 1 Number of Distinct Non-Detects 2 DW_EU6_PMPA General Statistics Warning: Only one distinct data value was detected! ProUCL (or any other software) should not be used on such a data set! It is suggested to use alternative site specific values determined by the Project Team to estimate environmental parameters (e.g., EPC, BTV). The data set for variable DW_EU6_PFO5DA was not processed! Total Number of Observations 16 Number of Distinct Observations 8 Number of Detects 7 Number of Non-Detects 9 Page 42 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Number of Distinct Detects 7 Number of Distinct Non-Detects 1 Minimum Detect 20 Minimum Non-Detect 10 Maximum Detect 1500 Maximum Non-Detect 10 Variance Detects 289598 Percent Non-Detects 56.25% Mean Detects 505.1 SD Detects 538.1 Median Detects 380 CV Detects 1.065 Skewness Detects 1.112 Kurtosis Detects 0.828 Mean of Logged Detects 5.368 SD of Logged Detects 1.708 Lilliefors GOF Test Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.884 Shapiro Wilk GOF Test 5% Lilliefors Critical Value 0.304 Detected Data appear Normal at 5% Significance Level Detected Data appear Normal at 5% Significance Level 5% Shapiro Wilk Critical Value 0.803 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.186 405.4 Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 226.6 KM Standard Error of Mean 111 559.6 95% KM Chebyshev UCL 710.4 KM SD 411 95% KM (BCA) UCL 441.4 95% KM (t) UCL 421.2 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 919.7 99% KM Chebyshev UCL 1331 95% KM (z) UCL 409.2 95% KM Bootstrap t UCL 562.2 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.277 Anderson-Darling GOF Test 5% A-D Critical Value 0.739 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.181 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.323 Detected data appear Gamma Distributed at 5% Significance Level 9.861 nu star (bias corrected) 6.968 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.704 k star (bias corrected MLE) 0.498 Mean (detects) 505.1 Theta hat (MLE) 717.2 Theta star (bias corrected MLE) 1015 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 221 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 1500 Median 0.01 Page 43 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 SD 427.6 CV 1.935 k hat (MLE) 0.138 k star (bias corrected MLE) 0.154 Theta hat (MLE) 1602 Theta star (bias corrected MLE) 1438 nu hat (MLE) 4.413 nu star (bias corrected) 4.919 Adjusted Level of Significance (β) 0.0335 Approximate Chi Square Value (4.92, α) 1.115 Adjusted Chi Square Value (4.92, β) 0.926 95% Gamma Approximate UCL (use when n>=50) 975 95% Gamma Adjusted UCL (use when n<50) 1174 Estimates of Gamma Parameters using KM Estimates Mean (KM) 226.6 SD (KM) 411 Variance (KM) 168933 SE of Mean (KM) 111 k hat (KM) 0.304 k star (KM) 0.289 nu hat (KM) 9.729 nu star (KM) 9.238 theta hat (KM) 745.4 theta star (KM) 785 3.08 80% gamma percentile (KM) 344.1 90% gamma percentile (KM) 671.4 95% gamma percentile (KM) 1049 99% gamma percentile (KM) 2037 95% Gamma Approximate KM-UCL (use when n>=50) 603.1 95% Gamma Adjusted KM-UCL (use when n<50) 679.8 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (9.24, α) 3.471 Adjusted Chi Square Value (9.24, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.899 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.803 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.203 Lilliefors GOF Test 5% Lilliefors Critical Value 0.304 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 222.8 Mean in Log Scale 2.442 SD in Original Scale 426.6 SD in Log Scale 3.169 95% t UCL (assumes normality of ROS data) 409.8 95% Percentile Bootstrap UCL 396.4 95% BCA Bootstrap UCL 453.3 95% Bootstrap t UCL 581.1 95% H-UCL (Log ROS) 439963 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 3.644 KM Geo Mean 38.23 KM SD (logged) 1.845 95% Critical H Value (KM-Log) 4.178 KM Standard Error of Mean (logged) 0.498 95% H-UCL (KM -Log) 1536 3.254 KM SD (logged) 1.845 95% Critical H Value (KM-Log) 4.178 KM Standard Error of Mean (logged) 0.498 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 223.8 Mean in Log Scale Page 44 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 410.5 95% H-Stat UCL 4747 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 426 SD in Log Scale 2.208 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 421.2 DW_EU7_HFPO-DA General Statistics Total Number of Observations 92 Number of Distinct Observations 68 Number of Detects 82 Number of Non-Detects 10 Number of Distinct Detects 67 Number of Distinct Non-Detects 1 472 Minimum Detect 5.2 Minimum Non-Detect 4 Maximum Detect 4000 Maximum Non-Detect 4 6.631 Kurtosis Detects 51.91 Variance Detects 222764 Percent Non-Detects 10.87% Mean Detects 219.1 SD Detects Mean of Logged Detects 4.406 SD of Logged Detects 1.443 Median Detects 91 CV Detects 2.154 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.422 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.325 Lilliefors GOF Test 5% Lilliefors Critical Value 0.098 Detected Data Not Normal at 5% Significance Level 284.1 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 195.7 KM Standard Error of Mean 46.98 336.7 95% KM Chebyshev UCL 400.5 KM SD 447.9 95% KM (BCA) UCL 283.1 95% KM (t) UCL 273.8 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 489.1 99% KM Chebyshev UCL 663.2 95% KM (z) UCL 273 95% KM Bootstrap t UCL 364.3 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only Page 45 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 A-D Test Statistic 1.562 Anderson-Darling GOF Test 5% A-D Critical Value 0.806 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.102 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.103 Detected data appear Gamma Distributed at 5% Significance Level 102.4 nu star (bias corrected) 99.98 Detected data follow Appr. Gamma Distribution at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.624 k star (bias corrected MLE) 0.61 Mean (detects) 219.1 Theta hat (MLE) 350.9 Theta star (bias corrected MLE) 359.4 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 195.3 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 4000 Median 60.5 SD 450.5 CV 2.307 k hat (MLE) 0.362 k star (bias corrected MLE) 0.357 Theta hat (MLE) 539.6 Theta star (bias corrected MLE) 546.5 nu hat (MLE) 66.58 nu star (bias corrected) 65.74 Adjusted Level of Significance (β) 0.0474 Approximate Chi Square Value (65.74, α) 48.09 Adjusted Chi Square Value (65.74, β) 47.85 95% Gamma Approximate UCL (use when n>=50) 267 95% Gamma Adjusted UCL (use when n<50) 268.3 Estimates of Gamma Parameters using KM Estimates Mean (KM) 195.7 SD (KM) 447.9 Variance (KM) 200610 SE of Mean (KM) 46.98 k hat (KM) 0.191 k star (KM) 0.192 nu hat (KM) 35.13 nu star (KM) 35.32 theta hat (KM) 1025 theta star (KM) 1020 22.56 80% gamma percentile (KM) 252.2 90% gamma percentile (KM) 591.6 95% gamma percentile (KM) 1019 99% gamma percentile (KM) 2204 95% Gamma Approximate KM-UCL (use when n>=50) 304.2 95% Gamma Adjusted KM-UCL (use when n<50) 306.4 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (35.32, α) 22.72 Adjusted Chi Square Value (35.32, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.965 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.0923 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0922 Lilliefors GOF Test Page 46 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 5% Lilliefors Critical Value 0.098 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 195.6 Mean in Log Scale 4.047 SD in Original Scale 450.4 SD in Log Scale 1.719 95% t UCL (assumes normality of ROS data) 273.7 95% Percentile Bootstrap UCL 279.7 95% BCA Bootstrap UCL 343.5 95% Bootstrap t UCL 355 95% H-UCL (Log ROS) 433.7 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 4.077 KM Geo Mean 58.99 KM SD (logged) 1.648 95% Critical H Value (KM-Log) 2.958 KM Standard Error of Mean (logged) 0.173 95% H-UCL (KM -Log) 382.3 KM SD (logged) 1.648 95% Critical H Value (KM-Log) 2.958 KM Standard Error of Mean (logged) 0.173 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 195.5 Mean in Log Scale 4.002 SD in Original Scale 450.4 SD in Log Scale 1.79 95% t UCL (Assumes normality) 273.5 95% H-Stat UCL 488.1 Suggested UCL to Use 95% KM Approximate Gamma UCL 304.2 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Gamma Distributed at 5% Significance Level Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU7_PEPA When a data set follows an approximate (e.g., normal) distribution passing one of the GOF test When applicable, it is suggested to use a UCL based upon a distribution (e.g., gamma) passing both GOF tests in ProUCL Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. General Statistics Total Number of Observations 47 Number of Distinct Observations 23 Number of Detects 24 Number of Non-Detects 23 Number of Distinct Detects 22 Number of Distinct Non-Detects 3 Minimum Detect 20 Minimum Non-Detect 20 Page 47 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 179.5 Maximum Detect 770 Maximum Non-Detect 10000 1.987 Kurtosis Detects 4.543 Variance Detects 32208 Percent Non-Detects 48.94% Mean Detects 176.8 SD Detects Mean of Logged Detects 4.703 SD of Logged Detects 1.044 Median Detects 125 CV Detects 1.015 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.791 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.916 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.191 Lilliefors GOF Test 5% Lilliefors Critical Value 0.177 Detected Data Not Normal at 5% Significance Level 145.8 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 106.2 KM Standard Error of Mean 23.29 176.1 95% KM Chebyshev UCL 207.7 KM SD 151.1 95% KM (BCA) UCL 147.3 95% KM (t) UCL 145.3 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 251.6 99% KM Chebyshev UCL 337.9 95% KM (z) UCL 144.5 95% KM Bootstrap t UCL 158.5 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.279 Anderson-Darling GOF Test 5% A-D Critical Value 0.768 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.105 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.182 Detected data appear Gamma Distributed at 5% Significance Level 57.61 nu star (bias corrected) 51.74 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.2 k star (bias corrected MLE) 1.078 Mean (detects) 176.8 Theta hat (MLE) 147.3 Theta star (bias corrected MLE) 164 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 93.73 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 770 Median 21 SD 154.6 CV 1.65 k hat (MLE) 0.189 k star (bias corrected MLE) 0.191 Page 48 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Theta hat (MLE) 495.8 Theta star (bias corrected MLE) 490.3 nu hat (MLE) 17.77 nu star (bias corrected) 17.97 Adjusted Level of Significance (β) 0.0449 Approximate Chi Square Value (17.97, α) 9.368 Adjusted Chi Square Value (17.97, β) 9.171 95% Gamma Approximate UCL (use when n>=50) 179.8 95% Gamma Adjusted UCL (use when n<50) 183.6 Estimates of Gamma Parameters using KM Estimates Mean (KM) 106.2 SD (KM) 151.1 Variance (KM) 22839 SE of Mean (KM) 23.29 k hat (KM) 0.494 k star (KM) 0.476 nu hat (KM) 46.42 nu star (KM) 44.79 theta hat (KM) 215.1 theta star (KM) 222.9 30.06 80% gamma percentile (KM) 174 90% gamma percentile (KM) 290.2 95% gamma percentile (KM) 415 99% gamma percentile (KM) 723.4 95% Gamma Approximate KM-UCL (use when n>=50) 156.3 95% Gamma Adjusted KM-UCL (use when n<50) 158.2 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (44.79, α) 30.44 Adjusted Chi Square Value (44.79, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.959 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.916 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.102 Lilliefors GOF Test 5% Lilliefors Critical Value 0.177 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 98.42 Mean in Log Scale 3.537 SD in Original Scale 151.2 SD in Log Scale 1.575 95% t UCL (assumes normality of ROS data) 135.5 95% Percentile Bootstrap UCL 136.3 95% BCA Bootstrap UCL 149.6 95% Bootstrap t UCL 151.7 95% H-UCL (Log ROS) 239.4 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 3.947 KM Geo Mean 51.76 KM SD (logged) 1.13 95% Critical H Value (KM-Log) 2.473 KM Standard Error of Mean (logged) 0.175 95% H-UCL (KM -Log) 148 4.062 KM SD (logged) 1.13 95% Critical H Value (KM-Log) 2.473 KM Standard Error of Mean (logged) 0.175 715.5 95% H-Stat UCL 654.5 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 417.1 Mean in Log Scale SD in Original Scale 1219 SD in Log Scale 1.77 95% t UCL (Assumes normality) Page 49 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Gamma Distributed at 5% Significance Level Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM Adjusted Gamma UCL 158.2 95% GROS Adjusted Gamma UCL 183.6 DW_EU7_PFECA-G General Statistics Total Number of Observations 47 Number of Distinct Observations 4 Number of Detects 0 Number of Non-Detects 47 Number of Distinct Detects 0 Number of Distinct Non-Detects 4 The data set for variable DW_EU7_PFECA-G was not processed! DW_EU7_PFESA-BP1 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). 0 Number of Distinct Non-Detects 5 General Statistics Total Number of Observations 47 Number of Distinct Observations 5 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 47 Number of Distinct Detects General Statistics Total Number of Observations 47 Number of Distinct Observations 25 The data set for variable DW_EU7_PFESA-BP1 was not processed! DW_EU7_PFESA-BP2 Page 50 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Number of Detects 24 Number of Non-Detects 23 Number of Distinct Detects 22 Number of Distinct Non-Detects 3 20.59 Minimum Detect 3.7 Minimum Non-Detect 2 Maximum Detect 65 Maximum Non-Detect 9500 0.945 Kurtosis Detects -0.49 Variance Detects 423.9 Percent Non-Detects 48.94% Mean Detects 24.96 SD Detects Mean of Logged Detects 2.857 SD of Logged Detects 0.908 Median Detects 20 CV Detects 0.825 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.833 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.916 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.219 Lilliefors GOF Test 5% Lilliefors Critical Value 0.177 Detected Data Not Normal at 5% Significance Level 21.01 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 15.59 KM Standard Error of Mean 2.928 24.37 95% KM Chebyshev UCL 28.35 KM SD 18.6 95% KM (BCA) UCL 21.03 95% KM (t) UCL 20.5 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 33.87 99% KM Chebyshev UCL 44.72 95% KM (z) UCL 20.4 95% KM Bootstrap t UCL 21.16 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.524 Anderson-Darling GOF Test 5% A-D Critical Value 0.761 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.137 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.181 Detected data appear Gamma Distributed at 5% Significance Level 73.67 nu star (bias corrected) 65.79 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.535 k star (bias corrected MLE) 1.371 Mean (detects) 24.96 Theta hat (MLE) 16.26 Theta star (bias corrected MLE) 18.21 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 14.47 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Page 51 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Maximum 65 Median 7.454 SD 18.85 CV 1.303 k hat (MLE) 0.28 k star (bias corrected MLE) 0.276 Theta hat (MLE) 51.68 Theta star (bias corrected MLE) 52.37 nu hat (MLE) 26.31 nu star (bias corrected) 25.96 Adjusted Level of Significance (β) 0.0449 Approximate Chi Square Value (25.96, α) 15.35 Adjusted Chi Square Value (25.96, β) 15.09 95% Gamma Approximate UCL (use when n>=50) 24.47 95% Gamma Adjusted UCL (use when n<50) 24.89 Estimates of Gamma Parameters using KM Estimates Mean (KM) 15.59 SD (KM) 18.6 Variance (KM) 345.9 SE of Mean (KM) 2.928 k hat (KM) 0.702 k star (KM) 0.672 nu hat (KM) 66.03 nu star (KM) 63.15 theta hat (KM) 22.19 theta star (KM) 23.2 45.4 80% gamma percentile (KM) 25.66 90% gamma percentile (KM) 39.51 95% gamma percentile (KM) 53.85 99% gamma percentile (KM) 88.21 95% Gamma Approximate KM-UCL (use when n>=50) 21.46 95% Gamma Adjusted KM-UCL (use when n<50) 21.68 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (63.15, α) 45.87 Adjusted Chi Square Value (63.15, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.943 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.916 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.116 Lilliefors GOF Test 5% Lilliefors Critical Value 0.177 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 15.1 Mean in Log Scale 2.025 SD in Original Scale 18.12 SD in Log Scale 1.245 95% t UCL (assumes normality of ROS data) 19.54 95% Percentile Bootstrap UCL 19.4 95% BCA Bootstrap UCL 20.02 95% Bootstrap t UCL 20.56 95% H-UCL (Log ROS) 26.53 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.018 KM Geo Mean 7.522 KM SD (logged) 1.238 95% Critical H Value (KM-Log) 2.599 KM Standard Error of Mean (logged) 0.201 95% H-UCL (KM -Log) 26.03 KM SD (logged) 1.238 95% Critical H Value (KM-Log) 2.599 KM Standard Error of Mean (logged) 0.201 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Page 52 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 2.41 605.8 95% H-Stat UCL 415.2 Mean in Original Scale 319.4 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Gamma Distributed at 5% Significance Level SD in Original Scale 1170 SD in Log Scale 2.182 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM Adjusted Gamma UCL 21.68 95% GROS Adjusted Gamma UCL 24.89 DW_EU7_PFMOAA General Statistics Total Number of Observations 47 Number of Distinct Observations 27 Number of Detects 27 Number of Non-Detects 20 Number of Distinct Detects 24 Number of Distinct Non-Detects 3 89.71 Minimum Detect 7.1 Minimum Non-Detect 5 Maximum Detect 480 Maximum Non-Detect 9500 3.862 Kurtosis Detects 17.45 Variance Detects 8047 Percent Non-Detects 42.55% Mean Detects 72.08 SD Detects Mean of Logged Detects 3.837 SD of Logged Detects 0.961 Median Detects 51 CV Detects 1.245 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.574 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.923 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.267 Lilliefors GOF Test 5% Lilliefors Critical Value 0.167 Detected Data Not Normal at 5% Significance Level 67.99 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 46.81 KM Standard Error of Mean 11.7 81.92 95% KM Chebyshev UCL 97.83 KM SD 76.08 95% KM (BCA) UCL 69.69 95% KM (t) UCL 66.46 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 119.9 99% KM Chebyshev UCL 163.3 95% KM (z) UCL 66.06 95% KM Bootstrap t UCL 85.64 90% KM Chebyshev UCL Page 53 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.597 Anderson-Darling GOF Test 5% A-D Critical Value 0.768 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.137 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.172 Detected data appear Gamma Distributed at 5% Significance Level 68.9 nu star (bias corrected) 62.58 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.276 k star (bias corrected MLE) 1.159 Mean (detects) 72.08 Theta hat (MLE) 56.49 Theta star (bias corrected MLE) 62.2 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 43.2 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 480 Median 18 SD 76.16 CV 1.763 k hat (MLE) 0.235 k star (bias corrected MLE) 0.234 Theta hat (MLE) 183.9 Theta star (bias corrected MLE) 184.5 nu hat (MLE) 22.08 nu star (bias corrected) 22.01 Adjusted Level of Significance (β) 0.0449 Approximate Chi Square Value (22.01, α) 12.34 Adjusted Chi Square Value (22.01, β) 12.11 95% Gamma Approximate UCL (use when n>=50) 77.03 95% Gamma Adjusted UCL (use when n<50) 78.49 Estimates of Gamma Parameters using KM Estimates Mean (KM) 46.81 SD (KM) 76.08 Variance (KM) 5788 SE of Mean (KM) 11.7 k hat (KM) 0.379 k star (KM) 0.369 nu hat (KM) 35.58 nu star (KM) 34.65 theta hat (KM) 123.7 theta star (KM) 127 21.86 80% gamma percentile (KM) 74.74 90% gamma percentile (KM) 134.1 95% gamma percentile (KM) 200 99% gamma percentile (KM) 367.4 95% Gamma Approximate KM-UCL (use when n>=50) 73.12 95% Gamma Adjusted KM-UCL (use when n<50) 74.17 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (34.65, α) 22.18 Adjusted Chi Square Value (34.65, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.955 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.923 Detected Data appear Lognormal at 5% Significance Level Page 54 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Lilliefors Test Statistic 0.145 Lilliefors GOF Test 5% Lilliefors Critical Value 0.167 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 45.52 Mean in Log Scale 3.003 SD in Original Scale 74.66 SD in Log Scale 1.34 95% t UCL (assumes normality of ROS data) 63.8 95% Percentile Bootstrap UCL 64.66 95% BCA Bootstrap UCL 74.85 95% Bootstrap t UCL 77.99 95% H-UCL (Log ROS) 84.61 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 3.021 KM Geo Mean 20.52 KM SD (logged) 1.295 95% Critical H Value (KM-Log) 2.666 KM Standard Error of Mean (logged) 0.202 95% H-UCL (KM -Log) 78.93 3.223 KM SD (logged) 1.295 95% Critical H Value (KM-Log) 2.666 KM Standard Error of Mean (logged) 0.202 632.1 95% H-Stat UCL 599.9 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 346.9 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Gamma Distributed at 5% Significance Level SD in Original Scale 1165 SD in Log Scale 2.039 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM Adjusted Gamma UCL 74.17 95% GROS Adjusted Gamma UCL 78.49 DW_EU7_PFO2HxA General Statistics Total Number of Observations 47 Number of Distinct Observations 28 Number of Detects 29 Number of Non-Detects 18 Number of Distinct Detects 26 Number of Distinct Non-Detects 3 Minimum Detect 4.1 Minimum Non-Detect 2 Maximum Detect 1200 Maximum Non-Detect 9200 Variance Detects 54557 Percent Non-Detects 38.3% Page 55 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 233.6 3.558 Kurtosis Detects 14.82 Mean Detects 154.1 SD Detects Mean of Logged Detects 4.276 SD of Logged Detects 1.349 Median Detects 85 CV Detects 1.516 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.586 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.926 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.282 Lilliefors GOF Test 5% Lilliefors Critical Value 0.161 Detected Data Not Normal at 5% Significance Level 156.7 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 102.5 KM Standard Error of Mean 30.64 194.4 95% KM Chebyshev UCL 236 KM SD 199.7 95% KM (BCA) UCL 161.8 95% KM (t) UCL 153.9 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 293.8 99% KM Chebyshev UCL 407.3 95% KM (z) UCL 152.9 95% KM Bootstrap t UCL 205.6 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.58 Anderson-Darling GOF Test 5% A-D Critical Value 0.783 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.154 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.169 Detected data appear Gamma Distributed at 5% Significance Level 45.33 nu star (bias corrected) 41.97 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.782 k star (bias corrected MLE) 0.724 Mean (detects) 154.1 Theta hat (MLE) 197.2 Theta star (bias corrected MLE) 212.9 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 98.37 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 1200 Median 19 SD 197 CV 2.003 k hat (MLE) 0.208 k star (bias corrected MLE) 0.209 Theta hat (MLE) 472.1 Theta star (bias corrected MLE) 470.1 nu hat (MLE) 19.59 nu star (bias corrected) 19.67 Page 56 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Adjusted Level of Significance (β) 0.0449 Approximate Chi Square Value (19.67, α) 10.61 Adjusted Chi Square Value (19.67, β) 10.4 95% Gamma Approximate UCL (use when n>=50) 182.4 95% Gamma Adjusted UCL (use when n<50) 186.1 Estimates of Gamma Parameters using KM Estimates Mean (KM) 102.5 SD (KM) 199.7 Variance (KM) 39875 SE of Mean (KM) 30.64 k hat (KM) 0.263 k star (KM) 0.261 nu hat (KM) 24.75 nu star (KM) 24.5 theta hat (KM) 389.2 theta star (KM) 393.1 13.98 80% gamma percentile (KM) 150.9 90% gamma percentile (KM) 306.6 95% gamma percentile (KM) 489.8 99% gamma percentile (KM) 974.7 95% Gamma Approximate KM-UCL (use when n>=50) 176.4 95% Gamma Adjusted KM-UCL (use when n<50) 179.5 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (24.50, α) 14.23 Adjusted Chi Square Value (24.50, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.962 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.926 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.171 Lilliefors GOF Test 5% Lilliefors Critical Value 0.161 Detected Data Not Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 99.2 Mean in Log Scale 3.222 SD in Original Scale 195.8 SD in Log Scale 1.866 95% t UCL (assumes normality of ROS data) 147.1 95% Percentile Bootstrap UCL 150.9 95% BCA Bootstrap UCL 171.2 95% Bootstrap t UCL 191.5 95% H-UCL (Log ROS) 365.2 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 3.086 KM Geo Mean 21.88 KM SD (logged) 1.989 95% Critical H Value (KM-Log) 3.577 KM Standard Error of Mean (logged) 0.307 95% H-UCL (KM -Log) 451.8 3.314 KM SD (logged) 1.989 95% Critical H Value (KM-Log) 3.577 KM Standard Error of Mean (logged) 0.307 666.3 95% H-Stat UCL 3680 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 390 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons SD in Original Scale 1128 SD in Log Scale 2.55 95% t UCL (Assumes normality) Page 57 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Nonparametric Distribution Free UCL Statistics Detected Data appear Gamma Distributed at 5% Significance Level Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use a Adjusted KM-UCL (use when k<=1 and 15 < n < 50 but k<=1) 179.5 DW_EU7_PFO3OA General Statistics Total Number of Observations 47 Number of Distinct Observations 18 Number of Detects 17 Number of Non-Detects 30 Number of Distinct Detects 16 Number of Distinct Non-Detects 3 35.68 Minimum Detect 2 Minimum Non-Detect 2 Maximum Detect 130 Maximum Non-Detect 8800 2.437 Kurtosis Detects 5.457 Variance Detects 1273 Percent Non-Detects 63.83% Mean Detects 22.05 SD Detects Mean of Logged Detects 2.258 SD of Logged Detects 1.236 Median Detects 7.6 CV Detects 1.618 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.589 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.892 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.386 Lilliefors GOF Test 5% Lilliefors Critical Value 0.207 Detected Data Not Normal at 5% Significance Level 17.16 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 10.4 KM Standard Error of Mean 3.727 21.58 95% KM Chebyshev UCL 26.64 KM SD 23.69 95% KM (BCA) UCL 16.83 95% KM (t) UCL 16.66 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 33.67 99% KM Chebyshev UCL 47.48 95% KM (z) UCL 16.53 95% KM Bootstrap t UCL 28.72 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 1.409 Anderson-Darling GOF Test 5% A-D Critical Value 0.779 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.311 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.218 Detected Data Not Gamma Distributed at 5% Significance Level Page 58 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 24.5 nu star (bias corrected) 21.51 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.721 k star (bias corrected MLE) 0.633 Mean (detects) 22.05 Theta hat (MLE) 30.6 Theta star (bias corrected MLE) 34.86 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 8.857 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 130 Median 0.01 SD 23.65 CV 2.67 k hat (MLE) 0.192 k star (bias corrected MLE) 0.194 Theta hat (MLE) 46.1 Theta star (bias corrected MLE) 45.64 nu hat (MLE) 18.06 nu star (bias corrected) 18.24 Adjusted Level of Significance (β) 0.0449 Approximate Chi Square Value (18.24, α) 9.566 Adjusted Chi Square Value (18.24, β) 9.366 95% Gamma Approximate UCL (use when n>=50) 16.89 95% Gamma Adjusted UCL (use when n<50) 17.25 Estimates of Gamma Parameters using KM Estimates Mean (KM) 10.4 SD (KM) 23.69 Variance (KM) 561.3 SE of Mean (KM) 3.727 k hat (KM) 0.193 k star (KM) 0.195 nu hat (KM) 18.11 nu star (KM) 18.29 theta hat (KM) 53.97 theta star (KM) 53.45 9.401 80% gamma percentile (KM) 13.5 90% gamma percentile (KM) 31.44 95% gamma percentile (KM) 53.97 99% gamma percentile (KM) 116.3 95% Gamma Approximate KM-UCL (use when n>=50) 19.81 95% Gamma Adjusted KM-UCL (use when n<50) 20.23 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (18.29, α) 9.601 Adjusted Chi Square Value (18.29, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.901 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.892 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.22 Lilliefors GOF Test 5% Lilliefors Critical Value 0.207 Detected Data Not Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Page 59 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Mean in Original Scale 8.962 Mean in Log Scale 0.478 SD in Original Scale 23.38 SD in Log Scale 1.909 95% t UCL (assumes normality of ROS data) 14.69 95% Percentile Bootstrap UCL 15.16 95% BCA Bootstrap UCL 18.11 95% Bootstrap t UCL 28.18 95% H-UCL (Log ROS) 26.48 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.397 KM Geo Mean 4.044 KM SD (logged) 1.09 95% Critical H Value (KM-Log) 2.429 KM Standard Error of Mean (logged) 0.18 95% H-UCL (KM -Log) 10.82 1.9 KM SD (logged) 1.09 95% Critical H Value (KM-Log) 2.429 KM Standard Error of Mean (logged) 0.18 558.9 95% H-Stat UCL 324.1 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 293.5 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Lognormal Distributed at 5% Significance Level SD in Original Scale 1084 SD in Log Scale 2.263 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 10.82 DW_EU7_PFO4DA General Statistics Total Number of Observations 47 Number of Distinct Observations 14 Number of Detects 11 Number of Non-Detects 36 Number of Distinct Detects 10 Number of Distinct Non-Detects 5 19.28 Minimum Detect 1.71 Minimum Non-Detect 1.1 Maximum Detect 67 Maximum Non-Detect 9700 3.038 Kurtosis Detects 9.504 Variance Detects 371.6 Percent Non-Detects 76.6% Mean Detects 10.39 SD Detects Mean of Logged Detects 1.546 SD of Logged Detects 1.108 Median Detects 3.3 CV Detects 1.855 Skewness Detects Page 60 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.501 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.85 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.392 Lilliefors GOF Test 5% Lilliefors Critical Value 0.251 Detected Data Not Normal at 5% Significance Level 6.824 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 3.821 KM Standard Error of Mean 1.606 8.639 95% KM Chebyshev UCL 10.82 KM SD 10.02 95% KM (BCA) UCL 7.303 95% KM (t) UCL 6.517 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 13.85 99% KM Chebyshev UCL 19.8 95% KM (z) UCL 6.463 95% KM Bootstrap t UCL 18.37 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 1.388 Anderson-Darling GOF Test 5% A-D Critical Value 0.762 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.296 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.265 Detected Data Not Gamma Distributed at 5% Significance Level 16.56 nu star (bias corrected) 13.37 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.753 k star (bias corrected MLE) 0.608 Mean (detects) 10.39 Theta hat (MLE) 13.81 Theta star (bias corrected MLE) 17.09 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 2.614 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 67 Median 0.01 SD 10.05 CV 3.846 k hat (MLE) 0.187 k star (bias corrected MLE) 0.189 Theta hat (MLE) 14 Theta star (bias corrected MLE) 13.83 nu hat (MLE) 17.55 nu star (bias corrected) 17.76 Adjusted Level of Significance (β) 0.0449 Approximate Chi Square Value (17.76, α) 9.22 Adjusted Chi Square Value (17.76, β) 9.025 95% Gamma Approximate UCL (use when n>=50) 5.037 95% Gamma Adjusted UCL (use when n<50) 5.146 Estimates of Gamma Parameters using KM Estimates Page 61 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Mean (KM) 3.821 SD (KM) 10.02 Variance (KM) 100.5 SE of Mean (KM) 1.606 k hat (KM) 0.145 k star (KM) 0.15 nu hat (KM) 13.66 nu star (KM) 14.12 theta hat (KM) 26.29 theta star (KM) 25.43 6.492 80% gamma percentile (KM) 4.164 90% gamma percentile (KM) 11.33 95% gamma percentile (KM) 21.02 99% gamma percentile (KM) 49.14 95% Gamma Approximate KM-UCL (use when n>=50) 8.108 95% Gamma Adjusted KM-UCL (use when n<50) 8.311 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (14.12, α) 6.655 Adjusted Chi Square Value (14.12, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.823 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.85 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.197 Lilliefors GOF Test 5% Lilliefors Critical Value 0.251 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 2.963 Mean in Log Scale -0.414 SD in Original Scale 9.931 SD in Log Scale 1.609 95% t UCL (assumes normality of ROS data) 5.395 95% Percentile Bootstrap UCL 5.664 95% BCA Bootstrap UCL 7.565 95% Bootstrap t UCL 15.8 95% H-UCL (Log ROS) 4.992 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.67 KM Geo Mean 1.954 KM SD (logged) 0.799 95% Critical H Value (KM-Log) 2.129 KM Standard Error of Mean (logged) 0.176 95% H-UCL (KM -Log) 3.457 KM SD (logged) 0.799 95% Critical H Value (KM-Log) 2.129 KM Standard Error of Mean (logged) 0.176 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 316.8 Mean in Log Scale 1.453 SD in Original Scale 1197 SD in Log Scale 2.28 95% t UCL (Assumes normality) 609.8 95% H-Stat UCL 219.6 Suggested UCL to Use KM H-UCL 3.457 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Lognormal Distributed at 5% Significance Level Page 62 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 4 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. 0 Number of Distinct Non-Detects 4 DW_EU7_PFO5DA General Statistics Total Number of Observations 47 Number of Distinct Observations Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 47 Number of Distinct Detects General Statistics Total Number of Observations 47 Number of Distinct Observations 35 The data set for variable DW_EU7_PFO5DA was not processed! DW_EU7_PMPA Number of Detects 38 Number of Non-Detects 9 Number of Distinct Detects 33 Number of Distinct Non-Detects 2 521.1 Minimum Detect 12 Minimum Non-Detect 10 Maximum Detect 2500 Maximum Non-Detect 8400 1.849 Kurtosis Detects 4.697 Variance Detects 271585 Percent Non-Detects 19.15% Mean Detects 519 SD Detects Mean of Logged Detects 5.602 SD of Logged Detects 1.392 Median Detects 325 CV Detects 1.004 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.83 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.938 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.187 Lilliefors GOF Test 5% Lilliefors Critical Value 0.142 Detected Data Not Normal at 5% Significance Level 581.5 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 449.6 KM Standard Error of Mean 77.74 KM SD 508.8 95% KM (BCA) UCL 580.5 95% KM (t) UCL 580.1 95% KM (Percentile Bootstrap) UCL Page 63 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 682.8 95% KM Chebyshev UCL 788.4 97.5% KM Chebyshev UCL 935 99% KM Chebyshev UCL 1223 95% KM (z) UCL 577.4 95% KM Bootstrap t UCL 617.2 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.406 Anderson-Darling GOF Test 5% A-D Critical Value 0.782 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.0941 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.148 Detected data appear Gamma Distributed at 5% Significance Level 68.33 nu star (bias corrected) 64.27 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.899 k star (bias corrected MLE) 0.846 Mean (detects) 519 Theta hat (MLE) 577.2 Theta star (bias corrected MLE) 613.7 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 440.9 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 2500 Median 280 SD 504 CV 1.143 k hat (MLE) 0.369 k star (bias corrected MLE) 0.36 Theta hat (MLE) 1195 Theta star (bias corrected MLE) 1226 nu hat (MLE) 34.68 nu star (bias corrected) 33.8 Adjusted Level of Significance (β) 0.0449 Approximate Chi Square Value (33.80, α) 21.5 Adjusted Chi Square Value (33.80, β) 21.19 95% Gamma Approximate UCL (use when n>=50) 693.1 95% Gamma Adjusted UCL (use when n<50) 703.2 Estimates of Gamma Parameters using KM Estimates Mean (KM) 449.6 SD (KM) 508.8 Variance (KM) 258886 SE of Mean (KM) 77.74 k hat (KM) 0.781 k star (KM) 0.745 nu hat (KM) 73.39 nu star (KM) 70.03 theta hat (KM) 575.9 theta star (KM) 603.4 51.27 80% gamma percentile (KM) 737.2 90% gamma percentile (KM) 1112 95% gamma percentile (KM) 1496 99% gamma percentile (KM) 2409 95% Gamma Approximate KM-UCL (use when n>=50) 608.2 95% Gamma Adjusted KM-UCL (use when n<50) 614.1 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (70.03, α) 51.77 Adjusted Chi Square Value (70.03, β) Page 64 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.911 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.938 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.157 Lilliefors GOF Test 5% Lilliefors Critical Value 0.142 Detected Data Not Lognormal at 5% Significance Level Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 438.6 Mean in Log Scale 5.191 SD in Original Scale 502.2 SD in Log Scale 1.635 95% t UCL (assumes normality of ROS data) 561.5 95% Percentile Bootstrap UCL 559.4 95% BCA Bootstrap UCL 577.8 95% Bootstrap t UCL 589.7 95% H-UCL (Log ROS) 1441 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 5.152 KM Geo Mean 172.7 KM SD (logged) 1.706 95% Critical H Value (KM-Log) 3.19 KM Standard Error of Mean (logged) 0.261 95% H-UCL (KM -Log) 1652 5.267 KM SD (logged) 1.706 95% Critical H Value (KM-Log) 3.19 KM Standard Error of Mean (logged) 0.261 946 95% H-Stat UCL 4168 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 688.3 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Gamma Distributed at 5% Significance Level SD in Original Scale 1052 SD in Log Scale 2.003 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use a Adjusted KM-UCL (use when k<=1 and 15 < n < 50 but k<=1) 614.1 DW_EU8_HFPO-DA General Statistics Total Number of Observations 357 Number of Distinct Observations 168 Number of Detects 309 Number of Non-Detects 48 Page 65 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Number of Distinct Detects 163 Number of Distinct Non-Detects 8 131.9 Minimum Detect 0.92 Minimum Non-Detect 0.567 Maximum Detect 1300 Maximum Non-Detect 4.3 4.857 Kurtosis Detects 32.75 Variance Detects 17387 Percent Non-Detects 13.45% Mean Detects 72.67 SD Detects Mean of Logged Detects 3.455 SD of Logged Detects 1.256 Median Detects 32 CV Detects 1.815 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.524 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.293 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0508 Detected Data Not Normal at 5% Significance Level 74.51 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 63.11 KM Standard Error of Mean 6.619 82.97 95% KM Chebyshev UCL 91.96 KM SD 124.9 95% KM (BCA) UCL 74.13 95% KM (t) UCL 74.03 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 104.4 99% KM Chebyshev UCL 129 95% KM (z) UCL 74 95% KM Bootstrap t UCL 76.48 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 9.643 Anderson-Darling GOF Test 5% A-D Critical Value 0.8 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.142 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.0536 Detected Data Not Gamma Distributed at 5% Significance Level 447.6 nu star (bias corrected) 444.5 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.724 k star (bias corrected MLE) 0.719 Mean (detects) 72.67 Theta hat (MLE) 100.3 Theta star (bias corrected MLE) 101 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 62.9 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 1300 Median 24 Page 66 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 SD 125.1 CV 1.989 k hat (MLE) 0.376 k star (bias corrected MLE) 0.374 Theta hat (MLE) 167.5 Theta star (bias corrected MLE) 168 nu hat (MLE) 268.2 nu star (bias corrected) 267.2 Adjusted Level of Significance (β) 0.0493 Approximate Chi Square Value (267.25, α) 230.4 Adjusted Chi Square Value (267.25, β) 230.3 95% Gamma Approximate UCL (use when n>=50) 72.96 95% Gamma Adjusted UCL (use when n<50) 73.01 Estimates of Gamma Parameters using KM Estimates Mean (KM) 63.11 SD (KM) 124.9 Variance (KM) 15588 SE of Mean (KM) 6.619 k hat (KM) 0.256 k star (KM) 0.255 nu hat (KM) 182.4 nu star (KM) 182.2 theta hat (KM) 247 theta star (KM) 247.3 151.9 80% gamma percentile (KM) 92.32 90% gamma percentile (KM) 189.1 95% gamma percentile (KM) 303.6 99% gamma percentile (KM) 607.4 95% Gamma Approximate KM-UCL (use when n>=50) 75.66 95% Gamma Adjusted KM-UCL (use when n<50) 75.71 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (182.23, α) 152 Adjusted Chi Square Value (182.23, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.983 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.389 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0436 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0508 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 63.22 Mean in Log Scale 3.09 SD in Original Scale 125 SD in Log Scale 1.508 95% t UCL (assumes normality of ROS data) 74.13 95% Percentile Bootstrap UCL 74.17 95% BCA Bootstrap UCL 77.42 95% Bootstrap t UCL 76.39 95% H-UCL (Log ROS) 84.2 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 3.028 KM Geo Mean 20.66 KM SD (logged) 1.608 95% Critical H Value (KM-Log) 2.688 KM Standard Error of Mean (logged) 0.0887 95% H-UCL (KM -Log) 94.6 3.057 KM SD (logged) 1.608 95% Critical H Value (KM-Log) 2.688 KM Standard Error of Mean (logged) 0.0887 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 63.13 Mean in Log Scale Page 67 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 74.04 95% H-Stat UCL 87.9 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Lognormal Distributed at 5% Significance Level SD in Original Scale 125 SD in Log Scale 1.551 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 94.6 DW_EU8_PEPA General Statistics Total Number of Observations 208 Number of Distinct Observations 47 Number of Detects 53 Number of Non-Detects 155 Number of Distinct Detects 43 Number of Distinct Non-Detects 5 78.29 Minimum Detect 6.5 Minimum Non-Detect 11 Maximum Detect 380 Maximum Non-Detect 10000 2.157 Kurtosis Detects 4.744 Variance Detects 6130 Percent Non-Detects 74.52% Mean Detects 70.86 SD Detects Mean of Logged Detects 3.82 SD of Logged Detects 0.91 Median Detects 39 CV Detects 1.105 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.716 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 8.346E-13 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.26 Lilliefors GOF Test 5% Lilliefors Critical Value 0.121 Detected Data Not Normal at 5% Significance Level 32.11 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 25.12 KM Standard Error of Mean 3.437 35.43 95% KM Chebyshev UCL 40.1 KM SD 47.73 95% KM (BCA) UCL 32.91 95% KM (t) UCL 30.8 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 46.59 99% KM Chebyshev UCL 59.32 95% KM (z) UCL 30.78 95% KM Bootstrap t UCL 31.76 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only Page 68 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 A-D Test Statistic 2.041 Anderson-Darling GOF Test 5% A-D Critical Value 0.773 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.19 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.125 Detected Data Not Gamma Distributed at 5% Significance Level 135.1 nu star (bias corrected) 128.8 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.275 k star (bias corrected MLE) 1.215 Mean (detects) 70.86 Theta hat (MLE) 55.59 Theta star (bias corrected MLE) 58.31 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 18.34 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 380 Median 0.01 SD 49.9 CV 2.721 k hat (MLE) 0.15 k star (bias corrected MLE) 0.151 Theta hat (MLE) 122 Theta star (bias corrected MLE) 121.2 nu hat (MLE) 62.51 nu star (bias corrected) 62.94 Adjusted Level of Significance (β) 0.0488 Approximate Chi Square Value (62.94, α) 45.69 Adjusted Chi Square Value (62.94, β) 45.59 95% Gamma Approximate UCL (use when n>=50) 25.26 95% Gamma Adjusted UCL (use when n<50) 25.32 Estimates of Gamma Parameters using KM Estimates Mean (KM) 25.12 SD (KM) 47.73 Variance (KM) 2279 SE of Mean (KM) 3.437 k hat (KM) 0.277 k star (KM) 0.276 nu hat (KM) 115.2 nu star (KM) 114.9 theta hat (KM) 90.69 theta star (KM) 90.95 91.02 80% gamma percentile (KM) 37.68 90% gamma percentile (KM) 74.77 95% gamma percentile (KM) 118 99% gamma percentile (KM) 231.4 95% Gamma Approximate KM-UCL (use when n>=50) 31.67 95% Gamma Adjusted KM-UCL (use when n<50) 31.72 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (114.91, α) 91.17 Adjusted Chi Square Value (114.91, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.958 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.112 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.128 Lilliefors GOF Test Page 69 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 5% Lilliefors Critical Value 0.121 Detected Data Not Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 23.13 Mean in Log Scale 2.062 SD in Original Scale 48.46 SD in Log Scale 1.458 95% t UCL (assumes normality of ROS data) 28.68 95% Percentile Bootstrap UCL 29.3 95% BCA Bootstrap UCL 29.76 95% Bootstrap t UCL 30.47 95% H-UCL (Log ROS) 29.52 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.575 KM Geo Mean 13.13 KM SD (logged) 0.929 95% Critical H Value (KM-Log) 2.086 KM Standard Error of Mean (logged) 0.0969 95% H-UCL (KM -Log) 23.12 KM SD (logged) 0.929 95% Critical H Value (KM-Log) 2.086 KM Standard Error of Mean (logged) 0.0969 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 50.1 Mean in Log Scale 2.717 SD in Original Scale 348.2 SD in Log Scale 0.938 95% t UCL (Assumes normality) 89.99 95% H-Stat UCL 26.92 Suggested UCL to Use KM H-UCL 23.12 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Lognormal Distributed at 5% Significance Level 5 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. 0 Number of Distinct Non-Detects 5 DW_EU8_PFECA-G General Statistics Total Number of Observations 208 Number of Distinct Observations Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 208 Number of Distinct Detects Page 70 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 General Statistics Total Number of Observations 214 Number of Distinct Observations 14 The data set for variable DW_EU8_PFECA-G was not processed! DW_EU8_PFESA-BP1 Number of Detects 1 Number of Non-Detects 213 Number of Distinct Detects 1 Number of Distinct Non-Detects 13 DW_EU8_PFESA-BP2 General Statistics Warning: Only one distinct data value was detected! ProUCL (or any other software) should not be used on such a data set! It is suggested to use alternative site specific values determined by the Project Team to estimate environmental parameters (e.g., EPC, BTV). The data set for variable DW_EU8_PFESA-BP1 was not processed! Total Number of Observations 214 Number of Distinct Observations 82 Number of Detects 122 Number of Non-Detects 92 Number of Distinct Detects 77 Number of Distinct Non-Detects 7 Minimum Detect 1.1 Minimum Non-Detect 1.1 Maximum Detect 63 Maximum Non-Detect 9500 Variance Detects 101.1 Percent Non-Detects 42.99% Mean Detects 11.17 SD Detects 10.06 Median Detects 8.2 CV Detects 0.9 Skewness Detects 2.443 Kurtosis Detects 7.593 Mean of Logged Detects 2.105 SD of Logged Detects 0.79 Lilliefors GOF Test Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.76 Normal GOF Test on Detected Observations Only 5% Lilliefors Critical Value 0.0806 Detected Data Not Normal at 5% Significance Level Detected Data Not Normal at 5% Significance Level 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.234 8.08 Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 7.008 KM Standard Error of Mean 0.634 8.909 95% KM Chebyshev UCL 9.769 KM SD 9.114 95% KM (BCA) UCL 8.043 95% KM (t) UCL 8.055 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 10.96 99% KM Chebyshev UCL 13.31 95% KM (z) UCL 8.05 95% KM Bootstrap t UCL 8.255 90% KM Chebyshev UCL Page 71 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Gamma GOF Tests on Detected Observations Only A-D Test Statistic 1.377 Anderson-Darling GOF Test 5% A-D Critical Value 0.768 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.13 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.0851 Detected Data Not Gamma Distributed at 5% Significance Level 432.2 nu star (bias corrected) 422.9 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.771 k star (bias corrected MLE) 1.733 Mean (detects) 11.17 Theta hat (MLE) 6.306 Theta star (bias corrected MLE) 6.445 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 6.48 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 63 Median 3.3 SD 9.359 CV 1.444 k hat (MLE) 0.283 k star (bias corrected MLE) 0.282 Theta hat (MLE) 22.92 Theta star (bias corrected MLE) 22.99 nu hat (MLE) 121 nu star (bias corrected) 120.6 Adjusted Level of Significance (β) 0.0489 Approximate Chi Square Value (120.62, α) 96.26 Adjusted Chi Square Value (120.62, β) 96.12 95% Gamma Approximate UCL (use when n>=50) 8.12 95% Gamma Adjusted UCL (use when n<50) 8.133 Estimates of Gamma Parameters using KM Estimates Mean (KM) 7.008 SD (KM) 9.114 Variance (KM) 83.06 SE of Mean (KM) 0.634 k hat (KM) 0.591 k star (KM) 0.586 nu hat (KM) 253.1 nu star (KM) 250.9 theta hat (KM) 11.85 theta star (KM) 11.96 215 80% gamma percentile (KM) 11.55 90% gamma percentile (KM) 18.32 95% gamma percentile (KM) 25.43 99% gamma percentile (KM) 42.66 95% Gamma Approximate KM-UCL (use when n>=50) 8.17 95% Gamma Adjusted KM-UCL (use when n<50) 8.178 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (250.86, α) 215.2 Adjusted Chi Square Value (250.86, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.982 Shapiro Wilk GOF Test Page 72 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 5% Shapiro Wilk P Value 0.606 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.082 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0806 Detected Data Not Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 7.079 Mean in Log Scale 1.321 SD in Original Scale 8.968 SD in Log Scale 1.174 95% t UCL (assumes normality of ROS data) 8.092 95% Percentile Bootstrap UCL 8.094 95% BCA Bootstrap UCL 8.261 95% Bootstrap t UCL 8.269 95% H-UCL (Log ROS) 8.98 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.28 KM Geo Mean 3.597 KM SD (logged) 1.152 95% Critical H Value (KM-Log) 2.279 KM Standard Error of Mean (logged) 0.0803 95% H-UCL (KM -Log) 8.361 1.3 KM SD (logged) 1.152 95% Critical H Value (KM-Log) 2.279 KM Standard Error of Mean (logged) 0.0803 66.52 95% H-Stat UCL 11.57 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 29.88 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Lognormal Distributed at 5% Significance Level SD in Original Scale 324.4 SD in Log Scale 1.356 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 8.361 DW_EU8_PFMOAA General Statistics Total Number of Observations 214 Number of Distinct Observations 85 Number of Detects 144 Number of Non-Detects 70 Number of Distinct Detects 81 Number of Distinct Non-Detects 6 Minimum Detect 4.6 Minimum Non-Detect 1.13 Maximum Detect 260 Maximum Non-Detect 9500 Page 73 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 38.1 3.344 Kurtosis Detects 14.25 Variance Detects 1451 Percent Non-Detects 32.71% Mean Detects 32.74 SD Detects Mean of Logged Detects 3.068 SD of Logged Detects 0.888 Median Detects 21 CV Detects 1.163 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.655 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.24 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0742 Detected Data Not Normal at 5% Significance Level 27.08 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 22.86 KM Standard Error of Mean 2.377 29.99 95% KM Chebyshev UCL 33.22 KM SD 34.43 95% KM (BCA) UCL 27.65 95% KM (t) UCL 26.79 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 37.71 99% KM Chebyshev UCL 46.51 95% KM (z) UCL 26.77 95% KM Bootstrap t UCL 27.34 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 2.794 Anderson-Darling GOF Test 5% A-D Critical Value 0.775 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.125 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.0798 Detected Data Not Gamma Distributed at 5% Significance Level 383.2 nu star (bias corrected) 376.6 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.331 k star (bias corrected MLE) 1.308 Mean (detects) 32.74 Theta hat (MLE) 24.61 Theta star (bias corrected MLE) 25.04 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 22.17 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 260 Median 11 SD 34.74 CV 1.567 k hat (MLE) 0.284 k star (bias corrected MLE) 0.284 Theta hat (MLE) 77.93 Theta star (bias corrected MLE) 78.17 Page 74 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 nu hat (MLE) 121.7 nu star (bias corrected) 121.4 Adjusted Level of Significance (β) 0.0489 Approximate Chi Square Value (121.36, α) 96.92 Adjusted Chi Square Value (121.36, β) 96.77 95% Gamma Approximate UCL (use when n>=50) 27.75 95% Gamma Adjusted UCL (use when n<50) 27.8 Estimates of Gamma Parameters using KM Estimates Mean (KM) 22.86 SD (KM) 34.43 Variance (KM) 1185 SE of Mean (KM) 2.377 k hat (KM) 0.441 k star (KM) 0.438 nu hat (KM) 188.8 nu star (KM) 187.5 theta hat (KM) 51.84 theta star (KM) 52.2 156.6 80% gamma percentile (KM) 37.24 90% gamma percentile (KM) 63.51 95% gamma percentile (KM) 92.04 99% gamma percentile (KM) 163.1 95% Gamma Approximate KM-UCL (use when n>=50) 27.34 95% Gamma Adjusted KM-UCL (use when n<50) 27.37 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (187.45, α) 156.8 Adjusted Chi Square Value (187.45, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.959 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.00245 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0626 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0742 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 23.2 Mean in Log Scale 2.414 SD in Original Scale 34.12 SD in Log Scale 1.249 95% t UCL (assumes normality of ROS data) 27.05 95% Percentile Bootstrap UCL 27.38 95% BCA Bootstrap UCL 28.01 95% Bootstrap t UCL 27.56 95% H-UCL (Log ROS) 29.87 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.207 KM Geo Mean 9.087 KM SD (logged) 1.49 95% Critical H Value (KM-Log) 2.605 KM Standard Error of Mean (logged) 0.122 95% H-UCL (KM -Log) 35.95 2.419 KM SD (logged) 1.49 95% Critical H Value (KM-Log) 2.605 KM Standard Error of Mean (logged) 0.122 82.37 95% H-Stat UCL 34.44 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 45.67 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons SD in Original Scale 324.9 SD in Log Scale 1.338 95% t UCL (Assumes normality) Page 75 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Lognormal Distributed at 5% Significance Level Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 35.95 DW_EU8_PFO2HxA General Statistics Total Number of Observations 214 Number of Distinct Observations 100 Number of Detects 150 Number of Non-Detects 64 Number of Distinct Detects 97 Number of Distinct Non-Detects 5 87.96 Minimum Detect 2 Minimum Non-Detect 1.1 Maximum Detect 560 Maximum Non-Detect 9200 3.053 Kurtosis Detects 11.04 Variance Detects 7736 Percent Non-Detects 29.91% Mean Detects 60.66 SD Detects Mean of Logged Detects 3.34 SD of Logged Detects 1.291 Median Detects 31.5 CV Detects 1.45 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.64 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.252 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0727 Detected Data Not Normal at 5% Significance Level 52.26 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 43.15 KM Standard Error of Mean 5.39 59.32 95% KM Chebyshev UCL 66.64 KM SD 78.39 95% KM (BCA) UCL 52.61 95% KM (t) UCL 52.05 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 76.81 99% KM Chebyshev UCL 96.78 95% KM (z) UCL 52.02 95% KM Bootstrap t UCL 54.57 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 2.161 Anderson-Darling GOF Test 5% A-D Critical Value 0.794 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.106 Kolmogorov-Smirnov GOF Page 76 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 5% K-S Critical Value 0.0795 Detected Data Not Gamma Distributed at 5% Significance Level 233.4 nu star (bias corrected) 230.1 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.778 k star (bias corrected MLE) 0.767 Mean (detects) 60.66 Theta hat (MLE) 77.97 Theta star (bias corrected MLE) 79.1 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 42.57 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 560 Median 15 SD 78.63 CV 1.847 k hat (MLE) 0.259 k star (bias corrected MLE) 0.258 Theta hat (MLE) 164.5 Theta star (bias corrected MLE) 164.8 nu hat (MLE) 110.8 nu star (bias corrected) 110.5 Adjusted Level of Significance (β) 0.0489 Approximate Chi Square Value (110.54, α) 87.28 Adjusted Chi Square Value (110.54, β) 87.14 95% Gamma Approximate UCL (use when n>=50) 53.92 95% Gamma Adjusted UCL (use when n<50) 54 Estimates of Gamma Parameters using KM Estimates Mean (KM) 43.15 SD (KM) 78.39 Variance (KM) 6144 SE of Mean (KM) 5.39 k hat (KM) 0.303 k star (KM) 0.302 nu hat (KM) 129.7 nu star (KM) 129.2 theta hat (KM) 142.4 theta star (KM) 142.9 103.8 80% gamma percentile (KM) 66.28 90% gamma percentile (KM) 127.2 95% gamma percentile (KM) 197 99% gamma percentile (KM) 378.3 95% Gamma Approximate KM-UCL (use when n>=50) 53.63 95% Gamma Adjusted KM-UCL (use when n<50) 53.71 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (129.21, α) 104 Adjusted Chi Square Value (129.21, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.968 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.0289 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0457 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0727 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Page 77 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 43.19 Mean in Log Scale 2.476 SD in Original Scale 78.31 SD in Log Scale 1.779 95% t UCL (assumes normality of ROS data) 52.03 95% Percentile Bootstrap UCL 52.33 95% BCA Bootstrap UCL 53.3 95% Bootstrap t UCL 54.3 95% H-UCL (Log ROS) 82.54 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.395 KM Geo Mean 10.97 KM SD (logged) 1.826 95% Critical H Value (KM-Log) 2.962 KM Standard Error of Mean (logged) 0.126 95% H-UCL (KM -Log) 84.11 2.391 KM SD (logged) 1.826 95% Critical H Value (KM-Log) 2.962 KM Standard Error of Mean (logged) 0.126 100.8 95% H-Stat UCL 105.4 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 64.52 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Lognormal Distributed at 5% Significance Level SD in Original Scale 321.2 SD in Log Scale 1.929 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 84.11 DW_EU8_PFO3OA General Statistics Total Number of Observations 214 Number of Distinct Observations 60 Number of Detects 79 Number of Non-Detects 135 Number of Distinct Detects 54 Number of Distinct Non-Detects 7 11.3 Minimum Detect 1.4 Minimum Non-Detect 1.1 Maximum Detect 69 Maximum Non-Detect 8800 3.932 Kurtosis Detects 18.11 Variance Detects 127.8 Percent Non-Detects 63.08% Mean Detects 8.335 SD Detects Mean of Logged Detects 1.682 SD of Logged Detects 0.842 Median Detects 4.6 CV Detects 1.356 Skewness Detects Page 78 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.552 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.27 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0998 Detected Data Not Normal at 5% Significance Level 4.757 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 3.88 KM Standard Error of Mean 0.535 5.484 95% KM Chebyshev UCL 6.211 KM SD 7.7 95% KM (BCA) UCL 4.869 95% KM (t) UCL 4.763 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 7.219 99% KM Chebyshev UCL 9.2 95% KM (z) UCL 4.759 95% KM Bootstrap t UCL 5.186 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 3.911 Anderson-Darling GOF Test 5% A-D Critical Value 0.775 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.171 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.103 Detected Data Not Gamma Distributed at 5% Significance Level 202.6 nu star (bias corrected) 196.2 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.282 k star (bias corrected MLE) 1.242 Mean (detects) 8.335 Theta hat (MLE) 6.501 Theta star (bias corrected MLE) 6.711 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 3.103 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 69 Median 0.01 SD 7.936 CV 2.557 k hat (MLE) 0.215 k star (bias corrected MLE) 0.215 Theta hat (MLE) 14.45 Theta star (bias corrected MLE) 14.44 nu hat (MLE) 91.93 nu star (bias corrected) 91.97 Adjusted Level of Significance (β) 0.0489 Approximate Chi Square Value (91.97, α) 70.86 Adjusted Chi Square Value (91.97, β) 70.73 95% Gamma Approximate UCL (use when n>=50) 4.028 95% Gamma Adjusted UCL (use when n<50) 4.035 Page 79 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Estimates of Gamma Parameters using KM Estimates Mean (KM) 3.88 SD (KM) 7.7 Variance (KM) 59.3 SE of Mean (KM) 0.535 k hat (KM) 0.254 k star (KM) 0.253 nu hat (KM) 108.7 nu star (KM) 108.5 theta hat (KM) 15.28 theta star (KM) 15.31 85.3 80% gamma percentile (KM) 5.662 90% gamma percentile (KM) 11.63 95% gamma percentile (KM) 18.7 99% gamma percentile (KM) 37.49 95% Gamma Approximate KM-UCL (use when n>=50) 4.926 95% Gamma Adjusted KM-UCL (use when n<50) 4.934 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (108.47, α) 85.44 Adjusted Chi Square Value (108.47, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.923 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 6.7185E-5 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.12 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0998 Detected Data Not Lognormal at 5% Significance Level Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 3.525 Mean in Log Scale 0.16 SD in Original Scale 7.786 SD in Log Scale 1.494 95% t UCL (assumes normality of ROS data) 4.404 95% Percentile Bootstrap UCL 4.444 95% BCA Bootstrap UCL 4.655 95% Bootstrap t UCL 4.747 95% H-UCL (Log ROS) 4.683 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.731 KM Geo Mean 2.077 KM SD (logged) 0.909 95% Critical H Value (KM-Log) 2.073 KM Standard Error of Mean (logged) 0.0663 95% H-UCL (KM -Log) 3.573 0.706 KM SD (logged) 0.909 95% Critical H Value (KM-Log) 2.073 KM Standard Error of Mean (logged) 0.0663 59.1 95% H-Stat UCL 5.08 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 25.15 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Data do not follow a Discernible Distribution at 5% Significance Level SD in Original Scale 300.6 SD in Log Scale 1.206 95% t UCL (Assumes normality) Suggested UCL to Use Page 80 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. 95% KM (Chebyshev) UCL 6.211 DW_EU8_PFO4DA General Statistics Total Number of Observations 214 Number of Distinct Observations 32 Number of Detects 25 Number of Non-Detects 189 Number of Distinct Detects 22 Number of Distinct Non-Detects 11 3.567 Minimum Detect 1.1 Minimum Non-Detect 1.1 Maximum Detect 17 Maximum Non-Detect 9700 2.351 Kurtosis Detects 6.53 Variance Detects 12.72 Percent Non-Detects 88.32% Mean Detects 4.169 SD Detects Mean of Logged Detects 1.173 SD of Logged Detects 0.698 Median Detects 3.3 CV Detects 0.855 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.747 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.918 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.214 Lilliefors GOF Test 5% Lilliefors Critical Value 0.173 Detected Data Not Normal at 5% Significance Level 1.722 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 1.525 KM Standard Error of Mean 0.115 1.869 95% KM Chebyshev UCL 2.025 KM SD 1.568 95% KM (BCA) UCL 1.736 95% KM (t) UCL 1.714 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 2.241 99% KM Chebyshev UCL 2.666 95% KM (z) UCL 1.714 95% KM Bootstrap t UCL 1.809 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.565 Anderson-Darling GOF Test 5% A-D Critical Value 0.756 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.145 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.177 Detected data appear Gamma Distributed at 5% Significance Level Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 2.118 k star (bias corrected MLE) 1.891 Page 81 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 105.9 nu star (bias corrected) 94.54 Mean (detects) 4.169 Theta hat (MLE) 1.968 Theta star (bias corrected MLE) 2.205 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 0.588 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 17 Median 0.01 SD 1.807 CV 3.073 k hat (MLE) 0.237 k star (bias corrected MLE) 0.237 Theta hat (MLE) 2.476 Theta star (bias corrected MLE) 2.479 nu hat (MLE) 101.6 nu star (bias corrected) 101.5 Adjusted Level of Significance (β) 0.0489 Approximate Chi Square Value (101.55, α) 79.3 Adjusted Chi Square Value (101.55, β) 79.16 95% Gamma Approximate UCL (use when n>=50) 0.753 95% Gamma Adjusted UCL (use when n<50) 0.754 Estimates of Gamma Parameters using KM Estimates Mean (KM) 1.525 SD (KM) 1.568 Variance (KM) 2.459 SE of Mean (KM) 0.115 k hat (KM) 0.946 k star (KM) 0.936 nu hat (KM) 404.7 nu star (KM) 400.4 theta hat (KM) 1.612 theta star (KM) 1.63 354.7 80% gamma percentile (KM) 2.467 90% gamma percentile (KM) 3.569 95% gamma percentile (KM) 4.677 99% gamma percentile (KM) 7.263 95% Gamma Approximate KM-UCL (use when n>=50) 1.72 95% Gamma Adjusted KM-UCL (use when n<50) 1.721 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (400.41, α) 355 Adjusted Chi Square Value (400.41, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.968 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.918 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.109 Lilliefors GOF Test 5% Lilliefors Critical Value 0.173 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 0.929 Mean in Log Scale -0.911 SD in Original Scale 1.744 SD in Log Scale 1.286 95% t UCL (assumes normality of ROS data) 1.126 95% Percentile Bootstrap UCL 1.133 95% BCA Bootstrap UCL 1.18 95% Bootstrap t UCL 1.189 Page 82 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 95% H-UCL (Log ROS) 1.137 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.267 KM Geo Mean 1.305 KM SD (logged) 0.427 95% Critical H Value (KM-Log) 1.768 KM Standard Error of Mean (logged) 0.0366 95% H-UCL (KM -Log) 1.506 KM SD (logged) 0.427 95% Critical H Value (KM-Log) 1.768 KM Standard Error of Mean (logged) 0.0366 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 25.01 Mean in Log Scale 0.22 SD in Original Scale 331.5 SD in Log Scale 0.94 95% t UCL (Assumes normality) 62.45 95% H-Stat UCL 2.219 Suggested UCL to Use 95% KM Approximate Gamma UCL 1.72 95% GROS Approximate Gamma UCL 0.753 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Gamma Distributed at 5% Significance Level 5 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. 0 Number of Distinct Non-Detects 5 DW_EU8_PFO5DA General Statistics Total Number of Observations 208 Number of Distinct Observations Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 208 Number of Distinct Detects General Statistics Total Number of Observations 208 Number of Distinct Observations 94 The data set for variable DW_EU8_PFO5DA was not processed! DW_EU8_PMPA Page 83 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Number of Detects 166 Number of Non-Detects 42 Number of Distinct Detects 91 Number of Distinct Non-Detects 3 207.9 Minimum Detect 11 Minimum Non-Detect 5.3 Maximum Detect 1600 Maximum Non-Detect 8400 4.044 Kurtosis Detects 20.48 Variance Detects 43233 Percent Non-Detects 20.19% Mean Detects 153.5 SD Detects Mean of Logged Detects 4.571 SD of Logged Detects 0.908 Median Detects 93 CV Detects 1.354 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.572 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.263 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0692 Detected Data Not Normal at 5% Significance Level 147.2 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 124.2 KM Standard Error of Mean 13.58 164.9 95% KM Chebyshev UCL 183.4 KM SD 194.8 95% KM (BCA) UCL 145.8 95% KM (t) UCL 146.6 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 209 99% KM Chebyshev UCL 259.3 95% KM (z) UCL 146.5 95% KM Bootstrap t UCL 151.5 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 5.224 Anderson-Darling GOF Test 5% A-D Critical Value 0.778 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.155 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.0742 Detected Data Not Gamma Distributed at 5% Significance Level 405.1 nu star (bias corrected) 399.1 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.22 k star (bias corrected MLE) 1.202 Mean (detects) 153.5 Theta hat (MLE) 125.8 Theta star (bias corrected MLE) 127.7 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 122.8 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Page 84 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Maximum 1600 Median 76 SD 195.5 CV 1.592 k hat (MLE) 0.331 k star (bias corrected MLE) 0.329 Theta hat (MLE) 371.1 Theta star (bias corrected MLE) 372.9 nu hat (MLE) 137.6 nu star (bias corrected) 137 Adjusted Level of Significance (β) 0.0488 Approximate Chi Square Value (136.99, α) 110.9 Adjusted Chi Square Value (136.99, β) 110.8 95% Gamma Approximate UCL (use when n>=50) 151.6 95% Gamma Adjusted UCL (use when n<50) 151.8 Estimates of Gamma Parameters using KM Estimates Mean (KM) 124.2 SD (KM) 194.8 Variance (KM) 37952 SE of Mean (KM) 13.58 k hat (KM) 0.406 k star (KM) 0.404 nu hat (KM) 169 nu star (KM) 167.9 theta hat (KM) 305.6 theta star (KM) 307.6 138.8 80% gamma percentile (KM) 200.6 90% gamma percentile (KM) 350.2 95% gamma percentile (KM) 514.3 99% gamma percentile (KM) 926.7 95% Gamma Approximate KM-UCL (use when n>=50) 150.1 95% Gamma Adjusted KM-UCL (use when n<50) 150.3 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (167.93, α) 139 Adjusted Chi Square Value (167.93, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.973 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.0773 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0805 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0692 Detected Data Not Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 125.6 Mean in Log Scale 4.166 SD in Original Scale 193.9 SD in Log Scale 1.17 95% t UCL (assumes normality of ROS data) 147.8 95% Percentile Bootstrap UCL 148.8 95% BCA Bootstrap UCL 154.5 95% Bootstrap t UCL 153.9 95% H-UCL (Log ROS) 154 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 3.996 KM Geo Mean 54.39 KM SD (logged) 1.413 95% Critical H Value (KM-Log) 2.524 KM Standard Error of Mean (logged) 0.0985 95% H-UCL (KM -Log) 189 KM SD (logged) 1.413 95% Critical H Value (KM-Log) 2.524 KM Standard Error of Mean (logged) 0.0985 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Page 85 of 86 December 2019 Output C-8 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 5 through 8 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Mean in Original Scale 143.7 Mean in Log Scale 3.993 SD in Original Scale 343.3 SD in Log Scale 1.486 95% t UCL (Assumes normality) 183 95% H-Stat UCL 213.9 Suggested UCL to Use KM H-UCL 189 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Lognormal Distributed at 5% Significance Level Page 86 of 86 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 UCL Statistics for Data Sets with Non-Detects User Selected Options Date/Time of Computation ProUCL 5.112/6/2019 11:53:21 AM From File WorkSheet.xls Full Precision OFF Confidence Coefficient 95% Number of Bootstrap Operations 2000 Page 1 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 General Statistics Total Number of Observations 287 Number of Distinct Observations 120 DW_EU9_HFPO-DA Number of Detects 236 Number of Non-Detects 51 Number of Distinct Detects 115 Number of Distinct Non-Detects 6 83.23 Minimum Detect 1.71 Minimum Non-Detect 0.591 Maximum Detect 610 Maximum Non-Detect 4 3.111 Kurtosis Detects 13.45 Variance Detects 6928 Percent Non-Detects 17.77% Mean Detects 65.31 SD Detects Mean of Logged Detects 3.577 SD of Logged Detects 1.122 Median Detects 35.5 CV Detects 1.274 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.683 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.222 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0581 Detected Data Not Normal at 5% Significance Level 61.96 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 53.91 KM Standard Error of Mean 4.686 67.97 95% KM Chebyshev UCL 74.34 KM SD 79.21 95% KM (BCA) UCL 62.62 95% KM (t) UCL 61.65 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 83.18 99% KM Chebyshev UCL 100.5 95% KM (z) UCL 61.62 95% KM Bootstrap t UCL 62.64 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 3.442 Anderson-Darling GOF Test 5% A-D Critical Value 0.786 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.0894 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.0613 Detected Data Not Gamma Distributed at 5% Significance Level 454.3 nu star (bias corrected) 449.9 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.963 k star (bias corrected MLE) 0.953 Mean (detects) 65.31 Theta hat (MLE) 67.85 Theta star (bias corrected MLE) 68.52 nu hat (MLE) Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs Page 2 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 53.71 GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 610 Median 24 SD 79.48 CV 1.48 k hat (MLE) 0.36 k star (bias corrected MLE) 0.358 Theta hat (MLE) 149.3 Theta star (bias corrected MLE) 149.9 nu hat (MLE) 206.5 nu star (bias corrected) 205.7 Adjusted Level of Significance (β) 0.0492 Approximate Chi Square Value (205.68, α) 173.5 Adjusted Chi Square Value (205.68, β) 173.3 95% Gamma Approximate UCL (use when n>=50) 63.67 95% Gamma Adjusted UCL (use when n<50) 63.73 Estimates of Gamma Parameters using KM Estimates Mean (KM) 53.91 SD (KM) 79.21 Variance (KM) 6274 SE of Mean (KM) 4.686 k hat (KM) 0.463 k star (KM) 0.461 nu hat (KM) 265.9 nu star (KM) 264.5 theta hat (KM) 116.4 theta star (KM) 117 227.7 80% gamma percentile (KM) 88.15 90% gamma percentile (KM) 148.3 95% gamma percentile (KM) 213.2 99% gamma percentile (KM) 374.1 95% Gamma Approximate KM-UCL (use when n>=50) 62.59 95% Gamma Adjusted KM-UCL (use when n<50) 62.64 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (264.48, α) 227.8 Adjusted Chi Square Value (264.48, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.978 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.146 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0542 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0581 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 54.3 Mean in Log Scale 3.133 SD in Original Scale 79.09 SD in Log Scale 1.416 95% t UCL (assumes normality of ROS data) 62.01 95% Percentile Bootstrap UCL 62.37 95% BCA Bootstrap UCL 63.36 95% Bootstrap t UCL 62.86 95% H-UCL (Log ROS) 77.14 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.942 KM Geo Mean 18.96 KM SD (logged) 1.717 95% Critical H Value (KM-Log) 2.822 KM Standard Error of Mean (logged) 0.113 95% H-UCL (KM -Log) 110.3 Page 3 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 3.032 KM SD (logged) 1.717 95% Critical H Value (KM-Log) 2.822 KM Standard Error of Mean (logged) 0.113 61.74 95% H-Stat UCL 89.7 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 54.02 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Lognormal Distributed at 5% Significance Level SD in Original Scale 79.28 SD in Log Scale 1.561 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 110.3 DW_EU9_PEPA General Statistics Total Number of Observations 167 Number of Distinct Observations 48 Number of Detects 63 Number of Non-Detects 104 Number of Distinct Detects 44 Number of Distinct Non-Detects 5 75.4 Minimum Detect 12 Minimum Non-Detect 11 Maximum Detect 460 Maximum Non-Detect 10000 2.688 Kurtosis Detects 9.744 Variance Detects 5686 Percent Non-Detects 62.28% Mean Detects 80.65 SD Detects Mean of Logged Detects 4.09 SD of Logged Detects 0.753 Median Detects 55 CV Detects 0.935 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.729 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 2.776E-15 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.234 Lilliefors GOF Test 5% Lilliefors Critical Value 0.111 Detected Data Not Normal at 5% Significance Level Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 38.48 KM Standard Error of Mean 4.499 KM SD 57.01 95% KM (BCA) UCL 46.71 Page 4 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 46.17 51.97 95% KM Chebyshev UCL 58.09 95% KM (t) UCL 45.92 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 66.57 99% KM Chebyshev UCL 83.24 95% KM (z) UCL 45.88 95% KM Bootstrap t UCL 48.01 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 1.472 Anderson-Darling GOF Test 5% A-D Critical Value 0.765 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.139 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.114 Detected Data Not Gamma Distributed at 5% Significance Level 228.6 nu star (bias corrected) 219.1 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.815 k star (bias corrected MLE) 1.739 Mean (detects) 80.65 Theta hat (MLE) 44.45 Theta star (bias corrected MLE) 46.38 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 30.68 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 460 Median 0.01 SD 60.43 CV 1.97 k hat (MLE) 0.165 k star (bias corrected MLE) 0.166 Theta hat (MLE) 185.6 Theta star (bias corrected MLE) 184.4 nu hat (MLE) 55.22 nu star (bias corrected) 55.56 Adjusted Level of Significance (β) 0.0486 Approximate Chi Square Value (55.56, α) 39.43 Adjusted Chi Square Value (55.56, β) 39.31 95% Gamma Approximate UCL (use when n>=50) 43.23 95% Gamma Adjusted UCL (use when n<50) 43.36 Estimates of Gamma Parameters using KM Estimates Mean (KM) 38.48 SD (KM) 57.01 Variance (KM) 3251 SE of Mean (KM) 4.499 k hat (KM) 0.455 k star (KM) 0.451 nu hat (KM) 152.1 nu star (KM) 150.7 theta hat (KM) 84.48 theta star (KM) 85.27 123.1 80% gamma percentile (KM) 62.81 90% gamma percentile (KM) 106.3 95% gamma percentile (KM) 153.3 99% gamma percentile (KM) 270 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (150.71, α) 123.3 Adjusted Chi Square Value (150.71, β) Page 5 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 95% Gamma Approximate KM-UCL (use when n>=50) 47.02 95% Gamma Adjusted KM-UCL (use when n<50) 47.1 Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.976 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.477 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0871 Lilliefors GOF Test 5% Lilliefors Critical Value 0.111 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 36.54 Mean in Log Scale 2.78 SD in Original Scale 57.78 SD in Log Scale 1.309 95% t UCL (assumes normality of ROS data) 43.93 95% Percentile Bootstrap UCL 44.05 95% BCA Bootstrap UCL 45.16 95% Bootstrap t UCL 46.09 95% H-UCL (Log ROS) 48.67 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 3.098 KM Geo Mean 22.16 KM SD (logged) 0.922 95% Critical H Value (KM-Log) 2.097 KM Standard Error of Mean (logged) 0.0782 95% H-UCL (KM -Log) 39.4 3.04 KM SD (logged) 0.922 95% Critical H Value (KM-Log) 2.097 KM Standard Error of Mean (logged) 0.0782 118.4 95% H-Stat UCL 47.67 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 68.69 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Lognormal Distributed at 5% Significance Level SD in Original Scale 388.5 SD in Log Scale 1.12 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 39.4 DW_EU9_PFECA-G General Statistics Total Number of Observations 168 Number of Distinct Observations 8 Page 6 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Number of Detects 2 Number of Non-Detects 166 Number of Distinct Detects 2 Number of Distinct Non-Detects 6 Minimum Detect 2.3 Minimum Non-Detect 1.1 Maximum Detect 2.5 Maximum Non-Detect 9600 Variance Detects 0.02 Percent Non-Detects 98.81% Mean Detects 2.4 SD Detects 0.141 Median Detects 2.4 CV Detects 0.0589 Skewness Detects N/A Kurtosis Detects N/A Warning: Data set has only 2 Detected Values. This is not enough to compute meaningful or reliable statistics and estimates. Normal GOF Test on Detects Only Mean of Logged Detects 0.875 SD of Logged Detects 0.059 N/A Not Enough Data to Perform GOF Test Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 1.116 KM Standard Error of Mean 0.0164 1.166 95% KM Chebyshev UCL 1.188 KM SD 0.146 95% KM (BCA) UCL N/A 95% KM (t) UCL 1.144 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 1.219 99% KM Chebyshev UCL 1.28 95% KM (z) UCL 1.143 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only Not Enough Data to Perform GOF Test Gamma Statistics on Detected Data Only k hat (MLE) 575.7 k star (bias corrected MLE) N/A Theta hat (MLE) 0.00417 Theta star (bias corrected MLE) N/A nu hat (MLE) 2303 nu star (bias corrected) N/A Estimates of Gamma Parameters using KM Estimates Mean (KM) 1.116 SD (KM) 0.146 Mean (detects) 2.4 Variance (KM) 0.0212 SE of Mean (KM) 0.0164 k hat (KM) 58.66 k star (KM) 57.62 nu hat (KM) 19711 nu star (KM) 19360 theta hat (KM) 0.019 theta star (KM) 0.0194 80% gamma percentile (KM) 1.238 90% gamma percentile (KM) 1.309 95% gamma percentile (KM) 1.369 99% gamma percentile (KM) 1.487 Gamma Kaplan-Meier (KM) Statistics Adjusted Level of Significance (β) 0.0486 Page 7 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 1.135 95% Gamma Adjusted KM-UCL (use when n<50) 1.136 Lognormal GOF Test on Detected Observations Only Not Enough Data to Perform GOF Test Lognormal ROS Statistics Using Imputed Non-Detects Approximate Chi Square Value (N/A, α) 19037 Adjusted Chi Square Value (N/A, β) 19035 95% Gamma Approximate KM-UCL (use when n>=50) Mean in Original Scale 1.074 Mean in Log Scale 0.0194 SD in Original Scale 0.357 SD in Log Scale 0.323 95% t UCL (assumes normality of ROS data) 1.12 95% Percentile Bootstrap UCL 1.117 95% BCA Bootstrap UCL 1.124 95% Bootstrap t UCL 1.122 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.105 KM Geo Mean 1.111 95% H-UCL (Log ROS) 1.122 KM SD (logged) 0.0872 95% Critical H Value (KM-Log) N/A KM Standard Error of Mean (logged) 0.00982 95% H-UCL (KM -Log) N/A 0.155 KM SD (logged) 0.0872 95% Critical H Value (KM-Log) N/A KM Standard Error of Mean (logged) 0.00982 79.36 95% H-Stat UCL 2.49 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 32.08 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Data do not follow a Discernible Distribution at 5% Significance Level SD in Original Scale 370.5 SD in Log Scale 1.071 95% t UCL (Assumes normality) 95% KM (BCA) UCL N/A Warning: One or more Recommended UCL(s) not available! Suggested UCL to Use 95% KM (t) UCL 1.144 KM H-UCL N/A 17 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU9_PFESA-BP1 General Statistics Total Number of Observations 179 Number of Distinct Observations Number of Detects 0 Number of Non-Detects 179 Page 8 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 0 Number of Distinct Non-Detects 17 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Distinct Detects General Statistics Total Number of Observations 179 Number of Distinct Observations 70 The data set for variable DW_EU9_PFESA-BP1 was not processed! DW_EU9_PFESA-BP2 Number of Detects 86 Number of Non-Detects 93 Number of Distinct Detects 60 Number of Distinct Non-Detects 10 7.142 Minimum Detect 2.3 Minimum Non-Detect 1.1 Maximum Detect 32 Maximum Non-Detect 9500 1.209 Kurtosis Detects 0.85 Variance Detects 51.01 Percent Non-Detects 51.96% Mean Detects 11.04 SD Detects Mean of Logged Detects 2.208 SD of Logged Detects 0.631 Median Detects 8.8 CV Detects 0.647 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.865 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 8.933E-11 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.18 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0957 Detected Data Not Normal at 5% Significance Level 7.063 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 6.159 KM Standard Error of Mean 0.549 7.806 95% KM Chebyshev UCL 8.553 KM SD 7.096 95% KM (BCA) UCL 7.021 95% KM (t) UCL 7.067 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 9.588 99% KM Chebyshev UCL 11.62 95% KM (z) UCL 7.062 95% KM Bootstrap t UCL 7.215 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.871 Anderson-Darling GOF Test 5% A-D Critical Value 0.76 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.109 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.0973 Detected Data Not Gamma Distributed at 5% Significance Level Detected Data Not Gamma Distributed at 5% Significance Level Page 9 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 470.1 nu star (bias corrected) 455 Gamma Statistics on Detected Data Only k hat (MLE) 2.733 k star (bias corrected MLE) 2.645 Mean (detects) 11.04 Theta hat (MLE) 4.04 Theta star (bias corrected MLE) 4.174 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 5.718 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 32 Median 2.7 SD 7.288 CV 1.275 k hat (MLE) 0.303 k star (bias corrected MLE) 0.301 Theta hat (MLE) 18.88 Theta star (bias corrected MLE) 18.97 nu hat (MLE) 108.4 nu star (bias corrected) 107.9 Adjusted Level of Significance (β) 0.0487 Approximate Chi Square Value (107.91, α) 84.94 Adjusted Chi Square Value (107.91, β) 84.77 95% Gamma Approximate UCL (use when n>=50) 7.264 95% Gamma Adjusted UCL (use when n<50) 7.278 Estimates of Gamma Parameters using KM Estimates Mean (KM) 6.159 SD (KM) 7.096 Variance (KM) 50.36 SE of Mean (KM) 0.549 k hat (KM) 0.753 k star (KM) 0.744 nu hat (KM) 269.7 nu star (KM) 266.5 theta hat (KM) 8.176 theta star (KM) 8.274 229.4 80% gamma percentile (KM) 10.1 90% gamma percentile (KM) 15.24 95% gamma percentile (KM) 20.5 99% gamma percentile (KM) 33.02 95% Gamma Approximate KM-UCL (use when n>=50) 7.146 95% Gamma Adjusted KM-UCL (use when n<50) 7.155 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (266.50, α) 229.7 Adjusted Chi Square Value (266.50, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.969 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.148 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0716 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0957 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 6.532 Mean in Log Scale 1.402 SD in Original Scale 6.707 SD in Log Scale 1.003 Page 10 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 95% t UCL (assumes normality of ROS data) 7.36 95% Percentile Bootstrap UCL 7.409 95% BCA Bootstrap UCL 7.508 95% Bootstrap t UCL 7.491 95% H-UCL (Log ROS) 7.913 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.17 KM Geo Mean 3.223 KM SD (logged) 1.147 95% Critical H Value (KM-Log) 2.299 KM Standard Error of Mean (logged) 0.0888 95% H-UCL (KM -Log) 7.583 1.25 KM SD (logged) 1.147 95% Critical H Value (KM-Log) 2.299 KM Standard Error of Mean (logged) 0.0888 78.57 95% H-Stat UCL 12.66 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 34.71 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Lognormal Distributed at 5% Significance Level SD in Original Scale 354.9 SD in Log Scale 1.424 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 7.583 DW_EU9_PFMOAA General Statistics Total Number of Observations 179 Number of Distinct Observations 72 Number of Detects 100 Number of Non-Detects 79 Number of Distinct Detects 63 Number of Distinct Non-Detects 10 36.51 Minimum Detect 3.2 Minimum Non-Detect 1.14 Maximum Detect 190 Maximum Non-Detect 9500 2.37 Kurtosis Detects 6.199 Variance Detects 1333 Percent Non-Detects 44.13% Mean Detects 38.93 SD Detects Mean of Logged Detects 3.331 SD of Logged Detects 0.819 Median Detects 27 CV Detects 0.938 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.733 Normal GOF Test on Detected Observations Only Page 11 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.202 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0889 Detected Data Not Normal at 5% Significance Level 27.26 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 22.83 KM Standard Error of Mean 2.499 30.33 95% KM Chebyshev UCL 33.72 KM SD 33 95% KM (BCA) UCL 27.2 95% KM (t) UCL 26.96 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 38.44 99% KM Chebyshev UCL 47.7 95% KM (z) UCL 26.94 95% KM Bootstrap t UCL 27.73 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 1.376 Anderson-Darling GOF Test 5% A-D Critical Value 0.768 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.105 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.091 Detected Data Not Gamma Distributed at 5% Significance Level 331.7 nu star (bias corrected) 323 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.658 k star (bias corrected MLE) 1.615 Mean (detects) 38.93 Theta hat (MLE) 23.48 Theta star (bias corrected MLE) 24.1 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 22 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 190 Median 11 SD 33.32 CV 1.514 k hat (MLE) 0.231 k star (bias corrected MLE) 0.231 Theta hat (MLE) 95.17 Theta star (bias corrected MLE) 95.23 nu hat (MLE) 82.77 nu star (bias corrected) 82.72 Adjusted Level of Significance (β) 0.0487 Approximate Chi Square Value (82.72, α) 62.76 Adjusted Chi Square Value (82.72, β) 62.62 95% Gamma Approximate UCL (use when n>=50) 29 95% Gamma Adjusted UCL (use when n<50) 29.07 Estimates of Gamma Parameters using KM Estimates Mean (KM) 22.83 SD (KM) 33 Variance (KM) 1089 SE of Mean (KM) 2.499 Page 12 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 k hat (KM) 0.478 k star (KM) 0.474 nu hat (KM) 171.3 nu star (KM) 169.7 theta hat (KM) 47.71 theta star (KM) 48.15 140.4 80% gamma percentile (KM) 37.39 90% gamma percentile (KM) 62.43 95% gamma percentile (KM) 89.36 99% gamma percentile (KM) 155.9 95% Gamma Approximate KM-UCL (use when n>=50) 27.56 95% Gamma Adjusted KM-UCL (use when n<50) 27.6 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (169.74, α) 140.6 Adjusted Chi Square Value (169.74, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.977 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.398 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0635 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0889 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 23.99 Mean in Log Scale 2.485 SD in Original Scale 32.1 SD in Log Scale 1.223 95% t UCL (assumes normality of ROS data) 27.95 95% Percentile Bootstrap UCL 28.32 95% BCA Bootstrap UCL 28.64 95% Bootstrap t UCL 29.16 95% H-UCL (Log ROS) 31.49 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.015 KM Geo Mean 7.5 KM SD (logged) 1.659 95% Critical H Value (KM-Log) 2.821 KM Standard Error of Mean (logged) 0.134 95% H-UCL (KM -Log) 42.2 2.335 KM SD (logged) 1.659 95% Critical H Value (KM-Log) 2.821 KM Standard Error of Mean (logged) 0.134 94.98 95% H-Stat UCL 42.66 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 51.11 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Lognormal Distributed at 5% Significance Level SD in Original Scale 355 SD in Log Scale 1.498 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Suggested UCL to Use KM H-UCL 42.2 Page 13 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU9_PFO2HxA General Statistics Total Number of Observations 179 Number of Distinct Observations 91 Number of Detects 109 Number of Non-Detects 70 Number of Distinct Detects 82 Number of Distinct Non-Detects 10 82.71 Minimum Detect 2 Minimum Non-Detect 1.1 Maximum Detect 530 Maximum Non-Detect 9200 2.891 Kurtosis Detects 10.91 Variance Detects 6841 Percent Non-Detects 39.11% Mean Detects 67.03 SD Detects Mean of Logged Detects 3.543 SD of Logged Detects 1.291 Median Detects 44 CV Detects 1.234 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.706 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.216 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0852 Detected Data Not Normal at 5% Significance Level 50.63 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 41.75 KM Standard Error of Mean 5.438 58.06 95% KM Chebyshev UCL 65.45 KM SD 72.06 95% KM (BCA) UCL 50.86 95% KM (t) UCL 50.74 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 75.71 99% KM Chebyshev UCL 95.85 95% KM (z) UCL 50.69 95% KM Bootstrap t UCL 52.63 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.643 Anderson-Darling GOF Test 5% A-D Critical Value 0.789 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.0741 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.0901 Detected data appear Gamma Distributed at 5% Significance Level 193 nu star (bias corrected) 189 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.885 k star (bias corrected MLE) 0.867 Mean (detects) 67.03 Theta hat (MLE) 75.74 Theta star (bias corrected MLE) 77.33 nu hat (MLE) Page 14 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 40.85 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 530 Median 11 SD 72.28 CV 1.769 k hat (MLE) 0.22 k star (bias corrected MLE) 0.22 Theta hat (MLE) 185.5 Theta star (bias corrected MLE) 185.5 nu hat (MLE) 78.82 nu star (bias corrected) 78.83 Adjusted Level of Significance (β) 0.0487 Approximate Chi Square Value (78.83, α) 59.38 Adjusted Chi Square Value (78.83, β) 59.24 95% Gamma Approximate UCL (use when n>=50) 54.23 95% Gamma Adjusted UCL (use when n<50) 54.36 Estimates of Gamma Parameters using KM Estimates Mean (KM) 41.75 SD (KM) 72.06 Variance (KM) 5192 SE of Mean (KM) 5.438 k hat (KM) 0.336 k star (KM) 0.334 nu hat (KM) 120.2 nu star (KM) 119.5 theta hat (KM) 124.4 theta star (KM) 125.1 95.06 80% gamma percentile (KM) 65.53 90% gamma percentile (KM) 121.4 95% gamma percentile (KM) 184.4 99% gamma percentile (KM) 346.2 95% Gamma Approximate KM-UCL (use when n>=50) 52.37 95% Gamma Adjusted KM-UCL (use when n<50) 52.47 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (119.47, α) 95.23 Adjusted Chi Square Value (119.47, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.945 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 3.5475E-4 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.109 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0852 Detected Data Not Lognormal at 5% Significance Level Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 41.92 Mean in Log Scale 2.426 SD in Original Scale 71.7 SD in Log Scale 1.821 95% t UCL (assumes normality of ROS data) 50.78 95% Percentile Bootstrap UCL 51.34 95% BCA Bootstrap UCL 52.94 95% Bootstrap t UCL 52.36 95% H-UCL (Log ROS) 89.34 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution Page 15 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 KM Mean (logged) 2.226 KM Geo Mean 9.26 KM SD (logged) 1.955 95% Critical H Value (KM-Log) 3.153 KM Standard Error of Mean (logged) 0.148 95% H-UCL (KM -Log) 99.26 2.23 KM SD (logged) 1.955 95% Critical H Value (KM-Log) 3.153 KM Standard Error of Mean (logged) 0.148 111.4 95% H-Stat UCL 136 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 68.3 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Gamma Distributed at 5% Significance Level SD in Original Scale 348.4 SD in Log Scale 2.082 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM Approximate Gamma UCL 52.37 DW_EU9_PFO3OA General Statistics Total Number of Observations 179 Number of Distinct Observations 65 Number of Detects 63 Number of Non-Detects 116 Number of Distinct Detects 52 Number of Distinct Non-Detects 13 10.36 Minimum Detect 1.44 Minimum Non-Detect 1.1 Maximum Detect 59 Maximum Non-Detect 8800 2.779 Kurtosis Detects 9.147 Variance Detects 107.3 Percent Non-Detects 64.8% Mean Detects 9.344 SD Detects Mean of Logged Detects 1.848 SD of Logged Detects 0.833 Median Detects 5.9 CV Detects 1.109 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.677 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.253 Lilliefors GOF Test 5% Lilliefors Critical Value 0.111 Detected Data Not Normal at 5% Significance Level Detected Data Not Normal at 5% Significance Level Page 16 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 5.193 Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 4.188 KM Standard Error of Mean 0.568 5.892 95% KM Chebyshev UCL 6.663 KM SD 7.37 95% KM (BCA) UCL 5.306 95% KM (t) UCL 5.127 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 7.735 99% KM Chebyshev UCL 9.839 95% KM (z) UCL 5.122 95% KM Bootstrap t UCL 5.428 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 2.041 Anderson-Darling GOF Test 5% A-D Critical Value 0.77 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.146 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.114 Detected Data Not Gamma Distributed at 5% Significance Level 181.1 nu star (bias corrected) 173.8 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.437 k star (bias corrected MLE) 1.38 Mean (detects) 9.344 Theta hat (MLE) 6.501 Theta star (bias corrected MLE) 6.773 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 3.383 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 59 Median 0.01 SD 7.591 CV 2.244 k hat (MLE) 0.21 k star (bias corrected MLE) 0.21 Theta hat (MLE) 16.12 Theta star (bias corrected MLE) 16.1 nu hat (MLE) 75.15 nu star (bias corrected) 75.22 Adjusted Level of Significance (β) 0.0487 Approximate Chi Square Value (75.22, α) 56.24 Adjusted Chi Square Value (75.22, β) 56.11 95% Gamma Approximate UCL (use when n>=50) 4.525 95% Gamma Adjusted UCL (use when n<50) 4.536 Estimates of Gamma Parameters using KM Estimates Mean (KM) 4.188 SD (KM) 7.37 Variance (KM) 54.32 SE of Mean (KM) 0.568 k hat (KM) 0.323 k star (KM) 0.321 nu hat (KM) 115.6 nu star (KM) 115 theta hat (KM) 12.97 theta star (KM) 13.04 80% gamma percentile (KM) 6.523 90% gamma percentile (KM) 12.24 95% gamma percentile (KM) 18.74 99% gamma percentile (KM) 35.47 Page 17 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 91.05 95% Gamma Approximate KM-UCL (use when n>=50) 5.278 95% Gamma Adjusted KM-UCL (use when n<50) 5.288 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (114.98, α) 91.22 Adjusted Chi Square Value (114.98, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.954 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.0462 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0846 Lilliefors GOF Test 5% Lilliefors Critical Value 0.111 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 3.871 Mean in Log Scale 0.311 SD in Original Scale 7.373 SD in Log Scale 1.467 95% t UCL (assumes normality of ROS data) 4.782 95% Percentile Bootstrap UCL 4.782 95% BCA Bootstrap UCL 4.996 95% Bootstrap t UCL 5.107 95% H-UCL (Log ROS) 5.331 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.769 KM Geo Mean 2.157 KM SD (logged) 0.976 95% Critical H Value (KM-Log) 2.147 KM Standard Error of Mean (logged) 0.0774 95% H-UCL (KM -Log) 4.063 0.814 KM SD (logged) 0.976 95% Critical H Value (KM-Log) 2.147 KM Standard Error of Mean (logged) 0.0774 71.41 95% H-Stat UCL 7.309 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 30.76 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Lognormal Distributed at 5% Significance Level SD in Original Scale 328.9 SD in Log Scale 1.357 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 4.063 DW_EU9_PFO4DA Page 18 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 General Statistics Total Number of Observations 179 Number of Distinct Observations 32 Number of Detects 20 Number of Non-Detects 159 Number of Distinct Detects 18 Number of Distinct Non-Detects 16 3.265 Minimum Detect 1.1 Minimum Non-Detect 1.1 Maximum Detect 15 Maximum Non-Detect 9700 2.446 Kurtosis Detects 6.693 Variance Detects 10.66 Percent Non-Detects 88.83% Mean Detects 3.937 SD Detects Mean of Logged Detects 1.149 SD of Logged Detects 0.64 Median Detects 2.9 CV Detects 0.829 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.714 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.905 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.304 Lilliefors GOF Test 5% Lilliefors Critical Value 0.192 Detected Data Not Normal at 5% Significance Level 1.649 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 1.448 KM Standard Error of Mean 0.113 1.787 95% KM Chebyshev UCL 1.94 KM SD 1.426 95% KM (BCA) UCL 1.659 95% KM (t) UCL 1.634 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 2.153 99% KM Chebyshev UCL 2.572 95% KM (z) UCL 1.633 95% KM Bootstrap t UCL 1.777 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.791 Anderson-Darling GOF Test 5% A-D Critical Value 0.75 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.22 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.196 Detected Data Not Gamma Distributed at 5% Significance Level 96.55 nu star (bias corrected) 83.4 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 2.414 k star (bias corrected MLE) 2.085 Mean (detects) 3.937 Theta hat (MLE) 1.631 Theta star (bias corrected MLE) 1.888 nu hat (MLE) Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs Page 19 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 0.472 This is especially true when the sample size is small. Maximum 15 Median 0.01 SD 1.636 CV 3.466 k hat (MLE) 0.234 k star (bias corrected MLE) 0.233 Theta hat (MLE) 2.02 Theta star (bias corrected MLE) 2.022 nu hat (MLE) 83.63 nu star (bias corrected) 83.56 Adjusted Level of Significance (β) 0.0487 Approximate Chi Square Value (83.56, α) 63.49 Adjusted Chi Square Value (83.56, β) 63.35 95% Gamma Approximate UCL (use when n>=50) 0.621 95% Gamma Adjusted UCL (use when n<50) 0.622 Estimates of Gamma Parameters using KM Estimates Mean (KM) 1.448 SD (KM) 1.426 Variance (KM) 2.034 SE of Mean (KM) 0.113 k hat (KM) 1.03 k star (KM) 1.017 nu hat (KM) 368.9 nu star (KM) 364 theta hat (KM) 1.405 theta star (KM) 1.424 320.5 80% gamma percentile (KM) 2.327 90% gamma percentile (KM) 3.32 95% gamma percentile (KM) 4.311 99% gamma percentile (KM) 6.611 95% Gamma Approximate KM-UCL (use when n>=50) 1.643 95% Gamma Adjusted KM-UCL (use when n<50) 1.644 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (364.01, α) 320.8 Adjusted Chi Square Value (364.01, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.955 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.905 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.17 Lilliefors GOF Test 5% Lilliefors Critical Value 0.192 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 0.736 Mean in Log Scale -1.388 SD in Original Scale 1.598 SD in Log Scale 1.467 95% t UCL (assumes normality of ROS data) 0.933 95% Percentile Bootstrap UCL 0.947 95% BCA Bootstrap UCL 1.027 95% Bootstrap t UCL 1.041 95% H-UCL (Log ROS) 0.977 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.23 KM Geo Mean 1.258 KM SD (logged) 0.402 95% Critical H Value (KM-Log) 1.765 KM Standard Error of Mean (logged) 0.0328 95% H-UCL (KM -Log) 1.439 KM SD (logged) 0.402 95% Critical H Value (KM-Log) 1.765 KM Standard Error of Mean (logged) 0.0328 Page 20 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 0.255 75.61 95% H-Stat UCL 2.865 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 30.78 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Lognormal Distributed at 5% Significance Level SD in Original Scale 362.7 SD in Log Scale 1.105 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 1.439 DW_EU9_PFO5DA General Statistics Total Number of Observations 168 Number of Distinct Observations 9 Number of Detects 3 Number of Non-Detects 165 Number of Distinct Detects 3 Number of Distinct Non-Detects 6 Minimum Detect 6 Minimum Non-Detect 1.1 Maximum Detect 8.9 Maximum Non-Detect 11000 Variance Detects 2.123 Percent Non-Detects 98.21% Mean Detects 7.533 SD Detects 1.457 Median Detects 7.7 CV Detects 0.193 Skewness Detects -0.508 Kurtosis Detects N/A Warning: Data set has only 3 Detected Values. This is not enough to compute meaningful or reliable statistics and estimates. Normal GOF Test on Detects Only Mean of Logged Detects 2.006 SD of Logged Detects 0.199 Shapiro Wilk Test Statistic 0.99 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.767 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.212 Lilliefors GOF Test 5% Lilliefors Critical Value 0.425 Detected Data appear Normal at 5% Significance Level Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs Page 21 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 KM Mean 1.222 KM Standard Error of Mean 0.087 KM SD 0.893 95% KM (BCA) UCL N/A 95% KM (t) UCL 1.366 95% KM (Percentile Bootstrap) UCL N/A 95% KM (z) UCL 1.365 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL 1.483 95% KM Chebyshev UCL 1.602 N/A 97.5% KM Chebyshev UCL 1.766 99% KM Chebyshev UCL 2.088 231.9 nu star (bias corrected) N/A Gamma GOF Tests on Detected Observations Only Not Enough Data to Perform GOF Test Gamma Statistics on Detected Data Only k hat (MLE) 38.65 k star (bias corrected MLE) Mean (detects) 7.533 Theta hat (MLE) 0.195 Theta star (bias corrected MLE) N/A nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 0.292 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 8.9 Median 0.01 SD 1.172 CV 4.022 k hat (MLE) 0.248 k star (bias corrected MLE) 0.247 Theta hat (MLE) 1.177 Theta star (bias corrected MLE) 1.179 nu hat (MLE) 83.22 nu star (bias corrected) 83.07 Adjusted Level of Significance (β) 0.0486 Approximate Chi Square Value (83.07, α) 63.06 Adjusted Chi Square Value (83.07, β) 62.91 95% Gamma Approximate UCL (use when n>=50) 0.384 95% Gamma Adjusted UCL (use when n<50) N/A Estimates of Gamma Parameters using KM Estimates Mean (KM) 1.222 SD (KM) 0.893 Variance (KM) 0.798 SE of Mean (KM) 0.087 k hat (KM) 1.872 k star (KM) 1.843 nu hat (KM) 629.1 nu star (KM) 619.2 theta hat (KM) 0.653 theta star (KM) 0.663 562 80% gamma percentile (KM) 1.847 90% gamma percentile (KM) 2.423 95% gamma percentile (KM) 2.976 99% gamma percentile (KM) 4.206 95% Gamma Approximate KM-UCL (use when n>=50) 1.345 95% Gamma Adjusted KM-UCL (use when n<50) 1.347 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (619.16, α) 562.4 Adjusted Chi Square Value (619.16, β) Page 22 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.977 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.767 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.236 Lilliefors GOF Test 5% Lilliefors Critical Value 0.425 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 1.185 Mean in Log Scale -0.228 SD in Original Scale 1.26 SD in Log Scale 0.894 95% t UCL (assumes normality of ROS data) 1.346 95% Percentile Bootstrap UCL 1.356 95% BCA Bootstrap UCL 1.378 95% Bootstrap t UCL 1.382 95% H-UCL (Log ROS) 1.37 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.132 KM Geo Mean 1.141 KM SD (logged) 0.262 95% Critical H Value (KM-Log) 1.707 KM Standard Error of Mean (logged) 0.0255 95% H-UCL (KM -Log) 1.222 0.218 KM SD (logged) 0.262 95% Critical H Value (KM-Log) 1.707 KM Standard Error of Mean (logged) 0.0255 91.87 95% H-Stat UCL 3.179 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 37.69 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 424.6 SD in Log Scale 1.201 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 1.366 DW_EU9_PMPA General Statistics Total Number of Observations 167 Number of Distinct Observations 82 Number of Detects 127 Number of Non-Detects 40 Number of Distinct Detects 80 Number of Distinct Non-Detects 4 Page 23 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 276.6 Minimum Detect 10 Minimum Non-Detect 5.3 Maximum Detect 2300 Maximum Non-Detect 8400 4.042 Kurtosis Detects 25.22 Variance Detects 76533 Percent Non-Detects 23.95% Mean Detects 219.3 SD Detects Mean of Logged Detects 4.822 SD of Logged Detects 1.116 Median Detects 120 CV Detects 1.262 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.668 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.225 Lilliefors GOF Test 5% Lilliefors Critical Value 0.079 Detected Data Not Normal at 5% Significance Level 202.9 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 169.1 KM Standard Error of Mean 20.06 229.2 95% KM Chebyshev UCL 256.5 KM SD 257.5 95% KM (BCA) UCL 204.5 95% KM (t) UCL 202.2 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 294.4 99% KM Chebyshev UCL 368.7 95% KM (z) UCL 202.1 95% KM Bootstrap t UCL 212.6 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.939 Anderson-Darling GOF Test 5% A-D Critical Value 0.783 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.085 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.0849 Detected Data Not Gamma Distributed at 5% Significance Level 257.8 nu star (bias corrected) 253 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.015 k star (bias corrected MLE) 0.996 Mean (detects) 219.3 Theta hat (MLE) 216 Theta star (bias corrected MLE) 220.1 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 167.1 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 2300 Median 81 SD 258.4 CV 1.546 Page 24 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 k hat (MLE) 0.279 k star (bias corrected MLE) 0.278 Theta hat (MLE) 599.2 Theta star (bias corrected MLE) 601.4 nu hat (MLE) 93.16 nu star (bias corrected) 92.82 Adjusted Level of Significance (β) 0.0486 Approximate Chi Square Value (92.82, α) 71.6 Adjusted Chi Square Value (92.82, β) 71.44 95% Gamma Approximate UCL (use when n>=50) 216.7 95% Gamma Adjusted UCL (use when n<50) 217.2 Estimates of Gamma Parameters using KM Estimates Mean (KM) 169.1 SD (KM) 257.5 Variance (KM) 66300 SE of Mean (KM) 20.06 k hat (KM) 0.431 k star (KM) 0.427 nu hat (KM) 144 nu star (KM) 142.7 theta hat (KM) 392.2 theta star (KM) 395.6 115.9 80% gamma percentile (KM) 274.7 90% gamma percentile (KM) 471.8 95% gamma percentile (KM) 686.5 99% gamma percentile (KM) 1223 95% Gamma Approximate KM-UCL (use when n>=50) 207.8 95% Gamma Adjusted KM-UCL (use when n<50) 208.2 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (142.72, α) 116.1 Adjusted Chi Square Value (142.72, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.976 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.265 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0746 Lilliefors GOF Test 5% Lilliefors Critical Value 0.079 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 169.9 Mean in Log Scale 4.233 SD in Original Scale 256.7 SD in Log Scale 1.475 95% t UCL (assumes normality of ROS data) 202.8 95% Percentile Bootstrap UCL 205.2 95% BCA Bootstrap UCL 211.3 95% Bootstrap t UCL 211.1 95% H-UCL (Log ROS) 275.9 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 4.086 KM Geo Mean 59.48 KM SD (logged) 1.649 95% Critical H Value (KM-Log) 2.8 KM Standard Error of Mean (logged) 0.129 95% H-UCL (KM -Log) 331.7 4.099 KM SD (logged) 1.649 95% Critical H Value (KM-Log) 2.8 KM Standard Error of Mean (logged) 0.129 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 193.2 Mean in Log Scale SD in Original Scale 404.5 SD in Log Scale 1.702 Page 25 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 244.9 95% H-Stat UCL 374.6 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Lognormal Distributed at 5% Significance Level 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 331.7 DW_EU10_HFPO-DA General Statistics Total Number of Observations 35 Number of Distinct Observations 29 Number of Detects 27 Number of Non-Detects 8 Number of Distinct Detects 25 Number of Distinct Non-Detects 4 19.64 Minimum Detect 0.866 Minimum Non-Detect 2.6 Maximum Detect 76.4 Maximum Non-Detect 4 1.597 Kurtosis Detects 2.184 Variance Detects 385.7 Percent Non-Detects 22.86% Mean Detects 17.47 SD Detects Mean of Logged Detects 2.164 SD of Logged Detects 1.318 Median Detects 9.9 CV Detects 1.124 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.802 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.923 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.217 Lilliefors GOF Test 5% Lilliefors Critical Value 0.167 Detected Data Not Normal at 5% Significance Level 19.58 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 13.83 KM Standard Error of Mean 3.136 23.24 95% KM Chebyshev UCL 27.5 KM SD 18.2 95% KM (BCA) UCL 19.61 95% KM (t) UCL 19.13 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 33.41 99% KM Chebyshev UCL 45.03 95% KM (z) UCL 18.99 95% KM Bootstrap t UCL 21.03 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.374 Anderson-Darling GOF Test Page 26 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 5% A-D Critical Value 0.78 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.127 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.174 Detected data appear Gamma Distributed at 5% Significance Level 45.67 nu star (bias corrected) 41.93 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.846 k star (bias corrected MLE) 0.776 Mean (detects) 17.47 Theta hat (MLE) 20.66 Theta star (bias corrected MLE) 22.5 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 13.52 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 76.4 Median 4.8 SD 18.69 CV 1.383 k hat (MLE) 0.38 k star (bias corrected MLE) 0.366 Theta hat (MLE) 35.58 Theta star (bias corrected MLE) 36.9 nu hat (MLE) 26.59 nu star (bias corrected) 25.65 Adjusted Level of Significance (β) 0.0425 Approximate Chi Square Value (25.65, α) 15.11 Adjusted Chi Square Value (25.65, β) 14.72 95% Gamma Approximate UCL (use when n>=50) 22.95 95% Gamma Adjusted UCL (use when n<50) 23.55 Estimates of Gamma Parameters using KM Estimates Mean (KM) 13.83 SD (KM) 18.2 Variance (KM) 331.3 SE of Mean (KM) 3.136 k hat (KM) 0.577 k star (KM) 0.547 nu hat (KM) 40.42 nu star (KM) 38.29 theta hat (KM) 23.95 theta star (KM) 25.29 24.61 80% gamma percentile (KM) 22.78 90% gamma percentile (KM) 36.71 95% gamma percentile (KM) 51.45 99% gamma percentile (KM) 87.4 95% Gamma Approximate KM-UCL (use when n>=50) 21.08 95% Gamma Adjusted KM-UCL (use when n<50) 21.52 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (38.29, α) 25.12 Adjusted Chi Square Value (38.29, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.951 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.923 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.138 Lilliefors GOF Test 5% Lilliefors Critical Value 0.167 Detected Data appear Lognormal at 5% Significance Level Page 27 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 13.9 Mean in Log Scale 1.792 SD in Original Scale 18.42 SD in Log Scale 1.36 95% t UCL (assumes normality of ROS data) 19.17 95% Percentile Bootstrap UCL 19.45 95% BCA Bootstrap UCL 20.67 95% Bootstrap t UCL 21.11 95% H-UCL (Log ROS) 30 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.758 KM Geo Mean 5.801 KM SD (logged) 1.368 95% Critical H Value (KM-Log) 2.944 KM Standard Error of Mean (logged) 0.239 95% H-UCL (KM -Log) 29.49 1.773 KM SD (logged) 1.368 95% Critical H Value (KM-Log) 2.944 KM Standard Error of Mean (logged) 0.239 19.12 95% H-Stat UCL 29.89 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 13.84 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Gamma Distributed at 5% Significance Level SD in Original Scale 18.46 SD in Log Scale 1.367 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use a Adjusted KM-UCL (use when k<=1 and 15 < n < 50 but k<=1) 21.52 DW_EU10_PEPA General Statistics Total Number of Observations 23 Number of Distinct Observations 7 Number of Detects 6 Number of Non-Detects 17 Number of Distinct Detects 5 Number of Distinct Non-Detects 3 11.26 Minimum Detect 20 Minimum Non-Detect 11 Maximum Detect 49 Maximum Non-Detect 100 Variance Detects 126.7 Percent Non-Detects 73.91% Mean Detects 32.5 SD Detects Median Detects 33.5 CV Detects 0.346 Page 28 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 0.275 Kurtosis Detects -1.104 Mean of Logged Detects 3.429 SD of Logged Detects 0.358 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.925 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.788 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.187 Lilliefors GOF Test 5% Lilliefors Critical Value 0.325 Detected Data appear Normal at 5% Significance Level 26.2 Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 17.79 KM Standard Error of Mean 2.901 26.49 95% KM Chebyshev UCL 30.43 KM SD 11.54 95% KM (BCA) UCL 27.41 95% KM (t) UCL 22.77 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 35.9 99% KM Chebyshev UCL 46.65 95% KM (z) UCL 22.56 95% KM Bootstrap t UCL 21.48 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.339 Anderson-Darling GOF Test 5% A-D Critical Value 0.698 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.228 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.332 Detected data appear Gamma Distributed at 5% Significance Level 117 nu star (bias corrected) 59.84 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 9.752 k star (bias corrected MLE) 4.987 Mean (detects) 32.5 Theta hat (MLE) 3.333 Theta star (bias corrected MLE) 6.517 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 11.88 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 49 Median 4.865 SD 14.99 CV 1.262 k hat (MLE) 0.259 k star (bias corrected MLE) 0.254 Theta hat (MLE) 45.9 Theta star (bias corrected MLE) 46.77 nu hat (MLE) 11.91 nu star (bias corrected) 11.69 Adjusted Level of Significance (β) 0.0389 Approximate Chi Square Value (11.69, α) 5.022 Adjusted Chi Square Value (11.69, β) 4.708 Page 29 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 95% Gamma Approximate UCL (use when n>=50) 27.65 95% Gamma Adjusted UCL (use when n<50) 29.5 Estimates of Gamma Parameters using KM Estimates Mean (KM) 17.79 SD (KM) 11.54 Variance (KM) 133.2 SE of Mean (KM) 2.901 k hat (KM) 2.376 k star (KM) 2.095 nu hat (KM) 109.3 nu star (KM) 96.35 theta hat (KM) 7.489 theta star (KM) 8.493 73.33 80% gamma percentile (KM) 26.49 90% gamma percentile (KM) 34.23 95% gamma percentile (KM) 41.59 99% gamma percentile (KM) 57.87 95% Gamma Approximate KM-UCL (use when n>=50) 22.94 95% Gamma Adjusted KM-UCL (use when n<50) 23.37 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (96.35, α) 74.71 Adjusted Chi Square Value (96.35, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.917 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.788 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.22 Lilliefors GOF Test 5% Lilliefors Critical Value 0.325 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 16.11 Mean in Log Scale 2.524 SD in Original Scale 12.25 SD in Log Scale 0.733 95% t UCL (assumes normality of ROS data) 20.5 95% Percentile Bootstrap UCL 20.46 95% BCA Bootstrap UCL 21.21 95% Bootstrap t UCL 21.58 95% H-UCL (Log ROS) 23.05 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.724 KM Geo Mean 15.23 KM SD (logged) 0.513 95% Critical H Value (KM-Log) 1.985 KM Standard Error of Mean (logged) 0.129 95% H-UCL (KM -Log) 21.59 2.85 KM SD (logged) 0.513 95% Critical H Value (KM-Log) 1.985 KM Standard Error of Mean (logged) 0.129 28.75 95% H-Stat UCL 32.26 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 22.63 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 17.09 SD in Log Scale 0.741 95% t UCL (Assumes normality) Page 30 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 22.77 DW_EU10_PFECA-G General Statistics Total Number of Observations 24 Number of Distinct Observations 4 Number of Detects 0 Number of Non-Detects 24 Number of Distinct Detects 0 Number of Distinct Non-Detects 4 The data set for variable DW_EU10_PFECA-G was not processed! DW_EU10_PFESA-BP1 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). 0 Number of Distinct Non-Detects 7 General Statistics Total Number of Observations 27 Number of Distinct Observations 7 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 27 Number of Distinct Detects General Statistics Total Number of Observations 27 Number of Distinct Observations 15 The data set for variable DW_EU10_PFESA-BP1 was not processed! DW_EU10_PFESA-BP2 Number of Detects 11 Number of Non-Detects 16 Number of Distinct Detects 10 Number of Distinct Non-Detects 5 Minimum Detect 2.37 Minimum Non-Detect 1.1 Maximum Detect 35 Maximum Non-Detect 50 Page 31 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 10.93 0.286 Kurtosis Detects -0.875 Variance Detects 119.5 Percent Non-Detects 59.26% Mean Detects 16.68 SD Detects Mean of Logged Detects 2.535 SD of Logged Detects 0.874 Median Detects 18 CV Detects 0.655 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.914 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.85 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.19 Lilliefors GOF Test 5% Lilliefors Critical Value 0.251 Detected Data appear Normal at 5% Significance Level 12.46 Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 8.551 KM Standard Error of Mean 2.32 15.51 95% KM Chebyshev UCL 18.66 KM SD 10.61 95% KM (BCA) UCL 12.8 95% KM (t) UCL 12.51 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 23.04 99% KM Chebyshev UCL 31.63 95% KM (z) UCL 12.37 95% KM Bootstrap t UCL 13.34 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.553 Anderson-Darling GOF Test 5% A-D Critical Value 0.739 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.272 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.259 Detected Data Not Gamma Distributed at 5% Significance Level 42.65 nu star (bias corrected) 32.35 Detected data follow Appr. Gamma Distribution at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.938 k star (bias corrected MLE) 1.47 Mean (detects) 16.68 Theta hat (MLE) 8.604 Theta star (bias corrected MLE) 11.34 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 7.715 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 35 Median 1.658 SD 10.69 CV 1.385 k hat (MLE) 0.236 k star (bias corrected MLE) 0.235 Theta hat (MLE) 32.68 Theta star (bias corrected MLE) 32.89 Page 32 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 nu hat (MLE) 12.75 nu star (bias corrected) 12.67 Adjusted Level of Significance (β) 0.0401 Approximate Chi Square Value (12.67, α) 5.668 Adjusted Chi Square Value (12.67, β) 5.371 95% Gamma Approximate UCL (use when n>=50) 17.24 95% Gamma Adjusted UCL (use when n<50) 18.19 Estimates of Gamma Parameters using KM Estimates Mean (KM) 8.551 SD (KM) 10.61 Variance (KM) 112.5 SE of Mean (KM) 2.32 k hat (KM) 0.65 k star (KM) 0.602 nu hat (KM) 35.09 nu star (KM) 32.53 theta hat (KM) 13.16 theta star (KM) 14.2 19.88 80% gamma percentile (KM) 14.09 90% gamma percentile (KM) 22.22 95% gamma percentile (KM) 30.73 99% gamma percentile (KM) 51.29 95% Gamma Approximate KM-UCL (use when n>=50) 13.57 95% Gamma Adjusted KM-UCL (use when n<50) 13.99 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (32.53, α) 20.49 Adjusted Chi Square Value (32.53, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.888 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.85 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.294 Lilliefors GOF Test 5% Lilliefors Critical Value 0.251 Detected Data Not Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 8.294 Mean in Log Scale 1.323 SD in Original Scale 10.11 SD in Log Scale 1.347 95% t UCL (assumes normality of ROS data) 11.61 95% Percentile Bootstrap UCL 11.67 95% BCA Bootstrap UCL 12 95% Bootstrap t UCL 12.42 95% H-UCL (Log ROS) 20.58 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.262 KM Geo Mean 3.532 KM SD (logged) 1.348 95% Critical H Value (KM-Log) 3.007 KM Standard Error of Mean (logged) 0.295 95% H-UCL (KM -Log) 19.4 1.452 KM SD (logged) 1.348 95% Critical H Value (KM-Log) 3.007 KM Standard Error of Mean (logged) 0.295 14.74 95% H-Stat UCL 40.5 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 10.9 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons SD in Original Scale 11.7 SD in Log Scale 1.565 95% t UCL (Assumes normality) Page 33 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 12.51 DW_EU10_PFMOAA General Statistics Total Number of Observations 27 Number of Distinct Observations 17 Number of Detects 12 Number of Non-Detects 15 Number of Distinct Detects 12 Number of Distinct Non-Detects 5 21.05 Minimum Detect 5.5 Minimum Non-Detect 1.17 Maximum Detect 65 Maximum Non-Detect 50 0.836 Kurtosis Detects -0.55 Variance Detects 443.2 Percent Non-Detects 55.56% Mean Detects 26.97 SD Detects Mean of Logged Detects 2.975 SD of Logged Detects 0.875 Median Detects 20.5 CV Detects 0.781 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.876 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.859 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.195 Lilliefors GOF Test 5% Lilliefors Critical Value 0.243 Detected Data appear Normal at 5% Significance Level 19.87 Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 13.57 KM Standard Error of Mean 3.859 25.15 95% KM Chebyshev UCL 30.39 KM SD 18.66 95% KM (BCA) UCL 21.07 95% KM (t) UCL 20.15 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 37.67 99% KM Chebyshev UCL 51.97 95% KM (z) UCL 19.92 95% KM Bootstrap t UCL 22.22 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.298 Anderson-Darling GOF Test 5% A-D Critical Value 0.744 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.134 Kolmogorov-Smirnov GOF Page 34 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 5% K-S Critical Value 0.249 Detected data appear Gamma Distributed at 5% Significance Level 41.14 nu star (bias corrected) 32.19 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.714 k star (bias corrected MLE) 1.341 Mean (detects) 26.97 Theta hat (MLE) 15.73 Theta star (bias corrected MLE) 20.11 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 12.63 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 65 Median 1.018 SD 19.16 CV 1.517 k hat (MLE) 0.227 k star (bias corrected MLE) 0.226 Theta hat (MLE) 55.65 Theta star (bias corrected MLE) 55.78 nu hat (MLE) 12.26 nu star (bias corrected) 12.23 Adjusted Level of Significance (β) 0.0401 Approximate Chi Square Value (12.23, α) 5.378 Adjusted Chi Square Value (12.23, β) 5.089 95% Gamma Approximate UCL (use when n>=50) 28.72 95% Gamma Adjusted UCL (use when n<50) 30.35 Estimates of Gamma Parameters using KM Estimates Mean (KM) 13.57 SD (KM) 18.66 Variance (KM) 348.3 SE of Mean (KM) 3.859 k hat (KM) 0.529 k star (KM) 0.495 nu hat (KM) 28.55 nu star (KM) 26.71 theta hat (KM) 25.67 theta star (KM) 27.43 15.39 80% gamma percentile (KM) 22.28 90% gamma percentile (KM) 36.8 95% gamma percentile (KM) 52.33 99% gamma percentile (KM) 90.57 95% Gamma Approximate KM-UCL (use when n>=50) 22.76 95% Gamma Adjusted KM-UCL (use when n<50) 23.54 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (26.71, α) 15.93 Adjusted Chi Square Value (26.71, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.936 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.859 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.129 Lilliefors GOF Test 5% Lilliefors Critical Value 0.243 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Page 35 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 13.86 Mean in Log Scale 1.852 SD in Original Scale 18.3 SD in Log Scale 1.292 95% t UCL (assumes normality of ROS data) 19.87 95% Percentile Bootstrap UCL 19.95 95% BCA Bootstrap UCL 21.34 95% Bootstrap t UCL 22.35 95% H-UCL (Log ROS) 30.79 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.54 KM Geo Mean 4.665 KM SD (logged) 1.514 95% Critical H Value (KM-Log) 3.26 KM Standard Error of Mean (logged) 0.32 95% H-UCL (KM -Log) 38.64 1.959 KM SD (logged) 1.514 95% Critical H Value (KM-Log) 3.26 KM Standard Error of Mean (logged) 0.32 21.76 95% H-Stat UCL 42.97 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 15.69 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 18.49 SD in Log Scale 1.389 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 20.15 DW_EU10_PFO2HxA General Statistics Total Number of Observations 27 Number of Distinct Observations 19 Number of Detects 14 Number of Non-Detects 13 Number of Distinct Detects 14 Number of Distinct Non-Detects 5 66.21 Minimum Detect 3 Minimum Non-Detect 1.1 Maximum Detect 230 Maximum Non-Detect 50 1.956 Kurtosis Detects 3.753 Variance Detects 4384 Percent Non-Detects 48.15% Mean Detects 47.18 SD Detects Mean of Logged Detects 2.942 SD of Logged Detects 1.435 Median Detects 14.5 CV Detects 1.403 Skewness Detects Page 36 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.716 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.874 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.302 Lilliefors GOF Test 5% Lilliefors Critical Value 0.226 Detected Data Not Normal at 5% Significance Level 42.89 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 25.39 KM Standard Error of Mean 10.25 56.15 95% KM Chebyshev UCL 70.09 KM SD 51.28 95% KM (BCA) UCL 45.02 95% KM (t) UCL 42.88 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 89.43 99% KM Chebyshev UCL 127.4 95% KM (z) UCL 42.26 95% KM Bootstrap t UCL 58.43 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.617 Anderson-Darling GOF Test 5% A-D Critical Value 0.778 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.183 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.239 Detected data appear Gamma Distributed at 5% Significance Level 18.68 nu star (bias corrected) 16.01 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.667 k star (bias corrected MLE) 0.572 Mean (detects) 47.18 Theta hat (MLE) 70.71 Theta star (bias corrected MLE) 82.5 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 24.47 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 230 Median 3 SD 52.62 CV 2.151 k hat (MLE) 0.191 k star (bias corrected MLE) 0.194 Theta hat (MLE) 128.3 Theta star (bias corrected MLE) 126 nu hat (MLE) 10.29 nu star (bias corrected) 10.48 Adjusted Level of Significance (β) 0.0401 Approximate Chi Square Value (10.48, α) 4.246 Adjusted Chi Square Value (10.48, β) 3.995 95% Gamma Approximate UCL (use when n>=50) 60.41 95% Gamma Adjusted UCL (use when n<50) 64.21 Page 37 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Estimates of Gamma Parameters using KM Estimates Mean (KM) 25.39 SD (KM) 51.28 Variance (KM) 2630 SE of Mean (KM) 10.25 k hat (KM) 0.245 k star (KM) 0.243 nu hat (KM) 13.24 nu star (KM) 13.1 theta hat (KM) 103.6 theta star (KM) 104.7 5.653 80% gamma percentile (KM) 36.47 90% gamma percentile (KM) 76.36 95% gamma percentile (KM) 124 99% gamma percentile (KM) 251.3 95% Gamma Approximate KM-UCL (use when n>=50) 55.81 95% Gamma Adjusted KM-UCL (use when n<50) 58.83 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (13.10, α) 5.96 Adjusted Chi Square Value (13.10, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.936 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.874 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.126 Lilliefors GOF Test 5% Lilliefors Critical Value 0.226 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 24.96 Mean in Log Scale 1.283 SD in Original Scale 52.39 SD in Log Scale 2.158 95% t UCL (assumes normality of ROS data) 42.16 95% Percentile Bootstrap UCL 42.86 95% BCA Bootstrap UCL 49.38 95% Bootstrap t UCL 61.07 95% H-UCL (Log ROS) 228.7 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.645 KM Geo Mean 5.183 KM SD (logged) 1.723 95% Critical H Value (KM-Log) 3.588 KM Standard Error of Mean (logged) 0.351 95% H-UCL (KM -Log) 76.9 1.706 KM SD (logged) 1.723 95% Critical H Value (KM-Log) 3.588 KM Standard Error of Mean (logged) 0.351 43.73 95% H-Stat UCL 128.7 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 26.68 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Gamma Distributed at 5% Significance Level SD in Original Scale 51.96 SD in Log Scale 1.87 95% t UCL (Assumes normality) Suggested UCL to Use Page 38 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. a Adjusted KM-UCL (use when k<=1 and 15 < n < 50 but k<=1) 58.83 DW_EU10_PFO3OA General Statistics Total Number of Observations 27 Number of Distinct Observations 10 Number of Detects 4 Number of Non-Detects 23 Number of Distinct Detects 4 Number of Distinct Non-Detects 6 5.103 Minimum Detect 4.1 Minimum Non-Detect 1.1 Maximum Detect 15 Maximum Non-Detect 50 -0.125 Kurtosis Detects -3.885 Variance Detects 26.04 Percent Non-Detects 85.19% Mean Detects 9.753 SD Detects Mean of Logged Detects 2.154 SD of Logged Detects 0.599 Median Detects 9.955 CV Detects 0.523 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.928 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.238 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Normal at 5% Significance Level N/A Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 2.605 KM Standard Error of Mean 0.906 5.322 95% KM Chebyshev UCL 6.553 KM SD 3.762 95% KM (BCA) UCL N/A 95% KM (t) UCL 4.15 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 8.261 99% KM Chebyshev UCL 11.62 95% KM (z) UCL 4.095 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.321 Anderson-Darling GOF Test 5% A-D Critical Value 0.659 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.282 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.396 Detected data appear Gamma Distributed at 5% Significance Level Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 4.215 k star (bias corrected MLE) 1.22 Page 39 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 33.72 nu star (bias corrected) 9.764 Mean (detects) 9.753 Theta hat (MLE) 2.314 Theta star (bias corrected MLE) 7.991 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 1.53 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 15 Median 0.01 SD 3.913 CV 2.559 k hat (MLE) 0.199 k star (bias corrected MLE) 0.202 Theta hat (MLE) 7.68 Theta star (bias corrected MLE) 7.583 nu hat (MLE) 10.75 nu star (bias corrected) 10.89 Adjusted Level of Significance (β) 0.0401 Approximate Chi Square Value (10.89, α) 4.507 Adjusted Chi Square Value (10.89, β) 4.246 95% Gamma Approximate UCL (use when n>=50) 3.697 95% Gamma Adjusted UCL (use when n<50) N/A Estimates of Gamma Parameters using KM Estimates Mean (KM) 2.605 SD (KM) 3.762 Variance (KM) 14.15 SE of Mean (KM) 0.906 k hat (KM) 0.479 k star (KM) 0.451 nu hat (KM) 25.89 nu star (KM) 24.35 theta hat (KM) 5.433 theta star (KM) 5.777 13.61 80% gamma percentile (KM) 4.252 90% gamma percentile (KM) 7.196 95% gamma percentile (KM) 10.38 99% gamma percentile (KM) 18.29 95% Gamma Approximate KM-UCL (use when n>=50) 4.494 95% Gamma Adjusted KM-UCL (use when n<50) 4.658 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (24.35, α) 14.11 Adjusted Chi Square Value (24.35, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.924 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.253 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 2.126 Mean in Log Scale -0.309 SD in Original Scale 3.755 SD in Log Scale 1.477 95% t UCL (assumes normality of ROS data) 3.359 95% Percentile Bootstrap UCL 3.34 95% BCA Bootstrap UCL 3.9 95% Bootstrap t UCL 4.94 Page 40 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 95% H-UCL (Log ROS) 5.528 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.453 KM Geo Mean 1.574 KM SD (logged) 0.81 95% Critical H Value (KM-Log) 2.287 KM Standard Error of Mean (logged) 0.195 95% H-UCL (KM -Log) 3.141 0.718 KM SD (logged) 0.81 95% Critical H Value (KM-Log) 2.287 KM Standard Error of Mean (logged) 0.195 8.72 95% H-Stat UCL 11.66 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 5.792 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level SD in Original Scale 8.921 SD in Log Scale 1.363 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (t) UCL 4.15 DW_EU10_PFO4DA General Statistics Total Number of Observations 27 Number of Distinct Observations 8 Number of Detects 2 Number of Non-Detects 25 Number of Distinct Detects 2 Number of Distinct Non-Detects 6 Minimum Detect 2.34 Minimum Non-Detect 1.1 Maximum Detect 3.4 Maximum Non-Detect 50 Variance Detects 0.562 Percent Non-Detects 92.59% Mean Detects 2.87 SD Detects 0.75 Median Detects 2.87 CV Detects 0.261 Skewness Detects N/A Kurtosis Detects N/A Warning: Data set has only 2 Detected Values. This is not enough to compute meaningful or reliable statistics and estimates. Mean of Logged Detects 1.037 SD of Logged Detects 0.264 Page 41 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Normal GOF Test on Detects Only N/A Not Enough Data to Perform GOF Test Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 1.254 KM Standard Error of Mean 0.154 1.716 95% KM Chebyshev UCL 1.926 KM SD 0.523 95% KM (BCA) UCL N/A 95% KM (t) UCL 1.517 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 2.216 99% KM Chebyshev UCL 2.787 95% KM (z) UCL 1.507 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only Not Enough Data to Perform GOF Test Gamma Statistics on Detected Data Only k hat (MLE) 28.99 k star (bias corrected MLE) N/A Theta hat (MLE) 0.099 Theta star (bias corrected MLE) N/A nu hat (MLE) 115.9 nu star (bias corrected) N/A Estimates of Gamma Parameters using KM Estimates Mean (KM) 1.254 SD (KM) 0.523 Mean (detects) 2.87 Variance (KM) 0.273 SE of Mean (KM) 0.154 k hat (KM) 5.756 k star (KM) 5.141 nu hat (KM) 310.8 nu star (KM) 277.6 theta hat (KM) 0.218 theta star (KM) 0.244 80% gamma percentile (KM) 1.68 90% gamma percentile (KM) 1.994 95% gamma percentile (KM) 2.28 99% gamma percentile (KM) 2.883 1.45 95% Gamma Adjusted KM-UCL (use when n<50) 1.464 Gamma Kaplan-Meier (KM) Statistics Adjusted Level of Significance (β) 0.0401 Lognormal GOF Test on Detected Observations Only Not Enough Data to Perform GOF Test Lognormal ROS Statistics Using Imputed Non-Detects Approximate Chi Square Value (277.62, α) 240 Adjusted Chi Square Value (277.62, β) 237.8 95% Gamma Approximate KM-UCL (use when n>=50) Mean in Original Scale 0.615 Mean in Log Scale -0.942 SD in Original Scale 0.735 SD in Log Scale 0.94 95% t UCL (assumes normality of ROS data) 0.856 95% Percentile Bootstrap UCL 0.843 95% BCA Bootstrap UCL 0.926 95% Bootstrap t UCL 1.059 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution 95% H-UCL (Log ROS) 0.952 Page 42 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 KM Mean (logged) 0.177 KM Geo Mean 1.194 KM SD (logged) 0.271 95% Critical H Value (KM-Log) 1.802 KM Standard Error of Mean (logged) 0.0799 95% H-UCL (KM -Log) 1.363 0.453 KM SD (logged) 0.271 95% Critical H Value (KM-Log) 1.802 KM Standard Error of Mean (logged) 0.0799 7.466 95% H-Stat UCL 6.703 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 4.617 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Data do not follow a Discernible Distribution at 5% Significance Level SD in Original Scale 8.681 SD in Log Scale 1.234 95% t UCL (Assumes normality) 95% KM (BCA) UCL N/A Warning: One or more Recommended UCL(s) not available! Suggested UCL to Use 95% KM (t) UCL 1.517 KM H-UCL 1.363 4 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. 0 Number of Distinct Non-Detects 4 DW_EU10_PFO5DA General Statistics Total Number of Observations 24 Number of Distinct Observations Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 24 Number of Distinct Detects General Statistics Total Number of Observations 23 Number of Distinct Observations 15 The data set for variable DW_EU10_PFO5DA was not processed! DW_EU10_PMPA Number of Detects 16 Number of Non-Detects 7 Page 43 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Number of Distinct Detects 14 Number of Distinct Non-Detects 1 140.5 Minimum Detect 5.8 Minimum Non-Detect 10 Maximum Detect 580 Maximum Non-Detect 10 1.763 Kurtosis Detects 4.837 Variance Detects 19739 Percent Non-Detects 30.43% Mean Detects 158.3 SD Detects Mean of Logged Detects 4.574 SD of Logged Detects 1.215 Median Detects 155 CV Detects 0.888 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.819 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.887 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.194 Lilliefors GOF Test 5% Lilliefors Critical Value 0.213 Detected Data appear Normal at 5% Significance Level 161.1 Detected Data appear Approximate Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 111.9 KM Standard Error of Mean 28.73 198.1 95% KM Chebyshev UCL 237.1 KM SD 133.4 95% KM (BCA) UCL 159.5 95% KM (t) UCL 161.2 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 291.3 99% KM Chebyshev UCL 397.7 95% KM (z) UCL 159.1 95% KM Bootstrap t UCL 177.6 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.55 Anderson-Darling GOF Test 5% A-D Critical Value 0.761 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.227 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.22 Detected Data Not Gamma Distributed at 5% Significance Level 37.02 nu star (bias corrected) 31.42 Detected data follow Appr. Gamma Distribution at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.157 k star (bias corrected MLE) 0.982 Mean (detects) 158.3 Theta hat (MLE) 136.8 Theta star (bias corrected MLE) 161.2 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 110.5 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 580 Median 42 Page 44 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 SD 137.6 CV 1.245 k hat (MLE) 0.267 k star (bias corrected MLE) 0.261 Theta hat (MLE) 414 Theta star (bias corrected MLE) 423.2 nu hat (MLE) 12.27 nu star (bias corrected) 12.01 Adjusted Level of Significance (β) 0.0389 Approximate Chi Square Value (12.01, α) 5.231 Adjusted Chi Square Value (12.01, β) 4.91 95% Gamma Approximate UCL (use when n>=50) 253.5 95% Gamma Adjusted UCL (use when n<50) 270.2 Estimates of Gamma Parameters using KM Estimates Mean (KM) 111.9 SD (KM) 133.4 Variance (KM) 17797 SE of Mean (KM) 28.73 k hat (KM) 0.703 k star (KM) 0.641 nu hat (KM) 32.36 nu star (KM) 29.47 theta hat (KM) 159.1 theta star (KM) 174.6 17.43 80% gamma percentile (KM) 184.3 90% gamma percentile (KM) 286.7 95% gamma percentile (KM) 393.2 99% gamma percentile (KM) 649.3 95% Gamma Approximate KM-UCL (use when n>=50) 182.4 95% Gamma Adjusted KM-UCL (use when n<50) 189.2 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (29.47, α) 18.08 Adjusted Chi Square Value (29.47, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.897 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.887 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.265 Lilliefors GOF Test 5% Lilliefors Critical Value 0.213 Detected Data Not Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 113.4 Mean in Log Scale 3.846 SD in Original Scale 135.3 SD in Log Scale 1.551 95% t UCL (assumes normality of ROS data) 161.8 95% Percentile Bootstrap UCL 160.3 95% BCA Bootstrap UCL 172.7 95% Bootstrap t UCL 181.8 95% H-UCL (Log ROS) 467.6 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 3.717 KM Geo Mean 41.13 KM SD (logged) 1.625 95% Critical H Value (KM-Log) 3.443 KM Standard Error of Mean (logged) 0.35 95% H-UCL (KM -Log) 507.7 KM SD (logged) 1.625 95% Critical H Value (KM-Log) 3.443 KM Standard Error of Mean (logged) 0.35 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 111.6 Mean in Log Scale 3.672 Page 45 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 SD in Original Scale 136.6 SD in Log Scale 1.718 95% t UCL (Assumes normality) 160.6 95% H-Stat UCL 640.3 Suggested UCL to Use 95% KM (t) UCL 161.2 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Normal Distributed at 5% Significance Level Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU11_HFPO-DA When a data set follows an approximate (e.g., normal) distribution passing one of the GOF test When applicable, it is suggested to use a UCL based upon a distribution (e.g., gamma) passing both GOF tests in ProUCL Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. General Statistics Total Number of Observations 126 Number of Distinct Observations 94 Number of Detects 111 Number of Non-Detects 15 Number of Distinct Detects 90 Number of Distinct Non-Detects 4 70.5 Minimum Detect 0.723 Minimum Non-Detect 2.6 Maximum Detect 528 Maximum Non-Detect 4 4.496 Kurtosis Detects 24.81 Variance Detects 4970 Percent Non-Detects 11.9% Mean Detects 42.11 SD Detects Mean of Logged Detects 2.944 SD of Logged Detects 1.326 Median Detects 20.8 CV Detects 1.674 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.541 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.279 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0844 Detected Data Not Normal at 5% Significance Level 47.72 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 37.3 KM Standard Error of Mean 6.01 55.33 95% KM Chebyshev UCL 63.5 KM SD 67.15 95% KM (BCA) UCL 47.53 95% KM (t) UCL 47.26 95% KM (Percentile Bootstrap) UCL 95% KM (z) UCL 47.19 95% KM Bootstrap t UCL 52.79 90% KM Chebyshev UCL Page 46 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 97.5% KM Chebyshev UCL 74.84 99% KM Chebyshev UCL 97.1 Gamma GOF Tests on Detected Observations Only A-D Test Statistic 1.382 Anderson-Darling GOF Test 5% A-D Critical Value 0.795 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.0822 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.09 Detected data appear Gamma Distributed at 5% Significance Level 166.8 nu star (bias corrected) 163.6 Detected data follow Appr. Gamma Distribution at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.751 k star (bias corrected MLE) 0.737 Mean (detects) 42.11 Theta hat (MLE) 56.04 Theta star (bias corrected MLE) 57.13 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 37.1 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 528 Median 15.35 SD 67.53 CV 1.82 k hat (MLE) 0.417 k star (bias corrected MLE) 0.412 Theta hat (MLE) 89.01 Theta star (bias corrected MLE) 90.01 nu hat (MLE) 105 nu star (bias corrected) 103.9 Adjusted Level of Significance (β) 0.0481 Approximate Chi Square Value (103.86, α) 81.34 Adjusted Chi Square Value (103.86, β) 81.11 95% Gamma Approximate UCL (use when n>=50) 47.37 95% Gamma Adjusted UCL (use when n<50) 47.5 Estimates of Gamma Parameters using KM Estimates Mean (KM) 37.3 SD (KM) 67.15 Variance (KM) 4510 SE of Mean (KM) 6.01 k hat (KM) 0.309 k star (KM) 0.307 nu hat (KM) 77.76 nu star (KM) 77.24 theta hat (KM) 120.9 theta star (KM) 121.7 57.8 80% gamma percentile (KM) 57.5 90% gamma percentile (KM) 109.7 95% gamma percentile (KM) 169.5 99% gamma percentile (KM) 324.3 95% Gamma Approximate KM-UCL (use when n>=50) 49.68 95% Gamma Adjusted KM-UCL (use when n<50) 49.85 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (77.24, α) 58 Adjusted Chi Square Value (77.24, β) Lognormal GOF Test on Detected Observations Only Page 47 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Shapiro Wilk Approximate Test Statistic 0.979 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.422 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.052 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0844 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 37.36 Mean in Log Scale 2.674 SD in Original Scale 67.4 SD in Log Scale 1.454 95% t UCL (assumes normality of ROS data) 47.3 95% Percentile Bootstrap UCL 48.26 95% BCA Bootstrap UCL 51.27 95% Bootstrap t UCL 52.47 95% H-UCL (Log ROS) 58.83 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.647 KM Geo Mean 14.11 KM SD (logged) 1.488 95% Critical H Value (KM-Log) 2.673 KM Standard Error of Mean (logged) 0.135 95% H-UCL (KM -Log) 60.92 KM SD (logged) 1.488 95% Critical H Value (KM-Log) 2.673 KM Standard Error of Mean (logged) 0.135 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 37.3 Mean in Log Scale 2.653 SD in Original Scale 67.43 SD in Log Scale 1.477 95% t UCL (Assumes normality) 47.25 95% H-Stat UCL 60.07 Suggested UCL to Use 95% KM Approximate Gamma UCL 49.68 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Gamma Distributed at 5% Significance Level Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU11_PEPA When a data set follows an approximate (e.g., normal) distribution passing one of the GOF test When applicable, it is suggested to use a UCL based upon a distribution (e.g., gamma) passing both GOF tests in ProUCL Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. General Statistics Total Number of Observations 63 Number of Distinct Observations 22 Page 48 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Number of Detects 25 Number of Non-Detects 38 Number of Distinct Detects 20 Number of Distinct Non-Detects 3 41.9 Minimum Detect 11 Minimum Non-Detect 11 Maximum Detect 200 Maximum Non-Detect 100 2.613 Kurtosis Detects 8.158 Variance Detects 1755 Percent Non-Detects 60.32% Mean Detects 42.16 SD Detects Mean of Logged Detects 3.415 SD of Logged Detects 0.786 Median Detects 27 CV Detects 0.994 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.706 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.918 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.229 Lilliefors GOF Test 5% Lilliefors Critical Value 0.173 Detected Data Not Normal at 5% Significance Level 31.81 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 25.14 KM Standard Error of Mean 3.885 36.79 95% KM Chebyshev UCL 42.07 KM SD 29.69 95% KM (BCA) UCL 32.52 95% KM (t) UCL 31.62 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 49.4 99% KM Chebyshev UCL 63.79 95% KM (z) UCL 31.53 95% KM Bootstrap t UCL 35.61 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.673 Anderson-Darling GOF Test 5% A-D Critical Value 0.76 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.126 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.177 Detected data appear Gamma Distributed at 5% Significance Level 83.9 nu star (bias corrected) 75.17 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.678 k star (bias corrected MLE) 1.503 Mean (detects) 42.16 Theta hat (MLE) 25.12 Theta star (bias corrected MLE) 28.04 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 20.74 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Page 49 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Maximum 200 Median 12 SD 32.34 CV 1.56 k hat (MLE) 0.272 k star (bias corrected MLE) 0.269 Theta hat (MLE) 76.31 Theta star (bias corrected MLE) 76.98 nu hat (MLE) 34.24 nu star (bias corrected) 33.94 Adjusted Level of Significance (β) 0.0462 Approximate Chi Square Value (33.94, α) 21.62 Adjusted Chi Square Value (33.94, β) 21.38 95% Gamma Approximate UCL (use when n>=50) 32.56 95% Gamma Adjusted UCL (use when n<50) 32.91 Estimates of Gamma Parameters using KM Estimates Mean (KM) 25.14 SD (KM) 29.69 Variance (KM) 881.5 SE of Mean (KM) 3.885 k hat (KM) 0.717 k star (KM) 0.693 nu hat (KM) 90.32 nu star (KM) 87.35 theta hat (KM) 35.07 theta star (KM) 36.26 66.38 80% gamma percentile (KM) 41.33 90% gamma percentile (KM) 63.24 95% gamma percentile (KM) 85.86 99% gamma percentile (KM) 139.9 95% Gamma Approximate KM-UCL (use when n>=50) 32.87 95% Gamma Adjusted KM-UCL (use when n<50) 33.07 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (87.35, α) 66.8 Adjusted Chi Square Value (87.35, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.947 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.918 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.113 Lilliefors GOF Test 5% Lilliefors Critical Value 0.173 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 24.28 Mean in Log Scale 2.766 SD in Original Scale 30.42 SD in Log Scale 0.881 95% t UCL (assumes normality of ROS data) 30.68 95% Percentile Bootstrap UCL 30.91 95% BCA Bootstrap UCL 32.79 95% Bootstrap t UCL 35.95 95% H-UCL (Log ROS) 29.85 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.916 KM Geo Mean 18.47 KM SD (logged) 0.664 95% Critical H Value (KM-Log) 1.98 KM Standard Error of Mean (logged) 0.0945 95% H-UCL (KM -Log) 27.22 KM SD (logged) 0.664 95% Critical H Value (KM-Log) 1.98 KM Standard Error of Mean (logged) 0.0945 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Page 50 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 2.827 31.7 95% H-Stat UCL 28.72 Mean in Original Scale 25.16 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Gamma Distributed at 5% Significance Level SD in Original Scale 31.1 SD in Log Scale 0.798 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM Approximate Gamma UCL 32.87 95% GROS Approximate Gamma UCL 32.56 DW_EU11_PFECA-G General Statistics Total Number of Observations 63 Number of Distinct Observations 3 Number of Detects 0 Number of Non-Detects 63 Number of Distinct Detects 0 Number of Distinct Non-Detects 3 The data set for variable DW_EU11_PFECA-G was not processed! DW_EU11_PFESA-BP1 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). 0 Number of Distinct Non-Detects 5 General Statistics Total Number of Observations 65 Number of Distinct Observations 5 Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 65 Number of Distinct Detects The data set for variable DW_EU11_PFESA-BP1 was not processed! DW_EU11_PFESA-BP2 Page 51 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 General Statistics Total Number of Observations 65 Number of Distinct Observations 37 Number of Detects 42 Number of Non-Detects 23 Number of Distinct Detects 34 Number of Distinct Non-Detects 3 24.02 Minimum Detect 2.2 Minimum Non-Detect 1.1 Maximum Detect 140 Maximum Non-Detect 50 3.98 Kurtosis Detects 18.19 Variance Detects 576.7 Percent Non-Detects 35.38% Mean Detects 16.31 SD Detects Mean of Logged Detects 2.297 SD of Logged Detects 0.908 Median Detects 8.65 CV Detects 1.472 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.524 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.942 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.278 Lilliefors GOF Test 5% Lilliefors Critical Value 0.135 Detected Data Not Normal at 5% Significance Level 16.21 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 11.37 KM Standard Error of Mean 2.576 19.1 95% KM Chebyshev UCL 22.6 KM SD 20.39 95% KM (BCA) UCL 16.9 95% KM (t) UCL 15.67 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 27.46 99% KM Chebyshev UCL 37 95% KM (z) UCL 15.61 95% KM Bootstrap t UCL 19.36 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 1.893 Anderson-Darling GOF Test 5% A-D Critical Value 0.775 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.22 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.14 Detected Data Not Gamma Distributed at 5% Significance Level 96.39 nu star (bias corrected) 90.84 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.148 k star (bias corrected MLE) 1.081 Mean (detects) 16.31 Theta hat (MLE) 14.22 Theta star (bias corrected MLE) 15.09 nu hat (MLE) Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs Page 52 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 10.93 This is especially true when the sample size is small. Maximum 140 Median 5.36 SD 20.72 CV 1.896 k hat (MLE) 0.297 k star (bias corrected MLE) 0.294 Theta hat (MLE) 36.78 Theta star (bias corrected MLE) 37.21 nu hat (MLE) 38.64 nu star (bias corrected) 38.19 Adjusted Level of Significance (β) 0.0463 Approximate Chi Square Value (38.19, α) 25.04 Adjusted Chi Square Value (38.19, β) 24.79 95% Gamma Approximate UCL (use when n>=50) 16.67 95% Gamma Adjusted UCL (use when n<50) 16.84 Estimates of Gamma Parameters using KM Estimates Mean (KM) 11.37 SD (KM) 20.39 Variance (KM) 415.9 SE of Mean (KM) 2.576 k hat (KM) 0.311 k star (KM) 0.307 nu hat (KM) 40.4 nu star (KM) 39.87 theta hat (KM) 36.58 theta star (KM) 37.07 26.15 80% gamma percentile (KM) 17.53 90% gamma percentile (KM) 33.44 95% gamma percentile (KM) 51.64 99% gamma percentile (KM) 98.81 95% Gamma Approximate KM-UCL (use when n>=50) 17.17 95% Gamma Adjusted KM-UCL (use when n<50) 17.33 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (39.87, α) 26.4 Adjusted Chi Square Value (39.87, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.917 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.942 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.146 Lilliefors GOF Test 5% Lilliefors Critical Value 0.135 Detected Data Not Lognormal at 5% Significance Level Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 11.33 Mean in Log Scale 1.628 SD in Original Scale 20.45 SD in Log Scale 1.262 95% t UCL (assumes normality of ROS data) 15.56 95% Percentile Bootstrap UCL 15.89 95% BCA Bootstrap UCL 17.33 95% Bootstrap t UCL 19.59 95% H-UCL (Log ROS) 15.96 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.605 KM Geo Mean 4.976 KM SD (logged) 1.256 95% Critical H Value (KM-Log) 2.184 KM Standard Error of Mean (logged) 0.162 95% H-UCL (KM -Log) 15.43 KM SD (logged) 1.256 95% Critical H Value (KM-Log) 2.184 KM Standard Error of Mean (logged) 0.162 Page 53 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 1.673 16.65 95% H-Stat UCL 19.08 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 12.37 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Data do not follow a Discernible Distribution at 5% Significance Level SD in Original Scale 20.69 SD in Log Scale 1.342 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (Chebyshev) UCL 22.6 DW_EU11_PFMOAA General Statistics Total Number of Observations 65 Number of Distinct Observations 33 Number of Detects 41 Number of Non-Detects 24 Number of Distinct Detects 31 Number of Distinct Non-Detects 3 105.3 Minimum Detect 5 Minimum Non-Detect 2.6 Maximum Detect 685 Maximum Non-Detect 50 6.072 Kurtosis Detects 38.03 Variance Detects 11082 Percent Non-Detects 36.92% Mean Detects 38.73 SD Detects Mean of Logged Detects 2.9 SD of Logged Detects 0.968 Median Detects 15 CV Detects 2.718 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.288 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.941 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.374 Lilliefors GOF Test 5% Lilliefors Critical Value 0.137 Detected Data Not Normal at 5% Significance Level 47.29 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 25.97 KM Standard Error of Mean 10.59 KM SD 84.32 95% KM (BCA) UCL 48.61 95% KM (t) UCL 43.65 95% KM (Percentile Bootstrap) UCL 95% KM (z) UCL 43.39 95% KM Bootstrap t UCL 95.55 Page 54 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 57.75 95% KM Chebyshev UCL 72.15 97.5% KM Chebyshev UCL 92.13 99% KM Chebyshev UCL 131.4 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 3.455 Anderson-Darling GOF Test 5% A-D Critical Value 0.788 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.233 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.143 Detected Data Not Gamma Distributed at 5% Significance Level 64.43 nu star (bias corrected) 61.05 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.786 k star (bias corrected MLE) 0.744 Mean (detects) 38.73 Theta hat (MLE) 49.29 Theta star (bias corrected MLE) 52.02 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 24.95 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 685 Median 9.6 SD 85.28 CV 3.418 k hat (MLE) 0.241 k star (bias corrected MLE) 0.24 Theta hat (MLE) 103.5 Theta star (bias corrected MLE) 103.9 nu hat (MLE) 31.34 nu star (bias corrected) 31.23 Adjusted Level of Significance (β) 0.0463 Approximate Chi Square Value (31.23, α) 19.46 Adjusted Chi Square Value (31.23, β) 19.25 95% Gamma Approximate UCL (use when n>=50) 40.04 95% Gamma Adjusted UCL (use when n<50) 40.47 Estimates of Gamma Parameters using KM Estimates Mean (KM) 25.97 SD (KM) 84.32 Variance (KM) 7110 SE of Mean (KM) 10.59 k hat (KM) 0.0948 k star (KM) 0.101 nu hat (KM) 12.33 nu star (KM) 13.09 theta hat (KM) 273.8 theta star (KM) 257.8 5.845 80% gamma percentile (KM) 18.2 90% gamma percentile (KM) 69.31 95% gamma percentile (KM) 150.6 99% gamma percentile (KM) 411 95% Gamma Approximate KM-UCL (use when n>=50) 57.09 95% Gamma Adjusted KM-UCL (use when n<50) 58.16 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (13.09, α) 5.954 Adjusted Chi Square Value (13.09, β) Page 55 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.909 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.941 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.118 Lilliefors GOF Test 5% Lilliefors Critical Value 0.137 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 25.73 Mean in Log Scale 2.154 SD in Original Scale 85.01 SD in Log Scale 1.341 95% t UCL (assumes normality of ROS data) 43.33 95% Percentile Bootstrap UCL 46.45 95% BCA Bootstrap UCL 58.15 95% Bootstrap t UCL 97.42 95% H-UCL (Log ROS) 30.83 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.249 KM Geo Mean 9.475 KM SD (logged) 1.19 95% Critical H Value (KM-Log) 2.229 KM Standard Error of Mean (logged) 0.153 95% H-UCL (KM -Log) 26.81 2.299 KM SD (logged) 1.19 95% Critical H Value (KM-Log) 2.229 KM Standard Error of Mean (logged) 0.153 44.29 95% H-Stat UCL 29.58 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 26.72 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Lognormal Distributed at 5% Significance Level SD in Original Scale 84.87 SD in Log Scale 1.225 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 26.81 DW_EU11_PFO2HxA General Statistics Total Number of Observations 65 Number of Distinct Observations 39 Number of Detects 42 Number of Non-Detects 23 Number of Distinct Detects 36 Number of Distinct Non-Detects 3 Page 56 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 101.8 Minimum Detect 2.4 Minimum Non-Detect 1.1 Maximum Detect 646 Maximum Non-Detect 50 5.226 Kurtosis Detects 30.25 Variance Detects 10370 Percent Non-Detects 35.38% Mean Detects 49.31 SD Detects Mean of Logged Detects 3.1 SD of Logged Detects 1.21 Median Detects 21.5 CV Detects 2.065 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.411 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.942 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.323 Lilliefors GOF Test 5% Lilliefors Critical Value 0.135 Detected Data Not Normal at 5% Significance Level 51.99 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 32.68 KM Standard Error of Mean 10.55 64.33 95% KM Chebyshev UCL 78.67 KM SD 84 95% KM (BCA) UCL 54.03 95% KM (t) UCL 50.29 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 98.56 99% KM Chebyshev UCL 137.7 95% KM (z) UCL 50.03 95% KM Bootstrap t UCL 78.75 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 1.383 Anderson-Darling GOF Test 5% A-D Critical Value 0.789 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.158 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.142 Detected Data Not Gamma Distributed at 5% Significance Level 63.01 nu star (bias corrected) 59.85 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.75 k star (bias corrected MLE) 0.712 Mean (detects) 49.31 Theta hat (MLE) 65.74 Theta star (bias corrected MLE) 69.22 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 32.03 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 646 Median 9.7 SD 84.85 CV 2.649 Page 57 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 k hat (MLE) 0.24 k star (bias corrected MLE) 0.239 Theta hat (MLE) 133.7 Theta star (bias corrected MLE) 134.2 nu hat (MLE) 31.14 nu star (bias corrected) 31.03 Adjusted Level of Significance (β) 0.0463 Approximate Chi Square Value (31.03, α) 19.31 Adjusted Chi Square Value (31.03, β) 19.1 95% Gamma Approximate UCL (use when n>=50) 51.48 95% Gamma Adjusted UCL (use when n<50) 52.05 Estimates of Gamma Parameters using KM Estimates Mean (KM) 32.68 SD (KM) 84 Variance (KM) 7056 SE of Mean (KM) 10.55 k hat (KM) 0.151 k star (KM) 0.155 nu hat (KM) 19.68 nu star (KM) 20.1 theta hat (KM) 215.9 theta star (KM) 211.3 10.77 80% gamma percentile (KM) 36.46 90% gamma percentile (KM) 97.3 95% gamma percentile (KM) 178.8 99% gamma percentile (KM) 413.8 95% Gamma Approximate KM-UCL (use when n>=50) 60.12 95% Gamma Adjusted KM-UCL (use when n<50) 60.98 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (20.10, α) 10.93 Adjusted Chi Square Value (20.10, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.935 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.942 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0696 Lilliefors GOF Test 5% Lilliefors Critical Value 0.135 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 32.71 Mean in Log Scale 2.16 SD in Original Scale 84.6 SD in Log Scale 1.697 95% t UCL (assumes normality of ROS data) 50.22 95% Percentile Bootstrap UCL 52.89 95% BCA Bootstrap UCL 62.5 95% Bootstrap t UCL 80.51 95% H-UCL (Log ROS) 64.32 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.104 KM Geo Mean 8.202 KM SD (logged) 1.704 95% Critical H Value (KM-Log) 2.669 KM Standard Error of Mean (logged) 0.217 95% H-UCL (KM -Log) 61.88 2.143 KM SD (logged) 1.704 95% Critical H Value (KM-Log) 2.669 KM Standard Error of Mean (logged) 0.217 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 33.32 Mean in Log Scale SD in Original Scale 84.51 SD in Log Scale 1.753 Page 58 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 50.81 95% H-Stat UCL 72.07 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Lognormal Distributed at 5% Significance Level 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 61.88 DW_EU11_PFO3OA General Statistics Total Number of Observations 65 Number of Distinct Observations 15 Number of Detects 14 Number of Non-Detects 51 Number of Distinct Detects 12 Number of Distinct Non-Detects 4 23.88 Minimum Detect 2 Minimum Non-Detect 1.1 Maximum Detect 92.8 Maximum Non-Detect 50 3.34 Kurtosis Detects 11.59 Variance Detects 570.3 Percent Non-Detects 78.46% Mean Detects 12.83 SD Detects Mean of Logged Detects 1.83 SD of Logged Detects 1.03 Median Detects 4.7 CV Detects 1.862 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.474 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.874 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.388 Lilliefors GOF Test 5% Lilliefors Critical Value 0.226 Detected Data Not Normal at 5% Significance Level 6.449 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 3.701 KM Standard Error of Mean 1.516 8.25 95% KM Chebyshev UCL 10.31 KM SD 11.74 95% KM (BCA) UCL 6.637 95% KM (t) UCL 6.232 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 13.17 99% KM Chebyshev UCL 18.79 95% KM (z) UCL 6.195 95% KM Bootstrap t UCL 15.93 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 1.632 Anderson-Darling GOF Test Page 59 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 5% A-D Critical Value 0.768 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.285 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.237 Detected Data Not Gamma Distributed at 5% Significance Level 22.95 nu star (bias corrected) 19.37 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.82 k star (bias corrected MLE) 0.692 Mean (detects) 12.83 Theta hat (MLE) 15.65 Theta star (bias corrected MLE) 18.54 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 2.77 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 92.8 Median 0.01 SD 12 CV 4.332 k hat (MLE) 0.177 k star (bias corrected MLE) 0.179 Theta hat (MLE) 15.66 Theta star (bias corrected MLE) 15.47 nu hat (MLE) 23 nu star (bias corrected) 23.27 Adjusted Level of Significance (β) 0.0463 Approximate Chi Square Value (23.27, α) 13.3 Adjusted Chi Square Value (23.27, β) 13.13 95% Gamma Approximate UCL (use when n>=50) 4.848 95% Gamma Adjusted UCL (use when n<50) 4.912 Estimates of Gamma Parameters using KM Estimates Mean (KM) 3.701 SD (KM) 11.74 Variance (KM) 137.9 SE of Mean (KM) 1.516 k hat (KM) 0.0994 k star (KM) 0.105 nu hat (KM) 12.92 nu star (KM) 13.65 theta hat (KM) 37.25 theta star (KM) 35.24 6.221 80% gamma percentile (KM) 2.751 90% gamma percentile (KM) 10.04 95% gamma percentile (KM) 21.41 99% gamma percentile (KM) 57.36 95% Gamma Approximate KM-UCL (use when n>=50) 7.977 95% Gamma Adjusted KM-UCL (use when n<50) 8.122 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (13.65, α) 6.335 Adjusted Chi Square Value (13.65, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.85 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.874 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.192 Lilliefors GOF Test 5% Lilliefors Critical Value 0.226 Detected Data appear Lognormal at 5% Significance Level Page 60 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 3.051 Mean in Log Scale -1.037 SD in Original Scale 11.94 SD in Log Scale 2.059 95% t UCL (assumes normality of ROS data) 5.524 95% Percentile Bootstrap UCL 5.76 95% BCA Bootstrap UCL 7.873 95% Bootstrap t UCL 14.41 95% H-UCL (Log ROS) 6.528 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.49 KM Geo Mean 1.632 KM SD (logged) 0.861 95% Critical H Value (KM-Log) 2.15 KM Standard Error of Mean (logged) 0.113 95% H-UCL (KM -Log) 2.982 0.497 KM SD (logged) 0.861 95% Critical H Value (KM-Log) 2.15 KM Standard Error of Mean (logged) 0.113 7.627 95% H-Stat UCL 4.627 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 4.955 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Lognormal Distributed at 5% Significance Level SD in Original Scale 12.91 SD in Log Scale 1.187 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 2.982 DW_EU11_PFO4DA General Statistics Total Number of Observations 65 Number of Distinct Observations 10 Number of Detects 8 Number of Non-Detects 57 Number of Distinct Detects 7 Number of Distinct Non-Detects 4 8.252 Minimum Detect 1.7 Minimum Non-Detect 1.1 Maximum Detect 25.7 Maximum Non-Detect 50 Variance Detects 68.1 Percent Non-Detects 87.69% Mean Detects 5.399 SD Detects Median Detects 2.4 CV Detects 1.529 Page 61 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 2.764 Kurtosis Detects 7.709 Mean of Logged Detects 1.163 SD of Logged Detects 0.894 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.502 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.818 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.414 Lilliefors GOF Test 5% Lilliefors Critical Value 0.283 Detected Data Not Normal at 5% Significance Level 2.503 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 1.716 KM Standard Error of Mean 0.433 3.015 95% KM Chebyshev UCL 3.603 KM SD 3.146 95% KM (BCA) UCL 2.534 95% KM (t) UCL 2.438 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 4.419 99% KM Chebyshev UCL 6.023 95% KM (z) UCL 2.428 95% KM Bootstrap t UCL 4.687 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 1.53 Anderson-Darling GOF Test 5% A-D Critical Value 0.734 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.396 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.301 Detected Data Not Gamma Distributed at 5% Significance Level 17.46 nu star (bias corrected) 12.25 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.091 k star (bias corrected MLE) 0.765 Mean (detects) 5.399 Theta hat (MLE) 4.947 Theta star (bias corrected MLE) 7.053 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 0.673 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 25.7 Median 0.01 SD 3.261 CV 4.843 k hat (MLE) 0.209 k star (bias corrected MLE) 0.209 Theta hat (MLE) 3.223 Theta star (bias corrected MLE) 3.214 nu hat (MLE) 27.15 nu star (bias corrected) 27.23 Adjusted Level of Significance (β) 0.0463 Approximate Chi Square Value (27.23, α) 16.33 Adjusted Chi Square Value (27.23, β) 16.14 Page 62 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 95% Gamma Approximate UCL (use when n>=50) 1.123 95% Gamma Adjusted UCL (use when n<50) 1.136 Estimates of Gamma Parameters using KM Estimates Mean (KM) 1.716 SD (KM) 3.146 Variance (KM) 9.897 SE of Mean (KM) 0.433 k hat (KM) 0.298 k star (KM) 0.294 nu hat (KM) 38.68 nu star (KM) 38.23 theta hat (KM) 5.767 theta star (KM) 5.835 24.83 80% gamma percentile (KM) 2.618 90% gamma percentile (KM) 5.073 95% gamma percentile (KM) 7.9 99% gamma percentile (KM) 15.27 95% Gamma Approximate KM-UCL (use when n>=50) 2.617 95% Gamma Adjusted KM-UCL (use when n<50) 2.642 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (38.23, α) 25.07 Adjusted Chi Square Value (38.23, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.689 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.818 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.358 Lilliefors GOF Test 5% Lilliefors Critical Value 0.283 Detected Data Not Lognormal at 5% Significance Level Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 0.928 Mean in Log Scale -1.517 SD in Original Scale 3.226 SD in Log Scale 1.61 95% t UCL (assumes normality of ROS data) 1.596 95% Percentile Bootstrap UCL 1.67 95% BCA Bootstrap UCL 2.085 95% Bootstrap t UCL 3.432 95% H-UCL (Log ROS) 1.342 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.272 KM Geo Mean 1.312 KM SD (logged) 0.478 95% Critical H Value (KM-Log) 1.851 KM Standard Error of Mean (logged) 0.0723 95% H-UCL (KM -Log) 1.643 KM SD (logged) 0.478 95% Critical H Value (KM-Log) 1.851 KM Standard Error of Mean (logged) 0.0723 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 2.929 Mean in Log Scale 0.213 SD in Original Scale 6.492 SD in Log Scale 0.974 95% t UCL (Assumes normality) 4.273 95% H-Stat UCL 2.612 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Data do not follow a Discernible Distribution at 5% Significance Level Page 63 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Suggested UCL to Use 95% KM (Chebyshev) UCL 3.603 3 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. 0 Number of Distinct Non-Detects 3 DW_EU11_PFO5DA General Statistics Total Number of Observations 63 Number of Distinct Observations Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 63 Number of Distinct Detects General Statistics Total Number of Observations 63 Number of Distinct Observations 41 The data set for variable DW_EU11_PFO5DA was not processed! DW_EU11_PMPA Number of Detects 50 Number of Non-Detects 13 Number of Distinct Detects 40 Number of Distinct Non-Detects 2 143.7 Minimum Detect 5.5 Minimum Non-Detect 10 Maximum Detect 570 Maximum Non-Detect 50 1.586 Kurtosis Detects 1.777 Variance Detects 20661 Percent Non-Detects 20.63% Mean Detects 159.4 SD Detects Mean of Logged Detects 4.71 SD of Logged Detects 0.896 Median Detects 110 CV Detects 0.902 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.779 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.947 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.254 Lilliefors GOF Test 5% Lilliefors Critical Value 0.125 Detected Data Not Normal at 5% Significance Level Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs Page 64 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 157.7 KM Mean 127.7 KM Standard Error of Mean 17.97 181.6 95% KM Chebyshev UCL 206 KM SD 141.2 95% KM (BCA) UCL 161.2 95% KM (t) UCL 157.7 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 239.9 99% KM Chebyshev UCL 306.5 95% KM (z) UCL 157.3 95% KM Bootstrap t UCL 163 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 1.32 Anderson-Darling GOF Test 5% A-D Critical Value 0.767 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.163 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.127 Detected Data Not Gamma Distributed at 5% Significance Level 153 nu star (bias corrected) 145.2 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.53 k star (bias corrected MLE) 1.452 Mean (detects) 159.4 Theta hat (MLE) 104.1 Theta star (bias corrected MLE) 109.8 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 126.5 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 570 Median 84 SD 143.4 CV 1.134 k hat (MLE) 0.331 k star (bias corrected MLE) 0.326 Theta hat (MLE) 382.4 Theta star (bias corrected MLE) 388.5 nu hat (MLE) 41.67 nu star (bias corrected) 41.02 Adjusted Level of Significance (β) 0.0462 Approximate Chi Square Value (41.02, α) 27.34 Adjusted Chi Square Value (41.02, β) 27.08 95% Gamma Approximate UCL (use when n>=50) 189.7 95% Gamma Adjusted UCL (use when n<50) 191.6 Estimates of Gamma Parameters using KM Estimates Mean (KM) 127.7 SD (KM) 141.2 Variance (KM) 19925 SE of Mean (KM) 17.97 k hat (KM) 0.818 k star (KM) 0.79 nu hat (KM) 103.1 nu star (KM) 99.55 theta hat (KM) 156 theta star (KM) 161.6 80% gamma percentile (KM) 208.8 90% gamma percentile (KM) 311.5 95% gamma percentile (KM) 416.1 99% gamma percentile (KM) 663.5 Page 65 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 77.08 95% Gamma Approximate KM-UCL (use when n>=50) 164 95% Gamma Adjusted KM-UCL (use when n<50) 164.9 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (99.55, α) 77.53 Adjusted Chi Square Value (99.55, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.954 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.947 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.106 Lilliefors GOF Test 5% Lilliefors Critical Value 0.125 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 130.2 Mean in Log Scale 4.318 SD in Original Scale 140.2 SD in Log Scale 1.129 95% t UCL (assumes normality of ROS data) 159.7 95% Percentile Bootstrap UCL 157.9 95% BCA Bootstrap UCL 163.4 95% Bootstrap t UCL 163.9 95% H-UCL (Log ROS) 196.6 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 4.096 KM Geo Mean 60.12 KM SD (logged) 1.443 95% Critical H Value (KM-Log) 2.404 KM Standard Error of Mean (logged) 0.184 95% H-UCL (KM -Log) 264.8 4.096 KM SD (logged) 1.443 95% Critical H Value (KM-Log) 2.404 KM Standard Error of Mean (logged) 0.184 157.7 95% H-Stat UCL 276.6 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 127.8 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Lognormal Distributed at 5% Significance Level SD in Original Scale 142.2 SD in Log Scale 1.465 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 264.8 DW_EU12_HFPO-DA Page 66 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 General Statistics Total Number of Observations 384 Number of Distinct Observations 153 Number of Detects 254 Number of Non-Detects 130 Number of Distinct Detects 143 Number of Distinct Non-Detects 16 37.08 Minimum Detect 0.749 Minimum Non-Detect 0.575 Maximum Detect 270 Maximum Non-Detect 4 4.112 Kurtosis Detects 19.71 Variance Detects 1375 Percent Non-Detects 33.85% Mean Detects 23.03 SD Detects Mean of Logged Detects 2.502 SD of Logged Detects 1.073 Median Detects 12 CV Detects 1.61 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.528 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.274 Lilliefors GOF Test 5% Lilliefors Critical Value 0.056 Detected Data Not Normal at 5% Significance Level 18.36 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 15.54 KM Standard Error of Mean 1.63 20.43 95% KM Chebyshev UCL 22.65 KM SD 31.87 95% KM (BCA) UCL 18.41 95% KM (t) UCL 18.23 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 25.72 99% KM Chebyshev UCL 31.76 95% KM (z) UCL 18.23 95% KM Bootstrap t UCL 18.8 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 7.783 Anderson-Darling GOF Test 5% A-D Critical Value 0.788 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.129 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.0593 Detected Data Not Gamma Distributed at 5% Significance Level 466.8 nu star (bias corrected) 462.7 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.919 k star (bias corrected MLE) 0.911 Mean (detects) 23.03 Theta hat (MLE) 25.06 Theta star (bias corrected MLE) 25.29 nu hat (MLE) Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Page 67 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 15.24 Maximum 270 Median 5.9 SD 32.05 CV 2.103 k hat (MLE) 0.267 k star (bias corrected MLE) 0.267 Theta hat (MLE) 56.98 Theta star (bias corrected MLE) 57.06 nu hat (MLE) 205.4 nu star (bias corrected) 205.1 Adjusted Level of Significance (β) 0.0494 Approximate Chi Square Value (205.09, α) 172.9 Adjusted Chi Square Value (205.09, β) 172.8 95% Gamma Approximate UCL (use when n>=50) 18.07 95% Gamma Adjusted UCL (use when n<50) 18.08 Estimates of Gamma Parameters using KM Estimates Mean (KM) 15.54 SD (KM) 31.87 Variance (KM) 1015 SE of Mean (KM) 1.63 k hat (KM) 0.238 k star (KM) 0.238 nu hat (KM) 182.8 nu star (KM) 182.7 theta hat (KM) 65.32 theta star (KM) 65.35 152.3 80% gamma percentile (KM) 22.16 90% gamma percentile (KM) 46.81 95% gamma percentile (KM) 76.36 99% gamma percentile (KM) 155.6 95% Gamma Approximate KM-UCL (use when n>=50) 18.63 95% Gamma Adjusted KM-UCL (use when n<50) 18.64 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (182.67, α) 152.4 Adjusted Chi Square Value (182.67, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.975 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.0487 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0447 Lilliefors GOF Test 5% Lilliefors Critical Value 0.056 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 15.69 Mean in Log Scale 1.679 SD in Original Scale 31.84 SD in Log Scale 1.506 95% t UCL (assumes normality of ROS data) 18.37 95% Percentile Bootstrap UCL 18.49 95% BCA Bootstrap UCL 18.77 95% Bootstrap t UCL 18.83 95% H-UCL (Log ROS) 20.34 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.578 KM Geo Mean 4.845 KM SD (logged) 1.583 95% Critical H Value (KM-Log) 2.669 KM Standard Error of Mean (logged) 0.087 95% H-UCL (KM -Log) 21.05 KM SD (logged) 1.583 95% Critical H Value (KM-Log) 2.669 KM Standard Error of Mean (logged) 0.087 Page 68 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 1.736 18.37 95% H-Stat UCL 18.23 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 15.69 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Lognormal Distributed at 5% Significance Level SD in Original Scale 31.84 SD in Log Scale 1.406 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 21.05 DW_EU12_PEPA General Statistics Total Number of Observations 315 Number of Distinct Observations 34 Number of Detects 46 Number of Non-Detects 269 Number of Distinct Detects 32 Number of Distinct Non-Detects 3 19.94 Minimum Detect 15 Minimum Non-Detect 11 Maximum Detect 130 Maximum Non-Detect 100 2.306 Kurtosis Detects 8.405 Variance Detects 397.6 Percent Non-Detects 85.4% Mean Detects 39.22 SD Detects Mean of Logged Detects 3.571 SD of Logged Detects 0.43 Median Detects 34 CV Detects 0.508 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.816 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.945 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.16 Lilliefors GOF Test 5% Lilliefors Critical Value 0.129 Detected Data Not Normal at 5% Significance Level 17.13 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 15.69 KM Standard Error of Mean 0.816 18.14 95% KM Chebyshev UCL 19.25 KM SD 12.48 95% KM (BCA) UCL 17.17 95% KM (t) UCL 17.04 95% KM (Percentile Bootstrap) UCL 95% KM (z) UCL 17.03 95% KM Bootstrap t UCL 17.24 90% KM Chebyshev UCL Page 69 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 97.5% KM Chebyshev UCL 20.79 99% KM Chebyshev UCL 23.81 Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.655 Anderson-Darling GOF Test 5% A-D Critical Value 0.753 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.101 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.131 Detected data appear Gamma Distributed at 5% Significance Level 485.8 nu star (bias corrected) 455.5 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 5.28 k star (bias corrected MLE) 4.951 Mean (detects) 39.22 Theta hat (MLE) 7.427 Theta star (bias corrected MLE) 7.922 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 6.987 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 130 Median 0.01 SD 15.76 CV 2.255 k hat (MLE) 0.171 k star (bias corrected MLE) 0.172 Theta hat (MLE) 40.81 Theta star (bias corrected MLE) 40.69 nu hat (MLE) 107.9 nu star (bias corrected) 108.2 Adjusted Level of Significance (β) 0.0492 Approximate Chi Square Value (108.18, α) 85.17 Adjusted Chi Square Value (108.18, β) 85.08 95% Gamma Approximate UCL (use when n>=50) 8.874 95% Gamma Adjusted UCL (use when n<50) 8.884 Estimates of Gamma Parameters using KM Estimates Mean (KM) 15.69 SD (KM) 12.48 Variance (KM) 155.9 SE of Mean (KM) 0.816 k hat (KM) 1.58 k star (KM) 1.567 nu hat (KM) 995.1 nu star (KM) 987 theta hat (KM) 9.934 theta star (KM) 10.02 914.7 80% gamma percentile (KM) 24.16 90% gamma percentile (KM) 32.35 95% gamma percentile (KM) 40.29 99% gamma percentile (KM) 58.15 95% Gamma Approximate KM-UCL (use when n>=50) 16.92 95% Gamma Adjusted KM-UCL (use when n<50) 16.93 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (986.97, α) 915 Adjusted Chi Square Value (986.97, β) Lognormal GOF Test on Detected Observations Only Page 70 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Shapiro Wilk Test Statistic 0.974 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.945 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0819 Lilliefors GOF Test 5% Lilliefors Critical Value 0.129 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 12.42 Mean in Log Scale 2.061 SD in Original Scale 14.27 SD in Log Scale 0.961 95% t UCL (assumes normality of ROS data) 13.75 95% Percentile Bootstrap UCL 13.75 95% BCA Bootstrap UCL 13.97 95% Bootstrap t UCL 13.95 95% H-UCL (Log ROS) 13.96 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 2.609 KM Geo Mean 13.59 KM SD (logged) 0.45 95% Critical H Value (KM-Log) 1.768 KM Standard Error of Mean (logged) 0.0378 95% H-UCL (KM -Log) 15.72 2.473 KM SD (logged) 0.45 95% Critical H Value (KM-Log) 1.768 KM Standard Error of Mean (logged) 0.0378 15.66 95% H-Stat UCL 14.36 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 14.42 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Gamma Distributed at 5% Significance Level SD in Original Scale 13.37 SD in Log Scale 0.526 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM Approximate Gamma UCL 16.92 95% GROS Approximate Gamma UCL 8.874 DW_EU12_PFECA-G General Statistics Total Number of Observations 322 Number of Distinct Observations 13 Number of Detects 3 Number of Non-Detects 319 Number of Distinct Detects 3 Number of Distinct Non-Detects 10 Minimum Detect 2.1 Minimum Non-Detect 1.1 Page 71 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Maximum Detect 2.3 Maximum Non-Detect 50 Variance Detects 0.01 Percent Non-Detects 99.07% Mean Detects 2.2 SD Detects 0.1 Median Detects 2.2 CV Detects 0.0455 Skewness Detects -1.98E-14 Kurtosis Detects N/A Warning: Data set has only 3 Detected Values. This is not enough to compute meaningful or reliable statistics and estimates. Normal GOF Test on Detects Only Mean of Logged Detects 0.788 SD of Logged Detects 0.0455 Shapiro Wilk Test Statistic 1 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.767 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.175 Lilliefors GOF Test 5% Lilliefors Critical Value 0.425 Detected Data appear Normal at 5% Significance Level Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 1.11 KM Standard Error of Mean 0.0073 KM SD 0.106 95% KM (BCA) UCL N/A 95% KM (t) UCL 1.122 95% KM (Percentile Bootstrap) UCL N/A 95% KM (z) UCL 1.122 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL 1.132 95% KM Chebyshev UCL 1.142 N/A 97.5% KM Chebyshev UCL 1.156 99% KM Chebyshev UCL 1.183 4352 nu star (bias corrected) N/A Gamma GOF Tests on Detected Observations Only Not Enough Data to Perform GOF Test Gamma Statistics on Detected Data Only k hat (MLE) 725.4 k star (bias corrected MLE) Mean (detects) 2.2 Theta hat (MLE) 0.00303 Theta star (bias corrected MLE) N/A nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 0.87 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 2.3 Median 0.852 SD 0.467 CV 0.537 k hat (MLE) 1.856 k star (bias corrected MLE) 1.84 Page 72 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Theta hat (MLE) 0.469 Theta star (bias corrected MLE) 0.473 nu hat (MLE) 1195 nu star (bias corrected) 1185 Adjusted Level of Significance (β) 0.0493 Approximate Chi Square Value (N/A, α) 1106 Adjusted Chi Square Value (N/A, β) 1106 95% Gamma Approximate UCL (use when n>=50) 0.932 95% Gamma Adjusted UCL (use when n<50) N/A Estimates of Gamma Parameters using KM Estimates Mean (KM) 1.11 SD (KM) 0.106 Variance (KM) 0.0113 SE of Mean (KM) 0.0073 k hat (KM) 108.8 k star (KM) 107.8 nu hat (KM) 70046 nu star (KM) 69394 theta hat (KM) 0.0102 theta star (KM) 0.0103 68780 80% gamma percentile (KM) 1.199 90% gamma percentile (KM) 1.249 95% gamma percentile (KM) 1.292 99% gamma percentile (KM) 1.374 95% Gamma Approximate KM-UCL (use when n>=50) 1.12 95% Gamma Adjusted KM-UCL (use when n<50) 1.12 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (N/A, α) 68783 Adjusted Chi Square Value (N/A, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 1 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.767 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.176 Lilliefors GOF Test 5% Lilliefors Critical Value 0.425 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 1.204 Mean in Log Scale 0.159 SD in Original Scale 0.284 SD in Log Scale 0.232 95% t UCL (assumes normality of ROS data) 1.23 95% Percentile Bootstrap UCL 1.232 95% BCA Bootstrap UCL 1.231 95% Bootstrap t UCL 1.231 95% H-UCL (Log ROS) 1.231 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.102 KM Geo Mean 1.107 KM SD (logged) 0.0669 95% Critical H Value (KM-Log) N/A KM Standard Error of Mean (logged) 0.00459 95% H-UCL (KM -Log) N/A KM SD (logged) 0.0669 95% Critical H Value (KM-Log) N/A KM Standard Error of Mean (logged) 0.00459 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 1.192 Mean in Log Scale -0.0195 SD in Original Scale 2.319 SD in Log Scale 0.368 95% t UCL (Assumes normality) 1.405 95% H-Stat UCL 1.087 Page 73 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Suggested UCL to Use 95% KM (t) UCL 1.122 DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Normal Distributed at 5% Significance Level 23 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. 0 Number of Distinct Non-Detects 23 DW_EU12_PFESA-BP1 General Statistics Total Number of Observations 357 Number of Distinct Observations Warning: All observations are Non-Detects (NDs), therefore all statistics and estimates should also be NDs! Specifically, sample mean, UCLs, UPLs, and other statistics are also NDs lying below the largest detection limit! The Project Team may decide to use alternative site specific values to estimate environmental parameters (e.g., EPC, BTV). Number of Detects 0 Number of Non-Detects 357 Number of Distinct Detects General Statistics Total Number of Observations 357 Number of Distinct Observations 85 The data set for variable DW_EU12_PFESA-BP1 was not processed! DW_EU12_PFESA-BP2 Number of Detects 138 Number of Non-Detects 219 Number of Distinct Detects 76 Number of Distinct Non-Detects 14 2.512 Minimum Detect 1.1 Minimum Non-Detect 1.1 Maximum Detect 13 Maximum Non-Detect 50 1.286 Kurtosis Detects 1.217 Variance Detects 6.311 Percent Non-Detects 61.34% Mean Detects 4.237 SD Detects Mean of Logged Detects 1.287 SD of Logged Detects 0.559 Median Detects 3.57 CV Detects 0.593 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.861 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.173 Lilliefors GOF Test Page 74 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 5% Lilliefors Critical Value 0.0758 Detected Data Not Normal at 5% Significance Level 2.546 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 2.346 KM Standard Error of Mean 0.116 2.695 95% KM Chebyshev UCL 2.853 KM SD 2.176 95% KM (BCA) UCL 2.528 95% KM (t) UCL 2.538 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 3.072 99% KM Chebyshev UCL 3.504 95% KM (z) UCL 2.537 95% KM Bootstrap t UCL 2.559 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 1.924 Anderson-Darling GOF Test 5% A-D Critical Value 0.758 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.1 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.0801 Detected Data Not Gamma Distributed at 5% Significance Level 923 nu star (bias corrected) 904.3 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 3.344 k star (bias corrected MLE) 3.276 Mean (detects) 4.237 Theta hat (MLE) 1.267 Theta star (bias corrected MLE) 1.293 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 1.801 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 13 Median 0.616 SD 2.516 CV 1.397 k hat (MLE) 0.318 k star (bias corrected MLE) 0.317 Theta hat (MLE) 5.668 Theta star (bias corrected MLE) 5.682 nu hat (MLE) 226.8 nu star (bias corrected) 226.3 Adjusted Level of Significance (β) 0.0493 Approximate Chi Square Value (226.27, α) 192.5 Adjusted Chi Square Value (226.27, β) 192.3 95% Gamma Approximate UCL (use when n>=50) 2.117 95% Gamma Adjusted UCL (use when n<50) 2.119 Estimates of Gamma Parameters using KM Estimates Mean (KM) 2.346 SD (KM) 2.176 Variance (KM) 4.734 SE of Mean (KM) 0.116 k hat (KM) 1.162 k star (KM) 1.154 nu hat (KM) 829.8 nu star (KM) 824.2 Page 75 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 theta hat (KM) 2.018 theta star (KM) 2.032 758.3 80% gamma percentile (KM) 3.728 90% gamma percentile (KM) 5.213 95% gamma percentile (KM) 6.682 99% gamma percentile (KM) 10.06 95% Gamma Approximate KM-UCL (use when n>=50) 2.549 95% Gamma Adjusted KM-UCL (use when n<50) 2.549 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (824.17, α) 758.5 Adjusted Chi Square Value (824.17, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.962 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.00908 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0707 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0758 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 2.203 Mean in Log Scale 0.347 SD in Original Scale 2.278 SD in Log Scale 0.954 95% t UCL (assumes normality of ROS data) 2.402 95% Percentile Bootstrap UCL 2.397 95% BCA Bootstrap UCL 2.422 95% Bootstrap t UCL 2.418 95% H-UCL (Log ROS) 2.478 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.578 KM Geo Mean 1.783 KM SD (logged) 0.667 95% Critical H Value (KM-Log) 1.887 KM Standard Error of Mean (logged) 0.0363 95% H-UCL (KM -Log) 2.382 0.467 KM SD (logged) 0.667 95% Critical H Value (KM-Log) 1.887 KM Standard Error of Mean (logged) 0.0363 2.676 95% H-Stat UCL 2.42 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 2.409 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Lognormal Distributed at 5% Significance Level SD in Original Scale 3.062 SD in Log Scale 0.814 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). Suggested UCL to Use KM H-UCL 2.382 Page 76 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. DW_EU12_PFMOAA General Statistics Total Number of Observations 357 Number of Distinct Observations 116 Number of Detects 205 Number of Non-Detects 152 Number of Distinct Detects 105 Number of Distinct Non-Detects 13 16.13 Minimum Detect 1.84 Minimum Non-Detect 1.15 Maximum Detect 146 Maximum Non-Detect 50 3.741 Kurtosis Detects 23.15 Variance Detects 260.1 Percent Non-Detects 42.58% Mean Detects 18.3 SD Detects Mean of Logged Detects 2.647 SD of Logged Detects 0.706 Median Detects 14 CV Detects 0.881 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.718 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.175 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0623 Detected Data Not Normal at 5% Significance Level 12.63 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 11.26 KM Standard Error of Mean 0.788 13.62 95% KM Chebyshev UCL 14.69 KM SD 14.75 95% KM (BCA) UCL 12.65 95% KM (t) UCL 12.56 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 16.18 99% KM Chebyshev UCL 19.1 95% KM (z) UCL 12.55 95% KM Bootstrap t UCL 12.74 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 2.524 Anderson-Darling GOF Test 5% A-D Critical Value 0.766 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.0967 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.0639 Detected Data Not Gamma Distributed at 5% Significance Level 850.7 nu star (bias corrected) 839.6 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 2.075 k star (bias corrected MLE) 2.048 Mean (detects) 18.3 Theta hat (MLE) 8.821 Theta star (bias corrected MLE) 8.938 nu hat (MLE) Gamma ROS Statistics using Imputed Non-Detects Page 77 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 10.62 GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 146 Median 6.3 SD 15.16 CV 1.428 k hat (MLE) 0.273 k star (bias corrected MLE) 0.273 Theta hat (MLE) 38.85 Theta star (bias corrected MLE) 38.91 nu hat (MLE) 195.1 nu star (bias corrected) 194.8 Adjusted Level of Significance (β) 0.0493 Approximate Chi Square Value (194.81, α) 163.5 Adjusted Chi Square Value (194.81, β) 163.4 95% Gamma Approximate UCL (use when n>=50) 12.65 95% Gamma Adjusted UCL (use when n<50) 12.66 Estimates of Gamma Parameters using KM Estimates Mean (KM) 11.26 SD (KM) 14.75 Variance (KM) 217.5 SE of Mean (KM) 0.788 k hat (KM) 0.583 k star (KM) 0.58 nu hat (KM) 416 nu star (KM) 413.9 theta hat (KM) 19.32 theta star (KM) 19.42 367.5 80% gamma percentile (KM) 18.55 90% gamma percentile (KM) 29.51 95% gamma percentile (KM) 41.02 99% gamma percentile (KM) 68.94 95% Gamma Approximate KM-UCL (use when n>=50) 12.67 95% Gamma Adjusted KM-UCL (use when n<50) 12.68 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (413.85, α) 367.7 Adjusted Chi Square Value (413.85, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.982 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.468 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.058 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0623 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 11.8 Mean in Log Scale 1.926 SD in Original Scale 14.4 SD in Log Scale 1.066 95% t UCL (assumes normality of ROS data) 13.06 95% Percentile Bootstrap UCL 13.04 95% BCA Bootstrap UCL 13.15 95% Bootstrap t UCL 13.32 95% H-UCL (Log ROS) 13.7 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.681 KM Geo Mean 5.371 KM SD (logged) 1.282 95% Critical H Value (KM-Log) 2.37 Page 78 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 KM Standard Error of Mean (logged) 0.0772 95% H-UCL (KM -Log) 14.35 1.863 KM SD (logged) 1.282 95% Critical H Value (KM-Log) 2.37 KM Standard Error of Mean (logged) 0.0772 12.94 95% H-Stat UCL 13.65 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 11.67 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Lognormal Distributed at 5% Significance Level SD in Original Scale 14.59 SD in Log Scale 1.113 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 14.35 DW_EU12_PFO2HxA General Statistics Total Number of Observations 357 Number of Distinct Observations 142 Number of Detects 231 Number of Non-Detects 126 Number of Distinct Detects 131 Number of Distinct Non-Detects 13 32.77 Minimum Detect 1.27 Minimum Non-Detect 1.1 Maximum Detect 290 Maximum Non-Detect 50 3.973 Kurtosis Detects 22.93 Variance Detects 1074 Percent Non-Detects 35.29% Mean Detects 22.63 SD Detects Mean of Logged Detects 2.478 SD of Logged Detects 1.111 Median Detects 12 CV Detects 1.448 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.619 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.257 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0587 Detected Data Not Normal at 5% Significance Level Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 15.11 KM Standard Error of Mean 1.499 Page 79 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 17.75 19.6 95% KM Chebyshev UCL 21.64 KM SD 28.23 95% KM (BCA) UCL 17.81 95% KM (t) UCL 17.58 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 24.47 99% KM Chebyshev UCL 30.02 95% KM (z) UCL 17.57 95% KM Bootstrap t UCL 17.93 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 5.148 Anderson-Darling GOF Test 5% A-D Critical Value 0.788 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.134 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.0621 Detected Data Not Gamma Distributed at 5% Significance Level 420.8 nu star (bias corrected) 416.7 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 0.911 k star (bias corrected MLE) 0.902 Mean (detects) 22.63 Theta hat (MLE) 24.85 Theta star (bias corrected MLE) 25.09 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 14.69 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 290 Median 4.6 SD 28.47 CV 1.938 k hat (MLE) 0.262 k star (bias corrected MLE) 0.262 Theta hat (MLE) 56.03 Theta star (bias corrected MLE) 56.1 nu hat (MLE) 187.2 nu star (bias corrected) 187 Adjusted Level of Significance (β) 0.0493 Approximate Chi Square Value (186.96, α) 156.3 Adjusted Chi Square Value (186.96, β) 156.2 95% Gamma Approximate UCL (use when n>=50) 17.57 95% Gamma Adjusted UCL (use when n<50) 17.58 Estimates of Gamma Parameters using KM Estimates Mean (KM) 15.11 SD (KM) 28.23 Variance (KM) 797.2 SE of Mean (KM) 1.499 k hat (KM) 0.286 k star (KM) 0.286 nu hat (KM) 204.5 nu star (KM) 204.1 theta hat (KM) 52.76 theta star (KM) 52.86 80% gamma percentile (KM) 22.88 90% gamma percentile (KM) 44.81 95% gamma percentile (KM) 70.19 99% gamma percentile (KM) 136.6 Gamma Kaplan-Meier (KM) Statistics Page 80 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 171.9 95% Gamma Approximate KM-UCL (use when n>=50) 17.92 95% Gamma Adjusted KM-UCL (use when n<50) 17.94 Approximate Chi Square Value (204.07, α) 172 Adjusted Chi Square Value (204.07, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.966 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 0.00172 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.0529 Lilliefors GOF Test 5% Lilliefors Critical Value 0.0587 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Approximate Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 15.07 Mean in Log Scale 1.563 SD in Original Scale 28.28 SD in Log Scale 1.607 95% t UCL (assumes normality of ROS data) 17.54 95% Percentile Bootstrap UCL 17.68 95% BCA Bootstrap UCL 18 95% Bootstrap t UCL 18.13 95% H-UCL (Log ROS) 21.81 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 1.658 KM Geo Mean 5.247 KM SD (logged) 1.435 95% Critical H Value (KM-Log) 2.516 KM Standard Error of Mean (logged) 0.0766 95% H-UCL (KM -Log) 17.8 1.599 KM SD (logged) 1.435 95% Critical H Value (KM-Log) 2.516 KM Standard Error of Mean (logged) 0.0766 17.64 95% H-Stat UCL 19.52 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 15.17 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Approximate Lognormal Distributed at 5% Significance Level SD in Original Scale 28.3 SD in Log Scale 1.524 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM H-UCL 17.8 DW_EU12_PFO3OA General Statistics Page 81 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Total Number of Observations 357 Number of Distinct Observations 61 Number of Detects 57 Number of Non-Detects 300 Number of Distinct Detects 44 Number of Distinct Non-Detects 19 9.785 Minimum Detect 1.3 Minimum Non-Detect 1.1 Maximum Detect 70 Maximum Non-Detect 50 5.244 Kurtosis Detects 32.74 Variance Detects 95.74 Percent Non-Detects 84.03% Mean Detects 6.342 SD Detects Mean of Logged Detects 1.411 SD of Logged Detects 0.812 Median Detects 3.7 CV Detects 1.543 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.472 Normal GOF Test on Detected Observations Only 5% Shapiro Wilk P Value 0 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.303 Lilliefors GOF Test 5% Lilliefors Critical Value 0.117 Detected Data Not Normal at 5% Significance Level 2.393 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 1.977 KM Standard Error of Mean 0.232 2.672 95% KM Chebyshev UCL 2.987 KM SD 4.325 95% KM (BCA) UCL 2.449 95% KM (t) UCL 2.359 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 3.424 99% KM Chebyshev UCL 4.282 95% KM (z) UCL 2.358 95% KM Bootstrap t UCL 2.667 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 3.119 Anderson-Darling GOF Test 5% A-D Critical Value 0.773 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.184 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.121 Detected Data Not Gamma Distributed at 5% Significance Level 146.7 nu star (bias corrected) 140.3 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 1.287 k star (bias corrected MLE) 1.231 Mean (detects) 6.342 Theta hat (MLE) 4.929 Theta star (bias corrected MLE) 5.154 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Page 82 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Minimum 0.01 Mean 1.021 Maximum 70 Median 0.01 SD 4.523 CV 4.43 k hat (MLE) 0.201 k star (bias corrected MLE) 0.201 Theta hat (MLE) 5.088 Theta star (bias corrected MLE) 5.083 nu hat (MLE) 143.3 nu star (bias corrected) 143.4 Adjusted Level of Significance (β) 0.0493 Approximate Chi Square Value (143.41, α) 116.7 Adjusted Chi Square Value (143.41, β) 116.6 95% Gamma Approximate UCL (use when n>=50) 1.254 95% Gamma Adjusted UCL (use when n<50) 1.255 Estimates of Gamma Parameters using KM Estimates Mean (KM) 1.977 SD (KM) 4.325 Variance (KM) 18.71 SE of Mean (KM) 0.232 k hat (KM) 0.209 k star (KM) 0.209 nu hat (KM) 149.1 nu star (KM) 149.2 theta hat (KM) 9.464 theta star (KM) 9.459 121.9 80% gamma percentile (KM) 2.663 90% gamma percentile (KM) 5.977 95% gamma percentile (KM) 10.07 99% gamma percentile (KM) 21.25 95% Gamma Approximate KM-UCL (use when n>=50) 2.418 95% Gamma Adjusted KM-UCL (use when n<50) 2.42 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (149.19, α) 122 Adjusted Chi Square Value (149.19, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Approximate Test Statistic 0.921 Shapiro Wilk GOF Test 5% Shapiro Wilk P Value 9.6510E-4 Detected Data Not Lognormal at 5% Significance Level Lilliefors Test Statistic 0.12 Lilliefors GOF Test 5% Lilliefors Critical Value 0.117 Detected Data Not Lognormal at 5% Significance Level Detected Data Not Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 1.319 Mean in Log Scale -1.212 SD in Original Scale 4.473 SD in Log Scale 1.706 95% t UCL (assumes normality of ROS data) 1.71 95% Percentile Bootstrap UCL 1.78 95% BCA Bootstrap UCL 1.961 95% Bootstrap t UCL 1.983 95% H-UCL (Log ROS) 1.64 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.333 KM Geo Mean 1.395 KM SD (logged) 0.579 95% Critical H Value (KM-Log) 1.835 KM Standard Error of Mean (logged) 0.033 95% H-UCL (KM -Log) 1.745 KM SD (logged) 0.579 95% Critical H Value (KM-Log) 1.835 KM Standard Error of Mean (logged) 0.033 DL/2 Statistics Page 83 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 0.173 2.417 95% H-Stat UCL 1.662 DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 1.993 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Data do not follow a Discernible Distribution at 5% Significance Level SD in Original Scale 4.85 SD in Log Scale 0.723 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use 95% KM (Chebyshev) UCL 2.987 DW_EU12_PFO4DA General Statistics Total Number of Observations 357 Number of Distinct Observations 33 Number of Detects 16 Number of Non-Detects 341 Number of Distinct Detects 12 Number of Distinct Non-Detects 22 1.579 Minimum Detect 1.57 Minimum Non-Detect 1.1 Maximum Detect 6.7 Maximum Non-Detect 50 0.976 Kurtosis Detects -0.278 Variance Detects 2.494 Percent Non-Detects 95.52% Mean Detects 3.277 SD Detects Mean of Logged Detects 1.088 SD of Logged Detects 0.449 Median Detects 2.5 CV Detects 0.482 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.858 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.887 Detected Data Not Normal at 5% Significance Level Lilliefors Test Statistic 0.251 Lilliefors GOF Test 5% Lilliefors Critical Value 0.213 Detected Data Not Normal at 5% Significance Level 1.26 Detected Data Not Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 1.211 KM Standard Error of Mean 0.0324 1.308 95% KM Chebyshev UCL 1.352 KM SD 0.561 95% KM (BCA) UCL 1.265 95% KM (t) UCL 1.264 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 1.413 99% KM Chebyshev UCL 1.533 95% KM (z) UCL 1.264 95% KM Bootstrap t UCL 1.281 90% KM Chebyshev UCL Page 84 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.754 Anderson-Darling GOF Test 5% A-D Critical Value 0.741 Detected Data Not Gamma Distributed at 5% Significance Level K-S Test Statistic 0.233 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.216 Detected Data Not Gamma Distributed at 5% Significance Level 167 nu star (bias corrected) 137 Detected Data Not Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 5.219 k star (bias corrected MLE) 4.282 Mean (detects) 3.277 Theta hat (MLE) 0.628 Theta star (bias corrected MLE) 0.765 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 0.19 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 6.7 Median 0.01 SD 0.767 CV 4.047 k hat (MLE) 0.278 k star (bias corrected MLE) 0.277 Theta hat (MLE) 0.683 Theta star (bias corrected MLE) 0.684 nu hat (MLE) 198.3 nu star (bias corrected) 198 Adjusted Level of Significance (β) 0.0493 Approximate Chi Square Value (197.97, α) 166.4 Adjusted Chi Square Value (197.97, β) 166.3 95% Gamma Approximate UCL (use when n>=50) 0.226 95% Gamma Adjusted UCL (use when n<50) 0.226 Estimates of Gamma Parameters using KM Estimates Mean (KM) 1.211 SD (KM) 0.561 Variance (KM) 0.315 SE of Mean (KM) 0.0324 k hat (KM) 4.657 k star (KM) 4.62 nu hat (KM) 3325 nu star (KM) 3299 theta hat (KM) 0.26 theta star (KM) 0.262 3166 80% gamma percentile (KM) 1.642 90% gamma percentile (KM) 1.965 95% gamma percentile (KM) 2.261 99% gamma percentile (KM) 2.888 95% Gamma Approximate KM-UCL (use when n>=50) 1.261 95% Gamma Adjusted KM-UCL (use when n<50) 1.262 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (N/A, α) 3166 Adjusted Chi Square Value (N/A, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.92 Shapiro Wilk GOF Test Page 85 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 5% Shapiro Wilk Critical Value 0.887 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.211 Lilliefors GOF Test 5% Lilliefors Critical Value 0.213 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 0.429 Mean in Log Scale -1.662 SD in Original Scale 0.77 SD in Log Scale 1.267 95% t UCL (assumes normality of ROS data) 0.497 95% Percentile Bootstrap UCL 0.503 95% BCA Bootstrap UCL 0.514 95% Bootstrap t UCL 0.511 95% H-UCL (Log ROS) 0.496 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.149 KM Geo Mean 1.161 KM SD (logged) 0.232 95% Critical H Value (KM-Log) 1.69 KM Standard Error of Mean (logged) 0.0147 95% H-UCL (KM -Log) 1.218 -0.0252 KM SD (logged) 0.232 95% Critical H Value (KM-Log) 1.69 KM Standard Error of Mean (logged) 0.0147 1.424 95% H-Stat UCL 1.126 DL/2 Statistics DL/2 Normal DL/2 Log-Transformed Mean in Original Scale 1.226 Mean in Log Scale DL/2 is not a recommended method, provided for comparisons and historical reasons Nonparametric Distribution Free UCL Statistics Detected Data appear Lognormal Distributed at 5% Significance Level SD in Original Scale 2.275 SD in Log Scale 0.45 95% t UCL (Assumes normality) Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL. Recommendations are based upon data size, data distribution, and skewness. These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006). However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician. Suggested UCL to Use KM Student's t 1.211 KM H-UCL 1.218 DW_EU12_PFO5DA General Statistics Total Number of Observations 322 Number of Distinct Observations 14 Number of Detects 4 Number of Non-Detects 318 Number of Distinct Detects 4 Number of Distinct Non-Detects 11 Minimum Detect 5 Minimum Non-Detect 1.1 Maximum Detect 9.7 Maximum Non-Detect 100 Page 86 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 1.982 -0.972 Kurtosis Detects 1.5 Variance Detects 3.927 Percent Non-Detects 98.76% Mean Detects 7.7 SD Detects Mean of Logged Detects 2.013 SD of Logged Detects 0.285 Median Detects 8.05 CV Detects 0.257 Skewness Detects Normal GOF Test on Detects Only Shapiro Wilk Test Statistic 0.951 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Normal at 5% Significance Level Lilliefors Test Statistic 0.25 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Normal at 5% Significance Level N/A Detected Data appear Normal at 5% Significance Level Kaplan-Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs KM Mean 1.183 KM Standard Error of Mean 0.0491 1.33 95% KM Chebyshev UCL 1.397 KM SD 0.759 95% KM (BCA) UCL N/A 95% KM (t) UCL 1.264 95% KM (Percentile Bootstrap) UCL 97.5% KM Chebyshev UCL 1.489 99% KM Chebyshev UCL 1.671 95% KM (z) UCL 1.263 95% KM Bootstrap t UCL N/A 90% KM Chebyshev UCL Gamma GOF Tests on Detected Observations Only A-D Test Statistic 0.34 Anderson-Darling GOF Test 5% A-D Critical Value 0.657 Detected data appear Gamma Distributed at 5% Significance Level K-S Test Statistic 0.282 Kolmogorov-Smirnov GOF 5% K-S Critical Value 0.394 Detected data appear Gamma Distributed at 5% Significance Level 141.8 nu star (bias corrected) 36.79 Detected data appear Gamma Distributed at 5% Significance Level Gamma Statistics on Detected Data Only k hat (MLE) 17.73 k star (bias corrected MLE) 4.599 Mean (detects) 7.7 Theta hat (MLE) 0.434 Theta star (bias corrected MLE) 1.674 nu hat (MLE) For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates Minimum 0.01 Mean 0.176 Gamma ROS Statistics using Imputed Non-Detects GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs GROS may not be used when kstar of detects is small such as <1.0, especially when the sample size is small (e.g., <15-20) For such situations, GROS method may yield incorrect values of UCLs and BTVs This is especially true when the sample size is small. Maximum 9.7 Median 0.01 SD 0.97 CV 5.524 k hat (MLE) 0.27 k star (bias corrected MLE) 0.27 Theta hat (MLE) 0.65 Theta star (bias corrected MLE) 0.651 Page 87 of 91 December 2019 Output C-9 Screening-Level Exposure Assessment ProUCL UCL Statistics Output Surface Soil at Exposure Units 9 through 12 nu hat (MLE) 174.1 nu star (bias corrected) 173.8 Adjusted Level of Significance (β) 0.0493 Approximate Chi Square Value (173.78, α) 144.3 Adjusted Chi Square Value (173.78, β) 144.2 95% Gamma Approximate UCL (use when n>=50) 0.211 95% Gamma Adjusted UCL (use when n<50) N/A Estimates of Gamma Parameters using KM Estimates Mean (KM) 1.183 SD (KM) 0.759 Variance (KM) 0.576 SE of Mean (KM) 0.0491 k hat (KM) 2.427 k star (KM) 2.407 nu hat (KM) 1563 nu star (KM) 1550 theta hat (KM) 0.487 theta star (KM) 0.491 1459 80% gamma percentile (KM) 1.732 90% gamma percentile (KM) 2.204 95% gamma percentile (KM) 2.649 99% gamma percentile (KM) 3.626 95% Gamma Approximate KM-UCL (use when n>=50) 1.256 95% Gamma Adjusted KM-UCL (use when n<50) 1.256 Gamma Kaplan-Meier (KM) Statistics Approximate Chi Square Value (N/A, α) 1460 Adjusted Chi Square Value (N/A, β) Lognormal GOF Test on Detected Observations Only Shapiro Wilk Test Statistic 0.905 Shapiro Wilk GOF Test 5% Shapiro Wilk Critical Value 0.748 Detected Data appear Lognormal at 5% Significance Level Lilliefors Test Statistic 0.29 Lilliefors GOF Test 5% Lilliefors Critical Value 0.375 Detected Data appear Lognormal at 5% Significance Level Detected Data appear Lognormal at 5% Significance Level Lognormal ROS Statistics Using Imputed Non-Detects Mean in Original Scale 0.694 Mean in Log Scale -1.041 SD in Original Scale 1.087 SD in Log Scale 1.164 95% t UCL (assumes normality of ROS data) 0.794 95% Percentile Bootstrap UCL 0.802 95% BCA Bootstrap UCL 0.816 95% Bootstrap t UCL 0.814 95% H-UCL (Log ROS) 0.805 Statistics using KM estimates on Logged Data and Assuming Lognormal Distribution KM Mean (logged) 0.119 KM Geo Mean 1.127 KM SD (logged) 0.215 95% Critical H Value (KM-Log) 1.685 KM Standard Error of Mean (logged) 0.0139 95% H-UCL (KM -Log) 1.177 0.0131 KM SD (logged) 0.215 95% Critical H Value (KM-Log) 1.685 KM Standard Error of Mean (logged) 0.0139 1.95 95% H-Stat UCL