2019.12.31_CCO.p16_ChemoursCorrectiveActionPlan-AppendixF
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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
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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
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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
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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
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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
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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
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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
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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.
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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.
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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
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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.
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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.
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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.
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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
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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.
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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,
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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.
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• 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
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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;
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• 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.
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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
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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
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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
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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.
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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
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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]
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EU9EU12
EU5
EU7
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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
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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)
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!(EU5 (30)
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!(EU7 (30)
!(EU8 (30)
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EU Surface ISM Soil Location and Increment Counts
3 0 31.5 Kilometers
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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
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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
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!(Largemouth Bass
!(Redbreasted Sunfish
#*Surface Water
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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 1.196
DL/2 Statistics
DL/2 Normal DL/2 Log-Transformed
Mean in Original Scale 1.511 Mean in Log Scale
DL/2 is not a recommended method, provided for comparisons and historical reasons
SD in Original Scale