Mayo_NEBA_CommunityImpactAnalysis_20181115

Community Impact Analysis
of Ash Basin Closure Options
at the Mayo Steam Electric
Plant

Exponent
Community Impact Analysis of Ash
Basin Closure Options at the Mayo
Steam Electric Plant
Prepared on behalf of Duke Energy Progress, LLC
Prepared by
r
Dr. Ann Michelle Morrison
Exponent
1 Mill & Main Place, Suite 150
Maynard, MA 01754
November 15, 2018
© Exponent, Inc.
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Contents
Page
List of Figures
iv
List of Tables
v
Acronyms and Abbreviations
vii
Limitations
viii
Executive Summary
ix
1 Qualifications
1
2 Assignment and Retention
3
3 Reliance Materials
4
4 Introduction
5
4.1 Site Setting
6
4.2 Closure of the Ash Impoundment at the Mayo Plant
10
5 Approach to Forming Conclusions
14
5.1 Net Environmental Benefit Analysis
16
5.2 Linking Stakeholder Concerns to NEBA
18
5.3 NEBA Risk Ratings
24
5.4 Risk Acceptability
25
6 Summary of Conclusions
27
7 Conclusion 1: All closure options for the Mayo ash basin are protective of
human health.
29
7.1 Private water supply wells pose no meaningful risk to the community around
Mayo.
29
7.2 CCR constituents from the Mayo ash basin pose no meaningful risk to human
populations.
30
7.3 NEBA — Protection of Human Health from CCR Exposure
32
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8 Conclusion 2: All closure options for the Mayo ash basin are protective of
ecological health. 34
8.1 No meaningful risks to ecological receptors from CCR exposure exist under
current conditions or any closure option. 34
8.2 NEBA — Protection of Ecological Health from CCR Exposure 38
9 Conclusion 3: All closure options for the Mayo ash basin create low levels of
community disturbance. 40
9.1 There is no meaningful risk from diesel emissions to people living and working
along the transportation corridor. 42
9.2 The likelihood of noise, traffic, and accidents from transportation activities is
comparable under all closure options. 45
9.2.1 Noise and Congestion 45
9.2.2 Traffic Accidents 46
9.3 NEBA — Minimize Human Disturbance
47
10 Conclusion 4: Most closure options for the Mayo ash basin produce no net
environmental disturbance. 50
10.1 Excavation closure results in a greater net loss of environmental services
than CIP closure. 52
10.2 NEBA — Minimize Environmental Disturbance 56
11 Conclusion 5: Most closure options for the Mayo ash basin produce comparable
environmental services. 58
12 References
61
Appendix A Curriculum vitae of Dr. Ann Michelle Morrison, Sc.D.
Appendix B Human Health and Ecological Risk Assessment Summary Update for Mayo
Steam Electric Plant
Appendix C Exposure Modeling and Human Health Risk Assessment for Diesel Emissions
Appendix D Habitat Equivalency Analysis
Appendix E Net Environmental Benefit Analysis
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List of Figures
Paue
Figure 4-1. Map of the Mayo Plant. Reproduced and adapted from Figure 2-1 of the
2017 CSA Supplement (SynTerra 2017). 7
Figure 4-2. Images of forest habitat at the Mayo Plant, October 30, 2017. 8
Figure 4-3. Images of Mayo Lake, October 30, 2017.
we
Figure 4-4. Elemental composition of bottom ash, fly ash, shale, and volcanic ash. 10
Figure 8-1. Exposure areas evaluated in the 2018 Ecological Risk Assessment update. 37
Figure 9-1. Normalized differences between offsite transportation activities under CIP,
excavation, and hybrid closure options. 42
Figure 10-1. Map of habitat types currently present at the Mayo Plant 51
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List of Tables
Page
Table 4-1.
Ash basin closure options provided by Duke Energy (2018b)
12
Table 4-2.
Overview of some key logistical differences between CIP and excavation
closure of the Mayo Plant ash basin.
12
Table 5-1.
Relationships between environmental services and concerns to the local
community associated with CCR and ash basin closure hazards
20
Table 5-2.
Associations between objectives for closure and remediation of the Mayo
ash basin and environmental services
21
Table 5-3.
Matrix of key environmental services, attributes, and comparative metrics
applied in the NEBA
22
Table 5-4.
Risk -ranking matrix for impacts and risk from remediation and closure
activities.
25
Table 7-1.
Summary of human health risk assessment hazard index (HI) and excess
lifetime cancer risk (ELCR) from SynTerra (2018)
32
Table 7-2. Summary of relative risk ratings for attributes that characterize potential
hazards to humans from CCR exposure in drinking water, surface water,
groundwater, soil, sediment, food, and through recreation 33
Table 8-1. Summary of relative risk rating for attributes that characterize potential
hazards to ecological resources from CCR exposure in surface water, soil,
sediment, and food 38
Table 9-1. Summary of offsite transportation logistics associated with each closure
option (Duke Energy 2018b) 41
Table 9-2. Hazard indices (HI) and excess lifetime cancer risk (ELCR) from exposure
to diesel exhaust emissions along transportation corridors in northern North
Carolina. 44
Table 9-3. Comparative metrics for increased noise and congestion and traffic accidents 47
Table 9-4. Summary of relative risk rating for attributes that characterize potential
hazards to communities during remediation activities. 49
Table 10-1. Summary ofNPP DSAYs for closure options
Table 10-2. Percent impact of ash basin closure options.
56
57
Table 10-3. Summary of relative risk ratings for habitat changes that affect provision of
environmental services. 57
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Table 11-1. NEBA for closure of the ash basin at the Mayo Plant. 60
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Acronyms and Abbreviations
AADT
annual average daily traffic
CAMA
North Carolina Coal Ash Management Act
CAP
corrective action plan
CCR
coal combustion residuals
CCR Rule
EPA Coal Combustion Residuals Rule of 2015
CERCLA
Comprehensive Environmental Response, Compensation and Liability
Act
CIP
cap in place
COI
constituent of interest
COPC
chemical of potential concern
CSA
comprehensive site assessment
DPM
diesel particulate matter
Duke Energy
Duke Energy Progress, LLC
DSAY
discounted service acre -year
ELCR
excess lifetime cancer risk
EPA
U.S. Environmental Protection Agency
ERA
ecological risk assessment
GIS
geographic information system
HEA
habitat equivalency analysis
HHRA
human health risk assessment
HI
hazard index
HQ
hazard quotient
LOAEL
lowest -observed -adverse -effects level
Mayo Plant
Mayo Steam Electric Plant
MOVES
Mobile Vehicle Emissions Simulator
NEBA
net environmental benefit analysis
NCDEQ
North Carolina Department of Environmental Quality
NCDOT
North Carolina Department of Transportation
NOAA
National Oceanic and Atmospheric Administration
NOAEL
no -observed -adverse -effects level
NPDES
National Pollutant Discharge Elimination System
NPP
net primary productivity
NRDA
natural resource damage assessment
OSAT-2
Operational Science Advisory Team-2
RCRA
Resource Conservation and Recovery Act
REL
reference exposure level
SOC
Special Order by Consent
TRV
toxicity reference value
TVA
Tennessee Valley Authority
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Limitations
This report sets forth my conclusions, which are based on my education, training, and
experience; field work; established scientific methods; and information reviewed by me or
under my direction and supervision. These conclusions are expressed to a reasonable degree of
scientific certainty. The focus of this report is on local community impacts. I have, therefore, not
attempted to evaluate broader environmental impacts, such as impacts from greenhouse gas
emissions, that would be associated with each closure option.
The conclusions in this report are based on the documents made available to me by Duke
Energy Progress, LLC (Duke Energy) or collected as part of my investigation. I reserve the right
to supplement my conclusions if new or different information becomes available to me. As an
example, the excavation option presented in this report assumes that landfilling of excavated ash
can be accommodated within the boundaries of the currently permitted landfill space. The
currently permitted landfill space was sized to accommodate future ash production and did not
include the addition of excavated ash from the Mayo Steam Electric Plant (Mayo Plant) ash
basin. If additional landfill space is required to accommodate both excavated ash and future ash
production, then additional habitat destruction would be necessary, and that impact has not been
factored into this analysis.
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Executive Summary'
In 2015, the U.S. Environmental Protection Agency (EPA) issued a rule called the "Hazardous
and Solid Waste Management System; Disposal of Coal Combustion Residuals [CCR] from
Electric Utilities" (CCR Rule), which, among other things, regulates closure of coal ash
impoundments in the United States. Closure of coal ash impoundments in North Carolina is
further regulated by the North Carolina Coal Ash Management Act of 2014 (LAMA) as
amended by H.B. 630, Sess. L. 2016-95. Under both the North Carolina CAMA and the federal
CCR Rule, there are two primary alternatives for closure of an ash impoundment:
• "Cap in place" (CIP) closure involves decanting the impoundment and
placing a low -permeability liner topped by appropriate cap material, soil, and
grass vegetation over the footprint of the ash to restrict vertical transport of
water through the ash, as well as a minimum of 30 years of post -closure care,
which requires the implementation of corrective action measures if and as
necessary;
• Excavation closure involves decanting the impoundment, excavating all ash
in the basin, transporting the ash to an appropriate, permitted, lined landfill,
and restoring the site.
Duke Energy Progress, LLC's (Duke Energy's) Mayo Steam Electric Plant (Mayo Plant) has
one onsite ash basin and a separate onsite, lined landfill. Duke Energy has evaluated three
representative types of closure for the ash impoundment at the Mayo Plant: CIP; excavation to
the existing (expanded) onsite, lined landfall; and a hybrid closure, which involves excavating
and consolidating ash within the basin footprint to reduce the spatial area of CIP closure (Duke
Energy 2018b). The administrative process for selecting an appropriate closure plan is ongoing.
' Note that this Executive Summary does not contain all of the technical evaluations and analyses that support the
conclusions. Hence, the main body of this report is at all times the controlling document.
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The purpose of my report is to examine how the local community's environmental health and
environmental services are differently affected by each closure option as currently defined and
to evaluate these differences in a structured framework that can support decision -making in this
matter.
Environmental Decision -Making
Environmental decision -making involves understanding complex issues that concern multiple
stakeholders. Identifying the best management alternative often requires tradeoffs among
stakeholder values. These tradeoffs necessitate a transparent and systematic method to compare
alternative actions and support the decision -making process. My analyses in this matter have
used a net environmental benefit analysis (NEBA) framework (Efroymson et al. 2003, 2004) to
compare the relative risks and benefits from CIP closure, excavation closure, or a hybrid CIP
and excavation closure of the ash basin at the Mayo Plant. The NEBA framework relies on
scientifically supported estimates of risk to compare the reduction of risk associated with
chemicals of potential concern (COPCs)3 under different remediation and closure alternatives
alongside the creation of any risk during the remediation and closure, providing an objective,
scientifically structured foundation for weighing the tradeoffs between remedial and closure
alternatives.
Despite the scientific basis of the risk characterization process used in NEBA, stakeholders in
any environmental decision -making scenario may place different values on different types of
risk (i.e., stakeholders may have different priorities for the remediation and closure). NEBA
does not, by design, elevate, or increase the value of, any specific risk or benefit in the
framework. The purpose of NEBA is to simultaneously and systematically examine all tradeoffs
that affect the services provided to humans and the ecosystem by the environment under
2 Environmental services, or ecosystem services, are ecological processes and functions that provide value to
individuals or society (Efroymson et al. 2003, 2004).
s COPCs are "any physical, chemical, biological, or radiological substance found in air, water, soil or biological
matter that has a harmful effect on plants or animals"
(hops://ofMpub.cpa.gov/sor intemet/regisLry/ten-nreg/searchandretrieve/glossariesandkeywordlists/search.do?de
tails=&glo ssaaName=Eco%20Risk%2OAs se ssment%20G10 ssary).
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remediation and closure, allowing decision -makers to more fully understand all potential
benefits and risks of each alternative.
NEBA and similar frameworks have been used extensively by regulatory agencies such as the
National Oceanic and Atmospheric Administration (NOAA) and EPA to support evaluating
tradeoffs in mitigation (e.g., NOAA 1990), remediation (e.g., U.S. EPA 1988, 1994), and
restoration (e.g., NOAA 1996). The National Environmental Policy Act (40 CFR § 1502) relies
on a structured framework to conduct environmental assessments and produce environmental
impact statements; these analyses evaluate potential adverse effects from development projects
and identify alternatives to minimize environmental impacts and/or select mitigation measures.
Natural resource damage assessment (NRDA) utilizes a structured process to estimate
environmental injury and lost services and identify projects that restore the impacted
environment and compensate the public for the lost environmental services (e.g., NOAA 1996).
The Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA)
remedial investigation/feasibility study process uses a set of evaluation criteria to identify
remediation projects for contaminated Superfund sites that meet remediation objectives for
effectiveness, implementability, and cost (U.S. EPA 1988). Within the Superfund Program, EPA
has also recognized the importance of remediation that comprehensively evaluates cleanup
actions "to ensure protection of human health and the environment and to reduce the
environmental footprint of cleanup activities to the maximum extent possible" (U.S EPA 2010).
The Tennessee Valley Authority (TVA) recently used a structured framework to compare the
impacts and benefits of ash basin closure alternatives at ten of its facilities (TVA 2016).
Through a NEBA-like analysis, the TVA identified "issue areas," such as air quality,
groundwater, vegetation, wildlife, transportation, and noise and created a summary table that
provided a side -by -side comparison of the impacts of "no action," "closure -in -place," and
"closure -by -removal" actions. As a result of this analysis, TVA identified "closure -in -place" as
"its preferred alternative" for all ten facilities stating, "[t]his alternative would achieve the
purpose and need for TVA's proposed actions and compared to Closure -by -Removal with less
environmental impact, shorter schedules, and less cost" (TVA 2016). The Mayo ash basin
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closure presents similar "issue areas" that can benefit from a similar, systematic analysis of net
benefits resulting from closure activities.
Linking Stakeholder Concerns to NEBA
To better understand stakeholder concerns related to closure of the ash basin at Mayo, I
reviewed written communications about ash pond closure plans for the Mayo Plant submitted to
and summarized by the North Carolina Department of Environmental Quality (NCDEQ 2016).
From this review, I identified the following categories of stakeholder concerns:
• Drinking water quality
• Groundwater quality
• Surface water quality
• Fish and wildlife
• Maintaining property value
• Preservation of natural beauty
• Recreational value
• Swimming safety
• Failure of the ash impoundment
• Risk created by the closure option outweighing risk from contamination.
The primary concerns expressed by community stakeholders involve perceived risks from
exposure to CCR constituents that could negatively affect environmental services that benefit
the local community: provision of safe drinking water and food, safe recreational enjoyment
(hunting, fishing, swimming), and protection of natural beauty and biodiversity.4 Potential
hazards to the community associated with closure activities include physical disturbance of
existing habitats; air pollution from diesel emissions resulting from transportation activities; and
traffic, noise, and accidents that could result in property damage, injuries, and fatalities. Table
4 Biodiversity is the variety of plants and animals present at a location. Protection of biodiversity refers to
provision of habitat and related functions capable of sustaining biological populations.
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ES-1 links concerns over CCR exposure and potential hazards created by ash basin closure to
environmental services that could be affected by closure activities.
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Table ES-1. Relationships between environmental services and concerns to the local community associated with CCR
and ash basin closure hazards
Environmental Services
Safe drinking Safe surface Safe air Safe food Protection of Recreation Natural Safe community
water quality water quality quality quality biodiversity beauty environment
CCR Concerns
Drinking water
X
X
X
contamination
Groundwater contamination
X
X
X
Surface water
X
X
X X
X
X
X
contamination
Fish/wildlife contamination
X X
X
X
X
Contamination impacting
X
X
X X
X
X
X
property value
Contamination impacting
X
X
X
natural beauty
Contamination impacting
X
X
X
X
X
recreational enjoyment
Contamination impacting
X
X
X
X
swimming safety
Failure of the ash
X
X
X X
X
X
X
impoundment
Closure Hazards
Habitat loss X X X X X
Contamination of air X X X X
Noise, Traffic, Accidents X X
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In recognition of the potential discrepancy between stakeholder priorities and the broad and
balanced treatment of service risks and benefits in NEBA, I organized the NEBA analysis
around the following five objectives for ash basin closure that recognize local stakeholder
concerns while being consistent with the methods and purpose of NEBA:
1. Protect human health from CCR constituent exposure
2. Protect ecological health from CCR constituent exposure
3. Minimize risk and disturbance to humans from closure
4. Minimize risk and disturbance to the local environment from closure
5. Maximize local environmental services.
In my analysis, I linked environmental services to the local community that could be potentially
impacted by ash basin closure and the identified objectives of ash basin closure, and I identified
attributes and comparative metrics that characterize the condition of the environmental services
(Efroymson et al. 2003, 2004).
I used human health attributes (e.g., risk to onsite construction workers, risk to offsite
swimmers) and risk quotients (hazard index [HI], excess lifetime cancer risk [ELCR]) to
evaluate whether there would be a potential impact to environmental services related to safe
water, air, and food under each ash basin closure option. I also used human health attributes to
evaluate whether there would be an impact to air quality during closure activities. I used
ecological health attributes (e.g., risk to birds, mammals) and risk quotients (hazard quotients
[HQs]) to evaluate whether there would be a potential impact to environmental services related
to safe surface water and food and protection of biodiversity and natural beauty under the ash
basin closure options. I evaluated risk and disturbance associated with traffic and accidents
using transportation metrics and trucking logistics (e.g., number of truck miles driven)
associated with each closure option to evaluate potential impacts to community safety. I used
5 For purposes of this analysis, an attribute is a feature that characterizes environmental services and may be
impacted by a closure option. Comparative metrics are features of the attribute (e.g., risk quotients, acreage of
habitat) that can be measured and compared between closure options.
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net primary productivity (NPP)6 and discounted service acre -years (DSAYs)7 to characterize
differences in the environmental services that derive from habitats (e.g., protection of
biodiversity, natural beauty) and that would be impacted by ash basin closure activities. Finally,
I assembled all attributes, services, and objectives within a full NEBA to examine which of the
closure options best maximizes environmental services for the local community. The metrics I
used are scientifically appropriate and commonly applied metrics to evaluate risk to humans and
the environment (U.S. EPA 1989, 1997, 2000; NHTSA 2016) and to quantitatively measure
differences in environmental services associated with impact and restoration (Dunford et al.
2004; Desvousges et al. 2018; Penn undated; Efroymson et al. 2003, 2004).
Of note, my analysis did not consider the risks involved with onsite construction activities. For
example, I did not attempt to evaluate occupational accidents created by onsite construction and
excavation. Nor did I attempt to evaluate emissions associated with onsite construction
activities. Finally, I did not attempt to consider the risk created by disturbing the ash basin and
exposing it to the elements during excavation activities.
Some stakeholders also expressed concern over safety of the ash impoundment dam (NCDEQ
2016). The most recent dam safety report produced by Amec Foster Wheeler and submitted to
NCDEQ indicates "the construction, design, operation, and maintenance of the CCR surface
impoundments have been sufficiently consistent with recognized and generally accepted
engineering standards for protection of public safety and the environment" (Williams and Tice
2018).
Three possible options for closure of the ash basin at the Mayo Plant were identified by Duke
Energy (Duke Energy 2018b) and summarized in (Table ES-2). I used these options in the
6 NPP represents the mass of chemically fixed carbon produced by a plant community during a given time
interval. It reflects the rate at which different ecosystems are able to sequester carbon, which is related to
mitigating climate change (hops:Hearthobservatory.nasa.gov/GlobalMgps/view.php?dl=MOD17A2 M PSN).
DSAYs are derived from habitat equivalency analysis (HEA). HEA is an assessment method that calculates
debits based on services lost and credits for services gained from a remediation action (Dunford et al. 2004;
Desvousges et al. 2018; Penn undated). A discount rate is used to standardize the different time intervals in
which the debits and credits occur, and in doing so, present the service debits and credits at present value. The
present value of the services is usually expressed in terms of discounted service acre -years of equivalent habitat,
or DSAYs, which provide a means to compare the different service levels of affected habitat acres (Dunford et
al. 2004; Desvousges et al. 2018; Penn undated).
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NEBA to examine how different closure possibilities impact environmental services to the local
community.
Table ES-2. Ash basin closure options provided by Duke Energy (2018)
Closure Description
CIP CIP
Excavation Excavate to expanded Mayo landfill
Hybrid Partially excavate to consolidate ash and
CIP consolidated ash
Closure Duration Construction Duration
Nearsla Nearslb
6 4
10 7
8 5
a Includes pre -design investigation, design and permitting, site preparation, construction, and site restoration.
b Includes only site preparation, construction, and site restoration.
NEBA Risk Ratings
NEBA organizes environmental hazard and benefit information into a unitless metric that
represents the degree and the duration of impact from remediation and closure alternatives. One
approach to structure this analysis is to create a risk -ranking matrix that maps the proportional
impact of a hazard (i.e., risk) with the duration of the impact, which is directly related to the
time to recovery (Robberson 2006). The risk -ranking matrix used for this application of NEBA
is provided in Table ES-3. In this application, the matrix uses alphanumeric coding to indicate
the severity of an impact: higher numbers and higher letters (e.g., 4F) indicate a greater extent
and a longer duration of impact. Shading of cells within the matrix supports visualization of the
magnitude of the effect according to the extent and duration of impact.$ When there is no
meaningful risk, the cell is not given an alphanumeric code. Relative risk ratings for each
attribute and closure option examined were assembled into objective -specific summaries to
compare the net benefits of the closure options. All closure options in the NEBA were evaluated
against current conditions as a "baseline" for comparison.
s Categories and shading as defined in the risk -ranking matrix are based on best professional judgment and used
for discussion of the relative differences in relative risk ratings. Alternative risk matrices and resulting NEBA
classifications are explored in Appendix E.
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Table ES-3. Risk -ranking matrix for impacts and risk from closure activities.
Darker shading and higher codes indicate greater impact.
Duration of Impact (years)
10-15
(4)
5-9
(3)
1-4
(2)
<1
(1,
No meaningful risk
--
--
--
--
<5% (A)
4A
3A
2A
1A
5-19% (B)
4B
3B
2B
1 B
a
E
20-39% (C)
4C
3C
2C
1C
40-59% (D)
3D
2D
1 D
60-79% (E)
2E
1E
>80% (F)
1 F .
NEBA analysis of possible closure options for the ash basin at the Mayo Plant helps both Duke
Energy and other stakeholders understand the net environmental benefits from the closure
option configurations that were examined. If a closure option that is preferred for reasons not
considered in the NEBA does not rate as one of the options that best maximizes environmental
services to the local community, closure plans for that option can be re-examined, and
opportunities to better maximize environmental benefits can be identified (e.g., including an
offsite habitat mitigation project to offset environmental services lost from habitat alteration).
The NEBA can then be re -run with the updated plan to compare the revised closure plan with
other closure options.
The following is a summary of my conclusions and supporting analyses, which are structured
around the five objectives identified above.
Conclusion 1: All closure options for the Mayo ash basin are
protective of human health.
The first objective for ash basin closure, to protect human health from CCR constituent
exposure, is represented by environmental services that provide safe drinking water, safe
groundwater, safe surface water, safe food consumption, and safe recreation. For purposes of the
NEBA, these safety considerations were evaluated based on the following:
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1. Provision of permanent alternative drinking water supplies to private well
water supply users within a 0.5-mile radius of the Mayo ash basin compliance
boundary (Holman 2018);
2. Concentrations of CCR constituents of interest (COIs)9 in drinking water
wells that could potentially affect local residents and visitors, as characterized
by SynTerra (2015a, 2016b, 2017) in the Comprehensive Site Assessment
(CSA); and
3. Risk to various human populations from CCR exposure, as characterized in
the updated human health and ecological risk assessment conducted by
SynTerra (2018; Appendix B).
Based on these analyses, no CCR impacts to drinking water and no meaningful risk to humans
from CCR exposure were found under current conditions10 or under any closure option. Using
the NEBA framework and relative risk ratings, these results are summarized in Table ES-4
within the objective of protecting human health from exposure to CCR constituents.
9 COIs are constituents relevant to analysis of potential exposure to CCR constituents but are not necessarily
associated with risk to human or ecological receptors.
10 SynTerra's updated human health risk assessment (HHRA) considered only potential exposure pathways that
currently exist and could remain after ash basin closure under any closure option. Any potential risk currently
associated with seeps (or areas of wetness [AOWs]) at Mayo was not evaluated in the HHRA or considered in this
analysis because any risk resulting from seeps will be eliminated, reduced, or mitigated per the court -enforceable
Special Order by Consent (SOC) that Duke Energy entered with the North Carolina Environmental Management
Commission on August 15, 2018 (EMC SOC WQ S 18-005; See Section 4.2). The SOC requires Duke Energy to
accelerate the schedule for decanting the ash basin to "substantially reduce or eliminate" seeps that may be
affecting state or federal waters; the SOC also requires Duke Energy to take appropriate corrective actions for any
seeps remaining after decanting is complete to ensure the remaining seeps are managed "in a manner that will be
sufficient to protect public health, safety, and welfare, the environment, and natural resources" (EMC SOC WQ
S 18-005).
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Table ES-4. Summary of relative risk ratings for attributes that characterize potential
hazards to humans from CCR exposure in drinking water, surface water,
groundwater, food, and recreation
Objective
Protect Human
Health from CCR
Hazard
Exposure to CCR
o
L
L
0
o
7
Q
0
i
co
O
d
v7
>
�
v,CV
d
n
Q
a
O
0
CV
Q
U
U
(n
C
ry
f4
0
.=
O
J
d
p
O
a
Scenario
Baseline -- -- --
CIP
Excavation -- -- --
Hybrid -- -- --
--" indicates "no meaningful risk."
Current conditions and conditions under all closure options support provision of safe drinking
water, safe surface water, safe food, and safe recreation, satisfying the first objective of ash
basin closure —to protect human health from CCR constituent exposure.
Conclusion 2: All closure options for the Mayo ash basin are
protective of ecological health.
The second objective for ash basin closure, to protect ecological health from CCR constituent
exposure, is represented by environmental services that provide safe surface water, safe food
consumption, and protection of biodiversity and natural beauty. For purposes of the NEBA,
these considerations were evaluated based on the following:
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1. Risk to ecological receptors from CCR constituent exposure, as characterized
by SynTerra (2018; Appendix B) in the updated human health and ecological
risk assessment; and
2. Aquatic community health in Mayo Lake as reported in the 2017
environmental monitoring report (Duke Energy 2018a).
From my review of these analyses, no evidence of impacts to ecological receptors from CCR
constituent exposure was identified under current conditions I or under any closure option, and
Mayo Lake continues to support a healthy aquatic community (Duke Energy 2018a). Using the
NEBA framework and relative risk ratings, these results are summarized in Table ES-5 within
the objective of protecting environmental health from exposure to CCR constituents.
Current conditions and conditions under all closure options support provision of safe surface
water, safe food consumption, and protection of biodiversity and natural beauty, satisfying the
second objective of ash basin closure —to protect ecological health from CCR constituent
exposure.
" SynTerra's updated ecological risk assessment (ERA) considered only potential exposure pathways that currently
exist and could remain after ash basin closure under any closure option. Any potential risk currently associated
with seeps (or AOWs) at Mayo was not evaluated in the ERA or considered in this analysis because any risk
resulting from seeps will be eliminated, reduced, or mitigated per the court -enforceable SOC that Duke entered
with the North Carolina Environmental Management Commission on August 15, 2018 (EMC SOC WQ S 18-005;
See Section 4.2). The SOC requires Duke Energy to accelerate the schedule for decanting the ash basin to
"substantially reduce or eliminate" seeps that may be affecting state or federal waters; the SOC also requires Duke
Energy to take appropriate corrective actions for any seeps remaining after decanting is complete to ensure the
remaining seeps are managed "in a manner that will be sufficient to protect public health, safety, and welfare, the
environment, and natural resources" (EMC SOC WQ 518-005).
1707466.000 - 6216
XXl

Table ES-5. Summary of relative risk ratings for attributes that characterize potential
hazards to ecological resources from CCR exposure in surface water, soil,
sediment, and food
Objective
Protect Ecological Health from CCR
Hazard
Exposure to CCR
^
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--
--
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--
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--
--
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--
--
--
--
--
--
--
--
--
Excavation
--
--
--
--
--
--
--
--
--
--
Hybrid
--
--
--
--
--
--
--
--
--
--" indicates "no meaningful risk."
Conclusion 3: All closure options for the Mayo ash basin create
low levels of community disturbance.
The third objective for ash basin closure, to minimize risk and disturbance to humans from
closure, is represented by environmental services that provide safe air quality and a safe
community environment. For purposes of the NEBA, these considerations were evaluated based
on the following:
1. Health risks from diesel exhaust emissions to the community living and
working along transportation corridors during trucking operations to haul
materials to and from the ash basin, as evaluated through the application of
diesel truck air emissions modeling and human health risk assessment; and
1707466.000 - 6216
XXll

2. The relative risk for disturbance and accidents resulting from trucking
operations affecting residents living and working along transportation
corridors during construction operations, as evaluated by comparing the
relative differences in trucking operations among the closure options.
From these analyses, no meaningful health risk is expected from diesel exhaust emissions under
any closure option, but all closure options are expected to produce different levels of community
disturbance in the form of noise and traffic congestion and risk from traffic accidents.
I used the number of trucks per day passing12 a receptor along a near -site transportation corridor
to examine the differences in noise and traffic congestion under the closure options. I compared
the increase in the average number of trucks hauling materials to Mayo under the closure
options13 to the current number of truck passes for the same receptor. I specified a baseline level
of truck passes14 on the transportation corridor under current conditions of 314 passes per day.
Based on the assumed 314-truck-per-day baseline level and the number of truck trips per day
from Duke Energy's projections (Duke Energy 2018b), all options would have a less than 3%
impact (CIP = 2.9%, excavation = 0.01 %, hybrid = 2.3%) on noise and traffic congestion. I
input these percent changes to the risk -ranking matrix (Table ES-3) along with the total duration
of construction activities (4 years CIP; 7 years excavation; and 5 years hybrid) to evaluate which
of the closure options best minimizes human disturbances.
I also evaluated risk of traffic accidents by comparing the average number of annual offsite road
miles driven between closure options relative to an estimate of the current road miles driven in
Person County, North Carolina. I specified a current, or baseline, level of annual road miles
12 Truck passes per day resulting from closure activities are calculated as the total number of loads required to
transport earthen fill, geosynthetic materials, and other materials multiplied by two to account for return trips.
The resulting total number of passes is then divided evenly among the total number of months of construction
time multiplied by 26 working days per month.
13 Truck trips to haul ash were not included in the estimate for Mayo ash basin closure because, with the exception
of crossing U.S. Highway 501, trucks hauling ash would not leave the Mayo Plant property and would not
affect community receptors along the transportation corridors.
14 A baseline estimate of trucking passes per day for transportation corridors near Mayo was derived from North
Carolina Department of Transportation (NCDOT) data of annual average daily traffic (AADT) at thousands of
locations across the state and the proportion of road miles driven by large trucks in North Carolina (See
Appendix E for details).
1707466.000 - 6216
XXlll

driven along the transportation corridor near the Mayo Plant of 33.5 million miles,15 and the
road miles driven under the closure options are from the trucking projections provided by Duke
Energy (2018b). Using the 33.5-million-truck-miles baseline assumption, CIP has a 0.13%
impact; excavation has a 0.01% impact; and the hybrid closure option has a 0.09% impact. All
closure options have a relative risk rating of <5%. These relative risk ratings appear to be
insensitive to lower assumed baseline annual truck miles (Appendix E).
Table ES-6 summarizes the NEBA relative risk ratings based on the trucking projections and
implementation schedules provided by Duke Energy (2018b) for the objective of minimizing
disturbance to humans during closure. Disturbance and risk created by all closure options are
low (i.e., risk rating of A). While the excavation and hybrid closure options have a longer
duration (i.e., risk rating of 3 compared to 2 for CIP), the impact levels for the excavation and
hybrid closure options are less than the impacts created by CIP closure on a daily or annual
basis.
15 To estimate the number of baseline truck miles, I multiplied the number of total vehicle miles traveled in Person
County (NCDW 2017) by the Person County average 9.5% contribution of trucks to total AADT (NCDOT
2015).
1707466.000 - 6216
XX1V

Table ES-6. Summary of relative risk ratings for attributes that characterize
potential hazards to communities during closure activities.
Darker shading and higher codes indicate greater impact.
Objective
Minimize Human Disturbance
Noise and
Hazard
Traffic
Traffic
Air
Accidents
Pollution
Congestion
o
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baseline
baseline
baseline
CIP
2A
2A
--
Excavation
3A
3A
--
Hybrid
3A
3A
--
--" indicates "no meaningful risk."
All closure options support safe air quality from diesel truck emissions along the transportation
routes and create minimal disturbance to community safety. Thus, all closure options
comparably satisfy the third objective of ash basin closure —to minimize risk and disturbance to
humans from closure.
Conclusion 4: Most closure options for the Mayo ash basin
produce no net environmental disturbance.
The fourth objective for ash basin closure, to minimize risk and disturbance to the environment
from closure, is represented by two environmental services: protection of biodiversity and
natural beauty. For purposes of the NEBA, these considerations were evaluated based on
differences in the NPP of impacted habitats under the closure options, as estimated by the
number of DSAYs calculated by a habitat equivalency analysis (HEA).
1707466.000 - 6216
XXv

The results of the HEA indicate that all but one closure option produce a net gain in
environmental services as indicated by a positive DSAY total. Only CIP closure results in a net
loss of environmental services due primarily to reduced NPP services provided by grass cap,16
such that environmental services produced after closure will not compensate for the service
losses resulting from the closure. The differences in NPP services are summarized in Table ES-
7. A full description of the methods, assumptions, results, and sensitivity analyses for the HEA
are provided in Appendix D and E.
Table ES-7. Summary of NPP DSAYs for closure options
CIP
Excavation
Hybrid
Ash basin losses
Open Field
Grass Cap
-27
-26
-26
Open Water
-167
-162
-162
Stream
Wetland
Wooded
-161
-156
-156
Total losses
-356
-344
-344
Ash basin post -closure gains
Open Field
127
26
Grass Cap
295
148
Open Water
Stream
8
3
Wetland
16
3
Wooded
2,438
1,305
Total gains
295
2,589
1,486
Landfill/borrow losses
Forest
-371
-590
Open field
-151
Grass Cap
-9
Wetland
Total losses
-371
-741
-9
Landfill/borrow post -closure gains
Forest
265
Grass Cap
56
9
Total gains
265
56
9
Net Gain/Loss per Option
-166
1,559
1,142
16 An open field provides a relatively lower NPP service level than forest habitat (40% of forest NPP; Ricklefs
2008), and since a grass cap requires periodic maintenance inowing, for purposes of the HEA it was assumed
never to reach a level of NPP service equivalent to an open field. Grass cap was assigned a post -closure service
level of 8%, with full service attained in 2 years.
1707466.000 - 6216
XXVl

The impact of closure on environmental services was computed as the percentage difference in
net DSAYs produced by the closure option and the baseline DSAYs (or the absolute value of
the DSAY losses). The DSAY losses represent the NPP services that would have been produced
by the ash basin, borrow areas, and landfills but for the project closure. The DSAY gains
represent the NPP services restored after project closure plus any future gains realized from
existing habitats before remediation begins. The sum of DSAY losses and gains represents the
net change of NPP services for the project resulting from closure. Dividing the closure option
net DSAYs by the absolute value of the DSAY losses provides a percentage of the impact. From
these calculations, CIP closure as currently defined will have a 23% impact, 17 while all other
closure options will have no net adverse impact on NPP services and will, in fact, increase net
NPP services. These percent impacts were input to the risk -ranking matrix (Table ES-3) along
with the duration of the closure activities (4 years CIP; 7 years excavation; and 5 years hybrid)
to visualize, within the NEBA framework, which of the closure options best minimizes
environmental disturbances (Table ES-8).
Table ES-8. Summary of relative risk ratings for habitat changes that
affect protection of biodiversity and natural beauty.
Darker shading and higher codes indicate greater impact.
Objective
Minimize Environmental
Disturbance
Hazard
Habitat Change
Attribute
DSAYs
Scenario
Baseline
baseline
CIP
2C
Excavation
--
Hybrid
--
Within the objective of minimizing environmental disturbance from closure, my analyses
indicate that excavation and hybrid closure options produce a net benefit in habitat -derived
environmental services; however, CIP closure as currently defined decreases habitat -derived
environmental services. Thus, all closure options except CIP satisfy the fourth objective of ash
basin closure —to minimize risk and disturbance to the local environment from closure.
" As discussed below, this habitat impact could be offset with an appropriate reforestation project.
1707466.000 - 6216
XXVll

Conclusion 5: Most closure options for the Mayo ash basin
produce comparable environmental services.
Identifying environmental actions that maximize environmental services (the fifth objective for
ash basin closure) is a function of NEBA (Efroymson et al. 2003, 2004) and the overarching
objective that encompasses each of the other four objectives and all of the environmental
services that have been considered to this point.
I organized my analyses around the following five objectives for ash basin closure, and I found
the following:
1. Protect human health from CCR constituent exposure
All closure options for the Mayo ash basin are protective of human health.
2. Protect ecological health from CCR constituent exposure
All closure options for the Mayo ash basin are protective of ecological
health.
3. Minimize risk and disturbance to humans from closure
All closure options for the Mayo ash basin create low levels of community
disturbance.
4. Minimize risk and disturbance to the local environment from closure
Most closure options for the Mayo ash basin produce no net environmental
disturbance.
5. Maximize local environmental services
Most closure options for the Mayo ash basin produce comparable
environmental services.
Table ES-9 summarizes the relative risk ratings for all attributes and objectives that have been
considered. From this analysis, which is based on a scientific definition of risk acceptability and
includes no value weighting, all closure options except CIP closure produce comparable
environmental benefits, similarly satisfying the fifth objective of ash basin closure —to
maximize environmental services.
1707466.000 - 6216
XXVlll

As noted previously, NEBA analysis also provides an opportunity to better understand the net
environmental benefits of possible closure options. If Duke Energy's preferred closure option
for reasons not considered in the NEBA does not best maximize environmental services to the
local community as currently defined, the NEBA results provide insight into how environmental
services could be improved for that closure option. For instance, if Duke Energy's preferred
closure option for the Mayo Plant is CIP closure but the HEA results for the currently defined
CIP closure option estimate a net environmental service loss of an approximate 166 DSAYs,
Duke Energy could consider incorporating into an updated CIP closure plan for the Mayo Plant
a mitigation project that compensates for the net environmental service losses projected from the
currently defined CIP closure option. As an example, if Duke Energy started a reforestation
project outside of the ash basin in 2021 (when onsite preparation of the ash basin begins), the
reforestation project would gain 25.1 DSAYs/acre over the lifetime of the site (150 years in the
HEA), requiring an approximate 6.6 acre project to compensate for the 166 DSAY loss
projected from the HEA based on the current CIP closure plan. Re -analysis of the HEA
component of the NEBA for the updated possible closure options would then result in no net
environmental losses (as NPP services) from habitat alteration of the basin under any closure
option.
By looking at a wide variety of attributes that represent a number of different environmental
services that directly link to local stakeholder concerns for the Mayo ash basin, I conclude, with
a reasonable degree of scientific certainty, that all closure options except CIP provide similar net
environmental services and disturbance to the community and the environment.
1707466.000 - 6216
XX1X

Table ES-9. NEBA for closure of the ash basin at the Mayo Plant.
Darker shading and higher alphanumeric codes indicate greater impact.
Objective
Protect Human
Health from
CCR
Protect Ecological Health from CCR
Minimize Human Disturbance
Minimize
Environmental
Disturbance
Hazard
Exposure to CCR
Exposure to CCR
Noise and Traffic
Traffic
Air Pollution
Habitat Change
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1707466.000 - 6216
XXX

1 Qualifications
I am a senior managing scientist in the Ecological and Biological Sciences Practice at Exponent,
a scientific and engineering consulting firm. I am a professional ecologist, toxicologist, and
biologist with more than 20 years of experience studying the relationship between human
activities and effects on natural resources and people. I have Doctor of Science and Master of
Science degrees in environmental health from the Harvard University School of Public Health. I
have a Bachelor of Science degree in biology from Rhodes College. My academic and
professional training includes a broad background in topics ranging from biology, ecology,
toxicology, epidemiology, pollution fate and transport, and statistical analysis. Key areas of my
practice involve the use of structured frameworks for evaluating multiple lines of evidence to
assess causation of environmental impacts and to weigh the benefits and consequences of
decisions that affect ecological and human health.
Decision support projects I have conducted include the following:
• Net environmental benefit analysis (NEBA) to facilitate the selection of a
remediation plan for a lead contaminated river and to support closure option
analysis for several coal ash basins;
• Developing beach management tools to improve public advisories related to
elevated fecal bacteria from sewage contamination at recreational beaches;
• Selecting cleanup thresholds for sediment remediation that quantitatively
weigh the tradeoff between sensitivity and specificity of potential thresholds
to meet cleanup objectives;
• Natural resource damage assessment (NRDA) to support injury quantification
and restoration selection; and
• Review and testimony on the sufficiency of environmental impact analysis to
support development planning.
Projects I have been involved in have concerned coal ash basin closures, oil spills, sewage
releases, heavy metal contamination, development planning, and various industrial and
1707466.000 - 6216

municipal facilities that have generated complex releases to the aquatic environment. A list of
my publications, presentations, and cases for which I have written expert reports, been deposed,
and/or provided trial testimony is provided in my curriculum vitae, included as Appendix A of
this report.
1707466.000 - 6216 2

2 Assignment and Retention
I was asked to examine how local environmental health and environmental services are
differently affected under potential closure options for the coal ash basin at Duke Energy
Progress, LLC's (Duke Energy's) Mayo Steam Electric Plant (Mayo Plant) and to evaluate these
differences in a structured framework that can support decision -making. My assignment
included review of the comprehensive site assessment (CSA) and corrective action plan (CAP)
documents for the Mayo Plant, as well as documents available through the North Carolina
Department of Environmental Quality's (NCDEQ's) website and documents prepared as part of
Duke Energy's National Pollutant Discharge Elimination System (NPDES) permitting. I visited
the Mayo Plant on October 30, 2017, and I reviewed expert reports prepared for related matters
involving the Mayo Plant. A list of the primary documents I relied upon in formulating my
conclusions is provided in Section 3 of this report.
1707466.000 - 6216 3

3 Reliance Materials
In the process of formulating my conclusions in this matter, I have reviewed many documents.
Of those, I have relied most on the following reports and documents. Technical (scientific
literature) references are cited in subsequent sections of this report and listed in Section 12.
• Comprehensive Site Assessment (CSA) for the Mayo Steam Electric Plant (SynTerra
2015a, 2016b, 2017)
• Corrective Action Plan (CAP) for the Mayo Steam Electric Plant (SynTerra 2015b,
2016a)
o Baseline Human Health and Ecological Risk Assessment for the Mayo Steam
Electric Plant (SynTerra 2016c [Appendix E of CAP 2])
• 2017 environmental monitoring report for Mayo Lake (Duke Energy 2018a)
• NCDEQ Mayo Meeting Officer Report (NCDEQ 2016)
o Attachment V. Written Public Comments Received
o Attachment VIII. Public Comment Summary Spreadsheet
• Human Health and Ecological Risk Assessment Summary Update for the Mayo Steam
Electric Plant (SynTerra 2018; Appendix B)
• Closure logistics estimates (Duke Energy 2018b).
1707466.000 - 6216

4 Introduction
In 2015, the U.S. Environmental Protection Agency (EPA) issued a rule called the "Hazardous
and Solid Waste Management System; Disposal of Coal Combustion Residuals [CCR] from
Electric Utilities" (CCR Rule), which, among other things, regulates closure of coal ash
impoundments in the United States. Closure of coal ash impoundments in North Carolina is
further regulated by the North Carolina Coal Ash Management Act of 2014 (LAMA), as
amended by H.B. 630, Sess. L. 2016-95. Under both the North Carolina CAMA and the federal
CCR Rule, there are two primary alternatives for closure of an ash impoundment:
• "Cap in place" (CIP) closure involves decanting the impoundment and
placing a low permeability liner topped by appropriate cap material, soil, and
grass vegetation over the footprint of the ash to restrict vertical transport of
water through the ash, as well as a minimum of 30 years of post -closure care,
which requires the implementation of corrective action measures if and as
necessary;
• Excavation closure involves decanting the impoundment, excavating all ash
in the basin, transporting the ash to an appropriate, permitted, lined landfill,
and restoring the site.
Duke Energy has evaluated three representative types of closure for the ash impoundment at the
Mayo Plant: CIP; excavation to the existing (expanded) onsite, lined landfall; and a hybrid
closure, which involves excavating and consolidating ash within the basin footprint to reduce
the spatial area of CIP closure (Duke Energy 2018b). The administrative process for selecting an
appropriate closure plan is ongoing.
The purpose of my report is to examine how the local community's environmental health and
environmental services 8 are differently affected by each closure option as currently defined and
18 Environmental services, or ecosystem services, are ecological processes and functions that provide value to
individuals or society (Efroymson et al. 2003, 2004).
1707466.000 - 6216 5

to evaluate these differences in a structured framework that can support decision -making in this
matter.
4.1 Site Setting
The Mayo Plant is a coal-fired power plant that began operation in 1983. It is located in Person
County in north -central North Carolina on the North CarolinaNirginia border, approximately 10
miles northeast of the town of Roxboro, North Carolina (Figure 4-1). Bisected by U.S. Highway
501, the eastern portion of the plant encompasses 460 acres, excluding Mayo Lake, and includes
the majority of the operational facilities and equipment as well as the coal ash basin. A newly
operational lined ash monofill is located on the western portion of the Mayo Plant property,
across U.S. Highway 501.19
Coal ash from historical operations of the Mayo Plant is stored in an unlined, impounded basin.
The ash basin received all ash waste from the Mayo Plant until 2013 when the plant began
conversion to a dry -ash waste system. Since 2014, dry ash from the Mayo Plant has been
deposited in the lined onsite monofill located approximately one mile west of the ash basin. The
last ash received in the ash basin at Mayo was in 2016. The ash basin now holds approximately
6.6 million tons of CCR and covers approximately 140 acres of open water and exposed ash
(SynTerra 2017). Effluent from Mayo's active ash basin is discharged under NPDES (NPDES
Outfall 002) to Mayo Lake (SynTerra 2017).
19 Information presented in this section was derived from reviews of the CSA documents prepared by SynTerra
(2015a, 2016b, 2017).
1707466.000 - 6216 6

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The location of ash basin discharge to Mayo Lake was added (NPDES outfall 002).
1707466.000 - 6216
7

The region surrounding the Mayo Plant is an ecological transitional zone between the
Appalachian Mountains and the Atlantic coastal plain. Much of the region was transformed
historically from oak -hickory -pine forests to farmland and more recently from farmland again to
woodlands characterized by successional pine and hardwood forest (Griffith et al. 2002).
Current aerial imagery and onsite observations show that approximately 80% of the Mayo Plant
property is forested'20 and I observed extensive forest habitat areas at the Mayo Plant and near
the facility during my October 30, 2017 site visit (Figure 4-2). The many acres of game lands
adjacent to the Mayo Plant and Mayo Lake support annual hunting harvests of deer (Odocoileus
virginianus), turkey (Meleagris gallopavo silvestris), and black bear (Ursus americanus).21
a.
Figure 4-2. Images of forest habitat at the Mayo Plant, October 30, 2017.
(a) Primarily broadleaf forest canopy looking north over Crutchfield
Branch from the ash basin dam. (b) Forest understory looking north along
Crutchfield Branch. (c) Primarily coniferous forest along the banks of the
Mayo ash basin.
20 Based on interpretation of aerial satellite imagery and geographic information system (GIS) layers provided by
SynTerra for the Mayo Plant.
21 http://www.ncwildlife.org/Hunting/Seasons-Limits/Harvest-Statistics
1707466.000 - 6216 8

Mayo Lake is an approximately 2,880-acre impoundment of Mayo Creek. The reservoir was
constructed by Carolina Power & Light Co., a predecessor to Duke Energy, to provide cooling
water to the power station and receiving waters for heated water discharge22 and has since
become a popular location for recreational boating and fishing activities.23 Duke Energy owns
all shoreline property around Mayo Lake to the 450-foot contour elevation above mean sea
level, and per the 1987 permit from the U.S. Army Corps of Engineers, Duke Energy is required
to maintain the shoreline surrounding Mayo Lake in a natural and undisturbed condition, which
supports local wildlife and protects the lake. Game and Fish Magazine included Mayo Lake on
its list of four "less -pressured" high -quality fall bass lakes in North Carolina in October 2010.24
Figure 4-3 includes images of Mayo Lake.
Figure 4-3. Images of Mayo Lake, October 30, 2017.
(a) Looking east across Mayo Lake from the Mayo Plant. (b) Looking north
toward the Mayo Reservoir dam from the Mayo Plant. (c, d) Undisturbed
shoreline along Mayo Lake near the Mayo Plant.
22 Discharge of runoff from the ash basin into Mayo Lake is regulated by NCDEQ Division of Water Resources
under NPDES Permit NCO038377 at outfall 002.
21 For example: http://www.personcounly.net/departments-services/departments-i-z/parks-recreation/mayo-park-
and-lake.
24 http://www.gameandfishmag.com/fisMng/fisMng_bass-fishing_nc 0905_02/
1707466.000 - 6216 9

4.2 Closure of the Ash Impoundment at the Mayo Plant
Coal ash, or CCR, includes fly ash, bottom ash, boiler slag, and flue gas desulfurization material
(U.S. EPA 2017c). CCR are derived from the inorganic minerals in coal, which include quartz,
clays, and metal oxides (EPRI 2009). Fine-grained, amorphous particles that travel upward with
flue gas are called fly ash, while the coarser and heavier particles that fall to the bottom of the
furnace are called bottom ash (EPRI 2009). The chemical composition of coal ash is similar to
natural geologic materials found in the earth's crust, but the physical and chemical properties of
coal ash vary depending on the coal source and the conditions of coal combustion and cooling
of the flue gas (EPRI 2009). The majority of both fly ash and bottom ash are composed of
silicon, aluminum, iron, and calcium, similar to volcanic ash and shale (Figure 4-4). Trace
elements such as arsenic, cadmium, lead, mercury, selenium, and chromium generally constitute
less than 1% of total CCR composition (EPRI 2009; USGS 2015). CCR are classified as a non-
hazardous solid waste under the Resource Conservation and Recovery Act (RCRA).25
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O
€ 3W
47
V
20%
10%
0%
Volcanic Ash Shale Fly Ash Bottom Ash
5i ■AI Fe Ca ■Other Major Elements -iMinor Elements ■Trace Elements
Figure 4-4. Elemental composition of bottom ash, fly ash, shale, and volcanic ash.
Excerpt from EPRI (2009).
25 hllps://www.epa.gov/coalash/coal-ash-rule
1707466.000 - 6216 10

EPA's 2015 CCR Rule (40 CFR §§ 257 and 261) requires groundwater monitoring26 of CCR
landfills and surface impoundments and for corrective action, including closure, of CCR sites
under certain circumstances. Owners and operators of CCR landfills and impoundments that are
required to close under the regulation must conduct an analysis of the effectiveness of potential
corrective measures (a corrective measures assessment) and select a strategy that involves either
excavation or capping the "waste -in -place." Per § 257.97(b), the selected strategy must at a
minimum be protective of human health and the environment, attain groundwater protection
standards, control the source of releases so as to reduce or eliminate further releases of certain
CCR constituents into the environment, remove from the environment as much of the
contaminated material that was released from the CCR unit as is feasible, taking into account
factors such as avoiding inappropriate disturbance of sensitive ecosystems, and comply with the
standards for management of wastes in § 257.98(d).
The CCR Rule does not provide criteria for selecting between these closure alternatives because
they are both considered effective closure methods. The CCR Rule states both methods of
closure "can be equally protective, provided they are conducted properly." Hence, the final CCR
Rule allows the owner or operator to determine whether excavation or closure in place is
appropriate for their particular unit (80 FR 21412).
For the last several years, Duke Energy has been evaluating all of its ash impoundments and
remains in the midst of further evaluating each one, including at Mayo, under the CCR Rule and
pursuant to the administrative process set forth in LAMA. Ultimately, a final closure plan will
be approved by NCDEQ.
Three possible options for closure of the ash basin at the Mayo Plant were identified by Duke
Energy and are summarized in (Table 4-1). These options were used in the NEBA to examine
how different closure possibilities impact environmental services to the local community.
26 According to the CCR rule, groundwater must be evaluated for boron, calcium, fluoride, pH, sulfate, and total
dissolved solids, which are defined as the constituents for detection monitoring in Appendix III of the Rule.
When a statistically significant increase in Appendix III constituents over background concentrations is
detected, monitoring of assessment monitoring constituents (Appendix IV) is required. Assessment Monitoring
constituents are antimony, arsenic, barium, beryllium, cadmium, chromium, cobalt, fluoride, lead, lithium,
mercury, molybdenum, selenium, thallium, and radium 226 and 228, combined.
1707466.000 - 6216 11

Table 4-1. Ash basin closure options provided by Duke Energy (2018b)
Closure Option
Description
Closure Duration
Construction
(years)a
Duration (years)b
CIP
CIP
6
4
Excavation
Excavate to expanded Mayo
10
7
landfill
Hybrid
Partially excavate to consolidate
8
5
ash and CIP consolidated ash
a Includes pre -design investigation, design and permitting, site preparation, construction, and site restoration.
b Includes only site preparation, construction, and site restoration.
Table 4-2 provides a summary of some of the logistical differences between the closure options.
Key among these are the following: (1) a longer period of time is necessary to complete
excavation closure; (2) substantially more deforestation is required under an excavation
closure;27 and (3) substantially less average daily truck traffic results from excavation closure.
Considering logistics alone, however, does not provide a complete understanding of the
potential benefits and hazards associated with each closure option, and an integrated analysis is
necessary to place stakeholder concerns regarding risk from CCR in the larger context of risks
and benefits to environmental services.
Table 4-2. Overview of some key logistical differences between CIP and
excavation closure of the Mayo Plant ash basin.
Data provided by Duke Energy (2018).
Closure
Closure Completion
Deforested
Average
Option
Time (years)a
Acresb
Truck
trips/day'
CIP
6
12
5
Excavation
10
30
0.02
Hybrid 8 0 4
a Includes pre -design investigations, design and permitting, site preparation, construction,
and site restoration.
b Includes areas deforested to create borrow pits and/or landfill.
Includes the total number of offsite round trip truck trips to haul earthen, ash, and
geosynthetic material to and from the ash basin.
2' The Mayo Plant has an onsite, lined landfill that could accept some excavated ash from the Mayo ash basin;
however, there is insufficient capacity in the currently configured landfill to accept all of the coal ash from the
ash basin under an excavation closure. Forest would need to be cleared to expand the landfill capacity beyond
its current footprint to create this capacity. Deforestation is also likely under a CIP closure to access surface soil
for capping activities.
1707466.000 - 6216 12

Closure of the ash basin at Mayo involves decanting any overlying water in the basin and
excavating or capping in place the underlying ash, as specified under CAMA and the federal
CCR Rule. Additional activities related to, but separate from, closure under CAMA and the
CCR Rule concern constructed28 and non-constructed29 seeps associated with the ash basin.30 A
Special Order by Consent (SOC; EMC SOC WQ S18-005) was signed by the North Carolina
Environmental Management Commission and Duke Energy on August 15, 2018, to "address
issues related to the elimination of seeps" from Duke Energy's coal ash basins. The SOC
requires Duke Energy to accelerate the schedule for decanting the ash basin to "substantially
reduce or eliminate" seeps that may be affecting state or federal waters; the SOC also requires
Duke Energy to take appropriate corrective actions for any seeps remaining after decanting is
complete to ensure the remaining seeps are managed "in a manner that will be sufficient to
protect public health, safety, and welfare, the environment, and natural resources" (EMC SOC
WQ S18-005). Given the court -enforceable requirement for Duke Energy to remediate any
seeps remaining after decanting the ash basin to meet standards for the protection of public and
environmental health, for purposes of my analyses, seeps (or areas of wetness [AOWs]) are
assumed to contribute no meaningful risk to humans or the environment following any closure
option since all closure options will entail decanting the basins and remediating any risk
associated with remaining seeps as required by the SOC (EMC SOC WQ S18-005).
28 Constructed seeps are features within the dam structure, such as toe drains or filter blankets, that collect seepage
of liquid through the dam and discharge the seepage through a discrete, identifiable point source to a receiving
water.
29 Non -constructed seeps are not on or within the dam structure and do not convey liquid through a pipe or
constructed channel; non -constructed seeps at Mayo that require monitoring (and potentially action if they are
not eliminated after ash basin decanting) are listed in the SOC (EMC SOC WQ S 18-005).
s0 In 2014, Duke Energy provided a comprehensive evaluation of all areas of wetness (AOWs or seeps) on Duke
Energy property and formally applied for NPDES coverage for all seeps (EMC SOC WQ S 18-005).
1707466.000 - 6216 13

5 Approach to Forming Conclusions
Environmental decision -making involves complex issues that concern multiple stakeholders.
Identifying the best management alternative often requires tradeoffs among stakeholder values.
For example, remediation management alternatives can decrease potential risks to human health
and the environment from contaminants, but such benefits can also have unintended
consequences, such as adverse impacts to other functions of the environment (e.g., destruction
of habitat) or create other forms of risk (e.g., contamination of other environmental media).
These tradeoffs between existing and future environmental services necessitate a transparent and
systematic method to compare alternative actions and support the decision -making process.
Structured frameworks or processes are commonly used to weigh evidence and support
requirements for environmental decision -making. Examples include:
• Environmental assessment (EA) and environmental impact statement (EIS)
process that supports National Environmental Policy Act requirements for
evaluating impacts from development projects and selecting mitigation
measures (40 CFR § 1502);
• Comprehensive Environmental Response, Compensation, and Liability Act
(CERCLA) remedial investigation/feasibility study process that characterizes
risk from contaminants at a site and then evaluates remediation alternatives
(U.S. EPA 1988);
• RCRA corrective measures study that supports identification, development,
and evaluation of potential remedial alternatives for corrective action (U.S.
EPA 1994);
• EPA's causal analysis/diagnosis decision information system (CADDIS) that
supports stressor identification and selection of appropriate mitigation actions
under the Clean Water Act (Cormier et al. 2000);
• NRDA that characterizes injury and lost human services to support selection
of restoration projects under a number of environmental laws, including
CERCLA and the Oil Pollution Act of 1990 (e.g., NOAA 1996); and
1707466.000 - 6216 14

• NEBA that evaluates the tradeoffs in environmental impacts and benefits
from remediation alternatives (NOAA 1990; Efroymson et al. 2003, 2004).
These frameworks have different regulatory origins and somewhat different approaches to
accomplishing their specific objectives, but they all rely on a common core of analyses,
including characterization of exposures, identification of adverse effects, definition of complete
pathways between exposures and effects, characterization of risk or impact to exposed receptors
(i.e., human and ecological populations), and weight -of -evidence analysis.
My analyses in this matter have used a NEBA framework to compare the relative risks and
benefits derived from the closure options under consideration for the ash basin at the Mayo
Plant. NEBA was originally developed to examine impacts and benefits to ecological resources
and habitats excluding impacts and risk to humans (Efroymson et al. 2004); however, as noted
by U.S. EPA (2009), remediation and closure actions can also have both direct and indirect
consequences to humans. To support a more thorough analysis of the net benefits of each
closure option in this matter, I have included comparative analyses in the NEBA that consider
environmental health more broadly, including risks and benefits to both ecological and human
populations in the vicinity. My analyses draw on the core principles of the environmental
decision support frameworks discussed above and follow a pragmatic and transparent process.
In assembling information for the NEBA and forming my conclusions, I have relied on analyses
reported in the CSA and CAP documents, as well as information provided by Duke Energy.
Because a NEBA of environmental health necessarily encompasses a variety of scientific
disciplines, I assembled a team of professionals within Exponent with expertise in ecological
risk assessment (ERA), human health risk assessment (HHRA), contaminant fate and transport,
decision support analysis, and statistics to review documents and, where indicated, conduct
analyses at my direction. The results of these efforts are included in this report and have been
reviewed by me.
1707466.000 - 6216 15

5.1 Net Environmental Benefit Analysis
Net environmental benefits are defined as "the gains in environmental services or other
ecological properties attained by remediation or ecological restoration, minus the environmental
injuries caused by those actions" (Efroymson et al. 2003, 2004). Environmental services, or
ecosystem services, are ecological processes and functions that produce value to individuals or
society. A NEBA, as discussed above, is a structured framework for comparing impacts and
benefits to environmental services and support decision -making (Efroymson et al. 2003, 2004).
NEBA can be useful in evaluating and communicating the short-term and long-term impacts of
remedial alternatives but does not make a determination of which alternative is best; that
decision must be made by stakeholders and decision -makers and may ultimately involve
weighing or prioritizing some values or objectives over others (Efroymson et al. 2003, 2004).
NEBA relies on scientifically supported estimates of risk to compare the reduction of risk
associated with chemicals of potential concern (CopCs)31 under different remediation and
closure alternatives alongside the creation of any risk during the remediation and closure,
providing an objective, scientifically structured foundation for weighing the tradeoffs among
remedial and closure alternatives. Despite the scientific basis of the risk characterization
process, however, stakeholders in any environmental decision -making scenario may place
different values on different types of risk. In other words, stakeholders may have different
priorities for the remediation and closure. NEBA does not, by design, elevate, or increase the
value of, any specific risk or benefit in the framework. The purpose of NEBA is to
simultaneously and systematically examine all tradeoffs that affect the services (e.g., provision
of safe drinking water, protection of biodiversity32) provided to humans and the ecosystem by
the environment under remediation and closure, allowing decision -makers to more fully
understand all potential benefits and risks of each alternative.
31 COPCs are "any physical, chemical, biological, or radiological substance found in air, water, soil or biological
matter that has a harmful effect on plants or animals"
(hllj2s://ofmpub.cpa.gov/sor intemet/regisLry/termreg/searchandretrieve/glossariesandkeywordlists/search.do?de
tails=&glo ssaiyName=Eco%20Risk%2OAs se ssment%20G10 ssary).
32 Biodiversity is the variety of plants and animals present at a location. Protection of biodiversity refers to
provision of habitat and related functions capable of sustaining biological populations.
1707466.000 - 6216 16

EPA supports the use of NEBA (U.S. EPA 2009) as a means to compare remediation and
redevelopment alternatives "based on their contributions to human well-being." EPA and the
National Oceanic and Atmospheric Administration (NOAA) also use NEBA to support oil spill
response decision -making (Robberson 2006; NOAA 1990). Examples of NEBA in oil -spill
decision -making include:
• Exxon Valdez Oil Spill: NEBA was first applied to weigh the net
environmental benefits of rock -washing to remove beached oil versus leaving
the oil in place to naturally degrade (NOAA 1990).
• Deepwater Horizon Oil Spill: NEBA was used by the Operational Science
Advisory Team-2 (OSAT-2) to "compare the environmental consequences of
the defined cleanup endpoints for the oil and beach types considered, and the
consequences of cleanup beyond those endpoints," specifically noting, "It is
at this juncture that the concept of continued remedial efforts doing `more
harm than good' becomes a concern" (OSAT 2011).
I have personally applied NEBA to evaluate the net environmental benefits associated with two
alternative sediment remediation cleanup goals for lead contamination in a tidal river. At that
site, the river had been contaminated with lead from a battery manufacturing facility, and the
state required removal of contaminated sediment that could potentially pose a health risk to
people and the environment. The responsible party conducted human and ecological risk
assessments, toxicity tests, and benthic community analyses to support the selection of an
appropriate cleanup threshold for lead that would be protective of humans and the natural
environment. Uncertainty in the results, however, led to two different remediation threshold
concentrations being proposed by the state and by the responsible party. The NEBA was
conducted to examine the tradeoffs in environmental impacts associated with the two cleanup
thresholds. For one segment of the river, the footprint of remediation, including the size and
types of habitat impacted, was substantially different under the alternative cleanup goals. The
lower remediation threshold caused much greater impacts to submerged aquatic vegetation and
riparian (shoreline) habitat that had cascading consequences to animals that rely on those
environments. NEBA was able to demonstrate that remediation to the lower threshold would
cause greater ecological harm and disturbance to the local community with little or no decrease
1707466.000 - 6216 17

in risk to benthic invertebrates (the ecological receptor at issue).33 Consequently, the higher
remediation goal was applied to that segment of the river.
These examples of NEBA are particularly relevant to the issues at the Mayo Plant. Remediation
and closure of coal ash basins is specifically addressed in CAMA and the CCR Rule, and both
CIP and excavation closure satisfy defined cleanup endpoints. At issue is whether removal of
the coal ash under an excavation closure crosses the "juncture," as noted by OSAT-2, where the
action would do more harm than good (OSAT 2011).
5.2 Linking Stakeholder Concerns to NEBA
To better understand stakeholder concerns related to closure of the ash basin at the Mayo Plant,
I reviewed written communications about ash basin closure plans for the Mayo Plant submitted
to and summarized by NCDEQ (NCDEQ 2016). From this review, I identified the following
categories of stakeholder concerns:
• Drinking water quality
• Groundwater quality
• Surface water quality
• Fish and wildlife
• Maintaining property value
• Preservation of natural beauty
• Recreational value
• Swimming safety
• Failure of the ash impoundment
• Risk created by the closure option outweighing risk from contamination.
The primary concerns expressed by community stakeholders involve perceived risks from
exposure to CCR constituents that could negatively affect environmental services that benefit
ss Both remediation goals were found to be protective of human, fish, bird, and mammal health. Uncertainty in
toxicity test results and concern for protection of benthic macroinvertebrates (e.g., insect larvae and
crustaceans) led the state to propose a lower remediation threshold for lead.
1707466.000 - 6216 18

the community: provision of safe drinking water and food, safe recreational enjoyment (e.g.,
hunting, fishing, swimming), protection of natural beauty, and biodiversity. Potential hazards to
the community associated with closure activities include physical disturbance of existing
habitats; air pollution from diesel emissions; and traffic, noise, and accidents that could result in
property damage, injuries, and fatalities. Table 5-1 links concerns over CCR exposure and
potential hazards created by ash basin closure to environmental services that could be affected
by closure activities.
1707466.000 - 6216 19

Table 5-1. Relationships between environmental services and concerns to the local community associated with CCR
and ash basin closure hazards
Environmental Services
Safe drinking Safe surface Safe air Safe food Protection of Recreation Natural Safe community
water quality water quality quality quality biodiversity beauty environment
CCR Concerns
Drinking water
X
X
X
contamination
Groundwater contamination
X
X
X
Surface water
X
X
X X
X
X
X
contamination
Fish/wildlife contamination
X X
X
X
X
Contamination impacting
X
X
X X
X
X
X
property value
Contamination impacting
X
X
X
natural beauty
Contamination impacting
X
X
X
X
X
recreational enjoyment
Contamination impacting
X
X
X
X
swimming safety
Failure of the ash
X
X
X X
X
X
X
impoundment
Closure Hazards
Habitat alteration X X X X X
Contamination of air X X X X
Noise, Traffic, Accidents X X
1707466.000 - 6216
20

In recognition of the potential discrepancy between stakeholder priorities and the broad and
balanced treatment of service risks and benefits in NEBA, I organized the NEBA in this matter
around the following five objectives for ash basin closure that recognize stakeholder concerns
while being consistent with the methods and purpose of NEBA:
1. Protect human health from CCR constituent exposure
2. Protect ecological health from CCR constituent exposure
3. Minimize risk and disturbance to humans from closure
4. Minimize risk and disturbance to the local environment from closure
5. Maximize local environmental services.
Associations between environmental services to the local community that could be potentially
impacted by ash basin closure and the identified objectives of ash basin remediation are shown
in Table 5-2.
Table 5-2. Associations between objectives for closure and remediation of the Mayo
ash basin and environmental services
Ash Basin Closure Objectives
Protect
Protect
Minimize risk
Minimize risk
Maximize local
human health
ecological health
and
and disturbance
environmental
from CCR
from CCR
disturbance
to the local
services
Environmental
constituent
constituent
to humans
environment
Services
exposure
exposure
from closure
from closure
Safe drinking
X
X
X
water quality
Safe surface
X
X
X
water quality
Safe air quality
X
X
Safe food quality
X
X
X
Recreation
X
X
Natural beauty
X
X
X
Protection of
X
X
X
biodiversity
Safe community
X
X
environment
1707466.000 - 6216 21

NEBA relies on comparative metrics for specific attributes of the environment to examine the
potential impacts and benefits from remediation and closure alternatives (Efroymson et al. 2003,
2004). NEBA methodology is not, however, prescriptive in defining attributes or comparative
metrics because each application of NEBA is unique to contaminant exposure, remediation and
closure alternatives, available data, and stakeholder concerns. NEBA is an extension of the risk
assessment process (Efroymson et al. 2004). As a result, receptors, exposure pathways, and risks
identified in a site risk assessment are key inputs to a NEBA. The links between key
environmental services, attributes that represent those services, and comparative metrics used in
this NEBA are summarized in Table 5-3.
Table 5-3. Matrix of key environmental services, attributes, and comparative metrics
applied in the NEBA
Attributes
Environmental Services Human Health Ecological Net Primary Transportation
Risk Health Risk Productivity Metrics
Safe ground water quality HI/ELCR -- --
Safe surface water quality HI/ELCR HQ
Safe soil and sediment quality HI/ELCR HQ --
Safe air quality HI/ELCR -- --
Safe food quality HI/ELCR HQ --
Protection of biodiversity HQ DSAYs
Recreation H I/ELCRa -- DSAYs
Natural beauty HQ DSAYs
Safe community environment -- Trucking
Logistics
Notes:
DSAYs — discounted service acre -years
ELCR — excess lifetime cancer risk
HI — hazard index
HQ — hazard quotient
a Estimated from health risks from consumption of fish
I used human health attributes (e.g., risk to onsite construction workers, risk to offsite
swimmers) and risk quotients (hazard index [HI], excess lifetime cancer risk [ELCR]) to
evaluate whether there would be a potential impact to environmental services related to safe
water, air, and food under each ash basin closure option. I also used human health attributes to
evaluate whether there would be an impact to air quality during closure activities. I used
1707466.000 - 6216 22

ecological health attributes (e.g., risk to birds, mammals) and risk quotients (hazard quotient
[HQ]) to evaluate whether there would be a potential impact to environmental services related to
safe surface water and food and protection of biodiversity and natural beauty under the ash basin
closure options. I evaluated risk and disturbance associated with traffic and accidents using
transportation metrics and trucking logistics (e.g., number of truck miles driven) associated with
each closure option to evaluate impacts to community safety. I used net primary productivity
(NPP)34 and discounted service acre -years (DSAYs)35 to characterize differences in the
environmental services that derive from habitats (e.g., protection of biodiversity, natural beauty)
and that would be impacted by ash basin closure activities. Finally, I assembled all attributes,
services, and objectives within a full NEBA to examine which of the closure options best
maximizes environmental services to the local community. These metrics represent
scientifically appropriate and commonly applied metrics to evaluate risk to humans and the
environment (U.S. EPA 1989, 1997, 2000; NHTSA 2016) and to quantitatively measure
differences in environmental services associated with impact and restoration (Dunford et al.
2004; Desvousges et al. 2018; Penn undated; Efroymson et al. 2003, 2004).
Of note, my analysis did not consider the risks involved with onsite construction activities. For
example, I did not attempt to evaluate occupational accidents created by onsite construction and
excavation. Nor did I attempt to evaluate emissions associated with onsite construction
activities. Finally, I did not attempt to consider the risk created by disturbing the ash basin and
exposing it to the elements during excavation activities.
Some stakeholders also expressed concern over safety of the ash impoundment dam (NCDEQ
2016). The most recent dam safety report produced by Amec Foster Wheeler and submitted to
34 NPP represents the mass of chemically fixed carbon produced by a plant community during a given time
interval. It reflects the rate at which different ecosystems are able to sequester carbon, which is related to
mitigating climate change (hops:Hearthobservatory.nasa.gov/GlobafMgps/view.php?dl=MOD17A2 M PSN).
ss DSAYs are derived from habitat equivalency analysis (HEA). HEA is an assessment method that calculates
debits based on services lost and credits for services gained from a remediation and closure action (Dunford et
al. 2004; Desvousges et al. 2018; Penn undated). A discount rate is used to standardize the different time
intervals in which the debits and credits occur, and in doing so, present the service debits and credits at present
value. The present value of the services is usually expressed in terms of discounted service acre -years of
equivalent habitat, or DSAYs, which provide a means to compare the different service levels of affected habitat
acres (Dunford et al. 2004; Desvousges et al. 2018; Penn undated).
1707466.000 - 6216 23

NCDEQ indicates "the construction, design, operation, and maintenance of the CCR surface
impoundments have been sufficiently consistent with recognized and generally accepted
engineering standards for protection of public safety and the environment" (Williams and Tice
2018).
5.3 NEBA Risk Ratings
NEBA organizes environmental hazard and benefit information into a unitless metric that
represents the degree and the duration of impact from a remediation and closure alternative
(Efroymson et al. 2003, 2004). One approach to structure this analysis is to create a risk -ranking
matrix that maps the proportional impact of a hazard (i.e., risk) with the duration of the impact
(Robberson 2006). The risk -ranking matrix used for this application of NEBA is provided in
Table 5-4. The matrix uses alphanumeric coding to indicate the severity of an impact: higher
numbers and higher letters (e.g., 4F) indicate a greater extent and a longer duration of impact,
respectively. Shading of cells within the matrix supports visualization of the magnitude of the
effect according to the extent and duration of an impact.36 When there is no meaningful risk, the
cell is not given an alphanumeric code. Risk ratings generated from the risk -ranking matrix for
each attribute and closure option examined were assembled into objective -specific summaries to
compare the net benefits of the closure options. All closure options in the NEBA were evaluated
against current conditions as a "baseline" for comparison.
36 Categories and shading as defined in the risk -ranking matrix are based on best professional judgment and used
for discussion of the relative differences in relative risk ratings. Alternative risk matrices and resulting NEBA
classifications are explored in Appendix E.
1707466.000 - 6216 24

Table 5-4. Risk -ranking matrix for impacts and risk from
remediation and closure activities.
Darker shading/higher codes indicate greater impact.
Duration of Impact (years)
10-15
(4)
5-9
(3)
1-4
(2)
<1
(1;
No meaningful risk
--
--
--
--
<5% (A)
4A
3A
2A
1 A
5-19% (B)
4B
3B
2B
1 B
CL
E
20-39% (C)
4C
3C
2C
1C
40-59% (D)
31D
2D
1D
60-79% (E)
2E
1E
>80% (F)
1F
NEBA analysis of possible closure options for the ash basin at the Mayo Plant helps both Duke
Energy and other stakeholders understand the net environmental benefits from the closure
option configurations that were examined. If a closure option that is preferred for reasons not
considered in the NEBA does not rate as one of the options that best maximizes environmental
services to the local community, closure plans for that option can be re-examined, and
opportunities to better maximize environmental benefits can be identified (e.g., including an
offsite habitat mitigation project to offset environmental services lost from habitat alteration).
The NEBA can then be re -run with the updated plan to compare the revised closure plan with
other closure options.
5.4 Risk Acceptability
Selecting any remediation, mitigation, restoration, or closure alternative involves considerations
of risk —risk posed by contamination in place, risk created by the action, risk remaining after the
action —and all of these risk considerations must be placed in some contextual framework if
informed decisions are to be made. Hunter and Fewtrell (2001) state, "The notion that there is
some level of risk that everyone will find acceptable is a difficult idea to reconcile and yet,
without such a baseline, how can it ever be possible to set guideline values and standards, given
that life can never be risk free?"
1707466.000 - 6216 25

EPA defines risk as "the chance of harmful effects to human health or to ecological systems
resulting from exposure to an environmental stressor" (U.S. EPA 2017a). In accordance with
EPA guidance for conducting ERAS (U.S. EPA 1997) and HHRAs (U.S. EPA 1989), risk to a
receptor (e.g., person, animal) exists when exposure to a stressor or stressors occur(s) at some
level of effect; however, because not all exposures produce adverse effects in humans or
ecological species, the exposure concentrations need to overlap with adverse effect thresholds
for there to be the potential for meaningful risk. The science supporting individual benchmarks
or levels of concern differs by the specific exposure at issue and the receptor at risk; however,
such benchmarks are considered by regulatory authorities to represent the best scientific
information available to create a baseline for risk (U.S. EPA 2017b).
The potential for risk associated with contamination is often evaluated using HQs, HIs, and
ELCRs to screen environmental media (e.g., water, soil) and identify the potential risk
associated with contamination (U.S. EPA 1989, 1997, 2000). The HQ is the ratio of an exposure
point concentration37 divided by an appropriate toxicity benchmark for the receptor, chemical,
and exposure scenario. An HI, which is used in HHRA, is the sum of the HQs for several
chemicals that share the same target organ. If the HQ or HI is less than 1, exposure to that
chemical (HQ) or group of chemicals (HI) is expected to result in no adverse effects to even the
most sensitive receptors. Cancer risk to humans is typically evaluated using a probabilistic
approach that considers an acceptable risk benchmark range of 10-4 to 10-6, meaning that a
person's ELCR from the exposure being assessed is less than 1 in 10,000 to 1 in 1,000,000 (U.S.
EPA 1989, 2000).
NEBA relies on scientifically supported estimates of risk; however, regardless of the scientific
acceptability of the risk characterization process, stakeholders may place different values on
different types of risk.
37 A conservative estimate of the chemical concentration available from a particular media and exposure pathway.
1707466.000 - 6216 26

6 Summary of Conclusions
Based on my review and analyses, I developed the following conclusions in this matter, which
are structured around the five objectives identified previously:
Conclusion 1: All closure options for the Mayo ash basin are protective of human health.
Current conditions38 and conditions under all closure options support provision of safe drinking
water, safe surface water, safe food, and safe recreation, satisfying the first objective of ash
basin closure —to protect human health from CCR constituent exposure.
Conclusion 2: All closure options for the Mayo ash basin are protective of ecological
health. Current conditions39 and conditions under all closure options support provision of safe
surface water, safe food consumption, and protection of biodiversity and natural beauty,
satisfying the second objective of ash basin closure —to protect ecological health from CCR
constituent exposure.
Conclusion 3: All closure options for the Mayo ash basin create low levels of community
disturbance. All closure options support safe air quality from diesel truck emissions along the
transportation routes and create minimal risk and disturbance to community safety. Thus, all
closure options similarly satisfy the third objective of ash basin closure —to minimize risk and
disturbance to humans from closure.
Conclusion 4: Most closure options for the Mayo ash basin produce no net environmental
disturbance. All closure options, except CIP, improve habitat -derived environmental services
38 SynTerra's updated HHRA considered only potential exposure pathways that currently exist and could remain
after ash basin closure under any closure option. Any potential risk currently associated with seeps at Mayo was
not evaluated in the HHRA or considered in this analysis because any risk resulting from seeps will be eliminated,
reduced, or mitigated per the court -enforceable SOC that Duke entered with the North Carolina Environmental
Management Commission on August 15, 2018 (EMC SOC WQ S 18-005; See Section 4.2).
s9 SynTerra's updated ERA considered only potential exposure pathways that currently exist and could remain after
ash basin closure under any closure option. Any potential risk currently associated with seeps at Mayo was not
evaluated in the ERA or considered in this analysis because any risk resulting from seeps will be eliminated,
reduced, or mitigated per the court -enforceable SOC that Duke entered with the North Carolina Environmental
Management Commission on August 15, 2018 (EMC SOC WQ S 18-005; See Section 4.2).
1707466.000 - 6216 27

over baseline conditions. Therefore, all closure options, except CIP,40 have no net impacts to
the protection of biodiversity and natural beauty, satisfying the fourth objective of ash basin
closure —to minimize risk and disturbance to the local environment from closure.
Conclusion 5: Most closure options for the Mayo ash basin produce comparable
environmental services. All closure options, except CIP, produce comparable environmental
benefits with equivalent protection of human and ecological health from CCR exposure, similar
levels of disturbance to humans, and net gains in habitat -derived environmental services,
similarly satisfying the fifth objective of ash basin closure —to maximize local environmental
services.
Each will be discussed in detail in the following sections.
40 As noted in Section 5 and further discussed in Section 11, the loss of habitat -derived environmental services
could be offset with an appropriate reforestation project.
1707466.000 - 6216 28

7 Conclusion 1: All closure options for the Mayo ash
basin are protective of human health.
The first objective for ash basin closure, to protect human health from CCR constituent
exposure, is represented by environmental services that provide safe drinking water, safe
groundwater, safe surface water, safe food consumption, and safe recreation. For purposes of the
NEBA, these safety considerations were evaluated based on the following:
1. Provision of permanent alternative drinking water supplies to private well
water supply users within a 0.5-mile radius of the Mayo ash basin
compliance boundary (Holman 2018);
2. Concentrations of CCR constituents of interest (COIs)41 in drinking water
wells that could potentially affect local residents and visitors, as
characterized by SynTerra (2015a, 2016b, 2017) in the CSA; and
3. Risk to various human populations from CCR exposure, as characterized
in the updated human health and ecological risk assessment conducted by
SynTerra (2018).
Through these lines of evidence, I evaluated whether CCR constituents are currently impacting
drinking water wells, whether they will in the future, and whether other exposures to CCR
constituents pose a risk to human populations now or with ash basin closure.
7.1 Private water supply wells pose no meaningful risk to the
community around Mayo.
Per H.B. 630, Sess. L. 2016-95, all residents with drinking water supply wells within a 0.5-mile
radius of the Mayo ash basin compliance boundary have been provided with permanent
alternative drinking water supplies (i.e., filter systems; Draovitch 2018),42 eliminating drinking
water as a potential CCR exposure pathway for local residents or visitors. Additionally,
41 COIs are constituents relevant to analysis of potential exposure to CCR constituents but are not necessarily
associated with risk to human or ecological receptors.
42 NCDEQ determined Duke Energy had satisfactorily completed the permanent alternative water provision under
CAMA General Statute (G.S.) 130A-309.21 1(cl) on October 12, 2108 (Holman 2018).
1707466.000 - 6216 29

available data indicate that private well water conditions are not impacted by CCR constituents
and groundwater flow paths from the ash basin are away from residential areas (SynTerra 2017).
One public well (Bethel Hill Baptist Church) and 20 private wells are located near, but
upgradient or cross -gradient, of the 0.5-mile radius around the ash basin (SynTerra 2017), and
no private wells are located downgradient of the ash basin within 0.5 miles. In 2015, two of
these private wells were found to have exceedances of the North Carolina Groundwater Quality
Standards (2L)43 for iron, manganese, and vanadium among the constituents of interest (COIs).
These constituents are naturally occurring but have also been associated with CCR (SynTerra
2015a). In this case, however, background concentrations of these constituents were also
elevated compared to the 2L standard (SynTerra 2017). In fact, exceedances of these
constituents were below estimates of background concentrations for the area.44 A study of
private drinking water wells within 0.5 miles of Mayo as well as private drinking water wells
located within a 2-1 0-mile radius of the Mayo Plant also detected some constituents that can
been associated with CCR, but sample concentrations were less than background concentrations
(SynTerra 2017).
7.2 CCR constituents from the Mayo ash basin pose no
meaningful risk to human populations.
To assess potential risk to humans both onsite and offsite using the most recent and
comprehensive data available, SynTerra updated the baseline HHRA (SynTerra 2018) originally
conducted by SynTerra (2016c) as a component of the CAP part 2 (SynTerra 2016a). The
updated HHRA included updates45 to the conceptual site model, exposure point concentrations
for human receptors with complete exposure pathways, screening level risk assessments for
43 North Carolina Administrative code 15A NCAC 02L Groundwater Rules.
44 Samples were below the bedrock groundwater provisional background threshold value (PBTV), which was
developed by SynTerra in the 2017 CSA Supplement (SynTerra 2017).
45 Updates to risk assessments are a natural part of the risk analysis process. EPA guidance for ecological risk
assessment notes, "The [risk assessment] process is more often iterative than linear, since the evaluation of new
data or information may require revisiting a part of the process or conducting a new assessment as more
information about a site is gained through site investigations, the risk assessment must be updated to reflect the
best knowledge of potential risk at a site" (U.S. EPA 1998). EPA similarly describes human health risk
characterization as an iterative process (U.S. EPA 2000).
1707466.000 - 6216 30

human receptors with complete exposure pathways, and hazard calculations (HI, ELCR) for
receptors and COPCs with plausible complete exposure pathways.
Consistent with the 2016 baseline human health and ecological risk assessment (SynTerra
2016c), the updated HHRA (SynTerra 2018) examined CCR constituent exposure to a range of
human populations, including onsite trespassers, construction workers, and waders, under
different pathways (i.e., exposure to sediment, surface water, or groundwater). HIs and ELCRs
were estimated for scenarios with plausible complete exposure pathways.
CCR exposure pathways considered complete and evaluated in the updated HHRA included the
following (SynTerra 2018):46
• Onsite trespassers via onsite sediment and surface water
• Offsite recreational waders via offsite surface water and sediment
• Onsite construction workers via groundwater.47
Since all households with drinking water supply wells within a 0.5-mile radius of the Mayo ash
basin compliance boundary have received permanent alternative water supplies (Holman 2018)
and no potable water wells are located downgradient of the Mayo Plant (SynTerra 2017),
drinking water risks were not further evaluated because there was no complete exposure
pathway. A summary of the risk assessment results from the updated HHRA (SynTerra 2018) is
provided in Table 7-1.
46 The 2016 HHRA (SynTerra 2016c) considered exposure to offsite recreational users of Crutchfield Branch
(e.g., offsite recreational swimmers, offsite recreational waders, offsite recreational boaters, offsite recreational
and subsistence fishers), onsite trespassers, onsite construction workers, and onsite commercial and industrial
workers. Several of these receptors were removed in the updated HHRA (SynTerra 2018). SynTerra (2018)
explains that the updated HHRA did not include onsite commercial and industrial workers because "use of
personal protective equipment (e.g., boots, gloves, safety glasses) and other safety behaviors exhibited by Site
workers limits exposure to CCR constituents," and did not include offsite swimmers, boaters, or fishers because
"updated modeling and data collection demonstrate that groundwater migration from the ash basin does not
influence Mayo Lake, and observations of Crutchfield Branch confirms that it is not of sufficient size to support
these recreational uses."
47 Groundwater exposure to onsite construction workers was evaluated in the updated HHRA, though a pathway
for exposure was considered incomplete by SynTerra (2018).
1707466.000 - 6216 31

Table 7-1. Summary of human health risk assessment hazard index (HI) and excess
lifetime cancer risk (ELCR) from SynTerra (2018)
Media
Receptor
HI
ELCR
Sediment
Trespasser
0.002
NC
Surface Water
Trespasser
0.008
1.4x10-7
Groundwater (Surficial Aquifer)
Construction Worker
0.001
NC
Groundwater (Transition/Bedrock)
Construction Worker
0.001
NC
Sediment
Recreational Wader
0.002
NC
Surface Water
Recreational Wader
0.04
1.9X10-6
Notes:
NC - Risk based concentration based on non -cancer M.
All exposure scenarios assessed by SynTerra (2018) indicated that exposure to CCR poses no
meaningful risks to humans.
7.3 NEBA — Protection of Human Health from CCR Exposure
Based on these analyses, there is no CCR risk from drinking water supplies, no evidence of
CCR impacts to drinking water wells, and no meaningful risk to humans from CCR exposure
under current conditions48 or under any closure option. Using the NEBA framework and relative
risk ratings, these results are summarized in Table 7-2 within the objective of protecting human
health from exposure to CCR constituents.
48 SynTerra's updated HHRA considered only potential exposure pathways that currently exist and could remain
after ash basin closure under any closure option. Any potential risk currently associated with seeps at Mayo was
not evaluated in the HHRA or considered in this analysis because any risk resulting from seeps will be eliminated,
reduced, or mitigated per the court -enforceable SOC that Duke entered with the North Carolina Environmental
Management Commission on August 15, 2018 (EMC SOC WQ S 18-005; See Section 4.2).
1707466.000 - 6216 32

Table 7-2. Summary of relative risk ratings for attributes that characterize potential
hazards to humans from CCR exposure in drinking water, surface water,
groundwater, soil, sediment, food, and through recreation
Objective
Protect Human
Health from CCR
Hazard
Exposure to CCR
o
L
L
0
C
0
Lco
O
D
co Q
C
O
co
Q
U
U
0
C
ry
N
f4
O
.=
O
J
d
0
O
a
Scenario
Baseline
--
--
--
CIP
Excavation
--
--
--
Hybrid
--
--
--
--" indicates "no meaninaful
risk."
Current conditions and conditions under all closure options support provision of safe drinking
water, safe surface water, safe food, and safe recreation, satisfying the first objective of ash
basin closure —to protect human health from CCR constituent exposure.
1707466.000 - 6216 33

8 Conclusion 2: All closure options for the Mayo ash
basin are protective of ecological health.
The second objective for ash basin closure, to protect ecological health from CCR constituent
exposure, is represented by environmental services that provide safe surface water, safe food
consumption, and protection of biodiversity and natural beauty. For purposes of the NEBA,
these considerations were evaluated based on the following:
1. Risk to ecological receptors from CCR exposure, as characterized by
SynTerra (2018; Appendix B) in the updated human health and ecological
risk assessment; and
2. Aquatic community health in Mayo Lake as reported in the 2017
environmental monitoring report (Duke Energy 2018a).
Through these two lines of evidence, I evaluated whether CCR constituents pose a risk to
ecological populations now or after ash basin closure.
8.1 No meaningful risks to ecological receptors from CCR
exposure exist under current conditions or any closure
option.
To assess potential risk to ecological receptors both onsite and offsite using the most recent and
comprehensive data available, SynTerra (2018) updated the baseline human health and
ecological risk assessment that was originally performed by SynTerra (2016c) as a component
of the CAP part 2 (SynTerra 2016a). The updated ERA included updates to the conceptual site
model, exposure point concentrations for receptors with potentially complete exposure
pathways, and screening level risk assessments for ecological receptors with potentially
complete exposure pathways. Updated HQs were estimated for receptors with plausible
potentially complete exposure pathways to CCR related COPCs (SynTerra 2018).
The ecological receptors evaluated in an ERA are common representatives of particular groups
of organisms inhabiting different habitats and aspects of the food web. Key receptors in
1707466.000 - 6216 34

SynTerra's updated ERA (SynTerra 2018) and their pathways for exposure included the
following:
• Birds: Avifauna species may be exposed by ingestion of food and surface
water and by incidental ingestion of sediment and soil. Aquatic/wetland
species included were mallard duck (omnivore), great blue heron (piscivore),
and bald eagle (carnivore)49; terrestrial species included were American robin
(omnivore) and red-tailed hawk (carnivore).
• Mammals: Aquatic/wetland or terrestrial species may be exposed by
ingestion of food and surface water and by incidental ingestion of sediment
and soil. Aquatic/wetland species included were muskrat (omnivore) and
river otter (piscivore), and terrestrial species included were meadow vole
(herbivore) and red fox (carnivore).
Ecological risk for these indicator species was characterized by SynTerra (2018) using a risk -
based screening approach that compared chemical exposure levels to chemical toxicity reference
values (TRVs) to calculate HQs for COPCs. TRVs in the ERA included no -observed -adverse -
effects levels (NOAELs)50 and lowest -observed -adverse -effects levels (LOAELs)51 derived
from the literature for each COPC.
49 The bald eagle was added to this risk assessment model because the species is federally protected and represents
a raptor that preys upon fish, primarily, while the red-tailed hawk primarily preys upon small terrestrial
vertebrates (e.g., rodents, snakes, etc.). Hazard quotient calculations for the bald eagle include hypothetical
consumption of fish that inhabit adjacent surface water areas in addition to terrestrial vertebrates that inhabit
upland areas.
50 A NOAEL is a concentration below which no adverse effects have been observed for a specific receptor and
pathway of exposure. NOAELs are typically estimated from laboratory toxicity tests.
51 A LOAEL is a concentration associated with the lowest concentration level at which adverse effects have been
observed for a specific receptor and pathway of exposure. LOAELs are typically estimated from laboratory
toxicity tests.
1707466.000 - 6216 35

HQ results for the site were evaluated for one area of Mayo52 (Figure 8-1). HQs less than 1
indicate no meaningful risk to ecological receptor species associated with exposure to the
COPCs evaluated.
• Crutchfield Branch: All HQs <1, indicating no meaningful risk to
ecological receptors in this area.
Additionally, the 2017 environmental monitoring report (Duke Energy 2018a) for Mayo Lake
reported results from biological sampling and water chemistry analyses conducted in 2017. The
report concluded that impacts from the Mayo Plant to water quality and aquatic life are minimal.
Based on analyses of fish community composition, the fish community was reported to be
balanced and "[s]uccessful reproduction of Bluegill and Largemouth Bass was evident
throughout the reservoir" (Duke Energy 2018a).
Given the lack of meaningful ecological risk from CCR exposure under current conditions based
on the lines of evidence evaluated, all closure options would be protective of ecological
receptors since all closure options reduce or eliminate potential exposure pathways following
closure.
52 The baseline ecological risk assessment conducted by SynTerra in 2016 (SynTerra 2016c) included four
exposure areas. The ash basin exposure area, the ash basin downgradient exposure area, and the South Creek
exposure area were not evaluated for the updated ERA because they represent the ash basin, AOWs (seeps), or
upgradient locations (SynTerra 2018). The separate Crutchfield Branch downgradient and Crutchfield Branch
exposure areas were evaluated as one exposure unit, Crutchfield Branch, in the updated ERA (SynTerra 2018).
1707466.000 - 6216 36

Figure 8-1. Exposure areas evaluated in the 2018 Ecological Risk Assessment update.
Reproduced from SynTerra (2018).
1707466.000 - 6216
37

8.2 NEBA — Protection of Ecological Health from CCR
Exposure
Based on these analyses, no meaningful risk to ecological receptors from CCR exposure was
found under current conditions53 or under any closure option. Using the NEBA framework and
relative risk ratings, within the objective of protecting ecological health from exposure to CCR
constituents, these results are summarized in Table 8-1.
Table 8-1. Summary of relative risk rating for attributes that characterize potential
hazards to ecological resources from CCR exposure in surface water, soil,
sediment, and food
Objective
Protect Ecological Health from CCR
Hazard
Exposure to CCR
^
..
i
^
Y
o
>
X
O
-2
Y
O
C
O
O
CO
L
—
CU
CD
L
` '
`i
to
CU
E
CO
Q
`-'
CD
"a
E
d
0
-2
cn
E
c0
m
CU
E
cu
CU
m
cn
m
C0
E
o
m
E
2
d
W
O
a_
O
>
m
O
CU
L
CU
E
L
O
O
Q
CC
S_
a) O
>
L
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>
L
>
E
O
>
>_
>
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ii
O
>
L)
C0
U
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v
a)
CU
L
C0
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CU
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D_
:V
=
U
tl
in
a)
°�
_
70
d
0
a
7
Cr
Q
:U
CO
CO
Q
CO
:
U
CU
CU
CO
.L
to
Q
Q
�
Q
~
Cu
Scenario
Baseline
--
--
--
--
--
--
--
--
--
--
C I P
--
--
--
--
--
--
--
--
--
--
Excavation
--
--
--
--
--
--
--
--
--
--
Hybrid
--
--
--
--
--
--
--
--
--
--" indicates "no meaningful risk."
ss SynTerra's updated ERA considered only potential exposure pathways that currently exist and could remain after
ash basin closure under any closure option. Any potential risk currently associated with seeps at Mayo was not
evaluated in the ERA or considered in this analysis because any risk resulting from seeps will be eliminated,
reduced, or mitigated per the court -enforceable SOC that Duke entered with the North Carolina Environmental
Management Commission on April 18, 2018 (EMC SOC WQ S17-009; See Section 4.2).
1707466.000 - 6216 38

Current conditions and conditions under all closure options support provision of safe surface
water, safe food consumption, and protection of biodiversity and natural beauty, satisfying the
second objective of ash basin closure —to protect ecological health from CCR constituent
exposure.
1707466.000 - 6216 39

9 Conclusion 3: All closure options for the Mayo ash
basin create low levels of community disturbance.
The third objective for ash basin closure, to minimize human disturbance and risk from closure,
is represented by environmental services that provide safe air quality and a safe community
environment. For purposes of the NEBA, these considerations were evaluated based on the
following:
1. Health risks from diesel exhaust emissions to the community living and
working along transportation corridors during trucking operations to haul
materials to and from the ash basin, as evaluated through the application of
diesel truck air emissions modeling and HHRA; and
2. The relative risk for disturbance and accidents resulting from trucking
operations affecting residents living and working along transportation
corridors during construction operations, as evaluated by comparing the
relative differences in trucking operations between the closure options.
All closure options require increased trucking activity to haul materials to the site (e.g., transport
cap material to the ash basin). These activities involve the use of diesel -powered dump trucks,
which increase local diesel exhaust emissions and traffic, both of which present potential
hazards to local populations in the form of air pollution and roadway hazards. Table 9-1
summarizes the transportation logistics associated with each of the closure options Duke Energy
is considering for the Mayo Plant (Duke Energy 2018b). Obvious from these numbers is that the
amount of trucking involved in CIP and hybrid closure is substantially greater than that involved
in excavation closure because there is only a small amount of offsite cover (i.e., geosynthetic
material for capping new landfill area) needed for excavation closure; fill, cover, and topsoil
requirements are expected to be met onsite from excavated portions of dams and embankments.
All ash hauling under the excavation and hybrid options occurs on site. These differences are
reflected in the number of truck loads required and the number of miles driven.
1707466.000 - 6216 40

Table 9-1. Summary of offsite transportation logistics associated with each closure
option (Duke Energy 2018b)
CIP Excavation Hybrid
Closure Duration (years)a
6
10
8
Construction Duration (years)b
4
7
5
Offsite truck loads to haul cap Mill
materials
5,740
50
5,709
Offsite miles driven to haul cap & fill
materials
175,560
27,500
156,049
a Includes design and permitting, decanting, site preparation, construction, and site
restoration.
b Includes site preparation, construction, and site restoration.
Includes cover soil, top soil, and geosynthetic material.
d Includes ash, over -excavated soil, and removed dams and embankments.
Costs to society associated with trucking include accidents (fatalities, injuries, and property
damage), emissions (air pollution and greenhouse gases), noise, and the provision, operation,
and maintenance of public roads and bridges (Forkenbrock 1999). Generally, the magnitude of
these impacts scales with the frequency, duration, and intensity of trucking operations
(Forkenbrock 1999). Figure 9-1 illustrates the normalized differences between offsite
transportation activities under the closure options. From these results, it is clear that risk and
disturbance associated with transportation activities will be substantially greater under a CIP or
hybrid closure compared to the excavation option because most materials for excavation closure
are available onsite and do not require offsite transportation.
1707466.000 - 6216 41

O
� N
ma
r
CL
.a U
M
2
1.8
1.6
1.4
1.2
0.8
0.6
0.4
0.2
0
Projected Construction Time (years)
Total Offsite Volume Moved
Total Offsite Loads
Total Offsite Miles
Excavation Hybrid
Figure 9-1. Normalized differences between offsite transportation activities under CIP,
excavation, and hybrid closure options.
Bars represent the increased activity under closure options compared to CIP.
9.1 There is no meaningful risk from diesel emissions to
people living and working along the transportation
corridor.
The types of large dump trucks that will be used in closure activities at the Mayo Plant are
generally diesel powered, and diesel exhaust includes a variety of different particulates and
gases, including more than 40 toxic air contaminants.54 North Carolina does not have a diesel -
specific health -based toxicity threshold because diesel exhaust is not currently regulated as a
toxic air pollutant. North Carolina also does not regulate PM2.5 or PMio55 as toxic air pollutants.
North Carolina defers to EPA's chronic non -cancer reference concentration (RfC) for diesel
particulate matter (DPM) of 5 µg/m3 based on diesel engine exhaust to estimate risk from diesel
emissions.56 California is, to my knowledge, the only state that currently regulates diesel as a
toxic air contaminant and has identified both an inhalation non -cancer chronic reference
exposure level (REL)57 of 5 µg/m3 and a range of inhalation potency factors indicating that a
54 hops://oehha.ca.gov/air/health-effects-diesel-exhaust
55 PM2.5 and PMio are airborne particulate matter sizes. PM2.5 is particulate matter that is 2.5 µm or less in size;
PM10 is particulate matter that is 10 µm or less in size.
56 Integrated Risk Information System (IRIS). U.S. EPA. Diesel engine exhaust.
5' A chronic REL is a concentration level (expressed in units of micrograms per cubic meter [µg/m3]) for
inhalation exposure at or below which no adverse health effects are anticipated following long-term exposure.
1707466.000 - 6216 42

"reasonable estimate" for the inhalation unit risk is 3.Ox 10-4 (µg/m3)-I "until more definitive
mechanisms of toxicity become available" (OEHHA 2015). California bases the non -cancer and
cancer health factors on the whole (gas and particulate matter) diesel exhaust and uses PMio as a
surrogate measure.
As PMio is the basis for both the non -cancer and inhalation risk factors for diesel exhaust
exposure in California, I relied on a PMio exposure model to evaluate potential non -cancer and
cancer health risks from diesel exhaust.58
A representative segment of road was simulated using EPA's AERMOD mode159 to quantify air
concentrations at set distances away from the road (U.S. EPA 2016). Diesel truck emissions
were configured in the model in a manner consistent with the recommendations from EPA's
Haul Road Working Group (U.S. EPA 2011). The emission rate for diesel trucks was calculated
using the U.S. EPA Mobile Vehicle Emissions Simulator (MOVES) model (U.S. EPA 2015).60
Emission factors were then applied to the average number of anticipated offsite truck trips each
year to define the average annual amount of DPM emitted along the representative road
segment, and these exposures were then summed over seventy years.61 AERMOD simulations
were run for four transportation orientation directions and used five years of local
meteorological data to estimate exposure point concentrations at regular intervals from 10 to
150 m perpendicular to either side of the road. The results of the model were translated into
average PMio exposure (µg/m3) and excess cancer risk over a 70-year period using reasonable
EPA has defined long-term exposure for these purposes as at least 12% of a lifetime, or about eight years for
humans.
58 California regulations and guidance indicate that when comparing whole diesel exhaust to speciated
components of diesel (e.g., polycyclic aromatic hydrocarbons, metals) the cancer risk from inhalation of whole
diesel exhaust will outweigh the multi -pathway analysis for speciated components.
59 AERMOD will calculate both the downwind transport and the dispersion of pollutants emitted from a source.
Both transport and dispersion are calculated based on the observed meteorology and characteristics of the
surrounding land. AERMOD is maintained by EPA and is the regulatory guideline model for short-range
applications (transport within 50 km).
60 The MOVES model allows a user to determine fleet average emission factors (in units of grams of pollutant per
mile traveled) for specific classes of vehicles and specific years. In this application, factors defined by MOVES
for single -unit short -haul diesel truck were used.
61 For the cancer risk analysis, emissions were calculated as an average over the regulatory default 70-year
residential exposure duration. If the truck activity for a closure option occurs over a shorter period of time, the
duration of the truck activity exposure is factored into the 70-year averaging time (OEHHA 2015).
1707466.000 - 6216 43

maximum exposure.62 Results of the exposure modeling are provided in Table 9-2. Full results
and a more detailed description of the model are provided in Appendix C.
Table 9-2. Hazard indices (HI) and excess lifetime cancer risk (ELCR)
from exposure to diesel exhaust emissions along
transportation corridors in northern North Carolina.
Results are for the maximum exposures modeled.
Perpendicular CIP
Excavation
Hybrid
Distance from
the Road
ELCR
HI
ELCR
HI
ELCR
HI
10 m
2.77E-09
0.0000
1.50E-11
0.0000
1.95E-09
0.0000
20 m
2.25E-09
0.0000
1.22E-11
0.0000
1.59E-09
0.0000
30 m
1.77E-09
0.0000
9.61E-12
0.0000
1.25E-09
0.0000
40 m
1.46E-09
0.0000
7.90E-12
0.0000
1.03E-09
0.0000
50 m
1.23E-09
0.0000
6.69E-12
0.0000
8.69E-10
0.0000
60 m
1.08E-09
0.0000
5.85E-12
0.0000
7.60E-10
0.0000
70 m
9.60E-10
0.0000
5.21E-12
0.0000
6.77E-10
0.0000
80 m
8.64E-10
0.0000
4.69E-12
0.0000
6.09E-10
0.0000
90 m
7.85E-10
0.0000
4.26E-12
0.0000
5.54E-10
0.0000
100 m
7.19E-10
0.0000
3.90E-12
0.0000
5.07E-10
0.0000
110 m
6.63E-10
0.0000
3.60E-12
0.0000
4.67E-10
0.0000
120 m
6.14E-10
0.0000
3.33E-12
0.0000
4.33E-10
0.0000
130 m
5.72E-10
0.0000
3.10E-12
0.0000
4.03E-10
0.0000
140 m
5.34E-10
0.0000
2.90E-12
0.0000
3.77E-10
0.0000
150 m
5.01E-10
0.0000
2.72E-12
0.0000
3.53E-10
0.0000
Based on the assumptions applied in the air model, no meaningful risk from diesel emissions
associated with ash basin closure trucking operations was identified for people living and
working along the transportation corridor. The exposure model and risk assessment applied here
represent a simple approach to estimate risk. A more refined estimate of risk could be computed
with a more sophisticated air and risk model; however, it is unlikely to change the conclusion
that there is no meaningful risk to people living and working along the transportation corridor
from diesel emissions associated with ash basin closure construction operations.
62 Long -tern exposure was incorporated into the air simulation as the average exposure given estimated trucking
rates for 12 hours per day -lam to 7 pm-6 days a week for the duration of the project trucking time.
1707466.000 - 6216 44

9.2 The likelihood of noise, traffic, and accidents from
transportation activities is comparable under all closure
options.
Increased trucking increases noise and traffic congestion and creates a statistically based risk for
increased traffic accidents that could result in fatalities, injuries, and/or property damage
(Forkenbrock 1999; NHTSA 2016). The primary public intersection along the transportation
route between the ash impoundment and the onsite lined landfill occurs at U.S. Highway 501
(see Figure 4-1). There will be an increase in trucking traffic under the excavation option at this
intersection, with a statistically increased likelihood of traffic accidents (NHTSA 2016). There
will also be an increased likelihood of accidents along the transportation corridor through which
earthen and geosynthetic material is brought to the Mayo Plant under each closure option. These
accidents and associated risks to life, health, and property will generally scale with the
frequency and duration of trucking, total number of truckloads, number of roundtrip truck trips
per day, and duration of the closure.
For purposes of the NEBA two attributes of offsite truck traffic that create disturbance to local
communities were considered: (1) noise and congestion and (2) accidents. Noise and congestion
were evaluated by comparing the number of times a construction truck would be expected to
pass a given location along the transportation corridor during closure construction activities. The
difference in the likelihood of traffic accidents between the closure options was assumed to be a
function of the number of offsite road miles driven by construction trucks (NHTSA 2016).
9.2.1 Noise and Congestion
Regardless of the option, closure of the ash basin at Mayo will result in an increased number of
large trucks63 on local roads (Table 9-1). Noise from these trucks includes engine and braking
noise, which can be disruptive to the communities through which they are passing,64 and trucks
frequently passing through rural communities may pose additional disturbance from roadway
63 Twenty -ton dump trucks, or similar vehicles for bulk transport, are assumed to be the primary vehicles that will
be involved in transporting materials during closure construction activities.
64 A typical construction dump truck noise level is approximately 88 decibels 50 ft. from the truck.
(https://www.thwa.dot.gov/ENVIRONMENT/noise/construction noise/handbook/handbook09.cfm)
1707466.000 - 6216 45

congestion. To compare the disturbance of trucking noise and congestion between closure
options, I used the average daily number of truck passes for trucks carrying earthen fill and
geosynthetic material to the construction site (Table 9-1). The number of passes of trucks
hauling ash from the ash basin to the landfill was not considered because these trucks do not
leave the site except for crossing U.S. Highway 501, and community noise receptors are not
present at this location. For the CIP option, it is estimated that a total of 11,480 truck passes
hauling cover material would occur at locations along the transportation corridor within 11
miles of the facility over the 48-month course of construction, for an average of 9 passes per
day, or one truck every 65 minutes, assuming a 10-hour work day. 65 For the hybrid option, there
would be 11,418 total truck passes hauling cover material along the transportation corridor for
60 months for an average of 7 passes per day, or one truck every 82 minutes. The excavation
option does not require offsite cover material except geosynthetics and, therefore, employs only
100 total truck passes for 84 months, or less than one truck per month on average. These results
and their relative differences (as the ratio to CIP closure) are summarized in Table 9-3.
9.2.2 Traffic Accidents
Traffic accidents are assumed to be a function of the total number of offsite road miles driven by
construction trucks (NHTSA 2016). As with noise and congestion, only the miles driven hauling
earthen fill and cap materials were considered because ash -hauling vehicles will only cross U.S.
Highway 501 in one location, and I have assumed that a traffic control method would be
implemented to reduce accidents to baseline levels at this location.66 The CIP option requires a
total of approximately 175,500 miles of driving, while the excavation option requires
approximately 27,500 miles of driving. The difference in distance driven between the CIP and
excavation option is equivalent to more than six round trips to the moon. Table 9-3 summarizes
the results for all disturbances considered.
65 All closure options assume 10-hour work days, 6-day work weeks, and 26 working days per month.
66 This assumption likely minimizes the risk for traffic accidents at the U.S. Highway 501 intersection because the
increased traffic would likely increase accident risk even with a traffic control measure.
1707466.000 - 6216 46

Table 9-3. Comparative metrics for increased noise and congestion and traffic
accidents
Noise and congestion
Traffic Accidents
Months of
Closure trucking Average truck Ratio Total offsite Ratio to
option passes per day to CIP road miles driven CIP
CIP 48 9 1 175,560 1
Excavation 84 0.05 0.005 27,500 0.16
Hybrid 60 7 0.80 156,049 0.89
9.3 NEBA — Minimize Human Disturbance
From these analyses, no meaningful health risk is expected from diesel exhaust emissions under
any closure option, but the closure options are expected to produce different levels of
community disturbance in the form of noise and traffic congestion and risk from traffic
accidents.
I used the number of trucks per day passing67 a receptor along a near -site transportation corridor
to examine the differences in noise and traffic congestion under the closure options. I compared
the increase in the average number of trucks hauling earthen fill, geosynthetic material, and
other materials under the closure options to the current number of truck passes for the same
receptor. I specified a baseline, or current, level of truck passes on the transportation corridor,
and the number of truck passes per day under the closure options derive directly from the
trucking projections and implementation schedules provided by Duke Energy (2018b).
A baseline estimate of trucking passes per day for transportation corridors near the Mayo Plant
was derived from North Carolina Department of Transportation (NCDOT) data of annual
average daily traffic (AADT) at thousands of locations across the state68 and the proportion of
67 Truck passes per day is calculated as the total number of loads required to transport earthen fill, geosynthetic
material, and other materials multiplied by two to account for return trips. The resulting total number of passes
is then divided evenly among the total number of months of trucking time multiplied by 26 working days per
month.
68 Annual average daily traffic (AADT) values are derived from counts of axle pairs in every lane travelling in
both directions using a pneumatic tube counter. At each monitoring station, raw data is collected for two days,
and these raw counts are adjusted using axle and seasonal correction factors to estimate the AADT. AADT
results are compared to historical values at the same location and values at nearby stations to provide temporal
1707466.000 - 6216 47

road miles driven by large trucks in Person County.69 Based on the assumed 314 truck per day
baseline level and the number of truck trips per day from Duke Energy's projections, all options
would have a less than 3% impact (CIP = 2.9%, excavation = 0.01 %, , hybrid = 2.3%) on noise
and congestion. I input these percent impacts to the risk -ranking matrix (Table 5-4) along with
the total duration of trucking activities (4 years CIP; 7 years excavation; and 5 years hybrid) to
evaluate which of the closure options best minimizes human disturbances (Table 9-4).
I evaluated risk from traffic accidents by comparing the average number of annual offsite road
miles driven between closure options relative to a baseline estimate of the current road miles
driven.70 I chose a baseline of 33.5 million annual road miles for Person County, North
Carolina, based on the reported total vehicle miles traveled in Person County (NCDMV 2017)
multiplied by the county average 9.5% contribution of trucks to total AADT (NCDOT 2015). I
used the increase in truck miles driven over baseline in the closure options as a surrogate for the
potential increase in traffic accidents.
Using the 33.5-million-truck-miles baseline assumption, the CIP option has a 0.13% impact, the
excavation option has 0.01 % impact, and the hybrid closure option has a 0.09% impact. All
closure options have a relative risk rating of <5%. These relative risk ratings appear to be
insensitive to lower assumed baseline annual truck miles (see Appendix E for sensitivity
analysis); reducing the baseline assumption (e.g., to 6.2 million truck miles, the minimum miles
driven in any North Carolina county [Hyde County]) does not appreciably increase the expected
percent impact and relative risk rating and, by extension, the risk from traffic accidents. Results
are summarized in the NEBA framework (Table 9-4) within the objective of minimizing
disturbance to humans during closure.
and spatial quality assurance. AADT data and a mapping application user interface are available online
(http://ncdot.maps.arcgis.com/apps/webgppviewer/index.html?id=5f6fe58c ld90482ab9l O7cccO3O26280)
69 A value of 3,300 AADT was chosen as a baseline value for all vehicle traffic by identifying potential
transportation routes to and from the Mayo ash basin and selecting the AADT station along the route that
currently has the lowest traffic and would experience the greatest proportional increase in trucking traffic from
ash basin closure. The baseline AADT value (3,300) was then multiplied by the county average of large truck
traffic volume (9.5%) to derive an estimated 314 passes per day along the most sensitive portion of the
transportation corridor to and from Mayo (Appendix E).
70 The difference of baseline miles and closure option miles was divided by the baseline miles and multiplied by
100 to get a percent impact.
1707466.000 - 6216 48

Table 9-4. Summary of relative risk ratings for attributes that characterize
potential hazards to communities during remediation activities.
Darker shading and higher codes indicate greater impact.
Objective
Minimize Human Disturbance
Noise and
Hazard
Traffic
Traffic
Air
Accidents
Pollution
Congestion
L
O
L
L
o
O
o
Q
CL
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21
CO
2
a+
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J
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d
CU
O
a
Scenario
Baseline
baseline
baseline
baseline
CIP
2A
2A
--
Excavation
3A
3A
--
Hybrid
3A
3A
--" indicates "no meaningful risk."
Disturbance and risk created by all closure options are minimal (i.e., risk rating of A).71All
closure options support safe air quality from diesel truck emissions along the transportation
routes and create minimal disturbance to community safety. Thus, all closure options
comparably satisfy the third objective of ash basin closure —to minimize risk and disturbance to
humans from closure.
71 Sensitivity analyses exploring different assumptions for CIP disturbance and subsequent effects to relative risk
ratings are provided in Appendix E.
1707466.000 - 6216 49

10 Conclusion 4: Most closure options for the Mayo
ash basin produce no net environmental
disturbance.
Environmental services are derived from ecological processes or functions that have value to
individuals or society, with provision of a healthy environment to humans being one of the most
essential environmental services. Environmental services that support human health include
functions to purify freshwater, provide food, supply recreational opportunities, and contribute to
cultural values (MEA 2005). For example, forests provide habitat for deer that are hunted for
food; surface water supports fish populations that are food for bald eagles, a previously
threatened and endangered species highly valued by our society;72 and soil and wetlands purify
groundwater and surface water, respectively, by adsorbing contaminants. Central to weighing
the net environmental benefits of the closure options under consideration here is understanding
how they differentially impact the variety of environmental services at the site and in the area.
The Mayo Plant, though an industrial site, supports a diversity of habitats that provide
environmental services. Figure 10-1 illustrates the types of habitats at the site. The ash
impoundment provides habitat that supports birds and mammals; the open water habitat of the
impoundment also removes solids from surface water by providing a low -flow environment in
which ash particles and other solids can settle into the sediment before the treated water can
enter Mayo Lake. The onsite forest provides biodiversity protection in the form of foraging,
shelter, and breeding habitat for birds and mammals, among other types of organisms;
watershed protection; landscape beauty; and carbon sequestration (Bishop and Landell-Mills
2012). Beyond the Mayo Plant, Mayo Lake provides aquatic habitat that supports a variety of
fish and aquatic life (Duke Energy 2018a), which then provide food for birds and mammals.
72 Bald eagles were taken off the federal list of threatened and endangered species in 2007
(hllj2s://www.fws.gov/niidwest/cagle ).
1707466.000 - 6216 50

Figure 10-1. Map of habitat types currently present at the Mayo Plant
a 0.5 Miles
1707466.000 - 6216
51

Plants serve a vital ecosystem role by converting solar energy and carbon dioxide into food (for
themselves) and oxygen. Plants then become food for other organisms. As such, "plants provide
the energy and air required by most life forms on Earth."73 NPP represents a measure of the
mass of chemically fixed carbon produced by a plant community during a given period and
reflects the rate at which different ecosystems are able to sequester carbon. Given the
foundational role of primary production in supporting ecological food webs and healthy air,
NPP is a good surrogate for environmental services provided by different habitat types
(Efroymson et al. 2003). For example, the annual NPP of a temperate forest habitat is
approximately 2.5 times higher than for temperate grasslands or freshwater ecosystems
(Ricklefs 2008). By multiplying the acres of habitat type by NPP, NPP becomes a single metric
by which to compare the different levels of environmental services impacted by ash basin
closure.74
The fourth objective for ash basin closure, to minimize environmental disturbance, is
represented by the environmental services protection of biodiversity and natural beauty. For
purposes of the NEBA, these considerations were evaluated based on differences in habitat -
derived services estimated from the NPP of impacted habitat acres under the closure options.
10.1 Excavation and hybrid closure options result in net gains
of habitat -derived environmental services.
Regardless of the closure option, habitat, and habitat -derived environmental services, will be
altered. CIP closure requires removing existing habitat within the footprint of the ash basin,
possible temporary removal of forest habitat to create a borrow pit to source earthen materials
for the cap, and restoring the ash basin with grass cap habitat. Excavation and onsite landfilling
require temporary loss and future modification of existing habitats within the footprint of the
ash basin and permanent conversion of some forest habitat to grass cap at the landfill site. The
hybrid option requires temporary loss and future modification of existing habitats within the
73 hops://earthobservatoKy.nasa.gov/GlobafMgps/view.php?dl=MOD17A2_M PSN
74 I used rates of NPP by stand age from He et al. (2012, Figure 2c.) for mixed forests as the basis for establishing
NPP of onsite wooded habitats and used relative rates of NPP from Ricklefs (2008) to scale NPP for other
habitat types.
1707466.000 - 6216 52

footprint of the ash basin. All closure options include restoration of the ash basin footprint, but
the collateral losses of habitat, the differences in service levels of restored habitat, and the
timelines for recovery of the habitats vary based on construction schedules and the acreages and
types of habitat lost or restored. This makes it challenging to appreciate the net gain or loss of
environmental services. To address this challenge, I used a HEA to quantify the differences in
environmental services resulting from each closure option.
HEA is an assessment method widely used in NRDA to facilitate restoration scaling for
environmental services (Dunford et al. 2004; Desvousges et al. 2018; Penn undated). Numerous
damage assessment restoration plans based on the use of HEA can be found on the U.S. Fish
and Wildlife Service71 and NOAA76 websites and include sites such as the St. Lawrence River
near Massena, New York; Onondaga Lake near Syracuse, New York; and LaVaca Bay in Texas.
As Desvousges et al. (2018) describe, use of HEA has expanded in recent years beyond original
applications for NRDA to address environmental service losses from other causes such as forest
fires and climate change. As the authors note, HEA has also been used as an assessment tool in
NEBA applications, such as evaluating the effects of transmission line routing on habitats of
greater sage -grouse (Centrocercus urophasianus), a proposed threatened species.
The objective of HEA is to estimate the amount of compensatory services necessary to equal the
value of the services lost because of a specific release or incident. The method calculates debits
based on services lost because of resource losses and credits for services gained due to resource
gains. The latter are often scaled to compensate for, or offset, the loss in services. A discount
rate is used to standardize the different time intervals in which the debits and credits occur, so
the services are usually expressed in terms of discounted acre -years of equivalent habitat, or
DSAYs (Dunford et al. 2004; Desvousges et al. 2018; Penn undated).
The HEA methodology was used here to estimate changes in environmental service levels that
will accrue under closure options. Environmental services currently provided by the site will be
eliminated when the ash basin is closed. After closure is complete, there will be a new level of
75 www.doi.gov/restoration
76 www.dgM.noaa.gov
1707466.000 - 6216 53

environmental services provided as habitat is restored. Since post -closure habitats may differ
from those that currently occur onsite, future services could be greater or less than what occurs
at present. Similarly, land used as a borrow area or converted to landfill, as per the closure
options, will also impact the net level of services, as services currently provided by those
habitats may be reduced or eliminated. The environmental service losses and gains from onsite
and offsite habitats must be considered together when determining the overall net effect of a
closure option.
A common ecological metric is required to make comparisons between service gains and losses
from various habitat types. For purposes of this evaluation, I used annual NPP as the metric to
standardize across habitat types. In terms of habitats currently occurring on the site, wooded
areas have the highest NPP, so that is used as the basis for defining service level, and the service
levels for other habitat types (open fields, open water) are expressed as a proportion of that
baseline service. Based on He et al. (2012), and assuming a tree stand age of 50 years, NPP
would be approximately 6.4 tons of carbon per hectare per year (6.4 t C/halyr) in wooded areas
onsite. Based on relative rates of NPP from Ricklefs (2008), the NPP for open field and open
water habitats would be approximately 40% of the temperate forest rate. To prevent
overestimation of NPP in open water areas of the ash basin that may not provide the same level
of NPP as natural freshwater habitats (perhaps from limited abundance or diversity of
vegetation), I assumed that open water areas of the ash basin produce NPP that is 25% that of
natural ecosystems.77 Therefore, I applied a four -fold habitat quality factor to scale NPP at these
open water areas of the ash basin to approximately 10% of the rate for wooded habitats.
Deforested land for borrow areas was assumed to be reforested after closure was complete, and
landfill areas were assumed to recover to grass cap. The grass cap on landfill was given a
service value of 8%,78 as was done for CIP.
77 I observed open water areas of the ash basin that supported aquatic vegetation but do not know the extent of
vegetation in the open water areas of the ash basin. Thus, I made a conservative assumption (i.e., one that
reduces the present value of the habitat) that these areas of the ash basin provide a reduced level of NPP
compared to natural open freshwater areas.
78 An open field provides a relatively lower NPP service level than forest habitat (40% of forest NPP; Ricklefs
2008), and since a grass cap requires periodic maintenance mowing, for purposes of the HEA it was assumed
never to reach a level of NPP service equivalent to an open field. Grass cap was assumed to have 20% of the
NPP service level for open field, which is 8% of forest NPP.
1707466.000 - 6216 54

For each closure option, I used the acreage of existing habitat types and the level of service of
that habitat type to establish a baseline level of service. Based on the timelines for the various
closure options, a HEA was conducted to calculate the net change in service flow of the closure
area over the next 150 years at a 3% discount rate.79 Similarly, a HEA was run to calculate the
net change in environmental services deriving from areas used either as borrow or for landfill
expansion. Because NPP standardizes service levels across habitat types, the DSAY estimates
for all affected habitats can be summed to calculate the net service gain/loss associated with
each closure option. In addition to the assumptions identified above, several other assumptions
were made to support the HEA, which are described in Appendix D.
Results of the HEA are presented in Table 10-00 and indicate that all but one closure option for
the ash basin at Mayo result in a net gain in NPP services. Only CIP closure will result in a net
loss of environmental services due primarily to the reduced NPP services provided by the grass
cap that will replace all the existing habitats in the ash basin, such that environmental services
produced after closure will not compensate for the service losses resulting from the closure.81
Excavation and hybrid closures produce net gains in environmental services because of the
amount of forested land that will be restored within the basin and the relatively smaller footprint
of the new landfill (excavation) or borrow area (hybrid) compared to the restored ash basin area.
79 Environmental services in future years are discounted, which places a lower value on benefits that will take
longer to accrue. The basis for this is that humans place greater value on services in the present and less value
on services that occur in the future.
80 A full description of the methods, assumptions, results, and sensitivity analyses for the HEA are provided in
Appendix D.
81 Note, however, that the environmental services lost due to CIP could be offset (see discussion in Section 11) by
a suitable reforestation project that would then result in all closure options causing no net loss of habitat -derived
environmental services in the HEA model.
1707466.000 - 6216 55

Table 10-1. Summary of NPP DSAYs for closure options
CIP
Excavation
Hybrid
Ash basin losses
Open Field
Grass Cap
-27
-26
-26
Open Water
-167
-162
-162
Stream
Wetland
Wooded
-161
-156
-156
Total losses
-356
-344
-344
Ash basin post -closure gains
Open Field
127
26
Grass Cap
295
148
Open Water
Stream
8
3
Wetland
16
3
Wooded
2,438
1,305
Total gains
295
2,589
1,486
Landfill/borrow losses
Forest
-371
-590
Open field
-151
Grass Cap
-9
Wetland
Total losses
-371
-741
-9
Landfill/borrow post -closure gains
Forest
265
Grass Cap
56
9
Total gains
265
56
9
Net Gain/Loss per Option
-166
1,559
1,142
Note: DSAYs for specific habitat types are reported here rounded to the nearest whole number. As such, the
net gain/loss per option differs slightly from the sum of the individual DSAYs reported in the table.
10.2 NEBA — Minimize Environmental Disturbance
The impact of the closure options on environmental services was computed as the percentage
difference in DSAYs produced by the closure option and the absolute value of the DSAY losses.
The DSAY losses represent the NPP services that would have been produced by the site, borrow
areas, and landfills but for the project closure. The DSAY gains represent the NPP services
restored after project closure plus any future gains realized from existing habitats before
remediation begins. The sum of DSAY losses and gains represents the net change of NPP
services for the project resulting from closure. Dividing the net DSAYs by the absolute value of
the DSAY losses provides a percentage of the impact. From these calculations, the CIP closure
1707466.000 - 6216 56

as currently defined will have a 23% impact,82 while all other closure options will have no net
adverse impact on NPP services and will, in fact, increase net NPP services (Table 10-2). These
percent impacts were input to the risk -ranking matrix (Table 5-4) along with the duration of the
closure activities (4 years CIP, 7 years Excavation, and 5 years hybrid) to evaluate, within the
NEBA construct, which of the closure options best minimizes environmental disturbances
(Table 10-3).
Table 10-2. Percent impact of ash basin closure options.
CIP Excavation Hvbrid
DSAY LosseSa —726 —1,085 —353
DSAY Gains 561 2,645 1,495
Percent Impact (%) 23% 0% 0%
I
Absolute value of DSAY losses is equivalent to baseline services of the affected
habitat but for the closure.
Table 10-3. Summary of relative risk ratings for habitat changes that
affect provision of environmental services.
Darker shading and higher codes indicate greater impact.
Objective
Minimize Environmental
Disturbance
Hazard
Habitat Change
Attribute
DSAYs
Scenario
Baseline
baseline
CIP
2C
Excavation
--
Hybrid
--
Within the objective of minimizing environmental disturbance from closure, my analyses
indicate that excavation and hybrid closure options produce a net benefit in habitat -derived
environmental services; CIP closure slightly decreases habitat -derived environmental services.
Thus, all closure options except CIP, as currently defined, satisfy the fourth objective of ash
basin closure —to minimize risk and disturbance to the local environment from closure.
82 As discussed below, this habitat impact could be offset with an appropriate reforestation project.
1707466.000 - 6216 57

11 Conclusion 5: Most closure options for the Mayo
ash basin produce comparable environmental
services.
Identifying environmental actions that maximize environmental services (the fifth objective for
ash basin closure) is a function of NEBA (Efroymson et al. 2003, 2004) and the overarching
objective that encompasses each of the other four objectives and all of the environmental
services that have been considered to this point. Table 11-1 summarizes the relative risk ratings
for all attributes and objectives. Impacts to environmental services considered in this NEBA
focused on key community -relevant concerns. Risk to construction workers from construction
operations, risks to local and global populations from increased greenhouse gas emissions, and
"wear -and -tear" damage to roadways from trucking were not estimated. Each of these risks,
however, would scale with the duration, frequency, and intensity of construction operations.
Sensitivity analyses of the specifications of the NEBA framework show that the specific relative
risk ratings presented in this NEBA can change depending on how baseline is defined (see
Appendix E). The purpose of the risk matrix, and the risk ratings that result from it, is to
consolidate the results from a variety of different analyses for a variety of different data types
and attributes into a single framework for comparative analysis. It is imperative, however, to
consider the underlying information used to develop the risk ratings to interpret the differences
between closure options, particularly when percent impacts or durations of closure options are
similar but receive different risk ratings.
As noted in Section 5, NEBA analysis provides an opportunity to better understand the net
environmental benefits of possible closure options. If Duke Energy's preferred closure option
for reasons not considered in the NEBA does not best maximize environmental services to the
local community as currently defined, the NEBA results provide insight into how environmental
services could be improved for that closure option. For instance, if Duke Energy's preferred
closure option for the Mayo Plant is CIP closure but the HEA results for the currently defined
CIP closure option estimate a net environmental service loss of an approximate 166 DSAYs,
Duke Energy could consider incorporating into an updated CIP closure plan for the Mayo plant
1707466.000 - 6216 58

a mitigation project that compensates for the net environmental service losses projected from the
currently defined CIP closure option. As an example, if Duke Energy started a reforestation
project outside of the ash basin in 2021 (when onsite preparation of the ash basin begins), the
reforestation project would gain 25.1 DSAYs/acre over the lifetime of the site (150 years in the
HEA), requiring an approximate 6.6 acre project to compensate for the 166 DSAY loss
projected in the HEA. Re -analysis of the HEA component of the NEBA for the updated possible
closure options would then result in no net environmental losses (as NPP services) from habitat
alteration of the basin under any closure option.
From the closure options considered and the analyses presented in this report, which are based
on a scientific definition of risk acceptability and include no value weighting, all closure options
except CIP as currently defined produce comparable environmental benefits because they offer
equivalent protection of human and ecological health from CCR exposure, similar levels of
disturbance to humans, and net gains in habitat -derived environmental services. Thus, all
closure options except CIP provide comparable net environmental services and disturbance to
the community, similarly satisfying the fifth objective of ash basin closure —to maximize local
environmental services.
1707466.000 - 6216 59

Table 11-1. NEBA for closure of the ash basin at the Mayo Plant.
Darker shading and higher alphanumeric codes indicate greater impact.
Objective
Protect Human
Health from
CCR
Protect Ecological Health from CCR
Minimize Human Disturbance
Minimize
Environmental
Disturbance
Hazard
Exposure to CCR
Exposure to CCR
Noise and Traffic
Traffic
Air Pollution
Habitat Change
Congestion
Accidents
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12 References
Bishop, J., and N. Landell-Mills. 2012. Forest Environmental Services: An Overview. In:
Selling Forest Environmental Services: Market -Based Mechanisms for Conservation and
Development. Eds. S. Pagiola, J. Bishop, and N. Landell-Mills. New York: Earthscan
Publications Limited.
Cormier, S., S. Norton, G. Suter, and D. Reed-Judkins. 2000. Stressor Identification Guidance
Document. U.S. Environmental Protection Agency, Washington, DC, EPA/822/B-00/025, 2000.
Desvousges, W.H., N. Gard, H.J. Michael, and A.D. Chance. 2018. Habitat and Resource
Equivalency Analysis: A Critical Assessment. Ecological Economics. 1(143):74-89.
Draovitch, P. 2018. Letter to Sheila Holman, NCDEQ, from Paul Draovitch, Duke Energy.
Subject: Mayo Steam Station HB630 Completion. August 30, 2018.
Dunford, R.W., T.C. Ginn, and W.H. Desvousges. 2004. The use of habitat equivalency analysis
in natural resource damage assessments. Ecological economics. 48(1):49-70.
Duke Energy. 2018a. Mayo Steam Electric Plant 2017 Environmental Monitoring Report. Water
Resources Unit Environmental Sciences Section. Duke Energy Progress. April 2018.
Duke Energy. 2018b. "Copy of DRAFT MAYO alternatives 20181102 (2)_BLB COMMENT
03NOV2018.xlsx".
Efroymson, R.A., J.P. Nicolette, and G.W. Suter. 2003. A Framework for Net Environmental
Benefit Analysis for Remediation or Restoration of Contaminated Sites. U.S. Department of
Energy National Petroleum Technology Office. ORNL/TM-2003/17.
Efroymson, R.A., J.P. Nicolette, and G.W. Suter. 2004. A framework for net environmental
benefit analysis for remediation or restoration of contaminated sites. Environ Manag.
34(3):315-331.
EPRL 2009. Coal Ash: Characteristics, Management and Environmental Issues. Electric Power
Research Institute, Palo Alto, California, September 2009.
Forkenbrock, D.J., 1999. External costs of intercity truck freight transportation. Transportation
Research Part A: Policy and Practice. 33(7):505-526.
Griffith, G., J. Omernik, and J. Comstock. 2002. Ecoregions of North Carolina Regional
Descriptions. August 31, 2002.
He, L., J.M. Chen, Y. Pan, R. Birdsey, and J. Kattge. 2012. Relationships between net primary
productivity and forest stand age in US forests. Global Biogeochemical Cycles. 26(3):
doi :10.1029/2010 GB 003 942.
1707466.000 - 6216 61

Holman, S. 2018. Letter to Paul Draovitch, Duke Energy, from Sheila Holman, NCDEQ.
Subject: Completion of Permanent Alternate Water Supply Requirements Under General Statute
130A-309.211(cl) Mayo Steam Electric Plant. October 12, 2018.
Hosmer, J. 2017. Expert Report of J. Lawrence Hosmer in the Matter of Roanoke River Basin
Association v. Duke Energy Progress, LLC. No. 1:16-cv-607 in the United States District Court
for the Middle District of North Carolina. December 1, 2017.
Hunter, P.R., and L. Fewtrell. 2001. Acceptable risk. In: Water Quality: Guidelines, Standards
and Health. Edited by Lorna Fewtrell and Jamie Bartram. World Health Organization (WHO).
Published by IWA Publishing, London, UK. ISBN: 1 900222 28 0.
MEA. 2005. Ecosystems and human well-being: Synthesis. Millennium Ecosystem Assessment.
World Resources Institute. Island Press, Washington, DC.
NCDEQ. 2016. Meeting Officer's Report Coal Ash Impoundment Classifications, Mayo Steam
Electric Plant. April 28, 2016.
NHTSA. 2016. 2015 Motor Vehicle Crashes: Overview. Traffic Safety Facts Research Note.
U.S. Department of Transportation. National Highway Traffic Safety Administration. DOT HS
812 318. August 2016.
NCDMV. 2017. North Carolina 2016 Traffic Crash Facts: An Illustrated Analysis of North
Carolina Traffic Crash Statistics. North Carolina Division of Motor Vehicles.
NCDOT. 2015. NCDOT 2015 vehicle classification station shapefiles and documentation. North
Carolina Department of Transportation. Available from:
https:Hconnect.ncdot.gov/resources/State-Mapping/Documents/Forms/AllItems.aspx. Accessed:
October 26, 2018.
NOAA. 1990. Excavation and rock washing treatment technology: Net environmental benefit
analysis. Hazardous Materials Response Branch, National Oceanic and Atmospheric
Administration, Seattle, Washington. July 1990.
NOAA. 1996. Guidance Document for Natural Resource Damage Assessment Under the Oil
Pollution Act of 1990. Damage Assessment and Restoration Program, National Oceanic and
Atmospheric Administration, Silver Spring, MD. August 1996.
OEHHA. 2015. Air Toxics Hot Spots Program. Guidance Manual for Preparation of Health
Risk Assessment. Appendix D. Risk Assessment Procedures to Evaluate Particulate Emissions
form Diesel -Fueled Engines. Office of Environmental Health Hazard Assessment California
EPA.
OSAT. 2011. Summary Report for the Fate and Effects of Remnant Oil in the Beach
Environment. Operational Science Advisory Team - 2. Gulf Coast Incident Management.
February 10, 2011.
1707466.000 - 6216 62

Penn, T. undated. A Summary of the Natural Resource Damage Assessment Regulations under
the United States Oil Pollution Act. National Oceanic and Atmospheric Administration. Silver
Spring, MD.
Ricklefs, R.E. 2008. The economy of nature. Sixth edition. W.H. Freeman and Company, New
York.
Robberson, B. 2006. Net environmental benefit analysis (NEBA) decision -making tool:
Developing consensus for environmental decision -making in emergency response [Internet].
U.S. EPA. Region 9 / Regional Response Teams; [cited 2016 Dec 8]. Available from
hLtp://slideplgyer.com/slide/4830548/.
SynTerra. 2015a. Comprehensive site assessment report - Mayo Steam Electric Plant.
September 2, 2015. Roxboro, NC.
SynTerra. 2015b. Corrective action plan - part 1: Mayo Steam Electric Plant. December 1, 2015.
Roxboro, NC.
SynTerra. 2016a. Corrective action plan - part 2: Mayo Steam Electric Plant. February 29, 2016.
Roxboro, NC.
SynTerra. 2016b. Comprehensive site assessment, supplement 1 - Mayo Steam Electric Plant.
July 7, 2016. Roxboro, NC.
SynTerra. 2016c. Baseline Human Health and Ecological Risk Assessment. Appendix E of
Corrective action plan - part 2. February 2016.
SynTerra. 2017. 2017 Comprehensive Site Assessment Update. October 31, 2017. Roxboro,
NC.
SynTerra. 2018. Human Health and Ecological Risk Assessment Summary Update. November
2018.
TVA. 2016. Final Ash Impoundment Closure Environmental Impact Statement: Part I —
Programmatic NEPA Review. Tennessee Valley Authority. Chattanooga, TN. June 2016.
USGS. 2015. Trace Elements in Coal Ash. Fact Sheet 2015-3037. U.S. Geological Survey.
May.
U.S. EPA. 1988. Guidance for Conducting Remedial Investigations and Feasibility Studies
Under CERCLA. U.S. Environmental Protection Agency, Office of Emergency and Remedial
Response. EPA/540/G-89/004. OSWER Directive 9355.3-01. October 1988.
U.S. EPA. 1989. Risk Assessment Guidance for Superfund: Volume 1 Human Health
Evaluation Manual (Part A). U.S. Environmental Protection Agency, Office of Emergency and
Remedial Response, Washington, DC. EPA/540/1-89/002. December.
1707466.000 - 6216 63

U.S. EPA. 1994. RCRA Corrective Action Plan (final). U.S. Environmental Protection Agency,
Office of Waste Programs Enforcement, Office of Solid Waste. OSWER Directive 9902.3-2A.
May 1994.
U.S. EPA. 1997. Ecological Risk Assessment Guidance for Superfund: Process for Designing
and Conducting Ecological Risk Assessments. U.S. Environmental Protection Agency, Office of
Solid Waste and Emergency Response, Washington, DC. EPA 540-R-97-006. June.
U.S. EPA. 1998. Guidelines for Ecological Risk Assessment. U.S. Environmental Protection
Agency. EPA/630/R-95/002F. April 1998.
U.S. EPA. 2000. Risk Characterization Handbook. U.S. Environmental Protection Agency,
Office of Science Policy and Office of Research and Development, Washington, DC. EPA 100-
B-00-002. December.
U.S. EPA. 2009. Characterization of Coal Combustion Residues from Electric Utilities -
Leaching and Characterization Data. U.S. Environmental Protection Agency. EPA-600/R-
09/151. December.
U.S. EPA. 2010. Superfund Green Remediation Strategy. Office of Superfund Remediation and
Technology Innovation. U.S. Environmental Protection Agency. September 2010.
U.S. EPA. 2011. Haul Road Workgroup Recommendations. U.S. Environmental Protection
Agency. November 2011.
U.S. EPA. 2015. MOVES2014a User Guide. U.S. Environmental Protection Agency,
Assessment and Standards Division, Office of Transportation and Air Quality. EPA-420-B-15-
095. November 2015.
U.S. EPA. 2016. User's Guide for the AMS/EPA Regulatory Model (AERMOD). U.S.
Environmental Protection Agency, Office of Air Quality Planning and Standards, Air Quality
Assessment Division, Air Quality Modeling Group. EPA-454/B-16-011. December 2016.
U.S. EPA. 2017a. About Risk Assessment. https://www.gpa.gov/risk/about-risk-
assessment9whatisrisk. Last updated: May 1, 2017. Accessed: November 8, 2017.
U.S. EPA. 2017b. Water Quality Criteria. hLtps://www.epa.gov/wqc. Last updated: July 5, 2017.
Accessed: November 8, 2017.
U.S. EPA. 2017c. Coal ash basics. https://www.epa.gov/coalash/coal-ash-basics. Last updated:
April 26, 2017. Accessed: November 9, 2017.
Williams, W.A., and J.A. Tice. 2018. 2018 Annual Coal Combustion Residuals Surface
Impoundment Inspection Report - Rogers Energy Complex. May 16, 2018.
1707466.000 - 6216 64

Appendix A
Curriculum Vitae of
Dr. Ann Michelle Morrison, Sc.D.

Professional Profile
Dr. Morrison has over 20 years of experience evaluating the relationship between anthropogenic
contamination and health effects to aquatic life and humans. Dr. Morrison specializes in natural resource
damage assessment (NRDA), environmental causal analysis, and assessments of water quality
conditions. Dr. Morrison has provided scientific consultation regarding the design of field studies for
NRDA, and she has worked closely with legal counsel during scientific assessments and settlement
negotiations with state and federal trustees. Dr. Morrison has performed detailed technical assessments
of injuries to aquatic resources, including vegetation, benthic infauna, fishes, shellfishes, and corals. She
has also developed site -specific sediment toxicity thresholds based on the empirical relationships of
chemical concentrations to biological effects. She has provided expert testimony concerning injury to
aquatic resources and the net environmental benefits of remediation alternatives.
Projects she has been involved with have concerned oil spills, sewage releases, heavy metal
contamination, and various industrial and municipal facilities that have generated complex releases to the
environment. Dr. Morrison applies statistical tools and weight -of -evidence approaches to delineate
exposure zones, predict the likelihood of contamination events, evaluate net environmental benefits, and
assess causation. She uses a broad knowledge of aquatic life and human health to assess risk and injury
to these populations.
Academic Credentials & Professional Honors
Sc.D., Environmental Health, Harvard University, 2004
M.S., Environmental Health, Harvard University, 2001
B.S., Biology, Rhodes College, 1997
Prior Experience
Senior Scientist, Sole Proprietor, Morrison Environmental Data Services, 2004-2007
Data Analyst, ETI Professionals, 2005
Scientist, NIH Toxicology Training Grant, Harvard School of Public Health, 2000-2004
Guest Student, Woods Hole Oceanographic Institution, Stegeman Lab, 2001-2004
Science Intern, Massachusetts Water Resources Authority, 03-05/2000, 10/2000-10/2001
Ann Michelle Morrison, Sc.D.
12/17 1 Page 1

Research technician, Bermuda Biological Station for Research, Inc., Benthic Ecology Research Program
(BERP), Bermuda, 01/1998-09/1999, 06-08/2000
Research Intern, Bermuda Biological Station for Research, Inc., Benthic Ecology Research Program
(BERP), Bermuda, 05/1997-12/1997
NSF Research Experience for Undergraduates Fellowship, Bermuda Biological Station for Research, Inc.,
Benthic Ecology Research Program (BERP), Bermuda, 08-11/1996
Professional Affiliations
American Chemical Society — ACS
Society for Risk Analysis — SRA
Society of Environmental Toxicology and Chemistry — SETAC
North Atlantic Chapter of SETAC
Publications
Mearns AJ, Reish DJ, Bissell M, Morrison AM, Rempel-Hester MA, Arthur C, Rutherford N, Pryor R.
Effects of pollution on marine organisms. Water Environment Research 2018; 90(10):1206-1300.
Mearns AJ, Reish DJ, Oshida PS, Morrison AM, Rempel-Hester MA, Arthur C, Rutherford N, Pryor R.
Effects of pollution on marine organisms. Water Environment Research 2017; 89(10):1704-1798.
Morrison AM, Edwards M, Buonagurio J, Cook L, Murray K, Boehm P. Assessing the representativeness
and sufficiency of water samples collected during an oil spill. Proceedings, 2017 International Oil Spill
Conference, Vol 2017, No 1.
Mearns AJ, Reish DJ, Oshida PS, Morrison AM, Rempel-Hester MA, Arthur C, Rutherford N, Pryor R.
Effects of pollution on marine organisms. Water Environment Research 2016; 88(10):1693-1807.
Morrison AM, Kashuba R, Menzie CA. Evaluating alternative causes of environmental change.
Environmental Perspectives 2016; 1.
Boehm PD, Morrison AM, Semenova S, Kashuba R, Ahnell A, Monti C. Comprehensive oil spill liability
estimation. Environmental Perspectives 2016; 1.
Boehm PD, Morrison AM. Oil spill liability modeling: helping to manage existential risks. Oil & Gas Insight,
2016; 4.
Morrison AMS, Goldstone JV, Lamb DC, Kubota A, Lemaire B, Stegeman JJ. Identification, modeling and
ligand affinity of early deuterostome CYP51 s, and functional characterization of recombinant zebrafish
sterol 14a-demethylase. Biochimica et Biophysica Acta, 2014; 1840:1825-1836.
Menzie C, Kane Driscoll SB, Kierski M, Morrison AM. Advances in risk assessment in support of sediment
risk management. In: Processes, Assessment and Remediation of Contaminated Sediments. Reible DID
(ed), SERDP ESTCP Environmental Remediation Technology, Vol. 6, pp. 107-130, 2014.
Mudge S, Morrison AM. Tracking sources of sewage in the environment. Environmental Forensic Notes,
2010; 9.
Ann Michelle Morrison, Sc.D.
12/17 1 Page 2

Pietari J, Bigham G, Morrison AM. Source tracking for identification of microbial pollution sources
Environmental Forensic Notes, 2009; 6.
Goldstone JV, Goldstone HMH, Morrison AM, Tarrant AM, Kern SE, Woodin BR, Stegeman JJ.
Cytochrome P450 1 genes in early deuterostomes (tunicates and sea urchins) and vertebrates (chicken
and frog): Origin and diversification of the CYP1 gene family. Molecular Biology and
Evolution 24(12):2619-31, 2007.
Morrison AM. Receiver Operating Characteristic (ROC) Curve Analysis of Antecedent Rainfall and the
Alewife/Mystic River Receiving Waters. Boston: Massachusetts Water Resources Authority. Report
ENQUAD 2005-04, 2005. 26 p.
Morrison AM, Coughlin K. Results of intensive monitoring at Boston Harbor beaches, 1996-2004. Boston,
Massachusetts Water Resources Authority, Report ENQUAD 2005-05, 76 pp., 2004.
Morrison AM, Coughlin K, Shine JP, Coull BA, Rex AC. Receiver operating characteristic curve analysis
of beach water quality indicator variables. Applied and Environmental Microbiology, 2003; 69:6405-6411.
Coughlin K, Stanley AM. Boston Harbor beach study suggests a change in beach management.
Coastlines, 2001; Issue 11.6.
Coughlin K, Stanley AM. Water quality at four Boston Harbor beaches: Results of intensive monitoring
1996-2000. Boston, Massachusetts Water Resources Authority, Report ENQUAD 2001-18, 46 pp., 2001.
Published Abstracts
Stegeman J, Handley -Goldstone H, Goldstone J, Tarrant A, Morrison AM, Wilson J, Kern S. Pantomic
studies in environmental toxicology answers, questions and extrapolation. Journal of Experimental
Zoology Part a -Comparative Experimental Biology, 2006; 305A:181.
Goldstone JV, Goldstone HMH, Morrison AM, Tarrant A, Kern SE, Woodin BR, Stegeman JJ. Functional
evolution of the cytochrome P4501 gene family: Evidence of a pre -vertebrate origin. Marine Environmental
Research, 2006; 62: S47
Handley HH, Goldstone JV, Morrison AM, Tarrant, Wilson JY, Godard CA, Woodin BR, Stegeman JJ.
Abstracts from the 12th International Symposium on Pollutant Responses in Marine Organisms (PRIMO
12) — Receptors and Regulation of Cytochrome P450. Marine Environmental Research, 2004; 58:131+.
Morrison AM, Stegeman JJ. Abstracts from the Twelfth International Symposium on Pollutant Responses
in Marine Organisms (PRIMO 12) — Cloning, Expression and Characterization of Cytochrome P450 51:
An investigation of CYP51 azole sensitivity in aquatic animals. Marine Environmental Research, 2004;
58:131 +.
Morrison AM, Stegeman JJ. CYP51 azole sensitivity in lower vertebrates and invertebrate. Drug
Metabolism Reviews: Biotransformation and Disposition of Xenobiotics, 2003; 35(2):179.
Presentations
Morrison AM, Ma J, Gard N, Palmquist K, Lin C, Deines A. Ecosystem services accounting in support of
corporate environmental stewardship in a changing climate. Society of Environmental Toxicology and
Chemistry (SETAC) North America 39th Annual Meeting, Sacramento, CA. November 5-8, 2018.
Pietari J, Morrison AM, Kashuba R, Boehm PD. Incorporating a framework for risk assessment, risk
management, and risk mitigation of extreme weather events at Superfund sites. Society of Environmental
Ann Michelle Morrison, Sc.D.
12/17 1 Page 3

Toxicology and Chemistry (SETAC) North America 39th Annual Meeting, Sacramento, CA. November 5-
8, 2018.
Deines AM, Palmquist K, Morrison AM. Global Status and Risk of Non -Native Fish Aquaculture. 148th
Annual Meeting of the American Fisheries Society, Atlantic City, NJ. August 19-23, 2018.
Morrison AM, Palmquist K, Kashuba R. Baseline in the Open -Access and "Big Data" Era. Law Seminars
International. Washington, D.C. March 1, 2018.
Palmquist K, Morrison AM, Edwards ME. Addressing white hat bias: Lessons from environmental
litigation. Society of Environmental Toxicology and Chemistry (SETAC) North America 38th Annual
Meeting, Minneapolis, MN. November 12-16, 2017.
Palmquist KR, Ginn TC, Morrison AM, Boehm PD. 2017. Addressing Spatial Data Gaps in Deep-sea
Benthic Sediment Sampling Following a Large -Scale Oil Spill. Battelle Sediment Conference in New
Orleans, LA.
Morrison AM. The Science. Natural Resource Damages 101. Law Seminars International. Washington,
D.C. March 9, 2016.
Morrison AM, Murray KJ, Cook LC, Boehm PD. Spatial and Temporal Extent of PAHs Associated with
Surface Oil Distributions (Anomalies). Gulf of Mexico Research Initiative Conference. Tampa, FL.
February 1-4, 2016.
Boehm PD, Morrison AM. The Interplay of Data Needs and Data Analysis Frameworks to Optimize the
Collection and Use of Data from Oil Spills. Gulf of Mexico Research Initiative Conference. Tampa, FL.
February 1-4, 2016.
Whaley JE, Morrison AM, Savery LC. Using the Causal Analysis Framework to Investigate Marine
Mammal Unusual Mortality Events (poster), Society of Marine Mammalogy Biennial Conference, San
Francisco, CA. December 2015.
Kashuba R, Morrison AM, Menzie C. The Application and Misapplication of Directed Acyclic Graphs for
Causal Inference in Ecology. Society of Environmental Toxicology and Chemistry (SETAC) North America
36th Annual Meeting, Salt Lake City, UT. November 1-5, 2015.
Kierski M, Morrison AM, Kane Driscoll S, Menzie C. A Refined Multi -Site Model to Estimate the Toxicity of
PAH-Contaminated Sediments at MGP Sites. Society of Environmental Toxicology and Chemistry
(SETAC) North America 36th Annual Meeting, Salt Lake City, UT. November 1-5, 2015.
Morrison AM, McArdle M, Menzie C. A Tiered Approach to Causal Analysis in Natural Resource Damage
Assessment. 35th Annual Society of Environmental Toxicology and Chemistry (SETAC) Meeting,
Vancouver, BC, Canada. November 9-13, 2014.
Morrison AM, Kane Driscoll S, McArdle M, Menzie C. Integrated environmental benefit analysis of
sediment remediation thresholds. 32nd Annual Society of Environmental Toxicology and Chemistry
(SETAC) Meeting, Boston, MA. November 14-17, 2011.
Kierski M, Morrison AM, Kane Driscoll S, Menzie C. A multi -site model to estimate the toxicity of PAH
contaminated sediments at MGP sites. 32nd Annual Society of Environmental Toxicology and Chemistry
(SETAC) Meeting, Boston, MA. November 14-17, 2011.
Kierski M, Morrison AM, Kane Driscoll S, Menzie C. Use of receiver operating characteristic curve
analysis to estimate ecological risk zones as part of an ecological risk assessment. 31 st Annual Society
Ann Michelle Morrison, Sc.D.
12/17 1 Page 4

of Environmental Toxicology and Chemistry (SETAC) Meeting, Portland, OR. November 7-11, 2010
Morrison AM, Coughlin K, Rex A. Bayesian network predictions of Enterococcus exceedances at four
Boston Harbor beaches. Water Resources Conference 2008, Amherst, MA. April 8, 2008.
Stegeman J, Handley -Goldstone H, Goldstone J, Tarrant A, Morrison AM, Wilson J, Kern S. Pantomic
studies in environmental toxicology answers, questions and extrapolation. 15th International Congress of
Comparative Endocrinology, Boston, MA. 2005.
Goldstone JV, Goldstone HMH, Morrison AM, Tarrant A, Kern SE, Woodin BR, Stegeman JJ. Functional
evolution of the cytochrome P4501 gene family: Evidence of a pre -vertebrate origin. 13th International
Symposium on Pollutant Responses in Marine Organisms (PRIMO 13), Alessandria, Italy, June 2005.
Morrison AM, Stegeman JJ. CYP51 azole sensitivity in lower vertebrates and invertebrate. 12th North
American Meeting of the International Society for the Study of Xenobiotics, Providence, RI. October 12-
16, 2003.
Morrison AM, Stegeman JJ. Cloning, expression and characterization of Cytochrome P450 51: An
investigation of CYP51 azole sensitivity in aquatic animals. 12th International Symposium, Pollutant
Responses in Marine Organisms, Tampa, FL. May 2003.
Handley HH, Goldstone JV, Morrison AM, Tarrant AM, Wilson JY, Godard CA, Woodin BR, Stegeman JJ.
12th International Symposium, Pollutant Responses in Marine Organisms, Tampa, FL. May 2003.
Morrison AM, Coughlin KA, Shine JP, Coull BA, Rex AC. Receiver operating characteristic curve analysis
of beach water quality indicator variables. Pathogens, Bacterial Indicators, and Watersheds: Treatment,
Analysis, Source Tracking, and Phase 11 Stormwater Issues. New England Watershed Association,
Milford, MA. May 14, 2003.
Stanley AM, Coughlin KA, Shine JP, Coull BA, Rex AC. Receiver operating characteristic analysis is a
simple and effective tool for using rainfall data to predict bathing beach bacterial water quality. 102nd
General Meeting, American Society for Microbiology, Salt Lake City, UT. May 2002.
Coughlin K, Stanley AM. Five years of intensive monitoring at Boston harbor beaches: Overview of beach
water quality and use of the Enterococcus standard to predict water quality. Massachusetts Coastal Zone
Marine Monitoring Symposium, Boston, MA. May 2001.
Smith SR, Grayston LM, Stanley AM, Webster G, McKenna SA. CARICOMP coral reef monitoring: A
comparison of continuous intercept chain and video transect techniques. Scientific Aspects of Coral Reef
Assessment, Monitoring and Management, National Coral Reef Institute (NCRI), Nova Southeastern
University, Ft. Lauderdale, FL. 1999.
Project Experience
Dr. Morrison has been involved in numerous complex projects relating to environmental contamination
and potential risk to humans and biological resources in the affected environment.
Risk Assessments and Natural Resource Assessments
Expert witness concerning net environmental benefits from coal ash closure alternatives at two coal ash
plants in North Carolina. Roanoke River Basin Association v. Duke Energy Progress, LLC, United States
District Court, Middle District of North Carolina, Case No. 1:16-cv-607 and Roanoke River Basin
Association v. Duke Energy Progress, LLC, United States District Court, Middle District of North Carolina,
Case No. No. 1:17-cv-452.
Ann Michelle Morrison, Sc.D.
12/17 1 Page 5

Expert witness concerning potential damages to terrestrial and aquatic resources, including coral reefs,
endangered sea turtles, fish and shellfish, and seagrass beds, resulting from a coastal development
project on the Caribbean island of Nevis. Anne Hendricks Bass vs. Director of Physical Planning,
Development Advisory Committee, and Caribbean Development Consultant Limited. Eastern Caribbean
Supreme Court, in the High Court of Justice Saint Christopher and Nevis, Nevis Circuit, Civil Case No.
N EVHCV2016/0014.
Expert witness concerning potential impacts to California fishery populations from the Refugio oil spill.
Andrews et al. v. Plains All American Pipeline, L.P. et al. United States District Court, Central District of
California, Wester Division, Case No. 2:15-cv-04113-PSG-JEM.
Provided analysis and technical support in Florida v. Georgia United States Supreme Court case that
considered questions of causation relative to alleged adverse ecological changes in downstream river
and bay populations.
Conducted a comprehensive review of an environmental impact assessment of potential impacts to coral
reefs from a proposed dairy farm development in Hawaii.
Provided scientific support for the Deepwater Horizon NRDA in the Gulf of Mexico.
Developed a cooperative NRDA field study in the offshore waters of the Gulf of Mexico to collect
sediment samples for analysis of chemistry, toxicology, and benthic infauna.
Expert witness concerning alleged injuries to aquatic resources from disposal of bauxite ore processing
wastes for the case: Commissioner of the Department of Planning and Natural Resources, Alicia V.
Barnes, et al. v. Virgin Islands Alumina Company et al. District Court of the Virgin Islands, Division of St.
Croix, Civil Case No. 2005-0062.
Developed decision management products for beach water quality stakeholders using statistical data
analysis tools such as receiver operating characteristic (ROC) curves and Bayesian networks to improve
public beach advisories related to elevated fecal bacteria.
Developed net environmental benefit analysis (NEBA) for a lead contaminated river. This analysis used
site -specific data to evaluate the costs and benefits of two different remediation options that were being
considered. The NEBA was successfully used by the client to negotiate a higher remediation goal than
original proposed by the state Department of Environmental Protection.
Performed ROC curve analyses of site -specific polycyclic aromatic hydrocarbon (PAH) toxicity data to
assess the relationship between PAH concentration and toxicity at three ecological risk assessment
projects in Wisconsin. The curves were used to identify site -specific toxicity thresholds for PAH
concentration in sediment that were indicative of various zones of toxicity (no toxicity, low toxicity, and
high toxicity), with very limited misidentification of sediments.
Provided research support to calculate site -specific no -observed -adverse -effect level (NOAEL) and
lowest -observed -adverse -effect level (LOAEL) concentrations for mammals and birds for use in a
baseline ecological risk assessment in Wisconsin.
Performed ROC curve analysis of national mercury toxicity data to assess the relationship between
mercury concentration and toxicity. The curves were also used to identify a threshold mercury
concentration for sediment that indicates likely toxicity, with very limited misidentification of sediments that
are not toxic.
Assembled and analyzed data and reviewed remedial investigations to conduct a screening -level
Ann Michelle Morrison, Sc.D.
12/17 1 Page 6

ecological risk assessment for sediment, surface water, and groundwater for a site in Connecticut. The
chemicals considered were total petroleum hydrocarbons (TPH), metals, and PAHs.
Reviewed species lists and created summary descriptions of organisms that could be potentially impacted
by dam construction on a high -altitude river in the Caribbean. This information was important to develop
the risk assessment from dam construction.
Researched the toxicity of malathion to fish to support a technical review of the National Marine Fisheries
biological opinion for the registration of pesticides containing malathion.
Ecological and Toxicity Studies
Conducted surveys to assess the health of coral reefs, seagrass beds, and mangrove swamps in the
nearshore environment of Bermuda. Projects included area -wide habitat surveys as well as targeted sites
potentially impacted by a heavy metals dump, hot water effluent from an incinerator, sedimentation from
cruise ship traffic, and chronic release of raw sewage. In addition to ecological surveys, water quality was
assessed through measurements of trace metals in water, sediment, and coral tissue.
Surveyed juvenile coral recruitment in the Florida Keys to evaluate if marine protected areas (MPAs)
provide a benefit to coral recruitment.
Studied cytochrome P450 family enzymes, including CYP51 and CYP1, examining their sensitivity to
environmental chemicals and their evolution through molecular biology and biochemistry approaches.
Environmental Forensics Projects
Performed document review, information management, and technical writing for numerous complex
projects that dealt with historical petroleum contamination and multiple site owners in several types of
environmental media.
Reviewed documents, assembled data, and researched metal concentrations associated with crude oil
and railroads in support of a Superfund project in Oklahoma.
Examined the correlation of multiple contaminants (PAHs, metals) with polychlorinated biphenyl (PCB)
congeners at a historically contaminated site in Alabama to identify the likely origins of the PCB
contamination.
Performed statistical analysis to determine source contribution in a chemical fingerprinting case at a
Superfund site in Washington that involved hydrocarbons in water, sediment, and groundwater.
Human Health Projects
Organized, managed, and simplified a complex database of field sampling reports for a litigation case in
Louisiana regarding human air exposure to PAHs.
Performed data analysis and document review for a Superfund site in Oklahoma. The analyses used
hydrocarbon chromatograms and limited PAH and metal data to identify the likely sources of
contamination.
Researched and compiled screening -level human health inhalation toxicity values for refinery -related
gases for an overseas project.
Developed a questionnaire and related database for industrial hygiene surveys to support regulatory
compliance for a highly specialized industry.
Ann Michelle Morrison, Sc.D.
12/17 1 Page 7

Appendix B
Human Health and Ecological
Risk Assessment Summary
Update for Mayo Steam
Electric Plant

410
synTerra
HUMAN HEALTH AND
ECOLOGICAL RISK ASSESSMENT
SUMMARY UPDATE
For
MAYO STEAM ELECTRIC PLANT
10660 BOSTON ROAD
ROXBORO, NORTH CAROLINA 27574
NOVEMBER 2018
PREPARED FOR
DUKE ENERGY PROGRESS, LLC
526 SOUTH CHURCH STREET
CHARLOTTE, NORTH CAROLINA 28202
(7 DUKE
V ENERGY,
PROGRESS
att Huddleston, Ph.D.
Senior Scientist
4-"AV �, �- -
Heather Smith
Environmental Scientist

Risk Assessment Summary Update November 2018
Mayo Steam Electric Plan SynTerra
1.0 INTRODUCTION
This update to the Mayo Steam Electric Plant (Mayo or Site) human health and
ecological risk assessment incorporates results from sampling events conducted
October 2008 through July 2018. The samples were collected from surface water,
sediment, and groundwater. This update was performed in support of a Net
Environmental Benefits Analysis. As set forth below in detail, this updated risk
assessment concludes that: (1) the Mayo ash basin does not cause any material increase
in risks to human health for potential human receptors located on -Site or off -Site; and
(2) the Mayo ash basin does not cause any material increase in risks to ecological
receptors.
The original 2016 risk assessment was a component of the Corrective Action Plan Part 2
pertaining to Mayo (SynTerra, 2016). To assist in corrective action decision making, the
risk assessment characterized potential effects on humans and wildlife exposed to
naturally occurring elements, often associated with coal ash, present in environmental
media. Corrective action is to be implemented with the goal of ensuring future site
conditions remain protective of human health and the environment, as required by the
2014 North Carolina General Assembly Session Law 2014-122, Coal Ash Management
Act (CAMA). The risk assessment was updated as part of the 2017 Comprehensive Site
Assessment (CSA) Update report (SynTerra, 2017). This update follows the methods of
the 2016 risk assessment (SynTerra, 2016) and is based on U.S. Environmental
Protection Agency (USEPA) risk assessment guidance (USEPA, 1989; 1991; 1998).
Areas of wetness (AOWs), or seeps, are not subject to this risk assessment update.
AOWs associated with engineered structures, also referred to as "constructed seeps,"
have been addressed in a National Pollutant Discharge Elimination System (NPDES)
permit. Under the permit, Duke Energy is required to capture the discharge from the
constructed seeps and pump it back into the basin. Other AOWs (non -constructed
seeps) are now addressed under a Special Order by Consent (SOC) issued by the North
Carolina Environmental Management Commission (EMC SOC WQ 518-005). Many
AOWs are expected to reduce in flow or be eliminated after decanting (i.e., removal of
the free water). The SOC requires that any seeps remaining after decanting must be
addressed with a corrective action plan that must "protect public health, safety, and
welfare, the environment, and natural resources" (EMC SOC WQ 518-005, 2. d.).
This risk assessment update includes results from samples of surface water, sediment,
and groundwater collected since the 2017 CSA update. New information regarding
groundwater flow and the treatment of source areas other than the ash basin has
resulted in refinement of exposure pathways and exposure areas. The Conceptual Site
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Risk Assessment Summary Update November 2018
Mayo Steam Electric Plan SynTerra
Models (CSMs) (Figures 1 and 2) reflect potentially complete exposure pathways with
potential risks, and exposure areas are depicted in Figures 3 and 4. Changes to the
CSMs include:
• Exposure to coal combustion residual (CCR) constituents by Site workers is
considered incomplete, because Duke Energy maintains strict health and safety
requirements and training. The use of personal protective equipment (e.g., boots,
gloves, safety glasses) and other safety behaviors exhibited by Site workers limits
exposure to CCR constituents. Following conservative risk assessment practices,
the initial risk assessment report considered CCR constituent exposure pathways
for Site workers to be potentially complete. Further information has revealed
that on -Site worker exposure pathways are incomplete, and this risk assessment
update has been revised to reflect this change.
• Swimming, boating, and fishing exposures are considered incomplete because
updated modeling and data collection demonstrate that groundwater migration
from the ash basin does not influence Mayo Lake, and observations of
Crutchfield Branch confirms that it is not of sufficient size to support these
recreational uses.
• The number of human exposure areas reduced from three to two (Figure 3), and
the number of ecological exposure areas reduced from four to one (Figure 4).
Other exposure areas evaluated in the 2016 risk assessment were eliminated
because they are not influenced by groundwater flow from the ash basin.
Results from samples of surface water, sediment, and groundwater were compared
with human health and ecological screening values (Attachments 1 and 2) to identify
constituents of potential concern (COPCs) for further review. Exposure point
concentrations (EPCs) were calculated for COPCs (Attachments 3 and 4) to incorporate
into human health and ecological risk models. Results of risk estimates (Attachments 5
and 6) are summarized below.
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Risk Assessment Summary Update November 2018
Mayo Steam Electric Plan SynTerra
2.0 SUMMARY OF RISK FINDINGS
2.1 Human Health
There is no exposure to residential receptors at Mayo because no one lives on -Site or
near enough to the Site to be affected by groundwater migration from the ash basin. A
potential receptor off -Site is a recreational wader in Crutchfield Branch. However,
background concentrations of the same elements also present similar risks to the same
potential receptors. Those risks are not associated with the ash basin.
• There is no material increase in risks associated with the off -Site wader exposure
scenario.
o There is no material increase in cancer risks attributable to the ash basin
for the wader exposure scenario. Incorporating hexavalent chromium
concentrations in surface water samples collected since the 2017 CSA
update produced modeled potential carcinogenic risks under the wader
scenario. However, the modeled risks are not materially greater than the
background level of risk. The hexavalent chromium EPC calculated based
on sampling data for use in the risk assessment was 1.6 µg/L, compared to
the upstream concentration of 0.94 µg/L. Although the EPC was slightly
greater than the background, it does not produce a materially greater
amount of risk in the model. There is, therefore, no material increase in
cancer risks attributable to the ash basin.
o No evidence of non -carcinogenic risks for the recreational wader was
identified.
• There is no increase in risks associated with on -Site exposure scenarios.
o The updated risk assessment found no evidence of risks associated with
exposure to groundwater by Site workers.
o Trespasser exposure was evaluated based on surface water and sediment
samples collected from the shallow on -Site portions of Crutchfield Branch,
which identified hexavalent chromium as a constituent of potential
concern. The hexavalent chromium EPC calculated based upon sampling
data for use in the risk assessment for on -Site surface water was 0.36 µg/L,
compared to the upstream concentration of 0.94 µg/L at sampling location
SW-REF1. There is, therefore, no increase in risks associated with the
trespasser exposure scenario.
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Risk Assessment Summary Update November 2018
Mayo Steam Electric Plan SynTerra
In summary, there is no material increase in risks to human health attributable to the
Mayo ash basin.
2.2 Ecological
There is no evidence of ecological risks associated with the Crutchfield Branch exposure
area.
In practice, ecological risks are quantified by comparing an average daily dose
(ADD) of a constituent to a toxicity reference value (TRV) for a given wildlife
receptor. The ratio of the ADD and TRV is the hazard quotient (HQ), where an
HQ less than unity (1) indicates no evidence of risks. TRVs are generally no -
observed -adverse -effects -levels (NOAEL) or a lowest -observed -adverse -effects -
levels (LOAEL) from toxicity studies published in scientific literature.
• No HQs based on NOAELS or LOAELs exceeded unity for the wildlife receptors
(mallard duck, great blue heron, muskrat, river otter, bald eagle, American robin,
meadow vole, red-tailed hawk, red fox) exposed to surface water and sediments.
In summary, the Mayo ash basin does not cause any increase in risks to ecological
receptors.
Page 4

Risk Assessment Summary Update November 2018
Mayo Steam Electric Plan SynTerra
3.0 REFERENCES
SynTerra. (2016). Corrective Action Plan Part 2 - Mayo Steam Electric Plant, February
2016.
SynTerra. (2017). 2017 Comprehensive Site Assessment Update, October 2017.
United States Environmental Protection Agency. (1989). Risk Assessment Guidance for
Superfund: Volume 1 - Human Health Evaluation Manual (Part A). Office of
Emergency and Remedial Response, Washington, D.C. EPA/540/1-89/002.
United States Environmental Protection Agency. (1991). Risk Assessment Guidance for
Superfund: Volume 1 - Human Health Evaluation Manual (Part B, Development
of Risk -based Preliminary Remediation Goals). Office of Emergency and
Remedial Response, Washington, D.C. EPA/540/R-92/003.
United States Environmental Protection Agency. (1998). Guidelines for Ecological Risk
Assessment. Washington, D.C. EPA/630/R-95/002F.
Page 5

Risk Assessment Summary Update November 2018
Mayo Steam Electric Plan SynTerra
FIGURES

Human Receptors
Primary
Secondary
Potential
Potential
Current/
Current/
Current/
Current/
Current/
Current/
Future Off -Site
Current/
Future On -site
Current/
Primary Secondary
Release
Release
Exposure
Exposure
Future Off -Site
Future On -Site
Future Off -Site
Future Off -Site Future Off -Site
Recreational /
Commercial/Construction
Future On -Site
Sources Sources
Mechanisms
Mechanisms
Media
Route
Resident
Recreational
Recreational
Recreational Recreational
Subsistence
Industrial
Adult/Child
Trespasser
Swimmer
Wader
Boater
Fisher
Worker
Worker
Dust
Outdoor Air
\
Incidental
Active Coal Ash
Infiltration/ Post Excavation
Soil Remaining
Ingestion
O
O
O
O
O
O
O
O
Basin
Leaching Soil
lo Post -Excavation
\
Dermal Contact
O
O
O
O
O
O
O
O
Runoff/Flooding
i
Drinking Water
O
O
O
O
O
O
O
O
(e
Surface Water
Incidental
(Off -site)
Ingestion
O
49
O
49(d)
O
O
O
O
\
Dermal Contact
O
O
O
•
O
O
O
O
Infiltration/
Mi ration to
9
;
Leaching
�
Surface Water
�
and Sediment
Incidental
Sediment
Ingestion
O
O
O
O
O
O
O
O
(Off -site)
Dermal Contact
O
O
O
O
O
O
O
O
i
Fish Tissue
Groundwater
Drinking Water
O
O
O
O
O
O
O
O
Use
Groundwater
Incidental1111.
O
O
O
O
O
O
O
O(e)
Ingestion
Dermal Contact
O
O
O
O
O
O
O
O(e)
AOW Water
Dermal Contact
O
O
O
O
O
O
O
O
(On -site)
AOWs (a)
�_
AOW Soil
Dermal Contact
O
O
O
O
O
O
O
O
NOTE
S
(On -site)
Potentially complete exposure pathway based on results of 2018 risk assessment
Incidental
update.
Surface Water
Ingestion
O
O
O
O
O
O
O
O
O
Pathway evaluated and found incomplete/insignificant.
(On -site)
(a)
Areas of wetness (AOWs) are addressed inthe SpecialOrder by Consent(SOC)and not
Dermal Contact
O
O
O
O
O
O
O
O
evaluated in the risk assessment update at this time.
(b)
Pathway incomplete as longas ash remainsin place; re-evaluation upon excavation (if
conducted) maybe warranted.
Incidental
O
O
O
O
O
O
O
O
(�)
Concentration of COPC in fish tissue modeled from surface water concentration.
Sediment
Ingestion
(On -site)
(d)
Incidental surfacewater ingestion assumed only to occurfor receptors for the wading
scenario.
Dermal Contact
O
O
O
O
O
O
O
O
(e)
Groundwater exposure evaluated inthe risk assessment update, although an incomplete
exposure pathway for construction worker.
FIGURE 1
41P
HUMAN HEALTH RISK ASSESSMENT
CONCEPTUAL
SITE MODEL
synTerlyd
MAYO STEAM ELECTRIC PLANT
ROXBORO, NORTH CAROLINA
Inhalation O O O O O O O O
Ingestion O O O O O O O O

Primary Sources Primary Release Secondary
Mechanisms Sources
Active Coal
Ash Basin Infiltration/ � Post Excavation
Leaching Soil
Runoff/Flooding
Infiltration/
Leaching
Groundwater
AOWs (a)
AQUATIC RECEPTORS
TERRESTRIAL RECEPTORS (e)
Avian (e)
Mammal
Avian
Mammal
Secondary Release Potential Potential
Mechanisms Exposure Media Exposure Route
Fish
Benthic
Invertebrates
Mallard
(Omnivore)
Great Blue
Heron
p
(scivore)
Muskrat
(Herbivore)
River Otter
(Piscivore)
Robin
(Omnivore)
Red -Tailed
awk
(Carnivore) vore)
Meadow Vole
(Herbivore)
Red Fox
(Carnivore)
Dust Outdoor Air
NOTES
Potentially complete exposure pathways based on results o 2018 risk assessment
u pdate.
O Pathway evaluated and found incomplete/insignificant.
(a) Areas of wetness (AOWs) are addressed in the Special Order by Consent (SOC) and not
evaluated in the risk assessment update at this time.
(b) Pathway incomplete as long as ash remains in place; re-evaluation upon excavation (if
conducted) may be warranted.
(c) Concentration of COPC in fish tissue modeled from surface water concentration.
(d) Based on screening against aquatic life criteria.
(e) Bald eagle (carnivore) included in the ecological risk assessment.
Groundwater
AOW Water
(On -site)
AOW Soil
(On -site)
Surface Water
(On -site)
Sed invent
(On -site)
Inhalation O O O O O O O O O O
Ingestion O O O O O O
Direct Contact O O O O O O
Ingestion O O O O O O 11 O O O O
1
Plant/Incidental
O
O
O
O
O
O
O
O
O
O
1 ngestio n
Ingestion
•(d)
0(d)
O
O
O
O
O
O
O
O
Direct Contact
O
O
O
O
O
O
O
O
O
O
Plant/Incidental
Ingestion
O
O
O
O
O
O
O
O
O
O
Direct Contact
O
•(d)
O
O
O
O
O
O
O
O
synTerra
FIGURE 2
ECOLOGICAL RISK ASSESSMENT
CONCEPTUAL SITE MODEL
MAYO STEAM ELECTRIC PLANT
ROXBORO, NORTH CAROLINA

Risk Assessment Summary Update November 2018
Mayo Steam Electric Plan SynTerra
ATTACHMENTS

TABLE 1-1
HUMAN HEALTH SCREENING - GROUNDWATER (SURFICIAL)
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Analyte
CAS
Number of
Samples
Frequency of
Detection
Range of Detection
(N9/L)
Concentration
Used for
Screening
(Ng/L)
15A NCAC 02L
.0202 Standard
(e)
(Ng/L)
15A NCAC
02L .0202
IMAC (e)
(Ng/L)
DHHS
Screening
Level (d)
(Ng/L)
Federal MCL/
SMCL (c)
(N9/L)
Tap Water RSL
HI = 0.2 (a)
(N9/L)
Screening
Value Used
(N9/L)
COPC?
Min.
I Max.
Aluminum
7429-90-5
32
28
6
158
158
NA
NA
3,500
50 to 200 (i)
4,000
3,500
N
Antimony
7440-36-0
72
1
2
2
2
1
NA
1
6
1.56 (m)
1
Y
Arsenic
7440-38-2
72
11
0.4
2.44
2.44
10
NA
10
10
0.052 (h,jj)
10
N
Barium
7440-39-3
72
72
20
137
137
700
NA
700
2,000
760
700
N
Beryllium
7440-41-7
72
1
0.502
0.502
0.502
NA
4
4
4
5
4
N
Boron
7440-42-8
72
68
122
1,330
1,330
700
NA
700
NA
800
700
Y
Cadmium
7440-43-9
72
1
0.092
0.092
0.092
2
NA
2
5
1.84
2
N
Chromium (Total)
7440-47-3
72
16
0.54
43
43
10
NA
10
100
4,400 (n)
10
Y
Chromium (VI)
18540-29-9
24
12
0.028
0.62
0.62
NA
NA
0.07
NA
0.035 0j)
0.07
Y
Cobalt
7440-48-4
68
44
1.07
10.3
10.3
NA
1
1
NA
1.2
1
Y
Copper
7440-50-8
36
5
0.338
1.32
1.32
1,000
NA
1,000
1,300 (k)
160
1,000
N
Lead
7439-92-1
72
2
0.22
1
1
15
NA
15
15 (1)
15 0j)
15
N
Lithium
7439-93-2
42
0
ND
ND
ND
NA
NA
NA
NA
8
8
N
Manganese
7439-96-5
36
36
6
1,530
1,530
50
NA
200
50 (i)
86
50
Y
Mercury
7439-97-6
72
3
0.06
0.12
0.12
1
NA
1
2
1.14 (o)
1
N
Molybdenum
7439-98-7
68
23
0.108
6.12
6.12
NA
NA
18
NA
20
18
N
Nickel
7440-02-0
36
26
0.627
4
4
100
NA
100
NA
78 (p)
100
N
Selenium
7782-49-2
72
1
1.6
1.6
1.6
20
NA
20
50
20
20
N
Strontium
7440-24-6
32
32
55
342
342
NA
NA
2,100
NA
2,400
2,100
N
Thallium
7440-28-0
72
0
ND
ND
ND
0.2
NA
0.2
2
0.04 (q)
0.2
N
Vanadium
7440-62-2
32
13
0.175
0.711
0.711
NA
NA
0.3
NA
17.2
0.3
Y
Zinc
7440-66-6
36
18
2.738
39
39
1
NA
1
5,000 (i)
1,200
1
Y
* Data evaluated includes data from 2015 to 2nd quarter 2018, unless otherwise noted
Notes:
AWQC - Ambient Water Quality Criteria
DENR - Department of Environment and Natural Resources
CAMA - Coal Ash Management Act
DHHS - Department of Health and Human Services
North Carolina Session Law 2014-122,
ESV - Ecological Screening Value
htto://www.nclea.net/Sessions/2013/Bills
HH - Human Health
/Senate/PDF/S729v7.pdf
HI- Hazard Index
CAS - Chemical Abstracts Service
IMAC - Interim Maximum Allowable Concentration
CCC - Criterion Continuous Concentration
MCL - Maximum Contaminant Level
CMC - Criterion Maximum Concentration
mg/kg - milligrams/kilogram
COPC - Constituent of Potential Concern
NA - Not Available
NC - North Carolina
NCAC
- North Carolina Administrative Code
ORNL
- Oak Ridge National Laboratory
PSRG
- Preliminary Soil Remediation Goal
Q - Qualifier
RSL -
Regional Screening Level
RSV -
Refinement Screening Value
SMCL
- Secondary Maximum Contaminant Level
SSL -
Soil Screening Level
Prepared by: HEG Checked by: HES
su - Standard units
Ng/L - micrograms/liter
USEPA - United States Environmental Protection Agency
WS - Water Supply
< - Concentration not detected at or above the reporting limit
j - Indicates concentration reported below Practical Quantitation Limit
(PQL) but above Method Detection Limit (MDL) and therefore concentration is estimated
Page 1 of 2

TABLE 1-1
HUMAN HEALTH SCREENING - GROUNDWATER (SURFICIAL)
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
(a) - USEPA Regional Screening Levels (May 2018). Values for Residential Soil, Industrial Soil, and Tap Water. HI = 0.2. Accessed October 2018.
https: //www. epa. gov/risk/regiona I -screen i ng-levels-rsls-generic-tables
(b) - USEPA National Recommended Water Quality Criteria. USEPA Office of Water and Office of Science and Technology. Accessed October 2018.
https: //www. epa. gov/wqc/national-recom mended-water-qual ity-criteria-hu man -health -criteria -table
USEPA AWQC Human Health for the Consumption of Organism Only apply to total concentrations.
(c) - USEPA 2018 Edition of the Drinking Water Standards and Health Advisories. March 2018. Accessed October 2018.
https: //www. epa. gov/sites/production/files/2018-03/documents/dwta ble20l8. pdf
(d) - DHHS Screening Levels. Department of Health and Human Services, Division of Public Health, Epidemiology Section, Occupational and Environmental
Epidemiology Branch. http://portal.ncdenr.org/c/document_library/get _file?p_I_id=1169848&folderld=24814087&name=DLFE-112704.pdf
(e) - North Carolina 15A NCAC 02L .0202 Groundwater Standards & IMACs. http://portal.ncdenr.org/c/document_library/get_file?uuid=laa3fal3-2cOf-45b7-ae96-5427fbld25b4&groupId=38364
Amended April 2013.
(f) - North Carolina 15A NCAC 02B Surface Water and Wetland Standards. Amended January 1, 2015.
http: //reports. oa h. state. nc. us/ncac/title%2015a%20-%20environmental%20q ua lity/chapter%2002%20-%20envi ron menta I%20management/subchapter%20b/su bchapter%20b%20rules. pdf
WS standards are applicable to all Water Supply Classifications. WS standards are based on the consumption of fish and water.
Human Health Standards are based on the consumption of fish only unless dermal contact studies are available.
For Class C, use the most stringent of freshwater (or, if applicable, saltwater) column and the Human Health column.
For a WS water, use the most stringent of Freshwater, WS and Human Health. Likewise, Trout Waters and High Quality Waters must adhere to the most stingent of all applicable standards.
(g) - USEPA Region 4. 2018. Region 4 Ecological Risk Assessment Supplemental Guidance. March 2018 Update.
https: //www. epa. gov/sites/production/files/2018-03/documents/era_regiona I_supplemental_gu idance_report-march-2018_u pdate. pdf
(h) - Value applies to inorganic form of arsenic only.
(i) - Value is the Secondary Maximum Contaminant Level.
https: //www. epa. gov/dwsta ndardsreg ulations/secondary-d ri nking-water-standards-guidance-nuisance-chem ica Is
(j) - Value for Total Chromium.
(k) - Copper Treatment Technology Action Level is 1.3 mg/L.
(1) - Lead Treatment Technology Action Level is 0.015 mg/L.
(m) - RSL for Antimony (metallic) used for Antimony.
(n) - Value for Chromium (III), Insoluble Salts used for Chromium.
(o) - RSL for Mercuric Chloride used for Mercury.
(p) - RSL for Nickel Soluble Salts used for Nickel.
(q) - RSL for Thallium (Soluble Salts) used for Thallium.
(r) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(s) - Value for Inorganic Mercury.
(t) - Acute AWQC is equal to 1/[(fl/CMCl) + (f2/CMC2)] where fl and f2 are the fractions of total selenium that are treated as selenite and selenate, respectively, and
CMC1 and CMC2 are 185.9 p/gL and 12.82 p/gL, respectively. Calculated assuming that all selenium is present as selenate, a likely overly conservative assumption.
(u) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(v) - Chloride Action Level for Toxic Substances Applicable to NPDES Permits is 230,000 p/gL.
(w) - Applicable only to persons with a sodium restrictive diet.
(x) - Los Alamos National Laboratory ECORISK Database. http://www.Ian1.gov/community-environment/environmental-stewardship/protection/eco-risk-assessment.php
(y) - Long, Edward R., and Lee G. Morgan. 1991. The Potential for Biological Effects of Sediment -Sorted Contaminants Tested in the National Status and Trends Program.
NOAA Technical Memorandum NOS OMA 52. Used effects range low (ER-L) for chronic and effects range medium (ER-M) for acute.
(z) - MacDonald, D.D.; Ingersoll, C.G.; Smorong, D.E.; Lindskoog, R.A.; Sloane, G.; and T. Bernacki. 2003. Development and Evaluation of Numerical Sediment Quality Assessment Guidelines for
Florida Inland Waters. Florida Department of Environmental Protection, Tallahassee, FL. Used threshold effect concentration (TEC) for the ESV and probable effect concentration (PEC) for the RSV.
(aa) - Persaud, D., R. Jaagumagi and A. Hayton. 1993. Guidelines for the protection and management of aquatic sediment quality in Ontario. Ontario Ministry of the Environment. Queen's Printer of Ontario.
(bb) - Los Alamos National Laboratory ECORISK Database. September 2017. http://www.lani.gov/environment/protection/eco-risk-assessment.php (pg/kg dw)
(cc) - Great Lakes Initiative (GLI) Clearinghouse resources Tier II criteria revised 2013. http://www.epa.gov/gliclearinghouse/
(dd) - Suter, G.W., and Tsao, C.L. 1996. Toxicological Benchmarks for Screening Potential Contaminants of Concern for Effects on Aquatic Biota: 1996 Revision. ES/ER/TM-96/R2.
http://www.esd.omi.gov/programs/ecorisk/documents/tm96r2.pdf
(ee) - USEPA. Interim Ecological Soil Screening Level Documents. Accessed October 2018. http://www2.epa.gov/chemical-research/interim-ecological-soil-screening-level-documents
(ff) - Efroymson, R.A., M.E. Will, and G.W. Suter II, 1997a. Toxicological Benchmarks for Contaminants of Potential Concern for Effects on Soil and Litter Invertebrates and Heterotrophic Process:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-126/R2. (Available at http://www.esd.orni.gov/programs/ecorisk/documents/tml26r2l.pdf)
(gg) - Efroymson, R.A., M.E. Will, G.W. Suter II, and A.C. Wooten, 1997b. Toxicological Benchmarks for Screening Contaminants of Potential Concern for Effects on Terrestrial Plants:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-85/R3. (Available at http://www.esd.orni.gov/programs/ecorisk/documents/tm85r3.pdf)
(hh) - North Carolina Preliminary Soil Remediation Goals (PSRG) Table. HI = 0.2. September 2015. http://portal.ncdenr.org/c/document_ library/get_file?uuid=Of60lffa-574d-4479-bbb4-253af0665bf5&groupId=38361
(ii) - As part of the water quality evaluation conducted under the CSA, pH was measured and is reported as a metric data set. The pH comparison criteria are included as ranges as opposed to single screening values. pH is not typically included
as part of a risk assessment based on potential toxic effects, therefore; pH was not investigated further as a category 1 COPC. Water quality relative to pH will be addressed as a component of water quality monitoring programs for the site.
(jj) - Hazard Index = 0.1
Page 2 of 2

TABLE 1-2
HUMAN HEALTH SCREENING - GROUNDWATER (TRANSITION/BEDROCK)
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Analyte
CAS
Number of
Samples
Frequency of
Detection
Range of Detection
(N9/L)
Concentration
Used for
Screening
(Ng/L)
15A NCAC 02L
.0202 Standard
(e)
(Ng/L)
15A NCAC
02L .0202
IMAC (e)
(Ng/L)
DHHS
Screening
Level (d)
(Ng/L)
Federal MCL/
SMCL (c)
(N9/L)
Tap Water RSL
HI = 0.2 (a)
(N9/L)
Screening
Value Used
(N9/L)
COPC?
Min.
Max.
Aluminum
7429-90-5
390
357
4.845
2,110
2,110
NA
NA
3,500
50 to 200 (i)
4,000
3,500
N
Antimony
7440-36-0
479
8
0.13
3.68
3.68
1
NA
1
6
1.56 (m)
1
Y
Arsenic
7440-38-2
479
62
0.28
143
143
10
NA
10
10
0.052 (h,jj)
10
Y
Barium
7440-39-3
479
416
1.845
1,080
1,080
700
NA
700
2,000
760
700
Y
Beryllium
7440-41-7
375
0
ND
ND
ND
NA
4
4
4
5
4
N
Boron
7440-42-8
479
127
3
5,090
5,090
700
NA
700
NA
800
700
Y
Cadmium
7440-43-9
479
20
0.037
2.19
2.19
2
NA
2
5
1.84
2
Y
Chromium (Total)
7440-47-3
479
47
0.383
53
53
10
NA
10
100
4,400 (n)
10
Y
Chromium (VI)
18540-29-9
174
89
0.025
3.7
3.7
NA
NA
0.07
NA
0.035 0j)
0.07
Y
Cobalt
7440-48-4
367
58
0.404
6.71
6.71
NA
1
1
NA
1.2
1
Y
Copper
7440-50-8
398
58
0.508
184
184
1,000
NA
1,000
1,300 (k)
160
1,000
N
Lead
7439-92-1
479
11
0.1
11
11
15
NA
15
15 (1)
15 0j)
15
N
Lithium
7439-93-2
125
45
1.672
24
24
NA
NA
NA
NA
8
8
Y
Manganese
7439-96-5
398
370
5
6,960
6,960
50
NA
200
50 (i)
86
50
Y
Mercury
7439-97-6
479
24
0.06
0.66
0.66
1
NA
1
2
1.14 (o)
1
N
Molybdenum
7439-98-7
367
223
0.358
269
269
NA
NA
18
NA
20
18
Y
Nickel
7440-02-0
398
75
0.38
56
56
100
NA
100
NA
78 (p)
100
N
Selenium
7782-49-2
479
10
0.395
150
150
20
NA
20
50
20
20
Y
Strontium
7440-24-6
270
270
57
3,070
3,070
NA
NA
2,100
NA
2,400
2,100
Y
Thallium
7440-28-0
479
7
0.012
0.361
0.361
0.2
NA
0.2
2
0.04 (q)
0.2
Y
Vanadium
7440-62-2
278
188
0.134
23.3
23.3
NA
NA
0.3
NA
17.2
0.3
Y
Zinc
7440-66-6
398
137
1.973
110
110
1
NA
1
5,000 (i)
1,200
1
Y
* Data evaluated includes data from 2015 to 2nd quarter 2018, unless otherwise noted
Notes:
AWQC - Ambient Water Quality Criteria
DENR - Department of Environment and Natural Resources
CAMA - Coal Ash Management Act
DHHS - Department of Health and Human Services
North Carolina Session Law 2014-122,
ESV - Ecological Screening Value
htto://www.nclea.net/Sessions/2013/Bills
HH - Human Health
/Senate/PDF/S729v7.pdf
HI- Hazard Index
CAS - Chemical Abstracts Service
IMAC - Interim Maximum Allowable Concentration
CCC - Criterion Continuous Concentration
MCL - Maximum Contaminant Level
CMC - Criterion Maximum Concentration
mg/kg - milligrams/kilogram
COPC - Constituent of Potential Concern
NA - Not Available
NC - North Carolina
NCAC
- North Carolina Administrative Code
ORNL
- Oak Ridge National Laboratory
PSRG
- Preliminary Soil Remediation Goal
Q - Qualifier
RSL -
Regional Screening Level
RSV -
Refinement Screening Value
SMCL
- Secondary Maximum Contaminant Level
SSL -
Soil Screening Level
Prepared by: HEG Checked by: HES
su - Standard units
Ng/L - micrograms/liter
USEPA - United States Environmental Protection Agency
WS - Water Supply
< - Concentration not detected at or above the reporting limit
j - Indicates concentration reported below Practical Quantitation Limit
(PQL) but above Method Detection Limit (MDL) and therefore concentration is estimated
Page 1 of 2

TABLE 1-2
HUMAN HEALTH SCREENING - GROUNDWATER (TRANSITION/BEDROCK)
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
(a) - USEPA Regional Screening Levels (May 2018). Values for Residential Soil, Industrial Soil, and Tap Water. HI = 0.2. Accessed October 2018.
https: //www. epa. gov/risk/regiona I -screen i ng-levels-rsls-generic-tables
(b) - USEPA National Recommended Water Quality Criteria. USEPA Office of Water and Office of Science and Technology. Accessed October 2018.
https: //www. epa. gov/wqc/national-recom mended-water-qual ity-criteria-hu man -health -criteria -table
USEPA AWQC Human Health for the Consumption of Organism Only apply to total concentrations.
(c) - USEPA 2018 Edition of the Drinking Water Standards and Health Advisories. March 2018. Accessed October 2018.
https: //www. epa. gov/sites/production/files/2018-03/documents/dwta ble20l8. pdf
(d) - DHHS Screening Levels. Department of Health and Human Services, Division of Public Health, Epidemiology Section, Occupational and Environmental
Epidemiology Branch. http://portal.ncdenr.org/c/document_library/get _file?p_I_id=1169848&folderld=24814087&name=DLFE-112704.pdf
(e) - North Carolina 15A NCAC 02L .0202 Groundwater Standards & IMACs. http://portal.ncdenr.org/c/document_library/get_file?uuid=laa3fal3-2cOf-45b7-ae96-5427fbld25b4&groupId=38364
Amended April 2013.
(f) - North Carolina 15A NCAC 02B Surface Water and Wetland Standards. Amended January 1, 2015.
http: //reports. oa h. state. nc. us/ncac/title%2015a%20-%20environmental%20q ua lity/chapter%2002%20-%20envi ron menta I%20management/subchapter%20b/su bchapter%20b%20rules. pdf
WS standards are applicable to all Water Supply Classifications. WS standards are based on the consumption of fish and water.
Human Health Standards are based on the consumption of fish only unless dermal contact studies are available.
For Class C, use the most stringent of freshwater (or, if applicable, saltwater) column and the Human Health column.
For a WS water, use the most stringent of Freshwater, WS and Human Health. Likewise, Trout Waters and High Quality Waters must adhere to the most stingent of all applicable standards.
(g) - USEPA Region 4. 2018. Region 4 Ecological Risk Assessment Supplemental Guidance. March 2018 Update.
https: //www. epa. gov/sites/production/files/2018-03/documents/era_regiona I_supplemental_gu idance_report-march-2018_u pdate. pdf
(h) - Value applies to inorganic form of arsenic only.
(i) - Value is the Secondary Maximum Contaminant Level.
https: //www. epa. gov/dwsta ndardsreg ulations/secondary-d ri nking-water-standards-guidance-nuisance-chem ica Is
(j) - Value for Total Chromium.
(k) - Copper Treatment Technology Action Level is 1.3 mg/L.
(1) - Lead Treatment Technology Action Level is 0.015 mg/L.
(m) - RSL for Antimony (metallic) used for Antimony.
(n) - Value for Chromium (III), Insoluble Salts used for Chromium.
(o) - RSL for Mercuric Chloride used for Mercury.
(p) - RSL for Nickel Soluble Salts used for Nickel.
(q) - RSL for Thallium (Soluble Salts) used for Thallium.
(r) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(s) - Value for Inorganic Mercury.
(t) - Acute AWQC is equal to 1/[(fl/CMCl) + (f2/CMC2)] where fl and f2 are the fractions of total selenium that are treated as selenite and selenate, respectively, and
CMC1 and CMC2 are 185.9 p/gL and 12.82 p/gL, respectively. Calculated assuming that all selenium is present as selenate, a likely overly conservative assumption.
(u) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(v) - Chloride Action Level for Toxic Substances Applicable to NPDES Permits is 230,000 p/gL.
(w) - Applicable only to persons with a sodium restrictive diet.
(x) - Los Alamos National Laboratory ECORISK Database. http://www.Ian1.gov/community-environment/environmental-stewardship/protection/eco-risk-assessment.php
(y) - Long, Edward R., and Lee G. Morgan. 1991. The Potential for Biological Effects of Sediment -Sorted Contaminants Tested in the National Status and Trends Program.
NOAA Technical Memorandum NOS OMA 52. Used effects range low (ER-L) for chronic and effects range medium (ER-M) for acute.
(z) - MacDonald, D.D.; Ingersoll, C.G.; Smorong, D.E.; Lindskoog, R.A.; Sloane, G.; and T. Bernacki. 2003. Development and Evaluation of Numerical Sediment Quality Assessment Guidelines for
Florida Inland Waters. Florida Department of Environmental Protection, Tallahassee, FL. Used threshold effect concentration (TEC) for the ESV and probable effect concentration (PEC) for the RSV.
(aa) - Persaud, D., R. Jaagumagi and A. Hayton. 1993. Guidelines for the protection and management of aquatic sediment quality in Ontario. Ontario Ministry of the Environment. Queen's Printer of Ontario.
(bb) - Los Alamos National Laboratory ECORISK Database. September 2017. http://www.lani.gov/environment/protection/eco-risk-assessment.php (pg/kg dw)
(cc) - Great Lakes Initiative (GLI) Clearinghouse resources Tier II criteria revised 2013. http://www.epa.gov/gliclearinghouse/
(dd) - Suter, G.W., and Tsao, C.L. 1996. Toxicological Benchmarks for Screening Potential Contaminants of Concern for Effects on Aquatic Biota: 1996 Revision. ES/ER/TM-96/R2.
http://www.esd.omi.gov/programs/ecorisk/documents/tm96r2.pdf
(ee) - USEPA. Interim Ecological Soil Screening Level Documents. Accessed October 2018. http://www2.epa.gov/chemical-research/interim-ecological-soil-screening-level-documents
(ff) - Efroymson, R.A., M.E. Will, and G.W. Suter II, 1997a. Toxicological Benchmarks for Contaminants of Potential Concern for Effects on Soil and Litter Invertebrates and Heterotrophic Process:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-126/R2. (Available at http://www.esd.orni.gov/programs/ecorisk/documents/tml26r2l.pdf)
(gg) - Efroymson, R.A., M.E. Will, G.W. Suter II, and A.C. Wooten, 1997b. Toxicological Benchmarks for Screening Contaminants of Potential Concern for Effects on Terrestrial Plants:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-85/R3. (Available at http://www.esd.orni.gov/programs/ecorisk/documents/tm85r3.pdf)
(hh) - North Carolina Preliminary Soil Remediation Goals (PSRG) Table. HI = 0.2. September 2015. http://portal.ncdenr.org/c/document_ library/get_file?uuid=Of60lffa-574d-4479-bbb4-253af0665bf5&groupId=38361
(ii) - As part of the water quality evaluation conducted under the CSA, pH was measured and is reported as a metric data set. The pH comparison criteria are included as ranges as opposed to single screening values. pH is not typically included
as part of a risk assessment based on potential toxic effects, therefore; pH was not investigated further as a category 1 COPC. Water quality relative to pH will be addressed as a component of water quality monitoring programs for the site.
(jj) - Hazard Index = 0.1
Page 2 of 2

TABLE 1-3
HUMAN HEALTH SCREENING - OFFSITE SEDIMENT
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Analyte
CAS
Number
of
Samples
Frequency
of
Detection
Range of Detection
(mg/kg)
Concentration
Used for
Screening
(mg/kg)
NC PSRG
Residential Health
Screening Level
(hh)
(mg/kg)
Residential Soil
RSL (a)
HI = 0.2
(mg/kg)
NC PSRG
Industrial Health
Screening Level
(hh)
(mg/kg)
Industrial Soil
RSL (a)
HI = 0.2
(mg/kg)
Residential
Screening
Value Used
(mg/kg)
Industrial
Screening
Value Used
(mg/kg)
Residential
COPC?
Industrial
COPC?
Min.
TMax.
Aluminum
7429-90-5
3
3
2,300
7,350
7,350
15,000
15,400
100,000
220,000
15,000
100,000
N
N
Antimony
7440-36-0
3
0
ND
ND
ND
6.2 (m)
6.2 (m)
94 (m)
94 (m)
6.2
94
N
N
Arsenic
7440-38-2
3
1
0.28
0.28
0.28
0.68 (h)
0.68 (h,jj)
3 (h)
3 (h,jj)
0.68
3
N
N
Barium
7440-39-3
3
3
18
98.2
98.2
3,000
3,000
44,000
44,000
3,000
44,000
N
N
Beryllium
7440-41-7
3
3
0.11
0.29
0.29
32
32
460
460
32
460
N
N
Boron
7440-42-8
3
0
ND
ND
ND
3,200
3,200
46,000
46,000
3,200
46,000
N
N
Cadmium
7440-43-9
3
0
ND
ND
ND
14
14.2
200
196
14
200
N
N
Chromium (Total)
7440-47-3
3
3
4.8
13.9
13.9
24,000 (r)
24,000 (n)
100,000 (n)
360,000 (n)
24,000
100,000
N
N
Cobalt
7440-48-4
3
3
1.5
6.1
6.1
4.6
4.6
70
70
4.6
70
Y
N
Copper
7440-50-8
3
3
1.7
9.5
9.5
620
620
9,400
9,400
620
9,400
N
N
Lead
7439-92-1
3
3
1.9
7.4
7.4
400
400 UD
800
800 (jj)
400
800
N
N
Manganese
7439-96-5
3
3
120
480
480
360
360
5,200
5,200
360
5,200
Y
N
Mercury
7439-97-6
3
1
0.027
0.027
0.027
4.6 (0)
4.6 (0)
3.1 (0)
70 (0)
4.6
3.1
N
N
Molybdenum
7439-98-7
3
0
ND
ND
ND
78
78
1,200
1,160
78
1,200
N
N
Nickel
7440-02-0
3
3
1.1
5
5
300 (p)
300 (p)
4,400 (p)
4,400 (p)
300
4,400
N
N
Selenium
7782-49-2
3
0
ND
ND
ND
78
78
1,200
1,160
78
1,200
N
N
Strontium
7440-24-6
3
3
5.3
16.3
16.3
9,400
9,400
100,000
140,000
9,400
100,000
N
N
Thallium
7440-28-0
3
0
ND
ND
ND
0.16 (q)
0.156 (q)
2.4 (q)
2.4 (q)
0.16
2.4
N
N
Vanadium
7440-62-2
3
3
6.2
19.2
19.2
78
78
1,160
1,160
78
1,160
N
N
Zinc
7440-66-6
3
3
7.3
31.4
31.4
4,600
4,600
70,000
70,000
4,600
70,000
N
N
* Data evaluated includes data from 2015 to 2nd quarter
2018, unless otherwise noted
Notes:
AWQC - Ambient Water Quality Criteria
DENR - Department of Environment and Natural Resources
NC - North Carolina
CAMA - Coal Ash Management Act
DHHS - Department of Health and Human Services
NCAC - North Carolina Administrative Code
North Carolina Session Law 2014-122,
ESV - Ecological Screening Value
ORNL - Oak Ridge National Laboratory
htto://www.ncleci.net/Sessions/2013/Bills
HH - Human HealtH
PSRG - Preliminary Soil Remediation Goal
/Senate/PDF/S729v7.pdf
HI - Hazard Index
Q - Qualifier
CAS - Chemical Abstracts Service
IMAC - Interim Maximum Allowable Concentration
RSL - Regional Screening Level
CCC - Criterion Continuous Concentration
MCL - Maximum Contaminant Level
RSV - Refinement Screening Value
CMC - Criterion Maximum Concentration
mg/kg - milligrams/kilogram
SMCL - Secondary Maximum Contaminant Level
COPC - Constituent of Potential Concern
NA - Not Available
SSL - Soil Screening Level
(a) - USEPA Regional Screening Levels (May 2018). Values for Residential Soil, Industrial Soil, and Tap Water. HI = 0.2. Accessed October 2018
https://www.epa.gov/risk/reg ional-screen i ng-levels-rsls-generic-tables
(b) - USEPA National Recommended Water Quality Criteria. USEPA Office of Water and Office of Science and Technology. Accessed October 2018.
https://www.epa.gov/wqc/national-reco mmended-water-qual ity-criteria-h u man -health -criteria -table
USEPA AWQC Human Health for the Consumption of Organism Only apply to total concentrations.
(c) - USEPA 2018 Edition of the Drinking Water Standards and Health Advisories. March 2018. Accessed October 2018.
https://www.epa.gov/sites/production/files/2018-03/documents/dwtable2018. pdf
(d) - DHHS Screening Levels. Department of Health and Human Services, Division of Public Health, Epidemiology Section, Occupational and Environmental
Epidemiology Branch. http://portal.ncdenr.org/c/document_library/get_file?p_I_id=1169848&folderld=24814087&name=DLFE-112704.pdf
su - Standard units
pg/L - micrograms/liter
USEPA - United States Environmental Protection Agency
WS - Water Supply
< - Concentration not detected at or above the reporting limit
j - Indicates concentration reported below Practical Quantitation Limit
(PQL) but above Method Detection Limit (MDL) and therefore concentration is estimated
Prepared by: HEG Checked by: HES
Page 1 of 2

TABLE 1-3
HUMAN HEALTH SCREENING - OFFSITE SEDIMENT
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
(e) - North Carolina 15A NCAC 02L .0202 Groundwater Standards & IMACs. http://portal.ncdenr.org/c/document_library/get_file?uuid=laa3fal3-2cOf-45b7-ae96-5427fbld25b4&groupId=38364
Amended April 2013.
(f) - North Carolina 15A NCAC 02B Surface Water and Wetland Standards. Amended January 1, 2015.
http://reports.oah.state.nc.us/ncac/title % 2015a % 20- % 20environmental % 20quality/chapter % 2002 % 20- % 20environmental % 20management/subchapter % 20b/subchapter % 206 % 20rules.pdf
WS standards are applicable to all Water Supply Classifications. WS standards are based on the consumption offish and water.
Human Health Standards are based on the consumption of fish only unless dermal contact studies are available.
For Class C, use the most stringent of freshwater (or, if applicable, saltwater) column and the Human Health column.
For a WS water, use the most stringent of Freshwater, WS and Human Health. Likewise, Trout Waters and High Quality Waters must adhere to the most stingent of all applicable standards.
(g) - USEPA Region 4. 2018. Region 4 Ecological Risk Assessment Supplemental Guidance. March 2018 Update.
https://www.epa.gov/sites/prod uction/fi les/2018-03/docu ments/era_reg ional_su pplemental_gu idance_report-march-2018_u pdate. pdf
(h) - Value applies to inorganic form of arsenic only.
(i) - Value is the Secondary Maximum Contaminant Level.
https://www.epa.gov/dwstandardsregu lations/secondary-d ri n ki ng-water-standards-g u idance-n u isance-chemicals
(j) - Value for Total Chromium.
(k) - Copper Treatment Technology Action Level is 1.3 mg/L.
(1) - Lead Treatment Technology Action Level is 0.015 mg/L.
(m) - RSL for Antimony (metallic) used for Antimony.
(n) - Value for Chromium (III), Insoluble Salts used for Chromium.
(o) - RSL for Mercuric Chloride used for Mercury.
(p) - RSL for Nickel Soluble Salts used for Nickel.
(q) - RSL for Thallium (Soluble Salts) used for Thallium.
(r) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(s) - Value for Inorganic Mercury.
(t) - Acute AWQC is equal to 1/[(fl/CMCl) + (f2/CMC2)] where fl and f2 are the fractions of total selenium that are treated as selenite and selenate, respectively, and
CMCl and CMC2 are 185.9 pg/L and 12.82 pg/L, respectively. Calculated assuming that all selenium is present as selenate, a likely overly conservative assumption.
(u) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(v) - Chloride Action Level for Toxic Substances Applicable to NPDES Permits is 230,000 pg/L.
(w) - Applicable only to persons with a sodium restrictive diet.
(x) - Los Alamos National Laboratory ECORISK Database. http://www.IanI.gov/community-environment/environmental-stewardship/protection/eco-risk-assessment.php
(y) - Long, Edward R., and Lee G. Morgan. 1991. The Potential for Biological Effects of Sediment-Sorbed Contaminants Tested in the National Status and Trends Program.
NOAA Technical Memorandum NOS OMA 52. Used effects range low (ER-L) for chronic and effects range medium (ER-M) for acute.
(z) - MacDonald, D.D.; Ingersoll, C.G.; Smorong, D.E.; Lindskoog, R.A.; Sloane, G.; and T. Bernacki. 2003. Development and Evaluation of Numerical Sediment Quality Assessment Guidelines for
Florida Inland Waters. Florida Department of Environmental Protection, Tallahassee, FL. Used threshold effect concentration (TEC) for the ESV and probable effect concentration (PEC) for the RSV.
(aa) - Persaud, D., R. Jaagumagi and A. Hayton. 1993. Guidelines for the protection and management of aquatic sediment quality in Ontario. Ontario Ministry of the Environment. Queen's Printer of Ontario.
(bb) - Los Alamos National Laboratory ECORISK Database. September 2017. http://www.IanI.gov/environment/protection/eco-risk-assessment.php (Ng/kg dw)
(cc) - Great Lakes Initiative (GLI) Clearinghouse resources Tier II criteria revised 2013. http://www.epa.gov/gliclearinghouse/
(dd) - Suter, G.W., and Tsao, C.L. 1996. Toxicological Benchmarks for Screening Potential Contaminants of Concern for Effects on Aquatic Biota: 1996 Revision. ES/ER/TM-96/R2.
http://www.esd.ornl.gov/programs/ecorisk/documents/tm96r2.pdf
(ee) - USEPA. Interim Ecological Soil Screening Level Documents. Accessed October 2018. http://www2.epa.gov/chemical-research/interim-ecological-soil-screening-level-documents
(ff) - Efroymson, R.A., M.E. Will, and G.W. Suter II, 1997a. Toxicological Benchmarks for Contaminants of Potential Concern for Effects on Soil and Litter Invertebrates and Heterotrophic Process:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-126/R2. (Available at http://www.esd.ornl.gov/programs/ecorisk/documents/tml26r2l.pdf)
(gg) - Efroymson, R.A., M.E. Will, G.W. Suter II, and A.C. Wooten, 1997b. Toxicological Benchmarks for Screening Contaminants of Potential Concern for Effects on Terrestrial Plants:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-85/R3. (Available at http://www.esd.ornl.gov/programs/ecorisk/documents/tm85r3.pdf)
(hh) - North Carolina Preliminary Soil Remediation Goals (PSRG) Table. HI = 0.2. September 2015. http://portal.ncdenr.org/c/document_library/get_file?uuid=Of60lffa-574d-4479-bbb4-253af0665bf5&groupId=38361
(ii) - As part of the water quality evaluation conducted under the CSA, pH was measured and is reported as a metric data set. The pH comparison criteria are included as ranges as opposed to single screening values. pH is not typically included
as part of a risk assessment based on potential toxic effects, therefore; pH was not investigated further as a category 1 COPC. Water quality relative to pH will be addressed as a component of water quality monitoring programs for the site.
(jj) - Hazard Index = 0.1
Page 2 of 2

TABLE 1-4
HUMAN HEALTH SCREENING - ONSITE SOIL SEDIMENT
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Analyte
CAS
Number of
Samples
Frequency
of Detection
Range of
9
Detection
(mg/kg)
Concentration
Used for
Screening
(mg/kg)
NC PSRG
Residential Health
Screening Level
(mg/kg)
Residential Soil
RSL (a)
HI = 0.2
(mg/kg)
NC PSRG
Industrial
Health
Screening
Level (hh)
(mg/kg)
Industrial Soil
RSL (a)
HI = 0.2
(mg/kg)
Residential
Screening
Value Used
(mg/kg)
Industrial
Screening
Used Value
(mg/kg)
Residential
COPC?
Industrial
COPC?
Min.
I Max. I
Aluminum
7429-90-5
3
3
4,800
6,760
6,760
15,000
15,400
100,000
220,000
15,000
100,000
N
N
Antimony
7440-36-0
3
0
ND
ND
ND
6.2 (m)
6.2 (m)
94 (m)
94 (m)
6.2
94
N
N
Arsenic
7440-38-2
3
1
0.44
0.44
0.44
0.68 (h)
0.68 (h, jj)
3 (h)
3 (h, jj)
0.67
3
N
N
Barium
7440-39-3
3
3
32
53.1
53.1
3,000
3,000
44,000
44,000
3,000
44,000
N
N
Beryllium
7440-41-7
3
3
0.29
0.44
0.44
32
32
460
460
32
460
N
N
Boron
7440-42-8
3
0
ND
ND
ND
3,200
3,200
46,000
46,000
3,200
46,000
N
N
Cadmium
7440-43-9
3
1
0.036
0.036
0.036
14
14.2
200
196
14
200
N
N
Chromium (Total)
7440-47-3
3
3
13.1
94.4
94.4
24,000 (n)
24,000 (n)
100,000 (n)
360,000 (n)
24,000
100,000
N
N
Cobalt
7440-48-4
3
3
3.4
7.4
7.4
4.6
4.6
70
70
4.6
70
Y
N
Copper
7440-50-8
3
3
4.5
10.4
10.4
620
620
9,400
9,400
620
9,400
N
N
Lead
7439-92-1
3
3
2.5
14
14
400
400 (jj)
800
800 (jj)
400
800
N
N
Manganese
7439-96-5
3
3
186
610
610
360
360
5,200
5,200
360
5,200
y
N
Mercury
7439-97-6
3
1
0.0065
0.0065
0.0065
4.6 (0)
4.6 (o)
3.1 (0)
70 (o)
4.6
3.1
N
N
Molybdenum
7439-98-7
3
0
ND
ND
ND
78
78
1,200
1,160
78
1,200
N
N
Nickel
7440-02-0
3
3
2.8
5.2
5.2
300 (p)
300 (p)
4,400 (p)
4,400 (p)
300
4,400
N
N
Selenium
7782-49-2
3
0
ND
ND
ND
78
78
1,200
1,160
78
1,200
N
N
Strontium
7440-24-6
3
3
8.3
10.3
10.3
91400
9,400
100,000
140,000
9,400
100,000
N
N
Thallium
7440-28-0
3
0
ND
ND
ND
0.16 (q)
0.156 (q)
2.4 (q)
2.4 (q)
0.16
2.4
N
N
Vanadium
7440-62-2
3
3
10
42.5
42.5
78
78
1,160
1,160
78
1,160
N
N
Zinc
7440-66-6
3
3
12.6
39.6
39.6
4,600
4,600
70,000
70,000
4,600
70,000
N
N
* Data evaluation includes data from 2015 to 2nd quarter 2018, unless otherwise noted
Notes:
AWQC - Ambient Water Quality Criteria DENR - Department of Environment and Natural Resource: NC - North Carolina
CAMA - Coal Ash Management Act DHHS - Department of Health and Human Services NCAC - North Carolina Administrative Code
North Carolina Session Law 2014-122, ESV - Ecological Screening Value ORNL - Oak Ridge National Laboratory
httn://www.nclea.net/Sessions/2013/Bills HH - Human Health PSRG - Preliminary Soil Remediation Goal
/Senate/PDF/S729v7.pdf HI - Hazard Index Q - Qualifier
CAS - Chemical Abstracts Service IMAC - Interim Maximum Allowable Concentration RSL - Regional Screening Level
CCC - Criterion Continuous Concentration MCL - Maximum Contaminant Level RSV - Refinement Screening Value
CMC - Criterion Maximum Concentration mg/kg - milligrams/kilogram SMCL - Secondary Maximum Contaminant Level
COPC - Constituent of Potential Concern NA - Not Available SSL - Soil Screening Level
(a) - USEPA Regional Screening Levels (May 2018). Values for Residential Soil, Industrial Soil, and Tap Water. HI = 0.2. Accessed October 2018.
https://www.epa.gov/risk/regional-screening-levels-rsls-generic-tables
(b) - USEPA National Recommended Water Quality Criteria. USEPA Office of Water and Office of Science and Technology. Accessed October 2018.
https://www.epa.gov/wqc/national-recommended-water-quality-criteria-human-health-criteria-table
USEPA AWQC Human Health for the Consumption of Organism Only apply to total concentrations.
(c) - USEPA 2018 Edition of the Drinking Water Standards and Health Advisories. March 2018. Accessed October 2018.
https://www.epa.gov/sites/production/files/2018-03/documents/dwtable2018. pdf
su - Standard units
µg/L - micrograms/liter
USEPA - United States Environmental Protection Agency
WS - Water Supply
< - Concentration not detected at or above the reporting limit
j - Indicates concentration reported below Practical Quantitation Limit
(PQL) but above Method Detection Limit (MDL) and therefore concentration is estimated
(d) - DHHS Screening Levels. Department of Health and Human Services, Division of Public Health, Epidemiology Section, Occupational and Environmental
Epidemiology Branch. http://portal.ncdenr.org/c/document_library/get_file?p_l_id=1169848&folderld=24814087&name=DLFE-112704.pdf
Prepared by: HEG Checked by: TCP
Page 1 of 2

TABLE 1-4
HUMAN HEALTH SCREENING - ONSITE SOIL SEDIMENT
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
(e) - North Carolina 15A NCAC 02L .0202 Groundwater Standards & IMACs. http://portal.ncdenr.org/c/document_library/get_file?uuid=laa3fal3-2cOf-45b7-ae96-5427fbld25b4&groupId=38364
Amended April 2013.
(f) - North Carolina 15A NCAC 02B Surface Water and Wetland Standards. Amended January 1, 2015.
http://reports.oah.state. nc. us/ncac/title%2015a%20-%20environmental%20quality/chapter%2002%20-%20environmental%20management/subchapter%20b/subchapter%20b%20rules. pdf
WS standards are applicable to all Water Supply Classifications. WS standards are based on the consumption of fish and water.
Human Health Standards are based on the consumption of fish only unless dermal contact studies are available.
For Class C, use the most stringent of freshwater (or, if applicable, saltwater) column and the Human Health column.
For a WS water, use the most stringent of Freshwater, WS and Human Health. Likewise, Trout Waters and High Quality Waters must adhere to the most stingent of all applicable standards.
(g) - USEPA Region 4. 2018. Region 4 Ecological Risk Assessment Supplemental Guidance. March 2018 Update.
https://www.epa.gov/sites/production/files/2018-03/documents/era_regional_supplemental_guidance_report-march-2018_update.pdf
(h) - Value applies to inorganic form of arsenic only.
(i) - Value is the Secondary Maximum Contaminant Level.
https://www.epa.gov/dwstandardsregulations/secondary-drinking-water-standards-guidance-nuisance-chemicals
(j) -Value for Total Chromium.
(k) - Copper Treatment Technology Action Level is 1.3 mg/L.
(1) - Lead Treatment Technology Action Level is 0.015 mg/L.
(m) - RSL for Antimony (metallic) used for Antimony.
(n) - Value for Chromium (III), Insoluble Salts used for Chromium.
(o) - RSL for Mercuric Chloride used for Mercury.
(p) - RSL for Nickel Soluble Salts used for Nickel.
(q) - RSL for Thallium (Soluble Salts) used for Thallium.
(r) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(s) - Value for Inorganic Mercury.
(t) - Acute AWQC is equal to 1/[(fl/CMCl) + (f2/CMC2)] where fl and f2 are the fractions of total selenium that are treated as selenite and selenate, respectively, and
CMC1 and CMC2 are 185.9 µg/L and 12.82 pg/L, respectively. Calculated assuming that all selenium is present as selenate, a likely overly conservative assumption.
(u) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(v) - Chloride Action Level for Toxic Substances Applicable to NPDES Permits is 230,000 pg/L.
(w) - Applicable only to persons with a sodium restrictive diet.
(x) - Los Alamos National Laboratory ECORISK Database. http://www.lanl.gov/community-environment/environmental-stewardship/protection/eco-risk-assessment.php
(y) - Long, Edward R., and Lee G. Morgan. 1991. The Potential for Biological Effects of Sediment-Sorbed Contaminants Tested in the National Status and Trends Program.
NOAA Technical Memorandum NOS OMA 52. Used effects range low (ER-L) for chronic and effects range medium (ER-M) for acute.
(z) - MacDonald, D.D.; Ingersoll, C.G.; Smorong, D.E.; Lindskoog, R.A.; Sloane, G.; and T. Bernacki. 2003. Development and Evaluation of Numerical Sediment Quality Assessment Guidelines for
Florida Inland Waters. Florida Department of Environmental Protection, Tallahassee, FL. Used threshold effect concentration (TEC) for the ESV and probable effect concentration (PEC) for the RSV.
(aa) - Persaud, D., R. Jaagumagi and A. Hayton. 1993. Guidelines for the protection and management of aquatic sediment quality in Ontario. Ontario Ministry of the Environment. Queen's Printer of Ontario.
(bb) - Los Alamos National Laboratory ECORISK Database. September 2017. http://www.Ian1.gov/environment/protection/eco-risk-assessment.php (Ng/kg dw)
(cc) - Great Lakes Initiative (GLI) Clearinghouse resources Tier II criteria revised 2013. http://www.epa.gov/gIiclearinghouse/
(dd) - Suter, G.W., and Tsao, C.L. 1996. Toxicological Benchmarks for Screening Potential Contaminants of Concern for Effects on Aquatic Biota: 1996 Revision. ES/ER/TM-96/R2.
http://www.esd.ornl.gov/programs/ecorisk/documents/tm96r2.pdf
(ee) - USEPA. Interim Ecological Soil Screening Level Documents. Accessed October 2018. http://www2.epa.gov/chemical-research/interim-ecological-soil-screening-level-documents
(ff) - Efroymson, R.A., M.E. Will, and G.W. Suter II, 1997a. Toxicological Benchmarks for Contaminants of Potential Concern for Effects on Soil and Litter Invertebrates and Heterotrophic Process:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-126/R2. (Available at http://www.esd.ornl.gov/programs/ecorisk/documents/tml26r2l.pdf)
(gg) - Efroymson, R.A., M.E. Will, G.W. Suter II, and A.C. Wooten, 1997b. Toxicological Benchmarks for Screening Contaminants of Potential Concern for Effects on Terrestrial Plants:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-85/R3. (Available at http://www.esd.ornl.gov/programs/ecorisk/documents/tm85r3.pdf)
(hh) - North Carolina Preliminary Soil Remediation Goals (PSRG) Table. HI = 0.2. September 2015. http://portal.ncdenr.org/c/document_library/get_file?uuid=Of60lffa-574d-4479-bbb4-253af0665bf5&groupId=38361
(ii) - As part of the water quality evaluation conducted under the CSA, pH was measured and is reported as a metric data set. The pH comparison criteria are included as ranges as opposed to single screening values. pH is not typically included
as part of a risk assessment based on potential toxic effects, therefore; pH was not investigated further as a category 1 COPC. Water quality relative to pH will be addressed as a component of water quality monitoring programs for the site.
(jj) - Hazard Index = 0.1
Page 2of2

TABLE 1-5
HUMAN HEALTH SCREENING - OFFSITE SURFACE WATER
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Analyte
CAS
Number of
Samples
Frequency of
Detection
Range of
Detection
(Ng/L)
Concentration
Used for
Screening (Ng/L)
USEPA AWQC
Consumption
of Water and
Organism (b)
(Ng/L)
USEPA AWQC
Consumption
of Organism
Only (b)
(Ng/L)
Federal MCL/
SMCL (c)
(Ng/L)
Tap Water RSL
HI = 0.2 (a)
(Ng/L)
Screening
Value Used
(Ng/L)
COPC?
Min.
Max.
Aluminum
7429-90-5
20
20
61
590
590
NA
NA
50 to 200 (i)
4,000
50
Y
Antimony
7440-36-0
20
0
ND
ND
ND
5.6
640
6
1.56 (m)
1
N
Arsenic
7440-38-2
20
2
0.76
1.06
1.06
0.018 (h)
0.14 (h)
10
0.052 (h,jj)
10
N
Barium
7440-39-3
20
20
32
90
90
1,000
NA
2,000
760
700
N
Beryllium
7440-41-7
20
0
ND
ND
ND
NA
NA
4
5
4
N
Boron
7440-42-8
20
20
422
1,110
1,110
NA
NA
NA
800
700
Y
Cadmium
7440-43-9
20
1
0.059
0.059
0.059
NA
NA
5
1.84
2
N
Chromium (Total)
7440-47-3
20
2
0.34
0.492
0.492
NA
NA
100
4,400 (n)
10
N
Chromium (VI)
18540-29-9
17
2
0.038
1.6
1.6
NA
NA
NA
0.035 (D)
0.035
Y
Cobalt
7440-48-4
20
19
0.891
3.05
3.05
NA
NA
NA
1.2
1
Y
Copper
7440-50-8
20
6
0.345
1.33
1.33
1,300
NA
1,300 (k)
160
1,000
N
Lead
7439-92-1
20
0
ND
ND
ND
NA
NA
15 (1)
15 (jj)
15
N
Lithium
7439-93-2
3
1
2.585
2.585
2.585
NA
NA
NA
8
8
N
Manganese
7439-96-5
20
20
745
8,330
8,330
50
100
50 (1)
86
50
Y
Mercury
7439-97-6
20
12
0.00124
0.00332
0.00332
NA
NA
2
1.14 (0)
1
N
Molybdenum
7439-98-7
20
9
0.094
1.1
1.1
NA
NA
NA
20
20
N
Nickel
7440-02-0
20
13
0.37
1.1
1.1
610
4,600
NA
78 (p)
100
N
Selenium
7782-49-2
20
0
ND
ND
ND
170
4,200
50
20
20
N
Strontium
7440-24-6
20
20
191
338
338
NA
NA
NA
2,400
2,400
N
Thallium
7440-28-0
20
3
0.092
0.119
0.119
0.24
0.47
2
0.04 (q)
0.2
N
Vanadium
7440-62-2
20
20
0.255
1.62
1.62
NA
NA
NA
17.2
17
N
Zinc
7440-66-6
20
13
3.072
10
10
7,400
26,000
5,000 (i)
1,200
1
Y
* Data evaluated includes data from 2015 to 2nd quarter 2018, unless otherwise noted.
Notes:
AWQC - Ambient Water Quality Criteria DENR - Department of Environment and Natural Resources
CAMA - Coal Ash Management Act DHHS - Department of Health and Human Services
North Carolina Session Law 2014-122, ESV - Ecological Screening Value
http://www.ncleg.net/Sessions/2013/Bills/Senate/PDF/S729v7.pdf HH - Human HealtH
CAS - Chemical Abstracts Service HI - Hazard Index
CCC - Criterion Continuous Concentration IMAC - Interim Maximum Allowable Concentration
CMC - Criterion Maximum Concentration MCL - Maximum Contaminant Level
COPC - Constituent of Potential Concern mg/kg - milligrams/kilogram
NA - Not Available
NC - North Carolina
NCAC - North Carolina Administrative Code
ORNL - Oak Ridge National Laboratory
PSRG - Preliminary Soil Remediation Goal
Q - Qualifier
RSL - Regional Screening Level
RSV - Refinement Screening Value
Prepared by: HEG Checked by: HES
Page 1 of 3

TABLE 1-5
HUMAN HEALTH SCREENING - OFFSITE SURFACE WATER
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
(a) - USEPA Regional Screening Levels (May 2018). Values for Residential Soil, Industrial Soil, and Tap Water. HI = 0.2. Accessed October 2018.
https://www.epa.gov/risk/mg ional-screeni ng-levels-mis-generic-tables
(b) - USEPA National Recommended Water Quality Criteria. USEPA Office of Water and Office of Science and Technology. Accessed October 2018.
https://www.epa.gov/wgc/national-recommended-water-q ual ity-criteria-human-health-criteria-table
USEPA AWQC Human Health for the Consumption of Organism Only apply to total concentrations.
(c) - USEPA 2018 Edition of the Drinking Water Standards and Health Advisories. March 2018. Accessed October 2018.
https://www.epa.gov/sites/production/files/2018-03/documents/dwtable2Ol8. pdf
(d) - DHHS Screening Levels. Department of Health and Human Services, Division of Public Health, Epidemiology Section, Occupational and Environmental
Epidemiology Branch. http://portal.ncdennorg/c/document_ library/get file?p_I_id=1169848&folderld=24814087&name=DLFE-112704.pdf
(e) - North Carolina 15A NCAC 02L .0202 Groundwater Standards &IMACs. http://portal.ncdenr.org/c/document_library/get _file?uuid=laa3fa13-2c0f-45b7-ae96-5427fb ld25b4&gmupId=38364
Amended April 2013.
(f) - North Carolina 15A NCAC 02B Surface Water and Wetland Standards. Amended January 1, 2015.
http://mports.oah.state.nc. us/ncac/title%2015a%20-%20envimnmental%20quality/chapters 2002%20-%20envimnmental%20management/subchapterO/ 20b/subchapter 20b%20rules.pdf
WS standards are applicable to all Water Supply Classifications. WS standards are based on the consumption of fish and water.
Human Health Standards are based on the consumption of fish only unless dermal contact studies are available.
For Class C, use the most stringent of freshwater (or, if applicable, saltwater) column and the Human Health column.
For a WS water, use the most stringent of Freshwater, WS and Human Health. Likewise, Trout Waters and High Quality Waters must adhere to the most stingent of all applicable standards.
(g) - USEPA Region 4. 2018. Region 4 Ecological Risk Assessment Supplemental Guidance. March 2018 Update.
https://www.epa.gov/sites/production/files/2018-03/documents/em_mgional_supplemental— uidance_report-march-2018_update.pdf
(h) - Value applies to inorganic form of arsenic only.
(i) - Value is the Secondary Maximum Contaminant Level.
https://www.epa.gov/dwstandardsmg ulations/secondary-d rinki ng-water-standards-guidance-nuisance-chemicals
(j) - Value for Total Chromium.
(k) - Copper Treatment Technology Action Level is 1.3 mg/L.
(1) - Lead Treatment Technology Action Level is 0.015 mg/L.
(m) - RSL for Antimony (metallic) used for Antimony.
(n) - Value for Chromium (III), Insoluble Salts used for Chromium.
(o) - RSL for Mercuric Chloride used for Mercury.
(p) - RSL for Nickel Soluble Salts used for Nickel.
(q) - RSL for Thallium (Soluble Salts) used for Thallium.
(r) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(s) - Value for Inorganic Mercury.
(t) - Acute AWQC is equal to 1/[(fl/CMCl) + (f2/CMC2)] where fl and f2 are the fractions of total selenium that are treated as selenite and selenate, respectively, and
CMC1 and CMC2 are 185.9 Ng/L and 12.82 Ng/L, respectively. Calculated assuming that all selenium is present as selenate, a likely overly conservative assumption.
(u) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(v) - Chloride Action Level for Toxic Substances Applicable to NPDES Permits is 230,000 Ng/L.
(w) - Applicable only to persons with a sodium restrictive diet.
(x) - Los Alamos National Laboratory ECORISK Database. http://www.lanl.gov/community-environment/environmental-stewardship/protection/eco-risk-assessment.php
(y) - Long, Edward R., and Lee G. Morgan. 1991. The Potential for Biological Effects of Sediment-Sorbed Contaminants Tested in the National Status and Trends Program.
NOAA Technical Memorandum NOS OMA 52. Used effects range low (ER-L) for chronic and effects range medium (ER-M) for acute.
(z) - MacDonald, D.D.; Ingersoll, C.G.; Smorong, D.E.; Lindskoog, R.A.; Sloane, G.; and T. Bernacki. 2003. Development and Evaluation of Numerical Sediment Quality Assessment Guidelines for
Florida Inland Waters. Florida Department of Environmental Protection, Tallahassee, FL. Used threshold effect concentration (TEC) for the ESV and probable effect concentration (PEC) for the RSV.
(aa) - Persaud, D., R. Jaagumagi and A. Hayton. 1993. Guidelines for the protection and management of aquatic sediment quality in Ontario. Ontario Ministry of the Environment. Queen's Printer of Ontario.
(bb) - Los Alamos National Laboratory ECORISK Database. September 2017. http://www.lanl.gov/envimnment/pmtection/eco-risk-assessment.php (Ng/kg dw)
(cc) - Great Lakes Initiative (GLI) Clearinghouse resources Tier II criteria revised 2013. http://www.epa.gov/gliclearinghouse/
Page 2 of 3

TABLE 1-5
HUMAN HEALTH SCREENING - OFFSITE SURFACE WATER
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
(dd) -Suter, G.W., and Tsao, C.L. 1996. Toxicological Benchmarks for Screening Potential Contaminants of Concern for Effects on Aquatic Biota: 1996 Revision. ES/ER/TM-96/R2.
http://www.esd.ornl.gov/pmgmms/ecorisk/documents/tm96r2.pdf
(ee) - USEPA. Interim Ecological Soil Screening Level Documents. Accessed October 2018. http://www2.epa.gov/chemical-research/interim-ecological-soil-screening-level-documents
(ff) - Efroymson, R.A., M.E. Will, and G.W. Suter II, 1997a. Toxicological Benchmarks for Contaminants of Potential Concern for Effects on Soil and Litter Invertebrates and Heterotrophic Process:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-126/R2. (Available at http://www.esd.ornl.gov/programs/ecorisk/documents/tml26r2l.pdf)
(gg) - Efroymson, R.A., M.E. Will, G.W. Suter II, and A.C. Wooten, 1997b. Toxicological Benchmarks for Screening Contaminants of Potential Concern for Effects on Terrestrial Plants:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-85/R3. (Available at http://www.esd.oml.gov/programs/ecorisk/documents/tm85r3.pdf)
(hh) - North Carolina Preliminary Soil Remediation Goals (PSRG) Table. HI = 0.2. September 2015. http://portal.ncdennorg/c/document_ library/get_file?uuid=Of601ffa-574d-4479-bbb4-253af0665bf5&gmupId=38361
(ii) - As part of the water quality evaluation conducted underthe CSA, pH was measured and is reported as a metric data set. The pH comparison criteria are included as ranges as opposed to single screening values. pH is not typically included
as part of a risk assessment based on potential toxic effects, therefore; pH was not investigated further as a category 1 COPC. Water quality relative to pH will be addressed as a component of water quality monitoring programs for the site.
(jj) - Hazard Index = 0.1
Page 3 of 3

TABLE 1-6
HUMAN HEALTH SCREENING - ONSITE SURFACE WATER
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Analyte
CAS
Number of
Samples
Frequency
of Detection
Range of
Detection
L
(Ng/ )
Concentration
Used for
Screening
(N9/L)
USEPA AWQC
Consumption
of Organism Only
(b)
(Ng/L)
Federal MCL/
SMCL (c)
(N9/L)
Tap Water RSL HI
= 0.2 (a)
(N9/L)
Screening
Value Used
(N9/L)
COPC?
Min.
Max.
Aluminum
7429-90-5
25
25
11
965
965
NA
50 to 200 (i)
4,000
50
Y
Antimony
7440-36-0
25
0
ND
ND
ND
640
6
1.56 (m)
1
N
Arsenic
7440-38-2
25
1
1.7
1.7
1.7
0.14 (h)
10
0.052 (h,jj)
10
N
Barium
7440-39-3
25
25
40
108
108
NA
2,000
760
700
N
Beryllium
7440-41-7
18
0
ND
ND
ND
NA
4
5
4
N
Boron
7440-42-8
25
25
637
1,510
1,510
NA
NA
800
700
Y
Cadmium
7440-43-9
25
0
ND
ND
ND
NA
5
1.84
2
N
Chromium (Total)
7440-47-3
25
1
1.25
1.25
1.25
NA
100
4,400 (n)
10
N
Chromium (VI)
18540-29-9
14
1
0.36
0.36
0.36
NA
NA
0.035 Uj)
0.035
Y
Cobalt
7440-48-4
18
13
0.541
6.29
6.29
NA
NA
1.2
1
Y
Copper
7440-50-8
25
6
0.347
1.65
1.65
NA
1,300 (k)
160
1,000
N
Lead
7439-92-1
25
0
ND
ND
ND
NA
15 (1)
15 0j)
15
N
Lithium
7439-93-2
3
2
1.67
3.106
3.106
NA
NA
8
8
N
Manganese
7439-96-5
25
25
536
4,370
4,370
100
50 0)
86
50
Y
Mercury
7439-97-6
25
16
0.00151
0.023
0.023
NA
2
1.14 (0)
1
N
Molybdenum
7439-98-7
25
1
2.53
2.53
2.53
NA
NA
20
20
N
Nickel
7440-02-0
25
10
0.419
1.52
1.52
41600
NA
78 (p)
100
N
Selenium
7782-49-2
25
0
ND
ND
ND
4,200
50
20
20
N
Strontium
7440-24-6
18
18
231
538
538
NA
NA
2,400
2,400
N
Thallium
7440-28-0
25
3
0.121
0.193
0.193
0.47
2
0.04 (q)
0.20
N
Vanadium
1 7440-62-2
1 18
1 14
1 0.31
1 1.83
1 1.83
1 NA
I NA
1 17.2
1 17
1 N
Zinc
1 7440-66-6
1 25
1 12
1 2.7
1 19
1 19
1 26,000
1 5,000 (i)
1 1,200
1 1
1 Y
* Data evaluation includes data from 2015 to 2nd quarter 2018, unless otherwise noted
Notes:
AWQC - Ambient Water Quality Criteria
CAMA - Coal Ash Management Act
North Carolina Session Law 2014-122,
httr)://www.ncleo.net/Sessions/2013/Bills
/Senate/PDF/S729v7. pdf
CAS - Chemical Abstracts Service
CCC - Criterion Continuous Concentration
CMC - Criterion Maximum Concentration
COPC - Constituent of Potential Concern
DENR - Department of Environment and Natural Resources
DHHS - Department of Health and Human Services
ESV - Ecological Screening Value
HH - Human Health
HI - Hazard Index
IMAC - Interim Maximum Allowable Concentration
MCL - Maximum Contaminant Level
mg/kg - milligrams/kilogram
NA - Not Available
NC - North Carolina
NCAC - North Carolina Administrative Code
ORNL - Oak Ridge National Laboratory
PSRG - Preliminary Soil Remediation Goal
Q - Qualifier
RSL - Regional Screening Level
RSV - Refinement Screening Value
SMCL - Secondary Maximum Contaminant Level
SSL - Soil Screening Level
(a) - USEPA Regional Screening Levels (May 2018). Values for Residential Soil, Industrial Soil, and Tap Water. HI = 0.2. Accessed October 2018.
https://www.epa.gov/risk/regional-screening-levels-rsls-generic-tables
(b) - USEPA National Recommended Water Quality Criteria. USEPA Office of Water and Office of Science and Technology. Accessed October 2018.
https://www. epa.gov/wqc/national-recommended-water-q uaIity-criteria-hu man -health -criteria -table
USEPA AWQC Human Health for the Consumption of Organism Only apply to total concentrations.
(c) - USEPA 2018 Edition of the Drinking Water Standards and Health Advisories. March 2018. Accessed October 2018.
https://www.epa.gov/sites/production/files/2018-03/documents/dwtable2O1S. pdf
Prepared by: HEG Checked by: TCP
Page 1 of 2

TABLE 1-6
HUMAN HEALTH SCREENING - ONSITE SURFACE WATER
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
(d) - DHHS Screening Levels. Department of Health and Human Services, Division of Public Health, Epidemiology Section, Occupational and Environmental
Epidemiology Branch. http://portal.ncdenr.org/c/document_Iibrary/get_file?p_I_id=1169848&foIderld=24814087&name=DLFE-112704.pdf
(e) - North Carolina 15A NCAC 02L .0202 Groundwater Standards & IMACs. http://portal.ncdenr.org/c/document_library/get_file?uuid=laa3fal3-2cOf-45b7-ae96-5427fbld25b4&groupId=38364
Amended April 2013.
(f) - North Carolina 15A NCAC 02B Surface Water and Wetland Standards. Amended January 1, 2015.
http: //reports. oah. state. nc. us/ncac/title%2015a%20-%20environmenta 1%20qua I ity/chapter%2002%20-0/a20environmenta 1%20management/subchapter%20 b/subchapter°/a20b°/a20ru les. pdf
WS standards are applicable to all Water Supply Classifications. WS standards are based on the consumption of fish and water.
Human Health Standards are based on the consumption of fish only unless dermal contact studies are available.
For Class C, use the most stringent of freshwater (or, if applicable, saltwater) column and the Human Health column.
For a WS water, use the most stringent of Freshwater, WS and Human Health. Likewise, Trout Waters and High Quality Waters must adhere to the most stingent of all applicable standards.
(g) - USEPA Region 4. 2018. Region 4 Ecological Risk Assessment Supplemental Guidance. March 2018 Update.
https://www.epa.gov/sites/production/files/2018-03/documents/era_regional_supplemental_guidance_report-march-2018_u pdate. pdf
(h) - Value applies to inorganic form of arsenic only.
(i) - Value is the Secondary Maximum Contaminant Level.
https://www.epa.gov/dwstandardsregulations/secondary-drinking-water-standards-guidance-nuisance-chemicals
(j) - Value for Total Chromium.
(k) - Copper Treatment Technology Action Level is 1.3 mg/L.
(1) - Lead Treatment Technology Action Level is 0.015 mg/L.
(m) - RSL for Antimony (metallic) used for Antimony.
(n) - Value for Chromium (III), Insoluble Salts used for Chromium.
(o) - RSL for Mercuric Chloride used for Mercury.
(p) - RSL for Nickel Soluble Salts used for Nickel.
(q) - RSL for Thallium (Soluble Salts) used for Thallium.
(r) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(s) - Value for Inorganic Mercury.
(t) - Acute AWQC is equal to 1/[(fl/CMC1) + (f2/CMC2)] where fl and f2 are the fractions of total selenium that are treated as selenite and selenate, respectively, and
CMC1 and CMC2 are 185.9 Ng/L and 12.82 Ng/L, respectively. Calculated assuming that all selenium is present as selenate, a likely overly conservative assumption.
(u) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(v) - Chloride Action Level for Toxic Substances Applicable to NPDES Permits is 230,000 Ng/L.
(w) - Applicable only to persons with a sodium restrictive diet.
(x) - Los Alamos National Laboratory ECORISK Database. http://www.Ian1.gov/community-environment/environmental-stewardship/protection/eco-risk-assessment.php
(y) - Long, Edward R., and Lee G. Morgan. 1991. The Potential for Biological Effects of Sediment-Sorbed Contaminants Tested in the National Status and Trends Program.
NOAA Technical Memorandum NOS OMA 52. Used effects range low (ER-L) for chronic and effects range medium (ER-M) for acute.
(z) - MacDonald, D.D.; Ingersoll, C.G.; Smorong, D.E.; Lindskoog, R.A.; Sloane, G.; and T. Bernacki. 2003. Development and Evaluation of Numerical Sediment Quality Assessment Guidelines for
Florida Inland Waters. Florida Department of Environmental Protection, Tallahassee, FL. Used threshold effect concentration (TEC) for the ESV and probable effect concentration (PEC) for the RSV.
(aa) - Persaud, D., R. Jaagumagi and A. Hayton. 1993. Guidelines for the protection and management of aquatic sediment quality in Ontario. Ontario Ministry of the Environment. Queen's Printer of Ontario.
(bb) - Los Alamos National Laboratory ECORISK Database. September 2017. http://www.IanI.gov/environment/protection/eco-risk-assessment.php (Ng/kg dw)
(cc) - Great Lakes Initiative (GLI) Clearinghouse resources Tier II criteria revised 2013. http://www.epa.gov/gIiclearinghouse/
(dd) - Suter, G.W., and Tsao, C.L. 1996. Toxicological Benchmarks for Screening Potential Contaminants of Concern for Effects on Aquatic Biota: 1996 Revision. ES/ER/TM-96/R2.
http://www.esd.ornl.gov/programs/ecorisk/documents/tm96r2.pdf
(ee) - USEPA. Interim Ecological Soil Screening Level Documents. Accessed October 2018. http://www2.epa.gov/chemical-research/interim-ecological-soil-screening-level-documents
(ff) - Efroymson, R.A., M.E. Will, and G.W. Suter II, 1997a. Toxicological Benchmarks for Contaminants of Potential Concern for Effects on Soil and Litter Invertebrates and Heterotrophic Process:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-126/R2. (Available at http://www.esd.ornl.gov/programs/ecorisk/documents/tml26r2l.pdf)
(gg) - Efroymson, R.A., M.E. Will, G.W. Suter II, and A.C. Wooten, 1997b. Toxicological Benchmarks for Screening Contaminants of Potential Concern for Effects on Terrestrial Plants:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-85/R3. (Available at http://www.esd.ornl.gov/programs/ecorisk/documents/tm85r3.pdf)
(hh) - North Carolina Preliminary Soil Remediation Goals (PSRG) Table. HI = 0.2. September 2015. http://portal.ncdenr.org/c/document_library/get_file?uuid=Of601ffa-574d-4479-bbb4-253af0665bf5&groupId=38361
(ii) - As part of the water quality evaluation conducted under the CSA, pH was measured and is reported as a metric data set. The pH comparison criteria are included as ranges as opposed to single screening values. pH is not typically included
as part of a risk assessment based on potential toxic effects, therefore; pH was not investigated further as a category 1 COPC. Water quality relative to pH will be addressed as a component of water quality monitoring programs for the site.
(jj) - Hazard Index = 0.1
Page 2 of 2

TABLE 2-1
ECOLOGICAL SCREENING - SEDIMENT - CRUTCHFIELD BRANCH
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Analyte
CAS
Number of
Samples
Frequency
of
Detection
Range of Detection
(mg/kg)
Concentration
Used for
Screening
(mg/kg)
USEPA Region 4 Sediment
Screening Values(g)
(mg/kg)
Screening Value
Used (mg/kg)
COPC?
Min.
Max.
ESV
RSV
Aluminum
7429-90-5
6
6
2,300
7,350
7,350
25,000 (x)
58,000 (x)
25,000
N
Antimony
7440-36-0
6
0
ND
ND
ND
2 (y)
25 (y)
2
N
Arsenic
7440-38-2
6
2
0.28
0.44
0.44
9.8 (z)
33 (z)
9.8
N
Barium
7440-39-3
6
6
18
98.2
98.2
20 (z)
60 (z)
20
y
Beryllium
7440-41-7
6
6
0.11
0.44
0.44
NA
NA
NA
N
Boron
7440-42-8
6
0
ND
ND
ND
NA
NA
NA
N
Cadmium
7440-43-9
6
1
0.036
0.036
0.036
1 (z)
5 (z)
1
N
Chromium (Total)
7440-47-3
6
6
4.8
94.4
94.4
43.4 (z)
111 (z)
43.4
y
Cobalt
7440-48-4
6
6
1.5
7.4
7.4
50 (aa)
NA (aa)
50
N
Copper
7440-50-8
6
6
1.7
10.4
10.4
31.6 (z)
149 (z)
31.6
N
Lead
7439-92-1
6
6
1.9
14
14
35.8 (z)
128 (z)
35.8
N
Manganese
7439-96-5
6
6
120
610
610
460 (bb)
1,100 (bb)
460
y
Mercury
7439-97-6
6
2
0.0065
0.027
0.027
0.18 (z)
1.1 (z)
0.18
N
Molybdenum
7439-98-7
6
0
ND
ND
ND
NA
NA
NA
N
Nickel
7440-02-0
6
6
1.1
5.2
5.2
22.7 (z)
48.6 (z)
22.7
N
Selenium
7782-49-2
6
0
ND
ND
ND
0.8 (bb)
1.2 (bb)
0.8
N
Strontium
7440-24-6
6
6
5.3
16.3
16.3
NA
NA
NA
N
Thallium
7440-28-0
6
0
ND
ND
ND
NA
NA
NA
N
Vanadium
7440-62-2
6
6
6.2
42.5
42.5
NA
NA
NA
N
Zinc
1 7440-66-6
1 6
6
7.3
39.6
1 39.6
1 121 (z)
459 (z)
121
N
* Data evaluated includes data from 2015 to 2nd quarter 2018, unless otherwise noted
Notes:
AWQC - Ambient Water Quality Criteria
DENR - Department of Environment and Natural Resources
CAMA - Coal Ash Management Act
DHHS - Department of Health and Human Services
North Carolina Session Law 2014-122,
ESV - Ecological Screening Value
htto://www.ncleg.net/Sessions/2013/Bills
HH - Human Health
/Senate/ PDF/S729v7. pdf
HI- Hazard Index
CAS - Chemical Abstracts Service
IMAC - Interim Maximum Allowable Concentration
CCC - Criterion Continuous Concentration
MCL - Maximum Contaminant Level
CMC - Criterion Maximum Concentration
mg/kg - milligrams/kilogram
COPC - Constituent of Potential Concern
NA - Not Available
Prepared by: HEG Checked by: HES
NC - North Carolina
su - Standard units
NCAC
- North Carolina Administrative Code
Ng/L - micrograms/liter
ORNL
- Oak Ridge National Laboratory
USEPA - United States Environmental Protection Agency
PSRG
- Preliminary Soil Remediation Goal
WS - Water Supply
Q - Qualifier
< - Concentration not detected at or above the reporting limit
RSL -
Regional Screening Level
j - Indicates concentration reported below Practical Quantitatioi
RSV -
Refinement Screening Value
(PQL) but above Method Detection Limit (MDL) and therefor
SMCL
- Secondary Maximum Contaminant Level
SSL -
Soil Screening Level
Page 1 of 2

TABLE 2-1
ECOLOGICAL SCREENING - SEDIMENT - CRUTCHFIELD BRANCH
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
(a) - USEPA Regional Screening Levels (May 2018). Values for Residential Soil, Industrial Soil, and Tap Water. HI = 0.2. Accessed October 2018.
https: //www. epa. gov/ri sk/regi ona I -screen i ng-level s-rsls-generic-tables
(b) - USEPA National Recommended Water Quality Criteria. USEPA Office of Water and Office of Science and Technology. Accessed October 2018.
https: //www. epa. gov/wqc/nationa I-recom mended-water-q ua I ity-criteria-aquatic-I ife-criteria-table
USEPA AWQC Human Health for the Consumption of Organism Only apply to total concentrations.
(c) - USEPA 2018 Edition of the Drinking Water Standards and Health Advisories. March 2018. Accessed October 2018.
https: //www. epa. gov/sites/production/files/2018-03/documents/dwta ble20l8. pdf
(d) - DHHS Screening Levels. Department of Health and Human Services, Division of Public Health, Epidemiology Section, Occupational and Environmental
Epidemiology Branch. http://portal.ncdenr.org/c/document_ library/get_file?p_I_id=1169848&folderld=24814087&name=DLFE-112704.pdf
(e) - North Carolina 15A NCAC 02L .0202 Groundwater Standards & IMACs. http://portal.ncdenr.org/c/document_ library/get_file?uuid=laa3fal3-2cOf-45b7-ae96-5427fbld25b4&groupId=38364
Amended April 2013.
(f) - North Carolina 15A NCAC 02B Surface Water and Wetland Standards. Amended January 1, 2015.
http: //reports. oa h .state. n c. u s/ncac/title%2015a%20-%20envi ron menta I%20qua I ity/chapter%2002%20-%20envi ron m enta I%20m a nagem ent/subchapter%20b/su bcha pter%20b%20ruI es. pdf
WS standards are applicable to all Water Supply Classifications. WS standards are based on the consumption of fish and water.
Human Health Standards are based on the consumption of fish only unless dermal contact studies are available.
For Class C, use the most stringent of freshwater (or, if applicable, saltwater) column and the Human Health column.
For a WS water, use the most stringent of Freshwater, WS and Human Health. Likewise, Trout Waters and High Quality Waters must adhere to the most stingent of all applicable standards.
(g) - USEPA Region 4. 2018. Region 4 Ecological Risk Assessment Supplemental Guidance. March 2018 Update.
https: //www. epa. gov/sites/production/fi I es/2018-03/documents/era_reg iona I_su pplem enta I_g u ida nce_report-march-2018_u pdate. pdf
(h) - Value applies to inorganic form of arsenic only.
(i) - Value is the Secondary Maximum Contaminant Level.
https: //www. epa. gov/dwsta nda rdsregu lations/seconda ry-d ri n ki ng-water-standards-gu i da nce-n u isa nce-chem i ca I s
(j) - Value for Total Chromium.
(k) - Copper Treatment Technology Action Level is 1.3 mg/L.
(I) - Lead Treatment Technology Action Level is 0.015 mg/L.
(m) - RSL for Antimony (metallic) used for Antimony.
(n) - Value for Chromium (III), Insoluble Salts used for Chromium.
(o) - RSL for Mercuric Chloride used for Mercury.
(p) - RSL for Nickel Soluble Salts used for Nickel.
(q) - RSL for Thallium (Soluble Salts) used for Thallium.
(r) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(s) - Value for Inorganic Mercury.
(t) - Acute AWQC is equal to 1/[(fl/CMC1) + (f2/CMC2)] where fl and f2 are the fractions of total selenium that are treated as selenite and selenate, respectively, and
CMC1 and CMC2 are 185.9 pg/L and 12.82 pg/L, respectively. Calculated assuming that all selenium is present as selenate, a likely overly conservative assumption.
(u) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(v) - Chloride Action Level for Toxic Substances Applicable to NPDES Permits is 230,000 pg/L.
(w) - Applicable only to persons with a sodium restrictive diet.
(x) - Los Alamos National Laboratory ECORISK Database. http://www.lani.gov/community-environment/environmental-stewardship/protection/eco-risk-assessment.php
(y) - Long, Edward R., and Lee G. Morgan. 1991. The Potential for Biological Effects of Sediment-Sorbed Contaminants Tested in the National Status and Trends Program.
NOAA Technical Memorandum NOS OMA 52. Used effects range low (ER-L) for chronic and effects range medium (ER-M) for acute.
(z) - MacDonald, D.D.; Ingersoll, C.G.; Smorong, D.E.; Lindskoog, R.A.; Sloane, G.; and T. Bemacki. 2003. Development and Evaluation of Numerical Sediment Quality Assessment Guidelines for
Florida Inland Waters. Florida Department of Environmental Protection, Tallahassee, FL. Used threshold effect concentration (TEC) for the ESV and probable effect concentration (PEC) for the RSV.
(aa) - Persaud, D., R. Jaagumagi and A. Hayton. 1993. Guidelines for the protection and management of aquatic sediment quality in Ontario. Ontario Ministry of the Environment. Queen's Printer of Ontario.
(bb) - Los Alamos National Laboratory ECORISK Database. September 2017. http://www.lani.gov/environment/protection/eco-risk-assessment.php (pg/kg dw)
(cc) - Great Lakes Initiative (GLI) Clearinghouse resources Tier II criteria revised 2013. http://www.epa.gov/gliclearinghouse/
(dd) - Suter, G.W., and Tsao, C.L. 1996. Toxicological Benchmarks for Screening Potential Contaminants of Concern for Effects on Aquatic Biota: 1996 Revision. ES/ER/TM-96/R2.
http://www.esd.omi.gov/programs/ecorisk/documents/tm96r2.pdf
(ee) - USEPA. Interim Ecological Soil Screening Level Documents. Accessed October 2018. http://www2.epa.gov/chemical-research/interim-ecological-soil-screening-level-documents
(ff) - Efroymson, R.A., M.E. Will, and G.W. Suter II, 1997a. Toxicological Benchmarks for Contaminants of Potential Concern for Effects on Soil and Litter Invertebrates and Heterotrophic Process:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-126/R2. (Available at http://www.esd.orni.gov/programs/ecorisk/documents/tml26r2l.pdf)
(gg) - Efroymson, R.A., M.E. Will, G.W. Suter II, and A.C. Wooten, 1997b. Toxicological Benchmarks for Screening Contaminants of Potential Concern for Effects on Terrestrial Plants:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-85/R3. (Available at http://www.esd.orni.gov/programs/ecorisk/documents/tm85r3.pdf)
(hh) - North Carolina Preliminary Soil Remediation Goals (PSRG) Table. HI = 0.2. September 2015. http://portal.ncdenr.org/c/document_library/get_file?uuid=Of60lffa-574d-4479-bbb4-253af0665bf5&groupId=38361
(ii) - As part of the water quality evaluation conducted under the CSA, pH was measured and is reported as a metric data set. The pH comparison criteria are included as ranges as opposed to single screening values. pH is i
as part of a risk assessment based on potential toxic effects, therefore; pH was not investigated further as a category 1 COPC. Water quality relative to pH will be addressed as a component of water quality monitorin
Page 2 of 2

TABLE 2-2
ECOLOGICAL SCREENING - SURFACE WATER - CRUTCHFIELD BRANCH
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Analyte
CAS
Number
of
Samples
Frequency
of
Detection
Range of
Detection
(pg/L)
Concentration
Used for
Screening
(pg/L)
15A NCAC 2B
Freshwater Aquatic
Life Acute (f)
(pg/L)
15A NCAC 2B
Freshwater Aquatic Life
Chronic (f)
(pg/L)
USEPA Region 4
Freshwater Acute Screening
Values (g)
(pg/L)
USEPA Region 4
Freshwater Chronic
Screening Values (g)
(pg/L)
USEPA
AWQC (b)
CMC (acute)
(Ng/L)
USEPA
AWQC (b)
CCC (chronic)
(pg/L)
Screening
Value Used
(pg/L)
COPC?
Min.
Max.
Total
Dissolved
Total
Dissolved
Total
Dissolved
Total
Dissolved
Total
Dissolved
Total
Dissolved
Aluminum
7429-90-5
44
44
11
965
965
NA
NA
NA
NA
750 (b)
NA
87 (b)
NA
750
NA
87
NA
87
Y
Antimony
7440-36-0
44
0
ND
ND
ND
NA
NA
NA
NA
900 (cc)
NA
190 (cc)
NA
NA
NA
NA
NA
190
N
Arsenic
7440-38-2
44
2
1.06
1.7
1.7
NA
340
NA
150
340 (b, h)
NA
150 (b, h)
NA
340 (h)
NA
150 (h)
NA
150
N
Barium
7440-39-3
44
44
32
108
108
NA
NA
NA
NA
2000 (cc)
NA
220 (cc)
NA
NA
NA
NA
NA
220
N
Beryllium
7440-41-7
37
0
ND
ND
ND
NA
65
NA
6.5
31 (r, cc)
NA
3.6 (r, cc)
NA
NA
NA
NA
NA
4
N
Boron
7440-42-8
44
44
422
1,510
1,510
NA
NA
NA
NA
34,000 (cc)
NA
7,200 (cc)
NA
NA
NA
NA
NA
7,200
N
Cadmium
7440-43-9
44
1
0.059
0.059
0.059
NA
NA
NA
NA
1.1 (r)
NA
0.16 (r)
NA
NA
1.8 (r)
NA
0.72 (r)
0.16
N
Chromium (Total)
7440-47-3
44
3
0.34
1.25
1.25
NA
NA
50
NA
1,022 (n, r)
NA
48.8 (n, r)
NA
NA
NA
NA
NA
50
N
Chromium (VI)
18540-29-9
30
3
0.038
1.6
1.6
NA
16
NA
11
16
NA
11
NA
NA
16
NA
11
11
N
Cobalt
7440-48-4
37
31
0.541
6.29
6.29
NA
NA
NA
NA
120 (cc)
NA
19 (cc)
NA
NA
NA
NA
NA
19
N
Copper
7440-50-8
44
12
0.345
1.65
1.65
NA
NA
NA
NA
7.3 (r)
NA
5.16 (r)
NA
NA
NA
NA
NA
5
N
Lead
7439-92-1
44
0
ND
ND
ND
NA
NA
NA
NA
33.8 (r)
NA
1.32 (r)
NA
NA
65 (r)
NA
2.5 (r)
1
N
Manganese
7439-96-5
44
44
536
8,330
8,330
NA
NA
NA
NA
1,680 (cc)
NA
93 (cc)
NA
NA
NA
NA
NA
93
Y
Mercury
7439-97-6
44
28
0.00124
0.023
0.023
NA
NA
0.012
NA
1.4 (b, s)
NA
0.77 (b, s)
NA
NA
1.4 (s)
NA
0.77 (s)
0.01
Y
Molybdenum
7439-98-7
44
9
0.094
2.53
2.53
NA
NA
NA
NA
7,200 (cc)
NA
800 (cc)
NA
NA
NA
NA
NA
800
N
Nickel
7440-02-0
44
22
0.37
1.52
1.52
NA
NA
NA
NA
261 (r)
NA
29 (r)
NA
NA
470 (r)
NA
52.0 (r)
29
N
Selenium
7782-49-2
44
0
ND
ND
ND
NA
NA
5
NA
20 (cc)
NA
5 (cc)
NA
NA
NA
NA
NA
5
N
Strontium
7440-24-6
37
37
191
538
538
NA
NA
NA
NA
48,000 (cc)
NA
5,300 (cc)
NA
NA
NA
NA
NA
5,300
N
Thallium
7440-28-0
44
6
0.092
0.193
0.193
NA
NA
NA
NA
54 (cc)
NA
6 (cc)
NA
NA
NA
NA
NA
6
N
Vanadium
7440-62-2
37
33
0.255
1.83
1.83
NA
NA
NA
NA
79 (cc)
NA
27 (cc)
NA
NA
NA
NA
NA
27
N
Zinc
7440-66-6
44
25
2.7
19
19
NA
NA
NA
NA
67 (r)
NA
67 (r)
NA
120 (r)
NA
120 (r)
NA
67
N
* Data evaluated includes data from 2015 to 2nd quarter 2018, unless otherwise noted
Notes:
AWQC - Ambient Water Quality Criteria DENR - Department of Environment and Natural Resources
CAMA - Coal Ash Management Act DHHS - Department of Health and Human Services
North Carolina Session Law 2014-122, ESV - Ecological Screening Value
htto://www.ncleo.net/Sessions/2013/Bills HH - Human Health
/Senate/PDF/S729v7.pdf HI - Hazard Index
CAS - Chemical Abstracts Service IMAC - Interim Maximum Allowable Concentration
CCC - Criterion Continuous Concentration MCL - Maximum Contaminant Level
CMC - Criterion Maximum Concentration mg/kg - milligrams/kilogram
NC - North Carolina su - Standard units
NCAC - North Carolina Administrative Code pg/L - micrograms/liter
ORNL - Oak Ridge National Laboratory USEPA - United States Environmental Protection Agency
PSRG - Preliminary Soil Remediation Goal WS - Water Supply
Q - Qualifier < - Concentration not detected at or above the reporting limit
RSL - Regional Screening Level j - Indicates concentration reported below Practical Quantitation Limit
RSV - Refinement Screening Value (PQL) but above Method Detection Limit (MDL) and therefore concentration is estimated
SMCL - Secondary Maximum Contaminant Level
Prepared by: HEG Checked by: HES
Page 1 of 2

TABLE 2-2
ECOLOGICAL SCREENING - SURFACE WATER - CRUTCHFIELD BRANCH
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
COPC - Constituent of Potential Concern NA - Not Available
(a) - USEPA Regional Screening Levels (May 2018). Values for Residential Soil, Industrial Soil, and Tap Water. HI = 0.2. Accessed October 2018.
https://www.epa.gov/risk/mg ional-screeni ng-levels-mis-generic-tables
(b) - USEPA National Recommended Water Quality Criteria. USEPA Office of Water and Office of Science and Technology. Accessed October 2018.
https://www.epa.gov/wgc/national-recommended-water-q ual ity-criteria-aquatic-I ife-criteria-table
USEPA AWQC Human Health for the Consumption of Organism Only apply to total concentrations.
(c) - USEPA 2018 Edition of the Drinking Water Standards and Health Advisories. March 2018. Accessed October 2018.
https://www.epa.gov/sites/production/files/2018-03/documents/dwtable2Ol8. pdf
(d) - DHHS Screening Levels. Department of Health and Human Services, Division of Public Health, Epidemiology Section, Occupational and Environmental
Epidemiology Branch. http://portal.ncdennorg/c/document_ library/get file?p_I_id=1169848&folderld=24814087&name=DLFE-112704.pdf
(e) - North Carolina 15A NCAC 02L .0202 Groundwater Standards &IMACs. http://portal.ncdenr.org/c/document_library/get _file?uuid=laa3fa13-2c0f-45b7-ae96-5427fb ld25b4&gmupId=38364
Amended April 2013.
(f) - North Carolina 15A NCAC 02B Surface Water and Wetland Standards. Amended January 1, 2015.
http://mports.oah.state.nc. us/ncac/title%2015a%20-%20envimnmental%20quality/chapters 2002%20-%20envimnmental%20management/subchapterO/ 20b/subchapter 20b%20rules.pdf
WS standards are applicable to all Water Supply Classifications. WS standards are based on the consumption of fish and water.
Human Health Standards are based on the consumption of fish only unless dermal contact studies are available.
For Class C, use the most stringent of freshwater (or, if applicable, saltwater) column and the Human Health column.
For a WS water, use the most stringent of Freshwater, WS and Human Health. Likewise, Trout Waters and High Quality Waters must adhere to the most stingent of all applicable standards.
(g) - USEPA Region 4. 2018. Region 4 Ecological Risk Assessment Supplemental Guidance. March 2018 Update.
https://www.epa.gov/sites/production/files/2018-03/documents/em_mgional_supplemental— uidance_report-march-2018_update.pdf
(h) - Value applies to inorganic form of arsenic only.
(i) - Value is the Secondary Maximum Contaminant Level.
https://www.epa.gov/dwstandardsmg ulations/secondary-d rinki ng-water-standards-guidance-nuisance-chemicals
(j) - Value for Total Chromium.
(k) - Copper Treatment Technology Action Level is 1.3 mg/L.
(1) - Lead Treatment Technology Action Level is 0.015 mg/L.
(m) - RSL for Antimony (metallic) used for Antimony.
(n) - Value for Chromium (III), Insoluble Salts used for Chromium.
(o) - RSL for Mercuric Chloride used for Mercury.
(p) - RSL for Nickel Soluble Salts used for Nickel.
(q) - RSL for Thallium (Soluble Salts) used for Thallium.
(r) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(s) - Value for Inorganic Mercury.
(t) - Acute AWQC is equal to 1/[(fl/CMCl) + (f2/CMC2)] where fl and f2 are the fractions of total selenium that are treated as selenite and selenate, respectively, and
CMC1 and CMC2 are 185.9 Ng/L and 12.82 Ng/L, respectively. Calculated assuming that all selenium is present as selenate, a likely overly conservative assumption.
(u) - Criterion expressed as a function of total hardness (mg/L). Value displayed is the site -specific total hardness of mg/L.
(v) - Chloride Action Level for Toxic Substances Applicable to NPDES Permits is 230,000 Ng/L.
(w) - Applicable only to persons with a sodium restrictive diet.
(x) - Los Alamos National Laboratory ECORISK Database. http://www.lanl.gov/community-environment/environmental-stewardship/protection/eco-risk-assessment.php
(y) - Long, Edward R., and Lee G. Morgan. 1991. The Potential for Biological Effects of Sediment-Sorbed Contaminants Tested in the National Status and Trends Program.
NOAA Technical Memorandum NOS OMA 52. Used effects range low (ER-L) for chronic and effects range medium (ER-M) for acute.
(z) - MacDonald, D.D.; Ingersoll, C.G.; Smorong, D.E.; Lindskoog, R.A.; Sloane, G.; and T. Bernacki. 2003. Development and Evaluation of Numerical Sediment Quality Assessment Guidelines for
Florida Inland Waters. Florida Department of Environmental Protection, Tallahassee, FL. Used threshold effect concentration (TEC) for the ESV and probable effect concentration (PEC) for the RSV.
(aa) - Persaud, D., R. Jaagumagi and A. Hayton. 1993. Guidelines for the protection and management of aquatic sediment quality in Ontario. Ontario Ministry of the Environment. Queen's Printer of Ontario.
(bb) - Los Alamos National Laboratory ECORISK Database. September 2017. http://www.lanl.gov/envimnment/pmtection/eco-risk-assessment.php (Ng/kg dw)
(cc) - Great Lakes Initiative (GLI) Clearinghouse resources Tier II criteria revised 2013. http://www.epa.gov/gliclearinghouse/
(dd) - Suter, G.W., and Tsao, C.L. 1996. Toxicological Benchmarks for Screening Potential Contaminants of Concern for Effects on Aquatic Biota: 1996 Revision. ES/ER/TM-96/R2.
http://www.esd.ornl.gov/pmgmms/ecorisk/documents/tm96r2.pdf
(ee) - USEPA. Interim Ecological Soil Screening Level Documents. Accessed October 2018. http://www2.epa.gov/chemical-research/interim-ecological-soil-screening-level-documents
(ff) - Efroymson, R.A., M.E. Will, and G.W. Suter II, 1997a. Toxicological Benchmarks for Contaminants of Potential Concern for Effects on Soil and Litter Invertebrates and Heterotrophic Process:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-126/R2. (Available at http://www.esd.ornl.gov/programs/ecorisk/documents/tml26r2l.pdf)
(gg) - Efroymson, R.A., M.E. Will, G.W. Suter II, and A.C. Wooten, 1997b. Toxicological Benchmarks for Screening Contaminants of Potential Concern for Effects on Terrestrial Plants:
1997 Revision. Oak Ridge National Laboratory, Oak Ridge, TN. ES/ER/TM-85/R3. (Available at http://www.esd.oml.gov/programs/ecorisk/documents/tm85r3.pdf)
(hh) - North Carolina Preliminary Soil Remediation Goals (PSRG) Table. HI = 0.2. September 2015. http://portal.ncdenr.org/c/document_ library/get_file?uuid=Of601ffa-574d-4479-bbb4-253af0665bf5&gmupId=38361
Page 2 of 2

TABLE 3-1
SUMMARY OF EXPOSURE POINT CONCENTRATIONS
HUMAN HEALTH - GROUNDWATER (SURFICIAL)
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Constituent
Reporting
Units
Number of
Samples
Frequency of
Detection
Minimum
Detected
Concentration
Maximum
Detected
Concentration
Mean of
Detected
Concentration
UCL Selected
UCL
Exposure Point
Concentration
Exposure Point
Concentration
m L
Antimony
pg/L
72
1
2
2
2
2
0.002
Boron
pg/L
72
68
122
1,330
755.5
95% KM (Chebychev)
914.2
914.2
0.9142
Chromium (Total)
pg/L
72
16
0.54
43
8.228
KM H
1.84
1.84
0.00184
Chromium (VI)
pg/L
24
12
0.028
0.62
0.2
95% KM (Chebychev)
0.235
0.235
0.000235
Cobalt
pg/L
68
44
1.07
10.3
3.342
95% GROS Approximate Gamma
3.013
3.013
0.003013
Manganese
pg/L
36
36
6
1,530
625.1
95% Adjusted Gamma
810.3
810.3
0.8103
Vanadium
pg/L
32
13
0.175
0.711
0.409
95% KM (t)
0.338
0.338
0.000338
Zinc
/L
1 36
18
2.738
39
10.21
95% GROS Approximate Gamma
9.683
9.683
0.009683
Data evaluated includes data horn 2015 to 2nd quarter 2018, unless otherwise noted
Notes-
: Calml.tims were not performed due to 1-1, of samples NU - Not Determined
Mean - Arithmeti[ mean UCL - 95% Upper Confi&— Limit
mg/L - milligrams per liter
pg/L - mi[rbgr.ms per liter
Prepared by: HEG Checked by: HES
(.)- Mean [alculated by PmUCL using the Kaplan -Meier (KM) estimation method for non-deteR values: only given for d.bsets with FM less than 100% and that met the minimum sample size and FM requirements fa use with
PmUCL; see note (b).
(b)- S.m Ple size was greater man or equal to 1b ma the number or da—d values was greater roan a equal W b, taererore, a 9— UUL was c.lml.ted by Prout;L. I ne ULL sr— is the one recommended by Prout;L. it more man one
UCL was recommended, the hioher UCL was s 1,bted. PmUCL. version 5.0
(c) - 0 is defined as a number of samples analyzed br the frequenry of Jet Ubn among samples.
he 9— UCL values are [al[ubte0 using the R—L sbttware (V. S.0; USEPA, 2013.). 1 he R—L sbttware performs a goodness-ar-Yit test b.t..... nts for data sets wibout any mmdeteR observatims, as well as data sets win, nm-dete[t observations.
eterm The -11 .re thm dines the distret ibution of the data sfor whi[h the EPC is being derived (e.g., normal, Imp-1, gamma, br nmsco -dirn.ble), and thm colmlates a cose nrvative and stable 95% UCL value in —cods[r .— with the ftmn—k deibed in
er 'Calowaticg uppConfidence Limits roocentr t Exp... Poict Conations at Hazardous waste sites" (USEPA, 2002b). The software icditd- numerous algotltnms for caicuiating 95% UCL values, and pi- a recommended UCL value b—d on the algotltnm that
is ost appli[.ble W the statistical distiibutim bf the dab set. PmUCL will c.lml.te a 95% UCL where there are 3 m mare total samples with deteRed concentrations. Where too few samples br detxts are available, the maximum & ted cbnrentratibn is used
as the EW.

TABLE 3-2
SUMMARY OF EXPOSURE POINT CONCENTRATIONS
HUMAN HEALTH - GROUNDWATER (TRANSITION/BEDROCK)
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Constituent
Reporting
Units
Number of
Samples
Frequency of
Detection
Minimum
Detected
Concentration
Maximum
Detected
Concentration
Mean of
Detected
Concentration
UCL Selected
UCL
Exposure Point
Concentration
Exposure Point
Concentration
m L
Antimony
pg/L
479
8
0.13
3.68
1.49
95% KM (t)
0.191
0.191
0.000191
Arsenic
pg/L
479
62
0.28
143
11.47
950 KM (Chebychev)
4.012
4.012
0.004012
Barium
pg/L
479
416
1.845
1,080
72.97
950 KM (Chebychev)
90.88
90.88
0.09088
Boron
pg/L
479
127
3
5,090
1,026
950 KM (Chebychev)
419.2
419.2
0.4192
Cadmium
pg/L
479
20
0.037
2.19
0.331
KM H
0.0802
0.0802
0.0000802
Chromium (Total)
pg/L
479
47
0.383
53
4.518
KM H
0.896
0.896
0.000896
Chromium (VI)
pg/L
174
89
0.025
3.7
0.292
KM H
0.156
0.156
0.000156
Cobalt
pg/L
367
58
0.404
6.71
2.692
KM H
0.898
0.898
0.000898
Lithium
pg/L
125
45
1 1.672
24
6.526
KM H
4.864
4.864
0.004864
Manganese
pg/L
398
370
5
6,960
614.8
950 KM (Chebychev)
801.4
801.4
0.8014
Molybdenum
pg/L
367
223
0.358
269
10.23
950 KM (Chebychev)
10.54
10.54
0.01054
Selenium
pg/L
479
10
0.395
150
15.84
950 KM (Chebychev)
2.377
2.377
0.002377
Strontium
pg/L
270
270
57
3,070
498.4
950 Chebychev (Mean, Sd)
667.5
667.5
0.6675
Thalliumu
pg/L
479
7
0.012
0.361
0.133
950 KM (t)
0.0889
0.0889
0.0000889
Vanadim
pg/L
278
188
0.134
23.3
1.553
950 KM (Chebychev)
1.713
1.713
0.001713
Zinc
I pg/L
1 398
137
1.973
110
14.96
950 KM (Chebychev)
9.762
9.762
0.009762
Data evaluated Includes data ft- 2015 to 2nd quarter 2018, unless otherwise noted
Notes•
- -: Calculations were not performed due to lack of samples ND - Nat Determined
Mean - Arithmetic mean UCL - 95% Upper Cmfidenre Limit
mg/L - milligrams per liter
pg/L - micrograms per liter
Prepared by: HEG Checked by: HES
(a)- Mean [al[ulnted by PmUCL using the Kaplan -Meier (KM) estimation method for non-deteR values: only given for dabsets with FM less than 100% and that met the minimum sample size and FM requirements fa use with
PmUCL; see note (b).
(b)- Sample size was greater man or equal to 1p ono the number or da-d values was greater tnan a equal m b, mererore, a 9- UUL was [mmlated by Prout;L. I ne ULL sm-n is the one remmmmded by Prout;L. it more man one
UCL was recommended. the hioher UCL was seleRed. PmUCL. version 5.0
N- 0 is defined as a number of samples analyzed or the freque by of der Ubn among samples.
- he 9- UCL values are [al[ubte0 using the R-L software (V. S.0; USEPA, 2013a). 1 he R-L software performs a goodness-bf-tit test that accounts to data sets witb- any non-deteR observ,bm,, as well as data sets wib nm-detect observations.
The -ft -thm determines the distribution of the dab set for which the EPC is being derived (e.g., normal, lognormal, gamma, or nm-discornable), and thm [almlates a conservative and stnble 95% UCL value in a[mrdan- with the homework described in
"Calculaer ting uppConfidence Limits rot Exposure P-t Concentrations at Hazardous waste sites" (USEPA, 2002b). The software Includes numerous algorithms for calculating 95% UCL values, arid pr-d- a recommended UCL value b-d on the algorithm that
ost applicable b the statistical distiibutim of the dab set. PmUCL will ,lml.t. a 95% UCL where there are 3 or more btal samples with deteRed .n rtrations. Where W. few samples or detxts are available, the maximum deteRed con-ntiation is used
as the ETC.

TABLE 3-3
SUMMARY OF EXPOSURE POINT CONCENTRATIONS
HUMAN HEALTH - OFFSITE SEDIMENT
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Minimum
Maximum
Exposure Point
Reporting
Number of
Frequency
Mean Detected
Constituent
Units
Samples
of Detection
Detected
Concentration
Detected
Concentration
Concentration
UCL Selected
UCL
Concentration
(mg/kg)
Cobalt
mg/kg
1 3
1 3
1 1.5
1 6.1
1 3.7
1 ---
6.1
Man anese
I mg/kg
1 3
1 3
1 120
1 480
1 327.7
1 ---
I ---
1 480
* Data evaluated includes data from 2015 to 2nd quarter 2018, unless otherwise noted
Notes:
---: Calculations were not performed due to lack of samples ND - Not Determined
Mean - Arithmetic mean UCL - 95 % Upper Confidence Limit
mg/kg - milligrams per kilogram
Prepared by: HEG Checked by: HES
(a)- Mean calculated by ProUCL using the Kaplan -Meier (KM) estimation method for non -detect values: only given for datasets with FOD less than 100 % and that met the minimum sample size and FOD requirements for use with ProUCL; see note
( b ) .
(b)- Sample size was greater than or equal to 10 and the number of detected values was greater than or equal to 6, therefore, a 95 % UCL was calculated by ProUCL. The UCL shown is the one recommended by ProUCL. If more than one UCL was
recommended, the higher UCL was selected. ProUCL, version 5.0
(c) - 0 is defined as a number of samples analyzed or the frequency of detection among samples.
(d) - I he 95 % UCL values are calculated using the ProUCL software (V. 5.U; UbLPA, 2U13a). I he ProUCL software performs a goodness-ot-tit test that accounts for data sets without any non -detect observations, as well as data sets with non -
detect observations. The software then determines the distribution of the data set for which the EPC is being derived (e.g., normal, lognormal, gamma, or non -discernable), and then calculates a conservative and stable 95 % UCL value in
accordance with the framework described in "Calculating Upper Confidence Limits for Exposure Point Concentrations at Hazardous Waste Sites" (USEPA, 2002b). The software includes numerous algorithms for calculating 95 % UCL values, and
provides a recommended UCL value based on the algorithm that is most applicable to the statistical distribution of the data set. ProUCL will calculate a 95 % UCL where there are 3 or more total samples with detected concentrations. Where too
few samples or detects are available, the maximum detected concentration is used as the EPC.

TABLE 3-4
SUMMARY OF EXPOSURE POINT CONCENTRATIONS
HUMAN HEALTH - ONSITE SEDIMENT
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Minimum
Maximum
Exposure Point
Reporting
Number of
Frequency
Mean Detected
Constituent
Units
Samples
of Detection
Detected
Concentration
Detected
Concentration
Concentration
UCL Selected
UCL
Concentration
(mg/kg)
Cobalt
I mg/kg
1 3
1 3
1 3.4
1 7.4
1 5.1
1 ---
7.4
Man anese
I mg/kg
1 3
1 3
1 186
1 610
1 452.7
1 ---
I ---
1 610
* Data evaluated includes data from 2015 to 2nd quarter 2018, unless otherwise noted
Notes:
---: Calculations were not performed due to lack of samples ND - Not Determined
Mean - Arithmetic mean UCL - 95 % Upper Confidence Limit
mg/kg - milligrams per kilogram
Prepared by: HEG Checked by: TCP
(a)- Mean calculated by ProUCL using the Kaplan -Meier (KM) estimation method for non -detect values: only given for datasets with FOD less than 100 % and that met the minimum sample size and FOD requirements for use
with ProUCL; see note (b).
(b)- Sample size was greater than or equal to 10 and the number of detected values was greater than or equal to 6, therefore, a 95 % UCL was calculated by ProUCL. The UCL shown is the one recommended by ProUCL. If
more than one UCL was recommended, the higher UCL was selected. ProUCL, version 5.0
(c) - 0 is defined as a number of samples analyzed or the frequency of detection among samples.
(d) - I he 95 % UCL values are calculated using the ProUCL software (V. 5.U; UbLPA, 2U13a). I he ProUCL software performs a goodness-ot-tit test that accounts for data sets without any non -detect observations, as well as data sets with non -detect
observations. The software then determines the distribution of the data set for which the EPC is being derived (e.g., normal, lognormal, gamma, or non -discernable), and then calculates a conservative and stable 95 % UCL value in accordance with
the framework described in "Calculating Upper Confidence Limits for Exposure Point Concentrations at Hazardous Waste Sites" (USEPA, 2002b). The software includes numerous algorithms for calculating 95 % UCL values, and provides a
recommended UCL value based on the algorithm that is most applicable to the statistical distribution of the data set. ProUCL will calculate a 95 % UCL where there are 3 or more total samples with detected concentrations. Where too few samples or
detects are available, the maximum detected concentration is used as the EPC.

TABLE 3-5
SUMMARY OF EXPOSURE POINT CONCENTRATIONS
HUMAN HEALTH - OFFSITE SURFACE WATER
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Constituent
Reporting
Units
Number of
Samples
Frequency of
Detection
Minimum
Detected
Concentration
Maximum
Detected
Concentration
Mean Detected
Concentration
UCL Selected
UCL
Exposure Point
Concentration
Exposure Point
Concentration
m L
Aluminum
pg/L
20
20
61
590
160
95% Adjusted Gamma
213.4
213.4
0.2134
Boron
pg/L
20
20
422
1,110
808.8
95%Student's-t
892.5
892.5
0.8925
Chromium (VI)
pg/L
17
2
0.038
1.6
0.819
---
---
1.6
0.0016
Cobalt
pg/L
20
19
0.891
3.05
1.516
95% KM (BCA)
1.756
1.756
0.001756
Manganese
pg/L
20
20
745
8,330
2,174
95% H
2,954
2954
2.954
Zinc
/L
20
13
3.072
10
5.869
95% KM t
6.009
6.009
0.006009
Data evaluated includes data trom 2015 to 2nd quarter 201S, unless otherwise noted
Notes:
---: Calculations were not performed due to lack of samples NO - Not Determined
Mean - Arithmetic mean UCL - 95% Upper Confidence Limit
mg/L - milligrams per liter
pg/L - micrograms per liter
Prepared by: HEG Checked by: HES
(a)- Mean calculated by ProUCL using the Kaplan -Meier (KM) estimation method for non -detect values: only given for datasets with FOD less than 100 % and that met the minimum sample size and FOD requirements for use with ProUCL; see note (b).
(b)- Sample size was greater than or equal to 10 and the number of detected values was greater than or equal to 6, therefore, a 95% UCL was calculated by ProUCL. The UCL shown is the one recommended by ProUCL. If more than one UCL was recommended, the
higher UCL was selected. ProUCL, version 5.0
(c) - 0 is defined as a number of samples analyzed or the frequency of detection among samples.
(d) - The 95% UCL values are calculated using the ProUCL software (V. 5.0; USEPA, 2013a). The ProUCL software performs a goodness -of -fit test that accounts for data sets without any non -detect observations, as well as data sets with non -detect observations. The software then determines
the distribution of the data set for which the EPC is being derived (e.g., normal, lognormal, gamma, or non -discernable), and then calculates a conservative and stable 95% UCL value in accordance with the framework described in "Calculating Upper Confidence Limits for Exposure Point
Concentrations at Hazardous Waste Sites' (USEPA, 2002b). The software includes numerous algorithms for calculating 95% UCL values, and provides a recommended UCL value based on the algorithm that is most applicable to the statistical distribution of the data set. ProUCL will calculate a
95% UCL where there are 3 or more total samples with detected concentrations. Where too few samples or detects are available, the maximum detected concentration is used as the EPC.

TABLE 3-6
SUMMARY OF EXPOSURE POINT CONCENTRATIONS
HUMAN HEALTH -ONSITE SURFACE WATER
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Constituent
Reporting
Units
Number of
Samples
Frequency
of Detection
Minimum
Detected
Concentration
Maximum
Detected
Concentration
Mean Detected
Concentration
UCL Selected
UCL
Exposure Point
Concentration
Exposure Point
Concentration
m L
Aluminum
pg/L
25
25
11
965
140.1
95% H-UCL
221
221
0.2206
Boron
pg/L
25
25
637
1,510
1,183
95%Student's-t
1,247
1,247
1.247
Chromium (VI)
pg/L
14
1
0.36
0.36
0.36
---
---
0.36
0.00036
Cobalt
pg/L
18
13
0.541
6.29
1.776
95% KM (Chebychev)
3.015
3.015
0.003015
Manganese
pg/L
25
25
536
4,370
1,071
95% Modified-t UCL
1,358
1,358
1.358
Zinc
/L
25
12
2.7
19
7.009
95% GROS Adjusted Gamma UCL
7.206
7.206
0. 007206
* Data evaluated includes data from 2015 to 2nd quarter 2018, unless otherwise noted Prepared by: HEG Checked by: TCP
Notes:
---: Calculations were not performed due to lack of samples NO - Not Determined
Mean - Arithmetic mean UCL - 95% Upper Confidence Limit
mg/L - milligrams per liter
pg/L - micrograms per liter
(a)- Mean calculated by ProUCL using the Kaplan -Meier (KM) estimation method for non -detect values: only given for datasets with FOD less than 100 % and that met the minimum sample size and FOD requirements for use with ProUCL; see note (b)
(b)- Sample size was greater than or equal to 10 and the number of detected values was greater than or equal to 6, therefore, a 95% UCL was calculated by ProUCL. The UCL shown is the one recommended by ProUCL. If more than one UCL was recommended, the higher UCL was
selected. ProUCL, version 5.0
(c) - 0 is defined as a number of samples analyzed or the frequency of detection among samples.
(d) - The 95% UCL values are calculated using the ProUCL software (V. 5.0; USEPA, 2013a). The ProUCL software performs a goodness -of -fit test that accounts for data sets without any non -detect observations, as well as data sets with non -detect observations. The software then determines the
distribution of the data set for which the EPC is being derived (e.g., normal, lognormal, gamma, or non -discernable), and then calculates a conservative and stable 95% UCL value in accordance with the framework described in "Calculating Upper Confidence Limits for Exposure Point Concentrations at
Hazardous Waste Sites' (USEPA, 2002b). The software includes numerous algorithms for calculating 95% UCL values, and provides a recommended UCL value based on the algorithm that is most applicable to the statistical distribution of the data set. ProUCL will calculate a 95% UCL where there are 3 or
more total samples with detected concentrations. Where too few samples or detects are available, the maximum detected concentration is used as the EPC.

TABLE 4-1
SUMMARY OF EXPOSURE POINT CONCENTRATIONS
ECOLOGICAL - SEDIMENT - CRUTCHFIELD BRANCH
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Minimum
Maximum
Mean
Exposure Point
Reporting
Number of
Frequency of
Constituent
Units
Samples
Detection
Detected
Detected
Detected
UCL Selected
UCL
Concentration
Concentration
Concentration
Concentration
(mg/kg)
Barium
mg/kg
1 6
1 6
1 18
1 98.2
1 45.93
1 --
---
98.2
Chromium (Total)
I mg/kg
1 6
1 6
1 4.8
1 94.4
1 26.38
1 --
--
94.4
Man anese
I mg/kg
1 6
1 6
1 120
1 610
1 390.2
1 --
--
610
* Data evaluated includes data from 2015 to 2nd quarter 2018, unless otherwise noted
Notes:
---: Calculations were not performed due to lack of samples pg/L - micrograms per liter
Mean - Arithmetic mean UCL - 95% Upper Confidence Limit
mg/kg - milligrams per kilogram
Prepared by: HEG Checked by: HES
(a)- Sample size was greater than or equal to 10 and the number of detected values was greater than or equal to 6, therefore, a 95% UCL was calculated by ProUCL. The UCL shown is the one recommended by ProUCL. If more than one UCL was
recommended, the higher UCL was selected. ProUCL, version 5.0
(b) - 0 is defined as a number of samples analyzed or the frequency of detection among samples.
(c) - The 95% UCL values are calculated using the ProUCL software (V. 5.0; USEPA, 2013a). The ProUCL software performs a goodness -of -fit test that accounts for data sets without any non -detect observations, as well as data sets with non -detect
observations. The software then determines the distribution of the data set for which the EPC is being derived (e.g., normal, lognormal, gamma, or non-discemable), and then calculates a conservative and stable 95% UCL value in accordance with
the framework described in "Calculating Upper Confidence Limits for Exposure Point Concentrations at Hazardous Waste Sites' (USEPA, 2002b). The software includes numerous algorithms for calculating 95% UCL values, and provides a
recommended UCL value based on the algorithm that is most applicable to the statistical distribution of the data set. ProUCL will calculate a 95% UCL where there are 3 or more total samples with detected concentrations. Where too few samples or
detects are available, the maximum detected concentration is used as the EPC.

TABLE 4-2
SUMMARY OF EXPOSURE POINT CONCENTRATIONS
ECOLOGICAL - SURFACE WATER-CRUTCHFIELD BRANCH
MAYO STEAM STATION
DUKE ENERGY CAROLINAS, LLC, ROXBORO, NC
Minimum
Maximum
Mean
Exposure Point
Reporting
Number of
Frequency of
Exposure Point
Constituent
Units
Samples
Detection
Detected
Detected
Detected
UCL Selected
UCL
Concentration
Concentration
Concentration
Concentration
Concentration
(mg/L)
Aluminum
ug/L
1 44
1 44
1 11
1 965
1 149.7
1 95% H-UCL
198.6
198.6
0.1986
Manganese
I pg/L
1 44
1 44
1 536
1 8,330
1 1,561
1 951/o Chebyshev (Mean, Sd) UCL
2,501
2,501
2.501
Mercur
/L
1 44
1 28
1 0.00124
1 0.023
1 0.00351
1 95% H-UCL
0.00389
0.00389
0.00000389
Data evaluated includes data from 2015 to 2nd quarter 2018, unless otherwise noted
Notes:
---: Calculations were not performed due to lack of samples pg/L - micrograms per liter
Mean - Arithmetic mean UCL - 95% Upper Confidence Limit
mg/L - milligrams per liter
Prepared by: HEG Checked by: HES
(a)- Sample size was greater than or equal to 10 and the number of detected values was greater than or equal to 6, therefore, a 95% UCL was calculated by ProUCL. The UCL shown is the one recommended by ProUCL. If more than one UCL was recommended, the higher
UCL was selected. ProUCL, version 5.0
(b) - 0 is defined as a number of samples analyzed or the frequency of detection among samples.
(c) - The 95% UCL values are calculated using the ProUCL software (V. 5.0; USEPA, 2013a). The ProUCL software performs a goodness -of -fit test that accounts for data sets without any non -detect observations, as well as data sets with non -detect observations. The
software then determines the distribution of the data set for which the EPC is being derived (e.g., normal, lognormal, gamma, or non -discernable), and then calculates a conservative and stable 95% UCL value in accordance with the framework described in "Calculating
Upper Confidence Limits for Exposure Point Concentrations at Hazardous Waste Sites" (USEPA, 2002b). The software includes numerous algorithms for calculating 95% UCL values, and provides a recommended UCL value based on the algorithm that is most applicable to
the statistical distribution of the data set. ProUCL will calculate a 95% UCL where there are 3 or more total samples with detected concentrations. Where too few samples or detects are available, the maximum detected concentration is used as the EPC.

TABLE 5-1
SUMMARY OF ON -SITE SEDIMENT EPC/RBC COMPARISON
ON -SITE TRESPASSER - ADOLESCENT (AGE 6 to <16)
MAYO STEAM ELECTRIC PLANT
DUKE ENERGY PROGRESS, LLC ROXBORO, NC
COPC
CAS
Risk -Based Concentration
Sediment
Risk Ratio
Non -Cancer
Cancer
Final
Basis
Exposure
Point
Concentration
Non -Cancer
Cancer
(mg/kg)
(mg/kg)
(mg/kg)
(mg/kg)
Cobalt
7440-48-4
1 1.1E+04
I
1.1E+04
I nc
1 7
0.001
nc
Man anese
7439-96-5
1 5.0E+05
I nc
I 5.0E+05
I nc
1 610
0.001
nc
Cumulative
Risk
1 0.002
1 0.0E+00
Notes:
COPC - Chemical of potential concern
c - Remedial goal based on cancer risk
nc - Remedial goal based on non -cancer hazard index
Incidental Ingestion
Dermal Contact
Particulate Inhalation
Ambient Vapor Inhalation
Exposure Routes Evaluated
No
Yes
No
No
Target Hazard Index (per Chemical) 1E+00
Target Cancer Risk (per Chemical) 1E-04
Prepared by: HHS Checked by: TCP
Page 1of1

TABLE 5-2
SUMMARY OF ON -SITE SURFACE WATER EPC/RBC COMPARISON
ON -SITE TRESPASSER - ADOLESCENT (AGE 6 to <16)
MAYO STEAM ELECTRIC PLANT
DUKE ENERGY PROGRESS, LLC ROXBORO, NC
COPC
CAS
Risk -Based Concentration
Surface Water
Risk Ratio
Non -Cancer
Cancer
Final
Basis
Exposure Point
Concentration
Non -Cancer
Cancer
(mg/L)
(mg/L)
(mg/L)
(mg/L)
Aluminum
7429-90-5
1.3E+04
nc
1.3E+04
nc
0.2
0.00002
nc
Boron
7440-42-8
2.6E+03
nc
2.6E+03
nc
1
0.0005
nc
Chromium (VI)
18540-29-9
1.7E+00
2.6E-01
2.6E-01
c
0.0004
0.001
0.0014
Cobalt
7440-48-4
4.6E+00
nc
4.6E+00
nc
0.003
0.001
nc
Manganese
7439-96-5
2.4E+02
nc
2.4E+02
nc
1
0.006
nc
Zinc
7440-66-6
4.4E+03
nc
4.4E+03
nc
0.01
0.000002
nc
Cumulative Risk
0.01
1.4E-03
Prepared by: HHS Checked by: TCP
Notes•
COPC - Chemical of potential concern
c - Remedial goal based on cancer risk NA - No toxicity value available; remedial goal not calculated
nc - Remedial goal based on non -cancer hazard index NC - Not Calculated
(a) Final RBC value for lead is 15 ug/L or surface/seep water exposures. Refer to Attachment D, Section 2.5 of the Mayo Steam Electric Plant CAP (SynTerra 2015).
(b) Lead was not included in the cumulative risk calculation.
Exposure Routes Evaluated
Incidental Ingestion No
Dermal Contact Yes
Ambient Vapor Inhalation No
Target Hazard Index (per Chemical) 1E+00
Target Cancer Risk (per Chemical) 1E-04
Page 1of1

TABLE 5-3
SUMMARY OF ON -SITE GROUNDWATER EPC/RBC COMPARISON
CONSTRUCTION - CONSTRUCTION WORKER (ADULT)
MAYO STEAM ELECTRIC PLANT
DUKE ENERGY PROGRESS, LLC ROXBORO, NC
COPC
CAS
Risk -Based Concentration
Ash Basin- Surficial
Groundwater
Risk Ratio
Non -Cancer
Cancer
Final
Basis
Exposure Point
Concentration
Non -Cancer
Cancer
(nrl
(nrl
(nrl
(nrl
Antimony
7440-36-0
1.7E+01
nc
1.7E+01
nc
0.002
0.0001
nc
Boron
7440-42-8
1.9E+04
nc
1.9E+04
nc
0.9
0.00005
nc
Chromium, Total
7440-47-3
8.6E+03
nc
8.6E+03
nc
0.002
0.0000002
nc
Chromium (VI)
18540-29-9
2.8E+01
7.6E+01
2.8E+01
nc
0.0002
0.00001
nc
Cobalt
7440-48-4
3.3E+02
nc
3.3E+02
nc
0.003
0.00001
nc
Manganese
7439-96-5
2.2E+03
nc
2.2E+03
nc
0.8
0.0004
nc
Vanadium
7440-62-2
9.6E+02
nc
9.6E+02
nc
0.0003
0.0000004
nc
Zinc
7440-66-6
1 3.1E+04
I nc
1 3.1E+04
nc
1 0.01
1 0.0000003
1 nc
Cumulative Risk
1 0.001
1 0.00E+00
Prepared by: HHS Checked by: TCP
COPC
CAS
Risk -Based Concentration
Ash Basin
Transition/Bedrock
Groundwater
Risk Ratio
Non -Cancer
Cancer
Final
Basis
Exposure Point
Concentration
Non -Cancer
Cancer
(ni
(mg/L)
(nrl
(nrl
Antimony
7440-36-0
1.7E+01
nc
1.7E+01
nc
0.0002
0.00001
nc
Arsenic
7440-38-2
2.9E+01
4.5E+02
2.9E+01
nc
0.004
0.0001
nc
Barium
7440-39-3
5.0E+03
nc
5.0E+03
nc
0.09
0.00002
nc
Boron
7440-42-8
1.9E+04
nc
1.9E+04
nc
0.4
0.00002
nc
Cadmium
7440-43-9
1.0E+01
nc
1.0E+01
nc
0.0001
0.00001
nc
Chromium, Total
7440-47-3
8.6E+03
nc
8.6E+03
nc
0.001
0.0000001
nc
Chromium (VI)
18540-29-9
2.8E+01
7.6E+01
2.8E+01
nc
0.0002
0.00001
nc
Cobalt
7440-48-4
3.3E+02
nc
3.3E+02
nc
0.001
0.000003
nc
Lithium
7439-93-2
NA
0.005
NC
nc
Manganese
7439-96-5
2.2E+03
nc
2.2E+03
nc
0.8
0.0004
nc
Molybdenum
7439-98-7
4.8E+02
nc
4.8E+02�nLc
0.01
0.00002
nc
Selenium
7782-49-2
4.8E+02
nc
4.8E+020.002
0.000005
nc
Strontium
7440-24-6
1.9E+05
nc
1.9E+05
0:7
0.000003
nc
Thallium
7440-28-0
NA
0.0001
NC
nc
Vanadium
7440-62-2
9.6E+02
nc
9.6E+02 nc
0.002
0. 000002
nc
Zinc
7440-66-6
3.1E+04
nc
3.1E+04 nc
0.01
0.0000003
nc
Cumulative Risk
1 0.001
0.00E+00
Prepared by: HHS Checked by: TCP
Notes:
COPC - Chemical of potential concern NA - No toxicity value available; remedial goal not calculated
c - Remedial goal based on cancer risk NC - Not Calculated
nc - Remedial goal based on non -cancer hazard index
Exposure Routes Evaluated
Incidental Ingestion Yes
Dermal Contact Yes
Ambient Vapor Inhalation No
Target Hazard Index (per Chemical) IE+00
Target Cancer Risk (per Chemical) 1E-04
Page 1of1

TABLE 5-4
SUMMARY OF OFF -SITE SEDIMENT EPC/RBC COMPARISON
RECREATIONAL WADER - CHILD, ADOLESCENT, and ADULT
MAYO STEAM ELECTRIC PLANT
DUKE ENERGY PROGRESS, LLC ROXBORO, NC
COPC
CAS
Risk -Based Concentration
Sediment
Risk Ratio
Non -Cancer
Cancer
Final
Basis
Exposure Point
Concentration
Non -Cancer
Cancer
(mg/kg)
(mg/kg)
(mg/kg)
(mg/kg)
Cobalt
7440-48-4
3.7E+03
nc
3.7E+03
nc
6
0.002
nc
Manganese
7439-96-5
1 1.7E+06
I
1.7E+06
I nc
1 480
1 0.0003
F nc
Cumulative
Risk
0.002
0.00E+00
Notes:
COPC - Chemical of potential concern
c - Remedial goal based on cancer risk
nc - Remedial goal based on non -cancer hazard index
Incidental Ingestion
Dermal Contact
Particulate Inhalation
Ambient Vapor Inhalation
Exposure Routes Evaluated
Yes
Yes
No
No
Target Hazard Index (per Chemical) 1E+00
Target Cancer Risk (per Chemical) 1E-04
Prepared by: HHS Checked by: TCP
Page 1of1

TABLE 5-5
SUMMARY OF OFF -SITE SURFACE WATER EPC/RBC COMPARISON
RECREATIONAL WADER - CHILD, ADOLESCENT, and ADULT
MAYO STEAM ELECTRIC PLANT
DUKE ENERGY PROGRESS, LLC ROXBORO, NC
COPC
CAS
Risk -Based Concentration
Surface Water
Risk Ratio
Non -Cancer
Cancer
Final
Basis
Exposure
Point
Concentra
Non -Cancer
Cancer
r_(M_9 / L)
(mg/L)
(mg/L)
(mg/L)
Aluminum
7429-90-5
1.2E+03
nc
1.2E+03
nc
0.2
0.000
nc
Boron
7440-42-8
2.4E+02
nc
2.4E+02
nc
0.9
0.004
nc
Chromium (VI)
18540-29-9
9.5E-01
8.3E-02
8.3E-02
c
0.002
0.002
1.9E-02
Cobalt
7440-48-4
3.6E-01
nc
I 3.6E-01
nc
0.002
0.005
nc
Manganese
7439-96-5
1 9.0E+01
I nc
I 9.0E+01
I nc
1 3
0.03
nc
Zinc
7440-66-6
1 3.6E+02
I nc
I 3.6E+02
I nc
1 0.006
1 0.00002
1 nc
Cumulative Risk
10.04
11.9E-02
Notes:
COPC - Chemical of potential concern
c - Remedial goal based on cancer risk
nc - Remedial goal based on non -cancer hazard index
Exposure Routes Evaluated
Incidental Ingestion
Dermal Contact
Ambient Vapor Inhalation
Target Hazard Index (per Chemical)
Target Cancer Risk (per Chemical)
NA - No toxicity value available; remedial goal not calculated
NC - Not Calculated
Yes
Yes
No
1E+00
1E-04
Prepared by: HHS Checked by: TCP
Page 1of1

TABLE 5-6
SUMMARY OF RISK ESTIMATES
MAYO STEAM ELECTRIC PLANT
DUKE ENERGY PROGRESS, LLC ROXBORO, NC
Source Table
(PRG Tables)
Media
Exposure Pathway
Risk Ratio -
Non - cancer
Risk Ratio -
Cancer
TABLE 5-1
Sediment - On -Site
ON -SITE TRESPASSER - ADOLESCENT (AGE 6-<16)
0.002
0.00E+00
TABLE 5-2
Surface Water - On -site
ON -SITE TRESPASSER - ADOLESCENT (AGE 6-<16)
0.008
1.36E-03
TABLE 5-3
Groundwater-Surficial Aquifer
CONSTRUCTION - CONSTRUCTION WORKER (ADULT)
0.001
0.00E+00
Groundwater -Transition /Bedrock
1CONSTRUCTION - CONSTRUCTION WORKER (ADULT)
0.001
0.00E+00
TABLE 5-4
Sediment- Off -Site
OFF -SITE RECREATIONAL WADER - CHILD, ADOLESCENT, and ADULT
0.002
0.00E+00
TABLE 5-5
Surface Water- Off -Site
OFF -SITE RECREATIONAL WADER - CHILD ADOLESCENT and ADULT
0.04
1.92E-02
Prepared by: HHS Checked by: TCP
Page 1of1

Table 1
Exposure Parameters for Ecological Receptors
Crutchfield Branch
Baseline Ecological Risk Assessment
Duke Energy
Mayo Steam Electric Plant, Roxboro, NC
Parameter
Body Weight
Food Ingestion Rate
Water Ingestion
Rate
Dietary Composition
Home
Range
Seasonal Use
Factor
Plants
Mammaerr.
Vertebratrates
Fish
Invertebrates
Birds
Soil
Algorithm ID
BW
IRF
IRw
PF
AM
AF
A,
AB
SF
HR
SUF
Units
kg
kg/kg BW/day
L/kg BW/day
%
%
%
%
%
%
hectares
unitless
HERBIVORE
Meadow Vole
0.033
0.33
0.21
97.6%
0%
0%
0%
0%
2.4%
0.027
1
Muskrat
1.17
0.3
0.97
99.3%
0%
0%
0%
0%
0.7%
0.13
1
N
OMNIVORE
a
Mallard Duck`
1.134
0.068
0.057
48.3%
0%
0%
48.3%
0%
3.3%
435
1
v
American Robin
0.08
0.129
0.14
40%
0%
0%
58%
0%
2%
0.42
1
CARNIVORE
Red -Tailed Hawke
1.06
0.18
0.058
0%
91.5%
0%
0%
8.5%
0%
876
1
0
o
Bald Eagle'
3.75
0.12
0.058
0%
28%
58%
0%
13.5%
0.5%
2199
1
Red Fox'
4.54
0.16
0.085
6%
89%
0%
2%
0%
3%
1226
1
PISCIVORE
River Otter'
6.76
0.19
0.081
0%
1 0%
100%
0%
0%
0%
348
1
Great Blue Heron'
1 2.229
1 0.18
1 0.045
1 0%
1 0%
1 90%
1 9.5%
1 0%
1 0.5%
227
1 1
NOTES:
BW - Body Weight PF - Plant Matter Ingestion Percentage kg/kg BW/day - Kilograms Food per Kilograms Body Weight per Day
kg - Kilograms AM - Mammal/Terrestrial Vertebrate ingestion percentage L/kg BW/day - Liters Water per Kilogram Body Weight per Day
IR - Ingestion Rate AF - Fish Ingestion Percentage
HR- Home Range AB- Bird Ingestion Percentage
SUF - Seasonal Use Factor SF - Soil Ingestion Percentage
a BW, IRf, IRw, PF, HR from USEPA 1993 (sections 2-328 and 2-329); SF from Sample and Suter 1994
n BW, IRf, IRw, PF, HR from USEPA 1993 (sections 2-340 and 2-341); SF from TechLaw Inc. 2013; IRF from Nagy 2001
BW, PF, A,, HR from USEPA 1993 (sections 2-43 and 2-45); SF from Beyer et al. 1994; IRF from Nagy 2001
d BW, PF, Al, HR from USEPA 1993 (sections 2-197 and 2-198); SF from Sample and Suter 1994; IRF from Nagy 2001
e BW, PF, AM, AB, IRF, HR from USEPA 1993 (sections 2-82 and 2-83)
f BW, PF, AD AM, AB, HR from USEPA 1993 (sections 2-91 and 2-97); IRF from Nagy 2001
' BW, PF, AD Al, HR from USEPA 1993 (sections 2-224 and 2-225); SF from Beyer et al. 1994
h BW, IRw, AD HR from USEPA 1993 (sections 2-264 and 2-266); SF from Sample and Suter 1994; IRF from Nagy 2001
BW, PF, AD Al, HR from USEPA 1993 (sections 2-8 and 2-9); SF from Sample and Suter 1994; IRF from Nagy 2001
j Seasonal Use Factor is set to a default of 1 to be overly conservative and protective of ecological receptors.

Table 2
Toxicity Reference Values for Ecological Receptors
Crutchfield Branch
Baseline Ecological Risk Assessment
Duke Energy
Mayo Steam Electric Plant, Roxboro, NC
Analyte
TRVs (NOAEL)
Aquatic
Terrestrial
Mallard Duck
(mg/kg/day)
Great Blue
Heron
(mg/kg/day)
Bald Eagle
(mg/kg/day)
Muskrat
(mg/kg/day)
River Otter
(mg/kg/day)
American
Robin
(mg/kg/day)
Red -Tailed
Hawk
(mg/kg/day)
Meadow Vole
(mg/kg/day)
Red Fox
(mg/kg/day)
Aluminum'
110
110
110
1.93
1.93
110
110
1.93
1.93
Antimony'
NA
NA
NA
0.059
0.059
NA
NA
0.059
0.059
ArseniCb
2.24
2.24
2.24
1.04
1.04
2.24
2.24
1.04
1.04
Barium`
20.8
20.8
20.8
51.8
51.8
20.8
20.8
51.8
51.8
Beryllium'
NA
NA
NA
0.532
0.532
NA
NA
0.532
0.532
Boron''b
28.8
28.8
28.8
28
28
28.8
28.8
28
28
Cadmium'
1.47
1.47
1.47
0.77
0.77
1.47
1.47
0.77
0.77
Calcium
EN
EN
EN
EN
EN
EN
EN
EN
EN
Chromium, Total'
1
1
1
2740
2740
1
1
2740
2740
Chromium VI (hexavalent)'
NA
NA
NA
9.24
9.24
NA
NA
9.24
9.24
Chromium III'
2.66
2.66
2.66
2.4
2.4
2.66
2.66
2.4
2.4
Cobalt'
7.61
7.61
7.61
7.33
7.33
7.61
7.61
7.33
7.33
Copper'
4.05
4.05
4.05
5.6
5.6
4.05
4.05
5.6
5.6
Iron
EN
EN
EN
EN
EN
EN
EN
EN
EN
Lead
1.63
1.63
1.63
4.7
4.7
1.63
1.63
4.7
4.7
Magnesium
EN
EN
EN
EN
EN
EN
EN
EN
EN
Manganese'
179
179
179
51.5
51.5
179
179
51.5
51.5
Mercury'
3.25
3.25
3.25
1.01
1.01
3.25
3.25
1.01
1.01
MolybdenuMa, d
3.53
3.53
3.53
0.26
0.26
3.53
3.53
0.26
0.26
Nickel'
6.71
6.71
6.71
1.7
1.7
6.71
6.71
1.7
1.7
Potassium
EN
EN
EN
EN
EN
EN
EN
EN
EN
Selenium'
0.29
0.29
0.29
0.143
0.143
0.29
0.29
0.143
0.143
Sodium
EN
EN
EN
EN
EN
EN
EN
EN
EN
Strontium''d
NA
NA
NA
263
263
NA
NA
263
263
Thallium'
NA
NA
NA
0.015
0.015
NA
NA
0.015
0.015
Titanium
NA
NA
NA
NA
NA
NA
NA
NA
NA
Vanadium'
0.344
0.344
0.344
4.16
4.16
0.344
0.344
4.16
4.16
Zinc'
66.1
66.1
66.1
75.4
75.4
66.1
66.1
75.4
75.4
Nitrate'
NA
NA
NA
507
507
NA
NA
507
507

Table 2 (Cont.)
Analyte
TRVs (LOAEL)
Aquatic
Terrestrial
Mallard Duck
(mg/kg/day)
Heron
(mg/kg/day)
Bald Eagle
(mg/kg/day)
Muskrat
(mg/kg/day)
River Otter
(mg/kg/day)
Robin
(mg/kg/day)
Hawk
(mg/kg/day)
Meadow Vole
(mg/kg/day)
Red Fox
(mg/kg/day)
Aluminum'
1100
1100
1100
19.3
19.3
1100
1100
19.3
19.3
Antimony'
NA
NA
NA
0.59
0.59
NA
NA
0.59
0.59
Arsenic'
40.3
40.3
40.3
1.66
1.66
40.3
40.3
1.66
1.66
Barium`
41.7
41.7
41.7
75
75
41.7
41.7
75
75
Beryllium'
NA
NA
NA
6.6
6.6
NA
NA
6.6
6.6
Boron'''
100
100
100
93.6
93.6
100
100
93.6
93.6
Cadmium'
2.37
2.37
2.37
10
10
2.37
2.37
10
10
Calcium
EN
EN
EN
EN
EN
EN
EN
EN
EN
Chromium, Total°
5
5
5
27400
27400
5
5
27400
27400
Chromium VI (hexavalent)'
NA
NA
NA
40
40
NA
NA
40
40
Chromium III'
2.66
2.66
2.66
9.625
9.625
2.66
2.66
9.625
9.625
Cobalt'
7.8
7.8
7.8
10.9
10.9
7.8
7.8
10.9
10.9
Copper'
12.1
12.1
12.1
9.34
9.34
12.1
12.1
9.34
9.34
Iron
EN
EN
EN
EN
EN
EN
EN
EN
EN
Lead'
3.26
3.26
3.26
8.9
8.9
3.26
3.26
8.9
8.9
Magnesium
EN
EN
EN
EN
EN
EN
EN
EN
EN
Manganese'
348
348
348
71
71
348
348
71
71
Mercury'
0.37
0.37
0.37
0.16
0.16
0.37
0.37
0.16
0.16
MolybdenuMa, d
35.3
35.3
35.3
2.6
2.6
35.3
35.3
2.6
2.6
Nickel'
11.5
11.5
11.5
3.4
3.4
11.5
11.5
3.4
3.4
Potassium
EN
EN
EN
EN
EN
EN
EN
EN
EN
Selenium'
0.579
0.579
0.579
0.215
0.215
0.579
0.579
0.215
0.215
Sodium
EN
EN
EN
EN
EN
EN
EN
EN
EN
Strontium''d
NA
NA
NA
2630
2630
NA
NA
2630
2630
Thallium'
NA
NA
NA
0.075
0.075
NA
NA
0.075
0.075
Vanadium'
0.688
0.688
0.688
8.31
8.31
0.688
0.688
8.31
8.31
Zinc'
66.5
66.5
66.5
75.9
75.9
66.5
66.5
75.9
75.9
NitratedI
NA
NA
I NA
1 1130
1130
NA
NA
1130
1130
NOTES:
NOAEL - No Observed Adverse Effects Level
LOAEL - Lowest Observed Effects Level
EN - Essential nutrient
NA - Not available
TRV - Toxicity Reference Value
' CH2M Hill. 2014. Tier 2 Risk -Based Soil Concentrations Protective of Ecological Receptors at the Hanford Site. CHPRC-01311. Revision 2. July.
Http:Hpdw.hanford.gov/arpir/pdf.cfm?accession=0088115
b USEPA 2005 EcoSSL
`Only a single paper (Johnson et al., 1960) with data on the toxicity of barium hydroxide to one avian species (chicken) was identified by USEPA (2005); therefore, an avian TRV could not
be derived and an Eco-SSL could not be calculated for avian wildlife (calculation requires a minimum of three results for two test species). Johnson et al. (1960) reports a subchronic
NOAEL of 208.26 mg/kg/d. The NOAEL was multiplied by an uncertainty factor of 0.1 to derive a very conservative TRV of 20.8 mg/kg/d.
d Sample et al. 1996

Table 3
Exposure Area and Area Use Factors for Ecological Receptors
Crutchfield Branch
Baseline Ecological Risk Assessment
Duke Energy
Mayo Steam Electric Plant, Roxboro, NC
Exposure Point
p
Exposure Areaa
Area Use Factor (AUF)
Mallard
Great Blue
River
Bald
American
Red -Tailed
Meadow
(hectares)
Muskrat
Red Fox
Duck
Heron
Otter
Eagle
Robin
Hawk
Vole
Crutchfield Branch
4.3
0.99%
1.89%
100%
1.24%
0.20%
100%
0.491%
100%
0.35%
NOTES:
a Crutchfield Branch flow northeast from the northeast side of the ash basin. The exposure area includes some on site and off site sample locations.

Table 4
EPCs for Use in the Risk Assessment
Crutchfield Branch
Baseline Ecological Risk Assessment
Duke Energy
Mayo Steam Electric Plant, Roxboro, NC
Terrestrial EPCsa
Aquatic EPCsa, b
COPC
CASRN
Soil EPC Used in Risk
Assessment` (mg/kg)
Seep Water EPC Used in
Risk Assessment (mg/L)
Sediment EPC Used in
Risk Assessment
(mg/kg)
Surface Water EPC Used
in Risk Assessment
(mg/L)
Aluminum
7429-90-5
0.1986
0.1986
Barium
7440-39-3
98.2
98.2
Chromium, Total
7440-47-3
94.4
94.4
Manganese
7439-96-5
610
2.501
610
2.501
Mercury
7439-97-6
0.00000389
0.00000389
Created By: TCP Checked By: HES
NOTES:
COPC - Constituent of Potential Concern
CASRN - Chemical Abstracts Service Registration Number
EPC - Exposure Point Concentration
a EPCs for surface water are based on 95% UCLs. EPCs for sediment are based on maximum detected values.
b Terrestrial EPCs listed are values from the Aquatic EPCs list and are used to evaluate exposure to terrestrial receptor groups in this model.
`Analysis of solids (i.e., soil and sediment) was reported as dry weight.

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a,o�a,�ae,��'�� �o'a aefaen of �o� �o ke eoe�e�a�,�e Rea pro�ett,�e of e<e�ee,�� re<ep�or=.

Table 6
Calculation of Average Daily Doses for Red -Tailed Hawk
Crutchfield Branch
Baseline Ecological Risk Assessment
Duke Energy
Mayo Steam Electric Plant, Roxboro, NC
AVERAGE DAILY DOSE VIA:
WATER
VERTEBRATE PREY
NIRw
ADDw
PT
Pp
NIRf
NIR,
ADD,
BF
ADD,
SUF
AUF
ADDmr
EPCw EPC, EPCm
Food
Area Use
Slope, or
Estimated
Water
Unadjusted
Fraction Diet
Fraction Diet
Ingestion
Vertebrate
Unadjusted
Carnivore
Seasonal Use
Factor
Adjusted Total
Analyze
COPEC in
COPEC in Solid
Vertebrate
Intercept
Concentration in
Ingestion Rate
Average Daily
Terrestrial
Avian
Rate, Wet
Ingestion Rate
Average Daily
Bioavailability'
Intake
Factor
(Exposure
Carnivore
Water (mg/L)
(mg/kg)
Mammals and
Dose Water
Vertebrates
Vertebrates
(kg/k9
Dose
(percent)
Average Daily
Uptake (BAT )'
Birds (mg/kg)
(L/kg BW/day)
(mg/kg/day)
(percent)
(percent)
BW/day)
(mg/kg/day)
(mg/kg/day)
(unities
Area/Home
Dose (mg/kg/day)
W/cla
BW/day)
Range)
Aluminum
0.1986
1
0
0.058
0.01
91.5%
8.5%
0.18
0.18
0
100%
0.01
1
0.0049
0.00006
Barium
98.2
0.7
-1.412
6.04
0.058
0
91.5%
8.5%
0.18
0.18
1.0877441
100%
1.088
1
0.0049
0.005339
Chromium, Total
94.4
0.1444
-1.4599
0.45
0.058
0
1 91.5%
1 8.5%
0.18
1 0.18
1 0.0806180
1 100%
1 0.0806
1
1 0.0049
1 0.0003957
Manganese
2.501
610
0.004
2.44
0.058
0.15
91.5%
8.5%
0.18
0.18
0.4392000
100%
0.58
1
0.0049
0.0029
Mercury
0.00000389
0.058
0.0000002
91.5%
8.5%
0.18
0.18
0
100%
0.0000002
1
0.0049
0.0000000oi
NOTES:
EPC- Exposure Point Concentration BF - Bioavailability Factor SUF -Seasonal Use Factor
NIR- Normalized Ingestion Rate BAF- Bioaccumulaton Factor AUF - Area Use Factor
ADD- Average Daily Dose BCF- Bioconcentration Factor
r Sample et al. 1998a; EPA 2007 EcoSSLs, Aft 41, Table 4a
Bioavail ability is set to a default of 100% to be conservative and protective of ecological receptors.

Table 7
Calculation of Average Daily Doses for Meadow Vole
Crutchfield Branch
Baseline Ecological Risk Assessment
Duke Energy
Mayo Steam Electric Plant, Roxboro, NC
AVERAGE DAILY DOSE VIA:
WATER
PLANTS / VEGETATION
SOIL
NIRµ,
ADDµ,
Pr
NIRr
I NIR,
ADD,
Sr
NIR,
ADD,
BF
ADD,
SUF
AUF
ADD_
EPCw EPC, EPC,
Area Use
Adjusted Total
Estimated'
Water
Unadjusted
Fraction Diet
Food Ingestion
Plant
Unadjusted
Soil Ingestion
Unadjusted
Herbivore
Factor
Herbivore
in
Cter
COPEC in Solid
Slope, or Plant
Concentration in
Average Daily
Rate, Wet
Ingestion
Average Daily
Fraction Diet
Rate (kg
Average Daily
eioavailability�
Seasonal Use
Water (mg/L)
(
(mg/kg)
Uptake (BAF)
Intercept
Vegetation
Ingestion Rate
Dose Water
Plant Matter
(kg kgW/da
Rate, Dry
Dose Plant
Soil (percent)
dry/kg
Dose Soil
(percent)
Intake
Factor
(Exposure
Average Daily
(mg/kg dry)
(L/kg BW/day)
(mg/kg/day)
(percent)
BW/day)
(kg/kg/day)
(mg/kg/day)
BW/day)
(mg/kg/day)
(mg/kg/day)
Area/Home
Dose
Range)
(mg/kg/day)
Aluminum
0.1986
0.0008
0
0.21
0.04
97.6%
0.33
0.048
0
2.4%
0.001
0
100%
0.042
1
1
0.04
Barium
98.2
0.03
L946
0.21
0
97.6%
0.33
0.048
0.142327
L4%
0.001
0.10111
100%
0.243
1
1
0.2434
Chromium, Total
94.4
0.0011
0.1416
0.21
0
97.6%
0.33
0.048
0.006841
2.4%
0.001
0.09719
100%
0.104
1
1
0.104035
Man anew
2.501
610
0.05
30.5
0.21
0.53
97.6%
0.33
0.048
1.473516
2.4%
0.001
0.62806
100%
2.627
1
1
L63
Mercury
0.00000389
1
0.21
0.000001
97.6%
0.33
0.048
0
2.4%
0.001
0
100%
0.000
1
1
0.000001
NOTES:
EPC- Exposure Point Concentration BF- Bioavailability Factor SUF- Seasonal Use Factor
NIR- Normalized Ingestion Rate BAF- Bioaccumulation Factor AUF - Area Use Factor
ADD- Average Daily Dose BCF- Bioconcentation Factor
i Bechtel Jacobs Company 1998a; Baes et al. 1984 (M.); Environmental Restoration Division - Manual ERD-AG-003 1999; default value of I is used for const0uents for which a BAF could not be Found.
Bioavailability is set to a defauk of 100% to be conservative and protective of ecological receptors.

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ew/aayl
a SoaiN
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ladi�a/aayl
ianiiitJ
alvercaoq
o.
mrana
lae/i�a/aavl
race«
lamcH•ssl
ar' usuaccori�
area/ as
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NIR- V oaiiry �aB.xafe _ « n our -amuse tact«
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Table 10
Calcul Mion of Average Daily Doses for Great Blue Heron
Cmtchfield Branch
Baseline Ecological Risk Assessment
Duke Energy
Mayo Steam Electric Plant, Roxboro, NC
NOTES:
EPC- Exposure Point Concentration BF- Bimvailabildy Facia RUF-Reasmal Use F.d.,
NIR-NDrmalized Ingestion Rate RAF-Bi—c...hb. Facia AUF-Area Use Facipr
ADD - Average Daily Dose BCF- ftcm..t,e,.. FaclDr
r Al (VDigt et al. 2015), mean Df fish tissue DA'; Ca (USEPA 1980); Environmental Restoration Division - Manual ERD-AG-0031999.
' Bechtel Jacobs Company 1998b, Table 2, median — for sediment tD beethic invertebrates for As, Cd, Cr, Ca, R& Ni, PI and 1, Sample et A.1998b (earthworms) for Me; default value Df 1 N used for constituents for which a BAE could not be found.
'Bimvaila bilityN sett. a default Df 100% tD be conservative and prof—¢ Df ecologic. l receptors.

Table 11
( kulation of Average Daily Dosesfor Bald Eagle
Crutchfield Branch
Baseline Ecological Risk Assessment
Duke Energy
Mayo Steam Elertric Plant, Roxboro, NC
-GEDAILYDOSEVIA:
WATER VERTEBRATE PREY SOIL
EPC_ EPC< EPC-, EPQ., I NIR. I ADO. I N., I P. NIR I NIR.., I NIR, I ADD, I 5. I NIR I ADD. BF ADD, I SUF I AUF I ADD.
Esfimated'
Water
Unadjuned
Fraction of
Food
Unadjuned
Soil ingese"on
Unadjuned
Area Use
Adjuned Total
COPEC in
COPEC in Solid
Slope, or
ConcentrMion in
Fish
Estr c'
Ingestion Rate
Average Daily
Fraction of
Die[Mammal
Ingestion
Fish inges
Mammal/Bird
Average Daily
Fraction Diet
RMe (kg
Average Daily
Bioavailability'
(bmivore
Seasonal Use
Facor
LS mivore
Aralyte
WMerm L
( g/)
(mg/kg)
VertebrMe
UlaUke (BAF)
Intercept
Mammals and
Ula�ke
(BCF)
Concentration
in Fish (mg/kg)
(L/kg
Dose Water
Diet Rsh
(PercenQ
+Birds
RMe, We[
(kg/kg
RMe(kg/kg
BW/Day
Ingestion Rate
(kg/kg BW/day)
Dose
Soil(percent)
dry/kg
Dose Soil
(P.,=t)
Intake
(mg/kg/day)
Facor
(Exposure
Area/Home
Average Daily
Birds(mg/kg)
BW/day)
(mdkg/dW)
(Percent)
BW d
(-&g/day)
BW/day)
(mg/kgjc!W)
Ran e
Dose(mg/kg/c!W)
Aluminum
0.1986
1
0
0.1
0.01986
0.0.
0.01
58%
42%
0.12
0.0696
0.0498
0.001
0.5%
0.0006
0
100%
0.01
1
0.00196
0.0000
Barium
98.2
0.7
-1-
6.04
4
0
Dom
0
58%
42%
0.12
0.0696
0.0498
0.-
0.5%
11-6
0.00766
100%
0.3086
1
0.00196
0.000603
Chromium, Total
94.4
0.1444
-14599
0.45
2.
0
Dom
0
58%
42%
0.12
0.0696
0.0498
0.02
0.5%
0.0006
0.00736
100%
0.02967
1
0.00196
0.00005801
Ma a
2.501
610
DOW
2.44
4.
1,000.4
Dom
0.15
58%
42%
0.12
0.0696
0.0498
69.T5
0.-
0.0006
0.04758
100%
69.90
1
0.00196
0.137
Mercun�
0.000004
63,.0
0.24507
0.058
0.0..02
58%
42%
0.12
0.0696
0.0498
0.02
0.5%
0.0006
0
100%
O.OITOST
1
0.00196
0.0.03.
NOTES:
EPC-ExposureP CDncentration BF-Bioavail ,b yFactor SUF-Sea nal Use Factor
NIR- Normalized lngesdon Rate BAF- BioaccumuI.-Factor AUF - Area U-FaCt0!
ADD -Average Daily Dose BCF- Bioconcen[ration Factor
r Sample et a1.1998a; EPA 200T ECDS51s, Att4-1, Table 4a
:S.
(Vdgt et al. NI15�, mean Dffsh dssue BAh; Cu (USEPA 1980�; Environmenml Hesroradon Division- Manual ER6AGU031999.
' Bioavailabiliry is setm a default M 10O%m be conservative and prIXeRive M ecdogical recepmrs.

Table 12
Calculation of Average Daily Doses for Muskrat
Crutchfield Branch
Baseline Ecological Risk Assessment
Duke Energy
Mayo Steam Electric Plant, Roxboro, NC
AVERAGE
DAILY DOSE VIA:
WATER
PLANTS / VEGETATION
SOIL
NIRw
ADD,
P,
NIR,
I NIR,
ADD,
S,
NIR,
ADD,
BF
ADD,
SUF
AUF
ADD -
EPC„. EP4 EPC,
Adjusted Total
Estimated'
Water Ingestion
Unadjurted
Fraction Diet
Food Ingestion
Plant Ingestion
Unadjurted
Soil Ingertion
Unadjurted
Herbivore
Area Use Fa ctor
Herbivore
Analyze
COPEC in Water
COPEC in Solid
Slope, or Plant
Intercept
Concentration
Rate (L/kg
Average Daily
Plant Matter
Rate, Wet
Rate, Dry
Average Daily
Fraction DiM
Rate (kg dry/kg
Average Daily
Bioavailabiliry'
Intake
Seasonal Use
(Exposure
Average Daily
Img/L)
(mg/kg)
Uptake(BAF)
in Vegetation
BW/daY)
Dose Water
(percent)
(kg/kg BW/daY)
(kg/kg/daV)
Dose Plant
Soil Porca t)
BW/daY)
Dose Soil
(percent)
(mg/kg/daY)
Factor(unitless)
Area/Home
Dose
(mg/kg dry)
(mg/kg/day)
(mg/kg/daY)
(mg/kg/daY)
Range)
(mg/kg/day)
Aluminum
0.1986
0.0008
0
0.97
0.19
99%
0.3
2.041
0
1%
0.000273
0
100%
0.19
1
1
0.19
Barium
98.2
0.03
2.946
0.9]
0
99%
0.3
D.045
D.131 A
1%
D.DDD2]3
0.00349
LBO%
0.14
1
1
0.14
Chromium, Total
94.4
0.0015
0.1416
0.9]
0
99%
0.3
0.045
0.00633
1%
0.00D2]3
0.00335
lOD%
0.01
1
1
0.01
Manganese
2.501
610
0.01
30.1
0.9]
Lot
2.43
99%
0.3
0.045
1.36299
1%
0.000273
0.02165
100%
3.81
1
1
3.81
Mercury
D.000004
0.000004
99%
0.3
0.045
0
1%
0.000273
0
1 1DO%
1 0.000004
1 1
1
0.000004
NOTES:
EPC- Exposure Point Concentration BF-Bi-ilabildy Factor SUF - Seasonal Use Faclor
NIR- Normalized Ingertion Rate BAF- Bioaccumalalion Faclor AUF-Area Use Faclor
ADD- Aveage Daily Dose BGF- Bioconcenlralion Faclor
' Bechtel Jacobs Company 1998a; Baes et al. 1994 (M.); Environmental Restoration Division- Manual EMAG-0031999, default value of 1 N used for mnslituents for which a RAF Could not be found.
' Bioavail ability N set to a default of 100%to be mnservative and pro-m of ecological receptors.

Table 13
Calculation of Average Daily Doses for River Otter
Crutchfield Branch
Baseline Ecological Risk Assessment
Duke Energy
Mayo Steam Electric Plant, Roxboro, NC
AVERAGE DAILY DOSE VIA:
DRINKING WATER
FISH
Nik
AD%
Pf
NIR,
NIR,
ADD,
BF
ADDt
SUF
AUF
ADDtot
EPCw EPC, EPCPRcY
Area Use
Adjusted Total
i
Unadjusted
Unadjusted
COPEC in
COPEC in Solid
Fish Uptake
Estimated
Water
Average Daily
Fraction Diet
Food Ingestion
Fish Ingestion
Average Daily
Bioavailabilityz
Piscivore
Seasonal Use
Factor
Piscivore
Concentration
Ingestion Rate
Animal Matter
Rate, Wet
Rate (kg/kg
Intake
Factor
(Exposure
Average Daily
Water(mg/L)
(mg/kg)
(BCF)
in Fish (mg/kg)
(L/kg BW/day)
Dose Water
(Percent)
(kg/kg BW/day)
BW/day)
Dose
(percent)
(mg/kg/day)
(unitless)
A
Dose
Analyte
(mg/kg/day)
(mg/kg/day)
Raa/Home
l y)
Aluminum
0.1986
0.1
0.02
0.081
0.016
100%
0.19
0.19
0.0038
100%
0.0199
1
0.012
0.000245
Barium
98.2
4
0
0.081
0
100%
0.19
0.19
0
100%
0
1
0.012
0
Chromium, Total
94.4
200
0
0.081
0
100%
0.19
0.19
0
100%
0
1
0.012
0
Manganese
2.501
610
400
1,000.4
0.081
0.203
100%
0.19
0.19
190.08
100%
190.279
1
0.012
2.351143
Mercury
0.000004
63,000
0.25
0.081
0.0000003
100%
0.19
0.19
1 0.047
100%
0.047
1
0.012
0.000575
NOTES:
EPC- Exposure Point Concentration BF - Bioavailability Factor SUF - Seasonal Use Factor
NIR - Normalized Ingestion Rate BAF - Bioaccumulation Factor AUF -Area Use Factor
ADD - Average Daily Dose BCF - Bioconcentration Factor
Al (Voigt et al. 2015), mean of fish tissue BAFs; Cu (USEPA 1980); Environmental Restoration Division - Manual ERD-AG-003 1999.
z Bioavailability is set to a default of 100% to be conservative and protective of ecological receptors.

Table 14
Hazard Quotients for COPCs - Terrestrial Receptors
Crutchfield Branch
Baseline Ecological Risk Assessment
Duke Energy
Mayo Steam Electric Plant, Roxboro, NC
Analyte
Wildlife Receptor Hazard Quotient Estimated using the'No Observed Adverse Effects
Level'
Terrestrial
American Robin
Red -Tailed Hawk
Meadow Vole
Red Fox
Aluminum
2.53E-04
5.14E-07
2.16E-02
3.07E-05
Barium
1.28E-02
2.57E-04
4.70E-03
6.33E-05
Chromium, Total
1.18E-01
3.96E-04
3.80E-05
1.62E-07
Manganese
6.34E-03
1.60E-05
5.10E-02
6.81E-05
Mercury
I 1.68E-07
3.41E-10
8.09E-07
1.15E-09
Analyte
Wildlife Receptor Hazard Quotient Estimated using the'Lowest Observed Adverse Effects
Level'
Terrestrial
American Robin
Red -Tailed Hawk
Meadow Vole
Red Fox
Aluminum
2.53E-05
5.14E-08
2.16E-03
3.07E-06
Barium
6.38E-03
1.28E-04
3.25E-03
4.37E-05
Chromium, Total
2.37E-02
7.91E-05
3.80E-06
1.62E-08
Manganese
3.26E-03
8.24E-06
3.70E-02
4.94E-05
Mercury
I 1.47E-06
2.99E-09
5.11E-06
7.25E-09
NOTES:
Hazard Quotients greater than or equal to 1 are highlighted in gray and in boldface.
NC - Not calculated due to lack of a Toxicity Reference Value

Table 15
Hazard Quotients for COPCs - Aquatic Receptors
Crutchfield Branch
Baseline Ecological Risk Assessment
Duke Energy
Mayo Steam Electric Plant, Roxboro, NC
Analyte
Wildlife Receptor Hazard Quotient Estimated using the 'No Observed Adverse Effects Level'
Aquatic
Mallard Duck
Great Blue Heron
Bald Eagle
Muskrat
River Otter
Aluminum
1.02E-06
2.22E-06
1.78E-05
9.98E-02
1.27E-04
Barium
3.58E-04
9.40E-05
2.61E-03
Chromium, Total
9.53E-04
1.96E-03
3.53E-06
Manganese
I 4.01E-05
1.72E-02
1.09E-05
7.40E-02
4.57E-02
Mercury
I 6.74E-10
5.79E-05
6.02E-04
3.74E-06
5.70E-04
Analyte
Wildlife Receptor Hazard Quotient Estimated using the 'Lowest Observed Adverse Effects Level'
Aquatic
Mallard Duck
Great Blue Heron
Bald Eagle
Muskrat
River Otter
Aluminum
1.02E-07
2.22E-07
1.78E-06
9.98E-03
1.27E-05
Barium
1.78E-04
4.69E-05
1.80E-03
Chromium, Total
1.91E-04
3.91E-04
3.53E-07
Manganese
2.06E-05
8.83E-03
5.62E-06
5.37E-02
3.31E-02
Mercury
5.92E-09
5.08E-04
5.28E-03
2.36E-05
3.60E-03
NOTES:
Hazard Quotients greater than or equal to 1 are highlighted in gray and in boldface.
NM - Not measured due to lack of a Toxicity Reference Value
1 The bald eagle was added to this risk assessment model because the species is federally protected and represents a raptor that preys upon fish,
primarily, while the Red -Tailed Hawk primarily preys upon small terrestrial vertebrates (e.g., rodents, snakes, etc.). Hazard quotient calculations for
the Bald Eagle include hypothetical consumption of fish that inhabit adjacent surface water areas in addition to terrestrial vertebrates that inhabit
adjacent areas.

Appendix C
Exposure Modeling and
Human Health Risk
Assessment for Diesel
Emissions

Air Dispersion Modeling for Mayo Ash Basin Closure
I used screening models to evaluate the potential for both cancer and non -cancer risks from
diesel exhaust emissions due to increased trucking operations related to the closure of the coal
ash basin at the Duke Energy Mayo Plant. The calculated cancer and non -cancer risks are
associated with increased diesel trucking activity near residential properties that lie along
transportation corridors near the Mayo Plant. Modelling was conducted for cap -in -place (CIP),
excavation to an expanded onsite landfill, and hybrid closure options. Details of these closure
options are provided in the main body of the report.
Emission rates for the fleet of diesel trucks operating as part of closure activities were calculated
based on truck activity and emission factors representative of the region from the U.S.
Environmental Protection Agency (EPA) Mobile Vehicle Emissions Simulator (MOVES). I
estimated airborne concentrations of emitted pollutants using the EPA model AERMOD for
atmospheric dispersion and transport. AERMOD is a Gaussian plume model that accounts for
the impacts of meteorology and land characteristics on airborne pollutants. Together these tools
allowed for the estimation of airborne concentrations of diesel particulate matter (DPM) emitted
from passing trucks and subsequent calculation of potential non -cancer health impacts (hazard
index [HI]) and cancer risk estimates (excess lifetime cancer risk [ELCR]).
The following sections detail the data and models used in this evaluation, including the
meteorological data, trucking operations, emissions calculations, and dispersion modeling. I also
include additional discussion of the results and associated uncertainties.
1707466.000 - 6216
C-1

Methodology
Meteorological Data
AERMOD-ready five-yearl meteorological data sets of hourly surface meteorological data for
the years 2012-2016 were generated from the National Weather Service (NWS) Automated
Surface Observing System (ASOS) station at the Danville Regional Airport (KDAN) in
Danville, Virginia.2 The Danville Regional Airport is located approximately 35 km from Duke
Energy's Mayo Plant. I judged this station to be representative of the meteorology in the region
of the Mayo Plant. Surface parameters applied to the modeling study included wind speed and
direction, temperature, pressure, relative humidity, and cloud cover. Twice daily rawinsonde3
observations of upper air winds and temperatures were taken from Greensboro, North Carolina
(KGSO), which, at 105 km from Mayo Plant, is the closest upper air sounding site.4
The meteorological data were processed using AERMET (v16216) with default options.5 To
better resolve lower wind speeds and avoid over -estimating calm conditions, AERMINUTE was
also applied.6 AERSURFACE7 was used to define the land -use characteristics in the region
around the surface observational site (i.e., Danville Regional Airport). The surface
' Use of five years of meteorological data is standard in regulatory application of AERMOD (EPA Guideline on
Air Quality Models, Section 8.3.1, 2005).
2 Integrated surface hourly weather observations are available at ftp://ftp.ncdc.noaa.gov/pub/data/noaa/. 2-minute
average ASOS wind data are available at ftp://ftp.ncdc.noaa.gov/pub/data/asos-onemin/.
3 A rawinsonde is a device typically carried by weather balloons that collects meteorological and atmospheric
data, especially regarding winds.
4 Not all meteorological stations will record upper air data (soundings); however, the difference in locations does
not substantively affect the model because the atmosphere at higher levels has less spatial variability. Thus,
upper atmospheric conditions at Greensboro, North Carolina, are likely to be similar to those at Danville,
Virginia, and, by extension, at the Mayo Plant.
5 AERMET is an EPA program that will read standard recorded meteorological observations, calculate boundary
layer meteorological parameters, and output the data in a format readable by the AERMOD model (U.S. EPA
2016).
6 Because the Danville Regional Airport has an ASOS where 2-minute average wind direction and wind speed
data are recorded every minute, it was possible to use AERMINUTE with AERMOD. More frequent
measurements of wind data allow for better resolution of wind characteristics.
AERSURFACE is the EPA model used to calculate average land -use characteristics. It can read standard
databases and calculate the average values of surface roughness, albedo, and Bowen ratios, consistent with EPA
recommended methods.
1707466.000 - 6216
C-2

characteristics, which are important when calculating the level of atmospheric dispersion in
meteorological modeling, include surface roughness, albedo,8 and Bowen ratio.9
Trucking Operations
Diesel emissions estimates from trucking are based on the number of trucks passing a given
receptor location along transportation corridors used during ash basin closure. The total number
of truckloads required for transporting ash, earthen fill, and geosynthetic materials under the
Mayo closure scenarios were projected by Duke Energy (2018b). These truckloads equate to
11,481 total truck passes for CIP closure; 100 truck passes for excavation to an expanded onsite
landfill; and 11,418 truck passes for the hybrid option. I included only loads hauling earthen fill,
geosynthetic materials, and other materials in transportation emissions estimates for all options
because trucks hauling ash in the excavation option do not leave the Mayo Plant except for
crossing U.S. Highway 501, and no residences are present within 150 m of the road along the
onsite hauling route. Trucks hauling earthen fill are assumed to travel I I miles one way from
the site, and trucks hauling geosynthetic material are assumed to travel 275 miles one way from
Georgetown, South Carolina. Air modeling is conducted for a receptor along the transportation
route within the I I -mile radius traveled both by trucks hauling earthen fill and trucks hauling
geosynthetic material. Trucks are assumed to travel in round trips, so the number of material
loads was doubled to represent the number of truck passes.
AERMOD
The AERMOD modeling system (U.S. EPA 2016) is a steady-state plume model that
incorporates air dispersion based on planetary boundary layer turbulence structure and scaling
concepts, including treatment of surface and elevated sources. EPA's "Guideline on Air Quality
Models" (U.S. EPA 2016) identifies AERMOD as the preferred refined dispersion modeling
technique for receptors within 50 km of a modeled source.
s Albedo is the ratio of reflected flux density to incident flux density. It indicates how much incoming energy is
absorbed by the land surface. Light surfaces (such as snow) will reflect higher levels of incoming energy.
9 Bowen ratio is the ratio of sensible to latent heat fluxes from the earth's surface up into the air. Lower Bowen
ratio is indicative of greater water content in the land surface.
1707466.000 - 6216
C-3

The latest version of AERMOD (v16216r) was used with default options to conduct the
modeling.
Modeled Source and Receptors
AERMOD was configured to simulate an approximately 1-km stretch of road. This road
segment was assumed representative of any segment along the proposed transportation
corridors. The road emission source was modeled as a continuous distribution of emission along
the road due to the passage of multiple trucks. In the cross -road direction, the emissions drop off
based on a normal (or Gaussian) distribution. The road emissions were represented using a line
of closely spaced volume sources running down the center of the road. Volume sources define
the initial pollutant distribution based on an initial release height and the standard deviation of
the normal distribution in both the vertical and horizontal directions (sigma-y and sigma-z). The
appropriate values for the release height and standard deviations were calculated based on
guidance in EPA's Haul Road Working Group Final Report (U.S. EPA 2010).
Transport and dispersion of pollutants away from the road segment may be sensitive to the
predominant wind directions at the site and the orientation of the road compared to those
predominant wind directions. To fully evaluate the impacts of any road segment, four
orientations of the road were considered. Modeled orientations included roads running
north/south, east/west, northeast/southwest, and northwest/southeast. For each modeled road
orientation, receptors were included on both sides of the road to represent impacts at distances
between 10 and 150 m from the edge of the road. The representative road segments and
sampling receptor locations are shown in Figure C-1.
AERMOD was run for the five-year period (2012-2016) defined by the meteorological data.
The resulting five-year average dispersion factors were assumed representative of long-term
average dispersion of truck roadway emissions along roads in this region.
1707466.000 - 6216
C-4

Figure C-1. Location of road sources (blue) and sampling receptors (red) for each of 4 road
orientations
Source Emission Rates
Emission rates for mobile sources are typically calculated based on a combination of emission
factors and activity rates. The emission factors define the amount of pollutant emitted per unit
distance traveled (grams of pollutant per kilometer traveled), and the activity rates define how
much activity occurs (i.e., the number of kilometers driven by the vehicles). Emission factors
will be specific to the type of vehicle being considered, the model year, the age of the vehicle,
and the local climate. For this evaluation, EPA's MOVES model was used to define fleet
average emission factors for various years between 2018 and 2050 (2050 is the last year
simulated by MOVES) (U.S. EPA 2015). The 2050 emission factors were retained for all years
1707466.000 - 6216
C-5

after 2050. These emission factors are specific to North Carolina and have been selected to
represent large, single -unit diesel trucks
Tailpipe emissions from diesel trucks (DPM) are the subset of PMio of particular interest when
evaluating the cancer and non -cancer risk estimates in this analysis. The DPM emission factors
generated by MOVES were multiplied by the expected number of trucks under each of the
considered scenarios to calculate emission rates for each scenario.
For the cancer risk analysis, emissions were calculated as an average over the regulatory default
70-year residential exposure duration. If the truck activity for a scenario occurs over a shorter
period, the duration of the truck activity exposure is factored into the 70-year averaging time
(OEHHA 2015). These average emission rates were multiplied by the dispersion factors
calculated by AERMOD to predict airborne concentrations. The resulting values were then
multiplied by the cancer unit risk factor10 to quantify cancer risk.
For the non -cancer analysis, airborne concentrations of DPM were calculated and compared to
the non -cancer risk threshold of 5 µg/m3 11 In this case, the average concentrations are not tied
to a 70-year period and are calculated over the period of operation for each closure option.
10 A "reasonable estimate" for the inhalation unit risk of 3.0 X 10-4 (µg/m3)-, was applied based on California
guidelines (OEHHA 2015).
" North Carolina defers to the EPA's chronic non -cancer reference concentration (RfQ for DPM of 5 µghu3
based on diesel engine exhaust to estimate risk from diesel emissions (Integrated Risk Information System
[IRIS]. U.S. EPA. Diesel engine exhaust).
1707466.000 - 6216
C-6

Uncertainties
A number of uncertainties should be considered when evaluating the modeled results. First, air
dispersion modeling is a mathematical calculation of pollutant transport and dispersion and may
differ from real world conditions. Typically, for regulatory applications, air dispersion models
are expected to predict concentrations within a factor of two. Longer averaging periods, such as
those used in this study, would often have lower uncertainties as compared with shorter average
periods such as 1-hour or 24-hour averages.
The calculation of emission factors is meant to represent fleet average characteristics. The fleet
of trucks used at this specific site may differ from the average values included in MOVES. This
may result in higher or lower actual emission rates. Additionally, MOVES includes predictions
of future year emission factors based on typical patterns of vehicle turnover and any regulations
scheduled to be implemented in future years. Not all future regulations are presently known and
future conditions may vary from these estimates.
For the non -cancer risk, an evaluation of the average concentrations was calculated over the
actual period of activity, which varies between closure options. For this portion of the
evaluation, there was no accounting for how long the emissions were present. The non -cancer
risk value is generally considered applicable over a period of approximately eight years. For
activities that occur for less than eight years, comparison with this risk value may overstate the
actual risk. Correspondingly, for activities that run significantly longer than eight years, there
may be sub -periods with higher average concentrations and higher associated non -cancer risk.
1707466.000 - 6216
C-/

Results
Worst -case impacts were calculated for each distance from the modeled road. The worst -case
result represents the highest value calculated over the four road orientations. This may not be
the same orientation for all distances. For example, a road that runs northeast/southwest aligns
with the predominant wind direction. This results in higher concentrations for receptors close to
the road. For receptors farther away from the edge of the road, the worst case occurs for a
northwest/southeast road where winds are perpendicular to the road. Worst -case results are
reported in Table 9-2 of the main report. The following sections include results for all road
orientations and distances from both sides of the road.
Model -estimated cancer risk
ELCR results for the four road orientations and both sides of the road are provided in Table C-1.
1707466.000 - 6216 C-Op

Table C-1. ELCR estimates from DPM exposure due to trucking operations
associated with closure of the Mayo Plant under CIP closure, excavation
closure, and hybrid closure. Results are for each road orientation and
distances from both sides of the road (ELCR columns per orientation).
E-W Run NE -SW Run N-S Run NW -SE Run
CIP
10 m
2.1E-09
2.0E-09
2.5E-09
2.8E-09
2.2E-09
1.7E-09
1.6E-09
1.6E-09
20 m
2.0E-09
1.8E-09
2.0E-09
2.2E-09
2.1E-09
1.6E-09
1.6E-09
1.8E-09
30 m
1.6E-09
1.4E-09
1.6E-09
1.8E-09
1.7E-09
1.3E-09
1.3E-09
1.5E-09
40 m
1.3E-09
1.2E-09
1.3E-09
1.5E-09
1.4E-09
1.1E-09
1.1E-09
1.2E-09
50 m
1.1E-09
1.0E-09
1.0E-09
1.2E-09
1.2E-09
9.4E-10
9.7E-10
1.1E-09
60 m
1.0E-09
8.8E-10
8.9E-10
1.1E-09
1.1E-09
8.3E-10
8.6E-10
9.6E-10
70 m
9.0E-10
7.8E-10
7.7E-10
9.4E-10
9.6E-10
7.4E-10
7.7E-10
8.6E-10
80 m
8.2E-10
7.0E-10
6.8E-10
8.4E-10
8.6E-10
6.7E-10
7.0E-10
7.8E-10
90 m
7.4E-10
6.3E-10
6.1E-10
7.5E-10
7.9E-10
6.1E-10
6.4E-10
7.1E-10
100 m
6.9E-10
5.8E-10
5.5E-10
6.8E-10
7.2E-10
5.6E-10
5.9E-10
6.6E-10
110 m
6.3E-10
5.3E-10
4.9E-10
6.2E-10
6.6E-10
5.2E-10
5.5E-10
6.1E-10
120 m
5.9E-10
4.9E-10
4.5E-10
5.7E-10
6.1E-10
4.9E-10
5.1E-10
5.7E-10
130 m
5.5E-10
4.6E-10
4.1E-10
5.2E-10
5.7E-10
4.6E-10
4.8E-10
5.3E-10
140 m
5.2E-10
4.3E-10
3.8E-10
4.8E-10
5.3E-10
4.3E-10
4.5E-10
5.0E-10
150 m
4.9E-10
4.0E-10
3.5E-10
4.5E-10
5.0E-10
4.1E-10
4.3E-10
4.7E-10
Excavation
10 m
1.1E-11
1.1E-11
1.4E-11
1.5E-11
1.2E-11
9.3E-12
8.8E-12
8.9E-12
20 m
1.1E-11
9.8E-12
1.1E-11
1.2E-11
1.1E-11
8.8E-12
8.9E-12
9.7E-12
30 m
8.6E-12
7.8E-12
8.5E-12
9.6E-12
9.2E-12
7.1E-12
7.2E-12
8.0E-12
40 m
7.2E-12
6.5E-12
6.8E-12
7.9E-12
7.8E-12
5.9E-12
6.1E-12
6.8E-12
50 m
6.2E-12
5.5E-12
5.7E-12
6.7E-12
6.7E-12
5.1E-12
5.3E-12
5.9E-12
60 m
5.5E-12
4.8E-12
4.8E-12
5.8E-12
5.9E-12
4.5E-12
4.7E-12
5.2E-12
70 m
4.9E-12
4.2E-12
4.2E-12
5.1E-12
5.2E-12
4.0E-12
4.2E-12
4.7E-12
80 m
4.4E-12
3.8E-12
3.7E-12
4.5E-12
4.7E-12
3.6E-12
3.8E-12
4.2E-12
90 m
4.0E-12
3.4E-12
3.3E-12
4.1E-12
4.3E-12
3.3E-12
3.5E-12
3.9E-12
100 m
3.7E-12
3.1E-12
3.0E-12
3.7E-12
3.9E-12
3.1E-12
3.2E-12
3.6E-12
110 m
3.4E-12
2.9E-12
2.7E-12
3.4E-12
3.6E-12
2.8E-12
3.0E-12
3.3E-12
120 m
3.2E-12
2.7E-12
2.4E-12
3.1E-12
3.3E-12
2.6E-12
2.8E-12
3.1E-12
130 m
3.0E-12
2.5E-12
2.2E-12
2.8E-12
3.1E-12
2.5E-12
2.6E-12
2.9E-12
140 m
2.8E-12
2.3E-12
2.1E-12
2.6E-12
2.9E-12
2.3E-12
2.4E-12
2.7E-12
150 m
2.7E-12
2.2E-12
1.9E-12
2.4E-12
2.7E-12
i 2.2E-12
2.3E-12
i 2.6E-12
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C-9

Table C-1. (cont). ELCR estimates from DPM exposure due to trucking operations
associated with closure of the Mayo Plant under CIP closure, excavation
closure, and hybrid closure. Results are for each road orientation and
distances from both sides of the road (ELCR columns per orientation).
E-W Run NE -SW Run N-S Run NW -SE Run
Hybrid
10 m
1.5E-09
1.4E-09
1.8E-09
2.0E-09
1.6E-09
1.2E-09
1.1E-09
1.2E-09
20 m
1.4E-09
1.3E-09
1.4E-09
1.6E-09
1.5E-09
1.1E-09
1.2E-09
1.3E-09
30 m
1.1E-09
1.0E-09
1.1E-09
1.2E-09
1.2E-09
9.2E-10
9.4E-10
1.0E-09
40 m
9.4E-10
8.4E-10
8.9E-10
1.0E-09
1.0E-09
7.7E-10
7.9E-10
8.8E-10
50 m
8.1E-10
7.2E-10
7.4E-10
8.7E-10
8.7E-10
6.6E-10
6.9E-10
7.6E-10
60 m
7.1E-10
6.2E-10
6.3E-10
7.5E-10
7.6E-10
5.8E-10
6.1E-10
6.8E-10
70 m
6.4E-10
5.5E-10
5.5E-10
6.6E-10
6.8E-10
5.2E-10
5.4E-10
6.0E-10
80 m
5.8E-10
4.9E-10
4.8E-10
5.9E-10
6.1E-10
4.7E-10
4.9E-10
5.5E-10
90 m
5.3E-10
4.5E-10
4.3E-10
5.3E-10
5.5E-10
4.3E-10
4.5E-10
5.0E-10
100 m
4.8E-10
4.1E-10
3.8E-10
4.8E-10
5.1E-10
4.0E-10
4.1E-10
4.6E-10
110 m
4.5E-10
3.8E-10
3.5E-10
4.4E-10
4.7E-10
3.7E-10
3.8E-10
4.3E-10
120 m
4.2E-10
3.5E-10
3.2E-10
4.0E-10
4.3E-10
3.4E-10
3.6E-10
4.0E-10
130 m
3.9E-10
3.2E-10
2.9E-10
3.7E-10
4.0E-10
3.2E-10
3.4E-10
3.8E-10
140 m
3.7E-10
3.0E-10
2.7E-10
3.4E-10
3.8E-10
3.0E-10
3.2E-10
3.5E-10
150 m
3.4E-10
2.8E-10
2.5E-10
3.2E-10
3.5E-10
I 2.9E-10
3.0E-10
3.3E-10
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C-10

Model -estimated non -cancer risk
HI results for the four road orientations and both sides of the road are provided in Table C-2.
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C-11

Table C-2. HI estimates from DPM exposure due to trucking operations associated
with closure of the Mayo Plant under CIP closure, excavation closures,
and hybrid closure. Results are for each road orientation and distances
from both sides of the road (HI columns per orientation).
E-W Run NE -SW Run N-S Run NW -SE Run
CIP
Excavation
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C-12

Table C-2. (cont). HI estimates from DPM exposure due to trucking operations
associated with closure of the Mayo Plant under CIP closure, excavation
closure, and hybrid closure. Results are for each road orientation and
distances from both sides of the road (HI columns per orientation).
E-W Run NE -SW Run N-S Run NW -SE Run
Hybrid
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C-13

Appendix D
Habitat Equivalency Analysis

Habitat Equivalency Analysis
Habitat equivalency analysis (HEA) was used to estimate changes in ecological service levels
under different closure options for the Mayo Plant ash basin. The extent of ecological service
flows currently provided by ash basin habitats (wooded areas, open field, open water, etc.) and
associated sites (borrow/landfill areas) was calculated and compared to service flows provided
by post -closure habitats in these areas.
The HEA proceeded in four steps:
1. Estimate habitat areas: The acres of different habitat types (e.g., forest,
open field, open water, wetland) that would be affected by closure under each
closure option (i.e., cap in place [CIP], excavation, and hybrid closures) were
estimated from aerial imagery.
2. Evaluate ecological service levels: The relative level of ecological services
provided by these habitats was estimated in terms of net primary productivity
(NPP)-
3. Apply discounting for future services: The relative levels of ecological
services were calculated over time according to the construction
implementation schedule developed by Duke Energy (2018b) and expressed
in units of discounted service acre -years (DSAYs).
4. Calculate discounted ecological services: DSAYs were summed across the
gains and losses of each habitat type to produce a net gain or loss in
ecological service levels for each closure option.
Estimate Habitat Areas
Acreages of current habitat types were calculated from geographic information system (GIS)
files provided by Duke Energy that included spatial representations of the current acreage of
open field, wetland, wooded area, and open water habitats surrounding the ash basin. The
acreages of ash basin to be closed and land converted to landfill or borrow were based on
information provided by Duke Energy (2018b) according to the assumptions below. For the
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D-1

excavation and hybrid options, the closure -by -removal portions of the ash basin were assumed
to be restored to historical, pre -basin conditions. Historical acreage of forested, open field, and
stream habitat types were estimated by measuring pre -basin aerial photographs provided in the
comprehensive site assessment (CSA; SynTerra 2015a) using GIS. Unclassified current habitat
areas in the ash basin footprint were assumed to be bare ground and to have a 0% service value.
Historical habitat types were broadly classified into forest, open water, and unclassified open
areas since not all currently measured habitat types (e.g., wetland) could be resolved from
historical images. Historical open unclassified areas (i.e., not forest or open water habitat types)
were estimated by assuming the current site -wide percentages of wetland (9.6%) and open field
(90.4%) applied to these areas within the historical ash basin footprint. It is important to note
that not all closure options impacted all basin habitat areas, thus different closure options may
be modeled in the HEA using different total areas.
Additional assumptions used to calculate habitat areas included:
• The historical stream habitat area of the Crutchfield Branch was available only as
linear spatial feature. To calculate the area of restored stream features as open water,
I assumed a restored stream would have a width of 6 ft.
• Fill material for closure was assumed to be derived from excavation of basin
dam features and new, onsite borrow pits. The areal extent of these borrow
pits was calculated from the volume (cubic yards) of required earthen fill
material, assuming borrow pits would be dug to 15 ft.
• Area lost to borrow pit excavation was assumed to contain forest habitat,
which is the predominant non -basin habitat type on the Mayo property.
Evaluate Ecological Services
NPP was used to standardize ecological services across habitat types. NPP is a measure of how
much photosynthesis occurs in an area greater than the amount required by the plants for
immediate respiration needs. Fundamentally, NPP is a measure of the energy available to
perform ecological services and is a useful currency for comparing habitats (Efroymson et al.
1707466.000 - 6216
D-2

2003). NPP is often referred to in terms of carbon fixation or carbon storage, as the removal of
carbon from the atmosphere is a primary reaction of photosynthesis.
Of the habitats currently occurring on the site, mixed forested areas have the highest NPP; that
is, per acre of forest, photosynthesis fixes more carbon/produces more energy for ecological
services (Ricklefs 2008). As such, NPP service levels for all habitat types were normalized to
the NPP service level of forested habitat. Specifically, the service levels for all habitat types
were expressed as a proportion of the maximum wooded area service level (He et al. 2012).
To compare results between the different closure options, a set of assumptions was used for all
options evaluated.
• Figure 22.12 from Ricklefs (2008) was used as the basis for determining
relative rates of NPP for different ecosystem types. For this evaluation,
temperate forest (woodland) was considered the base habitat with a relative
NPP of 100%. Other habitat types were normalized as a proportion of that
value based on the relative levels of NPP shown in Ricklefs' Figure 22.12
(2008), using temperate grassland as representative of open fields and
freshwater environments as representative of open water.
— Based on Ricklefs' Figure 22.12 (2008), NPP values for open field
and open water habitats were assumed to be 40% of the forest value.
However, because aquatic habitats of the ash basin may not be
functionally equivalent to naturally occurring freshwater ecosystems
(e.g., less abundant or diverse vegetation), a habitat quality
adjustment factor of 4 was applied, lowering the relative NPP value
for ash basin open water habitat to 10% of temperate forest NPP.
• Figure 2c from He et al. (2012) was used to estimate NPP of woodland areas
based on stand age.
— The NPP functions for the three forest types (broadleaf, needleleaf,
mixed) from Figure 2c of He et al. (2012) were digitized to allow
calculation of NPP by stand age. For example, for mixed forests this
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D-3

function shows rapidly increasing NPP up to a maximum at 45 years,
after which the NPP declines slightly to level off at approximately
85% of the maximum.
— All wooded areas currently occurring in the ash basin or on borrow or
landfill areas were assumed to be 50 years old, which, based on He et
al. (2012), provide approximately 97% of maximum NPP function in
the case of broadleaf and mixed forests and 84% for needleleaf
forests. Other habitats were normalized from the higher value using
the relative rates of NPP described above.
• Baseline levels of service (NPP) in the absence of closure activities were
assumed to continue at the current rate for 150 years, accounting for slight
changes in wooded area NPP by age as calculated from the NPP function of
He et al. (2012).
Apply Discounting for Future Services
HEA applies a discounting function when calculating the amount of ecological services derived
from an acre over a year and uses as its metric a discounted service acre -year, or DSAY.
Discounting is necessary because ecological services occurring in the future are assumed to be
less valuable to people than the same services performed now (Dunford et al. 2004; Desvousges
et al. 2018; Penn undated). This allows the ecological services occurring far in the future to be
considered on par with contemporary services. Thus, factors determining when closure and
remediation begin and the duration of these processes are important parameters of the final
DSAY estimate.
I used the closure schedule provided by Duke Energy (2018b) to develop timelines for habitat
loss and gain under each closure option. For purposes of the HEA, only site preparation,
construction, and site restoration times were included. Pre -design and design permitting periods
were assumed to have no effect on ecological services. The closure schedule estimated duration
of each activity in months; however, since the HEA model calculates DSAYs on an annual
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D-4

basis, the activity durations were rounded up the nearest full year. This has a negligible impact
on DSAY estimates.
The following assumptions were then used to standardize timing of activities among the closure
options:
• For all options, removal of existing onsite habitats was assumed to occur in
the year that construction begins and was assumed to be completed the same
year such that no ecological service is provided by the end of the first
construction year.
• Ecological services of areas used for borrow or as landfill were assumed to be
lost in the year construction starts, and borrow/landfill site preparation was
assumed to be complete the same year such that no ecological service is
provided by the end of the first construction year.
• Ecological service gains from restoration (ash basin and borrow area) were
assumed to begin in the year following completion of construction activities.
• Post -closure habitats were presumed eventually to provide the same level of
service as equivalent pre -closure habitats with the following conditions:
— Forests would be age 0 in the year when restoration was completed
and would generate an increasing level of NPP as they grow,
following the rates calculated from the NPP curves of He et al.
(2012).
— Restored open field habitat would take five years (based on
professional judgement) to reach the baseline relative to forest NPP of
40%, with service levels increasing linearly over that time.
— Restored wetland and stream habitat would be functionally equivalent
to natural freshwater ecosystems and would provide an NPP relative
to forests of 40% after five years (based on professional judgement),
increasing linearly over that time.
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D-5

— Periodic mowing is required to maintain a grass cap, so grass cap was
assumed never to reach a level of service equivalent to an open field.
Grass cap was assumed to have 20% of the NPP service level for open
field, which is 8% of forest NPP. Grass cap was assigned a post -
closure service level of 8%, with full service attained in 2 years.
— Bare ground was assumed to provide no ecological service.
• The base year for discounting is 2019 in all scenarios.
• A discount rate of 3% is applied in all scenarios.
• The HEA is run for 150 years for all closure options.
Calculate Discounted Ecological Services
Calculation of DSAYs is a summation of the discounted losses and gains in service values
across habitat types. The net DSAYs calculated for each closure option are reported in Table 10-
1 of the main body of this report.
A sensitivity analysis of key parameters (based on professional experience) and assumptions
used in the HEA was conducted to evaluate how sensitive the HEA results are to changes in (1)
the duration over which the services were evaluated (i.e., 150 years), (2) the assumed relative
NPP of ash basin open water and open fields, and (3) habitat created by restoration of borrow
areas. The results are discussed in the context of uncertainty in the net environmental benefit
analysis (NEBA) in Appendix E.
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D-6

Appendix E
Net Environmental Benefit
Analysis

Net Environmental Benefit Analysis
Net environmental benefit analysis (NEBA) is a structured framework for comparing impacts
and benefits to environmental services to support decision -making (Efroymson et al. 2003,
2004). In the NEBA application for Mayo ash basin closure, a risk -ranking approach, based on
that described by Robberson (2006), was applied. The risk -ranking approach develops
alphanumerical estimates of relative risk by closure option and by attribute (e.g., risk to a
receptor, change in ecological services), which allows comparison of the relative differences in
impact between closure options to a variety of attributes. In this way, tradeoffs can be visualized
to inform decision -making.
Risk -Ranking Matrix
The risk -ranking matrix includes two axes that characterize risk. The y-axis shows the level of
impact, or risk, to an attribute, and the x-axis shows the duration of the impact (which is directly
related to the time to recovery). Both are important to evaluate the relative differences in risk
posed by closure options. A moderate level of impact over a long duration can potentially have
an overall greater negative impact on the environment than a higher impact over a very short
period (Robberson 2006). The pattern of shading of the risk matrix conveys this general
principle, though the exact shading of the cells is based on best professional judgement.
Robberson (2006) describes darker shading as indicating a higher level of concern over the level
of impact to a resource or environmental service. The NEBA matrix developed by the
Operational Science Advisory Team-2 (OSAT 2011) used a similar color coding approach to
compare risk from further cleanup of oil on beaches of the Gulf of Mexico following the
Deepwater Horizon oil spill. The risk -ranking matrix used in the NEBA of closure options for
the Mayo ash basin is shown in Table E-1.
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E-1

Table E-1. Risk -ranking matrix for impacts and risk from closure activities. Darker
shading and higher codes indicate greater impact.
Duration of Impact (years)
10-15
(4)
5-9
(3)
1-4
(2)
1 <1
(1,
No meaningful risk
--
--
--
--
<5% (A)
4A
3A
2A
1A
5-19% (B)
4B
3B
2B
1 B
20-39% (C)
4C
3C
2C
1C
40-59% (D)
3D
2D
1 D
60-79% (E)
2E
1E
>80% (F)
1F.
The percent impact levels (e.g., <5%, 5-19%) were defined based on best professional
judgement and regulatory precedent. A <5% impact characterizes a very minor potential or
expected impact that may be functionally indistinct from baseline conditions due to uncertainty
in metrics or the estimated effects. As such, this level of impact was given no shading,
regardless of the duration of impact. Impacts between 5-19% are considered low in the NEBA
framework (Efroymson et al. 2003). This impact level was shaded to reflect this low risk. Levels
of impact >20% were separated at intervals of 20% based on best professional judgement and
consistent with the risk -ranking approach used by Robberson (2006).
Similarly, the categories used to define duration of impact were based on best professional
judgment and regulatory precedent. Robberson (2006) defines recovery in <1 year as "rapid,"
with shading that indicates a generally low level of concern across the levels of impact. The
remaining categories of time in the risk -ranking matrix were divided at roughly 5-year intervals.
As Robberson (2006) notes, the exact size of the risk matrix is a function of decisions made
about scaling the matrix, which is a function of the closure and remediation being considered
and the attributes included in the NEBA. The risk -ranking matrix applied here could have been
defined differently. For example, the duration of impact categories could have been expanded to
six (e.g., <1 year, 1-3 years, 3-6 years, 6-10 years, 10-15 years, >15 years), which would have
changed the alphanumeric risk ratings and perhaps some of the shading of attributes evaluated
in the NEBA. The purpose of the risk matrix, and the risk ratings that result from it, is to
1707466.000 - 6216
E-2

consolidate the results from a variety of different analyses for a variety of different data types
and attributes into a single framework for comparative analysis. It is imperative, however, to
consider the underlying information used to develop the risk ratings to interpret the differences
between closure options, particularly when percent impacts or durations of closure options are
similar but receive different risk ratings. It is inappropriate to assume a risk rating for one
attribute is scientifically equivalent to the risk rating of another attribute because the
comparative metrics that form the foundation of the risk ratings can be fundamentally different
(e.g., a hazard quotient for risk to a bird species is different from discounted service acre -years
[DSAYs] for environmental services from a habitat). Thus, the risk ratings in the NEBA matrix
permit a relative comparison of impacts between closure options within attributes. Decision -
makers can use the NEBA framework to identify the relative impacts of closure options across
many different attributes, but the NEBA matrix does not, by design, elevate, or increase the
value of, any specific risk or benefit in the framework.
Risk Rating Sensitivity
Uncertainty in a NEBA can be evaluated by examining the uncertainty in the assumptions and
analyses used as inputs to the risk -ranking matrix. The following sections examine how
differences in assumptions could affect relative risk ratings in the NEBA framework for
attributes found to have levels of impact. Attributes for which no meaningful risk was found
(e.g., human health risk assessments, ecological health risk assessments) are not included in the
following discussion.
Noise and congestion from trucking traffic
I used the number of trucks per day passings a receptor along a near -site transportation corridor
as a metric to examine the differences in noise and traffic congestion under the closure options. I
compared the increase in truck passes due to hauling earthen fill, geosynthetic material, and
' Truck passes per day resulting from trucking activities is calculated as the total number of loads required to
transport earthen fill, geosynthetic materials, and other materials multiplied by two to account for return trips.
The resulting total number of passes is then divided evenly among the total number of months of trucking time
multiplied by 26 working days per month.
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E-3

other materials under the closure options to the current number of truck passes for the same
receptor.
The current (or baseline) number of truck passes was estimated from North Carolina
Department of Transportation (NCDOT) annual average daily traffic (AADT) data collected at
thousands of locations across the state and the proportion of road miles driven by large trucks in
North Carolina. AADT is an estimated daily traffic volume at a specific location, which
captures traffic in all lanes traveling in both directions and is assumed to represent typical traffic
volume for a year.3 Not all AADT data, however, differentiate between large trucks such as
those to be used in ash basin closure and other traffic such as cars, which is a relevant
distinction when considering impacts to communities from increased noise. NCDOT performs
vehicle classification4 on trucking routes to estimate annualized truck percentage to apply to
AADT to determine truck AADT (NCDOT 2015). The average annualized truck percentage for
Person County is 9.5%.
The precise transportation corridor for all trucks travelling to and from the Mayo ash basin and
landfill sites during ash basin closure is unknown; however, likely corridors in the communities
local to Mayo can be identified by examining road maps and AADT statistics. The Mayo Plant
is situated along US 501 (Boston Rd) (Figure E-1). The excavation closure option involves a
single crossing of US 501 immediately west of the ash basin, and the US 501 corridor is
assumed to be the primary transportation route for offsite hauling for cover materials including
topsoil and geosynthetic materials. The nearest traffic measuring station to Mayo is immediately
north of the Mayo Plant where US 501 crosses into Virginia with Station ID 7200001 reporting
3,300 AADT in 2017. South of the Mayo Plant on US 501 is Station ID 7200002, which reports
3,800 AADT in 2017. To best capture trucking related impacts to sensitive communities along
Truck trips to haul ash were not included in the estimate for Mayo ash basin closure because trucks hauling ash
would not leave the Mayo property (with the exception of crossing U.S. Route 501) and would not affect
community receptors along the transportation corridors.
s AADT is calculated from two days of traffic counts at each station during weekdays, excluding holidays. Raw
monitoring data consists of counts of axle pairs made by pneumatic tube counters that are converted to traffic
volume by applying axle correction factors, and expanded to annual estimates by seasonal correction factors.
Derived AADT values are checked for quality against nearby stations and historical station -specific values
(NCDOT 2015).
4 Vehicle classification is assigned based on number of axles, space between axles, weight of the first axle, and
total weight of the vehicle.
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E-4

the transportation corridor, I assumed a baseline truck passes per day of 314, which was
computed by multiplying 3,300 AADT (2017 estimate from US 501 Station ID 7200001 in
2017) by the Person County average percent of truck AADT (9.5%; NCDOT 2015).5
,f
58
01 LEGEND
Annual average daily traffic
(Baseline consideration)
AW. ■ 2,000 - 3,499
Mayo Active Ash Basin 0 3,500 - 5,499
Annual average daily traffic
- - 3,300 ■ 80 - 199
IN OF, is .., �
•
200 - 499
3,800 • 500 - 999
Sap, • 1,000 - 1,999
• • 2,000 - 3,499
• 3,500 - 5,499
• 5,500 - 8,499
•0 8,500 - 12,499
a *0 • 12,500 - 16,000
� r
® 0 2.5 5 Miles
ko
f
� Q i= 0 3 fi KiEometers
�
Figure E-1. NCDOT annual average daily traffic (AADT) measurement stations near Mayo.
Traffic stations and AADT values considered when determining the baseline
number of truck passes are indicated as squares.
The sensitivity of the NEBA relative risk ratings to the baseline assumption of 314 trucks per
day was evaluated by calculating relative risk ratings for a range of baseline truck traffic levels,
based on the minimum and maximum AADT values for any NCDOT station within a 50-mile
radius of the Mayo ash basin, using AADT from the most recent year that data are available for
a particular station and assuming 9.5% truck traffic as previously described. Figure E-2 plots the
5 AADT data are not available for every road or every location along a road. It is possible during closure of the
Mayo ash basin that trucks will utilize less traveled roads (i.e., with lower AADT), which would have a lower
baseline truck passes per day estimate and result in a higher percent impact from ash basin closure for these
sensitive communities; however, by choosing the lowest available AADT estimate from roads within 10 miles
of Mayo along the most likely transportation corridors to and from Mayo to a major road (e.g., highway), my
analyses have considered sensitive communities that would be more affected by traffic noise and congestion
from ash basin closure trucking.
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E-5

resulting percent impact for closure options along with the resulting relative risk rating across
the range of 2 to 18,541 truck passes per day.
102.0
10'.0
100.0
ci
a10-2.0
E
0
102.0
101.0
100.0
10-1.0
10-2.0
0 100 200 300 400 500
0 100 200 300 400 500
Assumed Baseline Truck Passes Per Day
Risk Rating • A • B • C • D • E • F
Figure E-2. Sensitivity of NEBA relative risk rating for noise and congestion impacts from
trucking operations. The vertical line indicates the assumed baseline 314 truck
passes per day. The y-axis is plotted on a log10 scale and the X axis is
truncated at 500 to improve visualization.
Using a baseline truck passes per day of 314, all closure options (CIP, excavation, and hybrid)
fall into the lowest relative risk rating (A, <5%) for traffic -induced noise and congestion during
closure of the Mayo ash basin (Figure E-2). Higher risk ratings would result from a lower
baseline truck traffic assumption; decreasing the baseline truck traffic assumption to 180 in the
CIP option or 140 in the hybrid option would increase risk to the B (5-19%) risk rating. The
average daily truck passes in the excavation option would need to be between 1 and 2 trucks per
day to increase to a B risk rating.
Traffic accidents
I evaluated risk of traffic accidents by comparing the average number of annual offsite road
miles driven between closure options relative to a baseline estimate of the current annual road
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E-6

miles driven.6 I chose a baseline of 33.5 million annual truck road miles based on the reported
total vehicle miles traveled in Person County, North Carolina (NCDOT 2017) multiplied by the
county average 9.5% contribution of trucks to total AADT (NCDOT 2015).
The sensitivity of the NEBA relative risk ratings to the baseline assumption of 33.5 million
truck miles per year was evaluated by calculating relative risk ratings for alternative baseline
truck mile assumptions derived from the counties in NC with the minimum (Hyde County) and
maximum (Mecklenburg County) reported vehicle miles driven, resulting in a sensitivity range
estimated from 6.2 million to 641 million truck miles per year. Figure E-3 plots the resulting
percent impact for the CIP, excavation, and hybrid closure options, along with the resulting
relative risk ratings across the range of truck miles per year.
100,0
10-05
10-1.0
10-1.5
10-2.0
10-2.5
f+
10-3.0
Ca
C
100.0
0
10-0.5
10-i.0
10-1.5
10-2.0
10-2.5
10-3.0
0 200 400 600
0 200 400 600
Assumed Baseline Million Truck Miles Per Year
Risk Rating • A
Figure E-3. Sensitivity of NEBA relative risk rating for traffic accidents due to trucking
activities. The vertical line indicates the assumed baseline 33.5 million truck
miles per year. The y-axis is plotted on a log10 scale to improve visualization.
6 The difference between the baseline miles assumption and the closure assumption was divided by the baseline
miles assumption and multiplied by 100 to get a percent impact.
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E-7

Using the 33.5 million truck miles baseline assumption, the CIP option has a 0.13% impact;
excavation has a 0.01% impact; and the hybrid closure option has a 0.09% impact. All closure
options have a relative risk rating of A (<5%). These relative risk ratings do not appear to be
sensitive to lower assumed baseline annual truck miles. The vertical lines in Figure E-3 indicate
the location of the baseline assumption. Reducing the baseline assumption to the 6.2 million
truck miles minimum increases percent impact to 0.7, 0.06, and 0.5% for CIP, excavation, and
hybrid closure options, respectively; the risk ratings are unchanged.
Habitat Equivalency Analysis
Uncertainty in the habitat equivalency analysis (HEA) that examined disruption of ecological
services from ash basin closure was explored through sensitivity analyses of key assumptions in
the HEA. To test sensitivity, I re -ran HEA models with the following changes:
1. Running the HEA for 100 years instead of 150 years.
2. Assuming the open water habitats of the ash ponds provide ecological
services at 40% of wooded areas instead of 10%.
3. Assuming open field habitats provide ecological services at 20% of wooded
areas instead of 40%.
4. Assuming borrow areas under the CIP option are restored to open fields, not
reforested.
For each sensitivity analysis, all parameters in the base model were held constant except the one
parameter varied to understand the sensitivity of the model to each assumption (Table E-2).
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E-8

Table E-2. Change in DSAYs from base mode la for key HEA assumptions
Closure
100-year
Ash basin
Borrow
Open Field
Option
modelb
water 40%°
becomes fields
20%e
CIP
2
—501
—240
0
Excavation
—107
—486
0
-60
Hybrid
—66
—486
0
-12
a Base models were run for 150 years with ash basin open water NPP services at 10%,
borrow fields were assumed to become forest (CIP closure) or grass cap (hybrid and
excavation closure), and open field NPP services at 40%.
b Base models except the HEA was run for 100 years.
Base models except ash basin open water NPP service at 40%.
Base models except borrow pits were assumed to become open field for CIP option.
e Base models except open field NPP services decreased to 20%.
Running HEAs for 100 years increased net DSAYs slightly for the CIP closure option and
decreased net DSAYs for excavation and hybrid closure options. Increasing the ash basin open
water service level to 40% resulted in net decreases in DSAYs for all options. Assuming borrow
areas would be returned to open field resulted in a decrease in net DSAYs for CIP; there are no
borrow areas in the excavation or hybrid closures, so there is no net change in DSAYs for that
option. Decreasing open field services to 20% slightly reduced net DSAYs in all options except
for CIP closure.
Looking at the change in net DSAYs between the sensitivity models and their base models, the
changes in assumptions have relatively consistent effects on net DSAYs. For example, changing
ash basin open water services from 10 to 40% affects all closure options similarly, since the
same level of service change is applied over the same areal extent (54 acres of open water) in all
closure options. The slight difference in DSAY losses between options is due to differences in
the year construction starts and hence existing services are lost. Assuming open field services at
20% has a larger effect on the excavation option since this option restores greater open field
acreage than the hybrid option. Changing the service level of borrow acreage habitat after
borrow is complete only affects options that have borrow areas (CIP). However, since the
directionality of net NPP services provided by the closure options does not change under this
sensitivity analysis (i.e., hybrid closure and excavation closure have net NPP service gains,
while CIP closure results in net NPP service losses), this demonstrates that the model can
differentiate between relative differences in NPP service level changes with consistency.
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E-9

Changes in net DSAYs with changing assumptions may change the relative risk rating applied
to a closure option in the NEBA. However, the relative similarity in the how DSAYs change
with assumptions between the various closure options and the result that the excavation or
hybrid closure options always result in substantially greater net DSAYs than CIP under any
sensitivity analysis supports the relative risk ratings for decision support in the NEBA.
Closure Option Assumptions
The following assumptions were used to calculate NEBA input values related to trucking
activities and habitat acreages, unless otherwise specified by Duke Energy (2018).
• The density of ash was assumed to be 1.2 ash tons/CY.
• Borrow pit acreage required to supply earthen fill and cover material was
assumed to be dug to a depth of 15 ft to meet volume requirements. Borrow
pits not specifically identified were assumed to contain a mixed forest habitat
that would be restored upon closure completion.
• Excavation was assumed to proceed at a rate of 1,000,000 CY/year for all
types of excavation material combined including ash, underlying over -
excavated or residual soil, and dam and embankment material.
• CIP cover systems were assumed to require two layers of geosynthetic
material. New landfill areas were assumed to require five layers of
geosynthetic material. Geosynthetic material was assumed to be transported
from Georgetown, South Carolina, at a rate of six loads per day, and 3 acres
per load.
• Covers/caps for both CIP and landfills were assumed to receive 18 in. of
cover soil plus 6 in. of topsoil. New landfills also were assumed to receive 2
ft of liner soil. Topsoil was assumed to come from an offsite commercial
facility requiring no additional borrow area.
• Unless otherwise specified, offsite borrow material and topsoil were assumed
to be from sources 11 miles away (one way).
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• Offsite truck capacity was assumed to be 20 CY of ash or earthen material.
• Working hours were assumed to be 10 hr/days, 6 days/week, and 26
days/month.
• Earthen fill material was assumed to be hauled in at a rate based on 1,000,000
CY/year.
• In excavated areas, 1 ft of over -excavation of residual soil was assumed.
When restoring these areas, 2 ft of additional soil material plus 6 in. of top
soil was assumed necessary to establish vegetative stabilization over the total
area.
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