United States Office of Water EPA-821-R-20-002
Environmental Protection Washington, DC 20460 August 2020
Agency
vvEPA
United States
Environmental Protection
Agency
Supplemental Environmental
Assessment for Revisions to the
Effluent Limitations Guidelines and
Standards for the Steam Electric
Power Generating Point Source
Category
EPA-821 -R-20-002
August 2020
U.S. Environmental Protection Agency
Office of Water (4303T)
Washington, DC 20460
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Disclaimer
This document was prepared by the Environmental Protection Agency. Neither the United States
Government nor any of its employees, contractors, subcontractors, or their employees make any
warrant, expressed or implied, or assume any legal liability or responsibility for any third party's
use of or the results of such use of any information, apparatus, product, or process discussed in
this report, or represents that its use by such party would not infringe on privately owned rights.
Questions regarding this document should be directed to:
U.S. EPA Engineering and Analysis Division (4303T)
1200 Pennsylvania Avenue NW
Washington, DC 20460
(202) 566-1000
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Table of Contents
TABLE OF CONTENTS
Page
SECTION 1 INTRODUCTION 1-1
1.1 Background on Steam Electric Wastewater Discharges 1-1
1.2 Scope of the Analysis 1-2
SECTION 2 ENVIRONMENTAL AND HUMAN HEALTH CONCERNS
ASSOCIATED WITH THE EVALUATED WASTESTREAMS 2-1
2.1 Pollutants Discharged in the Evaluated Wastestreams 2-1
2.1.1 Total Dissolved Solids (TDS) and Salinity 2-2
2.1.2 Bromide 2-4
2.1.3 Iodine 2-8
2.2 Supplemental Literature Review on Environmental Impacts of Other
Pollutants in Discharges of the Evaluated Wastestreams 2-10
SECTION 3 OVERVIEW OF METHODOLOGY FOR THE SUPPLEMENTAL
QUANTITATIVE ENVIRONMENTAL ASSESSMENT 3-1
3.1 Impact Areas Selected for Quantitative Assessment 3-1
3.2 Scope of Evaluated Plants and Immediate Receiving Waters 3-2
3.3 Pollutant Loadings for the Evaluated Wastestreams 3-6
3.4 Overview of Immediate Receiving Water (IRW) Model 3-7
3.4.1 Structure of the IRW Model 3-7
3.4.2 Pollutants Evaluated by IRW Model 3-9
3.5 Downstream Analysis 3-10
3.6 Proximity Analysis for Impaired Waters and Fish Consumption Advisory
Waters 3-11
SECTION 4 RESULTS OF THE SUPPLEMENTAL QUANTITATIVE
ENVIRONMENTAL ASSESSMENT 4-1
4.1 Estimated Pollutant Loadings for the Evaluated Wastestreams 4-1
4.2 Key Impacts Identified by IRW Model 4-5
4.2.1 Water Quality Module 4-5
4.2.2 Wildlife Module 4-10
4.2.3 Human Health Module 4-12
4.3 Impacts in Downstream Surface Waters 4-18
4.4 Discharges to Impaired Waters and Fish Consumption Advisory Waters 4-20
4.4.1 Impaired Waters 4-20
4.4.2 Fish Consumption Advisories 4-24
SECTION 5 REFERENCES 5-1
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Table of Contents
TABLES OF CONTENTS (Continued)
APPENDIX A
APPENDIX B
APPENDIX C
APPENDIX D
APPENDIX E
APPENDIX F
EXAMPLES OF POTENTIAL ADVERSE IMPACTS FROM
EXPOSURE TO METALS AND TOXIC AND
BIO ACCUMULATIVE POLLUTANTS
EXAMPLES OF POTENTIAL ADVERSE IMPACTS FROM
EXPOSURE TO TOTAL DISSOLVED SOLIDS
WATER QUALITY MODULE METHODOLOGY
WILDLIFE MODULE METHODOLOGY
HUMAN HEALTH MODULE METHODOLOGY
ADDITIONAL IRW MODEL RESULTS
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List of Tables
LIST OF TABLES
Page
Table 1-1. Wastestreams Evaluated in the Supplemental EA 1-3
Table 2-1. Maximum Contaminant Levels (MCLs) and Maximum Contaminant Level
Goals (MCLGs) for Drinking Water Disinfection Byproducts (DBPs) 2-7
Table 3-1. Plants, Generating Units, and Immediate Receiving Waters Evaluated in the
Supplemental EA 3-4
Table 3-2. Plants, Generating Units, and Immediate Receiving Waters with Pollutant
Loadings under Baseline and Regulatory Options 3-4
Table 4-1. Estimated Industry-Level Pollutant Loadings and Estimated Change in
Loadings by Regulatory Option 4-2
Table 4-2. Estimated Annual Baseline Mass Pollutant Loadings and Estimated Change in
Loadings Under Regulatory Options for the Evaluated Wastestreams
(Supplemental EA Subset of Pollutants) 4-4
Table 4-3. Modeled IRWs with Exceedances of NRWQC and MCLs under Baseline and
Regulatory Options 4-6
Table 4-4. Modeled IRWs with Exceedances of Any NRWQC or MCL, by Pollutant
under Baseline and Regulatory Options 4-7
Table 4-5. Modeled IRWs with Exceedances of NRWQC and MCLs under Baseline and
Regulatory Options: Best- and Worst-Case Monthly Scenarios 4-8
Table 4-6. Modeled IRWs with Exceedances of TECs and NEHCs under Baseline and
Regulatory Options 4-11
Table 4-7. Modeled IRWs with Exceedances of Oral RfD (Non-Cancer Human Health
Effects) under Baseline and Regulatory Options 4-13
Table 4-8. Modeled IRWs with LECR Greater Than One-in-a-Million (Cancer Human
Health Effects) under Baseline and Regulatory Options 4-14
Table 4-9. Modeled IRWs with Exceedances of Oral RfD (Non-Cancer Human Health
Effects), by Race Category, under Baseline and Regulatory Options 4-15
Table 4-10. Comparison of Modeled T4 Fish Tissue Concentrations to Fish Advisory
Screening Values under Baseline and Regulatory Options 4-17
Table 4-11. Modeled Downstream River Miles with Exceedances of Any Pollutant
Evaluation Benchmark Value under Baseline and Regulatory Options 4-19
Table 4-12. IRWs Identified as CWA Section 303(d) Impaired Waters or Fish
Consumption Advisory Waters under Baseline and Regulatory Options 4-20
Table 4-13. IRWs Listed as CWA Section 303(d) Impaired for Pollutants Present in the
Evaluated Wastestreams under Baseline and Regulatory Options 4-21
Table 4-14. IRWs with Fish Consumption Advisories for Pollutants Present in the
Evaluated Wastestreams under Baseline and Regulatory Options 4-24
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List of Figures
LIST OF FIGURES
Page
Figure 3-1. Locations of Immediate Receiving Waters Evaluated in the Supplemental EA 3-5
Figure 3-2. Overview of IRW Model 3-9
Figure 4-1. Worst-Case Months for Water Quality Conditions in Immediate Receiving
Waters 4-10
Figure 4-2. Immediate Receiving Waters Impaired by Mercury 4-22
Figure 4-3. Immediate Receiving Waters Impaired by Metals, Other Than Mercury 4-22
Figure 4-4. Immediate Receiving Waters Impaired by Nutrients 4-23
Figure 4-5. Immediate Receiving Waters with Fish Consumption Advisory for Mercury 4-25
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List of Abbreviations
LIST OF ABBREVIATIONS
l^g/g
Micrograms per gram
Hg/L
Micrograms per liter
|ig/m3
Micrograms per cubic meter
|iS/cm
MicroSiemens per centimeter
ADES
Advanced Emissions Solutions, Inc.
ADD
Average daily dose
AT SDR
Agency for Toxic Substances and Disease Registry
AWWARF
American Water Works Association Research Foundation
BAF
Bioaccumulation factor
BAT
Best Available Technology Economically Achievable
BCA
Benefit and Cost Analysis
BCF
Bioconcentration factor
BLM
Biotic Ligand Model
Br-DBP
Brominated disinfection byproduct
Ca
Calcium
CCME
Canadian Council of Ministers of the Environment
CCR
Coal combustion residuals
CFR
Code of Federal Regulations
CI
Chlorine
C032"
Carbonate
CSF
Cancer slope factor
CUWA
California Urban Water Agencies
CWA
Clean Water Act
DBP
Disinfection by-product
DCN
Document control number
D-FATE
Downstream Fate and Transport Equations
DNA
Deoxyribonucleic acid
DWTP
Drinking water treatment plant
EA
Environmental assessment
ED
Exposure duration
EJ
Environmental justice
ELGs
Effluent limitations guidelines and standards
EPA
U.S. Environmental Protection Agency
EPRI
Electric Power Research Institute
ERG
Eastern Research Group, Inc.
EROM
Extended Unit Runoff Method
FGD
Flue gas desulfurization
FR
Federal Register
FW
Freshwater
g/kg
Grams per kilogram
GIS
Geographic information system
HAA5
Haloacetic acids
HCO32-
Bicarbonate
HHO
Human Health for the consumption of Organism Only
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HH WO
HQ
ICAC
I-DBP
IRIS
IRW
K
K
KDEP
LADD
lb/year
L/kg
LC50
LECR
LOEC
MCL
MCLG
MRL
Mg
mg/day
mg/kg
mg/kg-day
mg/m3
mg/L
mS/cm
N
Na
NCDC
NaCl
NEHC
NHDES
NHDPlus
NO A A
NPS
NRC
NRWQC
POTW
ppb
ppm
ppt
PSES
RfD
RIA
S02
STORET
T3
List of Abbreviations
Human Health for the consumption of Water and Organism
Hazard quotient
Institute of Clean Air Companies
Iodinated disinfection byproduct
Integrated Risk Information System
Immediate receiving water
Potassium
Kelvin (degrees)
Kentucky Department for Environmental Protection
Lifetime average daily dose
Pounds per year
Liter per kilogram
Median lethal concentration
Lifetime excess cancer risk
Lowest observed effect concentration
Maximum contaminant level
Maximum contaminant level goal
Minimal risk level
Magnesium
Milligrams per day
Milligrams per kilogram
Milligrams per kilogram per day
Milligram per cubic meter
Milligrams per liter
MilliSiemens per centimeter
Nitrogen
Sodium
National Climatic Data Center
Sodium chloride
No effect hazard concentration
New Hampshire Department of Environmental Services
National Hydrography Dataset Plus
National Oceanic and Atmospheric Administration
National Park Service
National Research Council of the National Academies
National Recommended Water Quality Criteria
Publicly owned treatment works
Parts per billion
Parts per million
Parts per thousand
Pretreatment Standards for Existing Sources
Reference dose
Regulatory impact analysis
Sulfur dioxide
EPA's STOrage and RETrieval Data Warehouse
Trophic level 3
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T4
TDD
TDS
TEC
TEL
TKN
TSS
TTHM
USGS
U.S. DOJ
U.S. EPA
UV
VIP
WHO
List of Abbreviations
Trophic level 4
Technical Development Document
Total dissolved solids
Threshold effect concentration
Threshold effect level
Total Kjeldahl nitrogen
Total suspended solids
Total trihalomethanes
United States Geological Survey
United States Department of Justice
United States Environmental Protection Agency
Ultraviolet
Voluntary incentive program
World Health Organization
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Section 1—Introduction
SECTION 1
INTRODUCTION
The U.S. Environmental Protection Agency (EPA) promulgated revised effluent limitations
guidelines and standards (ELGs) for the Steam Electric Power Generating Point Source Category
(40 CFR 423) on November 3, 2015 (80 FR 67838), referred to hereinafter as the "2015 rule." In
support of the development of the 2015 rule, EPA conducted an environmental assessment (EA)
to evaluate the environmental impact of pollutant loadings discharged by coal-fired steam
electric power plants and assess the potential environmental improvement from pollutant loading
changes under the rule. EPA documented the EA in the September 2015 report, Environmental
Assessment for the Effluent Limitations Guidelines and Standards for the Steam Electric Power
Generating Point Source Category (EPA 821-R-15-006) (U.S. EPA, 2015 a), referred to
hereinafter as the "2015 Final EA." Following promulgation, EPA received seven petitions for
review of the 2015 rule, and the Administrator announced his decision to reconsider the 2015
rule in an April 12, 2017, letter. See the Supplemental Technical Development Document for
Revisions to the Effluent Guidelines and Standards for the Steam Electric Power Generating
Point Source Category (Supplemental TDD) (821-R-20-001) (U.S. EPA, 2020a) for additional
background and information on rulemaking history. EPA conducted a new rulemaking regarding
the appropriate technology bases and associated limitations for the best available technology
economically achievable (BAT) effluent limitations and pretreatment standards for existing
sources (PSES) applicable to flue gas desulfurization (FGD) wastewater and bottom ash
transport water discharged from coal-fired steam electric power plants. To support the new
rulemaking, EPA conducted a Supplemental EA on the two wastestreams being evaluated.
The Clean Water Act (CWA) does not require that EPA assess the water quality-related
environmental impacts, or the benefits, of its ELGs, and the Agency did not make its decisions in
the final rule based on the expected benefits of the rule. EPA does, however, inform itself and the
public of the benefits of its proposed and final rules, as required by Executive Order 12866. See
the Benefit and Cost Analysis for Revisions to the Effluent Limitations Guidelines and Standards
for the Steam Electric Power Generating Point Source Category (BCA Report) (EPA-821-R-20-
003) (U.S. EPA, 2020b). This Supplemental EA presents EPA's evaluation of the potential
environmental impacts due to pollutant loadings under baseline discharge practices (i.e.,
following full implementation of the 2015 rule) and the changes in those impacts under the final
rule and the other regulatory options EPA considered.
1.1 Background on Steam Electric Wastewater Discharges
Based on demonstrated impacts documented in literature and modeled receiving water pollutant
concentrations, discharges of coal-fired steam electric power plant wastewater can impact the
water quality in receiving waters, impact the wildlife in the surrounding environments, and pose
a human health risk to nearby communities. There is substantial evidence that certain pollutants
found in these wastewater discharges, such as mercury and selenium, propagate from the aquatic
environment to terrestrial food webs, indicating a potential for broader impacts on surrounding
ecological systems by diminishing population diversity and disrupting community dynamics.
Ecosystem recovery from exposure to these pollutants can be extremely slow, and even short
periods of exposure (e.g., less than a year) can cause observable ecological impacts that last for
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Section 1—Introduction
years (Brandt et al., 2017 and 2019; Canedo-Argiielles et al., 2013; CCME, 2018; Coughlan and
Velte, 1989; Evans and Frick, 2001; Evers et al., 2011; Garrett and Inman, 1984; Guthrie and
Cherry, 1976; Hallock and Hallock, 1993; Javed et al., 2016; Kimmel and Argent, 2010; Lemly,
1985, 1993, 1997, 1999, and 2018; NPS, 1997; NRC, 2006; Rowe et al., 2001 and 2002; Ruhl et
al., 2012; Sorensen, 1988; Specht et al., 1984; U.S. EPA, 2015a; U.S. EPA Region 5, 2016;
Velasco et al., 2018; Weber-Scannell and Duffy, 2007; WHO, 1992).
Coal-fired steam electric power plants often discharge wastewater into waterbodies used for
recreation and/or as sources of drinking water. Numerous studies have raised concern regarding
the toxicity of these wastestreams and their impacts on downstream drinking water treatment
systems (Brandt et al., 2017; Cornwell et al., 2018; ERG, 2019a, 2019b, 2019c, 2020a, and
2020b; Good and VanBriesen, 2016 and 2017; Kolb et al., 2020; Lemly, 2018; McTigue et al.,
2014; Ruhl et al., 2012; States et al., 2013). These discharges can also elevate halogen levels in
surface water, which may contribute to disinfection byproduct formation at downstream drinking
water treatment plants.
1.2 Scope of the Analysis
The Steam Electric Power Generating Point Source Category ELGs apply to establishments
whose generation of electricity is the predominant source of revenue or principal reason for
operation, and whose generation results primarily from a process utilizing fossil-type fuels (coal,
oil, or gas), fuel derived from fossil fuel (e.g., petroleum coke, synthesis gas), or nuclear fuel in
conjunction with a thermal cycle using the steam water system as the thermodynamic medium.
As noted earlier, EPA evaluated two wastestreams from coal-fired steam electric power plants
whose limitations would be revised under the new rulemaking (FGD wastewater and bottom ash
transport water), as described in Table 1-1.1
The goal of this Supplemental EA is to answer the following two questions regarding pollutant
loadings from the two evaluated wastestreams:
• What are the environmental and human health concerns regarding the pollutants
being discharged with the evaluated wastestreams?
• What are the potential changes to water quality, wildlife, and human health impacts
under the regulatory options compared to baseline (i.e., the 2015 rule)?
1 The steam electric ELGs control the discharge of pollutants to surface waters and do not regulate "wastewater." To
allow for more concise discussion in this Supplemental EA, EPA occasionally refers to "wastewater" discharges and
impacts without referencing the pollutants in the wastewater discharges.
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Section 1—Introduction
Table 1-1. Wastestreams Evaluated in the Supplemental EA
Evaluated
Wastcstrcam
Description
FGD wastewater
Wastewater generated from a wet FGD scrubber system. Wet FGD systems are used to
control sulfur dioxide (SO2) and mercury emissions from the flue gas generated in the plant's
boiler.
The pollutant concentrations in FGD wastewater vary from plant to plant depending on the
coal type, the burning of refined coal, the sorbents and additives used, the materials used to
construct the FGD system, the FGD system operation, the level of recycle within the
absorber, and the air pollution control systems operated upstream of the FGD system. FGD
wastewater contains chlorides, total dissolved solids (TDS), total suspended solids (TSS),
nutrients, halogens, metals, and other toxic and bioaccumulative pollutants, such as arsenic
and selenium (see the Supplemental TDD for further details).
In the 2015 rule, EPA established numeric effluent limitations for mercury, arsenic, selenium,
and nitrate/nitrite as nitrogen (N) in FGD wastewater, based on treatment using chemical
precipitation followed by high residence time reduction biological treatment.
Bottom ash
transport water
Water used to convey the bottom ash particles collected at the bottom of the boiler.
Bottom ash transport waters contain halogens, total dissolved solids (TDS), total suspended
solids (TSS), metals, and other toxic and bioaccumulative pollutants, such as arsenic and
selenium (see the Supplemental TDD for further details). The effluent from surface
impoundments typically contains low concentrations of TSS; however, arsenic, bromide,
selenium, and metals are still present in the wastewater, predominantly in dissolved form.
In the 2015 rule, EPA established zero discharge limitations for bottom ash transport water
based on one of two technologies: (1) dry handling or (2) closed-loop systems.
This Supplemental EA presents EPA's evaluation of environmental concerns and potential
exposures (ecological and human) to pollutants commonly found in wastewater discharges from
coal-fired steam electric power plants. EPA completed both qualitative and quantitative analyses.
Qualitative analyses included reviewing additional literature documenting site impacts and
pollutant-specific research; assessing the pollutant loadings to receiving waters—including those
designated as impaired or with a fish consumption advisory—under baseline and the regulatory
options; and reviewing the effects of pollutant exposure on ecological and human receptors. To
quantify impacts associated with these discharges, EPA used a computer model2 to estimate
pollutant concentrations in the immediate receiving waters, pollutant concentrations in fish
tissue, and potential exposure doses to ecological and human receptors from fish consumption.
EPA compared the values calculated by the model to benchmark values to assess the extent of
the environmental impacts nationwide. EPA evaluated the impacts of FGD wastewater and
bottom ash transport water discharges.
EPA presents four main regulatory options, summarized in Table VII-1 of the preamble to the
final rule. The four main regulatory options analyzed at proposal (1, 2, 3, and 4), the details of
which were discussed in the proposed rule (84 FR 64620), correspond generally to regulatory
Options D, A, B, and C here, but do contain differences as detailed in the preamble. The
2 See Section 3.4 of this report for an overview of the model.
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Section 1—Introduction
availability and achievability of technologies with better pollutant removals, as well as the
general lack of public comments in support for proposed regulatory Option 1, led EPA to focus
updates to the Agency's analysis on the remaining three regulatory options. EPA did not update
the analyses for regulatory Option D, but rather retained the results of the proposed rule analyses
for this option (see the Supplemental Environmental Assessment for Proposed Revisions to the
Effluent Limitations Guidelines and Standards for the Steam Electric Power Generating Point
Source Category (2019 Supplemental EA), Document No. EPA-821-R-19-010 (U.S. EPA,
2019a)).
EPA evaluated 87 plants that discharge one or both of the evaluated wastestreams directly or
indirectly to surface waters under baseline and/or the regulatory options, and performed the
quantitative modeling on a subset of 82 of these plants. The analyses presented in this report
account for publicly announced plans from the steam electric power generating industry to retire
or modify electric generating units at specific plants by December 31, 2028. See Section 3.2 of
this report for additional details on the scope of this Supplemental EA.
The assessments described in this Supplemental EA focus on environmental impacts caused by
exposure to pollutants in the evaluated wastestreams through the surface water exposure
pathway. However, the final rule may have other environmental impacts unrelated to exposure to
pollutants in wastewater discharges. Examples include changes in ground water and surface
water withdrawals by plants; changes in the amount of dredging activity necessary to maintain
capacities in reservoirs and navigational channels downstream from plants; and changes in air
emissions due to changes in electricity use, transportation requirements, and the profile of
electricity generation. These impacts are discussed in EPA's Benefit and Cost Analysis for
Revisions to the Effluent Limitations Guidelines and Standards for the Steam Electric Power
Generating Point Source Category (BCA Report) (EPA-821-R-20-003).
This Supplemental EA does not discuss impacts caused by migration of pollutants from surface
impoundments into ground water. The preamble to the final rule discusses how EPA's Coal
Combustion Residual (CCR) Part A Rule addresses this type of impact and how it relates to this
final rulemaking.
This report presents the methodology and results of the qualitative and quantitative analyses
performed for this Supplemental EA. In addition to this Supplemental EA, the final rule is
supported by several reports including:
• Regulatory Impact Analysis for Revisions to the Effluent Limitations Guidelines and
Standards for the Steam Electric Power Generating Point Source Category (RIA),
Document No. EPA-821-R-20-004 (U.S. EPA, 2020c). This report presents a profile
of the steam electric power generating industry, a summary of the costs and impacts
associated with the regulatory options, and an assessment of the final rule's impact on
employment and small businesses.
• Benefit and Cost Analysis for Revisions to the Effluent Limitations Guidelines and
Standards for the Steam Electric Power Generating Point Source Category (BCA
Report), Document No. EPA-821-R-20-003 (U.S. EPA, 2020b). This report
summarizes the monetary benefits and societal costs that result from implementation
of the final rule.
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Section 1—Introduction
• Supplemental Technical Development Document for Revisions to the Effluent
Limitations Guidelines and Standards for the Steam Electric Power Generating Point
Source Category (Supplemental TDD), Document No. EPA-821-R-20-001 (U.S.
EPA, 2020a). This report includes background on the final rule; industry description;
wastewater characterization and identification of pollutants of concern; treatment
technologies and pollution prevention techniques; and documentation of EPA's
engineering analyses to support the final rule, including cost estimates, pollutant
loadings, and a non-water-quality environmental impact assessment.
These reports are available in the public record for the final rule and on EPA's website at
https://www.epa.gOv/eg/2020-steam-electric-reconsideration-rule#final-rule.
The final rule is based on data generated or obtained in accordance with EPA's Quality System
and Information Quality Guidelines.3 EPA's quality assurance and quality control activities for
this rulemaking include the development, approval, and implementation of Quality Assurance
Project Plans for using environmental data generated or collected from all sampling and
analyses, existing databases, and literature searches, and for developing any models that used
environmental data. Unless otherwise stated within this document, EPA evaluated the data used
and associated data analyses as described in these quality assurance documents to ensure that
they are of known and documented quality; meet EPA's requirements for objectivity, integrity,
and utility; and are appropriate for the intended use.
3 See the following EPA websites for further details: https://www.epa.gov/aualitv/about-epas-aualitv-SYStem and
https://www.epa.gov/aualitv/epa-information-qualitv-guidelines
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Section 2—Environmental and Human Health Concerns Associated with the Evaluated Wastestreams
SECTION 2
ENVIRONMENTAL AND HUMAN HEALTH CONCERNS
ASSOCIATED WITH THE EVALUATED WASTESTREAMS
Discharges of flue gas desulfurization (FGD) wastewater and bottom ash transport water (the
evaluated wastestreams) from coal-fired steam electric power plants contain toxic and
bioaccumulative pollutants (e.g., selenium, mercury, arsenic, nickel), halogen compounds
(containing bromide, chloride, or iodide), nutrients, and total dissolved solids (TDS), which can
cause environmental harm through the contamination of surface waters. Certain pollutants in the
discharges pose a danger to ecological communities due to their persistence in the environment
and bioaccumulation in organisms. These factors can slow ecological recovery and can have
long-term impacts on aquatic organisms, wildlife, and human health. Numerous studies
document ecological impacts such as fish mortality, genotoxicity, and lower fish survival and
reproduction rates resulting from exposure to pollutants in coal-fired steam electric power plant
discharges.4 Halogen compounds associated with coal-fired steam electric power plant
discharges also raise ecological and human health concerns. Halogens in source water for
drinking water treatment plants (DWTPs) can interact with disinfection processes to form
halogenated disinfection byproducts (DBPs), which can pose a risk to human health.
EPA documented environmental and human health concerns from coal-fired steam electric
power plant discharges in the 2015 Final EA (U.S. EPA, 2015a). For this Supplemental EA, EPA
conducted supplemental literature reviews that consisted of identifying and evaluating peer-
reviewed journal articles, other published materials, and materials submitted during the proposed
rule public comment period that focused on environmental, ecological, and human health
impacts resulting from discharges of pollutants in FGD wastewater and bottom ash transport
water. This section presents a summary of relevant findings. Some of the articles documented
impacts of coal-fired steam electric power plant discharges but did not provide specific
wastestream details. When such details were documented in reviewed articles, EPA included
details regarding applicable wastestreams. See the memoranda titled "Methodology and Results
of a Targeted Literature Search of Environmental Impacts from Steam Electric Power Plants"
(ERG, 2019a) and "Methodology and Results for Targeted Literature Search for the 2020 Steam
Electric Supplemental Environmental Assessment" (ERG, 2020a) for additional details.
This section details environmental concerns associated with wastewater discharges from coal-
fired steam electric power plants, including the contamination of surface water, toxic effects on
fish and aquatic life, and human health concerns.
2.1 Pollutants Discharged in the Evaluated Wastestreams
EPA evaluated the pollutants discharged in FGD wastewater and bottom ash transport water for
this Supplemental EA. Once these pollutants are released into the environment, they can reside
for a long time in the receiving waters, bioaccumulating and/or binding with sediments. The
2015 Final EA presented the potential environmental, ecological, and human health concerns
4 See 2015 Final EA; Brandt et al., 2017; Javed et al., 2016; Lemly, 2018.
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Section 2—Environmental and Human Health Concerns Associated with the Evaluated Wastestreams
associated with exposure to metals, toxic bioaccumulative pollutants, nutrients, and TDS.5 This
Supplemental EA provides additional information on the impacts of discharges of TDS (and the
resulting salinity of the receiving water) and halogens. Appendix A provides examples of
potential adverse impacts to humans and wildlife resulting from exposure to metals and toxic
bioaccumulative pollutants in the evaluated wastestreams and provides the minimal risk level
(MRL) for human oral exposure (or similar benchmark value) for reference. Adverse impacts
from coal-fired steam electric power plant discharges of these pollutants and nutrients are
discussed further in the 2015 Final EA.
2.1.1 Total Dissolved Solids (TPS) and Salinity
TDS represents the concentration of combined dissolved organic and inorganic matter, while
salinity represents the total concentration of dissolved inorganic salts.
At coal-fired steam electric power plants, EPA estimates that the average TDS concentration in
FGD wastewater is 33,300 milligrams per liter (mg/L) prior to treatment and 32,500 mg/L
following treatment via surface impoundments (U.S. EPA, 2015b and 2020a). EPA estimates
that untreated FGD wastewater contains average concentrations of the following selected ions
(U.S. EPA, 2015b):6
• Calcium: 3,290 mg/L (total) and 2,050 mg/L (dissolved).
• Chloride: 7,180 mg/L (total).
• Magnesium: 3,250 mg/L (total) and 3,370 mg/L (dissolved).
• Sodium: 2,520 mg/L (total) and 276 mg/L (dissolved).
• Sulfate: 13,300 mg/L (total).
EPA estimates that treated bottom ash transport water effluent contains TDS at an average
concentration of 1,290 mg/L and average concentrations of the following selected pollutants
(U.S. EPA, 2020a):7'8
• Calcium: 154 mg/L (total).
• Chloride: 321 mg/L (total).
• Magnesium: 55.7 mg/L (total).
5 The 2015 Final EA discussed chloride and bromide discharges as part of the TDS parameter.
6 EPA calculated the average concentrations based on various data sets available for untreated FGD wastewater. As
a result of using various data sets, the average dissolved concentrations presented here may be higher than the total
concentrations. In samples in which both dissolved and undissolved metals are present, dissolved metals are a subset
of total metals.
7 Data reflect bottom ash transport water that has been treated in surface impoundments, which typically include
other wastestreams (e.g., low volume wastewaters, cooling water) in addition to bottom ash transport water. As a
result of this dilution, the data may underestimate the pollutant concentrations in treated bottom ash transport water.
8 EPA did not estimate average dissolved pollutant concentrations in bottom ash transport water. Dissolved
concentrations in treated effluent may be lower than the total concentrations presented here, depending on various
factors including the pollutant's solubility.
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Section 2—Environmental and Human Health Concerns Associated with the Evaluated Wastestreams
• Sodium: 119 mg/L (total).
• Sulfate: 504 mg/L (total).
Exposure to the dissolved bioaccumulative pollutants and halogens in the evaluated
wastestreams may cause human health and ecological effects, as described in Appendix A and
the following sections.
Salts can enter water naturally, through erosion of soils and geologic formations over time and
introduction of their dominant ions to local freshwater systems (Olson and Hawkins, 2012; Hem,
1985; Pond, 2004; U.S. EPA, 201 lc). In North America, the mean salinity of river water is 132.4
mg/L. The most commonly occurring cation in North American river water is calcium (Ca2+),
with a mean concentration of 21 mg/L. Other commonly occurring cations include sodium (Na+),
magnesium (Mg2+), and potassium (K+). The most commonly occurring anions are carbonate
(CO32") and bicarbonate (HCO32"), with a mean combined concentration of 68 mg/L. Other
commonly occurring anions include sulfate (SO42") and chloride (CI") (Evans and Frick, 2001;
Weber-Scannell and Duffy, 2007). Salinity in freshwater lakes typically falls within the 100 to
500 mg/L range and is predominantly driven by calcium carbonate (Evans and Frick, 2001).
Researchers have documented the potential consequences of elevated salinity on aquatic
ecosystems. Increased salinity has been linked to adverse effects including increases in invasive
species, lower rates of organic matter processing, changes in biogeochemical cycles, decreased
riparian vegetation, and altered composition of primary producers (i.e., plants, bacteria, and
algae) (Canedo-Argiielles et al., 2013). Increases in aquatic salinity may cause shifts in biotic
communities, limit biodiversity, exclude less-tolerant species, and result in acute or chronic
effects at specific life stages (Weber-Scannell and Duffy, 2007). Salt additions can lead to loss of
exchangeable cations in soil, and the mobility and toxicity of some pollutants, especially metals,
can be enhanced at high salt concentrations (Stets et al., 2020). Because interactions between
ions can affect the bioavailability and toxicity of individual TDS constituents, the net ecological
effect of elevated TDS levels in the aquatic environment depends on its ionic composition
(Moore et al., 2017; Mount et al., 1993 and 1997).
Velasco et al. (2018) performed a meta-analysis of studies that evaluated salinity impacts in
aquatic environments and found that 43 percent of the studies reported negative impacts to
aquatic organisms (e.g., decreased survival and growth, increased osmolyte concentration in
body fluids, and changes to metabolic rates), while 20 percent of the studies found positive
impacts, primarily on increased survival or tolerance to heat or cold stress. A meta-analysis by
Berger et al. (2019) also identified a correlation between increased salinity and reduced
decomposition rates and biodiversity.
Once salinity has increased in freshwater systems, the effect can be persistent. In lentic waters
such as lakes and ponds, even small increases in salt levels can result in long-term increases in
salinity, lasting months or years (Evans and Frick, 2001). Kaushal et al. (2005) reported that,
after application of deicing salts in winter, chloride concentrations in urban streams remain
elevated into spring, summer, and fall and contribute to an accumulation of salts in groundwater
and aquifers that may persist over several decades.
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Freshwater aquatic organisms are adapted to specific salinity ranges and can experience adverse
effects on fitness and survival when salinity increases beyond their tolerance (Canedo-Argiielles
et al., 2018). Several studies summarized by Scannell and Jacobs (2001) have indicated that TDS
concentrations higher than 700 mg/L can result in reduced growth, decreased survival rates, and
altered behavior in macroinvertebrate communities (e.g., Hamilton et al., 1975; Hoke et al.,
1992; Khangarot, 1991; Mount et al., 1997; Tietge and Hockett, 1997). Benthic invertebrates,
including caddisfly, mayfly, Nais variabilis (oligochaete), and mosquito larvae, exposed to
sodium chloride (NaCl) concentrations ranging from 1,300 to 12,000 mg/L exhibit mortality and
reduced survival (Evans and Frick, 2001). Fish mortality occurs at NaCl concentrations ranging
from 5,500 to 12,000 mg/L for certain species of rainbow trout, Indian carp fry, minnows, and
goldfish. At higher concentrations (14,000 to 50,000 mg/L), other fish species (e.g., bluegill
sunfish, channel catfish, rainbow trout species, brook trout, and golden shiners) exhibit decreased
survival and recovery (Evans and Frick, 2001). Appendix B presents examples of adverse
impacts associated with elevated TDS concentrations in freshwater systems.
Elevated levels of TDS in the source water can also negatively impact downstream drinking
water treatment and distribution by accelerating corrosion of transport pipes and producing
organoleptic effects (e.g., undesirable taste and smell). EPA has not set a primary maximum
contaminant level (MCL) for TDS but has set a secondary MCL for TDS as a nuisance parameter
at 500 mg/L. Above this level, drinking water can demonstrate excessive hardness, deposits,
color, staining, and a salty taste (U.S. EPA, 2020d). Individual halides, such as bromide,
chloride, and iodide, in source water can contribute to the formation of DBPs at downstream
DWTPs, which can impact human health (Cornwell et al., 2018; Corsi et al., 2010; ERG, 2019c;
Good and VanBriesen, 2016 and 2017; McTigue et al., 2014; Ruhl et al., 2012; States et al.,
2013).
As presented earlier within this section, discharges of FGD wastewater and bottom ash transport
water can include elevated TDS levels. Other anthropogenic sources of TDS are widespread in
the environment, making it more likely that receiving waters for the discharges of the evaluated
wastestreams already carry excessive TDS loads. These other sources include mining activities,
use of road salt for de-icing, and discharge of sewage and industrial wastewater (Canedo-
Argiielles et al., 2013; Corsi et al., 2010). Multiple studies point to the positive relationship
between urbanization and salinity in surface waters (Moore et al., 2017; Steele & Aitkenhead-
Peterson, 2011; Stets et al., 2020). Land use decisions, such as construction, resource extraction,
and irrigation activities, can indirectly increase salt concentrations by increasing erosion and the
transport of ions to surface waters (Canedo-Argiielles et al., 2018). Wastewater treatment
facilities may be contributors; Novotny et al. (2009) estimated that, despite the significant
application of road salt, the majority (72 percent) of chloride added to rivers in the Minnesota
Twin Cities Metropolitan area was contributed by publicly owned treatment works (POTWs).
Construction of roads and culverts in coastal areas can facilitate saltwater intrusion into
freshwater systems, resulting in ecological changes (Stewart et al., 2002).
2.1.2 Bromide
Bromine is naturally present in coal. Some coal-fired steam electric power plants also add
bromine to their combustion processes to enhance mercury emissions control or burn refined
coal amended with bromide compounds (U.S. EPA, 2020a). After combustion, bromine
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partitions in part to FGD wastewater and bottom ash transport water in its anion form, known as
bromide (EPRI, 2014; Peng et al., 2013). Documented bromide levels in FGD wastewater vary
widely and can exceed 175 mg/L (EPRI, 2009; Good, 2018; U.S. EPA, 2015c and 2020a).
Average bromide levels of 5.1 mg/L have been documented in bottom ash transport wastewaters
(U.S. EPA, 2020a). These levels are higher than the average levels of 0.014 mg/L to 0.2 mg/L
reported for freshwater surface waters (Flury and Papritz, 1993; Health Canada, 2015; McGuire
et al., 2002). Field-based and modeling studies document elevated bromide levels in surface
waters downstream of steam electric power plants and identify FGD wastewater discharges as a
substantive source of bromide loadings from the plants (Cornwell et al., 2018; Good and
VanBriesen, 2016, 2017, and 2019; Kolb et al., 2020; McTigue et al., 2014; Ruhl et al., 2012;
States et al., 2013; U.S. DOJ, 2015; U.S. EPA, 2015c).
Bromide is highly soluble and nonreactive in freshwater systems and is consequently used as a
tracer for hydrology field studies (Brantley et al., 2014; Cowie et al., 2014; Cox et al., 2003;
Flury and Papritz, 1993; Writer et al., 2011). Because of this stability, studies of bromide fate
and transport in freshwater systems focus on downstream transport and dilution of mass loadings
in surface water flow volume (Cornwell et al., 2018; Good and VanBriesen, 2016, 2017, and
2019; Harkness et al., 2015; Ruhl et al., 2012; States et al., 2013; Weaver et al., 2015; Wilson
and VanBriesen, 2013).
Bromide's toxicity in freshwater aquatic environments is low relative to substances such as
copper or cadmium cations. Reviews of freshwater aquatic organism toxicology studies cite
effect concentrations that range from 110 to 4,600 mg/L for single-celled organisms, 2.2 to
11,000 mg/L for invertebrates, and 7.8 to 24,000 mg/L for fish (EPRI, 2014; Flury and Papritz,
1993). Bromide's toxicity for human beings through oral ingestion is also low relative to other
substances. The World Health Organization (WHO) estimates that consumption of drinking
water supplies with bromide concentrations below 2.0 mg/L would meet acceptable daily intake
levels for both children and adults (WHO, 2009). As noted in Section 2.1.1, bromide also
contributes to TDS levels, salinity levels, and potential associated effects in surface waters.
While bromide's direct toxicity is relatively low, toxicity associated with its contribution to DBP
formation in drinking water treatment and distribution systems can be greater (Krasner et al.,
2006; Krasner, 2009; Regli et al., 2015; Richardson and Postigo, 2011; U.S. EPA, 2016a; Yang
et al., 2014). DBPs are a broad class of compounds that form as byproducts of drinking water
disinfection, some of which have toxic properties. Bromide in source water becomes highly
reactive in the presence of commonly used drinking water disinfectants and can form brominated
DBPs (Br-DBPs) at low source water concentrations (Bond et al., 2014; Chang et al., 2001; Heeb
et al., 2014; Landis et al., 2016; Parker et al., 2014; Richardson et al., 2007; U.S. EPA, 2016a;
Wang et al., 2017; Westerhoff et al., 2004). While multiple factors affect DBP formation9,
increases and decreases in source water bromide levels are generally associated with concurrent
increases and decreases in both total DBP and bromide speciation levels in treated water
(AWWARF and U.S. EPA, 2007; Bond et al., 2014; Cornwell et al., 2018; Ged and Boyer, 2014;
Hua et al., 2006; Huang et al., 2019; Landis et al., 2016; McTigue et al., 2014; Obolensky and
9 Additional factors influencing DBP formation include pH, temperature, disinfection process type and dosage level,
organic material levels and type, and treatment and distribution system residence time (Brown et al., 2011; Hong et
al., 2013; Obolensky and Singer, 2008).
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Singer, 2008; Pan and Zhang, 2013; Regli et al., 2015; Sawade et al., 2016; States et al., 2013;
Yang and Shang, 2004; Zha et al., 2014).
Toxicology and epidemiology studies have documented evidence of genotoxic (including
mutagenic), cytotoxic, and carcinogenic properties of DBPs, including Br-DBPs (National
Toxicology Program, 2018; Richardson et al., 2007; U.S. EPA, 2016a). Studies have
documented evidence of a linkage between DBP exposure and bladder cancer and, to a lesser
degree, colon and rectal cancer, other cancers, and reproductive and developmental effects
(Cantor et al., 2010; Chisholm, 2008; Regli et al., 2015; Richardson et al., 2007; U.S. EPA,
2016a; Villanueva et al., 2004, 2007, and 2015). Br-DBPs generally have higher toxicity than
their chlorinated analogues (Cortes and Marcos, 2018; Plewa et al., 2008; Richardson et al.,
2007; Sawade et al., 2016; U.S. EPA, 2016a; Yang et al., 2014). Due to bromide's reactivity and
DBP toxicity, elevated bromide levels in source waters have been associated with elevated health
risks from disinfected water (Hong et al., 2007; Kolb et al., 2017a; Regli et al., 2015; Sawade et
al., 2016; Wang et al., 2017; Yang et al., 2014).
Table 2-1 lists the Maximum Contaminant Level (MCL) limits that EPA has issued for select
DBPs in disinfected drinking water. These limits are intended to serve as indicator metrics for
control of total DBPs of which more than 700 individual species have been identified to date
(Richardson and Plewa, 2020; Richardson and Postigo, 2011; U.S. EPA, 2006 and 2016a). The
DBP MCLs aim to balance the need for adequate disinfection to control human health risks from
microbial pathogens with the human health risks from DBPs (Li and Mitch, 2018; Plewa et al.,
2017; U.S. EPA, 2016a). DWTPs must produce water of a quality that complies with MCLs. The
Maximum Contaminant Level Goal (MCLG) limits listed in Table 2-1 reflect the level below
which there is no known or expected risk to human health and are not treatment level
requirements (U.S. EPA, 2009a).
DWTPs comply with DBP MCLs through a variety of techniques to adjust source water quality,
disinfection processes, and/or DBP removal as needed (McGuire et al., 2014; U.S. EPA, 2016a).
Source water quality control through direct bromide removal is infeasible in conventional
treatment systems (States et al., 2013) and instead requires specialized treatment processes (Chen
et al., 2008; CUWA, 2011; U.S. EPA, 2016a; Watson et al., 2012). In addition to cost and
operational feasibility considerations, many compliance approaches have human health risk
considerations because they modify, rather than eliminate, DBP mixtures and may not decrease
total human health risk (Bond et al., 2011; Cadwallader and VanBriesen, 2019; Francis et al.,
2010; Huang et al., 2017; Kolb et al., 2017b; Krasner, 2009; Li and Mitch, 2018; McGuire et al.,
2014; Plewa et al., 2017; U.S. EPA, 2016a; Wagner and Plewa, 2017; Watson et al., 2014)
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Table 2-1. Maximum Contaminant Levels (MCLs) and
Maximum Contaminant Level Goals (MCLGs) for Drinking
Water Disinfection Byproducts (DBPs)
Kouuliilod DBPs
MCI.
mci.c;
Bromate (plants that use ozone)
0.010 mg/L
Zero
Chlorite (plants that use chlorine dioxide)
1.0 mg/L
0.8 mg/L
Haloacetic Acids-5 (HAA5)
0.060 mg/L
--
Monochloroacetic acid
--
--
Dichloroacetic acid
--
Zero
Trichloroacetic acid
--
0.3 mg/L
Bromoacetic acid
--
--
Dibromoacetic acid
--
--
Total Trihalomethanes (TTHM)
0.080 mg/L
--
Chloroform
--
--
Bromodichloromethane
--
Zero
Dibromochloromethane
--
0.06 mg/L
Bromoform
--
Zero
Source: U.S. EPA, 2009a.
Acronyms: DBP (disinfectionbyproduct); mg/L (milligrams per liter).
Several studies have identified elevated bromide levels at DWTP intakes downstream of FGD
wastewater discharges from coal-fired steam electric power plants (McTigue et al., 2014; States
et al., 2013; U.S. DOJ, 2015; U.S. EPA, 2015c). Studies have also identified changes in total
DBP and Br-DBP levels at DWTPs corresponding to changes in upstream bromide discharges
(Cadwallader and VanBriesen, 2019; Cornwell et al., 2018; Marusak, 2017; McTigue et al.,
2014; States et al., 2013; U.S. DOJ, 2015; U.S. EPA, 2019c; Wang et al., 2017). The BCA
Report (U.S. EPA, 2020b) describes EPA's estimate of changes in bromides loadings from steam
electric power plants under the regulatory options, and the effects of these changes on
downstream DWTPs and associated human health risks.
In addition to their formation in DWTPs, Br-DBP formation has been documented in POTWs
and other wastewater treatment facilities that disinfect bromide-containing waters prior to
discharge (Chen et al., 2009; Hladik et al., 2014; Krasner, 2009; Pignata et al., 2011). A subset of
steam electric power plants transfers wastewater to POTWs (U.S. EPA, 2020a). Discharges from
the treatment facilities to surface waters could contribute to elevated Br-DBP levels in
downstream surface water drinking water sources and aquatic ecosystems. The toxicity of Br-
DBPs to organisms has been documented in laboratory settings but has not been well
characterized in natural aquatic environments (Butler et al., 2005; Chen et al., 2009;
Environment Canada and Health Canada, 2010; Hanigan et al., 2017; Soltermann et al., 2016).
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2.1.3 Iodine
Iodine is naturally present in coal.10 Some coal-fired steam electric power plants also add iodine
to their combustion processes to enhance mercury emissions control or burn refined coal
amended with iodide compounds (ADES, 2016; Gadgil, 2016; ICAC, 2019; Sahu, 2017; Senior
et al., 2016; Sjostrom et al., 2016; Sjostrom and Senior, 2019; Tinuum, 2020).11 Iodine
volatilizes during combustion and partitions to FGD wastewaters and, to a lesser extent, to
bottom ash transport waters (ADES, 2016; ICAC, 2019; Meij, 1994; Peng et al., 2013; Sjostrom
et al., 2016). In FGD wastewaters, iodine occurs as iodide/triiodide anions and elemental iodine
(Sjostrom et al., 2016). Limited data on typical iodine concentrations in FGD wastewater and
bottom ash transport waters are available, though methods have been proposed for maintaining
iodine concentrations in FGD wastewater below approximately 100 mg/L to ensure normal FGD
system operation and to recover iodine for reuse (Sjostrom et al., 2016).
Typical iodine levels in freshwater surface waters are less than 0.020 mg/L, though levels
ranging from 0.00001 to 0.212 mg/L have been reported.12 In freshwater, elemental iodine
dissociates to its anionic form and/or reacts with organic material to form iodinated organic
compounds. Iodide is highly soluble and exhibits conservative fate and transport in freshwater
(Fuge and Johnson, 1986; Moran et al., 2002).
Available data on iodide's ecotoxicity in freshwater aquatic environments suggests that it is
generally lower than that of substances such as copper or cadmium cations. Estimates of median
lethal toxic concentrations (LCso) for iodide range from 860 to 8,230 mg/L for freshwater fish
and from 0.17 to 0.83 mg/L for Daphnia magna, an aquatic invertebrate (Flury and Papritz,
1993; Laverock et al., 1995). Toxicity to single-celled organisms is reported to be similar to that
of bromide (Bringmann and Kiihn, 1980; Flury and Papritz, 1993). In comparison, elemental
iodine toxicity is higher for freshwater fish, with LCso concentrations from 0.53 mg/L to greater
than 10 mg/L, and is similar to iodide toxicity for D. magna, with LCso concentrations from 0.16
to 1.75 mg/L (Laverock et al., 1995; LeValley, 1982). As noted in Section 2.1.1, iodide also
contributes to TDS levels, salinity levels, and the potential associated effects in surface waters.
For humans, iodine is an essential element for thyroid hormone production and metabolic
regulation. Excessive consumption can lead to hypothyroidism (diminished production of thyroid
hormones), hyperthyroidism (excessive production and/or secretion of thyroid hormones), or
thyroiditis (inflammation of the thyroid gland) (ATSDR, 2004). The MRL for acute and chronic
oral exposure to iodide is 0.01 milligrams per kilogram-day (mg/kg-day) based on endocrine
effects (ATSDR, 2020a).
While iodide's direct toxicity is relatively low, toxicity associated with iodine's contribution to
DBP formation in drinking water treatment and distribution systems can be greater. DBPs are a
broad class of compounds, some of which have toxic properties, that form as byproducts of
10 Native iodine levels in coal range from 0.14 to 12.9 ppm (Bettinelli et al., 2002; Gluskoter et al., 1977; Good,
2018). One source states that many coals used by utility plants have iodine levels greater than 3 ppm (Sjostrom et
al., 2016).
11 Addition rates are reported to range from 1-30 ppm and are typically less than 10 ppm (Gadgil, 2016; ICAC,
2019; Sahu, 2017; Sjostrom etal., 2016).
12 The highest measured levels reflect influence of irrigation water return flows in arid areas.
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drinking water disinfection. Iodine in source water becomes reactive during chlorine-, chlorine
dioxide-, chloramine-, or ultraviolet (UV)-based disinfection and combines with organic material
in source waters to form iodinated DBPs (I-DBPs) (Bichsel and Von Gunten, 2000; Criquet et
al., 2012; Dong et al., 2019; Ersan et al., 2020; Hua et al., 2006; Hua and Reckhow, 2007;
Krasner, 2009; Krasner et al., 2006; Postigo and Zonja, 2019; Richardson et al., 2008; Tugulea et
al., 2018; U.S. EPA, 2016a; Weinberg et al., 2002). Both iodide and iodinated organic
compounds in source waters can contribute to I-DBP formation during drinking water
disinfection (Ackerson et al., 2018; Dong et al., 2019; Duirk et al., 2011; MacKeown et al., 2020;
Pantelaki and Voutsa, 2018; Tugulea et al., 2018). Iodate, a non-toxic iodine compound that can
form in the presence of oxidants (including certain DWTP disinfectants), can also contribute to I-
DBP formation under certain conditions (Dong et al., 2019; Postigo and Zonja, 2019; Tian et al.,
2017; Xia et al., 2017; Yan et al., 2016; Zhang et al., 2016). I-DBP levels are influenced by
multiple factors and have generally been found to increase with iodide or total iodine levels in
source water (Criquet et al., 2012; Dong et al., 2019; Gruchlik et al., 2015; Postigo and Zonja,
2019; Tugulea et al., 2018; Ye et al., 2013; Zha et al., 2014).13
In vitro toxicology studies with bacteria and mammalian cells have documented evidence of
genotoxic (including mutagenic), cytotoxic, tumorigenic, and developmental toxicity properties
of I-DBPs. Individual I-DBP species have higher toxicity than their chlorinated and brominated
analogues and are among the most cytotoxic DBPs identified to date (Dong et al., 2019; Hanigan
et al., 2017; National Toxicology Program, 2018; Richardson et al., 2007 and 2008; Richardson
and Plewa, 2020; U.S. EPA, 2016a; Wagner and Plewa, 2017; Wei et al., 2013; Yang et al.,
2014). While studies have documented evidence linking disinfected drinking water and DBP
exposure to adverse human health effects (see Section 2.1.2), additional research is needed to
characterize the contribution of I-DBPs to these effects (Cortes and Marcos, 2018; Dong et al.,
2019; Postigo and Zonja, 2019; U.S. EPA, 2016a). I-DBPs can also affect drinking water
aesthetics by creating medicinal flavors and odors that are detectable at low concentrations
(Cancho et al., 2000 and 2001; Hansson et al., 1987).
The MCLs and MCLGs listed in Table 2-1 do not include limits for I-DBPs in drinking water.
As noted in Section 2.1.2, the current limits address a subset of DBPs and are indicators for
control of total DBPs, of which more than 700 individual species have been identified to date
(Richardson and Plewa, 2020; Richardson and Postigo, 2011; U.S. EPA, 2006 and 2016a).
Because conventional drinking water treatment processes do not effectively remove iodide from
source waters and vary in their reduction of organic material levels (U.S. EPA, 2016a; Watson et
al., 2012), they have the potential to generate I-DBPs when their source waters contain iodine.
DWTPs are not required to monitor I-DBP levels in treated water and may not be aware of the
presence of I-DBPs in their systems (Tugulea et al., 2018). As DWTPs take steps to decrease
concentrations of regulated DBPs, their actions may or may not reduce I-DBP levels, depending
on the nature of the process change (Criquet et al., 2012; Dong et al., 2019; Gruchlik et al., 2015;
13 Additional factors influencing I-DBP formation include pH, temperature, disinfection process type and dosage
level, bromide levels, ammonium levels, organic material levels and type, and treatment and distribution system
residence time.
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Hua and Reckhow, 2007; Krasner, 2009; Li and Mitch, 2018; McGuire et al., 2014; Tugulea et
al., 2018; U.S. EPA, 2016a).
In addition to their formation in DWTPs, I-DBP formation has been documented in POTWs and
other wastewater treatment facilities that disinfect iodine-containing waters prior to discharge
(Gong and Zhang 2015; Hladik et al., 2014 and 2016). A subset of coal-fired steam electric
power plants transfers wastewater to POTWs (U.S. EPA, 2020a). Discharges from the treatment
facilities to surface waters could contribute to elevated I-DBP levels in downstream surface
waters, drinking water sources, and aquatic ecosystems. The toxicity of I-DBPs to organisms has
been documented in laboratory settings but has not yet been characterized in natural aquatic
environments (Hanigan et al., 2017; Hladik et al., 2016).There is limited information available
on the presence of iodine in the wastestreams addressed in this final rule (see Section 6.2.1 of the
Supplemental TDD).
2.2 Supplemental Literature Review on Environmental Impacts of Other
Pollutants in Discharges of the Evaluated Wastestreams
This section summarizes the new information identified in the supplemental literature review on
environmental impacts caused by exposure to pollutants in discharges of the evaluated
wastestreams other than TDS, bromine, and iodine (which are described in Section 2.1).
According to the recently published peer-reviewed studies summarized below, discharges from
coal-fired steam electric power plants have the potential to cause or contribute to ecological
impacts including lethal impacts, such as fish kills, and sublethal impacts, such as teratogenic
deformities, oxidative stress, deoxyribonucleic acid (DNA) damage, and genotoxicity (Brandt et
al., 2017 and 2019; Javed et al., 2016; Lemly, 2018). Additional information on ecological
impacts, human health effects, and documented cases of water quality impacts from coal-fired
steam electric power plants can be found in Section 3.3 of the 2015 Final EA. This section
discusses the findings of four additional studies identified in the supplemental literature review.
Lemly (2018) investigated selenium pollution from the E.W. Brown Electric Generating Station
in Herrington Lake, Kentucky, where coal ash wastewater discharged from ash disposal ponds
led to elevated selenium concentrations in water, sediment, benthic macroinvertebrates, and fish
tissue. The study found selenium levels two to nine times higher than the level that is toxic to
fish reproduction and survival (i.e., toxic thresholds of 1.5 micrograms per liter ((J,g/L) in water,
2 micrograms per gram (j_ig/g) in sediment, and 3 j_ig/g in macroinvertebrates) (Lemly, 2018;
U.S. EPA, 2016b). The study collected and examined juvenile largemouth bass (Micropterus
salmoides) and found that 12.2 percent displayed teratogenic deformities, including spinal,
craniofacial, and fin deformities. The abnormality rate is 25 times the background abnormality
rate (0.5 percent). Background abnormalities consist of only minor fin deformities. The
occurrences of morphological abnormalities and toxic levels of selenium in fish tissue confirm
that coal ash discharges into Herrington Lake are contributing to elevated toxicity in fish tissue.
The study findings were consistent with a previous study, conducted by the State of Kentucky in
2016 (KDEP, 2016), in which mature bluegill (Lepomis macrochirus) and mature largemouth
bass were collected from Herrington Lake and analyzed for toxic effects. The KDEP (2016)
study reported whole-body selenium concentrations that exceeded biological effects thresholds.
Nine out of the ten sampled fish exceeded EPA's national ambient water quality criterion of 8.5
milligrams of selenium per kilogram (mg/kg) of whole-body fish tissue (U.S. EPA, 2016b).
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Brandt et al. (2017) examined the impacts of selenium on freshwater ecosystems associated with
effluent discharges from coal-fired steam electric power plants. Selenium discharges can lead to
long-term issues in ecosystems due to prolonged retention in the environment and cycling and
propagation in the food chain. The study evaluated selenium samples from six North Carolina
lakes between 2010 and 2015. Three of the lakes received current or historical selenium
discharges from coal-fired steam electric power plants and the other three lakes did not receive
selenium discharges from coal-fired steam electric power plants (i.e., they were reference lakes14
that corresponded to each of the impacted lakes). Sutton Lake, which received the highest
selenium loading during the study period, had the highest level of selenium in aquatic organism
tissues.15 The study found that 85 percent of fish had muscle selenium concentrations exceeding
EPA's fish tissue-specific criterion of 11.3 mg/kg and 31 percent had ovary/egg selenium
concentrations exceeding the criterion of 15.1 mg/kg. Fish tissue samples from Mayo Lake
showed that 27 percent of fish had selenium concentrations exceeding the criterion and no
ovary/egg concentrations exceeding the criterion. Fish tissue and ovary/egg selenium
concentrations were significantly16 elevated in fish from all three lakes receiving historical or
current effluent discharges from coal-fired steam electric power plants relative to those from
their corresponding reference lakes.
In a subsequent study, Brandt et al. (2019) conducted further sampling in the same six lakes from
the 2017 study and evaluated the trends and relationships in concentrations of 10 parameters
(aluminum, arsenic, cadmium, copper, lead, manganese, nickel, selenium, strontium, and zinc)
between lakes and across environmental compartments (e.g., abiotic and biotic). In the abiotic
compartments, the authors found that average selenium levels in Sutton Lake exceeded the
National Recommended Water Quality Criteria (NRWQC) of 1.5 [j,g/L for chronic impacts to
freshwater aquatic life (see Table C-7); sediment concentrations of copper, arsenic, and selenium
were significantly higher in the lakes that received coal ash pond effluent and exceeded the
threshold effect concentrations (TECs) defined in MacDonald et al. (2000) for copper and
arsenic; and sediments from Sutton Lake also exceeded the probable effect concentrations for
copper, arsenic, and nickel, indicating likely toxic effects. The authors found that the majority of
parameters that were enriched in the abiotic compartments of lakes that received coal ash pond
effluent were also enriched in the biotic compartments. Specifically, lakes that received coal ash
pond effluent had significantly higher concentrations in fish liver tissues (driven by higher
concentrations of copper, zinc, and selenium); higher concentrations in fish muscle tissues
(primarily driven by selenium); and higher concentrations of nearly all parameters in biofilm and
zooplankton. The authors concluded that the potential impacts of coal ash pond effluent extend
beyond those posed by excess selenium accumulation, with coenrichment of at least three
parameters characterizing the burdens within all studied abiotic and biotic lake compartments,
and that these collective findings strongly support the conclusion that coal-fired steam electric
power plant effluents lead to multielement ecosystem contamination.
The literature also documented heavy metals originating from coal-fired steam electric power
plant discharges as being responsible for oxidative stress and genotoxicity in receiving water fish
14 The reference lakes are control locations that represent "natural" selenium introduction into the environment.
15 Collected aquatic organisms included largemouth bass (Micropterus salmoides), bluegill sunfish (Lepomis
macrochirus), redear sunfish (Lepomis microlophus), and redbreast sunfish (Lepomis auritus).
16 The exception was two cases (both ovary/egg selenium concentrations comparisons) in which the count of fish
collected was insufficient to establish a statistical difference.
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Section 2—Environmental and Human Health Concerns Associated with the Evaluated Wastestreams
species. Javed et al. (2016) collected the spotted snakehead (Channapunctatus) as a bioindicator
species to evaluate the impact of metal discharges on aquatic species. Javed et al. (2016) noted in
the study's introduction that before an increase in the plant's capacity in the 1970s, the receiving
water (a canal in Kasimpur, India) had a diverse fish population. Following an increase in
effluent discharges, numerous species disappeared. The author did not identify any studies that
examined whether the plant was the cause of the species loss. Their study evaluated fish tissue
samples for metal concentrations (chromium, cobalt, copper, iron, manganese, nickel, and zinc)
and fish biomarkers.17 Iron was highly bioavailable and accumulated in the liver, kidney, muscle,
and integument of the fish. Biomarkers showed oxidative stress and DNA damage in fish tissues.
The kidney was the most impacted organ, while muscle tissue was the least impacted. DNA
damage was observed at statistically significant levels in the fishes' gill cells and liver.
Evaluation of fish tissue appropriate for human consumption found that manganese fell above
the WHO benchmark of 1 mg/kg (Javed et al., 2016).
17 Biomarkers included lipid peroxidation (LPO), superoxide dismutase (SOD), catalase (CAT), glutathione S
transferase (GST), reduced glutathione (GSH), and DNA damage (Javed et al., 2016).
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Section 3—Overview of Methodology for the Supplemental Quantitative Environmental Assessment
SECTION 3
OVERVIEW OF METHODOLOGY FOR THE SUPPLEMENTAL
QUANTITATIVE ENVIRONMENTAL ASSESSMENT
This section provides an overview of EPA's methodology for quantitatively evaluating the
environmental and human health effects of discharges of the evaluated wastestreams to surface
waters.
3.1 Impact Areas Selected for Quantitative Assessment
An exposure pathway is the route a pollutant takes from its source (e.g., an emission stack or
wastewater outfall) to its endpoint (e.g., a surface water), and how receptors (e.g., wildlife or
people) can come into contact with it. This Supplemental EA focused the quantitative analysis on
the surface water exposure pathway and evaluated the pollutant loadings and impacts associated
with two wastestreams: flue gas desulfurization (FGD) wastewater and bottom ash transport
water.
EPA focused its quantitative assessment on the following wildlife and human health impacts
caused by discharges of the evaluated wastestreams to surface waters under baseline (i.e.,
following full implementation of the 2015 rule) and the potential changes in those impacts under
the final rule and each of the other regulatory options considered:
• Wildlife Impacts:
- Potential toxic effects to aquatic life based on changes in surface water quality—
specifically, exceedances of the acute and chronic National Recommended Water
Quality Criteria (NRWQC) for freshwater aquatic life.
- Potential toxic effects on sediment biota based on changes in sediment quality
within surface waters—specifically, exceedances of threshold effect
concentrations (TECs) for sediment biota.
- Bioaccumulation of contaminants and potential toxic effects on wildlife from
consuming contaminated aquatic organisms—specifically, exceedances of no
effect hazard concentrations (NEHCs), indicating a potential risk of reduced
reproduction rates in piscivorous wildlife.
• Human Health Impacts:
- Exceedances of the human health NRWQC based on two standards: 1) standard
for the consumption of water and organisms and 2) standard for the consumption
of organisms only.
- Exceedances of drinking water maximum contaminant levels (MCLs). Although
MCLs apply to drinking water produced by public water systems and not surface
waters themselves, EPA identified the extent to which immediate receiving waters
exceeded an MCL as an indication of the degradation of the overall water quality
following exposure to the evaluated wastestreams.
- Elevated cancer risk due to consuming fish caught from contaminated receiving
waters—specifically, instances where the calculated lifetime excess cancer risk
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Section 3—Overview of Methodology for the Supplemental Quantitative Environmental Assessment
(LECR) due to inorganic arsenic is greater than one excess cancer case risk per
one million lifetimes (also expressed as 10"6).
- Elevated non-cancer health risks (e.g., reproductive or neurological impacts) due
to consuming fish caught from contaminated receiving waters—specifically,
instances where the calculated average daily dose (ADD) of a pollutant exceeds
the oral reference dose (RfD) for that pollutant.
EPA performed this quantitative assessment using the Immediate Receiving Water (IRW)
Model, described later in this section. Appendices C, D, and E of this report and Section 5 of the
2015 Final EA (U.S. EPA, 2015a) provide additional details on the IRW Model and the water
quality, wildlife, and human health benchmark values selected for use in the evaluation of
environmental effects.
EPA also evaluated additional wildlife and human health impacts resulting from changes in
surface water quality, including impacts on threatened and endangered species; changes in
ecosystem services; and neurological effects from exposure to lead and mercury. The
methodologies and results of these analyses are presented in the BCA Report (U.S. EPA, 2020b).
All analyses compare changes under the final rule to the 2015 rule.
3.2 Scope of Evaluated Plants and Immediate Receiving Waters
EPA estimates that 427 coal-fired electric generating units operated at 218 plants will be
operating after December 31, 2028 (the date the final rule will be fully implemented) and could
be subject to the compliance dates in this final rule. Section 3 of the Supplemental TDD (U.S.
EPA, 2020a) describes how EPA updated the industry profile to reflect changes since the 2015
rule, including an assessment of impacts of other regulations affecting steam electric power
plants, such as the Coal Combustion Residual (CCR) Part A Rule.
Within this industry profile, EPA limited the scope of this Supplemental EA to the subset of 87
plants that discharge one or both of the evaluated wastestreams directly or indirectly to surface
waters under baseline and/or one or more regulatory options.18 The IRW Model, which excludes
discharges to the Great Lakes and estuaries, encompasses 82 plants that discharge to 89
immediate receiving waters.19 The IRW Model excludes Great Lake and estuarine immediate
receiving waters because the specific hydrodynamics and scale of the analysis required to
appropriately model and quantify pollutant concentrations in these types of waterbodies are more
complex than can be represented in the IRW Model.
Table 3-1 presents the number of plants, generating units, and immediate receiving waters
evaluated in this Supplemental EA. Figure 3-1 shows the locations of the immediate receiving
waters evaluated in this Supplemental EA and indicates those that are included in the IRW
modeling. See the memorandum titled "Receiving Waters Characteristics Analysis and
Supporting Documentation for the 2020 Steam Electric Supplemental Environmental
18 Of the 87 plants in this Supplemental EA, 86 plants discharge directly to surface water and one plant discharges
both directly to a surface water and indirectly to a publicly owned treatment works (POTW).
19 Seven of the 82 plants included in the IRW Model discharge to more than one immediate receiving water.
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Section 3—Overview of Methodology for the Supplemental Quantitative Environmental Assessment
Assessment" (ERG, 2020c) for the list of immediate receiving waters and for details regarding
EPA's methodology for identifying the immediate receiving waters.
The number of evaluated plants and generating units, and the number of the associated
immediate receiving waters, vary across baseline and the regulatory options evaluated for the
final rule. This is due to differences in the stringency of controls, applicability of these controls
based on subcategorization, and estimates of the control technologies that plants would
implement to meet requirements (see the preamble for details). Table 3-2 presents the number of
plants, generating units, and immediate receiving waters with nonzero pollutant loadings for
baseline and each regulatory option evaluated.
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Section 3—Overview of Methodology for the Supplemental Quantitative Environmental Assessment
Table 3-1. Plants, Generating Units, and Immediate Receiving Waters Evaluated in the
Supplemental EA
Calegon
Number r.\alualed in Polliilanl
Loadings Analysis. Downstream
Analysis, and Pro\imil\ Analysis
Suhsel Also l'.\aliialed
in IRW Model
Plants
87
82
Electric Generating Units
208
196
Immediate Receiving Waters
River/Stream
74
74
Lake/Pond/Reservoir
15
15
Great Lakesa
3
-
Estuary/Bay/Other
1
-
Total Immediate Receiving Waters
93
89
Source: ERG, 2020c and 2020d.
a - One Great Lake immediate receiving water receives discharges from two plants.
Table 3-2. Plants, Generating Units, and Immediate Receiving Waters with Pollutant
Loadings under Baseline and Regulatory Options
Category
Baseline
Option D"
Option A
Option B
Option C
Any
Scenario b
Pollutant Loadings, Downstream, and Proximity Analyses*
Plants
53
111
84
83
69
87
Electric Generating Units
131
250
201
198
167
208
Immediate Receiving Waters
53
111
90
89
69
93
Subset Also Evaluated in IRW Model"
Plants
50
104
79
78
66
82
Electric Generating Units
123
235
189
186
159
196
Immediate Receiving Waters
50
105
86
85
66
89
Source: ERG, 2020d.
a - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
b - Values do not account for Option D. See above footnote.
c - The IRW Model excludes discharges to the Great Lakes and estuaries because the specific hydrodynamics
and scale of the analysis required to appropriately model and quantify pollutant concentrations in these types of
waterbodies are more complex than can be represented in the IRW Model.
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Section 3—Overview of Methodology for the Supplemental Quantitative Environmental Assessment
93 Immediate Receiving Waters in Pollutant
Loadings, Downstream, and Proximity Analyses
Subset: 89 Rivers and Lakes Also Evaluated with
IRW Model
Figure 3-1. Locations of Immediate Receiving Waters Evaluated in the Supplemental EA
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Section 3—Overview of Methodology for the Supplemental Quantitative Environmental Assessment
3.3 Pollutant Loadings for the Evaluated Wastestreams
To support the quantitative evaluation of environmental impacts via the surface water exposure
pathway, EPA calculated plant-specific baseline and post-compliance pollutant loadings (in
pounds per year) for FGD wastewater and bottom ash transport water being discharged to surface
water or through publicly owned treatment works (POTWs) to surface water. EPA estimated
baseline pollutant loadings for these two wastestreams based on the requirements established in
the 2015 rule (i.e., baseline assumes full compliance with the 2015 rule), whereas the post-
compliance loadings represent full implementation of the regulatory options across all plants
subject to the requirements of the final rule. The Supplemental TDD describes how EPA
calculated estimates of the baseline and post-compliance pollutant loadings for each evaluated
wastestream.
One plant reported transferring wastewater to a POTW rather than discharging directly to surface
water. For these POTW transfers, EPA adjusted the baseline and post-compliance loadings to
account for pollutant removals expected during treatment at the POTW for each analyte.
Section 4.1 of this report presents the industry-wide annual baseline pollutant loadings for FGD
wastewater and bottom ash transport water, and the post-compliance pollutant changes (relative
to baseline) for each of the regulatory options.20 The plant-specific annual loadings were used
throughout the analyses described in the remainder of this section. The Supplemental EA did not
evaluate the impacts of any discharges other than the two evaluated wastestreams; therefore, the
pollutant loadings and subsequent quantitative analyses do not represent a complete assessment
of environmental impacts from coal-fired steam electric power plants.
In addition to calculating estimated plant-specific baseline and post-compliance pollutant
loadings, EPA also calculated pollutant loadings to represent current industry practices
conditions for FGD wastewater and bottom ash transport water. These loadings represent the
continued use of the existing technologies at each plant, and do not assume compliance with the
discharge limitations promulgated in the 2015 rule. The memorandum titled "Pollutant Loadings
Associated with Current Discharges of FGD Wastewater and Bottom Ash Transport Water"
(ERG, 2020e) describes EPA's methodology for calculating the current industry practices
loadings for each evaluated wastestream. EPA used these estimated loadings to assess the
potential for impacts that could occur due to factors including extended compliance deadlines;
discharges from generating units or plants that are subject to a subcategory with different
20 Pollutant loadings estimates reflect conditions expected after December 31, 2028 - the date the final rule will be
fully implemented. Baseline loadings reflect pollutant loadings in FGD wastewater and/or bottom ash transport
water to surface water or through POTWs to surface water and assume plants install the technologies selected as
BAT/PSES basis of the 2015 rule. Post-compliance loadings reflect pollutant loadings in FGD wastewater and/or
bottom ash transport water to surface water or through POTWs to surface water after full implementation of the final
rule technology options (i.e., assumes all plants subject to the requirements of the final rule will install and operate
wastewater treatment and pollution prevention technologies equivalent to the technology bases for the regulatory
options).
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Section 3—Overview of Methodology for the Supplemental Quantitative Environmental Assessment
requirements; and discharges from plants that elect to participate in the Voluntary Incentives
Program (VIP).21
The memorandum titled "Pollutant Loadings Analysis and Supporting Documentation for the
2020 Steam Electric Supplemental Environmental Assessment" (ERG, 2020d) provides
additional documentation of the Supplemental EA loadings analyses.
3.4 Overview of Immediate Receiving Water (IRW) Model
EPA used the IRW Model to complete the quantitative assessment of potential wildlife and
human health impacts described in Section 3.1. EPA used the same IRW Model described in the
2015 Final EA and incorporated updates to selected parameters and benchmark values, as
documented in Appendices C, D, and E.
The IRW Model evaluates impacts within the immediate surface water22 where discharges occur.
Section 4.2 presents the results of the IRW Model analyses based on baseline and post-
compliance pollutant loadings for the two evaluated wastestreams.
3.4.1 Structure of the IRW Model
The IRW Model has three interrelated modules: a Water Quality Module, a Wildlife Module, and
a Human Health Module, which are described in further detail below. Figure 3-2 provides an
overview of the IRW Model inputs and the connections among the three modules to support
EPA's modeling framework. Appendices C, D, and E describe the IRW Model equations, input
data, and environmental parameters in detail. The appendices also describe the limitations and
assumptions for each module. Section 5.1 of the 2015 Final EA provides additional information
on the IRW Model, including a detailed discussion of the equilibrium-partition modeling
methodology used in the Water Quality Module.
• Water Quality Module. This module uses plant-specific input data (annual average
pollutant loadings and cooling water flow rates) and surface water-specific
characteristic data (e.g., annual average flow rate, lake volume) to calculate annual
average total and dissolved pollutant concentrations in the water column and
sediment. The module compares these concentrations to selected water quality
benchmark values (NRWQC and MCLs) as an indicator of potential impacts on
aquatic life and human health. EPA supplemented these annual average outputs by
modeling the water column pollutant concentrations during best-case months (low
21 As described in the preamble, EPA included and evaluated a VIP as part of Options A, B, and D. The VIP
establishes more stringent effluent limitations, based on membrane filtration, for FGD wastewater in exchange for
additional time to comply with those limitations (until December 31, 2028).
22 The length of the immediate receiving water, as defined in the National Hydrography Dataset Plus (NHDPlus)
Version 2, generally ranges from approximately 0.25 to 5 miles; the longest immediate receiving water is 9.1 miles.
The upstream and downstream boundaries are defined in NHDPlus Version 2, and each plant outfall is located
somewhere along the associated immediate receiving water (i.e., the outfalls are not specifically indexed to the
upstream end, midpoint, or downstream end). See the memorandum titled "Receiving Waters Characteristics
Analysis and Supporting Documentation for the 2020 Steam Electric Supplemental Environmental Assessment"
(ERG, 2020c) for details on the immediate discharge zone and length of stream reach represented at each discharge
location.
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Section 3—Overview of Methodology for the Supplemental Quantitative Environmental Assessment
loadings and high flow rates, resulting in greater dilution) and worst-case months
(high loadings and low flow rates, resulting in less dilution) and comparing the results
to the NRWQC and MCLs.23
• Wildlife Module. This module uses the annual average water column pollutant
concentrations from the Water Quality Module to calculate the bioaccumulation of
pollutants in fish tissue, providing results for both trophic level 3 (T3) and trophic
level 4 (T4) fish.24 The module compares these concentrations, and the sediment
concentrations calculated by the Water Quality Module, to benchmark values that
represent potential impacts on exposed sediment biota (TECs)25 and piscivorous
wildlife (NEHCs). EPA selected minks and eagles as representative piscivorous
wildlife that consume T3 and T4 fish, respectively.
• Human Health Module. This module uses the fish tissue concentrations from the
Wildlife Module to calculate non-cancer and cancer risks to human populations from
consuming fish that are caught from contaminated receiving waters. EPA performed
this analysis using two sets of fish consumption rates:26
A "standard cohort" data set with consumption rates for recreational fishers and
subsistence fishers (and their families), with separate age categories for adult and
child fishers. Subsistence fishers are individuals who rely on self-caught fish for a
larger share of their food intake as compared to recreational fishers.
A data set with consumption rates for recreational and subsistence fishers in
different race categories (Non-Hispanic White; Non-Hispanic Black; Mexican-
American; Other Hispanic; and Other, including Multiple Races). EPA used this
data set in an Environmental Justice analysis to evaluate whether the post-
compliance change in human health impacts (relative to baseline) will
disproportionately impact minority groups.27
23 Data regarding actual monthly loadings were not available for this analysis. Therefore, EPA estimated monthly
loadings using monthly net electricity generation data at the electric generating unit level as an indicator of monthly
discharges of the evaluated wastestreams. Using monthly flow rate data for each immediate receiving water from
NHDPlus Version 2, EPA then identified the months that would produce the lowest (best-case) and highest (worst-
case) ratios of pollutant loadings to flow rates for each immediate receiving water and performed water quality
modeling for those selected months. See the memorandum titled "Monthly Water Quality Modeling Analysis and
Supporting Documentation for the 2020 Steam Electric Supplemental Environmental Assessment" (ERG, 2020k) for
further details.
24 T3 fish (e.g., carp, smelt, perch, catfish, sucker, bullhead, sauger) are those that primarily consume invertebrates
and plankton, while T4 fish (e.g., salmon, trout, walleye, bass) are those that primarily consume other fish.
25 In the case of the TEC for selenium, exceedances of the TEC represent potential impacts on higher trophic levels
due to consumption of sediment biota with elevated levels of selenium.
26 See the memorandum titled "Fish Consumption Rates Used in the EA Human Health Module" (ERG, 2015) for
details regarding the selection of fish consumption rates for these analyses.
27 See Chapter 14 of the BCA Report.
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Section 3—Overview of Methodology for the Supplemental Quantitative Environmental Assessment
Risk to
Sediment
Biota
Risk to
Human
Health
Risk to
Wildlife
Risk to
Human
Health
Risk to
Aquatic
Life and
Human
Health
Figure 3-2. Overview of I RW Model
EPA also assessed the potential for discharges of the evaluated wastestreams to cause or
contribute to fish advisories, thereby posing a human health risk. EPA compared the T4 fish
tissue concentrations from the Wildlife Module to fish consumption advisory screening values.
Screening values are defined as concentrations of target analytes in fish or shellfish tissue that
are of potential public health concern; they are used as threshold values to which levels of
contamination in similar tissue collected from the ambient environment can be compared.
Exceedance of these screening values indicates that more intensive site-specific monitoring
and/or evaluation of human health risks should be conducted (U.S. EPA, 2000a, Table 5-3).28
3.4.2 Pollutants Evaluated by IRW Model
In the 2015 Final EA, EPA focused the IRW Model quantitative analyses on 10 toxic pollutants,
all of which can bioaccumulate in fish and impact wildlife and human receptors via fish
consumption. These pollutants were arsenic, cadmium, hexavalent chromium (chromium VI),
28 See the memorandum titled "IRW Model: Water Quality, Wildlife, and Human Health Analyses and Supporting
Documentation for the 2020 Steam Electric Supplemental Enviromnental Assessment" (ERG, 2020j) for
documentation of the fish advisory screening level analysis.
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Section 3—Overview of Methodology for the Supplemental Quantitative Environmental Assessment
copper, lead, mercury, nickel, selenium, thallium, and zinc. Sections 4.1.2 and 5.1.1 of the 2015
Final EA provide additional discussion on the selection of these pollutants for evaluation using
the IRW Model.
For this Supplemental EA, EPA evaluated the same pollutants with the exception of chromium
VI.29 The Supplemental TDD describes EPA's methodology for estimating baseline and post-
compliance pollutant loadings for each evaluated wastestream.
As was the case with the 2015 Final EA, this Supplemental EA did not use water quality
modeling to assess the impacts associated with discharges of total dissolved solids (TDS),
bromides, chlorides, or nutrients (total nitrogen and total phosphorus). These pollutants were
excluded from the IRW Model analyses primarily because of the limited availability of national-
level numeric water quality, wildlife, and human health benchmark values for comparison with
the model outputs. EPA did include some of these pollutants in the surface water quality
modeling of immediate and downstream waters, which was performed for the economic benefits
analysis (see the BCA Report).
3.5 Downstream Analysis
As part of the economic benefits analysis, EPA used a separate pollutant fate and transport model
(D-FATE) to calculate the concentrations of pollutants in surface waters downstream from the
immediate receiving water for each plant that discharges FGD wastewater or bottom ash
transport water. See the BCA Report for a detailed discussion of the D-FATE model and the
analysis, which uses annual average pollutant loadings and surface water flow rates.
For this Supplemental EA, EPA used these downstream concentrations from D-FATE as inputs
for an analysis that identified which downstream reaches would have at least one exceedance of
a water quality, wildlife, or human health benchmark value under baseline or post-compliance
loadings. EPA used this approach to estimate the extent (in river miles) of impacts in
downstream surface waters under baseline and the changes in these impacts under the regulatory
options evaluated. Results are presented in Section 4.3 of this report. See the memorandum titled
"Downstream Modeling Analysis and Supporting Documentation for the 2020 Steam Electric
Supplemental Environmental Assessment" (ERG, 2020f) for details regarding the methodology
for this analysis.
29 The analytical data sets used to characterize the wastestreams evaluated for the 2015 rule included concentration
data for chromium VI. However, the analytical data sets characterizing wastestreams evaluated for this final rule do
not include concentration data for chromium VI. Therefore, EPA did not estimate baseline or post-compliance
chromium VI loadings for the final rule and did not evaluate the potential environmental and human health impacts
of this pollutant in this Supplemental EA.
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Section 3—Overview of Methodology for the Supplemental Quantitative Environmental Assessment
3.6 Proximity Analysis for Impaired Waters and Fish Consumption Advisory
Waters
As was the case with the 2015 Final EA, EPA performed a proximity analysis to identify:
• Immediate receiving waters that states, territories, and authorized tribes have
identified, pursuant to Section 303(d) of the Clean Water Act (CWA), as impaired
waterbodies that can no longer meet their designated uses (e.g., drinking, recreation,
and aquatic habitat) due to pollutant concentrations that exceed water quality
standards. These impaired waterbodies are also known as "CWA Section 303(d)-
listed waterbodies."
• Immediate receiving waters for which states, territories, and authorized tribes have
issued fish consumption advisories, which indicates that pollutant concentrations in
the tissues of fish inhabiting those waters are considered unsafe for human
consumption at any or some consumption levels.
Section 4.4 of this report presents the results of the proximity analysis. See the memorandum
titled "Proximity Analyses and Supporting Documentation for the 2020 Steam Electric
Supplemental Environmental Assessment" (ERG, 2020g) for a description of the proximity
analysis methodology.
EPA also performed further spatial analyses to identify public drinking water supply intakes
downstream from discharges of FGD wastewater and/or bottom ash transport water. See the
BCA Report regarding the methodology and results of that analysis.
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
SECTION 4
RESULTS OF THE SUPPLEMENTAL
QUANTITATIVE ENVIRONMENTAL ASSESSMENT
This section presents the estimated pollutant loadings in flue gas desulfurization (FGD)
wastewater and bottom ash transport water discharges—the evaluated wastestreams—under
baseline, the estimated pollutant loading changes associated with each of the regulatory options,
and the results of the quantitative analyses described in Section 3, which include the following:
• Use of EPA's Immediate Receiving Water (IRW) Model to:
- Estimate the annual average pollutant concentrations in immediate receiving
waters due to discharges of the evaluated wastestreams under baseline; estimate
the bioaccumulation of pollutants in fish tissue within those waters; and estimate
the daily and lifetime pollutant exposure doses among humans who consume
those fish.
Compare those estimated concentrations and estimated exposure doses to various
benchmark values as indicators of potential water quality, wildlife, and human
health impacts (including Environmental Justice (EJ) concerns associated with
differential fish consumption rates).
- Evaluate the estimated changes in those impacts under the regulatory options.
- Perform a supplemental "best-case" and "worst-case" monthly water quality
analysis.
• Use of pollutant fate and transport model (D-FATE) outputs to estimate potential
water quality, wildlife, and human health impacts in downstream surface waters
under baseline and evaluate the estimated changes in those impacts under the
regulatory options.
• A proximity analysis to identify immediate receiving waters that are designated as
Clean Water Act (CWA) Section 303(d)-listed impaired waterbodies or have been
issued fish consumption advisories.
The BCA Report (U.S. EPA, 2020b) discusses EPA's evaluation of other impacts that were not
quantified in this Supplemental EA.
4.1 Estimated Pollutant Loadings for the Evaluated Wastestreams
EPA analyzed four regulatory options at proposal, the details of which were discussed in the
proposed rule (84 FR 64620). For the final rule, EPA evaluated four regulatory options as shown
in Table VII-1 of the preamble. Proposed regulatory Options 1, 2, 3, and 4 correspond generally
to regulatory Options D, A, B, and C considered in the final rule, but do contain some
differences as detailed in the preamble. Public commenters generally supported three of the
regulatory options that EPA proposed or variants thereof. The availability and achievability of
technologies with better pollutant removals, as well as the lack of public comments in support of
proposed regulatory Option 1, led EPA to focus updates to the Agency's analysis on the
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
remaining three regulatory options. EPA did not update the analyses for regulatory Option D, but
rather retained the results of the proposed rule analyses for this option. This section discusses
estimated annual pollutant loadings in the discharges of the evaluated wastestreams from coal-
fired steam electric power plants under baseline and each regulatory option evaluated for these
final revisions to the 2015 rule.
Under baseline, EPA estimates that the coal-fired steam electric power plant industry annually
discharges more than 1,530,000,000 pounds of pollutants in the evaluated wastestreams to
surface waters, either directly or via publicly owned treatment works (POTWs). Under the final
rule (Option A), EPA estimates that, once all plants in scope have implemented the provisions of
the final rule, this figure will decrease by 972,000 pounds relative to the 2015 rule baseline.
Table 4-1 presents the estimated total industry pollutant loadings, in pounds per year, for
baseline and estimated pollutant loadings changes for each regulatory option. EPA estimated the
changes in pollutant loadings by subtracting the baseline loadings from the post-compliance
loadings. Pollutant loadings and removals represent loadings once all plants and generating units
achieve compliance with the regulatory option presented. Values presented in this document do
not account for the timing or exact date of implementation (e.g., when treatment systems are
installed by the industry). The memorandum titled "Pollutant Loadings Analysis and Supporting
Documentation for the 2020 Steam Electric Supplemental Environmental Assessment" (ERG,
2020d) discusses EPA's methodology for estimating total industry pollutant loadings for baseline
and each regulatory option.
Table 4-1. Estimated Industry-Level Pollutant Loadings and Estimated Change in
Loadings by Regulatory Option
Regulatory Option
Estimated Total Industry Pollutant
Loadings
(lb/year)
Estimated Change in Total Industry
Pollutant Loadings
(Ib/vear)"
Baseline
1,530,000,000
--
Option D b
1,680,000,000
13,400,000
Option A
1,530,000,000
-972,000
Option B
1,510,000,000
-14,700,000
Option C
15,600,000
-1,510,000,000
Source: ERG, 2020d.
Note: Pollutant loadings and removals are rounded to three significant figures, so figures do not sum due to
independent rounding. For example, estimated changes in pollutant loadings from baseline for Option A are
calculated as 1,528,154,581 lb/year- 1,529,126,625 lb/year = -972,044 lb/year, which when rounded to three
significant figures becomes 1,530,000,000 - 1,530,000,000 in Table 4-1, but still results in -972,000 lb/year. See
the Supplemental TDD (U.S. EPA, 2020a) and DCN SE08644 for details.
a - Negative values represent an estimated decrease in loadings to surface waters compared to baseline. Positive
values represent an estimated increase in loadings to surface waters compared to baseline,
b - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
The pollutants with the greatest estimated reductions in annual mass loadings under Option A are
bromide (2,850,000 lb/year decrease relative to baseline), magnesium (2,640,000 lb/year
decrease), chloride (1,550,000 lb/year decrease), total dissolved solids (TDS) (1,230,000 lb/year
decrease), boron (144,000 lb/year decrease), iodine (12,300 lb/year decrease), and manganese
(10,800 lb/year decrease).30 However, loadings for 29 out of 38 pollutants for which EPA
calculated loadings, including all the bioaccumulative pollutants and metals modeled in the IRW
Model, will have slightly higher loadings under Option A relative to baseline.31
This Supplemental EA and the 2015 Final EA (U.S. EPA, 2015a) focus on a subset of the
pollutants for which EPA calculated loadings. Table 4-2 presents estimated pollutant loadings
under baseline and pollutant loadings changes for each of the regulatory options for this subset of
pollutants. The memorandum titled "Pollutant Loadings Analysis and Supporting Documentation
for the 2020 Steam Electric Supplemental Environmental Assessment" (ERG, 2020d) discusses
EPA's methodology for estimating pollutant loadings for each immediate receiving water and
presents pollutant loadings under baseline and the net change associated with each of the
regulatory options for all 38 pollutants for which EPA calculated loadings.
Table 4-2 presents estimated changes in pollutant loadings that would be achieved after industry-
wide implementation of the control technologies needed to comply with any applicable effluent
limitations at each plant. The pollutant loadings for each plant account for all verified
retirements, fuel conversions, and updates to wet FGD systems, FGD wastewater treatment, and
bottom ash handling systems expected to occur by December 31, 2028.32 Implementation timing
for each plant varies by regulatory option, wastestream, subcategorization, and the plant's permit
renewal schedule. Plants would implement bottom ash transport water control technologies no
later than December 31, 2025. Plants would implement FGD wastewater control technologies by
December 31, 2025 under Options A and B; and by December 31, 2028 under Option C. Under
Options A and B, plants participating in the Voluntary Incentives Program (VIP) may implement
FGD wastewater controls by December 31, 2028.33 See the preamble for further discussion of
the regulatory options and associated compliance deadlines.
Due to the differing compliance timelines for individual wastestreams and plants, the net change
in pollutant loadings and corresponding environmental changes will be staggered over time as
the plants implement control technologies. This Supplemental EA presents EPA's estimates of
30 EPA did not identify data indicating the specific halogen additive (i.e., bromine or iodine) used at each plant to
reduce mercury emissions. Therefore, EPA estimated potential ranges of bromide and iodine loadings as described
in the footnotes to Table 4-2. Changes in halogen loadings relative to baseline are represented by the "Bromide
(max)" and "Iodine (min)" loadings calculations given that the majority of plants use bromide additives, but actual
loadings may be lesser or greater, respectively.
31 Under Option A, EPA estimates that some plants will decrease FGD wastewater pollutant loadings by recycling
FGD wastewater (reducing total flow of FGD wastewater discharged), installing the Option A technology basis, or
by participating in the VIP (installing membrane filtration). Other plants are estimated to have increases in total
pollutant loadings, based on new subcategories and the purge allowance for high recycle rate systems for bottom ash
transport water.
32 EPA did not adjust pollutant loadings and removals estimates to account for planned changes in operation that 1)
were not verified by February 2020 or 2) are expected to occur after December 31, 2028.
33 EPA estimates that 8 of 61 plants discharging FGD wastewater (13 percent) may conclude that the VIP for FGD
wastewater under Option A is the least costly option. The Supplemental TDD describes how EPA estimated which
technology would be the least costly for each plant.
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
post-compliance environmental changes associated with each regulatory option using steady-
state annual average pollutant loadings reflecting full implementation of the effluent limitations.
Therefore, the results presented in this Supplemental EA may underestimate short-term
environmental impacts for the period prior to full implementation of the regulatory options
during which plants transition from current discharges to discharges associated with full
implementation.
Table 4-2. Estimated Annual Baseline Mass Pollutant Loadings and Estimated Change in
Loadings Under Regulatory Options for the Evaluated Wastestreams (Supplemental EA
Subset of Pollutants)
Pollutant
llsliiiiiilcd
liasclinc Ptilliiliinl
Loadings (ll)Aoiii')
r.Mimak'd ( huntie in Ptilliiliinl Loadings Kelali\o to liasolinc
(ll>/M-ar)
Option 1)
Option A
Option 1}
Option (
Aluminum
7,570
8,780
16,800
10,100
2,710
Arsenic
368
95.7
178
105
-256
Boron
14,300,000
54,600
-144,000
-219,000
-14,200,000
Bromide (min)0
2,740,000
52,500
-73,600
-116,000
-2,680,000
Bromide (max)0
24,200,000
52,500
-2,850,000
-2,890,000
-24,200,000
Cadmium
265
7.41
9.60
3.36
-256
Chloride
452,000,000
3,300,000
-1,550,000
-5,110,000
-448,000,000
Chromium
406
52.2
93.4
52.9
-345
Copper
238
40.6
73.9
42.7
-190
Iodine (min)0
195,000
NAd
-12,300
-12,500
-195,000
Iodine (max)0
700,000
NAd
-117,000
-117,000
-700,000
Iron
7,000
6,950
13,200
7,980
1,130
Lead
214
107
202
121
-88.4
Magnesium
214,000,000
573,000
-2,640,000
-3,580,000
-214,000,000
Manganese
790,000
1,570
-10,800
-13,900
-788,000
Mercury
3.19
6.55
3.17
1.16
-1.96
Nickel
398
355
377
202
-188
Nitrogen, Totale
474,000
5,970,000
1,340,000
22,200
-442,000
Phosphorus, Total
20,300
2,280
4,030
2,260
-17,600
Selenium
362
57,900
12,800
140
-215
TDS
1,530,000,000
13,200,000
-1,230,000
-14,900,000
-1,510,000,000
Thallium
619
11.7
11.6
1.28
-605
Vanadium
802
104
187
106
-680
Zinc
1,260
347
647
381
-851
Totalf
707,000,000
10,000,000
-5,810,000
-11,800,000
-702,000,000
Source: ERG, 2020d.
Acronyms: lb/year (pounds per year); TDS (total dissolved solids).
Note: Pollutant loadings and removals are rounded to three significant figures, so figures may not sum due to
independent rounding.
a - Negative values represent an estimated decrease in loadings to surface waters compared to baseline. Positive
values represent an estimated increase in loadings to surface waters compared to baseline.
4-4
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
b - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
c - EPA did not identify data indicating the specific halogen additive (i.e., bromine or iodine) used at each plant to
reduce mercury emissions. Therefore, EPA estimated potential ranges of bromide and iodine loadings. EPA
defined the ranges' lower and upper bounds as follows (ERG, 2020h and 2020i; U.S. EPA, 2020a):
Bromide (min): Bromide loadings in bottom ash transport water and FGD wastewater from native coal
content and the addition of bromide in the flue gas (i.e., as brominated activated carbon).
Bromide (max): Same as "Bromide (min)" plus bromide loadings due to the use of refined coal or
halogen addition at the boiler. Assumes all plants burning refined coal or adding halogens at the boiler
use bromine additives.
Iodine (min): Iodine loadings in FGD wastewater from native coal content only. EPA had insufficient
data to estimate iodine loadings in bottom ash transport water.
Iodine (max): Same as "Iodine (min)" plus iodine loadings due to the use of refined coal or halogen
addition at the boiler. Assumes all plants burning refined coal or adding halogens at the boiler use iodine
additives.
d - EPA did not estimate iodine loadings as part of the proposed rule analysis.
e - Total nitrogen loadings are the sum of ammonia and total Kjeldahl nitrogen (TKN) for FGD wastewater and
the sum of nitrate-nitrite (as N) and TKN for bottom ash transport water.
f - Represents the summed loadings for the subset of pollutants focused on in the Supplemental EA, excluding
TDS (to avoid double-counting mass). Halogen loadings are represented by the sum of "Bromide (max)" and
"Iodine (min)" given that the majority of plants use bromide additives, but actual loadings may be lesser or
greater, respectively.
4.2 Key Impacts Identified by IRW Model
The IRW Model includes modules assessing potential changes in impacts on water quality,
wildlife, and human health in waters receiving discharges of the evaluated wastestreams from
coal-fired steam electric power plants.34 See Section 3 of this document and Appendices C, D,
and E for detailed discussions of the IRW Model's structure.
The following sections present the results from each module. The results identify modeled
exceedances of water quality, wildlife, and human health benchmark values under baseline and
the net changes in those exceedances under each regulatory option.35 Appendix F includes
additional IRW Model outputs.
4.2.1 Water Quality Module
The IRW Water Quality Module assesses the quality of surface waters that receive discharges of
the evaluated wastestreams by comparing estimated pollutant concentrations in the water column
to the National Recommended Water Quality Criteria (NRWQC) and drinking water maximum
34 This Supplemental EA encompasses a total of 93 immediate receiving waters and loadings from 87 plants (some
of which discharge to multiple receiving waters). The IRW Model, which excludes the Great Lakes and estuaries,
analyzes a total of 89 immediate receiving waters and loadings from 82 plants.
35 The net change represents the change in benchmark value exceedances under each regulatory option relative to
baseline. Under regulatory Options A, B, and C, there are scenarios in which some receiving waters no longer have
exceedances observed at baseline, and other immediate receiving waters have "new" exceedances. For example,
under regulatory Option C, increased discharges of bottom ash transport water result in a net increase in
exceedances despite the use of membrane treatment for FGD wastewater.
4-5
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
contaminant levels (MCLs) under baseline and each regulatory option. The module considers
modeled exceedances of the Freshwater Acute NRWQC, Freshwater Chronic NRWQC, Human
Health Water and Organism NRWQC, Human Health Organism Only NRWQC, and drinking
water MCL. Table 4-3 summarizes the Water Quality Module results. Table 4-4 presents the
number of immediate receiving waters with exceedances of any NRWQC or MCL by pollutant.
Table 4-3. Modeled IRWs with Exceedances of NRWQC and MCLs under Baseline and
Regulatory Options
\\ aler Qu;ili(> l.\ alualion
lienchmark
Number of Modeled IRWs l-lxceeding lienchmark Value
(Difference Kelali\e (o ISaseline)
ISaseline
Option 1)
Option A
Option 1}
Option (
Freshwater Acute NRWQC
0
2
(+2)
© o
© o
© o
Freshwater Chronic NRWQC
0
10
(+10)
0
(0)
0
(0)
0
(0)
Human Health Water and
Organism NRWQC
8
20
(+11)
17
(+9)
17
(+9)
13
(+5)
Human Health Organism Only
NRWQC
3
9
(+5)
7
(+4)
7
(+4)
6
(+3)
Drinking Water MCL
1
3
(+2)
1
(0)
1
(0)
0
(-1)
Total Number of Unique
Immediate Receiving Waters0
8
21
(+12)
17
(+9)
17
(+9)
13
(+5)
Source: ERG, 2020j.
Acronyms: IRW (immediate receiving water); MCL (maximum contaminant level); NRWQC (National
Recommended Water Quality Criteria).
a - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters). Of these 89 immediate
receiving waters, 50 receive discharges of the evaluated wastestreams under baseline, 86 under Option A, 85 under
Option B, and 69 under Option C.
b - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
c - Total may not equal the sum of the individual values because some immediate receiving waters have multiple
types of exceedances.
4-6
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
Table 4-4. Modeled IRWs with Exceedances of Any NRWQC or MCL, by Pollutant
under Baseline and Regulatory Options
Modeled Nil m her of IRWs r.\cmlin» NUWQC or M(l. (DiHemice Relati\e to
Pollutant
ISasolino)
liasclinc
Option 1)
Option A
Option 1}
Option (
Arsenic
8
20
17
17
13
(+11)
(+9)
(+9)
(+5)
Cadmium
0
0
0
0
0
(0)
(0)
(0)
(0)
Copper
0
0
0
0
0
(0)
(0)
(0)
(0)
Lead
0
1
0
0
0
(+1)
(0)
(0)
(0)
Mercury
0
0
0
0
0
(0)
(0)
(0)
(0)
Nickel
0
0
0
0
0
(0)
(0)
(0)
(0)
Selenium
0
10
0
0
0
(+10)
(0)
(0)
(0)
Thallium
3
5
3
3
0
(+1)
(0)
(0)
(-3)
Zinc
0
0
0
0
0
(0)
(0)
(0)
(0)
Any Pollutant0
8
21
17
17
13
(+12)
(+9)
(+9)
(+5)
Source: ERG, 2020j.
Acronyms: IRW (immediate receiving water); MCL (maximum contaminant level); NRWQC (National
Recommended Water Quality Criteria).
a - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters). Of these 89 immediate
receiving waters, 50 receive discharges of the evaluated wastestreams under baseline, 86 under Option A, 85 under
Option B, and 69 under Option C.
b - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
c - Total may not equal the sum of the individual values because some immediate receiving waters have
exceedances for multiple pollutants.
The Water Quality Module results described above are based on estimated annual average
loadings and flow rates. As described in Section 3.4, EPA also performed a water quality
analysis using estimated monthly pollutant loadings of the same nine pollutants evaluated in the
Water Quality Module and monthly surface water flow rates to assess the significance of
monthly variability in the modeled water quality impacts. Table 4-5 presents the number of
immediate receiving waters with modeled exceedances of each water quality benchmark in this
monthly analysis.
4-7
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
Table 4-5. Modeled IRWs with Exceedances of NRWQC and MCLs under Baseline and
Regulatory Options: Best- and Worst-Case Monthly Scenarios
Water Quality Evaluation
Modeled Number of IRWs Exceeding NRWQC or MCL
(Difference Relative to Baseline)"
Benchmark
Baseline
Option D
Option A
Option B
Option C
Best-Case Monthly Scenario (Lowest Ratio of Loadings to Flow Rate)
Freshwater Acute NRWQC
0
0
0
0
0
(0)
(0)
(0)
(0)
Freshwater Chronic NRWQC
0
4
0
0
0
(+4)
(0)
(0)
(0)
Human Health Water and
3
8
8
8
7
Organism NRWQC
(+4)
(+5)
(+5)
(+4)
Human Health Organism Only
2
4
3
3
1
NRWQC
(+2)
(+1)
(+1)
(-1)
Drinking Water MCL
0
0
0
0
0
(0)
(0)
(0)
(0)
Any Water Quality
3
8
8
8
7
Evaluation Benchmark0
(+4)
(+5)
(+5)
(+4)
Worst-Case Monthly Scenario (Highest Ratio of Loadings to Flow Rate) d
Freshwater Acute NRWQC
0
3
0
0
0
(+3)
(0)
(0)
(0)
Freshwater Chronic NRWQC
2
17
3
3
1
(+15)
(+1)
(+1)
(-1)
Human Health Water and
11
30
24
23
19
Organism NRWQC
(+17)
(+13)
(+12)
(+8)
Human Health Organism Only
5
16
15
15
11
NRWQC
(+9)
(+10)
(+10)
(+6)
Drinking Water MCL
2
6
2
2
0
(+3)
(0)
(0)
(-2)
Any Water Quality
11
32
24
23
19
Evaluation Benchmark0
(+19)
(+13)
(+12)
(+8)
Source: ERG, 2020k.
Acronyms: IRW (immediate receiving water); MCL (maximum contaminant level); NRWQC (National
Recommended Water Quality Criteria).
a - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters). Of these 89 immediate
receiving waters, 50 receive discharges of the evaluated wastestreams under baseline, 86 under Option A, 85 under
Option B, and 69 under Option C.
b - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
c - Total may not equal the sum of the individual values because some immediate receiving waters have multiple
types of exceedances.
d - The Human Health Water and Organism NRWQC, Human Health Organism Only NRWQC, and Drinking
Water MCL benchmark values are based on long-term (i.e., lifetime) exposure. This analysis estimates monthly
average concentrations only and therefore does not provide an assessment of average lifetime exposure levels.
The results of the monthly analysis are similar to those of the annual average analysis in that
total arsenic and, to a lesser extent, total thallium (for the Human Health Water and Organism
NRWQC in the best-case analysis) remain the primary drivers of the water quality exceedances
4-8
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
(ERG, 2020k). The monthly analysis also provides information beyond that provided by the
annual average analysis:
• Most worst-case months occur during the summer, whereas most best-case months
occur during the winter and early spring.
• Under the best-case monthly analysis, approximately half of immediate receiving
waters with exceedances in the annual average analysis continue to have exceedances
of at least one water quality benchmark value.
• Under the worst-case monthly analysis, a limited number of receiving waters
experience exceedances of the Freshwater Chronic NRWQC (compared to zero
identified in the annual average analysis). This suggests the potential for impacts on
aquatic life during certain periods characterized by low flows, high loadings, or a
combination of the two.
These results suggest that seasonal water quality impacts from discharges of the evaluated
wastestreams, and their increase under the regulatory options, may be more prevalent than
indicated by the annual average analysis (ERG, 2020k).
EPA evaluated whether there are geographic clusters of immediate receiving waters whose
worst-case months occur during the same time of year, indicating the potential for seasonal
cumulative effects in the affected watersheds. Figure 4-1 illustrates the worst-case month
identified for each immediate receiving water in the supplemental monthly analysis. The analysis
shows the following geographic patterns:
• Nearly the entire length of the Ohio River has clusters of immediate receiving waters
with worst-case months during July, August, September, and October.
• The Allegheny River and Conemaugh River watersheds in western Pennsylvania have
a cluster of five immediate receiving waters with worst-case months during July or
August.
• Several other parts of the country have smaller clusters of immediate receiving waters
with worst-case months during the same season. Examples include the Mississippi
River watershed upstream of the confluence with the Missouri River (January) and
the Wabash River watershed in western Indiana (September and October).
The watersheds referenced above are examples of areas that could potentially experience adverse
seasonal cumulative effects due to concurrent, or nearly concurrent, discharges of evaluated
wastestreams from multiple plants. This dynamic could be particularly pronounced during
summer and early autumn. EPA expects that swimming, fishing, and boating in local waterways
are more common during these seasons, potentially increasing opportunities for exposure to
degraded water quality conditions in the immediate receiving waters.
4-9
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
Figure 4-1. Worst-Case Months for Water Quality Conditions in Immediate Receiving
Waters
Fish species that spawn in the affected waterways during these periods (including federally
threatened or endangered species) could have an increased potential for adverse impacts from
pollutant exposure, since the timing of their sensitive life stages would align with worst-case
water quality conditions. For example, the Northern madtom (Noturus stigmosus), a small
catfish, lives in tributaries along the Ohio River, including the lower Ohio watershed; it spawns
in June and July and is currently listed as endangered in Ohio. Since the Northern madtom
spawns during worst-case conditions in the Ohio River watershed, it could experience reduced
fecundity and its population could he further compromised by seasonal fluctuations in pollutant
loadings from coal-fired steam electric power plants.
Data regarding actual monthly loadings were not available for this analysis. This analysis is
intended only to illustrate that seasonal impacts resulting from discharges of the evaluated
wastestreams, and the increase in those impacts under the final rule, may be more extensive than
shown in the annual average analysis, and that some watersheds (not necessarily the examples
noted in this discussion) could experience increased seasonal impacts depending on the seasonal
discharge patterns of plants in those watersheds.
4.2.2 Wildlife Module
The 1RVV Wildlife Module compares sediment pollutant concentrations to threshold effect
concentrations (TECs) for sediment biota; calculates the bioaccumulation of pollutants in trophic
4-10
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
level 3 (T3) and trophic level 4 (T4) fish tissue; and compares these tissue concentrations to no
effect hazard concentrations (NEHCs) for minks and eagles. This analysis expands on the
evaluation of potential wildlife impacts based on the Freshwater Chronic and Acute NRWQC in
the Water Quality Module.
Table 4-6 presents the number of immediate receiving waters with modeled exceedances of the
TECs and NEHCs under baseline and changes in those exceedances under the regulatory options.
Results are presented for all pollutants in aggregate and individually for selenium and mercury,
which cause most of the exceedances.
Table 4-6. Modeled IRWs with Exceedances of TECs and NEHCs under Baseline and
Regulatory Options
Wildlife
Modeled Number of IRWs l.\ceedin» TI C or M.IK
l-'.\ illllill ifill
Pollutant
(Difference Kelati\e lo liaseline)
lienehmark
liaseline
Option 1)
Option A
Option 1}
Option (
Sediment
Any Pollutant
2
20
5
5
4
TEC
(+18)
(+3)
(+3)
(+2)
Cadmium d
1
0
1
1
0
(0)
(0)
(0)
(-1)
Nickel
0
3
2
2
1
(+3)
(+2)
(+2)
(+1)
Selenium
2
20
5
5
4
(+18)
(+3)
(+3)
(+2)
Mercury
0
5
2
2
1
(+5)
(+2)
(+2)
(+1)
Fish Ingestion
Any Pollutant
0
10
1
1
1
NEHC for
(+10)
(+1)
(+1)
(+1)
Minks
Selenium
0
9
0
0
0
(+9)
(0)
(0)
(0)
Mercury
0
3
1
1
1
(+3)
(+1)
(+1)
(+1)
Fish Ingestion
Any Pollutant
1
11
4
4
2
NEHC for
(+10)
(+3)
(+3)
(+1)
Eagles
Selenium
0
9
0
0
0
(+9)
(0)
(0)
(0)
Mercury
1
6
4
4
2
(+5)
(+3)
(+3)
(+1)
Any Wildlife Pollutant
2
20
5
5
4
Benchmark for Any Pollutante
(+18)
(+3)
(+3)
(+2)
Source: ERG, 2020j.
Acronyms: IRW (immediate receiving water); TEC (Threshold Effect Concentration); NEHC (No Effect Hazard
Concentration).
a - Appendix F presents results for all individual modeled pollutants.
b - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters). Of these 89 immediate
receiving waters, 50 receive discharges of the evaluated wastestreams under baseline, 86 under Option A, 85 under
Option B, and 69 under Option C.
c - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
d - Cadmium exceedances, though noted in Table F-3, were omitted from Table 4-6 in the 2019 Supplemental EA
(U.S. EPA, 2019a).
4-11
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
e - Total may not equal the sum of the individual values because some immediate receiving waters have multiple
types of exceedances.
4.2.3 Human Health Module
The IRW Human Health Module evaluates non-cancer and cancer human health impacts among
various human cohorts (recreational and subsistence fishers; children and adults; and different
race categories) from consuming fish caught from immediate receiving waters that are
contaminated by discharges of the evaluated wastestreams. The module uses oral reference doses
(RfDs) to evaluate changes in non-cancer health risks, and a lifetime excess cancer risk (LECR)
benchmark value of one-in-a-million, or 10"6. This analysis expands on the evaluation of
potential human health impacts based on the NRWQC and MCLs in the Water Quality Module.
Under baseline, EPA estimates the average daily doses (for one or more pollutants) among
subsistence fishers exceed the oral RfDs (non-cancer) in 6 to 9 percent of immediate receiving
waters, depending on the age group evaluated. Average daily doses among recreational fishers
exceed oral RfDs in 3 to 6 percent of immediate receiving waters. The exceedances are primarily
driven by thallium and mercury (as methylmercury). The lower prevalence of exceedances
among recreational fishers is primarily due to their lower average fish tissue consumption rates.
These results suggest that fish in immediate receiving waters can have non-cancer health effects
on surrounding fisher populations.
EPA estimates that the number of immediate receiving waters contributing to oral RfD (non-
cancer) exceedances increases for all standard cohorts (i.e., cohorts that are not split into
different race categories) under all regulatory options. Under Option A, EPA estimates that
average pollutant concentrations in fish tissue increase for all modeled pollutants relative to
baseline concentrations. The pollutants that cause increased potential for non-cancer health
effects based on oral RfDs are mercury (as methylmercury), selenium, and thallium. For
example, the number of immediate receiving waters with methylmercury concentrations that
pose a non-cancer risk to humans increases from 2 to 6 percent (under baseline) to 7 to 17
percent (under Option A), with the specific increase depending on the cohort. Table 4-7 presents
the number of immediate receiving waters where the average daily dose of the modeled
pollutants exceeds the corresponding oral RfD.
Although EPA did not directly assess the potential non-cancer health effects posed by lead in this
Supplemental EA,36 Option A increases the annual loadings of lead to the environment by 202
pounds per year compared to baseline. The monetized human health effects associated with
changes in lead discharges are discussed in the BCA Report.
36 EPA has not developed an RfD for lead because adverse health effects "may occur at blood lead levels so low as
to be essentially without a threshold" (U.S. EPA, 2019e).
4-12
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
Table 4-7. Modeled IRWs with Exceedances of Oral RfD (Non-Cancer Human Health
Effects) under Baseline and Regulatory Options
Age iiiid I'ishinii
Mode Cohort
Pollutant
Modeled Number of IRWs r.\cmlin» Oral Kl'l)
(DilToivnce Kclali\c to ISasolino)
liasclini-
Option 1)
Option A
Option 1}
Option C
Child - Recreational
Any Pollutant
5
15
(+9)
10
(+5)
10
(+5)
7
(+2)
Mercury (as
methylmercury)
4
11
(+6)
9
(+5)
9
(+5)
7
(+3)
Selenium
0
9
(+9)
0
(0)
0
(0)
0
(0)
Thallium d
5
9
(+3)
7
(+2)
7
(+2)
3
(-2)
Child - Subsistence
Any Pollutant
8
23
(+14)
16
(+8)
15
(+7)
11
(+3)
Mercury (as
methylmercury)
5
19
(+13)
15
(+10)
14
(+9)
11
(+6)
Selenium
2
16
(+14)
4
(+2)
4
(+2)
2
(0)
Thallium d
8
14
(+5)
9
(+1)
9
(+1)
5
(-3)
Adult - Recreational
Any Pollutant
3
10
(+6)
7
(+4)
7
(+4)
6
(+3)
Mercury (as
methylmercury)
2
10
(+7)
6
(+4)
6
(+4)
6
(+4)
Selenium
0
6
(+6)
0
(0)
0
(0)
0
(0)
Thallium d
3
6
(+2)
4
(+1)
4
(+1)
1
(-2)
Adult - Subsistence
Any Pollutant
5
16
(+10)
10
(+5)
10
(+5)
7
(+2)
Mercury (as
methylmercury)
5
14
(+8)
10
(+5)
10
(+5)
7
(+2)
Selenium
0
10
(+10)
1
(+1)
1
(+1)
0
(0)
Thallium d
5
10
(+4)
8
(+3)
8
(+3)
5
(0)
Any Pollutant and Age/Consumption
Cohorte
8
23
(+14)
16
(+8)
15
(+7)
11
(+3)
Source: ERG, 2020j.
Acronyms: IRW (immediate receiving water); RfD (reference dose),
a - Appendix F presents results for each individual modeled pollutant.
b - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters). Of these 89 immediate
receiving waters, 50 receive discharges of the evaluated wastestreams under baseline, 86 under Option A, 85 under
Option B, and 69 under Option C.
c - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
d -EPA used the chronic oral exposure value cited in U.S. EPA, 2012 for soluble thallium as the RfD.
e - Total may not equal the sum of the individual values because some immediate receiving waters have
exceedances for multiple pollutants and/or cohorts.
4-13
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
Under baseline and the final regulatory options, EPA estimates that none of the immediate
receiving waters would contain fish contaminated with inorganic arsenic that present cancer risks
greater than the LECR benchmark value of one in one million for the most sensitive, standard
cohort. Table 4-8 presents the number of immediate receiving waters where the LECR for
inorganic arsenic exceeds one-in-a-million, which occurred only under Option D (i.e., proposed
Option 1). The BCA Report further discusses EPA's assessment of potential cancer impacts for
human populations.
Table 4-8. Modeled IRWs with LECR Greater Than One-in-a-Million (Cancer Human
Health Effects) under Baseline and Regulatory Options
Modeled Number of IRWs with LECR Greater than One-in-a-Million
Age and Fishing Mode Cohort
(Difference Relative to Baseline) '
Baseline
Option D
Option A
Option B
Option C
Child - Recreational
0
0
0
0
0
(0)
(0)
(0)
(0)
Child - Subsistence
0
0
0
0
0
(0)
(0)
(0)
(0)
Adult - Recreational
0
1
0
0
0
(+1)
(0)
(0)
(0)
Adult - Subsistence
0
1
0
0
0
(+1)
(0)
(0)
(0)
Total Number of Unique
0
1
0
0
0
Immediate Receiving Waters0
(+1)
(0)
(0)
(0)
Source: ERG, 2020j.
Acronyms: IRW (immediate receiving water); LECR (lifetime excess cancer risk).
a - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters). Of these 89 immediate
receiving waters, 50 receive discharges of the evaluated wastestreams under baseline, 86 under Option A, 85
under Option B, and 69 under Option C.
b - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
c - Total may not equal the sum of the individual values because some immediate receiving waters have
exceedances for multiple cohorts.
EPA also performed an Environmental Justice (EJ) analysis, using fish consumption rates for
recreational and subsistence fishers in different race categories, to assess whether the post-
compliance change in human health impacts (relative to baseline) will disproportionately impact
minority groups. Table 4-9 presents the number of immediate receiving waters in which the
modeled average daily dose of mercury, selenium, or thallium exceeds the oral RfD. Results are
presented by cohort (recreational and subsistence fisher) and race category.
Appendix E describes the Human Health Module and Appendix F presents the non-cancer and
cancer risk results for each age group (for both standard and EJ cohorts).
4-14
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
Table 4-9. Modeled IRWs with Exceedances of Oral RfD (Non-Cancer Human Health Effects), by Race Category, under
Baseline and Regulatory Options
Age and Fishing
Mode Cohort
Race Category
Modeled Number of IRWs Exceeding Oral Rt'D
(Difference Relative to Baseline) '1
Baseline
Option D1'
Option A
Option B
Option C
Mercury (as methylmercury)
Recreational
Non-Hispanic White
2
10 (+7)
6 (+4)
6 (+4)
6 (+4)
(All age cohorts)
Non-Hispanic Black
2
10 (+7)
6 (+4)
6 (+4)
6 (+4)
Mexican-American
2
11 (+8)
7 (+5)
7 (+5)
7 (+5)
Other Hispanic
2
10 (+7)
6 (+4)
6 (+4)
6 (+4)
Other, Including Multiple Races
2
11 (+8)
7 (+5)
7 (+5)
7 (+5)
Subsistence
Non-Hispanic White
4
14 (+9)
10 (+6)
10 (+6)
7 (+3)
(All age cohorts)
Non-Hispanic Black
5
14 (+8)
10 (+5)
10 (+5)
7 (+2)
Mexican-American
5
16 (+10)
11 (+6)
11 (+6)
8 (+3)
Other Hispanic
5
16 (+10)
11 (+6)
11 (+6)
8 (+3)
Other, Including Multiple Races
5
17 (+11)
12 (+7)
12 (+7)
9 (+4)
Selenium
Recreational
Non-Hispanic White
0
6 (+6)
0(0)
0(0)
0(0)
(All age cohorts)
Non-Hispanic Black
0
6 (+6)
0(0)
0(0)
0(0)
Mexican-American
0
6 (+6)
0(0)
0(0)
0(0)
Other Hispanic
0
6 (+6)
0(0)
0(0)
0(0)
Other, Including Multiple Races
0
6 (+6)
0(0)
0(0)
0(0)
Subsistence
Non-Hispanic White
0
10 (+10)
1 (+1)
1 (+1)
0(0)
(All age cohorts)
Non-Hispanic Black
0
10 (+10)
1 (+1)
1 (+1)
0(0)
Mexican-American
0
12 (+12)
3 (+3)
3 (+3)
1 (+1)
Other Hispanic
0
12 (+12)
3 (+3)
3 (+3)
1 (+1)
Other, Including Multiple Races
1
12 (+11)
3 (+2)
3 (+2)
1(0)
4-15
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
Table 4-9. Modeled IRWs with Exceedances of Oral RfD (Non-Cancer Human Health Effects), by Race Category, under
Baseline and Regulatory Options
Age and Fishing
Mode Cohort
Race Category
Modeled Number of IRWs Exceeding Oral RfD
(Difference Relative to Baseline) '1
Baseline
Option D1'
Option A
Option B
Option C
Thallium
Recreational
(All age cohorts)
Non-Hispanic White
3
6 (+2)
4 (+1)
4 (+1)
l(-2)
Non-Hispanic Black
3
6 (+2)
4 (+1)
4 (+1)
l(-2)
Mexican-American
4
7 (+2)
5 (+1)
5 (+1)
l(-3)
Other Hispanic
3
6 (+2)
4 (+1)
4 (+1)
l(-2)
Other, Including Multiple Races
4
7 (+2)
5 (+1)
5 (+1)
l(-3)
Subsistence
(All age cohorts)
Non-Hispanic White
5
10 (+4)
8 (+3)
8 (+3)
4 (-1)
Non-Hispanic Black
5
10 (+4)
8 (+3)
8 (+3)
5(0)
Mexican-American
5
11 (+5)
8 (+3)
8 (+3)
5(0)
Other Hispanic
5
11 (+5)
8 (+3)
8 (+3)
5(0)
Other, Including Multiple Races
7
14 (+6)
9 (+2)
9 (+2)
5 (-2)
Source: ERG, 2020j.
Acronyms: IRW (immediate receiving water); RfD (reference dose).
a - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters and loadings from 82 (some of which discharge
to multiple receiving waters). Of these 89 immediate receiving waters, 50 receive discharges of the evaluated wastestreams under baseline, 86 under Option A,
85 under Option B, and 69 under Option C.
b - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019 proposed rule (see Section 6.4 of the 2019
Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect changes in the baseline, plant universe, and other analytical inputs for the analysis of Options
A, B, and C.
4-16
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
EPA also compared T4 fish tissue pollutant concentrations to fish consumption advisory
screening values to assess the potential for discharges of the evaluated wastestreams to cause or
contribute to fish advisories and pose a human health risk.37 Based on the modeling results, up to
6 percent of the evaluated immediate receiving waters may contain fish with contamination
levels that could trigger advisories for recreational and/or subsistence fishers under baseline; this
increases to approximately 12 percent under Option A. Mercury and selenium are the pollutants
most likely to exceed screening values. Table 4-10 presents the number of immediate receiving
waters where the modeled T4 fish tissue concentrations exceed screening values used for fish
advisories.38
Table 4-10. Comparison of Modeled T4 Fish Tissue Concentrations to Fish Advisory
Screening Values under Baseline and Regulatory Options
Pollutant
Screening
Value (ppm)
Number of IRWs with Modeled T4 Fish Tissue Concentrations
Exceeding Screening Value (Difference Relative to Baseline)'
Baseline
Option D1'
Option A
Option B
Option C
Recreational Fishers
Arsenic (as
inorganic arsenic)
0.026
0
0(0)
0(0)
0(0)
0(0)
Cadmium
4
0
0(0)
0(0)
0(0)
0(0)
Mercury (as
methylmercury)
0.4
2
7 (+5)
4 (+2)
4 (+2)
3 (+1)
Selenium
20
0
5 (+5)
0(0)
0(0)
0(0)
Total for Any Pollutant in
Evaluated Wastestreams b
2
8 (+6)
4 (+2)
4 (+2)
3 (+1)
Subsistence Fishers
Arsenic
0.00327
0
0(0)
0(0)
0(0)
0(0)
Cadmium
0.491
0
0(0)
0(0)
0(0)
0(0)
Mercury (as
methylmercury)
0.049
5
16 (+10)
11 (+6)
11 (+6)
8 (+3)
Selenium
2.457
0
12 (+12)
3 (+3)
3 (+3)
1 (+1)
Total for Any Pollutant in
Evaluated Wastestreams 0
5
18 (+12)
11 (+6)
11 (+6)
8 (+3)
Sources: ERG, 2020j.
Acronyms: IRW (immediate receiving water); ppm (parts per million); T4 (trophic level 4).
a - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 (some of which discharge to multiple receiving waters). Of these 89 immediate receiving
waters, 50 receive discharges of the evaluated wastestreams under baseline, 86 under Option A, 85 under Option B,
and 69 under Option C.
37 For this analysis, EPA used the fish consumption advisory screening values from EPA's Guidance for Assessing
Chemical Contaminant Data for Uses in Fish Advisories, Volume 1 (U.S. EPA, 2000a).
38 As described in Section 4.4.2, none of the immediate receiving waters are under fish consumption advisories for
arsenic, cadmium, or selenium; each advisory screening value exceedance shown in Table 4-10 for these pollutants
therefore indicates a "new" receiving water of concern that may warrant additional monitoring and/or evaluation of
human health risk. Similarly, for mercury under Option A, 4 of the 11 immediate receiving waters with modeled
exceedances of the advisory screening value are "new" receiving waters of concern that are not under fish
consumption advisories for mercury.
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
b - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
c - Total may not equal the sum of the individual values because some immediate receiving waters are impaired for
multiple pollutants.
4.3 Impacts in Downstream Surface Waters
EPA performed an analysis of surface waters downstream from the immediate receiving water
for each plant that discharges the evaluated wastestreams. The downstream analysis uses the
outputs from a separate pollutant fate and transport model (see the BCA Report for a description
of the model) to assess potential water quality, wildlife, and human health impacts in
approximately 15,600 river miles of downstream surface waters. The methodology, which uses
estimated annual average pollutant loadings and surface water flow rates, is summarized in
Section 3.5 of this report and presented in further detail in the memorandum titled "Downstream
Modeling Analysis and Supporting Documentation for the 2020 Steam Electric Supplemental
Environmental Assessment" (ERG, 2020f).
Table 4-11 presents the results of this downstream analysis. This table lists each of the water
quality, wildlife, and human health benchmark values used in the IRW Model39 and indicates the
total length of downstream surface waters for which EPA calculated an exceedance of a
benchmark value for at least one of the modeled pollutants.
39 The water quality outputs used in the downstream analysis were derived from a pollutant fate and transport model
that does not simulate pollutant partitioning to the benthic layer; therefore, this analysis does not include
comparisons to the sediment TEC.
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
Table 4-11. Modeled Downstream River Miles with Exceedances of Any Pollutant
Evaluation Benchmark Value under Baseline and Regulatory Options
Evaluation Benchmark
Modeled Number of Downstream River Miles Exceeding Benchmark
Value (Difference Relative to Baseline)
Baseline
Option D11
Option A
Option B
Option C
Water Quality Results
Freshwater Acute NRWQC
1.13
4.66
(+4.66)
0
(-1.13)
0
(-1.13)
0
(-1.13)
Freshwater Chronic NRWQC
1.13
26.1
(+26.1)
0
(-1.13)
0
(-1.13)
0
(-1.13)
Human Health Water and
Organism NRWQC
70.1
143
(+78.5)
115
(+44.7)
115
(+44.7)
70.2
(+0.105)
Human Health Organism Only
NRWQC
16.3
43.4
(+23.9)
25.2
(+8.90)
25.2
(+8.90)
16.9
(+0.544)
Drinking Water MCL
3.69
7.84
(+5.28)
2.56
(-1.13)
2.56
(-1.13)
0
(-3.69)
Wildlife Results
Fish Ingestion NEHC for Minks
12.3
49.1
(+48.8)
5.91
(-6.36)
5.91
(-6.36)
1.45
(-10.8)
Fish Ingestion NEHC for Eagles
25.6
69.0
(+53.1)
24.1
(-1.53)
24.1
(-1.53)
17.0
(-8.65)
Human Health Results - Non-Cancer
Oral RfD for Child (Recreational)
71.7
90.4
(+47.8)
58.7
(-13.0)
58.7
(-13.0)
32.6
(-39.1)
Oral RfD for Adult (Recreational)
34.7
53.8
(+25.3)
35.0
(+0.331)
35.0
(+0.331)
26.6
(-8.03)
Oral RfD for Child (Subsistence)
306
179
(+77.8)
128
(-178)
128
(-178)
83.1
(-223)
Oral RfD for Adult (Subsistence)
129
110
(+60.3)
73.0
(-56.4)
73.0
(-56.4)
41.5
(-87.9)
Human Health Results - Cancer
LECR for Child (Recreational)
0
0
(0)
0
(0)
0
(0)
0
(0)
LECR for Adult (Recreational)
0
0
(0)
0
(0)
0
(0)
0
(0)
LECR for Child (Subsistence)
0
0
(0)
0
(0)
0
(0)
0
(0)
LECR for Adult (Subsistence)
0.992
2.51
(+2.51)
0
(-0.992)
0
(-0.992)
0
(-0.992)
Source: ERG, 2020f.
Acronyms: LECR (lifetime excess cancer risk); MCL (maximum contaminant level); NEHC (no effect hazard
concentration); NRWQC (National Recommended Water Quality Criteria); RfD (reference dose).
Note: River miles are rounded to three significant figures, so figures may not sum due to independent rounding. As
part of this analysis, EPA evaluated approximately 15,600 river miles of surface waters downstream of immediate
receiving waters.
a - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
4-19
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
4.4 Discharges to Impaired Waters and Fish Consumption Advisory Waters
Discharges of the evaluated wastestreams to CWA Section 303(d) impaired waters and fish
consumption advisory waters40 may contribute to water quality impairments, increased health
risk associated with consuming fish, and a reduction in the extent of viable downstream fisheries.
Table 4-12 summarizes the number of immediate receiving waters that are classified as either a
CWA Section 303(d) impaired water or a fish consumption advisory water under baseline and
each regulatory option. Sections 4.4.1 and 4.4.2 present the results of EPA's assessment of
immediate receiving waters that are impaired under CWA Section 303(d) or fish consumption
advisory waters, respectively.41
Table 4-12. IRWs Identified as CWA Section 303(d) Impaired Waters or Fish
Consumption Advisory Waters under Baseline and Regulatory Options
Number of IRWs (DilTcmicc Kcl;ili\c to ISiisoliuo)
ISiiscliuc
Option 1)
Option A
Option 1}
Option (
Impaired water
29
59 (+20)
47 (+18)
46 (+17)
35 (+6)
Subset impaired for one or more
pollutants associated with the
evaluated wastestreams.
20
42 (+16)
34 (+14)
33 (+13)
24 (+4)
Fish consumption advisory water
44
67 (+17)
71 (+27)
70 (+26)
52 (+8)
Subset with a fish consumption
advisory for one or more pollutants
associated with the evaluated
wastestreams.
37
46 (+9)
59 (+22)
58 (+21)
43 (+6)
Source: ERG, 2020g.
a - For this proximity analysis, EPA evaluated 93 immediate receiving waters that receive discharges of the
evaluated wastestreams under any scenario, either directly or indirectly via a POTW. Of these 93 immediate
receiving waters, 53 receive discharges of the evaluated wastestreams under baseline, 90 under Option A, 89 under
Option B, and 69 under Option C.
b - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
4.4.1 Impaired Waters
EPA estimated that more than half (47 of 93) of the immediate receiving waters analyzed in this
Supplemental EA are CWA Section 303(d) impaired waters.42 As shown in Table 4-13, 20 of the
immediate receiving waters under baseline (22 percent) and 34 of the immediate receiving
waters under Option A (37 percent) are impaired for a pollutant present in the evaluated
40 Fish consumption advisory waters are waterbodies for which states, territories, and authorized tribes have issued
fish consumption advisories, indicating that pollutant concentrations in the tissues of fish inhabiting those waters are
considered unsafe to consume.
41 See the memorandum titled "Proximity Analyses and Supporting Documentation for the 2020 Steam Electric
Supplemental Environmental Assessment" (ERG, 2020g) for a description of the methodology used to evaluate the
proximity of plants to CWA Section 303(d) impaired waters, fish consumption advisory waters, and other sensitive
environments.
42 See the memorandum titled "Proximity Analyses and Supporting Documentation for the 2020 Steam Electric
Supplemental Environmental Assessment" (ERG, 2020g) for a complete list of the impairment categories identified
in EPA's CWA Section 303(d) waters proximity analysis.
4-20
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
wastestreams. Figure 4-2, Figure 4-3, and Figure 4-4 present the locations of immediate
receiving waters that are classified as impaired by high concentrations of mercury, metals (other
than mercury),43 and nutrients, respectively.
Table 4-13. IRWs Listed as CWA Section 303(d) Impaired for Pollutants Present in the
Evaluated Wastestreams under Baseline and Regulatory Options
Pollutant Causing
Impairment
Number of IRWs Listed as CWA Section 303(d) Impaired Waters
(Difference Relative to Baseline)"
Baseline
Option D
Option A
Option B
Option C
Mercury
10
22 (+10)
16 (+6)
16 (+6)
13 (+3)
Metals, other than mercury 0
6
14 (+5)
11 (+5)
11 (+5)
7 (+1)
Nutrients
6
12 (+4)
7 (+1)
6(0)
3 (-3)
TDS, including chlorides
0
2 (+1)
1 (+1)
1 (+1)
1(+1)
Total for Any Pollutant in
Evaluated Wastestreams d
20
42 (+16)
34 (+14)
33 (+13)
24 (+4)
Source: ERG, 2020g.
Acronyms: IRW (immediate receiving water); TDS (total dissolved solids).
a - For this proximity analysis, EPA evaluated 93 immediate receiving waters that receive discharges of the
evaluated wastestreams under any scenario, either directly or indirectly via a POTW. Of these 93 immediate
receiving waters, 53 receive discharges of the evaluated wastestreams under baseline, 90 under Option A, 89
under Option B, and 69 under Option C.
b - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
c - Of the 11 immediate receiving waters classified as impaired for "metal, other than mercury" under baseline or
any regulatory option, 10 immediate receiving waters are specifically listed as impaired for one or more of the
following individual pollutants evaluated in this Supplemental EA: cadmium (1), copper (1), iron (6), lead (2),
manganese (1), selenium (1), silver (1), and zinc (1).
d - Total may not equal the sum of the individual values because some immediate receiving waters are impaired
for multiple pollutants.
43 The "metals (other than mercury)" impairment category inEPA's national CWA Section 303(d) impaired waters
dataset includes impairments caused by metalloids and nonmetals such as arsenic, boron, and selenium.
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
Figure 4-2. Immediate Receiving Waters Impaired by Mercury
Figure 4-3. Immediate Receiving Waters Impaired by Metals, Other Than Mercury
4-22
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
Figure 4-4. Immediate Receiving Waters Impaired by Nutrients
Option A has a net increase on the loadings of pollutants to waters that are already impaired for
those pollutants. Once requirements under Option A have been met at all plants (i.e., by
December 31, 2028), EPA estimates the following net changes relative to baseline in pollutant
loadings to impaired waters:
• Nitrogen increase of 14,900 lb/year and phosphorus increase of 53.0 lb/year to
nutrient-impaired waters.
• Phosphorus increase of 37.5 lb/year to phosphorus-impaired waters.
• Mercury increase of 0.206 lb/year to mercury-impaired waters.
• Net changes in loadings to receiving waters impaired for a metal (except mercury):
Aluminum increase of 1,110 lb/year.
Arsenic increase of 12.1 lb/year.
- Boron increase of 6,920 lb/year.
Cadmium increase of 0.940 lb/year.
Chromium increase of 6.62 lb/year.
Copper increase of 5.14 lb/year.
Iron increase of 881 lb/year.
- Lead increase of 13.6 lb/year.
- Magnesium increase of 72,700 lb/year.
4-23
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
- Manganese increase of 199 lb/year.
Nickel increase of 22.8 lb/year.
Selenium increase of 16.0 lb/year.
Thallium increase of 1.48 lb/year.
Vanadium increase of 13.2 lb/year.
Zinc increase of 44.1 lb/year.
4.4.2 Fish Consumption Advisories
EPA estimated that 44 of the immediate receiving waters under baseline (47 percent) and 71 of
the immediate receiving waters under Option A (76 percent) are under fish consumption
advisories.44 As shown in Table 4-14, 37 of the 44 immediate receiving waters (under baseline)
and 59 of the 71 immediate receiving waters (under Option A) are under an advisory for a
pollutant associated with the evaluated wastestreams. All of these immediate receiving waters
are under fish consumption advisories for mercury. EPA also reviewed fish consumption
advisories for arsenic, cadmium, chromium, copper, lead, selenium, zinc, and unspecified metals,
but did not identify any immediate receiving waters receiving discharges under baseline or the
regulatory options with advisories for these pollutants. Under Option A, EPA estimates a 1.59-lb
increase in annual mercury loadings to immediate receiving waters with fish consumption
advisories for mercury. Figure 4-5 illustrates the locations of immediate receiving waters with
fish consumption advisories for mercury.
Table 4-14. IRWs with Fish Consumption Advisories for Pollutants Present in the
Evaluated Wastestreams under Baseline and Regulatory Options
Pollutant Causing Fish
Consumption Advisory
Number of IRWs with Fish Consumption Advisory
(Difference Relative to Baseline) '
Baseline
Option Db
Option A
Option B
Option C
Mercury
37
46 (+9)
59 (+22)
58 (+21)
43 (+6)
Total for Any Pollutant in
Evaluated Wastestreams
37
46 (+9)
59 (+22)
58 (+21)
43 (+6)
Source: ERG, 2020g.
Acronyms: IRW (immediate receiving water).
a - For this proximity analysis, EPA evaluated 93 immediate receiving waters that receive discharges of the
evaluated wastestreams under any scenario, either directly or indirectly via a POTW. Of these 93 immediate
receiving waters, 53 receive discharges of the evaluated wastestreams under baseline, 90 under Option A, 89
under Option B, and 69 under Option C.
b - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
44 See the memorandum titled "Proximity Analyses and Supporting Documentation for the 2020 Steam Electric
Supplemental Environmental Assessment" (ERG, 2020g) for a complete list of the types of advisories identified in
EPA's fish consumption advisories proximity analysis, including advisories due to pollutants that are not associated
with the evaluated wastestreams.
4-24
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Section 4 — Results of the Supplemental Quantitative Environmental Assessment
Figure 4-5. Immediate Receiving Waters with Fish Consumption Advisory for Mercury
4-25
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Section 5 — References
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Regulations. EPA 816-F-09-004. Washington, DC. (May). DCN SE01909.
U.S. EPA. 2009b. U.S. Environmental Protection Agency. Toxicological Review of Thallium and
Compounds. Integrated Risk Information System. EPA/635/R-08/001F. Washington, DC.
(September). DCN SE01907.
U.S. EPA. 2009c. U.S. Environmental Protection Agency. National Recommended Water
Quality Criteria. Washington, DC. DCN SE01908.
U.S. EPA. 2009d. U.S. Environmental Protection Agency. Steam Electric Power Generating
Point Source Category: Final Detailed Study Report. EPA-821-R-09-008. Washington, DC.
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5-18
-------
Section 5 — References
U.S. EPA. 201 lb. U.S. Environmental Protection Agency. Exposure Factors Handbook: 2011
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DCN SE07271.
U.S. EPA. 2016b. U.S. Environmental Protection Agency. Aquatic Life Ambient Water Quality
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Criteria for Cadmium - 2016. EPA 820-R-16-002. (March). DCN SE07246.
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5-19
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Section 5 — References
U.S. EPA. 2019a. U.S. Environmental Protection Agency. Supplemental Environmental
Assessment for Proposed Revisions to the Effluent Limitations Guidelines and Standards for
the Steam Electric Power Generating Point Source Category (2019 Supplemental EA). EPA-
821-R-19-010. (October). DCN SE07243.
U.S. EPA. 2019b. U.S. Environmental Protection Agency. Supplemental Technical Development
Document for Proposed Revisions to the Effluent Limitations Guidelines and Standards for
the Steam Electric Power Generating Point Source Category (2019 Supplemental TDD).
EPA-821-R-19-009. (October). DCN SE07101.
U.S. EPA. 2019c. U.S. Environmental Protection Agency. Case Studies of Changes In Total
Trihalomethanes Concentrations in Treated Water from Public Water Systems Downstream
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U.S. EPA. 2019d. U.S. Environmental Protection Agency. Health Effects of Exposures to
Mercury (website). Available online at: https://www.epa.gov/mercury/health-effects-
exposures-mercury (Last updated January 29). DCN SE07346.
U.S. EPA. 2019e. U.S. Environmental Protection Agency. Integrated Risk Information System
(IRIS). National Center for Environmental Assessment. Washington, DC. Available online
at: http://www.epa.gov/IRIS/. DCN SE08765.
U.S. EPA. 2020a. U.S. Environmental Protection Agency. Supplemental Technical Development
Document for Revisions to the Effluent Limitations Guidelines and Standards for the Steam
Electric Power Generating Point Source Category (Supplemental TDD). EPA-821-R-20-
001. (August). DCN SE08650.
U.S. EPA. 2020b. U.S. Environmental Protection Agency. Benefit and Cost Analysis for
Revisions to the Effluent Limitations Guidelines and Standards for the Steam Electric Power
Generating Point Source Category (BC A Report). EPA-821-R-20-003. (August).
U.S. EPA. 2020c. U.S. Environmental Protection Agency. Regulatory Impact Analysis for
Revisions to the Effluent Limitations Guidelines and Standards for the Steam Electric Power
Generating Point Source Category (RIA). EPA-821-R-20-004. (August).
U.S. EPA. 2020d. U.S. Environmental Protection Agency. Secondary Drinking Water Standards:
Guidance for Nuisance Chemicals (website). Available online at:
https://www.epa.gov/sdwa/secondary-drinking-water-standards-guidance-nuisance-chemicals
(Last updated January 27). DCN SE09134.
U.S. EPA. 2020e. U.S. Environmental Protection Agency. Estimation of Acute and Chronic
Aquatic Life Ambient Freshwater Water Quality Criteria for Copper (for Use in Analyses
Supporting the Revised Steam ELG). (August). DCN SE08757.
U.S. EPA Region 5. 2016. U.S. Environmental Protection Agency - Region 5. Ecological
Toxicity Information (website). Available online at:
https://archive.epa.gov/reg5sfun/ecology/web/html/toxprofiles.html (Last updated February
21). DCN SE07347.
5-20
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Section 5 — References
USGS. 2008. U.S. Geological Survey. Environmental contaminants in freshwater fish and their
risk to piscivorous wildlife based on a national monitoring program. Environmental
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Velasco, J. C. Gutierrez-Canovas, M. Botella-Cruz, D. Sanchez-Fernandez, P. Arribas, J.A.
Carbonell, A. Millan, and S. Pallares. 2018. Effects of salinity changes on aquatic organisms
in a multiple stressor context. Philosophical Transactions of the Royal Society B
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Villanueva, C.M., K.P. Cantor, S. Cordier, J.J.K. Jaakkola, W.D. King, C.F. Lynch, S. Porru, and
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Epidemiology 15(3):357-367. (June). DCN SE07932.
Villanueva, C.M., K.P. Cantor, J.O. Grimalt, N. Malats, D. Silverman, A. Tardon, R. Garcia-
Closas, C. Serra, A. Carrato, G. Castano-Vinyals, R. Marcos, N. Rothman, F.X. Real, M.
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Vinceti, M., T. Filippini, S. Cilloni, A. Bargellini, A.V. Vergoni, A. Tsatsakis, and M. Ferrante.
2017. Health risk assessment of environmental selenium: Emerging evidence and challenges
(Review). Molecular Medicine Reports 15:3323-3335. EPA-HQ-OW-2009-0819-8465-A2
(Attachment 2).
Wagner, E. D., and M.J. Plewa. 2017. CHO cell cytotoxicity and genotoxicity analyses of
disinfection by-products: An updated review. Journal of Environmental Sciences 58:64-76.
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5-21
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Section 5 — References
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5-22
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Appendix A —Adverse Impacts from Exposure to Metals and Toxic and Bioaccumulative Pollutants
APPENDIX A
EXAMPLES OF POTENTIAL ADVERSE IMPACTS FROM
EXPOSURE TO METALS AND TOXIC AND
BIOACCUMULATIVE POLLUTANTS
Table A-l presents examples of adverse impacts from exposure to elevated concentrations of
metals and toxic and bioaccumulative pollutants, which are present in discharges of the evaluated
wastestreams (flue gas desulfurization (FGD) wastewater and bottom ash transport water) from
coal-fired steam electric power plants. The table is not an exhaustive list of adverse impacts but
provides context for an assessment of environmental, ecological, and human health impacts from
exposure to these pollutants. Additional information is available in Environmental Assessment
for the Effluent Limitations Guidelines and Standards for the Steam Electric Power Generating
Point Source Category (2015 Final EA) (U.S. EPA, 2015a).
A-l
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Appendix A —Adverse Impacts from Exposure to Metals and Toxic and Bioaccumulative Pollutants
Table A-l. Examples of Potential Adverse Impacts from Exposure to Elevated Concentrations of Metals and Toxic and
Bioaccumulative Pollutants
Polliiliini
Mil niiiii 1 lo;il 111
lionchniiirk Value ;|
lionchniiirk \ iilno
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I'Aiimpk's (il' Ad\ci sc linpiicls
Aluminum
Minimal risk level
(MRL) b for intermediate
and chronic oral
exposure is 1.0
milligrams per
kilograms per day
(mg/kg/day).
Neurological impacts
Elevated levels of aluminum can adversely impact some species' ability to regulate ions and
can inhibit respiratory functions (U.S. EPA, 2018). Oral exposures to aluminum in animal
studies show that the nervous system is a sensitive target (ATSDR, 2008).
High levels of aluminum can also cause both brain and bone disease in children with kidney
disease, and bone disease in children taking some medicines containing aluminum (ATSDR,
2008).
Arsenic 0
MRL for acute oral
exposure is 0.005
mg/kg/day.
Gastrointestinal
impacts
Arsenic tends to bioaccumulate in aquatic communities and potentially impacts higher-trophic
level organisms. Elevated arsenic tissue concentrations are associated with liver poisoning,
developmental abnormalities, behavioral impairments, metabolic failure, reduced growth, and
appetite loss in aquatic organisms (NRC, 2006; Rowe et al., 2002; U.S. EPA, 2011a).
In humans, arsenic contamination is associated with an increased risk of bladder, lung, and
skin cancer, particularly in inorganic forms. Arsenic is also a potential endocrine disrupter.
Non-cancer impacts from long-term exposure include dermal impacts, developmental effects,
diabetes, cardiovascular disease, and pulmonary disease. Chronic exposure via drinking water
has been associated with excess incidence of miscarriages, stillbirths, preterm births, and low
birth weights (Diamanti-Kandarakis etal., 2009; WHO, 2018).
MRL for chronic oral
exposure is 0.0003
mg/kg/day.
Dermal impacts
Boron
MRL for acute and
intermediate oral
exposure is 0.2
mg/kg/day.
Developmental
impacts
Boron can be toxic to vegetation and to wildlife at certain water concentrations and dietary
levels. Toxicity in fish can occur at levels of 10 to 300 milligrams per liter (mg/L) and
mallard duckling growth can be impacted at dietary levels of 30 to 300 mg/kg. Boron does not
magnify through the food chain but does accumulate in aquatic and terrestrial plants (WHO,
1998). In animals, acute excessive amounts of boron can cause lethargy, rapid respiration, eye
inflammation, and dermal impacts (U.S. EPA, 2008a).
In humans, exposure via ingestion of large quantities over a short time period can adversely
impact the stomach, intestines, liver, kidney, and brain. Human exposure to high
concentrations of boron (85 mg/kg) can cause nausea, vomiting, diarrhea, and redness of the
skin (ATSDR, 2010; U.S. EPA, 2008a).
A-2
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Appendix A —Adverse Impacts from Exposure to Metals and Toxic and Bioaccumulative Pollutants
Table A-l. Examples of Potential Adverse Impacts from Exposure to Elevated Concentrations of Metals and Toxic and
Bioaccumulative Pollutants
Polliiliini
Mil niiiii 1 lo;il 111
lionchniiirk Value ;|
lionchniiirk \ iilno
l.ii(l|)(iinl ¦'
I'Aiimpk's (il' Ad\ci sc linpiicls
Cadmium
MRL for intermediate
oral exposure is 0.0005
mg/kg/day.
Musculoskeletal
impacts
Cadmium can readily bioaccumulate in aquatic organisms, especially mollusks, soil
invertebrates, and microorganisms. Cadmium contamination can lead to skeletal
malformations in fish (WHO, 1992).
Cadmium is a probable human carcinogen. Human exposure to high concentrations of
cadmium in drinking water and food can irritate the stomach, leading to vomiting and
diarrhea, and sometimes death. Chronic oral exposure via diet or drinking water to lower
concentrations can lead to kidney damage and weakened bones (ATSDR, 2012a and 2012b).
MRL for chronic oral
exposure is 0.0001
mg/kg/day.
Renal impacts
Chromium
(III)
MRL for intermediate
inhalation exposure
(soluble particulates) is
0.0001 milligrams per
cubic meter (mg/m3).
Respiratory impacts
The toxicity of chromium (III) to aquatic organisms is impacted by water hardness, being
more toxic in soft water (U.S. EPA, 1980a). Fawad et al. (2016) studied chromium (III)
accumulation in goldfish (Carassius auratus) and found highest accumulation in the gills,
followed by the intestines, and then the skin. When chromium (III) levels exceed
recommended limits, more of the metal accumulates in the fish organs such as the liver,
muscle, and gills and raises the mortality rate. Chromium can cause physiological and
behavioral changes (e.g., loss of appetite and reduced growth) (Fawad et al., 2016).
Potential risks to humans from chromium exposure include respiratory and immunological
damage (ATSDR, 2012c).
Copper
MRL for acute and
intermediate oral
exposure is 0.01
mg/kg/day.
Gastrointestinal
impacts
Copper can be lethal to freshwater fish at concentrations ranging from 10 to 20 ppb in soft
water (in hard water, the cations reduce the bioavailability of the dissolved copper). Adverse
impacts to fish include impaired neurological function, reduced reproduction, and damage to
gills, olfactory receptors, and lateral line cilia. Other freshwater aquatic organism impacts
include inhibited algae photosynthesis, reduced growth and reproduction of zooplankton (due
to impacts to algae food supply), and impaired growth and survival of mussels (Woody and
O'Neal, 2012).
Human exposure to high concentrations of copper can cause gastrointestinal distress (i.e.,
nausea, vomiting, and/or abdominal pain), liver and kidney damage, and anemia (U.S. EPA,
1980b).
A-3
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Appendix A —Adverse Impacts from Exposure to Metals and Toxic and Bioaccumulative Pollutants
Table A-l. Examples of Potential Adverse Impacts from Exposure to Elevated Concentrations of Metals and Toxic and
Bioaccumulative Pollutants
Polliiliini
Mil niiiii 1 lo;il 111
lionchniiirk Value ;|
lionchniiirk \ iilno
l.ii(l|)(iinl ¦'
l.\;iiii|)k's (il' A(l\ci sc linpiicls
Iron
NoMRL
Iron contamination can cause sublethal impacts to aquatic organisms, including reduced
growth, reduced development, and reduced reproduction. Iron also increases turbidity,
reduces primary production, and reduces interstitial spaces in benthic sediment, which can
smother invertebrates, periphyton, and eggs. Iron precipitates can clog and damage the gills of
fish resulting in respiratory impacts (Cadmus et al., 2018).
In humans, individuals with iron overload disorders can experience oxidative damage and
organ dysfunction, impacting metabolism (i.e., diabetes mellitus), the liver (i.e., cirrhosis), the
heart (i.e., cardiomyopathy), and endocrine glands (Dev and Babitt, 2017).
Lead
NoMRL
Lead contamination can delay embryonic development, suppress reproduction, and inhibit
growth in fish, crab, and several other aquatic organisms (U.S. EPA, 1984 and 201 la).
Human exposure to high concentrations of lead in drinking water (and via other exposure
pathways) can result in adverse impacts to almost every organ and body system. Lead impacts
include cardiovascular effects (e.g., hypertension and coronary heart disease), renal effects
(e.g., decreased kidney function), reproductive effects (e.g., changes to sperm, increased time
to conception, reduced fetal growth, and lower birth weight), developmental effects (e.g.,
delayed puberty, decreased postnatal growth), immune effects (e.g., atopic and inflammatory
responses, reduced bacterial resistance), and neurological effects (e.g., cognitive function
decrements). Among children, observed neurological and behavioral impacts include
decreased motor function, lower academic performance, attention-related behavioral
problems, impulsivity, hyperactivity, and conduct disorders (e.g., delinquent, criminal, or
antisocial behavior). Animal studies provided EPA with evidence to determine a likely causal
relationship between lead exposure and cancer (National Toxicology Program, 2012; U.S.
EPA, 2014b).
Magnesium
NoMRL
Magnesium generally does not pose a risk to aquatic life unless associated with other anions,
such as chloride or sulfate. Such compounds can contribute to salinity stress and impact
species diversity in sensitive aquatic communities (NHDES, 2019).
In humans, increased intake of magnesium salts may cause a change in bowel habits
(diarrhea). Drinking water in which both magnesium and sulfate concentrations are present in
high concentrations (approximately 250 mg/L each) can have a laxative effect (Sengupta,
2013).
A-4
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Appendix A —Adverse Impacts from Exposure to Metals and Toxic and Bioaccumulative Pollutants
Table A-l. Examples of Potential Adverse Impacts from Exposure to Elevated Concentrations of Metals and Toxic and
Bioaccumulative Pollutants
Polliiliini
Mil niiiii 1 lo;il 111
lionchniiirk Value ;|
lionchniiirk \ iilno
l.ii(l|)(iinl ¦'
I'Aiimpk's (il' Ad\ci sc linpiicls
Manganese
MRL for chronic
inhalation exposure is
0.3 micrograms per
cubic meter (|ig/m3).
Neurological impacts
Manganese primarily accumulates in organisms lower in the food chain, such as
phytoplankton, algae, mollusks, and some fish (ATSDR, 2012d).
Although high levels can be toxic to humans, manganese is not generally considered toxic
when ingested (WHO, 2011). The most common impacts due to human exposure to high
concentrations of manganese involve the nervous system (ATSDR, 2012d).
Mercury d
MRL for chronic oral
exposure to
methylmercury is 0.0003
mg/kg/day.
Developmental
impacts
Once in the environment, mercury can convert into methylmercury, increasing the potential
for bioaccumulation. Methylmercury contamination can reduce growth and reproductive
success in fish and invertebrates. Adverse impacts on wildlife include behavioral and
reproductive effects (Evers et al., 2011).
In humans, high exposure to inorganic mercury may result in damage to the gastrointestinal
tract, the nervous system, and the kidneys. Exposure at levels above the drinking water
maximum contaminant level (MCL), 0.002 mg/L, can result in kidney damage (U.S. EPA,
2019d). Fetuses, infants, and children are particularly susceptible to impaired neurological
development from methylmercury exposure (ATSDR, 1999; Evers et al., 2011).
Molybdenum
MRL for chronic
inhalation exposure is
0.002 mg/m3.
Respiratory impacts
In humans, molybdenum exposure through inhalation may impair lung function or cause
dyspnea or cough (ATSDR, 2020b). Oral exposure may result in kidney damage, weight loss,
anemia, or a decrease in sperm count (ATSDR, 2020b). High levels of ingestion through
drinking water may cause mineral imbalances and increased copper excretion, which may
increase the risk of anemia associated with copper deficiency (U.S. EPA, 2019e).
MRL for intermediate
oral exposure is 0.06
mg/kg/day.
Renal impacts
Nickel
MRL for intermediate
inhalation exposure is
0.0002 mg/m3.
Respiratory impacts
Nickel can inhibit the growth of microorganisms (e.g., bacteria and protozoans) and algae.
Nickel toxicity in fish and aquatic invertebrates varies among species and can reduce fish
growth and adversely impact the immune system, muscles, gills, and liver. Nickel does not
biomagnify in the aquatic food web (ATSDR, 2005a; Eisler, 1998; Min et al., 2015; U.S.
EPA, 1986).
Human exposure to high concentrations of nickel via drinking water (e.g., 250 parts per
million (ppm)), can cause gastrointestinal effects (stomachache) and adverse effects to the
blood and kidneys (ATSDR, 2005a).
MRL for chronic
inhalation exposure is
0.00009 mg/m3.
Respiratory impacts
A-5
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Appendix A —Adverse Impacts from Exposure to Metals and Toxic and Bioaccumulative Pollutants
Table A-l. Examples of Potential Adverse Impacts from Exposure to Elevated Concentrations of Metals and Toxic and
Bioaccumulative Pollutants
Polliiliini
Mil niiiii 1 lo;il 111
lionchniiirk Value ;|
lionchniiirk \ iilno
l.ii(l|)(iinl ¦'
I'Aiimpk's (il' Ad\ci sc linpiicls
Selenium
MRL for chronic oral
exposure is 0.005
mg/kg/day.
Dermal impacts
Selenium readily bioaccumulates. The bioaccumulation of selenium is of particular concern
due to its potential to impact higher trophic levels through biomagnification (Coughlan and
Velte, 1989). Elevated concentrations have caused fish kills and numerous sublethal effects
(e.g., organ damage, decreased growth rates, reproductive failure) to aquatic and terrestrial
organisms (NPS, 1997). The most well-documented, overt, and severe toxic symptoms in fish
are reproductive teratogenesis and larval mortality (U.S. EPA, 2016b).
In humans, acute exposure via food or water consumption adversely impacts the liver,
respiratory system (e.g., pulmonary edema and lesions of the lung), cardiovascular system
(e.g., tachycardia), gastrointestinal system (e.g., nausea and vomiting.), and neurological
system (e.g., aches, irritability, chills, and tremors). Chronic exposure via food or water
consumption can cause skin and tooth discoloration, loss of hair and nails, excess tooth decay,
and neurological impacts (e.g., lack of mental alertness and listlessness) (U.S. EPA, 2000b).
Chronic oral exposure may increase the risk of type-2 diabetes and certain cancers such as
prostate cancer, non-melanoma skin cancer, and possibly breast cancer in high-risk women
(Vinceti et al., 2017).
Thallium
Reference dose for
chronic oral exposure
(soluble thallium) is 1.00
x 10"5 mg/kg/day (U.S.
EPA, 2012).
Hair follicle atrophy
(U.S. EPA, 2012)
Thallium can bioaccumulate in fish and vegetation in fresh and marine waters, as well as in
marine invertebrates, which suggests that thallium may be a potential risk to higher-order
organisms invulnerable ecosystems (U.S. EPA, 2011a).
In humans, short-term exposure to thallium can lead to neurological symptoms (e.g.,
weakness, sleep disorders, muscular problems), alopecia, gastrointestinal effects, and
reproductive and developmental damage. Long-term exposures at levels above the MCL
(0.002 mg/L) change blood chemistry and damage liver, kidney, and intestinal and testicular
tissues (U.S. EPA, 2009a and 2009b).
Vanadium
MRL for intermediate
oral exposure is 0.01
mg/kg/day.
Hematological
impacts
Vanadium contamination can increase blood pressure, decrease blood cell count, and cause
mild neurological effects in animals (ATSDR, 2012e).
There are very few reported cases of oral exposure to vanadium in humans; however, a few
reported incidences documented nausea, diarrhea, and stomach cramps (ATSDR, 2012e).
A-6
-------
Appendix A —Adverse Impacts from Exposure to Metals and Toxic and Bioaccumulative Pollutants
Table A-l. Examples of Potential Adverse Impacts from Exposure to Elevated Concentrations of Metals and Toxic and
Bioaccumulative Pollutants
Polliiliini
Mil niiiii 1 lo;il 111
lionchniiirk Value ;|
lionchniiirk \ iilno
l.ii(l|)(iinl ¦'
I'Aiimpk's (il' Ad\ci sc linpiicls
Zinc
MRL for intermediate
and chronic oral
exposure is 0.3
mg/kg/day.
Hematological
impacts
Elevated zinc levels adversely impact aquatic plant and animal growth, survival, and
reproduction. At higher concentrations, zinc is lethal to aquatic organisms by causing
irreversible destruction of the gill epithelium. Zinc contamination changes behavior, reduces
oxygen supply, interferes with gill uptake of calcium, and impairs reproduction in fish. High
zinc levels in birds can cause mortality, reduce growth, or damage the pancreas (CCME,
2018; U.S. EPA Region 5, 2016).
In humans, short-term exposure to levels 10-15 times the recommended daily allowance (11
mg/day for men and 8 mg/day for women) can cause nausea, vomiting, and stomach cramps.
Long-term exposure at high levels can cause anemia and damage the pancreas (ATSDR,
2005b).
Acronyms: mg/day (milligrams per day); mg/kg (milligrams per kilograms); mg/kg/day (milligram per kilogram-day); mg/L (milligrams per liter); milligrams
per cubic meter (mg/m3); MRL (minimal risk level); ppb (parts per billion); ppm (parts per million),
a - Reference is ATSDR, 2020a unless otherwise listed.
b - The MRL is an estimate of the amount of a chemical a person can eat, drink, or breathe each day without a detectable risk of non-cancer health effects,
c - EPA based its quantitative human health assessments on the estimated concentration of inorganic arsenic in fish tissue (see Section 4).
d - EPA based its quantitative wildlife and human health assessments on the estimated concentration of methylmercury in fish tissue (see Section 4).
A-7
-------
Appendix B —Adverse Impacts from Exposure to Total Dissolved Solids
APPENDIX B
EXAMPLES OF POTENTIAL ADVERSE IMPACTS FROM
EXPOSURE TO TOTAL DISSOLVED SOLIDS
Table B-l presents examples of adverse impacts from exposure to elevated concentrations of
total dissolved solids (TDS), which is present in discharges of the evaluated wastestreams (flue
gas desulfurization (FGD) wastewater and bottom ash transport water) from coal-fired steam
electric power plants. The table is not an exhaustive list of adverse impacts but provides context
for an assessment of environmental and ecological impacts from exposure to TDS and the
corresponding increase in salinity of the receiving water.
B-l
-------
Appendix B —Adverse Impacts from Exposure to Total Dissolved Solids
Table B-l. Examples of Potential Adverse Impacts from Exposure to Elevated Concentrations of TDS
Aquatic Organism
TDS Concentration
Adverse Impacts
Literature Details
Sou rce
Invertebrates
Salinity. >8.2 ppt
Oxygen consumption decreases
significantly among invertebrates
due to physiological stress.
Silva and Davies,
1999
Ephemeroptera
(mayfly), Plecoptera
(stonefly), and
Pulmonate (molluscs)
Salinity. >3 mS/cm
(milliSiemens per
centimeter)
These organisms were rarely found
in salinities higher than 3 mS/cm.
48- and 72-hour LC50 is
approximately 5 to 20 mS/cm.
48- and 72-hour exposure.
Williams et al., 2003;
Hassell et al., 2006;
Echols et al., 2010;
Kefford et al., 2012
Chironomids
(Chironomus tentans)
Chironomids exhibited toxic
effects at >1,100 mg/L.
Researchers synthesized Red Dog
Mine effluent and exposed larval
chironomids to a TDS concentration
of 2,089 mg/L. Their dry weight (a
growth indicator for these
organisms) was reduced by 45
percent. The researchers also
observed reduced survival among
larval chironomids exposed to
synthetic Kensington Mine effluent
at TDS concentrations of 1,750 and
2,240 mg/L.
Researchers maintained larval
chironomids in test containers and
exposed them to synthetic effluent
(based on discharge from one of two
local mines in Alaska) for 10 days.
They measured mortality and dry
weight at the end of the incubation.
Chapman et al., 2000
Coontail
(Ceratophyllus
demersum) and
cattail (Typha sp.)
1,170 mg/L (estimated)
In a 1988 study of plant
communities near irrigation drains
in Stillwater Marsh, researchers
found that coontails and cattails
growing in the marsh had nearly
been eliminated. TDS
concentrations were modeled to
have increased from 270 mg/L
(historical values from 1845 to
1860) to 1,170 mg/L (projected
values for 1992 and beyond, as
estimated in 1988).
Reported TDS concentration data at the
wetland inlet flow at Stillwater Marsh,
Nevada, were estimated for 1992 and
beyond. Reductions in coontail and
cattail in Stillwater Marsh were based
on comparisons of observed
populations in 1988 to populations
recorded in a 1959 survey by the U.S.
Fish and Wildlife Service.
Hallock and Hallock,
1993
B-2
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Appendix B —Adverse Impacts from Exposure to Total Dissolved Solids
Table B-l. Examples of Potential Adverse Impacts from Exposure to Elevated Concentrations of TDS
Aquatic Organism
TDS Concentration
Adverse Impacts
Literature Details
Sou rce
Fish and vascular
aquatic plants
20,000 mg/L
After Carson Sink was inundated
and TDS concentrations rose to
20,000 mg/L, vascular aquatic
plants died. Fish did well initially,
but they started dying after about a
year when water evaporated and the
TDS concentration increased.
Historical TDS concentrations in
Carson Sink, Nevada, likely varied
dramatically based on inundation. The
plant species that were reported to be
present in a 1929 survey could
withstand TDS concentrations between
650 and 16,800 mg/L during normal
conditions. TDS concentrations when
the wetland is filled have been recorded
at 3,100 mg/L (1983) and 20,000 mg/L
(1987).
Hallock and Hallock,
1993
American coot
(Fulica americana)
1,170 mg/L (estimated)
Coots had reduced field nest
success and low fecundity due to
vegetation loss and subsequent nest
exposure. Nesting success
decreased from 43 to 52 percent
(1968 to 1970) to 25 percent (1988).
The researchers attributed
vegetation loss to drought,
increased TDS, and increased
predation.
Nesting success for the study was
measured during an annual assessment
in May 1988. Those values were
compared to nesting surveys conducted
in the Stillwater Wildlife Management
Area in 1968-1970, 1983, and 1987-
1988.
Hallock and Hallock,
1993
Atlantic salmon
(Salmo salar),
rainbow trout (Salmo
gairdneri), and brook
trout (Salvelinus
fontinalis)
>522 mg/L calcium sulfate
(CaS04) Calcium in the
experimental water ranged
between 34-544 mg/L.
Researchers found low survival
rates (~33 percent) when eggs were
incubated in very hard water with
calcium sulfate concentrations >522
mg/L during water hardening (the
process by which the shells of
newly shed eggs absorb water and
become firm over the course of a
few hours). High concentrations of
chloride, sulfate, and sodium ions
did not affect egg survival.
Eggs were incubated to eye-up (the
point at which eyes develop on the
embryo). Eggs were exposed to
treatment water for 1.5 or 3.5 hours of
hardening, depending on the
experiment. Egg survival rates were not
significantly affected by water
chemistry after hardening.
Ketolaetal., 1988
B-3
-------
Appendix B —Adverse Impacts from Exposure to Total Dissolved Solids
Table B-l. Examples of Potential Adverse Impacts from Exposure to Elevated Concentrations of TDS
Aquatic Organism
TDS Concentration
Adverse Impacts
Literature Details
Sou rce
Fish communities
2,000 - 2,300 mg/L
Researchers documented notably
lower species richness and density
at two sampling locations
immediately downstream of the
coal mining wastewater discharges.
Fish community metrics declined
notably at three sampling stations
among 17 stations compared to the
reference station. However, one of
these three sites may have been
impacted by factors other than TDS
concentrations (i.e., toxicity from
untreated coal plant runoff and
sewage). Based on TDS data
collected at all sampling sites,
researchers identified 2,000 to
2,300 mg/L as the limit before fish
communities experience adverse
effects.
Researchers sampled fish populations
and measured water quality parameters
at 17 locations along the South Fork of
Tenmile Creek in southwestern
Pennsylvania during the summers of
2007 and 2008. Researchers collected
10,940 fish representing seven families
and 42 species/hybrids during the
survey.
Kimmel and Argent,
2010
Walleye (Stizostdion
vitreum), northern
pike (Esox lucius),
yellow perch (Perca
flavescens), white
sucker (Catostomus
commersoni), and
common carp
(Cyprinus carpio)
1,750-6,700 mg/L
(concentrations at which
eggs were incubated)
>2,400 mg/L (concentration
at which adverse impacts
were observed)
Fish egg hatching success
significantly decreased at TDS
concentrations above 2,400 mg/L
for all species studied except
common carp. Embryo survival
decreased at TDS concentrations
above 2,400 mg/L for walleye and
northern pike. Survival to hatching
was less than 2 percent for all
species except common carp at TDS
concentrations above 2,400 mg/L.
Researchers collected fish eggs during
spawning runs between mid-April and
May 1992 in Devils Lake, North
Dakota, and Many Point Lake,
Minnesota. They incubated the
fertilized eggs overnight, and assessed
fertilization success after one or three
days, depending on species. Live
embryos were incubated and counted
every one to three days until hatching.
Koel and Peterka,
1995
B-4
-------
Appendix B —Adverse Impacts from Exposure to Total Dissolved Solids
Table B-l. Examples of Potential Adverse Impacts from Exposure to Elevated Concentrations of TDS
Aquatic Organism
TDS Concentration
Adverse Impacts
Literature Details
Sou rce
Water flea
(Ceriodaphnia dubia)
Variable ion concentrations
(highest reported
concentration):
Na = 15,000 mg/L,
K = 450 mg/L,
Ca =1,800 mg/L,
Mg = 320 mg/L,
CI = 26,000 mg/L
Concentrations in four (of six total)
samples were acutely toxic to C.
dubia.
Grab samples were collected from the
Black Warrior Basin, Alabama.
Twenty-four- and 48-hour survival for
two species of water flea (C. dubia and
Daphnia magna) and flathead minnows
(Pimephales promelas) were
ascertained. Within 36 hours of
collection, all samples were tested for
acute toxicity. Exposure began with the
organisms that were less than 24 hours
old and lasted 48 hours.
Mount etal., 1993
Daphnids (Daphnia
magna)
Elevated concentration of
major ions (conductivity up
to 30,300 |iS/cm). Variable
ion concentration in
leachate (highest reported
concentration):
Na = 7,700 mg/L,
K = 270 mg/L,
Ca = 379 mg/L,
Mg = 758 mg/L,
CI = 11,200 mg/L
Concentrations in two (of five total)
samples showed acute toxicity to D.
magna.
Water samples were taken from
irrigation drain waters from the
Stillwater Wildlife Management Area
in southwestern Nevada. 24-and 48-
hour survival for two species of water
flea (C. dubia and Daphnia magna)
and flathead minnows (Pimephales
promelas) was determined. Acute
toxicity tests with Daphnia magna
were conducted on both ambient
samples as well as reconstituted waters.
Mount etal., 1993
Daphnids
(iCeriodaphnia dubia
and Daphnia magna)
and fathead minnows
(Pimephales
promelas)
10,000 mg/L a
No clear information on adverse
impacts were provided. However,
marginal plots of the regression
equations from the ion toxicity
model showed that C. dubia are, in
general, the most sensitive of the
three species to major ion toxicity,
while fathead minnows are the least
sensitive.
All organisms were obtained from in-
house culture. Daphnids were less than
24 hours old at test initiation while
fathead minnows were 1 to 7 days old.
Researchers followed general EPA
guideline for conducting acute whole
effluent toxicity tests. Exposure periods
were 48 hours for C. dubia and D.
magna and 96 hours for fathead
minnows, with daily observations of
mortality. Tests were conducted under
a 16-hour:8-hour light:dark
photoperiod.
Mount etal., 1997
B-5
-------
Appendix B —Adverse Impacts from Exposure to Total Dissolved Solids
Table B-l. Examples of Potential Adverse Impacts from Exposure to Elevated Concentrations of TDS
Aquatic Organism
TDS Concentration
Adverse Impacts
Literature Details
Sou rce
Coho salmon
(Oncorhynchus
kisutch)
>1,250 ppm
Coho salmon eggs from two
broodyears experienced decreased
fertilization success when exposed
to high TDS concentrations. For
both broodyears, fertilization
success decreased as the TDS
concentration during fertilization
increased. For one broodyear, eggs
experienced higher mortality
between eye-up and the alevin stage
when maintained at high TDS
concentrations after fertilization.
Adverse impacts were observed
beginning at TDS concentrations of
1,250 ppm.
Researchers incubated fertilized coho
salmon embryos from broodyears 1999
and 2000 for 96 hours.
Stekoll et al., 2003
Coho salmon
(Oncorhynchus
kisutch), chum
salmon (0. keta),
king salmon (0.
tschawytscha), pink
salmon (0.
gorbuscha),
steelhead salmon (0.
mykiss), and arctic
char (Salvelinus
alpinus)
For the continuous exposure
study: LOEC: 750 ppm for
chum and steelhead salmon.
LOEC: 250 ppm for king,
pink, and coho salmon.
LOEC: 1875 ppm for arctic
char.
For the fertilization
exposure study, every
species had a different
LOEC ranging from 250 to
1875 ppm.
The number of unfertilized eggs
increased with TDS concentrations
for all species except arctic char.
The most sensitive species (coho
salmon) exhibited adverse effects at
TDS concentrations of 250 ppm.
Steelhead salmon were the only
species that exhibited a significant
effect in the post-fertilization
exposure experiment, with a
reported LOEC of 1875 ppm.
Researchers incubated fertilized eggs to
the 4- or 8-cell stage, which lasted from
18 to 43 hours. These bioassays were
conducted for broodyears 2000 and
2001.
TDS concentrations in the test solution
ranged from 0 to 2,500 ppm.
Stekoll et al., 2003
B-6
-------
Appendix B —Adverse Impacts from Exposure to Total Dissolved Solids
Table B-l. Examples of Potential Adverse Impacts from Exposure to Elevated Concentrations of TDS
Aquatic Organism
TDS Concentration
Adverse Impacts
Literature Details
Sou rce
Coho salmon
(Oncorhynchus
kisutch)
>2,500 ppm
No consistent adverse impacts
related to TDS were documented at
the TDS concentrations tested.
Researchers exposed coho salmon
eggs to differing chronic TDS
concentrations as they developed.
Higher TDS concentrations during
fertilization were found to result in
higher pre-hatch mortality, and
higher TDS concentrations at
hatching were related to higher
post-hatch mortality. Fish exposed
to higher TDS concentrations
generally had shorter lengths and
lower weights at button-up (stage at
which fish have no visible yolk
sac).
Researchers incubated the fish eggs for
at least six months.
TDS ranged from 125 to 2,500 ppm in
test solutions.
Stekoll et al., 2003
Acronyms: Ca (calcium); CI (chlorine); K (potassium); LC50 (lethal concentration required to kill 50 percent of the population); LOEC (lowest observed effects
concentration); Mg (magnesium); mg/L (milligrams per liter); mS/cm (milliSiemens per centimeter); |iS/cm (microSiemens per centimeter); Na (sodium); ppm
(parts per million); ppt (parts per thousand); TDS (total dissolved solids).
a - The test solutions were prepared in a lab by dissolving individual 10,000 mg/L of ion salts with moderately hard reconstituted water. For tests evaluating only
one salt (one cation and one anion), test solutions were prepared by serially diluting the 10,000-mg/L stock solutions with moderately hard reconstituted water to
develop a series of test concentrations.
B-7
-------
Appendix C— Water Quality Module Methodology
APPENDIX C
WATER QUALITY MODULE METHODOLOGY
This appendix presents the model equations, input variables and constants, pollutant benchmark
values, and methodology limitations/assumptions for the Water Quality Module of the
Immediate Receiving Water (IRW) Model. This supplemental environmental assessment
(Supplemental EA) focuses on only the changes to the 2015 rule regarding best available
technology economically achievable (BAT) effluent limitations and pretreatment standards for
existing sources (PSES) for the evaluated wastestreams—specifically, flue gas desulfurization
(FGD) wastewater and bottom ash transport water.
The Water Quality Module equations are organized by the methodology for nonvolatile
pollutants (arsenic, cadmium, copper, lead, nickel, selenium, thallium, and zinc) and volatile
pollutants (mercury). EPA used the equations to calculate total and dissolved pollutant
concentrations in receiving waters and total pollutant concentrations in sediment within the
immediate discharge zone. The following tables describe the input requirements and data sources
used in the Water Quality Module:
• Table C-l. Input Variables with Values from Site-Specific Data Sources.
• Table C-2. Input Variables and Constants with Globally Assigned Values.
• Table C-3. Input Variables with Values from Regional Data Sources.
• Table C-4. Partition Coefficients.
• Table C-5. Total Suspended Solids (TSS) Concentrations in Surface Waters.
• Table C-6. Regional Surface Water Temperatures.
• Table C-l. National Recommended Water Quality Criteria (NRWQC) and Drinking
Water Maximum Contaminant Levels (MCLs).
EPA calculated effluent pollutant loadings associated with the discharge of the evaluated
wastestreams as part of its engineering analysis—see the Supplemental Technical Development
Document for Revisions to the Effluent Limitations Guidelines and Standards for the Steam
Electric Power Generating Point Source Category (Supplemental TDD), Document No. EPA-
821-R-20-001 (U.S. EPA, 2020a). The Water Quality Module performs calculations on a per-
immediate-receiving-water basis. For coal-fired steam electric power plants that discharge to
multiple receiving waters, EPA divided the plant-specific pollutant loadings accordingly among
the receiving waters based on water diagrams provided in response to the Questionnaire for the
Steam Electric Power Generating Effluent Guidelines (Steam Electric Survey) (U.S. EPA, 2010).
EPA used the IRW Model to evaluate the environmental impacts from 82 plants discharging to
89 unique immediate receiving waters).
While the Water Quality Module is not designed to account for pollutant speciation, EPA did
include assumptions of pollutant speciation for arsenic and mercury as appropriate in the
subsequent Wildlife and Human Health Modules (see Appendix D and Appendix E,
respectively). EPA used total selenium loadings in the Water Quality Module; however, due to
the partition coefficients available, EPA assumed the dominant form of selenium in the receiving
C-l
-------
Appendix C— Water Quality Module Methodology
water was selenate (i.e., selenium (VI)). EPA selected the selenate partition coefficient because,
per the Steam Electric Survey, the significant majority of plants (113 of 150, or 75 percent)
operating wet FGD systems use forced oxidation systems (U.S. EPA, 2010). According to Maher
et al. (2010), the majority of selenium discharged from these types of scrubbers is in the form of
selenate.
Methodology Updates Subsequent to the 2015 Final EA
Since the completion of the 2015 Final EA, EPA incorporated the following updates to the
equations, data sets, and parameter values used in the Water Quality Module:
• NHDPlus Version 2. EPA used the most recent version of the National Hydrography
Dataset Plus (NHDPlus). NHDPlus Version 2 has been updated by its developers to
incorporate higher resolution data sets and revised watershed boundaries and
elevation data, among other improvements.
• Lake depth. For the 2015 Final EA, EPA obtained site-specific mean and maximum
lake depth values by researching external sources. NHDPlus Version 2 now includes
modeled estimates of mean lake depth. For this Supplemental EA, EPA continued to
use the site-specific mean depth values used in the 2015 Final EA, where available.
However, for those receiving waters where EPA had previously identified only a
maximum lake depth value (instead of the mean depth, which is preferred), EPA used
the modeled mean depth values provided by the Lake Morphometry layer in
NHDPlus Version 2.
• Lake surface area. For the 2015 Final EA, EPA obtained site-specific lake surface
area values by researching external sources. The Lake Morphometry layer in
NHDPlus Version 2 now includes surface area data. For this Supplemental EA, EPA
used surface area data from the Lake Morphometry layer, where available; otherwise,
EPA used external sources for surface area.
• Average annual stream/low. For the 2015 Final EA, EPA selected the average annual
streamflow data calculated using the Vogel method in NHDPlus. For this
Supplemental EA, EPA used the updated flow values in NHDPlus Version 2 that
were calculated using the Extended Unit Runoff Method (EROM). EPA determined
that EROM was a more up-to-date and robust method for calculating streamflow than
the Vogel method due to its use of more recent data in its calculations and availability
of estimated monthly flow rates in addition to average annual flow rates.
• Freshwater NRWQC. EPA incorporated updated NRWQC for cadmium, copper, and
selenium.
Cadmium. EPA has updated the acute and chronic NRWQC to match updates
finalized in 2016.
Copper. For this Supplemental EA for the final rule, EPA calculated acute and
chronic NRWQC using the Biotic Ligand Model (BLM) and input water quality
data that are representative of the ecoregions containing surface waters that
receive discharges of the evaluated wastestreams (and their downstream waters)
(U.S. EPA, 2020e). This is an update to the 2015 Final EA and the Supplemental
Environmental Assessment for Proposed Revisions to the Effluent Limitations
C-2
-------
Appendix C— Water Quality Module Methodology
Guidelines and Standards for the Steam Electric Power Generating Point Source
Category (2019 Supplemental EA), Document No. EPA-821-R-19-010 (U.S.
EPA, 2019a), where EPA used the hardness-based 1995 acute and chronic
NRWQC expressed on a dissolved basis (U.S. EPA, 2002). EPA finalized revised
NRWQC in 2007 based on the BLM, a metal bioavailability model that uses
receiving water body characteristics and monitoring data to develop site-specific
water quality criteria (U.S. EPA, 2007).
- Selenium. EPA has updated the NRWQC to reflect updates finalized in 2016.
Selenium acute and chronic NRWQC were changed to include discrete values for
lotic and lentic systems. This was intended to reflect differences in selenium
bioaccumulation documented in lotic and lentic environments.
IRW Model: Water Quality Module Equations
EPA calculated the nonvolatile pollutant concentrations for the following compartments within
the receiving water:
• Total pollutant concentration in water column (Cwc).
• Dissolved pollutant concentration in water column (Cdw).
• Total pollutant concentration in sediment (Cbs).
EPA used the equations presented below to calculate receiving water concentrations for arsenic,
cadmium, copper, lead, mercury, nickel, selenium, thallium, and zinc.
Equation C-l
„ _ Lt0tai
WT°t' Rivers ~ 7q +Q ") x f , + K , X v ¦
vV„or)i V ¦ ) xwater AN-wt v river
cuui river
Where:
CwTot,Rivers
Total pollutant concentration in the
waterbody (water and sediment) in rivers
and streams from pollutant loading (grams
per cubic meter (g/m3) or milligrams per
liter (mg/L))
Output from Equation C-l
Ltotal
Average pollutant loading from evaluated
wastestreams (grams per day (g/day))
Site-specific value from
engineering analysis, based
on annual average
(see Table C-l)
Qcool
Total cooling water effluent flow (cubic
meters per day (m3/day))
Site-specific value from
engineering analysis
(see Table C-l)
Qriver
Receiving water average annual flow
(m3/day)
Site-specific value from
NHDPlus Version 2
(see Table C-l)
C-3
-------
Appendix C— Water Quality Module Methodology
fwater
=
Fraction of total waterbody pollutant
concentration in water column (unitless)
Output from Equation C-6
Kwt
=
Water concentration dissipation rate
constant (1/day)
Output from Equation C-10
Vriver
=
Flow independent mixing volume for rivers
and streams (m3)
Output from Equation C-l 1
Equation C-2
„ _ Lt0tai
WTOt' ^ _ (Qcool + Q^Jxfwater + KwtXV^
Where:
CwTot, Lake
Total pollutant concentration in the
waterbody (water and sediment) in lakes,
ponds, and reservoirs from pollutant loading
(g/m3 or mg/L)
Output from Equation C-2
Ltotal
Average pollutant loading from evaluated
wastestreams (g/day)
Site-specific value from
engineering analysis, based
on annual average
(see Table C-l)
Qcool
Total cooling water effluent flow (m3/day)
Site-specific value from
engineering analysis
(see Table C-l)
Qlake
Average annual flow exiting the lake, pond,
or reservoir (m3/day)
Site-specific value from
NHDPlus Version 2
(see Table C-l)
fwater
=
Fraction of total waterbody pollutant
concentration in water column (unitless)
Output from Equation C-6
Kwt
=
Water concentration dissipation rate
constant (1/day)
Output from Equation C-10
Vlake
=
Flow independent mixing volume for lakes,
ponds, and reservoirs (m3)
Output from Equation C-l2
C-4
-------
Appendix C— Water Quality Module Methodology
Equation C-3
Where:
Cwc
=
Total pollutant concentration in water column
(mg/L)
Output from Equation C-3
fwater
=
Fraction of total waterbody pollutant
concentration in water column (unitless)
Output from Equation C-6
CwTot
(Rivers or
Lakes)
Total pollutant concentration in the waterbody
(water and sediment) from pollutant loading
(g/m3 or mg/L)
Output from Equation C-l
or Equation C-2
dz
(Rivers or
=
Depth of the waterbody, including upper
benthic layer (meters (m))
River or stream: output
from Equation C-9
Lakes)
Lake, pond, or reservoir:
site-specific value (see
Table C-l)
dw
(Rivers or
=
Depth of water column (m)
River or stream: output
from Equation C-9
Lakes)
Lake, pond, or reservoir:
site-specific value (see
Table C-l)
Equation C-4
Cdw " Cwc (l +Kdsw x TSS x 0.000001
Where:
Cdw
=
Dissolved pollutant concentration in water
(mg/L)
Output from Equation C-4
Cwc
=
Total pollutant concentration in water column
(mg/L)
Output from Equation C-3
Kdsw
Suspended sediment-surface water partition
coefficient (milliliters per gram (mL/g))
Globally assigned value
(see Table C-2 and Table
C-4)
TSS
Total suspended solids (mg/L)
Regionally assigned value
(see Table C-3 and Table
C-5)
0.000001
=
Conversion factor (L/mL)(g/mg)
Conversion factor
dz
— "P x x
^ \vc xwater ^ wtot (Rivers or Lakes) i
aw
C-5
-------
Appendix C— Water Quality Module Methodology
Equation C-5
Where:
Cbs
't otal pollutant concentration in sediment
(mg/L)
Output from Equation C-5
fBenth
Fraction of total waterbody pollutant
concentration in benthic sediment (unitless)
Output from Equation C-15
CwTot
(Rivers or
Lakes)
Total pollutant concentration in the waterbody
(water and sediment) from pollutant loading
(g/m3 or mg/L)
Output from Equation C-l
or Equation C-2
dz
(Rivers or
Lakes)
Depth of the waterbody, including upper
benthic layer (m)
River or stream: output
from Equation C-9
Lake, pond, or reservoir:
site-specific value (see
Table C-l)
db
(Rivers or
Lakes)
Depth of upper benthic sediment layer (m)
Globally assigned value of
0.03 m (see Table C-2)
Equation C-6
[1 + (Kdsw x TSS x 0.000001)] x $£
^ Oz
(bsp + Kdbs x bsd) x ^
UZ_
Where:
fwater
Fraction of total waterbody pollutant
concentration in water column
(unitless)
Output from Equation C-6
Kdsw
=
Suspended sediment-surface water
partition coefficient (mL/g)
Globally assigned value
(see Table C-2 and Table C-4)
TSS
=
Total suspended solids (mg/L)
Regionally assigned value
(see Table C-3 and Table C-5)
0.000001
=
Conversion factor (L/mL)(g/mg)
Conversion factor
dz
^bs — ^Beiitti X (Rivers or Lakes) X "7"
Oh
^ water
[1 + (Kdsw x TSS x 0.000001)] x ^
C-6
-------
Appendix C— Water Quality Module Methodology
dw
(Rivers or
Lakes)
Depth of water column (m)
River or stream: output from
Equation C-7
Lake, pond, or reservoir:
site-specific value (see Table C-l)
dz
(Rivers or
Lakes)
Depth of the waterbody, including
upper benthic layer (m)
River or stream: output from
Equation C-9
Lake, pond, or reservoir:
site-specific value (see Table C-l)
Bsp
Bed sediment porosity (cubic
centimeter per cubic centimeter
(cm3/cm3))
Globally assigned value of 0.6
cm3/cm3 (see Table C-2)
Kdbs
=
Bottom sediment-pore water partition
coefficient (mL/g)
Globally assigned value
(see Table C-2) and Table C-4)
Bsd
Bed sediment bulk density (gram per
cubic centimeter (g/cm3)) or
(kilogram per liter (kg/L))
Globally assigned value of 1 g/cm3
(see Table C-2)
db
=
Depth of upper benthic layer (m)
Globally assigned value of 0.03 m
(see Table C-2)
Equation C-7
Q
i _ ^nver
w ~ V x Width
Where:
dw, river
=
Depth of water column (m)
Output from Equation C-7
Qriver
Receiving water average annual flow
(m3/s)
Site-specific value from
NHDPlus Version 2
(see Table C-l)
V
Receiving water velocity (m/s)
Site-specific value from
NHDPlus Version 2
(see Table C-l)
Width river
=
Receiving water width (m)
Output from Equation C-8
C-7
-------
Appendix C— Water Quality Module Methodology
Equation C-8
Widthriver= 5.1867 X Q04559
over
Where:
Widthriver
=
Receiving water width (m)
Output from Equation C-8
Qriver
Receiving water average annual flow
(m3/s)
Site-specific value from
NHDPlus Version 2
(see Table C-l)
Equation C-9
dz, river — db + dw, river
Where:
dz, river
=
Depth of the waterbody, including upper
benthic layer (m)
Output from Equation C-9
db
=
Depth of upper benthic sediment layer (m)
Globally assigned value 0.03
m (see Table C-2)
dw, river
=
Depth of water column (m)
Output from Equation C-7
Equation C-10
Kwt — (fwater X ksw) + (fbenth X kSed) (f\vaterX kVo l) + (fbenth X Kb)
Where:
Kwt
Water concentration dissipation rate
constant (1/day) for nonvolatile pollutants
(see Equation C-l6 for volatile pollutants)
Output from Equation C-10
fwater
=
Fraction of total waterbody pollutant
concentration in water column (unitless)
Output from Equation C-6
ksw
=
Degradation rate for water column (1/day)
Globally assigned value of
0/day (see Table C-2)
fbenth
Fraction of total waterbody pollutant
concentration in benthic sediment
(unitless)
Output from Equation C-l 5
ksed
=
Degradation rate for sediment (1/day)
Globally assigned value of
0/day (see Table C-2)
kvol
=
Water column volatilization loss rate
constant (1/day)
Globally assigned value of
0/day (see Table C-2)
Kb
=
Benthic burial rate (1/day)
Output from Equation C-l4
C-8
-------
Appendix C— Water Quality Module Methodology
Equation C-ll
Vriver Wldthriver ^ Lcil
x dz,river
Where:
Vriver
=
Flow independent mixing volume for
rivers and streams (m3)
Output from Equation C-ll
Widthriver
=
Receiving water width (m)
Output from Equation C-8
Len
Length of stream reach (m)
Site-specific value from
NHDPlus Version 2
(see Table C-l)
dz, river
=
Depth of the waterbody, including upper
benthic layer (m)
Output from Equation C-9
Equation C-12
Vlake = Area x dz,lake
Where:
Vlake
=
Flow independent mixing volume for
lakes, ponds, and reservoirs (m3)
Output from Equation C-12
Area
Surface area of the lake (m2)
Site-specific value from
NHDPlus Version 2
(see Table C-l
dz,lake
Depth of the lake, including upper benthic
layer (m)
Site-specific value from
NHDPlus Version 2 or other
data source (see Table C-l)
Equation C-13
1
^ =
d 1+Kdswx TSS x 0.000001
Where:
fd
=
Dissolved fraction in water (unitless)
Output from Equation C-13
KdSw
Suspended sediment-surface water
partition coefficient (mL/g)
Globally assigned value
(see Table C-2) and Table C-
4)
TSS
=
Total suspended solids (mg/L)
Regionally assigned value (see
Table C-3 and Table C-5)
0.000001
=
Conversion factor (L/mL)(g/mg)
Conversion factor
C-9
-------
Appendix C— Water Quality Module Methodology
Equation C-14
Where:
WB
Kb — fbenth X ~ j
ab
Kb
=
Benthic burial rate (1/day)
Output from Equation C-14
fbenth
Fraction of total waterbody pollutant
concentration in benthic sediment
(unitless)
Output from Equation C-15
WB
=
Rate of burial (m/day)
Globally assigned value of 0
m/day (see Table C-2)
db
=
Depth of upper benthic sediment layer (m)
Globally assigned value of
0.03 m (see Table C-2)
Equation C-15
fBenth "
(bsp + Kdbs x bsd) x ^
[1 + (Kdsw x TSS x 0.000001)] x ^
(bsp + Kdbs x bsd) x -£¦
Where:
fbenth
Fraction of total waterbody pollutant
concentration in benthic sediment
(unitless)
Output from Equation C-15
bsp
=
Bed sediment porosity (cm3/cm3)
Globally assigned value of 0.6
cm3/cm3 (see Table C-2)
Kdbs
Bottom sediment-pore water partition
coefficient (mL/g)
Globally assigned value
(see Table C-2) and Table C-
4)
bsd
=
Bed sediment bulk density (g/cm3) or
(kg/L)
Globally assigned value of 1
g/cm3 (see Table C-2)
db
=
Depth of upper benthic sediment layer (m)
Globally assigned value of
0.03 m (see Table C-2)
dz
=
Depth of the waterbody, including upper
benthic layer (m)
Output from Equation C-9
KdSw
Suspended sediment-surface water
partition coefficient (mL/g)
Globally assigned value
(see Table C-2) and Table C-
4)
TSS
=
Total suspended solids (mg/L)
Regionally assigned value
(see Table C-3 and Table C-5)
C-10
-------
Appendix C— Water Quality Module Methodology
0.000001
=
Conversion factor (L/mL)(g/mg)
Conversion factor
dw
(Rivers or
Lakes)
Depth of water column (m)
River or stream: output from
Equation C-7
Lake, pond, or reservoir:
site-specific value
(see Table C-l)
EPA calculated the volatile pollutant concentrations in each of the three compartments within the
receiving water by building off the equations used to calculate nonvolatile pollutant
concentrations. The water concentration dissipation rate constant, Kwt, in Equation C-10 was
replaced with a Kwt,volatile factor (see Equation C-16) that takes into account volatilization loss
(kvoi). EPA used the equations presented below in combination with the preceding equations to
calculate receiving water concentrations for mercury only.
Equation C-16
Kwt, volatile — (^water X ksw) (fbenth X ksed) (^water X ^d X kVo l) + (fbenth X Kb)
Where:
Kwt, volatile
=
Water concentration dissipation rate
constant (1/day)
Output from Equation C-16
fwater
=
Fraction of total waterbody pollutant
concentration in water column (unitless)
Output from Equation C-6
ksw
=
Degradation rate for water column (1/day)
Globally assigned value of
0/day (see Table C-2)
fbenth
Fraction of total waterbody pollutant
concentration in benthic sediment
(unitless)
Output from Equation C-l 5
ksed
=
Degradation rate for sediment (1/day)
Globally assigned value of
0/day (see Table C-2)
fd
=
Dissolved fraction in water (unitless)
Output from Equation C-l3
kvoi
=
Water column volatilization loss rate
constant (1/day)
Output from Equation C-l7
Kb
=
Benthic burial rate (1/day)
Output from Equation C-l4
C-ll
-------
Appendix C— Water Quality Module Methodology
Equation C-17
Where:
kvoi
=
Water column volatilization loss rate
constant (1/day)
Output from Equation C-17
Kv
=
Diffusion transfer rate (m/day)
Output from Equation C-18
fd
=
Dissolved fraction in water (unitless)
Output from Equation C-13
dw
(Rivers or
Lakes)
Depth of water column (m)
River or stream: output from
Equation C-7
Lake, pond, or reservoir:
site-specific value (see Table
C-l)
Equation C-18
Where:
Kv
=
Diffusion transfer rate (m/day)
Output from Equation C-18
©water
=
Temperature correction (unitless)
Globally assigned value of
1.026 (see Table C-2)
Tw
Temperature of the waterbody (Kelvin
(K))
River or stream: regionally
assigned value
(see Table C-3 and Table C-6)
Lake, pond, or reservoir:
globally assigned value (see
Table C-3 and Table C-6)
Thlc
=
Temperature of Henry's Law Constant
(HLC) (K)
Globally assigned value of 298
K (see Table C-2)
Kl
(Rivers or
Lakes)
Liquid-phase transfer coefficient (m/day)
River or stream: output from
Equation C-l9
Lake, pond, or reservoir:
output from Equation C-21
_KvXfd
•vol 1
dw
C-12
-------
Appendix C— Water Quality Module Methodology
Kg
(Rivers or
Lakes)
Gas-phase transfer coefficient (m/day)
River or stream: globally
assigned value of 100 m/day
(see Table C-2)
Lake, pond, or reservoir:
output from Equation C-23
HLC
Henry's Law Constant (atm-m3/mole) 1
Globally assigned value of
0.0113 atm-m3/mol (see Table
C-2)
R
Universal gas constant (atm-m3/K-mole)
Globally assigned value of
0.00008205 atm-m3/K-mole
(see Table C-2)
Equation C-19
Where:
KL(Rivers)
=
Liquid-phase transfer coefficient (m/day)
Output from Equation C-19
Dw
=
Diffusivity of the pollutant in water
(square centimeter per second (cm2/s))
Output from Equation C-20
V
=
Receiving water velocity (m/s)
Site-specific value from
NHDPlus Version 2
(see Table C-l)
dz,river
=
Depth of waterbody, including upper
benthic layer (m)
Output from Equation C-9
86,400
=
Conversion factor (s/day)
Conversion factor
Equation C-20
_ 22xl0"5
°w mw2/3
Where:
Dw
=
Diffusivity of the pollutant in water
(cm2/s)
Output from Equation C-20
MW
Molecular weight (grams per mole
(g/mol))
Globally assigned value of
200.59 g/mol for mercury (see
Table C-2)
1 Units for Henry's Law Constant are atmospheres of absolute pressure (atm) per cubic meter (m3) per mole (mol).
I10"4 xDwxv
KL(Rivers)- | ~j X 86,400
C-13
-------
Appendix C— Water Quality Module Methodology
Equation C-21
Id /k°'33\
KL(Lakes) = Vc7 x w10 x U x _ x Sc;067 x 86,400
Where:
KL(Lakes)
=
Liquid-phase transfer coefficient (m/day)
Output from Equation C-21
Cd
=
Drag coefficient (unitless)
Globally assigned value of
0.0011 (see Table C-2)
Wio
=
Wind velocity 10 meters above water
surface (m/s)
Regionally assigned value
(see Table C-3)
Pa
=
Density of air corresponding to water
temperature (g/cm3)
Globally assigned value of
0.0012 g/cm3 (see Table C-2)
Pw
=
Density of water corresponding to water
temperature (g/cm3)
Globally assigned value of 1
g/cm3 (see Table C-2)
k
=
Von Karman's constant (unitless)
Globally assigned value of 0.4
(see Table C-2)
^2
=
Dimensionless viscous sublayer thickness
(unitless)
Globally assigned value of 4
(see Table C-2)
Scw
=
Water Schmidt number (dimensionless)
Output from Equation C-22
86,400
=
Conversion factor (s/day)
Conversion factor
Equation C-22
\K
«c = ' w
" P.-D.
Where:
Scw
=
Water Schmidt number (dimensionless)
Output from Equation C-22
|iw
=
Viscosity of water corresponding to water
temperature (g/cm-s)
Globally assigned value of
0.0169 g/cm-s (see Table C-2)
Pw
=
Density of water corresponding to water
temperature (g/cm3)
Globally assigned value of 1
g/cm3 (see Table C-2)
Dw
=
Diffusivity of the pollutant in water
(cm2/s)
Output from Equation C-20
C-14
-------
Appendix C— Water Quality Module Methodology
Equation C-23
/k033\
Kg(Lakes) = VQ x W10 x f — J X Scf67 x 86,400
Where:
Kg(lakes)
=
Gas-phase transfer coefficient (m/day)
Output from Equation C-23
Cd
=
Drag coefficient (unitless)
Globally assigned value of
0.0011 (see Table C-2)
Wio
=
Wind velocity 10 meters above water
surface (m/s)
Regionally assigned value
(see Table C-3)
k
=
Von Karman's constant (unitless)
Globally assigned value of 0.4
(see Table C-2)
^2
=
Dimensionless viscous sublayer thickness
(unitless)
Globally assigned value of 4
(see Table C-2)
SCa
=
Air Schmidt number (dimensionless)
Output from Equation C-24
86,400
=
Conversion factor (s/day)
Conversion factor
Equation C-24
(1.32 + 0.009TJ x 105
mw2/3
Where:
SCa
=
Air Schmidt number (dimensionless)
Output from Equation C-24
Ta
=
Air temperature (K)
Regionally assigned value (see
Table C-3)
MW
Molecular weight (g/mol)
Globally assigned value of
200.59 g/mol for mercury (see
Table C-2)
EPA calculated the potential water quality impacts to aquatic life and humans by comparing the
pollutant concentration in the water column (Cwc or Cdw, depending on the benchmark) to the
water quality benchmark values presented in Table C-7.
C-15
-------
Appendix C— Water Quality Module Methodology
IRW Model: Water Quality Module Inputs
Table C-l. Input Variables with Values from Site-Specific Data Sources
Input
Variable
Input Category and
Description
Site-Specific Data Source
Ltotal
Plant-specific effluent
characteristic.
Total waterbody loading.
EPA estimated the pollutant discharge loadings using the
methodology presented in the Supplemental TDD.
Qcool
Plant-specific effluent
characteristic.
Total cooling water effluent
flow by receiving water.
EPA estimated the cooling water flow for each plant by outfall based
on an assessment of industry survey results using the methodology
outlined in the memorandum "Receiving Water Characteristics
Analysis and Supporting Documentation for the 2020 Steam Electric
Supplemental Environmental Assessment" (the Receiving Water
Characteristics memorandum) (ERG, 2020c).
Qriver
Receiving water characteristic
for rivers and streams.
Waterbody average annual
flow.
EPA extracted average annual flow values from the NHDPlus
Version 2 data set using the methodology outlined in the Receiving
Water Characteristics memorandum (ERG, 2020c). EPA used the
average annual flow values calculated using the Enhanced Runoff
Method (EROM). See the memorandum "Monthly Water Quality
Modeling Analysis and Supporting Documentation for the 2020
Steam Electric Supplemental Environmental Assessment" (the
Monthly Water Quality Modeling memorandum) (ERG, 2020k)
regarding the flow values used in the supplemental monthly analysis.
V
Receiving water characteristic
for rivers and streams.
Receiving water velocity.
EPA extracted average annual velocity values from the NHDPlus
Version 2 data set using the methodology outlined in the Receiving
Water Characteristics memorandum (ERG, 2020c). The NHDPlus
Version 2 data set includes estimated mean annual velocity values
for each stream reach within the network calculated with regression
analyses using the mean annual flow.
Len
Receiving water characteristic
for rivers and streams.
Length of stream reach.
EPA estimated the stream reach length based on outfall locations
using the methodology described in the Receiving Water
Characteristics memorandum (ERG, 2020c).
Qlake
Receiving water characteristic
for lakes, ponds, and reservoirs.
Average annual discharge flow
exiting the lake/pond system.
EPA extracted average annual flow values from the NHDPlus
Version 2 data set using the methodology outlined in the Receiving
Water Characteristics memorandum (ERG, 2020c). EPA used the
average annual flow values calculated using EROM.
Area
Receiving water characteristic
for lakes, ponds, and reservoirs.
Surface area of the lake, pond,
or reservoir.
EPA estimated the surface area of the lake, pond, or reservoir based
on the surface area field from the NHDPlus Version 2 Lake
Morphometry data layer, or site-specific data as described in the
Receiving Water Characteristics memorandum (ERG, 2020c).
dw,lake
Receiving water characteristic
for lakes, ponds, and reservoirs.
Depth of the water column.
The EPA estimated the depth of the lake, pond, or reservoir based on
the mean depth field from the NHDPlus Version 2 Lake
Morphometry data layer, or site-specific data as described in the
Receiving Water Characteristics memorandum (ERG, 2019d).
C-16
-------
Appendix C— Water Quality Module Methodology
Table C-2. Input Variables and Constants with Globally Assigned Values
Input Variable
or Constant
Description
Assigned
Value
Rationale/Data Source
bsp
Bed sediment porosity.
0.6 cm3/cm3
Bed sediment porosity is the volume of water per
volume of benthic space with typical values ranging
between 0.4 and 0.8 (U.S. EPA, 1998). EPA selected
an average value to use for this input variable.
bsd
Bed sediment bulk
density.
1 g/cm3
Bed sediment bulk densities typically range between
0.5 to 1.5 g/cm3 (U.S. EPA, 1998). EPA selected an
average value to use for this input variable.
db
Depth of upper benthic
layer.
0.03 m
The upper benthic layer variable represents the portion
of the bed in equilibrium with the water column.
Typical values can range from 0.01 to 0.05 m (U.S.
EPA, 1998). EPA selected an average value to use for
this input variable.
ksw
Degradation rate for
water column.
0/day
EPA assumed no loss from pollutant degradation in
the water column, as an environmentally conservative
assumption.
kvd
Water column
volatilization loss rate
constant.
0/day
EPA selected a volatilization rate of 0 for nonvolatile
pollutants (i.e., all pollutants except mercury).
ksed
Degradation rate for
sediment.
0/day
EPA assumed no loss from pollutant degradation in
the sediment, as an environmentally conservative
assumption.
WB
Rate of burial.
0/day
EPA assumed no pollutant loss from burial within the
waterbody sediments, as an environmentally
conservative assumption.
©water
Temperature correction.
1.026
(unitless)
EPA selected the temperature correction factor based
on the value provided in U.S. EPA (1998).
K-g(Rivers)
Gas phase transfer
coefficient for rivers or
streams.
36,500 m/yr
(100 m/day)
EPA selected the gas phase transfer coefficient for
rivers and streams based on the value provided in U.S.
EPA (1998).
R
Ideal gas constant.
0.00008205
atm-m3/
K-mole
The ideal gas constant is a known chemical constant.
cd
Drag coefficient.
0.0011
(unitless)
EPA selected the drag coefficient based on the value
provided in U.S. EPA (1998).
pa
Density of air
corresponding to water
temperature.
0.0012
g/cm3
EPA selected the density of air corresponding to water
temperature based on the value provided in U.S. EPA
(2005a).
Pw
Density of water
corresponding to water
temperature.
1 g/cm3
EPA selected the density of water corresponding to
water temperature based on the value provided in U.S.
EPA (2005a).
k
VonKarman's constant.
0.4
(unitless)
The von Karman constant is a known dimensionless
constant used to describe the velocity profile of a
turbulent fluid flow near a boundary.
C-17
-------
Appendix C— Water Quality Module Methodology
Table C-2. Input Variables and Constants with Globally Assigned Values
Input Variable
or Constant
Description
Assigned
Value
Rationale/Data Source
Kdsw
Suspended sediment-
surface water partition
coefficient.
See
Table C-4
The suspended sediment partition coefficient
describes the partitioning of a pollutant between
sorbing material, in this case suspended sediment, and
surface water. EPA identified U.S. EPA (2005a) as the
primary source for the pollutant-specific suspended
sediment partition coefficients.
Kdbs
Bottom sediment-pore
water partition
coefficient.
See
Table C-4
The bottom sediment partition coefficient describes
the partitioning of a pollutant between sorbing
material, in this case bottom sediment, and pore water.
EPA identified U.S. EPA (2005a) as the primary
source for the pollutant-specific bottom sediment
partition coefficients.
\,2
Dimensionless viscous
sublayer thickness.
4
(unitless)
EPA selected the viscous sublayer thickness value
based on the value provided in U.S. EPA (2005a).
(J-W
Viscosity of water
corresponding to water
temperature.
0.0169
g/cm-s
EPA selected the viscosity of water value based on the
value provided in U.S. EPA (2005a).
HLC
Henry's Law Constant.
0.0113
atm-m3/mol
Henry's Law Constant is used in Equation C-18 to
estimate the receiving water concentration for volatile
pollutants. Mercury is the only volatile pollutant
included in the IRW Model. Therefore, the assumed
model default value is set to Henry's Law Constant
for mercury at 298 K.
Thic
Temperature of Henry's
Law Constant.
298 K
The value 298 K is the standard temperature value
provided for Henry's Law Constant.
MW
Molecular weight.
200.59
g/mol
Molecular weight is used in Equation C-20 and
Equation C-24 to estimate the receiving water
concentration for volatile pollutants. Mercury is the
only volatile pollutant included in the IRW Model.
Therefore, the assumed model default value is set to
the molecular weight for mercury.
C-18
-------
Appendix C— Water Quality Module Methodology
Table C-3. Input Variables with Values from Regional Data Sources
Input Variable
Description
Assigned
Value
Regional Data Source
TSS
Total suspended solids.
See
Table C-5
EPA used the geometric mean of the regional and
national TSS concentrations determined as part of the
Human and Ecological Risk Assessment of Coal
Combustion Residuals (U.S. EPA, 2014a).
W10:
Wind velocity 10 m above
the water surface.
See
Figure C-l
National Climatic Data Center national mean annual
wind speed GIS coverage, downloaded on May 12,
2011 (NCDC, 2011). EPA selected, as an
environmentally conservative estimate, the lower of
the wind speed range values for the analysis.
Ta
Air temperature.
See
Figure C-2
National Climatic Data Center national mean annual
temperature GIS coverage, downloaded on May 12,
2011 (NCDC, 2011). EPA selected, as an
environmentally conservative estimate, the lower of
the air temperature range values for the analysis.
Tw
Temperature of the
surface water.
See
Table C-6
EPA used the regional surface temperatures used in
the Human and Ecological Risk Assessment of Coal
Combustion Residuals (U.S. EPA, 2014a).
STATES
iN SPEED OF WIND (MPH)
- ANNUAL -
A < 6.0
B 6.0 - 6.9
C 7.0-7.9
D 8.0-8.9
E 9.0 - 9.9
F 10.0-10.9
G 11.0-11.9
H > 11.9
TITLE
Figure C-1. National Climatic Data Center National Mean Annual Wind Speeds
¦k
~
13 ME/
sr.
ANNUAL
MEAN WIND SPEED
C-19
-------
Appendix C— Water Quality Module Methodology
STATES
^N DAILY AVG TEMP (DEG_F)
- ANNUAL -
A < 32.0
B 32.0-40.0
C 40.1 -45.0
D 45.1 - 50.0
E 50.1 - 55.0
F 55.1 - 60.0
G 60.1 -65.0
H 65.1 - 70.0
I > 70.0
TITLE
Figure C-2. National Climatic Data Center National Mean Annual Temperatures
Table C-4. Partition Coefficients
Pollutant
Suspended Sediment-
Water Partition
Coefficient (Kdsw)
(mL/g)
Bottom Sediment-Pore
Water Partition
Coefficient (Kdbs)
(mL/g)
Arsenic
7,900
250
Cadmium
79,000
2,000
Copper
50,000
3,200
Lead
500,000
40,000
Mercury (II)
200,000
79,000
Nickel
20,000
7,900
Selenium (IV)
25,000
4,000
Thallium
13,000
20
Zinc
100,000
13,000
Source: U.S. EPA, 2005a.
C-20
-------
Appendix C— Water Quality Module Methodology
Table C-5. TSS Concentrations in Surface Waters
llvdrolo^ic
Roiiion •'
Number of
Mcsisiiiyiik'iiIs
Number of
Aiimiiil Modiiius
Ail ill
(lo» I
Mill
-------
Appendix C— Water Quality Module Methodology
Table C-6. Regional Surface Water Temperatures
Hydrologic Region
Climate
Surface Water
Temperature (°C)
Su rface Water
Temperature (K)
1
North
14
287
2
North
16
289
3
South
21
294
4
North
14
287
5
North
17
290
6
South
18
291
7
North
15
288
8
South
20
293
9
North
10
283
10
North
13
286
11
South
17
290
12
South
21
294
13
South
16
289
14
South
9
282
15
South
17
290
16
South
9
282
17
North
11
284
Source: U.S. EPA, 2014a; Legacy STORET database.
C-22
-------
Appendix C— Water Quality Module Methodology
Table C-7. NRWQC and MCLs
l"\\ Anile
l \\ Chronic
llll WO
llll ()
\1( I."1
(niii/l.)
Polliiliini
\U\\Q( ''
\U\\Q( ''
\U\\Q( ,h
\ U\\ („)(' •l h
(inii/l.)
(inii/l.)
(inii/l.)
(inii/l.)
Arsenic
0.34
0.15
0.000018e
0.00014e
0.01
Cadmium
0.0018fg
0.00072f,g
--
--
0.005
Copper
0.014h
0.009 h
1.3
—
1.3 (Action
Level); 1.01
Lead
0.065f
0.0025f
—
--
0.015 (Action
Level)
Mercury
0.0014
0.00077
--
--
0.002e
Nickel
0.47f
0.052f
0.61
4.6
--
Selenium
Lentic: 0.045J
Lotic: 0.094J
Lentic: 0.0015 k
Lotic: 0.003 lk
0.17
4.2
0.05
Thallium
--
--
0.00024
0.00047
0.002
Zinc
0.12f
0.12f
7.4
26
51
Acronyms: FW (freshwater); HH O (human health organisms only); HH WO (human health water and organisms);
MCL (Maximum Contaminant Level); mg/L (milligrams per liter); NRWQC (National Recommended Water
Quality Criteria).
Source: U.S. EPA, 2009a, 2009c, 2016b, 2016c, and 2020e.
a - designates instances where a benchmark value does not exist for the pollutant, or the benchmark value is a
secondary standard.
b - Unless otherwise noted, pollutant concentrations were compared to NRWQC from EPA's National
Recommended Water Quality Criteria (U.S. EPA, 2009c).
c - Benchmark value is expressed in terms of the dissolved pollutant in the water column. For all pollutants except
selenium, this is calculated using a total-to-dissolved conversion factor (U.S. EPA, 2009c).
d - Unless otherwise noted, pollutant concentrations were compared to the MCL from EPA's National Primary
Drinking Water Regulations (U.S. EPA, 2009a).
e - Benchmark value is for inorganic form of pollutant.
f - The FW NRWQC for this metal are expressed as a function of hardness (mg/L) in the water column. The values
given here correspond to a hardness of 100 mg/L.
g- The cadmium benchmark values are based on the FW NRWQC from EPA's Aquatic Life Ambient Water Quality
Criteria for Cadmium - 2016 (U.S. EPA, 2016c).
h - For this analysis, EPA calculated FW NRWQC for copper using the Biotic Ligand Model (BLM) and input
water quality data that are representative of the ecoregions containing surface waters that receive discharges of the
evaluated wastestreams (and their downstream waters) (U.S. EPA, 2020e).
i - EPA evaluated both the action level of 1.3 mg/L and the secondary (nonenforceable) drinking water standard of
1.0 mg/L for copper (U.S. EPA, 2020d). The results presented in Section 4 of the report and Appendix F are based
on the number of immediate receiving waters with exceedances of the lower secondary drinking water standard (1.0
mg/L).
j - The selenium benchmark values are based on the NRWQC from EPA's Aquatic Life Ambient Water Quality
Criteria for Selenium - Freshwater 2016 (U.S. EPA, 2016b). The selenium acute NRWQC, as calculated here,
assumes a background selenium concentration of zero and an intermittent exposure duration of 1 day, which is the
shortest exposure period to be used when applying the criterion. This serves as an intermittent exposure element of
the chronic water quality criterion, intended to address short-term exposures that contribute to chronic effects
through selenium bioaccumulation.
k - The selenium benchmark values are based on the NRWQC from EPA's Aquatic Life Ambient Water Quality
Criteria for Selenium - Freshwater 2016 (U.S. EPA, 2016b). The selenium chronic water column NRWQC applies
only in the absence of fish tissue measurements. Use of this water column benchmark value may therefore over- or
underestimate the number of exceedances.
1 - EPA has not defined an MCL or action level for zinc. This benchmark value represents the secondary
(nonenforceable) drinking water standard for zinc (U.S. EPA, 2020d).
C-23
-------
Appendix C— Water Quality Module Methodology
IRW Model: Water Quality Module Methodology Limitations and Assumptions
The limitations and assumptions of the Water Quality Module include the following:
• The module is based on annual-average pollutant loadings from the two evaluated
wastestreams at coal-fired steam electric power plants and annual-average flow rates
within the immediate receiving waters. The module does not consider temporal
variability (e.g., seasonal differences, storm flows, low-flow events, catastrophic
events) and does not consider the potential for pollutants to accumulate in the
environment over extended discharge periods covering multiple years. The effect of
this limitation on the Water Quality Module outputs is undetermined, but it is likely
to underestimate the long-term accumulation of pollutants within lakes, ponds, and
reservoirs; this may subsequently underestimate the wildlife and human health
impacts resulting from exposure to pollutants in these systems. To illustrate potential
short-term temporal variability, EPA also performed Water Quality Module runs
using average monthly pollutant loadings and receiving water flow rates. This
analysis is documented in the Monthly Water Quality Modeling memorandum (ERG,
2020k) and the results are discussed in Section 4.4 of the report.
• The pollutant loadings used in the module are not based on site-specific discharge
data from each affected plant; rather, the loadings are reasonably estimated based on
average pollutant concentrations (calculated using available data from a subset of
plants) and plant-specific discharge flow rates. See Section 6 of the Supplemental
TDD. The net effect of this limitation on the Water Quality Module outputs is
undetermined, but it is likely to result in an overestimate of benchmark value
exceedances for some immediate receiving waters and an underestimate of
exceedances for other immediate receiving waters.
• The module represents only the waterbody concentration within the immediate
discharge zone (i.e., approximately 0.25 to 5 miles from the outfall) and does not
calculate pollutant concentrations in downstream waters. This limitation results in a
potential underestimate of the extent of surface waters with environmental and human
health impacts under baseline, as well as changes under the final rule and regulatory
options evaluated. However, EPA performed a downstream analysis using the outputs
from a separate pollutant fate and transport model. This analysis is documented in the
memorandum "Downstream EA Modeling Methodology and Supporting
Documentation for the 2020 Steam Electric Supplemental Environmental
Assessment" (ERG, 2020f), and the results are discussed in Section 4.5 of the report.
• The module does not take into consideration pollutant speciation within the receiving
stream. This limitation is particularly relevant to the wildlife impact analysis, as many
of the ecological impacts are tied to a specific pollutant species. For example,
inorganic arsenic is typically more toxic to aquatic life than organic arsenic. This
limitation results in a potential overestimation of the number of immediate receiving
waters with exceedances of water quality benchmark values for inorganic forms of
the pollutant (e.g., the human health NRWQC for arsenic).
• The module assumes that equilibrium is quickly attained within the waterbody
following discharge and is consistently maintained between the water column and
C-24
-------
Appendix C— Water Quality Module Methodology
surficial bottom sediments. This assumption is especially significant regarding
pollutant equilibrium within lakes, ponds, and reservoirs. The module equations
presented in Appendix C do not take into consideration the effects of currents,
inversion, or temperature variations within the water column, but assume that the
entire mass of the lake, pond, or reservoir is at equilibrium. As a result, the module
outputs do not reflect the potential spatial and temporal variability of pollutant
concentrations within the immediate receiving water, and potentially underestimate
the existence of isolated "hot spots" of elevated pollutant concentrations.
• The module assumes that pollutants dissolved or sorbed within the water column and
bottom sediments can be described by a partition coefficient. EPA used a single
partition coefficient to characterize the pollutant in the immediate receiving waters.
The partition coefficient in a specific waterbody will be influenced by geochemical
parameters (e.g., pH and presence of particulate organic matter and other sorbing
material). EPA used a mean or median value for the partition coefficients (central
tendency of Kd values) based on data gathered from published sources, statistical
analysis of retrieved data, geochemical modeling, and expert judgment (U.S. EPA,
2005a). The result of this assumption on the Water Quality Module outputs is
undetermined due to site-specific factors.
• The module assumes that pollutants sorbed to bottom sediments are considered a net
loss from the water column. This assumes that bottom sediments are not resuspended
and deposited further downstream but remain within the immediate discharge zone
and do not further contribute to the dissolved or suspended sediment concentrations
within the water column. This assumption results in a potential overestimation of
pollutant concentrations within the bottom sediments and a potential underestimation
of pollutant concentrations within the water column and downstream reaches.
• The module assumes a pollutant burial rate of zero within bottom sediment. This is an
environmentally protective assumption that might overestimate impacts to sediment
receptors to some degree. The burial rate constant is a function of the deposition of
sediments from the water column to the upper bed and accounts for the soil eroding
into a waterbody becoming bottom sediment rather than suspended sediment. The rate
of burial used for each segment of a waterbody may be difficult to obtain (U.S. EPA,
1998). EPA had neither measured values nor the data to estimate burial rates for each
immediate receiving water. This assumption results in a potential overestimation of
impacts in the bottom sediment.
• The module does not take into account ambient background pollutant concentrations
or contributions from other point and nonpoint sources. Also, the pollutant loadings
included in the module are not representative of the total pollutant loadings from
coal-fired steam electric power plants, as there are several wastestreams that are not
included in the analysis (e.g., fly ash transport water, leachate, stormwater runoff,
metal cleaning wastes, and coal pile runoff). Because of this approach, the module
likely underestimates the number and magnitude of benchmark value exceedances at
baseline and under the final rule and evaluated regulatory options, which contributes
to uncertainty in the number of environmental and human health improvements or
impacts under the final rule and evaluated regulatory options relative to baseline.
C-25
-------
Appendix D — Wildlife Module Methodology
APPENDIX D
WILDLIFE MODULE METHODOLOGY
This appendix presents the model equations, input variables and constants, pollutant benchmark
values, and methodology limitations/assumptions for the Wildlife Module of the Immediate
Receiving Water (IRW) Model, which quantifies impacts to the following ecological receptors:
• Aquatic and sediment organisms (amphibians, fish, invertebrates) in direct contact
with receiving water and/or sediment in the immediate discharge zone of coal-fired
steam electric power plants.
• Wildlife (minks and eagles)1 that consume fish from receiving waters in the
immediate discharge zone of plants.
For this supplemental environmental assessment (Supplemental EA), EPA estimated pollutant
concentrations in the immediate receiving water and sediment using the Water Quality Module
(see Appendix C). The Wildlife Module uses these concentrations as inputs.
The following tables describe the input requirements and data sources used in the Wildlife
Module:
• Table D-l. Threshold Effect Concentrations (TECs) for Sediment Biota.
• Table D-2. Bioconcentration Factors (BCFs) and Bioaccumulation Factors (BAFs) for
Trophic Level 3 (T3) and Trophic Level 4 (T4) Fish.
• Table D-3. No Effect Hazard Concentrations (NEHCs) for Minks and Bald Eagles.
Methodology Updates Subsequent to the 2015 Final EA
Since the completion of the 2015 Final EA, EPA incorporated the following updates to the
equations, data sets, and parameter values used in the Wildlife Module:
• Sediment threshold effect concentrations: For the 2015 Final EA, EPA used
threshold effect levels (TELs) referenced in a single study (NOAA, 2008) as the
benchmark values for impacts to sediment biota. For this Supplemental EA, EPA
replaced the TELs with threshold effect concentrations (TECs) developed through a
consensus-based process (MacDonald et al., 2000). MacDonald et al. (2000) used six
sets of sediment quality guidelines to develop the TECs.
• Sediment benchmark value for selenium: For the 2015 Final EA, EPA did not
identify a sediment benchmark value for selenium. For this Supplemental EA, EPA
identified and used a sediment benchmark value for selenium developed by Lemly
(2002) using a long-term selenium concentration data set collected from 1970 through
1996 at Belews Lake, NC. Lemly recommended 2 micrograms selenium per gram of
sediment (|ig/g, equivalent to g/kg) as a toxicity benchmark value that would be
1 The EPA selected minks and eagles to represent national-scale impacts from coal-fired steam electric power plants
because their habitats cover the entire United States (i.e., can be used for a national assessment).
D-l
-------
Appendix D — Wildlife Module Methodology
protective of reproductive success in fish and aquatic birds that bioaccumulate
selenium through consumption of benthic organisms.
• Revised Equation D-l: The TELs used in the 2015 Final EA were expressed based
on a wet weight basis, while the TECs used in this Supplemental EA are expressed on
a dry weight basis. To accommodate this change, EPA revised Equation D-l to
convert the pollutant concentration in sediment (Cbs) from a volume basis (mg/L) to a
dry weight basis (mg/kg) using the assumed values in the Water Quality Module for
bed sediment bulk density and porosity.
• Cadmium bioconcentration factor: In the 2015 Final EA, EPA used a cadmium
bioconcentration factor (BCF) of 270 liters per kilogram (L/kg), derived from
Kumada et al. (1972), and applied this BCF to both trophic level 3 (T3) and trophic
level 4 (T4) fish. For this Supplemental EA, EPA calculated an updated cadmium
BCF using the bioaccumulation data sets available in Appendix G of the U.S. EPA's
Aquatic Life Ambient Water Quality Criteria for Cadmium - 2016 (U.S. EPA, 2016c),
which presents a set of "Acceptable Bioaccumulation Data" that were reviewed
during development of the revised criteria. EPA's calculations, which resulted in an
updated cadmium BCF of 113 L/kg for both trophic levels, are documented in the
Cadmium BCF Calculation spreadsheet (ERG, 2019e).
IRW Model: Wildlife Module Equations, Input Variables, and Impact Analysis
Impact to Aquatic Life Receptors from Direct Contact with Sediment. EPA identified potential
negative impacts to aquatic organisms from direct contact with the sediment in immediate
receiving waters by comparing the estimated pollutant concentration in the sediment (Cbs from
the Water Quality Module) to the consensus-based TECs for sediment biota listed in Table D-l.
The Wildlife Module expresses this comparison as a hazard quotient (HQ). An HQ of higher
than one (i.e., pollutant concentration exceeds the TEC) indicates a potential impact to the
exposed organism. EPA used Equation D-l to calculate the HQ for sediment biota.
Equation D-l
HO (§3) - (t^U
scd TECsed
Where:
HQsed
=
Hazard quotient for contact with sediment
Output from Equation D-l
Cbs
=
Total pollutant concentration in sediment
(milligrams per liter (mg/L))
Water Quality Module output
from Equation C-5
bsd
Bed sediment bulk density (gram per cubic
centimeter (g/cm3)) or (kilogram per liter
(kg/L))
Globally assigned value of 1
g/cm3 (see Table C-2)
bsp
=
Bed sediment porosity (cubic centimeter per
cubic centimeter (cm3/cm3))
Globally assigned value of 0.6
cm3/cm3 (see Table C-2)
D-2
-------
Appendix D — Wildlife Module Methodology
TECsed
=
Threshold effect concentration for sediment
Receptor-specific value
(milligrams per kilograms (mg/kg), dry
(see Table D-l)
weight basis)
Adverse Effects to Piscivorous Wildlife. EPA identified potential negative impacts to piscivorous
wildlife (i.e., wildlife that consume fish) from the ingestion of contaminated fish by estimating
fish tissue concentrations and comparing these concentrations to NEHCs as the selected
ecological benchmark values. Equation D-2 calculates pollutant concentrations in fish for the
evaluated pollutants, except for mercury. Because the more toxic form of mercury is
methylmercury, EPA used Equation D-3 for this pollutant (U.S. EPA, 2005b). Equation D-3
estimates the concentration of methylmercury in fish tissue, as opposed to total mercury.
EPA compared the calculated T3 fish tissue concentration to the NEHC for minks and the
calculated T4 fish tissue concentration to the NEHC for eagles (see Table D-3). The Wildlife
Module expresses this comparison as an HQ. EPA used Equation D-4 to calculate HQ values for
arsenic, cadmium, copper, lead, mercury (as methylmercury), nickel, selenium, thallium, and
zinc.
Equation D-2
CfishT = Cwc x bcft
Equation D-3
CfishT = (0.15 x Cdw) x BCFt
Where:
CfishT
Pollutant concentration in fish (wet weight),
where T represents trophic level T3 or T4
(mg/kg)
Output from Equation D-2 or
Equation D-3
Cwc
=
Total pollutant concentration in water (mg/L)
Water Quality Module output
from Equation C-3
Cdw
=
Dissolved pollutant concentration in water
(mg/L)
Water Quality Module output
from Equation C-4
0.15
=
Fraction of dissolved total mercury as
dissolved methylmercury (unitless)
Globally assigned value (U.S.
EPA, 2005b)
BCFt
Bioconcentration factor or bioaccumulation
factor for specified trophic level (liters per
kilogram (L/kg))
Pollutant-specific value
(see Table D-2)
D-3
-------
Appendix D — Wildlife Module Methodology
Equation D-4
Where:
HQi
=
Hazard quotient for ingestion of fish
Output from Equation D-4
CfishT
Pollutant concentration in fish (wet weight),
where T represents trophic level T3 or T4
(mg/kg)
Output from Equation D-2 or
Equation D-3
NEHC
=
No effect hazard concentration (jug/g)
Receptor- and pollutant-
specific (see Table D-3)
Table D-l. TECs for Sediment Biota
Pollutant in Wildlife
Impact Assessment
TEC (m^/ks)
Notes/Source
Arsenic
9.79
MacDonald et al., 2000.
Cadmium
0.99
MacDonald et al., 2000.
Copper
31.6
MacDonald et al., 2000.
Lead
35.8
MacDonald et al., 2000.
Mercury
0.18
MacDonald et al., 2000.
Nickel
22.7
MacDonald et al., 2000.
Selenium
2
Lemly, 2018.
Thallium
None identified
EPA could not complete the analysis for this pollutant - no TEC
available for comparison.
Zinc
121
MacDonald et al., 2000.
Acronyms: mg/kg (milligrams per kilogram); TEC (Threshold Effect Concentration).
n _ CfishT
hq'~nehc
D-4
-------
Appendix D — Wildlife Module Methodology
Table D-2. BCFs and BAFs for T3 and T4 Fish
Pollutant
BCF or BAF
Factor for T3 Fish
(L/kg)
Factor for T4 Fish
(L/kg)
Source
Arsenic
BCF
4
4
Barrows et al., 1980.
Cadmium
BCF
113
113
ERG, 2019e.
Coppera
BCF
36
36
U.S. EPA, 1980b.
Lead
BAF
46
46
Stephan, 1993.
Methylmercury
BAF
1.6 x 106
6.8 x 106
U.S. EPA, 1997a.
Nickelb
BCF
0.8
0.8
Calamari et al., 1982.
Selenium
BAF
490
1,700
Lemly, 1985.
Thallium
BCF
34
130
Barrows et al., 1980
and Stephan, 1993.
Zinc
BCF
350
350
Murphy et al., 1978.
Acronyms: BAF (bioaccumulation factor); BCF (bioconcentration factor); L/kg (liters per kilogram); T3 (trophic
level 3); T4 (trophic level 4).
a - BCF not specific to a particular trophic level; applies to fish consumed by humans,
b - Nickel (soluble salts).
Table D-3. NEHCs for Minks and Bald Eagles
Polliilanl in
\\ ildlifo Impacl
M'.IK lor Mink
(13 l-'isli) (.ug/g)
M.IK for l agle
(14 l-'isli) (fig/g)
Soles
Arsenic
7.65
22.4
Cadmium
5.66
14.7
Copper
41.2
40.5
Lead
34.6
16.3
Methylmercury
0.37
0.5
No NEHC for methylmercury. EPA compared the
modeled methylmercury concentrations to the
total mercury NEHC, which may underestimate
the impact to wildlife.
Nickel
12.5
67.1
Selenium
1.13
4
Thallium
None identified
None identified
EPA could not complete the analysis for this
pollutant - no NEHC available for comparison.
Zinc
904
145
Source: USGS, 2008.
Acronyms: |ig/g (micrograms per gram); NEHC (No Effect Hazard Concentration); T3 (trophic level 3); T4 (trophic
level 4).
D-5
-------
Appendix D — Wildlife Module Methodology
IRW Model: Wildlife Module Methodology Limitations and Assumptions
The limitations and assumptions of the Wildlife Module include the following:
• Cumulative Risks Across Exposure Pathways. The Wildlife Module does not
consider cumulative risks across exposure pathways. For example, the modeled
impacts to wildlife from ingesting contaminated fish do not consider the risk from
direct contact with surface water. The receptors chosen for the wildlife ingestion
model, minks and eagles, do not spend much time in contact with the surface water;
therefore, not including the impact of direct contact with surface water should only
minimally underestimate the impacts. In addition, the Wildlife Module does not
consider the impact from water ingestion. Because many of the pollutants considered
in this analysis are bioaccumulative in nature, the model considers only ingestion of
the food source, because it is likely that the dose from the food source is far greater
than the dose from water ingestion. However, the Wildlife Module may
underestimate bioaccumulation among aquatic species that do ingest relatively greater
volumes of water.
• Use of BCFs and BAFs. Where available, EPA used BAFs to represent the
accumulation of pollutants in fish tissue (e.g., for selenium, lead, and
methylmercury). Otherwise, EPA used BCFs, which do not account for accumulation
of pollutants via the food web. For certain pollutants, exposure via the aquatic food
web can be more significant than exposure via ingestion of water.2 The result of this
limitation on the Wildlife Module output for those pollutants that use a BCF is an
under-representation of pollutant bioaccumulation in fish tissue where exposure via
the aquatic food web is significant. However, BCFs are useful in a screening-level
assessment and appropriate for a national-level EA, where site-specific data are
unavailable and collection of site-specific data is not viable. The limitation of using a
single, national-level BAF/BCF is undetermined due to site-specific factors.
• Receptor Populations Evaluated. EPA considered the limitations and made multiple
assumptions in choosing receptor populations to evaluate. First, EPA assumed that,
because this is a national model, the receptor species and receiving water occur
together (i.e., all receiving waters evaluated in the Wildlife Module are habitat for the
receptor species, even though that may not always be the case). In addition, due to the
scope of the project, EPA considered a limited number of species as receptors. For the
wildlife receptors, EPA chose minks and eagles due to their national distribution and
data available to conduct the analysis (USGS, 2008). By choosing a limited number
of species, the Wildlife Module inherently excludes the impacts to critical assessment
endpoints such as threatened and endangered species.
• Wildlife Receptor Diet. To provide an environmentally protective estimate of dietary
pollutant exposure, the Wildlife Module assumes that the diet of adult minks and bald
2 All the routes (food, sediment, and water) by which fish and shellfish are exposed to highly bioaccumulative
pollutants may be important in determining the accumulation in fish tissue and the subsequent transfer to human
receptors. In addition, distributions of BAFs/BCFs may be better than single BAFs/BCFs because they account for
changes in bioaccumulation/bioconcentration rates at different water concentrations. The EPA is working to develop
BAF/BCF distributions for several pollutants to better represent the bioaccumulation in aquatic organisms.
D-6
-------
Appendix D — Wildlife Module Methodology
eagles consists entirely of fish inhabiting the immediate receiving waters. EPA
concludes this assumption is reasonable based on the following two factors:
(1) It is possible that in some habitats the diet of both minks and eagles consists
largely of fish, and EPA aims to be protective of wildlife across all habitats.
For example, studies have shown dietary composition as high as 75 and 85
percent fish for bald eagles and minks, respectively (U.S. EPA, 1993). In
addition, it is likely that the other organisms consumed by minks and eagles
are also contaminated with the pollutants of concern and are unaccounted for
in the model.
(2) With respect to home ranges, the case study water quality modeling results in
Section 8 of the 2015 Final EA demonstrate that pollutants discharged from
coal-fired steam electric power plants can continue to occur at elevated levels
downstream from the immediate receiving waters, contaminating fish outside
of immediate receiving waters and resulting in additional potential for
pollutant exposure among piscivorous wildlife.
Overall, however, this assumption likely results in a potential overestimation of
exposure to the modeled species. The Wildlife Module also assumes that the diet of
adult minks consists entirely of T3 fish and the diet of bald eagles consists entirely of
T4 fish. These assumptions likely result in a potential overestimation of exposure
among eagles (whose diet may also include T3 fish) and an underestimation of
exposure among minks (whose diet may also include T4 fish).
• Bioavailability and Speciation of Pollutants. The IRW Model assumes that all forms
of a pollutant are equally bioavailable to ecological receptors. Therefore, data inputs
for the Wildlife Module include total pollutant concentration in the water column
(i.e., dissolved particles plus particles sorbed to suspended sediment) or sediment
concentration for all pollutants analyzed, except where noted. In addition, some
pollutant forms are more toxic to organisms, such as various forms of arsenic. While
different forms of arsenic exist in the water column, it is not possible to determine the
percentages of each due to the complexities of the chemistry of a particular
waterbody. Because of bioavailability and pollutant speciation assumptions made for
the wildlife impact assessment, the impact to receptors may be over- or
underestimated.
• Indirect Ecological Effects. The Wildlife Module does not consider indirect
ecological effects, such as depletion of food sources. Such indirect effects are difficult
to assess and are thought to have minimal impact on some wildlife species because
the impacted receiving water is only a small portion of the species' habitat. In
addition, many species will move into other areas in search of prey if food sources in
their current habitat decline.
• Full Mixing Effects for Receiving Water. The Water Quality Module assumes that
the receiving waterbody is fully mixed. In reality, the water in lakes might stratify,
especially if they are deep enough. Chemical speciation, mostly based on pH, varies
by stratum; for example, if the hypolimnion (i.e., lowest stratum of a lake) has a much
lower pH than the epilimnion (i.e., upper stratum), the concentration or speciation of
many pollutants may vary between the two layers. Therefore, bottom-dwelling
D-7
-------
Appendix D — Wildlife Module Methodology
organisms would be exposed to different pollutant species and concentrations. Due to
the complexity of these relationships and necessity for site-specific data, none of the
impact analyses considered the stratification of receiving waters. The effect of this
limitation on the Wildlife Module outputs is undetermined.
• Multiple Pollutant Exposures. Because the evaluated wastestreams contain multiple
bioaccumulative pollutants, receptors will be exposed to multiple constituents
simultaneously. However, the Wildlife Module examines the impact of individual
pollutants to receptors and does not take into account how the interaction of multiple
pollutants impacts the receptors. For example, EPA did not consider the impact of
mercury on the uptake or toxicity of selenium. There is evidence in the literature
(Chapman et al., 2009) that these two compounds interact in the environment to
decrease each other's impact on a receptor. Conversely, the interaction of other
pollutants may increase the impact to a receptor. However, because the TECs and
NEHCs are based on the toxicity of individual chemicals, and the relationships
between chemicals are complex, it is beyond the scope of this analysis to include the
effects of multiple pollutant interactions on receptors.
• Ecological Benchmarks. EPA used TECs and NEHCs as described above to identify
potential adverse impacts to aquatic organisms. These benchmark values represent the
concentrations below which adverse effects are not expected to occur in the exposed
organism; an exceedance of these thresholds does not necessarily demonstrate that the
exposed organism will experience adverse effects. Use of these benchmark values
therefore results in an environmentally protective impact estimate.
D-8
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Appendix E — Human Health Module Methodology
APPENDIX E
HUMAN HEALTH MODULE METHODOLOGY
This appendix presents the model equations, input variables and constants, benchmark values,
and methodology limitations/assumptions for the Human Health Module of the Immediate
Receiving Water (IRW) Model. The module quantifies human health impacts to recreational and
subsistence fishers (adult and child cohorts) that consume fish exposed to pollutants as a result of
discharges from coal-fired steam electric power plants. Additionally, EPA performed an
environmental justice (EJ) analysis that evaluated the differences in human health impacts across
race categories due to differing fish consumption rates.1
For this supplemental environmental assessment (Supplemental EA), EPA estimated pollutant
concentrations in fish using the Model Wildlife Module (see Appendix D). The Human Health
Module uses these concentrations as inputs.
The following tables describe the input requirements and data sources used in the Human Health
Module:
• Table E-l. Calculation of Consumption Ratio for Trophic Level 3 (Ft3) and Trophic
Level 4 (Ft4) Fish.
• Table E-2. Assigned Values for Input Variables and Constants.
• Table E-3. Cohort-Specific Input Variables.
• Table E-4. Environmental Justice Analysis: Cohort-Specific Input Consumption Rate
by Race Category.
• Table E-5. Pollutant-Specific Benchmark Values.
Methodology Updates Subsequent to the 2015 Final EA
EPA did not identify any appropriate revisions to the equations, data sets, or parameter values
used in the Human Health Module since the completion of the 2015 Final EA.
IRW Model: Human Health Module Equations
EPA estimated the pollutant concentrations in fish fillets consumed by humans (i.e., dose) using
an assumed consumption ratio of trophic level 3 (T3) and trophic level 4 (T4) fish and site-
specific pollutant concentrations in fish. For each cohort, EPA estimated the average daily dose
(ADD) of the pollutant from eating fish and compared this ADD to non-cancer oral reference
doses (RfDs). The Human Health Module expresses this comparison as a hazard quotient (HQ).
An HQ of higher than one (i.e., pollutant dosage exceeds oral RfD) indicates a potential non-
cancer threat to the human cohort. EPA also estimated a lifetime average daily dose (LADD) and
a corresponding lifetime excess cancer risk (LECR) for each cohort. This study used the one-in-
a-million cancer risk benchmark when evaluating exposures associated with fish consumption.
1 See Chapter 14 of the Benefit and Cost Analysis for Revisions to the Effluent Limitations Guidelines and Standards
for the Steam Electric Power Generating Point Source Category (BCA Report), Document No. EPA 821-R-20-003
(U.S. EPA, 2020b).
E-l
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Appendix E — Human Health Module Methodology
EPA used the equations presented below to calculate the pollutant concentration in the fish fillet;
the ADD for arsenic, cadmium, copper, lead, mercury, nickel, selenium, thallium, and zinc; the
associated non-cancer threat HQ; and the LADD and LECR values for arsenic.
Equation E-l
Cfish fillet = Ft3 x CflshT3F + FT4 x CfishT4F
Where:
Cfish fillet
Average fish fillet concentration ingested by
humans (milligrams per kilograms (mg/kg))
Output from Equation E-l
CfishT3F
Concentration of contaminant in fish at
trophic level 3 (mg/kg)
Site-specific Wildlife Module
output from Equation D-2 and
Equation D-3
CfishT4F
Concentration of contaminant in fish at
trophic level 4 (mg/kg)
Site-specific Wildlife Module
output from Equation D-2 and
Equation D-3
Ft3
=
Fraction of trophic level 3 fish intake
(unitless)
0.36 (see calculation below)
Ft4
=
Fraction of trophic level 4 fish intake
(unitless)
0.64 (see calculation below)
To determine the fraction of T3 and T4 fish intake for human cohorts, EPA started with the data
presented in the 2011 Exposure Factors Handbook, Table 10-74 (U.S. EPA, 201 lb). EPA then
completed the following analysis:
1. Assigned trophic levels to fish if not already listed in the table.
2. Totaled the quantities of fish consumed by trophic level.
3. Determined fraction of fish consumed at each trophic level.
Table E-l documents the data and analysis performed. EPA chose to use the factors for fish
intake that corresponded to rivers and streams; this is the most common receiving water source
in the IRW Model.
Equation E-2 calculates the ADD, which is the daily intake of the contaminant from fish
ingestion. Based on a literature review (including references from EPA and the Agency for Toxic
Substances and Disease Registry (ATSDR)), arsenic in fish is mostly in the organic form and not
harmful to humans. The inorganic form of arsenic is harmful to humans. EPA's 1997 document,
Arsenic and Fish Consumption, reported the inorganic arsenic concentration in fish as between
0.4 and 4 percent of the total arsenic accumulating in fish (U.S. EPA, 1997b). EPA estimated the
inorganic arsenic concentration in fish by assuming that four percent of the total arsenic is
inorganic. EPA used this inorganic arsenic concentration in fish to determine human health
impacts. The Human Health Module multiplies the Cfish fillet total arsenic concentration by four
percent to estimate the inorganic arsenic concentration in fish.
E-2
-------
Appendix E — Human Health Module Methodology
Table E-l. Fish Consumed and Consumption Ratios of Fish at Trophic Levels 3 and 4
(Ft3 and Ft4)
Species
Ice Fishing
Lakes and Ponds
Rivers and Streams
Number of
Fish
Consumed
Mass
Consumed
(kg)
Number of
Fish
Consumed
Mass
Consumed
(kg)
Number of
Fish
Consumed
Mass
Consumed
(kg)
Trophic Level 3
Bottom fish (suckers, carp, and
sturgeon)
50
81
62
22
100
6.7
Chub
0
0
252
35
219
130
Hornpout (catfish and bullheads)
47
8.2
1,291
100
180
7.8
Lake whitefish
111
20
558
13
55
2.7
Pickerel
1,091
180
553
91
303
45
Smelt
7,808
150
428
4.9
4,269
37
White perch
2,544
160
6,540
380
3,013
180
Yellow perch
235
9.1
1,649
52
188
7.4
Trophic Level 4
Atlantic salmon
3
1.1
33
9.9
17
11
Bass (smallmouth and
largemouth)
474
120
73
5.9
787
130
Brook trout
1,309
100
3,294
210
10,185
420
Brown trout
275
54
375
56
338
23
Landlocked salmon
832
290
928
340
305
120
Togue (Lake trout)
483
200
459
160
33
2.7
Other
201
210
90
110
54
45
Totals by Trophic Level
T3
11,886
608
11,333
698
8,327
417
T4
3,376
765.1
5,162
781.8
11,665
751.7
Total
15,463
1,583
16,587
1,590
20,046
1,168
Calculation of Factors by Trophic Level
T3 Factor
0.77
0.38
0.68
0.44
0.42
0.36
T4 Factor
0.22
0.48
0.31
0.49
0.58
0.64
Source: U.S. EPA, 2011b.
Bold text indicates factors selected for the Human Health Module.
E-3
-------
Appendix E — Human Health Module Methodology
Equation E-2
__ Cfish gllet x CRfish x Fggjj
ADD =
1,000 x BW
Where:
ADD
Daily dose of pollutant from fish ingestion
(mg per kg of body weight per day (mg/kg
bw-day)
Output from Equation E-2
Cfish fillet
=
Average fish fillet concentration ingested by
humans (mg/kg)
Output from Equation E-l
CRfish
=
Consumption rate of fish (g wet weight/day)
Cohort-specific value (see
Table E-3 and Table E-4
Ffish
=
Fraction of fish intake from contaminated
source
Globally assigned value of 1
1,000
=
Conversion factor (grams per kilograms
(g/kg))
Conversion factor
BW
=
Body weight (kg)
Cohort-specific value (see
Table E-3
Equation E-3 calculates the LADD, based on the ADD. Arsenic is the only carcinogenic
pollutant for which sufficient information was available to estimate excess cancer risk using the
IRW Model. The model calculates the LADD of arsenic for each child cohort (six recreational
and six subsistence) and for each adult cohort (one recreational and one subsistence). EPA
assumed that the exposure durations (ED) for use in the LADD calculation are equal to the
length of time associated with each age and fish consumption cohort. EPA selected an exposure
frequency of 350 days per year, assuming residents take an average of two weeks of vacation
away from their homes each year.
Equation E-4 calculates the non-cancer HQ, based on the ADD.
Equation E-5 calculates the LECR for inorganic arsenic, based on the LADD.
Equation E-3
ADD x ED x EF
LADD =
AT x 365
Where:
LADD
=
Lifetime average daily dose (mg/kg bw-day)
Output from Equation E-3
ADD
=
Daily dose of pollutant from fish ingestion
(mg/kg bw-day)
Output from Equation E-2
E-4
-------
Appendix E — Human Health Module Methodology
ED
Exposure duration for oral ingestion (yr)
Cohort-specific value
(assumed value)
(see Table E-3)
EF
=
Exposure frequency (days/yr)
Globally assigned value of
350
AT
=
Averaging time (yr)
Globally assigned value of 70
(U.S. EPA, 2011b)
365
=
Conversion factor (days/yr)
Equation E-4
Where:
HQ
=
Hazard quotient
Output from Equation E-4
ADD
=
Daily dose of pollutant from fish ingestion
(mg/kg bw-day)
Output from Equation E-2
RfD
=
Non-cancer oral reference dose (mg/kg bw-
day)
Pollutant-specific value
(see Table E-5)
Equation E-5
LECR = LADD x CSF
Where:
LECR
=
Lifetime excess cancer risk
Output from Equation E-5
LADD
=
Lifetime average daily dose (mg/kg bw-day)
Output from Equation E-3
CSF
=
Cancer slope factor (mg/kg bw-day)"1
Pollutant-specific value
(see Table E-5)
IRW Model: Human Health Module Inputs and Benchmark Values
For this Supplemental EA and the economic benefits analyses,2 EPA focused on human exposure
to contaminated fish for recreational and subsistence fishers. Recreational fishers are non-
commercial, non-subsistence fishers and are more vulnerable to pollutant exposure by intake of
contaminated fish from a specific waterbody compared to the general population. Subsistence
fishers are individuals who consume fresh caught fish as a major food source. Intake rates for
subsistence fishers are generally higher than for the general population, and subsistence fishers
are more vulnerable to pollutant exposure by intake of contaminated fish from a specific
2 See the Benefit and Cost Analysis for Revisions to the Effluent Limitations Guidelines and Standards for the Steam
Electric Power Generating Point Source Category (BCA Report), Document No. EPA-821-R-20-003 (U.S. EPA,
2020b).
ADD
HQ=w
E-5
-------
Appendix E — Human Health Module Methodology
waterbody compared to both recreational fishers and the general population. Because of the
focus of human exposure on a subset of the general population that more frequently consume
local fish, EPA selected fish consumption rates from studies based on "consumer only" data.
Consumer-only fish consumption rates are the average intake rates across only those individuals
that consumed fish and shellfish during the survey time period. See the memorandum "Fish
Consumption Rates Used in the Environmental Assessment Human Health Module" for further
details (ERG, 2015).
The Human Health Module calculates annual-average daily doses of pollutants for recreational
and subsistence fishers and does not calculate the annual-average daily doses of pollutants for the
general population. In its economic benefits analysis (see the BCA Report), EPA evaluates
impacts to a subset of the population living near the immediate and downstream receiving
waters.
Table 5-1 of the 2000 EPA document Guidance for Assessing Chemical Contaminant Data for
Uses in Fish Advisories, Volume 1 provides protective fish intake rates based on the following
percentiles by fisher type: 1) general population and recreational fisher: 90th percentile of per
capita data and 2) subsistence fisher: 99th percentile of per capita data (U.S. EPA, 2000a). The
document does not provide guidance on which percentiles to use for consumer-only fish intake
rates. Therefore, EPA used best professional judgment and used the mean of consumer-only data
to represent recreational fishers and the 95th percentile of consumer-only data to represent
subsistence fishers.
Table E-2. Assigned Values for Input Variables and Constants
Input
Variable or
Constant
Description
Assigned
Value
Rationale/Data Source
Ft3
Fraction of trophic level 3 fish intake
0.36
U.S. EPA, 2011b
Ft4
Fraction of trophic level 4 fish intake
0.64
U.S. EPA, 2011b
Ffch
Fraction of fish intake from
contaminated source
1
EPA assumed that all fish consumed by the
cohort is from the contaminated surface water.
EF
Exposure frequency (days/yr)
350
EPA assumed that the fisher (cohort) travels
away from home for 15 days per year and does
not eat fish from contaminated surface water
during that period.
AT
Averaging time (yr)
70
U.S. EPA, 2011b
E-6
-------
Appendix E — Human Health Module Methodology
Table E-3. Cohort-Specific Input Variables
Alio ;ind I'isli (oiiMimplion
C oliori ¦'
limit Weight
(kg)''
C "(iiisii in pi ion
Usilc
Consumption
Usilc
l'l\|)OMIIV
Munition (u'iirs)
Child
Recreational
Fisher
1 to <2 years
11.4
1.6
18.2
1
2 to <3 years
13.8
1.6
22.1
1
3 to <6 years
18.6
1.3
24.2
3
6 to <11 years
31.8
1.1
35.0
5
11 to <16 years
56.8
0.66
37.5
5
16 to <21 years
71.6
0.66
47.3
5
Child
Subsistence
Fisher
1 to <2 years
11.4
4.9
55.9
1
2 to <3 years
13.8
4.9
67.6
1
3 to <6 years
18.6
3.6
67.0
3
6 to <11 years
31.8
2.9
92.2
5
11 to <16 years
56.8
1.7
96.6
5
16 to <21 years
71.6
1.7
122
5
Adult Recreational Fisher0
80
0.665
53.2
49
Adult Subsistence Fisher0
80
2.05
164
49
Sources: U.S. EPA, 2008b; U.S. EPA, 2011b.
Acronyms: g/day (grams per day); g/kg-day (grams per kilogram of body weight per day); kg (kilograms),
a - The child cohort age ranges correspond to the ranges provided in the 2008 Child-Specific Exposure Factors
Handbook (EFH) for body weights (U.S. EPA, 2008b).
b - EPA estimated consumption rates for child cohorts using data from Table 10-1 (Recommend Per Capita and
Consumer-Only Values for Fish Intake) for finfish consumption (U.S. EPA, 201 lb). EPA used consumer-only fish
consumption rates: mean values for recreational fishers and 95th percentile values for subsistence fishers. EPA
converted the listed consumption rate (g/kg-day) to g/day by multiplying by mean body weight for each cohort as
described in ERG (2015). Fish intake rates provided in U.S. EPA (201 lb) are recommended for the consumer-only
population; the selection of consumption rates for exposure assessment purposes may vary depending on the
exposure scenarios being evaluated.
c - Table 10-1 (U.S. EPA, 201 lb) presented multiple adult groups. EPA used the average fish consumption rate for
age groups "21 to <50 years" and "50+ years" to calculate a single adult cohort fish consumption rate.
E-7
-------
Appendix E — Human Health Module Methodology
Table E-4. Environmental Justice Analysis: Cohort-Specific Input Consumption Rate by Race Category
Fish Consumption and Race
Category Cohort
CRfish,
g/kg-day
(All ages)"
Consumption Rate (CRiish), g/day, by Cohortb
1 to <2
Years
2 to <3
Years
3 to <6
Years
6 to <11
Years
11 to <16
Years
16 to <21
Years
Adult
Recreational
Non-Hispanic White
0.67
7.64
9.25
12.5
21.3
38.1
48
53.6
Non-Hispanic Black
0.77
8.78
10.6
14.3
24.5
43.7
55.1
61.6
Mexican-American
0.93
10.6
12.8
17.3
29.6
52.8
66.6
74.4
Other Hispanic
0.82
9.35
11.3
15.3
26.1
46.6
58.7
65.6
Other, including
Multiple Races
0.96
10.9
13.2
17.9
30.5
54.5
68.7
76.8
Subsistence
Non-Hispanic White
1.9
21.7
26.2
35.3
60.4
108
136
152
Non-Hispanic Black
2.1
23.9
29.0
39.1
66.8
119
150
168
Mexican-American
2.8
31.9
38.6
52.1
89.0
159
200
224
Other Hispanic 0
2.7
30.8
37.3
50.2
85.9
153
193
216
Other, including
Multiple Races0
3.6
41.0
49.7
67.0
114
204
258
288
Source: U.S. EPA, 2011b.
Acronyms: CRnsh (consumption rate); g/day (grams per day); g/kg-day (grams per kilogram body weight per day).
a - For recreational fishers, EPA used the mean, consumer-only fish consumption rate for finfish (excludes shellfish). For subsistence fishers
percentile, consumer-only fish consumption rate for finfish (excludes shellfish). See Table 10-8 of U.S. EPA, 2011b.
b - Consumption rates provided as single value by race category (as g/kg-day). EPA multiplied these values by cohort-specific body weights
E-3, to calculate a cohort-specific consumption rate in g/day. Numbers presented as three significant digits,
c - Consumption rates for this race category are less statistically reliable due to the comparatively smaller data set.
, EPA used the 95th
, as listed in Table
E-8
-------
Appendix E — Human Health Module Methodology
Table E-5. Pollutant-Specific Benchmark Values
Pollutant in Human Health
Impact Assessment
Oral RfD
(mg/kg-day)
CSF
(mg/kg-day) 1
Notesa
Arsenic, inorganic
3.00 x 10"4
1.50
Oral RfD and CSF for drinking water
ingestion.
Cadmium, total
1.00 x 10"3
Oral RfD for food consumption.
Copper
1.00 x 10"2
Used the intermediate oral minimal risk level
(MRL) as the oral RfD (ATSDR, 2020a).
Lead, total
None available
Methylmercury
1.00 x 10"4
Oral RfD for fish consumption only.
Nickel, total
2.00 x 10"2
Oral RfD for soluble salts; used for food
consumption.
Selenium, total
5.00 x 10"3
Oral RfD for food consumption.
Thallium, total
1.00 x 10"5
Used value cited in U.S. EPA, 2012 for
soluble thallium as the oral RfD; used for
chronic oral exposure.
Zinc, total
3.00 x 101
Oral RfD for food consumption.
Acronyms: CSF (cancer slope factor); mg/kg-day (milligrams per kilogram body weight per day); RfD (reference
dose).
a - References include ATSDR (2020a) for copper; U.S. EPA (2012) for thallium, and U.S. EPA (2019e) for all
other pollutants.
IRW Model: Human Health Module Limitations and Assumptions
The Human Health Module limitations and assumptions include the following:
• Cumulative Risks Across Exposure Pathways. The Human Health Module does not
consider cumulative risks across exposure pathways. For example, the module
assumes that the human population consuming the fish is not also ingesting
contaminated drinking water. Exposures from fish consumption and drinking water
may occur over different time frames (because of ground water travel) and may
involve different receptors (e.g., a resident near a receiving water exposed to ground
water contamination may not be a recreational fisher). Similarly, the module assumes
that these populations are not coming in direct contact with contaminated surface
water or sediment through recreation. Based on these assumptions, the model may
underestimate total risk to human health from discharges of the evaluated
wastestreams.
• Bioavailability and Speciation of Pollutants. The assumptions listed for the Wildlife
Module in Appendix D apply to pollutant concentrations modeled in fish and
therefore affect the human health impact assessment.
• Full Mixing Effects for Receiving Water. The assumptions listed for the Wildlife
Module in Appendix D apply to pollutant concentrations modeled in fish and
therefore affect the human health impact assessment.
E-9
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Appendix E — Human Health Module Methodology
• Multiple Pollutant Exposures. Because the evaluated wastestreams contain multiple
bioaccumulative pollutants, people who ingest fish from impacted waters will likely
be exposed to multiple constituents simultaneously. However, the module evaluates
each pollutant individually. Such an approach does not account for interactive effects
that might be associated with exposures to mixtures. For example, some pollutants
may have a higher risk when consumed together because of their interaction, whereas
other pollutants may have less impact on human health when consumed together. Due
to the complexity of these interactions and because benchmark values are based on
the toxicity of individual pollutants, it is not possible to examine these synergistic
effects in this analysis. Based on this limitation, risks of pollutants may be over- or
underestimated.
• Sources of Consumed Fish. The Human Health Module assumes that all of the fish
consumed by recreational and subsistence fishers is caught from the immediate
receiving water, except during a two-week time period once per year. This
assumption potentially overestimates the annual-average daily dose of the pollutants
for these cohorts, particularly for recreational fishers. The proportion of fish eaten by
an individual from local surface waters will vary (e.g., consumption rate estimates in
studies might include seafood purchased from a grocery store and not locally caught).
• Human Exposure Factors. Individual exposure factors, such as ingestion rate, body
weight, and exposure duration, are variable due to the physical characteristics,
activities, and behavior of the individual. EPA used the most current data regarding
exposure assumptions, and these values represent EPA's current guidance on
exposure data (U.S. EPA, 2008b; U.S. EPA, 2011b).
• Human Health Benchmark Values. Uncertainties generally associated with human
health benchmark values are discussed in detail in EPA's Guidelines for Carcinogen
Risk Assessment (U.S. EPA, 2005c) and Integrated Risk Information System (IRIS)
(U.S. EPA, 2019e). IRIS defines the oral RfD as "an estimate (with uncertainty
spanning perhaps an order of magnitude) of a daily oral exposure to the human
population (including sensitive subgroups) that is likely to be without an appreciable
threat of deleterious effects during a lifetime." While doses less than the oral RfD are
not likely to be associated with adverse health risks, it should not be categorically
concluded that all doses below the oral RfD are risk-free, particularly for pollutants
(e.g., arsenic and nickel) whose oral RfDs have not been established with a high level
of confidence. Additionally, oral RfDs are typically based on an assumption of
lifetime exposure and may not be appropriate when applied to less-than-lifetime
exposure situations (U.S. EPA, 2019e). The cancer slope factor is an estimate of the
human cancer risk per milligram of chemical per kilogram body weight per day. To
calculate the LADD used for the cancer risk assessment, EPA used the time in the
cohort group (i.e., 1, 3, or 5 years, depending on child cohort, and 49 years for adult
cohort) as the ED. The ED is the length of time exposure occurs at the concentration.
This analysis may over- or under-estimate the cancer risk if exposure is shorter than
or longer than the ED, respectively. LADDs are appropriate when developing
screening-level estimates; however, EPA recommends calculating that risk by
integrating exposures or risks through all life stages (e.g., chronic exposure for a child
may occur across cohorts) (U.S. EPA, 201 lb).
E-10
-------
Appendix F — Additional IR WModel Results
APPENDIX F
ADDITIONAL IRW MODEL RESULTS
This appendix presents pollutant loadings and additional model outputs for all pollutants
included in the Immediate Receiving Water (IRW) Model (arsenic, cadmium, copper, lead,
mercury, nickel, selenium, thallium, and zinc) beyond those discussed in Section 4 of this
Supplemental EA and includes the following tables:
• Table F-l. Modeled IRWs Exceeding Benchmark Values for One or More Pollutants
under Baseline and Regulatory Options
• Table F-2. Modeled IRWs Exceeding Arsenic Benchmark Values under Baseline and
Regulatory Options
• Table F-3. Modeled IRWs Exceeding Cadmium Benchmark Values under Baseline
and Regulatory Options
• Table F-4. Modeled IRWs Exceeding Copper Benchmark Values under Baseline and
Regulatory Options
• Table F-5. Modeled IRWs Exceeding Lead Benchmark Values under Baseline and
Regulatory Options
• Table F-6. Modeled IRWs Exceeding Mercury Benchmark Values under Baseline
and Regulatory Options
• Table F-7. Modeled IRWs Exceeding Nickel Benchmark Values under Baseline and
Regulatory Options
• Table F-8. Modeled IRWs Exceeding Selenium Benchmark Values under Baseline
and Regulatory Options
• Table F-9. Modeled IRWs Exceeding Thallium Benchmark Values under Baseline
and Regulatory Options
• Table F-10. Modeled IRWs Exceeding Zinc Benchmark Values under Baseline and
Regulatory Options
• Table F-l 1. Modeled IRWs Exceeding Non-Cancer Oral Reference Dose Values
under Baseline and Regulatory Options, by Race Category
• Table F-12. Modeled IRWs with Lifetime Excess Cancer Risk for Inorganic Arsenic
Exceeding One-in-a-Million under Baseline and Regulatory Options, by Race
Category
F-l
-------
Appendix F — Additional IR WModel Results
Table F-l. Modeled IRWs Exceeding Benchmark Values for One or More Pollutants
under Baseline and Regulatory Options
Pcillii 1 ;iill 1.(Hidings Basis
Indusln Ptilliiliinl Loadings (ll)/\c;ir)
Baseline
Option 1)
Option A
Option B
Option (
Mass Loadings from all 87 Coal-Fired Power
Plants in Pollutant Loadings Analysis
3,730
63,500
18,000
4,720
1,070
Evaluation Benchmark
Modeled Number of IRWs Exceeding Benchmark Value 1 c
Baseline
Option D1'
Option A
Option B
Option C
Water Quality Results
Freshwater Acute NRWQC
0
2
0
0
0
Freshwater Chronic NRWQC
0
10
0
0
0
Human Health Water and Organism NRWQC
8
20
17
17
13
Human Health Organism Only NRWQC
3
9
7
7
6
Drinking Water MCL
1
3
1
1
0
Wildlife Results
Sediment TEC
2
20
5
5
4
Fish Ingestion NEHC for Minks
0
10
1
1
1
Fish Ingestion NEHC for Eagles
1
11
4
4
2
Human Health Results - Fish Consumption Advisories
T4 Fish Tissue Concentration Screening
Value (Recreational)
2
8
4
4
3
T4 Fish Tissue Concentration Screening
Value (Subsistence)
5
18
11
11
8
Human Health Results - Non-Cancer
Oral RfD for Child (Recreational)
5
15
10
10
7
Oral RfD for Child (Subsistence)
8
23
16
15
11
Oral RfD for Adult (Recreational)
3
10
7
7
6
Oral RfD for Adult (Subsistence)
5
16
10
10
7
Human Health Results - Cancer
LECR for Child (Recreational)
0
0
0
0
0
LECR for Child (Subsistence)
0
0
0
0
0
LECR for Adult (Recreational)
0
1
0
0
0
LECR for Adult (Subsistence)
0
1
0
0
0
Source: ERG, 2020d; ERG, 2020j.
Acronyms: IRW (immediate receiving water); lb/year (pounds per year); LECR (lifetime excess cancer risk); MCL
(maximum contaminant level); NEHC (no effect hazard concentration); NRWQC (National Recommended Water
Quality Criteria); RfD (reference dose); TEC (threshold effect concentration); T4 (trophic level 4).
Note: Pollutant loadings are rounded to three significant figures.
a - Values represent the industry loadings and the IRW Model outputs for the following nine evaluated pollutants:
arsenic, cadmium, copper, lead, mercury, nickel, selenium, thallium, and zinc.
b - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
c - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters).
F-2
-------
Appendix F — Additional IR WModel Results
Table F-2. Modeled IRWs Exceeding Arsenic Benchmark Values under Baseline and
Regulatory Options
Pol In I ;i ii I Loadings Basis
Indusln Arsenic Loadings (ll>/>car)
Baseline
Option 1)
Option A
Option B
Option (
Mass Loadings from all 87 Coal-Fired Power
Plants in Pollutant Loadings Analysis
368
503
546
473
112
Evaluation Benchmark
Modeled Number of IRWs Exceeding Arsenic Benchmark
Value 15
Baseline
Option D 1
Option A
Option B
Option C
Water Quality Results
Freshwater Acute NRWQCa
0
0
0
0
0
Freshwater Chronic NRWQCa
0
0
0
0
0
Human Health Water and Organism NRWQC b
8
20
17
17
13
Human Health Organism Only NRWQC b
3
9
7
7
6
Drinking Water MCL
0
1
0
0
0
Wildlife Results
Sediment TEC
0
0
0
0
0
Fish Ingestion NEHC for Minks
0
0
0
0
0
Fish Ingestion NEHC for Eagles
0
0
0
0
0
Human Health Results - Fish Consumption Advisories
T4 Fish Tissue Concentration Screening Value
(Recreational) b c
0
0
0
0
0
T4 Fish Tissue Concentration Screening Value
(Subsistence) b c
0
0
0
0
0
Human Health Results - Non-Cancer
Oral RfD for Child (Recreational) b
0
0
0
0
0
Oral RfD for Child (Subsistence) b
0
0
0
0
0
Oral RfD for Adult (Recreational) b
0
0
0
0
0
Oral RfD for Adult (Subsistence) b
0
0
0
0
0
Human Health Results - Cancer
LECR for Child (Recreational) b
0
0
0
0
0
LECR for Child (Subsistence) b
0
0
0
0
0
LECR for Adult (Recreational) b
0
1
0
0
0
LECR for Adult (Subsistence) b
0
1
0
0
0
Source: ERG, 2020d; ERG, 2020j.
Acronyms: IRW (immediate receiving water); lb/year (pounds per year); LECR (lifetime excess cancer risk); MCL
(maximum contaminant level); NEHC (no effect hazard concentration); NRWQC (National Recommended Water
Quality Criteria); RfD (reference dose); TEC (threshold effect concentration); T4 (trophic level 4).
Note: Pollutant loadings are rounded to three significant figures. All benchmark values are based on total arsenic
concentration, unless otherwise stated.
a - Benchmark value is based on dissolved arsenic.
b - Benchmark value is based on inorganic arsenic.
c - Values represent number of immediate receiving waters exceeding either the noncarcinogenic or carcinogenic
screening values.
d - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
e - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters).
F-3
-------
Appendix F — Additional IR WModel Results
Table F-3. Modeled IRWs Exceeding Cadmium Benchmark Values under Baseline and
Regulatory Options
Pcillii 1 ;iill 1.(Hidings Basis
Indusln Cadmium Loadings (ll>/>car)
Baseline
Option 1)
Option A
Option B
Option C
Mass Loadings from all 87 Coal-Fired Power
Plants in Pollutant Loadings Analysis
265
309
274
268
8.68
Evaluation Benchmark
Modeled Number of IRWs Exceeding Cadmium Benchmark
Value 1
Baseline
Option D1
Option A
Option B
Option C
Water Quality Results
Freshwater Acute NRWQCa
0
0
0
0
0
Freshwater Chronic NRWQCa
0
0
0
0
0
Human Health Water and Organism NRWQC
b
b
b
b
b
Human Health Organism Only NRWQC
b
b
b
b
b
Drinking Water MCL
0
0
0
0
0
Wildlife Results
Sediment TEC
1
1
1
1
0
Fish Ingestion NEHC for Minks
0
0
0
0
0
Fish Ingestion NEHC for Eagles
0
0
0
0
0
Human Health Results - Fish Consumption Advisories
T4 Fish Tissue Concentration Screening
Value (Recreational)
0
0
0
0
0
T4 Fish Tissue Concentration Screening
Value (Subsistence)
0
0
0
0
0
Human Health Results - Non-Cancer
Oral RfD for Child (Recreational)
0
0
0
0
0
Oral RfD for Child (Subsistence)
0
0
0
0
0
Oral RfD for Adult (Recreational)
0
0
0
0
0
Oral RfD for Adult (Subsistence)
0
0
0
0
0
Human Health Results - Cancer
LECR for Child (Recreational)
b
b
b
b
b
LECR for Child (Subsistence)
b
b
b
b
b
LECR for Adult (Recreational)
b
b
b
b
b
LECR for Adult (Subsistence)
b
b
b
b
b
Source: ERG, 2020d; ERG, 2020j.
Acronyms: IRW (immediate receiving water); lb/year (pounds per year); LECR (lifetime excess cancer risk); MCL
(maximum contaminant level); NEHC (no effect hazard concentration); NRWQC (National Recommended Water
Quality Criteria); RfD (reference dose); TEC (threshold effect concentration); T4 (trophic level 4).
Note: Pollutant loadings are rounded to three significant figures. All benchmark values are based on total cadmium
concentration, unless otherwise stated,
a - Benchmark value is based on dissolved cadmium.
b - A benchmark value is not yet established for this pollutant or was not included in EPA's analyses,
c - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
d - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters).
F-4
-------
Appendix F — Additional IR WModel Results
Table F-4. Modeled IRWs Exceeding Copper Benchmark Values under Baseline and
Regulatory Options
Pcillii 1 ;iill 1.(Hidings Basis
Indusln Copper Loadings (IhAear)
Baseline
Option 1)
Option A
Option B
Option C
Mass Loadings from all 87 Coal-Fired Power
Plants in Pollutant Loadings Analysis
238
304
312
280
47.5
Evaluation Benchmark
Modeled Number of IRWs Exceeding Copper Benchmark
Value 1
Baseline
Option
Option A
Option B
Option C
Water Quality Results
Freshwater Acute NRWQCa
0
0
0
0
0
Freshwater Chronic NRWQCa
0
0
0
0
0
Human Health Water and Organism NRWQC
0
0
0
0
0
Human Health Organism Only NRWQC
b
b
b
b
b
Drinking Water MCL
0
0
0
0
0
Wildlife Results
Sediment TEC
0
0
0
0
0
Fish Ingestion NEHC for Minks
0
0
0
0
0
Fish Ingestion NEHC for Eagles
0
0
0
0
0
Human Health Results - Fish Consumption Advisories
T4 Fish Tissue Concentration Screening
Value (Recreational)
b
b
b
b
b
T4 Fish Tissue Concentration Screening
Value (Subsistence)
b
b
b
b
b
Human Health Results - Non-Cancer
Oral RfD for Child (Recreational)
0
0
0
0
0
Oral RfD for Child (Subsistence)
0
0
0
0
0
Oral RfD for Adult (Recreational)
0
0
0
0
0
Oral RfD for Adult (Subsistence)
0
0
0
0
0
Human Health Results - Cancer
LECR for Child (Recreational)
b
b
b
b
b
LECR for Child (Subsistence)
b
b
b
b
b
LECR for Adult (Recreational)
b
b
b
b
b
LECR for Adult (Subsistence)
b
b
b
b
b
Source: ERG, 2020d; ERG, 2020j.
Acronyms: IRW (immediate receiving water); lb/year (pounds per year); LECR (lifetime excess cancer risk); MCL
(maximum contaminant level); NEHC (no effect hazard concentration); NRWQC (National Recommended Water
Quality Criteria); RfD (reference dose); TEC (threshold effect concentration); T4 (trophic level 4).
Note: Pollutant loadings are rounded to three significant figures. All benchmark values are based on total copper
concentration, unless otherwise stated,
a - Benchmark value is based on dissolved copper.
b - A benchmark value is not yet established for this pollutant or was not included in EPA's analyses,
c - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
d - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters).
F-5
-------
Appendix F — Additional IR WModel Results
Table F-5. Modeled IRWs Exceeding Lead Benchmark Values under Baseline and
Regulatory Options
Pcillii 1 ;iill 1.(Hidings Basis
lutliislr> Load Loadings (IhAear)
Baseline
Option 1)
Option A
Option B
Option (
Mass Loadings from all 87 Coal-Fired Power
Plants in Pollutant Loadings Analysis
214
347
416
335
125
Evaluation Benchmark
Modeled Number of IRWs Exceeding Lead Benchmark
Value 1
Baseline
Option D1
Option A
Option B
Option C
Water Quality Results
Freshwater Acute NRWQCa
0
0
0
0
0
Freshwater Chronic NRWQCa
0
0
0
0
0
Human Health Water and Organism NRWQC
b
b
b
b
b
Human Health Organism Only NRWQC
b
b
b
b
b
Drinking Water MCL
0
1
0
0
0
Wildlife Results
Sediment TEC
0
0
0
0
0
Fish Ingestion NEHC for Minks
0
0
0
0
0
Fish Ingestion NEHC for Eagles
0
0
0
0
0
Human Health Results - Fish Consumption Advisories
T4 Fish Tissue Concentration Screening
Value (Recreational)
b
b
b
b
b
T4 Fish Tissue Concentration Screening
Value (Subsistence)
b
b
b
b
b
Human Health Results - Non-Cancer
Oral RfD for Child (Recreational)
b
b
b
b
b
Oral RfD for Child (Subsistence)
b
b
b
b
b
Oral RfD for Adult (Recreational)
b
b
b
b
b
Oral RfD for Adult (Subsistence)
b
b
b
b
b
Human Health Results - Cancer
LECR for Child (Recreational)
b
b
b
b
b
LECR for Child (Subsistence)
b
b
b
b
b
LECR for Adult (Recreational)
b
b
b
b
b
LECR for Adult (Subsistence)
b
b
b
b
b
Source: ERG, 2020d; ERG, 2020j.
Acronyms: IRW (immediate receiving water); lb/year (pounds per year); LECR (lifetime excess cancer risk); MCL
(maximum contaminant level); NEHC (no effect hazard concentration); NRWQC (National Recommended Water
Quality Criteria); RfD (reference dose); TEC (threshold effect concentration); T4 (trophic level 4).
Note: Pollutant loadings are rounded to three significant figures. All benchmark values are based on total lead
concentration, unless otherwise stated,
a - Benchmark value is based on dissolved lead.
b - A benchmark value is not yet established for this pollutant or was not included in EPA's analyses,
c - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
d - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters).
F-6
-------
Appendix F — Additional IR WModel Results
Table F-6. Modeled IRWs Exceeding Mercury Benchmark Values under Baseline and
Regulatory Options
Pcillii 1 ;iill 1.(Hidings Basis
Indusin Mercun Loadings (IhAear)
Baseline
Option 1)
Option A
Option B
Option (
Mass Loadings from all 87 Coal-Fired Power
Plants in Pollutant Loadings Analysis
3.19
11.1
6.36
4.36
1.23
Evaluation Benchmark
Modeled Number of IRWs Exceeding Mcrcurv Benchmark
Value54
Baseline
Option D'
Option A
Option B
Option C
Water Quality Results
Freshwater Acute NRWQCa
0
0
0
0
0
Freshwater Chronic NRWQCa
0
0
0
0
0
Human Health Water and Organism NRWQC
b
b
b
b
b
Human Health Organism Only NRWQC
b
b
b
b
b
Drinking Water MCL 0
0
0
0
0
0
Wildlife Results
Sediment TEC
0
5
2
2
1
Fish Ingestion NEHC for Minks d
0
3
1
1
1
Fish Ingestion NEHC for Eagles d
1
6
4
4
2
Human Health Results - Fish Consumption Advisories
T4 Fish Tissue Concentration Screening
Value (Recreational) d
2
7
4
4
3
T4 Fish Tissue Concentration Screening
Value (Subsistence) d
5
16
11
11
8
Human Health Results - Non-Cancer
Oral RfD for Child (Recreational) de
4
11
9
9
7
Oral RfD for Child (Subsistence),Le
5
19
15
14
11
Oral RfD for Adult (Recreational),Le
2
10
6
6
6
Oral RfD for Adult (Subsistence),Le
5
14
10
10
7
Human Health Results - Cancer
LECR for Child (Recreational)
b
b
b
b
b
LECR for Child (Subsistence)
b
b
b
b
b
LECR for Adult (Recreational)
b
b
b
b
b
LECR for Adult (Subsistence)
b
b
b
b
b
Source: ERG, 2020d; ERG, 2020j.
Acronyms: IRW (immediate receiving water); lb/year (pounds per year); LECR (lifetime excess cancer risk); MCL
(maximum contaminant level); NEHC (no effect hazard concentration); NRWQC (National Recommended Water
Quality Criteria); RfD (reference dose); TEC (threshold effect concentration); T4 (trophic level 4).
Note: Pollutant loadings are rounded to three significant figures. All benchmark values are based on total mercury
concentration, unless otherwise stated,
a - Benchmark value is based on dissolved mercury.
b - A benchmark value is not yet established for this pollutant or was not included in EPA's analyses,
c - Benchmark value is based on inorganic mercury.
d - Comparison to benchmark value is based on modeled methylmercury concentration in fish tissue,
e - Benchmark value is based on methylmercury.
F-7
-------
Appendix F — Additional IR WModel Results
f - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
g - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters).
F-8
-------
Appendix F — Additional IR WModel Results
Table F-7. Modeled IRWs Exceeding Nickel Benchmark Values under Baseline and
Regulatory Options
Pcillii 1 ;iill 1.(Hidings Basis
Indusin Nickel Loadings (IhAear)
Baseline
Option 1)
Option A
Option B
Option (
Mass Loadings from all 87 Coal-Fired Power
Plants in Pollutant Loadings Analysis
398
909
775
600
210
Evaluation Benchmark
Modeled Number of IRWs Exceeding Nickel Benchmark
Value 1
Baseline
Option
Option A
Option B
Option C
Water Quality Results
Freshwater Acute NRWQCa
0
0
0
0
0
Freshwater Chronic NRWQCa
0
0
0
0
0
Human Health Water and Organism NRWQC
0
0
0
0
0
Human Health Organism Only NRWQC
0
0
0
0
0
Drinking Water MCL
b
b
b
b
b
Wildlife Results
Sediment TEC
0
3
2
2
1
Fish Ingestion NEHC for Minks
0
0
0
0
0
Fish Ingestion NEHC for Eagles
0
0
0
0
0
Human Health Results - Fish Consumption Advisories
T4 Fish Tissue Concentration Screening
Value (Recreational)
b
b
b
b
b
T4 Fish Tissue Concentration Screening
Value (Subsistence)
b
b
b
b
b
Human Health Results - Non-Cancer
Oral RfD for Child (Recreational)
0
0
0
0
0
Oral RfD for Child (Subsistence)
0
0
0
0
0
Oral RfD for Adult (Recreational)
0
0
0
0
0
Oral RfD for Adult (Subsistence)
0
0
0
0
0
Human Health Results - Cancer
LECR for Child (Recreational)
b
b
b
b
b
LECR for Child (Subsistence)
b
b
b
b
b
LECR for Adult (Recreational)
b
b
b
b
b
LECR for Adult (Subsistence)
b
b
b
b
b
Source: ERG, 2020d; ERG, 2020j.
Acronyms: IRW (immediate receiving water); lb/year (pounds per year); LECR (lifetime excess cancer risk); MCL
(maximum contaminant level); NEHC (no effect hazard concentration); NRWQC (National Recommended Water
Quality Criteria); RfD (reference dose); TEC (threshold effect concentration); T4 (trophic level 4).
Note: Pollutant loadings are rounded to three significant figures. All benchmark values are based on total nickel
concentration, unless otherwise stated,
a - Benchmark value is based on dissolved nickel.
b - A benchmark value is not yet established for this pollutant or was not included in EPA's analyses,
c - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
d - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters).
F-9
-------
Appendix F — Additional IR WModel Results
Table F-8. Modeled IRWs Exceeding Selenium Benchmark Values under Baseline and
Regulatory Options
Pcillii 1 ;iill 1.(Hidings Basis
Indusln Solon in in Loadings (ll)/\o;ir)
Baseline
Option 1)
Option A
Option B
Option (
Mass Loadings from all 87 Coal-Fired Power
Plants in Pollutant Loadings Analysis
362
58,500
13,100
502
148
Evaluation Benchmark
Modeled Number of IRWs Exceeding Selenium Benchmark
Value 1
Baseline
Option D1
Option A
Option B
Option C
Water Quality Results
Freshwater Acute NRWQCa
0
2
0
0
0
Freshwater Chronic NRWQCa
0
10
0
0
0
Human Health Water and Organism NRWQC
0
1
0
0
0
Human Health Organism Only NRWQC
0
0
0
0
0
Drinking Water MCL
0
2
0
0
0
Wildlife Results
Sediment TEC
2
20
5
5
4
Fish Ingestion NEHC for Minks
0
9
0
0
0
Fish Ingestion NEHC for Eagles
0
9
0
0
0
Human Health Results - Fish Consumption Advisories
T4 Fish Tissue Concentration Screening
Value (Recreational)
0
5
0
0
0
T4 Fish Tissue Concentration Screening
Value (Subsistence)
0
12
3
3
1
Human Health Results - Non-Cancer
Oral RfD for Child (Recreational)
0
9
0
0
0
Oral RfD for Child (Subsistence)
2
16
4
4
2
Oral RfD for Adult (Recreational)
0
6
0
0
0
Oral RfD for Adult (Subsistence)
0
10
1
1
0
Human Health Results - Cancer
LECR for Child (Recreational)
b
b
b
b
b
LECR for Child (Subsistence)
b
b
b
b
b
LECR for Adult (Recreational)
b
b
b
b
b
LECR for Adult (Subsistence)
b
b
b
b
b
Source: ERG, 2020d; ERG, 2020j.
Acronyms: IRW (immediate receiving water); lb/year (pounds per year); LECR (lifetime excess cancer risk); MCL
(maximum contaminant level); NEHC (no effect hazard concentration); NRWQC (National Recommended Water
Quality Criteria); RfD (reference dose); TEC (threshold effect concentration); T4 (trophic level 4).
Note: Pollutant loadings are rounded to three significant figures. All benchmark values are based on total selenium
concentration, unless otherwise stated,
a - Benchmark value is based on dissolved selenium.
b - A benchmark value is not yet established for this pollutant or was not included in EPA's analyses,
c - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
d - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters).
F-10
-------
Appendix F — Additional IR WModel Results
Table F-9. Modeled IRWs Exceeding Thallium Benchmark Values under Baseline and
Regulatory Options
Pcillii 1 ;iill 1.(Hidings Basis
Indusln Thallium Loadings (IhAear)
Baseline
Option 1)
Option A
Option B
Option (
Mass Loadings from all 87 Coal-Fired Power
Plants in Pollutant Loadings Analysis
619
687
631
620
13.7
Evaluation Benchmark
Modeled Number of IRWs Exceeding Thallium Benchmark
Value 1
Baseline
Option D
Option A
Option B
Option C
Water Quality Results
Freshwater Acute NRWQC
a
a
a
a
a
Freshwater Chronic NRWQC
a
a
a
a
a
Human Health Water and Organism NRWQC
3
5
3
3
0
Human Health Organism Only NRWQC
2
4
2
2
0
Drinking Water MCL
1
1
1
1
0
Wildlife Results
Sediment TEC
a
a
a
a
a
Fish Ingestion NEHC for Minks
a
a
a
a
a
Fish Ingestion NEHC for Eagles
a
a
a
a
a
Human Health Results - Fish Consumption Advisories
T4 Fish Tissue Concentration Screening
Value (Recreational)
a
a
a
a
a
T4 Fish Tissue Concentration Screening
Value (Subsistence)
a
a
a
a
a
Human Health Results - Non-Cancer
Oral RfD for Child (Recreational)
5
9
7
7
3
Oral RfD for Child (Subsistence)
8
14
9
9
5
Oral RfD for Adult (Recreational)
3
6
4
4
1
Oral RfD for Adult (Subsistence)
5
10
8
8
5
Human Health Results - Cancer
LECR for Child (Recreational)
a
a
a
a
a
LECR for Child (Subsistence)
a
a
a
a
a
LECR for Adult (Recreational)
a
a
a
a
a
LECR for Adult (Subsistence)
a
a
a
a
a
Source: ERG, 2020d; ERG, 2020j.
Acronyms: IRW (immediate receiving water); lb/year (pounds per year); LECR (lifetime excess cancer risk); MCL
(maximum contaminant level); NEHC (no effect hazard concentration); NRWQC (National Recommended Water
Quality Criteria); RfD (reference dose); TEC (threshold effect concentration); T4 (trophic level 4).
Note: Pollutant loadings are rounded to three significant figures. All benchmark values are based on total thallium
concentration, unless otherwise stated.
a - A benchmark value is not yet established for this pollutant or was not included in EPA's analyses,
b - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
c - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters).
F-ll
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Appendix F — Additional IR WModel Results
Table F-10. Modeled IRWs Exceeding Zinc Benchmark Values under Baseline and
Regulatory Options
Pcillii 1 ;iill 1.(Hidings Basis
Indusin Zinc Loadings (IhAear)
Baseline
Option 1)
Option A
Option B
Option (
Mass Loadings from all 87 Coal-Fired Power
Plants in Pollutant Loadings Analysis
1,260
1,910
1,900
1,640
407
Evaluation Benchmark
Modeled Number of IRWs Exceeding Zinc Benchmark
Value 1
Baseline
Option D
Option A
Option B
Option C
Water Quality Results
Freshwater Acute NRWQCa
0
0
0
0
0
Freshwater Chronic NRWQCa
0
0
0
0
0
Human Health Water and Organism NRWQC
0
0
0
0
0
Human Health Organism Only NRWQC
0
0
0
0
0
Drinking Water MCL
0
0
0
0
0
Wildlife Results
Sediment TEC
0
0
0
0
0
Fish Ingestion NEHC for Minks
0
0
0
0
0
Fish Ingestion NEHC for Eagles
0
0
0
0
0
Human Health Results - Fish Consumption Advisories
T4 Fish Tissue Concentration Screening
Value (Recreational)
b
b
b
b
b
T4 Fish Tissue Concentration Screening
Value (Subsistence)
b
b
b
b
b
Human Health Results - Non-Cancer
Oral RfD for Child (Recreational)
0
0
0
0
0
Oral RfD for Child (Subsistence)
0
0
0
0
0
Oral RfD for Adult (Recreational)
0
0
0
0
0
Oral RfD for Adult (Subsistence)
0
0
0
0
0
Human Health Results - Cancer
LECR for Child (Recreational)
b
b
b
b
b
LECR for Child (Subsistence)
b
b
b
b
b
LECR for Adult (Recreational)
b
b
b
b
b
LECR for Adult (Subsistence)
b
b
b
b
b
Source: ERG, 2020d; ERG, 2020j.
Acronyms: IRW (immediate receiving water); lb/year (pounds per year); LECR (lifetime excess cancer risk); MCL
(maximum contaminant level); NEHC (no effect hazard concentration); NRWQC (National Recommended Water
Quality Criteria); RfD (reference dose); TEC (threshold effect concentration); T4 (trophic level 4).
Note: Pollutant loadings are rounded to three significant figures. All benchmark values are based on total zinc
concentration, unless otherwise stated,
a - Benchmark value is based on dissolved zinc.
b - A benchmark value is not yet established for this pollutant or was not included in EPA's analyses,
c - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019
proposed rule (see Section 6.4 of the 2019 Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect
changes in the baseline, plant universe, and other analytical inputs for the analysis of Options A, B, and C.
d - The IRW Model, which excludes the Great Lakes and estuaries, analyzes 89 total immediate receiving waters
and loadings from 82 plants (some of which discharge to multiple receiving waters).
F-12
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Appendix F — Additional IR WModel Results
Table F-ll. Modeled IRWs Exceeding Non-Cancer Oral Reference Dose Values under Baseline and Regulatory Options, by
Race Category
Alio iind
Modeled Number
IRWs l-Acccding Non-Cancer Oral RID ol' Named Polliilanl
lishinii Mode
Race ( .Motion
Total Arsenic
Cadmium
Cohort
Base.
Opl. 1)
Opl. A
Opl. B
Opl. c
Base.
Opl. 1)
Opl. A
Opl. B
Opl. c
Recreational
Non-Hispanic White
0
0
0
0
0
0
0
0
0
0
(All age
Non-Hispanic Black
0
0
0
0
0
0
0
0
0
0
cohorts)
Mexican-American
0
0
0
0
0
0
0
0
0
0
Other Hispanic
0
0
0
0
0
0
0
0
0
0
Other, incl. Multiple Races
0
0
0
0
0
0
0
0
0
0
Subsistence
Non-Hispanic White
0
0
0
0
0
0
0
0
0
0
(All age
Non-Hispanic Black
0
0
0
0
0
0
0
0
0
0
cohorts)
Mexican-American
0
0
0
0
0
0
0
0
0
0
Other Hispanic
0
0
0
0
0
0
0
0
0
0
Other, incl. Multiple Races
0
0
0
0
0
0
0
0
0
0
Age and
Fishing Mode
Cohort
Race Category
Copper
Mercury (as Mcthylmercurv)
Base.
Opt. D
Opt. A
Opt. B
Opt. c
Base.
Opt. D
Opt. A
Opt. B
Opt. c
Recreational
Non-Hispanic White
0
0
0
0
0
2
10
6
6
6
(All age
Non-Hispanic Black
0
0
0
0
0
2
10
6
6
6
cohorts)
Mexican-American
0
0
0
0
0
2
11
7
7
7
Other Hispanic
0
0
0
0
0
2
10
6
6
6
Other, incl. Multiple Races
0
0
0
0
0
2
11
7
7
7
Subsistence
Non-Hispanic White
0
0
0
0
0
4
14
10
10
7
(All age
Non-Hispanic Black
0
0
0
0
0
5
14
10
10
7
cohorts)
Mexican-American
0
0
0
0
0
5
16
11
11
8
Other Hispanic
0
0
0
0
0
5
16
11
11
8
Other, incl. Multiple Races
0
0
0
0
0
5
17
12
12
9
F-13
-------
Appendix F — Additional IR WModel Results
Table F-ll. Modeled IRWs Exceeding Non-Cancer Oral Reference Dose Values under Baseline and Regulatory Options, by
Race Category
Alio and
Number IRWs l-Acceding Non-Cancer Oral Rfl) of Named Pollulanl
l ishinii Mode
Race Ciileiion
Nickel
Selenium
Cohort
Base.
()|)(. 1)
Opl. A
Opl. B
Opl. C
Base.
Opl. 1)
Opl. A
Opl. B
Opl. c
Recreational
Non-Hispanic White
0
0
0
0
0
0
6
0
0
0
(All age
Non-Hispanic Black
0
0
0
0
0
0
6
0
0
0
cohorts)
Mexican-American
0
0
0
0
0
0
6
0
0
0
Other Hispanic
0
0
0
0
0
0
6
0
0
0
Other, incl. Multiple Races
0
0
0
0
0
0
6
0
0
0
Subsistence
Non-Hispanic White
0
0
0
0
0
0
10
1
1
0
(All age
Non-Hispanic Black
0
0
0
0
0
0
10
1
1
0
cohorts)
Mexican-American
0
0
0
0
0
0
12
3
3
1
Other Hispanic
0
0
0
0
0
0
12
3
3
1
Other, incl. Multiple Races
0
0
0
0
0
1
12
3
3
1
Age and
Fishing Mode
Cohort
Race Category
Thallium
Zinc
Base.
Opt. D
Opt. A
Opt. B
Opt. c
Base.
Opt. D
Opt. A
Opt. B
Opt. c
Recreational
Non-Hispanic White
3
6
4
4
1
0
0
0
0
0
(All age
Non-Hispanic Black
3
6
4
4
1
0
0
0
0
0
cohorts)
Mexican-American
4
7
5
5
1
0
0
0
0
0
Other Hispanic
3
6
4
4
1
0
0
0
0
0
Other, incl. Multiple Races
4
7
5
5
1
0
0
0
0
0
Subsistence
Non-Hispanic White
5
10
8
8
4
0
0
0
0
0
(All age
Non-Hispanic Black
5
10
8
8
5
0
0
0
0
0
cohorts)
Mexican-American
5
11
8
8
5
0
0
0
0
0
Other Hispanic
5
11
8
8
5
0
0
0
0
0
Other, incl. Multiple Races
7
14
9
9
5
0
0
0
0
0
Source: ERG, 2020j.
Acronyms: Base. (Baseline); IRW (immediate receiving water); Opt. (Option); RfD (reference dose).
a - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019 proposed rule (see Section 6.4 of the 2019
Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect changes in the baseline, plant universe, and other analytical inputs for the analysis of Options
A, B, and C.
F-14
-------
Appendix F — Additional IR WModel Results
Table F-12. Modeled IRWs with Lifetime Excess Cancer Risk for Inorganic Arsenic Exceeding One-in-a-Million under
Baseline and Regulatory Options, by Race Category
Alio iiml l- ishiiiii Mode
R.tcc (
Modeled Nil in her of IRWs l.\m>dinu l.l-'.CR
Cohort
liiiseline
Option 1)
Option A
Option 1}
Option (
Recreational
Non-Hispanic White
0
1
0
0
0
(All age cohorts)
Non-Hispanic Black
0
1
0
0
0
Mexican-American
0
1
0
0
0
Other Hispanic
0
1
0
0
0
Other, including Multiple Races
0
1
0
0
0
Subsistence
Non-Hispanic White
0
1
0
0
0
(All age cohorts)
Non-Hispanic Black
0
1
0
0
0
Mexican-American
0
1
0
0
0
Other Hispanic
0
1
0
0
0
Other, including Multiple Races
0
2
1
1
0
Source: ERG, 2020j.
Acronyms: IRW (immediate receiving water); LECR (lifetime excess cancer risk).
a - Regulatory Option D reflects the population, methodology, and pollutant loadings for Option 1 in the 2019 proposed rule (see Section 6.4 of the 2019
Supplemental TDD (U.S. EPA, 2019b)). The values do not reflect changes in the baseline, plant universe, and other analytical inputs for the analysis of Options
A, B, and C.
F-15
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