Nicolette NEBA Expert Report Duke Energy Final_20160630

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
Expert Opinion of:
Joseph P. Nicolette
Prepared by:
EPS
1050 Crown Pointe Parkway, Suite 550
Atlanta, Georgia 30338
Tel: [phone]
June 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
Expert Opinion of:
Joseph P. Nicolette
EPS
Environmental Planning Specialists, Inc.
1050 Crown Pointe Pkwy, Suite 550
Atlanta, GA 30338
Tel: [phone]
June 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
June 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.......................................................... 4
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.......................................................
16
3.1
Alternative Construction Analysis............................................................
17
3.2
Air Emissions...........................................................................................
17
3.3
Safety Risks.............................................................................................
18
3.4
Cost.........................................................................................................
18
3.5
Human Health..........................................................................................
18
3.6
Ecological (Habitat Alteration)..................................................................
19
4 NEBA
SUMMARY RESULTS...................................................................................
32
4.1 Risks Driving Remedial Alternative Selection .......................................... 32
4.2 NEBA Assessment Parameter Impacts ................................................... 35
4.2.1 Human Heath Implementation Risks ............................................. 38
4.2.2 Air Emissions................................................................................ 40
4.2.3 Ecological Services....................................................................... 42
4.2.4 Costs............................................................................................. 44
4.2.5 Each Site Data Combined............................................................. 46
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4.2.6 Cumulative Assessment................................................................ 50
5 OPINIONS............................................................................................................. 51
6 REFERENCES....................................................................................................... 55
7 EXPERT REPORTS REVIEWED................................................................................ 58
Appendices
A Construction and Cost
B Air Emissions
C Health and Safety Risk
D Human Health Risk
E Ecological Services
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 (CIP), and comprehensive removal
(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 value; human
recreational value; greenhouse gas emissions (GHG) 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 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 at coal ash basins across the state, as necessary.
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 2415a, 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,
2015f, 2016a, 2016b, 2016c; Synterra 2015b, 2016). The CAP documents evaluated the three
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alternatives (for some criteria, only in a qualitative manner) for the remediation of on -site
groundwater according to the following criteria:
• Effectiveness;
• Implementability/feasibility;
• Environmental sustainability;
• Cost; and
• Stakeholder input.
NCDEQ classified the impoundments as either High, Intermediate, or Low risk. 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 the 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
' The state environmental department has proposed the risk classification for all coal ash ponds in North Carolina as
intermediate based on current conditions and available data, except for those already designated high priority by the
coal ash law. If all necessary modifications and dam repairs included in the Notice of Deficiencies had been made to
Department of Environmental Quality's (DEQ's) satisfaction, and if nearby wells were determined to not be affected
by the coal ash ponds to DEQ's satisfaction, or permanent alternate water was made available to nearby residents, then
these basins would have been classified as low. DEQ takes the position that the coal ash law does not grant DEQ the
authority to change a pond's classification based on new information after the final proposed classifications are
released. DEQ will therefore recommend that the law be changed to reflect dam safety repairs or the removal of any
threat to drinking water. DEQ states that it would consider these subsequent actions or impose such conditions and
reclassify the basins if the state law granted this authority.
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them to advocate for a remedy (Removal) that is less protective of the environment and the
community.
• 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 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.
• 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 to the local community (via the
extensive truck traffic) and to workers compared to other alternatives.
• Based upon my evaluation, the Removal alternative will create significantly 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 EIS
(Tennessee Valley Authority 2016).
• 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.
• 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 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; educational background; 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 documents for each
site (HDR 2015a through HDR 2015f; HDR 2016a through 2016c; Synterra 2015a, b; Synterra
2016); and analyses conducted at my direction. In addition, I conducted site visits at these four
locations during the period of June 6-9, 2014. I 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; 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.
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
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).
s 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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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 March 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 E.U. 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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EPS
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 value effects; GHG emissions (i.e., carbon
footprinting); 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. 2013).
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
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programs where the benefits and impacts of potential alternatives are significant and need to be
evaluated closely.
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
(i.e., carbon footprinting); 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."
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 services 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
a A NEBA can also be referred to as a net ecosystem service analysis (MESA) (Nicolette et al. 2013).
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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., 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.
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
net environmental, economic and social benefits. The court should not, therefore, adopt
Intervenors proposed remedy.
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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. 2011; Nicolette,
et al 2013).
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 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 Superfund site (Exhibit 1, USEPA 2001).
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Exhibit 1. Example USEPA groundwater Record of Decision change based on a NEBA.
Region
1690
"
:..
(hound Rater
state SuppOned the
Fed- 150 hour S
change The Site is
Conn. a $0
Woodland%, NJ
located in a [Alfa] area
1 99 (ROD -A)
7 1:99
and the local populaston
Est'd Sa}ings =
Route ?_'
supports tau MnCdy
S 976 M
Rowe i32
change.
Type of Change: From - ground water pump and treat: To - au spargingisod vapor extraction and natural attenuation -
Factual Basis-. BTAG memo indicated that the ground water pump and treat system would dewater the nearby wellands. In
addltwn. durmg remedial &-sign. the PRP successfully identified alteruatices 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 services values and
provides stakeholders a basis to balance the risks, benefits and trade-offs associated with
competing alternative 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 (e.g., HEA, REA) 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.
5 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.
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5. 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
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. "
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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 [..] Key opportunities for integrating core
elements ofgreen 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."
"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.
DCN: HWIDENCO01 12 June 30, 2016

0
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 their SEPA (§ 113A-3), that it
shall be the continuing policy of the State of North Carolina to conserve and protect its
natural resources (USEPA 2012).
"The State of North Carolina has declared, in their State environmental policy (§
113A-3), that it shall be the continuingpolicy of the State ofNorth 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 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 their programs with federal cleanup programs.
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 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.
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
DCN: HWIDENCO01 13 June 30, 2016

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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
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.
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 Agency 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
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 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.
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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". 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
public is to be compensated for natural resource injury that has occurred as a result of a release.
Under NRDA, 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 NEBA evaluation for the Allen, Buck, Cliffside, and Mayo sites compared the Removal, CIP
and MNA 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 priority air pollutants;
5. community Impacts (e.g., increased traffic, accidents);
6. human use value (groundwater, recreation, hunting, etc.); and
7. 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;
• ecological habitat services (terrestrial, aquatic, avian);
• Groundwater services;
• GHGs;
• pollutant emissions (e.g., NOx, particulate matter) - truck traffic, on -site construction
(yellow iron);
• human recreational uses; and
• capital costs including long-term operations and maintenance (O&M).
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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 Steam Station, Buck Steam Station, Cliffside Steam Station and Mayo Steam Station.
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, 2016). The quantity of
ash and land coverage of 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];
• Land disturbance footprint;
• Road miles traveled [air emissions; safety risks];
• Dimensions of work zones [safety risks]; and
• Costs.
The quantification aspects of the NEBA were conducted within the following analyses: air
emissions, safety risks, costs, human and ecological health, and ecological habitat alterations. Each
of these analyses are discussed, in turn, in the sections below.
3.2 Air Emissions
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 were determined to cause adverse health and environmental effects when
DCN: HWIDENC001 17 June 30, 2016

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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. 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 for the three remedial alternatives,
specific to each of the sites considered is provided in Appendix B.
3.3 Safety Risks
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. Results are presented in Appendix C.
3.4 Cost
Costs for the three remedial alternatives, for each of the four site considered, are provided in
Appendix A.
3.5 Human Health
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. 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 numerous assumptions and data extrapolations were
necessary in order to conduct this "forward projection" analysis.
The receptors evaluated included a commercial/industrial worker, construction worker, trespasser,
boater, swimmer, and wader. 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.
b There were insufficient data to evaluate subsistence and recreational fishermen.
DCN: HWIDENC001 18 June 30, 2016

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3.6 Ecological (Habitat Alteration)
The purpose of this evaluation was to understand how the Removal and CIP alternatives might
affect ecological habitat values associated with the Allen, Buck, Cliffside, and Mayo Steam Station
sites. A geographic information system (GIS) analysis was conducted in order to quantify the
dimensions of the major land cover types presently existing in those areas of each site (e.g., basins)
that would be affected by implementation of either the CIP or Removal alternatives. Those basins,
along with selected site specific photographs for each site, are presented for the Allen (Figures 1-
5), Buck (Figures 6-10), Cliffside (Figures 11-15), and Mayo (Figures 16-20) sites, respectively.
Through GIS polygon analysis, the affected aerial dimensions of each land cover type that would
undergo alternation for the cap -in -place and comprehensive removal alternatives were determined
for each site.
The primary method by which changes in ecological services (i.e., habitat quality) associated with
the various alternatives was evaluated was through the use of the HEA methodology. Actions
potentially affecting ecological services include both physical implementation impacts as well as
impacts associated with chemical releases and/or residuals. This methodology requires the
evaluation of available data to select and identify appropriate metric(s) that will represent overall
habitat service flows from the environment. My evaluation included the direct habitat impacts as
well as indirect impacts (i.e., influences on adjacent areas, etc.).
Because many ecological habitat services are not traded in the marketplace, they do not have a
direct monetary value. The HEA approach is a service quantification approach that evaluates
ecological habitat service losses and 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.
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). We used the HEA methodology to quantify the relative
impacts or benefits, independent from each other, associated with the remedial alternatives.
The evaluation of ecological habitat impacts projected under each remedial action alternative, for
each of the sites considered, is provided in Appendix E.
DCN: HWIDENCO01 19 June 30, 2016

Figure 1
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 La
— Structural Fill 1
Structural Fill 2
Site Visit Photo Locations
N
A
500 1,000
Feet
Environmental Planning Specialists, Inc.

EPS-11
Figure 2. Wooded forest habitat growing on top of old ash basin at Allen Steam Station
(Photo 1 location on Figure 1).
Figure 3. Vegetation growth, surface water, and wetland habitat in the active basin at Allen
Steam Station (Photo 2 location on Figure 1)
DCN: HWIDENCO01 21 June 30, 2016

EPS
Figure 4. Permitted outfall to the Catawba River (Lake Wylie) at Allen Steam Station
(Photo 3 location on Figure 1).
Figure 5. Early growth vegetation in the active basin at the Allen Steam Station (Photo 4
location on Figure 1).
DCN: HWIDENCO01 22 June 30, 2016

Figure 6
�--�
EPS Site Reconnaissance
June 2016
Buck Steam Station
,.
Salisbury, NC
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
Note Heron
the public. the
Rookery Eagle Nesting Site.
and
''%� Heron Rookery Site q
J
Legend
s ��.
Basins
Cell 1 (Active)
Cell 2 (Old Primary Cell)
i
" °�1
Eagle Nesting Site
Cell 3 (Secondary Primary)
f
( O
Ash Fill Area (storage)
1
Game Land
-W, Site Visit Photo Locations
y
pr
4
r
N
o rce. Esri, Digit D • be, G� eoEye, i-cubed, Earn soar Geographies,
_ - CNES/Airbus DS, USDA, USG,, AM Get tipping, Aerogrid, ION, MR
0 500 1,000
- swisstopo,
and the GIS User Community
Feet
Environmental Planning Specialists, Inc.

0
Figure 7. Wetland habitat and vegetation in active Cell 1 at Buck Steam Station (Photo 1
location on Figure 6).
Figure 8. Wetland, surface water, and forest habitat over the Old Primary Ash Basin (Cell
2) at Buck Steam Station (Photo 2 location on Figure 6).
DCN: HWIDENC001 24 June 30, 2016

EPS
Figure 9. Wooded forest growth over the in the Old Primary Ash Basin (Cell 2) at Buck
Steam Station (Photo 3 location on Figure 6).
Figure 10. 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 6).
DCN: HWIDENC001 25 June 30, 2016

Figure 11
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
Ash Storage Area 1
Site Visit Photo Locatio
N
A
500 1,000
Feet
Environmental Planning Specialists, Inc.

LP
Figure 12. The Broad River at Cliffside Steam Station (Near Photo 1 location on Figure
11).
Figure 13. Vegetation growing on the active ash basin (hill in background) at Cliffside
Steam Station (Photo 2 location on Figure 11).
DCN: HWIDENCO01 27 June 30, 2016

Figure 14. Vegetation growth and wetlands/surface water habitat in the active ash basin at
Cliffside Steam Station (Photo 3 location on Figure 11).
Figure 15. The Broad River near the permitted outfall at the Cliffside Steam Station.
(Photo 1 location on Figure 11).
DCN: HWIDENCO01 28 June 30, 2016

4::v •: �� ♦.� cFL�
Figure 16
EPS Site Reconnaissance
June 2016
Mayo Steam Station
Y
;
Roxboro, NC
Figure Narrative
-''
Shows vantage point locations
3 -
for photographs taken during
EPS site reconnaissance on
June 9, 2016.
Notes: Note extensive
-
gamelands adjacent to the ash
ponds.
2 r
=
Legend
Active Ash Basin
Active Basin
Game Land
Streams
si✓
Site Visit Photo Locations
N
'+
t•1�
DigitralGl be, GeoEye, i-cubed, Earthstar Geogr phics,
CNES/Airbus D-, SDA, U 'EX, Getmapping, Aerognd, IGN, IGF,
0 500 1,000
swisstopo, and the GIS User ommunity
Feet
Environmental Planning Specialists, Inc.

0
Figure 17. Clam shells and healthy aquatic vegetation in the outlet of the active basin at
Mayo Steam Station (Photo 1 location on Figure 16).
Figure 18. Waterfowl on the surface water of the active basin at Mayo Steam Station
(Photo 2 location on Figure 16).
DCN: HWIDENCO01 30 June 30, 2016

EPS
Figure 19. Wetland habitat in the active basin at Mayo Steam Station (Photo 3 location on
Figure 16).
Figure 20. Crutchfield Branch (Photo 4 location on Figure 16).
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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 pulling together 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 several data
summaries of the information developed in support of 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.
For the Allen, Buck, Cliffside, and Mayo sites, the "forward projection" of human health risks
modeled across the progression of the more aggressive remedial action alternatives (MNA to CIP
to Removal) at each of the four sites, is presented in Figures 21-24.
DCN: HWIDENCO01 32 June 30, 2016

EPS
Figure 21. Allen Steam Station - Human Health Risks
High Risk
1
a,
op
0.75 L
Y
U
✓i
�
G1
U
dl
Moderate
0
0.5
M Risk
a
al
0
0.25
0
a
Low Risk
NUA
0
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
a On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
[I Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
Figure 22. Buck Steam Station - Human Health Risks
High Risk
1
W
to
c
0.75
x
u
-cs
a
m
> Moderate
0.5
m Risk
v
d
0
0.25 a
�
a
0
¢ ¢ ¢ a a a a ¢
Low Risk
�_ r
NUA
0
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
o Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
DCN: HWIDENCO01 33 June 30, 2016

Figure23. ClifFside SteamStati+on -Human Health Risks
High Risk
a Moderate
m Risk
v
4 Q
Low Risk
NUA G z
Option 1. IVINA
High Risk
C Q C
Option 2. Cap -In -Place with NNA
0
1
Cu
rm
c
0.75 t
t�
-o
Y
u
a�
0.5 0
rn
c
0
0.25
C
fl
Q C C
0
Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, m od erate risk, high risk
o Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
Figure 24. Mayo Steam Station - Human Health Risks
of
Moderate
+ Risk
ra
v
it
3
0
¢ J ¢ ¢ ¢ a a a a
Low Risk z z z z z z z z
NUA
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
1
0.75 u
v
U
v
0.5 0
a
m
C:
0
0.25 o
Q
O
L
d
0
DCN: HWIDENCO01 34 June 30, 2016

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 three sites. Given this, it is readily apparent that
the implementation of the remedial alternatives of CIP or Removal provide no apparent 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 1, including those parameters that can be evaluated to understand effects to groundwater
services. As can be seen in Table 1, adverse groundwater service effects appear to be marginal if
any. 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?
4.2 NEBA Assessment Parameter Impacts
I next consider how the remedial actions might affect other parameters that are important to human
health, ecological resources, and community perspectives. Figures 25 through 45 demonstrate how
the assessment parameters will be affected given the MNA, CIP and Removal alternatives. In these
figures, the parameter with the greatest adverse impact is set to 1, and the corresponding parameter
in the other alternative is presented proportional to the highest value. This allows us to graph
multiple parameters with varying scales on the same graph. The higher the bars move upwards
from the x axis, the greater the environmental impact. This approach allows for the alternatives to
be evaluated and compared given all the assessment parameters.
The charts that follow are presented in turn, for each of the following parameters: human health
implementation risks, air emissions, ecological services, and costs (Figures 25-41). Each parameter
is further presented by site as follows: Allen, Buck, Cliffside, and Mayo. Following these Figures,
charts for each site with all assessment parameters displayed are presented in Figures 42-44).
Additionally, a cumulative chart is provided that displays the combined effect across all four sites
(Figure 45).
The overall results are presented in in Table 2.
7 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).
DCN: HWIDENCO01 35 June 30, 2016

Table 1. 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
D
Purposes
P
Study Activities
Attributable to Change in
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
D
Costs
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
No
Support of Plants
Health Risks Attributable to Change in Climate,
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

Table 2. Overall NEBA Summary Table.
NEBA Considerations
Human Health Pathways
Ecological Habitat Services
Social
Costs
Groundwater
Public off -site
On -Site
Truck traffic
Implementation
Implementation
GHG emissions/
1
Truck traffic
Terrestrial
Aquatic
Priority pollutant
NEBA Framework
(drinking water
( g
contaminant
contaminant
Fish Consumption
incidents risk
incidents - property
risks - project
Truck Trips - Public
communities
communities
carbon foot
emissions
Capital and O&M
consumption)
exposure2,4
exposure2,3
damage only
accident rate
Roads
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)
no unacceptable
HI/ELCR -no
HI/ELCR -no
no unacceptable
risk, low risk,
unacceptable risk,
unacceptable risk,
risk, low risk,
Fatalities (F) and
Fatalities (F) and
HEA based lost
HEA based lost
Tons/yr and tons of
Tons/yr of NOx,
Net present value
moderate risk, high
low risk, moderate
low risk, moderate
moderate risk, high
injuries/illnesses (1)
Incidents
injuries/illnesses (1)
Trips -Public Roads
DSAYs
DSAYs
CO2e emitted
PM10/2.5 emitted
in real dollars
risk
risk, high risk
risk, high risk
risk
NUA
NUA
Baseline =
1) No Action (MNA Only)
NUA
Baseline
Baseline
Baseline
0
Baseline
Baseline
Baseline
Baseline
0.004/--
0.1/5E-08
$ 7,315,000
NUA
NUA
$ 154,833,594
Allen
2) Capping with MNA
NUA
F - 0.1
8
F - 0.07
140,401
2,481
2,813
6,453.24 tons/yr
NOx - 29.20
0.002/--
0.02/1E-08
1 - 2.8
1 - 9.57
33,508.54 tons
PM10/2.5 - 1.01
Above Baseline
NUA
NUA
F - 0.68
F - 0.2
23,505.31 tons/yr
NOx - 138.43
$ 1,543,608,397
3) Removal with MNA
NUA
56
963,704
5,186
1,086
0.001/--
0.004/1E-10
1 - 19.2
1 - 61
383,819.67 tons
PM10/2.5 - 5.91
Above Baseline
NUA
Low Risk
Baseline =
1) No Action (MNA Only)
NUA
Baseline
Baseline
Baseline
0
Baseline
Baseline
Baseline
Baseline
0.02/2E-07
0.2/2E-06
$ 7,315,000
NUA
NUA
$ 85,402,106
2) Capping with MNA
NUA
F - 0.06
5
F - 0.04
88,108
1,550
452
6,399.53 tons/yr
NOx - 29.02
BUCK
0.01/4E-08
0.05/6E-07
1 - 1.76
1 - 6.04
21,118.45 tons
PM10/2.5 - 1.01
Above Baseline
NUA
NUA
$ 445,498,459
3) Removal with MNA
NUA
F - 0.19
16
F - 0.1
265,570
2,264
709
23,519.64 tons/yr
NOx - 138.47
0.009/2E-08
0.0006/6E-09
1 - 5.29
1 - 19
110,384.29 tons
PM10/2.5 - 5.91
Above Baseline
NUA
Low Risk
Baseline =
1) No Action (MNA Only)
NUA
Baseline
Baseline
Baseline
0
Baseline
Baseline
Baseline
Baseline
0.02/6E-07
0.2/2E-06
$ 9,872,500
NUA
NUA
$ 85,897,149
Cliffside
2) Capping with MNA
NUA
F - 0.06
5
F - 0.04
82,460
1,303
317
6,521.54 tons/yr
NOx - 29.43
0.02/1E-07
0.04/6E-07
1 - 1.65
1 - 5.65
19,564.61 tons
PM10/2.5 - 1.02
Above Baseline
NUA
NUA
F - 0.28
F - 0.1
23,504.36 tons/yr
NOx - 138.42
$ 648,986,943
3) Removal with MNA
NUA
27
394,596
2,624
498
0.02/6E-OS
0.01/4E-09
1 - 7.86
1 - 27
162,560.70 tons
PM10/2.5 - 5.91
Above Baseline
NUA
Low Risk
Baseline =
1) No Action (MNA Only)
NUA
Baseline
Baseline
Baseline
0
Baseline
Baseline
Baseline
Baseline
0.2/--
0.3/3E-06
$ 7,315,000
NUA
NUA
F - 0.05
F - 0.03
6,399.69 tons/yr
NOx - 29.02
$ 70,423,111
Mayo
2) Capping with MNA
NUA
0.2/--
0.09/7E-07
1 - 1.33
4
1 - 4.59
66,720
991
557
15,999.23 tons
PM10/2.5 - 1.01
Above Baseline
NUA
NUA
F - 0.23
F - 0.1
23,518.04 tons/yr
NOx - 138.47
$ 547,889,455
3) Removal with MNA
NUA
23
330,083
2,294
875
0.2/--
0.0002/-
I - 6.58
I - 23
136,357.55 tons
PM10/2.5 - 5.91
Above Baseline
Notes:
Current Baseline: Parameters are measured as a change from the current condition for each site. Footnotes:
1 ) No Action (MNA Only): Current Baseline: Parameters are measured as a change from the current condition for each site. 1. Insufficent data to evaluate
2) Capping with MNA: 2. Highest Hazard Index / ELCR 30 years after implementation
3) Removal with MNA: NUA: No Unacceptable Risk: HI < 1; ELCR <1E-06
Abbreviations: Low Risk: 1 < HI < 3; 1E-06 < ELCR < 1E-05
DSAY: discounted service acre year Moderate Risk: 1 < HI < 3; 1E-05 < ELCR < 1E-04
GHG: greenhouse gas High Risk: HI > 3; ELCR > 1E-04
NEBA: Net Environmental Benefit Analysis 3. Construction worker, Commercial/Industrial Worker or Trespasser
0&M: operation and management 4. Swimmer, Boater, Wader
Page 1 of 1

4.2.1 Human Heath Implementation Risks
Figure 25. Allen Steam Station - Human Implementation Risks
Ol N lD
O '-I O lD f1
High Risk
Y
0) Moderate
Z1 Risk o
M 0
N
or
v
m
N
EPS
N N U1 W W O N W
0! G! W N N
Low Risk z z z Co m m m m z z z z z z
NUA
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Truck traffic related accidents fatalities
■ Truck traffic related accidents Project Illness/Injury
Implementation risks - project fatalities
Implementation risks - project illness/injury
Truck traffic related accidents - property damage
Figure 26. Buck Steam Station - Human Health Implementation Risks
m o
m � �
o Sri o ti .�
High Risk
Moderate
Risk
o � o
K
3 v m a v v
o c c c c c
a a 'v 'v 'v "v "v a a a a a a
D . 7
Low Risk z z m m m m m z z z z z z
NUA
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Truck traffic related accidents fatalities
■ Truck traffic related accidents Project Illness/Injury
Implementation risks - project fatalities
Implementation risks - project illness/injury
Truck traffic related accidents - property damage
0
0
1
v
u
N
0.5
a
M
C
O
0.25 .L
O
Q
O
a
0
1
v
c
co
0.75 u
v
U
u
v
0.5 0
d
7E
C
O
0.25 0
DCN: HWIDENCO01 38 June 30, 2016

Figure 27. Cliffside Steam Station - Human Health Implementation Risks
o o
O n O N N
High Risk
Moderate
+� Risk
ca
Cu
z
o c c c c c
¢ ¢ h h
Low Risk z z m m 2 m m
NUA
Option 1. MINA
0
0
o
z z z
Option 2. Cap -In -Place with MNA
Option 3. Removal with MNA
EPS
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Truck traffic related accidents fatalities
■ Truck traffic related accidents Project Illness/Injury
Implementation risks - project fatalities
Implementation risks - project illness/injury
Truck traffic related accidents - property damage
Figure 28. Mayo Steam Station - Human Health Implementation Risks
m o
N lD N m O
O D O N N
High Risk
or
Moderate
+ Risk
m
N
Y
a a
Low Risk z z m m m m m
NUA
Option 1. MINA
m
0
C
� m �
a a a
z z z
Option 2. Cap -In -Place with MNA
Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Truck traffic related accidents fatalities
■ Truck traffic related accidents Project Illness/Injury
Implementation risks - project fatalities
Implementation risks - project illness/injury
Truck traffic related accidents - property damage
1
v
U0
C
m
0.75 u
0.25 o
Q
O
a`
0
1
v
00
c
M
0.75 U
v
U
v
0.5
0-
0
0.25 0
Q
O
a
0
DCN: HWIDENCO01 39 June 30, 2016

EPS
4.2.2 Air Emissions
Figure 29. Allen Steam Station - Air Emissions
m
ao m
High Risk 1
on
c
t
0.75 U
� v
U
it v
Q) Moderate 0.5
+--0-
Risk
a
v �
� � O
o N 0.25
v v v O
M Q
a a a v a w a a a ^ a a a O
Low Risk z z z Co m Co z z z z z z a
NUA 0
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ GHG emissions/ carbon foot -printing - Tons CO2e emitted
Emissions from increased truck traffic & yellow iron operations - Ton/yr Nox
Emissions from increased truck traffic & yellow iron operations - Ton/yr PM2.5
Figure 30. Buck Steam Station - Air Emissions m
o
ti ti �
High Risk 1 v
o.o
c
t
0.75 U
� v
U
of N
0) Moderate 0.5 0
+ Risk a
ca
Y C
O
N N o 0.25
O C C G a O
J a v 'v v a a a a a a fl-
Low Risk z z m m m z z z z z z a
NUA 0
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ GHG emissions/ carbon foot -printing - Tons CO2e emitted
Emissions from increased truck traffic & yellow iron operations - Ton/yr Nox
Emissions from increased truck traffic & yellow iron operations - Ton/yr PM2.5
DCN: HWIDENCO01 40 June 30, 2016

Figure 31. Cliffside Steam Station - Air Emissions
High Risk
Y VI
j Moderate
'Z Risk
10
v a c
0 0.25
3 v v v 0
a a 'v 'v 'v a a a a a a 0
Low Risk z z m m m z z z z z z a
NUA 0
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ GHG emissions/ carbon foot -printing - Tons CO2e emitted
Emissions from increased truck traffic & yellow iron operations - Ton/yr Nox
Emissions from increased truck traffic & yellow iron operations - Ton/yr PM2.5
1
EPS
Figure 32. Mayo Steam Station - Air Emissions m
o
m m
.ti ti vi
High Risk
C) Moderate
+ Risk
Ci
of
Y
3 v v v
o c c c
v w
Low Risk z z m m m
NUA
Option 1. MNA
O
0) N O
m
a a a
z z z
Option 2. Cap -In -Place with MNA
Option 3. Removal with MNA
0.5
a
1
W
ao
c
0.75 v
a�
U
U
v
0.5
a
c
O
0.25
O
a
O
a
0
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ GHG emissions/ carbon foot -printing - Tons CO2e emitted
Emissions from increased truck traffic & yellow iron operations - Ton/yr Nox
Emissions from increased truck traffic & yellow iron operations - Ton/yr PM2.5
DCN: HWIDENCO01 41 June 30, 2016

4.2.3 Ecological Services
High Risk
Cr
W Moderate
+J Risk
v
Y
Ln
Figure 33. Allen Steam Station - Ecological Services
m
1
V
N
C
EPS
1
v
on
c
t
0.75 U
v
U
N
0.5
a-
c
0
0.25
0
C C Q
a a a v v a a a a a a p
Low Risk z z z m z z z z z z
NUA 0
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ On -Site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Terrestrial Habitat - HEA based lost DSAYs
Aquatic Habitat - HEA based lost DSAYs
High Risk
Figure 34. Buck Steam Station - Ecological Services
1
0-
v
U
OJ Moderate 0.5 0
Risk
a
� O
0.25
3 v w O
o c c Q
a a a a a a a a p
Low Risk z z z z z z z z a
NUA 0
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑On -Site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Terrestrial Habitat - HEA based lost DSAYs
Aquatic Habitat - HEA based lost DSAYs
DCN: HWIDENCO01 42 June 30, 2016

Figure 35. Cliffside Steam Station - Ecological Services
High Risk
m
1
EPS
v
tiA
c
0.75 u
o U
� m U
Moderate 0.5 0
+ Risk a
v f°
of C:
y O
0.25
3 v v O
a J a v v a a a a a a O
Low Risk z z m z z z z z z a
NUA 0
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ On -Site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Terrestrial Habitat - HEA based lost DSAYs
Aquatic Habitat - HEA based lost DSAYs
Figure 36. Mayo Steam Station - Ecological Services
N
N 00
High Risk
Y
1
v
tiA
ro
t
0.75 u
v
a-
U
N
Q) Moderate 0.5 0
'Z Risk
a
Y O
0.25 .t
3 v v O
o a
a a 'v 'v a a a a a a O
Low Risk z z m z z z z z z a
NUA 0
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
[]On -Site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Terrestrial Habitat - HEA based lost DSAYs
Aquatic Habitat - HEA based lost DSAYs
DCN: HWIDENCO01 43 June 30, 2016

4.2.4 Costs
Figure 37. Allen Steam Station - Cost o
High Risk
Moderate
+ Risk
ca
v
of
EPS
1
a)
bA
c
t
0.75 U
a�
U
U
v
0.5 0
o_
c
o O
N 0.25
° O
a a a a a a a a a fl-
> O
Low Risk z z z z z z z z z
NUA 0
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Capital - Net Present Value (Millions)
Figure 38. Buck Steam Station - Cost oq
a
High Risk
QJ Moderate 0.5 0
+� Risk a
W c
� � O
m
0.25 .L
o O
a a a a a a a a O
> > ^ >
Low Risk z I—� z z z z ■ z z z a
1
NUA 0
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Capital - Net Present Value (Millions)
DCN: HWIDENCO01 44 June 30, 2016

of
Figure 39. Cliffside Steam Station - Cost
High Risk
EPS
1
v
b.0
C
t
0.75 U
v
U
N
IV Moderate 0.5 0`
+� Risk
a
co
v C
or O
w
0.25
3 °n O
0
Q
> > rn >
Low Risk z z a z z z z z z a
NUA 0
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑ Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Capital - Net Present Value (Millions)
High Risk
Figure 40. Mayo Steam Station - Cost N
1
v
u
v
Q) Moderate 0 5 0
+-� Risk
a
ca
a� C
� o
0.25 t
3 O
o Q
Low Risk z r_1 z z z z z z z a
NUA 0
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑On -Site worker contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Capital - Net Present Value (Millions)
DCN: HWIDENCO01 45 June 30, 2016

4.2.5 Each Site Data Combined
Figure 41. Allen Steam Station - Summary
0
N O
ti W N O m (Yf 06 1
W 10 Ol N .4 l 't , M C�
N O ri O lD V1 Vl M .--I V1 ah
High Risk
EPS
v Moderate
> ID
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o
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NUA
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑On -Site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Truck traffic related accidents fatalities
■ Truck traffic related accidents Project Illness/Injury
Implementation risks - project fatalities
Implementation risks - project illness/injury
Truck traffic related accidents - property damage
■ Terrestrial Habitat - HEA based lost DSAYs
Aquatic Habitat - HEA based lost DSAYs
■ GHG emissions/ carbon foot -printing - Tons CO2e emitted
Emissions from increased truck traffic & yellow iron operations - Ton/yr Nox
Emissions from increased truck traffic & yellow iron operations - Ton/yr PM2.5
■ Capital - Net Present Value (Millions)
1
v
on
0.75 rroo
t
U
N
u
v
0.5
a
C
O
O
0.25 C
CL
0
DCN: HWIDENCO01 46 June 30, 2016

Figure 42. Buck Steam Station - Summary
High Risk
Q) Moderate
+� Risk
v
3
o v m m m m m w v a w
c c c c c c c c c c
Low Risk > j�� ���- „m
z z m m m m m m m m m m �.
mmmmmm.n
NUA mmmm
Option 1. MNA
0
a
0
0
o o
0 o v
m
O ry ry 0 N
N
zzzzz
Option 2. Cap -In -Place with MNA
m m
a m n
N m.� of �oNoom°iv
Option 3. Removal with MNA
EPS
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑On -Site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Truck traffic related accidents fatalities
■ Truck traffic related accidents Project Illness/Injury
Implementation risks - project fatalities
Implementation risks - project illness/injury
Truck traffic related accidents - property damage
■ Terrestrial Habitat - HEA based lost DSAYs
Aquatic Habitat - HEA based lost DSAYs
■ GHG emissions/ carbon foot -printing - Tons CO2e emitted
Emissions from increased truck traffic & yellow iron operations - Ton/yr Nox
Emissions from increased truck traffic & yellow iron operations - Ton/yr PM2.5
■ Capital - Net Present Value (Millions)
1
v
0o
0.75 rroo
U
4!
u
v
0.5 21
a
O
0.25 0
a
0
DCN: HWIDENCO01 47 June 30, 2016

High Risk
Figure 43. Cliffside Steam Station - Summary
ti
m
O
a Ln v
W O N W N co m
EPS
Y m
� O
p[ m
Q) Moderate
Z1 Risk o
ro 0
v
� a
Y. O _q Ui N V N O W
rl �
o vavvavavvv
Low Risk y m m m m m m w o � 7)� D D
z z m m m m m m m m m m O z z z z z z
NUA
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑On -Site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Truck traffic related accidents fatalities
■ Truck traffic related accidents Project Illness/Injury
Implementation risks - project fatalities
Implementation risks - project illness/injury
Truck traffic related accidents - property damage
■ Terrestrial Habitat - HEA based lost DSAYs
Aquatic Habitat - HEA based lost DSAYs
■ GHG emissions/ carbon foot -printing - Tons CO2e emitted
Emissions from increased truck traffic & yellow iron operations - Ton/yr Nox
Emissions from increased truck traffic & yellow iron operations - Ton/yr PM2.5
■ Capital - Net Present Value (Millions)
1
v
on
0.75 rroo
t
U
v
U
N
0.5
a
co
C
O
O
0.25 C
L
a
0
DCN: HWIDENCO01 48 June 30, 2016

Figure 44. Mayo Steam Station - Summary
V N
a m 1.n
m o m co N
High Risk
Y
Moderate
+� Risk
ro
v
3
o v w m w a m w v a w
c c c c c c c c c c
Low Risk > j F Z Z 15 „ M
Z Z . . . . . . m . . m is
mmmmmmmmmm.n
NUA
EPS
Option 1. MNA Option 2. Cap -In -Place with MNA Option 3. Removal with MNA
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑On -Site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■ Truck traffic related accidents fatalities
■ Truck traffic related accidents Project Illness/Injury
Implementation risks - project fatalities
Implementation risks - project illness/injury
Truck traffic related accidents - property damage
■ Terrestrial Habitat - HEA based lost DSAYs
Aquatic Habitat - HEA based lost DSAYs
■ GHG emissions/ carbon foot -printing - Tons CO2e emitted
Emissions from increased truck traffic & yellow iron operations - Ton/yr Nox
Emissions from increased truck traffic & yellow iron operations - Ton/yr PM2.5
■ Capital - Net Present Value (Millions)
1
v
on
0.75 rroo
t
U
v
u
v
0.5 21
a
O
0.25 C
a
0
DCN: HWIDENCO01 49 June 30, 2016

4.2.6 Cumulative Assessment
Figure 45. Cumulative Assessment - All Sites
High Risk
Y
Moderate
+� Risk
v
Cr
J N N N N N N N N N N
C C C C C C C C C C
Low Risk =<)F1<5
Z Z ro m (a ro ro (a m ro m ro M
mmmmmmmmmm.n
NUA
Option 1. MNA
ti
N
m
�o
v
n
N
N �
�
7 N
V
VT
a a
M
Z Z Z
'
Option 2. Cap -In -Place with MNA
oo I r
T
oom o�m o��N
^?corm.--i Ni v�nmM
ey M O e1 .ti ci 01 Vt N V}
Option 3. Removal with MNA
EPS
■ Public off -site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑On -Site contaminant exposure - no unacceptable risk (NUA), low risk, moderate risk, high risk
❑Groundwater (drinking water consumption) - no unacceptable risk (NUA), low risk, moderate risk, high risk
■Trucktraffic related accidents -fatalities
■ Truck traffic related accidents - Project Illness/Injury
Implementation risks - project fatalities
Implementation risks - project illness/injury
Truck traffic related accidents - property damage
■ Terrestrial Habitat - HEA based lost DSAYs
Aquatic Habitat - HEA based lost DSAYs
■ GHG emissions/ carbon foot -printing - Tons CO2e emitted
Emissions from increased truck traffic & yellow iron operations - Ton/yr Nox
Emissions from increased truck traffic & yellow iron operations - Ton/yr PM2.5
■ Capital - Net Present Value (Millions)
1
v
on
0.75
t
U
N
N
0.5 °
0-
0
O
0.25 C
L
d
N
DCN: HWIDENCO01 50 June 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.
• 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 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.
• 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.
DCN: HWIDENCO01 51 June 30, 2016

0
o The Removal alternative will create greater risks to the local community (via the
extensive truck traffic) and to workers compared to other alternatives.
• Based upon my evaluation, the Removal alternative will create significantly greater risks
(and nuisance) to the local community (via the extensive truck traffic) and to workers,
compared to other alternatives.
• 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,
are overly conservative 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.
• A refinement of both the human and ecological risk assessments will reduce "perceived"
risks substantially, providing for the consideration of non -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, if implemented, 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 at any of the sites:
o The Removal alternative will 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"), 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.
DCN: HWIDENC001 52 June 30, 2016

0
Objective #2: Remedies require safe working practices.
Remediation work should be safe for on -site workers, local communities and the
environment.
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).
• 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 Allen, Buck, Cliffside, and Mayo sites meet the definition as to when a NEBA would
be of value in evaluating site remedial alternatives$. The site information indicates that
s "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
DCN: HWIDENC001 53 June 30, 2016

0
these sites retain significant ecological value. The Removal alternative proposed by the
Intervenors' will be environmentally damaging, the ecological risks from the COI's are
relatively small, uncertain, or limited to a component of the ecosystem, and remediation or
restoration might fail.
• 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 Intervenors' proposed remedy
(Removal) is clearly disproportionate to the risk.
small, uncertain, or limited to a component of the ecosystem, and when remediation or restoration might fail."
(Efroymson et al. 2004).
DCN: HWIDENC001 54 June 30, 2016

0
6 REFERENCES
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.
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.
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.
DCN: HWIDENC001 55 June 30, 2016

0
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 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. 2016. Corrective Action Plan Part 2, Mayo Steam Electric Plant. February 29, 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 Army Environmental Center. 2005. United States Army Natural Resource Injury
Guidance. September. http://aec.army.mil/portals/3/cleanup/nri- _ uigde.pdf
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-0I-
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.
DCN: HWIDENC001 56 June 30, 2016

0
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. 2011a. 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. og v/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.el2a. _og v/region4/soerfund/images/allmedia/pdfs/
annualreport2013.pdf.
USEPA Science Advisory Board (SAB). 2009. Valuing the Protection of Ecological Systems and
Services (EPA-SAB-09-012). Washington, DC: USEPA Science Advisory Board.
DCN: HWIDENC001 57 June 30, 2016

0
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.
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.
Hutson, Mark A. February 2016. Expert Report of. Mayo Steam Electric Plant Roxboro, 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: HWIDENCO01 58 June 30, 2016

EPS
APPENDIX A
Remedial Alternatives Construction Analysis

EPS
REMEDIAL ALTERNATIVE CONSTRUCTION
ANALYSIS
A construction and cost analysis for three remedial alternatives, monitored natural attenuation
(MNA), cap -in -place (with MNA), and comprehensive removal (with MNA) 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; HDR, 2016b; HDR, 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 tables following
this text. Supporting calculation worksheets are appended to the end of this Appendix.

EPS
Al TABLE 1. LAND USE DISTURBANCE
The first analysis category modeled 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 NINA only is not included in Table 1 as no significant land use disturbance occurs
under this scenario.
The cap -in -place 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. 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 cap -in -place and comprehensive
removal alternatives.
A1.1 Cap -in -Place Assumptions:
1. The size of each cap is set equal to the current footprint of 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 ft and a
side slope of 3 ft/ft.
4. A 50 ft perimeter buffer strip is included in the borrow area footprint.
A1.2 Comprehensive Removal Assumptions:
1. A conversion of 1.2 tons per cubic yard of ash is assumed based on a study by the Electric
Power Research Institute (EPRI, 2009).
2. To determine landfill size, each landfill is limited to a maximum height of 100 feet (ft) and
a side 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.

EPS
A2 TABLE 2. PROJECT DURATION
The second analysis category modeled the anticipated duration of each remedial alternative. The
removal alternative comprises of 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 cap -in -place alternative comprises of cap construction activities,
which is assumed to be limited by the rate at which capping material (i.e. soil and clay) can be
imported and placed on -site.
A2.1 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 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 miles
round-trip).
3. Landfill closure assumes 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.
A2.2 Cap -in -Place 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 miles round-trip).

EPS
A3 TABLE 3. COST SUMMARY OF
ALTERNATIVE REMEDIAL ACTIONS
The final analysis category projected expenditures 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 person
communications with industry expert (personal communication). Landfill construction cost is
estimated based on economic data cited in U.S. Environmental Protection Agency research (EPA,
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.

C
A4 REFERENCES
US EPA, 2014. Municipal Solid Waste Landfills, Economic Impact Analysis for the Proposed
New Subpart to the New Source Performance Standards. June 2014.
EPRI, 2009. Coal Ash: Characteristics, Management and Environmental Issues. Electric Power
Research Institute, 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.
SynTerra, 2016. Corrective Action Plan Part 2, Mayo Steam Electric Plant, February 29, 2016

Table 1. Land Use Change Summary
REMOVAL WITH MNA
CAPPING WITH MNA
Site
Existing Ash Pond/
Ash Fill Area
Volume of Ash
Landfill Construction
Area 1
Landfill Cap Barrow
Material Area 2
Landfill Total
CIP Barrow Material Areal
Acre
CY
Acre
Acres
Acres
Acres
Allen
322
16,058,333
225
93
319
190
Buck
180
4,425,000
94
35
129
122
Cliffside
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
521
Assumption:
Ash density: 1.2 tons/CY
Notes:
MNA: 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 foot buffer for development/construction support.
2. Borrow Area: Excavation area based on 10 depth, plus 50 foot buffer for development/construction support.

Table 2. Project Duration Summary
REMOVAL WITH MINA
CAPPING WITH MNA
Site
Construction'
Ash Excavation, Transport & Placennent2
Closure/Cap3
Cap Construction
Years
Work Days
Hours
Years
Work Days
Hours
Years
Work Days
Hours
Years
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
3.3
880
10,559
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
14.0
3,771.6
45,258.7
Notes:
CIP: Cap -in -place
MNA: Monitored Natural Attenuation
Model Assumptions:
CAPPING WITH
REMOVAL WITH MNA
MNA
Schedule Assumptions
Construction
Ash Excavation &Closure/Cap
Cap Construction
Transport
Work Days/Week
6
6
6
6
Work Weeks/Yearl
SO
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 an annual haul rate of 540,000 tons based on SO 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 (SO miles round-trip).

Table 3. Cost Summary
REMOVAL WITH MNA
CAPPING WITH MNA
Site
Construction
Ash Excavation,
Transport &
Placement
Closure/Cap
Monitoring
(Site and
Landfill)
10%
Contingency
TOTAL
Cap
Construction
Monitoring
(Site Only)
1ng
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
$84,288,278
$6,650,000
$8,428,827.83
$92,717,106.13
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
$389,430,419
$28,925,000
$38,943,042
$428,373,461
Site
MNA
Monitoring
Site Only)
10%
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
MNA: Monitored Natural Attenuation

Table S1. Road Travel Summary
REMOVAL WITH MNA
CAPPING WITH MNA
Ash Transport
Closure/Cap Material
Liner Material
Closure/Cap Material
Liner Material
Site
Trips
Miles'
Trips
Miles'
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
87,995
4,399,735
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
1 147,8051
453
1 90,5291
377,1561
18,857,796
533
106,603
Notes:
MNA: Monitored Natural Attenuation
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.

Table S2. Liner Specifications
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.)
3,470
3,470
3,470
3,470
3,470
Landfill Option
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
1,293
1,423
453
90,529
CIP Option
Total Ash Basin Area
Site
Ash Basin (ft2)
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

Table S3. Monitoring Cost Estimate
Landfill Monitoring
Site
Landfill Width
(ft)
# MWs
Well
Installation
Days/Event
Analytical
Cost
Labor Cost
Equipment
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
# MWs
Days/Event
Analytical
Labor Cost
Equipment
Reporting
Events/Year
Annual Cost
100 Years
Site
Cost
Cost
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

Table S4. Off -Site landfill Size and Cost Estimate
Landfill Requirements
Site
Tons
CY
ft3
Allen
19,270,000
16,058,333
433,575,000
Buck
5,310,000
4,425,000
119,475,000
Cliffside
7,890,000
6,575,000
177,525,000
Mayo
6,600,000
5,500,000
148,500,000
Total:
39,070,000
32,558,333
879,075,000
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
GOAL SEEK CALCULATION - LANDFILL GEOMETRY
Height
Bottom (Landfill Base)
Top
Volume (ft3)
51 (ft)
B1 (ft2)
S2 (ft)
B2 (ft2)
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
i 1,651
2,724,6151
951
903,7181
148,500,000
OUTPUT
Site
Landfill
Buffer Acres
Total Acreage
Base Area (ft2)
Acres
Low Cost
High Cost
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
$18,764,568
$37,529,136
45.51
108.0
Total:
I Total:
341
$102,428,6611
$204,857,321
207.41
548.8

Table S5. Estimated Duration of Landfill Construction
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

Table S6. Landfill Closure Cost Worksheet (RACER)
Site
Imported
Material Volume
Import Duration
(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
Mayo
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
Protect Duration Details
Annual Haul Rate (CY):
648,000
# Trucks:
6
Truck CY:
40
Trips/Day:
10
Days/Week
6
Weeks/Year
45
Hours/day
12
Fill Distance (miles):
1
Assumption
Folder Assembly Level Data Report (RACER)
Phase
Technology
Assembly No.
Assembly Description
City
UOM
Materials
Labor
Equipment
Equip. Units
Extended Cost
Allen
Capping
17030423
Unclassified Fill, 6" Lifts, Off -Site, Includes Delivery, Spreading, and
633,317
CY
21.97
0.92
0.72
$14,950,478
Allen
Capping
18050301
Loam or topsoil, imported topsoil, 6" deep, furnish and place
158,329
LCY
21.17
4.94
1.43
$4,359,413
Allen
Capping
18050402
Seeding, Vegetative Cover
157
ACR
2,623.43
423.05
161.57
$503,729
Allen
Capping
33080507
Clay, Low Permeability, 6"Lifts, Off -Site
531,986
CY
21.97
2.17
1.40
$13,584,019
Allen
Capping
33080571
60 Mil Polymeric Liner, High -density Polyethylene
7,523,805
SF
0.40
0.20
0.01
$4,638,925
Allen
Capping
Barrow Excavation Equipment
Allen
Capping
17030233
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
6,618
HR
$0.00
$57.39
$79.54
4
$3,624,899
Allen
Capping
17030706
D8 with U-Blade Bulldozer
6,618
HR
$0.00
$59.86
$106.51
2
$2,202,127
Allen
Capping
17030226
988, 7.0 CY, Wheel Loader
6,618
HR
$0.00
$59.86
$84.96
2
$1,916,884
Allen
Capping
17030295
35 Ton, 769, Off -highway Truck
6,618
HR
$0.00
$55.72
$89.09
2
$1,916,752
Allen
Capping
CAP Const. Equipment
Allen
Capping
17030704
D6 with A -blade Bulldozer
6,618
HR
$0.00
$59.86
$60.12
2
$1,588,094
Allen
Capping
17030101
Rough Grading, D6 Dozer
759,977
SY
$0.00
$0.28
$0.31
1
$448,386
Allen
Capping
17030431
580K, 1.0 CY, Backhoe with Front-end Loader
6,618
HR
$0.00
$59.86
$20.70
1
$533,159
Allen
Capping
18050413
Watering with 3,000-Gallon Tank Truck, per Pass
157
ACR
$154.66
$38.83
$36.99
1
$36,190
Allen
Capping
17030233
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
6,618
HR
$0.00
$57.39
$79.54
1
$906,225
Allen
Capping
33010505
50 KW, 120/240 VAC, Generator, Daily Rental
552
DAY
$0.00
$0.00
$163.38
1
$90,106
Imported Material:
1,323,632
CY
Direct Cost:
$51,299,388
Direct+
$82,079,521
Buck
Capping
17030423
Unclassified Fill, 6" Lifts, Off -Site, Includes Delivery, Spreading, and
218,152
CY
21.97
0.92
0.72
$5,152,556
Buck
Capping
18050301
Loam or topsoil, imported topsoil, 6" deep, furnish and place
54,538
LCY
21.17
4.94
1.43
$1,501,639
Buck
Capping
18050402
Seeding, Vegetative Cover
54
ACR
2,623.43
423.05
161.57
$173,524
Buck
Capping
33080507
Clay, Low Permeability, 6"Lifts, Off -Site
183,247
CY
21.97
2.17
1.40
$4,679,137
Buck
Capping
33080571
60 Mil Polymeric Liner, High -density Polyethylene
#REF!
SF
0.40
0.20
0.01
$1,323,205
Buck
Capping
Barrow Excavation Equipment
Buck
Capping
17030233
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
2,280
HR
$0.00
$57.39
$79.54
4
$1,248,629
Buck
Capping
17030706
D8 with U-Blade Bulldozer
2,280
HR
$0.00
$59.86
$106.51
2
$758,542
Buck
Capping
17030226
988, 7.0 CY, Wheel Loader
2,280
HR
$0.00
$59.86
$84.96
2
$660,288
Buck
Capping
17030295
35 Ton, 769, Off -highway Truck
2,280
HR
$0.00
$55.72
$89.09
2
$660,242
Buck
Capping
CAP Const. Equipment
Buck
Capping
17030704
D6 with A -blade Bulldozer
2,280
HR
$0.00
$59.861
$60.12
2
$547,033
Buck
lCapping
17030101
Rough Grading, D6 Dozer
261,796
SY
$0.00
$0.281
$0.31
1
$154,459
Buck
ICapping
17030431
580K, 1.0 CY, Backhoe with Front-end Loader
2,280
HR
1 $0.00
$59.861
$20.701
$183,651
Page 1 of 2

Table S6. Landfill Closure Cost Worksheet (RACER)
Phase
Technology
Assembly No.
Assembly Description
Qty
UOM
Materials
Labor
Equipment
Equip. Units
Extended Cost
Buck
Capping
18050413
Watering with 3,000-Gallon Tank Truck, per Pass
54
ACR
$154.66
$38.83
$36.99
1
$12,467
Buck
Capping
17030233
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
2,280
HR
$0.00
$57.39
$79.54
1
$312,157
Buck
Capping
33010505
50 KW, 120/240 VAC, Generator, Daily Rental
190
DAY
$0.00
$0.00
$163.38
1
$31,038
Imported Material:
455,937
CY
Direct Cost:
$17,398,567
Direct+
$27,837,707
Cliffside
Capping
17030423
Unclassified Fill, 6" Lifts, Off -Site, Includes Delivery, Spreading, and
300,154
CY
21.97
0.92
0.72
$7,089,377
Cliffside
Capping
18050301
Loam or topsoil, imported topsoil, 6" deep, furnish and place
75,038
LCY
21.17
4.94
1.43
$2,066,098
Cliffside
Capping
18050402
Seeding, Vegetative Cover
74
ACR
2,623.43
423.05
161.57
$238,744
Cliffside
Capping
33080507
Clay, Low Permeability, 6"Lifts, Off -Site
252,129
CY
21.97
2.17
1.40
$6,438,001
Cliffside
Capping
3308OS71
60 Mil Polymeric Liner, High -density Polyethylene
3,565,827
SF
0.40
0.20
0.01
$1,820,591
Cliffside
Capping
Barrow Excavation Equipment
Cliffside
Capping
17030233
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
3,137
HR
$0.00
$57.39
$79.54
4
$1,717,982
Cliffside
Capping
17030706
D8 with U-Blade Bulldozer
3,137
HR
$0.00
$59.86
$106.51
2
$1,043,675
Cliffside
Capping
17030226
988, 7.0 CY, Wheel Loader
3,137
HR
$0.00
$59.86
$84.96
2
$908,487
Cliffside
Capping
17030295
35 Ton, 769, Off -highway Truck
3,137
HR
$0.00
$55.72
$89.09
2
$908,424
Cliffside
Capping
CAP Const. Equipment
Cliffside
Capping
17030704
D6 with A -blade Bulldozer
3,137
HR
$0.00
$59.86
$60.12
2
$752,660
Cliffside
Capping
17030101
Rough Grading, D6 Dozer
360,193
SY
$0.00
$0.28
$0.31
1
$212,514
Cliffside
Capping
17030431
580K, 1.0 CY, Backhoe with Front-end Loader
3,137
HR
$0.00
$59.86
$20.70
1
$252,685
Cliffside
Capping
18050413
Watering with 3,000-Gallon Tank Truck, per Pass
74
ACR
$154.66
$38.83
$36.99
1
$17,152
Cliffside
Capping
17030233
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
3,137
HR
$0.00
$57.39
$79.54
1
$429,496
Cliffside
Capping
33010505
50 KW, 120/240 VAC, Generator, Daily Rental
261
DAY
$0.00
$0.00
$163.38
1
$42,705
Imported Material:
627,321
CY
Direct Cost:
$23,938,591
Direct +
$38,301,746
Mayo
Capping
17030423
Unclassified Fill, 6" Lifts, Off -Site, Includes Delivery, Spreading, and
262,780
CY
21.97
0.92
0.72
$6,206,633
Mayo
Capping
18050301
Loam or topsoil, imported topsoil, 6" deep, furnish and place
65,695
LCY
21.17
4.94
1.43
$1,808,835
Mayo
Capping
18050402
Seeding, Vegetative Cover
65
ACR
2,623.43
423.05
161.57
$209,005
Mayo
Capping
33080507
Clay, Low Permeability, 6"Lifts, Off -Site
220,735
CY
21.97
2.17
1.40
$5,636,364
Mayo
Capping
33080571
60 Mil Polymeric Liner, High -density Polyethylene
3,121,823
SF
0.40
0.20
0.01
$1,593,898
Mayo
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
$1,504,065
Mayo
Capping
17030706
D8 with U-Blade Bulldozer
2,746
HR
$0.00
$59.86
$106.51
2
$913,720
Mayo
Capping
17030226
988, 7.0 CY, Wheel Loader
2,746
HR
$0.00
$59.86
$84.96
2
$795,365
Mayo
Capping
17030295
35 Ton, 769, Off -highway Truck
2,746
HR
$0.00
$55.72
$89.09
2
$795,310
Mayo
Capping
CAP Const. Equipment
Mayo
Capping
17030704
D6 with A -blade Bulldozer
2,746
HR
$0.001
$59.86
$60.12
2
$658,942
Mayo
Capping
17030101
Rough Grading, D6 Dozer
315,326
SY
$0.00
$0.28
$0.31
1
$186,042
Mayo
Capping
17030431
580K, 1.0 CY, Backhoe with Front-end Loader
2,746
HR
$0.00
$59.86
$20.70
1
$221,222
Mayo
Capping
18050413
Watering with 3,000-Gallon Tank Truck, per Pass
65
ACR
$154.66
$38.83
$36.99
1
$15,016
Mayo
Capping
17030233
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
2,746
HR
$0.00
$57.39
$79.54
1
$376,016
Mayo
Capping
33010505
50 KW, 120/240 VAC, Generator, Daily Rental
229
DAY
$0.00
$0.00
$163.38
1
$37,387
Imported Material:
549,210
CY
Direct Cost:
$20,957,821
Direct+
$33,532,514
Page 2 of 2

Table S7.Off-Site Landfill Closure - Barrow Area Size
INPUT
Site
Imported Material
Volume (CY)
ft3
Allen
1,323,632
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
Barrow Parameters:
Height (ft)
10
Slope:
3
Buffer Width
Width (ft) 50
GOAL SEEK CALCULATION - BARROW PIT
Height
Bottom
Top
Volume (ft3)
Si (ft)
61 (ft2)
S2 (ft)
B2 (ft2)
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
1,331
1,772,448
1,271
1,616,288
16,937,679
10
1,248
1,556,522
1,188
1,410,410
14,828,659
OUTPUT
Barrow
Area (ft2)
Acres
Buffer Acres
Total Acreage
3,687,830
85
8.8
93.5
1,298,193
30
5.2
35.0
1,772,448
41
1 6.1
1 46.8
1,556,5221
36
1 5.7
1 41.5
Total:
191
1 25.9
1 217

Table S8. Excavation, Transportation and Placement of Ash
Site
Ash Tons
Duration (yrs)
Trips
Travel Miles
Days
Hours
Allen
19,270,000
35.69
963,500
48,175,000
9,635
115,620
Buck
5,310,000
9.83
265,500
13,275,000
2,655
31,860
Cliffside
7,890,000
14.61
394,500
19,725,000
3,945
47,340
Mayo
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
ject 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/Day:
2
Active Excavators:
4
Active Bulldozers:
2
Days/Week
6
Weeks/Year
45
Water Truck ($/day)
$100
Landfill Distance (miles):
25
Hours per work day;
12
Hours per year:
3,240
Phase Name
I Assembly No.
Assembly Description
Qty
UOM
Materials
Labor
Equipment
SubBid
Equip.
Extended Cost
Allen
1703028S
12 CY (20 Ton), Dump Truck
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
UOM
Materials
Labor
Equipment
SubBid
Equip.
Extended Cost
Buck
17030285
12 CY (20 Ton), Dump Truck
31,860
HR
$0.00
55.72
33.41
$0.00
50
$141,984,090
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
1703029S
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
Page 1 of 2

Table S8. Excavation, Transportation and Placement of Ash
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
$210,970,710
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
Assembly No.
Assembly Description
Qty
UOM
Materials
Labor
Equipment
SubBid
Equip.
Extended Cost
Mayo
17030285
12 CY (20 Ton), Dump Truck
39,600
HR
$0.00
55.72
33.41
$0.00
50
$176,477,400
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
3301050S
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
Page 2 of 2

Table S9. landfill Cost Summary
Landfill Construction
Design Landfill Construction Erosion/Control Engineering/Survey Acres (Landfill
Site /Planning Cost Measures Oversight Site Total Foot Print) Cost/Acre
Allen
$5,000,000
$92,397,143
$450,689.48
$2,522,442
$100,370,274 225
$445,408
Buck
$5,000,000
$31,539,723
$188,504.49
$861,034
$37,589,262 94
$398,816
Cliffside
$5,000,000
$43,391,319
$242,427.43
$1,184,583
$49,818,330 121
$410,996
Mayo
$5,000,000
$37,529,136
$216,041.52
$1,024,545
$43,769,723 108
$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 (Ash
Site
/Planning
Ash Dig &Transport
Measures
Oversight
Site Total
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 (Barrow)
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

Table S10. Cap Cost Worksheet (RACER)
Folder Assembly Level Data Report (RACER)
Phase Name
Assembly Description
Qty
UOM
Materials
Labor
Equipment
Equip. Units
Extended Cost
Allen
Unclassified Fill, 6" Lifts, Off -Site, Includes Delivery, Spreading, and Compaction
766,639
CY
21.97
0.92
0.72
$18,107,357
Allen
Loam or topsoil, imported topsoil, 6" deep, furnish and place
191,660
LCY
21.17
4.94
1.43
$5,277,131
Allen
Seeding, Vegetative Cover
190
ACR
2,623.43
423.05
161.57
$609,787
Allen
Clay, Low Permeability, 6"Lifts, Off -Site
643,977
CY
21.97
2.17
1.40
$16,443,644
Allen
160 Mil Polymeric Liner, High -density Polyethylene
9,107,670
SF
0.401
0.20
0.01
1 $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
Allen
Loam or topsoil, imported topsoil, 6" deep, furnish and place
143,742
LCY
21.17
4.94
1.43
$3,957,761
Allen
Seeding, Vegetative Cover
143
ACR
2,623.43
423.05
161.57
$457,308
Allen
Clay, Low Permeability, 6"Lifts, Off -Site
482,972
CY
21.97
2.17
1.40
$12,332,461
Allen
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
Allen
Rough Grading, D6 Dozer
921,406
SY
$0.00
$0.28
$0.31
1
$543,629.37
Allen
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
Allen
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:
$87,415,791
Direct+
$139,865,265
Buck
Unclassified Fill, 6" Lifts, Off -Site, Includes Delivery, Spreading, and Compaction
404,124
CY
21.97
0.92
0.72
$9,545,060
Buck
Loam or topsoil, imported topsoil, 6" deep, furnish and place
101,031
LCY
21.17
4.94
1.43
$2,781,771
Buck
Seeding, Vegetative Cover
100
ACR
2,623.43
423.05
161.57
$321,447
Buck
Clay, Low Permeability, 6"Lifts, 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
Buck
Unclassified Fill, 6" Lifts, Off -Site, Includes Delivery, Spreading, and Compaction
250,307
CY
21.97
0.92
0.72
$5,912,031
Buck
Loam or topsoil, imported topsoil, 6" deep, furnish and place
62,577
LCY
21.17
4.94
1.43
$1,722,977
Buck
Seeding, Vegetative Cover
62
ACR
2,623.43
423.05
161.57
$199,092
Buck
Clay, Low Permeability, 6"Lifts, Off -Site
210,258
CY
21.97
2.17
1.40
$5,368,831
Buck
60 Mil Polymeric Liner, High -density Polyethylene
2,973,644
SF
0.40
0.20
0.01
$1,518,242
$14,721,173
Buck
Unclassified Fill, 6" Lifts, Off -Site, Includes Delivery, Spreading, and Compaction
95,921
CY
21.97
0.92
0.72
$2,265,569
Buck
Loam or topsoil, imported topsoil, 6" deep, furnish and place
23,980
LCY
21.17
4.94
1.43
$660,268
Buck
Seeding, Vegetative Cover
24
ACR
2,623.43
423.05
161.57
$76,288
Buck
Clay, Low Permeability, 6"Lifts, Off -Site
80,574
CY
21.97
2.17
1.40
$2,057,407
Buck
60 Mil Polymeric Liner, High -density Polyethylene
1,139,540
SF
0.40
0.20
0.01
$581,811
$5,641,342
Buck
D6 with A -blade Bulldozer
10,559
HR
$0.00
$59.86
$60.12
2
$2,533,825.03
Buck
Rough Grading, D6 Dozer
591,673
SY
$0.00
$0.28
$0.31
1
$349,086.94
Buck
580K, 1.0 CY, Backhoe with Front-end Loader
10,559
HR
$0.00
$59.86
$20.70
1
$850,662.38
Buck
Watering with 3,000-Gallon Tank Truck, per Pass
122.2
ACR
$154.66
$38.83
$36.99
1
$28,175.36
Buck
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
10,559
HR
$0.00
$57.39
$79.54
1
$1,445,893.74
Buck
50 KW, 120/240 VAC, Generator, Daily Rental
880
DAY
$0.00
$0.00
$163.38
1
$143,765.74
$5,351,409
Imported Material:
1,759,894
CY
Direct Cost:
$49,481,481
Direct+
$79,170,369
Cliffside
Unclassified Fill, 6" Lifts, Off -Site, Includes Delivery, Spreading, and Compaction
487,752
CY
21.97
0.92
0.72
$11,520,275
Cliffside
Loam or topsoil, imported topsoil, 6" deep, furnish and place
121,938
LCY
21.17
4.94
1.43
$3,357,420
Cliffside
Seeding, Vegetative Cover
121
ACR
2,623.43
423.05
161.57
$387,950
Cliffside
Clay, Low Permeability, 6"Lifts, Off -Site
409,711
CY
21.971
2.171
1.401
$10,461,786
Page 1 of 2

Table S10. Cap Cost Worksheet (RACER)
Folder Assembly Level Data Report (RACER)
Phase Name
Assembly Description
Qty
UOM
Materials
Labor
Equipment
Equip. Units
Extended Cost
Cliffside
60 Mil Polymeric Liner, High -density Polyethylene
5,794,488
SF
0.40
0.20
0.01
$2,958,470
$28,685,901
Cliffside
Unclassified Fill, 6" Lifts, Off -Site, Includes Delivery, Spreading, and Compaction
58,357
CY
21.97
0.92
0.72
$1,378,340
Cliffside
Loam or topsoil, imported topsoil, 6" deep, furnish and place
14,589
LCY
21.17
4.94
1.43
$401,697
Cliffside
Seeding, Vegetative Cover
14
ACR
1 2,623.43
423.05
161.57
$46,421
Cliffside
Clay, Low Permeability, 6"Lifts, Off -Site
49,020
CY
21.97
2.17
1.40
$1,251,697
Cliffside
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
Cliffside
Loam or topsoil, imported topsoil, 6" deep, furnish and place
60,460
LCY
21.17
4.94
1.43
$1,664,685
Cliffside
Seeding, Vegetative Cover
60
ACR
2,623.43
423.05
161.57
$192,355
Cliffside
IClay, Low Permeability, 6"Lifts, Off -Site
203,144
CY
21.97
2.17
1.40
$5,187,193
Cliffside
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
Cliffside
Rough Grading, D6 Dozer
555,690
SY
$0.00
$0.28
$0.31
1
$327,857.28
Cliffside
580K, 1.0 CY, Backhoe with Front-end Loader
9,881
HR
$0.00
$59.86
$20.70
1
$796,001.45
Cliffside
Watering with 3,000-Gallon Tank Truck, per Pass
114.8
ACR
$154.66
$38.83
$36.99
1
$26,461.88
Cliffside
Crawler -mounted, 3.125 CY, 245 Hydraulic Excavator
9,881
HR
$0.00
$57.39
$79.54
1
$1,352,985.08
Cliffside
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 place
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
Clay, Low Permeability, 6"Lifts, 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
$0.001
$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
$0.001
$163.38
1
$108,848.71
$4,056,339
Imported Material:
1,332,461
CY
Direct Cost:
$41,551,744
Direct+
$66,482,791
Page 2 of 2

Table S11. Off -Site Cap Source Material - Barrow Area Size
INPUT
Site
Imported Material
Volume (CY)
ft3
Allen
2,803,955
75,706,791
Buck
1,759,894
47,517,139
Cliffside
1,646,809
44,463,835
Mayo
1,332,461
35,976,436
Total:
19,463,717
525,520,366
Barrow Parameters:
Height (ft)
10
Slope:
3
Buffer Width
Width (ft) 50
GOAL SEEK CALCULATION - BORROW PIT
Height
Bottom
Top
Volume (ft3)
S1 (ft)
B1 (ft2)
S2 (ft)
B2 (ft2)
10
2,781
7,736,365
2,721
7,406,193
75,706,791
10
2,210
4,883,100
2,150
4,621,527
47,517,139
10
2,139
4,573,498
2,079
4,320,469
44,463,835
10
1,927
3,712,044
1,867
3,484,444
35,976,43 "
OUTPUT
Site
Barrow Area (ft2)
Acres
Buffer Acres
Total Acreage
Allen
7,736,365
178
12.8
190.4
Buck
4,883,100
112
10.1
122.2
Cliffside
4,573,498
105
9.8
114.8
Mayo
3,712,044
85
8.8
94.1
Total:
1 480
41.6
521

Table 512. CIP Cost Summary
Site
Design*
Construction Cost
Dewatering/
Treatment
Erosion/Control
Measures
Engineering/Survey
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
$79,170,369
$1,469,921
$360,126
$2,287,862
$84,288,278
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
$367,678,411
$6,257,339
$1,688,615
$9,806,054
$389,430,419
*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
Eng/Survey Oversight Details
Engineer
$1,500 day
Survey
$750 day
Days/Week
6
Weeks/Year
52
Imported
Material
Import Duration
Site
Volume (CY)
(yrs)
Trips
Travel Miles
Days
Hours
Allen
2,803,955
5.2
140,198
7,009,888
1,402
16,824
Buck
1,759,894
3.3
87,995
4,399,735
880
10,559
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:
7,543,119
14.0
377,156
18,857,796
3,772
45,259
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 2000

Table S13. Projected Excavation Details for Stations of Interest
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 2
560,000
Ash Landfill and Subgrade
1,740,000
Allen Fills/Landfills Tota12
2,730,000
Allen Total
19,270,000
14,035,895
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 a (Secondary)
270,000
997,296
23
5,348
Buck Basins Total
5,060,000
Ash Fill Area
250,000
Buck Fills Tota12
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 S 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 Tota12
200,000
Cliffside Total
7,890,000
8,219,196
E1'a
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.

EPS
APPENDIX B
Air Emissions Analysis of Remedial Alternatives

0
B1 INTRODUCTION
The expected air emissions 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).
131.1 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 PM10; 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 PM10 and PM2.5 are significant, they have also been estimated for this NEBA analysis.
131.2 Greenhouse Gases
Greenhouse gases, 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
Appendix B I June 30, 2016
Air Emissions Analysis of Remedial Alternatives

EPS
different Global Warming Potential (GWP), a relative measure of the heat trapped by each gas
compared to CO2. The net effect of potential GHG emissions have been normalized to a standard
called "CO2 equivalent" (CO2e) based on their relative GWPs.
Appendix B 2 June 30, 2016
Air Emissions Analysis of Remedial Alternatives

EPS
B2 EMISSION ESTIMATION METHODOLOGY
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. Each emission factor source is referenced in
notes below the emissions tables appended to this Appendix report.
B2.1 Monitoring Only
For the first remedial alternative, which consists of leaving the ash in place and periodically
monitoring the groundwater, 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 options, 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
options.
B2.2 Cap -in -Place (CIP)
For the second option, capping -in -place, 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. This evaluation focuses primarily on the direct
emissions from the engines associated with the on -site activities and truck transport. 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.
B2.3 Excavation and Landfilling
The last option, excavation/landfilling, 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
Appendix B 3 June 30, 2016
Air Emissions Analysis of Remedial Alternatives

0
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 but does not include fugitive dust emissions.
Appendix B 4 June 30, 2016
Air Emissions Analysis of Remedial Alternatives

0
B3 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 (ton/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.
PM10/PM2.5
Cumulative
NOx Emissions
CO2e Emissions
Scenario
Emissions
CO2e Emissions
(tons/yr)
(tons/yr)
(tons/yr)
(tons)
Cap in Place
29.20
1.01
6,453.24
33,508.54
d
Excavation &
138.43
5.91
23,505.31
383,819.67
Landfill
Cap in Place
29.02
1.01
6,399.53
21,118.45
x
U
oa
Excavation &
Landfill
138.47
5.91
23,519.64
110,384.29
Cap in Place
29.43
1.02
6,521.54
19,564.61
w
U
Excavation &
Landfill
138.42
5.91
23,504.36
162,560.70
Cap in Place
29.02
1.01
6,399.69
15,999.23
o
Excavation &
Landfill
138.47
5.91
23,518.04
136,357.55
Cap in Place
116.67
4.05
25,774.00
90,190.83
0
F-
Excavation &
553.79
23.62
94,047.36
793,122.22
Landfill
PSD Significant
40
15/10
NA
NA
Threshold
GHG Reporting
NA
NA
25,000
NA
H
Threshold
Appendix B 5 June 30, 2016
Air Emissions Analysis of Remedial Alternatives

0
As shown in the table, the NOx emissions from the CIP scenario are substantial, about 117 tons/yr,
which is well above the significance level of 40 tons/yr established in the federal Prevention of
Significant Deterioration (PSD) regulations. 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 emissions from the excavation/landfill option are even more significant
and are typically about 554 tons/yr.
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 PMIO/PM2.5
emissions from the CIP alternative are estimated to be about 4 ton/yr and for the excavation/landfill
alternative are about 24 ton/yr. It is important to remember that these value only includes
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 CIP and excavation/landfill alternatives are 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 GHG emissions from the CIP
alternative exceed this threshold for both the CIP and excavation/landfill options on an annual
basis (25,774 ton/yr and 94,047 ton/yr, respectively). Additionally, it is important to note that
there are also other indirect GHG emissions from the remediation, as there are GHG emissions
associated with the production and delivery of the fuels used by the various equipment associated
with the alternatives. A more complete analysis would likely show that the carbon footprint (direct
plus indirect GHG emissions) for these alternatives are much higher than these estimates.
Based on the estimated air emissions and their comparisons with regulatory thresholds, it is
apparent that the air quality impact from capping in place would be considerably higher than
monitoring the ash ponds without capping. The air emissions from excavation of the ash and
transporting it to a landfill would be even more substantial.
Appendix B 6 June 30, 2016
Air Emissions Analysis of Remedial Alternatives

REMOVAL WITH MNA
CAPPING WITH MNA
Site
NOx
PM10/PM2.5
CO2e
Cumulative CO2e
NOx
PM10/PM2.5
CO2e
Cumulative CO2e
Emissions
Emissions
Emissions
Emissions
Emissions
Emissions
Emissions
Emissions
(tons/yr)
(tons/yr)
(tons/yr)
(tons)
(tons/yr)
(tons/yr)
(tons/yr)
(tons)
Allen
138.43
5.91
23,505.31
383,819.67
29.20
1.01
6,4S3.24
33,508.54
Buck
138.47
5.91
23,519.64
110,384.29
29.02
1.01
6,399.53
21,118AS
Cliffside
138.42
5.91
23,504.36
162,S60.70
29.43
1.02
6,S21.54
19,564.61
Mayo
138.47
5.91
23,518.04
136,357.55
29.02
1.01
6,399.69
1S,999.23
Total
553.79
23.62
94,047.36
793,122.22
116.67
4.05
25,774.00
90,190.83
Thresholds
PSD
Significant
40
15/10
NA
NA
40
15/10
NA
NA
Threshold
GHG
Reporting
NA
NA
25,000
NA
NA
NA
25,000
NA
Threshold

Option 1:
Monitor Only
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.
Option 2: Cap in Place (CIP)
CIP Duration = 12 hr/day 270 day/yr 5.2 years 140198 truck trips carrying cap material
203 truck trips carrying liner material
Usage
Emission Factors
Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value
Units
Value
Units
Value
Units
Value
Units
Value
Units
NOx
PM10/PM2.5
CO2e
CO2e
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
0.05
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 Vehicles2,3,1,5,6
121500
miles/yr
0.95
g/mile
0.0045
g/mile
410
g/mile
0.0452
g/mile
0.13
0.00
55.10
286.11
Truck Transport- Cap Material''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 Material''8.9,10,11
39
truck trips/yr
I 1838.20
g/truck trip
1 43.00
Ig/truck trip
I 552000
g/truck trip
1 1.02
g/truck trip
0.08
0.00
23.79
123.53
1
29.20
1.01
6,453.24
33,508.54
Option 3
Landfill Construction Duration =
Excavation Duration =
Closure Duration =
Excavation and Landfill
12 hr/day 300 day/yr 3.6 years 204 truck trips carrying liner material (construction and 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
Usage
Emission Factors
Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value
Units
Value
Units
Value
Units
Value
Units
Value
Units
NOx
PM10/PM2.5
CO2e
CO2e
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 Vehicles2,3,4,5
121500
miles/yr
0.95
g/mile
0.0045
g/mile
410
g/mile
0.0452
g/mile
0.13
0.001
55.101
1967.09

Usage
Emission Factors
Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value
Units
Value
Units
Value
Units
Value
Units
Value
Units
NOx
PM10/PM2.5
CO2e
CO2e
MATERIAL TRANSPORT
Truck Transport - Ash''s,9,10
26989
truck trips/yr
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 Material''$'9'10
16546
truck trips/yr
18.38
g/truck trip
0.43
g/truck trip
5520
g/trucktrip
0.0102
g/truck trip
0.34
0.01
100.68
201.36
Truck Transport - Liner Material"s'9,10,i1
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
22.17
124.13
LANDFILL CONSTRUCT.
8 Tracked Excavators'
25920
hr/yr
0.6603
Ib/hr
0.0332
Ib/hr
120
Ib/hr
0.0089
Ib/hr
8.56
0.43
1558.08
8725.27
8 Dozers'
25920
hr/yr
2.0891
Ib/hr
0.0858
Ib/hr
239
Ib/hr
0.0234
Ib/hr
27.07
1.11
3105.02
17388.12
4 Vibratory Compactors'
25920
hr/yr
0.568
Ib/hr
0.0234
Ib/hr
123
Ib/hr
0.0065
Ib/hr
7.36
0.30
1596.19
8938.64
4 Wheeled Loaders'
12960
hr/yr
0.7114
Ib/hr
0.0375
Ib/hr
109
Ib/hr
0.0089
Ib/hr
4.61
0.24
707.76
3963.47
8 Dump Trucks'
25920
hr/yr
0.0587
Ib/hr
0.0024
Ib/hr
7.6
Ib/hr
0.0008
Ib/hr
0.76
0.03
98.76
553.03
4 Water Trucks'
12960
hr/yr
1.3322
Ib/hr
0.0459
Ib/hr
260
Ib/hr
0.0164
Ib/hr
8.63
0.30
1687.46
9449.76
4 Wheeled Backhoes'
12960
hr/yr
0.4070
Ib/hr
0.0258
Ib/hr
66.8
Ib/hr
0.0055
Ib/hr
2.64
0.17
433.76
2429.03
4 6-8" Pumps'
25920
hr/yr
0.3830
Ib/hr
0.0239
Ib/hr
49.6
Ib/hr
0.0051
Ib/hr
4.96
0.31
644.47
3609.02
4 Maint/Service Trucks'
12960
hr/yr
1.3322
Ib/hr
0.0459
Ib/hr
260
Ib/hr
0.0164
Ib/hr
1 8.63
0.30
1687.46
9449.76
4 55 KVA Diesel Generator'
12960
hr/yr
0.6102
Ib/hr
0.0431
Ib/hr
77.9
Ib/hr
0.0073
Ib/hr
3.95
0.28
505.97
2833.46
100 Personal Vehicles2'3'4,5
810000
miles/yr
0.95
g/mile
0.0045
g/mile
410
g/mile
0.0452
g/mile
0.85
0.00
367
2057.09
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
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
0.0452
g/mile
0.13
0.00
55.10
1967.09
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
Ig/mile
1 0.13
0.00
55.10
110.20
138.43
5.91
23,505.31
383,819.67

Usage
Emission Factors
I Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value I Units
I Value I Units
Value I Units
Value I Units
I Value I Units
I NOx I PM10/P 2.51 CO2e
I CO2e
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/files/publications/nati onal_transportation_statisti cs/htm I/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 forGasoline-FueledPassenger 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 lb GVWR--since it is for
20 ton (40,000 lb) material +truck) --based on the in -use fleet from July 2008 from https://www3.epa.gov/otaq/consumer/420f08027.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 lb (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 lb/roll * 1 ton/2000 lb * 6 rolls/truck trip = 10 ton/truck trip).

Option 1:
Monitor Only
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.
Option 2: Cap in Place (CIP)
CIP Duration = 12 hr/day 270 day/yr 3.3 years 87995 truck trips carrying cap material
114 truck trips carrying liner material
Usage
Emission Factors
Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value
Units
Value
Units
Value
Units
Value
Units
Value
Units
NOx
PM10/PM2.5
CO2e
CO2e
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
2561.64
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
357.85
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
357.85
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
1392.15
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
359.13
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
642.71
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
1392.15
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
417.43
15 Personal Vehicles2,3,1,5,6
121500
miles/yr
0.95
g/mile
0.0045
g/mile
410
g/mile
0.0452
g/mile
0.13
0.00
55.10
181.83
Truck Transport- Cap Material''8'9'10
26665
truck trips/yr
459.55
g/truck trip
10.75
g/truck trip
138000
g/truck trip
0.255
g/truck trip
13.51
0.32
4056.47
13386.34
Truck Transport - Liner Material''8.9,10,11
35
truck trips/yr
I 1838.20
g/truck trip
1 43.00
Ig/truck trip
I 552000
g/truck trip
1 1.02
g/truck trip
0.07
0.00
21.02
69.37
1
29.02
1.01
6,399.53
21,118.45
Option 3
Landfill Construction Duration =
Excavation Duration =
Closure Duration =
Excavation and Landfill
12 hr/day 300 day/yr 1.2 years 70 truck trips carrying liner material (construction and 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
Usage
Emission Factors
Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value
Units
Value
Units
Value
Units
Value
Units
Value
Units
NOx
PM10/PM2.5
CO2e
CO2e
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
3817.30
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
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
Ib/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
Ib/hr
0.0239
Ib/hr
49.6
Ib/hr
0.0051
Ib/hr
1.24
0.08
161.12
1578.95
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
1239.64
15 Personal Vehicles2,3,4,5
121500
miles/yr
0.95
g/mile
0.0045
g/mile
410
g/mile
0.0452
g/mile
0.13
0.001
55.101
539.99

Usage
Emission Factors
Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value
Units
Value
Units
Value
Units
Value
Units
Value
Units
NOx
PM10/PM2.5
CO2e
CO2e
MATERIAL TRANSPORT
Truck Transport - Ash''s,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''$'9'10
16283
truck trips/yr
18.38
g/truck trip
0.43
g/truck trip
5520
g/trucktrip
0.0102
g/truck trip
0.33
0.01
99.08
69.36
Truck Transport - Liner Material"s'9,10,i3
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'
25920
hr/yr
0.6603
Ib/hr
0.0332
Ib/hr
120
Ib/hr
0.0089
Ib/hr
8.56
0.43
1558.08
2960.36
8 Dozers'
25920
hr/yr
2.0891
Ib/hr
0.0858
Ib/hr
239
Ib/hr
0.0234
Ib/hr
27.07
1.11
3105.02
5899.54
4 Vibratory Compactors'
25920
hr/yr
0.568
Ib/hr
0.0234
Ib/hr
123
Ib/hr
0.0065
Ib/hr
7.36
0.30
1596.19
3032.75
4 Wheeled Loaders'
12960
hr/yr
0.7114
Ib/hr
0.0375
Ib/hr
109
Ib/hr
0.0089
Ib/hr
4.61
0.24
707.76
1344.75
8 Dump Trucks'
25920
hr/yr
0.0587
Ib/hr
0.0024
Ib/hr
7.6
Ib/hr
0.0008
Ib/hr
0.76
0.03
98.76
187.63
4 Water Trucks'
12960
hr/yr
1.3322
Ib/hr
0.0459
Ib/hr
260
Ib/hr
0.0164
Ib/hr
8.63
0.30
1687.46
3206.17
4 Wheeled Backhoes'
12960
hr/yr
0.4070
Ib/hr
0.0258
Ib/hr
66.8
Ib/hr
0.0055
Ib/hr
2.64
0.17
433.76
824.13
4 6-8" Pumps'
25920
hr/yr
0.3830
Ib/hr
0.0239
Ib/hr
49.6
Ib/hr
0.0051
Ib/hr
4.96
0.31
644.47
1224.49
4 Maint/Service Trucks'
12960
hr/yr
1.3322
Ib/hr
0.0459
Ib/hr
260
Ib/hr
0.0164
Ib/hr
8.63
0.30
1687.46
3206.17
4 55 KVA Diesel Generator'
12960
hr/yr
0.6102
Ib/hr
0.0431
Ib/hr
77.9
Ib/hr
0.0073
Ib/hr
3.95
0.28
505.97
961.35
100 Personal Vehicles2'3'4'5
810000
miles/yr
0.95
g/mile
0.0045
g/mile
410
g/mile
0.0452
g/mile
0.85
0.00
367
697.94
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
7607.30
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
1062.70
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
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
4134.27
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
1066.51
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
1908.65
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
4134.27
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
1239.64
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
Ib/hr
0.0858
Ib/hr
239
Ib/hr
0.0234
Ib/hr
6.77
0.28
776.26
543.38
Tractor'
3240
hr/yr
0.4070
Ib/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
Ib/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
Ib/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
0.6102
Ib/hr
0.0431
Ib/hr
77.9
Ib/hr
0.0073
Ib/hr
0.99
0.07
126.49
88.55
Personal VehicleS1,3,4,1'6
121500
miles/yr
0.95
g/mile
0.0045
g/mile
410
g/mile
0.0452
g/mile
0.13
0.00
55.10
38.57
138.47
5.91
23,519.64
110,384.29

Usage
Emission Factors
I Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value I Units
I Value I Units
Value I Units
Value I Units
I Value I Units
I NOx I PM10/P 2.51 CO2e
I CO2e
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/files/publications/nati onal_transportation_statisti cs/htm I/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 forGasoline-FueledPassenger 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 lb GVWR--since it is for
20 ton (40,000 lb) material +truck) --based on the in -use fleet from July 2008 from https://www3.epa.gov/otaq/consumer/420f08027.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 lb (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 lb/roll * 1 ton/2000 lb * 6 rolls/truck trip = 10 ton/truck trip).

Option 1:
Monitor Only
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.
Option 2: Cap in Place (CIP)
CIP Duration = 12 hr/day 270 day/yr 3.0 years 82340 truck trips carrying cap material
119 truck trips carrying liner material
Usage
Emission Factors
Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value
Units
Value
Units
Value
Units
Value
Units
Value
Units
NOx
PM10/PM2.5
CO2e
CO2e
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
2328.77
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
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
Ib/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
0.5273
Ib/hr
0.0353
Ib/hr
67
Ib/hr
0.0071
Ib/hr
0.85
0.06
108.83
326.48
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
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
Ib/hr
0.0431
Ib/hr
77.9
Ib/hr
0.0073
Ib/hr
0.99
0.07
126.49
379.48
15 Personal Vehicles2,3,1,5,6
121500
miles/yr
0.95
g/mile
0.0045
g/mile
410
g/mile
0.0452
g/mile
0.13
0.00
55.10
165.30
Truck Transport- Cap Material''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 Material''8.9,10,11
40
truck trips/yr
I 1838.20
g/truck trip
1 43.00
Ig/truck trip
I 552000
g/truck trip
1 1.02
g/truck trip
0.08
0.00
24.14
72.41
1
29.43
1.02
6,521.S4
19,564.61
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 and 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
Usage
Emission Factors
Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value
Units
Value
Units
Value
Units
Value
Units
Value
Units
NOx
PM10/PM2.5
CO2e
CO2e
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
5687.01
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
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
Ib/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
Ib/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
Ib/hr
0.0239
Ib/hr
49.6
Ib/hr
0.0051
Ib/hr
1.24
0.08
161.12
2352.31
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
1846.81
15 Personal Vehicles2,3,4,5
121500
miles/yr
0.95
g/mile
0.0045
g/mile
410
g/mile
0.0452
g/mile
0.13
0.001
55.101
804.47

Usage
Emission Factors
Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value
Units
Value
Units
Value
Units
Value
Units
Value
Units
NOx
PM10/PM2.5
CO2e
CO2e
MATERIAL TRANSPORT
Truck Transport - Ash''s,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''$'9'10
15683
truck trips/yr
18.38
g/truck trip
0.43
g/truck trip
5520
g/trucktrip
0.0102
g/truck trip
0.32
0.01
95.43
95.43
Truck Transport - Liner Material"s'9,10,i3
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'
25920
hr/yr
0.6603
Ib/hr
0.0332
Ib/hr
120
Ib/hr
0.0089
Ib/hr
8.56
0.43
1558.08
4206.83
8 Dozers'
25920
hr/yr
2.0891
Ib/hr
0.0858
Ib/hr
239
Ib/hr
0.0234
Ib/hr
27.07
1.11
3105.02
8383.56
4 Vibratory Compactors'
25920
hr/yr
0.568
Ib/hr
0.0234
Ib/hr
123
Ib/hr
0.0065
Ib/hr
7.36
0.30
1596.19
4309.70
4 Wheeled Loaders'
12960
hr/yr
0.7114
Ib/hr
0.0375
Ib/hr
109
Ib/hr
0.0089
Ib/hr
4.61
0.24
707.76
1910.96
8 Dump Trucks'
25920
hr/yr
0.0587
Ib/hr
0.0024
Ib/hr
7.6
Ib/hr
0.0008
Ib/hr
0.76
0.03
98.76
266.64
4 Water Trucks'
12960
hr/yr
1.3322
Ib/hr
0.0459
Ib/hr
260
Ib/hr
0.0164
Ib/hr
8.63
0.30
1687.46
4556.13
4 Wheeled Backhoes'
12960
hr/yr
0.4070
Ib/hr
0.0258
Ib/hr
66.8
Ib/hr
0.0055
Ib/hr
2.64
0.17
433.76
1171.14
4 6-8" Pumps'
25920
hr/yr
0.3830
Ib/hr
0.0239
Ib/hr
49.6
Ib/hr
0.0051
Ib/hr
4.96
0.31
644.47
1740.06
4 Maint/Service Trucks'
12960
hr/yr
1.3322
Ib/hr
0.0459
Ib/hr
260
Ib/hr
0.0164
Ib/hr
8.63
0.30
1687.46
4556.13
4 55 KVA Diesel Generator'
12960
hr/yr
0.6102
Ib/hr
0.0431
Ib/hr
77.9
Ib/hr
0.0073
Ib/hr
3.95
0.28
505.97
1366.13
100 Personal Vehicles2'3'4'5
810000
miles/yr
0.95
g/mile
0.0045
g/mile
410
g/mile
0.0452
g/mile
0.85
0.00
367
991.81
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
11333.33
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
1583.21
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
1583.21
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
6159.22
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
1588.88
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
2843.50
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
6159.22
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
1846.81
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
Ib/hr
0.0858
Ib/hr
239
Ib/hr
0.0234
Ib/hr
6.77
0.28
776.26
776.26
Tractor'
3240
hr/yr
0.4070
Ib/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
Ib/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
Ib/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
0.6102
Ib/hr
0.0431
Ib/hr
77.9
Ib/hr
0.0073
Ib/hr
0.99
0.07
126.49
126.49
Personal VehicleS1,3,4,1'6
121500
miles/yr
0.95
g/mile
0.0045
g/mile
410
g/mile
0.0452
g/mile
0.13
0.00
55.10
55.10
138.42
5.91
23,504.36
162,560.70

Usage
Emission Factors
I Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value I Units
I Value I Units
Value I Units
Value I Units
I Value I Units
I NOx I PM10/P 2.51 CO2e
I CO2e
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/files/publications/nati onal_transportation_statisti cs/htm I/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 forGasoline-FueledPassenger 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 lb GVWR--since it is for
20 ton (40,000 lb) material +truck) --based on the in -use fleet from July 2008 from https://www3.epa.gov/otaq/consumer/420f08027.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 lb (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 lb/roll * 1 ton/2000 lb * 6 rolls/truck trip = 10 ton/truck trip).

Option 1:
Monitor Only
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.
Option 2: Cap in Place (CIP)
CIP Duration = 12 hr/day 270 day/yr 2.5 years 66623 truck trips carrying cap material
97 truck trips carrying liner material
Usage
Emission Factors
Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value
Units
Value
Units
Value
Units
Value
Units
Value
Units
NOx
PM10/PM2.5
CO2e
CO2e
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
1940.64
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
271.10
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
271.10
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
1054.66
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
272.07
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
486.90
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
1054.66
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
316.23
15 Personal Vehicles2,3,1,5,6
121500
miles/yr
0.95
g/mile
0.0045
g/mile
410
g/mile
0.0452
g/mile
0.13
0.00
55.10
137.75
Truck Transport- Cap Material''8'9'10
26649
truck trips/yr
459.55
g/truck trip
10.75
g/truck trip
138000
g/truck trip
0.255
g/truck trip
13.50
0.32
4054.04
10135.10
Truck Transport - Liner Material''8.9,10,11
39
truck trips/yr
I 1838.20
g/truck trip
1 43.00
Ig/truck trip
I 552000
g/truck trip
1 1.02
g/truck trip
0.08
0.00
23.61
59.02
1
29.02
1.01
6,399.69
15,999.23
Option 3
Landfill Construction Duration =
Excavation Duration =
Closure Duration =
Excavation and Landfill
12 hr/day 300 day/yr 1.5 years 83 truck trips carrying liner material (for construction and closure)
12 hr/day 270 day/yr 12.2 years 330000 truck trips carrying ash
12 hr/day 270 day/yr 0.8 years 13730 truck trips carrying closure material
Usage
Emission Factors
Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value
Units
Value
Units
Value
Units
Value
Units
Value
Units
NOx
PM10/PM2.5
CO2e
CO2e
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
4752.15
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
9470.32
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
2158.67
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
301.20
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
5146.74
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
1322.95
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
1965.63
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
1543.22
15 Personal Vehicles2,3,4,5
121500
miles/yr
0.95
g/mile
0.0045
g/mile
410
g/mile
0.0452
g/mile
0.13
0.001
55.101
672.23

Usage
Emission Factors
Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value
Units
Value
Units
Value
Units
Value
Units
Value
Units
NOx
PM10/PM2.5
CO2e
CO2e
MATERIAL TRANSPORT
Truck Transport - Ash''s,9,10
27049
truck trips/yr
459.55
g/truck trip
10.75
g/truck trip
138000
g/truck trip
0.2550
g/truck trip
13.70
0.32
4114.89
50201.62
Truck Transport- Closure Material''$'9'10
17163
truck trips/yr
18.38
g/truck trip
0.43
g/truck trip
5520
g/trucktrip
0.0102
g/truck trip
0.35
0.01
104.43
83.55
Truck Transport - Liner Material"s'9,10,i1
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
21.96
50.51
LANDFILL CONSTRUCT.
8 Tracked Excavators'
25920
hr/yr
0.6603
Ib/hr
0.0332
Ib/hr
120
Ib/hr
0.0089
Ib/hr
8.56
0.43
1558.08
3583.59
8 Dozers'
25920
hr/yr
2.0891
Ib/hr
0.0858
Ib/hr
239
Ib/hr
0.0234
Ib/hr
27.07
1.11
3105.02
7141.55
4 Vibratory Compactors'
25920
hr/yr
0.568
Ib/hr
0.0234
Ib/hr
123
Ib/hr
0.0065
Ib/hr
7.36
0.30
1596.19
3671.23
4 Wheeled Loaders'
12960
hr/yr
0.7114
Ib/hr
0.0375
Ib/hr
109
Ib/hr
0.0089
Ib/hr
4.61
0.24
707.76
1627.85
8 Dump Trucks'
25920
hr/yr
0.0587
Ib/hr
0.0024
Ib/hr
7.6
Ib/hr
0.0008
Ib/hr
0.76
0.03
98.76
227.14
4 Water Trucks'
12960
hr/yr
1.3322
Ib/hr
0.0459
Ib/hr
260
Ib/hr
0.0164
Ib/hr
8.63
0.30
1687.46
3881.15
4 Wheeled Backhoes'
12960
hr/yr
0.4070
Ib/hr
0.0258
Ib/hr
66.8
Ib/hr
0.0055
Ib/hr
2.64
0.17
433.76
997.64
4 6-8" Pumps'
25920
hr/yr
0.3830
Ib/hr
0.0239
Ib/hr
49.6
Ib/hr
0.0051
Ib/hr
4.96
0.31
644.47
1482.28
4 Maint/Service Trucks'
12960
hr/yr
1.3322
Ib/hr
0.0459
Ib/hr
260
Ib/hr
0.0164
Ib/hr
1 8.63
0.30
1687.46
3881.15
4 55 KVA Diesel Generator'
12960
hr/yr
0.6102
Ib/hr
0.0431
Ib/hr
77.9
Ib/hr
0.0073
Ib/hr
3.95
0.28
505.97
1163.74
100 Personal Vehicles2'3'4'5
810000
miles/yr
0.95
g/mile
0.0045
g/mile
410
g/mile
0.0452
g/mile
0.85
0.00
367
844.88
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
9470.32
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
1322.95
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
1322.95
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
5146.74
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
1327.70
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
2376.08
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
5146.74
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
1543.22
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
672.23
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
621.00
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
86.75
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
86.75
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
337.49
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
87.06
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
155.81
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
337.49
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
101.19
Personal VehicleS1,3,4,1'6
121500
miles/yr
0.95
g/mile
0.0045
g/mile
410
g/mile
0.0452
g/mile
0.13
0.00
55.10
44.08
138.47
5.91
23,518.04
136,357.55

Usage
Emission Factors
I Emissions
Cumulative Emissions
NOx
PM10/PM2.5
CO2
CH4
(tons/yr)
(tons)
Activity
Value I Units
I Value I Units
Value I Units
Value I Units
I Value I Units
I NOx I PM10/P 2.51 CO2e
I CO2e
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/files/publications/nati onal_transportation_statisti cs/htm I/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 forGasoline-FueledPassenger 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 lb GVWR--since it is for
20 ton (40,000 lb) material +truck) --based on the in -use fleet from July 2008 from https://www3.epa.gov/otaq/consumer/420f08027.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 lb (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 lb/roll * 1 ton/2000 lb * 6 rolls/truck trip = 10 ton/truck trip).

EPS
APPENDIX C
Traffic and Implementation Risk Analysis

C
C 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 selection process. Additionally, the risk of property
damage should also be 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.

EPS
C2 TRUCK TRAFFIC RISK
The risks of fatality and injury due to truck traffic associated with ash removal and capping -in -
place 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 was calculated for the construction analysis for each facility.
Significantly more truck miles are associated with the ash removal option than with the capping -
in -place option. 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 in 2014 (Federal Motor Carrier Safety Administration,
2016) 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.

EPS
C3 IMPLEMENTATION RISK
In addition to truck traffic risks, there are substantial risks associated with performing the
excavation, landfill construction, and cap construction. Occupational risks calculated for remedial
alternatives implementation are also presented on Table 1. Data on occupational fatalities and
nonfatal injuries and illnesses was 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) was 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 capping -in -place). 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) was used to calculated 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 an
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 was estimated
based on scope and is outlined in the separate Construction Analysis appendix. Here, 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.

EPS
C4 SAMPLE CALCULATIONS
C4.1 Truck Traffic Risk Calculations
C4.1.1 Fatalities due to Truck Traffic
Ft,2014
Ft = x Dt
Dt,2014
C4.1.2 Injuries due to Truck Traffic
I t,2014
It = x Dt
Dt,2014
C4.1.3 PDO Truck Crashes
Pt,2014
Pt = x Dt
Dt,2014
C4.2 Implementation Risk Calculations
C4.2.1 Fatalities due to Implementation
F FL,2014XT +XTFC,2014
L- _L c
TL,2014 TC,2014
C4.2.2 Injuries and Illnesses due to Implementation
IIL,2014 X T + IC,2014 X T
t _ - L C
TL,2014 TC,2014
C4.3 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 Construction Analysis appendix)

C
It = Injuries resulting from truck traffic, including workers and non -workers (number of cases)
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)
F; = 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)
TL = Total hours worked clearing wooded land (hours), calculated based on a clearing rate of 2
acres per day and a crew size of 17 persons (see Construction Analysis appendix)
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 Construction Analysis
appendix)
I; = 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)

EPS
C5 RESULTS
The calculations show that removing the ash and constructing an offsite landfill will produce
significantly more fatalities and injuries or illnesses for each site considered when compared to the
alternate option of capping in place. 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 ash removal option. 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 capping -in -
place alternative exhibits less risk with an estimated total of 7.5 injuries to the public and 26
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.

C
C6 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 rates2014hb.pd
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:
htlps://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.

Table 1. Summary of Traffic and Implementation Risks
REMOVAL WITH MNA
CAPPING WITH MNA
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
1.8
6.0
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:
11.4
0.5
38.9
131
114
0.3
0.2
7.5
25.8
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
Total number of
traveled - 2014
occupant fatalities -
people" fatalities -
6
occupant injuries -
people" injuries -
injuries per truck
Involving Large
millions 1
2014 1
2014 1
fatalities per mile
20141
20141
mile 6
Trucks - 2014 9
279,132
657
3,246
1.40E-08
27,000
84,000
3.98E-07
326,000
Table 3. Implementation Risk Reference Values
Injuries/Illnesses -
Injuries/Illnesses
Injuries/illnesses
Fatalities - 2014
Total hours worked
Fatalities per hour
Industry
2,3
3
7
2014 (total
incident rate -
per hour worked -
(total number)
(millions) - 2014
worked - 2014
4
s
s
number)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:
MINA - Monitored Natural Attenuation
PDO - Property Damage Only
Values represent total expected fatalities and injuries or illnesses over the estimated lifespan of the project, excluding post MINA activities
(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.

EPS
APPENDIX D
Human Health Contaminant Exposure

C
DI INTRODUCTION
Potential impacts to humans in contact with chemicals in environmental media was estimated for
30 years after implementation of the three corrective action options (Monitored Natural
Attenuation (MNA), Capping, and Excavation). 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 scenarios. The purpose
is not to accurately determine the actual expected risk for each scenario.
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. 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 cancer risk (ELCR) and non -carcinogenic hazard (HI).
Appendix D 1 Jun 30, 2016
Human Health Contaminant Exposure

C
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
scenario 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 capping scenario. 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 excavation scenario all contaminants in
soil would be removed, thus there would be no contaminants in any future AOWs. Accordingly,
there is no projected excavation risk. Table IA and Table 2 show the calculation of the projected
risks for the AOW/seep Soil and Water, 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 IB. 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.

EPS
D3 GROUNDWATER
Groundwater modeling was conducted for each site projecting concentrations in groundwater into
the future for the three different scenarios. 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 scenario 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 scenarios. The output provided contained excel spreadsheets with
concentrations of each of the chemical under each scenario 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 extracted. 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 scenario. 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. Table 3A shows the risk calculations for
the future scenarios. 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 excavation
scenario. The groundwater model presented in the CAP Part 1 report did include the excavation
scenario. The ratio of the excavation model to the MNA model from the CAP Part 1 report was
used to estimate the excavation 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 scenarios 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 scenarios. The MNA scenario is the same scenario as
the current risk assessment. However, the MNA scenario needed to be projected 30 years into the

C
future. The graphs were used to determine the ratio between the concentrations for the MNA
scenario 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 MNA scenario was determined by multiply
the current risk values by 1.5. For the Cap scenario the graphs were used to estimate the ratio of
the concentrations from the Cap scenario to the MNA scenario 30 years from now. The average
of these ratios (0.5) was multiplied by the MNA risk to estimate the Cap risk. The same process
was conducted for the Excavation scenario 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 scenario. The changes in plume size between
these figures were used to estimate the projected risk between the different scenarios 30 years into
the future. The risk for the MNA scenario was estimated by multiplying the current risk by 1.5.
The risk for the Cap scenario was estimated by multiplying the MNA risk by 0.25. The risk for
the Excavation scenario was estimated by multiplying the Cap risk by 0.1. A summary of the
results is presented in Table 3D.

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 the MNA scenario it was assumed
that the risk is the same as in the current risk assessment. Under the Cap and Excavation scenarios
there is minimal if any risk into the future. However, to be conservative for the Cap scenario it
was assumed that the risk is 25% of the MNA risk. It assumed there is no risk under the Excavation
scenario. Table 4 shows the projected risk calculations for on -site soil and Table 5 for on -site
surface water.

EPS
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 the MNA scenario it was assumed that the risk is the same as in the current
risk assessment. Under the Cap and Excavation scenarios there is minimal if any risk into the
future. However, to be conservative it was assumed that the risk under capping would be 25% of
the MNA risk and the risk under excavation would be 10% of the MNA risk. Table 6 shows the
projected risk calculations for off -site soil.

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 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 corrective action scenarios. These surface water
concentrations were then multiplied by the RBCs from the risk assessments for each site to
estimate the risk of the different scenarios 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 scenarios 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 Cap and Excavate scenarios factors of 0.93 and 0.94 (respectively) were estimated by
dividing the projected surface water concentrations for Cap and Excavation by the MNA
concentration. Accordingly, the 30-year Cap and Excavate scenarios 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 scenario in the future, the ratios from current year to 2030 for MNA (1.05) and for MNA
to Cap (0.96) or Excavate (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.

V-S
D7 SUMMARY
Table 8A and Table 8B show the combined risks for each scenario where the risk for each medium
is summed to determine the total risk for each receptor. Figures are shown showing the combined
risks for each receptor in each scenario compared to acceptable risk criteria (HI of 1 and 3 and
ELCR of I E-5 and I E-4).
This information is further summarized on 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.

Table 1A. AOW/Seep Soil
Hazard Index
ELCR
Current Risk
30-year
30-year 30-year
Current Risk
30-year
30-year 30-year
Site
Receptor
Assessment
MNA
Cap Excavate
Assessment
MNA
Cap Excavate
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 1
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
I --
--
--
1 Concentrations for current scenario updated from the original Risk Assessment (see Table 1B)
-- Not Applicable
30-year MNA: same as current risk assessment
30-year Cap: 0.25 x 30-year MNA
30-year Excavate: 0

Table 1B - Revised AOW/Seep Soil Current Condition Risk Calculations
Cliffside
Receptor Analyte EPC (mg/kg)
HI RBC ELCR RBC
HI 3 ELCR 4
Commerical/Industrial Worker Aluminum 15674 1
1.20E+06
0.013
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
1.60E+05
0.064 2.7E-10
0.0090
Commerical/Industrial Worker Manganese 1447 1
Commerical/Industrial Worker Vanadium 39.87 1
5.80E+03
0.0069
Total
0.11 2.3E-06
Construction Worker Aluminum
15674 1
1.50E+06
0.010
_
Construction Worker Arsenic
6.88 2
6.40E+02 9.90E+03
0.011 6.9E-08
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
0.0072
Construction Worker Vanadium 39.87
1
1.50E+04
0.0027
Total
0.036 7.0E-08
Trespasser
Aluminum
156741
3.60E+06
0.0044
Trespasser
Arsenic
6.88 2
1.50E+03
2.40E+03
0.0046 2.9E-07
Trespasser
1.10E+03
2.30E+08
0.020 9.7E-12
Cobalt
Manganese
22.24 2
14471
Trespasser
5.00E+05
0.0029
Trespasser
Vanadium
39.871
_
1.80E+04
0.0022
Total
0.034 2.9E-07
Mayo
Receptor Analyte EPC (mg/kg)
HI RBC ELCR RBC
HI 3 ELCR 4
Commerical/Industrial Worker
Arsenic 8.8 2
4.80E+02
0.018 2.9E-06
Commerical/Industrial Worker
Cobalt 1112
_3.00E+02
3.50E+02 8.30E+06
0.031 1.3E-10
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 9.90E+03
0.014 8.9E-08
Construction Worker Cobalt
ill
4.40E+03 4.30E+08
0.0025 2.6E-12
Construction Worker Iron 209217 1
1.00E+06
0.21
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
Cobalt
Trespasser
112
1.10E+03 2.30E+08
0.010 4.8E-12
Iron
2.50E+06
Trespasser
209217 1
0.084
Trespasser
0.012
Manganese
60661
5.00E+05
Total
0.11 3.7E-07
1 Original EPC from risk assessment
2 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

Table 2. AOW/Seep Water
Hazard Index
ELCR
Current Risk
30-year
30-year 30-year
Current Risk
30-year
30-year 30-year
Site
Assessment
MNA
Cap Excavate
Assessment
MNA
Cap Excavate
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 Cap: 0.25 x 30-year MNA
30-year Excavate: 0

Table 3A. Cliffside Groundwater Risk
Const Wkr
Const Wkr
30 Year Modeled Groundwater 2
30
Year Estimated
HI 3
30 Year Estimated ELCR 4
MNA
Cap
Excavate
MNA
Cap
Excavate
MNA
Cap Excavate
Analyte
HI RBC ELCR RBC
µg/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

Table 3B. Allen Groundwater Risk
Const Wkr Const Wkr
30 Year Modeled Groundwater 2
30
Year Estimated
HI 3
30 Year Estimated ELCR 4
MNA
Cap
Excavate
MNA
Cap
Excavate
MNA Cap Excavate
Analyte
HI RBC ELCR RBC
µg/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
1 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

Table 3C. Buck Groundwater Risk
Hazard Index
ELCR
Current Risk 30-year 30-year 30-year
Current Risk 30-year 30-year 30-year
Receptor
Assessment MNAl CapZ Excavate3
Assessment MNAl Cape Excavate3
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
Hazard Index
ELCR
Current Risk 30-year 30-year 30-year
Current Risk 30-year 30-year 30-year
Receptor
Assessment MNAl CapZ Excavate3
Assessment MNAl Cape Excavate3
Construction Worker
1.00E-03 0.0015 0.0004 0.00015
-- -- -- --
1 30-year MNA = Current Risk Assessment x 1.5
2 30-year Cap = 30-year MNA x 0.25
2 30-year Cap = 30-year MNA x 0.1
-- Not applicable

Table 4. On -Site Sediment
Hazard Index
ELCR
Current Risk
30-year
30-year 30-year
Current Risk
30-year
30-year 30-year
Site
Receptor
Assessment
MNA
Cap Excavate
Assessment
MNA
Cap Excavate
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
2.5E-08
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
8.737E-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 Cap: 0.25 x 30-year MNA
30-year Excavate: 0

Table 5. On -Site Surface Water
Hazard Index
ELCR
Current Risk
30-year
30-year 30-year
Current Risk 30-year 30-year 30-year
Site
Receptor
Assessment
MNA
Cap Excavate
Assessment MNA Cap Excavate
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 Cap: 0.25 x 30-year MNA
30-year Excavate: 0

Table 6. Off -Site Sediment
Hazard Index
ELCR
Current Risk
30-year
30-year
30-year
Current Risk
30-year
30-year
30-year
Site
Receptor
Assessment
MNA
Cap
Excavate
Assessment
MNA
Cap
Excavate
Allen
Commerical/Industrial Worker
--
--
--
--
--
--
--
--
Construction Worker
--
--
--
--
--
--
--
--
Trespasser
--
--
--
--
--
Boater
0.00017
0.00017
0.000042
1.7E-OS
--
--
--
--
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
1.6E-08
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
5.533E-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 Cap: 0.25 x 30-year MNA
30-year Excavate: 0

Table 7A. Off -Site Surface Water: Allen
2046 MNA
2046 Cap
2046 Excavate
Model CGW
CSW Chronic
Model CGW
CSW Chronic
Model CGW
CSW Chronic
Analyte Criver
(µg/L)
(µg/L)
(µg/L)
(µg/L)
(µg/L)
(µg/L)
(µg/L)
Aluminum
251
8128
12
63
0.30
7146
10
58
0.30
2735
2.5
38
0.26
Cobalt 0.25
Manganese
5 1
9355
48
8224
43
3147
20
Zinc
0.0051
50
0.241
44
0.211
17
0.083
1 Not included in surface water model. Cf1Vef based on 1/2 of typical detection limits.
Cs = (QGWXCGW + QriverXCriver)/ (Qgw + Qriver)
QGW (cfs) 0.64
Qriver(Cf5) 137.0882
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 Cap Excavate
µg/L µg/L µg/L
MNA Cap Excavate
MNA Cap Excavate
Boater Aluminum
5.6E+07 --
4.2E+04 --
3.1E+05 --
2.8E+07 --
63 58 38
0.30 0 0
1.1E-06 1.0E-06 6.7E-07
-- -- --
-- -- --
-- -- --
-- -- --
Boater
ICobalt
7.2E-06 7.1E-06 6.2E-06
Boater
Manganese
48 43 20
1.6E-04 1.4E-04 6.3E-05
8.5E-09 7.5E-09 3.0E-09
Boater Zinc
0.24 0 0
Total
1.6E-04 1.5E-04 7.0E-05
-- -- --
Swimmer
Swimmer
Aluminum
Cobalt
1.1E+06 --
3.5E+02 --
63 58 38
0.30 0 0
5.7E-05 5.3E-05 3.4E-05
8.6E-04 8.5E-04 7.4E-04
-- -- --
-- -- --
Swimmer
Manganese
4.1E+04 --
48 43 20
1.2E-03 1.1E-03 4.8E-04
Swimmer
Zinc
3.4E+05 --
0.24 0 0
7.0E-07 6.2E-07 2.5E-07
-- -- --
Total
2.1E-03 2.0E-03 1.3E-03
-- -- --
Wader
Wader
Aluminum
1.2E+06 --
3.6E+02 -
9.0E+04 --
3.6E+05 -
63 58 38
0.30 0 0
5.2E-05 4.8E-05 3.1E-05
8.4E-04 8.2E-04 7.2E-04
-- -- --
-- -- --
Cobalt
Wader
Wader
Manganese
48 43 20
0.24 0 01
5.4E-04 4.8E-04 2.2E-04
6.6E-07 5.8E-07 2.3E-07
-- -- --
-- -- --
Zinc
Total
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

Table 7B. Off -Site Surface Water: Cliffside
2046 MNA
2046
Cap
2046 Excavate
Analyte
Criver
Model CGW
CSW Chronic
Model CGW
CSW Chronic
Model CGW
CSW Chronic
(µg/L)
(µg/L)
(µg/L)
(µg/L)
(µg/L)
(µg/L)
(µg/L)
Aluminum
251
27163
9681
1678
594
27138
1676
26743
9531
1652
585
Manganese 5 1
9672 594
Zinc
0.0051
153
9.34
151
9.20
153 9.35
1 Not included in surface water model. C,1Vef 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)/ (C gw + Qriver)
CtcW (cfs) 0.14
Qriver (Cf5) 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 Cap Excavate
µg/L µg/L µg/L
MNA Cap Excavate
MNA Cap Excavate
Boater
Boater
Aluminum
Manganese
5.6E+07 -
3.1E+05 --
2.8E+07 --
_ 1678
594
9.35
1676
594
9
1652
585
9
3.0E-05
3.0E-05
3.0E-05
-- -- --
-- -- --
-- -- --
1.9E-03 1.9E-03
1.9E-03
Boater
Zinc
3.3E-07 3.3E-07
3.3E-07
Total
1.9E-03
1.9E-03
1.9E-03
-- -- --
Swimmer
Swimmer
Aluminum
1.1E+06� _ --
4.1E+04 -
3.4E+05 -
1678
594
9.35
1676
594
9
1652
585
9
1.5E-03
1.4E-02
1.5E-03
1.4E-02
1.5E-03
1.4E-02
-- -- --
-- -- --
-- -- --
Manganese
Swimmer
Zinc
2.7E-05 2.7E-05
2.7E-05
Total
I
1.6E-02
1.6E-02
1.6E-02
-- -- --
Wader
Wader
Wader
Aluminum
1.2E+06 -
9.0E+04 --
3.6E+05 -
1678
594
9.35
1676
594
9
1652
585
9
1.4E-03
1.4E-03
1.4E-03
-- -- --
Manganese
6.6E-03 6.6E-03
2.6E-05 2.6E-05
6.5E-03
2.6E-05
-- -- --
-- -- --
Zinc
Total
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

Table 7C. Off -Site Surface Water: Buck
Receptor
Hazard Index
ELCR
Current Risk 30-year 30-year
Assessment MNA1 Cape
30-year
Excavate3
Current Risk 30-year 30-year 30-year
Assessment MNA1 Cape Excavate3
Boater
0.00099
0.0010
0.0010
0.00098
-- -- -- --
-- -- -- --
-- -- -- --
Swimmer
Wader
0.0077 0.0081 0.0075
0.0075999
0.0035 0.0037 0.0034
0.0035
1 30-year MNA = Current Risk Assessment x 1.05
2 30-year Cap = 30-year MNA x 0.93
2 30-year Cap = 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 MNAl Capz Excavate3
Assessment MNAl Capz Excavate3
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 Cap = 30-year MNA x 0.96
2 30-year Cap = 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,

Table 8A. Total Hazard Index for Each Receptor and Scenario
30-Year MNA - 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
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
Trespasser
3.0E-02
1.1E-02
--
5.9E-04
4.3E-03
--
--
4.6E-02
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
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
Swimmer
--
--
--
--
--
1.3E-02
8.1E-03
2.1E-02
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
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
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
30-Year Cap - 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
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
Trespasser
7.6E-03
2.8E-03
--
1.5E-04
1.1E-03
--
--
1.2E-02
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
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
Swimmer
--
--
--
--
--
3.3E-03
7.5E-03
1.1E-02
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
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
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
2.0E-01
Wader
--
--
--
--
--
7.5E-04
1.0E-01
1.0E-01
30-Year Excavate - 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
--
-- -- -- --
--
--
0.0E+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

Table 8B. Total ELCR for Each Receptor and Scenario
30-Year MNA - 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
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
-- - - -- -- -- -
Rec Fisher
--
-
--
--
--
-- -
Sub Fisher
-- -- -- - -- - -
Swimmer
--
-
-
--
--
- -
Wader
Buck
Commerical/Industrial Wkr
2.2E-06
2AE-08
-
2.6E-09
-
- -
22E-06
Construction Worker
6.6E-08
-
1.1E-08
-
-
- -
7.7E-08
9.4E-07
Trespasser
2.7E-07 6.4E-07 - 2.5E-08 - - -
Boater
--
-
-
-
-
1.6E-08 -
1.6E-08
Rec Fisher
-- - - 0.0E+00 O.OE+00 0.0E+00 -
Sub Fisher
--
-
-
0.0E+00
0.0E+00
0.0E+00 -
1.7E-07
Swimmer
-- - - - - 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
Construction Worker
7.0E-08
-
4.2E-09
-
-
- -
7.4E-08
2.5E-06
Trespasser
2.9E-07 2.1E-06 - 8.7E-08 - - -
Boater
--
-
-
-
-
5.5E-08 -
5.5E-08
Rec Fisher
-- - - 0.0E+00 0.0E+00 0.0E+00 -
Sub Fisher
--
-
-
0.0E+00
0.0E+00
0.0E+00 -
5.9E-07
Swimmer
-- - - - - 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
4.7E-07
Trespasser
3.7E-07 - - 1.0E-07 - - -
Boater
--
-
-
-
-
- -
Rec Fisher
-- - - 0.0E+00 O.OE+00 0.0E+00 -
Sub Fisher
--
--
--
0.0E+00
0.0E+00
0.0E+00 -
Swimmer
--
-
--
--
-
- -
Wader
30-Year Cap -ELCR
AOW
AOW Groundwater On -Site On -Site
Off -Site Off -Site
Total
Site::
Receptor
Sol[
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
-
- -
-
- -
1:5E-12
1.4E-08
Trespasser
3.3E-12 1.3E-08 8.2E-10 - - - -
Boater
--
-
- -
-
-
Rec Fisher
-- - - - - -
Sub Fisher
--
-
- -
-
- -
Sw1mmer
-- - - - - - -
Wader
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
2.3E-07
Trespasser
6.8E-08 1.6E-07 - 6.3E-09 - - -
Boater
--
-
- -
-
4.0E-09 -
4.0E-09
Rec Fisher
-- - - 0.0E+00 0.0E+D0 0.0E+DO -
Sub Fisher
--
-
- 0.0E+0D
0.0E+00
0.0E+DO -
4.3E-08
Swimmer
-- - - - - 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
Construction Worker
1.7E-08
-
4.2E-09 -
-
- -
2.22E-OS
62E-07
Trespasser
72E-08 5.3E-07 - 2.2E-08 - - -
Boater
--
-
- -
-
1.4E-08 -
1.4E-08
Rec Fisher
-- - - 0.0E+00 0.0E+D0 0.0E+DO -
Sub Fisher
--
-
- 0.0E+0D
0.0E+00
0.0E+DO -
1.5E-07
Swimmer
-- - - - - 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
12E-07
Trespasser
92E-08 - - 2.5E-08 - - -
Boater
--
-
- -
-
- -
Rec Fisher
-- - - 0.0E+00 0.0E+D0 0.0E+DO -
Sub Fisher
-
-
- 0.0E+00
0.0E+00
0.0E+DO -
Swimmer
- - - - - - -
Wader
30-Year Excavate -
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
--
-- O.0E+00
--
--
-- --
--
Construction Worker
--
-- 1.4E-10
--
--
-- -
1.4E-10
--
Trespasser
-- -- -- -- --
Boater
--
-- --
--
--
- -
Rec Fisher
-- -- -- -- -- - -
Sub Fisher
--
-- -
--
--
-
Swimmer
-- - - -- - -
Wader
Buck
Commerical/Industrial Wkr
--
- 0.0E+00
-
-
- -
Constructian Worker
--
- 6.3E-09
-
-
- -
6.3E-09
Trespasser
-- - - - - - -
Runter
--
- -
-
-
1.6E-09 -
1.26E-09
Rec Fisher
-- - - 0.0E+00 0.0E+00 0.0E+00 -
Sub Fisher
--
- -
0.0E+00
O.OE+DO
0.0E+DO -
1.7E-08
Swimmer
-- - - - - 1.7E-08 -
Wader
6.6E-09
6.6E-09
Cliffside
Commerical/Industrial Wkr
--
- 0.0E+00
-
-
- -
Construction Worker
-
- 4.2E-09
-
-
- -
4.2E-09
Trespasser
-- - - - - - -
Boater
--
- -
-
-
5.5E-09 -
5.5E-09
Rec Fisher
-- - - 0.0E+00 0.0E+00 0.0E+00 -
Sub Fisher
--
- -
0.0E+00
O.OE+00
0.0E+DO -
5.9E-08
Swimmer
-- - - - - 5.9E-08 -
Wader
2.3E-08
2.3E-08
Mayo
Commerical/Industrial Wkr
--
- 0.0E+00
-
-
- -
Construction Worker
--
- -
-
-
- -
--
Trespasser
- - - - - - -
Boater
-
- -
-
--
- -
Rec Fisher
- - - 0.0E+00 0.0E+00 0.0E+00 -
5ub Fisher
-
- -
0.0E+00
0.0E+00
0.0E+00
Swimmer
- - - - - -
Wader

Table 9. Summary of Risks for Each Scenario
Allen
Hazard Index
ELCR
On -Site Off -Site
On -Site Off -Site
MNA
0.1 0.004
5 E-08 --
Cap
0.02 0.002
1E-08 --
Excavate
1 0.004 0.001
1E-10 --
Buck
Hazard Index
ELCR
On -Site Off -Site
On -Site Off -Site
MNA
0.2 0.02
2 E-06 2 E-07
Cap
0.05 0.01
6E-07 4E-08
Excavate
1 0.0006 0.009
6E-09 2E-08
Cliffside
Hazard Index
ELCR
On -Site Off -Site
On -Site Off -Site
MNA
0.2 0.02
2E-06 6E-07
Cap
0.04 0.02
6E-07 1E-07
Excavate
1 0.01 0.02
4E-09 6E-08
Mayo
Hazard Index
ELCR
On -Site Off -Site
On -Site Off -Site
MNA
0.3 0.2
3E-06 --
Cap
0.09 0.2
7E-07 --
Excavate
1 0.0002 0.2
-- --
On-Site: Maximum of commercial/industrial worker,
construction worker and trespasser
Off -Site: Maximum of boater, swimmer and wader

3
2.5
2
1.5
1
0.5
0
3
2.5
2
1.5
1
0.5
0
Allen -HI-30Yr
MNA Cap Excavation
■ Commerical/Industrial Wkr ■ Construction Worker ■ Trespasser ■ Boater ■ Swimmer ■ Wader
Buck - HI - 30 Yr
MNA Cap Excavation
■Commerical/Industrial Wkr ■ Construction Worker ■Trespasser ■Boater ■Swimmer 0Wader

Cliffside - HI - 30 Yr
3
2.5
2
1.5
1
0.5
0
M NA Cap Excavation
■ Commerical/Industrial Wkr ■ Construction Worker ■Trespasser ■ Boater ■ Swimmer ■ Wader
Mayo -HI-30Yr
3
2.5
2
1.5
1
0.5
■_■. _ ■__ _ a :■ _ ■
M NA Cap Excavation
■Commerical/Industrial Wkr ■ Construction Worker ■Trespasser ■Boater ■Swimmer 0Wader

1.00E-04
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 Cap Excavation
■ Commerical/Industrial Wkr ■ Construction Worker ■ Trespasser ■ Boater ■ Swimmer ■ Wader
Buck - ELCR - 30 Yr
MNA Cap Excavation
■ Commerical/Industrial Wkr ■ Construction Worker ■ Trespasser ■ Boater ■ Swimmer ■ Wader

1.00E-04
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
Cliffside - ELCR - 30 Yr
MNA Cap Excavation
■ Commerical/Industrial Wkr ■ Construction Worker ■ Trespasser ■ Boater ■ Swimmer ■ Wader
Mayo - ELCR - 30 Yr
MNA Cap Excavation
■ Commerical/Industrial Wkr ■ Construction Worker ■ Trespasser ■ Boater ■ Swimmer ■ Wader

Updated EPC Calculations

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_SD_20150627
Arsenic
51.4
1
detect
AOW Soil
CLFTD052
CLFTD052_SD_20150627
Arsenic
33.2
1
detect
AOW Soil
CLFTDO04
CLFTDO04_SD_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
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

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-1 7SD20150603
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-1 9SD20150603
Cobalt
50.4
1
detect
AOW Soil
S-11
S-1 1SD20150629
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-1 5SD20150602
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
Outlier Tests for Selected Uncensored Variables
User Selected Options
Date/Time of Computation 6/21/2016 10:05:21 AM
From File As Co.xls
Full Precision OFF
Rosner's Outlier Test for Cobalt
Mean 56.06
Standard Deviation 169.2
Number of data 29
Number of suspected outliers 4
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

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

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.

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

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.

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
1
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
1
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)

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

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.

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
11661
For gamma distributed detected data, BTVs and UCLs may be computed using gamma distribution on KM estimates

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.

EPS
APPENDIX E
Ecological Habitat Services

0
ECOLOGICAL HABITAT SERVICES
The purpose of this evaluation was to understand how the Removal and CIP alternatives might
affect ecological habitat values associated with the Allen, Buck, Cliffside, and Mayo Steam Station
sites. A geographic information system (GIS) analysis was conducted in order to quantify the
dimensions of the major land cover types presently existing in those areas of each site (e.g., basins)
that would be affected by implementation of either the CIP or Removal alternatives. The land
cover types were established based upon review of GIS files data provided by HDR and SynTerra,
aerial photography and site visits. The land cover types included the following:
Terrestrial Habitats
•
Bottomland Hardwoods
•
Mixed Hardwoods
•
Mixed Pines
•
Oak Hickory Hardwoods
•
Pine Plantation
•
Early Successional
•
Scrub Shrub
•
Ash
Wetlands
•
Emergent
•
Forested
•
Open Water
Other
•
Parking/Roads
•
Other features
Through GIS polygon analysis, the projected affected aerial dimensions of each land cover type
that would undergo alteration by either the CIP or Removal alternatives were determined for each
site, including a 30-foot work zone buffer around each basin that was would be affected by each
alternative. These data were grouped by major habitat type for purposes of the evaluation (Table
E-1). The focus was on how the terrestrial and wetland/surface water habitats will be affected
given implementation of the alternatives.
Appendix E 1 June 30, 2016
Ecological Habitat Services

EPS
Table E-1. 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.
Site
Allen
Buck
Cliffside
Mayo
Total Evaluation Area (acres)
342
196
195
181
Terrestrial
Early Successional/Shrub Scrub
99.9
52.1
42.2
42.5
Forest
34.2
36.3 1
25.1
11.0
Open Field -Grass
72.9
34.2
51.5
14.0
Wetland
Wetland and Surface Water
98.0
64.5
1 44.6
�79.2
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.
Appendix E 2 June 30, 2016
Ecological Habitat Services

EPS
El ECOSYSTEM SERVICES ASSESSMENT
METHODOLOGY
An integral part of the NEBA approach is to understand the value of the ecosystem services being
provided within the study area. Ecosystem services can be viewed as both ecological and human
use services. It is important to understand that many human use services are provided by the
presence of the ecological 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 affecting ecological habitats can result in significant human use
service losses while actions that enhance habitats can result in increased human use value.
Importantly, the net environmental benefits will be assessed using the current status of the
environment (the project baseline) against which the potential change in ecosystem service values
associated with each of the remedial alternatives will be compared.
Since these benefits and costs occur over varying time frames, they can be normalized to their net
present value 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. NEBA incorporates the use of
ecological service valuation methods such as habitat equivalency analysis (HEA) and resource
equivalency analysis (REA) to evaluate changes in habitat value over time.
E1.1 Ecological Services
The primary method by which changes in ecological services (i.e., habitat quality) associated with
the various alternatives was evaluated was through the use of the HEA methodology. Actions
potentially affecting ecological services include both physical implementation impacts as well as
impacts associated with chemical releases and/or residuals. This methodology requires the
evaluation of available data to select and identify appropriate metric(s) that will represent overall
habitat service flows from the environment. Our evaluation focused on the direct habitat impacts
as well as indirect impacts (i.e., influences on adjacent areas, etc.).
Because many ecological habitat services are not traded in the marketplace, they do not have a
direct monetary value. The HEA approach is a service quantification approach that evaluates
ecological habitat service losses and 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.
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). We used the HEA methodology to quantify the relative
impacts or benefits, independent from each other, associated with the remedial alternatives.
Appendix E 3 June 30, 2016
Ecological Habitat Services

0
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, 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 the scientific knowledge. The metric(s) are typically incorporated into
a curve that represents the loss or gain of services over time.
Aside from a base year, the ecological service calculations also involve a discount rate that allows
for the gains and losses to be evaluated from a net present value (NPV) standpoint. Within the
HEA methodology, 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. The discount rate is the rate at which the public is indifferent to consuming goods
now or sometime in the future. We used a 3% discount rate, this rate commonly used in NRDA
cases across the country.
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 of the shape of the various ecological habitat service flow curves 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 and
incorporated into the European Union Environmental Liabilities Directive (EU ELD).
The analysis of changes in ecological services was conducted by examining how changes in the
existing habitats will occur given implementation of the CIP and Removal alternatives. The
analysis conducted herein addressed the major terrestrial, wetland/surface water, and grass/field
habitats likely to be affected.
Terrestrial —Forest, Shrub Scrub, and Grass/Open Field Analysis
For the terrestrial analysis, three ecological service flow graphics were developed for each site per
habitat type. The curves represent how the service level might change over time (the flow of value)
given the implementation of each alternative.
United States v Melvin Fisher , 977 F. Supp 1193 (SD Fla 1997); United States, et al v Great Lakes Dredge and Dock Co, Docket no 97-
02510-CV-EBD (SD Fla 2001).
Appendix E 4 June 30, 2016
Ecological Habitat Services

0
E1.2 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 forest,
and increases as the forest moves through successional stages, as projected through time in Figure
E 1 (adapted from McMahon et al. 2010). That is, as the vertical structure and complexity increases,
so does the ecological value and biodiversity. "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).
100
0
v
U
> 75
L
v
V)
U
U
Up 50
O
O
U
W
4-
0
25
L
O
U_
011 1 1 1
0 50 100 150 200 250
Years
Figure E1. Graphic showing the relationship between above -ground biomass (AGB) and
stand age of multiple forest plots in a temperate deciduous forest in Edgewater, MD.
Adapted from McMahon et al. (2010).
In addition, in a typical forest the diversity increases as succession proceeds to climax as shown in
Figure E2 (Enviroscience 2016).
Appendix E 5 June 30, 2016
Ecological Habitat Services

young mature forest
climax
Y;"<r� 20 40 60 80
EPS
old growth
— — — — • — moist coniferous forest
♦
♦
♦
pine forest
Stages of Succession
100
Figure E2. Graphic showing the relationship between diversity and production of forest
at different stages of succession. Reproduced from Enviroscience (2008).
The assumption of the projected forest value based upon Figure E1 was kept consistent with all
alternatives. This will keep the comparison of flow changes across alternatives consistent. The
baseline ecosystem service value for forest habitat at the Allen site is depicted in Figure E3. Note
that the value estimate starts at an approximate age of 25 years for the forest stands being evaluated.
This is conservative in estimating the baseline value as the tree stands are likely older on average
than 25 years of age. Additionally, the flow of value, for all sites and scenarios was calculated over
a 200-year period, 2016-2216. For shrub -scrub habitat, the start time on the successional curve
was adjusted to 5 years.
Appendix E 6 June 30, 2016
Ecological Habitat Services

100
0
V)
v
v 75
i
N
to
ro
u
50
3b
O
Current age
Ou
of tree
stands
w
n
25
N
i
O
LL
0
0 t2016
/
On -site baseline value (34.2 acres) 539 dSAYs
Baseline forest ecological
services projected into future
50 100 150 200 250
t2216
Years
EPS
Figure E3. Ecological service flow framework used to evaluate service flow changes on forest
habitats at the Allen Steam Station — depicts current baseline of ecosystem service
flows into the future.
This curve shows the conceptual model under which the forest dSAY value (539) was calculated.
The value was discounted at a 3% discount rate. This represents the loss of service value projected
into the future with removal of the forest habitat.
For the grass/open field habitats, they would convert to grass under the CIP alternative, or
regenerate to forest under the Removal alternative.
EU CIP Alternative
The next step was to evaluate how ecological services would change given implementation of the
CIP and Removal options, for each site.
For the CIP alternative, the "red" area in Figure E4 represents the loss of forest habitat value when
that forest habitat is removed for the cap construction. The tree removal for the CIP alternative at
the Allen site will take several years to be completed, so the initial loss is calculated over that
removal time frame. As can be seen in Figure E4, when 36.4 acres of forest habitat are removed,
the future stream of benefits that the forest provides is also lost. The on -site forest loss is -505
dSAYs. It should be kept in mind that a significant amount of cover material will need to be
brought into each site as part of the CIP alternative. In the case of the Allen site, it was estimated
that, as part of the construction evaluation provided in Appendix A, 190 acres of forest off -site
Appendix E 7 June 30, 2016
Ecological Habitat Services

0
would need to be removed to provide an area from which to obtain enough cover material to
support the CIP development. The need for fill material and off -site forest impacts results in an
estimated loss of -2,992 dSAYs.
However, positive ecological services will be generated from the cap grass habitat once it is
completed (Figure E4) and natural regeneration of the forest in the area where the landfill cover
material was obtained. Mowed grass habitat is significantly less valuable forest habitat. Based
upon Figures E1 and E2, I assumed that mowed grass habitat has one -tenth the value of forest
habitat. This is likely an overestimate of the value of the grass habitat compared to the forest habitat
(based upon diversity, carbon, etc.) but I was conservative in order to not overestimate the loss of
forest habitat value from the CIP alternative. The estimated positive ecological service value of
the grass cap for the Allen site is 91 dSAYs. In addition, I did not calculate the edge effects that
would result from conversion of forest to grass, so was conservative in estimating the loss of value
associated with the CIP alternative. As shown in Figure E4, the grass value remains constant after
it is in place as it is a mowed and maintained habitat.
In addition, the off -site forest area that was impacted to gain cover material will naturally recover.
It will therefore provide positive ecological service value that would follow the same curve shape
as depicted in Figure El but the recovery start point will be delayed several years for each site
depending upon the pace of removal for the CIP development. The time that this recovery would
start is based upon the years in which the cover material would be removed from the offsite area
and ranges from 3-6 years depending upon the site. The estimated gain in forest value provided by
the regeneration of the forest at the off -site cover material area was estimated to be 1,844 dSAYs.
The overall estimated net loss of forest ecological service value for the Allen Station was -1,562
dSAYs.
0
100
75
50
25
0
0
Lost on -site forest ecological
services projected into the future
On -site forest loss (34.2 acres) -505 dSAYs
Off -site forest loss (190 acres) -2,992 dSAYs
FV44 Off -site forest regeneration (190 acres) 1,844 dSAYs
0#4 Net Loss -1,562 dSAYs
Grass cap ecological services with cap -in -place 91 dSAYs
t2016
50 100 150 200 t2216 250
Years
Appendix E 8 June 30, 2016
Ecological Habitat Services

EPS
Figure E4. Ecological service flow framework used to evaluate service flow changes, on
forest habitats that will be associated with the "Cap -in -Place" option, at the Allen
Steam Station.
E1.4 Removal Alternative
I next estimated the net change in ecological value for the Removal alternative. The ecosystem
service curve for this scenario is presented in Figure E5.
100
0
Ln
v
U
75
L
v
up 50
O
O
v
w
4-
25
L
O
1.L
Lost on -site forest ecological
services projected into the future
V On -site forest losses (34.2 acres) -505 dSAYs
On -site forest regeneration (34 acres) 135 dSAYs
Off -site forest losses (319 acres) -5,024 dSAYs
Off -site forest regeneration (93 acres) 903 dSAYs
011 I
0 50 100 150 200
t2016 t2216
Years
Figure E5. Ecological service flow framework used to evaluate service flow changes, on forest
habitats that will be associated with the "Removal" option, at the Allen Steam Station.
As can be seen in Figure E5, the on -site forest losses with the Removal alternative remain at -505
dSAYs, but do get offset to some extent as the end condition after removal is a natural forest
through regeneration as depicted by the "green" area. The on -site regeneration value is 135 dSAYs.
Similar to the CIP alternative, there will also be offsite forest ecological losses associated with the
creation of a new landfill disposal area plus the additional loss of ecological habitat associated
with cover material area of about -5,024 BAYS. The off -site cover material area will gain some
ecological value as it naturally regenerates (903 dSAYs). These data are depicted in Figure E5.
The overall estimated net loss of forest ecological service value for the Allen Station under the
Removal alternative was -4,491 dSAYs.
This process was conducted for all four sites, and habitat type groupings (forest, shrub -scrub,
wetland/surface water, and grass/open field).
Appendix E 9 June 30, 2016
Ecological Habitat Services

0
E2 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 enough to identify impacts and differences between alternatives.
The ecosystem service value curves for all four stations, habitat types, and remedial alternatives
are depicted in Figures E3 through E50 (at the end of this appendix). The figures provide a
representation of multiple actions affecting ecosystem service values, both positive and negative
given actions affecting ecological services.
The results of the analysis, across all sites are presented in Table E2.
Table E2. Summary of changes in ecological service value associated with the CIP and
Removal alternatives.
Table E2. Summary of changes
in ecological service value associated with the CIP and Removal alternatives (units in dSAYs).
Ecosystem service changes
associated with each action, by
site and habitat type.
Allen
Allen
Allen
Allen
Buck
Buck
Buck
Buck
Cliffside
Cliffside
Cliffside
Cliffside
Mayo
Mayo
Mayo
Mayo
Forest
SS/ES
Wetland
Grass
Forest
SS/ES
Wetland
Grass
Forest
SS/ES
Wetland
Grass
Forest
SS/ES
Wetlan
Grass
MNA
Action
539
1,129
3,356
250
572
587
2,191
117
395
474
1,541
176
173
474
2,705
48
CAP In Place
Onsite
Cap Grass
91
266
261
194
103
139
170
91
71
112
120
137
32
112
210
37
Onsite
Removal
(505)
(1,129)
(3,074)
(250)
(554)
(587)
(622)
(117)
(383)
(474)
(437)
(176)
(168)
(474)
(767)
(48)
Offsite
Removal
(2,992)
(1,921)
(1,811)
(1,480)
Offsite
Regeneration
1,844
1,296
1,221
998
SubTotal
(1,562)
(863)
(2,813)
(56)
(1,076)
(448)
(452)
(26)
(902)
(362)
(317)
(39)
(618)
(362)
(557)
(11)
Removal
Onsite
Removal
(505)
(1,129)
(2,037)
(250)
(554)
(587)
(1,330)
(117)
(383)
(474)
(935)
(176)
(168)
(474)
(1,642)
(48)
Onsite
Regeneration
135
396
951
288
313
206
621
135
186
166
437
204
87
166
767
55
Offsite
Removal
(5,024)
(2,032)
(2,646)
(2,347)
Offsite
Regeneration
903
372
499
1
1
1 435
SubTotal
(4,491)
(733)
(1,086)
38
(1,901)
(381)
(709)
18
(2,344)
(308)
(499)
28
(1,993)
(308)
(875)
7
Forest, early successional, and grass habitat values were combined and are presented in Table E3.
These habitat values (forest and early successional) fall along the same successional curve, and
grass habitats were quality adjusted and can be compared through time, with differing starting
points in the successional progression. DSAY values between different habitat types may not be
equivalent and when combining DSAYs between habitat types this must be considered and need
to take into account quality differences between the habitat types being compared. For my analysis,
I grouped the wetland/surface water habitat value changes together with the terrestrial values. This
assumes that 1 dSAY of a wetland/surface water is equivalent to 1 dSAY of the terrestrial habitat.
Wetland/surface water habitat is likely more valuable than forest habitat as mitigation ratios often
ask for more riparian buffer acreage (e.g., 10:1) to offset wetland impacts. However, to be
conservative and not overestimate the impacts from the remedial actions, I have kept them on a 1
to 1 basis in Table E3.
Appendix E 10 June 30, 2016
Ecological Habitat Services

0
In order to put dSAY values into perspective, approximately 34.2 dSAYs are provided by one acre
of habitat, Therefore, one can infer the impact of the lost dSAYs by dividing by 34.2. 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 approximately 309 and 457 acres of habitat value
into perpetuity, respectively. This loss includes any ecological value as well as any associated
human use values. Based on the conservatism in the analysis, these losses are likely higher.
Table E3. Changes (i.e., losses) in habitat value associated with the alternatives by site.
Site
Allen
Buck
Cliffside
Mayo
Total
MNA
Cap in Place (dSAY loss)
(5,294)
(2,002)
(1,620)
(1,548)
(10,464)
Removal (dSAY loss)
(6,272)
(2,973)
(3,122)
(3,169)
(15,536)
MNA
-
-
-
-
Cap in Place (acres lost into
perpetuity)
(155)
(59)
(47)
(45)
(306)
Removal (acres lost into
perpetuity)
(183)
(87)
(91)
(93)
(454)
Appendix E 11 June 30, 2016
Ecological Habitat Services

EPS
E3 HUMAN RECREATIONAL SERVICES
For this evaluation, since the site is 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 12 June 30, 2016
Ecological Habitat Services

0
E4 REFERENCES
Enviroscience. 2008. Web Accessed June 23, 2016.
http://envirosci.net/I I I/succession/succession.htm
Greenpeace. Web Accessed June 23, 2016.
http://www. rg eenpeace.org/international/en/campaigns/forests/solutions/
McMahon, S. M., Parkera, G. G., and Millera, 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.
United States v. Melvin Fisher, 977 F. Supp 1193 (SD Fla 1997); United States, et al v Great
Lakes Dredge and Dock Co, Docket no 97-02510-CV-EBD (SD Fla 2001).
Appendix E 13 June 30, 2016
Ecological Habitat Services
C

Forest Curves

100
0
cn
U
'j 75
N
(0
U
W 50
O
O
U
W
a--+
N 25
O
LL
W
0 50 100 150 200 250
Yea rs
Figure E1. Graphic showing the relationship between above -ground biomass (AGB) and stand age of multiple
forest plots in a temperate deciduous forest in Edgewater, MD. Adapted from McMahon et al. (2010).

0
N
U
L
c�
U
O
0
U
w
V)
N
L
O
100
75
50
25
W
On -site baseline value (34.2 acres) 539 cISAYs
Baseline forest ecological
services projected into future
0 50 100 150 200 250
t2016 t2216
Yea rs
Figure E3. Ecological service flow framework used to evaluate service flow changes on forest habitats at the
Allen Steam Station — depicts current baseline of ecosystem service flows into the future.

0
cn
v
U
(3)
V)
c�
U
.O
O
U
W
cn
v
O
LL
100
Lost on -site forest ecological
75 services projected into the future
50
25
0 1 1 I
0 50
tzo16
On -site forest loss (34.2 acres) -505 dSAYs
Off -site forest loss (190 acres) -2,992 dSAYs
Off -site forest regeneration (190 acres) 1,8
Grass cap ecological services with cap -in -place 91 dSAYs
Will
Years
150
200 250
t2216
Figure E4. Ecological service flow framework used to evaluate service flow changes, on forest habitats that will
be associated with the "Cap -in -Place" option, at the Allen Steam Station.
y

100
0
Lost on -site forest ecological
75 services projected into the future
a�
V)
c�
U
'pip 50 On -site forest losses (34.2 acres) -505 dSAYs
O On -site forest regeneration (34 acres) 135 dSAYs
O
U
w Off -site forest losses (319 acres) -5,024 dSAYs
4-1
a 25 Off -site forest regeneration (93 acres) 903 dSAYs
O
LL
0
0 50 100 150 200
t2016 t2216
Yea rs
Figure E5. Ecological service flow framework used to evaluate service flow changes, on forest habitats that will
be associated with the "Removal" option, at the Allen Steam Station.

100
0
cn
U
'j
75
N
On -site baseline value (36.3 acres) 572 cISAYs
U
.W
50
O
Current age
Ostands
Baseline forest ecological
UJ
N
services projected into future
a)
25
LL
0
50
0 t2016
100 150 200 250
t2216
Yea rs
Figure E6. Ecological service flow framework used to evaluate service flow changes on forest habitats at the
Buck Steam Station — depicts current baseline of ecosystem service flows into the future.

100
Lost forest ecological services
projected into the future
U
'j 75
N
ca
U
'O 50 On -site forest loss with tree clearance (36.3 acres) -554 dSAY
O Off -site forest loss (122 acres) -1,921 dSAY
U Off -site Forest Regeneration (122 acres) 1,296 dSAY
w
4-1
N25 • ; , 1 •
i
O
Grass cap ecological services with cap -in -place 103 dSAYs
0
0 50 100 150 200
t2016 t2216
Yea rs
Figure ET Ecological service flow framework used to evaluate service flow changes, on forest habitats that will
be associated with the "Cap -in -Place" option, at the Buck Steam Station.
Wis]
y

100
I*- y
a Lost on -site forest ecological
U services projected into the future
'j 75
N
U On -site forest losses (36 acres) -554 dSAYs
O50 On -site forest regeneration (36 acres) 313 dSAYs
O
w Off -site forest losses (129 acres) -2,032 dSAYs
N 25 Off -site forest regeneration (35 acres) 372 dSAYs
a�
O
0-
0 t2016 t2216 50 100 150 200 250
Yea rs
Figure E8. Ecological service flow framework used to evaluate service flow changes, on forest habitats that will
be associated with the "Removal" option, at the Buck Steam Station.

100
0
cn
U
'j
75
N
ca
U
.W
50
O
Current age
O
of tree
U
w
stands
4-1
N
25
O
LL
0
0
t2016
On -site baseline value (25 acres) 395 dSAYs
Baseline forest ecological
services projected into future
Yea rs
150 200 250
t2216
Figure E9. Ecological service flow framework used to evaluate service flow changes on forest habitats at the
Cliffside Steam Station — depicts current baseline of ecosystem service flows into the future.

100
Lost forest ecological services
a projected into the future
U
'j 75
N
ca
U
O50 On -site forest loss with tree clearance (25 acres) -383 dSAYs
p Off -site forest loss (115 acres) -1,811 dSAYs
w Off -site forest regeneration (115 acres) 1,221 dSAYs
4-1
LL
Grass cap ecological services with cap -in -place 71 dSAYs
0 50 100 150 200
t2016 t2216
Yea rs
Figure E10. Ecological service flow framework used to evaluate service flow changes, on forest habitats that
will be associated with the "Cap -in -Place" option, at the Cliffside Steam Station.
y

100
ONO Lost on -site forest ecological y
services projected into the future
U
'j 75
N
ca
W 50
On -site forest losses (25 acres) -383 dSAYs
O On -site forest regeneration (25 acres) 186 dSAYs
O
U
w Off -site forest losses (168 acres) -2,646 dSAYs
v 25 Off -site forest regeneration (47 acres) 499 dSAYs
a�
O
0-
0 t2016 t2216 50 100 150 200 250
Yea rs
Figure Ell. Ecological service flow framework used to evaluate service flow changes, on forest habitats that
will be associated with the "Removal" option, at the Cliffside Steam Station.

100
0
cn
U
'j
75
N
ca
U
.W
50
O
Current age
O
of tree
U
w
stands
4-1
N
25
O
LL
0
0
t2016
On -site baseline value (11 acres) 173 dSAYs
Baseline forest ecological
services projected into future
50 100 150
Yea rs
200 250
t2216
Figure E12. Ecological service flow framework used to evaluate service flow changes on forest habitats at the
Mayo Steam Station — depicts current baseline of ecosystem service flows into the future.

100
0
N Lost forest ecological services
U projected into the future
'j 75
c6
U
.� 50 On -site forest loss with tree clearance (11 acres) -168 dS
O Off -site forest loss (94 acres) -1,480 dSA
U Off -site forest regeneration (94 acres) 998 dSA
w
`n 25
(UNet Loss. dSAYs
O
U_
Grass cap ecological services with cap -in -place 32 dSAYs
0 s
0 50 100 150 200
t2016 t2216
Years
Figure E13. Ecological service flow framework used to evaluate service flow changes, on forest habitats that
will be associated with the "Cap -in -Place" option, at the Mayo Steam Station.
y
W
Wiz

100
0
N Lost on -site forest ecologicalCli y
U services projected into the future
'j 75
N
U On -site forest losses (11 acres) -168 dSAYs
O50 On -site forest regeneration (11 acres) 87 dSAYs
O
w Off -site forest losses (149 acres) -2,347 dSAYs
N 25 Off -site forest regeneration (41 acres) 435 dSAYs
aU
O
0
0 t2016 t2216 50 100 150 200 250
Yea rs
Figure E14. Ecological service flow framework used to evaluate service flow changes, on forest habitats that
will be associated with the "Removal" option, at the Mayo Steam Station.

Wetland/Surface Water Curves

100
75
U
O
O 50
U
W
25
ca
N
0
es
0 50 100 150 200
t2016 t2216
Yea rs
alit
Figure E15. Ecological service flow framework used to evaluate service flow changes on wetland/surface water
habitats at the Allen Steam Station — depicts current baseline of ecosystem service flows into the future.

0 100
0
N
U
L
cn 75
U
.O
O 50
U
W
25
ca
N
0
0 50
t2016
WIN
Yea rs
150
Baseline ecological services
200
t2216
w
M1111
Figure E16. Ecological service flow framework used to evaluate service flow changes, to wetland/surface water
habitats that will be associated with the "Cap -in -Place" option, at the Allen Steam Station.

cBaseline ecological services
100 MUM
U On -site wetland loss (98 acres) -2,037 dSAYs
cn 75
U
O
O 50
U
w On -site forest regeneration
(98 acres) 951 dSAYs
0 25
C
N
710W
0 f_
0 t2016 t2216 50 100 150 200 250
Yea rs
Figure E17. Ecological service flow framework used to evaluate service flow changes, on wetland/surface water
habitats that will be associated with the "Removal' option, at the Allen Steam Station.

0 100
Ln
N
U
L
cn 75
U
O
O 50
U
W
25
ca
N
0
0 50 100 150 200
t2016 t2216
Yea rs
Figure E18. Ecological service flow framework used to evaluate service flow changes on wetland/surface water
habitats at the Buck Steam Station — depicts current baseline of ecosystem service flows into the future.
alit

0 100
0
N
U
L
cn 75
U
O
O 50
U
W
25
ca
N
0
0 50
t2016
WIN
Yea rs
150
Baseline ecological services
200 250
t2216
Figure E19. Ecological service flow framework used to evaluate service flow changes, to wetland/surface water
habitats that will be associated with the "Cap -in -Place" option, at the Buck Steam Station.

cBaseline ecological services
100 MUM
U On -site wetland loss (64 acres) -1,330 dSAYs
cn 75
U
O
O 50
U
w On -site forest regeneration
(64 acres) 621 dSAYs
0 25
N
7
0 t2016 t2216 50 100 150 200 250
Yea rs
Figure E20. Ecological service flow framework used to evaluate service flow changes, on wetland/surface water
habitats that will be associated with the "Removal' option, at the Buck Steam Station.

0 100
Ln
N
U
L
cn 75
U
O
O 50
U
W
25
ca
N
0
0 50 100 150 200
t2016 t2216
Yea rs
Figure E21. Ecological service flow framework used to evaluate service flow changes on wetland/surface water
habitats at the Cliffside Steam Station — depicts current baseline of ecosystem service flows into the
future.
alit

0 100
0
N
U
L
cn 75
U
O
O 50
U
W
25
ca
N
0
0 50
t2016
WIN
Yea rs
150
Baseline ecological services
200 250
t2216
Figure E22. Ecological service flow framework used to evaluate service flow changes, to wetland/surface water
habitats that will be associated with the "Cap -in -Place" option, at the Cliffside Steam Station.

cBaseline ecological services
100 MUM
U On -site wetland loss (45 acres) -935 dSAYs
Q
Ln 75
U
O
O 50
U
w On -site forest regeneration
(45 acres) 437 dSAYs
0 25
C
0
0 t2016 t2216 50 100 150 200 250
Yea rs
Figure E23. Ecological service flow framework used to evaluate service flow changes, on wetland/surface water
habitats that will be associated with the "Removal' option, at the Cliffside Steam Station.

100
75
U
O
O 50
U
W
25
ca
N
0
0 50 100 150 200
t2016 t2216
Yea rs
alit
Figure E24. Ecological service flow framework used to evaluate service flow changes on wetland/surface water
habitats at the Mayo Steam Station — depicts current baseline of ecosystem service flows into the future.

0 100
0
N
U
L
cn 75
U
O
O 50
U
W
25
ca
N
0
0 50
t2016
WIN
Yea rs
150
Baseline ecological services
200 250
t2216
Figure E25. Ecological service flow framework used to evaluate service flow changes, to wetland/surface water
habitats that will be associated with the "Cap -in -Place" option, at the Mayo Steam Station.

cBaseline ecological services
100 MUM
U On -site wetland loss (79 acres) -1,642 dSAYs
cn 75
U
O
O 50
U
w On -site forest regeneration
(79 acres) 767 dSAYs
0 25
N
0
0 t2016 t2216 50 100 150 200 250
Yea rs
Figure E26. Ecological service flow framework used to evaluate service flow changes, on wetland/surface water
habitats that will be associated with the "Removal' option, at the Mayo Steam Station.

Early Successional/Shrub/Scrub Curves

� o
U
� N
\ U_
O •>
•N �
U
U U
>, O
i Q
M U
W W
100
75
50
25
W
On -site baseline value (100 acres) 1,129 dSAYs
Current age
of Baseline ecological services
vegetation projected into future
0 t2016 t2216 50 100 150 200 250
Yea rs
Figure E27. Ecological service flow framework used to evaluate service flow changes on early succession/scrub
habitats at the Allen Steam Station — depicts current baseline of ecosystem service flows into the future.

100
�
o
U
Ln
75
\
U_
•>
O
•N
�
v
N
Ln
v
50
U
=3
• U_
(/)
bn
O
i
O
M
U
25
w
w
W
0 t2016 t2216 50 100 150 200 250
Yea rs
Figure E28. Ecological service flow framework used to evaluate service flow changes, to early succession/scrub
habitats that will be associated with the "Cap -in -Place" option, at the Allen Steam Station.

100
�
o
U
Ln
75
\
U
'>
0
•N
v
L
Ln
50
v
U
=3
U
'aA
v)
0
i
0
M
U
25
w
w
0
0
Lost on -site ecological services
projected into the future
Current age
of
vegetation
t2o16
On -site losses (100 acres) -1,129 dSAYs
On -site forest regeneration (100 acres) 396 dSAYs
1
50 100 150 200 250
tzz16
Yea rs
Figure E29. Ecological service flow framework used to evaluate service flow changes, to early succession/scrub
habitats that will be associated with the "Removal" option, at the Allen Steam Station.

100
o
U
75
\
U_
�>
O
On -site baseline value (52 acres) 587 dSAYs
U
_ 50
U
=3
ru
.V
Curren/age000000
�
aA
of
Baseline ecological services
>,
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w
w 25
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Figure E30. Ecological service flow framework used to evaluate service flow changes on early succession/scrub
habitats at the Buck Steam Station — depicts current baseline of ecosystem service flows into the future.

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Figure E31. Ecological service flow framework used to evaluate service flow changes, to early succession/scrub
habitats that will be associated with the "Cap -in -Place" option, at the Buck Steam Station.

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On -site losses (52 acres) -587 dSAYs
On -site regeneration (52 acres) 206 dSAYs
Yea rs
1
150 200 250
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Figure E32. Ecological service flow framework used to evaluate service flow changes, to early succession/scrub
habitats that will be associated with the "Removal" option, at the Buck Steam Station.

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150 200 250
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Figure E33. Ecological service flow framework
used to evaluate service flow changes on early succession/scrub
habitats at the Cliffside Steam Station —
depicts current baseline of ecosystem service flows into the
future.

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Figure E34. Ecological service flow framework used to evaluate service flow changes, to early succession/scrub
habitats that will be associated with the "Cap -in -Place" option, at the Cliffside Steam Station.

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Lost on -site ecological services
projected into the future
Current age
of
vegetation
t2o16 50
well]
On -site losses (42 acres) -474 dSAYs
On -site regeneration (42 acres) 166 dSAYs
Yea rs
1
150 200 250
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Figure E35. Ecological service flow framework used to evaluate service flow changes, to early succession/scrub
habitats that will be associated with the "Removal" option, at the Cliffside Steam Station.

100
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Figure E36. Ecological service flow framework used to evaluate service flow changes on early succession/scrub
habitats at the Mayo Steam Station — depicts current baseline of ecosystem service flows into the future.

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Figure E37. Ecological service flow framework used to evaluate service flow changes, to early succession/scrub
habitats that will be associated with the "Cap -in -Place" option, at the Mayo Steam Station.

100
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projected into the future
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of
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t2o16 50
well]
On -site losses (42 acres) -474 dSAYs
On -site regeneration (42 acres) 166 dSAYs
Yea rs
1
150 200 250
tzz16
Figure E38. Ecological service flow framework used to evaluate service flow changes, to early succession/scrub
habitats that will be associated with the "Removal" option, at the Mayo Steam Station.

Grass Curves

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Figure E39. Ecological service flow framework used to evaluate service flow changes on grass habitats at the
Allen Steam Station — depicts current baseline of ecosystem service flows into the future.

100
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L 1
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On -site grass loss (72.9 acres) -250 dSAYs
On -site grass gain (72.9 acres) 194 dSAYs
Net Loss -56 dSAYs
Grass cap ecological services gain with cap -in -place
well]
Years
Mil
200 250
t2216
Figure E40. Ecological service flow framework used to evaluate service flow changes, on grass habitat that will
be associated with the "Cap -in -Place" option, at the Allen Steam Station. Grass converts to grass.

100
0
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W 50
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services projected into the future
Lost on -site grass ecological
services projected into the future
KIII7
On -site forest gains (72.9 acres) 288 dSAYs
On -site grass losses (72.9 acres) -250 dSAYs
Yea rs
150 200
tzz16
Figure E41. Ecological service flow framework used to evaluate service flow changes, on grass habitats that will
be associated with the "Removal" option, at the Allen Steam Station. Grass habitat converts to forest.

100
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Figure E42. Ecological service flow framework used to evaluate service flow changes on grass habitats at the
Buck Steam Station — depicts current baseline of ecosystem service flows into the future.

100
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w On -site grass gain (34.2 acres) 91 dSAYs
v`ni 25 On -site grass loss Net Loss -26 dSAYs
ca
� 1
Grass cap ecological services gain with cap -in -place
0
0 50 100 150 200
t2016 t2216
Yea rs
Figure E43. Ecological service flow framework used to evaluate service flow changes, on grass habitat that will
be associated with the "Cap -in -Place" option, at the Buck Steam Station. Grass converts to grass.
alit

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services projected into the future
Lost on -site grass ecological
services projected into the future
KIII7
On -site forest gains (34.2 acres) 135 dSAYs
On -site grass losses (34.2 acres) -117 dSAYs
Yea rs
150 200
tzz16
Figure E44. Ecological service flow framework used to evaluate service flow changes, on grass habitats that will
be associated with the "Removal" option, at the Buck Steam Station. Grass converts to forest.

100
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Figure E45. Ecological service flow framework used to evaluate service flow changes on grass habitats at the
Cliffside Steam Station — depicts current baseline of ecosystem service flows into the future.

100
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ca
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w On -site grass gain (51.5 acres) 137 dSAYs
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ca
� 1
Grass cap ecological services gain with cap -in -place
0
0 50 100 150 200
t2016 t2216
Yea rs
Figure E46. Ecological service flow framework used to evaluate service flow changes, on grass habitat that will
be associated with the "Cap -in -Place" option, at the Cliffside Steam Station. Grass converts to grass.
alit

100
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(,
U 75
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O
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W
v4-ai 25
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services projected into the future
Lost on -site grass ecological
services projected into the future
will]
On -site forest gains (51.5 acres) 204 dSAYs
On -site grass losses (51.5 acres) -176 dSAYs
Yea rs
150
200
tzz16
Figure X47. Ecological service flow framework used to evaluate service flow changes, on grass habitats that will
be associated with the "Removal' option, at the Cliffside Steam Station. Grass converts to forest.

100
0
N
N
U
'j 75
N
cn
M
U
'Ep 50
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0
0 25
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0 t2016 t2216 50 100 150 200 250
Yea rs
Figure E48. Ecological service flow framework used to evaluate service flow changes on grass habitats at the
Mayo Steam Station — depicts current baseline of ecosystem service flows into the future.

100
0
N
aJ
U
•� 75
N
V)
ca
U
' 50
O
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L 25 On -site grass loss
L 1
0 1 —1-
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t2o16
On -site grass loss (14 acres) -48 dSAYs
On -site grass gain (14 acres) 37 dSAYs
Net Loss -11 dSAYs
Grass cap ecological services gain with cap -in -place
well]
Years
Mil
200 250
t2216
Figure E49. Ecological service flow framework used to evaluate service flow changes, on grass habitat that will
be associated with the "Cap -in -Place" option, at the Mayo Steam Station. Grass converts to grass.

100
0
Ln
(,
U 75
a)
V)
M
U
•Eb 50
O
O
U
W
v4-ai 25
a,
LL
W
Gained on -site forest ecological
services projected into the future
Lost on -site grass ecological
services projected into the future
KIII7
On -site forest gains (14 acres) 55 dSAYs
On -site grass losses (14 acres) -48 dSAYs
Yea rs
150 200
tzz16
Figure E50. Ecological service flow framework used to evaluate service flow changes, on grass habitats that will
be associated with the "Removal" option, at the Mayo Steam Station. Grass converts to forest.

EPS
APPENDIX F
Joseph Nicolette CV

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
2
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/NRDA liability allocation support for
industrial clients. He has developed and reviewed
allocation models for specific sites, determining
estimates of the portion of remedial and NRDA liability
associated with various PRP's at the site.
Joseph is also trained in hierarchical relational scientific
database design, structuring and management.
0

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
3
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
0

Joseph Nicolette
N
N
I
(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
L,
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 MNA 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
0

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 benefits1limpacts 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.
s
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 (BRAG) 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
0

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
rel
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 MNA 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

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 NRDA 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.
7
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.
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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
$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
0

Joseph Nicolette
requested by the USAGE. 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
a
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

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
10
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
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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.
it
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
12
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.
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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.
13
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
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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.
14
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
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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
15
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.
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