MultiID#'s_Amended NEBA Report Allen Buck Cliffside Mayo_20160930

NET ENVIRONMENTAL BENEFIT ANALYSIS OF
PROPOSED REMEDIAL ALTERNATIVES TO
ADDRESS ALLEGED RELEASES FROM COAL ASH
IMPOUNDMENTS AT THE
ALLEN, BUCK, CLIFFSIDE, AND MAYO
STEAM STATIONS
AMENDED
Expert Opinion of:
Joseph P. Nicolette
Prepared by:
EPS
1050 Crown Pointe Parkway, Suite 550
Atlanta, Georgia 30338
Tel: [phone]
September 30, 2016

NET ENVIRONMENTAL BENEFIT ANALYSIS OF PROPOSED
REMEDIAL ALTERNATIVES TO ADDRESS ALLEGED RELEASES
FROM COAL ASH IMPOUNDMENTS AT THE ALLEN, BUCK,
CLIFFSIDE, AND MAYO STEAM STATIONS
AMENDED
Expert Opinion of:
Joseph P. Nicolette
EPS
Environmental Planning Specialists, Inc.
1050 Crown Pointe Pkwy, Suite 550
Atlanta, GA 30338
Tel: [phone]
September 30, 2016

EPS
NET ENVIRONMENTAL BENEFIT ANALYSIS OF PROPOSED REMEDIAL
ALTERNATIVES TO ADDRESS ALLEGED RELEASES FROM COAL ASH
IMPOUNDMENTS AT THE ALLEN, BUCK, CLIFFSIDE, AND MAYO STEAM
STATIONS
AMENDED
September 30, 2016
TABLE OF CONTENTS
1 INTRODUCTION....................................................................................................... 1
1.1 Background................................................................................................1
1.2 Summary of Opinions................................................................................ 2
1.3 Qualifications............................................................................................. 4
1.3.1 General...........................................................................................4
1.3.2 NEBA and Site Remediation Experience ........................................ 4
1.3.3 Ecosystem Service Valuation.......................................................... 5
2 NEBA AND APPLICATION TO SITE REMEDIATION...................................................... 6
2.1 What is NEBA?.......................................................................................... 6
2.1.1 Why is a NEBA Analysis Necessary for Developing Appropriate
Remedial Actions for the Allen, Buck, Cliffside, and Mayo Coal Ash
Basins?........................................................................................... 8
2.1.2 Summary.......................................................................................14
2.1.3 Understanding Risks and Injury .................................................... 15
3 NEBA EVALUATION METHODS AND ANALYSIS....................................................... 17
3.1 Alternative Construction Analysis............................................................ 18
3.2 Traffic and Implementation Safety Risk Analysis ..................................... 20
3.3 Air Emissions and Energy Use Analysis .................................................. 20
3.4 Human Health Risk Analysis.................................................................... 20
3.5 Ecological Habitat Service Analysis......................................................... 21
3.6 Cost Analysis........................................................................................... 35
4 NEBA SUMMARY RESULTS................................................................................... 36
4.1 Risks Driving Remedial Alternative Selection .......................................... 36
4.2 NEBA Assessment Parameter Evaluation ............................................... 46
4.2.1 Implementation Health and Safety Risks ...................................... 50
4.2.2 Truck Trips.................................................................................... 52
4.2.3 Air Emissions................................................................................ 54
4.2.4 Energy Use................................................................................... 56
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4.2.5
Ecological Habitat Services...........................................................
58
4.2.6
Costs.............................................................................................
60
4.2.7
Each Site - Data Combined...........................................................
62
4.2.7.1 Allen Steam Station.........................................................
62
4.2.7.2 Buck Steam Station.........................................................
66
4.2.7.3 Cliffside Steam Station ....................................................
70
4.2.7.4 Mayo Steam Station........................................................
74
4.2.8
Cumulative Assessment................................................................
79
5 OPINIONS............................................................................................................. 80
6 REFERENCES....................................................................................................... 84
7 EXPERT REPORTS REVIEWED................................................................................ 89
Appendices
Appendix A Remedial Alternatives Construction Analysis
Appendix B Traffic and Implementation Risk Analysis
Appendix C Air Emissions and Energy Analysis
Appendix D Human Health Risk Analysis
Appendix E Ecological Habitat Services
Appendix F Joseph Nicolette CV
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I INTRODUCTION
I was retained on this project to conduct a net environmental benefit analysis (NEBA) of three
remedial alternatives for the Duke Energy Carolinas, LLC or Duke Energy Progress, LLC ("Duke
Energy") Allen, Buck, Cliffside, and Mayo Steam Station sites. The three alternatives evaluated
were monitored natural attenuation (MNA), cap -in-place with NINA (CIP), and comprehensive
removal with MNA (Removal). The NEBA was used to compare how the remedial alternatives
for each site differ with regard to their human and ecological chemical and physical risk profiles,
environmental footprint (e.g., environmental and community benefits and costs); ecological
habitat service value; human recreational use value; air emissions (e.g., greenhouse gases (GHG)
and criteria pollutants); and monetary costs. Background on the development of the proposed
remedial alternatives is provided in the following section, followed by a summary of my opinions,
an overview of NEBA, my qualifications, the NEBA analysis, and, based on the NEBA, my overall
opinions regarding appropriate remedial alternatives for the Allen, Buck, Cliffside, and Mayo sites.
I reserve the right to supplement my opinions should additional information become available.
1.1 Background
Coal ash stored in unlined basins associated with the Duke Energy Allen, Buck, Cliffside, and
Mayo sites has resulted in some elevated metal concentrations in groundwater and limited on-site
surface water features (e.g., seeps) at these sites. These sites are currently the subject of an
enforcement action brought by the North Carolina Department of Environmental Quality
(NCDEQ). Organizations represented by the Southern Environmental Law Center ("Intervenors")
are also parties to this litigation. The litigation seeks to establish violations of state law concerning
migration of constituents of interest from these basins to surface water and groundwater, and
impose a remedy for such violations.
After this litigation commenced, North Carolina enacted the Coal Ash Management Act (CAMA).
CAMA, within the North Carolina General Assembly Session Law 2014-122, requires the owner
of coal combustion waste surface impoundments (e.g., Duke Energy) to conduct groundwater
monitoring, assessment and remedial activities as necessary at coal ash basins across the state.
Duke Energy was required to submit a Groundwater Assessment Plan (GAP) to NCDEQ by
December 31, 2014. Comprehensive Site Assessment (CSA) documents that reported the results
of site characterization activities were required to be submitted within 180 days of approval of the
GAP. Information developed under the CSAs (HDR 2015a, 2015b, 2015c; SynTerra 2015a)
provided the data to be used to prepare Corrective Action Plans (CAPS) that were to be submitted
to NCDEQ within 90 days of submittal of the CSA. An agreement between Duke Energy and
NCDEQ resulted in breaking the CAP document into two parts: Part 1 and Part 2 (HDR 2015d,
2015e, 2015f, 2016a, 2016b, 2016c; SynTerra 2015b, 2016a). The CAP documents evaluated
three alternatives (for some criteria, only in a qualitative manner) for the remediation of on-site
groundwater according to the following criteria:
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• Effectiveness;
• Implementability/feasibility;
• Environmental sustainability;
• Cost; and
• Stakeholder input.
NCDEQ classified the impoundments as either "High", "Intermediate", or "Low risk". The CAMA
specifies that any impoundments classified by NCDEQ as "High" be closed no later than
December 31, 2019 by dewatering the waste and either a) excavating the ash and converting the
impoundment to an industrial landfill, or b) excavating and transporting the waste off-site for
disposal in an appropriately licensed landfill. "Intermediate" risk impoundments are required to be
closed similarly to "High" risk impoundments, but under a closure deadline of December 31, 2024.
Impoundments classified as "Low" by NCDEQ must be closed by December 31, 2029 either
similarly to the "High" and "Intermediate" risk sites, or by dewatering to the extent practicable
and capping the waste in place.
The Allen, Buck, Cliffside, and Mayo sites were most recently proposed (May 18, 2016) to be
classified as "Intermediate" by NCDEQ, which would require closure by dewatering the waste and
either a) excavating the ash and converting the impoundment to an industrial landfill, or b)
excavating and transporting the waste off-site for disposal in an appropriately licensed landfill. In
the May 18, 2016 proposed classifications, surface water, dam safety, and groundwater were
ranked individually'.
A summary of my opinions regarding the overall net benefit associated with the proposed remedies
to address alleged releases to groundwater and surface water is presented below.
1.2 Summary of Opinions
• The Intervenors failed to take a holistic view of all of the environmental and community
impacts and risks (environmental footprint) associated with alternative implementation
during their remedial evaluation stage. This has skewed their remedy selection and leads
them to advocate for a remedy (Removal) that is less protective of the environment and the
community.
' It should be noted that there were recent amendments to the CAMA pursuant to NC House Bill 630 (ratified July 1,
2016 and signed by the governor on July 14, 2016). Important points associated with these amendments include:
under the new 130A-309.21 l (c 1), Duke Energy must provide a permanent alternative water supply to nearby residents
with drinking water wells. Generally, this will be by providing connection to municipal water, but there is a provision
that allows for Duke Energy to provide a filtration system at the household's election in some circumstances. Duke
Energy must provide permanent alternative water supply as soon as practical but no later than October 15, 2018;
however, the Department may grant an extension of time of up to a year if needed. Also, under the new 130A -
0309.213(d), no later than 30 days after the deadline set in 130A-309.211(cl) or any extension granted thereunder,
the Department shall issue a final classification for each impoundment. If an impoundment has established permanent
water supplies as required by 130A-309.211(cl) and if it has rectified any dam safety deficiencies, it will be classified
"Low" risk.
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• The Intervenors do not consider the environmental footprint of the Removal alternatives,
nor do they consider methods to reduce the footprint of these alternatives at any of the four
sites. Metrics that may have significant social and economic impacts (e.g., GHG emissions,
extended truck traffic through local communities, pollutant emissions, energy and resource
consumption) or ecological impacts (e.g., terrestrial and aquatic habitat disturbance
associated with removal, capping, or the development of off-site disposal units) were not
considered quantitatively by the Intervenors.
• Developing a remedy should employ a NEBA evaluation to develop sustainable remedial
alternatives that manage site risks while maximizing benefits and minimizing costs to the
public.
• Human health risks associated with implementation of the Removal alternative far
outweigh the marginal, if any, human health risks given the current and projected future
state of the groundwater condition.
• The impact of metals in groundwater on groundwater ecosystem service flows provided by
each individual site is marginal, if any.
• The Removal alternative will cause more ecological injury through the destruction of
habitat than the ecological injury projected by the risk assessment.
• The Removal remedy that the Intervenors propose for the Allen, Buck, Cliffside, and Mayo
sites does not appear to provide any net benefit to off-site ecological or human use services,
over other alternatives.
o The Removal alternative will create greater harm to the environment compared to other
alternatives.
o The Removal alternative will create greater risks (and nuisance) to the local community
(via the extensive truck traffic) and to workers compared to other alternatives.
• In comparing the CIP alternative to the Removal alternative, the Removal alternative has
a much greater environmental footprint and creates significantly more environmental and
community harm. This is consistent with the Tennessee Valley Authority findings in their
review of CIP and Removal alternatives for coal ash as part of their programmatic
Environmental Impact Statement (EIS) (Tennessee Valley Authority 2016).
• The Intervenors base their arguments for Removal on risks based solely upon chemical
concentrations of the constituents of interest (COIs) in groundwater and limited surface
water seep areas. In doing so, they neglected to consider factors other than chemical
concentrations during the implementation of their preferred remedial alternative that also
have the potential to influence, either positively or negatively, human health and ecological
risks and services.
• The Intervenors' proposal for Removal is unjustified and, from a net benefit analysis,
detrimental.
• There is no need to order closure, much less closure by Removal, to remedy the alleged
violations in this case. A basic NEBA demonstrates that the Intervenors' proposed remedy
(Removal) is clearly disproportionate to the risk.
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1.3 Qualifications
1.3.1 General
The basis for my opinions presented herein include my 30+ years of experience as an
environmental consultant; my educational background; my research and professional experience
in NEBA, remedial alternatives analysis, natural resource damage assessment (NRDA), and
ecosystem service valuation; review of the CSA, CAP Part 1, and CAP Part 2, and supplemental
CSA documents for each site (HDR 2015a through HDR 2015f, HDR 2016a through 2016f,
SynTerra 2015a, b; SynTerra 2016a, b); and analyses conducted at my direction. In
addition, I conducted site visits at these four locations during the period of June 7-10, 2016. 1
hold an M.S. degree in Fisheries Management from the University of Minnesota (1983), a
B.S. degree in Environmental Resource Management from Penn State University (1980),
and am a certified fisheries scientist with the American Fisheries Society. My CV is provided
in Appendix F.
1.3.2 NEBA and Site Remediation Experience
I co-authored the first formalized NEBA framework for remediation and restoration
of contaminated sites with co-authors from the United States Environmental Protection
Agency (USEPA) and Oak Ridge National Laboratory in 2003 (Efroymson et al. 2003). The
formalized NEBA framework has been recognized by the National Oceanic and Atmospheric
Administration (NOAA), the USEPA, the USEPA Science Advisory Board (USEPA SAB)3,
and the Australian Maritime Safety Authority. I have over 24 years of experience in the
application of NEBA concepts and ecosystem service valuation approaches on over 75
projects with experience in over 16 countries. These projects have included NEBA
approaches to compare land management alternatives and remediation alternatives for
groundwater, sediment, and soils and at various sites. These projects have included work for the
USEPA, the U.S. Department of Defense, and private industry. Example projects include Crab
Orchard National Wildlife Refuge; National Aeronautics and Space Administration (NASA)
Edwards Air Force Base; NASA Marshall Space Flight Center; Army Base Realignment and
Closure sites in Washington, Alabama, California, and Illinois; Prince William Sound,
Alaska; Hudson River, New York; Troutdale, Oregon; Rocky Mountain Arsenal, CO;
Homestead AFB, Florida; Tennessee Valley Authority, Tennessee; and Calcasieu River
Estuary, Louisiana.
2 The natural resources provided by the earth's ecosystems serve as the building block upon which human well-being
flows. Ecosystems represent a complex and dynamic array of animal, plant, and microbe along non -living physical
elements interacting as a functioning unit. This gives rise to many benefits, known as ecosystem services, which are
the benefits people obtain from naturally functioning ecosystems (Nicolette et al. 2013a).
3 United States Environmental Protection Agency (USEPA) Science Advisory Board (SAB). 2009. Valuing the
Protection of Ecological Systems and Services (EPA -SAB -09-012). Washington, DC: USEPA Science Advisory
Board.
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1.3.3 Ecosystem Service Valuation
I pioneered the ecological service valuation method known as habitat equivalency analysis (HEA)
prior to its codification into NRDA regulations in the United States. I have applied these methods
to a multitude of cases across the United States as well as internationally. My experience includes
over 75 NRDA-related cases, spanning from the Exxon Valdez release up through the Deepwater
Horizon incident. I was the lead author of a book chapter (published in May of 2013 by the Oxford
Press) that provided an overview of the NRDA regulations and the development of HEA and
resource equivalency analysis (REA) approaches (Nicolette et al. 2013b). The book was entitled
The EU Liability Directive: A Commentary. I led Chapter 9 that was entitled "Experience with
Restoration of Environmental Damage." I am a Senior Principal and Ecosystem Services Practice
Director with Environmental Planning Specialists, Inc. (EPS), in Atlanta, Georgia. I have served
on the Steering and/or Planning Committee of the Community of Ecosystem Services sponsored
by the United States Geological Survey since 2008.
I bill $240 per hour through EPS for my time.
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2 NEBA AND APPLICATION TO SITE
REMEDIATION
NEBA has been identified by USEPA as an important decision-making tool in the Superfund
program (USEPA SAB 2009). In addition, the USEPA Superfund program supports the adoption
of `green site assessment and remediation', which is defined as the practice of considering all
environmental impacts of studies, selection and implementation of a given remedy, and
incorporating strategies to maximize the net environmental benefit of cleanup actions. USEPA has
committed to prioritizing and emphasizing green remediation approaches and maximizing the net
environmental benefit of Superfund cleanups (USEPA 2013).
As examples, USEPA and other federal agencies used NEBA to guide remedial decision-making,
including recent remediation work on the Kalamazoo River (USEPA 2012a). The NOAA and the
United States Coast Guard (USCG) identify the use of NEBA to evaluate opportunities for no net
loss of resources and habitats during oil spill response planning (Aurand et al. 2000; NOAA 2011),
and have used NEBA to evaluate environmental responses on the Gulf of Mexico (NOAA 2011).
The United States Army Environmental Center (USAEC) also identifies NEBA as an important
tool for assessing natural resource injury (USAEC 2005).
2.1 What is NEBA?
In a site remediation context, a NEBA is a framework for comparing site remedial alternatives that
includes the incorporation of a broad array of human, social, economic and environmental metrics
to demonstrate differences among the various remedial alternatives with regard to human and
ecological chemical and physical risk profiles; community and socioeconomic benefits and costs;
ecological habitat value; human recreational use value; GHG emissions and criteria pollutants; and
remedial costs. The formalized framework for NEBA, as recognized by the USEPA Science
Advisory Board (USEPA SAB 2009), is provided in Efroymson et al. 2003 and 2004.
A NEBA framework can be used to demonstrate the net positive or negative changes in ecosystem
service (ecological, social, and economic) values between various remedial alternatives. A NEBA
framework also is useful for assessing and comparing the sustainability of different remedial
alternatives through the quantification of impacts over time associated with the implementation
and long-term performance of each alternative (Efroymson et al. 2004; Nicolette et al. 2013a).
NEBA has been shown to be an objective approach for evaluating the risks, benefits, and tradeoffs
associated with different alternatives for remediation and environmental restoration work
(Efroymson et al. 2003, 2004; USEPA 2009a; NOAA 2011). The NEBA approach is consistent
with USEPA risk management objectives (USEPA 2009b) and provides a framework to help
USEPA comply with its policy, guidance, and direction, particularly with large scale remedial
programs where the benefits and impacts of potential alternatives are significant and need to be
evaluated closely.
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A NEBA framework incorporates quantified analyses that consider changes in various metrics that
influence ecosystem service values which, in turn, help to highlight differences between remedial
alternatives. NEBA is a systematic process for quantifying and comparing the benefits and costs
among competing alternatives; it does not rely solely on monetization but rather also includes non -
monetary environmental metrics. A NEBA framework for comparing each remedial alternative
should include, among others, the incorporation of a broad array of metrics to demonstrate
associated changes in human and ecological chemical and physical risk profiles; community and
socioeconomic issues; ecological habitat value; human recreational value effects; GHG emissions;
and remedial costs.
NEBA is similar to cost -benefit analysis (CBA), which USEPA and other federal agencies have
used for decades to support decision-making. NEBA and CBA both consider time -accumulated
service flows (i.e., benefits and costs over time); since these benefits and costs occur over varying
time frames, they can be normalized to their net present value using a discount rate. The NEBA
approach, however, moves beyond the traditional CBA approach by demonstrating environmental
stewardship and sustainability through the quantification of environmental metrics. A NEBA
typically involves the comparison of several management alternatives that may include: (1) leaving
the site condition "as is"; (2) physically, chemically or biologically treating the site condition; (3)
improving ecological value through restoration alternatives that do not directly focus on removal
of site materials; or (4) a combination of those alternatives (Efroymson et al. 2004). Understanding
these benefits, and how they may change among remedial actions, maximizes benefits to the
environment and the public while managing costs and site risks.
As stated in Efroymson et al., 2004, "This framework for NEBA should be useful when the balance
of risks and benefits from remediation of a site is ambiguous. This ambiguity arises when the
contaminated site retains significant ecological value, when the remedial actions are themselves
environmentally damaging, when the ecological risks from the contaminants are relatively small,
uncertain, or limited to a component of the ecosystem, and when remediation or restoration might
fail." As set forth more fully below, these are precisely the circumstances present with the Duke
Energy sites that I have analyzed.
NEBA typically considers a broader range of environmental effects than the traditional human
health and ecological risk assessment processes that drive remedial action decisions. Typically,
these processes consider only the remedial alternatives' ability to limit exposure and human risks
from a chemical condition. The effects on other ecosystem services (e.g., human use and
ecological benefits) associated with implementation of a remedial alternative are typically not
considered in the traditional remedy selection process. A NEBA shows formally the positive and
negative effects on ecosystem services4 and/or surrogate metrics associated with a remedial action
in relation to the incremental changes in risk. By considering the effects of a given remedial
alternative on all services provided by the site, the net effects on all service flows are considered,
including any potential loss of services. In some cases, for example, a remedial alternative may
destroy or significantly degrade the ecological landscape and achieve little or no reduction in
4 A NEBA can also be referred to as a net ecosystem service analysis (MESA) (Nicolette et al. 2013b).
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ecological or human health risk. In simpler terms, NEBA can be used to determine, for each
remedial alternative, whether "the cure is worse than the disease."
2.1.1 Why is a NEBA Analysis Necessary for Developing Appropriate Remedial
Actions for the Allen, Buck, Cliffside, and Mayo Coal Ash Basins?
1. The effects of the Removal or CIP remedial alternatives on ecosystem services have not
been fully quantified. As such, this can lead to remedial alternatives that can either:
— cause more ecological injury through the destruction of habitat than the ecological
injury projected by the risk assessment (e.g., "the cure is worse than the disease"), or;
— provide a marginal benefit or no net increase in ecosystem service value for the effort
expended; this is especially true when ecological risks from the contaminants are
relatively small, uncertain, or limited to a component of the ecosystem.
It is important to understand that within the regulatory cleanup framework (e.g., as applied
in North Carolina), the selection of remedial alternatives to address the site condition is
typically based upon the potential for the chemical to pose a human health and/or
ecological risk (or in some circumstances, the remedial action is considered necessary
simply to address impaired groundwater regardless of risk) and the cost of the alternative.
Within this framework, the net effect that a remedial action may have on the ecosystem,
positive or negative, is rarely formally quantified when considering among remedial
alternatives. It is my understanding, however, that a court exercising its equity jurisdiction
to fashion a remedy for a violation of environmental regulations has the ability to consider
the broader implications of its actions. The NEBA fits squarely within the type of analysis
that I understand a court would employ in considering injunctive relief.
2. NEBA Will Improve the Validity of the Remedial Evaluation Decision -Making Process to
Stakeholders
Intervenors have not fully considered the environmental impacts, health risks and socio-
economic consequences of both the short-term and the long-term impacts of the remedial
alternatives. Each certain or possible impact should have been included in a formal analysis
using a NEBA framework.
A NEBA is needed to provide a scientifically -sound basis for remedial decision-making.
Specifically, and per USEPA guidance, the NEBA provides transparency and consistency
in the evaluation and decision-making process so that stakeholders and the public are aware
of the full extent of potential social, health, and environmental impacts of the proposed
remedy.
The Intervenors provide insufficient information to demonstrate that they adequately and
transparently considered important factors with environmental, social and economic
implications consistent with policy, guidance and direction. Specifically, they did not
demonstrate (1) a preference for green remediation or a sustainable solution; (2) the
environmental footprints of the various remedial alternatives; (3) the environmental and
social risks associated with the various remedial alternatives; and (4) the consideration of
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net environmental, economic and social benefits. The court should not, therefore, adopt
the Intervenors' proposed remedy.
3. NEBA Support in Decision -Making Mandated by USEPA
NEBA has been conducted by several federal agencies, including USEPA, because it
provides an approach for balancing the risks, benefits and tradeoffs associated with
competing remedial alternatives in a transparent manner by which all stakeholders can
understand the basis for a decision. The merits of using a NEBA framework (based on
formally quantified metrics) for transparent decision-making associated with site
remediation, compensatory restoration and ecosystem service tradeoffs have been
discussed by various authors (Efroymson et al. 2003, 2004; Colombo et al. 2012; Nicolette
et al. 2013a).
The need for transparency in decision-making is made apparent in the 1995 USEPA Risk
Characterization Program memorandum by Carol Browner, former USEPA Administrator
(USEPA 1995). In the Browner memorandum, the core values that the USEPA is striving
to achieve are transparency, clarity, consistency and reasonableness. These same core
values have been repeated often in USEPA guidance from the 1990s to the present.
Excerpts from the Memorandum Written by Former USEPA Administrator,
Carol Browner (USEPA 1995)
"First, we must adopt as values transparency in our decision-making process and
clarity in communication with each other and the public regarding environmental risk
and the uncertainties associated with our assessments of environmental risk. "
"Second, because transparency in decision-making and clarity in communication will
likely lead to more outside questioning of our assumptions and science policies, we
must be more vigilant about ensuring that our core assumptions and science policies
are consistent and comparable across programs, well grounded in science, and that
they fall within a `zone of reasonableness, " While I believe that the American public
expects us to err on the side of protection in the face of scientific uncertainty, I do not
want our assessments to be unrealistically conservative. We cannot lead the fight for
environmental protection into the next century unless we use common sense in all we
do. "
As an example, NEBA was used by the USEPA at the Woodlands Superfund site located
in New Jersey where it was applied to assess the ecological impacts of the preferred
remedial groundwater action. The NEBA demonstrated that the preferred remedy (pump
and treat) would cause injury to the ecosystem, while a lower cost alternative (air
sparge/vapor extraction) would not cause injury and would save $87 million in remedial
costs. The Record of Decision was subsequently changed to the air sparge/vapor extraction
alternative supported by the NEBA. In this case, the downgradient portion of the
groundwater plumes at both sites was allowed to naturally attenuate. The USEPA deemed
the application of NEBA as successful in an agency -published report describing the
remedial decision at the Woodlands Superf ind site (Exhibit 1, USEPA 2001).
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Exhibit 1. Example USEPA groundwater Record of Decision change based on a NEBA.
Region
1640
12J93
:..
Cnound water
state supported the
Fed= 13Oe hours
change The Site is
ry
Con. = JO
Woodland%, NJ
located in a [Alfa] area
1 "(ROD -A)
1+'1199
and the local populmon
Est'd Sa}ings =
Route ?_'
suppons tau remcdsy
S 81.6 M
Rause i32
change.
Type of Change: From - ground nater pump and treat: To - air spargingisod vapor extraction and natural attenuation -
Factual Basis-. STAG memo indicated that the ground water pump and treat system would dewater the nearby wellands. In
addltwn. durmg remedial &-sign. the PRP successfully identified altrruances that would. meet ROD objectives ai much lower
cost
4. A systematic, transparent, and scientifically -based approach for a fully informed remedial
decision-making process is needed.
A NEBA is a comparative analysis that incorporates ecosystem service values and provides
stakeholders a basis to balance the risks, benefits and trade-offs associated with competing
management alternatives. Incorporation of ecosystem service valuation concepts with
formally quantified values within an alternatives decision-making process provides
decision makers with an opportunity to make informed choices about the net benefits of
actions that affect the environment. By "informed," I mean an approach that is:
— systematic,
— transparent and understandable to stakeholders,
— non -arbitrary,
— scientifically -based and defendable,
— quantitative in nature where possible,
— based on internationally recognized concepts and approaches, and
— considerate of all stakeholder concerns thus providing a holistic perspective to the
decision-making process.
NEBA incorporates the use of ecosystem service valuation concepts and methods that have
been litigation -tested and upheld in federal court (United States 1997, 2001) to evaluate
changes in habitat value over time. In addition, a variety of human use economics -based
models can be incorporated into a NEBA to evaluate changes in human use value
(recreational, commercial, aesthetic, educational, scientific, etc.) over time. A NEBA can
also incorporate implementation risks, chemical contamination risks, and a variety of proxy
metrics (e.g. GHGs) to help in differentiating between alternatives.
S. It is the public policy of the State of North Carolina to carefully consider the environmental
impacts associated with each remedial alternative as part of the decision-making process
for selection of a preferred remedy. This is consistent with the direction and policy of the
State of North Carolina Environmental Policy Act (SEPA) and Federal USEPA policy,
guidance, and direction for remedial decision-making.
Determining the appropriate remedy for this case requires a consistent, detailed and
transparent assessment of the environmental, social and economic impacts associated with
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remedial alternatives specified for each site. The following examples from the USEPA and
the State of North Carolina illustrate the importance of providing consistent, adequate,
clear, and transparent information.
Example 1. Risk managers must assess and balance risks between site contaminants and
proposed remedies (USEPA 1997).
EPA Superfund Ecological Risk Assessment (ERA) Guidance (Step 8) specifically
states that:
"The risk manager must balance (1) residual risks posed by site contaminants before
and after implementation of the selected remedy with (2) the potential impacts of the
selected remedy on the environment independent of contaminant effects. "
"In instances where substantial ecological impact will result from the remedy (e.g.,
dredging a wetland), the risk manager will need to consider ways to mitigate the impact
of the remedy and compare mitigated impacts to the threats posed by the site
contamination. "
Example 2. This balance should be incorporated into the decision-making process for
contaminated sites (USEPA 2005).
"Project managers are encouraged to use the concept of comparing net risk reduction
between alternatives as part of their decision-making process for contaminated
sediment sites, within the overall framework of the NCP remedy selection criteria.
Consideration should be given not only to risk reduction associated with reduced
human and ecological exposure to contaminants, but also to risks introduced by
implementing the alternatives [..] Evaluation of both implementation risk and residual
risk are existing important parts of the NCP remedy selection process. By evaluating
these two concepts in tandem, additional information may be gained to help in the
remedy selection process. "
Example 3. Feasibility Studies should include a comparison of environmental footprints
(USEPA 2008).
"Green remediation focuses on maximizing the net environmental benefit of cleanup,
while preserving remedy effectiveness as part of the Agency's primary mission to
protect human health and the environment [..J Key opportunities for integrating core
elements of green remediation can be found when designing and implementing cleanup
measures. Regulatory criteria and standards serve as a foundation for building green
practices. Key elements include reducing atmospheric release of toxic or priority
pollutants, and reducing emissions of greenhouse gases that contribute to climate
change."
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"In accordance with green remediation strategies, feasibility studies could include
comparison of the environmental footprint expected from each cleanup alternative,
including GHG emissions, carbon sequestration capability, and water drawdown
(lowering of the water table or surface water levels). "
Example 4: Green remediation technologies should be considered for response actions
(USEPA 2011 a, 2011 b).
The USEPA Superfund program supports the adoption of "green site assessment and
remediation", which is defined as the practice of considering all environmental impacts
of studies, selection and implementation of a given remedy, and incorporating
strategies to maximize the net environmental benefit of cleanup actions. USEPA has
established a "Clean & Green" policy to enhance the environmental benefits of
Superfund cleanups by promoting technologies and practices that are sustainable. The
policy applies to all Superfund cleanups. Under this policy, certain green remediation
technologies will serve as touchstones for response actions.
Example 5: USEPA has identified a framework to quantify various metrics to help
understand and reduce a project's environmental footprint (USEPA 2012b).
"Green remediation strategies can include a detailed analysis in which components of
a remedy are closely examined and large contributions to the footprint are identified.
More effective steps can then be taken to reduce the footprint while meeting regulatory
requirements driving the cleanup [...J. The term "environmental footprint" as
referenced in the methodology comprehensively includes metrics such as energy use
and water use as well as air emissions to fully represent the effects a cleanup project
may have on the environment. "
"The methodology is a general framework to help site teams understand the remedy
components with the greatest influence on the project's environmental footprint.
Quantifying the metrics can serve as an initial step in reducing the remedy footprint.
The overall process allows those involved in the remedial process to analyze a remedy
from another perspective and potentially yields viable and effective improvements that
may not have been identified otherwise. "
Example 6: The State of North Carolina has declared, in its State Environmental Policy
Act (SEPA) (§ 113A-3), that it shall be the continuing policy of the State of North
Carolina to conserve and protect its natural resources (North Carolina 1971).
The State of North Carolina has declared, in its SEPA (§ 113A-3), "that it shall be the
continuing policy of the State of North Carolina to conserve and protect its natural
resources and to create and maintain conditions under which man and nature can exist
in productive harmony. Further, it shall be the policy of the State to seek, for all of its
citizens, safe, healthful, productive and aesthetically pleasing surroundings; to attain
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the widest range of beneficial uses of the environment without degradation, risk to
health or safety; and to preserve the important historic and cultural elements of our
common inheritance. (1971, c. 1203, s. 3.)"
Consistent with this declaration and USEPA direction, the State of North Carolina
Waste Management Division integrates its programs with federal cleanup programs.
The question arises, have the proposed remedial solutions been properly vetted as to
their protection of natural resources and are they providing the widest range of
beneficial uses of the environment without degradation? For the reasons set forth in
this document, the Intervenors' proposal for a remedy (Removal) fails this test.
Example 7. Guidelines for establishing remediation goals at Resource Conservation and
Recovery Act (RCRA) Hazardous Waste Sites (NCDEQ 2013)
The Hazardous Waste Sites (HWS) goal is that RCRA facilities remediate all releases
of hazardous waste or hazardous constituents to unrestricted use levels. For
groundwater, the unrestricted use level is the North Carolina Division of Water Quality,
15A NCAC 2L groundwater standard (2L) or site-specific background concentration.
For soil, the unrestricted use level is either the site-specific background concentration
or the lowest of a soil screening level protective of groundwater and the health -based
residential Preliminary Soil Remediation Goal (PSRG). Unrestricted use levels are the
starting points for the HWS preliminary screening process. The HWS does recognize
that, in some cases, it may be infeasible to remediate to unrestricted use levels.
Although USEPA has classified coal ash and coal combustion residuals as non-
hazardous, these guidelines represent an important reference tool for the present
situation. If the HWS guidelines recognize a NEBA approach to remediation of
hazardous waste, then NEBA should also apply to non -hazardous wastes as well.
Example 8. Planning and Promoting Ecological Land Reuse of Remediated Sites (ITRC
2006, State of North Carolina is a Member)
"The Interstate Technology and Regulatory Council (ITRC) Ecological Land Reuse
Team has developed this guidance document to promote ecological land reuse as an
integrated part of site remediation strategies and as an alternative to conventional
property development or redevelopment. This reuse may be achieved through a design
that considers natural or green technologies or through more traditional cleanup
remedies. The decision process presented here helps stakeholders to integrate future
land use and stakeholder input into an ecological land end -use -based remediation
project. "
"Ecological benefits have not traditionally been designed into, nor credited to, the
value of the reusable land until successful remediation was completed. Now, natural
and green technologies can improve the ecology of the site as long as they support the
intent of the land's use and do not jeopardize the elimination or reduction of the human
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or environmental risk. Consideration of ecological benefits, as well as the end use of
an environmentally impacted site, is an integral component of the remediation
process.
This guidance raises the question, has the ecology and end land use been properly
considered in the development of the remedy? It is clear that the Intervenors have not
considered these values in advocating their proposed remedy.
Example 9: In a recent Memorandum (August 2, 2016), the USEPA recommends
approaches for Superfund programs to consider conducting a best practices or footprint
analysis and using greener cleanup activities through the CERCLA cleanup process
(USEPA 2016).
As stated in this reference, OSWER's "... goal is to evaluate cleanup actions
comprehensively to ensure protection of human health and the environment and to
reduce the environmental footprint of cleanup activities, to the maximum extent
possible. In considering these Principles, OSWER cleanup programs will assure that
the cleanups and subsequent environmental footprint reduction occur in a manner that
is consistent with statutes and regulations governing EPA cleanup programs and
without compromising cleanup objectives, community interests, the reasonableness of
cleanup time frames, or the protectiveness of the cleanup actions. "
In addition, the memorandum outlines five key factors that regional staff should
generally consider when implementing greener cleanups (i.e., minimize total energy
use and maximize use of renewable energy; minimize air pollutants and greenhouse
gas emissions; minimize water use and impacts to water resources; reduce, reuse, and
recycle materials and waste; and protect land and ecosystems).
2.1.2 Summary
A NEBA should be conducted by the Court to determine the remedy for this case, since remedial
decision-making policy and guidance obligates the regulatory authorities to evaluate the
environmental and community impacts associated with potential remedial actions and dictates that
the remedies should be sustainable and demonstrate a net environmental benefit to the public.
USEPA has made "greener" cleanups part of its cleanup program mission, which the USEPA has
stated strives to reduce adverse impacts on the environment, use natural resources and energy
efficiently, minimize or eliminate pollution at its source, use renewable energy and recycled
materials whenever possible, and reduce waste to the greatest extent possible. According to
USEPA, the practice of "green remediation" involves strategies that consider all environmental
effects associated with remedy implementation at contaminated sites, and the selection of
alternatives that maximize the net environmental benefit of cleanup actions (USEPA 2008).
The use of a NEBA evaluation ensures that on a site-specific basis, decision -makers consider, at
the remedy selection stage, not only the benefits of a remedial approach, but also the residual risks
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associated with the approach and the risks associated with implementing the remedial approach.
This differs from the traditional approach of either considering implementation risks at the remedy
implementation stage or assuming that remedial approaches will be 100% effective on
implementation, thereby bypassing any consideration of residual risk. NEBA is consistent with
the National Oil and Hazardous Substances Pollution Contingency Plan's (NCP) 9 -point criteria
(40 CFR §300.430(e)(9)(iii)), which require evaluation and balancing of short-term and long-term
risks and benefits, including residual risk. Failure to take a holistic view of all of the
environmental and community impacts and risks associated with alternative implementation
during the remedial evaluation stage can skew remedy selection and result in a remedy that
is less protective of the environment and the community.
The NEBA was conducted to examine key parameters associated with remedial alternatives
proposed at the Allen, Buck, Cliffside, and Mayo sites. This analysis follows; however, prior to
discussing the NEBA analysis, I provide a brief discussion on the difference between "perceived"
risk, "real" risk, and injury. These distinctions are important when determining appropriate
remedial actions.
2.1.3 Understanding Risks and Injury
It is important to understand the distinction between risk and injury and the ramifications that this
distinction has on remedial alternative selection. In the 1998 USEPA Guidelines for Ecological
Risk Assessment (EPA/630/R-95/002F) (an expansion and replacement for the 1992 ecological
risk assessment guidelines), risk assessment is defined as "...a process that evaluates the likelihood
that adverse ecological effects may occur or are occurring as a result of exposure to one or more
stressors" (USEPA 1998). "Risks" result from the existence of a hazard and uncertainty about its
expression. Uncertainty is defined as "Imperfect knowledge concerning the present or future state
of the system under consideration; a component of risk resulting from imperfect knowledge of the
degree of hazard or of its spatial and temporal pattern of expression" (Suter 1993). Since a "risk"
evaluation typically looks at the "likelihood" of an adverse effect, it thus includes an implied level
of uncertainty in an effect. Thus, simply put, a "risk" represents the "potential" that adverse effects
may occur (with some level of uncertainty), not a definitive measure of observable effects.
In many cases, uncertainty in risk assessment is handled through the use of layers of conservative
assumptions (e.g., use of maximum concentrations, extended exposure periods, unrealistic
exposure assumptions) that cumulatively may predict a risk when, in fact, no injury is occurring
(a "perceived" risk). As such, there may be no adverse effects, and no "real" risks in an area where
contaminant concentrations are above a criterion and remediation is being required. A key function
in the strategic site assessment is to be able to understand and differentiate between what would
be considered a "perceived" risk versus a "real" risk.
The meaning of observable effect to a natural resource is very different than a "risk" to a natural
resource. This distinction is important when it comes to understanding those effects that have been
documented (quantified/measured) through actual field studies, versus those effects that "may
have" or "potentially have" occurred, or those effects that "may" or "potentially" be occurring now
and/or into the future. The differentiation between risk and observable effects (i.e., injury) has
been made prominent based upon the NRDA regulations in CERCLA (43 CFR 11), where the
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public is to be compensated for natural resource injury that has occurred as a result of a release.
Under NKDA, the lost natural resource services (injury) are quantified so that an appropriately
scaled restoration program can be developed ("service -to -service" equivalency approach). In this
approach, injury must be measured (with some level of certainty) and used to develop the scale of
the restoration program. Thus, there is some certainty that there is indeed injury and therefore, that
restoration or remediation is required and adequate.
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3 NEBA EVALUATION METHODS AND
ANALYSIS
The basic NEBA evaluation presented herein for the Allen, Buck, Cliffside, and Mayo coal ash
basins compared the NINA, CIP, and Removal alternatives as to how they would affect, positively
or negatively, ecosystem service values (human use and ecological) and associated metrics for
each site; and therefore provide an improved understanding of the environmental footprint and
community risks associated with the alternatives. In order to conduct the NEBA analysis, several
key factors were identified and considered to help establish an understanding of the environmental
footprint that would be associated with the various alternatives. These included:
1. chemical risks associated with contaminant exposures (ecological and human);
2. health and safety and implementation risks (mortality, injuries, illness);
3. physical impacts on the habitats and related ecological services associated with the actions;
4. GHG's and other criteria air pollutants;
5. energy use;
6. community impacts (e.g., increased traffic, accidents);
7. human use value (groundwater, recreation, hunting, etc.); and
8. costs.
These factors resulted in specific parameters that were considered to help assess predicted changes
over time, given implementation of the remedial alternatives. For the analysis, I considered the
following parameters:
• human health - public off-site contaminant exposure (wader, boater, swimmer);
• human health - on-site contaminant exposure (commercial industrial worker, construction
worker, trespasser);
• human health - fish consumption (recreational, subsistence fishermen);
• human health - drinking water (i.e., from groundwater consumption);
• implementation risks - truck traffic related accidents/mortality;
• implementation risks - on-site worker safety;
• community nuisance — truck trips (e.g., relates to noise, dust, aesthetics);
• energy use — cumulative energy requirements;
• GHGs;
• pollutant emissions (e.g., NOX, particulate matter) - truck traffic, on-site construction
(yellow iron);
• ecological habitat services (terrestrial, aquatic, avian);
• groundwater services;
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• human recreational uses; and
• capital costs including long-term operations and maintenance (O&M).
Although the above parameters were considered in the analysis, not all were able to be quantified
given the lack of available information. Therefore, the NEBA presented herein is not fully
comprehensive in the scope of the supporting quantitative evaluations — the most pertinent and
impactful elements are quantified. Other elements, if considered, would push the NEBA further in
the disparity amongst the remedial alternatives considered. Those parameters not quantified were
considered from a qualitative standpoint in support of evaluating the environmental footprint and
community risks associated with the remedial alternatives. The analysis is sufficiently robust,
however, to require rejection of the Intervenors' proposed remedy.
3.1 Alternative Construction Analysis
As part of the evaluation, it was necessary to evaluate the construction activities, equipment
necessary, etc. that would be associated with the proposed remedial alternatives in order to
understand those factors that would affect the environmental footprint and associated risks
associated with the proposed remedial alternatives.
A construction and cost analysis for the MNA, CIP and Removal alternatives was conducted for
the Allen, Buck, Cliffside, and Mayo Steam Stations. The three remedial alternatives evaluated
were based on the remedial assessment completed by HDR Engineering, Inc. and SynTerra
Corporation as detailed in the Corrective Action Plan, Part 2 for each respective steam station
(HDR 2016a, 2016b, 2016c; SynTerra 2016a). The quantity of ash and land coverage of the
existing ash basins for each steam station were provided by Duke Energy.
The construction analysis was subdivided into three categories: land disturbance, project duration,
and cost. The detailed analysis of construction implementation details for the three alternatives,
for each of the four sites considered, is provided in Appendix A. This analysis developed the
following information in support of the various components of the quantitative evaluation:
• Types of equipment used and duration [air emissions, energy];
• Land disturbance footprint (ecological habitat alteration);
• Road miles traveled [air emissions; truck trips, safety risks];
• Dimensions of work zones [safety risks]; and
• Costs.
As shown in Figure 1, the CIP alternative is estimated to require 5.2, 2.9, 3.0, and 2.5 years at the
Allen, Buck, Cliffside, and Mayo sites, respectively. In comparison, the Removal alternative is
estimated to require 35.7, 9.8, 14.6, and 12.2 years to implement (for ash excavation and transport
only) at the Allen, Buck, Cliffside, and Mayo sites, respectively. The affected acreage for each
alternative at each site, both direct on-site and off-site impacts, is presented in Figure 2 and detailed
in Appendix A.
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Figure 1. Projected duration (years) of the CIP and Removal alternatives
353
i
T
C
O
+
14.6
i
12.2
�
9.8
5.2
■
■
0
Allen Buck Cliffside
Mayo
L. CIP ■ Removal
*Removal duration includes ash basin excavation and transport to landfill only.
*CIP construction assumes that the capping rate is subjectto import rate of cover material
and does not include preconstruction activities including basin dewatering.
Figure 2. Projected acreage affected by the CIP and Removal alternatives for
the duration of each alternative
700
6
319
00
N
v sao 190
V
M
v 400
Q
L
C 168
R
-0 300 322322
Q) 110 129-0 115 149
3 94
_N 200
180 180 189 189
153 153
ioo
0
CIP Removal CIP Removal CIP Removal CIP Removal
Allen Buck Cliffside Mayo
sm On-site Off-site
The parameter quantification was conducted within the following analyses: implementation safety
risk (fatalities, injury, illness, property damage), air emissions (truck trips, GHG emissions - CO2e,
criteria pollutant emissions, energy use), human and ecological health, ecological habitat
alterations, and cost. Each of these analyses are discussed, in turn, in the following sections.
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3.2 Traffic and Implementation Safety Risk Analysis
Multiple accidents associated with coal ash removal and management construction activities
have been documented over the past 10 years and include fatalities and property damage.
Selected examples of these include incidents in South Carolina, Tennessee, West Virginia,
Ohio, Pennsylvania, Wisconsin, and Illinois (see "Selected Examples of Truck Traffic and
Construction Implementation Related Accidents over the past 10 years" section of the
Reference Section of this report). The risk of life to workers and public due to construction
activities for each alternative was quantified. National statistics were used to evaluate the fatality
and non -fatality (injury/illness) risks, as well as property damage incidents associated with
truck traffic and onsite implementation for the four sites considered. The quantitative
evaluation of implementation safety risks is provided in Appendix B with the summary results
presented in Section 4.2.1.
3.3 Air Emissions and Energy Use Analysis
Air emissions can be divided into two separate categories, criteria pollutants and GHGs.
The criteria pollutants, which were established in the Clean Air Act of 1970, consist of
carbon monoxide (CO), nitrogen oxides (NOX), ozone, sulfur oxides (SOX), particulate matter
(PM), and lead. These pollutants cause adverse health and environmental effects when present
above specific concentrations in the atmosphere. For the purposes of this evaluation, NO, and
PM were evaluated based on their expected emissions from the activities involved in the
remedial activities. Based on previous experience with air emissions from remedial activities,
the impacts from the other criteria pollutants were expected to be minimal and so were not
included in this evaluation. Criteria pollutants are also referred to as criteria pollutants.
Greenhouse gases, which consist primarily of carbon dioxide (CO2), methane (CH4), nitrous
oxide (N2O), and fluorinated gases, were also determined by USEPA to have adverse health
and environmental effects due to their contribution to climate change. The quantitative
evaluation of each of these types of air emissions, as well as truck trips and energy use, for
the three remedial alternatives, specific to each of the sites considered is provided in
Appendix C. The results are presented in Sections 4.2.2, 4.2.3, and 4.2.4.
3.4 Human Health Risk Analysis
Potential impacts to humans in contact with chemicals in environmental media were estimated
for 30 years after implementation of the three remedial alternatives. A current condition (i.e.,
year 2015-2016) risk assessment was conducted for each site as part of each CAP Part 2
document. These risk assessments formed the basis of estimating the risks in the future for the
three different remedial alternatives. It is important to note that the purpose of this risk analysis
is to compare the three different remedial alternatives; the analysis does not necessarily
represent the true risk remaining after implementation of a particular remedial action
alternative given the numerous assumptions and data extrapolations that were necessary in
order to conduct this "forward projection" analysis.
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The receptors evaluated included a commercial/industrial worker, construction worker, trespasser,
boater, swimmer, and waders. There were two considerations in extrapolating the current risk
assessment to the future condition: the first was to forward project into the future (30 years from
implementation/completion of the remedial action); the second was to project (estimate) the
changes to various environmental media due to a given remedial action. The detailed evaluation
of human health risks projected under each remedial action alternative, for each of the sites
considered, is provided in Appendix D. The results are presented in Section 4.1.
3.5 Ecological Habitat Service Analysis
The purpose of this evaluation was to understand how implementation of the Removal and CIP
alternatives might affect ecological habitat service values associated with the Allen, Buck,
Cliffside, and Mayo Steam Station sites6. The analysis for each site consisted of three main steps
as follows:
1. The first step was to identify the general habitat types existing within the areas that would
be impacted by the remedial alternatives at each site and to estimate the surface area of
each habitat type. This step combined habitat type boundaries presented in the CAP
(available as GIS "shape" boundary layers), aerial photography reviews, site visit
observations, and an updated GIS analysis. The basins that would be impacted, along with
selected site specific photographs, are presented for the Allen (Figures 3-7), Buck (Figures
8-12), Cliffside (Figures 13-17), and Mayo (Figures 18-22) sites, respectively.
2. The second step was to develop assumptions regarding the timing and level of impact (i.e.,
projected change in ecological service value over time) that implementation of each
alternative would have on the major habitat types evaluated. The general assumptions as
to the timing and level of impact projected for each alternative at each site were based upon
the construction analysis information provided in Appendix A and professional experience
with remedial activity implementation.
3. The third step was to estimate the change (i.e., loss) in the net present value (NPV) of
ecological habitat services that would be projected to occur given the habitats, acreages,
and assumptions developed as part of Steps 1 and 2. An estimate of the NPV of the losses
in ecological habitat value were developed through the use of the HEA methodology. In
this case, projected habitat alterations (e.g., removal, displacement of habitat) were used to
directly assess changes in ecological habitat quality and resulting value. My evaluation
included both the major direct on-site and off-site habitat impacts. Indirect impacts
associated with alternative implementation were not estimated, as such, my estimation of
impacts are conservative (i.e., underestimate projected losses).
s There were insufficient data to evaluate subsistence and recreational fishermen.
6 It should be noted that ecological risks, as currently understood, were used to inform the overall assessment as to
how implementation of the CIP and Removal alternatives might affect the current risks. This is discussed further in
Section 4.1.
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The detailed quantitative evaluation of the loss of ecological habitat service value projected under
the CIP and Removal alternatives, for each of the four sites, is provided in Appendix E. The results
are presented in Section 4.2.5.
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Figure 3
EPS Site Reconnaissance
June 2016
Allen Steam Station
Belmont, NC
Figure Narrative
Shows vantage point locations
for photographs taken during
EPS site reconnaissance on
June 7, 2016.
Notes
Legend
Primary Ash Basins
Name
Active Basin
QInactive Basin
Ash Storage Units
Basin Name
Ash Storage
Retired Ash Basin Ash
— Structural Fill 1
— Structural Fill 2
Site Visit Photo Locations
Blue arrows indicate the general
direction that the photograph was
taken
N
A
0 500 1,000
Feet

EPS
Figure 4. Wooded forest habitat growing on top of old ash basin at Allen Steam Station
(Photo 1 location on Figure 3)
i".p
Figure 5. Vegetation growth, surface water, and wetland habitat in the active basin at Allen
Steam Station (Photo 2 location on Figure 3)
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EPS
Figure 6. Permitted outfall to the Catawba River (Lake Wylie) at Allen Steam Station
(Photo 3 location on Figure 3)
Figure 7. Early growth vegetation in the active basin at the Allen Steam Station (Photo 4
location on Figure 3)
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Figure 8
�--�
EPS Site Reconnaissance
June 2016
. ,� ..
Buck Steam Station
Salisbury, NC
�-iii+! t y "t i•� ;-,�� '
J< _
s>
3
Figure Narrative
Shows vantage point locations
for photographs taken during
EPS site reconnaissance on
June 8, 2016.
Notes: Game lands are present
around the site. These lands
provide hunting, trapping and
inland fishing opportunities for
the public. Note the Heron
Rookery and Eagle Nesting Site.
Heron Rookery Site q
s
Legend
e
2
Basins
11e dA
Cell 1 (Active)
•.
Q Cell 2 (Old Primary Cell)
,
Eagle Nesting Site
Cell 3 (Secondary Primary)
Ash Fill Area (storage)
Game Land
y `
Site Visit Photo Locations
a
�b`'
x
Blue arrows indicate the general
:•. I
direction that the photograph was
taken
� �"t � �?� �; M _ ; ' • fir:
SAN\
Dige, iEMT bed, E t star Geogr phics,
- CNES/Airbus D-, SDA, AEy a tipping, Aerogrid, IGN, IG
0 500 1,000
- swisst• po,
and the GdS User Community
Feet
Environmental Planning Specialists, Inc.
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EPS
Figure 9. Wetland habitat and vegetation in active Cell l at Buck Steam Station (Photo l
location on Figure 8)
RIM
aAll
x
It
Figure 10. Wetland, surface water, and forest habitat over the Old Primary Ash Basin (Cell
2) at Buck Steam Station (Photo 2 location on Figure 8)
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EPS
Figure 11. Wooded forest growth over the in the Old Primary Ash Basin (Cell 2) at Buck
Steam Station (Photo 3 location on Figure 8)
Figure 12. Heron Rookery located adjacent to the surface water at the Old Primary Ash
Basin (Cell 2) at Buck Steam Station with active nests (Photo 4 location on Figure 8)
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Figure 13
EPS Site Reconnaissance
June 2016
Cliffside Steam Station
Cliffside, NC
Figure Narrative
Shows vantage point locations
for photographs taken during
EPS site reconnaissance on
June 6, 2016.
Notes: Figure 14 was taken near
the location that Figure 12 was
taken.
Legend
Basins
Active Ash Basin
Unit 5 Inactive Basin
Units 1-4 Inactive Basin
t 7 Ash Storage Area 1
* Site Visit Photo Locations
Blue arrows indicate the general
direction that the photograph was
taken
N
A
500 1,000
Feet

EPS
Figure 14. The Broad River at Cliffside Steam Station (Near Photo 1 location on Figure 13)
Figure 15. Vegetation growing on the active ash basin (hill in background) at Cliffside
Steam Station (Photo 2 location on Figure 13)
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Figure 16. Vegetation growth and wetlands/surface water habitat in the active ash basin at
Cliffside Steam Station (Photo 3 location on Figure 13)
Figure 17. The Broad River near the permitted outfall at the Cliffside Steam Station.
(Photo 1 location on Figure 13)
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Figure 18
EPS Site Reconnaissance
June 2016
Mayo Steam Station
Roxboro, NC
Figure Narrative
Shows vantage point locations
for photographs taken during
EPS site reconnaissance on
June 9, 2016.
Notes: Note extensive
gamelands adjacent to the ash
ponds.
Legend
Active Ash Basin
Active Basin
Game Land
Streams
Site Visit Photo Locations
Blue arrows indicate the general
direction that the photograph was
taken
N
A
500 1,000
Feet

EPS
Figure 19. Clam shells and healthy aquatic vegetation in the outlet of the active basin at
Mayo Steam Station (Photo 1 location on Figure 18)
Figure 20. Waterfowl on the surface water of the active basin at Mayo Steam Station
(Photo 2 location on Figure 18)
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EPS
Figure 21. Wetland habitat in the active basin at Mayo Steam Station (Photo 3 location on
Figure 18)
Figure 22. Crutchfield Branch (Photo 4 location on Figure 18)
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3.6 Cost Analysis
The quantitative evaluation of remedial alternative cost estimates for the three remedial
alternatives, for each of the four sites considered, are provided in Appendix A and presented in
Section 4.2.6.
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4 NEBA SUMMARY RESULTS
The analyses developed as presented in Appendices A-E provide quantification of a variety of
metrics that can be used to ascertain the relative environmental footprint that one remedial
alternative may have in comparison to another. In addition, we can evaluate how risks change
through the implementation of the alternatives. In evaluating the information developed to date, I
have developed several opinions as to the risks and benefits that would be associated with
implementation of the alternatives. Prior to presenting my opinions, I provide summaries of the
information that support my opinions.
4.1 Risks Driving Remedial Alternative Selection
Developing an appropriate remedy is based on a solution that manages site risks while maximizing
benefits to the public and minimizing cost. For the Allen, Buck, Cliffside, and Mayo sites, risks
that the final remedy should look to manage include potential human health and ecological risks.
The remedy should effect a meaningful change in reducing the human health and/or ecological
risk that is the basis for the remedy. Without a meaningful change in a risk parameter, the remedy
should look to minimize environmental harm and reduce cost.
A "forward projection" of human health risks was conducted across the progression of the more
aggressive remedial action alternatives (MNA to CIP to Removal) at each of the four sites (Allen,
Buck, Cliffside, and Mayo) and is presented in Figures 23-26, respectively (see Appendix D). In
addition to projected human health risks, Figures 23-26 also include the estimation of current
ecological risks provided in the available CAP 2 documents for the Allen, Buck, Cliffside, and
Mayo sites (HDR 2016a through 2016c, and SynTerra 2016a respectively). The current ecological
risk categorization depicted in the figures is based upon the lowest observed effect level (LOAEL).
The LOAEL was used since all of the ecological risk assessments require additional data and
further refinement is needed to address uncertainties associated with the evaluation of these
scenarios such as the occurrence of the ecological receptors in the areas adjacent to the ash basins,
the bioavailability of any source or background COIs applicable to the risk assessments', and
refinement of the exposure and toxicity assumptions used in the ecological risk characterization.
These refinements would likely reduce potential ecological risks further.
That said, the ecological risk information for the Allen, Buck, and Mayo sites support a risk
categorization that there is no unacceptable risk to ecological receptors at these sites in the current
condition. For Cliffside, the ecological risk information supports a risk categorization that there is
low risk to ecological receptors at this site in the current condition. The LOAEL risk categorization
information is provided for the Allen, Buck, Cliffside, and Mayo sites in Tables 1, 2, 3, and 4,
respectively.
It is my understanding that the question of source -related versus background COIs is to be addressed by other Duke
Energy experts. As such, I reserve the right to supplement my opinions on this point when their reports become
available to me.
DCN: HWIDENCOOIA 36 September 30, 2016

High Risk
Y
N
rY
jModerate
" Risk
M
d
z
Low Risk
NUA
Figure 23. Allen Steam Station - Human Health and Ecological Risks
a
a
a
a
a
a
a
a
a
a
a
a
Z
Z
Z
Z
Z
Z
Z
Z
Z
Z
Z
Z
MINA
■Groundwater (drinkingwater consumption)
❑ On -Site contaminant exposure
NUA -No Unacceptable Risk
High Risk
Y
N
tY
j Moderate
R
Risk
d
rz
Low Risk
NUA
CI P Removal
❑ Public off-site conta minant exposure
0 Ecological Risk
Figure 24. Buck Steam Station - Human Health and Ecological Risks
MINA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
NUA -No Unacceptable Risk
CI P Removal
❑ Public off-site contaminant exposure
0 Ecological Risk
EPS
DCN: HWIDENC001A 37 September 30, 2016
3
0
J
a
a
a
a
a
a
a
a
a
a
a
z
z
z
z
>
z
z
z
z
z
z
z
z
z
z
z
z
z
z
z
z
z
MINA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
NUA -No Unacceptable Risk
CI P Removal
❑ Public off-site contaminant exposure
0 Ecological Risk
EPS
DCN: HWIDENC001A 37 September 30, 2016

High Risk
Y
N_
Q)
> Moderate
; Risk
Q)
Low Risk
NUA
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
NUA -No Unacceptable Risk
Figure 25. Cliffside Steam Station - Human Health and Ecological Risks
a a a a a a ¢ a
z z z z z z z z
High Risk
Y
_N
_> Moderate
" Risk
m
v
Low Risk
NUA
CIP Removal
❑ Public off-site contaminant exposure
■ Ecological Risk
Figure 26. Mayo Steam Station - Human Health and Ecological Risks
3
0
a a J a
> > 7
z z z
MNA
10 Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
NUA - No Unacceptable Risk
z
Z z Z z z z
Z Z Z z Z Z
CIP Removal
© Public off-site contaminant exposure
■ Ecologica I Risk
EPS
DCN: HWIDENCOOIA 38 September 30, 2016

Table 1. Allen Ecological Hazard Quotients (HQ)l for COPECs.
Analyte
Wildlife Receptor HQ Estimated using the "Lowest Observed Adverse Effects Level"
Aquatic
Mallard Duck Great Blue Heron Muskrat River Otter
Eco Area 1 AOW Water, Sediment and Surface Water3
Aluminum 0.000002
0.0002
0.008
0.0005
Barium 0.02
0.08
0.1
0.002
Cobalt 0.000007
0.07
0.0004
0.002
Copper 0.0000002
0.008
0.00002
0.0004
Manganese 0.003
0.07
0.2
0.01
Mercury 0.0000001
0.06
0.00002
0.006
Zinc 0.002
0.02
Eco Area 2 AOW Water
Aluminum 0.000000004
0.000007
0.001
0.0000009
Barium 0.00000001
0.004
0.00003
0.000004
Cobalt 0.0000000006
0.0001
0.000002
0.0000002
Copper 0.00000001
0.01
0.00007
0.00003
Manganese 0.000000004
1 0.001 1
0.0001
0.000009
Mercury 0.000000002
0.03 1
0.00003
0.0001
Eco Area 3 Sediments
Barium 0.0003
0.06
0.04
0.00009
Manganese 0.00004
0.0009
0.04
0.00001
Zinc 0.00004
0.02
0.004
0.00004
Eco Area 4 Surface Water
Aluminum 0.00000002
0.00004
0.006
0.000005
Barium 0.00000004
0.01
0.0001
0.00001
Cobalt 0.00000002
0.005
0.00009
0.000007
Copper 0.000000002
0.002
0.00002
0.000006
Manganese 0.00000006
1 0.02 1
0.001
0.0001
Mercury 0.00000000010
0.001 1
0.000001
0.000006
Notes:
IA Hazard Quotient is estimated by dividing the Exposure Point Concentration for that species by its respective Toxicity Reference Value for the COPEC.
2 Exposures are adjusted for the proportion of this exposure area that represents the animal's home range, i.e. 1 acres/10 acres = 0.1.
3 Reproduced from Table 6-5 of Appendix F of Corrective Action Plan Part 2: Allen Steam Station Ash Basin (February 19, 2016).
4 Reproduced from Table 6-6 of Appendix F of Corrective Action Plan Part 2: Allen Steam Station Ash Basin (February 19, 2016).
5 Reproduced from Table 6-7 of Appendix F of Corrective Action Plan Part 2: Allen Steam Station Ash Basin (February 19, 2016).
6 Reproduced from Table 6-8 of Appendix F of Corrective Action Plan Part 2: Allen Steam Station Ash Basin (February 19, 2016).
HQ >= 1
39

Table 2. Buck Ecological Hazard Quotients (HQ)1 for COPECs.
Analyte
Wildlife Receptor
HQ Estimated using the "Lowest Observed
Adverse Effects Level"
Aquatic
Mallard Duck Great Blue Heron Muskrat
River Otter
Eco Area 1 AOW Water and Sedimenta
Aluminum
0.0008
0.00005
0.8
0.00007
Arsenic
0.000005
0.003
Barium
0.007
0.03
0.1
0.0004
Beryllium
0.000005
0.000002
Cadmium
0.000000002
0.0009
0.00000007
0.000004
Chromium (Total
0.003
0.0007
0.00001
0.000000003
Cobalt
0.0004
0.02
0.008
0.0003
Copper
0.001
0.02
0.04
0.0004
Lead
0.0000002
0.00002
0.00001
0.0000002
Manganese
0.001
0.0002
0.2
0.00003
Mercury
0.000000009
0.01
0.000003
0.0005
Nickel
0.0008
0.003
0.06
0.0002
Selenium
0.0000002
0.02
0.0001
0.001
Vanadium
0.00001
0.2
0.0002
0.0004
Zinc
0.0007
0.03
0.01
0.0005
Eco Area 2 AOW Water, Sediment and
Surface Water
Aluminum
0.003
0.00007
1
0.0002
Arsenic
0.00006
0.01
Barium
0.02
0.02
0.2
0.0005
Cadmium
0.0001
0.0008
0.0002
0.000008
Chromium (Total
0.002
0.0001
0.000002
0.000000001
Cobalt
0.0009
0.01
0.008
0.0003
Copper
0.002
0.01
0.03
0.0007
Lead
0.0000001
0.000007
0.000004
0.0000002
Manganese
0.002
0.05
0.1
0.01
Mercury
0.0000008
0.4
0.0001
0.04
Nickel
0.0009
0.0006
0.02
0.00009
Selenium
0.02
0.02
0.8
0.002
Vanadium
0.00001
0.06
0.00006
0.0002
Zinc
0.007
0.3
0.06
0.01
Eco Area 3 AOW Water and Sediments
Aluminum
0.000007
0.00003
0.2
0.000004
Arsenic
0.0000004
0.007
Barium
0.0001
0.01
0.06
0.00001
Beryllium
0.000002
0.00000002
Cadmium
0.00000000004
0.0002
0.00000005
0.00000009
Chromium (Total
0.00001
0.0001
0.0000006
0.00000000004
Cobalt
0.000002
0.0002
0.001
0.0000002
Co22er
0.000008
0.0005
0.009
0.000001
Lead
0.000000001
0.000001
0.000002
0.000000002
Manganese
0.000003
0.0000003
0.01
0.000000005
Mercury
0.00000000004
0.0006
0.0000005
0.000002
Nickel
0.00001
0.00005
0.004
0.0000003
Selenium
0.00003
0.007
0.07
0.00004
Vanadium
0.0000002
0.04
0.0001
0.000005
Zinc
0.00001
1 0.003 1
0.007
0.000004
40 Page 1 of 2

41 Page 2 of 2
Wildlife Receptor HQ
Estimated using the 'Lowest Observed Adverse Effects
Level"
Analyte
Aquaticz
Mallard Duck
Great Blue Heron Muskrat
River Otter
Eco Area 4 AOW Water and Sediment
Aluminum 0.002
0.002 1
0.006
Arsenic 0.00002
0.008
Barium 0.03
0.1 0.3
0.003
Beryllium
0.00003
0.00002
Cadmium 0.00000002
0.005 0.0000004
0.00005
Chromium (Total 0.0009
0.008 0.000001
0.00000006
Cobalt 0.003
1 0.04
0.03
Copper 0.0009
0.2 0.02
0.01
Lead 0.000008
0.0005 0.0003
0.00001
Manganese 0.01
0.1 1
0.03
Mercury 0.0000006
0.4 0.0001
0.03
Nickel 0.0007
0.01 0.01
0.002
Selenium 0.006
0.4 0.2
0.04
Notes:
'A Hazard Quotient is estimated by dividing the Exposure Point Concentration for that species by its respective Toxicity Reference Value for the COPEC.
2 Exposures are adjusted for the proportion of this exposure area that represents the animal's home range, i.e. 1 acres/10 acres = 0.1.
s Reproduced from Table 6-5 of Appendix F of Corrective Action Plan Part 2: Buck Station Ash Basin (February 19, 2016).
° Reproduced from Table 6-6 of Appendix F of Corrective Action Plan Part 2: Buck Steam Station Ash Basin (February 19, 2016).
5 Reproduced from Table 6-7 of Appendix F of Corrective Action Plan Part 2: Buck Steam Station Ash Basin (February 19, 2016).
6 Reproduced from Table 6-8 of Appendix F of Corrective Action Plan Part 2: Buck Steam Station Ash Basin (February 19, 2016).
HQ >= 1
41 Page 2 of 2

Table 3. Cliffside Ecological Hazard Quotients (HQ)1 for COPECs.
Analyte
Wildlife
Receptor HQ
Estimated using the
"Lowest Observed Adverse Effects Level"
Aquatic2 Terrestrial2
Mallard Duck
I Great Blue HeronI
Muskrat
I River Otter
American Robin
Red -Tailed Hawkj
Meadow Vole I
Red Fox
Eco Area 1 Soil,
AOW Water, Sediment and Surface Water
Aluminum
0.002
0.0002
0.6
0.0007
0.1
0.000003
0.8
0.0002
Arsenic
0.0003
0.03
0.06
0.04
0.02
0.00002
0.09
0.002
Barium
0.02
0.05
0.1
0.002
0.000002
0.000003
Beryllium
0.00002
0.00002
0.006
0.0002
Boron
0.001
0.00001
0.0002
Cadmium
0.0002
0.003
0.0002
0.00004
0.02
0.0002
0.0002
0.00008
Chromium (Total
0.002
0.0001
0.000001
0.000000001
0.0000002
8E-1 I
Cobalt
0.0007
0.2
0.005
0.007
0.03
0.0001
0.007
0.0001
Copper
0.0008
0.001
0.008
0.0001
0.04
0.001
0.01
0.0007
Lead
0.001
0.000006
0.003
0.0000002
0.1
0.002
0.004
0.0002
Manganese
0.006
0.1
0.3
0.03
0.2
0.00001
0.4
0.01
Mercury
0.0000001
0.05
0.00002
0.008
0.0000004
0.000002
Molybdenum
0.06
0.0008
0.09
0.003
Nickel
0.001
0.004
0.01
0.0009
0.1
0.0003
0.02
0.0003
Selenium
0.01
0.05
0.3
0.009
0.5
0.003
0.4
0.02
Thallium
0.0005
0.002
0.00001
Vanadium
0.000004
0.02
0.00002
0.0001
0.000002
0.0000004
Zinc
0.002
0.05
0.01
0.003
0.2
0.002
0.01
0.0007
Eco Area 2 Soil,
AOW Water, Sediment and Surface Water
Aluminum
0.0003
0.06
4
0.02
0.2
0.00004
8
0.006
Arsenic
0.0000002
0.006
0.002
0.0007
0.0000001
0.000008
Barium
0.0009
1
0.07
0.003
0.000004
0.000005
Beryllium
0.0003
0.00003
0.003
0.000007
Cadmium
0.00000002
0.04
0.000003
0.00005
0.0000001
0.00000007
Chromium (Total
0.0002
0.1
0.000005
0.0000001
0.00001
0.000000006
Cobalt
0.00006
0.7
0.008
0.003
0.03
0.00001
0.01
0.00002
Copper
0.0001
3
0.02
0.02
0.07
0.0001
0.03
0.0001
Lead
0.0003
0.007
0.01
0.00002
0.3
0.0002
0.02
0.00004
Manganese
0.00008
2
0.09
0.04
0.04
0.000009
0.2
0.0002
Mercury
0.000000002
0.009
0.000003
0.0001
0.000000005
0.00000003
Nickel
0.0001
0.2
0.04
0.003
0.2
0.00004
0.08
0.00008
Selenium
0.000007
2
0.01
0.03
0.000006
0.00004
Thallium
0.01
0.004
0.00003
Vanadium
0.0002
10
0.01
0.004
0.00009
0.00002
Zinc
0.0002
0.5
0.01
0.002
0.2
0.0002
0.01
0.00006
Sulfide
42 Page 1 of 2

Analyte
Wildlife Receptor HQ
Estimated using the
"Lowest Observed Adverse Effects Level'
Aquatic Terrestrial
Mallard Duck I Great Blue Heronj Muskrat I River Otter American Robin Red-Tailed HawkI Meadow Vole
I Red Fox
Eco Area 3 Soil, AOW Water, Sediment and Surface Waters
Aluminum
0.000003
0.000007
0.09
0.0000008
0.02
0.00000002
0.1
0.0000002
Barium
0.00003
0.008
0.01
0.000007
0.00000001
0.00000001
Beryllium
0.001
0.0000005
Chromium (Total
0.00002
0.00003
0.0000009
0.000000000009
0.000000001
0.0000000000006
Cobalt
9E-10
0.0002
0.000003
0.0000003
0.0000000005
0.0000000008
Copper
0.000007
0.001
0.005
0.000002
0.03
0.00001
0.006
0.000006
Lead
0.000009
0.000003
0.002
0.000000003
0.05
0.00001
0.002
0.000001
Manganese
0.000001
0.0004
0.004
0.000003
0.004
0.00000006
0.005
0.000002
Nickel
0.00002
0.00007
0.002
0.0000004
0.2
0.000002
0.003
0.0000009
Thallium
0.00003
0.000002
0.00000001
Vanadium
0.00000003
0.005
0.00001
0.0000008
0.00000002
0.000000003
Zinc
0.00001
0.003
0.004
0.000005
0.1
0.00003
0.004
0.000003
Eco Area 4 Soil, AOW Water, Sediment and Surface Water
Aluminum
0.003
0.003
1
0.01
0.2
0.00003
2
0.004
Arsenic
0.00009
0.002
0.02
0.004
0.005
0.000004
0.02
0.0006
Barium
0.04
0.07
0.2
0.003
0.000004
0.000005
Beryllium
0.0002
0.0003
0.04
0.001
Boron
0.03
0.00002
0.004
Cadmium
0.0004
0.02
0.0003
0.0003
0.05
0.0003
0.0004
0.0001
Chromium (Total
0.003
0.007
0.000003
0.00000009
0.00001
0.000000006
Cobalt
0.03
0.1
0.2
0.005
1
0.02
0.2
0.004
Copper
0.002
0.04
0.02
0.003
0.08
0.002
0.02
0.002
Lead
0.004
0.0003
0.007
0.00001
0.3
0.003
0.009
0.0004
Manganese
0.02
0.2
1
0.05
0.7
0.00002
1
0.04
Mercury
0.00000007
0.02
0.000008
0.004
0.0000002
0.000001
Nickel
0.004
0.005
0.09
0.001
0.2
0.001
0.1
0.002
Selenium
0.1
0.6
3
0.1
4
0.007
3
0.2
Thallium
0.001
0.005
0.00003
Vanadium
0.0002
0.8
0.0008
0.005
0.00009
0.00002
Zinc
0.004
0.06
0.02
0.004
0.3
0.003
0.03
0.002
Sulfide
Notes:
IA Hazard Quotient is estimated by dividing the Exposure Point Concentration for that species by its respective Toxicity Reference Value for the COPEC.
2 Exposures are adjusted for the proportion of this exposure area that represents the animal's home range, i.e. 1 acres/10 acres = 0.1.
3 Reproduced from Table 6-5 of Appendix F of Corrective Action Plan Part 2: Cliffside Steam Station Ash Basin (February 12, 2016).
4 Reproduced from Table 6-6 of Appendix F of Corrective Action Plan Part 2: Cliffside Steam Station Ash Basin (February 12, 2016).
5 Reproduced from Table 6-7 of Appendix F of Corrective Action Plan Part 2: Cliffside Steam Station Ash Basin (February 12, 2016).
e Reproduced from Table 6-8 of Appendix F of Corrective Action Plan Part 2: Cliffside Steam Station Ash Basin (February 12, 2016).
HQ >= 1
43 Page 2 of 2

Table 4. Mayo Ecological Hazard Quotients (HQ)1 for COPECs.
Ash Basin;
Wildlife Receptor HQ Estimated using the "Lowest Observed Adverse Effects Level"
Analyte
Terrestrial2
American Robin Red -Tailed Hawk Meadow Vole
Red Fox
Aluminum
0.00001
0.0000002
0.002
0.00002
Manganese
0.00003
0.0000004
0.0004
0.000005
Analyte
Aquatic2
Mallard Duck Great Blue Heron Muskrat
River Otter
Aluminum
0.0000003
0.00002
0.0009
0.00009
Manganese
1 0.0000008
0.005
0.0002
0.002
South Creek Downgradient4
Analyte
Wildlife Receptor Hazard
Quotient Estimated using the
"Lowest Observed Adverse Effects Level"
Aquatic2
Mallard Duck Great Blue Heron Muskrat River Otter
Aluminum
0.00000
0.0002000
0.009
0.00020
Barium
0.00400
0.080
Iron
Manganese
0.00000
0.0400000
0.001
0.00400
Zinc
0.00100
0.020
Crutchfield Branch Downgradient5
Analyte
Wildlife Receptor Hazard
Mallard Duck
Quotient Estimated using the
Aquatic2
Great Blue Heron
"Lowest Observed Adverse Effects Level"
Muskrat River Otter
Aluminum
0.00000
0.0001000
0.007
0.00010
Barium
0.00300
0.100
Iron
Manganese
0.00001
0.4000000
0.020
0.02000
Zinc
0.00000
0.0200000
0.000
0.00020
Crutchfield Branch 6
Analyte
Wildlife Receptor Hazard
American Robin
Quotient Estimated using the "Lowest Observed Adverse Effects Level"
Terrestrial
Red -Tailed Hawk Meadow Vole Red Fox
Aluminum
0.03000
0.0000040
0.400
0.00060
Arsenic
0.01000
0.0000020
0.040
0.00004
Barium
0.00100
0.0000030
0.002
0.00000
Boron
0.00300
0.000
Chromium
Cobalt
0.05000
0.0000600
0.010
0.00005
Copper
0.00003
0.0000001
0.000
0.00000
Iron
Lead
0.00040
0.0000020
0.000
0.00000
Manganese
0.50000
0.0000100
1.000
0.00010
Vanadium
0.10000
0.002
Zinc
0.30000
0.0005000
0.030
0.00040
44 Page 1 of 2

Analyte Aquaticz
Mallard Duck Great Blue Heron Muskrat
River Otter
Aluminum 0.0000009 0.0002 0.01
0.0002
Arsenic 0.00001 0.01
Barium 0.006 0.2
Boron
Chromium 0.0008 0.000004
Cobalt
Copper 0.0000002 0.02 0.00006
0.0004
Iron
Lead
Manganese 0.001 0.3 0.3
0.02
Vanadium
Zinc
Notes:
]A Hazard Quotient is estimated by dividing the Exposure Point Concentration for that species by its respective Toxicity Reference
Value for the COPC.
2 Exposures are adjusted for the proportion of this exposure area that represents the animal's home range, i.e. 1 acres/10 acres = 0.1.
3 Reproduced from Table 6-3 of Appendix E of Corrective Action Plan Part 2: Mayo Steam Electric Plant (February 29, 2016).
° Reproduced from Table 6-4 of Appendix E of Corrective Action Plan Part 2: Mayo Steam Electric Plant (February 29, 2016).
5 Reproduced from Table 6-5 of Appendix E of Corrective Action Plan Part 2: Mayo Steam Electric Plant (February 29, 2016).
6 Reproduced from Table 6-6 of Appendix E of Corrective Action Plan Part 2: Mayo Steam Electric Plant (February 29, 2016).
HQ >= 1
45 Page 2 of 2

0
As will be noted in these figures, there are no unacceptable off-site human health risks at any of
the four sites$. For the on-site scenarios, nearly all forward projected risks are below the most
conservative risk thresholds (i.e., a Hazard Index of unity (1) for non -carcinogens, and an Excess
Lifetime Cancer Risk (ELCR) of lE-6). The only identified risk above this lower threshold was
for an on-site construction worker at the Buck, Cliffside and Mayo sites where the projected risk
was between 2E-6 and 3E-6. For the sake of the NEBA exercise, this level of risk was considered
as "low" even though it is within the EPA accepted risk range of lE-4 to lE-6.
Therefore, a more reasonable scenario would likely drive the "perceived" risk within a "no
unacceptable risk" range ("real" risk range) at the four sites. Given this, it is apparent that the
implementation of the remedial alternatives of CIP or Removal are not likely to provide any benefit
from a risk management standpoint.
Groundwater Service Value
It should be recognized that a groundwater aquifer has the potential to provide a variety of service
flows (USEPA 1995). The services that potentially can be provided by groundwater are listed in
Table 5, including those parameters that can be evaluated to understand effects to groundwater
services. As can be seen in Table 5, adverse groundwater service effects appear to be marginal if
any. This is supported by the groundwater risk analysis conducted by Lisa Bradley, PhD (Haley
and Aldrich 2016). Thus, the question arises, are the environmental and community risks that will
arise from remedy implementation and the implementation costs worth incurring to manage what
appears to be marginal levels of risk, if any? Based on the evaluation conducted herein and as
demonstrated in this section, it is evident that the projected environmental and community impacts
associated with implementing the Removal alternative far outweigh any benefit associated with
implementation of the Removal alternative.
4.2 NEBA Assessment Parameter Evaluation
I next consider how the remedial actions might affect other parameters that are important to human
health, community perspectives, and ecological resources. A demonstration as to how the
assessment parameters were estimated to be affected given the MNA, CIP and Removal
alternatives is presented in a series of figures. In each figure, each individual parameter with the
greatest adverse impact is set to 1 (on the right vertical axis), regardless of alternative. Then, all
other corresponding parameter values are presented proportional to the highest value for that
specific parameter. This permits multiple parameters with varying scales to be displayed on the
same graph and for relative comparison of projected parameter changes between alternatives. The
a Fish consumption scenarios (recreational and subsistence) were not evaluated in the "forward projection" modeling
as there is too little information to estimate whether any "true" risk exists for this scenario (not likely however, as the
original risk assessments were overly conservative as they used limited site data and assumed unrealistic exposures).
The risk assessments included in the CAP 2 reports used two overly conservative assumptions: 1) the bioconcentration
factors that were used to estimate fish tissue concentrations based on surface water concentrations were very
conservative (most notably the factor used for cobalt is known to be overly conservative (ATSDR 2004) for freshwater
fish), and 2) the surface water concentrations used were from limited on-site surface water sampling, not from surface
water collected in the receiving stream or reservoir.
DCN: HWIDENCOOIA 46 September 30, 2016

Table 5. Groundwater Services, Effects, and Parameter Evaluation.
FUNCTION: STORAGE OF WATER
EFFECTS
SERVICE
FUNCTION: DISCHARGE TO
EFFECTS
SERVICE
RESERVE (STOCK)
EFFECT
STREAMS/LAKES/WETLANDS
EFFECT
Change in Welfare from Increase or Decrease in
Drinking Water through Surface
Change in Welfare from Increase or Decrease in
Drinking Water;
Availability of Drinking Water, Change in Human
No
Water Supplies;
Availability of Drinking Water, Change in Human
No
Health or Health Risks
Health or Health Risks
Water for Crop Irrigation;
Change in Value of Crops or Production Costs,
No
Water for Crop Irrigation through
Change in Value of Crops or Production Costs,
No
Change in Human Health or Health Risks
Surface Water Supplies;
Change in Human Health or Health Risks
Change in Value of Livestock Products or
Water for Livestock through Surface
Change in Value of Livestock Products or Production
Water for Livestock;
Production Costs, Change in Human Health or
No
Water Supplies;
Costs, Change in Human Health or Health Risks
No
Health Risks
Water for Food Product
Change in Value of Food Products or Production
Water for Food Product Processing
Change in Value of Food Products or Production
Processing;
Costs, Change in Human Health or Health Risks
No
through Surface Water Supplies;
Costs, Change in Human Health or Health Risks
No
Water for Other Manufacturing
Change in Value of Manufactured Goods or
Water for Other Manufacturing
Change in Value of Manufactured Goods or
Processes;
Production Costs;
No
Processes through Surface Water
Production Costs;
No
Supplies;
Heated Water for Geothermal
Provision of Cooling Water for
Power Plants;
Change in Cost of Electricity Generation
No
Power Plants through Surface Water
Change in Cost of Electricity Generation
No
Supplies
Change in Cost of Maintaining Public or Private
Cooling Water for Other Power
Provision of Erosion, Flood, and
Property, Change in Human Health or Health Risks
Plants;
Change in Cost of Electricity Generation
No
Storm Protection
through Personal Injury Protection, Change in
No
Economic Output Attributable to Use of Surface
Water Supplies for Disposing Wastes
Change in Human Health or Health Risks Attributable
Transport and Treatment of Wastes
to Change in Surface Water Quality, Change in
Water/Soil Support System
Change in Cost of Maintaining Public or Private
and Other By -Products of Human
Animal Health or Health Risks Attributable to Change
Preventing Land Subsidence;
Property
No
Economic Activity through Surface
in Surface Water Quality, Change in Economic Output
No
Water Supplies
Attributable to Use of Surface Water Supplies for
Disposing Wastes
Erosion and Flood Control
Change in Cost of Maintaining Public or Private
Support of Recreational Swimming,
Change in Quantity or Quality Recreational Activities,
through Absorption of Surface
Property
No
Boating, Fishing, Hunting, Trapping
Change in Human Health or Health Risks
No
Water Run -Off;
and Plant Gathering
Medium for Wastes and Other
Change in Human Health or Health Risks
Support of Commercial Fishing,
By -Products of Human Economic
Attributable to Change in Ground water Quality
No
Hunting,
Change in Value of Commercial Harvest or Costs
No
Activity;
Trapping, Plant Gathering
Change in Human Health or Health Risks
Attributable to Change in Water Quality, Change
Marginal,
Support of On -Site Observation or
Clean Water through Support of
in Animal Health or Health Risks Attributable to
if any, see
Study of Fish, Wildlife, and Plants
Change in Quantity or Quality of On -Site Observation
Living Organisms;
Change in Water Quality, Change in Value of
Appendix
for Leisure, Educational, or Scientific
or
No
Economic Output or Productions Costs
Study Activities
Attributable to Change in
D
Purposes
P
Water Quality
Passive or Non -Use Services
Marginal,
Support of Indirect, Off -Site Fish,
Change in Quantity or Quality of Indirect, Off -Site
(e.g., Existence or Bequest
Change in Personal Utility
if any
Wildlife, and Plant Uses (e.g.
Activities
No
Motivations).
viewing wildlife photos)
Change in Human Health or Health Risks Attributable
Provision of Clean Air through
to
Support of Living Organisms
Change in Air Quality, Change in Animal Health or
No
Health Risks Attributable to Change in Air Quality
Change in Human Health or Health Risks Attributable
to
Marginal,
Provision of Clean Water through
Change in Water Quality, Change in Animal Health or
if any, see
Support of Living Organisms
Health Risks Attributable to Change in Water Quality,
Appendix
Change in Value of Economic Output or Productions
Costs
D
Attributable to Change in Water Quality
Change in Human Health or Health Risks Attributable
to
Regulation of Climate through
Change in Climate, Change in Animal Health or
Support of Plants
Health Risks Attributable to Change in Climate,
No
Change in Value of Economic Output or Production
Costs Attributable to Change in Climate
Provision of Non -Use Services (e.g.,
Existence Services) Associated with
Marginal,
Surface Water Body or Wetlands
Change in Personal Utility or Satisfaction
if any
Environments or Ecosystems
Supported by Ground water
47

0
higher a bar moves upward from the x-axis, the greater the environmental, health and safety, or
social impact. This approach allows for the alternatives to be evaluated and compared visually in
a holistic manner, including in comparison to changes in human and ecological risks (left vertical
axis) associated with implementation of each alternative.
It should be recognized that the approach taken in the overall NEBA analysis was to approximate
the parameter values for each of the alternatives based upon consistent assumptions where
applicable. As such, the parameter estimates are approximate values and not intended to be exact,
but enough to identify impacts and differences between alternatives to a reasonable degree of
certainty.
The overall results of the NEBA are presented in Table 6 and the following figures demonstrate
how ecological and human health risks and the estimated parameter values are projected to change
given implementation of the CIP and Removal alternatives. The figures are presented in turn, for
each of the following parameter groups by site: implementation health and safety risks, truck trips,
air emissions (criteria pollutants), energy use, ecological habitat losses, and costs (Figures 27-50).
Following these figures, three graphics are presented for each site. The first displays all assessment
parameters, the second compares projected health impacts between alternatives, and the third
compares GHG and NOX emissions to established reporting and permitting thresholds (Figures 51-
62). Additionally, a cumulative graphic is provided that displays the combined effect across all
four sites (Figure 63).
DCN: HWIDENCOOIA 48 September 30, 2016

Table 6. Overall NEBA Summary Table.
NEBA Considerations
Ecological Risks
Human Health Pathways, Risks, and Social Consequences
Ecological Habitat Impacts
Additional Environmental and Social
Costs
Consequences
Groundwater
Public
On-Site
Truck traffic
Implementation
Implementation
Wetland and
Overall EcologicalGHG
emissions s/
Ecological Risk
(drinking water
contaminant
contaminant
Fish Consumption
t
Truck traffic
incidents-
risks- project
Truck Trips-Public
Terrestrial HabitatPriority
Surface Water
�
carbon foot-
pollutant
Total Energy
Capital and 0&M
NEBA Framework
consumption)
z'4
z'a
incidents -risk
property
accident rate
Roads'
Value
Habitat Value
Habitat Value
emissions
Used
exposure
exposure
ldamage
printing
Environmental
Justice Concerns
Site
Alternative
Metric(s)
Metric(s)
Metric(s)
Metric(s)
Metric(s)
Metric(s)
Metric(s)
Metric(s)
Metric(s)
Metric(s)
Metric(s)
Metric(s)
Metric(s)
Metric(s)
Metric(s)
Metric(s)
no unacceptable
no unacceptable
HI/ELCR -no
H/ELCR -no
no unacceptable
risk, low risk,
risk; low risk,
unacceptable risk,
unacceptable risk,
risk, low risk,
Fatalities (F) andFatalities
(F) and
Trips - Public
Tons/yr and tons
Tons/yr of NOx,
Net present value
moderate risk,
moderate risk,
low risk, moderate
low risk, moderate
moderate risk,
injuries/illnesses(1)
Incidents
injuries/illnesses(1)
Roads
Lost dSAVs
Lost dSAVs
Lost dSAVs
of COze emitted
PM30/2.5 emitted
MINI BTU
in real dollars
high risk
high risk
risk, high risk
risk, high risk
high risk
Monitored Natural
NUA
NUA
Baseline=
Attenuation (MNA)
NUA
NUA
0.004/-
0.1/5E-08
Baseline
Baseline
Baseline
0
Baseline
Baseline
Baseline
Baseline
Baseline
Baseline
$ 7,315,000
NUA
NUA
$ 154,833,594
Allen
Cap-in-Place (CIP)
NUA
NUA
F-0.10
8
F-0.07
140,401
2,477
3,212
5,690
7,376.46 tons/yr
NOx-29.20
446,861
0.002/--
0.02/lE-OS
1-2.8
1-9.6
38,302.34 tons
PM10/2.5-1.01
Above Baseline
NUA
NUA
F-0.68
F-0.23
30,940.04 tons/yr
NOx-143.01
$ 1,543,608,397
Removal
NUA
NUA
0.001/--
0.004/1E-10
1-19.2
56
1-61
99fi,795
3,735
3,212
6,947
465,225.76 tons
PM30/2.5-6.12
51648,213
Above Baseline
Monitored Natural
NUA
Low Risk
Baseline=
Attenuation (MNA)
NUA
NUA
0.02/2E-07
0.2/2E-06
Baseline
Baseline
Baseline
0
Baseline
Baseline
Baseline
Baseline
Baseline
Baseline
$ 7,315,000
NUA
NUA
$ 83,948,029
Cap-in-Place (CIP)
NUA
NUA
F-0.06
$
F-0.04
78,526
1,617
2,114
3,730
7,376.55 tons/yr
NOx-29.20
242'972
Buck
0.01/4E-08
0.05/6E-07
1-1.6
1-5.4
21,422.52 tons
PM30/2.5-1.01
Above Baseline
NUA
NUA
$ 445,498,459
F-0.19
F-0.08
30,954.67 tons/yr
NOx-143.05
Removal
NUA
NUA
0.009/2E-08
0.0006/6E-09
1-5.3-19
16
276,968
1,352
2,114
3,466
133,968.79 tons
PM10/2.5-6.12
1,614,833
Above Baseline
Monitored Natural
NUA
Low Risk
Baseline=
Attenuation (MNA)
Low Risk
NUA
0.02/6E-07
0.2/2E-06
Baseline
Baseline
Baseline
0
Baseline
Baseline
Baseline
Baseline
Baseline
Baseline
$ 9,872,500
NUA
NUA
$ 85,897,149
Cliffside
Cap-In-Place (CIP)
NUA
NUA
F-0.06
5
F-0.04
82,459
1,476
1,460
2,936
7,446.20 tons/yr
NOx-29.43
255,655
0.02/1E-07
0.04/6E-07
1-1.6
1-5.7
22,338.61 tons
PM10/2.5-1.02
Above Baseline
NUA
NUA
F-0.28
F-0.11
30,939.07 tons/yr
NOx-143.00
$ 648,986,943
Removal
NUA
NUA
0.02/6E-08
0.01/4E-09
1-7.9
27
I -27
410,279
1,842
1,460
3,303
197,207.80 tons
PM10/2.5-6.12
2,379,322
Above Baseline
Monitored Natural
NUA
Low Risk
Baseline=
Attenuation (MNA)
NUA
NUA
0.2/-
0.3/3E-06
Baseline
Baseline
Baseline
0
Baseline
Baseline
Baseline
Baseline
Baseline
Baseline
$ 7,315;000
NUA
NUA
F-0.05
F-0.03
7,321.77 tons/yr
NO. -29.02
$ 70,423,111
Mayo
Cap-In-Place (CIP)
NUA
NUA
02/
0.09/7E-07
1-1.3
4
1-4.6
66,720
997
2,595
3,592
18,304.42 tons
PM10/2.5-1.01
210,687
Above Baseline
NUA
NUA
F-0:23
F-0.09
30,953.04 tons/yr
NOx-143.05
$ 547,889,455
Removal
NUA
NUA
0.2/--
0.0002/-
1-6.6
23
1-23
343,813
1,058
2,595
3,654
165,651.27 tons
PM10/2.5-6.12
2'007'693
Above Baseline
Noter.
Current Baseline: Parameters are measured as a change from the current condition for each site. Footnotes:
MNA - Monitored Natural Attenuation 1. Insufficient data to evaluate
CIP - Cap-in-Place with MNA 2. Highest Hazard Index / ELCR 30 years after implementation
Removal- Full Removal with MNA NUA: No Unacceptable Risk: HI<1; ELCR<1E-06
Abbreviations: Low Risk: 1 <HI <3; 1E-06 <ELCR <5E-05
dSAY: discounted service acre year NEBA: net environmental benefit analysis Moderate Risk: 1<HI<3; 1E-05<ELCR<1E-04
ELCR: excess lifetime cancer risk O&M: operation and management High Risk: HI>3; ELCR>3E-04
F: fatalities 3. Construction worker, Commercial/Industrial Worker or Trespasser
GHG: greenhouse gas 4. Swimmer, Boater, Wader
HI: hazard index S.Trucktrips include transport of cap material and liner for Capping and include transport of ash,closure/cap material, and linerfor Removal
I: Injuries/illnesses 6. GHG emissions include both direct (consumption) and indirect (well-to-pump) contributions
7. Overall Ecological Habitat Value, assumes a 1:1 ratio between terrestrial and wetland/surface water habitat

4.2.1 Implementation Health and Safety Risks
Figure 27. Allen Steam Station - Implementation Health and Safety Risks
0
o
High Risk 1
Y
N
i
'a.. Moderate
M
Risk
Low Risk
NUA
MINA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Truck traffic incidents -Fatalities
Truck traffic incidents - property damage only
h Implementation risks - Injuries/Illness
CI P Removal
❑ Public off-site contaminant exposure
® Ecological Risk
■ Truck traffic incidents -Injuries/Illness
Implementation risks - Fatalities
NUA -No Unacceptable Risk
O
CL
O
0.25 d
0
Figure 28. Buck Steam Station - Implementation Health and Safety Risks
High Risk 1
Y
_N
cc
4/
Moderate
m Risk
v
z
Low Risk
NUA
3
Za v v
� `m m m m m z I z z
MINA CIP Removal
■ Groundwater (drinking water consumption) ❑ Public off-site contaminant exposure
❑ On -Site contaminant exposure ■ Ecological Risk
■ Truck traffic incidents -Fatalities ■Trucktraffic incidents -Injuries/Illness
Truck traffic incidents - property damage only Implementation risks - Fatalities
Implementation risks - Injuries/Illness NUA - No Unacceptable Risk
4J
0.75 00
C
M
L
v
Q!
V
0.5 O
a`
m
c
0
`o
0.25 a
O
0
CL
EPS
DCN: HWIDENC001A 50 September 30, 2016

High Risk
Y
> Moderate
" Risk
m
v
Low Risk
NUA
Figure 29. Cliffside Steam Station - Implementation Health and Safety
Risks m
N W
O 1 N O N
0
� N
O lD l0
O ,y
3 3
v v v
a
1
CPS]-
High
('S
a!
0.75 C
m
t
V
QJ
QJ
u
Cu
0.5 2
0.
c
0
Y
O
0.25 O-
O
0
MNA CIP Removal
■ Groundwater (drinking water consumption) ❑ Public off-site contaminant exposure
❑ On -Site contaminant exposure ■ Ecological Risk
■ Truck traffic incidents - Fatalities ■ Truck traffic incidents - Injuries/Illness
11 Truck traffic incidents - property damage only Implementation risks - Fatalities
■ Implementation risks - Injuries/Illness NUA -No Unacceptable Risk
Figure 30. Mayo Steam Station - Implementation Health and Safety Risks
m m
High Risk 1
Y
N
j Modera
m
Ri!
v
Low Ri
NU,
kI
0
0
o m
0
0
3
v v v v v
\k
L4.
'z
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Truck traffic incidents -Fatalities
• Truck traffic incidents - property damage only
■ Implementation risks - Injuries/Illness
DCN: HWIDENCOOIA
CIP Removal
© Public off-site contaminant exposure
■ Ecological Risk
■ Truck traffic incidents - Injuries/Illness
Implementation risks - Fatalities
NUA -No Unacceptable Risk
51
a
a)
0.75
M
S
V
13
a1
u
ar
0.5 O
a`
m
c
O
Z
O
0.25 r
0
CL
September 30, 2016

4.2.2 Truck Trips
High Risk
Y
K
Ol
m Moderate
Risk
Low Risk
NUA
Figure 31. Allen Steam Station -Truck Trips
O
a
0
a
a a a a a a a a
z z a z z z z z
0
MNA CIP Removal
■Groundwater(drinkingwaterconsumption) ❑Public off-site contaminant exposure
❑ On -Site contaminant exposure ■ Ecological Risk
■ImplementationTruckTrips- Public Roads NUA-No Unacceptable Risk
High Risk
Y
cc
Qj
> Moderate
Risk
v
cc
Low Risk
NUA
Figure 32. Buck Steam Station -Truck Trips
3
¢ a
z z
a
z o
a a a a
z z z z
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Implementation Truck Trips -Pub I ic Roads
CIP Removal
M Public off-site contaminant exposure
■ Ecological Risk
NUA - No Unacceptable Risk
N
MA
C
0.75 s
v
G/
w
GJ
O
a`
0.5
m
o_
.Y
0
C
O
0.25 0-
0 0
a
0.75 oA
C
M
s
J
d
a-.
u
G/
0.5 O
a`
m
0
0
�Y
Q
0.25 0.
O
CL
0
EPS
DCN: HWIDENCOOIA 52 September 30, 2016

High
Y
> Mode
I
v
z
Figure 33. Cliffside Steam Station -Truck Trips
N
O
V
ate
isk
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Implementation Truck Trips -Public Roads
High Ris
Y
H
> Moderate
ra
Risk
d
Low Ris
NUA
CI P Removal
❑ Public off-site contaminant exposure
❑ Ecological Risk
NUA - No Unacceptable Risk
Figure 34. Mayo Steam Station - Truck Trips I
o
0
N
n
3 ILII
v
aa a a a a a
> > > > > > > > > > >
z z z m z z z z z z z z
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Implementation Truck Trips -Public Roads
CI P Removal
❑ Public off-site contaminant exposure
• Ecologica I Risk
NUA -No Unacceptable Risk
EPS
1
d
0.75
f6
L
v
O1
u
d
0.5 O
a
C
C
0
L
O
0.25 Q
O
CL
0
1
Cu
0.75 C
R
L
V
N
a.+
Cu
0.5 O
CL
c
O
L
O
0.25 C.
O
CL
0
DCN: HWIDENC001A 53 September 30, 2016
C
W
o
o
Risk
a
a
UA
z
z
z
z
z
z
z
z
z z
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Implementation Truck Trips -Public Roads
High Ris
Y
H
> Moderate
ra
Risk
d
Low Ris
NUA
CI P Removal
❑ Public off-site contaminant exposure
❑ Ecological Risk
NUA - No Unacceptable Risk
Figure 34. Mayo Steam Station - Truck Trips I
o
0
N
n
3 ILII
v
aa a a a a a
> > > > > > > > > > >
z z z m z z z z z z z z
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Implementation Truck Trips -Public Roads
CI P Removal
❑ Public off-site contaminant exposure
• Ecologica I Risk
NUA -No Unacceptable Risk
EPS
1
d
0.75
f6
L
v
O1
u
d
0.5 O
a
C
C
0
L
O
0.25 Q
O
CL
0
1
Cu
0.75 C
R
L
V
N
a.+
Cu
0.5 O
CL
c
O
L
O
0.25 C.
O
CL
0
DCN: HWIDENC001A 53 September 30, 2016

4.2.3 Air Emissions
Figure 35. Allen Steam Station - Air Emissions
0
High Risk
Y
K
Moderate
a Risk
K
Low Risk
¢ a a a = _ _ = a
NUA
MNA
■Groundwater (drinking water consumption)
❑On -Site contaminant exposure
■GHG emissions - tons/yr CO2e emitted
Criteria pollutant emissions - tons/yr of NOx
NUA -No Unacceptable Risk
Hig
Y
K
ar Moderatf
@ RIO
v
Low Ris
NUA
1
0
CIP Removal
Public off-site contaminant exposure
■ Ecological Risk
■ GHG emissions -tons of CO2e emitted
Criteria pollutant emissions -tons/yr of PM 10/2.5
Figure 36. Buck Steam Station - Air Emissions
o a
w �
1
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ GHG emissions - tons/yr CO2e emitted
Criteria pollutant emissions - tons/yr of N Ox
NUA -No Unacceptable Risk
ai
0.75 bo
C
(6
L
U
al
V
v
0.5 O
a`
m
c
0
`O
0.25 a
0
0
CIP Removal
0 Public off-site contaminant exposure
■ Ecologica I Risk
■ GHG emissions - tons of CO2e emitted
Criteria pollutant emissions -tons/yr of PM 10/2.5
0.
EPS
DCN: HWIDENCOOIA 54 September 30, 2016

High Risk
Y
N
jModerate
m
Risk
v
Low Ri,
NU
Figure 37. Cliffside Steam Station - Air Emissions m
o m o
e
m o
3 .3 N ti
k 2 2 v v
z z
z z z z
1
G!
0.75 c
A
t
U
G1
V
41
0.5 O
a
c
0
8
0.25 a
O
CL
0
MNA CIP Removal
■ Groundwater (drinking water consumption) ❑ Public off-site contaminant exposure
❑ On -Site contaminant exposure ■ Ecological Risk
■ GHG emissions -tons/yr CO2e emitted ■ GHG emissions - tons of CO2e emitted
Criteria pollutant emissions -tons/yr of NOx Criteria pollutant emissions -tons/yr of PM 10/2.5
NUA - No Unacceptable Risk
Figure 38. Mayo Steam Station - Air Emissions m
m
o v
High Ris
Y
_N
v
Moderate
@ Risk
v
Low Ris
NUA
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ GHG emissions - tons/yr CO2e emitted
Criteria pollutant emissions -tons/yr of NOx
NUA -No Unacceptable Risk
DCN: HWIDENCOOIA
1
GJ
0.75 c
m
t
U
Y
u
G1
0.5 O
L
m
c
0
O
0.25 0
0
CIP Removal
❑ Public off-site contaminant exposure
■ Ecological Risk
■ GHG emissions - tons of CO2e emitted
Criteria pollutant emissions -tons/yr of PM10/2.5
55
CL
September 30, 2016
N
O
N
V O
O
v a v v
�
a a
z
a = w, .w
m m m m
z z z z
z z z i
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ GHG emissions - tons/yr CO2e emitted
Criteria pollutant emissions -tons/yr of NOx
NUA -No Unacceptable Risk
DCN: HWIDENCOOIA
1
GJ
0.75 c
m
t
U
Y
u
G1
0.5 O
L
m
c
0
O
0.25 0
0
CIP Removal
❑ Public off-site contaminant exposure
■ Ecological Risk
■ GHG emissions - tons of CO2e emitted
Criteria pollutant emissions -tons/yr of PM10/2.5
55
CL
September 30, 2016

4.2.4 Energy Use
High Risk
Y
i
Moderate
a Risk
cc
Low Risk
NUA
High Risk
Y
_N
a Moderate
+� Risk
R
v
Figure 39. Allen Steam Station - Energy Use
MNA CIP Removal
■ Groundwater (drinking water consumption) ❑ Public off-site contaminant exposure
❑ On -Site contaminant exposure ■ Ecological Risk
■ Total Energy - MMBTU Used NUA - No Unaccepta bl a Risk
Low Risk
NUA
Figure 40. Buck Steam Station - Energy Use a
cri
_ N
3
a I� a — a a
MNA
■ Groundwater (dd nking water consumption)
❑ On -Site contaminant exposure
■ Total Energy - MMBTU Used
CIP Removal
f Public off-site contaminant exposure
■ Ecologica I Risk
NUA -No Unacceptable Risk
a
m
C
0.75 z
v
a
U
v
'o
a`
O.5 -Fa
c
0
`0
CL
0
a`
0.25
0
1
v
0.75
C
R
t
V
G/
V
41
0.5 'O
a`
r
c
0
0
0.25 0.
0
CL
0
EPS
DCN: HWIDENCOOIA 56 September 30, 2016

High Risk
Y
> Moderate
Risk
v
Y
Low Risk
NUA
Figure 41. Cliffside Steam Station - Energy Use
I .3 .3-3
a a z z a a 'z z a a
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Total Energy - MMBTU Used
High Risl
K
> Mode
M
v
ate
risk
CIP Removal
❑ Public off-site contaminant exposure
■ Ecological Risk
NUA - No Unacceptable Risk
m
Figure 42. Mayo Steam Station - Energy s
c
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Total Energy - MMBTU Used
CIP Removal
❑ Public off-site contaminant exposure
■ Ecological Risk
NUA -No Unacceptable Risk
1
Gl
0.75 C
M
L
u
d
u
d
0.5 O
CL
ro
c
0
Y
O
0.25 G
0
CL
n
1
d
0.75
L
U
d
u
N
0.5 0
a`
c
0
0
0.25 0-
0
CL
0
0
DCN: HWIDENCOOIA 57 September 30, 2016
3 O
tisk
a
J -
UA
m ��
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Total Energy - MMBTU Used
CIP Removal
❑ Public off-site contaminant exposure
■ Ecological Risk
NUA -No Unacceptable Risk
1
Gl
0.75 C
M
L
u
d
u
d
0.5 O
CL
ro
c
0
Y
O
0.25 G
0
CL
n
1
d
0.75
L
U
d
u
N
0.5 0
a`
c
0
0
0.25 0-
0
CL
0
0
DCN: HWIDENCOOIA 57 September 30, 2016

4.2.5 Ecological Habitat Services
Figure 43. Allen Steam Station - Ecological Habitat Service Losses
High Risk
Y
K
J
Moderate
a
Risk
Low Risk
NUA
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Terrestrial Habitat Value -lost dSAYs
■ Overall Ecological Habitat Value -lost dSAYs
High Risk
W
d
Moderate
—y Risk
Low Risk
NUA
MINA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Terrestrial Habitat Value - lost dSAYs
■ Overa II Ecological Habitat Value - lost dSAYs
CI P Removal
i] Public off-site contaminant exposure
■ Ecological Risk
Aquatic Habitat Value - lost dSAYs
NUA - No Unacceptable Risk
Figure 44. Buck Steam Station - Ecological Habitat Service Losses
o
3
a a a — — — a a a a a a a a
CI P Removal
❑ Public off-site contaminant exposure
■ Ecological Risk
Aquatic Habitat Value - lost dSAYs
NUA - No Unacceptable Risk
t
Q)
NO
C
M
0.75 L
V
'0
O/
u
G1
O
a`
0.5 q
c
0
0
CL
0
a`
025
I
0.25
0
0
a
0
CPS]-
4.2.5
PS
DCN: HWIDENCOOIA 58 September 30, 2016

High Risk
Y
N
W
Moderate
Risk
a
Low Risk
NUA
Figure 45. Cliff side Steam Station - Ecological Habitat Service Losses
0
a . o
rri
1
MNA CIP Removal
■ Groundwater (drinking water consumption) 0 Public off-site contaminant exposure
❑ On -Site contaminant exposure 0 Ecological Risk
■ Terrestrial Habitat Value - lost dSAYs Aquatic Habitat Value - lost dSAYs
■ Overall Ecological Habitat Value - lost dSAYs NUA - No Una ccepta bl a Ri s
Figure 46. Mayo Steam Station - Ecological Habitat Service Losses
N
N
o
High Ri
Y
N
OC
v
Moderat
m Ris
v
Low Ri
NU
k
m
3
3
a
z
z
z
m m
z z
z
z
z
z z
kv v v
¢ ¢ a 'yw —
a a a a
MNA CIP Removal
■ Groundwater (drinking water consumption) 0 Public off-site contaminant exposure
❑ On -Site contaminant exposure 0 Ecological Risk
■ Terrestrial Habitat Value - lost dSAYs Aquatic Habitat Value - lost dSAYs
■ Overall Ecological Habitat Value - lost dSAYs NUA - No Una ccepta bl a Ri s
Figure 46. Mayo Steam Station - Ecological Habitat Service Losses
N
N
o
High Ri
Y
N
OC
v
Moderat
m Ris
v
Low Ri
NU
k
m
c
a
kv v v
¢ ¢ a 'yw —
a a a a
a a
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Terrestrial Habitat Value - lost dSAYs
■ Overall Ecological Habitat Value - lost dSAYs
DCN: HWIDENCOOIA
CIP Removal
0 Public off-site contaminant exposure
■ Ecological Risk
Aquatic Habitat Value - lost dSAYs
NUA - No Unacceptable Risk
59
v
ao
c
0.75 m
s
u
v
v
'o
0.5 a
c
0
0
0.25 0
0
0
1
CL
W
c
0.75
s
u
G!
u
N
'O
0.5 a
c
0
O
Q
0.25 2
a
0
EPS
September 30, 2016

4.2.6 Costs
High Risk
Y
41
" Moderate
v Risk
Low Ri
NU
Figure 47. Allen Steam Station - Cost
k
a a a a a a a a a a a a
a z z z z z z z z z z z z
MNA CI P Removal
■ Groundwater (drinking water consumption) E3 Public off-site contaminant exposure
❑ On -Site contaminant exposure ■ Ecological Risk
■Capital Cost -Net Present Value (Millions) NUA - No Unacceptable Risk
High Risk
Y
N_
i Moderate
io
Risk
CU
Low Risk
NUA
Figure 48. Buck Steam Station - Cost
3
a
n
z z z z z
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Capital Cost- Net Present Value (Millions)
CI P Removal
❑ Public off-site contaminant exposure
■ Ecological Risk
NUA -No Una cceptableRisk
i
v
00
c
M
0.75 s
v
v
v
V
d
O
a`
0.5 p
c
0
`o
a
0
CL
0.25
0
1
v
0.75 W
C
M
L
U
d
U
a
0.5 O
CL
c
0
0
0.25 0.
0
CL
0
EPS
DCN: HWIDENCOOIA 60 September 30, 2016

High Risk
Y
H
OC
Moderate
+, Risk
m
v
Low Risk
NUA
Figure 49. Cliffside Steam Station - Cost
MNA
■ Groundwater (drinkingwater consumption)
0 On -Site contaminant exposure
■ Capital Cost- Net Present Value (Millions)
High Risk
Y
y Moderate
Risk
v
Low Risk
NUA
CIP Removal
E3 Public off-site contaminant exposure
■ Ecological Risk
NUA -No Unacceptable Risk
Figure 50. Mayo Steam Station - Cost
n
3
aanam =___�
z z z
z
MNA
■ Groundwater (drinking water consumption)
0 On -Site contaminant exposure
■ Capital Cost -Net Present Value (Millions)
CIP Removal
* Public off-site contaminant exposure
■ Ecological Risk
NUA - No Unacceptable Risk
i
ar
0.75 r_
L
V
al
V
Au
0.5 O
a`
m
c
0
`o
0.25 a
0
a
0
I
ai
0.75
A
L
U
a1
u
A)
0.5 O
L
c
0
Y
O
0.25 a
0
a
0
i EPS
DCN: HWIDENCOOIA 61 September 30, 2016
-
-
r`
m
Z
Z
N
Z
Z
Z
Z
MNA
■ Groundwater (drinkingwater consumption)
0 On -Site contaminant exposure
■ Capital Cost- Net Present Value (Millions)
High Risk
Y
y Moderate
Risk
v
Low Risk
NUA
CIP Removal
E3 Public off-site contaminant exposure
■ Ecological Risk
NUA -No Unacceptable Risk
Figure 50. Mayo Steam Station - Cost
n
3
aanam =___�
z z z
z
MNA
■ Groundwater (drinking water consumption)
0 On -Site contaminant exposure
■ Capital Cost -Net Present Value (Millions)
CIP Removal
* Public off-site contaminant exposure
■ Ecological Risk
NUA - No Unacceptable Risk
i
ar
0.75 r_
L
V
al
V
Au
0.5 O
a`
m
c
0
`o
0.25 a
0
a
0
I
ai
0.75
A
L
U
a1
u
A)
0.5 O
L
c
0
Y
O
0.25 a
0
a
0
i EPS
DCN: HWIDENCOOIA 61 September 30, 2016

0
4.2.7 Each Site - Data Combined
This section provides a comparison, based on the evaluation conducted herein, of the potential
impacts of the CIP and Removal alternatives in relation to one another and the MMA alternative
for each site.
4.2.7.1 Allen Steam Station
As can be seen in Figure 51, the Removal alternative provides significantly more adverse impacts
when compared to the CIP alternative, without providing a meaningful reduction in risk. In
addition, the CIP alternative is projected to provide significantly more impacts when compared to
the NINA alternative, without providing a meaningful reduction in risk.
High Ris
GJ
Moderat
M Ris
v
Low Ris
NU
k
e
k
0
cn
O
n
n
o� M
a
co
o
Risk
Figure 51. Allen Steam Station - Summary
p O N
nvrio 06�rvn�
N O Of N M" M N V N
�O��O � OlOtp V I� NOt
A
CIP Removal
■ Groundwater (drinking water consumption)
❑ Public off-site contaminant exposure
❑ On -Site contaminant exposure
■ Ecological Risk
■ Truck traffic incidents - Fatalities
■ Truck traffic incidents - Injuries/Illness
Truck traffic incidents - property damage only
Implementation risks - Fatalities
■ Implementation risks - Injuries/Illness
■ Implementation Truck Trips - Public Roads
■ GHG emissions - tons/yr CO2e emitted
■ GHG emissions - tons of CO2e emitted
Criteria pollutant emissions -tons/yr of NOx
Criteria pollutant emissions -tons/yr of PM10/2.5
® Total Energy - MMBTU Used
■ Terrestrial Habitat Value - lost dSAYs
Aquatic Habitat Value - lost dSAYs
■ Overall Ecological Habitat Value - lost dSAYs
■ Capital Cost- Net Present Value (Millions)
aaaa`vv`-
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-A
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1
0.75
0.5
0.25
0
MNA
CIP Removal
■ Groundwater (drinking water consumption)
❑ Public off-site contaminant exposure
❑ On -Site contaminant exposure
■ Ecological Risk
■ Truck traffic incidents - Fatalities
■ Truck traffic incidents - Injuries/Illness
Truck traffic incidents - property damage only
Implementation risks - Fatalities
■ Implementation risks - Injuries/Illness
■ Implementation Truck Trips - Public Roads
■ GHG emissions - tons/yr CO2e emitted
■ GHG emissions - tons of CO2e emitted
Criteria pollutant emissions -tons/yr of NOx
Criteria pollutant emissions -tons/yr of PM10/2.5
® Total Energy - MMBTU Used
■ Terrestrial Habitat Value - lost dSAYs
Aquatic Habitat Value - lost dSAYs
■ Overall Ecological Habitat Value - lost dSAYs
■ Capital Cost- Net Present Value (Millions)
NUA -No Unacceptable Risk
G1
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v
v
d
0
L
a
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0
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0
0-
0
L
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DCN: HWIDENCOOIA 62 September 30, 2016

0
A comparison of the human health risk driving the remedial action and the risks projected from
implementation of the alternatives follows. The human health risks associated with
implementing either the CIP or Removal alternatives at Allen Steam Station far outweigh
the human health risks that are driving a remedy in the first place. By way of example, this
assertion is supported in Figure 52 and by the following:
The chance that someone may get cancer due to exposure to chemicals at the site (without
any active remediation) is 5E-8, assuming the scenario evaluated. This means that if one
hundred million people have significant exposure to chemicals at the site, that five of them
might get cancer (or 5 of 100,000,000). To put this into perspective, the American Cancer
Society estimates the lifetime risk for a male to develop some type of cancer in their
lifetime is 43.31% (or 433,100 out of 1,000,000 people)9. There will be far fewer than
100,000,000 people with exposure at the site; if one assumes that 100 people have
exposure, then approximately 0.000005 people would have an increased risk of getting
cancer.
• Although it is unlikely that someone would get cancer due to exposure at the site, there is
a real likelihood that people would be injured and possibly die under either of the two
active remedial alternatives (i.e., CIP or Removal). There is a statistical likelihood that 12
people would be injured and 0.17 people might die under the capping scenario at Allen
Steam Station. Similarly, it is likely that 80 people would be injured and 0.91 might die
under the Removal scenario.
• There is also a risk to human health from breathing in pollutants emitted into the air due to
implementation of the remedial alternatives. The EPA has established threshold levels for
air emissions that are to be protective of human health. In the case of NOX, the emissions
under the Removal alternative are 3.6 times higher than the permitting threshold
established by the USEPA to be protective of the National Ambient Air Quality Standard.
This means there is a real likelihood that persons working at the site or along the
transportation route could incur health impacts as a result of the implementing the Removal
alternative. High NOX levels can result in causing or worsening respiratory disease (such
as emphysema and bronchitis), aggravating existing heart disease, and increased hospital
admissions and premature deaths10. These impacts would disproportionately affect
minority and economically disadvantaged people, as statistics show that such communities
are more likely to live within close proximity to the routes on which trucks would transport
material from the site to a disposal area". This raises significant environmental justice
concerns.
9 http://www.cancer.org/cancer/cancerbasics/lifetime-probability-of-developing-or-dying-from-cancer
i0 https://www3.epa.gov/airquality/nitrogenoxides/health.html
"htlps://www3.epa. og v/airqualiiy/nitroizenoxides/health.html
https://www.cdc.gov/mmwr/preview/mmwrhtml/su6203a8.htm
DCN: HWIDENCOOIA 63 September 30, 2016

Figure 52. Allen Steam Station
Number of Persons with Negative Health Impacts Projected for Proposed
Alternatives
80.2
IV
CL
0
v
a
w
0
L
a
�C
C
Z 12.4
5.00E-06 1.00E-06 0.17 1.00E-08 0.91
Cancer * Fatality Injury
Cancer * Fatality Injury
Cancer * Fatality Injury
MNA
CIP
Removal
* chemical exposure on-site
excludes health impacts due to air pollution
In regard to other impacts on the nearby community, such as noise, nuisance, etc., and
overarching climate impacts, it should be recognized that:
• The duration of the CIP and the Removal alternatives is projected to take a minimum of
5.2 and 35.7 years, respectively;
• The evaluation estimated a projected number of truck trips on nearby public roads in the
local community of over 140,401 and 996,795, for the CIP and Removal alternatives,
respectively, over the life of the projects;
• The energy consumption of each alternative is equivalent to the energy expenditure of
1,800 and 9,700 personal vehicles commuting five days a week for the duration of the CIP
and Removal alternatives, respectively;
• The estimated costs of the CIP and the Removal alternatives are projected to be about
$162.2 Million and $1.55 Billion, respectively;
• The projected yearly GHG emissions would exceed the USEPA established reporting
threshold for the Removal alternative (Figure 53a).
• The projected yearly NO, emissions would exceed the USEPA established threshold for
major modifications under the Prevention of Significant Deterioration program for the
Removal alternative (Figure 53b). -
In comparing the ecological risks to the ecological injury projected from implementation of the
alternatives, the ecological injury associated with implementing either the CIP or Removal
alternatives at the Allen Steam Station far outweigh any ecological risks predicted with
chemical concentrations.
12 The significance levels in the Prevention of Significant Deterioration program are cited for an order of magnitude
comparison. I take no position on whether the activity in fact triggers the requirement for a PSD permit.
DCN: HWIDENC001A 64 September 30, 2016

EPS
The basic NEBA conducted herein indicates that implementation of the CIP and Removal
alternatives increase fatality, injury, health/illness and property damage risks of the local
community, increase community nuisance such as noise and pollution, and increase ecological
habitat destruction. As such, Intervenors' proposal for Removal is unjustified and, from a net
benefit analysis, detrimental.
35,000
: 30,000
d
W25,000
c0
}
QJ 20,000
N
0
V
C 15,000
F
C10,000
.
H
E
W 5,000
2
C7
0
T
Figure 53a. GHG Emissions projected by remedial alternative compared to
the GHG Reporting Threshold for Allen Steam Station
7,376
0
30,940
MINA CIP Removal
GHG emissions-tons/yr CO2e emitted
-GHG Reporting Threshold (25,000 tons)
Figure 53b. NO, Emissions projected by remedial alternative compared to
IL- w1l1 n.....Y:rr.._.. TL......L-IJ C-- n II-- ea.._.Y
IVIIVH Ur Kemoval
Criteria pollutant emissions -tons/yrof Nox
-NOx Permitting Threshold (40 Tons)
DCN: HWIDENC001A 65 September 30, 2016

0
4.2.7.2 Buck Steam Station
As can be seen in Figure 54, the Removal alternative provides significantly more adverse impacts
when compared to the CIP alternative, without providing a meaningful reduction in risk. In
addition, the CIP alternative is projected to provide significantly more impacts when compared to
the NINA alternative, without providing a meaningful reduction in risk.
High Risk
Y
N
al
> Moderate
f6 Risk
v
Low Risk
NU..
Figure 54. Buck Steam Station - Summary
M
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Ot Of m01 � �
0
O N
� N
n
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mm mmmommm mm mm m`"
zzzz
MNA CIP
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Truck traffic incidents -Fatalities
Truck traffic incidents - property damage only
■ Implementation risks - Injuries/Illness
■ GHG emissions - tons/yr CO2e emitted
Criteria pollutant emissions -tons/yr of NOx
E Total Energy - MMBTU Used
Aquatic Habitat Value - lost cISAYs
■ Capital Cost- Net Present Value (Millions)
Removal
ai
ao
0.75 C
t
V
aJ
N
u
aJ
0.5 O
a`
c
O
L
O
0.25 CL
O
a`
❑ Public off-site contaminant exposure
■ Ecological Risk
■ Truck traffic incidents - Injuries/Illness
Implementation risks - Fatalities
■ Implementation Truck Trips - Public Roads
■ GHG emissions - tons of CO2e emitted
Criteria pollutant emissions -tons/yrof PM10/2.5
■ Terrestrial Habitat Value - lost cISAYs
■ Overall Ecological Habitat Value - lost cISAYs
NUA -No Unacceptable Risk
A comparison of the human health risk driving the remedial action and the risks projected from
implementation of the alternatives follows. The human health risks associated with
implementing either the CIP or Removal alternatives at Buck Steam Station far outweigh
the human health risks that are driving a remedy in the first place. By way of example, this
assertion is supported in Figure 55 and by the following:
• The chance that someone may get cancer due to exposure to chemicals at the site (without
any active remediation) is 2E-6, assuming the scenario evaluated. This means that if one
million people have significant exposure to chemicals at the site, that two of them might
DCN: HWIDENCOOIA 66 September 30, 2016

0
get cancer (or 2 of 1,000,000). To put this into perspective, the American Cancer Society 13
estimates the lifetime risk for a male to develop some type of cancer in their lifetime is
43.31% (or 433,100 out of 1,000,000 people). There will be far fewer than 1,000,000
people with exposure at the site; if one assumes that 100 people have exposure, then
approximately 0.0002 people would have an increased risk of getting cancer.
• Although it is unlikely that someone would get cancer due to exposure at the site, there is
a real likelihood that people would be injured and possibly die due to active remediation
(i.e., capping or Removal). There is a statistical likelihood that 8 people would be injured
and 0.1 people might die under the capping scenario at Buck Steam Station. Similarly, it
is likely that 24 people would be injured and 0.27 might die under the Removal scenario.
• There is also a risk to human health from breathing in pollutants emitted into the air due to
implementation of the remedial alternatives. In the case of NO,, the emissions under the
Removal alternative are 3.6 times higher than the permitting threshold established by the
USEPA to be protective of the National Ambient Air Quality Standard. This means there
is a real likelihood that persons working at the site or along the transportation route could
incur health impacts as a result of the implementing the Removal alternative. High NO,
levels can result in causing or worsening respiratory disease (such as emphysema and
bronchitis), aggravating existing heart disease, and increased hospital admissions and
premature deaths14. These impacts would disproportionately affect minority and
economically disadvantaged people, as statistics show that such communities are more
likely to live within close proximity to the routes on which trucks would transport material
from the site to a disposal area15. This raises significant environmental justice concerns.
Figure 55. Buck Steam Station
Numberof Persons with Negative Health Impacts Projected for Proposed
Alternatives
v
a
0
v
a
0
v
E
0
Z 0.0002
'ITINTITIT1111111111111111111=1
Cancer * Fatality Injury I Cancer * Fatality
MNA I CIP
* chemical exposure on-site
excludes health impacts due to air pollution
24.3
7
0.0000006 0.27
Injury Cancer * Fatality Injury
Re mova I
13 http://www.cancer.org/cancer/cancerbasics/lifetime-probability-of-developing-or-dying-from-cancer
14 https://www3.epa.aov/airgualiiy/nitrogenoxides/health.html
"https://www3.epa. og v/airgualiiy/nitrolzenoxides/health.html
https://www.cdc.gov/mmwr/preview/mmwrhtml/su6203a8.httn
DCN: HWIDENC001A 67 September 30, 2016

0
In regard to other impacts on the nearby community, such as noise, nuisance, etc., it should be
recognized that:
• The duration of the CIP and the Removal alternatives is projected to take a minimum of
3.3 and 9.8 years, respectively;
• The evaluation estimated a projected number of truck trips on nearby public roads in the
local community of over 88,109 and 276,968 for the CIP and Removal alternatives,
respectively, over the life span of each project;
• The energy consumption of each alternative is equivalent to the energy expenditure of
1,800 and 9,700 personal vehicles commuting five days a week for the duration of the CIP
and Removal alternatives, respectively;
• The estimated costs of the CIP and the Removal alternatives are projected to be about $92.1
Million and $452.8 Million, respectively;
• The projected yearly GHG emissions would exceed the USEPA established reporting
threshold for the Removal alternative (Figure 56a).
• The projected yearly NOX emissions would exceed the USEPA established threshold for
major modifications under the Prevention of Significant Deterioration program for the
Removal alternative (Figure 56b)16
35,000
30,000
Y
Y
E
W 25,000
d
N 20,000
0
V
C
i—O 15,000
C
O
10,000
E
w
l7
= 5,000
l7
Figure 56a. GHG Emissions projected by remedial alternative compared to
ine c nc, KeDorting I nresnoia - DUCK steam mation
30,955
7,377
MNA CIP Removal
�GHG emissions - tons/yr CO2e emitted
-GHG Reporting Threshold (25,000 tons)
16 The significance levels in the Prevention of Significant Deterioration program are cited for an order of magnitude
comparison. I take no position on whether the activity in fact triggers the requirement for a PSD permit.
DCN: HWIDENCOOlA 68 September 30, 2016

160
N
140
W
120
N
X
O 100
Z
c 80
O
F
C 60
O
LU 40
x
O
Z 20
Figure 56b. NO,, Emissions projected by remedial alternative compared to
the NO, Permitting Threshold for Buck Steam Station
29
0
MNA CIP Removal
Criteria pollutant emissions -tons/yr of NOx
_NOx Permitting Threshold (40 Tons)
EPS
In comparing the ecological risks to the ecological injury projected from implementation of the
alternatives, the ecological injury associated with implementing either the CIP or Removal
alternatives at the Buck Steam Station far outweigh any ecological risks predicted with
chemical concentrations.
The basic NEBA conducted herein indicates that implementation of the CIP and Removal
alternatives increase fatality, injury, health/illness and property damage risks of the local
community, increase community nuisance such as noise and pollution, and increase ecological
habitat destruction. These impacts appear to outweigh the human and ecological risks that are
driving the remediation in the first place. As such, Intervenors' proposal for Removal is unjustified
and, from a net benefit analysis, detrimental.
DCN: HWIDENCOOIA 69 September 30, 2016

0
4.2.7.3 Cliffside Steam Station
As can be seen in Figure 57, the Removal alternative provides significantly more adverse impacts
when compared to the CIP alternative, without providing a meaningful reduction in risk. In
addition, the CIP alternative is projected to provide significantly more impacts when compared to
the NINA alternative, without providing a meaningful reduction in risk.
High Risk
Y
v
> Moderate
Risk
co
v
Low Risk
NUA
Figure 57. Cliffside Steam Station - Summary
n e+ o e w
rvm �°'r rvma�MN
onrvor�a����rv�`t-imw
MNA
■Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Truck traffic incidents - Fatalities
Truck traffic incidents - property damage only
■ Implementation risks - Injuries/Illness
■ GHG emissions - tons/yr CO2e emitted
Criteria pollutant emissions -tons/yr of NOx
® Total Energy - MMBTU Used
Aquatic Habitat Value - lost dSAYs
■ Capital Cost- Net Present Value (Millions)
CIP Removal
Q)
tw
c
0.75
s
v
Gl
u
N
0-
0.5
0.5 a`
is
c
O
E
O
O.
0.25 O
a
❑ Public off-site contaminant exposure
■ Ecological Risk
■ Truck traffic incidents -Injuries/Illness
Implementation risks - Fatalities
■ Implementation Truck Trips - Public Roads
■ GHG emissions - tons of CO2e emitted
Criteria pollutant emissions - tons/yr of PM 10/2.5
■Terrestrial Habitat Value - lost dSAYs
■ Overall Ecological Habitat Value - lost dSAYs
NUA - No Una cceptableRisk
A comparison of the human health risk driving the remedial action and the risks projected from
implementation of the alternatives follows. The human health risks associated with
implementing either the CIP or Removal alternatives at Cliffside Steam Station far outweigh
the human health risks that are driving a remedy in the first place. By way of example, this
assertion is supported in Figure 58 and by the following:
0 The chance that someone may get cancer due to exposure to chemicals at the site (without
any active remediation) is 2E-6, assuming the scenario evaluated. This means that if one
million people have significant exposure to chemicals at the site, that two of them m
DCN: HWIDENCOOIA 70 September 30, 2016
a
0
0
a
O1 a
J
w w
a v m w a w a w
> >>
ZZ
M..
� ZZZZ
ZZZZ
MNA
■Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Truck traffic incidents - Fatalities
Truck traffic incidents - property damage only
■ Implementation risks - Injuries/Illness
■ GHG emissions - tons/yr CO2e emitted
Criteria pollutant emissions -tons/yr of NOx
® Total Energy - MMBTU Used
Aquatic Habitat Value - lost dSAYs
■ Capital Cost- Net Present Value (Millions)
CIP Removal
Q)
tw
c
0.75
s
v
Gl
u
N
0-
0.5
0.5 a`
is
c
O
E
O
O.
0.25 O
a
❑ Public off-site contaminant exposure
■ Ecological Risk
■ Truck traffic incidents -Injuries/Illness
Implementation risks - Fatalities
■ Implementation Truck Trips - Public Roads
■ GHG emissions - tons of CO2e emitted
Criteria pollutant emissions - tons/yr of PM 10/2.5
■Terrestrial Habitat Value - lost dSAYs
■ Overall Ecological Habitat Value - lost dSAYs
NUA - No Una cceptableRisk
A comparison of the human health risk driving the remedial action and the risks projected from
implementation of the alternatives follows. The human health risks associated with
implementing either the CIP or Removal alternatives at Cliffside Steam Station far outweigh
the human health risks that are driving a remedy in the first place. By way of example, this
assertion is supported in Figure 58 and by the following:
0 The chance that someone may get cancer due to exposure to chemicals at the site (without
any active remediation) is 2E-6, assuming the scenario evaluated. This means that if one
million people have significant exposure to chemicals at the site, that two of them m
DCN: HWIDENCOOIA 70 September 30, 2016

0
get cancer (or 2 of 1,000,000). To put this into perspective, the American Cancer Society"
estimates the lifetime risk for a male to develop some type of cancer in their lifetime is
43.31% (or 433,100 out of 1,000,000 people). There will be far fewer than 1,000,000
people with exposure at the site; if one assumes that 100 people have exposure, then
approximately 0.0002 people would have an increased risk of getting cancer.
• Although it is unlikely that someone would get cancer due to exposure at the site, there is
a real likelihood that people would be injured and possibly die due to active remediation
(i.e., capping or Removal). There is a statistical likelihood that 7 people would be injured
and 0.1 people might die under the capping scenario at Cliffside Steam Station. Similarly,
it is likely that 35 people would be injured and 0.39 might die under the Removal scenario.
• There is also a risk to human health from breathing in pollutants emitted into the air due to
implementation of the remedial alternatives. In the case of NOx, the emissions under the
Removal alternative are 3.6 times higher than the permitting threshold established by the
USEPA to be protective of the National Ambient Air Quality Standard. This means there
is a real likelihood that persons working at the site or along the transportation route could
incur health impacts as a result of the implementing the Removal alternative. High NOx
levels can result in causing or worsening respiratory disease (such as emphysema and
bronchitis), aggravating existing heart disease, and increased hospital admissions and
premature deaths'$. These impacts would disproportionately affect minority and
economically disadvantaged people, as statistics show that such communities are more
likely to live within close proximity to the routes on which trucks would transport material
from the site to a disposal area19. This raises significant environmental justice concerns.
Figure 58. Cliffside Steam Station
Number of Persons with Negative Health Impacts Projected for Proposed
Alternatives
34.9
ai
Q.
0
a,
a
0
L
ai
7.3
z
0.0002 0.00006 0.1 0.0000004 0.39
Cancer * Fatality Injury Cancer * Fatality Injury I Cancer* Fatality Injury
MNA CIP I Removal
* chemical exposure on-site
excludes health impacts due to air pollution
17 http://www.cancer.org/cancer/cancerbasics/lifetime-probability-of-developing-or-dying-from-cancer
18 https://www3.epa. og v/airqualiiy/nitrogenoxides/health.html
19hllps://www3.epa. og v/airquali , /nitrogenoxides/health.html
https://www.cdc.gov/mmwr/preview/mmwrhtml/su6203a8.htm
DCN: HWIDENCOOIA 71 September 30, 2016

0
In regard to other impacts on the nearby community, such as noise, nuisance, etc., it should be
recognized that:
• The duration of the CIP and the Removal alternatives is projected to take a minimum of
3.0 and 14.6 years, respectively;
• The evaluation estimated a projected number of truck trips on nearby public roads in the
local community of over 82,459 and 410,279 for the CIP and Removal alternatives,
respectively, over the life span of each project;
• The energy consumption of each alternative is equivalent to the energy expenditure of
1,800 and 9,700 personal vehicles commuting five days a week for the duration of the CIP
and Removal alternatives, respectively;
• The estimated costs of the CIP and the Removal alternatives are projected to be about $95.7
Million and $658.8 Million, respectively.
• The projected yearly GHG emissions would exceed the USEPA established reporting
threshold for the Removal alternative (Figure 59a).
• The projected yearly NOX emissions would exceed the USEPA established threshold for
major modifications under the Prevention of Significant Deterioration program for the
Removal alternative (Figure 59b)20.
Figure 59a. GHG Emissions projected by remedial alternative compared to
the UHU Keporting i nresnow Tor UnrTsiae steam station
35,000
O/
+• 30,000
W
25,000
}
v
N
0 20,000
C
O
H
N 15,000
C
O
E 10,000
W
C7
2
l7 5,000
0
7,446
30,939
MNA CIP Removal
�GHG emissions - tons/yr CO2e emitted
-GHG Reporting Threshold (25,000 tons)
20 The significance levels in the Prevention of Significant Deterioration program are cited for an order of magnitude
comparison. I take no position on whether the activity in fact triggers the requirement for a PSD permit.
DCN: HWIDENCOOIA 72 September 30, 2016

0
In comparing the ecological risks to the ecological injury projected from implementation of the
alternatives, the ecological injury associated with implementing either the CIP or Removal
alternatives at the Cliffside Steam Station far outweigh any ecological risks predicted with
chemical concentrations.
160
a 140
d
a.+
w
120
v
100
x
O
z
c
80
0
r
60
0
.N
E 40
UJ
x
O
z zo
0
Figure 59b. NO. Emissions projected by remedial alternative compared to
the NU, Permitting I nresnoia Tor Clittsiae Steam Jtation
29
0
14
MNA CIP Removal
Criteria pollutant emissions - tons/yr of NOx
NOx Permitting Threshold (40 Tons)
The basic NEBA conducted herein indicates that implementation of the CIP and Removal
alternatives increase fatality, injury, health/illness and property damage risks of the local
community, increase community nuisance such as noise and pollution, and increase ecological
habitat destruction. These impacts appear to outweigh the human and ecological risks that are
driving the remediation in the first place. As such, Intervenors' proposal for Removal is unjustified
and, from a net benefit analysis, detrimental.
DCN: HWIDENCOOIA 73 September 30, 2016

0
4.2.7.4 Mayo Steam Station
As can be seen in Figure 60, the Removal alternative provides significantly more adverse impacts
when compared to the CIP alternative, without providing a meaningful reduction in risk. In
addition, the CIP alternative is projected to provide significantly more impacts when compared to
the NINA alternative, without providing a meaningful reduction in risk.
A comparison of the human health risk driving the remedial action and the risks projected from
implementation of the alternatives follows. The human health risks associated with
implementing either the CIP or Removal alternatives at Mayo Steam Station far outweigh
the human health risks that are driving a remedy in the first place. By way of example, this
assertion is supported in Figure 61 and by the following:
High Risk
G1
>_ Moderate
c*o Risk
d
Low Risk
NUA
Figure 60. Mayo Steam Station - Summary
m �
Nv1 -O ti00NMN
O.O NO Nt�+l M.O-i .ai SON VT
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Truck traffic incidents - Fatalities
Truck traffic incidents - property damage only
■ Implementation risks - Injuries/Illness
■ GHG emissions - tons/yr CO2e emitted
Criteria pollutant emissions - tons/yr of NOx
M Total Energy - MMBTU Used
Aquatic Habitat Value - lost cISAYs
■ Capital Cost- Net Present Value (Millions)
CIP Removal
v
as
c
0.75 m
s
v
Gl
U
G1
0-
0.5
0.5 a
�a
c
0
L
O
0.
0.25 p
a
❑ Public off-site contaminant exposure
■ Ecological Risk
■ Truck traffic incidents -Injuries/Illness
Implementation risks - Fatalities
■ Implementation Truck Trips - Public Roads
■ GHG emissions - tons of CO2e emitted
Criteria pollutant emissions -tons/yrof PM10/2.5
■ Terrestrial Habitat Value - lost cISAYs
■ Overall Ecological Habitat Value - lost cISAYs
NUA - No Una cceptableRisk
• The chance that someone may get cancer due to exposure to chemicals at the site (without
any active remediation) is 3E-6, assuming the scenario evaluated. This means that if one
million people have significant exposure to chemicals at the site, that three of them might
DCN: HWIDENCOOIA 74 September 30, 2016
0
O N
N M
o. m vO1i ^ a
v� `ion
m
o
J
.
"
zz
>„
z�mmmmmmmmmmmm
»»
zzzz
»»
zzzz
MNA
■ Groundwater (drinking water consumption)
❑ On -Site contaminant exposure
■ Truck traffic incidents - Fatalities
Truck traffic incidents - property damage only
■ Implementation risks - Injuries/Illness
■ GHG emissions - tons/yr CO2e emitted
Criteria pollutant emissions - tons/yr of NOx
M Total Energy - MMBTU Used
Aquatic Habitat Value - lost cISAYs
■ Capital Cost- Net Present Value (Millions)
CIP Removal
v
as
c
0.75 m
s
v
Gl
U
G1
0-
0.5
0.5 a
�a
c
0
L
O
0.
0.25 p
a
❑ Public off-site contaminant exposure
■ Ecological Risk
■ Truck traffic incidents -Injuries/Illness
Implementation risks - Fatalities
■ Implementation Truck Trips - Public Roads
■ GHG emissions - tons of CO2e emitted
Criteria pollutant emissions -tons/yrof PM10/2.5
■ Terrestrial Habitat Value - lost cISAYs
■ Overall Ecological Habitat Value - lost cISAYs
NUA - No Una cceptableRisk
• The chance that someone may get cancer due to exposure to chemicals at the site (without
any active remediation) is 3E-6, assuming the scenario evaluated. This means that if one
million people have significant exposure to chemicals at the site, that three of them might
DCN: HWIDENCOOIA 74 September 30, 2016

0
get cancer (or 3 of 1,000,000). To put this into perspective, the American Cancer Society,I
estimates the lifetime risk for a male to develop some type of cancer in their lifetime is
43.31% (or 433,100 out of 1,000,000 people). There will be far fewer than 1,000,000
people with exposure at the site; if one assumes that 100 people have exposure, then
approximately 0.0003 people would have an increased risk of getting cancer.
• Although it is unlikely that someone would get cancer due to exposure at the site, there is
a real likelihood that people would be injured and possibly die due to active remediation
(i.e., capping or Removal). There is a statistical likelihood that 6 people would be injured
and 0.08 people might die under the capping scenario at Mayo Steam Station. Similarly,
it is likely that 30 people would be injured and 0.32 might die under the Removal scenario.
• There is also a risk to human health from breathing in pollutants emitted into the air due to
implementation of the remedial alternatives. The EPA has established threshold levels for
air emissions that are to be protective of human health. In the case of NOx, the emissions
under the Removal alternative are 3.6 times higher than the permitting threshold
established by the USEPA to be protective of the National Ambient Air Quality Standard.
This means there is a real likelihood that persons working at the site or along the
transportation route could incur health impacts as a result of the implementing the Removal
alternative. High NOx levels can result in causing or worsening respiratory disease (such
as emphysema and bronchitis), aggravating existing heart disease, and increased hospital
admissions and premature deaths22. These impacts would disproportionately affect
minority and economically disadvantaged people, as statistics show that such communities
are more likely to live within close proximity to the routes on which trucks would transport
material from the site to a disposal area 23. This raises significant environmental justice
concerns.
W
CL
0
v
a
0
0
v
E
3
Z
Figure 61. Mayo Steam Station
Number of Persons with Negative Health Impacts Projected for Proposed
Alternatives
0.0003 0.00007 0.08
Cancer * Fatality Injury Cancer * Fatality
MNA CIP
* chemical exposure on-site
excludes health impacts due to air pollution
5.9
0 0.32
29.6
Injury Cancer * Fatality Injury
Removal
21 http://www.cancer.org/cancer/cancerbasics/lifetime-probability-of-developing-or-dying-from-cancer
22 https://www3.epa. og v/airqualiiy/nitrogenoxides/health.html
23https://www3.epa. og v/airquali , /nitrogenoxides/health.html
https://www.cdc.gov/mmwr/preview/mmwrhtml/su6203a8.htm
DCN: HWIDENCOOIA 75 September 30, 2016

0
In regard to other impacts on the nearby community, such as noise, nuisance, etc., it should be
recognized that:
• The duration of the CIP and the Removal alternatives is projected to take a minimum of
2.5 and 12.2 years, respectively;
• The evaluation estimated a projected number of truck trips on nearby public roads in the
local community of over 66,720 and 343,813 for the CIP and Removal alternatives,
respectively, over the life span of each project;
• The energy consumption of each alternative is equivalent to the energy expenditure of
1,800 and 9,700 personal vehicles commuting five days a week for the duration of the CIP
and Removal alternatives, respectively;
• The estimated costs of the CIP and the Removal alternatives are projected to be about $77.7
Million and $555.2 Million, respectively.
• The projected yearly GHG emissions would exceed the USEPA established reporting
threshold for the Removal alternative (Figure 62a).
35,000
d
30,000
E
W
y 25,000
Y
W
N
0 20,000
C
F
n 15,000
C
O
.N
ti
10,000
W
0
Figure 62a. GHG Emissions projected by remedial alternative compared to
the GHG Reporting Threshold for Mayo Steam Station
7,322
0
30,953
MNA CIP Removal
GHG emissions - tons/yr CO2e emitted
-GHG Reporting Threshold (25,000 tons)
DCN: HWIDENCOOIA 76 September 30, 2016

0
• The projected yearly NOx emissions would exceed the USEPA established threshold for
major modifications under the Prevention of Significant Deterioration program for the
Removal alternative (Figure 62b)24.
160
G1
140
W
L
M 120
X
O
Z 100
H80
N
v� 60
h
E
W
X 40
O
Z
20
Figure 62b. NO,, Emissions projected by remedial alternative compared to
the NO, Permitting Threshold for Mayo Steam Station
29
0
143
MNA CIP Removal
Criteria pollutant emissions - tons/yr of NOx
�NOx Permitting Threshold (40 Tons)
In comparing the ecological risks to the ecological injury projected from implementation of the
alternatives, the ecological injury associated with implementing either the CIP or Removal
alternatives at the Buck Steam Station far outweigh any ecological risks predicted with chemical
concentrations.
The basic NEBA conducted herein indicates that implementation of the CIP and Removal
alternatives increase fatality, injury, health/illness and property damage risks of the local
community, increase community nuisance such as noise and pollution, and increase ecological
habitat destruction. These impacts appear to outweigh the human and ecological risks that are
driving the remediation in the first place. As such, Intervenors' proposal for Removal is unjustified
and, from a net benefit analysis, detrimental.
24 The significance levels in the Prevention of Significant Deterioration program are cited for an order of magnitude
comparison. I take no position on whether the activity in fact triggers the requirement for a PSD permit.
DCN: HWIDENC001A 77 September 30, 2016

0
In a recent article published in the Roxboro Times, the evolution from Removal to CIP to handle
coal ash was discussed by State Representative Larry Yarborough and that this change was good
for the citizens of North Carolina. Several points consistent with the NEBA conducted herein were
mentioned within that article (Yarborough 2016). These points included a reference to EPA studies
of coal ash finding it to be non-toxic, and that removal would entail significant effort and disruption
of the neighboring communities for many years (e.g., dump trucks travelling through communities,
etc.).
DCN: HWIDENCOOIA 78 September 30, 2016

0
4.2.8 Cumulative Assessment
In order to put the cumulative effect of implementing the CIP and Removal alternatives in relation
to one another, the following figure provides a comparison of the alternatives. As can be seen, the
cumulative adverse impacts associated with the Removal alternative are significantly higher when
compared to the CIP alternative.
High Risk
Y
H
Moderate
Risk
.Y
m
d
Low Risk
NUA
Figure 63. Cumulative Assessment - Allen, Buck, Cliffside, 1.
�nm c
and Mayo combined
m0N rvf v1 �D� 00
d
oq
C
0.75 t
V
ai
v
G1
o-
0.5
0.5 d
m
c
O
.Y
O
0.25 p
a
MNA
3
o
0
o�
C)
o
�
a
❑ On -Site contaminant exposure
■ Ecological Risk
■ Truck traffic incidents - Fatalities
■ Truck traffic incidents -Injuries/Illness
aa1<
vavavvavaz:
aaaa
aaaa
■ GHG emissions - tons/yr CO2e emitted
■ GHG emissions - tons of CO2e emitted
Criteria pollutant emissions -tons/yr of NOx
Criteria pollutant emissions -tons/yr of PM10/2.5
»
zz
>
zmmmmmmmmmmmmm''"
»»
zzzz
»»
zzzz
■ Capital Cost- Net Present Value (Millions)
NUA - No Una cceptableRisk
d
oq
C
0.75 t
V
ai
v
G1
o-
0.5
0.5 d
m
c
O
.Y
O
0.25 p
a
MNA
CIP Removal
■ Groundwater (drinking water consumption)
❑ Public off-site contami nant exposure
❑ On -Site contaminant exposure
■ Ecological Risk
■ Truck traffic incidents - Fatalities
■ Truck traffic incidents -Injuries/Illness
Truck traffic incidents -property damage only
Implementation risks - Fatalities
■ Implementation risks - Injuries/Illness
■ Implementation Truck Trips - Public Roads
■ GHG emissions - tons/yr CO2e emitted
■ GHG emissions - tons of CO2e emitted
Criteria pollutant emissions -tons/yr of NOx
Criteria pollutant emissions -tons/yr of PM10/2.5
■ Total Energy - MMBTU Used
■ Terrestrial Habitat Value - lost cISAYs
Aquatic Habitat Value - lost cISAYs
■ Overall Ecological Habitat Value - lost dSAYs
■ Capital Cost- Net Present Value (Millions)
NUA - No Una cceptableRisk
DCN: HWIDENCOOIA 79 September 30, 2016

0
5 OPINIONS
• The Intervenors failed to take a holistic view of all of the environmental and community
impacts and risks (environmental footprint) associated with alternative implementation
during their remedial evaluation stage. This has skewed their remedy selection and leads
them to advocate for a remedy (Removal) that is less protective of the environment and the
community.
• The Intervenors do not consider the environmental footprint of the Removal alternative,
nor do they consider methods to reduce the footprint of these alternatives at any of the four
sites. Metrics that may have significant social and economic impacts (e.g., GHG emissions,
extended truck traffic, pollutant emissions through local communities, energy and resource
consumption) or ecological impacts (e.g., terrestrial and aquatic habitat disturbance
associated with removal, capping, or the development of off-site disposal units) were not
considered quantitatively by the Intervenors.
• Developing a remedy for the violations alleged requires employment of a NEBA evaluation
to develop sustainable remedial alternatives that manage site risks while maximizing
benefits and minimizing costs to the public.
• The Intervenors do not address four critical aspects of large, complex projects and
associated remedial evaluations:
o Sustainability and green remediation practices were not evaluated quantitatively;
o Social and community impacts were not evaluated quantitatively;
o Environmental footprints such as carbon and other greenhouse gas emissions were not
evaluated quantitatively; and,
o Net environmental, economic and social benefits and costs were not evaluated either
qualitatively or quantitatively.
• Based upon the NEBA evaluation, the Intervenors have not considered their obligation to
the public to develop sustainable remedial alternatives that manage site risks while
maximizing benefits and minimizing costs to the public.
• Based upon the NEBA presented herein, neither Removal or CIP is warranted as a remedy
for the violations alleged.
• The impact of metals in groundwater on groundwater ecosystem service flows provided by
each individual site is marginal, if any.
• The Removal remedy that the Intervenors propose for the Allen, Buck, Cliffside, and Mayo
sites does not appear to provide any net benefit to off-site ecological or human use services,
over other alternatives.
o The Removal alternative will create greater harm to the environment compared to other
alternatives.
o The Removal alternative will create greater risks (and nuisance) to the local community
(via the extensive truck traffic) and to workers compared to other alternatives.
DCN: HWIDENCOOIA 80 September 30, 2016

0
• Human health and ecological risk evaluations, on which the site classifications and
subsequent remedial alternatives for the Allen, Buck, Cliffside, and Mayo sites are based,
use highly if not overly conservative inputs and assumptions, and mainly represent
"perceived" risks, not "real" risks.
• The Removal alternative will not change human or ecological risk scenarios to any
meaningful level, compared to other alternatives.
• Human health risks associated with implementation of the Removal alternative far
outweigh the human health risks projected, given the current and projected state of
groundwater contamination.
• A refinement of both the human and ecological risk assessments will reduce "perceived"
risks substantially, providing for the consideration of less -intrusive alternatives for
managing "real" risks, if any.
• The marginal benefits to the "perceived" risk profile accomplished by the Intervenors'
proposed remedy do not justify the extreme differences in the cost profile, costs which are
largely borne by the communities served by Duke Energy.
• Based upon my evaluation, the Removal alternative would create greater environmental
and human health impacts at each of the four sites, compared to other alternatives.
• In comparing the CIP alternative to the Removal alternative, the Removal alternative has
a much greater environmental footprint and creates significantly more environmental and
community harm. This is consistent with the Tennessee Valley Authority findings in their
review of CIP and Removal alternatives for coal ash as part of their programmatic EIS
(Tennessee Valley Authority 2016).
• At all four sites, it appears that the following will occur should the Removal remedy
advocated by the Intervenors be implemented:
o The Removal alternative will cause more ecological injury through the destruction of
habitat than the ecological injury projected by the risk assessment, and;
o The Removal alternative provides no net increase in ecosystem service value for the
effort expended; the remedial actions are selected to address marginal, uncertain, and
localized/limited risks.
• With regard to the Removal alternative, the Intervenors have failed to demonstrate clear
and transparent consideration of the following often -stated Agency objectives:
Objective #1: Remedies should protect human health and the environment.
Remediation work should remove unacceptable risks to human health and to the
environment, with due consideration of the costs, benefits and technical feasibility
of the alternatives.
Objective #2: Remedies require safe working practices.
Remediation work should be safe for on-site workers, local communities and the
environment.
DCN: HWIDENCOOIA 81 September 30, 2016

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Objective #3: Remedial decision-making should consider sustainability.
Remediation decisions should be made with regard to the current and future
implications of environmental, social and economic factors. A sustainable
remediation solution should deliver the maximum net benefit achievable.
Objective #4: Remedial decisions and their underlying foundations should be
transparent.
Remediation decisions, including the assumptions and supporting data used to
reach them; should be documented in a clear and easily understood format.
Objective #S: Remedial decisions require good governance and stakeholder
involvement.
Remediation decisions should be made with regard to the views of stakeholders and
follow a clear process in which they can participate. In situations where a non-
optimal remediation decision must be made, because of other factors that are more
influential, a clear and transparent record of indicating why such a decision was
taken should be a minimum requirement in any decision making process.
Objective #6: Remedial decisions are based on sound science.
Decisions should be made on the basis of sound science, relevant and accurate data,
and clearly explained assumptions. Decisions should be based on the best available
information and should be justifiable and reproducible.
• Aside from recognizing the traditional requirements associated with remedial alternative
selection, namely protection of human health and the environment and compliance with
applicable or relevant and appropriate requirements), the Intervenors failed to present
evidence of an evaluation of the significant differences (if any) in the environmental
footprint when comparing the CIP and Removal alternatives that meets the requirements
prescribed by federal agency guidance (USEPA 2012b).
• The Intervenors base their arguments for Removal on risks based solely upon chemical
concentrations of the COIs in groundwater and limited surface water seep areas, and do not
provide information as to how those alternatives will change contaminant risk scenarios.
In doing so, they neglected to consider factors other than chemical concentrations during
the implementation of their preferred remedial alternative that also have the potential to
influence, either positively or negatively, human health and ecological risks and services.
• The Allen, Buck, Cliffside, and Mayo sites meet the definition as to when a NEBA would
be of value in evaluating site remedial alternatives .25 The site information indicates that
these sites retain significant ecological value in their current state. The Removal alternative
proposed by the Intervenors will be environmentally damaging, the ecological risks from
21 "This framework for NEBA should be useful when the balance of risks and benefits from remediation of a site is
ambiguous. This ambiguity arises when the contaminated site retains significant ecological value, when the remedial
actions are themselves environmentally damaging, when the ecological risks from the contaminants are relatively
small, uncertain, or limited to a component of the ecosystem, and when remediation or restoration might fail."
(Efroymson et al. 2004).
DCN: HWIDENC001A 82 September 30, 2016

0
the COI's are relatively small, uncertain, or limited to a component of the ecosystem, and
remediation or restoration may not be fully effective in managing COI mobility.
• The Intervenors' proposal for Removal is unjustified and, from a net benefit analysis,
detrimental.
• There is no need to order closure, much less closure by Removal, to remedy the alleged
violations in this case. A basic NEBA demonstrates that the Intervenors' proposed remedy
(Removal) is clearly disproportionate to the risk.
DCN: HWIDENCOOIA 83 September 30, 2016

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6 REFERENCES
ATSDR 2004. Cobalt Toxicity Profile (www.atsdr.cdc. og v/tomrofiles/tp33.pdf).
Aurand, D., Walko, L., and Pond, R. 2000. Developing Consensus Ecological Risk Assessments:
Environmental Protection in Oil Spill Response Planning A Guidebook. United States
Coast Guard. Washington, DC. 148p.
Colombo, F., Nicolette, J., Wenning, R., and Travers, M. 2012. Incorporating Ecosystem
Valuation in the Assessment of Risk and Remedy Implementation. Chemical Engineering
Transactions. 28, 55-60. DOI: 3303/CET1228010
Efroymson, R., Nicolette, J., and Suter, G. 2003. A Framework for Net Environmental Benefit
Analysis for Remediation or Restoration of Petroleum -Contaminated Sites; ORNL/TM-
2003/17; Oak Ridge National Laboratory: Oak Ridge, TN, USA, 2003.
Efroymson, R., Nicolette, J., and Suter, G. 2004. A Framework for Net Environmental Benefit
Analysis for Remediation or Restoration of Contaminated Sites. Environmental
Management. 34,315-331.
Haley & Aldrich, Inc. April 2016. Report on Evaluation of Water Supply Wells in the Vicinity of
Duke Energy Ash Basins in North Carolina. Lisa Bradley.
HDR Engineering, Inc. of the Carolinas (HDR). 2015a. Comprehensive Site Assessment Report,
Allen Steam Station Ash Basin. August 23, 2015.
HDR. 2015b. Comprehensive Site Assessment Report, Buck Steam Station Ash Basin. August 23,
2015.
HDR. 2015c. Comprehensive Site Assessment Report, Cliffside Steam Station Ash Basin. August
18, 2015.
HDR. 2015d. Corrective Action Plan Part 1, Allen Steam Station Ash Basin. November 20, 2015.
HDR. 2015e. Corrective Action Plan Part 1, Buck Steam Station Ash Basin. November 20, 2015.
HDR. 2015f. Corrective Action Plan Part 1, Cliffside Steam Station Ash Basin. November 16,
2015.
HDR. 2016a. Corrective Action Plan Part 2, Allen Steam Station Ash Basin. February 19, 2016.
HDR. 2016b. Corrective Action Plan Part 2, Buck Steam Station Ash Basin. February 19, 2016.
HDR. 2016c. Corrective Action Plan Part 2, Cliffside Steam Station Ash Basin. February 12, 2016.
HDR. 2016d. Comprehensive Site Assessment Supplement 2, Allen Steam Station Ash Basin.
August 2, 2016.
HDR. 2016e. Comprehensive Site Assessment Supplement 2, Buck Steam Station Ash Basin.
August 2, 2016.
DCN: HWIDENCOOIA 84 September 30, 2016

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HDR. 2016f. Comprehensive Site Assessment Supplement 2, Cliffside Steam Station Ash Basin.
August 8, 2016.
Interstate Technology and Regulatory Council (ITRC). 2006. Planning and Promoting Ecological
Land Reuse of Remediated Sites. Washington, DC: ITRC, Ecological Reuse Team.
National Oceanic and Atmospheric Administration (NOAA). 2011. (Shigenaka, G.) Summary
Report for Fate and Effects of Remnant Oil Remaining in the Environment. Annex M -
Net Environmental Benefit Analysis. National Oceanic and Atmospheric Administration.
Nicolette, J., Burr, S., and Rockel, M. 2013a. A Practical Approach for Demonstrating
Environmental Sustainability and Stewardship through a Net Ecosystem Service Analysis.
Sustainability 2013, 5, 2152-2177; doi:10.3390/su5052152, Published May 10, 2013.
Nicolette, J., Goldsmith, B., Wenning, R., Barber, T., and Colombo, F. 2013b. Chapter 9:
Experience with Restoration of Environmental Damage. In & L. Bergkamp (Ed.) & B.
Goldsmith (Ed.), The EU Environmental Liability Directive: A Commentary. Oxford
University Press. May 10, 2013.
North Carolina. 1971. North Carolina Environmental Policy Act of 1971. (1971, c. 1203, s. 1;
1991, c. 431, s. 1.)
North Carolina Department of Environmental Quality (NCDEQ). 2013. Division of Waste
Management, Hazardous Waste Section. Guidelines for Establishing Remediation Goals
at RCRA Hazardous Waste Sites. December 11, 2013.
Suter, G.W., II. 1993. Ecological Risk Assessment. Lewis Publishers, Boca Raton, Florida.
SynTerra. 2015a. Comprehensive Site Assessment Report, Mayo Steam Electric Plant. September
2, 2015.
SynTerra. 2015b. Corrective Action Plan Part 1, Mayo Steam Electric Plant. December 1, 2015.
SynTerra. 2016a. Corrective Action Plan Part 2, Mayo Steam Electric Plant. February 29, 2016.
SynTerra. 2016b. Comprehensive Site Assessment Supplement 1, Mayo Steam Station Ash Basin.
July 7, 2016.
Tennessee Valley Authority. 2016. Final Ash Impoundment Closure Environmental Impact
Statement Part I — Programmatic NEPA Review. Project Number: 2015-31, June 2016.
United States 1997. United States v. Melvin Fisher. United States District Court for the Southern
District of Florida, Key West Division Case Numbers 92-10027-CIV-DAVIS, and 95-
10051-CIV-DAVIS. Decided 30 July 1997, Filed 30 July 1997. 977 F. Supp. 1193; 1997
U.S. Dist. LEXIS 16767.
United States 2001. United States of America and Internal Improvement Trust Fund v. Great Lakes
Dredge and Dock Company. United States District Court for the Southern District of
Florida D. C. Docket No. 97 -02510 -CV -EBD.
United States Army Environmental Center. 2005. United States Army Natural Resource Injury
Guidance. September. http://aec.army.mil/portals/3/cleanup/nri-guide.pdf
DCN: HWIDENCOOIA 85 September 30, 2016

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United States Environmental Protection Agency (USEPA) 1995. A Framework for Measuring the
Economic Benefits of Groundwater. Office of Water and Office of Policy, Planning and
Evaluation. EPA 230-B-95-003. October 1995.
USEPA. 1997. Ecological Risk Assessment Guidance for Superfund: Process for Designing and
Conducting Ecological Risk Assessments (EPA 540-R-97-006). Washington, DC:
USEPA, OSWER.
USEPA. 1998. Guidelines for Ecological Risk Assessment (EPA/630/R-95/002F). Washington,
DC.
USEPA 2001. Updating Remedy Decision at Select Superfund Sites. Biannual Summary Report
FY 1998 and FY 1999. USEPA Office of Emergency Response (OERR) (EPA 540-R-01-
00, OSWER 9355.0-76) March 2001, 84 pp.
USEPA. 2005. Contaminated Sediment Remediation Guidance for Hazardous Waste Sites (EPA -
540 -R-05-012, OSWER 9355.0-85). Washington, DC: USEPA, OSWER.
USEPA. 2008. Green Remediation: Incorporating Sustainable Environmental Practices into
Remediation of Contaminated Sites (EPA 542-R-08-002). Washington DC: USEPA,
OSWER.
USEPA. 2009a. Endangerment and Cause or Contribute Findings for Greenhouse Gases Under
Section 202(a) of the Clean Air Act. Washington DC: Federal Register 74, no. 239: 66,
496-66, 546.
USEPA. 2009b. Principles for Greener Cleanups. Washington DC: USEPA, OSWER.
USEPA. 2011 a. Greener Cleanups: Contracting and Administrative Toolkit. Washington, DC:
USEPA, OSWER.
USEPA. 201 lb. Deferral for CO2 emissions from bioenergy and other biogenic sources under the
Prevention of Significant Deterioration (PSD) and Title V programs: Proposed rule (EPA -
HQ -OAR -2011-0083). Washington DC: Federal Register 76, no. 54: 15, 249-15, 266.
USEPA. 2012a. "Re: Proposed Order for Recovery of Submerged Oil." Letter to Enbridge
Energy, Limited Partnership. 3 Oct. 2012. MS. N.p.
https://www3.epa. ovg /region5/enbridgespill/pdfs/20121003-cover-letter-re-proposed-
order.pdf
USEPA. 2012b. Methodology for Understanding and Reducing a Project's Environmental
Footprint (EPA 542-R-12-002). Washington DC: USEPA, OSWER, Office of Superfund
Remediation and Technology Innovation.
USEPA. 2013. Region 4 Superfund Annual Report 2013. USEPA.
http://www.epa. og v/re iog n4/soerfund/images/allmedia/pdfs/
annualreport2013 .pdf.
USEPA. 2016. Consideration of Greener Cleanup Activities in the Superfund Cleanup Process.
Memorandum from J. Woolford, C. Bertrand, C. Mackey, and R. Albores to the Regional
DCN: HWIDENCOOIA 86 September 30, 2016

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Superfund National Program Managers. Regions 1-10 and Regional Counsels, Region 1-
10. 14 pp. August 2, 2016.
USEPA Science Advisory Board (SAB). 2009. Valuing the Protection of Ecological Systems and
Services (EPA -SAB -09-012). Washington, DC: USEPA Science Advisory Board.
Yarborough, Larry (North Carolina State Representative). Roxboro Courier -Times, 07-27-16.
http://www.personcountylife.com/news/2016-07-
27/Editorial/Coal ash law_ changes_ are wod_for our_citizens.html
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Selected Examples of Truck Traffic and Construction Implementation Related
Accidents over the past 10 years (Web -accessed September 27, 2016)
August 2016, Wisconsin
http://www.wsaw. com/content/news/Truck-accident-leads-to--3 909443 31.html
June 2016, South Carolina
http://thejoumalonline.com/2016/06/13jM-247-fatality/
June 2016, Kansas City Missouri
http: Hfox4kc. com/2016/06/20/semi-cgMing-fly-ash-involved-in-wreck-spills-it-all-over-
highway/
March 2015, Pennsylvania
htip: //www.wtae. com/news/triaxle-truck-crashes-spills-fly-ash-on-route-22/31754308
December 2013, West Virginia
http://www.tristateodate.com/story/24295024/fatal-crash-on-i-64 jams-U-traffic-near-institute-
wv-fatal-fatality-multi-vehicle
July 2009, Tennessee
http: //www.knoxnews. com/news/local/truck-driver-killed-in-accident-at-kingston-ash-spill-site-
ep-409808217-3 5 93 05271. html
July 2006, Ohio (loading dump truck with ash, pit collapsed)
https://www.osha.gov/pls/imis/accidentsearch.accident detail?id=201954740
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7 EXPERT REPORTS REVIEWED
Bedient, Philip B. 29 February 2016. Expert Opinion of Remediation of Soil and Groundwater at
the Allen Steam Station Operated by Duke Energy Carolinas, LLC, Belmont, North
Carolina.
Bedient, Philip B. 29 February 2016. Expert Opinion of. Remediation of Soil and Groundwater at
the Cliffside Steam Station Operated by Duke Energy Carolinas, LLC, Mooresboro, North
Carolina.
Bedient, Philip B. May 13, 2016. Expert Opinion of. Remediation of Soil and Groundwater at the
Marshall Steam Station Operated by Duke Energy Carolinas, LLC, Terrell, North Carolina.
Campbell, Steven K. and Richard K. Spruill. 29 February 2016. Expert Report. Buck Steam
Station, 1555 Dukeville Road, Salisbury, NC 28146.
Campbell, Steven K. and Richard K. Spruill. May 12, 2016. Expert Report. Buck Steam Station,
1555 Dukeville Road, Salisbury, NC 28146.
Campbell, Steven K. and Richard K. Spruill. May 12, 2016. Expert Report, Addendum #1. Buck
Steam Station, 1555 Dukeville Road, Salisbury, NC 28146.
Cosler, Douglas J. February 29, 2016. Expert Report of Allen Steam Station Ash Basins Belmont,
North Carolina.
Cosler, Douglas J. February 29, 2016. Expert Report of. Cliffside Steam Station Ash Basins
Mooresboro, North Carolina.
Cosler, Douglas J. April 18, 2016. Expert Report of. Marshall Steam Station Ash Basin, Terrell,
North Carolina.
Haley & Aldrich, Inc. April 2016. Report on Evaluation of Water Supply Wells in the Vicinity of
Duke Energy Ash Basins in North Carolina. Lisa Bradley.
Hutson, Mark A. February 2016. Expert Report of. Mayo Steam Electric Plant Roxboro, NC.
Hutson, Mark A. May 2016. Expert Report of. Belews Creek Steam Station Ash Basin, Belews
Creek, NC.
Hutson, Mark A. May 2016. Expert Report of Roxboro Steam Electric Plant, Semora, NC.
Parette, Robert. May 13, 2016. Opinions of the Appropriateness of Monitored Natural Attenuation
in Conjunction with Cap -in -Place at the Roxboro Steam Station, Semora, NC.
Parette, Robert. May 13, 2016. Opinions of the Appropriateness of Monitored Natural Attenuation
in Conjunction with Cap -in -Place at the Belews Creek Steam Station, Belews Creek, NC.
Parette, Robert. May 13, 2016. Opinions of the Appropriateness of Monitored Natural Attenuation
in Conjunction with Cap -in -Place at the Marshall Steam Station, Terrell, NC.
Parette, Robert. May 13, 2016. Opinions of the Appropriateness of Monitored Natural Attenuation
in Conjunction with Cap -in -Place at the Buck Steam Station, Salisbury, NC.
DCN: HWIDENCOOIA 89 September 30, 2016

EPS
Supplemental Expert Reports Reviewed
Campbell, Steven K. and Richard K. Spruill. August 30, 2016. Expert Report, Addendum #1. Buck
Steam Station, 1555 Dukeville Road, Salisbury, NC 28146.
Campbell, Steven K. and Richard K. Spruill. August 30, 2016. Expert Report, Addendum #2. Buck
Steam Station, 1555 Dukeville Road, Salisbury, NC 28146.
Cosler, Douglas J August 30, 2016. Supplemental Expert Report of Allen, Cliffside, and Marshall
Steam Station Ash Basins North Carolina.
Hutson, Mark A. August 2016. Supplemental Expert Report of. Belews Creek Steam Station Ash
Basin, Belews Creek, NC.
Hutson, Mark A. August 2016. Supplemental Expert Report of. Mayo Steam Electric Plant
Roxboro, NC.
Hutson, Mark A. August 2016. Supplemental Expert Report of. Roxboro Steam Electric Plant,
Semora, NC.
Parette, Robert. August 30, 2016. Supplemental Opinions of the Appropriateness of Monitored
Natural Attenuation in Conjunction with Cap -in -Place at the Allen, Belews Creek, Buck,
Cliffside, Marshall, Mayo, and Roxboro Steam Station, North Carolina.
DCN: HWIDENCOOIA 90 September 30, 2016

EPS
APPENDIX A
Remedial Alternatives Construction Analysis

0
Al REMEDIAL ALTERNATIVE
CONSTRUCTION ANALYSIS
A construction and cost analysis for three remedial alternatives, monitored natural attenuation
(MNA), cap -in-place with MNA (CIP), and comprehensive removal with MNA (Removal) were
assessed for the Allen Steam Station, Buck Steam Station, Cliffside Steam Station and Mayo
Steam Station. The three remedial alternatives evaluated are based on the remedial assessment
completed by HDR Engineering, Inc. and SynTerra Corporation as detailed in the Corrective
Action Plan, Part 2 for each respective steam station (HDR 2016a, 2016b, 2016c; SynTerra 2016).
The quantity of ash in basins and ash storage units for each steam station was provided by Duke
Energy. Land coverage dimensions were determined via GIS polygon analysis from shape files
provided by HDR and SynTerra (as provided in the CAP Part 2 documents).
The construction analysis is subdivided into three categories as summarized in Table 1 through
Table 3 following this text. Supporting calculation worksheets (Tables A-1 to A-13) are provided
at the end of this Appendix.
Appendix A — Remedial Alternative Construction Analysis A-1 September 30, 2016

A2 TABLE 1. LAND USE DISTURBANCE
The first analysis task was to model the land use disturbance associated with each remedial
alternative for each site, which established the basis for other tasks under the construction and cost
analysis. Note that MNA only is not included in Table 1 as no significant land use disturbance
occurs under this scenario.
The CIP alternative involves construction of a synthetic cover system (i.e., a Subtitle D cap design)
over the surface -area footprint of the ash basin(s). This alternative also involves the support of an
off-site soil borrow pit to provide the material for use in the cap. The comprehensive Removal
alternative involves excavation of materials contained within the ash basin(s), and transport of
material to a new off-site landfill construction specifically for the purpose of the particular site's
ash disposal. It was assumed that a new off-site landfill will be needed for the excavated ash
because of the insufficient space on-site and the lack of available landfills capable of accepting
such large volumes of material. Note that under this alternative, additional land disturbance is
incurred associated with the offsite landfill. The following parameters or assumptions were
applied in evaluating the land cover alteration associated with the CIP and comprehensive
Removal alternatives.
A2.1 CIP Assumptions:
1. The size of each cap is set equal to the current footprint of the existing ash basins.
2. The borrow material for cap construction is sourced from an off-site location 25 miles
away.
3. To determine borrow area size, the borrow area is set to a maximum depth of 10 feet (ft)
and a side slope of 3 ft/ft.
4. A 50 -ft perimeter buffer strip is included in the borrow area footprint.
A2.2 Comprehensive Removal Assumptions:
1. A conversion of 1.2 tons per cubic yard (CY) of ash is assumed based on a study by the
Electric Power Research Institute (Electric Power Research Institute 2009).
2. To determine landfill size, each landfill is limited to a maximum height of 100 ft and aside
slope of 3.5 ft/ft.
3. A 300 -ft perimeter buffer strip is included in the landfill footprint.
4. To determine borrow area size, the borrow area is set to a maximum depth of 10 ft and a
side slope of 3 ft/ft.
5. The borrow area is assumed to exist on the same property parcel as the off-site landfill. It
is assumed this distance is 1 mile (2 -mile round trip) from the landfill proper.
6. A 50 -ft perimeter buffer strip is included in the borrow area footprint.
Appendix A — Remedial Alternative Construction Analysis A-2 September 30, 2016

0
A3 TABLE 2. PROJECT DURATION
The second analysis task modeled the anticipated duration of each remedial alternative. The
Removal alternative comprises three primary tasks: 1) construction of an off-site landfill, 2)
excavation, transport and placement of ash into the constructed landfill, and 3) closure of the
landfill with synthetic cap. The CIP alternative comprises cap construction activities, which are
assumed to be limited by the rate at which capping material (i.e. soil and clay) can be imported
and placed on-site.
AM Removal Assumptions:
1. Landfill construction assumes a per acre activity rate of 1 day for clear & grub, 28 days for
earthwork, 7 days for survey control, 14 days for liner/leachate system installation, and 4
days for liner soil cover. Activities will occur concurrently; therefore, the rate of earthwork
is the limiting factor for the construction rate.
2. Ash basin excavation, transport to landfill, and ash placement assumes an annual haul rate
of 540,000 tons based on 50 trucks with 2 loads per day at 20 tons apiece, operating 12
hours per day for 270 days per year. Haul distance assumes 25 miles to the landfill (50 -
mile round trip).
3. Landfill closure assumes that the landfill capping rate is subject to import rate of cover
material. Import of cover material assumes an annual haul rate of 648,000 CY based on 6
trucks with 10 loads per day at 40 CY apiece, operating 12 hours per day for 270 days per
year. Haul distance assumes 1 mile from the on-site borrow area.
A3.2 CIP Assumptions:
1. Cap Construction: Assumes an annual haul rate of 540,000 tons based on 50 trucks with 2
loads per day at 20 tons apiece, operating 12 hours per day for 270 days per year. Haul
distance assumes 25 miles to the landfill (50 -mile round trip).
Appendix A — Remedial Alternative Construction Analysis A-3 September 30, 2016

EPS
A4 TABLE 3. COST SUMMARY OF
ALTERNATIVE REMEDIAL ACTIONS
The third analysis task was to project expenditures required to implement each remedial alternative
based on the modeled parameters for land use disturbance and project duration. Construction
material cost, labor and equipment rates are based on data from the Remedial Action Cost
Engineering and Requirements System (RACER) Software Package, Version 11.1.12.0 and from
communications with an industry expert (James R. Nelson, P.G., FGS, personal communication,
June 17, 2016). Landfill construction cost is estimated based on economic data cited in U.S.
Environmental Protection Agency research (USEPA 2014), which reports landfill construction
cost ranges from $300,000 to $800,000 per acre. A cost per acre of $600,000 was applied to for
the current cost analysis.
Appendix A — Remedial Alternative Construction Analysis A-4 September 30, 2016

0
A5 REFERENCES
Electric Power Research Institute. 2009. Coal Ash: Characteristics, Management and
Environmental Issues. September 2009.
HDR. 2016a. Corrective Action Plan Part 2, Allen Steam Station Ash Basin. February 19, 2016.
HDR. 2016b. Corrective Action Plan Part 2, Buck Steam Station Ash Basin. February 19, 2016.
HDR. 2016c. Corrective Action Plan Part 2, Cliffside Steam Station Ash Basin. February 12, 2016.
Nelson, James R. 2016. Personal communication. June 17, 2016.
SynTerra. 2016. Corrective Action Plan Part 2, Mayo Steam Electric Plant. February 29, 2016
USEPA. 2014. Municipal Solid Waste Landfills, Economic Impact Analysis for the Proposed New
Subpart to the New Source Performance Standards. June 2014.
Appendix A — Remedial Alternative Construction Analysis A-5 September 30, 2016

Assumption:
Ash density: 1.2 tons/CY
Notes:
MINA: Monitored Natural Attenuation
CY: Cubic Yards
CIP: Cap -in -Place
1. Estimated landfill footprint based on 100' height and 3.5 side slope, plus 300' buffer for development/construction support.
2. Borrow Area: Excavation area based on 10' depth, plus 50' buffer for development/construction support.
Appendix A - Remedial Alternative Construction Analysis A-7 September 30, 2016
REMOVAL
CIP
Site
Existing Ash Pond/
Ash Fill Area
Volume of Ash
Landfill Construction
1
Area
Landfill Cap Borrow
Z
Material Area
Landfill Total
2
Borrow Material Area
Acre
CY
Acre
Acre
Acre
Acre
Allen
322
16,058,333
225
93
319
190
Buck
180
4,425,000
94
35
129
110
CI iffs i d e
189
6,575,000
121
47
168
115
Mayo
153
5,500,000
108
41
149
94
Total:
844
32,558,333
549
217
766
509
Assumption:
Ash density: 1.2 tons/CY
Notes:
MINA: Monitored Natural Attenuation
CY: Cubic Yards
CIP: Cap -in -Place
1. Estimated landfill footprint based on 100' height and 3.5 side slope, plus 300' buffer for development/construction support.
2. Borrow Area: Excavation area based on 10' depth, plus 50' buffer for development/construction support.
Appendix A - Remedial Alternative Construction Analysis A-7 September 30, 2016

Notes:
Removal: Comprehensive removal of ash
CIP: Cap -in -Place
MNA: Monitored Natural Attenuation
Model Assumptions:
REMOVAL
CIP
REMOVAL
Construction
Ash Excavation &Closure/Cap
Trans ort
Cap Construction
Work Days/Week
CIP
6
Site
Years
Construction'
Work Days
Hours
Ash Excavation, Transport & Placement2
Years Work Days Hours
Years
Closure/Cap3
Work Days
Hours
Years
Cap Construction
Work Days
Hours
Allen
3.6
1,078
12,936
35.7
9,635
115,620
2.0
552
6,618
5.2
1,402
16,824
Buck
1.2
368
4,416
9.8
2,655
31,860
0.7
190
2,280
2.9
784
9,409
Cliffside
1.7
506
6,075
14.6
3,945
47,340
1.0
261
3,137
3.0
823
9,881
Mayo
1.5
438
5,254
12.2
3,300
39,600
0.8
229
2,746
2.5
666
7,995
Total:
8.0
2,390.0
28,680.0
72.4
19,535.0
234,420.0
4.6
1,231.7
14,780.5
13.6
3,675.7
44,108.8
Notes:
Removal: Comprehensive removal of ash
CIP: Cap -in -Place
MNA: Monitored Natural Attenuation
Model Assumptions:
1. Landfill Construction: Assumes a per acre activity rate of 1 day for clear & grub, 28 days for earthwork, 7 days for survey control, 14 days for liner/leachate system installation, and 4 days for liner soil cover.
2. Ash Basin Excavation & Transport to Landfill: Assumes an annual haul rate of 540,000 tons based on 50 trucks with 2 loads per day at 20 tons apiece, operating 12 hours per day for 270 days per year. Haul distance assumes 25 miles to landfill (50 miles round-
trip).
3. Landfill Closure: Assumes landfill capping rate is subject to import rate of cover material. Assumes an annual haul rate of 648,000 CY based on 6 trucks with 10 loads per day at 40 CY apiece, operating 12 hours per day for 270 days per year. Haul distance assumes
1 miles from on-site borrow area.
4. CIP Cap Construction: Assumes capping rate is subject to import rate of cover material and does not included preconstruction activities including basin dewatering. Assumes an annual haul rate of 540,000 tons based on 50 trucks with 2 loads per day at 20 tons
apiece, operating 12 hours per day for 270 days per year. Haul distance assumes 25 miles to landfill (50 miles round-trip).
Appendix A - Remedial Alternative Construction Analysis A-8 September 30, 2016
REMOVAL
CIP
Schedule Assumptions
Construction
Ash Excavation &Closure/Cap
Trans ort
Cap Construction
Work Days/Week
6
6
6
6
Work Weeks/Year
50
45
45
45
Hours/Dayl
12
12
12
12
Construction Days/Year
300
270
270
270
1. Landfill Construction: Assumes a per acre activity rate of 1 day for clear & grub, 28 days for earthwork, 7 days for survey control, 14 days for liner/leachate system installation, and 4 days for liner soil cover.
2. Ash Basin Excavation & Transport to Landfill: Assumes an annual haul rate of 540,000 tons based on 50 trucks with 2 loads per day at 20 tons apiece, operating 12 hours per day for 270 days per year. Haul distance assumes 25 miles to landfill (50 miles round-
trip).
3. Landfill Closure: Assumes landfill capping rate is subject to import rate of cover material. Assumes an annual haul rate of 648,000 CY based on 6 trucks with 10 loads per day at 40 CY apiece, operating 12 hours per day for 270 days per year. Haul distance assumes
1 miles from on-site borrow area.
4. CIP Cap Construction: Assumes capping rate is subject to import rate of cover material and does not included preconstruction activities including basin dewatering. Assumes an annual haul rate of 540,000 tons based on 50 trucks with 2 loads per day at 20 tons
apiece, operating 12 hours per day for 270 days per year. Haul distance assumes 25 miles to landfill (50 miles round-trip).
Appendix A - Remedial Alternative Construction Analysis A-8 September 30, 2016

Site
M NA
REMOVAL
Monitoring 10%
(Site Only) I Contingency
TOTAL
Allen
CIP
$665,000
$7,315,000
Site
Construction
Ash Excavation,
Transport &
Placement
Closure/Cap
Monitoring
(Site and
Landfill)
°
10%
Contingency
TOTAL
Cap
Construction
Monitoring
(Site Only)
10%
Contingency
TOTAL
Allen
$100,370,274
$1,213,386,592
$85,199,912
$12,070,941
$139,895,677.77
$1,550,923,397
$147,407,813
$6,650,000
$14,740,781.30
$162,148,594.28
BUCK
$37,589,262
$335,265,203
$29,901,706
$10,248,951
$40,275,617.09
$453,280,739
$82,966,390
$6,650,000
$8,296,638.96
$91,263,028.55
Cliffside
$49,818,330
$497,518,815
$40,574,949
$12,850,460
$58,791,209.40
$659,553,763
$87,063,317
$8,975,000
$8,706,331.75
$95,769,649.20
Mayo
$43,769,723
$415,854,735
$35,710,413
$10,394,177
$49,533,487.06
$555,262,535
$70,671,010
$6,650,000
$7,067,101.04
$77,738,111.42
Total:
$231,547,589
$2,462,025,345
$191,386,980
$45,564,529
$288,495,991
$3,219,020,434
$388,108,530
$28,925,000
$38,810,853
$426,919,383
Site
M NA
Monitoring 10%
(Site Only) I Contingency
TOTAL
Allen
$6,650,000
$665,000
$7,315,000
BUCK
$6,650,000
$665,000
$7,315,000
Cliffside
$8,975,000
$897,500
$9,872,500
Mayo
$6,650,000
$665,000
$7,315,000
Total:
$28,925,000
$2,892,500
$31,817,500
Notes:
Construction and material costs developed from Remedial Action Cost Engineering and Requirements System (RACER) Software Package, Version 11.1.12.0
Project durations and equipment levels based on personal communication with industry expert
Removal: Comprehensive removal of ash
CIP: Cap -in -Place
MNA: Monitored Natural Attenuation
Appendix A - Remedial Alternative Construction Analysis A-9 September 30, 2016

Notes:
Removal: Comprehensive removal of ash
CIP: Cap -in -Place
1. 25 miles one-way, public roads.
2. 1 miles one-way, on-site (non-public road) travel only.
3. 100 miles one-way, public roads.
Appendix A - Remedial Alternative Construction Analysis A- 10 September 30, 2016
REMOVAL
CIP
Ash Transport
Closure/Cap Material
Liner Material
Closure/Cap Material
Liner Material
Site
Trips
Miles'
Trips Miles2
Trips
Miles3
Trips
Miles'
Trips
Miles3
Allen
963,500
48,175,000
33,091 66,182
204
40,832
140,198
7,009,888
203
40,684
Buck
265,500
13,275,000
11,398 22,797
70
13,938
78,412
3,920,586
114
22,735
Cliffside
394,500
19,725,000
15,683 31,366
96
19,175
82,340
4,117,022
119
23,824
Mayo
330,000
16,500,000
13,730 27,460
83
16,585
66,623
3,331,152
97
19,361
Total:
1,953,5001
97,675,0001
73,903 147,805
453
90,529
367,573
18,378,6471
533
106,603
Notes:
Removal: Comprehensive removal of ash
CIP: Cap -in -Place
1. 25 miles one-way, public roads.
2. 1 miles one-way, on-site (non-public road) travel only.
3. 100 miles one-way, public roads.
Appendix A - Remedial Alternative Construction Analysis A- 10 September 30, 2016

Roll Dimensions
30 mil
40 mil
60 mil
80 mil
100 mil
1. Width (feet):
23
23
23
23
23
2. Length (feet)
1000
750
500
375
300
3. Area (square feet):
23,000
17,250
11,500
8,625
6,900
4. Gross Weight (pounds, approx.)
1 3,470
1 3,470 1
3,470
1 3,470
1 3,470
Removal Alternative
Site Liner Area (ft2) Cap Area Liner Rolls Cap Rolls Truck Trips Miles
Allen
6,708,033
7,378,836
583
642
204
40,832
Buck
2,289,784
2,518,762
199
219
70
13,938
Cliffside
3,150,210
3,465,231
274
301
96
19,175
Mayo
2,724,615
2,997,077
237
261
83
16,585
119
23,824
Mayo
1,293
1,423
453
90,529
CIP Alternative
Site
Total Ash Basin Area
Ash Basin (ft)
Rolls
Truck Trips
Miles
(Acres)
Allen
322
14,035,895
1,221
203
40,684
Buck
180
7,843,547
682
114
22,735
Cliffside
189
8,219,196
715
119
23,824
Mayo
153
6,679,392
581
97
19,361
3,198
533
106,603
Assumptions
Rolls/Truck:
6
Travel Distance (mile):
100
Appendix A - Remedial Alternative Construction Analysis A - 11 September 30, 2016

Landfill Monitoring
Appendix A - Remedial Alternative Construction Analysis A- 12 September 30, 2016
Landfill Width
Well
Analytical
Equipment
Site
(ft)
# MWs
Installation
Days/Event
Cost
Labor Cost
Cost
Reporting
Events/Year
Annual Cost
100 Years
Allen
2,590
22
$75,541
5
$6,474.97
$8,633.29
$1,618.74
$10,000.00
2
$53,454
$5,420,941.13
Buck
1,513
10
$35,308
3
$3,026.41
$4,035.21
$756.60
$10,000.00
2
$35,636
$3,598,951.37
Cliffside
1,775
12
$41,414
3
$3,549.77
$4,733.02
$887.44
$10,000.00
2
$38,340
$3,875,459.74
Mayo
1,651
11
$38,515
3
$3,301.28
$4,401.71
$825.32
$10,000.00
2
$37,057
$3,744,177.18
MNA Monitoring
Analytical
Equipment
Site
# MWs
Days/Event
Cost
Labor Cost
Cost
Reporting
Events/Year
Annual Cost
100 Years
Allen
30
8
$9,000.00
$12,000.00
$2,250.00
$10,000.00
2
$66,500
$6,650,000
Buck
30
8
$9,000.00
$12,000.00
$2,250.00
$10,000.00
2
$66,500
$6,650,000
Cliffside
45
11
$13,500.00
$18,000.00
$3,375.00
$10,000.00
2
$89,750
$8,975,000
Mayo
30
8
$9,000.00
$12,000.00
$2,250.00
$10,000.00
2
$66,500
$6,650,000
Assumptions:
Well Network Size:
Assumes one well every 300 feet on down -gradient
side of landfill,
and one well
every 600 feet
per side and up -gradient
side.
Analytical Cost/Well:
$300.00
Sample Events/Year:
2
Day Labor Rate:
$1,600.00
Equipment Dy Rate:
$300.00
Wells Sampled/Day:
4
Reporting Cost:
$10,000
Well Install Cost:
$3,500
Appendix A - Remedial Alternative Construction Analysis A- 12 September 30, 2016

Landfill Requirements
Site Tons CY ft
Allen 19,270,000
Buck 5,310,000
Cliffside 7,890,000
Mayo 6,600,000
Total: 39,070,000
Conversion
tons per CY: 1.2
Landfill Parameters:
Height (ft) 100
Slope: 3.5
Landfill Cost/Acre
Low: $300,000
High: $600,000
Landfill Buffer Width
Width (ft) 300
16,058,333
433,575,000
4,425,000
119,475,000
6,575,000
177,525,000
5,500,000
148,500,000
32,558,333
879,075,000
GOAL SEEK CALCULATION - LANDFILL GEOMETRY
OUTPUT
Site
Bottom (Landfill Base)
Top
Low Cost
3
Height
S1 (ft)
61 (ft)
S2 (ft)
B2 (ft2)
Volume (ft)
)
100
2,590
6,708,033
1,890
3,572,051
433,575,000
100
1,513
2,289,784
813
661,299
119,475,000
100
1,775
3,150,210
1,075
1,155,374
177,525,000
100
1,6511
2,724,615
9511
903,7181
148,500,000
OUTPUT
Site
2
Base Area (ft)
Landfill
Acres
Low Cost
High Cost
g
Buffer Acres
Total Acreage
Allen
6,708,033
154
$46,198,571
$92,397,143
71.3
225.3
Buck
2,289,784
53
$15,769,862
$31,539,723
41.7
94.3
Cliffside
3,150,210
72
$21,695,660
$43,391,319
48.9
121.2
Mayo
2,724,615
63
$18,764,5681
$37,529,136
45.51
108.0
Total:
I Total:
341
$102,428,6611
$204,857,321
207.41
548.8
Appendix A - Remedial Alternative Construction Analysis A- 13 September 30, 2016

Site
Size (Acres)
Construction days
Years
Const. Hours
Allen
154
1078.0
3.6
12,936
Buck
53
368.0
1.2
4,416
Cliffside
72
506.2
1.7
6,075
Mayo
63
437.8
1.5
5,254
Total:
341
2,390
8
28,680
Activity Duration/acre (days)
Clear/Grub 1
Excavation/Earthwork: 28 Limiting factor - Used as construction rate
Surveying 7
Liner/Leachate System 14
Protective Soil Liner 4
Construction Teams (sets of equipment)
# Construction Teams 4
Project Duration Details
Days/Week 6
Weeks/Year 50
Hours/day 12
Construction days/year 300
Appendix A - Remedial Alternative Construction Analysis A - 14 September 30, 2016

importea import Duration
Site Material Vol. (yrs) Trips Travel Miles Days Hours
Allen
1,323,632
2.0
33,091
66,182
552
6,618
Buck
455,937
0.7
11,398
22.797
190
2,280
Cliffside
627,321
1.0
15,683
31,366
261
3,137
Mavo
549,210
0.8
13.730
27,460
229
2,746
Total:
2,956,100
4.6
73,903
147,805
1,232
14,781
Project Duration Details
Technology
Annual Haul Rate (CY):
648.000
# Trucks:
6
Truck CY:
40
Trios/Dav:
10
Days/Week
6
Weeks/Year
45
Hours/dav
12
Fill Distance (miles):
1
Assumption
Folder Assembly Level Data Report (RACER)
Phase
Technology
Assembly
No. Assembly vescription
Qty
UOM
Materials
Labor
Equipment
Equip. Units Extended Cost
en
appingUnclassifiedi
its, ite, Includes Delivery, prea ing, an
en
appingLoam
ortopsoil, imported topsoil,deep, furnish and pace
.
en
apping
Seeding, Vegetative Cover
en
apping
ay, Low Permeability, its, ite
en
Tapping
Polymeric Liner, High-density Polyethylene
en
apping
arrow Excavation Equipment
Allen
Capping
17030233
Crawler -mounted 3.125 CY 245 Hydraulic Excavator
6,618
HR
$0.00
$57.39
$79.54
4
Tire
Tapp -in g
17030706
D8 with U -Blade Bulldozer
6,618
HR
$0.00
$59.86
$106.51
2 52,202,127
Tr Fen-
Tapping
17030226
988 7.0 CY Wheel Loader
6,618
HR
$0.00
$59.86
$84.96
2
TTI -e -n-
Tapp i _ng
17030295
35 Ton, 769, Off-highway Truck
6,618
HR
$0.00
$55.72
$89.09
2
en
appingConst.
Equipment
en
apping
17030704
D6 with A -blade Bulldozer
6,618
HR
$0.00
$59.86
$60.12
2
Tr Fen-
Tappi_ng
17030101
Row h Gradiniz, D6 Dozer
759,977
SY
$0.00
$0.28
$0.31
1
Allen
Capping
17030431
580K, 1.0 CY, Backhoe with Front-end Loader
6,618
HR
$0.00
$59.86
$20.70
1 5533,159
en
apping
18050413
Watering with 3,000 -Gallon Tank Truck per Pass
157
ACR
$154.66
$38.83
$36.99
1
en
apping
17030233
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
6,618
HR
$0.00
$57.39
$79.54
1
en
appi­ng
33010505
50 KW 120/240 VAC Generator Daily Rental
552
DAY
$0.00
$0.00
$163.38
1
Imported Material:
1,323,632erect
ost:
Direct + 717
BUCK
Lapping
17030423
TTn_cT5`ss`iTi`­e_dTiT, its, ite, Includes Delivery, Spreading, an
uc
appingLoam
ortopsoi,imported topsoil, deep,furnish and pace
uc
apping
Seeding, Vegetative Cover
uc
apping
ay, Low Permeability, its,Off-Site
uc
apping60
Mil Polymeric Liner, High-density Polyethylene
Tu -7-
apping
arrow Excavation Equipment
Buck
Capping
17030233
Crawler -mounted 3.125 CY 245 Hydraulic Excavator
2,280
HR
$0.00
$57.39
$79.54
4
BUCK
Lapping
17030706
D8 with U -Blade Bulldozer
2,280
HR
$0.00
$59.86
$106.51
2
uc
app -in g
17030226
988 7.0 CY Wheel Loader
2,280
HR
$0.00
$59.86
$84.96
2
Tc
apping
17030295
35 Ton, 769, Off-highway Truck
2,280
HR
$0.00
$55.72
$89.09
2
uc
apping
oust. T gwpment
uc
apping
17030704
D6 with A -blade Bulldozer
2,280
HR
$0.00
$59.86
$60.12
2
ucapping
17030101
Rou h Gradin D6 Dozer
261 796
SY
$0.00
$0.28
$0.31
1
Tu c17
apping
17030431
580K, 1.0 CY, Backhoe with Front-end Loader
2,280
HR
$0.00
$59.86
$20.70
1
Appendix A - Remedial Alternative Construction Analysis A - 15 September 30, 2016

Phase
Technology
Assembly
No. Assembly Description
Qty
UOM
Materials
Labor
Equipment
Equip. Units Extended Cost
uc
apping
18050413
Watering with 3,000 -Gallon Tank Truck, per Pass
54
ACR
$154.66
$38.83
$36.99
1 512,467
uc
appi­ng
17030233
Crawler -mounted 3.125 CY 245 Hydraulic Excavator
2,280
HR
$0.00
$57.39
$79.54
1
TucT
apping
33010505
50 KW, 120/240 VAC, Generator, Daily Rental
190
DAY
$0.00
$0.00
$163.38
1
Imported Material:
455,937
Direct ost: 7, ,5 7
Direct +
si a
appmgUnclassifiedi
, its, ite, Includes Delivery, Spreading, an
'Miffsi a
appingLoam
ortopsoil, imported topsoil,deep, furnish and pace
T7TfsicTe_Ta-ppmgT90TGTGT_Seeding,
Vegetative Cover
'UTfsi a
appmg
ay, Low Permeability, its, ite
252,129
TTifsiEFe_Ta-ppmgTTGTG57T__Polymeric
Liner, High-density Polyethylene
71 si a
Tapping
arrow Excavation Equipment
Cliffside
Capping
17030233
Crawler -mounted 3.125 CY 245 Hydraulic Excavator
3,137
HR
$0.00
$57.39
$79.54
4
si e
Tapping
17030706
D8 with U -Blade Bulldozer
3,137
HR
$0.00
$59.86
$106.51
2
1 si a
apping
17030226
988 7.0 CY Wheel Loader
3 137
HR
$0.00
$59.86
$84.96
2
Z Mi si Ua
Tapp -in g
17030295
35 Ton, 769, Off-highway Truck
3,137
HR
$0.00
$55.72
$89.09
2
UiTfs-i a
Tapping
onst. E gwpment
si e
apping
17030704
D6 with A -blade Bulldozer
3,137
HR
$0.00
$59.86
$60.12
2
si e
apping
17030101
Row h Gradiniz, D6 Dozer
360,193
SY
$0.00
$0.28
$0.31
1
Cliftside
Capping
17030431
580K, 1.0 CY, Backhoe with Front-end Loader
3,137
HR
$0.001
$59.86
$20.70
1
TTisi a
appi­ng
18050413
Watering with 3,000 -Gallon Tank Truckper Pass
74
ACR
$154.66
$38.83
$36.99
1
7s cTe
apping
17030233
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
3,137
HR
$0.00
$57.39
$79.54
1
si e
appi­ng
33010505
50 KW 120/240 VAC Generator Daily Rental
261
DAY
$0.00
$0.00
$163.38
1
Imported Material:
62
DirectCost:
Direct + 7
746
ayo
appingUnclassifiedi
, s, ite, Includes uelivery, preaclmg, an0.92
_76177=1
ayo
appingLoam
ortopsoil, imported topsoil,deep, furnish and pace
17_ayora_ppmgT9U5UT0T_Seeding,
Vegetative Cover
ayo
appmg
ay, Low Permeability, its,Off-Site
17_ayoTa_ppmg77U70S71_Polymeric
Liner, High-density Polyethylene
ayo
Capping
Barrow Excavation Equipment
Mayo
Capping
17030233
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
2,746
HR
$0.00
$57.39
$79.54
4 51,504,065
ayo
-Ca ppi­ng
17030706
D8 with U -Blade Bulldozer
2,746
HR
$0.00
$59.86
$106.51
2
ayo
apping
17030226
988, 7.0 CY, Wheel Loader
2,746
HR
$0.00
$59.86
$84.96
2
ayo
apping
17030295
35 Ton 769 Off -hi hwa Truck
2,746
HR
$0.00
$55.72
$89.09
2
ayo
apping
onst. quipment
ayo
Capping
17030704
D6 with A -blade Bulldozer
2,746
HR
$0.00
$59.86
$60.12
2 5658,942
ayo
Tapp _ng
17030101
Rough Grading, D6 Dozer
315,326
SY
$0.00
$0.28
$0.31
1
Mayo
Capping
17030431
580K 1.0 CY Backhoe with Front-end Loader
2,746
HR
$0.00
$59.86
$20.70
1
ayo
app _ng
18050413
Watering with 3,000 -Gallon Tank Truck, per Pass
65
ACR
$154.66
$38.83
$36.99
1 515,016
ayo
apping
17030233
Crawler -mounted 3.125 CY 245 Hydraulic Excavator
2,746
HR
$0.00
$57.39
$79.54
1
ayo
Tapping
33010505
50 KW, 120/240 VAC, Generator, Daily Rental
229
DAY
$0.00
$0.00
$163.38
1
jimported Material: i
549,2101
CY
I
i
DirectCost:j $20,957,821
Direct +
Appendix A - Remedial Alternative Construction Analysis A- 16 September 30, 2016

INPUT
Site
Imported Material
Volume (CY)
3
ft
Allen
11323,632
35,738,072
Buck
455,937
12,310,297
Cliffside
627,321
16,937,679
Mayo
549,210
14,828,659
Total:
2,956,100
79,814,707
Borrow Parameters:
1,3311
Height (ft)
10
1,616,288
Slope:
3
1,2481
Buffer Width
Width (ft) 50
GOAL SEEK CALCULATION - BORROW PIT
Height
Bottom
Top
3,687,830
Volume (ft)
S1 (ft) 131(ft) S2 (ft) B2 (ft 2)
10
1,920
3,687,830
1,860
3,460,985
35,738,072
10
1,139
1,298,193
1,079
1,165,067
12,310,297
10
1,3311
1,772,448
1,2711
1,616,288
16,937,679
10
1,2481
1,556,522
1,1881
1,410,410
14,828,659
OUTPUT
Borrow
Z
Area (ft)
Acres
Buffer Acres Total Acreage
3,687,830
85
8.8 93.5
1,298,193
30
5.2 35.0
1,772,4481
41
1 6.1 1 46.8
1,556,5221
36
1 5.7 1 41.5
Total:
1 191
1 25.9 1 217
Appendix A - Remedial Alternative Construction Analysis A- 17 September 30, 2016

site Ash Tons Trips Travel Miles Days Hours
963,500 48,175,000 9,635 115,620
265,500 13,275,000 2,655 31,860
394,500 19,725,000 3,945 47,340
Duration (yrs)
Allen 19,270,000
35.69
Buck 5,310,000
9.83
Cliffside 7,890,000
14.61
Mavo 6.600,000 12.22 330,000 16,500,000 3,300 39,600
Total: 39,070,000 72.4 1,953,500 97,675,000 19,535 234,420
Proiect Duration Details/Assumptions:
Annual Haul Rate (tons): 540,000
# On -road transport Trucks:
50
# Off-road transport trucks:
4
Truck (tons/load):
20
Truck Trips/Dav:
2
Active Excavators:
4
Active Bulldozers:
2
Days/Week
6
Weeks/Year
45
Water Truck (S/dav)
$100
Landfill Distance (miles):
25
Hours per work dav: 12
Hours per year: 3,240
Phase Name
I Assembly No. I
Assembly Description
Qty
UOM
Materia s
La or
Equipment
Su Bi
Equip.
Exten a Cost
Allen
17030285
12 CY 20 Ton), Dump I ruck
115,620
HR
$0.00
55.72
33.41
$0.00
50
$515,260,530
Allen
17030233
Crawler -mounted, 3.125 CY, 245 Hydraulic
115,620
HR
$0.00
$57.39
$79.54
$0.00
4
$63,327,386
Allen
17030706
D8 with U -Blade Bulldozer
115,620
HR
$0.00
$59.86
$106.51
$0.00
2
$38,471,399
Allen
17030226
988, 7.0 CY, Wheel Loader
115,620
HR
$0.00
$59.86
$84.96
$0.00
1
$16,744,088
Allen
17030295
35 Ton, 769, Off-highway Truck
115,620
HR
$0.00
$55.72
$89.09
$0.00
4
$66,971,729
Allen
18050413
Watering with 3,000 -Gallon Tank Truck, per Pass
9,635
DAY
$0.00
$38.83
$100.00
$0.00
1
$1,337,627
Allen
17030431
580K, 1.0 CY, Backhoe with Front-end Loader
115,620
HR
$0.00
$59.86
$20.70
$0.00
1
$9,314,347
Allen
33010505
10 KW, 120/240 VAC, Generator, Daily Rental
9,635
DAY
$0.00
$0.00
$0.00
$163.38
1
$1,574,166
Allen
33230516
8" Submersible Pump Rental, Day
9,635
DAY
$0.00
$0.00
$0.00
$48.60
2
$936,522
Landfill Spreading/Management
Allen
17030704
D6 with A -blade Bulldozer
115,620
HR
$0.00
$59.86
$60
$0
2
$27,744,175
Direct
$741,681,970
Direct +
$1,186,691,152
Phase Name
I Assembly No.
Assembly Description
Qty
DOM
Materials
Labor
Equipment
SubBid
Equip.
Extended Cost
Buck
17030285
12 CY 20 Ton), Dump I ruck
31,860
HR
$0.00
55.72
33.41
$0.00
50
5141,984,090
Buck
17030233
Crawler -mounted, 3.125 CY, 245 Hydraulic
31,860
HR
$0.00
$57.39
$79.54
$0.00
4
$17,450,359
Buck
17030706
D8 with U -Blade Bulldozer
31,860
HR
$0.00
$59.86
$106.51
$0.00
2
$10,601,096
Buck
17030226
988, 7.0 CY, Wheel Loader
31,860
HR
$0.00
$59.86
$84.96
$0.00
1
$4,613,965
Buck
17030295
35 Ton, 769, Off-highway Truck
31,860
HR
$0.00
$55.72
$89.09
$0.00
4
$18,454,586
Buck
18050413
Watering with 3,000 -Gallon Tank Truck, per Pass
2,655
DAY
$0.00
$38.83
$100.00
$0.00
1
$368,594
Buck
17030431
580K, 1.0 CY, Backhoe with Front-end Loader
31,860
HR
$0.00
$59.86
$20.70
$0.00
1
$2,566,642
Buck
33010505
10 KW, 120/240 VAC, Generator, Daily Rental
2,655
DAY
$0.00
$0.00
$0.00
$163.38
1
$433,774
Buck
33230516
8" Submersible Pump Rental, Day
2,655
DAY
$0.00
$0.00
$0.00
$48.60
2
$258,066
Landfill Spreading/Management
Buck
17030704
D6 with A -blade Bulldozer
31,860
HR
$0.00
$59.86
$60
$0
2
$7,645,126
Direct
$204,376,298
Direct +
$327,002,077
Appendix A - Remedial Alternative Construction Analysis A - 18 September 30, 2016

Phase Name
I Assembly No.
Assembly Description
Qty
UOM
Materials
Labor
Equipment
SubBid
Equip.
Extended Cost
Cliffside
17030285
12 CY 20 Ton , Dump Truck
47,340
HR
$0.00
55.72
33.41
$0.00
50
5210,970,710
Cliffside
17030233
Crawler -mounted, 3.125 CY, 245 Hydraulic
47,340
HR
$0.00
$57.39
$79.54
$0.00
4
$25,929,065
Cliffside
17030706
D8 with U -Blade Bulldozer
47,340
HR
$0.00
$59.86
$106.51
$0.00
2
$15,751,912
Cliffside
17030226
988, 7.0 CY, Wheel Loader
47,340
HR
$0.00
$59.86
$84.96
$0.00
1
$6,855,779
Cliffside
17030295
35 Ton, 769, Off-highway Truck
47,340
HR
$0.00
$55.72
$89.09
$0.00
4
$27,421,222
Cliffside
18050413
Watering with 3,000 -Gallon Tank Truck, per Pass
3,945
DAY
$0.00
$38.83
$100.00
$0.00
1
$547,684
Cliffside
17030431
580K, 1.0 CY, Backhoe with Front-end Loader
47,340
HR
$0.00
$59.86
$20.70
$0.00
1
$3,813,710
Cliffside
33010505
10 KW, 120/240 VAC, Generator, Daily Rental
3,945
DAY
$0.00
$0.00
$0.00
$163.38
1
$644,534
Cliffside
33230516
8" Submersible Pump Rental, Day
3,945
DAY
$0.00
$0.00
$0.00
$48.60
2
$383,454
Landfill Spreading/Management
Cliffside
17030704
D6 with A -blade Bulldozer
47,340
HR
$0.00
$59.86
$60
$0
2
$11,359,706
Direct
$303,677,776
Direct+
$485,884,442
Phase Name
I Assembly No.
Assembly Description
Qty
UOM
Materials
Labor
Equipment I
SubBid I
Equip. I
Extended Cost
Mayo
17030285
12 CY 20 Ton , Dump Truck
39,600
HR
$0.00
55.72
33.41
$0.00
50
5176,477,400
Mayo
17030233
Crawler -mounted, 3.125 CY, 245 Hydraulic
39,600
HR
$0.00
$57.39
$79.54
$0.00
4
$21,689,712
Mayo
17030706
D8 with U -Blade Bulldozer
39,600
HR
$0.00
$59.86
$106.51
$0.00
2
$13,176,504
Mayo
17030226
988, 7.0 CY, Wheel Loader
39,600
HR
$0.00
$59.86
$84.96
$0.00
1
$5,734,872
Mayo
17030295
35 Ton, 769, Off-highway Truck
39,600
HR
$0.00
$55.72
$89.09
$0.00
4
$22,937,904
Mayo
18050413
Watering with 3,000 -Gallon Tank Truck, per Pass
3,300
DAY
$0.00
$38.83
$10.00
$0.00
1
$161,139
Mayo
17030431
580K, 1.0 CY, Backhoe with Front-end Loader
39,600
HR
$0.00
$59.86
$20.70
$0.00
1
$3,190,176
Mayo
33010505
10 KW, 120/240 VAC, Generator, Daily Rental
3,300
DAY
$0.00
$0.00
$0.00
$163.38
1
$539,154
Mayo
33230516
8" Submersible Pump Rental, Day
3,300
DAY
$0.00
$0.00
$0.00
$48.60
2
$320,760
Landfill Spreading/Management
Mayo 17030704 D6 with A -blade Bulldozer 39,600 HR $0.00 $59.86 $60 $0 2 $9,502,416
Direct $253,730,037
Direct+ $405,968,059
Appendix A - Remedial Alternative Construction Analysis A- 19 September 30, 2016

Landfill Construction
Site
Allen
Buck
Cliffside
Mayo
Design/
Planning
$5,000,000
$5,000,000
$5,000,000
$5,000,000
Landfill Construction
Cost
$92,397,143
$31,539,723
$43,391,319
$37,529,136
Erosion/Control
Measures
$450,689.48
$188,504.49
$242,427.43
$216,041.52
Engineering/Survey
Oversight
$2,522,442
$861,034
$1,184,583
$1,024,545
Site Total
$100,370,274
$37,589,262
$49,818,330
$43,769,723
Acres (Landfill
Foot Print)
225
94
121
108
Cost/Acre
$445,408
$398,816
$410,996
$405,197
Total:
$20,000,000
$204,857,321
$1,097,663
$5,592,605
$231,547,589
Ash Dig & Transport
Design/
Erosion/Control
Engineering/Survey
Acres
Site
Planning
Ash Dig &Transport
Measures
Oversight
Site Total
(Ash Ponds)
Cost/Acre
Allen
$1,000,000
$1,186,691,152
$644,439.62
$25,051,000
$1,213,386,592
322
$3,765,711
Buck
$1,000,000
$327,002,077
$360,126.12
$6,903,000
$335,265,203
180
$1,861,932
Cliffside
$1,000,000
$485,884,442
$377,373.55
$10,257,000
$497,518,815
189
$2,636,744
Mayo
$1,000,000
$405,968,059
$306,675.47
$8,580,000
$415,854,735
153
$2,712,018
Total:
$4,000,000
$2,405,545,730
$1,688,615
$50,791,000
$2,462,025,345
Landfill Closure/Cap
Design/
Erosion/Control
Engineering/Survey
Site
Planning
Closure
Measures
Oversight
Site Total
Acres (Borrow)
Cost/Acre
Allen
$1,500,000
$82,079,021
$186,956.11
$1,433,935
$85,199,912
93
$911,443
Buck
$1,500,000
$27,837,707
$70,067.45
$493,932
$29,901,706
35
$853,512
Cliffside
$1,500,000
$38,301,746
$93,604.89
$679,598
$40,574,949
47
$866,941
Mayo
$1,500,000
$33,532,514
$82,922.11
$594,977
$35,710,413
41
$861,300
Total:
$6,000,000
$181,750,987
$433,551
$3,202,442
$191,386,980
Assumptions
Erosion Meas. (per acre): $2,000
Eng/Survey Oversight Details
Engineer (day)
$1,500
Survey crew (day)
$750
Days/Week
6
Weeks/Year
52
Hours/Day
12
Annual Hours
3744
Appendix A - Remedial Alternative Construction Analysis A - 20 September 30, 2016

Folder Assembly Level Data Report (RACER)
Phase Name
Assembly Description
Qty
UOM
Materials
Labor
Equipment
Equip. Units
Extended Cost
en
Unclassitied Fill, s,Ott-Site, Includes Delivery, Ipreacling, and
Compaction
/66,639
A en
Loam or topsoil, imported topsoil, 6deep, furnish and place
191,660
LCY
21.17
4.94
1.43
$5,277,131
A en
See ing, Vegetative Cover
190
ACR
2,623.43
423.05
161.57609,787
A en
Cay, Low Permeability, 6 Li ts, Off -Site
643,977
CY
21.97
2.17
1.4016,443,644
A Fen
60 Mil Polymeric Liner, High-density Polyethylene
9,107,670
SF
0.40
0.20
0.01
$4,650,070
45,087,989
Allen
Unclassified Fill, 6 Lifts, Off -Site, Includes Delivery, Spreading, and
Compaction
574,966
CY
21.97
0.92
0.72
$13,580,218
A en
Loam or topsoil, imported topsoil, 6deep, furnish and place
143,742
LCY
21.17
4.94
1.43
3,957,761
A en
See ing, Vegetative Cover
143
ACR
2,623.43
423.05
161.57457,308
A en
Cay, Low Permeability, 6 Li ts, Off -Site
482,972
CY
21.97
2.17
1.40
12,332,461
A en
60 Mil Polymeric Liner, High-density Polyethylene
6,830,602
SF
0.40
0.20
0.01
3,487,475
33,815,224
Allen
D6 with A -blade Bulldozer
16,824
HR
$0.00
$59.86
$60.12
2
$4,037,022.58
AlTen
Rough Grading, D6 Dozer
921,406
SY
$0.00
$0.28
$0.31
1
$543,629.37
AlTen
580K, 1.0 CY, Backhoe with Front-end Loader
16,824
HR
$0.00
$59.86
$20.70
1
$1,355,319.80
Allen
Watering with 3,000 -Gallon Tank Truck, per Pass
190.4
ACR
$154.66
$38.83
$36.99
1
$43,877.19
A en
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
16,824
HR
$0.00
$57.39
$79.54
1
$2,303,673.54
Allen
50 KW, 120/240 VAC, Generator, Daily Rental
1,402
DAY
$0.00
$0.00
$163.38
1
$229,055.10
8,512,578
Imported Material:
2,803,955
CY
Direct Cost:
587,415,791
Direct+
$139,865,265
Buc
Unclassified Fill, 6 Lifts, Off -Site, Includes Delivery, Spreading, and
Compaction
404,124
CY
21.97
0.92
0.72
9,545,060
Buc
Loam or topsoil, imported topsoil, 6deep, furnish and place
101,031
LCY
21.17
4.94
1.43
2,781,771
Buc
See ing, Vegetative Cover
100
ACR
2,623.43
423.05
161.57
321,447
Buc
Cay, Low Permeability, 6 Li ts, Off -Site
339,464
CY
21.97
2.17
1.40
$8,668,055
Buck
60 Mil Polymeric Liner, High-density Polyethylene
4,800,991
SF
0.40
0.20
0.01
2,451,224
23,767,557
Buc
Unclassified Fill, 6 Lifts, Off -Site, Includes Delivery, Spreading, and
Compaction
250,307
CY
21.97
0.92
0.72
$5,912,031
Buc
Loam or topsoil, imported topsoil, 6deep, furnish and place
62,577
LCY
21.17
4.94
1.43
1,722,977
Buc
See ing, Vegetative Cover
62
ACR
2,623.43
423.05
161.57
199,092
Buc
Cay, Low Permeability, 6 Li ts, Off -Site
210,258
CY
21.97
2.17
1.40
5,368,831
Buc
60 Mil Polymeric Liner, High-density Polyethylene
2,973,644
SF
0.40
0.20
0.01
$1,518,242
514,721,T73-
4,721,173Buc
Tuck
Unclassified Fill, 6 Lifts, Off -Site, Includes Delivery, Spreading, and
Compaction
95,921
CY
21.97
0.92
0.72
$2,265,569
Buc
Loam or topsoil, imported topsoil, 6deep, furnish and place
23,980
LCY
21.17
4.94
1.43
$660,268
Buc
See ing, Vegetative Cover
24
ACR
2,623.43
423.05
161.57
76,288
Buc
Cay, Low Permeability, 6 Li ts, Off -Site
80,574
CY
21.97
2.17
1.40
2,057,407
Buc
60 Mil Polymeric Liner, High-density Polyethylene
1,139,540
SF
0.40
0.20
0.01581,811
5,641,342
-Fuck
D6 with A -blade Bulldozer
9,409
HR
$0.00
$59.86
$60.12
2
$2,257,881.03
Buck
Rough Grading, D6 Dozer
530,647
SY
$0.00
$0.28
$0.31
1
$313,081.68
B ucT
580K, 1.0 CY, Backhoe with Front-end Loader
9,409
HR
$0.00
$59.86
$20.70
1
$758,021.74
Buck
Watering with 3,000 -Gallon Tank Truck, per Pass
109.6
ACR
$154.66
$38.83
$36.99
1
$25,269.32
Buc
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
9,409
HR
$0.00
$57.39
$79.54
1
$1,288,429.94
Buck
50 KW, 120/240 VAC, Generator, Daily Rental
784
DAY
$0.00
$0.00
$163.38
1
$128,109.06
4,770,793
Imported Material:
1,568,234
CY
Direct Cost:
$48,900,864
Direct+
78,241,383
C si e
Unclassified Fill, 6 Lifts, Off -Site, Includes Delivery, Spreading, and
Compaction
487,752
CY
21.97
0.92
0.72
$11,520,275
CTi fFsi e
Loam or topsoil, imported topsoil, 6deep, furnish and place
121,938
LCY
21.17
4.94
1.43
3,357,420
C i si e
See 21ng, Vegetative Cover
121
ACR
2,623.43
423.05
161.57
$387,950
ICliffside
IClay, Low Permeability, 6 Li ts, Off -Site
409,711
CY21.97
2.17
1.40
10,461,786
C si e
60 Mi Polymeric Liner, High-density Polyethylene
5,794,488
SF
0.40
u.zul
0.01
$2,958,470
28,685,901
Appendix A - Remedial Alternative Construction Analysis A - 21 September 30, 2016

Folder Assembly Level Data Report (RACER)
Phase Name
Assembly Description
Qty
UOM
Materials
Labor
Equipment
Equip. Units
Extended Cost
C sie
Unclassified Fill, 6 Lifts, Off -Site, Includes Delivery, Spreading, and Compaction
58,357
CY
21.97
0.92
0.721,378,340
C si e
Loam or topsoil, imported topsoil, 6deep, furnish and place
14,589
LCY
21.17
4.94
1.43
401,697
C si e
See ing, Vegetative Cover
14
ACR
2,623.43
423.05
161.57
46,421
C Ti ffs-i e
Cay, Low Permeability, 6 Li ts, Off -Site
49,020
CY
21.97
2.17
1.40
1,251,697
C si e
60 Mil Polymeric Liner, High-density Polyethylene
693,280
SF
0.40
0.20
0.01
$353,965
3,432,120
Cliffside
Unclassified Fill, 6 Lifts, Off -Site, Includes Delivery, Spreading, and Compaction
241,838
CY
21.97
0.92
0.72
$5,712,016
C si e
Loam or topsoil, imported topsoil, 6deep, furnish and place
60,460
LCY
21.17
4.94
1.43
1,664,685
C i si e
See ing, Vegetative Cover
60
ACR
2,623.43
423.05
161.57192,355
C si e
Cay, Low Permeability, 6 Li ts, Off -Site
203,144
CY
21.97
2.17
1.40
5,187,193
C si e
60 Mil Polymeric Liner, High-density Polyethylene
2,873,040
SF
0.40
0.20
0.01
1,466,877
$14,223,127
Cliffside
D6 with A -blade Bulldozer
9,881
HR
$0.00
$59.86
$60.12
2
$2,371,009.28
Clittside
Rough Grading, D6 Dozer
555,690
SY
$0.00
$0.28
$0.31
1
$327,857.28
C si e
580K, 1.0 CY, Backhoe with Front-end Loader
9,881
HR
$0.00
$59.86
$20.70
1
$796,001.45
CTittside
Watering with 3,000 -Gallon Tank Truck, per Pass
114.8
ACR
$154.66
$38.83
$36.99
1
$26,461.88
CTI TFsi e
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
9,881
HR
$0.00
$57.39
$79.54
1
$1,352,985.08
CTittside
50 KW, 120/240 VAC, Generator, Daily Rental
823
DAY
$0.00
$0.00
$163.38
1
$134,527.80
5,008,843
Imported Material:
1,646,809
CY
Direct Cost:
$51,349,991
Direct+
82,159,986
Mayo
Unclassified Fill, 6 Lifts, Off -Site, Includes Delivery, Spreading, and Compaction
637,541
CY
21.97
0.92
0.72
$15,058,174
Mayo
Loam or topsoil, imported topsoil, 6" deep, furnish and pace
159,385
LCY
21.17
4.94
1.43
$4,388,490
Mayo
Seeding, Vegetative Cover
158
ACR
2,623.43
423.05
161.57
507,097
Mayo
Cay, Low Permeability, 6 Li ts, Off -Site
535,534
CY
21.97
2.17
1.40
$13,674,622
Mayo
60 Mil Polymeric Liner, High-density Polyethylene
7,573,987
SF
0.40
0.20
0.01
$3,867,022
37,495,405
Mayo
D6 with A -blade Bulldozer
7,995
HR
$0.00
$59.86
$60.12
2
$1,918,423.47
Mayo
Rough Grading, D6 Dozer
455,264
SY
$0.00
$0.28
$0.31
1
$268,605.82
Mayo
580K, 1.0 CY, Backhoe with Front-end Loader
7,995
HR
$0.00
$59.86
$20.70
1
$644,058.16
Mayo
Watering with 3,000 -Gallon Tank Truck, per Pass
94.1
ACR
$154.66
$38.83
$36.99
1
$21,679.60
Mayo
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
7,995
HR
$0.00
$57.39
$79.54
1
$1,094,722.98
Mayo
50 KW, 120/240 VAC, Generator, Daily Rental
666
DAY
$0.00
$0.00
$163.38
1
$108,848.71
4,056,339
Imported Material:
1,332,461
CY
Direct Cost:j
$41,551,744
Direct +1
66,482,791
Appendix A - Remedial Alternative Construction Analysis A - 22 September 30, 2016

INPUT
Borrow Parameters:
Height (ft) 10
Slope: 3
Buffer Width
Width (ft) 50
GOAL SEEK CALCULATION - BORROW PIT
Height
Imported Material
3
Site
Volume (CY)
ft
Allen
2,803,955
75,706,791
Buck
1,568,234
42,342,326
Cliffside
1,646,809
44,463,835
Mayo
1,332,461
35,976,436
Total:
19,272,058
520,345,554
Borrow Parameters:
Height (ft) 10
Slope: 3
Buffer Width
Width (ft) 50
GOAL SEEK CALCULATION - BORROW PIT
Height
Bottom
Top
Buffer Acres
Volume (ft)
S1 (ft) B1 (ft') S2 (ft) B2 (ft)
10
2,781
7,736,365
2,721
7,406,193
75,706,791
10
1 2,088
4,358,292
21028
4,111,373
42,342,326
10
1 2,139
4,573,498
2,079
4,320,469
44,463,835
10
1 1,9271
3,712,044
1,8671
3,484,444
35,976,436
OUTPUT
Site
Borrow
Area (ft) Z
Acres
Buffer Acres
Total Acreage
Allen
7,736,365
178
12.8
190.4
Buck
4,358,292
100
9.6
109.6
Cliffside
4,573,4981
105
1 9.8
1 114.8
Mayo
3,712,0441
85
1 8.8
1 94.1
Total: 1
468
1 41.0
1 509
Appendix A - Remedial Alternative Construction Analysis A - 23 September 30, 2016

*Planning, survey, permits
Construction Cost Details
Subtitle D (non -hazardous) cap design and construction
Off -Site source of capping materials
40 Mil HDPE Liner
Current scenario does not account for any consolidation of ash material
Erosion/Control: Assumed cost of $2,000/acre
Dewatering/Treatment Details
System Mobilizatioi $150,000
Operation $3,000 day
Utilization 50%
Assume discharge under NPDES permit
Imported
Material Import Duration
Site Volume (CY) (yrs) Trips
Eng/Survey Oversight Details
Engineer
$1,500 day
Survey
Dewatering/
Erosion/Control
Engineering/Survey
Weeks/Year
Site
Design*
Construction Cost
Treatment
Measures
Oversight
Site Total
Allen
$1,000,000
$139,865,265
$2,252,966
$644,440
$3,645,142
$147,407,813
Buck
$1,000,000
$78,241,383
$1,326,176
$360,126
$2,038,705
$82,966,390
Cliffside
$1,000,000
$82,159,986
$1,385,107
$377,374
$2,140,851
$87,063,317
Mayo
$1,000,000
$66,482,791
$1,149,345
$306,675
$1,732,199
$70,671,010
Total:
$4,000,000
$366,749,425
$6,113,594
$1,688,615
$9,556,896
$388,108,530
*Planning, survey, permits
Construction Cost Details
Subtitle D (non -hazardous) cap design and construction
Off -Site source of capping materials
40 Mil HDPE Liner
Current scenario does not account for any consolidation of ash material
Erosion/Control: Assumed cost of $2,000/acre
Dewatering/Treatment Details
System Mobilizatioi $150,000
Operation $3,000 day
Utilization 50%
Assume discharge under NPDES permit
Imported
Material Import Duration
Site Volume (CY) (yrs) Trips
Eng/Survey Oversight Details
Engineer
$1,500 day
Survey
$750 day
Days/Week
6
Weeks/Year
52
Travel Miles Days Hours
Allen
2,803,955
5.2
140,198
7,009,888
1,402
16,824
Buck
1,568,234
2.9
78,412
3,920,586
784
9,409
Cliffside
1,646,809
3.0
82,340
4,117,022
823
9,881
Mayo
1,332,461
2.5
66,623
3,331,152
666
7,995
Total:
7,351,459
13.6
367,573
18,378,647
3,676
44,109
Project Duration Details
Annual Haul Rate (CY):
540,000
# Trucks:
50
Truck CY:
20
Trips/Day:
2
Days/Week
6
Weeks/Year
45
Hours/day
12
Fill Distance (miles):
25
Erosion Control & Measures
$/acre 2,000
Appendix A - Remedial Alternative Construction Analysis A - 24 September 30, 2016

Station
Basin
Approximate
Volume' (Tons)
Surface Area
Perimeter
(sq ft) (Ac)
(ft)
Allen
Active Ash Basin
10,380,000
8,004,259
184
15,515
Inactive Ash Basin 6,160,000
6,031,636 138
13,466
Allen Basins Total 16,540,000
Ash Fill 1 430,000
Ash Fill 560,000
Ash Landfill and Sub rade
1,740,000
Allen Fills/Landfills Tota 12 2,730,000
Allen Total 19,270,000
14,035,895 322
Buck
Cell 1 (Additional Primary)
2,840,000
4,232,788
97
10,468
Cell (Old Primary) 1,950,000
2,613,463 60
11,339
Cell (Secondary) 270,000
997,296 23
5,348
Buck Basins Total 5,060,000
Ash Fill Area 250,000
Buck Fills Tota 12 250,000
Buck Total 5,310,000
7,843,547 180
Cliffside
Active Ash Basin
5,040,000
5,089,416
117
19,329
Units 1-4 Inactive Ash Basin 300,000
622,773 14
3,136
Unit 5 Inactive Ash Basin
2,350,000
2,507,007
58
11,316
Cliffside Basins Total 7,690,000
Ash Storage Area 1 200,000
Cliffside Fills Tota 12 200,000
Cliffside Total 7,890,000
8,219,196 189
Mayo
Ash Pond
6,600,000
6,679,392
153
22,723
Mayo Total 6,600,000
6,679,392 153
Notes:
1. Ash quantities provided by Duke Energy.
2. Quantity includes ash located in permitted landfills, ash fills, and structural fills located on top of the ash basin(s). While these structures are not "CCR surface impoundments" under
the Coal Ash Management Act and, therefore, not subject to the statute's closure provisions, this figure includes the quantities in these structures in the event Duke Energy is required
to excavate them along with the basins.
3. Dimensions developed from GIS polygon analysis of ash basin configuration.
Appendix A - Remedial Alternative Construction Analysis A-25 September 30, 2016

EPS
APPENDIX B
Traffic and Implementation Risk Analysis
Appendix B — Traffic and Implementation Risk Analysis B-1 September 30, 2016

0
B I OVERVIEW
The risk to the health and life of workers and the public due to construction activities for each
alternative should be considered during the remedial alternative selection process. Additionally,
the risk of property damage was also evaluated. National statistics were used to evaluate the
fatality, injury/illness, and property damage risks associated with truck traffic and onsite
implementation for the Allen, Buck, Cliffside, and Mayo facilities.
Appendix B — Traffic and Implementation Risk Analysis B-2 September 30, 2016

0
B2 TRUCK TRAFFIC RISK
The risks of fatality and injury due to truck traffic associated with ash Removal and CIP are
presented on Table 1 of this appendix. Data on annual fatalities and injuries associated with large -
truck traffic and large -truck miles traveled per year was taken from the National Highway Traffic
Safety Administration's (NHTSA) large truck traffic safety fact sheet for 2014 (NHTSA 2016).
This is the most recent data available and accounts for fatalities and injuries for truck occupants as
well as non -truck occupants. Averages of the calculated fatality and injury rates for the years 2010
through 2014 were also examined and found to be similar to the 2014 rates. The reference values
used for the truck traffic risk calculations are given in Table 2 of this appendix.
Total truck driving miles were calculated for the construction analysis for each facility.
Significantly more truck miles are associated with Removal than with CIP. Transporting borrow
pit and liner material was also considered in these calculations.
In addition to the risk of health and life to the workers and the public, the risk of property damage
resulting from truck traffic was also considered for both alternatives. Data for Property Damage
Only (PDO) crashes involving large trucks (Federal Motor Carrier Safety Administration 2016)1
was used to estimate the expected number of PDO incidents for both alternatives at each facility.
The results are presented in Table 1 and the reference values are included in Table 2.
1 The most recent published PDO data (2014) were used in our analyses.
Appendix B — Traffic and Implementation Risk Analysis B-3 September 30, 2016

0
B3 IMPLEMENTATION RISK
In addition to truck traffic risks, there are substantial occupational (worker) risks associated with
performing the excavation, landfill construction, and cap construction. Occupational risks
calculated for remedial alternative implementation are also presented on Table 1. Data on
occupational fatalities and nonfatal injuries and illnesses were gathered from the Bureau of Labor
Statistics (BLS) National Consensus of Fatal Occupational Injuries in 2014 (Preliminary Results)
News Release (BLS 2015a), Fatal Occupational Injuries, Total Hours Worked, and Rates of Fatal
Occupational Injuries by Selected Worker Characteristics, Occupations, and Industries, Civilian
Workers, 2014 (BLS 2015b), and Employee -Reported Workplace Injuries and Illnesses, 2014
News Release (BLS 2015c). The reference values used for the occupational risk calculations are
given in Table 3.
Data from the forestry and logging industry (NAICS code 113) were used to calculate the fatality
and injury/illness risks associated with clearing wooded land for borrow pits and the proposed
landfills (if applicable). According to the BLS, "Industries in the Forestry and Logging subsector
grow and harvest timber on a long production cycle (i.e., of 10 years or more)" and include logging
equipment operators and heavy truck and tractor -trailer drivers. Mature tree removal at this caliber
is expected to occur at each facility where land will be cleared for a borrow pit and to prepare for
landfill construction. While a landfill area will only be cleared for the removal option, a borrow
pit will be needed for both alternatives (Removal and CIP). If additional tree removal will be
needed that has not been accounted for in either the borrow or proposed landfills areas, the fatality
and injury/illness risks will increase.
Data from the construction industry (NAICS code 23) were used to calculate the fatality and
injury/illness risks associated with excavation, landfill construction, and cap construction work,
where relevant. According to the BLS, "The construction sector comprises establishments
primarily engaged in the construction of buildings or engineering projects. Establishments
primarily engaged in the preparation of sites for new construction and establishments primarily
engaged in subdividing land for sale as building sites also are included in this sector." Occupations
falling in this category include construction laborers, operating engineers, first-line supervisors,
and heavy truck and tractor -trailer drivers. The excavation of the ash basins, construction of offsite
landfills, and the construction of an in-place cap all fall under this industry and therefore
construction -based risk statistics were used for these project phases in this evaluation.
Time and manpower to clear the land and complete construction for each alternative were
estimated based on scope and are outlined in Appendix A. A ratio of two days to clear one acre of
wooded land was used to calculate the total hours worked clearing the borrow pit and proposed
landfill areas.
Appendix B — Traffic and Implementation Risk Analysis B-4 September 30, 2016

EPS
B4 SAMPLE CALCULATIONS
B4.1 Truck Traffic Risk Calculations
B4.1.1 Fatalities due to Truck Traffic
Ft,2014
Ft = x Dt
Dt,2014
B4.1.2 Injuries due to Truck Traffic
It,2014
It = x Dt
Dt,2014
B4.1.3 PDO Truck Crashes
pt,2014
Pt = X Dt
Dt,2014
B4.2 Implementation Risk Calculations
134.2.1 Fatalities due to Implementation
F. _ FL,2014 X T + FC,2014 x T
1 — L C
TL,2014 TC,2014
B4.2.2 Injuries and Illnesses due to Implementation
IIL,2014 x T+ IC,2014 x T
Ii _ — L C
TL,2014 TC,2014
B4.3 Definitions
Ft = Fatalities resulting from truck traffic, including workers and non -workers (number of persons)
Ft,2014 = Fatalities resulting from large truck traffic, including truck occupants and other people, in
the United States in 2014 (number of persons) (NHTSA 2016)
Dt,2014 = Large -truck miles traveled in the United States in 2014 (miles) (NHTSA 2016)
Dt = Total truck distance traveled (miles), calculated (see Appendix A)
It = Injuries resulting from truck traffic, including workers and non -workers (number of cases)
Appendix B — Traffic and Implementation Risk Analysis B-5 September 30, 2016

EPS
It,2014 = Injuries resulting from large truck traffic, including truck occupants and other people, in
the United States in 2014 (number of cases) (NHTSA 2016)
Pt = Property damage only (PDO) truck crashes resulting from large truck traffic (number of
incidents) (FMCSA 2016)
P t,2014 = PDO crashes involving large trucks in the United States in 2014 (number of incidents)
(FMCSA 2016)
Fi = Fatalities resulting from implementation of the selected remedy (number of persons)
FL,2014 = Occupational fatalities in the forestry and logging industry in the United States in 2014
(number of persons) (BLS 2015b)
TL,2014 = Total hours worked in the forestry and logging industry in the United States in 2014
(hours) (BLS 2015b)
TI, = Total hours worked clearing wooded land (hours), calculated based on a clearing rate of 2
acres per day and a crew size of 24 persons (see Appendix A)
Fc,2014 = Occupational fatalities in the construction industry in the United States in 2014 (number
of persons) (BLS 2015b)
Tc,2014 = Total hours worked in the construction industry in the United States in 2014 (hours) (BLS
2015b)
Tc = Total hours worked completing remedy (hours), calculated (see Appendix A)
Ii = Injuries and illnesses resulting from implementation of the selected remedy (number of cases)
IL,2014 = Nonfatal occupational injuries and illnesses in the forestry and logging industry in the
United States in 2014 (number of cases) (BLS 2015c)
Ic,2014 = Nonfatal occupational injuries and illnesses in the construction industry in the United
States in 2014 (number of cases) (BLS 2015c)
Appendix B — Traffic and Implementation Risk Analysis B-6 September 30, 2016

0
B5 RESULTS
The calculations show that Removal and constructing an offsite landfill will produce significantly
more fatalities and injuries or illnesses for each site considered when compared to the CIP
alternative. With the highest risk of personal injury (workers and the general public) and personal
property damage (i.e., road accidents) over the lifespan of the project (see Table 1), the Allen
facility should expect approximately 19 injuries to the general public resulting from traffic
accidents and 61 worker injuries from construction activities associated with the Removal
alternative. Alternately, approximately 3 injuries to the general public and 10 worker injuries from
construction activities are estimated to result from -capping -in place for Allen. If all four facilities
proceed with the comprehensive removal alternative, then a total of approximately 39 injuries to
the general public and 131 worker injuries should be expected, along with 114 incidents of public
property damage resulting from truck crashes on public roads. The CIP alternative exhibits less
risk with an estimated total of 7.4 injuries to the public and 25 injuries to workers across all four
sites. With the MNA alternative, the incident rates are negligible as the risks associated with
trucking and construction are removed.
See Table 1 for a summary of estimated injury and traffic incident rates for the Allen, Buck,
Cliffside, and Mayo facilities.
Appendix B — Traffic and Implementation Risk Analysis B-7 September 30, 2016

0
B6 REFERENCES
Bureau of Labor Statistics (BLS). (2015a). National Consensus of Fatal Occupational Injuries in
2014 (Preliminary Results) News Release, available September 17, 2015. U.S. Department
of Labor.
BLS. (2015b). Fatal occupational injuries, total hours worked, and rates of fatal occupational
injuries by selected worker characteristics, occupations, and industries, civilian workers,
2014. Retrieved from the Bureau of Labor Statistics website:
http://www.bls.gov/iif/oshwc/cfoi/cfoi rates_2014hb.pdf
BLS. (2015c). Employer -Reported Workplace Injuries and Illnesses - 2014 News Release,
available October 29, 2015. U.S. Department of Labor.
Federal Motor Carrier Safety Administration (FMCSA). (2016). Large Truck and Bus Crash Facts
2014. Retrieved from the Federal Motor Carrier Safety Administration website:
https://www.fmcsa.dot.gov
National Highway Traffic Safety Administration (NHTSA). (2016). Traffic Safety Facts, Large
Trucks, 2014 Data, DOT HS 812 279, Revised May 2016. U.S. Department of
Transportation. Washington, D.C.
Appendix B — Traffic and Implementation Risk Analysis B-8 September 30, 2016

Table 1. Summary of Traffic and Implementation Risks
Table 2. Truck Traffic Risk Reference Values
Large -truck miles
Number of truck
Number of "other
REMOVAL
:
Number of "other
Total number of
PDO Crashes
CIP
worked (millions) -
Fatalities per hour
Site
Estimated
Fatalities from
Truck Traffic 1
Estimated
Fatalities from
Implementation 2,3
Estimated Injuries
or Illnesses from
Truck Traffic 1
Estimated Injuries
or Illnesses from
Implementation 4,6
Estimated Large-
Truck Crashes
Resulting in PDO
Estimated
Fatalities from
Truck Traffic 1
Estimated
Fatalities from
Implementation 2,3
Estimated Injuries
or Illnesses from
Truck Traffic 1
Estimated Injuries
or Illnesses from
Implementation 4,5
Estimated Large -
Truck Crashes
Resulting in PDO
Allen
0.68
0.23
19.2
61
56
0.10
0.07
2.8
9.6
8
Buck
0.19
0.08
5.3
19
16
0.06
0.04
1.6
5.4
5
Cliffside
0.28
0.11
7.9
27
23
0.06
0.04
1.6
5.7
5
Mayo
0.23
0.09
6.6
23
19
0.05
0.03
1.3
4.6
4
Total:l
1.4
1 0.5 1
38.9 1
131
1 114
1 0.3
1 0.2 1
7.4
1 25.2 1
22
Table 2. Truck Traffic Risk Reference Values
Large -truck miles
Number of truck
Number of "other
Number of truck
Number of "other
Total number of
PDO Crashes
Fatalities - 2014
worked (millions) -
Fatalities per hour
Total number
incident rate -
per hour worked -
2,1
(total number)
traveled - 2014
occupant fatalities
P
people" fatalities -
P P
6
occu ant injuries
P 1
people" injuries -
P P J
injuries per truck
1 P
Involving Large
g g
1
1
1
fatalities per mile
le
1
1
6
9
millions
2014
2014
logging
2014
2014
mile
Trucks - 2014
279,132
657
1 3,246
1.40E-08
27,000
84,000
3.98E-07
326,000
Table 3. Implementation Risk Reference Values
Notes:
CIP - Capping -in -Place
PDO - Property Damage Only
Values represent total expected fatalities and injuries or illnesses over the estimated lifespan of the project, excluding post MNA activitie!
(1) - Fact Sheet, Traffic Safety Facts 2014 Data. NHTSA's National Center for Statistics and Analysis, DOT HS 812 279, Washington, DC, revised May 2016
(2) - Bureau of Labor Statistics. National Consensus of Fatal Occupational Injuries in 2014 (Preliminary Results) News Release. Table 2. Fatal occupational injuries by industry and selected event or exposure, 2014. September 17, 2015
(3) - Bureau of Labor Statistics. Fatal occupational injuries, total hours worked, and rates of fatal occupational injuries by selected worker characteristics, occupations, and industries, civilian workers, 2014
(4) - Bureau of Labor Statistics. Employer -Reported Workplace Injuries and Illnesses - 2014 News Release. Table 2. Numbers of nonfatal occupational injuries and illnesses by case type and ownership, selected industries, 2014. October 29, 2015
(5) - Bureau of Labor Statistics. Employer -Reported Workplace Injuries and Illnesses - 2014 News Release. Table 1. Incidence rates of nonfatal occupational injuries and illnesses by case type and ownership, selected industries, 2014. October 29, 2015
(6) - Calculated from data provided in reference (1)
(7) - Calculated from data provided in reference (3)
(8) - Calculated from data provided in references (4) and (5)
(9) - Federal Motor Carrier Safety Administration Analysis Division, Large Track and Bus Crash Facts 2014. March 2016.
Appendix B - Traffic and Implementation Risk Analysis B-9 September 30, 2016
Total hours
Injuries/Illnesses -
Injuries/Illnesses
Injuries/illnesses
Industry
Fatalities - 2014
worked (millions) -
Fatalities per hour
2014 (total
incident rate -
per hour worked -
2,1
(total number)
3
7
worked - 2014
6
S
2014
number)4
2014
2014
Forestry and
logging
92
180
5.11E-07
2,800
5.1
2.55E-05
(NAICS code 113)
Construction
874
18,168
4.81E-08
200,900
3.6
1.80E-05
(NAICS code 23)
Notes:
CIP - Capping -in -Place
PDO - Property Damage Only
Values represent total expected fatalities and injuries or illnesses over the estimated lifespan of the project, excluding post MNA activitie!
(1) - Fact Sheet, Traffic Safety Facts 2014 Data. NHTSA's National Center for Statistics and Analysis, DOT HS 812 279, Washington, DC, revised May 2016
(2) - Bureau of Labor Statistics. National Consensus of Fatal Occupational Injuries in 2014 (Preliminary Results) News Release. Table 2. Fatal occupational injuries by industry and selected event or exposure, 2014. September 17, 2015
(3) - Bureau of Labor Statistics. Fatal occupational injuries, total hours worked, and rates of fatal occupational injuries by selected worker characteristics, occupations, and industries, civilian workers, 2014
(4) - Bureau of Labor Statistics. Employer -Reported Workplace Injuries and Illnesses - 2014 News Release. Table 2. Numbers of nonfatal occupational injuries and illnesses by case type and ownership, selected industries, 2014. October 29, 2015
(5) - Bureau of Labor Statistics. Employer -Reported Workplace Injuries and Illnesses - 2014 News Release. Table 1. Incidence rates of nonfatal occupational injuries and illnesses by case type and ownership, selected industries, 2014. October 29, 2015
(6) - Calculated from data provided in reference (1)
(7) - Calculated from data provided in reference (3)
(8) - Calculated from data provided in references (4) and (5)
(9) - Federal Motor Carrier Safety Administration Analysis Division, Large Track and Bus Crash Facts 2014. March 2016.
Appendix B - Traffic and Implementation Risk Analysis B-9 September 30, 2016

EPS
APPENDIX C
Air Emissions and Energy Use Analysis
Appendix C — Air Emissions and Energy Use Analysis C-1 September 30, 2016

0
C I INTRODUCTION
The expected air pollutant emissions and energy consumption were estimated as part of the NEBA
framework for the remedial alternatives under consideration. Air emissions can be divided into
two separate categories, criteria pollutants and greenhouse gases (GHGs).
C1.1 Criteria Pollutants
The criteria pollutants, which were established in the Clean Air Act of 1970, consist of carbon
monoxide (CO), nitrogen oxides (NOx), ozone, sulfur oxides (SOX), particulate matter (PM), and
lead. These pollutants were determined to cause adverse health & environmental effects when
present above specific concentrations in the atmosphere. For the purposes of this evaluation, NOx
and PM were evaluated based on their expected emissions from the activities involved in the
remedial activities. Based on previous experience with air emissions from remedial activities, the
impacts from the other criteria pollutants were expected to be minimal and so were not included
in this evaluation. For example, the sulfur content in the fuels, that are typically converted to SOx,
have been reduced by regulations to the extent that they are nearly negligible. Regulations have
also significantly reduced the VOC emissions from engines to the extent that they are relatively
small by comparison with NOx emissions.
In addition to the harmful effects of direct exposure to NOx, their emissions are also precursors in
the formation of ozone (another criteria pollutant), acid rain, and fine particulate matter. Therefore,
based on the anticipated quantity of NOx emissions combined with their environmental and health
effects, the NOx emissions were estimated as part of this NEBA analysis.
Particulate matter is subdivided into two categories: coarse particulate matter (particles that have
a diameter of 10 microns or less) also known as PM 10; and fine particulate matter (particles that
have a diameter of 2.5 microns or less), also known as PM2.5. These are particles that generally
pass through the throat and nose and enter the lungs. Once inhaled, these particles can affect the
heart and lungs and cause serious health effects. Because the health effects and expected emissions
of PM 10 and PM2.5 are significant, they have also been estimated for this NEBA analysis.
C1.2 Greenhouse Gases
GHGs, which consist primarily of carbon dioxide (CO2), methane (CH4), nitrous oxide (N20), and
fluorinated gases, were also determined by USEPA to have adverse health and environmental
effects due to their contribution to climate change. Climate change is expected to result in public
health risks associated with heat waves, increased smog, extreme weather events, and mosquito -
spread diseases among others. Climate change is also expected to affect environmental factors,
such as sea level and acidity. Each of the individual GHG pollutants has a different Global
Warming Potential (GWP), a relative measure of the heat trapped by each gas compared to CO2.
Appendix C — Air Emissions and Energy Use Analysis C-2 September 30, 2016

EPS
The net effect of potential GHG emissions have been normalized to a standard called "CO2
equivalent' (CO2e) based on their relative GWPs.
Additionally, the analysis of GHG emissions includes both direct and indirect GHG emissions.
Direct GHG emissions are those that are emitted directly from the engines used in the earth moving
and material transport involved in the remedial alternatives. Indirect GHG emissions are those
associated with the production of the fuel burned in the engines. These emissions are typically
called "Well -to -Pump" (WTP), which refers to processes and activities involved in producing a
fuel through when that fuel reaches a fueling station. This may include raw material extraction,
transportation, fuel production, distribution, and storage. For the purposes of this study, only WTP
GHG emissions are considered as indirect emissions. Indirect emissions in the PTW (Pump -to -
Wheels) stage, such as refueling and evaporation, are not included as indirect emissions.
C1.3 Energy Consumption
In addition to air emissions, the energy consumed as part of the remedial activities was assessed.
Although there may be some small amounts of electricity used by the monitoring equipment, this
analysis was confined to the energy in the fuels consumed by the earth moving and material
transport equipment involved.
Appendix C — Air Emissions and Energy Use Analysis C-3 September 30, 2016

0
C2 EMISSION ESTIMATION
Air pollutant emissions resulting from the three remedial options were evaluated. As described
above, the pollutants analyzed were restricted to nitrogen oxides (NOX), particulate matter
(PM10/PM2.5), and greenhouse gases (GHG). These were selected as being the pollutants for
which the impact to the environment would be significant, based on experience gained from
analysis of similar projects. Appropriate emission factors were taken from a variety of regulator -
approved sources, such as Off -Road Model Mobile Source Emission Factors from South Coast Air
Quality Management District and Direct Emissions from Mobile Combustion Sources from
USEPA Center for Corporate Climate Leadership. The indirect GHG emissions were developed
from the fuel usages that were determined as part of the energy analysis. Each emission factor
source is referenced in notes below the emissions tables provided at the end of this Appendix
report.
C2.1 Monitored Natural Attenuation
For the first remedial alternative, which consists of leaving the ash in place and periodically
monitoring the groundwater (i.e., Monitored Natural Attenuation (MNA)), it was assumed that the
air emissions would be negligible. Further, even if the minimal emissions associated with
monitoring were evaluated, these emissions would be duplicated for the other two alternatives, as
the monitoring would be required for all three options. Therefore, the first option represents the
baseline for evaluating the emissions from the other two alternatives.
C2.2 Cap -in -Place
For the second alternative, Cap -in -Place (CIP), the emissions from the necessary on-site activities
plus the emissions from the trucks transporting the cap material to the site were evaluated. The
on-site activities consist of earth moving and compacting equipment, on-site trucks, a diesel
generator, and the personal vehicles used by workers to commute to and from the site. For the
truck emissions associated with the transportation of cap material, it was assumed that the material
would be brought from a site 25 miles from the ash ponds. A liner would also be required for this
project, and it is assumed that the liner would be transported from a facility 100 miles away. This
evaluation focuses primarily on the direct emissions from the engines associated with the on-site
activities and truck transport. Indirect GHG emissions were also analyzed and added to the direct
GHG emissions to provide a more complete carbon footprint. Estimates for fugitive dust from
unpaved roads and material handling are not included although it is expected that some of the dust
would be PM10 or, to a significantly lesser extent, PM2.5. The duration of the project was
determined based on the amount of material needed to cap the ash ponds.
Appendix C — Air Emissions and Energy Use Analysis C-4 September 30, 2016

0
C2.3 Removal
The third alternative, Removal, included emissions from on-site activities at both the ash pond
location and the landfill site. The emissions from truck transport between the sites were also
evaluated. It was assumed for estimating purposes that the landfill would be located 25 miles from
the ash ponds. It was also assumed that the liner would be brought from a facility located 100 miles
from the ash ponds, and the closure material would be taken from an adjacent land parcel
approximately 1 mile from the ash ponds. The on-site activities at the ash pond includes equipment
similar to what is needed for the CIP alternative. At the landfill, the analysis includes the activities
required to construct the landfill, the operation of the landfill while ash is being received, and the
closure of the landfill. The durations were determined based on the amount of material that would
be transported during each phase. The analysis includes the direct emissions from the various
activities and truck transport plus the indirect GHG emissions, but does not include fugitive dust
emissions.
Appendix C — Air Emissions and Energy Use Analysis C-5 September 30, 2016

0
C3 ENERGY ANALYSIS
Energy consumption for the three remedial options was evaluated. As described previously, the
energy analysis was restricted to the energy contained in the fuels combusted in various engines.
The fuel usage was determined using the data developed as part of the emissions analysis.
Additionally, typical fuel efficiency factors were taken from the USDOT Bureau of Transportation
Statistics as noted in the appended calculations. Each emission factor source is referenced in notes
below the emissions tables appended to this Appendix report.
C3.1 MNA
For the first remedial alternative, which consists of leaving the ash in place and routinely
monitoring the groundwater, it was assumed that the energy consumption would be negligible.
C3.2 CIP
For the second alternative, CIP, the energy consumption from the necessary on-site activities plus
the energy consumed by trucks transporting the cap material to the site were evaluated. The on-
site activities consist of earth moving and compacting equipment, on-site trucks, a diesel generator,
and the personal vehicles used by workers to commute to and from the site. The duration of the
project was determined based on the amount of material needed to cap the ash ponds.
C3.3 Removal
The third alternative, Removal, included energy consumption from on-site activities at both the
ash pond location and the landfill site. The energy consumed by truck transport between the sites
were also evaluated. For the truck energy usage, the same assumptions were made regarding the
transportation of ash, closure material, and liner as used in the Removal estimates. The on-site
activities at the ash pond includes equipment similar to what is needed for the CIP alternative. At
the landfill, the analysis includes the activities required to construct the landfill, the operation of
the landfill while ash is being received, and the closure of the landfill. The durations were
determined based on the amount of material that would be transported during each phase.
Appendix C — Air Emissions and Energy Use Analysis C-6 September 30, 2016

0
C4 RESULTS
The emissions estimates for each scenario are shown in the attached table, along with any
assumptions and the sources of the emission factors. The results are reiterated in the following
table. The PM10 and PM2.5 are combined as a single entry because the emission factor data does
not distinguish between them. It can be assumed that the majority of the PM emissions are actually
PM2.5, as they are they are the products of diesel fuel combustion, which primarily consists of
very fine particulates. The GHG emissions are shown on an annual emissions basis (tons/yr) and
cumulatively over the duration of the project, as their effects are cumulative unlike the criteria
pollutants for which the impact is much shorter in duration.
C4.1 Estimated Emissions
The air emissions from each of the sites and for both the CIP and Removal alternatives are
summarized in the table below:
As shown in the table, the NO. emissions from the CIP scenario are about 29 tons/yr for each site,
which is below the significance level of 40 tons/yr established in the federal Prevention of
Appendix C — Air Emissions and Energy Use Analysis C-7 September 30, 2016
PM10/PM2.5
Cumulative CO2e
C.,
NO. Emissions
CO2e Emissions
Scenario
Emissions
Emissions
Cn
(tons/yr)
(tons/yr)
(tons/yr)
(tons)
Cap in Place
29.20
1.01
7,376
38,302
Removal
143.01
6.12
30,940
465,225
Cap in Place
29.20
1.01
7,377
21,423
U
Removal
143.05
6.12
30,955
133,969
Cap in Place
29.43
1.02
7,446
22,339
w
w
U
Removal
143.00
6.12
30,939
197,208
Cap in Place
29.02
1.01
7,322
18,304
o
Removal
143.05
6.12
30,953
165,651
.�
PSD Significant
40
15/10
NA
NA
Threshold
GHG Reporting
H
Threshold
NA
NA
25,000
NA
As shown in the table, the NO. emissions from the CIP scenario are about 29 tons/yr for each site,
which is below the significance level of 40 tons/yr established in the federal Prevention of
Appendix C — Air Emissions and Energy Use Analysis C-7 September 30, 2016

0
Significant Deterioration (PSD) regulations. The emissions from the Removal alternative are
much more significant and are typically about 143 tons/yr for each site, well above the PSD
Threshold. Under the PSD rules, a project with emissions at this level would require an extensive
permitting process, including air dispersion modeling to demonstrate that the emissions would not
cause an exceedance of the National Ambient Air Quality Standards.
The PM10/PM2.5 emissions for the CIP option are less than the NOX emissions, but the PSD
significance thresholds are also much lower for this pollutant. As shown, the PM10/PM2.5
emissions for each site from the CIP alternative are estimated to be about 1 ton/yr and from the
Removal alternative are about 6 tons/yr. It is important to remember that these values only include
particulate matter from fuel combustion. If the fugitive dust emissions from material handling and
unpaved roads were added, recognizing that some of this particulate matter would be larger than
10 microns, the total PM10/PM2.5 emissions would be much higher.
Finally, the estimated GHG emissions from the Removal alternative is also fairly significant.
Although there are few regulations limiting GHG emissions at this time, USEPA has begun
requiring sources that emit 25,000 tons or more of CO2e annually to report those emissions to
USEPA. This effort is being pursued by USEPA in order to develop a database of major emitters
and in anticipation of future regulations. The annual GHG emissions for the CIP option (7,400
tons/yr for each site) are below this threshold, but the annual GHG emissions for the Removal
option (31,000 tons/yr for each site) exceed this threshold.
Based on the estimated air emissions and their comparisons with regulatory thresholds, it is
apparent that the air quality impact from the CIP alternative would be considerably higher than
NINA. The air emissions from Removal and transporting it to a landfill would be even more
substantial.
C4.2 Estimated Energy Consumption
The energy consumption annually and cumulatively across the duration of the projects for both the
CIP and Removal alternatives are summarized in the tables below:
Annual Energy Consumed
Scenario
Energy Consumed (MMBtu/yr)
Allen
Buck
Cliffside
Mayo
Total
Cap in Place
82,040
82,040
82,574
81,621
328,274
Removal
441,541
441,652
441,533
441,640
1,766,366
Appendix C — Air Emissions and Energy Use Analysis C-8 September 30, 2016

Cumulative Energy Consumed
Scenario
Total Energy Consumed (MMBtu)
Allen
Buck
Cliffside
Mayo
Total
Cap in Place
446,861
242,972
255,655
210,687
1,156,174
Removal
5,648,213
1,614,833
2,379,322
2,007,693
11,650,061
Energy Consumption Comparison
Scenario
Equivalent Personal Vehicles (vehicles*)
Allen
Buck
Cliffside
Mayo
Total**
Cap in Place
1,800
1,800
1,800
1,800
7,200
Removal
9,700
9,700
9,700
9,700
39,000
*Personal vehicles commuting five days a week for the duration of the project
**Note that the projects have varying durations, and the Total only applies when all projects are occurring simultaneously
As shown, the CIP alternative would consume approximately 82,000 MMBtu/yr for each
individual site and about 329,000 MMBtu/yr collectively. For comparison, a personal vehicle
travelling 10 miles to work and back five days a week would consume about 45.6 MMBtu/yr in
gasoline. Therefore, the energy consumption for the CIP option for all three sites is equivalent to
about 7,200 personal vehicles commuting five days a week. The Removal alternative would
consume even more. As shown in the table, Removal at each site would consume about 442,000
MMBtu/yr, which corresponds to about 1,766,000 MMBtu/yr collectively. This is equivalent to
about 39,000 vehicles commuting 5 days a week.
Additionally, the second table presents the energy consumed for the entire duration of each project.
As shown, the Removal alternative would consume about 11.7 million MMBtu's cumulatively;
whereas the CIP alternative would consume only about 1.2 million MMBtu's.
Appendix C — Air Emissions and Energy Use Analysis C-9 September 30, 2016

Table 1. Summary of Air Emissions and Energy Usage
Appendix C - Air Emissions and Energy Analysis C-10 September 30, 2016
REMOVAL
CIP
Site
NOx
Emissions
(tons/yr)
PM10/PM2.5
Emissions
(tons/yr)
Total GHG
Emissions
(tons CO2e/yr)
Cumulative Total
GHG Emissions
(tons CO2e)
Energy Usage
(MMBtu/yr)
Cumulative
Energy Usage
(MMBtu)
NOx Emissions
(tons/yr)
PM10/PM2.5
Emissions
(tons/yr)
Total GHG
Emissions
(tons CO2e/yr)
Cumulative Total
GHG Emissions
(tons CO2e)
Energy Usage
(MMBtu/yr)
Cumulative
Energy Usage
(MMBtu)
Allen
143.01
6.12
30,940.04
465,224.76
441,541
5,648,213
29.20
1.01
7,376.46
38,302.34
82,040
446,861
Buck
143.05
6.12
30,954.67
133,968.79
441,652
1,614,833
29.20
1.01
7,376.55
21,422.52
82,040
242,972
Cliffside
143.00
6.12
30,939.07
197,207.80
441,533
2,379,322
29.43
1.02
7,446.20
22,338.61
82,574
255,655
Mayo
143.05
6.12
30,953.04
165,651.27
441,640
2,007,693
29.02
1.01
7,321.77
18,304.42
81,621
210,687
Total
572.11
24.49
123,786.81
962,052.62
1,766,366
11,650,061
116.85
4.06
29,520.98
100,367.88
328,274
1,156,174
Thresholds
PSD
Significant
Threshold
40
15/10
NA
NA
NA
NA
40
15/10
NA
NA
NA
NA
GHG
Reporting
Threshold
NA
NA
25,000
NA
NA
NA
NA
NA
25,000
NA
NA
NA
Appendix C - Air Emissions and Energy Analysis C-10 September 30, 2016

Alternative 1:
MNA
AIR EMISSIONS - ALLEN
Page 1 of 3
Since similar monitoring would be required for each option for the project duration, similar emissions are expected for each and the emissions are not included in this estimate. It is expected that the emissions contributions from personal
vehicles due to monitoring would be insignificant compared to the other emission sources.
Alternative 2:
CIP
CIP Duration = 12 hr/day 270 day/yr 5.2 years 140198 truck trips carrying cap material
203 truck trips carrying liner material
Appendix C - Air Emissions and Energy Analysis C-11 September 30, 2016
Usage
NOx
Emission Factors
PMID/PM2.5 Direct CO2
Direct CH4
Emissions
(tons/yr)
Cumulative Emissions
(tons CO2e)
Activity
Value Units
Value Units
Value Units
Value Units
Value Units
NOx
PMIo/PM2.5
Direct GHG (CO,e)
Direct GHG
2 Dozers'
6480 hr/yr
2.0891 Ib/hr
0.0858 Ib/hr
239 Ib/hr
0.0234 Ib/hr
6.77
0.28
776.26
4030.71
Tractor'
3240 hr/yr
0.4070 Ib/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
563.07
Wheeled Backhoe'
3240 hr/yr
0.4070 Ib/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
563.07
Water Truck'
3240 hr/yr
1.3322 Ib/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
2190.53
Vibratory Roller'
3240 hr/yr
0.5273 Ib/hr
0.0353 Ib/hr
67 Ib/hr
0.0071 Ib/hr
0.85
0.06
108.83
565.09
Tracked Excavator'
3240 hr/yr
0.6603 Ib/hr
0.0332 Ib/hr
120 Ib/hr
0.0089 Ib/hr
1.07
0.051
194.76
1011.30
Maint/Service Truck'
3240 hr/yr
1.3322 Ib/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
2190.53
55 KVA Diesel Generator'
3240 hr/yr
0.6102 Ib/hr
0.0431 Ib/hr
77.9 Ib/hr
0.0073 Ib/hr
0.99
0.07
126.49
656.82
15 Personal Vehicles2,3,4,5,6
121500 miles r
/y
0.95 g/mile
0.0045 g/mile
410 g/mile
0.0452 g/mile
0.13
0.00
55.10
286.11
Truck Transport - Cap Materia 17,8,9,10
27000 truck trips/yr
459.55 g/truck trip
10.75 g/truck trip
138000 g/truck trip
0.255 g/truck trip
13.68
0.32
4107.41
21327.78
Truck Transport - Liner Materia
p
39 truck tris r
p /y
1838.201g/truck trip I
43.00 g/truck trip I
552000 g/truck trip
1.02 g/truck trip
0.08
0.00
23.79
123.53
29.20 1
1.011
6,453.24
33,508.54
Appendix C - Air Emissions and Energy Analysis C-11 September 30, 2016

Alternative 3:
Landfill Construction Duration =
Excavation Duration =
Closure Duration =
Removal
12 hr/day 300 day/yr 3.6 years 204 truck trips carrying liner material (construction & closure)
12 hr/day 270 day/yr 35.7 years 963500 truck trips carrying ash
12 hr/day 270 day/yr 2.0 years 33091 truck trips carrying closure material
AIR EMISSIONS - ALLEN
Page 2 of 3
Appendix C - Air Emissions and Energy Analysis C-12 September 30, 2016
Usage
NOx
Emission Factors
PM1./PM2.5 Direct CO2
Direct CH,
Emissions
(tons/yr)
Cumulative Emissions
(tons CO2e)
Activity
Value Units
Value Units
Value Units
Value Units
Value Units
NOx
PM,O/PM2,s
Direct GHG (CO2e)
Direct GHG
EXCAVATION
2 Tracked Excavators'
6480 hr/yr
0.6603 Ib/hr
0.0332 Ib/hr
120 Ib/hr
0.0089 Ib/hr
2.14
0.11
389.52
13905.90
2 Dozers'
6480 hr/yr
2.0891 Ib/hr
0.0858 Ib/hr
239 Ib/hr
0.0234 Ib/hr
6.77
0.28
776.26
27712.32
Wheeled Loader'
3240 hr/yr
0.7114 Ib/hr
0.0375 Ib/hr
109 Ib/hr
0.0089 Ib/hr
1.15
0.06
176.94
6316.77
2 Dump Trucks'
6480 hr/yr
0.0587 Ib/hr
0.0024 Ib/hr
7.6 Ib/hr
0.0008 Ib/hr
0.19
0.01
24.69
881.39
Water Truck'
3240 hr/yr
1.3322 Ib/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
15060.55
Wheeled Backhoe'
3240 hr/yr
0.4070 Ib/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
3871.26
2 6-8" Pumps'
6480 hr/yr
0.3830 Ib/hr
0.0239 Ib/hr
49.6 Ib/hr
0.0051 Ib/hr
1.24
0.08
161.12
5751.88
55 KVA Diesel Generator'
3240 hr/yr
0.6102 Ib/hr
0.0431 Ib/hr
77.9 Ib/hr
0.0073 Ib/hr
0.99
0.07
126.49
4515.82
15 Personal Vehicles 7,3,4,5
121500 miles r
/y
0.95 g/mile
0.0045 g/mile
410 g/mile
0.0452 g/mile
0.13
0.00
55.10
1967.09
MATERIAL TRANSPORT
Truck Transport - Ash
p
26989 truck tri s/yr
p
459.55 g/truck trip
10.75 g/truck trip
138000 g/truck trip
0.2550 g/truck trip
13.67
0.32
4105.70
146573.51
Truck Transport - Closure Materia
pg/truck
16546 truck trips/yr
18.38 trip
0.43 g/truck trip
5520 g/truck trip
0.0102 g/truck trip
0.34
0.01
100.68
201.36
Truck Transport - Liner Materia
p
36 truck tri s/yr
p
1838.20 g/truck trip
43 g/truck trip
552000 g/truck trip
1.0200 g/truck trip
0.07
0.00
22.17
124.13
LANDFILL CONSTRUCT.
8 Tracked Excavators'
28800 hr/yr
0.6603 Ib/hr
0.0332 Ib/hr
120 Ib/hr
0.0089 Ib/hr
9.51
0.48
1731.20
9694.74
8 Dozers'
28800 hr/yr
2.0891 lb/hr
0.0858 Ib/hr
239 Ib/hr
0.0234 Ib/hr
30.08
1.24
3450.02
19320.13
4 Vibratory Compactors'
14400 hr/yr
0.568 Ib/hr
0.0234 Ib/hr
123 Ib/hr
0.0065 Ib/hr
4.09
0.17
886.77
4965.91
4 Wheeled Loaders'
14400 hr/yr
0.7114 Ib/hr
0.0375 Ib/hr
109 Ib/hr
0.0089 Ib/hr
5.12
0.27
786.40
4403.85
8 Dump Trucks'
28800 hr/yr
0.0587 Ib/hr
0.0024 Ib/hr
7.6 Ib/hr
0.0008 Ib/hr
0.85
0.03
109.73
614.48
4 Water Trucks'
14400 hr/yr
1.3322 Ib/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
9.59
0.33
1874.95
10499.73
4 Wheeled Backhoes'
14400 hr/yr
0.4070 Ib/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
2.93
0.19
481.95
2698.92
8 6-8" Pumps'
28800 hr/yr
0.3830 Ib/hr
0.0239 Ib/hr
49.6 Ib/hr
0.0051 Ib/hr
5.52
0.34
716.08
4010.03
4 Maint/Service Trucks'
14400 hr/yr
1.3322 Ib/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
9.59
0.33
1874.95
10499.73
4 55 KVA Diesel Generator'
14400 hr/yr
0.6102 Ib/hr
0.0431 Ib/hr
77.9 Ib/hr
0.0073 Ib/hr
4.39
0.31
562.19
3148.29
100 Personal Vehicles2,3,4;5
900000 miles/yr
0.95 g/mile
0.0045 g/mile
410 g/mile
0.0452 g/mile
0.94
0.00
408
2285.65
LANDFILL FILLING
2 Dozers'
6480 hr/yr
2.0891 Ib/hr
0.0858 Ib/hr
239 Ib/hr
0.0234 Ib/hr
6.77
0.28
776.26
27712.32
Tractor'
3240 hr/yr
0.4070 Ib/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
3871.26
Wheeled Backhoe'
3240 hr/yr
0.4070 Ib/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
3871.26
Water Truck'
3240 hr/yr
1.3322 Ib/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
15060.55
Vibratory Roller'
3240 hr/yr
0.5273 Ib/hr
0.0353 Ib/hr
67 Ib/hr
0.0071 Ib/hr
0.85
0.06
108.83
3885.14
Tracked Excavator'
3240 hr/yr
0.6603 Ib/hr
0.0332 Ib/hr
120 Ib/hr
0.0089 Ib/hr
1.07
0.05
194.76
6952.95
Maint/Service Truck'
3240 hr/yr
1.3322 Ib/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr 1
2.16
0.07
421.86
15060.55
55 KVA Diesel Generator'
3240 hr/yr
0.6102 Ib/hr
0.0431 Ib/hr
77.9 Ib/hr
0.0073 Ib/hr 1
0.99
0.07
126.49
4515.82
15 Personal Vehicles2,3'4,5,6
121500 miles/yr
0.95 g/mile
0.0045 g/mile
410 g/mile I
0.0452 g/mile 1
0.13
0.00
55.10
1967.09
Appendix C - Air Emissions and Energy Analysis C-12 September 30, 2016

AIR EMISSIONS - ALLEN
Page 3 of 3
Notes:
1. South Coast Air Quality Management District Off -Road Model Mobile Source Emission Factors for a 2016 fleet average from http://www.agmd.gov/home/regulations/ceqa/air-quality-analysis-handbook/off-road-mobile-source-emission-
factors.
2. USEPA Center for Corporate Climate Leadership Greenhouse Gas Inventory Guidance: Direct Emissions from Mobile Combustion Sources Tier 1 Gasoline Light -Duty Truck emission factors (0.0452 g CH4/mile) from
https://www.epa.gov/sites/prod uction/fi les/2016-03/documents/mobi leem issions_3_2016.pdf.
3. Personally Operated Vehicle (POV) use is estimated as:
-Excavation: 15 persons/day * 30 miles/person * 270 day/yr (it is assumed each person travels 15 -miles one-way to work);
-Landfill Construction: 25 persons/day * 30 miles/person * 270 day/yr.
4. USDOT Bureau of Transportation Statistics Average Fuel Efficiency of U.S. Light Duty Vehicles for calendar year 2014 (21.4 miles/gal) for POV CO2 emissions from
http://www. rita.dot.gov/bts/sites/rita.dot.gov. bts/fi les/publications/nationa I_tra nsportation_statistics/htm I/ta ble_04_23. htm I.
5. 100 -yr GWP for CH4 (25 kg CO2e/kg CH4) from Intergovernmental Panel on Climate Change (IPCC), Fourth Assessment Report (AR4), 2007.
6. USEPA Office of Transportation and Air Quality Average Annual Emissions and Fuel Consumption for Gasoline -Fueled Passenger Cars and Light Trucks light-duty trucks emissions estimates for the in -use fleet as of 2008 based on
https://www3.epa.gov/otaq/consumer/42OfO8O24.pdf.
7. It is assumed that the landfill location is 25 miles away, so 1 truck trip carrying ash is 50 miles, and 20 -ton trucks are used. It is assumed that the landfill cap/closure material for Option 3 is taken from an adjacent land parcel, thus 1 truck
trip carrying cap/closure material is taken to be 2 miles. It is assumed that the landfill cap/closure material for Option 2 is taken from a site 25 miles aways, so 1 truck trip carrying cap/closure material for Option 2 is taken to be 50 miles.
8. USEPA Office of Transportation and Air Quality Average In -Use Emissions from Heavy -Duty Trucks NOx and PM10/PM2.5 emission factors approximated as a diesel Heavy -Duty Vehicle Class Villa (33,001-60,000 Ib GVWR--since it is for 20
ton (40,000 Ib) material + truck) --based on the in -use fleet from July 2008 from https://www3.epa.gov/otaq/consumer/42OfO8O27.pdf.
9. USEPA Center for Corporate Climate Leadership Emission Factors for Greenhouse Gas Inventories greenhouse gas emission factors approximated as heavy duty vehicles for 1960 -present from Table 4 of
https://www.epa.gov/sites/production/files/2015-12/documents/emission-factors_nov_2015.pdf, dated November 2015.
10. It is assumed that the weight of the vehicle + load is approximately 60,000 Ib (20 -ton load and 10 -ton truck). Diesel heavy duty combination truck CO2 emission factor for MY2014/Class 8/Day Cab is 92 g CO2/ton-mile taken from
https://www.gpo.gov/fdsys/pkg/FR-2011-09-15/pdf/2011-20740.pdf (EPA/DOT Federal Register Vol. 76, No. 179, 15 September 2011).
-92 g CO2/ton-mile * (30 ton*x mile)/truck trip = y g CO2/truck trip
11. It is assumed that the liner is transported 100 miles to the site/landfill on public roads and approximately 10 tons of liner are transported per trip (3240 Ib/roll * 1 ton/2000 Ib * 6 rolls/truck trip = 10 ton/truck trip).
Appendix C - Air Emissions and Energy Analysis C-13 September 30, 2016
Usage
NOx
Emission Factors
PMI0/PM2.5 Direct CO2
Direct CH4
Emissions
(tons/yr)
Cumulative Emissions
(tons CO2e)
Activity
Value Units
Value Units
Value Units
Value Units
Value Units
NOx
PMI0/PM2.5
Direct GHG (CO2e)
Direct GHG
LANDFILL CLOSURE
2 Dozers'
6480 hr/yr
2.0891 Ib/hr
0.0858 Ib/hr
239 Ib/hr
0.0234 Ib/hr
6.77
0.28
776.26
1552.51
Tractor'
3240 hr/yr
0.4070 Ib/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
216.88
Wheeled Backhoe'
3240 hr/yr
0.4070 Ib/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
216.88
Water Truck'
3240 hr/yr
1.3322 Ib/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
843.73
Vibratory Roller'
3240 hr/yr
0.5273 Ib/hr
0.0353 Ib/hr
67 Ib/hr
0.0071 Ib/hr
0.85
0.06
108.83
217.66
Tracked Excavator'
3240 hr/yr
0.6603 Ib/hr
0.0332 Ib/hr
120 Ib/hr
0.0089 Ib/hr
1.07
0.05
194.76
389.52
Maint/Service Truck'
3240 hr/yr
1.3322 Ib/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
843.73
55 KVA Diesel Generator'
3240 hr/yr
0.6102 Ib/hr
0.0431 Ib/hr
77.9 Ib/hr
0.0073 Ib/hr
0.99
0.07
126.49
252.99
15 Personal Vehicles2,3,4,5,6
121500 miles/yr
0.95 g/mile
0.0045 g/mile
410 g/mile
0.0452 g/mile
0.13
0.00
55.10
110.20
143.01
6.12
23,995.46
386,564.50
Notes:
1. South Coast Air Quality Management District Off -Road Model Mobile Source Emission Factors for a 2016 fleet average from http://www.agmd.gov/home/regulations/ceqa/air-quality-analysis-handbook/off-road-mobile-source-emission-
factors.
2. USEPA Center for Corporate Climate Leadership Greenhouse Gas Inventory Guidance: Direct Emissions from Mobile Combustion Sources Tier 1 Gasoline Light -Duty Truck emission factors (0.0452 g CH4/mile) from
https://www.epa.gov/sites/prod uction/fi les/2016-03/documents/mobi leem issions_3_2016.pdf.
3. Personally Operated Vehicle (POV) use is estimated as:
-Excavation: 15 persons/day * 30 miles/person * 270 day/yr (it is assumed each person travels 15 -miles one-way to work);
-Landfill Construction: 25 persons/day * 30 miles/person * 270 day/yr.
4. USDOT Bureau of Transportation Statistics Average Fuel Efficiency of U.S. Light Duty Vehicles for calendar year 2014 (21.4 miles/gal) for POV CO2 emissions from
http://www. rita.dot.gov/bts/sites/rita.dot.gov. bts/fi les/publications/nationa I_tra nsportation_statistics/htm I/ta ble_04_23. htm I.
5. 100 -yr GWP for CH4 (25 kg CO2e/kg CH4) from Intergovernmental Panel on Climate Change (IPCC), Fourth Assessment Report (AR4), 2007.
6. USEPA Office of Transportation and Air Quality Average Annual Emissions and Fuel Consumption for Gasoline -Fueled Passenger Cars and Light Trucks light-duty trucks emissions estimates for the in -use fleet as of 2008 based on
https://www3.epa.gov/otaq/consumer/42OfO8O24.pdf.
7. It is assumed that the landfill location is 25 miles away, so 1 truck trip carrying ash is 50 miles, and 20 -ton trucks are used. It is assumed that the landfill cap/closure material for Option 3 is taken from an adjacent land parcel, thus 1 truck
trip carrying cap/closure material is taken to be 2 miles. It is assumed that the landfill cap/closure material for Option 2 is taken from a site 25 miles aways, so 1 truck trip carrying cap/closure material for Option 2 is taken to be 50 miles.
8. USEPA Office of Transportation and Air Quality Average In -Use Emissions from Heavy -Duty Trucks NOx and PM10/PM2.5 emission factors approximated as a diesel Heavy -Duty Vehicle Class Villa (33,001-60,000 Ib GVWR--since it is for 20
ton (40,000 Ib) material + truck) --based on the in -use fleet from July 2008 from https://www3.epa.gov/otaq/consumer/42OfO8O27.pdf.
9. USEPA Center for Corporate Climate Leadership Emission Factors for Greenhouse Gas Inventories greenhouse gas emission factors approximated as heavy duty vehicles for 1960 -present from Table 4 of
https://www.epa.gov/sites/production/files/2015-12/documents/emission-factors_nov_2015.pdf, dated November 2015.
10. It is assumed that the weight of the vehicle + load is approximately 60,000 Ib (20 -ton load and 10 -ton truck). Diesel heavy duty combination truck CO2 emission factor for MY2014/Class 8/Day Cab is 92 g CO2/ton-mile taken from
https://www.gpo.gov/fdsys/pkg/FR-2011-09-15/pdf/2011-20740.pdf (EPA/DOT Federal Register Vol. 76, No. 179, 15 September 2011).
-92 g CO2/ton-mile * (30 ton*x mile)/truck trip = y g CO2/truck trip
11. It is assumed that the liner is transported 100 miles to the site/landfill on public roads and approximately 10 tons of liner are transported per trip (3240 Ib/roll * 1 ton/2000 Ib * 6 rolls/truck trip = 10 ton/truck trip).
Appendix C - Air Emissions and Energy Analysis C-13 September 30, 2016

Alternative 1:
MNA
INDIRECT GHG EMISSIONS -ALLEN
Page 1 of 4
Since similar monitoring would be required for each option for the project duration, similar emissions are expected for each and the emissions are not included in this estimate. It is
expected that the emissions contributions from personal vehicles due to monitoring would be insignificant compared to the other emission sources.
Alternative 2:
CIP
CIP Duration = 12 hr/day 270 day/yr 5.2 years 140198 truck trips carrying cap material
203 truck trips carrying liner material
Activity
Number
of Units
Usage
Value Units
Annual Total
Energy Usage
Value Units
Total Project
GGE
Value Units
WTP (Indirect)
GHG Emissionss
Value Units
Project Indirect
GHG Emissions
Value Units
Dozers
2
6480 hr/yr
18319.9 MMBtu/yr
152062.6 GGE/yr
308 tons CO2e/yr
1599 tons CO2e
Tractor
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons CO2e/yr
240 tons CO2e
Wheeled Backhoe
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons CO2e/yr
240 tons CO2e
Water Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons CO2e/yr
800 tons CO2e
Vibratory Roller
1
3240 hr/yr
2198.4 MMBtu/yr
18247.5 GGE/yr
37 tons CO2e/yr
192 tons CO2e
Tracked Excavator
1
3240 hr/yr
3664.0 MMBtu/yr
30412.5 GGE/yr
62 tons CO2e/yr
320 tons CO2e
Maint/Service Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons CO2e/yr
800 tons CO2e
55 KVA Diesel Generator
1
3240 hr/yr
1080.9 MMBtu/yr
8971.7 GGE/yr
18 tons CO2e/yr
94 tons CO2e
Personal Vehicles
15
121500 miles/yr
10 tons CO2e/yr
53 tons CO2e
Truck Transport - Cap Material
N/A
27000 truck trips/yr
1350000 miles/yr
87 tons CO2e/yr
454 tons CO2e
Truck Transport - Liner Materia 12,3
N/A
39 truck trips/yr
7835 miles/yr
0.5 tons CO2e/yr
3 tons CO2e
923 Itons CO2e/yr
4,794 Itons CO2e
Appendix C - Air Emissions and Energy Analysis C-14 September 30, 2016

Alternative 3:
Landfill Construction Duration =
Excavation Duration =
Closure Duration =
Removal
12 hr/day 300 day/yr
12 hr/day 270 day/yr
12 hr/day 270 day/yr
INDIRECT GHG EMISSIONS -ALLEN
3.6 years 204 truck trips
35.7 years 963500 truck trips
2 years 33091 truck trips
Page 2 of 4
carrying liner material
carrying ash
carrying closure material
Activity
Number
of Units
Total Usage
Value Units
Annual Total
Energy Usage
Value Units
Total Project
GGE
Value Units
WTP (Indirect)
GHG Emissions5
Value Units
Project Indirect
GHG Emissions
Value Units
EXCAVATION
Tracked Excavators
2
6480 hr/yr
7328.0 MMBtu/yr
60825.0 GGE/yr
123 tons CO2e/yr
4398 tons CO2e
Dozers
2
6480 hr/yr
18319.9 MMBtu/yr
152062.6 GGE/yr
308 tons CO2e/yr
10995 tons CO2e
Wheeled Loader
1
3240 hr/yr
3206.0 MMBtu/yr
26611.0 GGE/yr
54 tons CO2e/yr
1924 tons CO2e
Dump Trucks
2
6480 hr/yr
916.0 MMBtu/yr
7603.1 GGE/yr
15 tons CO2e/yr
550 tons CO2e
Water Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons CO2e/yr
5497 tons CO2e
Wheeled Backhoe
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons CO2e/yr
1649 tons CO2e
6-8" Pumps
2
6480 hr/yr
3664.0 MMBtu/yr
30412.5 GGE/yr
62 tons CO2e/yr
2199 tons CO2e
55 KVA Diesel Generator
1
3240 hr/yr
1080.9 MMBtu/yr
8971.7 GGE/yr
18 tons CO2e/yr
649 tons CO2e
Personal Vehicles
15
121500 miles/yr
10 tons CO2e/yr
367 tons CO2e
MATERIAL TRANSPORT
Truck Transport - Ash
N/A
26989 truck trips/yr
1349440 miles/yr
87 tons CO2e/yr
3118 tons CO2e
Truck Transport - Closure Materia 12
N/A
16546 truck trips/yr
33091 miles/yr
2 tons CO2e/yr
4 tons CO2e
Truck Transport - Liner Materia 12,3
N/A
36 truck trips/yr
7291 miles/yr
0.5 tons CO2e/yr
3 tons CO2e
LANDFILL CONSTRUCTION
Tracked Excavators
8
28800 hr/yr
32568.7 MMBtu/yr
270333.5 1 GGE/yr
548 tons CO2e/yr
1971 tons CO2e
Dozers
8
28800 hr/yr
81421.8 MMBtu/yr
675833.9 GGE/yr
1369 tons CO2e/yr
4928 tons CO2e
Vibratory Compactors
4
14400 hr/yr
9770.6 MMBtu/yr
81100.1 GGE/yr
164 tons CO2e/yr
591 tons CO2e
Wheeled Loaders
4
14400 hr/yr
14248.8 MMBtu/yr
118270.9 GGE/yr
240 tons CO2e/yr
862 tons CO2e
Dump Trucks
8
28800 hr/yr
4071.1 MMBtu/yr
33791.7 GGE/yr
68 tons CO2e/yr
246 tons CO2e
Water Trucks
4
14400 hr/yr
40710.9 MMBtu/yr
337916.9 GGE/yr
684 tons CO2e/yr
2464 tons CO2e
Wheeled Backhoes
4
14400 hr/yr
12213.3 MMBtu/yr
101375.1 GGE/yr
205 tons CO2e/yr
739 tons CO2e
Appendix C - Air Emissions and Energy Analysis C-15 September 30, 2016

INDIRECT GHG EMISSIONS -ALLEN
Page 3 of 4
Activity
Number
of Units
Total Usage
Value Units
Annual Total
Energy Usage
Value Units
Total Project
GGE
Value Units
WTP (Indirect)
GHG Emissionss
Value Units
Project Indirect
GHG Emissions
Value Units
6-8" Pumps
8
28800 hr/yr
16284.4 MMBtu/yr
135166.8 GGE/yr
274 tons CO2e/yr
986 tons CO2e
Maint/Service Trucks
4
14400 hr/yr
40710.9 MMBtu/yr
337916.9 GGE/yr
684 tons CO2e/yr
2464 tons CO2e
55 KVA Diesel Generators
4
14400 hr/yr
4803.9 MMBtu/yr
39874.2 GGE/yr
81 tons CO2e/yr
291 tons CO2e
Personal Vehicles
100
900000 miles/yr
76 tons CO2e/yr
274 tons CO2e
LANDFILL FILLING
Dozers
2
6480 hr/yr
18319.9 MMBtu/yr
152062.6 GGE/yr
308 tons CO2e/yr
10995 tons CO2e
Tractor
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons CO2e/yr
1649 tons CO2e
Wheeled Backhoe
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons CO2e/yr
1649 tons CO2e
Water Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons CO2e/yr
5497 tons CO2e
Vibratory Roller
1
3240 hr/yr
2198.4 MMBtu/yr
18247.5 GGE/yr
37 tons CO2e/yr
1319 tons CO2e
Tracked Excavator
1
3240 hr/yr
3664.0 MMBtu/yr
30412.5 GGE/yr
62 tons CO2e/yr
2199 tons CO2e
Maint/Service Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons CO2e/yr
5497 tons CO2e
55 KVA Diesel Generator
1
3240 hr/yr
1080.9 MMBtu/yr
8971.7 GGE/yr
18 tons CO2e/yr
649 tons CO2e
Personal Vehicles
15
121500 miles/yr
10 tons CO2e/yr
367 tons CO2e
LANDFILL CLOSURE
Dozers
2
6480 hr/yr
18319.9 MMBtu/yr
152062.6 GGE/yr
308 tons CO2e/yr
616 tons CO2e
Tractor
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons CO2e/yr
92 tons CO2e
Wheeled Backhoe
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons CO2e/yr
92 tons CO2e
Water Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons CO2e/yr
308 tons CO2e
Vibratory Roller
1
3240 hr/yr
2198.4 MMBtu/yr
18247.5 GGE/yr
37 tons CO2e/yr
74 tons CO2e
Tracked Excavator
1
3240 hr/yr
3664.0 MMBtu/yr
30412.5 GGE/yr
62 tons CO2e/yr
123 tons CO2e
Maint/Service Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons CO2e/yr
308 tons CO2e
55 KVA Diesel Generator
1
3240 hr/yr
1080.9 MMBtu/yr
8971.7 GGE/yr
18 tons CO2e/yr
36 tons CO2e
Personal Vehicles
15 1
121500 miles/yr
10 tons CO2e/yr
21 tons CO2e
6,945 tons CO2e/yr
78,660 Itons CO2e
Appendix C - Air Emissions and Energy Analysis C-16 September 30, 2016

INDIRECT GHG EMISSIONS -ALLEN
Page 4 of 4
Notes:
1. Personally Operated Vehicle use is estimated as:
-Excavation: 15 persons/day * 30 miles/person * 270 day/yr (it is assumed each person travels 15 -miles one-way to work);
-Landfill Construction: 25 persons/day * 30 miles/person * 270 day/yr.
2. It is assumed that the landfill location is 25 miles away, so 1 truck trip carrying ash is 50 miles, and 20 -ton trucks are used. It is assumed that the landfill cap/closure material for
Option 3 is taken from an adjacent land parcel, thus 1 truck trip carrying cap/closure material is taken to be 2 miles. It is assumed that the landfill cap/closure material for Option 2
is taken from a site 25 miles aways, so 1 truck trip carrying cap/closure material for Option 2 is taken to be 50 miles.
3. It is assumed that the liner is transported 100 miles to the site/landfill on public roads and approximately 10 tons of liner are transported per trip
(3240 Ib/roll * 1 ton/2000 Ib * 6 rolls/truck trip = 10 ton/truck trip).
4. U.S. Energy Information Administration, Energy Explained - Energy Units and Calculators, 2015. Used diesel energy content of 137,871 Btu/gal and
gasoline energy content of 120,476 Btu/gal from http://www.eia.gov/energyexplained/?page=about_energy_u nits.
5. GHG emission factors from Results created by ANL on 11/12/2015 using GREETI_2015 version, October 2015 release, Argonne National Laboratory, 2015.
Emission Factors Well -To -Pump (WTP)16
Diesel 59 g CO2e/mi 1837 g CO2e/gge
Gasoline (E10) 77 g CO2e/mi
6. Annual Total Energy Usage values taken from Energy Usage calculations.
7. Conversion factor used: 1 HP = 2544.43 Btu/hr
Abbreviations:
GHG = Greenhouse Gas.
WTP = "Well -to -Pump" (also called Well -to -Tank, or WTT), refers to processes and activities involved in producing a fuel through when that fuel reaches a fueling station. This may
include raw material extraction, transportation, fuel production, distribution, and storage. For the purposes of this study, only WTP GHG emissions are considered as indirect
emissions. Indirect emissions in the PTW (Pump -to -Wheels) stage, such as refueling and evaporation, are not included as indirect emissions.
Appendix C - Air Emissions and Energy Analysis C-17 September 30, 2016

Alternative 1:
MINA
ENERGY USAGE - ALLEN
Page 1 of 4
Since similar monitoring would be required for each option for the project duration, similar energy usages are expected for each and the energy usage is not included in this estimate. It is
expected that the energy usage contributions from personal vehicles due to monitoring would be insignificant compared to the other source of energy usage.
Alternative 2:
CIP
CIP Duration = 12 hr/day 270 day/yr 5.2 years 140198 truck trips carrying cap material
203 truck trips carrying liner material
Activity
Number
of Units
Usage
Value Units
Value Units
Hourly (per Unit)
Energy Usage9
Value Units
Annual Total
Energy Usage
Value Units
Total Project Energy
Usage
Value Units
Estimated Engine Size
Dozers 1,7
2
6480 hr/yr
500 HP each
2.8 MMBtu/hr
18320 MMBtu/yr
95126 MMBtu
Tractors''
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
14269 MMBtu
Wheeled Backhoe 1,7
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
14269 MMBtu
Water Truck l''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
47563 MMBtu
Vibratory Rolled''
1
3240 hr/yr
120 HP each
0.7 MMBtu/hr
2198 MMBtu/yr
11415 MMBtu
Tracked Excavators''
1
3240 hr/yr
200 HP each
1.1 MMBtu/hr
3664 MMBtu/yr
19025 MMBtu
Maint/Service Truck s'7
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
47563 MMBtu
55 KVA Diesel Generators''
1
3240 hr/yr
59 HP each
0.3 MMBtu/hr
1081 MMBtu/yr
5612 MMBtu
Fuel Usage
Personal VehicleS2'3'8
15
121500 miles/yr
5678 gal/yr
684 MMBtu/yr
24419 MMBtu
Truck Transport - Cap Materia 14,6,8
N/A
27000 truck trips/yr
1350000 miles/yr
232759 gal/yr
32091 MMBtu/yr
166631 MMBtu
Truck Transport - Liner Material °' 5' 6'8
N/A
39 truck trips/yr
7835 miles/yr
1351 gal/yr
186 MMBtu/yr
967 MMBtu
82,040 MMBtu/yr
446,861 MMBtu
Appendix C - Air Emissions and Energy Analysis C-18 September 30, 2016

Alternative 3: Removal
Landfill Construction Duration = 12 hr/day 300 day/yr 3.6 years
Excavation Duration = 12 hr/day 270 day/yr 35.7 years
Closure Duration = 12 hr/day 270 day/yr 2 years
ENERGY USAGE - ALLEN
Page 2 of 4
204 truck trips carrying liner material
963500 truck trips carrying ash
33091 truck trips carrying closure material
Activity
Number
of Units
Total Usage
Value Units
Value Units
Hourly (per Unit)
Energy Usage
Value Units
Annual Total
Energy Usage
Value Units
Total Project Energy
Usage
Value Units
EXCAVATION
Estimated Engine Size
Tracked Excavators 1,7
2
6480 hr/yr
200 HP each
1.1 MMBtu/hr
7328 MMBtu/yr
261608 MMBtu
Dozers 1,7
2
6480 hr/yr
500 HP each
2.8 MMBtu/hr
18320 MMBtu/yr
654020 MMBtu
Wheeled Loaded''
1
3240 hr/yr
175 HP each
1.0 MMBtu/hr
3206 MMBtu/yr
114454 MMBtu
Dump Trucks 1,7
2
6480 hr/yr
25 HP each
0.1 MMBtu/hr
916 MMBtu/yr
32701 MMBtu
Water Truck l''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
327010 MMBtu
Wheeled Backhoe 1,7
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
98103 MMBtu
6-8" Pumpsl''
2
6480 hr/yr
100 HP each
0.6 MMBtu/hr
3664 MMBtu/yr
130804 MMBtu
55 KVA Diesel Generators''
1
3240 hr/yr
59 HP each
0.3 MMBtu/hr
1081 MMBtu/yr
38587 MMBtu
Fuel Usage
Personal VehicleS2'3'8
15
121500 miles/yr
5678 gal/yr
684 MMBtu/yr
24419.2 MMBtu
MATERIAL TRANSPORT
Fuel Usage
Truck Transport - Ash 4,6,8
N/A
26989 truck trips/yr
1349440 miles/yr
232662 gal/yr
32077 MMBtu/yr
1145161 MMBtu
Truck Transport - Closure Materia 14,6,8
N/A
16546 truck trips/yr
33091 miles/yr
5705 gal/yr
787 MMBtu/yr
1573 MMBtu
Truck Transport - Liner Materia 14,5,6,8
N/A
36 truck trips/yr
7291 miles/yr
1257 gal/yr
173 MMBtu/yr
971 MMBtu
LANDFILL CONSTRUCTION
Estimated Engine Size
Tracked Excavators s'7
8
28800 hr/yr
200 HP each
1.1 MMBtu/hr
32569 MMBtu/yr
117247 MMBtu
Dozers 1,7
8
28800 hr/yr
500 HP each
2.8 MMBtu/hr
81422 MMBtu/yr
293118 MMBtu
Vibratory Compactors''
4
14400 hr/yr
120 HP each
0.7 MMBtu/hr
9771 MMBtu/yr
35174 MMBtu
Wheeled Loaders''
4
14400 hr/yr
175 HP each
1.0 MMBtu/hr
14249 MMBtu/yr
51296 MMBtu
Dump Trucks s''
8
28800 hr/yr
25 HP each
0.1 MMBtu/hr
4071 MMBtu/yr
14656 MMBtu
Water Trucks s''
4
14400 hr/yr
500 HP each
2.8 MMBtu/hr
40711 MMBtu/yr
146559 MMBtu
Wheeled Backhoe S1,7
4
14400 hr/yr
150 HP each
0.8 MMBtu/hr
12213 MMBtu/yr
43968 MMBtu
6-8" Pumpss''
8
28800 hr/yr
100 HP each
0.6 MMBtu/hr
16284 MMBtu/yr
58624 MMBtu
Maint/Service Trucks''
4
14400 hr/yr
500 HP each
2.8 MMBtu/hr
40711 MMBtu/yr
146559 MMBtu
55 KVA Diesel Generators''
4
14400 hr/yr
591 HP each
0.3 MMBtu/hr
4804 MMBtu/yr
17294 MMBtu
Fuel Usage
Appendix C - Air Emissions and Energy Analysis C-19 September 30, 2016

ENERGY USAGE - ALLEN
Page 3 of 4
Activity
Number
of Units
Total Usage
Value Units
Value Units
Hourly (per Unit)
Energy Usage
Value Units
Annual Total
Energy Usage
Value Units
Total Project Energy
Usage
Value Units
Personal VehicleS2'3'8
100
900000 miles/yr
42056 gal/yr
5067 MMBtu/yr
18240.3 MMBtu
LANDFILL FILLING
Estimated Engine Size
Dozers 1,7
2
6480 hr/yr
500 HP each
2.8 MMBtu/hr
18320 MMBtu/yr
654020 MMBtu
Tractors''
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
98103 MMBtu
Wheeled Backhoe 1,7
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
98103 MMBtu
Water Trucks''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
327010 MMBtu
Vibratory Rolled''
1
3240 hr/yr
120 HP each
0.7 MMBtu/hr
2198 MMBtu/yr
78482 MMBtu
Tracked Excavators''
1
3240 hr/yr
200 HP each
1.1 MMBtu/hr
3664 MMBtu/yr
130804 MMBtu
Maint/Service Trucks''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
327010 MMBtu
55 KVA Diesel Generators''
1
3240 hr/yr
59 HP each
0.3 MMBtu/hr
1081 MMBtu/yr
38587 MMBtu
Fuel Usage
Personal VehicleS2'3'8
15
121500 miles/yr
5678 gal/yr
684 MMBtu/yr
24419.2 MMBtu
LANDFILL CLOSURE
Estimated Engine Size
Dozers 1,7
2
6480 hr/yr
500 HP each
2.8 MMBtu/hr
18320 MMBtu/yr
36640 MMBtu
Tractors''
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
5496 MMBtu
Wheeled Backhoe''?
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
5496 MMBtu
Water Trucks''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
18320 MMBtu
Vibratory Rolled''
1
3240 hr/yr
120 HP each
0.7 MMBtu/hr
2198 MMBtu/yr
4397 MMBtu
Tracked Excavators''
1
3240 hr/yr
200 HP each
1.1 MMBtu/hr
3664 MMBtu/yr
7328 MMBtu
Maint/Service Trucks''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
18320 MMBtu
55 KVA Diesel Generators''
1
3240 hr/yr
59 HP each
0.3 MMBtu/hr
1081 MMBtu/yr
2162 MMBtu
Fuel Usage
Personal VehicleS2'3'8
15
121500 miles/yr
5678 gal/yr
684 MMBtu/yr
1368.0 MMBtu
441,541 MMBtu/yr
5,648,213 MMBtu
Appendix C - Air Emissions and Energy Analysis C-20 September 30, 2016

ENERGY USAGE - ALLEN
Page 4 of 4
Notes:
1. South Coast Air Quality Management District Off -Road Model Mobile Source Emission Factors for a 2016 fleet average from http://www.agmd.gov/home/regulations/ceqa/air-quality-analysis-
handbook/off-road-mobile-source-emission-factors.
2. Personally Operated Vehicle use is estimated as:
-Excavation: 15 persons/day * 30 miles/person * 270 day/yr (it is assumed each person travels 15 -miles one-way to work);
-Landfill Construction: 25 persons/day * 30 miles/person * 270 day/yr.
3. USDOT Bureau of Transportation Statistics Average Fuel Efficiency of U.S. Light Duty Vehicles for calendar year 2014 U.S. light-duty vehicles ( 21.4 mi/gal) from
http://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/national_transportation_statistics/html/table_ 04_23.html.
4. It is assumed that the landfill location is 25 miles away, so 1 truck trip carrying ash is 50 miles, and 20 -ton trucks are used. It is assumed that the landfill cap/closure material for Option 3 is
taken from an adjacent land parcel, thus 1 truck trip carrying cap/closure material is taken to be 2 miles. It is assumed that the landfill cap/closure material for Option 2 is taken from a site 25
miles aways, so 1 truck trip carrying cap/closure material for Option 2 is taken to be 50 miles.
5. It is assumed that the liner is transported 100 miles to the site/landfill on public roads and approximately 10 tons of liner are transported per trip
(3240 Ib/roll * 1 ton/2000 Ib * 6 rolls/truck trip = 10 ton/truck trip).
6. Oak Ridge National Laboratory Transportation Energy Data Book, Edition 34, September 2015. Class 7-8 average fuel economy (2013) is 5.8 mi/gal from
http://cta.ornl.gov/data/tedb34/Edition34_Chapter05.pdf.
7. USDOE Office of Energy Efficiency and Renewable Energy, Just the Basics Diesel Engine , 2003. Used estimated diesel engine efficiency of 45% from
http://wwwl.eere.energy.gov/vehiclesandfuels/pdfs/basics/J*tb_diesel_engine.pdf.
8. U.S. Energy Information Administration, Energy Explained - Energy Units and Calculators, 2015. Used diesel energy content of 137,871 Btu/gal and
gasoline energy content of 120,476 Btu/gal from http://www.eia.gov/energyexplained/?page=about_energy_units.
9. Conversion factor used: 1 HP = 2544.43 Btu/hr
Appendix C - Air Emissions and Energy Analysis C-21 September 30, 2016

Alternative 1:
MINA
AIR EMISSIONS - BUCK
Page 1 of 3
Since similar monitoring would be required for each option for the project duration, similar emissions are expected for each and the emissions are not included in this estimate. It is expected that the emissions contributions from
personal vehicles due to monitoring would be insignificant compared to the other emission sources.
Alternative 2:
CIP
CIP Duration = 12 hr/day 270 day/yr 2.9 years 78412 truck trips carrying cap material
114 truck trips carrying liner material
Appendix C - Air Emissions and Energy Analysis C-22 September 30, 2016
Usage
NOx
Emission Factors
PM10/PM2_5 Direct CO.
Direct CH4
Emissions
(tons/yr)
Cumulative Emissions
(tons COze)
Activity
Value Units
Value Units
Value Units
Value Units
Value Units
NOx
PM30/PM2,5 Direct GHG (COze)
Direct GHG
2 Dozers'
6480 hr/yr
2.0891 lb/hr
0.0858 Ib/hr
239 Ib/hr
0.0234 lb/hr
6.77
0.28
776.26
2254.35
Tractor'
3240 hr/yr
0.4070 lb/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
314.92
Wheeled Backhoe'
3240 hr/yr
0.4070 Ib/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
314.92
Water Truck'
3240 hr/yr
1.3322 lb/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
1225.15
Vibratory Roller'
3240 hr/yr
0.5273lb/hr
0.0353 Ib/hr
67 Ib/hr
0.0071 lb/hr
0.85
0.06
108.83
316.05
Tracked Excavator'
3240 hr/yr
0.6603 lb/hr
0.0332 Ib/hr
120 Ib/hr
0.0089 Ib/hr
1.07
0.05
194.76
565.61
Maint/Service Truck'
3240 hr/yr
1.3322 Ib/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
1225.15
55 KVA Diesel Generator'
3240 hr/yr
0.6102 lb/hr
0.0431 lb/hr
77.9 Ib/hr
0.0073 Ib/hr
0.99
0.07
126.49
367.35
15 Personal Vehicles2,3,4,5,6
121500 miles r
/y
0.95 g/mile
0.0045 g/mile
410 g/mile j
0.0452 g/mile
0.13
0.00
55.10
160.02
Truck Transport - Cap Materia 17,8,9,10
27000 truck trips/yr
459.55 g/truck trip
10.75 g/truck trip
138000 g/truck trip 1
0.255 g/truck trip
13.68
0.32
4107.41
11928.47
Truck Transport - Liner Material �'$'9''°'"
39 truck trips/yr I
1838.20 g/truck trip I
43.00 g/truck trip I
552000 g/truck trip 1
1.02 g/truck trip
0.08
0.00
23.89
69.37
2 9.2 0
1.011
6,453.331
18, 741.37
Appendix C - Air Emissions and Energy Analysis C-22 September 30, 2016

Alternative 3:
Landfill Construction Duration =
Excavation Duration =
Closure Duration =
Removal
12 hr/day 300 day/yr 1.2 years 70 truck trips carrying liner material (construction & closure)
12 hr/day 270 day/yr 9.8 years 265500 truck trips carrying ash
12 hr/day 270 day/yr 0.7 years 11398 truck trips carrying closure material
AIR EMISSIONS - BUCK
Page 2 of 3
Appendix C - Air Emissions and Energy Analysis C-23 September 30, 2016
Usage
NOx
Emission Factors
PM10/PM2.5 Direct CO.
Direct CH4
Emissions
(tons/yr)
Cumulative Emissions
(tons CO2e)
Activity
Value Units
Value Units
Value Units
Value Units
Value Units
NOx
PM,,/PM,, Direct GHG (CO,e)
Direct GHG
EXCAVATION
2 Tracked Excavators'
6480 hr/yr
0.6603 lb/hr
0.0332 Ib/hr
120 Ib/hr
0.0089 lb/hr
2.14
0.11
389.52
3817.30
2 Dozers'
6480 hr/yr
2.0891 lb/hr
0.0858 Ib/hr
239 Ib/hr
0.0234 Ib/hr
6.77
0.28
776.26
7607.30
Wheeled Loader'
3240 hr/yr
0.7114 Ib/hr
0.0375 Ib/hr
109 Ib/hr
0.0089 Ib/hr
1.15
0.06
176.94
1734.02
2 Dump Trucks'
6480 hr/yr
0.0587 Ib/hr
0.0024 Ib/hr
7.6 Ib/hr
0.0008 Ib/hr
0.19
0.01
24.69
241.95
Water Truck'
3240 hr/yr
1.3322 lb/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
4134.27
Wheeled Backhoe'
3240 hr/yr
0.4070 Ib/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
1062.70
2 6-8" Pumps'
6480 hr/yr
0.3830 lb/hr
0.0239 Ib/hr
49.6 Ib/hr
0.0051lb/hr
1.24
0.08
161.12
1578.95
55 KVA Diesel Generator'
3240 hr/yr
0.6102 lb/hr
0.0431 lb/hr
77.9 Ib/hr
0.0073 Ib/hr
0.99
0.07
126.49
1239.64
15 Personal Vehicles2,3,4'5
121500 miles r
/y
0.95 g/mile
0.0045 g/mile
410 g/mile
0.0452 g/mile
0.13
0.00
55.10
539.99
MATERIAL TRANSPORT
Truck Transport - Ash 7,8,9,10
27092 truck trips/yr
459.55 g/truck trip
10.75 g/truck trip
138000 g/truck trip
0.2550 g/truck trip
13.72
0.32
4121.38
40389.48
Truck Transport - Closure Material 7'8""0
16283 truck trips/yr
18.38 g/truck trip
0.43 g/truck trip
5520 g/truck trip
0.0102 g/truck trip
0.33
0.01
99.081
69.36
Truck Transport - Liner Materia 17,8,9,10,11
37 truck trips/yr
1838.20 g/truck trip
43 g/truck trip
552000 g/truck trip
1.0200 g/truck trip
0.07
0.00
22.42
42.60
LANDFILL CONSTRUCT.
8 Tracked Excavators'
28800 hr/yr
0.6603 lb/hr
0.0332 Ib/hr
120 Ib/hr
0.0089 Ib/hr
9.51
0.48
1731.20
3289.29
8 Dozers'
28800 hr/yr
2.0891 Ib/hr
0.0858 Ib/hr
239 Ib/hr
0.0234 Ib/hr
30.08
1.24
3450.02
6555.05
4 Vibratory Compactors'
14400 hr/yr
0.568 Ib/hr
0.0234 Ib/hr
123 Ib/hr
0.0065 lb/hr
4.09
0.17
886.77
1684.86
4 Wheeled Loaders'
14400 hr/yr
0.7114 lb/hr
0.0375 Ib/hr
109 Ib/hr
0.0089 Ib/hr
5.12
0.27
786.40
1494.16
8 Dump Trucks'
28800 hr/yr
0.0587 lb/hr
0.0024 Ib/hr
7.6 Ib/hr
0.0008 Ib/hr
0.85
0.03
109.73
208.48
4 Water Trucks'
14400 hr/yr
1.3322 lb/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
9.59
0.33
1874.95
3562.41
4 Wheeled Backhoes'
14400 hr/yr
0.4070 lb/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
2.93
0.19
481.95
915.71
8 6-8" Pumps'
28800 hr/yr
0.3830 lb/hr
0.0239 Ib/hr
49.6 Ib/hr
0.0051 lb/hr
5.52
0.34
716.08
1360.54
4 M aint/Service Trucks'
14400 hr/yr
1.3322 lb/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
9.59
0.33
1874.95
3562.41
4 55 KVA Diesel Generator'
14400 hr/yr
0.6102 lb/hr
0.0431 lb/hr
77.9 Ib/hr
0.0073 Ib/hr
4.39
0.31
562.19
1068.17
100 Personal Vehicles2'3'4'5
900000 miles r
/y
0.95 g/mile
0.0045 g/mile
410 g/mile
0.0452 g/mile
0.94
0.00
408
775.49
LANDFILL FILLING
2 Dozers'
6480 hr/yr
2.0891 lb/hr
0.0858 Ib/hr
239 Ib/hr
0.0234 Ib/hr
6.77
0.28
776.26
7607.30
Tractor'
3240 hr/yr
0.4070 lb/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
1062.70
Wheeled Backhoel
3240 hr/yr
0.4070 Ib/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
1062.70
Water Truck'
3240 hr/yr
1.3322 lb/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
4134.27
Vibratory Roller'
3240 hr/yr
0.5273lb/hr I
0.0353 Ib/hr
67 Ib/hr
0.0071 lb/hr
0.85
0.06
108.83
1066.51
Tracked Excavator' I
3240 hr/yr I
0.6603lb/hr I
0.0332 Ib/hr I
120 Ib/hr
0.0089 Ib/hr
1.07
0.05
194.76
1908.65
M aint/Service Truck' 1
3240 hr/yr 1
1.3322 lb/hr I
0.0459 Ib/hr 1
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.861
4134.27
55 KVA Diesel Generator'
3240 hr/yr
0.6102lb/hr
0.0431lb/hr
77.9 Ib/hr
0.0073 Ib/hr
0.99
0.07
126.49
1239.64
Appendix C - Air Emissions and Energy Analysis C-23 September 30, 2016

AIR EMISSIONS - BUCK
Page 3 of 3
Notes:
1. South Coast Air Quality Management District Off -Road Model Mobile Source Emission Factors for a 2016 fleet average from http://www.agmd.gov/home/regulations/ceqa/air-quality-analysis-handbook/off-road-mobile-source-
emission-factors.
2. USEPA Center for Corporate Climate Leadership Greenhouse Gas Inventory Guidance: Direct Emissions from Mobile Combustion Sources Tier 1 Gasoline Light -Duty Truck emission factors (0.0452 g CH4/mile) from
https://www.epa.gov/sites/prod uction/files/2016-03/documents/mobi leem issions_3_2016. pdf.
3. Personally Operated Vehicle (POV) use is estimated as:
-Excavation: 15 persons/day * 30 miles/person * 270 day/yr (it is assumed each person travels 15 -miles one-way to work);
-Landfill Construction: 25 persons/day * 30 miles/person * 270 day/yr.
4. USDOT Bureau of Transportation Statistics Average Fuel Efficiency of U.S. Light Duty Vehicles for calendar year 2014 (21.4 miles/gal) for POV CO2 emissions from
http://www. rita.dot.gov/bts/sites/rita.dot.gov. bts/fi les/publications/nationa I_transportation_statistics/html/table_04 23.htm I.
S. 100 -yr GWP for CH4 (25 kg CO2e/kg CH4) from Intergovernmental Panel on Climate Change (IPCC), Fourth Assessment Report (AR4), 2007.
6. USEPA Office of Transportation and Air Quality Average Annual Emissions and Fuel Consumption for Gasoline -Fueled Passenger Cars and Light Trucks light-duty trucks emissions estimates for the in -use fleet as of 2008 based on
https://www3.epa.gov/otaq/consumer/42OfO8O24.pdf.
7. It is assumed that the landfill location is 25 miles away, so 1 truck trip carrying ash is 50 miles, and 20 -ton trucks are used. It is assumed that the landfill cap/closure material for Option 3 is taken from an adjacent land parcel,
thus 1 truck trip carrying cap/closure material is taken to be 2 miles. It is assumed that the landfill cap/closure material for Option 2 is taken from a site 25 miles aways, so 1 truck trip carrying cap/closure material for Option 2 is
taken to be 50 miles.
8. USEPA Office of Transportation and Air Quality Average In -Use Emissions from Heavy -Duty Trucks NOx and PM10/PM2.5 emission factors approximated as a diesel Heavy -Duty Vehicle Class Vllla (33,001-60,000 Ib GVWR--since
it is for 20 ton (40,000 Ib) material + truck) --based on the in -use fleet from July 2008 from https://www3.epa.gov/otaq/consumer/42OfO8O27.pdf.
9. USEPA Center for Corporate Climate Leadership Emission Factors for Greenhouse Gas Inventories greenhouse gas emission factors approximated as heavy duty vehicles for 1960 -present from Table 4 of
https://www.epa.gov/sites/production/files/2015-12/documents/emission-factors_nov_2015.pdf, dated November 2015.
10. It is assumed that the weight of the vehicle + load is approximately 60,000 Ib (20 -ton load and 10 -ton truck). Diesel heavy duty combination truck CO2 emission factor for MY2014/Class 8/Day Cab is 92 g CO2/ton-mile taken
from https://www.gpo.gov/fdsys/pkg/FR-2011-09-15/pdf/2011-20740.pdf (EPA/DOT Federal Register Vol. 76, No. 179, 15 September 2011).
-92 g CO2/ton-mile * (30 ton*x mile)/truck trip = y g CO2/truck trip
11. It is assumed that the liner is transported 100 miles to the site/landfill on public roads and approximately 10 tons of liner are transported per trip (3240 Ib/roll * 1 ton/2000 Ib * 6 rolls/truck trip = 10 ton/truck trip).
Appendix C - Air Emissions and Energy Analysis C-24 September 30, 2016
Usage
NOx
Emission Factors
PMlo/PMZ 5 Direct CO,
Direct CH4
Emissions
(tons/yr)
Cumulative Emissions
(tons COze)
Activity
Value Units
Value Units
Value Units
Value Units
Value Units
NOx
PMlo/PM2.5 Direct GHG (COze)
Direct GHG
Personal Vehicles2'3'4'5'6
121500 miles/yr
0.95 g/mile
0.0045 g/mile
410 g/mile
0.0452 g/mile
0.13
0.00
55.10
539.99
LANDFILL CLOSURE
2 Dozers'
6480 hr/yr
2.0891 lb/hr
0.0858 Ib/hr
239 Ib/hr
0.0234 Ib/hr
6.77
0.28
776.26
543.38
Tractor'
3240 hr/yr
0.4070lb/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
75.91
Wheeled Backhoe'
3240 hr/yr
0.4070 Ib/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
75.91
Water Truck'
3240 hr/yr
1.3322 Ib/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
295.30
Vibratory Roller'
3240 hr/yr
0.5273 Ib/hr
0.0353 Ib/hr
67 Ib/hr
0.0071 Ib/hr
0.85
0.06
108.83
76.18
Tracked Excavator'
3240 hr/yr
0.6603 lb/hr
0.0332 Ib/hr
120 Ib/hr
0.0089 Ib/hr
1.07
0.05
194.76
136.33
Maint/Service Truck'
3240 hr/yr
1.3322 lb/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
295.30
55 KVA Diesel Generator'
3240 hr/yr
0.6102lb/hr
0.0431lb/hr
77.9 Ib/hr
0.0073 Ib/hr
0.99
0.07
126.49
88.55
Personal Vehicles2'3,4,5,6
121500 miles/yr
I 0.95 g/mile
I 0.0045 g/mile
I 410 g/mile
0.0452 g/mile
0.13
0.00
55.10
38.57
143.05
6.12
24,009.79
111,315.58
Notes:
1. South Coast Air Quality Management District Off -Road Model Mobile Source Emission Factors for a 2016 fleet average from http://www.agmd.gov/home/regulations/ceqa/air-quality-analysis-handbook/off-road-mobile-source-
emission-factors.
2. USEPA Center for Corporate Climate Leadership Greenhouse Gas Inventory Guidance: Direct Emissions from Mobile Combustion Sources Tier 1 Gasoline Light -Duty Truck emission factors (0.0452 g CH4/mile) from
https://www.epa.gov/sites/prod uction/files/2016-03/documents/mobi leem issions_3_2016. pdf.
3. Personally Operated Vehicle (POV) use is estimated as:
-Excavation: 15 persons/day * 30 miles/person * 270 day/yr (it is assumed each person travels 15 -miles one-way to work);
-Landfill Construction: 25 persons/day * 30 miles/person * 270 day/yr.
4. USDOT Bureau of Transportation Statistics Average Fuel Efficiency of U.S. Light Duty Vehicles for calendar year 2014 (21.4 miles/gal) for POV CO2 emissions from
http://www. rita.dot.gov/bts/sites/rita.dot.gov. bts/fi les/publications/nationa I_transportation_statistics/html/table_04 23.htm I.
S. 100 -yr GWP for CH4 (25 kg CO2e/kg CH4) from Intergovernmental Panel on Climate Change (IPCC), Fourth Assessment Report (AR4), 2007.
6. USEPA Office of Transportation and Air Quality Average Annual Emissions and Fuel Consumption for Gasoline -Fueled Passenger Cars and Light Trucks light-duty trucks emissions estimates for the in -use fleet as of 2008 based on
https://www3.epa.gov/otaq/consumer/42OfO8O24.pdf.
7. It is assumed that the landfill location is 25 miles away, so 1 truck trip carrying ash is 50 miles, and 20 -ton trucks are used. It is assumed that the landfill cap/closure material for Option 3 is taken from an adjacent land parcel,
thus 1 truck trip carrying cap/closure material is taken to be 2 miles. It is assumed that the landfill cap/closure material for Option 2 is taken from a site 25 miles aways, so 1 truck trip carrying cap/closure material for Option 2 is
taken to be 50 miles.
8. USEPA Office of Transportation and Air Quality Average In -Use Emissions from Heavy -Duty Trucks NOx and PM10/PM2.5 emission factors approximated as a diesel Heavy -Duty Vehicle Class Vllla (33,001-60,000 Ib GVWR--since
it is for 20 ton (40,000 Ib) material + truck) --based on the in -use fleet from July 2008 from https://www3.epa.gov/otaq/consumer/42OfO8O27.pdf.
9. USEPA Center for Corporate Climate Leadership Emission Factors for Greenhouse Gas Inventories greenhouse gas emission factors approximated as heavy duty vehicles for 1960 -present from Table 4 of
https://www.epa.gov/sites/production/files/2015-12/documents/emission-factors_nov_2015.pdf, dated November 2015.
10. It is assumed that the weight of the vehicle + load is approximately 60,000 Ib (20 -ton load and 10 -ton truck). Diesel heavy duty combination truck CO2 emission factor for MY2014/Class 8/Day Cab is 92 g CO2/ton-mile taken
from https://www.gpo.gov/fdsys/pkg/FR-2011-09-15/pdf/2011-20740.pdf (EPA/DOT Federal Register Vol. 76, No. 179, 15 September 2011).
-92 g CO2/ton-mile * (30 ton*x mile)/truck trip = y g CO2/truck trip
11. It is assumed that the liner is transported 100 miles to the site/landfill on public roads and approximately 10 tons of liner are transported per trip (3240 Ib/roll * 1 ton/2000 Ib * 6 rolls/truck trip = 10 ton/truck trip).
Appendix C - Air Emissions and Energy Analysis C-24 September 30, 2016

Alternative 1:
MNA
INDIRECT GHG EMISSIONS - BUCK
Page 1 of 4
Since similar monitoring would be required for each option for the project duration, similar emissions are expected for each and the emissions are not included in this estimate.
It is expected that the emissions contributions from personal vehicles due to monitoring would be insignificant compared to the other emission sources.
Alternative 2:
CIP
CIP Duration = 12 hr/day 270 day/yr 2.9 years 78412 truck trips carrying cap material
114 truck trips carrying liner material
Activity
Number
of Units
Usage
Value Units
Annual Total
Energy Usage
Value Units
Total Project
GGE
Value Units
WTP (Indirect)
GHG Emissions5
Value Units
Project Indirect
GHG Emissions
Value Units
Dozers
2
6480 hr/yr
18319.9 MMBtu/yr
152062.6 GGE/yr
308 tons COze/yr
894 tons COZe
Tractor
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons COze/yr
134 tons COze
Wheeled Backhoe
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons COZe/yr
134 tons COze
Water Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons COze/yr
447 tons COze
Vibratory Roller
1
3240 hr/yr
2198.4 MMBtu/yr
18247.5 GGE/yr
37 tons COze/yr
107 tons COze
Tracked Excavator
1
3240 hr/yr
3664.0 MMBtu/yr
30412.5 GGE/yr
62 tons COze/yr
179 tons COze
Maint/Service Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons COze/yr
447 tons COze
55 KVA Diesel Generator
1
3240 hr/yr
1080.9 MMBtu/yr
8971.7 GGE/yr
18 tons COZe/yr
53 tons COZe
Personal Vehicles
15
121500 miles/yr
10 tons COze/yr
30 tons COZe
Truck Transport - Cap Material2
N/A
27000 truck trips/yr
1350000 miles/yr
87 tons COZe/yr
254 tons COze
2'3
Truck Transport - Liner Material
N/A
39 truck trips/yr
7828 miles/yr
0.5 tons COze/yr
1 tons COze
923 tons COZe/yr
2,681 Itons COze
Appendix C - Air Emissions and Energy Analysis C-25 September 30, 2016

Alternative 3: Removal
Landfill Construction Duration = 12 hr/day 300 day/yr 1.2 years
Excavation Duration = 12 hr/day 270 day/yr 9.8 years
Closure Duration = 12 hr/day 270 day/yr 0.7 years
INDIRECT GHG EMISSIONS - BUCK
Page 2 of 4
70 truck trips carrying liner material
265500 truck trips carrying ash
11398 truck trips carrying closure material
Activity
Number
of Units
Total Usage
Value Units
Annual Total
Energy Usage
Value Units
Total Project
GGE
Value Units
WTP (Indirect)
GHG Emissionss
Value Units
Project Indirect
GHG Emissions
Value Units
EXCAVATION
Tracked Excavators
2
6480 hr/yr
7328.0 MMBtu/yr
60825.0 GGE/yr
123 tons COZe/yr
1207 tons COZe
Dozers
2
6480 hr/yr
18319.9 MMBtu/yr
152062.6 GGE/yr
308 tons COze/yr
3018 tons COze
Wheeled Loader
1
3240 hr/yr
3206.0 MMBtu/yr
26611.0 GGE/yr
54 tons COze/yr
528 tons COze
Dump Trucks
2
6480 hr/yr
916.0 MMBtu/yr
7603.1 GGE/yr
15 tons COZe/yr
151 tons COze
Water Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons COze/yr
1509 tons COze
Wheeled Backhoe
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons COZe/yr
453 tons COZe
6-8" Pumps
2
6480 hr/yr
3664.0 MMBtu/yr
30412.5 GGE/yr
62 tons COze/yr
604 tons COZe
55 KVA Diesel Generator
1
3240 hr/yr
1080.9 MMBtu/yr
8971.7 GGE/yr
18 tons COze/yr
178 tons COze
Personal Vehicles
15
121500 miles/yr
10 tons COZe/yr
101 tons COze
MATERIAL TRANSPORT
Truck Transport - Ash
N/A
27092 truck trips/yr
1354592 miles/yr
88 tons COze/yr
859 tons COze
Truck Transport - Closure Material
N/A
16283 truck trips/yr
32567 miles/yr
2 tons COze/yr
1 tons COZe
Truck Transport - Liner Materia 12,3
N/A
37 truck trips/yr
7336 miles/yr
0.5 tons COZe/yr
1 tons COze
LANDFILL CONSTRUCTION
Tracked Excavators
8
28800 hr/yr
32568.7 MMBtu/yr
270333.5 GGE/yr
548 tons COze/yr
657 tons COze
Dozers
8
28800 hr/yr
81421.8 MMBtu/yr
675833.9 GGE/yr
1369 tons COze/yr
1643 tons COze
Vibratory Compactors
4
14400 hr/yr
9770.6 MMBtu/yr
81100.1 GGE/yr
164 tons COZe/yr
197 tons COZe
Wheeled Loaders
4
14400 hr/yr
14248.8 MMBtu/yr
118270.9 GGE/yr
240 tons COze/yr
287 tons COZe
Dump Trucks
8 1
28800 hr/yr
4071.1 MMBtu/yr
33791.7 GGE/yr
68 tons COze/yr
82 tons COze
Water Trucks
4 1
14400 hr/yr
40710.9 MMBtu/yr
337916.9 GGE/yr
684 tons COZe/yr
821 tons COze
Wheeled Backhoes
4 1
14400 hr/yr 1
12213.3 MMBtu/yr
101375.1 GGE/yr
205 tons COze/yr
246 tons COze
Appendix C - Air Emissions and Energy Analysis C-26 September 30, 2016

INDIRECT GHG EMISSIONS - BUCK
Page 3 of 4
Activity
Number
of Units
Total Usage
Value Units
Annual Total
Energy Usage
Value Units
Total Project
GGE
Value Units
WTP (Indirect)
GHG Emissionss
Value Units
Project Indirect
GHG Emissions
Value Units
6-8" Pumps
8
28800 hr/yr
16284.4 MMBtu/yr
135166.8 GGE/yr
274 tons COZe/yr
329 tons COZe
Maint/Service Trucks
4
14400 hr/yr
40710.9 MMBtu/yr
337916.9 GGE/yr
684 tons COze/yr
821 tons COZe
55 KVA Diesel Generators
4
14400 hr/yr
4803.9 MMBtu/yr
39874.2 GGE/yr
81 tons COze/yr
97 tons COze
Personal Vehicles
100
900000 miles/yr
76 tons COZe/yr
91 tons COze
LANDFILL FILLING
Dozers
2
6480 hr/yr
18319.9 MMBtu/yr
152062.6 GGE/yr
308 tons COze/yr
3018 tons COze
Tractor
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons COze/yr
453 tons COze
Wheeled Backhoe
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons COZe/yr
453 tons COZe
Water Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons COze/yr
1509 tons COZe
Vibratory Roller
1
3240 hr/yr
2198.4 MMBtu/yr
18247.5 GGE/yr
37 tons COze/yr
362 tons COze
Tracked Excavator
1
3240 hr/yr
3664.0 MMBtu/yr
30412.5 GGE/yr
62 tons COZe/yr
604 tons COze
Maint/Service Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons COze/yr
1509 tons COze
55 KVA Diesel Generator
1
3240 hr/yr
1080.9 MMBtu/yr
8971.7 GGE/yr
18 tons COze/yr
178 tons COze
Personal Vehicles
15
121500 miles/yr
10 tons COze/yr
101 tons COze
LANDFILL CLOSURE
Dozers
2
6480 hr/yr
18319.9 MMBtu/yr
152062.6 GGE/yr
308 tons COze/yr
216 tons COZe
Tractor
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons COze/yr
32 tons COze
Wheeled Backhoe
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons COZe/yr
32 tons COze
Water Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons COze/yr
108 tons COze
Vibratory Roller
1
3240 hr/yr
2198.4 MMBtu/yr
18247.5 GGE/yr
37 tons COze/yr
26 tons COze
Tracked Excavator
1
3240 hr/yr
3664.0 MMBtu/yr
30412.5 GGE/yr
62 tons COZe/yr
43 tons COze
Maint/Service Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons COze/yr
108 tons COze
55 KVA Diesel Generator
1
3240 hr/yr
1080.9 MMBtu/yr
8971.7 GGE/yr
18 tons COZe/yr
13 tons COZe
Personal Vehicles
15
121500 miles/yr
10 tons COze/yr
7 tons COZe
6,945 Itons COZe/yr
22,653 Itons COZe
Appendix C - Air Emissions and Energy Analysis C-27 September 30, 2016

INDIRECT GHG EMISSIONS - BUCK
Page 4 of 4
Notes:
1. Personally Operated Vehicle use is estimated as:
-Excavation: 15 persons/day * 30 miles/person * 270 day/yr (it is assumed each person travels 15 -miles one-way to work);
-Landfill Construction: 25 persons/day * 30 miles/person * 270 day/yr.
2. It is assumed that the landfill location is 25 miles away, so 1 truck trip carrying ash is 50 miles, and 20 -ton trucks are used. It is assumed that the landfill cap/closure material
for Option 3 is taken from an adjacent land parcel, thus 1 truck trip carrying cap/closure material is taken to be 2 miles. It is assumed that the landfill cap/closure material for
Option 2 is taken from a site 25 miles aways, so 1 truck trip carrying cap/closure material for Option 2 is taken to be 50 miles.
3. It is assumed that the liner is transported 100 miles to the site/landfill on public roads and approximately 10 tons of liner are transported per trip
(3240 Ib/roll * 1 ton/2000 Ib * 6 rolls/truck trip = 10 ton/truck trip).
4. U.S. Energy Information Administration, Energy Explained - Energy Units and Calculators, 2015. Used diesel energy content of 137,871 Btu/gal and
gasoline energy content of 120,476 Btu/gal from http://www.eia.gov/energyexplained/?page=about_energy_units.
5. GHG emission factors from Results created by ANL on 11/12/2015 using GREETI_2015 version, October 2015 release, Argonne National Laboratory, 2015.
Emission Factors Well -To -Pump (WTP)16
Diesel 59 g CO2e/mi 1837 g CO2e/gge
Gasoline (E10) 77 g CO2e/mi
6. Annual Total Energy Usage values taken from Energy Usage calculations.
7. Conversion factor used: 1 HP = 2544.43 Btu/hr
Abbreviations:
GHG = Greenhouse Gas.
WTP = "Well -to -Pump" (also called Well -to -Tank, or WTT), refers to processes and activities involved in producing a fuel through when that fuel reaches a fueling station. This
may include raw material extraction, transportation, fuel production, distribution, and storage. For the purposes of this study, only WTP GHG emissions are considered as
indirect emissions. Indirect emissions in the PTW (Pump -to -Wheels) stage, such as refueling and evaporation, are not included as indirect emissions.
Appendix C - Air Emissions and Energy Analysis C-28 September 30, 2016

Alternative 1:
MINA
ENERGY USAGE - BUCK
Page 1 of 4
Since similar monitoring would be required for each option for the project duration, similar energy usages are expected for each and the energy usage is not included in this estimate. It is
expected that the energy usage contributions from personal vehicles due to monitoring would be insignificant compared to the other source of energy usage.
Alternative 2:
CIP
CIP Duration = 12 hr/day 270 day/yr 2.9 years 78412 truck trips carrying cap material
114 truck trips carrying liner material
Activity
Number
of Units
Usage
Value Units
Value Units
Hourly (per Unit)
Energy Usage9
Value Units
Annual Total
Energy Usage
Value Units
Total Project Energy
Usage
Value Units
Estimated Engine Size
Dozers 1,7
2
6480 hr/yr
500 HP each
2.8 MMBtu/hr
18320 MMBtu/yr
53203 MMBtu
Tractors''
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
7981 MMBtu
Wheeled Backhoe 1,7
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
7981 MMBtu
Water Truck l''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
26602 MMBtu
Vibratory Rolled''
1
3240 hr/yr
120 HP each
0.7 MMBtu/hr
2198 MMBtu/yr
6384 MMBtu
Tracked Excavators''
1
3240 hr/yr
200 HP each
1.1 MMBtu/hr
3664 MMBtu/yr
10641 MMBtu
Maint/Service Truck s'7
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
26602 MMBtu
55 KVA Diesel Generators''
1
3240 hr/yr
59 HP each
0.3 MMBtu/hr
1081 MMBtu/yr
3139 MMBtu
Fuel Usage
Personal VehicleS2'3'8
15
121500 miles/yr
5678 gal/yr
684 MMBtu/yr
6703 MMBtu
Truck Transport - Cap Materia 14,6,8
N/A
27000 truck trips/yr
1350000 miles/yr
232759 gal/yr
32091 MMBtu/yr
93196 MMBtu
Truck Transport - Liner Material °' 5' 6'8
N/A
39 truck trips/yr
7828 miles/yr
1350 gal/yr
186 MMBtu/yr
540 MMBtu
82,040 MMBtu/yr
242,972 MMBtu
Appendix C - Air Emissions and Energy Analysis C-29 September 30, 2016

Alternative 3: Removal
Landfill Construction Duration =
Excavation Duration =
Closure Duration =
ENERGY USAGE - BUCK
Page 2 of 4
12 hr/day
300 day/yr
1.2 years
70 truck trips
carrying liner material
12 hr/day
270 day/yr
9.8 years
265500 truck trips
carrying ash
12 hr/day
270 day/yr
0.7 years
11398 truck trips
carrying closure material
Activity
Number
of Units
Total Usage
Value Units
Value Units
Hourly (per Unit)
Energy Usage
Value Units
Annual Total
Energy Usage
Value Units
Total Project Energy
Usage
Value Units
EXCAVATION
Estimated Engine Size
Tracked Excavators 1,7
2
6480 hr/yr
200 HP each
1.1 MMBtu/hr
7328 MMBtu/yr
71814 MMBtu
Dozers 1,7
2
6480 hr/yr
500 HP each
2.8 MMBtu/hr
18320 MMBtu/yr
179535 MMBtu
Wheeled Loaders''
1
3240 hr/yr
175 HP each
1.0 MMBtu/hr
3206 MMBtu/yr
31419 MMBtu
Dump Trucks 1,7
2
6480 hr/yr
25 HP each
0.1 MMBtu/hr
916 MMBtu/yr
8977 MMBtu
Water Truck l''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
89767 MMBtu
Wheeled Backhoe 1,7
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
26930 MMBtu
6-8" Pumpsl''
2
6480 hr/yr
100 HP each
0.6 MMBtu/hr
3664 MMBtu/yr
35907 MMBtu
55 KVA Diesel Generators''
1
3240 hr/yr
59 HP each
0.3 MMBtu/hr
1081 MMBtu/yr
10593 MMBtu
Fuel Usage
Personal VehicleS2'3'8
15
121500 miles/yr
5678 gal/yr
684 MMBtu/yr
6703.3 MMBtu
MATERIAL TRANSPORT
Fuel Usage
Truck Transport - Ash 4,6,8
N/A
27092 truck trips/yr
1354592 miles/yr
233550 gal/yr
32200 MMBtu/yr
315558 MMBtu
Truck Transport - Closure Materia 14,6,8
N/A
16283 truck trips/yr
32567 miles/yr
5615 gal/yr
774 MMBtu/yr
542 MMBtu
Truck Transport - Liner Materia 14,5,6,8
N/A
37 truck trips/yr
7336 miles/yr
1265 gal/yr
174 MMBtu/yr
331 MMBtu
LANDFILL CONSTRUCTION
Estimated Engine Size
Tracked Excavators 1'7
8
28800 hr/yr
200 HP each
1.1 MMBtu/hr
32569 MMBtu/yr
39082 MMBtu
Dozers 1,7
8
28800 hr/yr
500 HP each
2.8 MMBtu/hr
81422 MMBtu/yr
97706 MMBtu
Vibratory Compactors 1,7
4
14400 hr/yr
120 HP each
0.7 MMBtu/hr
9771 MMBtu/yr
11725 MMBtu
Wheeled Loaders 1,7
4
14400 hr/yr
175 HP each
1.0 MMBtu/hr
14249 MMBtu/yr
17099 MMBtu
Dump Trucks l''
8
28800 hr/yr
25 HP each
0.1 MMBtu/hr
4071 MMBtu/yr
4885 MMBtu
Water Trucks l''
4
14400 hr/yr
500 HP each
2.8 MMBtu/hr
40711 MMBtu/yr
48853 MMBtu
Wheeled Backhoe S1,7
4
14400 hr/yr
150 HP each
0.8 MMBtu/hr
12213 MMBtu/yr
14656 MMBtu
6-8" Pumpsl''
8
28800 hr/yr
100 HP each
0.6 MMBtu/hr
16284 MMBtu/yr
19541 MMBtu
Maint/Service Trucks 1,7
4
14400 hr/yr
500 HP each
2.8 MMBtu/hr
40711 MMBtu/yr
48853 MMBtu
55 KVA Diesel Generators 1,7
4
14400 hr/yr
591 HP each
0.3 MMBtu/hr
4804 MMBtu/yr
5765 MMBtu
Fuel Usage
Appendix C - Air Emissions and Energy Analysis C-30 September 30, 2016

ENERGY USAGE - BUCK
Page 3 of 4
Activity
Number
of Units
Total Usage
Value Units
Value Units
Hourly (per Unit)
Energy Usage
Value Units
Annual Total
Energy Usage
Value Units
Total Project Energy
Usage
Value Units
Personal VehicleS2'3'8
100
900000 miles/yr
42056 gal/yr
5067 MMBtu/yr
6080.1 MMBtu
LANDFILL FILLING
Estimated Engine Size
Dozers 1,7
2
6480 hr/yr
500 HP each
2.8 MMBtu/hr
18320 MMBtu/yr
179535 MMBtu
Tractors''
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
26930 MMBtu
Wheeled Backhoe 1,7
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
26930 MMBtu
Water Trucks''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
89767 MMBtu
Vibratory Rolled''
1
3240 hr/yr
120 HP each
0.7 MMBtu/hr
2198 MMBtu/yr
21544 MMBtu
Tracked Excavators''
1
3240 hr/yr
200 HP each
1.1 MMBtu/hr
3664 MMBtu/yr
35907 MMBtu
Maint/Service Trucks''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
89767 MMBtu
55 KVA Diesel Generators''
1
3240 hr/yr
59 HP each
0.3 MMBtu/hr
1081 MMBtu/yr
10593 MMBtu
Fuel Usage
Personal VehicleS2'3'8
15
121500 miles/yr
5678 gal/yr
684 MMBtu/yr
6703.3 MMBtu
LANDFILL CLOSURE
Estimated Engine Size
Dozers 1,7
2
6480 hr/yr
500 HP each
2.8 MMBtu/hr
18320 MMBtu/yr
12824 MMBtu
Tractors''
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
1924 MMBtu
Wheeled Backhoe''?
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
1924 MMBtu
Water Trucks''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
6412 MMBtu
Vibratory Rolled''
1
3240 hr/yr
120 HP each
0.7 MMBtu/hr
2198 MMBtu/yr
1539 MMBtu
Tracked Excavators''
1
3240 hr/yr
200 HP each
1.1 MMBtu/hr
3664 MMBtu/yr
2565 MMBtu
Maint/Service Trucks''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
6412 MMBtu
55 KVA Diesel Generators''
1
3240 hr/yr
59 HP each
0.3 MMBtu/hr
1081 MMBtu/yr
757 MMBtu
Fuel Usage
Personal VehicleS2'3'8
15
121500 miles/yr
5678 gal/yr
684 MMBtu/yr
478.8 MMBtu
441,652 MMBtu/yr
1,614,833 MMBtu
Appendix C - Air Emissions and Energy Analysis C-31 September 30, 2016

ENERGY USAGE - BUCK
Page 4 of 4
Notes:
1. South Coast Air Quality Management District Off -Road Model Mobile Source Emission Factors for a 2016 fleet average from http://www.agmd.gov/home/regulations/ceqa/air-quality-analysis-
handbook/off-road-mobile-source-emission-factors.
2. Personally Operated Vehicle use is estimated as:
-Excavation: 15 persons/day * 30 miles/person * 270 day/yr (it is assumed each person travels 15 -miles one-way to work);
-Landfill Construction: 25 persons/day * 30 miles/person * 270 day/yr.
3. USDOT Bureau of Transportation Statistics Average Fuel Efficiency of U.S. Light Duty Vehicles for calendar year 2014 U.S. light-duty vehicles ( 21.4 mi/gal) from
http://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/national_transportation_statistics/html/table_ 04_23.html.
4. It is assumed that the landfill location is 25 miles away, so 1 truck trip carrying ash is 50 miles, and 20 -ton trucks are used. It is assumed that the landfill cap/closure material for Option 3 is
taken from an adjacent land parcel, thus 1 truck trip carrying cap/closure material is taken to be 2 miles. It is assumed that the landfill cap/closure material for Option 2 is taken from a site 25
miles aways, so 1 truck trip carrying cap/closure material for Option 2 is taken to be 50 miles.
5. It is assumed that the liner is transported 100 miles to the site/landfill on public roads and approximately 10 tons of liner are transported per trip
(3240 Ib/roll * 1 ton/2000 Ib * 6 rolls/truck trip = 10 ton/truck trip).
6. Oak Ridge National Laboratory Transportation Energy Data Book, Edition 34, September 2015. Class 7-8 average fuel economy (2013) is 5.8 mi/gal from
http://cta.ornl.gov/data/tedb34/Edition34_Chapter05.pdf.
7. USDOE Office of Energy Efficiency and Renewable Energy, Just the Basics Diesel Engine , 2003. Used estimated diesel engine efficiency of 45% from
http://wwwl.eere.energy.gov/vehiclesandfuels/pdfs/basics/jtb_diesel_engine.pdf.
8. U.S. Energy Information Administration, Energy Explained- Energy Units and Calculators, 2015. Used diesel energy content of 137,871 Btu/gal and
gasoline energy content of 120,476 Btu/gal from http://www.eia.gov/energyexplained/?page=about_energy_units.
9. Conversion factor used: 1 HP = 2544.43 Btu/hr
Appendix C - Air Emissions and Energy Analysis C-32 September 30, 2016

Alternative 1:
MNA
AIR EMISSIONS - CLIFFSIDE
Page 1 of 3
Since similar monitoring would be required for each option for the project duration, similar emissions are expected for each and the emissions are not included in this estimate. It is expected that the emissions contributions from
personal vehicles due to monitoring would be insignificant compared to the other emission sources.
Alternative 2:
CIP
CIP Duration = 12 hr/day 270 day/yr 3.0 years 82340 truck trips carrying cap material
119 truck trips carrying liner material
Appendix C - Air Emissions and Energy Analysis C-33 September 30, 2016
Usage
NOx
Emission Factors
PM10/PM2_5 Direct CO.
Direct CH4
Emissions
(tons/yr)
Cumulative Emissions
(tons CO,e)
Activity
Value Units
Value Units
Value Units
Value Units
Value Units
NOx
PM10/PM2, Direct GHG (COze)
Direct GHG
2 Dozers'
6480 hr/yr
2.0891 lb/hr
0.0858 Ib/hr
239 Ib/hr
0.0234 lb/hr
6.77
0.28
776.26
2328.77
Tractor'
3240 hr/yr
0.4070 lb/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
325.32
Wheeled Backhoe'
3240 hr/yr
0.4070 Ib/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
325.32
Water Truck'
3240 hr/yr
1.3322 lb/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
1265.59
Vibratory Roller'
3240 hr/yr
0.5273lb/hr
0.0353 Ib/hr
67 Ib/hr
0.0071 lb/hr
0.85
0.06
108.83
326.48
Tracked Excavator'
3240 hr/yr
0.6603 lb/hr
0.0332 Ib/hr
120 Ib/hr
0.0089 Ib/hr
1.07
0.05
194.76
584.28
Maint/Service Truck'
3240 hr/yr
1.3322 Ib/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
1265.59
55 KVA Diesel Generator'
3240 hr/yr
0.6102 lb/hr
0.0431 lb/hr
77.9 Ib/hr
0.0073 Ib/hr
0.99
0.07
126.49
379.48
15 Personal Vehicles2,3,4,5,6
121500 miles r
/y
0.95 g/mile
0.0045 g/mile
410 g/mile j
0.0452 g/mile
0.13
0.00
55.10
165.30
Truck Transport - Cap Materia 17,8,9,10
27447 truck trips/yr
459.55 g/truck trip
10.75 g/truck trip
138000 g/truck trip
0.255 g/truck trip
13.90
0.33
4175.35
12526.06
Truck Transport - Liner Materia 17,8,9,10,11
40 truck trips/yr
1838.20 g/truck trip I
43.00 g/truck trip I
552000 g/truck trip 1
1.02 g/truck trip
0.08
0.00
24.14
72.41
29.43
1.02
6,521.54
19,564.61
Appendix C - Air Emissions and Energy Analysis C-33 September 30, 2016

Option 3:
Landfill Construction Duration =
Excavation Duration =
Closure Duration =
Excavation and Landfill
12 hr/day 300 day/yr 1.7 years 96 truck trips carrying liner material (construction & closure)
12 hr/day 270 day/yr 14.6 years 394500 truck trips carrying ash
12 hr/day 270 day/yr 1.0 years 15683 truck trips carrying closure material
AIR EMISSIONS - CLIFFSIDE
Page 2 of 3
Appendix C - Air Emissions and Energy Analysis C-34 September 30, 2016
Usage
NOx
Emission Factors
PM10/PM2.5 Direct CO.
Direct CH4
Emissions
(tons/yr)
Cumulative Emissions
(tons CO,e)
Activity
Value Units
Value Units
Value Units
Value Units
Value Units
NOx
PMI,/PM2, Direct GHG (COze)
Direct GHG
EXCAVATION
2 Tracked Excavators'
6480 hr/yr
0.6603 lb/hr
0.0332 Ib/hr
120 Ib/hr
0.0089 lb/hr
2.14
0.11
389.52
5687.01
2 Dozers'
6480 hr/yr
2.0891 lb/hr
0.0858 Ib/hr
239 Ib/hr
0.0234 Ib/hr
6.77
0.28
776.26
11333.33
Wheeled Loader'
3240 hr/yr
0.7114 Ib/hr
0.0375 Ib/hr
109 Ib/hr
0.0089 Ib/hr
1.15
0.06
176.94
2583.33
2 Dump Trucks'
6480 hr/yr
0.0587 Ib/hr
0.0024 Ib/hr
7.6 Ib/hr
0.0008 Ib/hr
0.19
0.01
24.69
360.46
Water Truck'
3240 hr/yr
1.3322 lb/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
6159.22
Wheeled Backhoe'
3240 hr/yr
0.4070 lb/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
1583.21
2 6-8" Pumps'
6480 hr/yr
0.3830 lb/hr
0.0239 Ib/hr
49.6 Ib/hr
0.0051lb/hr
1.24
0.08
161.12
2352.31
55 KVA Diesel Generator'
3240 hr/yr
0.6102 lb/hr
0.0431 lb/hr
77.9 Ib/hr
0.0073 Ib/hr
0.99
0.07
126.49
1846.81
15 Personal Vehicles2,3,4'5
121500 miles r
/y
0.95 g/mile
0.0045 g/mile
410 g/mile
0.0452 g/mile
0.13
0.00
55.10
804.47
MATERIAL TRANSPORT
Truck Transport - Ash 7,8,9,10
27021 truck trips/yr
459.55 g/truck trip
10.75 g/truck trip
138000 g/truck trip
0.2550 g/truck trip
13.69
0.32
4110.53
60013.75
Truck Transport - Closure Material 7'8'9'10
15683 truck trips/yr
18.38 g/truck trip
0.43 g/truck trip
5520 g/truck trip
0.0102 g/truck trip
0.32
0.01
95.43
95.43
Truck Transport - Liner Materia 17,8,9,10,11
36 truck trips/yr
1838.20 g/truck trip
43 g/truck trip
552000 g/truck trip
1.0200 g/truck trip
0.07
0.00
21.64
58.42
LANDFILL CONSTRUCT.
8 Tracked Excavators'
28800 hr/yr
0.6603 lb/hr
0.0332 Ib/hr
120 Ib/hr
0.0089 Ib/hr
9.51
0.48
1731.20
4674.25
8 Dozers'
28800 hr/yr
2.0891 Ib/hr
0.0858 Ib/hr
239 Ib/hr
0.0234 Ib/hr
30.08
1.24
3450.02
9315.06
4 Vibratory Compactors'
14400 hr/yr
0.568 Ib/hr
0.0234 Ib/hr
123 Ib/hr
0.0065 lb/hr
4.09
0.17
886.77
2394.28
4 Wheeled Loaders'
14400 hr/yr
0.7114 Ib/hr
0.0375 Ib/hr
109 Ib/hr
0.0089 Ib/hr
5.12
0.27
786.40
2123.29
8 Dump Trucks'
28800 hr/yr
0.0587 lb/hr
0.0024 Ib/hr
7.6 Ib/hr
0.0008 Ib/hr
0.85
0.03
109.73
296.27
4 Water Trucks'
14400 hr/yr
1.3322 lb/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
9.59
0.33
1874.95
5062.37
4 Wheeled Backhoes'
14400 hr/yr
0.4070 lb/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
2.93
0.19
481.95
1301.27
8 6-8" Pumps'
28800 hr/yr
0.3830 lb/hr
0.0239 Ib/hr
49.6 Ib/hr
0.0051lb/hr
5.52
0.34
716.08
1933.41
4 M aint/Service Trucks'
14400 hr/yr
1.3322 lb/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
9.59
0.33
1874.95
5062.37
4 55 KVA Diesel Generator'
14400 hr/yr
0.6102 lb/hr
0.0431 lb/hr
77.9 Ib/hr
0.0073 Ib/hr
4.39
0.31
562.19
1517.92
100 Personal Vehicles2'3'4'5
900000 miles r
/y
0.95 g/mile
0.0045 g/mile
410 g/mile
0.0452 g/mile
0.94
0.00
408
1102.01
LANDFILL FILLING
2 Dozers'
6480 hr/yr
2.0891 lb/hr
0.0858 Ib/hr
239 Ib/hr
0.0234 Ib/hr
6.77
0.28
776.26
11333.33
Tractor'
3240 hr/yr
0.4070 lb/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
1583.21
Wheeled Backhoel
3240 hr/yr
0.4070 lb/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
1583.21
Water Truck'
3240 hr/yr
1.3322 lb/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
6159.22
Vibratory Roller'
3240 hr/yr
0.5273lb/hr I
0.0353 Ib/hr
67 Ib/hr
0.0071 lb/hr
0.85
0.06
108.83
1588.88
Tracked Excavator' I
3240 hr/yr I
0.6603lb/hr I
0.0332 Ib/hr I
120 Ib/hr
0.0089 Ib/hr
1.07
0.05
194.761
2843.50
M aint/Service Truck' 1
3240 hr/yr 1
1.3322 lb/hr I
0.0459 Ib/hr 1
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
6159.22
55 KVA Diesel Generator'
3240 hr/yr
0.6102lb/hr
0.0431lb/hr
77.9 ZhrI
0.0073 Ib/hr 1
0.99
0.071
126.491
1846.81
Appendix C - Air Emissions and Energy Analysis C-34 September 30, 2016

AIR EMISSIONS - CLIFFSIDE
Page 3 of 3
Notes:
1. South Coast Air Quality Management District Off -Road Model Mobile Source Emission Factors for a 2016 fleet average from http://www.agmd.gov/home/regulations/ceqa/air-quality-analysis-handbook/off-road-mobile-source-
emission-factors.
2. USEPA Center for Corporate Climate Leadership Greenhouse Gas Inventory Guidance: Direct Emissions from Mobile Combustion Sources Tier 1 Gasoline Light -Duty Truck emission factors (0.0452 g CH4/mile) from
https://www.epa.gov/sites/prod uction/files/2016-03/documents/mobi leem issions_3_2016. pdf.
3. Personally Operated Vehicle (POV) use is estimated as:
-Excavation: 15 persons/day * 30 miles/person * 270 day/yr (it is assumed each person travels 15 -miles one-way to work);
-Landfill Construction: 25 persons/day * 30 miles/person * 270 day/yr.
4. USDOT Bureau of Transportation Statistics Average Fuel Efficiency of U.S. Light Duty Vehicles for calendar year 2014 (21.4 miles/gal) for POV CO2 emissions from
http://www. rita.dot.gov/bts/sites/rita.dot.gov. bts/fi les/publications/nationa I_transportation_statistics/html/table_04 23.htm I.
5. 100 -yr GWP for CH4 (25 kg CC2e/kg CH4) from Intergovernmental Panel on Climate Change (IPCC), Fourth Assessment Report (AR4), 2007.
6. USEPA Office of Transportation and Air Quality Average Annual Emissions and Fuel Consumption for Gasoline -Fueled Passenger Cars and Light Trucks light-duty trucks emissions estimates for the in -use fleet as of 2008 based on
https://www3.epa.gov/otaq/consumer/42OfO8O24.pdf.
7. It is assumed that the landfill location is 25 miles away, so 1 truck trip carrying ash is 50 miles, and 20 -ton trucks are used. It is assumed that the landfill cap/closure material for Option 3 is taken from an adjacent land parcel,
thus 1 truck trip carrying cap/closure material is taken to be 2 miles. It is assumed that the landfill cap/closure material for Option 2 is taken from a site 25 miles aways, so 1 truck trip carrying cap/closure material for Option 2 is
taken to be 50 miles.
8. USEPA Office of Transportation and Air Quality Average In -Use Emissions from Heavy -Duty Trucks NOx and PM10/PM2.5 emission factors approximated as a diesel Heavy -Duty Vehicle Class Vllla (33,001-60,000 Ib GVWR--since it
is for 20 ton (40,000 Ib) material + truck) --based on the in -use fleet from July 2008 from https://www3.epa.gov/otaq/consumer/42OfO8O27.pdf.
9. USEPA Center for Corporate Climate Leadership Emission Factors for Greenhouse Gas Inventories greenhouse gas emission factors approximated as heavy duty vehicles for 1960 -present from Table 4 of
https://www.epa.gov/sites/production/files/2015-12/documents/emission-factors_nov_2015.pdf, dated November 2015.
10. It is assumed that the weight of the vehicle + load is approximately 60,000 Ib (20 -ton load and 10 -ton truck). Diesel heavy duty combination truck CO2 emission factor for MY2014/Class 8/Day Cab is 92 g CO2/ton-mile taken
from https://www.gpo.gov/fdsys/pkg/FR-2011-09-15/pdf/2011-20740.pdf (EPA/DOT Federal Register Vol. 76, No. 179, 15 September 2011).
-92 g CO2/ton-mile * (30 ton*x mile)/truck trip = y g CO2/truck trip
11. It is assumed that the liner is transported 100 miles to the site/landfill on public roads and approximately 10 tons of liner are transported per trip (3240 Ib/roll * 1 ton/2000 Ib * 6 rolls/truck trip = 10 ton/truck trip).
Appendix C - Air Emissions and Energy Analysis C-35 September 30, 2016
Usage
NOx
Emission Factors
PMI,/PMZ 5 Direct CO,
Direct CH4
Emissions
(tons/yr)
Cumulative Emissions
(tons COZe)
Activity
Value Units
Value Units
Value Units
Value Units
Value Units
NOx
PM,,/PM,, Direct GHG (COZe)
Direct GHG
Personal VehicleS2'3'4'5'6
121500 miles/yr
0.95 g/mile
0.0045 g/mile
410 g/mile
0.0452 g/mile
0.13
0.00
55.10
804.47
LANDFILL CLOSURE
2 Dozers'
6480 hr/yr
2.0891 lb/hr
0.0858 Ib/hr
239 Ib/hr
0.0234 Ib/hr
6.77
0.28
776.26
776.26
Tractor'
3240 hr/yr
0.4070lb/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
108.44
Wheeled Backhoe'
3240 hr/yr
0.4070 Ib/hr
0.0258 Ib/hr
66.8 Ib/hr
0.0055 Ib/hr
0.66
0.04
108.44
108.44
Water Truck'
3240 hr/yr
1.3322 Ib/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
421.86
Vibratory Roller'
3240 hr/yr
0.5273 Ib/hr
0.0353 Ib/hr
67 Ib/hr
0.0071 Ib/hr
0.85
0.06
108.83
108.83
Tracked Excavator'
3240 hr/yr
0.6603 lb/hr
0.0332 Ib/hr
120 Ib/hr
0.0089 Ib/hr
1.07
0.05
194.76
194.76
Maint/Service Truck'
3240 hr/yr
1.3322 lb/hr
0.0459 Ib/hr
260 Ib/hr
0.0164 Ib/hr
2.16
0.07
421.86
421.86
55 KVA Diesel Generator'
3240 hr/yr
0.6102lb/hr
0.0431lb/hr
77.9 Ib/hr
0.0073 Ib/hr
0.99
0.07
126.49
126.49
Personal Vehicles2,3,4,5,6
121500 miles/yr
I 0.95 g/mile
I 0.0045 g/mile
I 410 g/mile
0.0452 g/mile
0.13
0.00
55.10
55.10
143.00
6.12
23,994.51
163,884.10
Notes:
1. South Coast Air Quality Management District Off -Road Model Mobile Source Emission Factors for a 2016 fleet average from http://www.agmd.gov/home/regulations/ceqa/air-quality-analysis-handbook/off-road-mobile-source-
emission-factors.
2. USEPA Center for Corporate Climate Leadership Greenhouse Gas Inventory Guidance: Direct Emissions from Mobile Combustion Sources Tier 1 Gasoline Light -Duty Truck emission factors (0.0452 g CH4/mile) from
https://www.epa.gov/sites/prod uction/files/2016-03/documents/mobi leem issions_3_2016. pdf.
3. Personally Operated Vehicle (POV) use is estimated as:
-Excavation: 15 persons/day * 30 miles/person * 270 day/yr (it is assumed each person travels 15 -miles one-way to work);
-Landfill Construction: 25 persons/day * 30 miles/person * 270 day/yr.
4. USDOT Bureau of Transportation Statistics Average Fuel Efficiency of U.S. Light Duty Vehicles for calendar year 2014 (21.4 miles/gal) for POV CO2 emissions from
http://www. rita.dot.gov/bts/sites/rita.dot.gov. bts/fi les/publications/nationa I_transportation_statistics/html/table_04 23.htm I.
5. 100 -yr GWP for CH4 (25 kg CC2e/kg CH4) from Intergovernmental Panel on Climate Change (IPCC), Fourth Assessment Report (AR4), 2007.
6. USEPA Office of Transportation and Air Quality Average Annual Emissions and Fuel Consumption for Gasoline -Fueled Passenger Cars and Light Trucks light-duty trucks emissions estimates for the in -use fleet as of 2008 based on
https://www3.epa.gov/otaq/consumer/42OfO8O24.pdf.
7. It is assumed that the landfill location is 25 miles away, so 1 truck trip carrying ash is 50 miles, and 20 -ton trucks are used. It is assumed that the landfill cap/closure material for Option 3 is taken from an adjacent land parcel,
thus 1 truck trip carrying cap/closure material is taken to be 2 miles. It is assumed that the landfill cap/closure material for Option 2 is taken from a site 25 miles aways, so 1 truck trip carrying cap/closure material for Option 2 is
taken to be 50 miles.
8. USEPA Office of Transportation and Air Quality Average In -Use Emissions from Heavy -Duty Trucks NOx and PM10/PM2.5 emission factors approximated as a diesel Heavy -Duty Vehicle Class Vllla (33,001-60,000 Ib GVWR--since it
is for 20 ton (40,000 Ib) material + truck) --based on the in -use fleet from July 2008 from https://www3.epa.gov/otaq/consumer/42OfO8O27.pdf.
9. USEPA Center for Corporate Climate Leadership Emission Factors for Greenhouse Gas Inventories greenhouse gas emission factors approximated as heavy duty vehicles for 1960 -present from Table 4 of
https://www.epa.gov/sites/production/files/2015-12/documents/emission-factors_nov_2015.pdf, dated November 2015.
10. It is assumed that the weight of the vehicle + load is approximately 60,000 Ib (20 -ton load and 10 -ton truck). Diesel heavy duty combination truck CO2 emission factor for MY2014/Class 8/Day Cab is 92 g CO2/ton-mile taken
from https://www.gpo.gov/fdsys/pkg/FR-2011-09-15/pdf/2011-20740.pdf (EPA/DOT Federal Register Vol. 76, No. 179, 15 September 2011).
-92 g CO2/ton-mile * (30 ton*x mile)/truck trip = y g CO2/truck trip
11. It is assumed that the liner is transported 100 miles to the site/landfill on public roads and approximately 10 tons of liner are transported per trip (3240 Ib/roll * 1 ton/2000 Ib * 6 rolls/truck trip = 10 ton/truck trip).
Appendix C - Air Emissions and Energy Analysis C-35 September 30, 2016

Alternative 1:
MNA
INDIRECT GHG EMISSIONS - CLIFFSIDE
Page 1 of 4
Since similar monitoring would be required for each option for the project duration, similar emissions are expected for each and the emissions are not included in this estimate. It is
expected that the emissions contributions from personal vehicles due to monitoring would be insignificant compared to the other emission sources.
Alternative 2:
CIP
CIP Duration = 12 hr/day 270 day/yr 3.0 years 82340 truck trips carrying cap material
119 truck trips carrying liner material
Activity
Number
of Units
Usage
Value Units
Annual Total
Energy Usage
Value Units
Total Project
GGE
Value Units
WTP (Indirect)
GHG Emissionss
Value Units
Project Indirect
GHG Emissions
Value Units
Dozers
2
6480 hr/yr
18319.9 MMBtu/yr
152062.6 GGE/yr
308 tons CO2e/yr
924 tons CO2e
Tractor
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons CO2e/yr
139 tons CO2e
Wheeled Backhoe
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons CO2e/yr
139 tons CO2e
Water Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons CO2e/yr
462 tons CO2e
Vibratory Roller
1
3240 hr/yr
2198.4 MMBtu/yr
18247.5 GGE/yr
37 tons CO2e/yr
111 tons CO2e
Tracked Excavator
1
3240 hr/yr
3664.0 MMBtu/yr
30412.5 GGE/yr
62 tons CO2e/yr
185 tons CO2e
Maint/Service Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons CO2e/yr
462 tons CO2e
55 KVA Diesel Generator
1
3240 hr/yr
1080.9 MMBtu/yr
8971.7 GGE/yr
18 tons CO2e/yr
55 tons CO2e
Personal Vehicles
15
121500 miles/yr
10 tons CO2e/yr
31 tons CO2e
Truck Transport - Cap Material
N/A
27447 truck trips/yr
1372341 miles/yr
89 tons CO2e/yr
266 tons CO2e
Truck Transport - Liner Materia 12,3
N/A
40 truck trips/yr
7941 miles/yr
0.5 tons CO2e/yr
2 tons CO2e
925 Itons CO2e/yr
2,774 Itons CO2e
Appendix C - Air Emissions and Energy Analysis C-36 September 30, 2016

Alternative 3:
Landfill Construction Duration =
Excavation Duration =
Closure Duration =
Removal
12 hr/day 300 day/yr
12 hr/day 270 day/yr
12 hr/day 270 day/yr
INDIRECT GHG EMISSIONS - CLIFFSIDE
1.7 years 96 truck trips
14.6 years 394500 truck trips
1 years 15683 truck trips
Page 2 of 4
carrying liner material
carrying ash
carrying closure material
Activity
Number
of Units
Total Usage
Value Units
Annual Total
Energy Usage
Value Units
Total Project
GGE
Value Units
WTP (Indirect)
GHG Emissionss
Value Units
Project Indirect
GHG Emissions
Value Units
EXCAVATION
Tracked Excavators
2
6480 hr/yr
7328.0 MMBtu/yr
60825.0 GGE/yr
123 tons CO2e/yr
1799 tons CO2e
Dozers
2
6480 hr/yr
18319.9 MMBtu/yr
152062.6 GGE/yr
308 tons CO2e/yr
4496 tons CO2e
Wheeled Loader
1
3240 hr/yr
3206.0 MMBtu/yr
26611.0 GGE/yr
54 tons CO2e/yr
787 tons CO2e
Dump Trucks
2
6480 hr/yr
916.0 MMBtu/yr
7603.1 GGE/yr
15 tons CO2e/yr
225 tons CO2e
Water Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons CO2e/yr
2248 tons CO2e
Wheeled Backhoe
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons CO2e/yr
674 tons CO2e
6-8" Pumps
2
6480 hr/yr
3664.0 MMBtu/yr
30412.5 GGE/yr
62 tons CO2e/yr
899 tons CO2e
55 KVA Diesel Generator
1
3240 hr/yr
1080.9 MMBtu/yr
8971.7 GGE/yr
18 tons CO2e/yr
265 tons CO2e
Personal Vehicles
15
121500 miles/yr
10 tons CO2e/yr
150 tons CO2e
MATERIAL TRANSPORT
Truck Transport - Ash
N/A
27021 truck trips/yr
1351027 miles/yr
87 tons CO2e/yr
1276 tons CO2e
Truck Transport - Closure Materia 12
N/A
15683 truck trips/yr
31366 miles/yr
2 tons CO2e/yr
2 tons CO2e
Truck Transport - Liner Materia 12,3
N/A
36 truck trips/yr
7102 miles/yr
0.5 tons CO2e/yr
1 tons CO2e
LANDFILL CONSTRUCTION
Tracked Excavators
8
28800 hr/yr
32568.7 MMBtu/yr
270333.5 GGE/yr
548 tons CO2e/yr
931 tons CO2e
Dozers
8
28800 hr/yr
81421.8 MMBtu/yr
675833.9 GGE/yr
1369 tons CO2e/yr
2327 tons CO2e
Vibratory Compactors
4
14400 hr/yr
9770.6 MMBtu/yr
81100.1 GGE/yr
164 tons CO2e/yr
279 tons CO2e
Wheeled Loaders
4
14400 hr/yr
14248.8 MMBtu/yr
118270.9 GGE/yr
240 tons CO2e/yr
407 tons CO2e
Dump Trucks
8 1
28800 hr/yr
4071.1 MMBtu/yr
33791.7 GGE/yr
68 tons CO2e/yr
116 tons CO2e
Water Trucks
4
14400 hr/yr
40710.9 MMBtu/yr
337916.9 GGE/yr
684 tons CO2e/yr
1163 tons CO2e
Wheeled Backhoes
4
14400 hr/yr
12213.3 MMBtu/yr
101375.1 GGE/yr
205 tons CO2e/yr
349 tons CO2e
Appendix C - Air Emissions and Energy Analysis C-37 September 30, 2016

INDIRECT GHG EMISSIONS - CLIFFSIDE
Page 3 of 4
Activity
Number
of Units
Total Usage
Value Units
Annual Total
Energy Usage
Value Units
Total Project
GGE
Value Units
WTP (Indirect)
GHG Emissionss
Value Units
Project Indirect
GHG Emissions
Value Units
6-8" Pumps
8
28800 hr/yr
16284.4 MMBtu/yr
135166.8 GGE/yr
274 tons CO2e/yr
465 tons CO2e
Maint/Service Trucks
4
14400 hr/yr
40710.9 MMBtu/yr
337916.9 GGE/yr
684 tons CO2e/yr
1163 tons CO2e
55 KVA Diesel Generators
4
14400 hr/yr
4803.9 MMBtu/yr
39874.2 GGE/yr
81 tons CO2e/yr
137 tons CO2e
Personal Vehicles
100
900000 miles/yr
76 tons CO2e/yr
129 tons CO2e
LANDFILL FILLING
Dozers
2
6480 hr/yr
18319.9 MMBtu/yr
152062.6 GGE/yr
308 tons CO2e/yr
4496 tons CO2e
Tractor
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons CO2e/yr
674 tons CO2e
Wheeled Backhoe
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons CO2e/yr
674 tons CO2e
Water Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons CO2e/yr
2248 tons CO2e
Vibratory Roller
1
3240 hr/yr
2198.4 MMBtu/yr
18247.5 GGE/yr
37 tons CO2e/yr
540 tons CO2e
Tracked Excavator
1
3240 hr/yr
3664.0 MMBtu/yr
30412.5 GGE/yr
62 tons CO2e/yr
899 tons CO2e
Maint/Service Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons CO2e/yr
2248 tons CO2e
55 KVA Diesel Generator
1
3240 hr/yr
1080.9 MMBtu/yr
8971.7 GGE/yr
18 tons CO2e/yr
265 tons CO2e
Personal Vehicles
15
121500 miles/yr
10 tons CO2e/yr
150 tons CO2e
LANDFILL CLOSURE
Dozers
2
6480 hr/yr
18319.9 MMBtu/yr
152062.6 GGE/yr
308 tons CO2e/yr
308 tons CO2e
Tractor
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons CO2e/yr
46 tons CO2e
Wheeled Backhoe
1
3240 hr/yr
2748.0 MMBtu/yr
22809.4 GGE/yr
46 tons CO2e/yr
46 tons CO2e
Water Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons CO2e/yr
154 tons CO2e
Vibratory Roller
1
3240 hr/yr
2198.4 MMBtu/yr
18247.5 GGE/yr
37 tons CO2e/yr
37 tons CO2e
Tracked Excavator
1
3240 hr/yr
3664.0 MMBtu/yr
30412.5 GGE/yr
62 tons CO2e/yr
62 tons CO2e
Maint/Service Truck
1
3240 hr/yr
9159.9 MMBtu/yr
76031.3 GGE/yr
154 tons CO2e/yr
154 tons CO2e
55 KVA Diesel Generator
1
3240 hr/yr
1080.9 MMBtu/yr
8971.7 GGE/yr
18 tons CO2e/yr
18 tons CO2e
Personal Vehicles
15
121500 miles/yr
I 1
10 tons CO2e/yr
10 tons CO2e
6,945 tons CO2e/yr
33,324 tons CO2e
Appendix C - Air Emissions and Energy Analysis C-38 September 30, 2016

INDIRECT GHG EMISSIONS - CLIFFSIDE
Page 4 of 4
Notes:
1. Personally Operated Vehicle use is estimated as:
-Excavation: 15 persons/day * 30 miles/person * 270 day/yr (it is assumed each person travels 15 -miles one-way to work);
-Landfill Construction: 25 persons/day * 30 miles/person * 270 day/yr.
2. It is assumed that the landfill location is 25 miles away, so 1 truck trip carrying ash is 50 miles, and 20 -ton trucks are used. It is assumed that the landfill cap/closure material for
Option 3 is taken from an adjacent land parcel, thus 1 truck trip carrying cap/closure material is taken to be 2 miles. It is assumed that the landfill cap/closure material for Option 2
is taken from a site 25 miles aways, so 1 truck trip carrying cap/closure material for Option 2 is taken to be 50 miles.
3. It is assumed that the liner is transported 100 miles to the site/landfill on public roads and approximately 10 tons of liner are transported per trip
(3240 Ib/roll * 1 ton/2000 Ib * 6 rolls/truck trip = 10 ton/truck trip).
4. U.S. Energy Information Administration, Energy Explained - Energy Units and Calculators, 2015. Used diesel energy content of 137,871 Btu/gal and
gasoline energy content of 120,476 Btu/gal from http://www.eia.gov/energyexplained/?page=about_energy_u nits.
5. GHG emission factors from Results created by ANL on 11/12/2015 using GREETI_2015 version, October 2015 release , Argonne National Laboratory, 2015.
Emission Factors Well -To -Pump (WTP)16
Diesel 59 g CO2e/mi 1837 g CO2e/gge
Gasoline (E10) 77 g CO2e/mi
6. Annual Total Energy Usage values taken from Energy Usage calculations.
7. Conversion factor used: 1 HP = 2544.43 Btu/hr
Abbreviations:
GHG = Greenhouse Gas.
WTP = "Well -to -Pump" (also called Well -to -Tank, or WTT), refers to processes and activities involved in producing a fuel through when that fuel reaches a fueling station. This may
include raw material extraction, transportation, fuel production, distribution, and storage. For the purposes of this study, only WTP GHG emissions are considered as indirect
emissions. Indirect emissions in the PTW (Pump -to -Wheels) stage, such as refueling and evaporation, are not included as indirect emissions.
Appendix C - Air Emissions and Energy Analysis C-39 September 30, 2016

Alternative 1:
MINA
ENERGY USAGE - CLIFFSIDE
Page 1 of 4
Since similar monitoring would be required for each option for the project duration, similar energy usages are expected for each and the energy usage is not included in this estimate. It is
expected that the energy usage contributions from personal vehicles due to monitoring would be insignificant compared to the other source of energy usage.
Alternative 2:
CIP
CIP Duration = 12 hr/day 270 day/yr 3.0 years 82340 truck trips carrying cap material
119 truck trips carrying liner material
Activity
Number
of Units
Usage
Value Units
Value Units
Hourly (per Unit)
Energy Usage9
Value Units
Annual Total
Energy Usage
Value Units
Total Project Energy
Usage
Value Units
Estimated Engine Size
Dozers 1,7
2
6480 hr/yr
500 HP each
2.8 MMBtu/hr
18320 MMBtu/yr
54960 MMBtu
Tractors''
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
8244 MMBtu
Wheeled Backhoe 1,7
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
8244 MMBtu
Water Truck l''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
27480 MMBtu
Vibratory Rolled''
1
3240 hr/yr
120 HP each
0.7 MMBtu/hr
2198 MMBtu/yr
6595 MMBtu
Tracked Excavators''
1
3240 hr/yr
200 HP each
1.1 MMBtu/hr
3664 MMBtu/yr
10992 MMBtu
Maint/Service Truck s'7
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
27480 MMBtu
55 KVA Diesel Generators''
1
3240 hr/yr
59 HP each
0.3 MMBtu/hr
1081 MMBtu/yr
3243 MMBtu
Fuel Usage
Personal VehicleS2'3'8
15
121500 miles/yr
5678 gal/yr
684 MMBtu/yr
9987 MMBtu
Truck Transport - Cap Materia 14,6,8
N/A
27447 truck trips/yr
1372341 miles/yr
236610 gal/yr
32622 MMBtu/yr
97865 MMBtu
Truck Transport - Liner Material °' 5' 6'8
N/A
40 truck trips/yr
7941 miles/yr
1369 gal/yr
189 MMBtu/yr
566 MMBtu
82,574 MMBtu/yr
255,655 MMBtu
Appendix C - Air Emissions and Energy Analysis C-40 September 30, 2016

Alternative 3: Removal
Landfill Construction Duration =
Excavation Duration =
Closure Duration =
ENERGY USAGE - CLIFFSIDE
Page 2 of 4
12 hr/day
300 day/yr
1.7 years
96 truck trips
carrying liner material
12 hr/day
270 day/yr
14.6 years
394500 truck trips
carrying ash
12 hr/day
270 day/yr
1 years
15683 truck trips
carrying closure material
Activity
Number
of Units
Total Usage
Value Units
Value Units
Hourly (per Unit)
Energy Usage
Value Units
Annual Total
Energy Usage
Value Units
Total Project Energy
Usage
Value Units
EXCAVATION
Estimated Engine Size
Tracked Excavators 1,7
2
6480 hr/yr
200 HP each
1.1 MMBtu/hr
7328 MMBtu/yr
106988 MMBtu
Dozers 1,7
2
6480 hr/yr
500 HP each
2.8 MMBtu/hr
18320 MMBtu/yr
267470 MMBtu
Wheeled Loaded''
1
3240 hr/yr
175 HP each
1.0 MMBtu/hr
3206 MMBtu/yr
46807 MMBtu
Dump Trucks 1,7
2
6480 hr/yr
25 HP each
0.1 MMBtu/hr
916 MMBtu/yr
13374 MMBtu
Water Truck l''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
133735 MMBtu
Wheeled Backhoe 1,7
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
40121 MMBtu
6-8" Pumpsl''
2
6480 hr/yr
100 HP each
0.6 MMBtu/hr
3664 MMBtu/yr
53494 MMBtu
55 KVA Diesel Generators''
1
3240 hr/yr
59 HP each
0.3 MMBtu/hr
1081 MMBtu/yr
15781 MMBtu
Fuel Usage
Personal VehicleS2'3'8
15
121500 miles/yr
5678 gal/yr
684 MMBtu/yr
9986.6 MMBtu
MATERIAL TRANSPORT
Fuel Usage
Truck Transport - Ash 4,6,8
N/A
27021 truck trips/yr
1351027 miles/yr
232936 gal/yr
32115 MMBtu/yr
468880 MMBtu
Truck Transport - Closure Materia 14,6,8
N/A
15683 truck trips/yr
31366 miles/yr
5408 gal/yr
746 MMBtu/yr
746 MMBtu
Truck Transport - Liner Materia 14,5,6,8
N/A
36 truck trips/yr
7102 miles/yr
1224 gal/yr
169 MMBtu/yr
456 MMBtu
LANDFILL CONSTRUCTION
Estimated Engine Size
Tracked Excavators s''
8
28800 hr/yr
200 HP each
1.1 MMBtu/hr
32569 MMBtu/yr
55367 MMBtu
Dozers 1,7
8
28800 hr/yr
500 HP each
2.8 MMBtu/hr
81422 MMBtu/yr
138417 MMBtu
Vibratory Compactors''
4
14400 hr/yr
120 HP each
0.7 MMBtu/hr
9771 MMBtu/yr
16610 MMBtu
Wheeled Loaders''
4
14400 hr/yr
175 HP each
1.0 MMBtu/hr
14249 MMBtu/yr
24223 MMBtu
Dump Trucks s''
8
28800 hr/yr
25 HP each
0.1 MMBtu/hr
4071 MMBtu/yr
6921 MMBtu
Water Trucks s''
4
14400 hr/yr
500 HP each
2.8 MMBtu/hr
40711 MMBtu/yr
69208 MMBtu
Wheeled Backhoe S1,7
4
14400 hr/yr
150 HP each
0.8 MMBtu/hr
12213 MMBtu/yr
20763 MMBtu
6-8" Pumpss''
8
28800 hr/yr
100 HP each
0.6 MMBtu/hr
16284 MMBtu/yr
27683 MMBtu
Maint/Service Trucks''
4
14400 hr/yr
500 HP each
2.8 MMBtu/hr
40711 MMBtu/yr
69208 MMBtu
55 KVA Diesel Generators''
4
14400 hr/yr
591 HP each
0.3 MMBtu/hr
4804 MMBtu/yr
8167 MMBtu
Fuel Usage
Appendix C - Air Emissions and Energy Analysis C-41 September 30, 2016

ENERGY USAGE - CLIFFSIDE
Page 3 of 4
Activity
Number
of Units
Total Usage
Value Units
Value Units
Hourly (per Unit)
Energy Usage
Value Units
Annual Total
Energy Usage
Value Units
Total Project Energy
Usage
Value Units
Personal VehicleS2'3'8
100
900000 miles/yr
42056 gal/yr
5067 MMBtu/yr
8613.5 MMBtu
LANDFILL FILLING
Estimated Engine Size
Dozers 1,7
2
6480 hr/yr
500 HP each
2.8 MMBtu/hr
18320 MMBtu/yr
267470 MMBtu
Tractors''
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
40121 MMBtu
Wheeled Backhoe 1,7
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
40121 MMBtu
Water Trucks''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
133735 MMBtu
Vibratory Rolled''
1
3240 hr/yr
120 HP each
0.7 MMBtu/hr
2198 MMBtu/yr
32096 MMBtu
Tracked Excavators''
1
3240 hr/yr
200 HP each
1.1 MMBtu/hr
3664 MMBtu/yr
53494 MMBtu
Maint/Service Trucks''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
133735 MMBtu
55 KVA Diesel Generators''
1
3240 hr/yr
59 HP each
0.3 MMBtu/hr
1081 MMBtu/yr
15781 MMBtu
Fuel Usage
Personal VehicleS2'3'8
15
121500 miles/yr
5678 gal/yr
684 MMBtu/yr
9986.6 MMBtu
LANDFILL CLOSURE
Estimated Engine Size
Dozers 1,7
2
6480 hr/yr
500 HP each
2.8 MMBtu/hr
18320 MMBtu/yr
18320 MMBtu
Tractors''
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
2748 MMBtu
Wheeled Backhoe''?
1
3240 hr/yr
150 HP each
0.8 MMBtu/hr
2748 MMBtu/yr
2748 MMBtu
Water Trucks''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
9160 MMBtu
Vibratory Rolled''
1
3240 hr/yr
120 HP each
0.7 MMBtu/hr
2198 MMBtu/yr
2198 MMBtu
Tracked Excavators''
1
3240 hr/yr
200 HP each
1.1 MMBtu/hr
3664 MMBtu/yr
3664 MMBtu
Maint/Service Trucks''
1
3240 hr/yr
500 HP each
2.8 MMBtu/hr
9160 MMBtu/yr
9160 MMBtu
55 KVA Diesel Generators''
1
3240 hr/yr
59 HP each
0.3 MMBtu/hr
1081 MMBtu/yr
1081 MMBtu
Fuel Usage
Personal VehicleS2'3'8
15
121500 miles/yr
5678 gal/yr
684 MMBtu/yr
684.0 MMBtu
441,533 MMBtu/yr
2,379,322 MMBtu
Appendix C - Air Emissions and Energy Analysis C-42 September 30, 2016

ENERGY USAGE - CLIFFSIDE
Page 4 of 4
Notes:
1. South Coast Air Quality Management District Off -Road Model Mobile Source Emission Factors for a 2016 fleet average from http://www.agmd.gov/home/regulations/ceqa/air-quality-analysis-
handbook/off-road-mobile-source-emission-factors.
2. Personally Operated Vehicle use is estimated as:
-Excavation: 15 persons/day * 30 miles/person * 270 day/yr (it is assumed each person travels 15 -miles one-way to work);
-Landfill Construction: 25 persons/day * 30 miles/person * 270 day/yr.
3. USDOT Bureau of Transportation Statistics Average Fuel Efficiency of U.S. Light Duty Vehicles for calendar year 2014 U.S. light-duty vehicles ( 21.4 mi/gal) from
http://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/national_transportation_statistics/html/table_04_23.html.
4. It is assumed that the landfill location is 25 miles away, so 1 truck trip carrying ash is 50 miles, and 20 -ton trucks are used. It is assumed that the landfill cap/closure material for Option 3 is
taken from an adjacent land parcel, thus 1 truck trip carrying cap/closure material is taken to be 2 miles. It is assumed that the landfill cap/closure material for Option 2 is taken from a site 25
miles aways, so 1 truck trip carrying cap/closure material for Option 2 is taken to be 50 miles.
S. It is assumed that the liner is transported 100 miles to the site/landfill on public roads and approximately 10 tons of liner are transported per trip
(3240 Ib/roll * 1 ton/2000 Ib * 6 rolls/truck trip = 10 ton/truck trip).
6. Oak Ridge National Laboratory Transportation Energy Data Book, Edition 34, September 2015. Class 7-8 average fuel economy (2013) is 5.8 mi/gal from
http://cta.ornl.gov/data/tedb34/Edition34_Chapter05.pdf.
7. USDOE Office of Energy Efficiency and Renewable Energy, lust the Basics Diesel Engine , 2003. Used estimated diesel engine efficiency of 45% from
http://wwwl.eere.energy.gov/vehiclesandfuels/pdfs/basics/jtb_diesel_engine.pdf.
8. U.S. Energy Information Administration, Energy Explained - Energy Units and Calculators, 2015. Used diesel energy content of 137,871 Btu/gal and
gasoline energy content of 120,476 Btu/gal from http://www.eia.gov/energyexplained/?page=about_energy_units.
9. Conversion factor used: 1 HP = 2544.43 Btu/hr
Appendix C - Air Emissions and Energy Analysis C-43 September 30, 2016

EPS
APPENDIX D
Human Health Risk Analysis
Appendix D — Human Health Risk Analysis D-1 September 30, 2016

0
DI INTRODUCTION
Potential impacts to humans in contact with chemicals in environmental media were estimated for
30 years after implementation of the three remedial alternatives (Monitored Natural Attenuation
(MNA), Cap -in -Place with MNA (CIP), and Removal with MNA Removal). A current condition
(i.e., year 2015-2016) risk assessment was conducted for each site. These risk assessments formed
the basis of estimating the risks' in the future for the three different corrective actions. It is
important to note that the purpose of this analysis is to compare the three different corrective action
alternatives. The purpose is not to accurately determine the actual expected risk for each
alternative.
The current condition risk assessments evaluated the following environmental media: (Area of
Wetness (AOW)/seep soil, AOW/seep water, groundwater, sediment, surface water and fish tissue.
The receptors evaluated included a commercial/industrial worker, construction worker, trespasser,
boater, swimmer, wader, recreational fisher and subsistence fisher. One exposure scenario and
one chemical were excluded from this risk evaluation for the Net Environmental Benefit Analysis
(NEBA). Fish consumption was excluded because the risk assessment for this scenario presented
in the Corrective Action Plan (CAP) documents was not based on fish tissue data and the
assessment as presented was overly -conservative and not representative of the true risk. Lead was
excluded because the risks due to lead are calculated differently than for other chemicals and they
are not additive with other chemicals.
There were two considerations in extrapolating the current risk assessment to the future condition.
The first was to forward project into the future (30 years from implementation/completion of the
corrective action). The second was to project the changes due to each corrective action.
The information available for each site varied. Accordingly, for some environmental media
different techniques were used to estimate the projected potential risks.
' Note, in risk evaluations calculations are performed differently for carcinogenic and non -carcinogenic chemicals.
The Hazard Index (HI) is the measurement used to determine the hazard of non -carcinogens. The Excess Lifetime
Cancer Risk (ELCR) is the measurement used for carcinogenic chemicals. For the purpose of the text of this document
the term "risk" is used to generically represent both the cancer risk and hazard. However, the associated tables do
differentiate between ELCR and non -carcinogenic hazard HI.
Appendix D — Human Health Risk Analysis D-2 September 30, 2016

EPS
D2 AOW SOIL AND AOW WATER
This evaluation was conducted the same for each site. It was assumed that the concentrations (and,
thus, risk) for the AOWs would not change from now to 30 years in the future. For the MNA
alternative it was assumed that the risk would be the same as the current risk. The CAPS indicate
that most if not all AOWs would not be present under the CIP alternative. However, to be
conservative it was assumed that 75% of the AOWs would be removed. Accordingly, the projected
MNA risk would be 25% of the current risk. Under the Removal alternative all contaminants in
soil would be removed, thus there would be no contaminants in any future AOWs. Accordingly,
there is no projected Removal risk. The calculation of the projected risks for the AOW/seep Soil
and Water, are shown in Table I and Table 2, respectively.
The Current Risk Assessment values for AOW/seep soil for Allen and Buck were taken from their
respective risk assessments. The current values for Cliffside and Mayo were revised. The revised
risk calculations are shown in Table 113. Cliffside was revised to remove outliers of arsenic and
cobalt that were skewing the dataset and overestimating the risk. Mayo was revised to include
more data (from perimeter soil samples and ash basin ash samples) as the original dataset had only
4 samples and was not representative of a realistic exposure.
Appendix D — Human Health Risk Analysis D-3 September 30, 2016

0
D3 GROUNDWATER
Groundwater modeling was conducted for each site projecting concentrations in groundwater into
the future for the three different alternatives. However, different amounts and types of information
were provided for the groundwater model output for each site. Accordingly, the projection of risks
due to groundwater into the future for each alternative for each site was conducted differently.
D3.1 Allen and Cliffside
The CAP Part 2 report for Cliffside presented results of a groundwater model predicting
concentrations under all three alternatives. The output provided contained excel spreadsheets with
concentrations of each of the chemical under each alternative for specific wells at the compliance
boundary for many years. The concentrations for these wells for 30 -years into the future (after the
action is taken) was estimated from the model. The results from all the wells presented were
averaged to determine estimated groundwater concentrations 30 years after each corrective action
was completed. These concentrations were then multiplied by the Risk Based Concentrations
(RBC) from the risk assessment (included in the CAP Part 2) to determine the projected risk 30
years in the future for each alternative. Not all chemicals included in the risk assessment were
evaluated in the groundwater model. For these chemicals, the concentrations 30 years into the
future were estimated by multiplying the current groundwater concentrations in the risk assessment
by a ratio, which was based on the future modeled groundwater concentrations for the modeled
chemicals divided by the groundwater concentrations used in the risk assessment. The risk
calculations for the future alternatives are shown in Table 3A. The only receptor with exposure to
groundwater is the construction worker.
Allen is similar to Cliffside in that the output of groundwater modeling available was the same so
that modeled concentrations from individual wells could be obtained for 30 years after the different
correction actions. However, the CAP Part 2 report for Allen did not include the Removal
alternative. The groundwater model presented in the CAP Part 1 report did include the Removal
alternative. The ratio of the Removal model to the NINA model from the CAP Part 1 report was
used to estimate the Removal concentrations based on the MNA model results from the CAP Part
2 report. Otherwise the risk estimations for Allen were conducted in the same manner as for
Cliffside and are summarized in Table 3B.
D3.2 Buck
The groundwater model output for Buck was not sufficiently detailed to perform the same analysis
as was conducted for Allen and Cliffside. Graphs depicting the change in concentrations over time
for the three alternatives were presented for some wells and a few chemicals. These graphs for the
wells closest to the downgradient edge of the plume were used to estimate an overall increase or
decrease in concentrations for the different alternatives. The MNA alternative is the same
alternative as the current risk assessment. However, the MNA alternative needed to be projected
Appendix D — Human Health Risk Analysis D-4 September 30, 2016

0
30 years into the future. The graphs were used to determine the ratio between the concentrations
for the NINA alternative 30 years from now to the concentration for the year of the risk assessment.
The MNA concentrations 30 years from now was on average 1.5 times the concentrations from
the year of the risk assessment. Thus, the estimated risks for the NINA alternative was determined
by multiply the current risk values by 1.5. For the CIP alternative the graphs were used to estimate
the ratio of the concentrations from CIP to MNA 30 years from now. The average of these ratios
(0.5) was multiplied by the MNA risk to estimate the CIP risk. The same process was conducted
for Removal using a multiple of 0.6. A summary of the results is presented in Table 3C.
DU Mayo
The output from the groundwater model for Mayo was presented as a series of figures depicting
the extent of the plume at different dates for each alternative. The changes in plume size between
these figures were used to estimate the projected risk between the different alternatives 30 years
into the future. The risk for the MNA alternative was estimated by multiplying the current risk by
1.5. The risk for CIP was estimated by multiplying the NINA risk by 0.25. The risk for Removal
was estimated by multiplying the CIP risk by 0.1. A summary of the results is presented in Table
3D.
Appendix D — Human Health Risk Analysis D-5 September 30, 2016

EPS
D4 SEDIMENT AND SURFACE WATER -
ON-SITE
The on-site sediment and surface water exposure pathways were evaluated the same way for all
sites. It was assumed that the concentrations (and, thus, risk) for on-site sediment and surface
water would not change from now to 30 years from now. For MNA it was assumed that the risk
is the same as in the current risk assessment. Under the CIP and Removal alternatives there is
minimal if any risk into the future. However, to be conservative for the CIP alternative it was
assumed that the risk is 25% of the MMA risk. It assumed there is no risk under the Removal
alternative. The projected risk calculations for on-site soil and on-site surface water are shown in
Tables 4 and 5, respectfully.
Appendix D — Human Health Risk Analysis D-6 September 30, 2016

0
D5 SEDIMENT - OFF-SITE
The off-site sediment exposure pathway was evaluated the same way for all sites. It was assumed
that the concentrations (and, thus, risk) for off-site sediment would not change from now to 30
years from now. For MNA it was assumed that the risk is the same as in the current risk
assessment. Under CIP and Removal there is minimal if any risk into the future. However, to be
conservative it was assumed that the risk under CIP would be 25% of the MNA risk and the risk
under Removal would be 10% of the MNA risk. The projected risk calculations for off-site
sediment are shown in Table 6.
Appendix D — Human Health Risk Analysis D-7 September 30, 2016

0
D6 SURFACE WATER — OFF-SITE
D6.1 Allen and Cliffside
The CAP Part 2 Report for Allen and Cliffside presented surface water mixing models that
estimated the current surface water concentrations based on the current modeled groundwater
concentrations. The estimated future groundwater concentrations presented in Table 3A and 3B
were used as input to the surface water model to estimate surface water concentrations 30 years
from implementation of the three different alternatives. These surface water concentrations were
then multiplied by the RBCs from the risk assessments for each site to estimate the risk of the
different alternatives in the future. A summary of these calculations is presented in Table 7A and
Table 7B for Allen and Cliffside, respectively.
D6.2 Buck
The CAP Part 2 Report for Buck presented a surface water mixing model that estimated the current
surface water concentrations based on the current modeled groundwater concentrations. However,
the analytes that are constituents of potential concern (COPC) for surface water were not included
in the groundwater or surface water model. Thus, the projected risks for the three alternatives in
the future were estimated by applying factors to the current risks presented in the risk assessment.
The results of the surface water model give a ratio of 1.05 for the 30 -year MNA surface water
concentration to the current surface water concentration. Thus, the 30 -year MNA surface water
concentrations for the COPCs were determined by multiplying the current risk value by 1.05. For
the 30 -year CIP and Removal alternatives factors of 0.93 and 0.94 (respectively) were estimated
by dividing the projected surface water concentrations for CIP and Removal by the MNA
concentration. Accordingly, the 30 -year CIP and Removal alternatives for the COPCs were
estimated by multiplying the 30 -year MNA risk by 0.93 and 0.94, respectively. These calculations
are summarized in Table 7C.
D6.3 Mayo
The Mayo CAP Part 2 Report did not include a surface water model. In order to project the risk
for each alternative in the future, the ratios from current year to 2030 for MNA (1.05) and for
MNA to CIP (0.96) or Removal (0.94) were estimated from the surface water models from the
other sites. The results of the projects for Mayo are shown in Table 7D.
Appendix D — Human Health Risk Analysis D-8 September 30, 2016

0
D7 SUMMARY
The combined risks for each alternative where the risk for each medium is summed to determine
the total risk for each receptor is shown in Tables 8A and 8B. This information is further
summarized in Table 9 where the maximum risk for on-site exposure (maximum risk between
commercial/industrial worker, construction worker and trespasser) and maximum risk for off-site
exposure (boater, swimmer and wader) is presented. Following Table 9, graphs depicting the
combined risks for each receptor in each alternative compared to acceptable risk criteria (HI of 1
and 3 and ELCR of lE-5 and 1E-4) are provided.
Appendix D — Human Health Risk Analysis D-9 September 30, 2016

Table 1A. AOW/Seep Soil
1 Concentrations for current scenario updated from the original Risk Assessment (see Table 113)
-- Not Applicable
30 -year MNA: same as current risk assessment
30 -year CIP: 0.25 x 30 -year MNA
30 -year Removal: 0
Appendix D - Human Health Risk Analysis D-10 September 30, 2016
Hazard Index
ELCR
Current Risk
30 -year
30 -year 30 -year
Current Risk
30 -year
30 -year 30 -year
Site
Receptor
Assessment
MNA
CIP Removal
Assessment
MNA
CIP Removal
Allen
Commerical/Industrial Worker
0.095
0.095
0.024 --
3.6E-10
3.6E-10
9.1E-11 --
Construction Worker
0.014
0.014
0.0036 --
7.0E-12
7.0E-12
1.8E-12 --
Trespasser
0.030
0.030
0.0076 --
1.3E-11
1.3E-11
3.3E-12 --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
--
--
--
Buck
Commerical/Industrial Worker
0.19
0.19
0.048 --
2.2E-06
2.2E-06
5.5E-07 --
Construction Worker
0.049
0.049
0.012 --
6.6E-08
6.6E-08
1.7E-08 --
Trespasser
0.062
0.062
0.016 --
2.7E-07
2.7E-07
6.8E-08 --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
--
--
--
Cliffside i
Commerical/Industrial Worker
0.11
0.11
0.03 --
2.3E-06
2.3E-06
5.7E-07 --
Construction Worker
0.04
0.04
0.009 --
7.0E-08
7.0E-08
1.7E-08 --
Trespasser
0.03
0.03
0.009 --
2.9E-07
2.9E-07
7.2E-08 --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
--
--
--
Mayo 1
Commerical/Industrial Worker
0.34
0.34
0.09 --
2.9E-06
2.9E-06
7.3E-07 --
Construction Worker
0.26
0.26
0.064 --
8.9E-08
8.9E-08
2.2E-08 --
Trespasser
0.11
0.11
0.028 --
3.7E-07
3.7E-07
9.2E-08 --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
--
--
--
1 Concentrations for current scenario updated from the original Risk Assessment (see Table 113)
-- Not Applicable
30 -year MNA: same as current risk assessment
30 -year CIP: 0.25 x 30 -year MNA
30 -year Removal: 0
Appendix D - Human Health Risk Analysis D-10 September 30, 2016

Table 1B - Revised AOW/Seep Soil Current Condition Risk Calculations
Cliffside
Receptor Analyte EPC (mg/kg)
HI RBC
ELCR RBC
HI
ELCR
Commerical/Industrial Worker Aluminum 15674 1
1.20E+06
3.00E+02
0.013
2.9E-06
Commerical/Industrial Worker Arsenic 6.88 2
4.80E+02
3.00E+02
0.014
2.3E-06
Commerical/Industrial Worker Cobalt 22.24 2
3.50E+02
8.30E+06
0.064
2.7E-10
Commerical/Industrial Worker Manganese 1447 1
1.60E+05
0.0090
Commerical/Industrial Worker Vanadium 39.87 1
5.80E+03
0.0069
2.9E-06
Total
6.40E+02
4.40E+03
1.00E+06
9.90E+03
4.30E+08
0.11
2.3E-06
Construction Worker Aluminum 15674 1
1.50E+06
6.40E+02
9.90E+03
0.010
0.011
6.9E-08
Construction Worker Arsenic 6.88 2
Construction Worker Cobalt 22.24 2
4.40E+03
4.30E+08
0.0051
5.2E-12
Construction Worker Manganese 1447 1
2.00E+05
Trespasser Arsenic 8.8 2
0.0072
2.40E+03
Construction Worker Vanadium 39.87 1
1.50E+04
Trespasser Cobalt 112
0.0027
2.30E+08
Total
4.8E-12
Trespasser Iron 209217 1
0.036
7.0E-08
Trespasser Aluminum 156741
3.60E+06
Trespasser Manganese 60661
0.0044
1 5.00E+05
Trespasser Arsenic 6.88 2
1.50E+03
2.40E+03
0.0046
2.9E-07
Trespasser Cobalt 22.24 2
1.10E+03
2.30E+08
0.020
9.7E-12
Trespasser Manganese 14471
5.00E+05
0.0029
Trespasser Vanadium 39.871
1 1.80E+04
0.0022
Total
1 0.034
2.9E-07
Mayo
Receptor Analyte EPC (mg/kg)
HI RBC
ELCR RBC
HI
ELCR
Commerical/Industrial Worker Arsenic 8.8 2
4.80E+02
3.00E+02
0.018
2.9E-06
Commerical/Industrial Worker Cobalt 11 2
1.3E-10
3.50E+02
8.30E+06
0.031
Commerical/Industrial Worker Iron 209217 1
8.20E+05
0.26
Commerical/Industrial Worker Manganese 6066 1
1.60E+05
0.038
Total
0.34
2.9E-06
Construction Worker Arsenic 8.8 2
6.40E+02
4.40E+03
1.00E+06
9.90E+03
4.30E+08
0.014
8.9E-08
2.6E-12
Construction Worker Cobalt 11 2
0.0025
0.21
Construction Worker Iron 209217 1
Construction Worker Manganese 6066 1
2.00E+05
_
0.030
Total
0.26
8.9E-08
Trespasser Arsenic 8.8 2
1.54E+03
2.40E+03
0.0057
3.7E-07
Trespasser Cobalt 112
1.10E+03
2.30E+08
0.010
4.8E-12
Trespasser Iron 209217 1
2.50E+06
0.084
Trespasser Manganese 60661
1 5.00E+05
0.012
Total
0.11
3.7E-07
Original EPC from risk assessment
Revised EPC. Cliffside: with statistical outliers removed from dataset.
Mayo: with additional data added to the dataset from perimeter soil samples and ash basin ash
3 EPC / HI RBC
4 EPC / ELCR RBC x 1E-04
EPC: Exposure Point Concentration
RBC: Risk-based Concentration from Risk Assessment
Appendix D - Human Health Risk Analysis D-11 September 30, 2016

Table 2. AOW/Seep Water
-- Not Applicable
30 -year MNA: same as current risk assessment
30 -year CIP: 0.25 x 30 -year MNA
30 -year Removal: 0
Appendix D - Human Health Risk Analysis D-12 September 30, 2016
Hazard Index
ELCR
Current Risk
30 -year
30 -year 30 -year
Current Risk
30 -year
30 -year 30 -year
Site
Assessment
MNA
CIP Removal
Assessment
MNA
CIP Removal
Allen
Commerical/Industrial Worker
0.00025
0.00025
0.000062 --
2.1E-09
2.1E-09
5.4E-10 --
Construction Worker
--
--
-- --
--
--
-- --
Trespasser
0.011
0.011
0.0028 --
5.3E-08
5.3E-08
1.3E-08 --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
--
--
--
Buck
Commerical/Industrial Worker
0.0021
0.0021
0.00053 --
2.4E-08
2.4E-08
6.0E-09 --
Construction Worker
--
--
-- --
--
--
-- --
Trespasser
0.13
0.13
0.033 --
6.4E-07
6.4E-07
1.6E-07 --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
--
--
--
Cliffside
Commerical/Industrial Worker
0.0036
0.0036
0.00090 --
7.5E-08
7.5E-08
1.9E-08 --
Construction Worker
--
--
-- --
--
--
-- --
Trespasser
0.12
0.12
0.031 --
2.1E-06
2.1E-06
5.3E-07 --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
--
--
--
Mayo
Commerical/Industrial Worker
0.000020
0.000020
0.0000050 --
--
--
-- --
Construction Worker
0.00000060
0.00000060
0.00000015 --
--
--
-- --
Trespasser
0.0000020
0.0000020
0.00000050 --
--
--
-- --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
I --
--
--
-- Not Applicable
30 -year MNA: same as current risk assessment
30 -year CIP: 0.25 x 30 -year MNA
30 -year Removal: 0
Appendix D - Human Health Risk Analysis D-12 September 30, 2016

Table 3A. Cliffside Groundwater Risk
1 Not included in groundwater model. Concentrations estimated based on ratio of modeled analytes to current concentrations used in risk assessment.
2 Average of modeled concentrations from wells included in the model (which were all at the compliance boundary)
3 Modeled groundwater concentration / HI RBC
4 Modeled groundwater concentration / ELCR RBC x 1E-04
RBC: Risk-based concentration from risk assessement
Appendix D - Human Health Risk Analysis D-13 September 30, 2016
Const Wkr
Const Wkr
30 Year Modeled Groundwater Z
30 Year Estimated HI 3
30 Year Estimated ELCR 4
Analyte
HI RBC
ELCR RBC
MNA
CIP
Removal
MNA
CIP
Removal
MNA CIP Removal
Vg/L
µg/L
µg/L
Aluminum 1
96000000
27163
27138
26743
0.00028
0.00028
0.00028
Antimony
17000
5.0
5.0
4.9
0.00029
0.00029
0.00029
Arsenic
29000
450000
11
10
10
0.00037
0.00036
0.00036
2.4E-09 2.3E-09 2.3E-09
Barium
5000000
94
74
76
0.000019
0.000015
0.000015
Beryllium
480000
1.1
1.0
1.0
0.0000023
0.0000022
0.0000022
Boron
19000000
307
257
212
0.000016
0.000014
0.000011
Chromium (total)
8600000
10
10
10
0.0000011
0.0000011
0.0000011
Chromium VI
28000
76000
1.4
1.4
1.4
0.000050
0.000051
0.000051
1.9E-09 1.9E-09 1.9E-09
Cobalt
330000
22
20
20
0.000066
0.000062
0.000061
Manganese 1
2200000
9681
9672
9531
0.0044
0.0044
0.0043
Mercury 1
50000
0.5
0.5
0.5
0.000010
0.000010
0.000010
Molybdenum 1
480000
91
91
89
0.00019
0.00019
0.00019
Nickel
1000000
14
12
12
0.000014
0.000012
0.000012
Strontium 1
190000000
7723
7715
7603
0.000041
0.000041
0.000040
Vanadium
960000
5.2
5.0
5.0
0.000005
0.000005
0.000005
Zinc 1
31000000
153
153
151
0.0000050
0.0000049
0.0000049
Total for Construction Worker
0.0058
0.0057
0.0057
4.2E-09 4.2E-09 4.2E-09
1 Not included in groundwater model. Concentrations estimated based on ratio of modeled analytes to current concentrations used in risk assessment.
2 Average of modeled concentrations from wells included in the model (which were all at the compliance boundary)
3 Modeled groundwater concentration / HI RBC
4 Modeled groundwater concentration / ELCR RBC x 1E-04
RBC: Risk-based concentration from risk assessement
Appendix D - Human Health Risk Analysis D-13 September 30, 2016

Table 313. Allen Groundwater Risk
1 Not included in groundwater model. Concentrations estimated based on ratio of modeled analytes to current concentrations used in risk assessment.
2 Average of modeled concentrations from wells included in the model (which were all at the compliance boundary)
3 Modeled groundwater concentration / HI RBC
4 Modeled groundwater concentration / ELCR RBC x 1E-04
RBC: Risk-based concentration from risk assessement
Appendix D - Human Health Risk Analysis D-14 September 30, 2016
Const Wkr Const Wkr
30 Year Modeled Groundwater Z
30 Year Estimated HI 3
30 Year Estimated ELCR 4
Analyte
HI RBC ELCR RBC
MNA
CIP
Removal
MNA
CIP
Removal
MNA CIP Removal
Vg/L
µg/L
µg/L
Aluminum
1
96000000
8128
7146
2735
0.000085
0.000074
0.000028
Antimony
17000
1.3
1.0
0.4
0.000075
0.000056
0.000022
Arsenic
29000 450000
4
4
1
0.00015
0.00013
0.000022
9.9E-10 8.2E-10 1.4E-10
Barium
5000000
191
173
59
0.000038
0.000035
0.000012
Beryllium
1
480000
4.0
3.6
1.4
0.0000084
0.0000074
0.0000028
Boron
19000000
438
370
0
0.000023
0.000019
0.0
Chromium (total)
8600000
10
11
0
0.0000012
0.0000013
0.0
Cobalt
330000
11.5
10.4
2.5
0.000035
0.000031
0.0000077
Manganese
1
2200000
9355
8224
3147
0.0043
0.0037
0.0014
Mercury
1
50000
253
222
85
0.0051
0.0044
0.0017
Molybdenum
1
480000
46.1
40.6
15.5
0.000096
0.000085
0.000032
Nickel
1
1000000
1222
1074
411
0.00122
0.00107
0.00041
Selenium
480000
1
1
0
0.0000016
0.0000015
0.00000044
Vanadium
960000
23.1
22.9
14.8
0.000024
0.000024
0.000015
Zinc
1
31000000
50
44
17
0.0000016
0.0000014
0.00000054
Total for Construction Worker
0.0111
0.0097
0.0037
9.9E-10 8.2E-10 1.4E-10
1 Not included in groundwater model. Concentrations estimated based on ratio of modeled analytes to current concentrations used in risk assessment.
2 Average of modeled concentrations from wells included in the model (which were all at the compliance boundary)
3 Modeled groundwater concentration / HI RBC
4 Modeled groundwater concentration / ELCR RBC x 1E-04
RBC: Risk-based concentration from risk assessement
Appendix D - Human Health Risk Analysis D-14 September 30, 2016

Table 3C. Buck Groundwater Risk
1 30 -year MNA = Current Risk Assessment x 1.5
2 30 -year Cap = 30 -year MNA x 0.5
2 30 -year Cap = 30 -year MNA x 0.6
Table 3D. Mayo Groundwater Risk
Hazard Index
ELCR
Current Risk 30 -year 30 -year 30 -year
Current Risk 30 -year 30 -year 30 -year
Receptor
Assessment MNA1 CIP2 Removal3
Assessment MNA1 CIP2 Removal3
Construction Worker
0.0007 0.0011 0.0005 0.00063
7.0E-09 1.1E-08 5.3E-09 6.3E-09
1 30 -year MNA = Current Risk Assessment x 1.5
2 30 -year Cap = 30 -year MNA x 0.5
2 30 -year Cap = 30 -year MNA x 0.6
Table 3D. Mayo Groundwater Risk
1 30 -year MNA = Current Risk Assessment x 1.5
2 30 -year CIP = 30 -year MNA x 0.25
2 30 -year CIP = 30 -year MNA x 0.1
-- Not applicable
Appendix D - Human Health Risk Analysis D-15 September 30, 2016
Hazard Index
ELCR
Current Risk 30 -year 30 -year 30 -year
Current Risk 30 -year 30 -year 30 -year
Receptor
Assessment MNA1 CIP2 Removal3
Assessment MNA1 CIP2 Removal3
Construction Worker
1.00E-03 0.0015 0.0004 0.00015
-- -- -- --
1 30 -year MNA = Current Risk Assessment x 1.5
2 30 -year CIP = 30 -year MNA x 0.25
2 30 -year CIP = 30 -year MNA x 0.1
-- Not applicable
Appendix D - Human Health Risk Analysis D-15 September 30, 2016

Table 4. On -Site Sediment
-- Not Applicable
30 -year MNA: same as current risk assessment
30 -year CIP: 0.25 x 30 -year MNA
30 -year Removal: 0
Appendix D - Human Health Risk Analysis D-16 September 30, 2016
Hazard Index
ELCR
Current Risk
30 -year
30 -year 30 -year
Current Risk
30 -year
30 -year 30 -year
Site
Receptor
Assessment
MNA
CIP Removal
Assessment
MNA
CIP Removal
Allen
Commerical/Industrial Worker
0.000043
0.000043
0.000011 --
--
--
-- --
Construction Worker
--
--
-- --
--
--
-- --
Trespasser
0.00059
0.00059
0.00015 --
--
--
-- --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
--
--
--
Buck
Commerical/Industrial Worker
0.00031
0.00031
0.000078 --
2.6E-09
2.6E-09
6.5E-10 --
Construction Worker
--
--
-- --
--
--
-- --
Trespasser
0.0044
0.0044
0.0011 --
2.5E-08
0.000000025
0.0000 --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
--
--
--
Cliffside
Commerical/Industrial Worker
0.000091
0.000091
0.000023 --
9.1E-09
9.1E-09
2.3E-09 --
Construction Worker
--
--
-- --
--
Trespasser
0.0018
0.0018
0.0005 --
8.7E-08
8.73684E-08
0.0000 --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
--
--
--
Mayo
Commerical/Industrial Worker
0.00050
0.00050
0.00013 --
2.0E-08
2.0E-08
5.0E-09 --
Construction Worker
--
--
-- --
--
Trespasser
0.0080
0.0080
0.0020 --
1.0E-07
0.0000001
0.0000 --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
I--
--
--
-- Not Applicable
30 -year MNA: same as current risk assessment
30 -year CIP: 0.25 x 30 -year MNA
30 -year Removal: 0
Appendix D - Human Health Risk Analysis D-16 September 30, 2016

Table 5. On -Site Surface Water
-- Not Applicable
30 -year MNA: same as current risk assessment
30 -year CIP: 0.25 x 30 -year MNA
30 -year Removal: 0
Appendix D - Human Health Risk Analysis D-17 September 30, 2016
Hazard Index
ELCR
Current Risk
30 -year
30 -year 30 -year
Current Risk 30 -year 30 -year 30 -year
Site
Receptor
Assessment
MNA
CIP Removal
Assessment MNA CIP Removal
Allen
Commerical/Industrial Worker
0.00015
0.00015
0.000036 --
-- -- -- --
Construction Worker
--
--
-- --
-- -- -- --
Trespasser
0.0043
0.0043
0.0011 --
-- -- -- --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
--
--
--
Buck
Commerical/Industrial Worker
0.000061
0.000061
0.000015 --
-- -- -- --
Construction Worker
--
--
-- --
-- -- -- --
Trespasser
0.0013
0.0013
0.0003 --
-- -- -- --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
--
--
--
Cliffside
Commerical/Industrial Worker
0.000017
0.000017
0.000004 --
-- -- -- --
Construction Worker
--
--
-- --
-- -- -- --
Trespasser
0.00037
0.00037
0.00009 --
-- -- -- --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
--
--
--
Mayo
Commerical/Industrial Worker
0.00070
0.00070
0.00018 --
-- -- -- --
Construction Worker
--
--
-- --
--
Trespasser
0.020
0.020
0.0050 --
-- -- -- --
Boater
--
--
--
Swimmer
--
--
-- --
--
Wader
I--
--
--
-- Not Applicable
30 -year MNA: same as current risk assessment
30 -year CIP: 0.25 x 30 -year MNA
30 -year Removal: 0
Appendix D - Human Health Risk Analysis D-17 September 30, 2016

Table 6. Off -Site Sediment
-- Not Applicable
30 -year MNA: same as current risk assessment
30 -year CIP: 0.25 x 30 -year MNA
30 -year Removal: 0
Appendix D - Human Health Risk Analysis D-18 September 30, 2016
Hazard Index
ELCR
Current Risk
30 -year
30 -year
30 -year
Current Risk
30 -year
30 -year
30 -year
Site
Receptor
Assessment
MNA
CIP
Removal
Assessment
MNA
CIP
Removal
Allen
Commerical/Industrial Worker
--
--
--
--
--
--
--
--
Construction Worker
--
--
--
--
--
Trespasser
--
--
--
--
--
Boater
0.00017
0.00017
0.000042
1.7E-05
--
--
--
--
Swimmer
0.0018
0.00176
0.00044
1.8E-04
--
--
--
--
Wader
0.0018
0.0018
0.00044
1.8E-04
--
--
--
--
Buck
Commerical/Industrial Worker
--
--
--
--
--
--
--
--
Construction Worker
--
--
--
--
--
Trespasser
--
--
--
--
--
Boater
0.0014
0.0014
0.00035
1.4E-04
1.6E-08
0.000000016
0.0000
1.6E-09
Swimmer
0.013
0.013
0.0033
1.3E-03
1.7E-07
1.7E-07
4.3E-08
1.7E-08
Wader
0.013
0.013
0.0033
1.3E-03
6.6E-08
6.6E-08
1.7E-08
6.6E-09
Cliffside
Commerical/Industrial Worker
--
--
--
--
--
--
--
--
Construction Worker
--
--
--
--
--
Trespasser
--
--
--
--
--
Boater
0.0010
0.0010
0.0003
1.0E-04
5.5E-08
5.53333E-08
0.0000
5.5E-09
Swimmer
0.0070
0.0070
0.0017
7.0E-04
5.9E-07
5.9E-07
1.5E-07
5.9E-08
Wader
0.0040
0.0040
0.0010
4.0E-04
2.3E-07
2.3E-07
5.8E-08
2.3E-08
Mayo
Commerical/Industrial Worker
--
--
--
--
--
--
--
--
Construction Worker
--
--
--
--
--
Trespasser
--
--
--
--
--
Boater
0.00030
0.00030
0.000075
3.0E-05
--
--
--
--
Swimmer
0.0030
0.0030
0.00075
3.0E-04
--
--
--
--
Wader
0.0030
0.0030
0.00075
3.0E-04
--
--
--
--
-- Not Applicable
30 -year MNA: same as current risk assessment
30 -year CIP: 0.25 x 30 -year MNA
30 -year Removal: 0
Appendix D - Human Health Risk Analysis D-18 September 30, 2016

Table 7A. Off -Site Surface Water: Allen
1 Not included in surface water model. Cr,,,, based on 1/2 of typical detection limits.
C,w = (QGWXCGW + QriverXCriver) / Aw + Qriver)
QGW (cfs) 0.64
Qriver(cfs) 137.0882
Model CGW from Table 36
Receptor
Analyte
2046 MNA
30 Year Surface Water
2046
CIP
2046 Removal
MNA CIP Removal
Analyte
Criver
Model CSW
CSW Chronic
Model CSW
CSW Chronic
Model CSW
CSW Chronic
1.0E-06
7.1E-06
(99A)
(99A)
(µ9/L)
(99A)
(µg/L)
(µg/L)
(99A)
Aluminum
251
8128
63
7146
58
2735
38
Cobalt
0.25
1 12
0.30
10
0.30
2.5
0.26
Manganese
5 1
9355
48
8224
43
3147
20
Zinc
0.0051
1 50
0.24
17
0.083
44 0.21
1 Not included in surface water model. Cr,,,, based on 1/2 of typical detection limits.
C,w = (QGWXCGW + QriverXCriver) / Aw + Qriver)
QGW (cfs) 0.64
Qriver(cfs) 137.0882
Model CGW from Table 36
Receptor
Analyte
HI RBC ELCR RBC
30 Year Surface Water
30 Year Estimated HI 1
30 Year Estimated ELCR 2
MNA CIP Removal
µg/L µg/L µg/L
MNA CIP Removal
MNA CIP Removal
Boater
Boater
Boater
Aluminum
Cobalt
Manganese
5.6E+07 -
4.2E+04 -
63
0.30
48
58
0
43
38
0
20
1.1E-06
7.2E-06
1.0E-06
7.1E-06
6.7E-07
6.2E-06
-- -- --
-- -- --
-- -- --
-- -- --
3.1E+05 --
1.6E-04 1.4E-04
6.3E-05
Boater Zinc
2.8E+07 --
0.24 0 0
8.5E-09 7.5E-09
3.0E-09
Total
1.6E-04
1.5E-04
7.0E-05
-- -- --
Swimmer
Swimmer
Swimmer
Swimmer
Aluminum
Cobalt
Manganese
Zinc
1.1E+06 --
63
58
38
5.7E-05
8.6E-04
5.3E-05
8.5E-04
3.4E-05
7.4E-04
-- -- --
-- -- --
-- -- --
-- -- --
3.5E+02 --
0.30 0 0
4.1E+04 --
48 43 20
1.2E-03 1.1E-03
7.0E-07 6.2E-07
4.8E-04
2.5E-07
3.4E+05 --
0.24 0 0
Total
2.1E-03
2.0E-03
1.3E-03
-- -- --
Wader
Aluminum
1.2E+06 --
63
58
38
5.2E-05
4.8E-05
3.1E-05
-- -- --
Wader
Cobalt
3.6E+02 --
0.30
0
0
8.4E-04
8.2E-04
7.2E-04
-- -- --
Wader
Manganese
9.0E+04 --
48
43
20
5.4E-04
4.8E-04
2.2E-04
-- -- --
Wader
Zinc
3.6E+05 --
0.24
0
01
6.6E-07
5.8E-07
2.3E-07
-- -- --
Total
I
I 1.4E-03
1.4E-03
9.7E-04
-- -- --
1 Modeled surface water concentration / HI RBC
2 Modeled surface water concentration / ELCR RBC x 1E-04
RBC: Risk-based concentration from risk assessement
Appendix D - Human Health Risk Analysis D-19 September 30, 2016

Table 713. Off -Site Surface Water: Cliffside
Analyte
Criver
2046 MNA
2046 CIP
2046 Removal
Model Caw CSW Chronic
Model CSW CSW Chronic
Model Caw CSW Chronic
MNA CIP Removal
(99A)
(99A)
(µg/L)
(99A)
(µg/L)
(µg/L)
(99A)
Aluminum
251
27163
1678
27138
1676
26743
1652
Manganese
5 1
_
9681
594
9672
594
9531
585
Zinc
0.0051
153
9.35
153
9.34
151
9.20
1 Not included in surface water model. Criver based on 1/2 of typical detection limits.
These calculations are for Suck Creek, which is more sensitive than the Broad River.
Csw = (QGWXCGW + QriverXCriver) / (Qgw + Qriver)
QGW (cfs) 0.14
Qf1Vef (cfs) 2.159
Model CGW from Table 3B
Receptor
Analyte
HI RBC ELCR RBC
30 Year Surface Water
30 Year Estimated HI 1
30 Year Estimated ELCR 2
MNA CIP Removal
µg/L µg/L µg/L
MNA CIP Removal
MNA CIP Removal
Boater
Boater
Boater
Aluminum
Manganese
Zinc
5.6E+07 -
3.1E+05 -
2.8E+07 -
1678
594
9.35
1676
594
9
1652
585
9
3.0E-05
1.9E-03
3.3E-07
3.0E-05
1.9E-03
3.3E-07
3.0E-05
1.9E-03
3.3E-07
-- -- --
-- -- --
-- -- --
Total
1.9E-03
1.9E-03
1.9E-03
-- -- --
Swimmer
Swimmer
Swimmer
Aluminum
Manganese
Zinc
1.1E+06 -
4.1E+04 --
1678
594
9.35
1676
594
9
1652
585
9
1.5E-03
1.4E-02
2.7E-05
1.5E-03
1.4E-02
2.7E-05
1.5E-03
1.4E-02
2.7E-05
-- -- --
-- -- --
-- -- --
3.4E+05 --
Total
1.6E-02
1.6E-02
1.6E-02
-- -- --
Wader
Wader
Wader
Aluminum
Manganese_
Zinc
1.2E+06 --
1678
594
9.35
1676
594
9
1652
585
9
1.4E-03
6.6E-03
2.6E-05
1.4E-03
6.6E-03
2.6E-05
1.4E-03
6.5E-03
2.6E-05
-- -- --
-- -- --
9.0E+04 --
3.6E+05 --
-- -- --
Total
I
8.0E-03
8.0E-03
7.9E-03
-- -- --
1 Modeled surface water concentration / HI RBC
2 Modeled surface water concentration / ELCR RBC x 1E-04
RBC: Risk-based concentration from risk assessement
Appendix D - Human Health Risk Analysis D-20 September 30, 2016

Table 7C. Off -Site Surface Water: Buck
1 30 -year MNA = Current Risk Assessment x 1.05
2 30 -year CIP = 30 -year MNA x 0.93
2 30 -year CIP = 30 -year MNA x 0.94
Factors were determined by projecting the results of the surface water model into the future for each scenario for the analytes used in the surface water model,
which were not the COPCs for surface water.
Table 7D. Off -Site Surface Water: Mayo
Hazard Index
ELCR
Current Risk 30 -year 30 -year 30 -year
Current Risk 30 -year 30 -year 30 -year
Receptor
Assessment MNA1 CIPZ Removal3
Assessment MNA1 CIPZ Removal3
Boater
0.00099 0.0010 0.0010 0.00098
-- -- -- --
Swimmer
0.0077 0.0081 0.0075 0.0076
-- -- -- --
Wader
0.0035 0.0037 0.0034 0.0035
-- -- -- --
1 30 -year MNA = Current Risk Assessment x 1.05
2 30 -year CIP = 30 -year MNA x 0.93
2 30 -year CIP = 30 -year MNA x 0.94
Factors were determined by projecting the results of the surface water model into the future for each scenario for the analytes used in the surface water model,
which were not the COPCs for surface water.
Table 7D. Off -Site Surface Water: Mayo
1 30 -year MNA = Current Risk Assessment x 1.05
2 30 -year CIP = 30 -year MNA x 0.96
2 30 -year CIP = 30 -year MNA x 0.94
Factors were determined by projecting the results of the surface water model into the future for each scenario for the analytes used in the surface water model,
Appendix D - Human Health Risk Analysis D-21 September 30, 2016
Hazard Index
ELCR
Current Risk 30 -year 30 -year 30 -year
Current Risk 30 -year 30 -year 30 -year
Receptor
Assessment MNA1 CIPZ Removal3
Assessment MNA1 CIPZ Removal3
Boater
0.02 0.021 0.020 0.020
-- -- -- --
Swimmer
0.2 0.21 0.20 0.20
-- -- -- --
Wader
0.1 0.11 0.10 0.10
-- -- -- --
1 30 -year MNA = Current Risk Assessment x 1.05
2 30 -year CIP = 30 -year MNA x 0.96
2 30 -year CIP = 30 -year MNA x 0.94
Factors were determined by projecting the results of the surface water model into the future for each scenario for the analytes used in the surface water model,
Appendix D - Human Health Risk Analysis D-21 September 30, 2016

Table 8A. Total Hazard Index for Each Receptor and Scenario
Appendix D - Human Health Risk Analysis D-22 September 30, 2016
30 -Year Removal - HI
30 -Year MNA - HI
AOW
AOW Groundwater On -Site On -Site
Off -Site
AOW
AOW
Groundwater
On -Site
On -Site
Off -Site
Off -Site
Total
Site
Receptor
Soil
Water
-- -- -- --
Sediment
Surface Water
Sediment
Surface Water
HI
Allen
Commerical/Industrial Wkr
9.5E-02
2.5E-04
--
4.3E-05
1.5E-04
--
--
9.6E-02
--
Construction Worker
1.4E-02
--
1.1E-02
--
--
--
--
2.5E-02
Swimmer
Trespasser
3.0E-02
1.1E-02
--
5.9E-04
4.3E-03
--
--
4.6E-02
1.8E-04
Boater
--
--
--
--
--
1.7E-04
1.6E-04
3.3E-04
Swimmer
--
--
--
--
--
1.8E-03
2.1E-03
3.9E-03
-- -- -- --
Wader
--
--
--
--
--
1.8E-03
1.4E-03
3.2E-03
Buck
Commerical/Industrial Wkr
1.9E-01
2.1E-03
--
3.1E-04
6.1E-05
--
--
1.9E-01
--
Construction Worker
4.9E-02
--
1.1E-03
--
-
--
--
5.0E-02
0.0E+00
Trespasser
6.2E-02
1.3E-01
--
4.4E-03
1.3E-03
--
--
2.0E-01
--
Boater
--
-
--
--
--
1.4E-03
1.0E-03
2.4E-03
1.9E-03
Swimmer
--
--
--
--
--
1.3E-02
8.1E-03
2.1E-02
Wader
Wader
--
--
--
--
-
1.3E-02
3.7E-03
1.7E-02
Cliffside Commerical/Industrial Wkr
1.1E-01
3.6E-03
--
9.1E-05
1.7E-05
--
--
1.1E-01
1.5E-04
Construction Worker
3.6E-02
--
5.8E-03
--
--
--
--
4.2E-02
--
Trespasser
3.4E-02
1.2E-01
--
1.8E-03
3.7E-04
--
--
1.6E-01
2.0E-01
Boater
--
--
--
--
-
1.0E-03
1.9E-03
2.9E-03
Swimmer
--
--
--
--
--
7.0E-03
1.6E-02
2.3E-02
Wader
--
--
--
--
-
4.0E-03
8.0E-03
1.2E-02
Mayo
Commerical/Industrial Wkr
3.4E-01
2.0E-05
--
5.0E-04
7.0E-04
--
--
3.4E-01
Construction Worker
2.6E-01
6.0E-07
1.5E-03
--
--
--
--
2.6E-01
Trespasser
1.1E-01
2.0E-06
--
8.0E-03
2.0E-02
-
--
1.4E-01
Boater
--
--
--
--
--
3.0E-04
2.1E-02
2.1E-02
Swimmer
--
--
--
--
--
3.0E-03
2.1E-01
2.1E-01
Wader
--
--
--
--
--
3.0E-03
1.1E-01
1.1E-01
Appendix D - Human Health Risk Analysis D-22 September 30, 2016
30 -Year Removal - HI
30 -Year CIP- HI
AOW
AOW Groundwater On -Site On -Site
Off -Site
AOW
AOW
Groundwater
On -Site
On -Site
Off -Site
Off -Site
Total
Site
Receptor
Soil
Water
-- -- -- --
Sediment
Surface Water
Sediment
Surface Water
HI
Allen
Commerical/Industrial Wkr
2.4E-02
6.2E-05
--
1.1E-05
3.6E-05
--
-
2.4E-02
--
Construction Worker
3.6E-03
--
9.7E-03
--
-
--
--
1.3E-02
Swimmer
Trespasser
7.6E-03
2.8E-03
--
1.5E-04
1.1E-03
--
--
1.2E-02
1.8E-04
Boater
--
--
--
--
-
4.2E-05
1.5E-04
1.9E-04
Swimmer
--
--
--
--
--
4.4E-04
2.0E-03
2.4E-03
-- -- -- --
Wader
--
--
--
--
--
4.4E-04
1.4E-03
1.8E-03
Buck
Commerical/Industrial Wkr
4.8E-02
5.3E-04
--
7.8E-05
1.5E-05
--
--
4.8E-02
--
Construction Worker
1.2E-02
--
5.3E-04
--
--
--
--
1.3E-02
0.0E+00
Trespasser
1.6E-02
3.3E-02
--
1.1E-03
3.3E-04
--
--
4.9E-02
--
Boater
--
--
--
--
--
3.5E-04
9.7E-04
1.3E-03
1.9E-03
Swimmer
--
-
--
--
--
3.3E-03
7.5E-03
1.1E-02
Wader
Wader
--
--
--
--
--
3.3E-03
3.4E-03
6.7E-03
Cliffside Commerical/Industrial Wkr
2.7E-02
9.0E-04
--
2.3E-05
4.3E-06
--
--
2.8E-02
1.5E-04
Construction Worker
9.0E-03
--
5.7E-03--
-
--
--
--
1.5E-02
--
Trespasser
8.6E-03
3.1E-02
--
4.6E-04
9.3E-05
--
--
4.0E-02
2.0E-01
Boater
--
--
--
--
--
2.5E-04
1.9E-03
2.2E-03
Swimmer
--
--
--
--
--
1.7E-03
1.6E-02
1.8E-02
Wader
--
--
--
--
-
1.0E-03
8.0E-03
9.0E-03
Mayo
Commerical/Industrial Wkr
8.6E-02
5.0E-06
--
1.3E-04
1.8E-04
-
--
8.6E-02
Construction Worker
6.4E-02
1.5E-07
3.8E-04
--
--
--
--
6.4E-02
Trespasser
2.8E-02
5.0E-07
--
2.0E-03
5.0E-03
--
--
3.5E-02
Boater
--
--
--
--
--
7.5E-05
2.0E-02
2.0E-02
Swimmer
--
--
--
--
--
7.5E-04
2.0E-01
2.oE-01
Wader
--
--
--
--
--
7.5E-04
1.0E-01
1.0E-01
Appendix D - Human Health Risk Analysis D-22 September 30, 2016
30 -Year Removal - HI
AOW
AOW Groundwater On -Site On -Site
Off -Site
Off -Site
Total
Site
Receptor
Soil
Water Sediment Surface Water
Sediment
Surface Water
HI
Allen
Commerical/Industrial Wkr
--
-- -- -- --
--
--
0.0E+00
Construction Worker
--
-- 3.7E-03 -- --
--
--
3.7E-03
Trespasser
--
-- -- -- --
--
--
0.0E+00
Boater
--
-- -- -- --
1.7E-05
7.0E-05
8.7E-05
Swimmer
--
-- -- -- --
1.8E-04
1.3E-03
1.4E-03
Wader
--
-- -- -- --
1.8E-04
9.7E-04
1.1E-03
Buck
Commerical/Industrial Wkr
--
-- -- -- --
--
--
0.0E+00
Construction Worker
--
-- 6.3E-04 -- --
--
--
6.3E-04
Trespasser
--
-- -- -- --
--
--
0.0E+00
Boater
--
-- - -- -
1.4E-04
9.8E-04
1.1E-03
Swimmer
-
-- -- -- --
1.3E-03
7.6E-03
8.9E-03
Wader
--
-- -- -- --
1.3E-03
3.5E-03
4.8E-03
Cliffside Commerical/Industrial Wkr
-
-- -- -- --
--
--
0.0E+00
Construction Worker
--
-- 5.7E-03 -- --
--
--
5.7E-03
Trespasser
--
-- -- -- -
--
--
O.0E+00
Boater
--
-- -- -- --
1.0E-04
1.9E-03
2.0E-03
Swimmer
--
-- -- -- --
7.0E-04
1.6E-02
1.6E-02
Wader
--
-- -- -- -
4.0E-04
7.9E-03
8.3E-03
Mayo
Commerical/Industrial Wkr
--
-- -- -- --
--
--
0.0E+00
Construction Worker
--
- 1.5E-04 -- --
--
--
1.5E-04
Trespasser
--
-- -- -- --
-
--
0.0E+00
Boater
--
-- -- -- --
3.0E-05
2.0E-02
2.0E-02
Swimmer
--
-- -- -- --
3.0E-04
2.0E-01
2.0E-01
Wader
--
-- -- -- --
3.0E-04
9.9E-02
9.9E-02
Appendix D - Human Health Risk Analysis D-22 September 30, 2016

Table 813. Total ELCR for Each Receptor and Scenario
Appendix D - Human Health Risk Analysis D-23 September 30, 2016
30-Year Removal - ELCR
30 -Year MNA - ELCR
AOW
AOW
AOW
Groundwater On -Site On -Site
Off -Site Off -Site
Site
Total
Site
Receptor
Soil
Water
Sediment Surface Water
Sediment Surface Water
ELCR
Allen
Commerical/Industrial Wkr
3.6E-10
2.1E-09
-- -- --
-- --
2.5E-09
-- --
Construction Worker
7.0E-12
--
9.9E-10 -- --
-- --
1.0E-09
Trespasser
1.3E-11
5.3E-08
-- -- --
-- --
5.3E-08
Boater
--
--
--
Wader
Swimmer
--
--
--
Buck
Commerical/Industrial Wkr
--
Wader
--
--
--
Construction Worker
--
Buck
Commerical/Industrial Wkr
2.2E-06
2.4E-08
-- 2.6E-09 --
-- --
2.2E-06
Construction Worker
6.6E-08
--
1.1E-08 -- --
-- --
7.7E-08
1.6E-09
Trespasser
2.7E-07
6.4E-07
-- 2.5E-08 --
-- --
9.4E-07
Boater
--
--
-- -- --
1.6E-08 --
1.6E-08
Commerical/Industrial Wkr
Swimmer
--
--
-- -- --
1.7E-07 --
1.7E-07
--
Wader
--
--
-- -- --
6.6E-08 --
6.6E-08
Cliffside
Commerical/Industrial Wkr
2.3E-06
7.5E-08
-- 9.1E-09 --
-- --
2.4E-06
5.5E-09 --
Construction Worker
7.0E-08
--
4.2E-09 -- --
-- --
7.4E-08
5.9E-08
Trespasser
2.9E-07
2.1E-06
-- 8.7E-08 --
-- --
2.5E-06
Mayo
Boater
--
--
-- -- --
5.5E-08 --
5.5E-08
Construction Worker
Swimmer
--
--
-- -- --
5.9E-07 --
5.9E-07
--
Wader
--
--
-- -- --
2.3E-07 --
2.3E-07
Mayo
Commerical/Industrial Wkr
2.9E-06
--
-- 2.0E-08 --
-- --
3.0E-06
Construction Worker
8.9E-08
--
-- -- --
-- --
8.9E-08
Trespasser
3.7E-07
--
-- 1.0E-07 --
-- --
4.7E-07
Boater
--
--
--
Swimmer
--
--
--
Wader
--
--
--
Appendix D - Human Health Risk Analysis D-23 September 30, 2016
30-Year Removal - ELCR
30-Year CIP - ELCR
AOW
AOW
AOW
Groundwater On -Site On -Site
Off -Site Off -Site
Site
Total
Site
Receptor
Soil
Water
Sediment Surface Water
Sediment Surface Water
ELCR
Allen
Commerical/Industrial Wkr
9.1E-11
5.4E-10
-- -- --
-- --
6.3E-10
-- --
Construction Worker
1.8E-12
--
-- -- --
-- --
1.8E-12
Trespasser
3.3E-12
1.3E-08
8.2E-10 -- --
-- --
1.4E-08
Boater
--
--
Wader
Swimmer
--
--
-- --
Buck
Commerical/Industrial Wkr
--
Wader
--
--
--
Construction Worker
--
Buck
Commerical/Industrial Wkr
5.5E-07
6.0E-09
-- 6.5E-10 --
-- --
5.6E-07
Construction Worker
1.7E-08
--
5.3E-09 -- --
-- --
2.2E-08
1.6E-09
Trespasser
6.8E-08
1.6E-07
-- 6.3E-09 --
-- --
2.3E-07
Boater
--
--
-- -- --
4.0E-09 --
4.0E-09
Commerical/Industrial Wkr
Swimmer
--
--
-- -- --
4.3E-08 --
4.3E-08
--
Wader
--
--
-- -- --
1.7E-08 --
1.7E-08
Cliffside
Commerical/Industrial Wkr
5.7E-07
1.9E-08
-- 2.3E-09 --
-- --
5.9E-07
5.5E-09 --
Construction Worker
1.7E-08
--
4.2E-09 -- --
-- --
2.2E-08
5.9E-08
Trespasser
7.2E-08
5.3E-07
-- 2.2E-08 --
-- --
6.2E-07
Mayo
Boater
--
--
-- -- --
1.4E-08 --
1.4E-08
Construction Worker
Swimmer
--
--
-- -- --
1.5E-07 --
1.5E-07
--
Wader
--
--
-- -- --
5.8E-08 --
5.8E-08
Mayo
Commerical/Industrial Wkr
7.3E-07
--
-- 5.0E-09 --
-- --
7.4E-07
Construction Worker
2.2E-08
--
-- -- --
-- --
2.2E-08
Trespasser
9.2E-08
--
-- 2.5E-08 --
-- --
1.2E-07
Boater
--
--
--
Swimmer
--
--
--
Wader
--
--
--
Appendix D - Human Health Risk Analysis D-23 September 30, 2016
30-Year Removal - ELCR
AOW
AOW Groundwater On -Site On -Site
Off -Site Off -Site
Total
Site
Receptor
Soil
Water Sediment Surface Water
Sediment Surface Water
ELCR
Allen
Commerical/Industrial Wkr
--
-- -- -- --
-- --
--
Construction Worker
--
-- 1.4E-10 -- --
-- --
1.4E-10
Trespasser
--
-- -- --
Boater
--
-- --
Swimmer
--
-- --
Wader
--
-- --
Buck
Commerical/Industrial Wkr
--
-- -- -- --
-- --
--
Construction Worker
--
-- 6.3E-09 -- --
-- --
6.3E-09
Trespasser
--
-- -- --
Boater
--
-- -- -- --
1.6E-09 --
1.6E-09
Swimmer
--
-- -- -- --
1.7E-08 --
1.7E-08
Wader
--
-- -- -- --
6.6E-09 --
6.6E-09
Cliffside
Commerical/Industrial Wkr
--
-- -- -- --
-- --
--
Construction Worker
--
-- 4.2E-09 -- --
-- --
4.2E-09
Trespasser
--
-- -- --
Boater
--
-- -- -- --
5.5E-09 --
5.5E-09
Swimmer
--
-- -- -- --
5.9E-08 --
5.9E-08
Wader
--
-- -- -- --
2.3E-08 --
2.3E-08
Mayo
Commerical/Industrial Wkr
--
-- -- -- --
-- --
--
Construction Worker
--
-- -- -- --
-- --
--
Trespasser
--
-- -- --
Boater
--
-- --
Swimmer
--
-- --
Wader
--
-- --
Appendix D - Human Health Risk Analysis D-23 September 30, 2016

Table 9. Summary of Risks for Each Scenario
Allen
Buck
Hazard Index
ELCR
On -Site Off -Site
On -Site Off -Site
MNA
0.1 0.004
5E-08 --
CIP
0.02 0.002
1E-08 --
Removal
1 0.004 0.001
1E-10 --
Buck
Cliffside
Hazard Index
ELCR
On -Site Off -Site
On -Site Off -Site
MINA
0.2 0.02
2E-06 2E-07
CIP
0.05 0.01
6E-07 4E-08
Removal
10.0006 0.009
6E-09 2E-08
Cliffside
Mayo
Hazard Index
ELCR
On -Site Off -Site
On -Site Off -Site
MINA
0.2 0.02
2E-06 6E-07
CIP
0.04 0.02
6E-07 1E-07
Removal
10.01 0.02
4E-09 6E-08
Mayo
On-Site: Maximum of commercial/industrial worker,
construction worker and trespasser
Off -Site: Maximum of boater, swimmer and wader
Appendix D - Human Health Risk Analysis D-24 September 30, 2016
Hazard Index
ELCR
On -Site Off -Site
On -Site Off -Site
MINA
0.3 0.2
3E-06 --
CIP
0.09 0.2
7E-07 --
Removal
10.0002 0.21
--
On-Site: Maximum of commercial/industrial worker,
construction worker and trespasser
Off -Site: Maximum of boater, swimmer and wader
Appendix D - Human Health Risk Analysis D-24 September 30, 2016

3
2.5
2
1.5
1
0.5
0
3
2.5
2
1.5
1
0.5
0
Allen -HI -30 Yr
MNA CIP Removal
■ Commerical/Industrial Wkr ■ Construction Worker ■ Trespasser Boater ■ Swimmer ■ Wader
Buck - HI - 30 Yr
MNA CIP Removal
■ Commerical/Industrial Wkr ■ Construction Worker ■ Trespasser Boater ■ Swimmer ■ Wader
8.00E-05
6.00E-05
4.00E-05
2.00E-05
0.00E+00
1.00E-04
8.00E-05
6.00E-05
4.00E-05
2.00E-05
0.00E+00
Allen - ELCR - 30 Yr
MNA CIP Removal
■ Commerical/Industrial Wkr ■ Construction Worker ■ Trespasser Boater ■ Swimmer ■ Wader
Buck - ELCR - 30 Yr
MNA CIP Removal
■ Commerical/Industrial Wkr ■ Construction Worker ■ Trespasser Boater ■ Swimmer ■ Wader
Appendix D - Human Health Risk Analysis D-25 September 30, 2016

3
2.5
2
1.5
1
0.5
0
3
2.5
2
1.5
1
0.5
0
Cliffside - HI - 30 Yr
1.00E-04
8.00E-05
6.00E-05
4.00E-05
2.00E-05
0.00E+00
Cliffside - ELCR - 30 Yr
MNA CIP Removal MNA CIP Removal
■ Commerical/Industrial Wkr ■ Construction Worker ■ Trespasser Boater ■ Swimmer ■ Wader ■ Commerical/Industrial Wkr ■ Construction Worker ■ Trespasser Boater ■ Swimmer ■ Wader
Mayo - HI - 30 Yr Mayo - ELCR - 30 Yr
MNA CIP Removal
■ Commerical/Industrial Wkr ■ Construction Worker ■ Trespasser Boater ■ Swimmer ■ Wader
1.00E-04
8.00E-05
6.00E-05
4.00E-05
C411U1:11111..1
1111111:11MII11
MNA CIP Removal
■ Commerical/Industrial Wkr ■ Construction Worker ■ Trespasser Boater ■ Swimmer ■ Wader
Appendix D - Human Health Risk Analysis D-26 September 30, 2016

FTWOVINTIMIM
Updated EPC Calculations
Appendix D - Human Health Risk Analysis D-27 September 30, 2016

Cliffside: Computation of New EPC
Matrix
Location
Sample ID
Constituent
Result
Result Flag for ProLICL
AOW Soil
S-11
S-11 SD 20150629
Arsenic
310.0
1
detect
AOW Soil
S-10
S-10 SD 20150627
Arsenic
250.0
1
detect
AOW Soil
CLFSP051
CLFSP051_SID _20150627
Arsenic
51.4
1
detect
AOW Soil
CLFTD052
CLFTD052_SD_20150627
Arsenic
33.2
1
detect
AOW Soil
CLFTDO04
CLFTDO04_SID _20150627
Arsenic
18.5
1
detect
AOW Soil
S-19
S-19 SD 20150603
Arsenic
10.4
1
detect
AOW Soil
S-3
S-3 SD 20150627
Arsenic
5.0
1
detect
AOW Soil
S-20
S-20 SD 20150627
Arsenic
4.4
1
detect
AOW Soil
S-1
S-1 SD 20150627
Arsenic
16.0
0
non -detect
AOW Soil
S-14
S-14 SD 20150602
Arsenic
15.9
0
non -detect
AOW Soil
S-17
S-17 SD 20150603
Arsenic
15.8
0
non -detect
AOW Soil
CLFSP059
CLFSP059_SD_20150627
Arsenic
14.3
0
non -detect
AOW Soil
S-18
S-18 SD 20150603
Arsenic
13.6
0
non -detect
AOW Soil
S-2
S-2 SD 20150603
Arsenic
13.5
0
non -detect
AOW Soil
S-12
S-12 SD 20150627
Arsenic
12.5
0
non -detect
AOW Soil
CLFSP061
CLFSP061_SD_20150629
Arsenic
10.8
0
non -detect
AOW Soil
CLFTDO05
CLFTD005_SD_20150709
Arsenic
10.3
0
non -detect
AOW Soil
S-15
S-15 SD 20150602
Arsenic
10.3
0
non -detect
AOW Soil
S-4
S-4 SD 20150629
Arsenic
10.3
0
non -detect
AOW Soil
S-5
S-5 SD 20150709
Arsenic
9.5
0
non -detect
AOW Soil
S-2
S-2 SD 20150627
Arsenic
9.2
0
non -detect
AOW Soil
CLFSTR065
CLFSTR065_SD_20150627
Arsenic
9.1
0
non -detect
AOW Soil
CLFSP058
CLFSP058_SD_20150627
Arsenic
8.8
0
non -detect
AOW Soil
S-16
S-16 SD 20150602
Arsenic
8.8
0
non -detect
AOW Soil
S-6
S-6 SD 20150627
Arsenic
8.8
0
non -detect
AOW Soil
S-9
S-9 SD 20150627
Arsenic
8.8
0
non -detect
AOW Soil
S-7
S-7 SD 20150627
Arsenic
7.6
0
non -detect
AOW Soil
S-8
S-8 SD 20150629
Arsenic
6.4
0
non -detect
AOW Soil
S-22
S-22 SD 20150627
Arsenic
6.0
0
non -detect
User Selected Options
Date/Time of Computation
From File
Full Precision
Outlier Tests for Selected Uncensored Variables
6/21/2016 10:05:21 AM
As_Co.xls
OFF
Rosner's Outlier Test for Arsenic
For 5% significance level, there are 4 Potential Outliers
Potential outliers are:
310, 250, 51.4, 33.2
For 1 % Significance Level, there are 4 Potential Outliers
Potential outliers are:
310, 250, 51.4, 33.2
Appendix D - Human Health Risk Analysis D-28 September 30, 2016
Mean
31.35
Standard Deviation
69.94
Number of data
29
Number of suspected outliers
4
Potential
Obs.
Test
Critical
Critical
# Mean
sd
outlier
Number
value
value (5%)
value (1 %)
1 31.35
68.72
310
1
4.055
2.89
3.22
2 21.4
45.76
250
2
4.996
2.88
3.2
3 12.93
9.499
51.4
3
4.049
2.86
3.18
4 11.45
5.69
33.2
4
3.821
2.84
3.16
For 5% significance level, there are 4 Potential Outliers
Potential outliers are:
310, 250, 51.4, 33.2
For 1 % Significance Level, there are 4 Potential Outliers
Potential outliers are:
310, 250, 51.4, 33.2
Appendix D - Human Health Risk Analysis D-28 September 30, 2016

Matrix
Location
Sample ID
Constituent
Result
Result Flag for ProUCL
AOW Soil
CLFTDO04
CLFTD004_SD_20150627
Cobalt
926.0
1
detect
AOW Soil
S-17
S-17 SD 20150603
Cobalt
95.8
1
detect
AOW Soil
S-18
S-18 SD 20150603
Cobalt
88.3
1
detect
AOW Soil
S-2
S-2 SD 20150603
Cobalt
81.6
1
detect
AOW Soil
S-19
S-19 SD 20150603
Cobalt
50.4
1
detect
AOW Soil
S-11
S-11 SD 20150629
Cobalt
45.2
1
detect
AOW Soil
S-2
S-2 SD 20150627
Cobalt
45.0
1
detect
AOW Soil
S-3
S-3 SD 20150627
Cobalt
33.6
1
detect
AOW Soil
CLFTD052
CLFTDO52_SD_20150627
Cobalt
29.0
1
detect
AOW Soil
CLFSP051
CLFSP051_SD_20150627
Cobalt
26.3
1
detect
AOW Soil
S-9
S-9 SD 20150627
Cobalt
26.0
1
detect
AOW Soil
CLFSP061
CLFSP061_SD_20150629
Cobalt
20.3
1
detect
AOW Soil
S-6
S-6 SD 20150627
Cobalt
11.6
1
detect
AOW Soil
S-1
S-1 SD 20150627
Cobalt
11.0
1
detect
AOW Soil
S-20
S-20 SD 20150627
Cobalt
8.4
1
detect
AOW Soil
S-22
S-22 SD 20150627
Cobalt
7.2
1
detect
AOW Soil
S-10
S-10 SD 20150627
Cobalt
6.9
1
detect
AOW Soil
CLFSTR065
CLFSTR065_SD_20150627
Cobalt
6.2
1
detect
AOW Soil
S-5
S-5 SD 20150709
Cobalt
5.6
1
detect
AOW Soil
CLFSP058
CLFSP058_SD_20150627
Cobalt
4.8
1
detect
AOW Soil
S-14
S-14 SD 20150602
Cobalt
15.9
0
non -detect
AOW Soil
CLFSP059
CLFSP059_SD_20150627
Cobalt
14.3
0
non -detect
AOW Soil
S-12
S-12 SD 20150627
Cobalt
12.5
0
non -detect
AOW Soil
CLFTDO05
CLFTD005_SD_20150709
Cobalt
10.3
0
non -detect
AOW Soil
S-15
S-15 SD 20150602
Cobalt
10.3
0
non -detect
AOW Soil
S-4
S-4 SD 20150629
Cobalt
10.3
0
non -detect
AOW Soil
S-16
S-16 SD 20150602
Cobalt
8.8
0
non -detect
AOW Soil
S-7
S-7 SD 20150627
Cobalt
7.6
0
non -detect
AOW Soil
S-8
S-8 SD 20150629
Cobalt
6.4
0
non -detect
User Selected Options
Date/Time of Computation
From File
Full Precision
Outlier Tests for Selected Uncensored Variables
6/21/2016 10:05:21 AM
As_Co.xls
OFF
Rosner's Outlier Test for Cobalt
Mean 56.06
Standard Deviation 169.2
Number of data 29
Number of suspected outliers 4
For 5% significance level, there are 4 Potential Outliers
Potential outliers are:
926, 95.8, 88.3, 81.6
For 1 % Significance Level, there are 4 Potential Outliers
Potential outliers are:
926, 95.8, 88.3, 81.6
Appendix D - Human Health Risk Analysis D-29 September 30, 2016
Potential
Obs.
Test
Critical
Critical
# Mean
sd
outlier
Number
value
value (5%)
value (1 %)
1 56.06
166.3
926
1
5.231
2.89
3.22
2 24.99
25.92
95.8
2
2.732
2.88
3.2
3 22.36
22.31
88.3
3
2.956
2.86
3.18
4 19.83
18.35
81.6
4
3.366
2.84
3.16
For 5% significance level, there are 4 Potential Outliers
Potential outliers are:
926, 95.8, 88.3, 81.6
For 1 % Significance Level, there are 4 Potential Outliers
Potential outliers are:
926, 95.8, 88.3, 81.6
Appendix D - Human Health Risk Analysis D-29 September 30, 2016

A B C I D I E I F I G I H I I I J K L
1 ProUCL Analysis: UCL Statistics for Data Sets with Non -Detects
2 User Selected Options
3 Date/Time of Computation
6/23/2016 8:23:26 PM
4 From File
Cliffside_As.xls
5 Full Precision
OFF
6 Confidence Coefficient
95%
7 Number of Bootstrap Operations
2000
8 Arsenic - Cliffside Facility AOW Soil
9
10 General Statistics
11 Total Number of Observations
25
Number of Distinct Observations
20
12 Number of Detects
4
Number of Non -Detects
21
13 Number of Distinct Detects
4
Number of Distinct Non -Detects
16
14 Minimum Detect
4.4
Minimum Non -Detect
6
151 Maximum Detect
18.5
Maximum Non -Detect
16
16 Variance Detects
42.68
Percent Non -Detects
84%
17 Mean Detects
9.575
SD Detects
6.533
18 Median Detects
7.7
CV Detects
0.682
19 Skewness Detects
1.141 Kurtosis Detects
0.224
20 Mean of Logged Detects
2.088 SD of Logged Detects
0.671
21
22 Normal GOF Test on Detects Only
23 Shapiro Wilk Test Statistic
0.877
Shapiro Wilk GOF Test
24 5% Shapiro Wilk Critical Value
0.748
Detected Data appear Normal at 5% Significance Level
25 Lilliefors Test Statistic
0.258
Lilliefors GOF Test
26 5% Lilliefors Critical Value
0.443
Detected Data appear Normal at 5% Significance Level
271 Detected Data appear Normal at 5% Significance Level
28
29 Kaplan -Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs
30 Mean
5.594
Standard Error of Mean
0.752
31 SD
2.975
95% KM (BCA) UCL
N/A
32 95% KM (t) UCL
6.88
95% KM (Percentile Bootstrap) UCL
N/A
331 95% KM (z) UCL
6.83
95% KM Bootstrap t UCL
N/A
34 90% KM Chebyshev UCL
7.849
95% KM Chebyshev UCL
8.87
35 97.5% KM Chebyshev UCL
10.29
99% KM Chebyshev UCL
13.07
36
37 Gamma GOF Tests on Detected Observations Only
38 A -D Test Statistic
0.355
Anderson -Darling GOF Test
39 5% A -D Critical Value
0.659
Detected data appear Gamma Distributed at 5% Significance Level
40 K -S Test Statistic
0.296
Kolmogrov-Smirnoff GOF
41 5% K -S Critical Value
0.397
Detected data appear Gamma Distributed at 5% Significance Level
42 Detected data appear Gamma Distributed at 5% Significance Level
43
44 Gamma Statistics on Detected Data Only
451 k hat (MLE)
3.072
k star (bias corrected MLE)
0.935
46 Theta hat (MLE)
3.117
Theta star (bias corrected MLE)
10.24
47 nu hat (MLE)
24.58
nu star (bias corrected)
7.477
48 MLE Mean (bias corrected)
9.575
MLE Sd (bias corrected)
9.904
49
50 Gamma Kaplan -Meier (KM) Statistics
51 k hat (KM)
3.536
nu hat (KM)
176.8
52 Approximate Chi Square Value (176.82, a)
147.1
Adjusted Chi Square Value (176.82, (i)
145.2
53 95% Gamma Approximate KM -UCL (use when n-50)
6.726
95% Gamma Adjusted KM -UCL (use when n<50)
6.811
54
Appendix D - Human Health Risk Analysis D-30 September 30, 2016

A B C D I E I F I G I H I I J K L
55 Gamma ROS Statistics using Imputed Non -Detects
56 GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs
57 GROS may not be used when kstar of detected data is small such as < 0.1
581 For such situations, GROS method tends to yield inflated values of UCLs and BTVs
59 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates
60 Minimum
1.864
Mean
5.349
61 Maximum
18.5
Median
4.676
62 SD
3.169
CV
0.593
631 k hat (MLE)
5.039
k star (bias corrected MLE)
4.461
64 Theta hat (MLE)
1.061
Theta star (bias corrected MLE)
1.199
65 nu hat (MLE)
252
nu star (bias corrected)
223.1
66 MLE Mean (bias corrected)
5.349
MLE Sd (bias corrected)
2.532
67
Adjusted Level of Significance (0)
0.0395
68 Approximate Chi Square Value (223.06, a)
189.5
Adjusted Chi Square Value (223.06, R)
187.4
691 95% Gamma Approximate UCL (use when n> 50)
6.297
95% Gamma Adjusted UCL (use when n<50)
N/A
70
71 Lognormal GOF Test on Detected Observations Only
72 Shapiro Wilk Test Statistic
0.912
Shapiro Wilk GOF Test
73 5% Shapiro Wilk Critical Value
0.748
Detected Data appear Lognormal at 5% Significance Level
74 Lilliefors Test Statistic
0.262
Lilliefors GOF Test
75 5% Lilliefors Critical Value
0.443
Detected Data appear Lognormal at 5% Significance Level
76 Detected Data appear Lognormal at 5% Significance Level
77
78 Lognormal ROS Statistics Using Imputed Non -Detects
79 Mean in Original Scale
5.651 Mean in Log Scale
1.657
80 SD in Original Scale
2.998 SD in Log Scale
0.345
81 95% t UCL (assumes normality of ROS data)
6.676 95% Percentile Bootstrap UCL
6.723
82 95% BCA Bootstrap UCL
7.298 95% Bootstrap t UCL
8.957
83 95% H -UCL (Log ROS)
6.338
84
85 UCLs using Lognormal Distribution and KM Estimates when Detected data are Lognormally Distributed
86 KM Mean (logged)
1.648
95% H -UCL (KM -Log)
6.192
871 KM SD (logged)
0.326
95% Critical H Value (KM -Log)
1.83
88 KM Standard Error of Mean (logged)
0.093
89
90 DL/2 Statistics
91 DL/2 Normal
DL/2 Log -Transformed
92 Mean in Original Scale
6.058
Mean in Log Scale
1.717
931 SD in Original Scale
3.117
SD in Log Scale
0.388
94 95% t UCL (Assumes normality)
7.125
95% H -Stat UCL
6.961
95 DL/2 is not a recommended method, provided for comparisons and historical reasons
96
97 Nonparametric Distribution Free UCL Statistics
98 Detected Data appear Normal Distributed at 5% Significance Level
99
100 Suggested UCL to Use
101 95% KM (t) UCL 6.88 95% KM (Percentile Bootstrap) UCL N/A
102 Warning: One or more Recommended UCL(s) not available!
103
104 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL.
1051 Recommendations are based upon data size, data distribution, and skewness.
106 These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006).
107 However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician.
Appendix D - Human Health Risk Analysis D-31 September 30, 2016

Appendix D - Human Health Risk Analysis D-32 September 30, 2016
A B C I D I E
I F I
G I H I I I J K
L
1
ProUCL Analysis: UCL Statistics for Data Sets with Non -Detects
2
User Selected Options
3
Date/Time of Computation
6/23/2016 8:40:48 PM
4
From File
Cliffside_AsCo.xls
5
Full Precision
OFF
6
Confidence Coefficient
95%
7
Number of Bootstrap Operations
2000
8
Cobalt - Cliffside Facility AOW Soil
9
10
General Statistics
11
Total Number of Observations
25
Number of Distinct Observations
23
12
Number of Detects
16
Number of Non -Detects
9
13
Number of Distinct Detects
16
Number of Distinct Non -Detects
7
14
Minimum Detect
4.8
Minimum Non -Detect
6.4
151
Maximum Detect
50.4
Maximum Non -Detect
15.9
16
Variance Detects
250.5
Percent Non -Detects
36%
17
Mean Detects
21.09
SD Detects
15.83
18
Median Detects
15.95
CV Detects
0.75
19
Skewness Detects
0.667
Kurtosis Detects
-0.959
20
Mean of Logged Detects
2.747
SD of Logged Detects
0.831
21
22
Normal GOF Test on Detects Only
23
Shapiro Wilk Test Statistic
0.866
Shapiro Wilk GOF Test
24
5% Shapiro Wilk Critical Value
0.887
Detected Data Not Normal at 5% Significance Level
25
Lilliefors Test Statistic
0.226
Lilliefors GOF Test
26
5% Lilliefors Critical Value
0.222
Detected Data Not Normal at 5% Significance Level
271
Detected Data Not Normal
at 5% Significance Level
28
29
Kaplan -Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs
30
Mean
15.82
Standard Error of Mean
2.934
31
SD
14.16
95% KM (BCA) UCL
20.84
32
95% KM (t) UCL
20.84
95% KM (Percentile Bootstrap) UCL
21
331
95% KM (z) UCL
20.65
95% KM Bootstrap t UCL
21.87
34
90% KM Chebyshev UCL
24.62
95% KM Chebyshev UCL
28.61
35
97.5% KM Chebyshev UCL
34.14
99% KM Chebyshev UCL
45.01
36
37
Gamma GOF
Tests on Detected Observations Only
38
A -D Test Statistic
0.641
Anderson -Darling GOF Test
39
5% A -D Critical Value
0.752
Detected data appear Gamma Distributed at 5% Significance Level
40
K -S Test Statistic
0.181
Kolmogrov-Smirnoff GOF
41
5% K -S Critical Value
0.218
Detected data appear Gamma Distributed at 5% Significance Level
42
Detected data appear Gamma Distributed at 5% Significance Level
43
44
Gamma
Statistics on Detected Data Only
451
k hat (MLE)
1.806
k star (bias corrected MLE)
1.509
46
Theta hat (MLE)
11.68
Theta star (bias corrected MLE)
13.98
47
nu hat (MLE)
57.79
nu star (bias corrected)
48.29
48
MLE Mean (bias corrected)
21.09
MLE Sd (bias corrected)
17.17
49
50
Gamma Kaplan -Meier (KM) Statistics
51
k hat (KM)
1.248
nu hat (KM)
62.42
52
Approximate Chi Square Value (62.42, a)
45.24
Adjusted Chi Square Value (62.42, (i)
44.25
53
95% Gamma Approximate KM -UCL (use when n-50)
21.83
95% Gamma Adjusted KM -UCL (use when n<50)
22.32
54
Appendix D - Human Health Risk Analysis D-32 September 30, 2016

A B C D I E I F I G I H I I J K L
55 Gamma ROS Statistics using Imputed Non -Detects
56 GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs
57 GROS may not be used when kstar of detected data is small such as < 0.1
581 For such situations, GROS method tends to yield inflated values of UCLs and BTVs
59 For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates
60 Minimum
0.676 Mean
15.35
61 Maximum
50.4 Median
7.2
62 SD
14.84 CV
0.967
631 k hat (MLE)
1.207 k star (bias corrected MLE)
1.089
64 Theta hat (MLE)
12.71 Theta star (bias corrected MLE)
14.09
65 nu hat (MLE)
60.37 nu star (bias corrected)
54.46
66 MLE Mean (bias corrected)
15.35 MLE Sd (bias corrected)
14.71
67
Adjusted Level of Significance (0)
0.0395
68 Approximate Chi Square Value (54.46, a)
38.5 Adjusted Chi Square Value (54.46, (i)
37.59
691 95% Gamma Approximate UCL (use when n> 50)
21.71 95% Gamma Adjusted UCL (use when n<50)
22.24
70
71 Lognormal GOF Test on Detected Observations Only
72 Shapiro Wilk Test Statistic
0.905
Shapiro Wilk GOF Test
73 5% Shapiro Wilk Critical Value
0.887
Detected Data appear Lognormal at 5% Significance Level
74 Lilliefors Test Statistic
0.168
Lilliefors GOF Test
75 5% Lilliefors Critical Value
0.222
Detected Data appear Lognormal at 5% Significance Level
76 Detected Data appear Lognormal at 5% Significance Level
77
78 Lognormal ROS Statistics Using Imputed Non -Detects
79 Mean in Original Scale
15.96
Mean in Log Scale
2.44
80 SD in Original Scale
14.36
SD in Log Scale
0.792
81 95% t UCL (assumes normality of ROS data)
20.88
95% Percentile Bootstrap UCL
20.69
82 95% BCA Bootstrap UCL
21.23
95% Bootstrap t UCL
22.44
83 95% H -UCL (Log ROS)
22.58
84
85 UCLs using Lognormal Distribution and KM Estimates when Detected data are Lognormally Distributed
86 KM Mean (logged)
2.421
95% H -UCL (KM -Log)
21.99
871 KM SD (logged)
0.787
95% Critical H Value (KM -Log)
2.24
88 KM Standard Error of Mean (logged)
0.166
89
90 DL/2 Statistics
91 DL/2 Normal
DL/2 Log -Transformed
92 Mean in Original Scale
15.43
Mean in Log Scale
2.349
931 SD in Original Scale
14.72
SD in Log Scale
0.868
94 95% t UCL (Assumes normality)
20.47
95% H -Stat UCL
23.08
95 DL/2 is not a recommended method, provided for comparisons and historical reasons
96
97 Nonparametric Distribution Free UCL Statistics
98 Detected Data appear Gamma Distributed at 5% Significance Level
99
100 Suggested UCL to Use
101 95% KM (Percentile Bootstrap) UCL
21.00
95% GROS Adjusted Gamma UCL 22.24
102 95% Adjusted Gamma KM -UCL
22.32
103
104 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL.
1051 Recommendations are based upon data size, data distribution, and skewness.
106 These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006).
107 However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician.
Appendix D - Human Health Risk Analysis D-33 September 30, 2016

Sample ID
Sample Collection
Date
Matrix
Arsenic
ProUCL
Flag
Cobalt
ProUCL
Flag
AB -01 (4-5)
03/19/2015
ash
3.1
0
3.1
0
AB -01 (34.3-35)
03/19/2015
ash
2.9
1
4.2
1
AB -01 (48-50)
03/19/2015
ash
2.6
1
3.4
1
AB -02 (4-5)
03/18/2015
ash
4.4
0
4.4
0
AB -02 (18-20)
03/18/2015
ash
3.3
1
4.5
1
AB -02 (32.9-33.7)
03/18/2015
ash
3.4
l
4.7
1
AB -03 (4-5)
03/18/2015
ash
3.3
0
3.3
0
AB -03 (21.6-23.4)
03/18/2015
ash
3.3
l
4
1
AB -04 (4-5)
03/17/2015
ash
3.5
0
3.5
0
AB -04 (33-35)
03/17/2015
ash
13.4
1
13.6
1
AB -04 (33-35) DUP
03/17/2015
ash
17.0
1
19.7
1
AB -04 (53-55)
03/17/2015
ash
10.0
1
12.9
1
ABMW-01 (1-1.5)
06/02/2015
ash
16.6
1
7.6 j
1
ABMW-01 (11.5-12)
06/02/2015
ash
26.2
1
8.3
1
MW-03BR (0.8-1.25)
02/05/2015
soil
3.0
0
5.4
1
MW-03BR (14.75-15)
02/05/2015
soil
2.5
0
4.3
1
MW-03BR (17-18)
02/05/2015
soil
2.7
0
3.6
1
MW-07BR (1-2)
04/23/2015
soil
5.1
0
5.1
0
MW-08BR (0.75-1.25)
02/11/2015
soil
3.2
0
21.3
1
MW-08BR (25.5-26)
02/11/2015
soil
2.7
0
32.9
1
MW-08BR (30.5-31)
02/11/2015
soil
2.7
0
7.4
1
MW-13BR (0-2)
04/12/2015
soil
6.5
0
6.5
0
MW-13BR (52-54)
04/13/2015
soil
5.1
0
6.6
1
MW-13BR (52-54) DUP
04/13/2015
soil
5.9
0
7.2
1
MW-15BR (0.5-1)
05/09/2015
soil
6.2
0
3.9
1
MW- 16BR (1-2)
04/25/2015
soil
6.5
0
6 j
1
MW-16BR (23-24)
04/26/2015
soil
5.0
0
4.6
1
MW-16BR (33-35)
04/25/2015
soil
7.5
0
12
1
MW-16BR (54.5-55.5)
04/25/2015
soil
5.2
0
19.6
1
SB -05 (1-2)
03/04/2015
soil
1.8
1
2.8
1
SB -05 (2.3-3.3)
03/04/2015
soil
1.1
1
1.7
1
SB -05 (8-9)
03/04/2015
soil
1.0
1
2.2
1
SB -06 (1-2)
03/04/2015
soil
1.2
1
2.5
1
SB -07 (1-2)
05/07/2015
soil
5.8
0
5.9
1
SB -07 (4.5-7.5)
05/07/2015
soil
6.0
0
6
0
S-01
05/12/2015
seep_soil
56.4
1
14.4
0
5-02
05/13/2015
seep_soil
6.8
0
16.4
1
S -02B
05/13/2015
seep_soil
6.3
0
4.7
1
5-08
05/13/2015
seep_soil
8.7
0
40.6
1
Notes:
Ash and perimeter soil data records were added to the AOW_soil data to recompute the EPC (expand the # of
data records for a more robust ProUCL statistical evaluation)
Appendix D - Human Health Risk Analysis D-34 September 30, 2016

Appendix D - Human Health Risk Analysis D-35 September 30, 2016
A B C D E
F
G H J K
L
1
ProUCL: UCL Statistics for Data Sets with Non -Detects
2
User Selected Options
3
Date/Time of Computation 6/23/2016 5:19:22 PM
4
From File Duke_EPC.xls
5
Full Precision OFF
6
Confidence Coefficient 95%
7
Number of Bootstrap Operations 2000
8
Arsenic
9
101
General
Statistics
11
Total Number of Observations
38
Number of Distinct Observations
32
12
Number of Detects
15
Number of Non -Detects
23
13
Number of Distinct Detects
14
Number of Distinct Non -Detects
19
14
Minimum Detect
1
Minimum Non -Detect
2.5
151
Maximum Detect
56.4
Maximum Non -Detect
7.5
16
Variance Detects
218.3
Percent Non -Detects
60.53%
17
Mean Detects
10.68
SD Detects
14.77
18
Median Detects
3.3
CV Detects
1.383
19
Skewness Detects
2.409
Kurtosis Detects
6.559
201
Mean of Logged Detects
1.622
SD of Logged Detects
1.259
21
22
Normal GOF Test on Detects Only
23
Shapiro Wilk Test Statistic
0.682
Shapiro Wilk GOF Test
24
5% Shapiro Wilk Critical Value
0.881
Detected Data Not Normal at 5% Significance Level
251
Lilliefors Test Statistic
0.289
Lilliefors GOF Test
26
5% Lilliefors Critical Value
0.229
Detected Data Not Normal at 5% Significance Level
27
Detected Data Not Normal at 5% Significance Level
28
29
Kaplan -Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs
30
Mean
5.304
Standard Error of Mean
1.686
31
1 SD
9.985
95% KM (BCA) UCL
8.162
32
95% KM (t) UCL
8.149
95% KM (Percentile Bootstrap) UCL
8.44
33
95% KM (z) UCL
8.077
95% KM Bootstrap t UCL
11.5
34
90% KM Chebyshev UCL
10.36
95% KM Chebyshev UCL
12.65
35
97.5% KM Chebyshev UCL
15.83
99% KM Chebyshev UCL
22.08
36
371
Gamma GOF
Tests on Detected Observations Only
38
A -D Test Statistic
0.735
Anderson -Darling GOF Test
39
5% A -D Critical Value
0.773
Detected data appear Gamma Distributed at 5% Significance Level
40
K -S Test Statistic
0.277
Kolmogrov-Smirnoff GOF
41
5% K -S Critical Value
0.23
Detected Data Not Gamma Distributed at 5% Significance Level
42
Detected data follow Appr.
Gamma Distribution at 5% Significance Level
43
44
Gamma
Statistics on Detected Data Only
45
k hat (MLE)
0.796
k star (bias corrected MLE)
0.681
46
Theta hat (MLE)
13.42
Theta star (bias corrected MLE)
15.68
47
nu hat (MLE)
23.88
nu star (bias corrected)
20.44
48
MLE Mean (bias corrected)
10.68
MLE Sd (bias corrected)
12.94
49
Appendix D - Human Health Risk Analysis D-35 September 30, 2016

A B C D E I F I G I H I J K L
50 Gamma Kaplan -Meier (KM) Statistics
51 k hat (KM) 0.282 nu hat (KM) 21.45
52 Approximate Chi Square Value (21.45, a)
11.92
Adjusted Chi Square Value (21.45, R) 11.63
53 95% Gamma Approximate KM -UCL (use when n> 50)
9.539
95% Gamma Adjusted KM -UCL (use when n<50) 9.781
54
55 Gamma ROS Statistics using Imputed Non -Detects
56 GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs
57 GROS may not be used when kstar of detected data is small such as < 0.1
58 For such situations, GROS method tends to yield inflated values of UCLs and BTVs
59 For gamma distributed detected data, BTUs and UCLs may be computed using gamma distribution on KM estimates
601 Minimum
0.01
Mean 4.298
61 Maximum
56.4
Median 0.01
62 SD
10.49
CV 2.44
63 k hat (MLE)
0.217
k star (bias corrected MLE) 0.218
64 Theta hat (MLE)
19.78
Theta star (bias corrected MLE) 19.74
65 nu hat (MLE)
16.51
nu star (bias corrected) 16.54
661 MLE Mean (bias corrected)
4.298
MLE Sd (bias corrected) 9.212
67
Adjusted Level of Significance ((3) 0.0434
68 Approximate Chi Square Value (16.54, a)
8.348
Adjusted Chi Square Value (16.54, R) 8.106
69 95% Gamma Approximate UCL (use when n> 50)
8.519
95% Gamma Adjusted UCL (use when n<50) 8.773
70
71 Lognormal GOF Test on Detected Observations Only
721 Shapiro Wilk Test Statistic
0.927
Shapiro Wilk GOF Test
73 5% Shapiro Wilk Critical Value
0.881
Detected Data appear Lognormal at 5% Significance Level
74 Lilliefors Test Statistic
0.224
Lilliefors GOF Test
75 5% Lilliefors Critical Value
0.229
Detected Data appear Lognormal at 5% Significance Level
76 Detected Data appear Lognormal at 5% Significance Level
77
781 Lognormal ROS Statistics Using Imputed Non -Detects
79 Mean in Original Scale
5.275
Mean in Log Scale
0.952
80 SD in Original Scale
10.12
SD in Log Scale
0.98
81 95% t UCL (assumes normality of ROS data)
8.043
95% Percentile Bootstrap UCL
8.241
82 95% BCA Bootstrap UCL
9.388
95% Bootstrap t UCL
12.13
83 95% H -UCL (Log ROS)
6.137
84
85 UCLs using Lognormal Distribution and KM Estimates when Detected data are Lognormally Distributed
86 KM Mean (logged)
0.934
95% H -UCL (KM -Log)
6.276
87 KM SD (logged)
1.006
95% Critical H Value (KM -Log)
2.402
88 KM Standard Error of Mean (logged)
0.197
89
901 DL/2 Statistics
91 DL/2 Normal
DL/2 Log -Transformed
92 Mean in Original Scale
5.65
Mean in Log Scale 1.126
93 SD in Original Scale
9.996
SD in Log Scale 0.918
94 95% t UCL (Assumes normality)
8.386
95% H -Stat UCL 6.655
95 DL/2 is not a recommended method, provided for comparisons and historical reasons
96
97 Nonparametric Distribution Free UCL Statistics
98 Detected Data appear Approximate Gamma Distributed at 5% Significance Level
99
100 Suggested UCL to Use
101 95% KM (t) UCL
8.149
95% GROS Adjusted Gamma UCL 8.773
102 95% Adjusted Gamma KM -UCL
9.781
103
104 Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL.
105 Recommendations are based upon data size, data distribution, and skewness.
106 These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006).
107 However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician.
Appendix D - Human Health Risk Analysis D-36 September 30, 2016

A B C D E F G H J K L
108 ProUCL: UCL Statistics for Data Sets with Non -Detects
109 User Selected Options
110 Date/Time of Computation 6/23/2016 5:19:22 PM
111 From File Duke_EPC.xls
112 Full Precision OFF
113 Confidence Coefficient 95%
114 Number of Bootstrap Operations 2000
115 Cobalt
116
117 General Statistics
1181 Total Number of Observations
39
Number of Distinct Observations 37
119 Number of Detects
31
Number of Non -Detects 8
120 Number of Distinct Detects
30
Number of Distinct Non -Detects 8
121 Minimum Detect
1.7
Minimum Non -Detect 3.1
122 Maximum Detect
40.6
Maximum Non -Detect 14.4
123 Variance Detects
83.31
Percent Non -Detects 20.51%
1241 Mean Detects
9.5
SD Detects 9.128
125 Median Detects
5.9
CV Detects 0.961
126 Skewness Detects
2.054
Kurtosis Detects 4.294
127 Mean of Logged Detects
1.918
SD of Logged Detects 0.793
128
129 Normal GOF Test on Detects Only
1301 Shapiro Wilk Test Statistic
0.742
Shapiro Wilk GOF Test
131 5% Shapiro Wilk Critical Value
0.929
Detected Data Not Normal at 5% Significance Level
132 Lilliefors Test Statistic
0.262
Lilliefors GOF Test
133 5% Lilliefors Critical Value
0.159
Detected Data Not Normal at 5% Significance Level
134 Detected Data Not Normal at 5% Significance Level
135
1361 Kaplan -Meier (KM) Statistics using Normal Critical Values and other Nonparametric UCLs
137 Mean
8.218
Standard Error of Mean 1.376
138 SD
8.426
95% KM (BCA) UCL 10.86
139 95% KM (t) UCL
10.54
95% KM (Percentile Bootstrap) UCL 10.46
140 95% KM (z) UCL
10.48
95% KM Bootstrap t UCL 11.4
141 90% KM Chebyshev UCL
12.34
95% KM Chebyshev UCL 14.21
1421 97.5% KM Chebyshev UCL
16.81
99% KM Chebyshev UCL 21.91
143
144 Gamma GOF Tests on Detected Observations Only
145 A -D Test Statistic 1.16
Anderson -Darling GOF Test
146 5% A -D Critical Value 0.762
Detected Data Not Gamma Distributed at 5% Significance Level
147 K -S Test Statistic 0.181
Kolmogrov-Smirnoff GOF
148 5% K -S Critical Value 0.16
Detected Data Not Gamma Distributed at 5% Significance Level
149 Detected Data Not Gamma Distributed at 5% Significance Level
150
151 Gamma Statistics on Detected Data Only
152 k hat (MLE)
1.647
k star (bias corrected MLE) 1.509
153 Theta hat (MLE)
5.768
Theta star (bias corrected MLE) 6.295
1541 nu hat (MLE)
102.1
nu star (bias corrected) 93.57
155 MLE Mean (bias corrected)
9.5
MLE Sd (bias corrected) 7.733
156
157 Gamma Kaplan -Meier (KM) Statistics
158 k hat (KM)
0.951
nu hat (KM) 74.2
159 Approximate Chi Square Value (74.20, a)
55.36
Adjusted Chi Square Value (74.20, (i) 54.72
160 95% Gamma Approximate KM -UCL (use when n>=50)
11.01
95% Gamma Adjusted KM -UCL (use when n<50) 11.14
161
162 Gamma ROS Statistics using Imputed Non -Detects
163 GROS may not be used when data set has > 50% NDs with many tied observations at multiple DLs
164 GROS may not be used when kstar of detected data is small such as < 0.1
165 For such situations, GROS method tends to yield inflated values of UCLs and BTVs
16 1 e , BTVs and UC be computed using gamma distribution on KM RSAWMher 10 ?016

Appendix D - Human Health Risk Analysis D-38 September 30, 2016
A B C D E F G H I J K
L
167
Minimum 0.01 Mean
7.834
168
Maximum 40.6 Median
4.6
169
SD 8.788 CV
1.122
170
k hat (MLE) 0.742 k star (bias corrected MLE)
0.702
171
Theta hat (MLE) 10.56 Theta star (bias corrected MILE)
11.16
172
nu hat (MLE) 57.87 nu star (bias corrected)
54.75
173
MLE Mean (bias corrected) 7.834 MLE Sd (bias corrected)
9.35
174
Adjusted Level of Significance ((3)
0.0437
175
Approximate Chi Square Value (54.75, a) 38.75 Adjusted Chi Square Value (54.75, (3)
38.22
176
95% Gamma Approximate UCL (use when n>=50) 11.07 95% Gamma Adjusted UCL (use when n<50)
11.22
177
178
Lognormal GOF Test on Detected Observations Only
179
Shapiro Wilk Test Statistic
0.956
Shapiro Wilk GOF Test
180
5% Shapiro Wilk Critical Value
0.929
Detected Data appear Lognormal at 5% Significance Level
181
Lilliefors Test Statistic
0.131
Lilliefors GOF Test
182
5% Lilliefors Critical Value
0.159
Detected Data appear Lognormal at 5% Significance Level
1831
Detected Data appear Lognormal at 5% Significance Level
184
185
Lognormal ROS Statistics Using Imputed Non -Detects
186
Mean in Original Scale
8.173
Mean in Log Scale
1.742
187
SD in Original Scale
8.542
SD in Log Scale
0.8
188
95% t UCL (assumes normality of ROS data)
10.48
95% Percentile Bootstrap UCL
10.48
189
95% BCA Bootstrap UCL
10.98
95% Bootstrap t UCL
11.61
190
95% H -UCL (Log ROS)
10.44
191
192
UCLs using Lognormal Distribution and KM Estimates when Detected data are Lognormally Distributed
193
KM Mean (logged)
1.748
95% H -UCL (KM -Log)
10.41
194
KM SD (logged)
0.793
95% Critical H Value (KM -Log)
2.179
1951
KM Standard Error of Mean (logged)
0.132
196
197
DL/2 Statistics
198
DL/2 Normal
DL/2 Log -Transformed
199
Mean in Original Scale
8.145
Mean in Log Scale
1.716
200
SD in Original Scale
8.585
SD in Log Scale
0.84
201
95% t UCL (Assumes normality)
10.46
95% H -Stat UCL
10.72
202
DL/2 is not a recommended method, provided for comparisons and historical reasons
203
204
Nonparametric Distribution Free UCL Statistics
205
Detected Data appear Lognormal Distributed at 5% Significance Level
206
2071
Suggested UCL to Use
208
95% KM (BCA) LICLI 10.86
209
210
Note: Suggestions regarding the selection of a 95% UCL are provided to help the user to select the most appropriate 95% UCL.
211
Recommendations are based upon data size, data distribution, and skewness.
212
These recommendations are based upon the results of the simulation studies summarized in Singh, Maichle, and Lee (2006).
12131
However, simulations results will not cover all Real World data sets; for additional insight the user may want to consult a statistician.
Appendix D - Human Health Risk Analysis D-38 September 30, 2016

[EN
APPENDIX E
Ecological Habitat Service Analysis
Appendix E — Ecological Habitat Service Analysis E-1 September 30, 2016

0
El ECOLOGICAL HABITAT SERVICE
ANALYSIS
The purpose of this evaluation was to understand how the CIP and Removal alternatives might
affect ecological habitat values associated with the Allen, Buck, Cliffside, and Mayo sites. As
stated in Section 3.5, the ecological habitat service analysis for each site consisted of three main
steps as follows:
The first step was to identify the major habitat types existing within the areas that would
be impacted by the remedial alternatives at each site and to estimate the surface area of
each major habitat type.
2. The second step was to develop assumptions regarding the timing and level of impact (i.e.,
projected change in ecological service value over time) that implementation of each
alternative would have on the habitat types evaluated.
3. The third step was to estimate the change (i.e., loss) in the net present value (NPV) of
ecological habitat services that would be projected to occur given the habitats, acreages,
and assumptions developed as part of Steps 1 and 2.
Each of these steps are discussed, in turn, in the following sections.
E1.1 Habitat Types and Areas
This step used a combination of existing geographic information system (GIS) habitat polygon
boundary information, aerial photography reviews, site visit observations, and GIS analysis to
understand the general distribution of the habitat types and their respective surface areas at each
of the four sites. The GIS files for the habitats at the Allen, Buck, and Cliffside sites were provided
by Duke Energy. In addition, I conducted site visits at all four sites during the June 7-10, 2016,
time period. For the Mayo site, GIS habitat files were not available. Therefore, habitat polygons
were developed through GIS analysis based upon the site visits and review of Google Earth aerial
photography. The GIS polygons for the Allen, Buck, Cliffside, and Mayo sites are presented in
Figures E1 -E4, respectively. Land habitat types were assigned to the following major categories:
Terrestrial Habitats
• Forest (included pine, hardwood, bottomland and mixed forest habitats)
• Shrub Scrub/ Early Successional
• Grass/open mowed field
Appendix E — Ecological Habitat Service Analysis E-2 September 30, 2016

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Wetlands and Surface Water
• Combined emergent wetland, forested wetland and open water habitats
I focused on the major habitat types that would be affected by the remedial alternatives. It should
be noted that parking areas, roads, water treatment facility basins, and barren ash areas (non-
vegetated) were excluded from the analysis.
Through the above GIS polygon analysis, the surface area of each habitat type that was projected
to be impacted by either the CIP or Removal alternative was determined for each site, including a
30 -foot work zone buffer around each basin that would be affected by each alternative. The GIS
polygon data for each site were grouped by major habitat type for the purposes of the evaluation
(Table E1). The focus was on how the major terrestrial and wetland/surface water habitats would
be affected given implementation of the alternatives.
Habitat Type by Site
Allen
Buck
Cliffside
Mayo
Terrestrial
Early Successional/Scrub
85
52
42
42
Forest
34
36
25
11
Open Field -Grass
88
34
52
14
Wetland and Surface Water
98
65
45
79
Total Acreage of Habitats
Evaluated
305
187
163
147
The evaluation area includes only those areas that were projected to be impacted by
the remedial actions, including a 30 foot buffer around the outside of each basin.
Areas with roads, water treatment facilities, and barren ash were not included in the
analysis.
Table E1. Acreage of the selected major habitat types under the current site condition
that would be physically impacted through implementation of the CIP or Removal
alternatives (rounded to nearest acre).
E1.2 Ecological Habitat Service Methodology and Assumptions
Ecosystems provide a variety of services to humans. These services have been classified as
supporting, provisioning, regulating, and cultural services as part of the Millennium Ecosystem
Assessment (2005). Habitats serve as the supporting structure from which provisioning, regulating,
and cultural services flow and hence provide value. That is, many human use services (bird
watching, recreational fishing, etc.) are provided by the presence of the ecological habitat services.
For example, state game lands provide recreational hunting and birdwatching activities that would
otherwise not be present if the ecology and habitat was not in place. Thus, actions adversely
Appendix E — Ecological Habitat Service Analysis E-7 September 30, 2016

m
affecting ecological habitat services can result in significant human use service losses while actions
that enhance habitats can result in increased human use service value. The focus of this section is
the quantification of the ecological habitat services that are projected to be impacted (either lost or
gained) by the CIP and Removal remedial alternatives.
Importantly, the net environmental benefits have been assessed using the current status of the
environment (the project baseline) against which the potential change in environmental condition
is measured. As such, projected changes in ecological habitat service values associated with
implementation of the CIP and Removal alternatives is compared to the current status of the
habitats on-site.
E1.2.1 Environmental Metric and Discounting
Since ecological habitat impacts can occur over varying time frames, they can be normalized to
their net present value (NPV) using a time discount rate. The discount rate is the rate at which the
public is indifferent to consuming goods now or sometime in the future. An estimate of the NPV
of the losses in ecological habitat value were developed through the use of the Habitat Equivalency
Analysis (HEA) methodology. In this case, projected habitat alterations (e.g., removal,
displacement of habitat) were used to directly assess changes in ecological habitat quality and
resulting value. My evaluation included both the major direct on-site and off-site habitat impacts.
Indirect impacts associated with alternative implementation were not estimated. Therefore, my
estimation of impacts is conservative (i.e., underestimates projected losses).
Because many ecological habitat services are not traded in the marketplace, they may not have a
direct monetary value and therefore, value can be expressed using non -monetary metrics. The HEA
approach is a service quantification approach that evaluates ecological habitat service losses or
gains based on non -monetary metrics over time. It is important to recognize that ecosystem
services are not static measurements but represent a flow of benefits over time. As such, the HEA
approach uses an environmental metric to measure changes to ecological habitat services and
focuses on quantifying the area (e.g., acres) and level of impact over time in units typically
represented as service -acre -years (SAY'S). For this evaluation, I used the HEA methodology to
quantify the relative habitat service losses associated with the CIP and Removal alternatives.
Ecological service losses and gains can be measured using a variety of indicator metrics and units.
In many cases, the quantification of changes in ecological service flows is based upon selecting or
developing an indicator (can be one or more metrics) that acts as a surrogate to represent the
ecological service flows provided over time by the habitat and expressing the changes in services
(for that indicator) under the different alternatives as a percentage change from a baseline or
reference condition.
Ecosystem studies, literature -based information, professional experience, or a combination
thereof, can be used to estimate how ecosystem services may change given an action. The metrics
or indicators are selected based upon the site, habitats, and professional judgment. The metric(s)
are typically developed to represent the flow of value (e.g., loss or gain of services) over time.
As stated earlier, the ecological service calculations also involve a discount rate that allows for the
gains and losses to be evaluated from an NPV standpoint. Within the HEA methodology,
Appendix E — Ecological Habitat Service Analysis E-8 September 30, 2016

0
calculations of ecological service losses and gains associated with a project are computed over
time and represent time accumulated service flows. In these cases, the units are typically displayed
as a discounted service acre year (dSAY) which represents an ecological habitat value that takes
into account the time value of the habitat services. I used a 3% discount rate, this rate commonly
used in NRDA cases within the United States.
In evaluating ecological habitat service flows, applications of the HEA methodology must account
for the absolute difference in the flow of services from the ecological resources resulting from an
action and how those services are distributed over time. In addition, for any given action, it is
likely that the ecological habitat service loss or gain may not always be constant over time. An
assessment as to how ecological habitat service flows may change over time is thus necessary.
Quantifying the ecological service value of a given action can be conducted prior to project
implementation through the use of projected metrics based on scientific data and professional
judgment. Use of the HEA methodology has been upheld in U.S. federal court' as an appropriate
method to evaluate changes in ecological habitat services associated with actions that affect the
environment and has also been incorporated into the European Union Environmental Liabilities
Directive (Nicolette et al. 2013).
The analysis of ecological habitat services was conducted by examining how changes to the
existing habitats would occur given implementation of the CIP and Removal alternatives. It should
be recognized that the approach taken in the ecological analysis was to approximate the parameter
values for each of the alternatives based upon consistent assumptions where applicable. As such,
the parameter estimates are approximate values and not intended to be exact, but robust enough to
identify impacts and differences between alternatives to a reasonable degree of certainty.
My analysis focused on the major terrestrial and aquatic habitats. A discussion of the analysis of
the ecological habitat service value associated with the terrestrial and aquatic habitats is provided
in the following sections
E1.2.2 Assumptions
For the terrestrial analysis, ecological habitat service flows were modeled for each site per major
habitat type (forest, shrub scrub/early successional, and mowed grass). Changes in terrestrial
habitat value were compared to the baseline terrestrial habitat condition at the sites.
Baseline "Current" Condition
For the baseline terrestrial condition at each site, the following assumption was made:
• The flow of ecological service value is consistent with the above -ground biomass of the
terrestrial habitats and increases as the terrestrial system moves through successional
stages. That is, as the vertical structure and complexity of the terrestrial vegetation
increases, so does the ecological habitat service value. In forest ecosystems, post -
United States 1997. United States v. Melvin Fisher. United States District Court for the Southern District of Florida, Key West Division Case
Numbers 92-10027-CIV-DAVIS, and 95-10051-CIV-DAVIS. Decided 30 July 1997, Filed 30 July 1997. 977 F. Supp. 1193; 1997 U.S. Dist.
LEXIS 16767.
United States 2001. United States of America and Internal Improvement Trust Fund v. Great Lakes Dredge and Dock Company. United States
District Court for the Southem District of Florida D. C. Docket No. 97 -02510 -CV -EBD.
Appendix E — Ecological Habitat Service Analysis E-9 September 30, 2016

0
disturbance biomass accumulation provides an index of carbon sequestration and the
reestablishment of biological control over a variety of ecosystem processes, such as those
controlling nutrient cycling (Johnson et al. 2000). A functional form of this relationship is
presented in Figure E5 (adapted from McMahon et al. 2010). The rate and asymptote of
this pattern of biomass recovery can differ across stands because of nutrient availability
and species composition; however, the functional form of this response remains similar
across forest types and regions (McMahon et al. 2010).
Ecological succession is the process of change in the species composition of an ecological
community over time. The process begins with relatively few pioneering plants and animals that
develop through increasing complexity until the ecological community becomes stable as a climax
stage community. Vertical and horizontal structural habitat complexity has been shown to drive
biodiversity by creating a greater variety of microclimates and microhabitats, which in turn
produce more diverse food and cover for a more diverse group of species (Verschuyl et al. 2008).
In addition, a positive relationship between tree species richness and above -ground productivity
has often been found (Parrotta 2012).
One study has also shown that old growth forests (50-250 years of age) serve as a stronger sink
for CO2 than a younger growth forest (i.e., 14 years of age), thus indicating a higher carbon
sequestration value as the forest gets older (Law et al. 2001). The value of forest habitat in
protecting biodiversity and ecosystem service values has also been demonstrated (e.g., Gibson et
al., 2011). "Protecting forests will not only preserve biodiversity and defend the rights of forest
communities, it's also one of the quickest and cost effective ways of halting climate change"
(Greenpeace 2016).
The curve used to depict the flow of ecological habitat service value is presented in Figure E5 and
was kept constant among all terrestrial habitats at all sites and was selected to serve as a standard
to which changes in terrestrial habitat at the sites can be evaluated and compared.
Appendix E — Ecological Habitat Service Analysis E-10 September 30, 2016

100
0
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U
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L
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CU
U
W 50
_O
O
U
LU +-
25
L
O
LL
EPS
011 1 1 1 1 1
0 50 100 150 200 250
Years
Figure E5. Graphic showing the relationship between above -ground biomass (AGB) (used as
a surrogate for ecological service value) and stand age of multiple forest plots in a
temperate deciduous forest in Edgewater, MD. Adapted from McMahon et al. (2010).
For calculation purposes, the percent (%) service value at various points along the curve was
estimated as depicted in Figure ET Yearly percent habitat service estimates were generated
through linear interpolation between the identified points presented in Figure E6.
Interpolated from Graph
s
0 50 100 ISO 200 250
Stand age (years)
Figure E6. Interpolation of service values used in calculations.
Years
AGB
%
0
0
0.00%
5
5
1.01%
10
45
9.09%
15
80
16.16%
20
110
22.22%
25
140
28.28%
30
165
33.33%
35
185
37.37%
40
205
41.41%
451
225
45.45%
50
245
49.49%
60
275
55.56%
70
305
61.62%
80
330
66.67%
90
355
71.72%
100
375
75.76%
125
415
83.84%
150
445
89.90%
175
475
95.96%
200
495
100.00%
Appendix E — Ecological Habitat Service Analysis E-11 September 30, 2016

MO
The baseline ecological service value for forest habitat at the Allen site is depicted in Figure E8.
Note that the value estimate starts at an approximate age of 25 years for the on-site forest stands
being evaluated. This assumption was also held for offsite areas where forest habitat would be
impacted. This is conservative in estimating the baseline value as the tree stands are likely older
on average than 25 years of age both on- and off-site. Additionally, the flow of value, for all sites
and scenarios was calculated over a 200 -year period (2016-2216).
For shrub-scrub/early successional habitat, the start time on the successional curve was adjusted
to 5 years to approximate the average age of the vegetation assigned to this habitat type.
The conceptual model under which the forest dSAY value (591) for the Allen Steam Station was
calculated (at a 3% discount rate) is presented in Figure E7. This represents the current service
value projected into the future of the on-site 34.2 acres of forest habitat. The on-site shrub
scrub/early successional habitat and the on-site grass/open field habitats would convert to a mowed
grass habitat under the CIP alternative, or regenerate to forest under the Removal alternative. Off-
site forest habitats that are impacted were assumed to reach a similar level of service value as their
pre -impact condition.
A similar process of calculating the projected changes in the flow of terrestrial ecological service
value was conducted for all four sites adjusting for the timing of implementation and the projected
level of impact to the habitat.
Wetland and surface water habitat was evaluated by projecting the change in the current condition
of the wetland and surface water habitat (the baseline). It was assumed that implementation of both
the CIP and Removal alternatives would result in a 100% (complete) loss of both the wetland and
surface water habitat on-site.
Appendix E — Ecological Habitat Service Analysis E-12 September 30, 2016

EPS
100
Ln 00—
(U 00*00
v
•� 75
N On-site baseline value (34.2 acres) 591 dSAYs
N
M 50 Current age
of tree Baseline forest ecological
O stands
O services projected into future
U
w 25
4-
L
O
0 12016 12216 50 100 150 200 250
Years
Figure E7. Ecological service flow framework used as a standard to evaluate service flow
changes on forest habitats at the Allen Steam Station — depicts baseline of ecological
service flows projected into the future.
My general assumptions for estimating the change in ecological service values for both the
terrestrial and aquatic habitats, given the CIP and Removal alternatives and their on-site and off-
site impacts, is detailed in Table E2 on the following page.
Appendix E — Ecological Habitat Service Analysis E-13 September 30, 2016

EPS.
Table E2. General assumptions used in evaluating changes in habitat values between
alternatives.
There are many factors that can influence the staging and timing of the construction work that would be required for the
implementation of the CIP and Removal alternatives at a site. These factors include: weather conditions, contractor availability,
economics, material availability, permitting, community acceptance, etc. As such, the habitat values (i.e., dSAYs) represented
are based upon general assumptions with the recognition that site specific conditions and influencing factors will dictate the
1
ultimate staging and timing of the actions associated with alternative implementation. The general assumptions were kept
consistent between the alternatives where applicable for the purposes of providing a comparison of the alternatives. The
ecological habitat estimates are approximate and not intended to be exact, but are robust enough to identify impacts and
evaluate and compare the alternatives with a reasonable degree of certainty.
2
The time frames for project implementation and completion are based upon the information presented in Appendix A.
The flow of ecological service value is consistent with the above -ground biomass of the terrestrial habitats and increases as the
3
terrestrial system moves through successional stages. That is, as the vertical structure and complexity of the terrestrial
vegetation increases, so does the ecological habitat service value.
4
Current on-site and off-site forest habitats were assumed to be 25 years of age.
5
Current scrub scrub habitats were assumed to be 5 years of age.
For both the removal and CIP alternatives, on-site habitat impacts to each terrestrial habitat type were assumed to initiate
upon implementation of the field construction activities and be completed in the first year of construction. With the CIP
6
alternative, the impacted terrestrial habitat area would eventually be converted to a mowed grass cover. With the Removal
alternative, those same impacted habitat areas would eventually be managed to encourage regrowth of forest habitat, that
would occur once the removal action was complete in that area and the work area developed to final grade.
For both the CIP and Removal alternatives, 100% of the on-site wetland and surface water habitat services would be lost over a
7
3 year period (linear) starting with initiation of construction as water is drawn out of the basin(s) to allow for capping,
Removal, and water management.
8
A 3% discount rate was used in calculating habitat values.
The Removal alternative necessitates the development of a new offsite landfill to store the removed ash. It was assumed that
9
the area where the offsite landfill would be placed would be a forest habitat. This forest habitat would be lost into perpetuity
and converted to a mowed grass cover upon completion of the landfill.
In addition, an off-site borrow area would be required to provide material for the new landfill under the Removal alternative as
10
well as for the CIP alternative.
Offsite areas serving as either borrow or landfill area were assumed to be forest habitat. This assumption was based on the
"Letter Reports" prepared by Amec Foster Wheeler for each of the sites, where they show the vast majority of potentially
11
suitable sites for landfill and borrow areas involved land that is presently forested (Amec Foster Wheeler 2015a, 2015b, 2015c,
and 2015d).
On -Site Habitat Conversion: Conversion of both the terrestrial and wetland areas onsite would be staggered with recovery of
12
50% of the area initiating at 50% project completion, regardless whether CIP or Removal alternative. The remaining 50% of the
area would initiate recovery at project completion, regardless whether the CIP or Removal alternative.
On -Site Habitat Conversion: All wetland and surface water impacted habitats currently on-site will be lost into perpetuity
13
(converted to either grass or forest).
The on-site CIP and offsite landfill cap areas result in a mowed grass cover. It was assumed that newly planted grass (cap cover)
would mature in a linear fashion over 5 years, starting once the cap was complete, and reach a maximum service value of 10%
14
(and continue at this rate into perpetuity). That is, mature grass habitat was assumed to generate 1/10 the value of the forest
habitat at maximum value at maturity.
Existing mowed grass habitats currently provide a constant 10% service value (as compared to the maximum forest habitat
15
value at maturity.
Offsite forest habitat removal at the new off-site landfill location will occur to 50% of the acreage during the first year of
construction for the Removal alternative. Subequently, the remaining 50% of forest will be removed halfway through the
16
projected project duration. Grass cap regeneration of the area where 50% of forest was initially removed for the landfill will
initiate halfway through project completion with the remaining 50% initiating recovery at project completion.
Offsite removal of forest at the borrow area location for the Removal alternative would occur at the following rate: 10% would
be removed upon project initiation, 45% would be removed at 40% completion and the remaining 45% of the acreage would
17
be removed at the 80% completion stage. Forest regeneration of these areas would occur with 50% of the impacted acreage
initiating at 50% project completion and the remaining 50% of impacted acreage initiating recovery at project completion.
Offsite forest habitat removal at the borrow area location will occur to 50% of the acreage during the first year of construction
for the CIP alternative. Subequently, the remaining 50% of forest will be removed halfway through the projected project
18
duration. Forest regeneration of the area where 50% of forest was initially removed for the landfill will initiate halfway through
project completion with the remaining 50% initiating recovery at project completion.
Appendix E — Ecological Habitat Service Analysis E-14 September 30, 2016

0
E1.2.3 Ecological Habitat Service Analysis Results
The approach taken in my analysis was developed to approximate the relative change in ecosystem
service value from one alternative to another, for the general categories evaluated based upon
similar assumptions where applicable. The dSAY calculations are approximate values and not
intended to be exact, but robust enough to identify and understand potential impacts and compare
between the alternatives.
The detailed results of the analysis, by site and remedial alternative, are presented in Table E3.
Forest, scrub shrub/early successional, and grass habitat values (terrestrial habitats) were combined
and presented in Table E3. The forest and scrub shrub/early successional habitats fall along the
same successional curve, and grass habitats were quality adjusted to the forest and scrub
shrub/early successional habitats, as such, their dSAY values are directly comparable given the
assumptions made.
For my analysis, I calculated the wetland/surface water values separate within the table. However,
since all of the wetland and surface water features will be lost as a result of both the CIP and
Removal alternatives, these areas will be subsequently converted to either mowed grass (CIP
alternative) or forest (Removal alternative).
It should be recognized that ecological habitat service values (i.e., dSAYs) between different
habitat types (e.g., wetlands and forest) may not be equivalent. Thus, care must be taken when
combining dSAYs between different habitat types. A recent study of the ecosystem service values
between various ecological biomes indicates that wetlands are significantly more valuable than
temperate forest/woodlands (estimates ranged from about 11-15 times more valuable, based on
median values) (de Groot et al. 2012). That same study also indicated that lakes and river habitats
were more valuable than temperate forest/woodland habitat (estimates ranged from about 2.6 — 3.5
times more valuable, based on median values). Wetland habitat was about 4 times more valuable
when compared to lake and river habitats in the de Groot study (2012).
In order to put the dSAY values into perspective, for a specific habitat such as a wetland or forest
functioning at 100% of its service value into perpetuity, 1 acre of that habitat is equivalent to about
34 dSAY's at a 3% discount rate. Therefore, one can infer the impact of the lost dSAYs, for each
habitat type at each site by dividing the total lost dSAYs for that site by 34.2. In addition, for the
purposes of comparing the change in value between the CIP and Removal alternatives, I set the
wetland/surface water dSAY value to be equivalent to the dSAY value of the existing forest habitat
value. This is a conservative estimate (i.e., underestimates the true impacts of both the CIP and
Removal alternatives) since the wetland/surface area ecological service value is higher than the
forest ecological service value.
As such and as presented in Table E3, the CIP and Removal alternatives each would result, given
the calculations herein, in the permanent removal of about 466 and 508 acres of old growth climax
forest habitat value into perpetuity, respectively. Based on the conservatism in the analysis, these
losses are likely higher.
Appendix E — Ecological Habitat Service Analysis E-15 September 30, 2016

Table E3. Summary of ecological habitat service values between alternatives by site, habitat type, and on-site
versus off-site impacts.
ONSITE LOSSES and GAINS
Allen
Buck
Cliffside
Mayo
Habitat Type by Site
Acres
dSAYs
Acres
dSAYs
Acres
dSAYs
Acres
dSAYs
ONSITE LOSSES
Terrestrial
Early Successional/Scrub
85
(981)
52
(600)
42
(485)
42
(489)
Forest
34
(591)
36
(629)
25
(434)
11
(190)
Mowed -Grass
88
(300)
34
(117)
52
(176)
14
(48)
Terrestrial Total
207
(1,872)
123
(1,346)
119
(1,096)
67
(727)
Wetland and Surface Water
98
(3,212)
65
(2,114)
45
(1,460)
79
(2,595)
Total Losses Onsite
(5,084)
(3,460)
(2,556)
(3,323)
ONSITE GAINS
Terrestrial
Cap -in -Place (CIP) - Grass Cap
305
863
187
561
163
489
147
441
Full Removal Alternative (Removal) - Forest Regeneration
305
1,441
187
1,534
163
1,210
147
1,155
NET ONSITE LOSSES
CIP - Net On -Site dSAY Loss 1
(4,222)
(2,899)
(2,067)
(2,882)
Removal - Net On -Site dSAY Loss 1
(3,643)
(1,926)
(1,347)
(2,168)
Total Acreage of Onsite Habitats Evaluated
305
187
163
147
OFFSITE LOSSES AND GAINS
Allen
Buck
Cliffside
Mayo
Habitat Type by Site
Acres
dSAYs
Acres
dSAYs
Acres
dSAYs
Acres
dSAYs
Terrestrial
OFFSITE LOSSES
CIP - Borrow Area - Forest
190
(3,195)
110
(1,877)
115
(1,962)
94
(1,604)
Removal - Borrow Area - Forest
93
(953)
35
(531)
47
(661)
41
(355)
Removal - Offsite Landfill Location
225
(3,122)
94
(1,536)
121
(1,924)
108
(1,717)
OFFSITE GAINS
CIP - Borrow Area - Forest Regeneration
190
1,727
110
1,045
115
1,093
94
893
Removal - Borrow Area - Forest Regeneration
93
439
35
287
47
349
41
322
Removal -Offsite Landfill Location (Grass Cap)
225
333
94
240
121
280
108
264
NET OFFSITE LOSSES
CIP - Net Off -Site Net Loss
(1,468)
(832)
(869)
(711)
Removal - Net Off -Site Net Loss
(3,303)
(1,540)
(1,956)
(1,485)
CIP -Total Acreage of Offsite Habitats Evaluated
190
110
115
94
Removal - Total Acreage of Offsite Habitats Evaluated
319
129
168
149
CIP - Total Acreage Evaluated495
297
278
241
Removal -Total Acreage Evaluated
624
316
331
296
NET LOSSES - TERRESTRIAL AND WETLAND/SURFACE WATER
CIP - Total Net Terrestrial Losses
(2,477)
(1,617)
(1,476)
(997)
CIP - Total Net Wetland/Surface Water Losses
(3,212)
(2,114)
(1,460)
1
(2,595)
Removal -Total Net Terrestrial Losses
(3,735)
(1,352)
(1,842)
(1,058)
Removal -Total Net Wetland/Surface Water Losses
(3,212)
(2,114)
(1,460)
(2,595)
OVERALL NET LOSSES
CIP - Overall Net cISAY Loss Z
(5,690)
(3,730)
(2,936)
(3,592)
Removal - Overall Net cISAY LOSS Z
(6,947)
(3,466)
(3,303)
(3,654)
PUTTING LOSSES IN PERSPECTIVE
Cap -in -Place (CIP) - Overall - Acres of Fully Functioning Climax
Forest that would be Lost into Perpetuity Z (minimum)
166
109
86
105
Full Removal - Overall - Acres of Fully Functioning Climax Forest
that would be Lost into Perpetuity 2 (minimum)
203
101
97
107
'Assumes that onsite habitats are affected similarly at initiation of the construction for both the Cap -in -Place and Removal alternatives.
2Assumes that the wetland and terrestrial dSAYs are equivalent, an assumption that underestimates ecological losses. Wetlands and surface water can be 10-20 times the value of
forest habitat (de Groot et al. 2012).
Appendix E - Ecological Habitat Service Analysis E-16 September 30, 2016

J�K
E2 HUMAN RECREATIONAL SERVICES
For this evaluation, since the sites are retained under private property, human recreational on-site
services were not considered. However, it should be recognized that game land areas can provide
significant human use value. In addition, as no off-site impacts were identified, off-site human
recreational service values were not evaluated.
Appendix E — Ecological Habitat Service Analysis E-17 September 30, 2016

0
E3 REFERENCES
Amec Foster Wheeler, 2015a. Letter Report — Waste Strategy Analysis (Revised) Allen Steam
Station. Prepared for Duke Energy April 9, 2015.
Amec Foster Wheeler, 2015b. Letter Report — Waste Strategy Analysis (Revised) Buck Steam
Station. Prepared for Duke Energy January 26, 2015.
Amec Foster Wheeler, 2015c. Letter Report — Waste Strategy Analysis, Cliffside Steam Station.
Prepared for Duke Energy April 17, 2015.
Amec Foster Wheeler, 2015d. Letter Report — Waste Strategy Analysis, Mayo Steam Station.
Prepared for Duke Energy March 31, 2015.
de Groot, R., Brander, L., van der Ploeg, S., Costanza, R., Bernard, F., Braat, L., Christie, M.,
Crossman, N., Ghermandi, A., Hein, L., Hussain, S., Kumar, P., McVittie, A., Portela, R.,
Rodriguez, L.C., ten Brink, P., van Beukering, P., 2012. Global estimates of the value of
ecosystems and their services in monetary units. Ecosyst. Serv. 1, 50-61.
Envirosci. 2008. Web Accessed June 23, 2016. http://envirosci.net/111/succession/succession.htm
Gibson, L., Lee, T., Koh, L., Brook, B., Gardner, T., Barlow, J., Peres, C., Bradshaw, C., Laurence,
W., Lovejoy, T. and Sodhi, N.S. 2011. Primary forests are irreplaceable for sustaining
tropical biodiversity. Nature 478: 378-381.
Greenpeace. Web Accessed June 23, 2016.
http://www. rg eenpeace.org/international/en/cainpaigns/forests/solutions/
Johnson C., Zarin D., and A. Johnson. 2000. Post -disturbance aboveground biomass accumulation
in global secondary forests. Ecology 81:1395-1401.
Law, B., Thornton, J., Anthoni, P. and S. Van Tuyl. 2001. Carbon storage and fluxes in ponderosa
pine forests at different developmental stages. Global Change Biology. 7, pp. 755-777
McMahon, S. M., Parker, G. G., and Miller, D. R. 2010. Evidence for a recent increase in forest
growth. PNAS, Edited by William H. Schlesinger, Institute of Ecosystem Studies,
Millbrook, NY, February 23, 2010, Vol. 107, No. 8, 3611-3615.
Millennium Ecosystem Assessment. Ecosystems and Human Well-being: Full Report; Island
Press: Washington, DC, USA, 2005.
Nicolette, J., Burr, S., and Rockel, M. 2013. A Practical Approach for Demonstrating
Environmental Sustainability and Stewardship through a Net Ecosystem Service Analysis.
Sustainability 2013, 5, 2152-2177; doi:10.3390/su5052152, Published May 10, 2013.
Appendix E — Ecological Habitat Service Analysis E-18 September 30, 2016

m
Parrotta, J. 2012. Understanding Relationships between Biodiversity, Carbon, Forests and People:
The Key to Achieving REDD+ Objectives. A Global Assessment Report. Prepared by the
Global Forest Expert Panel on Biodiversity, Forest Management, and REDD+. Wildburger
& Stephanie Mansourian (eds.) IUFRO World Series Volume 31. Vienna. 161 p. ISBN
978-3-902762-17-7, ISSN 1016-3263
Thompson, I.D., Mackey, B., McNulty, S. and Mosseler, A., 2009. Forest resilience, biodiversity,
and climate change. A synthesis of the biodiversity/resilience/stability relationship in forest
ecosystems. Technical Series no. 43. Montreal: Secretariat of the Convention on Biological
Diversity.
United States 1997. United States v. Melvin Fisher. United States District Court for the Southern
District of Florida, Key West Division Case Numbers 92-10027-CIV-DAVIS, and 95-
10051-CIV-DAVIS. Decided 30 July 1997, Filed 30 July 1997. 977 F. Supp. 1193; 1997
U.S. Dist. LEXIS 16767.
United States 2001. United States of America and Internal Improvement Trust Fund v. Great Lakes
Dredge and Dock Company. United States District Court for the Southern District of
Florida D. C. Docket No. 97 -02510 -CV -EBD.
Verschuyl, J., Hansen, A., McWethy, D., Sallabanks, R., and R. Hutto. 2008. Is the effect of forest
structure on bird diversity modified by forest productivity? Ecological Applications, 18(5),
pp. 1155-1170.
Appendix E — Ecological Habitat Service Analysis E-19 September 30, 2016

0
APPENDIX F
Joseph Nicolette CV
Appendix F — Joseph Nicolette CV F-1

Joseph Nicolette
Fields of Competence
Risk management and net environmental benefit
analysis (NEBA)
Natural resource damage assessment (NRDA)
Ecosystem service valuation
Site remediation alternatives analysis
Ecological and human health risk assessment evaluation
CERCLA project coordination
Oil spill response and planning
Aquatic ecology
Experience Summary
Expertise: Joseph Nicolette has over 30 years of
experience in the environmental consulting field with a
focus on NRDA, NEBA, ecosystem service valuation,
site risk management, remediation alternatives analysis,
project coordination and agency relations, and aquatic
ecology. He is a Senior Principal and Ecosystem
Services Practice Leader at Environmental Planning
Specialists, Inc. (EPS).
Joe has made demonstrated contributions both nationally
and internationally in developing what is known as the
net environmental benefits analysis (NEBA) or net
ecosystem service analysis (MESA) approaches. He co-
authored the first formalized NEBA framework
recognized by the United States Environmental
Protection Agency (USEPA), the USEPA Science
Advisory Board (USEPA SAB), the National Oceanic
and Atmospheric Administration (NOAA). Joe has
focused on NEBA applications to site risk management
and decision-making, incorporating ecosystem service
valuation, over the past 24 years.
He provides strategic advice and oversight for projects
to help balance the risks, benefits and tradeoffs
associated with competing alternatives (e.g., remediation
actions, mitigation and restoration, oil spill response, site
restoration, and decommissioning actions). He has
contributed to multiple environmental assessments
associated with oil and chemical releases, and has
managed NEBA, NRDA and CERCLA issues on behalf
of the responsible party. His role has been to provide
technical direction and assist the client in coordination
with Natural Resource Trustee Agencies (State and
Federal), the United States Environmental Protection
Agency (USEPA), state agencies, and other stakeholders
in the risk management and NRDA processes.
Joseph has participated in NRDA projects since 1990.
He is recognized for his NRDA experience and role in
pioneering NRDA injury and restoration ecological
Appendix F - Joseph Nicolette CV
economics approaches such as habitat equivalency
analysis (HEA). He has been involved in the conduct of
impact assessments for over 50 hazardous releases and
has led projects on behalf of the client, including agency
negotiations. These include assessments associated with
oil and chemical releases (including petroleum products,
PCB's, DDT, dioxin, metals, etc.) and damage
assessments associated with releases under US NRDA
regulations and the EU Environmental Liabilities
Directive (ELD). He has contributed to multiple
environmental assessments associated with oil releases
from the Exxon Valdez up to and including the
Deepwater Horizon Incident. Mr. Nicolette has managed
over 50 NRDA related projects. His services include
client strategy development regarding natural resource
injury and environmental assessment; ecological and
human health risk characterization; mitigation and
remedial planning, restoration valuation and planning,
allocation modeling, agency negotiations, technical
assessment design, and technical data review,
assessment, and interpretation.
Joseph has also worked with several law firms to provide
expert witness and litigation support for multiple NRDA
related environmental cases. He has provided written
affidavits to support his technical findings and provided
testimony through deposition by the Department of
Justice.
He has also served as the Project Coordinator and/or risk
management lead on behalf of the responsible party at
multiple Superfund (CERCLA) sites. He has experience
with sites in EPA Regions 2, 3, 4, 5, 6, 8 and 10. These
sites were primarily related to polychlorinated biphenyls
(PCBs), metals, dioxin, and TCE releases to a variety of
media such as soil, sediment, surface water and
groundwater. These projects involved the assessment of
ecological and human health risks and the feasibility of
various remedies to manage potential risks.
Mr. Nicolette has also provided PRP identification and
remedial/NKDA liability allocation support for
industrial clients. He has developed and reviewed
allocation models for specific sites, determining
estimates of the portion of remedial and NKDA liability
associated with various PRP's at the site.
Joseph is also trained in hierarchical relational scientific
database design, structuring and management.
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Joseph Nicolette
Credentials
M.S. Fisheries Management, 1983. University of
Minnesota - related fields: statistics, computer
applications, and aquatic invertebrates
B.S. Environmental Resources Management, 1980.
Pennsylvania State University
Certifications
Certified Fisheries Scientist, no. 2,042, since 1992
Career
2016 -Present
Senior Principal and Ecosystem Service Practice
Director
Joes role is to provide strategic consultation for projects
directed at managing client environmental liabilities
(e.g., NEBA, NRDA, oil spill response, offshore
decommissioning, remediation, risk management) and
assets, including natural resource valuations of land
parcels.
2009-2016
Principal, Global Ecosystem Services Director,
Ramboll Environ
Provided strategic consultation for projects directed at
managing client environmental liabilities (e.g., NEBA,
NRDA, oil spill response, offshore decommissioning,
remediation, risk management) and assets, including
natural resource valuations of land parcels.
1999-2009
Vice President, Natural Resource Liability and Asset
Management, C112M HILL
Provided strategic consultation for projects
directed at managing client environmental
liabilities (e.g., NEBA, NRDA, oil spill response,
offshore decommissioning, remediation, risk
management) and assets, including natural
resource valuations of land parcels.
1998-1999
President, Nicolette Environmental, Inc.
NRDA Project Strategy, Management, and
Negotiations
Appendix F - Joseph Nicolette CV
1990-1998
Senior Consultant, ENTRIX Inc.
Oil Spill Response and Damage Assessment Advisor
1984-1990
Operations Supervisor, Adirondack lakes Survey
Corporation Oversight of field operations, data
management, and QA/QC
1983-84
North Carolina State University
Acid Deposition Program. Database Manager.
Developed the Fish Information Network as part of acid
deposition studies in the United States.
Professional Affiliations
USGS sponsored ACES (a community of ecosystem
services) — Steering/Planning Committees 2008 -present
Net Environmental Benefits Analysis
Joe's contributions to the development of NEBA
approaches, aside from co-authoring the first
formalized NEBA framework, includes the conduct of
national and international presentations and workshops
(Brazil, Canada, Germany, Great Britain, Italy,
Malaysia, Norway, Scotland, South Africa, Sweden,
Thailand, United States, etc.) related to ecosystem
service valuation, benefits assessment (i.e., NEBA),
risk management, project development, resource
equivalency, oil spill response and planning, site
remediation and damage assessment.
Joes success in this area also includes:
✓ Recognition of, and incorporation of the formalized
NEBA framework by the USEPA in a report by the
USEPA Science Advisory Report entitled "Valuing
the Protection of Ecological Systems and
Services", (2009).
✓ A chapter regarding NEBA that was integrated into
Interstate Technical Regulatory Council Guidance
(2006).
✓ Pilot studies evaluating appropriate metrics for
NEBA for site cleanup, restoration, and
remediation on behalf of the US Environmental
Protection Agency (2008).
✓ Guidance for the London Energy Institute (2009
and 2010, London) on the Environmental Liability
Directive and on establishing ecological baselines
F, D

N
N
I
Joseph Nicolette
(pre -incident) using NEBA concepts.
NEBA support for the Oil and Gas Producers
(2015-2016) (OGP) Joint Industry Group (JIP)
related to oil spill response and planning in the
Arctic.
He was the lead author of a book chapter
(published in March of 2013 by the Oxford Press)
that provided an overview of the U.S. natural
resource damage assessment regulations and the
development of resource equivalency analysis
approaches. The book was entitled "The E.U.
Liability Directive: A Commentary". He led
Chapter 9 that was entitled "Experience with
Restoration of Environmental Damage". The
chapter also discusses the similarities and
differences of the U.S. NRDA rules in relation to
the ELD.
Led the first NEBA studies for decommissioning of
offshore oil and gas platforms in Australia and the
North Sea (2014 -Present).
Multiple published papers and reports related to
NEBA and ecosystem service valuation.
Multiple client projects using NEBA and
ecosystem service valuation approaches to address
remedial risk issues and manage costs
Joseph has served on the Planning and Steering
committees for the ACES Conferences (A
Community of Ecosystem Services), working with
the United States Geological Survey Conference
leaders since 2008.
Participated in the conduct of numerous
environmental assessments associated with the
development of restoration and remedial decisions.
This includes the ecosystem service valuation of
compensatory restoration projects related to NRDA
or other resolutions.
Example Projects
Armstrong World Industries CERCLA OU -1 Site,
Macon, Georgia. Joe served as the EPA Project
Coordinator on behalf of AWI and provided oversight of
Operable Unit 1 (OU -1) evaluations, including the
development of the environmental engineering/cost
analysis (EE/CA), remedial design/remedial action, Post -
Closure, NRDA/NEBA considerations, and supporting
field sampling. He assisted in negotiations with the
USEPA and State agencies and coordinated OU -1
CERCLA activities, on behalf of AWI, with the USEPA
and GAEPD. The primary contaminant of concern was
PCBs. He provided oversight of the site characterization
efforts including the development of study plans, the
Appendix F - Joseph Nicolette CV
ecological and human health risk assessments, and the site
remedy with a focus on the managing potential PCB risks.
BP Deepwater Horizon. Joe served as a Project Technical
Lead related to selected damage assessment (NRDA)
issues associated with the Deepwater Horizon Gulf of
Mexico oil release.
Crab Orchard National Wildlife Refuge, PCB
CERCLA/NRDA Site, Marion, Illinois. Joe led PCB site
characterization, remedial alternatives analysis through
NEBA, remediation implementation, and NRDA liability
management). Joseph served as the CERCLA Project
Coordinator jointly working with two PRP's
(Schlumberger and the USFWS). He helped negotiate
environmental remedial and NRDA associated liabilities
related to historical PCB releases at the site. In serving as
the Project Coordinator, he coordinated closely with the
federal (USFWS, USEPA) and state (IL DNR, IL EPA)
regulatory agencies. This was a unique case in that the
USFWS was a PRP and at the same time, a trustee for
natural resources. Innovative risk management data
collection and analysis approaches were used to support
risk management decision-making and included
incremental sampling study design and surface weighted
area concentration (SWAG) analysis A NEBA-based
approach using resource equivalency analysis was used as
part of the remedial and damage assessment resolution,
saving the client over $10 million dollars.
Edwards Air Force Base (EAFB) and NASA CERCLA
Site, California. NRDA and remedial NEBA
negotiations. Joe provided NRDA and remedial NEBA
support to EAFB as the responsible party at this site.
Joseph developed an overarching CERCLA NRDA and
NEBA strategy to EAFB and participated in agency
negotiations. Major issues were related to groundwater
and surface soil contamination. A NEBA was used to
demonstrate that the presumptive pump and treat remedy
would provide no net benefit to the public. A less
intrusive NINA alternative was instituted and reduced
project costs by $65 million.
USEPA OSWER NEBA Studies, Colorado and Florida
Joe served as the Principle Investigator for a project
evaluating the metrics that can be used to evaluate changes
in ecosystem services associated with site remediation and
local development. This work was conducted for the
F. D

Joseph Nicolette
USEPA OSWER group as it relates to evaluating the net
environmental benefit (NEBA) associated with remedial
actions at superfund sites. The USEPA was evaluating the
use of NEBA to help demonstrate the benefits and
environmental stewardship associated with site
remediation and in the selection of site management
alternatives. These studies were conducted for the USEPA
at Rocky Mountain Arsenal, Colorado, and Homestead
AFB, Florida. This project was directed at a "real world"
evaluation of metrics that can be used to evaluate changes
in ecosystem service values associated with site cleanup
decision making. This project was titled "Demonstrating
the Net Environmental Benefit of Site Cleanup; An
Evaluation of Ecological and Economic Metrics at Two
Superfund Sites" was conducted for the USEPA
Superfund group as it relates to evaluating the net
environmental benefit associated with remedial actions at
Superfund sites and appropriate metrics. This work was
developed to be consistent with the Millennium
Assessment ecological service categorization.
Texas: For Region 6 USEPA, Joe supported the conduct
of NEBAs to evaluate remedial alternatives at two
orphan sites in Texas. The NEBAs were used to
demonstrate the benefitslimpacts associated with
remediation. These are described below.
NEBA for USEPA: Jasper Creosoting Company
Superfund Site, Texas: An ecological risk assessment
(ERA) for a wetland indicated low to medium risks
for benthic invertebrates and a subset of upper trophic
level receptors associated with exposure to dioxin and
polycyclic aromatic hydrocarbons in sediment. Joe
supported the development of a NEBA for USEPA
Region 6 to quantify the net present value of the
ecological services associated with no further action
and six remedial alternatives involving monitoring,
phytoremediation and combinations of full removal,
partial removal and wetland enhancement. The
NEBA demonstrated that monitored natural
attenuation coupled with phytoremediation would
provide the greatest net environmental benefit at the
least cost and decrease ecological risks over time. The
cost of this alternative was estimated to be more than
$2 million less than the most intrusive remedy.
Appendix F - Joseph Nicolette CV
NEBA for USEPA: State Marine Superfund Site,
Texas: Joe supported the development of a NEBA for
the USEPA to evaluate remedial alternatives for
marginal ecological risks to benthic invertebrates
identified in intertidal sediments. The baseline level
of ecological service associated with no further action
and monitored natural attenuation was evaluated as
well as the net change in ecological services that
would be expected with a sediment removal action.
The NEBA results indicated that the loss of
ecological services associated with no further action
would be minor, if injury was occurring, and that the
intrusive remedy would create a greater net
ecological service loss because of impacts to habitat.
In this case, no further action was selected as the
preferred alternative as the NEBA demonstrated that
expenditure of more than $6 million on sediment
removal would not be protective of the environment.
Army Base Realignment and Closure (BRAC) Strategy
Studies Joe served as the Principal Investigator for the
U.S. Department of the Army of four studies designed to
understand site development and reuse strategies and
integration of natural resource values to maximize the
benefits associated with site natural resources and
remedial strategies. For these studies, potential site
remedial alternatives were evaluated in conjunction with
potential reuse scenarios to reflect the interdependencies
between remediation and property reuse. The goal for
each site was to identify the combination of remedial
action and re -use that would provide for the protection of
human health and the environment while providing the
greatest net ecological and human use value. This series
of studies conducted over two years and included the
following four Army BRAC sites: Camp Bonneville,
Washington; Savanna Army Depot, Illinois; Fort Ord,
California; and Fort McClellan, Alabama. The
Department of the Army used the information from these
analyses to develop preferred land management and
remedial actions for each site that minimize remedial costs
while maximizing natural resource values to the public.
Passaic River, New Jersey. Joe developed a preliminary
example NEBA evaluation for Passaic River remedial
alternatives (large scale sediment dredging) as proposed
by the USEPA. The overall goal was to demonstrate the
F, D

Joseph Nicolette
environmental and human health cost/benefit of proposed
intrusive remediation.
Tennessee EIS Support Eco Asset Valuation:
Comparing Economic Development and Conservation
of over 300 Land Parcels
Joe was the technical lead for a land eco -valuation project
for a confidential client. In partnership with the client's
Resource Stewardship Division, Joseph led a Land
Valuation Pilot for 14,000 acres that surrounded a
reservoir in Tennessee. This project was conducted as a
NEBA in support of the client's NEPA documentation
(e.g., supporting the preferred alternative) that will drive
the management of properties surrounding the reservoir.
As part of this work, he evaluated and compared the
environmental (e.g., natural resource) value and real estate
(e.g., "highest and best" land use) value associated with
the parcels located within the project area given the three
proposed land use alternative scenarios (e.g. no -action,
balanced conservation and recreation, and balanced
development and recreation). This analysis resulted in the
development of a 4th preferred alternative that maximized
ecosystem service values (ecological and human use) back
to the public.
Brownfield Site NEBA Options Analysis. Joe provided
oversight of the incorporation of a NEBA framework for
a large brownfield site. He collaboratively worked with
the City of Milwaukee, the public, regulatory agencies and
prospective developers as part of the City of Milwaukee's
Menomonee Valley Industrial Center Redevelopment
Program to create a sustainability -focused brownfield's
success. Through the use of a NEBA framework, he was
able to evaluate the development plans for the Brownfield
site and modify/tweak the designs to maximize ecological
and human use values to the public. We were able to
demonstrate that the revised plan for site restoration and
remediation activities created ecological, recreational and
aesthetic creation/enhancement benefits estimated at over
$120MM of value to the public. In addition, the NEBA
also assisted in identifying over $25MM in value -
engineered cost savings and new-found revenue streams
from the beneficial re -use of materials.
NEBA for PCB Related Dam Removal at Lake Hartwell,
South Carolina. Joe assisted a client in evaluation of the
ecological impacts associated with the removal of two
Appendix F - Joseph Nicolette CV
dams in South Carolina. The dam removals were being
conducted as part of an NRDA settlement associated with
PCB releases. Joe evaluated ongoing fish tissue PCB
concentrations associated with MMA activities.
Lower Passaic River, PRP Group NRDA Negotiations
and Strategy Advisement, New Jersey. Joe supported a
group of Cooperating PRP's in developing a strategy and
negotiating with the State and federal trustees regarding
the Lower Passaic River NRDA. Joseph directly
interfaced with the Companies and the State and federal
Trustees. His role was to assist the PRP's in developing a
strategy to manage their NRDA liability at the site. He
assisted with conducting preliminary evaluations of
ecological and human use injury and compensatory
restoration project identification.
LCP CERCLA Site, Brunswick, Georgia, PCB releases.
Joe provided remedial NEBA analysis and NRDA support
associated with PCB releases for a client in Brunswick,
GA. His role was to evaluate ecological risk data for the
purposes of integrating select areas of the estuary into a
NEBA sediment management approach. In addition, he
also evaluated injury assessment data and developed
potential compensatory restoration options as part of this
project. He participated in agency meetings and
discussions regarding remedial and NRDA issues.
Delaware River, Pennsylvania, PCBs. Joe supported a
PRP on ecological risk and NRDA issues associated with
historical PCB releases at the Metals Bank site.
Specifically, he evaluated potential impacts of PCBs on
aquatic invertebrates, fish, and birds. A resource
equivalency analysis approach was used as part of the
damage assessment. Joe evaluated agency impact analyses
and developed appropriate compensatory restoration.
Kalamazoo River, Michigan, PCBs. Joe assisted a client
on the Kalamazoo River in the evaluation of historical
PCB concentrations, potential impacts to fish and
terrestrial biota, development of appropriate SWAC
concentrations, and remedial alternative evaluations. Joe
evaluated fish tissue PCB concentrations and examined
trends of PCBs in fish along the river.
Sediment PCB Remedial NEBA Evaluation.
Confidential Client, Portland, Oregon. Joe provided
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Joseph Nicolette
technical and strategic support to a client on the
Willamette River to settle its NRDA mitigation liability.
Wisconsin Tissue, Fox River PCBs. Joe provided
technical and strategic advice to Wisconsin Tissue
regarding the Fox River NRDA and participated in trustee
negotiations on behalf of Wisconsin Tissue.
Confidential Client, Calumet River CERCLA,
Allocation, Remedial, and NADA Support. Joe
represented a potentially responsible party (PRP) with
remedial and NRDA liabilities associated with historical
PCBs, metals, etc. releases. In this context, Joe reviewed
allocation issues, HEA model runs, sediment ecological
and water toxicity data, and sediment and water column
concentration data to assist the client in responding to
demands of the natural resource trustees and other PRPs.
Allocation Modeling. Confidential Clients, New York,
New Jersey, and Indiana: Joe has provided PRP
identification and remedial liability allocation support for
two major industrial clients in the states of New York,
New Jersey, and Indiana. The overall purpose of these
projects was to identify potential PRPs and rank them by
estimated contribution in relation to one another. Based
upon the information gathered during this work (e.g.,
volumes released, parameter toxicity, geographic
location), supported the development of allocation models
and the approach for determining estimates of the portion
of remedial liability associated with each PRP.
Colonial Pipeline Company. Senior NRDA Advisor
(1993 -Present). Oil spill response, planning and
assessment. Joe's responsibilities included overall project
management (of oil release impact assessments, including
participation in company planning and drills) for Colonial
from a technical and administrative aspect, including
project strategy, coordination with the governmental
regulatory agencies, management of contractors, cost
control and management, task management, field study
coordination, risk management, technical expertise, and
report generation. In addition, he provides overall
management and oversight of necessary compensatory
restoration required as part of a spill settlement, if any.
Appendix F - Joseph Nicolette CV
Example emergency releases Joe has responded to and/or
provided expertise for environmental assessments include
the following:
o BP, Deepwater Horizon, Gulf of Mexico
o BP barge release, Elizabeth River, VA
o Sugarland Run, Potomac River
o Darling Creek, Louisiana
o Lookout Mountain, Tennessee
o Tennessee River/Goose Creek, Knoxville
o Reedy River, South Carolina
o San Jacinto River, Texas
o Pine Bend, Tennessee
o Simpsonville, South Carolina
o Sun Oil, barge release, Delaware River, DE
o Maritrans, tug barge release, Mississippi River, MN
o Amoco Pipeline, pipeline release, Whiting, Illinois
o Southern Pacific Railroad, tanker car (release of
metum sodium, Sacramento River, CA)
o Buckeye Pipeline release, Allegheny River, PA
o Buckeye Pipeline release, Quinnipiac River, CT
o EXXON, tanker, Prince William Sound, Valdez, AK
o Plantation Pipeline, pipeline release, Rich Fork, NC
o Plantation Pipeline, pipeline release, Ward Road, GA
o Conoco. Calcasieu Estuary, Louisiana
o Unocal, Guadalupe, CA
o Union Pacific Railroad, 7 train derailment releases,
UT, CO
o Petrobras, pipeline release, Brazil Rainforest
o CITGO, pipeline release, Texas
o Multiple smaller releases
Alabama, Marshall Space Flight Center. NRDA, NEBA,
and site remediation of groundwater contamination at
NASA Marshall Space Flight Center CERCLA Site in
Alabama. Joe was retained to provide oversight of a
NRDA for the NASA Marshall Space Flight Center in
Huntsville, Alabama. Joseph assisted in coordinating the
assessment with the natural resource trustees and provided
technical support for determining the potential levels of
injury and potential scale of compensatory restoration.
This project also entailed the use of NEBA to evaluate
potential remedial alternatives associated with the site.
D

Joseph Nicolette
Koch Site, Hastings, Minnesota Using natural resource
economics -based approaches, Joe supported an
assessment of the value to the public of converting a land
asset along the Mississippi River to a public recreational
use to obtain a consent decree, facilitate site closure, and
generate substantial goodwill with the public. The fair
market value of the property was $215,000 and the
recreational value, given the transfer scenario, was
approximately $30 million (see following press release).
"Plans Announced for Koch Riverfront Park; City to
Complete Bike Trail, Develop Park with Koch Petroleum
Group's Gift of Land, April 20, 2000 5:46 PM EDT
HASTINGS, Minn., April 20 /PRNewswire/ -- At a
ceremony held today on the west bank of the Mississippi
River, the City of Hastings and Koch Petroleum Group
unveiled a joint initiative to develop a bike trail and a
community park on riverfront property currently owned
by Koch. David Robertson, president of Koch Petroleum
Group, announced the company's donation of 43 acres of
Mississippi riverfront land to the city. Hastings Mayor
Mike Werner also announced that the city will name the
area Koch Riverfront Park. The announcement ceremony,
hosted by Werner and Robertson, was held at the
riverfront site immediately northwest of downtown
Hastings. "We sincerely hope that generations of area
families will enjoy the park, and that it will serve as a
gathering place that will connect community members to
each other and to the river, " said Robertson. The
appraised market value of the land is $215,000; its
potential recreation value to the public is estimated at $30
million based on a recent study... "
RMC, Troutdale Superfund Site, Oregon — CERCLA,
NEBA, CWA, NRDA. Joe provided strategic advice
regarding the evaluation of remediation options for
RMC's 16 -acre NPDES process water pond ("Company
Lake"). Regulatory agencies stated a desire to declare the
pond a Water of the State. Such a determination would
have eliminated RMC's ability to use the pond as part of
the plant's NPDES wastewater management system. This
would have required closing the plant or constructing a
replacement storm water treatment system. Joseph
supported a collaborative negotiation process that resulted
in integrating pond remediation, continued pond use for
NPDES purposes, plant storm water system upgrades, and
an informal settlement of NRD claims. Direct savings to
RMC in reduced project scope are estimated at more than
Appendix F - Joseph Nicolette CV
$1 million. Indirect savings associated with retaining use
of Company Lake are believed to exceed $10 million.
Land Transfer and Restoration Strategy, Confidential
Client, Utah Joe contributed to a study whose purpose was
to determine the status of real estate, contamination and
natural resource conditions for a large and complex
industrial site in Utah. This analysis served to develop a
path forward to demonstrate and maximize the value of a
site by integrating site cleanup with site reuse and future
development. This study considered and integrated
Property Reuse Alternatives, Alternative Remedial
Approaches, Natural Resource Assets, and Liability
Transfer Options. The results of the study provided the
high-level framework to establish a reasonable
performance target for the eventual reuse of the site and
helped the client to maximize the overall ecological and
human use values that the site could provide under various
reuse scenarios. For most large, complex sites there is an
initial degree of uncertainty associated with defining
environmental remediation and the potential impact on the
real estate and ecological assets of the site. The study
process was developed to establish high-level
opportunities for value enhancement through the
development of a proactive strategy to reduce this
uncertainty and effectively reposition the property for sale
and future site reuse. This study was a key step in the
process to ensure that the site is proactively repositioned,
sold and redeveloped. The study also reduced the
uncertainty associated with existing environmental
remediation and restoration and provides insight into the
environmental issues associated with site reuse.
Tactical Oil Response Plans. Joe has led the development
of tactical response plans for Colonial Pipeline for
multiple locations in the SE United States. These plans
have been developed with NEBA concepts in mind to
assist Colonial in managing response efforts in the event
of a release. Joe supports Colonial in annual spill drill
events. His role is to help Colonial Pipeline manage
environmental impacts and liabilities during an event,
including NEBA considerations in OSRP.
Pipeline Mitigation Projects Joe led a NEBA to evaluate
the mitigation requirements for a pipeline expansion
project in Louisiana. This project demonstrated that the
compensatory restoration was 60% less than that
F• D

Joseph Nicolette
requested by the USACE. This reduced the client project
costs substantially. The results were published in the Oil
and Gas Pipeline Magazine.
For the same client, Joe led a NEBA to evaluate the
mitigation requirements for a pipeline expansion project
in Texas. This project demonstrated that the compensatory
restoration was significantly less (greater than 50% less)
than what was estimated to be requested by the USACE.
This analysis incorporated the resource equivalency
approaches and consideration of socioeconomic benefits
Mitigation Bank Prospectus Development and Financial
Cash Flow Analysis For a confidential client, Joe led the
evaluation of the remedial liability and buffer land
wetland and stream mitigation banking value associated
with the clients property. Based on the evaluation,
ENVIRON staff calculated the credit values for both the
wetland and stream banking opportunities and developed
a mitigation bank prospectus that was negotiated with the
US Army Corps of Engineers. As with any mitigation
banking project, the primary uncertainties in determining
the cost and return of a project include: the quantity of
credits that can be realized, the market available for the
credits, the sale price of the credits and the cost of
restoration or creating the credits. Joe conducted an
analysis to understand the mitigation banking
uncertainties and minimize these uncertainties. A
financial cash flow analysis was conducted to bound the
project uncertainties.
The mitigation bank cash flow financial analysis was
conducted based upon our understanding of the credit
values, demand and potential site uplift (i.e., number of
credits to be allocated). This analysis provided our client
with the information necessary to evaluate the business
case for the bank as more refined information became
available. As such, it provided an "off ramp" should any
information arise that would make the mitigation bank
non -desirable from a financial perspective. The cash flow
analysis was a critical step to determine viability of the
project. The cost and returns were predicted under
conservative, likely and aggressive scenarios.
Confidential Railroad, Litigation Support (Utah,
Nevada, Colorado). Joe was retained by a major railroad
to support a major litigation case. Joe Nicolette served as
Appendix F - Joseph Nicolette CV
a technical expert for the railroad providing expertise
related to the environmental effects of chemical releases
to the environment (tanker car releases associated with
derailments along multiple sites: diesel and sulfuric acid
releases) and the NRDA process. He evaluated multiple
sites regarding NRDA liability and provided strategic
advice to the client regarding potential liabilities. This
case was settled prior to deposition.
Confidential Paper Company: Private and Public
Interest Property Valuation Joe led a study for a large
paper company to evaluate the natural resource value
associated with buffer properties surrounding a mill that
was scheduled for closure. The client was looking to
capture eco -asset values not typically considered in fair
market valuations. The evaluation considered multiple
land parcels for several hundred acres of property and
provided an assessment of the "private" and "public'
interest value associated with the property. Using this
information, the client was able to negotiate the sale of the
property, manage site liabilities, and capture value greater
than a fair market value. This project included an
evaluation of wetland and stream mitigation banking
value including calculation and estimation of potential
credit values and potential cash-flow for the site. The eco -
asset valuation estimated the minimum private interest
value (based on the ranges developed in this
memorandum) was estimated to be about $7,500,000. The
FMV of the property was in the range of $400,000. The
overall public interest value was estimated to be
$5,200,000. Client used this analysis to inform
negotiations regarding the sale of their property.
Confidential Client, Los Angeles Harbor, California —
NRDA. Joe assisted in an in-depth statistical analysis of
sediment toxicity PCB and DDT concentrations. This
project entailed a thorough analysis of sediment
concentration threshold data and the applicability of these
data to represent thresholds in sediments of the Los
Angeles Harbor area. This analysis was conducted to
provide a sound scientific basis to refute the apparent
effects threshold (AET) levels developed by a NOAA
expert witness.
Statistical Analysis, Lower Bayou d7nde and Calcasieu
River Estuary. Joe examined the spatial and temporal
trends of hexachlorobenzene, and hexachlorobutadiene
F, D

Joseph Nicolette
(HCB and HCBD, respectively), PCBs, and mercury in
sediments and biological tissues in these waterways.
Evaluated trend data in response to National Oceanic and
Atmospheric Administration (NOAA) comments
regarding analysis of the data. These data will be used in
creating a proposed restoration -based compensation
approach for the site using NEBA, HEA, and ROA.
American Petroleum Institute Aquatic Toxicity Studies.
Joe participated in a study to evaluate the toxicity of
petroleum products on fish, invertebrates, algae, and
zooplankton for use in NRDA's. The purpose of the
project was to conduct a critical review of toxicity values
for the purposes of identifying potential risks associated
with released oil. This study screened about 8,000
references published on the fate and effects of petroleum
in the environment. The study evaluated and compared
toxicity values for a range of petroleum substances from
crude oil to petroleum products. This analysis identified
the large disparity between acute (LC50) values for a
given compound for the same species and identified the
likely causes associated with methods used to derive
toxicity values.
Conoco, Clooney Loop, Louisiana. Assisted in
development of a net environmental benefits analysis to
demonstrate that a less intrusive remedy for ethylene
dichloride coupled with wetlands restoration resulted in
greater environmental benefit than dredging remedy.
Resulted in a cost savings of $19 million to Conoco.
Exxon Valdez, Alaska. When the supertanker Exxon
Valdez struck a rock reef and spilled approximately 11
million gallons of crude oil into Prince William Sound,
Joe participated in a project to evaluate the impacts of the
oil release on invertebrate populations in selected Prince
William Sound areas. The purpose of the work was to
collect data to contribute to a NEBA. Data were collected
to describe the epifauna and epiflora, cryptic fauna, and
infauna of oiled and reference beaches and to relate the
composition, numbers, and vertical distribution of infauna
to the amounts of subsurface oil.
International Project Examples
Landmark Enforcement Case, U.K. Joe provided
technical oversight (2013) for a recent landmark
Appendix F - Joseph Nicolette CV
enforcement undertaking in the U.K. for a water pollution
offence. This was the first enforcement undertaking
accepted by the environment agency for a pollution
incident. Joe led the technical effort for the client's
external legal representation in assessing suitable actions
to compensate for the environmental impacts of a river
pollution incident. The technical basis for the resolution
was the use of a resource equivalency analysis approach
(i.e., habitat equivalency analysis — HEA). The
Environment Agency accepted an enforcement
undertaking as a practical alternative to a prosecution and
fine. This was the first case in the U.K. to use this
approach.
Lago Maggiore, Italy Joe led a Comparative Analysis
(CA) (e.g. a NEBA) to provide a formal quantification of
the change in key ecosystem service values that would be
associated with the implementation of a remedial action
and compares those changes to costs and predicted
changes in risk. The goal of a CA is to provide information
to support the selection of remedial alternatives that
maximize benefits to the public, while managing site risks
and costs.
Offshore Decommissioning O&G platforms and
FPSO's in the North Sea and Western Australia
Confidential Clients Joe was the Principal Investigator
leading NEBA efforts associated with the
decommissioning of offshore O&G platforms and FPSO's
(Australia and the North Sea). These NEBA projects entail
an understanding of the environmental conditions of the
site; subsea infrastructure design, removal alternatives that
can be considered for the site, ROV analysis, fate and
transport of potential chemical releases and baseline
conditions, ecological and human risk assessment
evaluations for both potential chemical (NORM,
petroleum, mercury, etc.) releases and physical impacts
associated with removal alternative implementation;
associated GHG emissions of removal alternatives;
human use evaluation of the sites (e.g., commercial,
recreational fisheries); Marine life and CITES
evaluations; baseline and predictive impact assessment;
and worker health and safety.
Arctic NEBA, Oil and Gas Industry. Joe worked as part
of an integrated team to develop a NEBA tool for oil spill
response and planning for the Oil and Gas Producers

Joseph Nicolette
(OGP) Joint Industry Group (JIP) related to oil spill
response and planning in the Arctic. The overall goal of
the Phase 2 Project is to help evaluate oil spill response
technologies, their application in the Arctic environment,
and develop a decision-making tool to limit environmental
and social impacts in the event of an oil release.
Ecosystem Services Analysis of Chlorpyrifos Use in
Citrus Production, Spain Joe led an analysis of the effects
on ecosystem services (ES) of using an agricultural
insecticide (chlorpyrifos) in citrus orchards in south-
eastern Spain to identify risk management actions and
understand the consequences of the hypothetical situation
of discontinued use of chlorpyrifos. Farmers rely on
chlorpyrifos to limit the occurrence of skin blemishes on
the surface of citrus fruit caused by scale insects. Citrus
fruit is graded for sale based on size, shape and lack of
skin blemishes under European marketing regulations;
farmers only make a profit when unblemished fruit is sold
in Europe. ES, including income, were compared for the
current status and the hypothetical scenario. The study
concluded that discontinuation of chlorpyrifos use would
result in significant economic losses for the region when
only a small change in current orchard management, such
as using a vegetated conservation area for risk mitigation,
could offset potential ecological impacts while
maintaining farmer's income and the recreational value of
orchards to local people. The study informed advocacy
discussions between the client, scientists and policy
makers responsible for pesticide authorisation in Europe.
Ecosystem Services Analysis of an Agricultural
Molluscicide used in the UK Joe led an analysis of the
effects on ecosystem services (ES) of using an agricultural
molluscicide in winter wheat and oilseed rape production
in the UK. These are key crops and farmers in north-
western Europe rely on the control of slugs using pelleted
molluscicides for crop protection. The study compared
marketing leading molluscicides and presented the costs
and benefits of each across a range of ecosystem services,
including crop production, habitat services (e.g. indicator
farmland species), soil and drinking water services. The
findings informed advocacy discussions with pesticide
regulators at a national level and had implications for other
environmental policies, such as the European Water
Framework Directive.
Appendix F - Joseph Nicolette CV
Ecosystem Services Analysis of 1,3-Dichloropropene
(1,3-D) Use in Tomato Production, Italy The use of 1,3-
D as a soil fumigant for the control of damaging nematode
pests in tomato production in Southern Italy and Sicily
was evaluated using an ecosystem services approach. 1,3-
D is currently approved for emergency use in Italian
tomato cultivation, although its use is widespread and well
established amongst growers. A field visit and interviews
with farmers underpinned the socio-economic aspects of
the study. The findings compared traditional chemical
controls (1,3-D) with perceived `green' approaches to
cultivation, such as soil solarisation (covering soil with
plastic) and biofumigation (use of biological fumigants).
The study provided an analysis of the costs and benefits to
the environmental and socio-economic services for each
alternative, which could be used to inform policy makers.
Database Design and Structuring Examples
Gulf of Mexico Baseline Database System Development
- Deepwater Horizon (2010-2015). Based on his
experience in NRDA combined with his large scale
relational database training, design, and management,
Joseph was assigned to serve as technical lead for the
development of a baseline information management
system incorporating ecological, chemical, physical,
socioeconomic, and GIS mapping data in the Gulf of
Mexico. This database system was used to evaluate the
potential for natural resource damages associated with
ecological and human use services in the Gulf of Mexico,
and incorporated data from Florida, Alabama, Louisiana,
Mississippi, and Texas.
North Carolina Acid Deposition Program: USEPA Acid
Deposition and Fisheries Populations in the Northeast
U.S. Joe designed this database system that contains
chemical, physical and biological data on fish populations
potentially impacted by acidic deposition. The
development of this complex database required
integration and coordination of multiple databases across
multiple U.S. states and development of a database
structure to allow data transfer. The database was used by
the USEPA in evaluating acid deposition.
Adirondack Lakes Acid Deposition Data Management
System. This is a nationally recognized database which
incorporated physical, biological and chemical data

Joseph Nicolette
associated with over 1,700 lakes in New York State. The
database was funded by the State of New York
Department of Environmental Conservation (NYDEC)
and the Empire State Electric Energy Corporation
(ESEERCO). The Adirondack Lake database was used
primarily for acid deposition assessment by the EPA and
the National Acid Precipitation Assessment Program
(NAPAP).
Selected Publications and Project Reports
Deacon, S., Norman, S., Nicolette, J., Reub, G., Greene,
G., Osborn, R., and Andrews, P. 2015. Integrating
ecosystem services into risk management decisions:
Case study with Spanish citrus and the insecticide
chlorpyrifos. Science of the Total Environment.
Elsevier publishing. 505 (2015) 732-739.
http://dx.doi.org/10.1016/j.scitotenv.2014.10.034
Nicolette, J., Burr, S., and Rockel, M. 2013. A Practical
Approach for Demonstrating Environmental
Sustainability and Stewardship through a Net
Ecosystem Service Analysis. Sustainability 2013, 5,
2152-2177; doi:10.3390/su5052152, Published May
10, 2013.
Nicolette, J., Goldsmith, B., Wenning, R., Barber, T.,
and Colombo, Fabio. 2013, Experience with
Restoration of Environmental Damage. Chapter 9 of
the book entitled "The E.U. Liability Directive: A
Commentary", edited by L. Berkamp and B.
Goldsmith. Published March 14, 2013, Oxford Press.
Pages 181-219.
Colombo, F., Nicolette, J., Wenning, R., and M.
Travers. 2012. Incorporating Ecosystem Service
Valuation in the Assessment of Risk and Remedy
Implementation. Chemical Engineering Transactions,
28, 55-60 DOI: 10.3303/CET1228010
Nicolette, J. Rockel, M. and D. Pelletier. 2011.
Incorporating Ecosystem Service Valuation into
Remedial Decision -Making: Net Ecosystem Service
Analysis. American Bar Association. Superfund and
Natural Resource Damage Litigation Committee
Newsletter, December 2011, Vol. 7. No. 1.
S. Deacon, A. Goddard, N. Eury, and J. Nicolette. 2010.
Assessing risks to ecosystems: Using a net
Appendix F - Joseph Nicolette CV
environmental benefit analysis framework to assist
with environmental decision-making. In Restoration
and Recovery: Regenerating Land and Communities.
British Land Reclamation Society. Whittles
Publishing, Scotland, U.K. pages 164-175.
A. Campioni, J. Nicolette and V. Magar. 2010.
Riparazione danno ambientale: valutazione
tecnica/economica. Rifiuti e bonifiche:
www.ambientesicurezza.ilsole24ore.com. Pages 57-
60.
S. Deacon, N. Eury, J. Nicolette, and M. Travers. 2010.
The European Environmental Liability Directive and
Comparisons with U.S. Natural Resource Damage
Assessment Regulations. Air and Waste Management
Association.
Nicolette, J. 2008. Contributing Author. Use of net
environmental benefit analysis to demonstrate the
Net Benefit of Site Cleanup Actions: An Evaluation
of Ecological and Economic Metrics at Two
Superfund Sites. US. EPA Pilot Studies Report.
Nicolette, J. 2003-2004 Contributing Author.: Net
environmental benefit analyses (NEBA) for 4 Army
BRAC Sites: Fort McClellan, AL, Savanna Army
Depot, IL and Camp Bonneville, WA. Four separate
technical study reports). Technical Reports.
Efroymson, R., Nicolette, J. and Suter, G. 2004. A
Framework for net environmental benefit analysis for
remediation or restoration of contaminated sites.
Environmental Management. September 2004. Vol.
34: (3): pp 315-331.
Efroymson, R.A., Nicolette, J. and Suter II, G.W.
(2003). A Framework for Net Environmental Benefit
Analysis for Remediation or Restoration of
Petroleum -Contaminated Sites. Oak Ridge National
Laboratory (TM -2003/17), Oak Ridge, Tennessee.
Nicolette, J., Rockel, M. and Kealy M. 2001.
Quantifying ecological changes helps determine best
mitigation. Pipeline and Gas Industry Magazine.
September 2001.

Joseph Nicolette
CH2MHILL/Marstel-Day, Inc. Contributing Author
(2003-2004): Net environmental benefit analyses
(NEBA) for Fort McClellan, AL, Savanna Army
Depot, IL and Camp Bonneville, WA. Technical
Reports.
CH2MHILL. Contributing Author (2003-2004): Net
environmental benefit analyses for OU6 and OU1 at
Edwards Air Force Base, CA. Technical Reports.
CH2M Hill. 2000. Environmental Assessment and
Closure Report, Goose Creek, Knoxville, Tennessee
Release Site. Prepared for the Tennessee Department
of Environmental Conservation on Behalf of Colonial
Pipeline Company, Inc.
CH2M Hill. 2000. Draft Response Action Plan.
Terminal Road Site, Newington, Virginia. Prepared
for the Plantation Pipeline Company. February 4.
CH2M Hill. 2000. Contributing Author. Benthic
Macroinvertebrate Sampling Plan, Rich Fork
Release, North Carolina. Prepared for the Plantation
Pipeline Company.
CH2M Hill. 2000. Contributing Author. Evaluation of
the Koch Hastings terminal Site with Regards to an
NRDA. Prepared for Koch Petroleum.
CH2M Hill. 1999-2001. Contributing Author. Quarterly
Monitoring Reports aor the Darling Creek, Louisiana
Site. Prepared for Colonial Pipeline Company, Inc.
Quarterly Reports Beginning in First Quarter of 1999
Through 2000.
CH2M Hill. 1999. Contributing Author. Net
Environmental Benefits Analysis of Treatability
Studies. Prepared for NASA (Marshall Space Flight
Center) Superfund Site.
CH2M Hill and Peacock, B. 1999. Contributing Author.
Final Restoration Plan and Environmental
Assessment. Prepared for Colonial Pipeline and the
Natural Resource Trustees. Final Restoration Plan for
the Sugarland Run Oil Spill, NRDA case.
Appendix F - Joseph Nicolette CV
CH2M Hill 1999. Contributing Author. Preliminary
Natural Resources Asset and Liability Management
Study. Prepared for Pacific Gas and Electric
Company (PG&E).
Entrix, Nicolette Environmental, Inc., and Peacock, B.
1998. Draft Restoration Plan and Environmental
Assessment. Prepared for Colonial Pipeline and the
Natural Resource Trustees. Draft Restoration Plan
(for public review) for the Sugarland Run Oil Spill,
NRDA case.
Entrix and Nicolette Environmental, Inc. 1998c. Reedy
River Fisheries Population Assessment. Conducted as
Part of the Natural Resource Damage Assessment,
Report (Volumes I and II). Prepared for the Natural
Resource Trustees and Colonial Pipeline Company,
Inc. Project Number 773712. Draft. April 3.
Entrix and Nicolette Environmental, Inc. 1998d. Reedy
River Ecological Assessment Studies: Conducted as
part of the Reedy River NRDA. Prepared for the
Natural Resource Trustees and Colonial Pipeline
Company, Inc.
Entrix. 1998a. Contributing Author. Water Quality
Assessment: Conducted in Response to the Reedy
River Incident. Prepared for the Natural Resource
Trustees and Colonial Pipeline Company, Inc. Project
Number 773712. Draft April 3.
Entrix. 1998b. Contributing Author. Reedy River
Aquatic Macroinvertebrate Assessment: Conducted
as Part of the Natural Resource Damage Assessment.
Prepared for the Natural Resource Trustees and
Colonial Pipeline Company, Inc. Project Number
773712. Draft April 3.
Entrix. 1998c. Contributing Author. Preliminary
Recreational Lost Use and Compensatory Restoration
Assessment: Conducted as Part of the Natural
Resource Damage Assessment. Prepared for the
Natural Resource Trustees and Colonial Pipeline
Company, Inc. Project Number 773712. Draft April
3.
Entrix and Nicolette Environmental, Inc. 1998a. Reedy
River Corbicula Population and PAH
Bioaccumulation Assessment: Conducted as Part of

Joseph Nicolette
the Natural Resource Damage Assessment. Prepared
for the Natural Resource Trustees and Colonial
Pipeline Company, Inc. Project Number 773712.
Draft. April 3.
Entrix and Nicolette Environmental, Inc. 1998b. Reedy
River Crayfish Population and PAH Bioaccumulation
Assessment — Oct 1996 and Sep 1997: Conducted as
Part of the Natural Resource Damage Assessment.
Prepared for the Natural Resource Trustees and
Colonial Pipeline Company, Inc. Project Number
773712. Draft. Apr 3.
Entrix and Nicolette Environmental, Inc. 1997. Quality
Assurance Project Plan for the Reedy River Incident.
Entrix. 1996a. Contributing Author. Reedy River
Natural Resource Damage Assessment: Current
Status and Proposed Approach. Prepared for the
Natural Resource Trustees and Colonial Pipeline
Company, Inc. Project Number 773712. Draft
September 11.
Entrix. 1996b. Contributing Author. Assessing Potential
Injury to Wildlife Along the Reedy River: A
discussion Prepared as Part of the Natural Resource
Damage Assessment. Prepared for the Natural
Resource Trustees and Colonial Pipeline Company,
Inc. Project Number 773712. Draft October 15.
Entrix. 1996. Contributing Author. Natural Resource
Credit Analysis for a Confidential Site. Based upon
the Habitat Equivalency Analysis Framework.
Confidential Client.
Markarian, R.K., J.P. Nicolette, T. Barber, and L.
Giese. 1995. A Critical Review of Toxicity Values
and an Evaluation of the Persistence of Petroleum
Products for Use in Natural Resource Damage
Assessments. American Petroleum Institute (API)
Publication Number 4594. January.
Nicolette, J.P., T.R. Barber, R.K. Markarian, T.W.
Cervino, and D.V. Pearson. 1995. A Cooperative
Natural Resource Damage Assessment (NRDA) case
study: Coloial pipeline release, Reston, Virginia.
Proceedings: Toxic Substances in Water
Environments. Assessment and Control: Water
Environment Federation. Pp. 7-21 to 7-32. May.
Entrix. 1995. Contributing Author. Analytical
Chemistry Results: Oyster and Sediment Samples
from the Quinnipiac River, Connecticut. Prepared for
Buckeye Pipeline Company and the Connecticut
State Department of Agriculture.
Entrix. 1995.c Contributing Author. Habitat
Equivalency Analysis: Overview, Definition of
Terms, and Debit Calculations for Sugarland Run,
NRDA. Prepared for Colonial Pipeline Company and
the Natural Resource Trustees.
Entrix. 1994. Contributing Author. Addendum to the
Fisheries Injury Assessment for Sugarland Run.
Conducted as Part of the Natural Resource Damage
Assessment. Prepared for Colonial Pipeline
Company, Inc. and the Natural Resource Trustees.
Entrix, 1994. Contributing Author. Mass Balance of
Spilled Diesel: Simulation Modeling. Conducted as
Part of the Natural Resource Damage Assessment.
Prepared for Colonial Pipeline Company, Inc. and the
Natural Resource Trustees.
Entrix. 1994. Contributing Author. Fish Population
Survey and Injury Assessment for Sugarland Run:
Conducted as Part of the Natural Resource Damage
Assessment. Prepared for Colonial Pipeline
Company, Inc. and the Natural Resource Trustees.
Entrix. 1994. Contributing Author. Benthic
Macroinvertebrate Survey of Sugarland Run, Broad
Run, and the Potomac River: Conducted as Part of
the Natural Resource Damage Assessment. For
Colonial Pipeline Company, Inc. and the Natural
Resource Trustees.
Entrix. 1994. Contributing Author. Corbicula PAH
Bioaccumulation Study for Sugarland Run and the
Potomac River: Conducted as Part of the Natural
Resource Damage Assessment. For Colonial Pipeline
Company, Inc. and the Natural Resource Trustees.
Entrix. 1994. Contributing Author. Preliminary Survey:
Analytical Chemistry Data Analysis for Sugarland
Run and the Potomac River: Conducted as Part of
the Natural Resource Damage Assessment. Prepared
Appendix F - Joseph Nicolette CV F-14pj

Joseph Nicolette
for Colonial Pipeline Company, Inc. and the Natural
Resource Trustees.
Entrix. 1994. Contributing Author. Vegetation Survey
and Natural Communities of the Potomac River from
Lowes Island to Chicamuxen Creek. Prepared for
Colonial Pipeline Company, Inc., the USEPA, and
the Natural Resource Trustees.
Entrix. 1993. Contributing Author. NRDA Study Plan
and Status: Sugarland Run and the Potomac River:
Prepared for Colonial Pipeline Company, Inc. and the
Natural Resource Trustees.
Entrix. 1993. Contributing Author. Response Action
Plan for Remediation of Spilled Diesel. Prepared for
Colonial Pipeline Company, Inc.
Entrix. 1993. Contributing Author. Quality Assurance
Project Plan. Supplement to the Response Action
Plan. Specific action to address Section 10.1 of the
EPA Unilateral Order. Prepared for the Colonial
Pipeline Company, Inc.
Entrix. 1993. Contributing Author. Preliminary Survey
Plan for Sugarland Run and the Potomac River in
response to the EPA Administrative Order regarding
the Sugarland Run oil spill. Prepared for Colonial
Pipeline Company, Inc. and the NR Trustees.
Entrix. 1993. Contributing Author. Sediment and Water
Quality Toxicity Tests for Sugarland Run. Conducted
as part of the Natural Resource Damage Assessment.
Prepared for Colonial Pipeline Company, Inc. and the
Natural Resource Trustees.
Entrix. 1992. Contributing Author. Oil Spill Response
and Impact Assessment Report for British Petroleum
(BP). Norfolk, Virginia Crude Oil Release.
Entrix. 1992. Oil and Oil Product Toxicity Database
User's Guide for OILTOX. Prepared for the
American Petroleum Institute.
Entrix. 1991. Contributing Author. Instream Flow
Study and Gravel Enhancement on the White Salmon
Appendix F - Joseph Nicolette CV
River, Washington. FERC Relicensing Agency
Review Document.
Entrix. 1990. Contributing Author. Biological Data
Report on the Intertidal Communities of Prince
William Sound. Prepared for Exxon. Part of an
evaluation of the environmental costs associated with
oil cleanup in Prince William Sound as a result of the
Exxon Valdez Oil Spill.
EA Engineering, Science and Technology, Inc. 1989.
Contributing Author. Pilot Study Report -Predation
by Piscivorous Fish in the Lower Tuolumne River,
1989. 1991. Report for the Turlock -Modesto
Irrigation District.
EA Engineering, Science and Technology, Inc. 1989.
Contributing Author. An Evaluation of the Effect of
Gravel Ripping on Redd Distribution in the Lower
Tuolumne River. Report for the Turlock -Modesto
Irrigation District.
EA Engineering, Science and Technology, Inc. 1989.
Contributing Author. Tuolumne River Summer Flow
Study. Report for the Turlock -Modesto Irrigation
District.
EA Engineering, Science and Technology, Inc. 1989.
Contributing Author. Chinook Salmon Redd
Excavations. Report for the Turlock -Modesto
Irrigation District.
EA Engineering, Science and Technology, Inc. 1989.
Contributing Author. Adirondack Lakes Study:
1984-1987: An Evaluation of Fish Communities and
Water Chemistry. Adirondack Lakes Survey Corp.,
NY. Final Report.
Nicolette, J.P. and G.R. Spangler. 1986. Contributing
Author. Population Characteristics of Adult Pink
Salmon in Two Minnesota Tributaries to Lake
Superior. Journal of Great Lakes Research.
12(4):237-250.
Bagdovitz, M., W. Taylor, J. Nicolette, and G.R.
Spangler. 1986. Contributing Author. Pink Salmon
Populations in the U.S. Waters of Lake Superior,

Joseph Nicolette
1981-1984. Journal of Great Lakes Research.
12(1):72-81.
Nicolette, J.P. 1984. Contributing Author. A Three -
Year -Old Pink Salmon In An Odd -Year Run in Lake
Superior." North American Journal of Fisheries
Management. Vol. 4(1):130-132.
Baker, J, Harvey, T. and J.P. Nicolette. 1984.
Contributing Author. Compilation of Available Data
on the Status of Fish Populations in Regions of the
Eastern U.S. Final Report to the Environmental
Protection Agency, Corvallis, OR.
Nicolette, J.P. 1983. Contributing Author. Population
Dynamics of Pink Salmon in Two Minnesota
Tributaries to Lake Superior. M.S. Thesis. University
of Minnesota, St. Paul, MN. 94 p.
Appendix F - Joseph Nicolette CV F-16