SERA—
United States
Environmental Protection
Agency
Environmental Justice Analysis for
Supplemental Effluent Limitations Guidelines
and Standards for the Steam Electric Power
Generating Point Source Category
April 2024
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U.S. Environmental Protection Agency
Office of Water (4303T)
1200 Pennsylvania Avenue, NW
Washington, DC 20460
EPA-821-R-24-008
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Contents
1. Introduction 8
1.1 Steam Electric Power Generating Effluent Limitations Guidelines and Standards 8
1.2 Environmental Justice 8
1.2.1 Executive Orders 8
1.2.2 Considering EJ in Regulatory Actions 9
1.2.3 Definitions and Terminology 10
1.3 Purpose and Outline of the Environmental Justice Analysis 11
2. Literature on Potential Environmental Justice Concerns Associated with Coal-Fired Power Plants 13
3. Nationwide Proximity Analysis 16
3.1 Socioeconomic Characteristics of Populations Residing in Proximity to Steam Electric Power
Plants 16
3.2 Socioeconomic Characteristics of Populations Served by Affected Drinking Water Systems 20
3.3 Socioeconomic Characteristics of Populations Affected by Changes in Exposure to
Pollutants in Downstream Surface Waters 26
3.4 Key Findings 30
4. Analysis of the Distribution of Pollutant Exposures 31
4.1 Baseline and Regulatory Options 31
4.1.1 FGD Wastewater 31
4.1.2 BA Transport Water 31
4.1.3 CRL 32
4.1.4 Legacy Wastewater 32
4.2 Analysis of Exposures to Air Pollutants from Steam Electric Power Plants 33
4.2.1 Analysis of Changes in Air Quality Across Affected Areas of the Contiguous U.S 35
4.2.2 Distribution of Ozone Exposures in Communities with Predicted Changes in Air Quality
36
4.2.3 Distribution of PM2.5 Exposures in Communities with Predicted Changes in Air Quality42
4.2.4 Key Findings 48
4.3 Surface Water 48
4.3.1 Immediate Receiving Waters 48
4.3.2 Downstream Surface Waters 74
4.4 Drinking Water 79
4.4.1 Distribution of TTFIM Exposures Among Affected Communities 80
4.4.2 Distribution of Bladder Cancer Cases and Deaths Among Affected Communities 83
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Contents
4.4.3 Key Findings 88
4.5 Cumulative Risks 89
5. Analysis of the Distribution of Benefits and Costs of the Final Rule 90
5.1 Benefits 90
5.1.1 GHG Benefits 90
5.1.2 Conventional Air Pollutant Flealth Benefits 93
5.2 Costs 94
6. Limitations and Uncertainties 99
7. Conclusions 108
8. References 109
iv
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Attachments
Appendix A : Results from the Proximity Analysis of Downstream Surface Waters
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List of Figures
Figure 1. Number of People in the Contiguous U.S. Residing in Areas with Not Changing, Changing,
Improving, and Worsening Modeled Ozone and PM2.5 Concentrations in 2030 35
Figure 2. Map of 12-km Grid Cells with Modeled Changes in MDA8 Warm Season Ozone
Concentrations Improving or Worsening by at Least +/-0.007 ppb in 2030 36
Figure 3. Baseline MDA8 Ozone Concentrations and Population Counts in Areas with Not Changing,
Changing, Improving, and Worsening Modeled Ozone Concentrations in 2030 37
Figure 4. Distribution of Modeled MDA8 Ozone Concentrations Across Area Categories and Selected
Population Groups in 2030 41
Figure 5. Map of 12-km Grid Cells with Modeled Changes in Average Annual PM2.5 Concentrations
Improving or Worsening by at Least +/-0.0012 |ag/m3 in 2030 43
Figure 6. Baseline Average Annual PM2.5 Concentrations and Population Counts in Areas with Not
Changing, Changing, Improving, and Worsening Modeled PM2.5 concentrations in 2030 43
Figure 7. Distribution of Modeled Average Annual PM2.5 Concentrations Across Area Categories and
Selected Population Groups in 2030 47
Figure 8. Range of Estimated Average Annual Compliance Costs of the Proposed Rule (Option B) per
Residential Household under the Lower and Upper Bound Cost Scenarios, by NERC Region 98
List of Tables
Table 1. Percent of the Population Living Within 1 and 3 Miles of a Steam Electric Power Plant and
Associated Immediate Receiving Reach Identifying as A Person of Color or Low-Income, Compared to
the General Population 18
Table 2. Socioeconomic Characteristics of States with Communities Potentially Affected by Steam
Electric Plant Discharges, Compared to the National Average 18
Table 3. Socioeconomic Characteristics of Populations Served by Potentially Affected PWS,
Compared to the National Average 21
Table 4. Percent of Population in Tribal Areas with an Affected PWS Identifying as Low-Income
Compared to Their Respective State, National Rural, and National Average 24
Table 5. Percent of Population in Tribal Areas with an Affected PWS Identifying as a Racial or Ethnic
Minority Compared to Their Respective State, National Rural, and National Average 25
Table 6. Percent of the Population Living Within 50 Miles of an Affected Downstream Reach with
Modeled Concentrations of Selected Pollutants Under the Regulatory Options Compared to the
National Average (Period 2) 27
Table 7. Percent of the Population Living Within 50 Miles of an Affected Downstream Reach with
Modeled Concentrations of Selected Pollutants Under the Regulatory Options Identifying as a Racial
or Ethnic Minority Compared to the National Average (Period 2) 28
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List of Tables
Table 8. Percent of the Population Living Within 50 Miles of an Affected Downstream Reach with
Modeled Concentrations of Selected Pollutants Under the Regulatory Options Identifying as a Racial
or Ethnic Minority Compared to the National Average (Period 2) 29
Table 9. Regulatory Options Analyzed for the Final Rule 32
Table 10. Population Characteristics Included in the Ozone and PM2.5 Distributional Analyses 34
Table 11. Modeled MDA8 Ozone Concentrations (ppb) Across Area Categories and Selected
Population Groups in 2030 38
Table 12. Additional Information on the Column Headers Used in Table 11 and Table 13 39
Table 13. Modeled Average Annual PM2.5 Concentrations3 (|ag/m3) Across Area Categories and
Selected Population Groups in 2030b 45
Table 14. Immediate Receiving Water Community Demographics by Water Quality Benchmark
Exceedances under Baseline and the Regulatory Options 50
Table 15. Immediate Receiving Water Community Demographics by Sediment Benchmark
Exceedances under Baseline and the Regulatory Options 53
Table 16. Immediate Receiving Water Community Demographics NEHC Exceedances for Eagles
(Ingesting T4 Fish) under Baseline and the Regulatory Options 54
Table 17. Immediate Receiving Water Community Demographics NEHC Exceedances for Mink
(Ingesting T3 Fish) under Baseline and the Regulatory Options 55
Table 18. Immediate Receiving Water Community Demographics by Oral RfD Exceedances under
Baseline and the Regulatory Options, organized by Life Stage and Consumer Cohort 60
Table 19. Immediate Receiving Water Community Demographics by Lifetime Excess Cancer Risk
(LECR) Exceedances Above 1.00 x 10-6 for Arsenic under Baseline and the Regulatory Options,
organized by Life Stage and Consumer Cohort 69
Table 20. Modeled Total IQ Point Losses Under the Baseline and Avoided IQ Point Losses under the
Regulatory Options Among Infants of Subsistence and Recreational Fish Consumers Exposed to
Mercury in Utero, by Racial or Ethnic Population Group 76
Table 21. Modeled Total IQ Point Losses Under the Baseline and Avoided IQ Point Losses under the
Regulatory Options Among Infants of Subsistence and Recreational Fish Consumers Exposed to
Mercury in Utero, by Income Group 77
Table 22. Modeled Changes in TTHM Concentrations Under the Regulatory Options Among
Potentially Affected Drinking Water Systems, by State 81
Table 23. Modeled Changes in Total Bladder Cancer Cases Avoided Under the Regulatory Options
Among Potentially Affected Drinking Water Systems, by State 84
Table 24. Modeled Changes in Total Excess Bladder Cancer Deaths Avoided Under the Regulatory
Options Among Potentially Affected Drinking Water Systems, by State 86
Table 25. Energy Expenditures by Quintiles of Income before Taxes, 2022 94
Table 26. Demographics by Quintiles of Income before Taxes, 2022 95
Table 27. Energy Expenditures by Race, 2022 96
Table 28. Energy Expenditures by Race or Ethnicity, 2022 96
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List of Tables
Table 29. Limitations and Uncertainties of EPA's Nationwide Proximity Analysis 99
Table 30. Limitations and Uncertainties of EPA's Distributional Analysis of Air Impacts 100
Table 31. Limitations and Uncertainties of EPA's Distributional Analysis of Immediate Receiving
Water Impacts 101
Table 32. Limitations and Uncertainties of EPA's Distributional Analysis of Downstream Surface
Water Impacts 103
Table 33. Limitations and Uncertainties of EPA's Distributional Analysis of Drinking Water Impacts 104
Table 34. Limitations and Uncertainties of EPA's Distributional Analysis of Cumulative Risks 104
Table 35. Limitations and Uncertainties of EPA's Distributional Analysis of Costs and Benefits 106
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List of Abbreviations
ACS
American Community Survey
As-Cd-Pb
Arsenic-cadmium-lead
APS
Arizona Public Services
ASCC
Alaska Systems Coordinating Council
ATSDR
Agency for Toxic Substances and Disease Registry
BA
Bottom ash
BAT
Best available technology economically achievable
BCA
Benefit-cost analysis
BINWOE
Binary weight-of-evidence
BLL
Blood lead level
BMP
Best management practice
BPJ
Best professional judgement
BrO"
Hypobromite
CAA
Clean Air Act
CBG
Census block group
CCR
coal combustion residuals
CDC
Centers for Disease Control and Prevention
CES
Consumer Expenditure Survey
CFR
Code of Federal Regulations
C02
carbon dioxide
COMID
common identifier
COPD
chronic obstructive pulmonary disease
CP
chemical precipitation
CRE
cancer risk estimate
CRL
combustion residual leachate
CWA
Clean Water Act
DBP
disinfection byproduct
D-FATE
Downstream Fate and Transport Equations
EA
environmental assessment
EAB
Environmental Appeals Board
ELGs
effluent limitations guidelines and standards
EJ
environmental justice
E.O.
Executive Order
EPA
Environmental Protection Agency
FCPP
Four Corners Power Plant
FGD
flue gas desulfurization
FRN
Federal Register Notice
GHG
greenhouse gas
GIS
geographic information system
HI
hazard index
HICC
Flawaii Coordinating Council
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List of Abbreviations
HQ
hazard quotient
HRR
high recycle rate systems
ICIS
Integrated Compliance Information System
IEUBK
integrated exposure uptake biokinetic
IPCC
Intergovernmental Panel on Climate Change
IPM
Integrated Planning Model
IQ
intelligence quotient
IRW
immediate receiving water
JTA
Joint toxic action
LADD
Lifetime average daily dose
LECR
Lifetime excess cancer risk
LUEGU
Low-utilization electric generating unit
MCL
Maximum contaminant level
MCLG
Maximum contaminant level goal
MDA8
Maximum daily average 8-hour
Me-Hg-Pb
Methyl mercury-lead
MRL
Minimal risk level
MRO
Midwest Reliability Organization
NA
Not applicable
NAACP
National Association for the Advancement of Colored People
NAAQS
National Ambient Air Quality Standards
NASEM
National Academies of Science, Engineering, and Medicine
NC DEQ
North Carolina Department of Environmental Quality
NEHC
no effect hazard concentration
NERC
North American Energy Reliability Corporation
NHDPIus
National Hydrography Dataset Plus
NOx
nitrogen oxides
NPCC
Northeast Power Coordinating Council
NPDES
National Pollutant Discharge Elimination System
NRWQC
National Recommended Water Quality Criteria
NS
Not subcategorized
NTEC
Navajo Transitional Energy Company
OLEM
Office of Land and Emergency Management
OMB
Office of Management and Budget
OW
Office of Water
PFAS
Per- and polyfluoroalkyl substances
PM2.5
Fine particulate matter
PSES
Pretreatment Standards for Existing Sources
PWS
Public water systems
PWSID
Public water system ID
RCRA
Resource Conservation and Recovery Act
RF
Reliability First Corporation
RfD
Reference dose
RIA
Regulatory impact analysis
iv
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List of Abbreviations
SDWIS
Safe Drinking Water Information System
SERC
SERC Reliability Corporation
SI
Surface impoundment
SNAP
Supplemental Nutrition Assistance Program
S02
Sulfur dioxide
T3
Trophic level 3
T4
Trophic level 4
TDD
Technical development document
TDEQ
Texas Department of Environmental Quality
TEC
Threshold effect concentration
TRE
Texas Reliability Entity
THM
Trihalomethane
TMDL
Total maximum daily load
TTD
Target organ toxicity dose
TTHM
Total trihalomethanes
UCMR4
Fourth Unregulated Contaminant Monitoring Rule
USGCRP
U.S. Global Change Research Program
USGS
U.S. Geological Survey
USPS
U.S. Postal Service
WECC
Western Electricity Coordinating Council
ZCTA
Zip Code Tabulation Area
ZLD
Zero liquid discharge
Zn-Pb
Zinc-lead
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Executive Summary
The U.S. Environmental Protection Agency (EPA) analyzed the distribution of water quality and non-water
quality impacts of the final rule across all potentially affected communities and sought input from
stakeholders representing communities with potential environmental justice (EJ) concerns. Several
Executive Orders (E.O.s)—E.O. 12898, E.O. 13985, E.O. 14008, E.O. 12866, and E.O. 14096-call on
federal agencies to advance EJ and equity in developing policies by analyzing and addressing
disproportionate and adverse impacts on historically underserved, marginalized, and economically
disadvantaged people.
Under the authority of the Clean Water Act (CWA), EPA is finalizing revisions to the technology-based
effluents limitations guidelines and standards (ELGs) for the steam electric power generating point source
category for certain wastestreams. The ELGs address flue gas desulfurization (FGD) wastewater, bottom
ash (BA) transport water, combustion residual leachate (CRL), and legacy wastewater at existing sources,
and CRL at new sources.
As research has shown, steam electric power plants are often sited in low-income and communities of
color, and as a result, these communities are often differentially exposed to and experience the health
effects from pollution from steam electric power plants compared to the average community in the
United States (Henneman et al., 2023; NAACP, 2012; Tessum et al., 2019; Thind et al., 2019). Therefore,
understanding the socioeconomic characteristics of populations affected by steam electric plant
discharges is necessary to effectively analyze whether vulnerable populations — like low-income and
minority populations — may experience differential impacts under the baseline and to what extent the
supplemental ELGs may mitigate, exacerbate, or create differential impacts to these populations relative
to the baseline.1 To accomplish this, EPA conducted a distributional analysis of pollutant exposures,
health effects, and costs and benefits under the baseline and all three regulatory options across all
potentially affected communities.
This report details the EJ analysis for the final rule. Following the approach used at proposal, the analysis
is divided into several elements:
• A literature review of EJ concerns related to coal-fired power plants (Section 2).
• A national-level proximity analysis which EPA used as an initial assessment of the socioeconomic
characteristics of affected communities living in proximity to steam electric power plants, surface
waters receiving discharges from steam electric power plants, as well as affected communities served
by drinking water systems intaking water from receiving waters of steam electric power plants
(Section 3).
• A national-level analysis of the distribution of pollutant exposures and health effects across
population groups of concern in all potentially affected communities under the baseline and
1 EPA's Technical Guidance for Assessing Environmental Justice in Regulatory Analysis (2016) defines the term
disproportionate impacts as "differences in impacts or risks that are extensive enough that they may merit Agency
action." The Guidance further notes that "In general, the determination of whether there is a disproportionate
impact that may merit Agency action is ultimately a policy judgment which, while informed by analysis, is the
responsibility of the decision maker. The terms difference or differential indicate an analytically discernible
distinction in impacts or risks across population groups. It is the role of the analyst to assess and present differences
in anticipated impacts across population groups of concern for both the baseline and proposed regulatory options,
using the best available information (both quantitative and qualitative) to inform the decision maker and the
public."
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Executive Summary
regulatory options (Section 4). The exposure pathways, pollutant exposures, and/or human impacts
assessed include:
Exposure to fine particulate matter (PM2.5) and ozone from air pollution emitted by steam electric
power plants.
Water quality, wildlife, and non-cancer and cancer human health impacts from exposure to
pollutants in immediate receiving waters of steam electric power plants.
Human health impacts - neurological-, cardiovascular-, and cancer-related - caused by exposure
to lead, mercury, and arsenic from consuming fish caught in reaches downstream of receiving
waters of steam electric power plants.
Exposure to total trihalomethanes (TTHM) in drinking water sources from drinking water systems
that intake water from receiving waters of steam electric power plants, and the resulting
incidence of bladder cancer cases and bladder cancer deaths.
Health impacts from cumulative exposures to pollutants discharged by steam electric power
plants through consumption offish caught in immediate receiving waters of steam electric power
plants.
• An analysis that evaluates the distribution of costs and benefits among potentially affected
communities (Section 5).
Overall, EPA's EJ analysis showed that the extent to which the technologies steam electric power plants
implement to control wastewater discharges will reduce differential baseline exposures for low-income
populations and people of color in affected communities to pollutants in wastewater and resulting human
impacts varies. In particular, benefits associated with improvements to water quality, wildlife, and human
health resulting from reductions in pollutants in surface water will accrue to some low-income
populations and people of color at a higher rate under some or all of the regulatory options, while,
particularly for communities near immediate receiving waters, some population groups of concern may
experience new or exacerbated distributional disparities under the final rule. Benefits associated with
drinking water will accrue to people of color and low-income populations at a higher rate under the final
rule. Remaining exposures, impacts, costs, and benefits analyzed either accrue at a higher rate to
populations which are not people of color or low-income, accrue proportionately to all populations, or
are small enough that EPA could not conclude whether changes in disproportionate impacts would occur.
While the changes in GHGs attributable to the final rule are small compared to worldwide emissions,
findings from peer-reviewed evaluations demonstrate that actions that reduce GHG emissions are also
likely to reduce climate-related impacts on vulnerable communities, including low-income communities
and communities of color.
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1. Introduction
1.1 Steam Electric Power Generating Effluent Limitations Guidelines and
Standards
Under the authority of the Clean Water Act (CWA), the U.S. Environmental Protection Agency (EPA)
develops national wastewater discharge standards that apply to categories of industrial point source
wastewater dischargers, referred to as effluent limitations guidelines and standards (ELGs). Developed for
a specific industry, ELGs are technology-based standards that industrial point sources subject to them are
required, by regulation, to meet. Standards for direct industrial dischargers are implemented through the
National Pollutant Discharge Elimination System permits issued by states and EPA regional offices.
Standards for indirect dischargers are implemented through EPA, state, or local pretreatment programs.
One of the categories of industrial wastewater dischargers subject to ELGs is the steam electric power
generating point source category. This category covers power plants primarily engaged in the generation
of electricity for distribution and sale and that use nuclear or fossil fuels (such as coal, oil, and natural gas)
to heat water in boilers, which generates steam that drive turbines connected to electric generators. The
plants generate wastewater in the form of chemical pollutants and thermal pollution (heated water) from
their water treatment, power cycle, ash handling and air pollution control systems, as well as from coal
piles, yard and floor drainage, and other miscellaneous wastes.
The steam electric ELG sets technology-based standards for wastewater discharges from these steam
electric power plants. The steam electric rule was promulgated in 1974 and has been amended in 1977,
1978, 1980, 1982, 2015, and 2020. While EPA is currently revising the ELGs, permitting authorities are
implementing the requirements contained in the 2015 rule and the 2020 rule.2
With this final rule, EPA is revising the technology-based ELGs for wastestreams from coal-fired plants,
including flue gas desulfurization (FGD) wastewater, bottom ash (BA) transport water, combustion
residual leachate (CRL), and legacy wastewater.
1.2 Environmental Justice
EPA analyzed the distribution of water quality and non-water quality impacts of the final rule across all
potentially affected communities and sought input from stakeholders representing communities with
potential environmental justice (EJ) concerns.
The analysis has been conducted alongside other non-statutorily required analyses, such as the
Environmental Assessment (EA). It is intended to provide the public with a discussion of the potential
distributional impacts of the final rule and input received from communities potentially experiencing
differential impacts. The analysis does not form a basis or rationale for any of the actions EPA is finalizing
in this rulemaking.
1.2.1 Executive Orders
EPA performed the analysis following guidance on EJ issues to federal agencies through several Executive
Orders (E.O.s): Executive Order 12898: Federal Actions to Address Environmental Justice in Minority
Populations and Low-Income Populations; Executive Order 13985: Advancing Racial Equity and Support
for Underserved Communities through the Federal Government; Executive Order 14008: Tackling the
Climate Crisis at Home and Abroad; and Executive Order 14096: Revitalizing Our Nation's Commitment to
2 For more information on the 2015 rule and the 2020 rule see https://www.epa.Rov/eR/steam-electric-power-
ReneratinR-effluent-Ruidelines.
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Section 1 — Introduction
Environmental Justice for All (Executive Order 12898, 1994; Executive Order 13985, 2021; Executive
Order 14008, 2021; Executive Order 14096, 2023).
Each Federal agency must make the achievement of EJ part of its mission "by identifying and addressing,
as appropriate, disproportionately high and adverse human health or environmental effects of its
programs, policies, and activities on minority populations and low-income populations." (p.l) Section 2-2
of E.O. 12898 (59 FR 7629, February 16, 1994) provides that each Federal agency must conduct its
programs, policies, and activities that substantially affect human health or the environment in a manner
that ensures such programs, policies, and activities do not have the effect of (1) excluding persons
(including populations) from participation in; or (2) denying persons (including populations) the benefits
of; or (3) subjecting persons (including populations) to discrimination under, such programs, policies, and
activities because of their race, color, or national origin.
E.O. 14008 (86 FR 7619, February 1, 2021) calls on Federal agencies to make achieving environmental
justice part of their missions "by developing programs, policies, and activities to address the
disproportionately high and adverse human health, environmental, climate-related and other cumulative
impacts on disadvantaged communities, as well as the accompanying economic challenges of such
impacts." (p. 7629) It also declares a policy "to secure environmental justice and spur economic
opportunity for disadvantaged communities that have been historically marginalized and overburdened
by pollution and under-investment in housing, transportation, water and wastewater infrastructure and
health care." (p. 7629) Under E.O. 13563 (76 FR 3821, January 21, 2011), Federal agencies may consider
equity, human dignity, fairness, and distributional considerations, where appropriate and permitted by
law. E.O. 14008 directs Federal agencies to develop programs, polices and activities to address the
disproportionate health, environmental, economic, and climate impacts on disadvantaged, historically
marginalized and overburdened communities. Similarly, E.O. 14096 (88 FR 25251, April 26, 2023) re-
emphasizes the commitment of the Executive branch to include the achievement of environmental
justice in the mission of each agency and to evaluate the impacts of regulations and other Federal
activities on communities with environmental justice concerns. E.O. 14096 places a responsibility on
Federal agencies to "identify, analyze, and address disproportionate and adverse human health and
environmental effects (including risks) and hazards of Federal activities, including those related to climate
change and cumulative impacts of environmental and other burdens with environmental justice
concerns[.]" (p. 25253) Additionally, E.O. 14096 suggests improved environmental justice analyses
through "disaggregating environmental risk, exposure, and health data by race, national origin, income,
socioeconomic status, age, sex, disability, and other readily accessible and appropriate categories." (p.
25257) EPA has reflected this suggestion by disaggregating the following proximity and distributional
analyses by income, race and, ethnicity.
1.2.2 Considering EJ in Regulatory Actions
The incorporation of EJ into EPA's rulemakings is guided by two Agency documents: (1) Technical
Guidance for Assessing Environmental Justice in Regulatory Analysis (U.S. EPA, 2016) and (2) Guidance on
Considering Environmental Justice During the Development of Regulatory Action (U.S. EPA, 2015b). The
Technical Guidance for Assessing Environmental Justice in Regulatory Analysis (U.S. EPA, 2016)
establishes the expectation that regulatory analysts conduct the highest quality EJ analysis feasible in
support of rulemakings, recognizing that what is feasible will be context-specific.
When assessing the potential for disproportionate and adverse health or environmental impacts of
regulatory actions on historically underserved and overburdened communities, EPA aims to answer three
broad questions:
1. Is there evidence of potential EJ concerns in the baseline (defined as the state of the world absent the
regulatory action)? Assessing the baseline enables EPA to determine whether pre-existing disparities
are associated with the pollutant(s) under consideration (e.g., are the effects of the pollutant(s) more
concentrated in some population groups?).
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Section 1 — Introduction
2. Is there evidence of potential EJ concerns for the regulatory option(s) under consideration?
Specifically, how are the pollutant(s) and its (their) effects distributed for the regulatory options
under consideration? And
3. Do the regulatory option(s) under consideration exacerbate or mitigate EJ concerns relative to the
baseline?3
1.2.3 Definitions and Terminology
EPA defines EJ as the "just treatment and meaningful involvement of all people, regardless of income,
race, color, national origin, Tribal affiliation, or disability, in agency decision-making and other Federal
activities that affect human health and the environment so that people:
(i) are fully protected from disproportionate and adverse human health and environmental effects
(including risks) and hazards, including those related to climate change, the cumulative impacts of
environmental and other burdens, and the legacy of racism or other structural or systemic barriers;
and
(ii) have equitable access to a healthy, sustainable, and resilient environment in which to live, play,
work, learn, grow, worship, and engage in cultural and subsistence practices." (Executive Order
14096, 2023).
EPA has also defined meaningful involvement based on four key principles: "people have an opportunity
to participate in decisions about activities that may affect their environment and/or health; the public's
contributions can influence the regulatory agency's decision; community concerns will be considered in
the decision-making process; and decision makers will seek out and facilitate the involvement of those
potentially affected" (Executive Order 12898, 1994). The OMB has issued additional guidance on
including public participation and community engagement in the regulatory process across the federal
government (OMB, 2023).
Throughout this document the terms "potential EJ concern" and "population group(s) of concern" are
used:
A potential EJ concern is defined as "the actual or potential lack of fair treatment or meaningful
involvement of minority populations,4 low-income populations, Tribes, and Indigenous Peoples in the
development, implementation, and enforcement of environmental laws, regulations, and policies" (U.S.
EPA, 2016, p. 4). In a regulatory context, the term refers to "disproportionate impacts on minority
populations, low-income populations, and/or Indigenous Peoples that may exist prior to or may be
created by the proposed regulatory action" (U.S. EPA, 2016, p. 4). Therefore, this analysis uses the term
when discussing whether the results of EPA's quantitative and qualitative analyses indicate that there are
differential impacts under the baseline and/or regulatory options that could be considered
disproportionate.
3 Differential impacts on population groups of concern can only be identified in relation to a comparison group. A
comparison group can be defined in multiple ways, for instance in terms of individuals with similar socioeconomic
characteristics located at a broader geographic level or with different socioeconomic characteristics within an
affected area. The goal is to select a comparison group that allows one to identify how the effects of the regulation
vary by race, ethnicity, and income separate from other systematic differences across groups or geographic areas.
4 In relation to Executive Order (E.O.) 12898, the White House's Council on Environmental Quality defines minorities
as "individual(s) who are members of the following population groups: American Indian or Alaska Native; Asian or
Pacific Islander; Black, not of Hispanic origin; or Hispanic" (U.S. Environmental Protection Agency. (2016). Technical
Guidance for Assessing Environmental Justice in Regulatory Analysis. Retrieved from
https://www.epa.gOv/sites/default/files/2016-06/documents/ejtg_5_6_16_v5.l.pdf, p. 6).
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Section 1 — Introduction
E.O. 12898 identified a number of population groups of concern including people of color, low-income
populations, and Indigenous Peoples (E.O. 12898, 59 CFR 7629, February 16, 1994). E.O. 14096 expands
populations groups of concern to include consideration of national origin and disability status (88 FR
25251, April 26, 2023). Populations who primarily consume fish and/or wildlife for subsistence are also
included as a group that can overlap with other population groups of concern through unique exposure
pathways to pollutants (E.O. 12898, 59 CFR 7629, February 16, 1994). EPA has also advised that, when
appropriate, additional population characteristics-such as life stage and gender-can be used to evaluate
differences within a population group of concern (U.S. EPA, 2016). The term is used in this analysis when
referring to the apportionment of impacts among people of color, low-income populations, or Indigenous
populations as well as individual racial/ethnic population groups (e.g., Hispanic populations). (See Exec.
Order No. 12866, 1993, p. 1; Exec. Order No. 12898, 1994; Exec. Order No. 13985, 2021, p. 7009; Exec.
Order No. 14008, 2021, p. 7629; Exec. Order No. 14096, 2023, p. 25253; U.S. EPA, 2016, p. 4, 2022a)
1.3 Purpose and Outline of the Environmental Justice Analysis
EPA conducted this analysis to assess the distribution of pollutant exposures, environmental and human
health impacts, and costs and benefits among populations expected to be affected by the revised ELGs.
To advance the objectives of E.O. 12898, the analysis evaluates the distribution of environmental and
human health impacts under the baseline and regulatory options evaluated, giving particular attention to
whether differential impacts that could be considered disproportionate and adverse are experienced by
population groups of concern under the baseline and whether the regulatory options evaluated mitigate,
exacerbate, or create differential impacts among population groups of concern. This analysis also
advances the objectives of E.O.s 14008 and 14096 by evaluating, both quantitatively and qualitatively,
some of the cumulative risks experienced by populations expected to be affected by the proposed rule.
The distribution of these cumulative risks among population groups of concern is assessed underthe
baseline and regulatory options evaluated to determine whether the options mitigate, exacerbate, or
create a differential distribution of cumulative risks among population groups of concern. Additionally,
this analysis advances the objectives of E.O. 12866, as the costs and benefits of the options are evaluated
with respect to the distribution of economic impacts among populations expected to be affected by the
rule. Lastly, the analysis advances the objectives of E.O. 13985 by developing a more comprehensive
approach to considering the equity of impacts of the final rule, using results from quantitative analyses to
evaluate the distribution of environmental and human health impacts as well as results from qualitative
information gathered through the meaningful involvement of affected populations. This involvement
included public meetings EPA conducted with several affected communities during the development of
the proposed rule (see proposed rule EJA document; U.S. EPA, 2023b), and the review of public
comments EPA received on the proposed rule and considered as the Agency finalized the rule (see
Response to Comments document in the docket for this action, U.S. EPA, 2024d).
The results of this EJ analysis are presented in the following sections of this document:
• Section 2 presents a review of existing literature on potential EJ concerns related to pollution from
coal-fired power plants.
• Section 3 presents a nationwide assessment of the socioeconomic characteristics of communities
living near steam electric power plants and exposure pathways for pollutants discharged by the
plants.
• Section 4.1 defines the baseline and each of the regulatory options evaluated in the analysis.
• Sections 4.2 to 4.5 present EPA's evaluation of the distribution of environmental and/or human
health impacts under the baseline and the regulatory options. The results are shown for each of the
pollutant exposure pathways evaluated—air, surface water, and drinking water. This section also
presents the results of the distribution of cumulative risks among populations expected to be
affected by the revised ELGs.
• Section 5 discusses the distribution of benefits and costs of the final rule among affected populations.
11
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Section 1 — Introduction
• Section 6 discusses the limitations and uncertainties of the EJ analysis.
• Section 7 discusses the conclusions of the EJ analysis.
• Section 8 provides references cited in the text of the report.
Several appendices provide additional details on the analyses.
12
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2. Literature on Potential Environmental Justice Concerns
Associated with Coal-Fired Power Plants
EPA reviewed the available literature on EJ concerns related to coal-fired power plants, including
additional studies published since the proposed rule. EPA identified 14 papers that focused on coal-fired
power plants and EJ issues, eight of which focused on coal-fired power plants in the United States and
were considered by the Agency to be directly relevant to the scope of the final rule. Two of the eight
papers focused on a large study on coal-fired power plants conducted by the National Association for the
Advancement of Colored People (NAACP);5 one paper detailed the negative health consequences
associated with living near coal-fired power plants; another paper explored inequalities in communities
where coal-fired power plants are sited; three more papers focused explicitly on evaluating the disparate
impacts of fine particulate matter (PM2.5) pollution from coal power plants across income and race; and
the eighth was a study conducted in a coal-producing region evaluating predictors of proximity to older
coal waste impoundments. Additionally, EPA included a discussion of the results from a previous EPA EJ
analysis on the disposal of coal combustion residuals from electric utilities to detail previously discovered
EJ concerns related to coal-fired power plants. The findings of the literature review are discussed below.
Living near coal-fired power plants can be associated with adverse health impacts. These plants produce
air pollutants like sulfur dioxide (S02), nitrogen oxides (NOx), and PM25. Exposures to S02 and NOx are
associated in the short-term with acute respiratory illnesses like coughing and wheezing, and in the long-
term with asthma (Casey et al., 2020). Asthma has been found to particularly affect people who identify
as African American. African Americans are three times more likely, on average, to be hospitalized for
asthma than people who identify as White and have a death rate from asthma that is 172 percent higher
than people who identify as White (NAACP, 2012). Additionally, exposure to PM25 can cause chronic
bronchitis, irregular heart conditions, and asthma, and lead to premature death among people with heart
or lung disease (Thind et al., 2019). Coal-fired power plants also release heavy metals like mercury,
uranium, arsenic, and lead into the air and water. Pregnant women and their children are particularly
vulnerable to adverse health impacts from exposure to heavy metals, as in vitro exposures can cause
developmental disorders in children like impaired brain function, blindness, and development delays in
general (NAACP, 2012). Indigenous populations can also experience potentially disproportionate and
adverse health impacts from exposure to heavy metals, particularly mercury, due to their higher rates of
fish consumption (Israel & The Daily Climate, 2012). These findings suggest that people of color,
Indigenous populations, and children face potentially disproportionate and adverse health impacts from
exposures to pollutants released by coal-fired power plants into the air and water.
In 2012, the NAACP evaluated 378 coal-fired power plants in the United States based on their EJ
performance (NAACP, 2012). A plant's EJ performance was determined using a scoring system based on
five factors: emissions of S02, emissions of NOx, size of the population living within three miles of the
plant, median income of the total population living within three miles of the plant, and the percentage of
people of color living within three miles of the plant (NAACP, 2012). The analysis showed that individuals
living within three miles of a coal-fired power plant are on average poorer and more likely to be people of
color (NAACP, 2012). Particularly, coal-fired power plants sited in urban areas are differentially located in
communities of color (NAACP, 2012). Focusing on 75 plants that received "failing" EJ performance scores,
the study found that the four million people living within three miles of these plants had an average per
capita income of $17,500, or about $22,600 in 2022 dollars—about 25 percent less than the national
5 While the universe of steam electric plants has changed substantially since the NAACP report was published, this
report still provides relevant background on the potential health effects associated with living near steam electric
plants as well as a history of EJ concerns surrounding steam electric plants.
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Section 2—Literature on Potential Environmental Justice Concerns Associated with Coal-Fired Power
Plants
average6—and 53 percent were people of color compared to a national average of 36 percent (NAACP,
2012).
NAACP (2012) also found that coal-fired power plants contribute to climate justice issues through
emissions of carbon dioxide (C02) which contribute to climate change. The report cited a statement
made by EPA in 2009 that listed some of the impacts of climate change, including "increased drought,
increased number of heavy downpours and flooding, more frequent and intense heat waves and
wildfires, greater sea level rise, more intense storms, and harm to water resources, agriculture, wildlife,
and ecosystems" (NAACP, 2012, p. 18). The report noted that certain populations - including low-income
populations, Indigenous populations, people of color, elderly populations, and disabled populations - may
face a potentially disproportionate risk from these climate change impacts, given that they generally have
less capacity to recover from such events (NAACP, 2012). Based on these findings, coal-fired power plants
may lead to potentially disproportionate risks among these population groups beyond those who live
near a plant by increasing the likelihood of extreme weather and natural disasters in their communities.
While the current population of coal-fired power plants substantially differs from that evaluated in 2012
due to the conversion and retirement of coal-fired generating units in the last decade, more recent
studies reached similar conclusions regarding the differential impacts of coal-fired power plants on
certain populations. Kosmicki and Long (2016) empirically analyzed whether people of color and children
are more likely to live near coal-fired power plants as well as if poverty and income level are indicators of
proximity to a coal-fired power plant. The results of their multinomial logistic regression show that Census
tracts with higher percentages of people of color and a lower median income have an increased
probability of being located within ten miles of a coal-fired power plant. Similarly, Henneman et al. (2023)
found that Black populations and Indigenous populations have been inequitably exposed to coal-fired
power plant-related PM2.5 emissions. In this study, the authors identified annual PM2.5 source impacts
associated with S02 emissions from US coal-fired power plants from 1999-2020. Although PM2.5 emission
exposure has fallen across the board, the authors found that Black populations and Indigenous
populations are still inequitably exposed to this pollutant, particularly in the North Central and Western
region of the US.
Similar to Henneman et al. (2023), Thind et al. (2019) and Tessum et al. (2019) evaluate the exposure of
different population groups to PM2.5 emissions from coal-fired power plants. Both studies allocate the
burden of electricity production (as measured by the exposure to PM2.5 emissions) by fuel used to
produce electricity as well as how much electricity communities consume. Thind et al. (2019) found that
around 93 percent of deaths attributable to PM2.5 from electricity generation are attributable to coal-fired
power plants. Additionally, the authors found that low-income households are exposed to PM2.5 from
electricity generation at a much higher rate than high-income households. Similarly, Tessum et al. (2019)
found that Black and Hispanic populations are exposed to more PM2.5 pollution from electricity
generation relative to their consumption of electricity. These findings suggest that coal-fired power plants
tend to be located in low-income communities, communities of color, and Indigenous communities.
Additionally, EPA conducted an EJ analysis to support the proposed rule for Hazardous and Solid Waste
Management System: Disposal of Coal Combustion Residuals From Electric Utilities; Legacy CCR Surface
Impoundments (88 FR 31982). In that analysis, EPA found that Black populations, Native American
populations, Hispanic populations, households below the poverty level, households with less than a high
school education, and households experiencing linguistic isolation were more highly represented in the
populations living within one and three miles of facilities with legacy coal combustion residual (CCR)
surface impoundments than the national average (U.S. EPA, 2023). EPA also evaluated the cumulative
environmental impacts of facilities with legacy CCR surface impoundments by observing the levels of
certain environmental indicators, such as particulate matter (PM) 2.5, ozone, and diesel PM, among other
indicators. EPA found that within a mile of facilities with legacy CCR surface impoundments, more than
half of the environmental indicators observed were higher than the averages for the state where the
6 Expressed in 2022 dollars, the average per capita income in the U.S. was about $28,300.
14
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Section 2—Literature on Potential Environmental Justice Concerns Associated with Coal-Fired Power
Plants
facility is located. From these findings, EPA concluded that the proposed rule would reduce potential
disproportionate effects on the communities with EJ concerns by requiring closure and corrective actions
at legacy facilities, reducing the risks of exposure to contaminants from CCR (U.S. EPA, 2023).
Though coal production is not directly addressed by the revised ELG, EJ concerns have also been studied
in coal-producing areas. Since the decline in the coal industry and in the aftermath of the Martin County,
Kentucky coal waste impoundment disaster, Lievanos, Greenberg and Wishart (2018) found that the
strongest predictors of proximity to older coal waste impoundments were proximity to abandoned and
sealed mines and poverty levels. Particularly with poverty, the study found that a one percent increase in
the percent of block group residents living below the poverty line is associated with a 52-meter decrease
in distance to the nearest coal waste impoundment sited from 2001 to 2006 (Lievanos, Greenberg &
Wishart, 2018). Based on this finding, they concluded that "block group poverty levels consistently
represented the path of least resistance to new hazardous coal waste impoundments sited" within that
period (Lievanos, Greenberg & Wishart, 2018, p. 51). This suggests EJ concerns among low-income
populations in coal-producing areas with respect to the siting of new coal waste impoundments and
increased risks of potential disproportionate and adverse impacts as impoundments age and become
more susceptible to failure.
15
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3. Nationwide Proximity Analysis
EPA conducted a nationwide proximity analysis to identify and characterize communities near steam
electric power plants subject to the revised ELGs, downstream surface waters affected by plant
discharges, and communities served by drinking water systems potentially affected by plant discharges.
The methodology follows the same approach EPA used for the proposed rule, but with updated
socioeconomic data and set of affected steam electric power plants and the associated receiving and
downstream reaches.
3.1 Socioeconomic Characteristics of Populations Residing in Proximity to
Steam Electric Power Plants
For this analysis, EPA assessed the socioeconomic characteristics of the populations within specified
distances of steam electric power plants and of immediate reaches affected by steam electric plant
discharges. EPA conducted this analysis for the set of 112 steam electric power plants for which the
Agency modeled non-zero pollutant loadings under the baseline or regulatory options.
EPA collected 2017 to 2021 population-specific American Community Survey (ACS) data from the U.S.
Census Bureau(2022a) on:
• The percent of the population below the poverty threshold,7 referred to as "low-income population"
in this analysis.
• The percent of the population categorized in various racial/ethnic groups representing people of
color.8
EPA compiled these data for Census block groups (CBGs) located within one mile and three miles of
steam electric power plants. EPA assessed the spatial distribution of low-income individuals and specific
race and ethnicity categories to determine whether people in these groups are more or less represented
in the populations living near steam electric power plants that are expected to incur costs because of the
rule.9 Additionally, there are plants included in this analysis that are not expected to incur costs because
of the rule but do have non-zero baseline loads for the four waste streams in the final rule. EJ concerns
may exist in areas where the percent of the population that is low-income and/or people of color is
higher than the state or national averages.
The distance buffers from the steam electric power plants and their associated immediate receiving
reaches10 are denoted below as the "analysis region." Populations within the regions included in the
analysis may be affected by steam electric power plant discharges and other environmental impacts in
the immediate vicinity of the plant in the baseline and by environmental improvements resulting from the
regulatory options.11 EPA notes that these are not the only populations that could be affected by steam
7 For the ACS, the Census Bureau determines poverty status by comparing annual income to a set of dollar values,
called poverty thresholds, that vary by family size, number of children, and the age of the householder.
8 The racial/ethnic categories are based on available fish consumption data as well as the breakout of racial/ethnic
populations in Census data, which distinguishes racial groups within Flispanic and non-Flispanic categories.
9 In this analysis, EPA used the coordinates of each steam electric plant as the basis to define analysis regions using
various distance buffers.
10 The regulatory options are projected to result in reductions (or no change) in pollutant loadings discharged to
receiving waters; therefore, changes are generally anticipated to benefit populations living near the plants.
11 Throughout this discussion, unless stated otherwise, changes are in the direction of improving environmental
conditions.
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Section 3—Nationwide Proximity Analysis
electric power plants and other environmental impacts. For example, air pollutants emitted by steam
electric power plants may affect populations within hundreds of miles of that plant.
EPA used the U.S. Census Bureau's ACS data for 2017 to 2021 (U.S. Census Bureau, 2022a) to identify and
income status at the CBG, analysis region, state, and national levels. Table 1 summarizes the
socioeconomic characteristics of the analysis regions defined using buffer distances of one and three
miles from the steam electric power plants. As shown in Table 1, approximately 90,000 people live within
one mile of at least one steam electric power plant that is expected to incur compliance costs due to the
final rule or has a non-zero load for any of the four waste streams considered in the final rule, and
approximately 790,000 people live within three miles.12 For communities located within one and three
miles of a steam electric power plant, the proportion of the population that are people of color
(considered as a group, across all racial/ethnic categories) or is smaller than or similar to the national
average, with the exception of people who identify as American Indian or Alaska Native (non-Hispanic)
and those who identify as Other (non-Hispanic). These racial/ethnic categories have proportions that are
larger than the national average (Table 1).
The comparison to the national average does not account for important differences between states,
particularly given the non-uniform geographical distribution of steam electric power plants across the
country. Therefore, EPA also compared the demographic characteristics of communities around each
plant to that of the states intersected by each analysis region. Table 2 summarizes the state statistics
against which the communities around each plant were compared.
Steam electric power plants expected to incur compliance costs due to the final rule or that have a non-
zero load for any of the four waste streams considered in the final rule are located in 30 states across the
U.S. Across these states, EPA observed great variability in the percent of states' populations identified as
people of color or low-income. For example, across the 30 states, the percent of the states' populations
identified as African American (non-Hispanic) ranges from 0.8 to 37.4 percent (Table 2). Because of this,
EPA compared the results from Table 1 to the median of the state averages for each demographic
characteristic. For communities within one and three miles of a steam electric power plant identified as
belonging to the demographic groups analyzed, population proportions exceeded the median of the state
averages, except for people identified as low-income, Native Hawaiian/Pacific Islander (non-Hispanic),
and Hispanic/Latino (within one mile of a plant only) (Table 2).
12 For both buffer distances, around one percent of CBGs fall within the buffer area around multiple steam electric
plants. As a result, some individuals may be double counted in this estimation of total affected population.
17
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Section 3—Nationwide Proximity Analysis
Table 1. Percent of the Population Living Within 1 and 3 Miles of a Steam Electric Power Plant and Associated Immediate Receiving Reach
Identifying as A Person of Color or Low-Income, Compared to the General Population
Distance
from Plant
Total
Population
(Millions)3
Percent Low-
Income
Percent
African
American
(Non-
Hispanic)
Percent Asian
Percent
Native
Hawaiian/Pac
ific Islander
Percent
American
Indian/Alaska
Native
Percent Other
(Non-
Hispanic)
Percent
Hispanic/Lati
no
1 mile
0.09
12.2%
11.3%
3.1%
0.0%
0.9%
4.5%
5.9%
3 miles
0.79
13.0%
10.5%
2.7%
0.0%
0.9%
3.9%
8.0%
United States
333.0
12.9%
12.1%
5.6%
0.2%
0.6%
3.5%
19.2%
Source: U.S. EPA analysis, 2024.
Notes:
a. For both buffer distances, around one percent of CBGs fall within the buffer area around multiple steam electric plants.
Table 2. Socioeconomic Characteristics of States with Communities Potentially Affected by Steam Electric Plant Discharges, Compared to the
National Average
State
Percent Below
Poverty Level
Percent African-
American (Non-
Hispanic)
Percent Asian
(Non-Hispanic)
Percent Native
Hawaiian/Pacific
Islander (Non-
Hispanic)
Percent
American
Indian/Alaska
Native (Non-
Hispanic)
Percent Other
(Non-Hispanic)
Percent
Hispanic/Latino
AL
15.8%
26.3%
1.4%
0.0%
0.3%
2.5%
4.5%
AR
16.0%
15.2%
1.5%
0.3%
0.5%
4.0%
7.9%
FL
13.1%
15.1%
2.7%
0.1%
0.1%
3.2%
26.2%
GA
13.9%
31.1%
4.2%
0.0%
0.1%
3.2%
9.9%
IA
11.0%
3.7%
2.5%
0.1%
0.2%
2.8%
6.4%
IL
11.8%
13.8%
5.6%
0.0%
0.1%
2.7%
17.5%
IN
12.5%
9.3%
2.4%
0.0%
0.1%
3.0%
7.3%
KS
11.5%
5.4%
3.0%
0.1%
0.5%
3.9%
12.3%
KY
16.3%
7.9%
1.5%
0.1%
0.1%
2.8%
3.9%
LA
18.8%
31.7%
1.7%
0.0%
0.5%
2.9%
5.3%
Ml
13.3%
13.4%
3.2%
0.0%
0.4%
3.6%
5.4%
MN
9.2%
6.5%
5.0%
0.0%
0.8%
3.7%
5.6%
MO
12.8%
11.2%
2.0%
0.1%
0.2%
3.8%
4.4%
18
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Section 3—Nationwide Proximity Analysis
Table 2. Socioeconomic Characteristics of States with Communities Potentially Affected by Steam Electric Plant Discharges, Compared to the
National Average
State
Percent Below
Poverty Level
Percent African-
American (Non-
Hispanic)
Percent Asian
(Non-Hispanic)
Percent Native
Hawaiian/Pacific
Islander (Non-
Hispanic)
Percent
American
Indian/Alaska
Native (Non-
Hispanic)
Percent Other
(Non-Hispanic)
Percent
Hispanic/Latino
MS
19.4%
37.4%
1.0%
0.0%
0.4%
2.0%
3.2%
NC
13.7%
20.8%
3.0%
0.1%
1.0%
3.3%
9.8%
ND
10.7%
3.1%
1.6%
0.2%
4.8%
3.1%
4.1%
NE
10.3%
4.7%
2.5%
0.1%
0.7%
3.0%
11.5%
NH
7.4%
1.4%
2.7%
0.0%
0.1%
2.8%
4.1%
NM
18.3%
1.8%
1.5%
0.1%
8.5%
2.5%
49.6%
OH
13.4%
12.2%
2.3%
0.0%
0.1%
3.5%
4.1%
OK
15.2%
7.1%
2.2%
0.2%
7.2%
7.9%
11.2%
PA
11.8%
10.5%
3.5%
0.0%
0.1%
3.0%
7.9%
SC
14.5%
26.0%
1.6%
0.1%
0.2%
2.9%
6.0%
TN
14.3%
16.3%
1.8%
0.1%
0.2%
2.9%
5.8%
TX
14.0%
11.8%
5.0%
0.1%
0.2%
2.5%
39.8%
UT
8.8%
1.1%
2.3%
0.9%
0.8%
3.2%
14.4%
VA
9.9%
18.7%
6.7%
0.1%
0.2%
4.1%
9.8%
WA
10.0%
3.7%
8.9%
0.6%
0.9%
6.1%
13.2%
Wl
10.7%
6.2%
2.8%
0.0%
0.7%
2.9%
7.2%
WV
16.9%
3.4%
0.8%
0.0%
0.1%
2.8%
1.7%
WY
10.7%
0.8%
0.9%
0.1%
2.0%
3.0%
10.3%
Median State
Average
13.1%
6.5%
2.1&
0.1%
0.2%
2.8%
6.6%
United States
12.9%
12.1%
5.6%
0.2%
0.6%
3.5%
19.2%
Source: U.S. EPA analysis, 2024.
19
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Section 3—Nationwide Proximity Analysis
3.2 Socioeconomic Characteristics of Populations Served by Affected Drinking
Water Systems
in addition to considering proximity to steam electric power plants, EPA assessed the socioeconomic
characteristics of communities served by public water systems (PWS) whose source waters are affected
by steam electric power plant discharges. To do this, EPA estimated reductions in pollutant
concentrations in PWS source waters affected by steam electric power plants' discharges, and
characterized the populations served by the PWS directly or indirectly affected by these changes.
EPA determined the service area of each PWS using a multi-tiered approach based on data availability.
EPA first used service areas identified in the Hydroshare Community Water Systems Service Boundaries
(CWSSB) dataset (SimpleLab EPIC, 2022),13 then 2022 TIGER ZIP code tabulated areas (ZCTAs), and finally
county boundaries when no other data were available.14 Over 95 percent of PWS with facilities
downstream from steam electric plants had boundaries defined in the CWSBB dataset. Three percent of
the PWS service areas were matched based on the ZIP code, and approximately one percent were
matched based on the county. This approach to estimating service area boundaries differs from the
approach used for the proposed rule, in that it relies primarily on the CWSSB dataset, which provides a
more accurate estimate of service area boundaries than using just ZCTAs and county boundaries as was
done in the proposed rule.
As with the proximity analysis for communities near steam electric power plants, EPA collected 2017 to
2021 population-specific ACS data from the U.S. Census Bureau (2022a) on:
• The percent of the population below the poverty threshold,15 referred to as "low-income population"
for this analysis.
• The population categorized in various racial/ethnic groups representing people of color.16
EPA conducted the analysis at the Census block group (CBG) level and compared the socioeconomic
characteristics of the affected BGs (based on the service areas of affected PWS) to those of the state
containing each CBG (U.S. Census Bureau, 2022b). EJ concerns may exist in areas where the share of the
population that is low-income and/or minority (including specific racial or ethnic categories) is higher than
the respective state average.
As Table 3 summarizes the socioeconomic characteristics of the estimated population potentially affected
by changes in drinking water quality resulting from changes in pollutant levels in source waters.
13 The CWSSB dataset uses a 3-tiered approach to assign more specific boundaries to PWS service areas. Tier 1
includes all PWS with explicit water service boundaries provided by states. Tier 2 assigns a boundary based on a
match with a TIGER place name. Any PWS not in tier 1 or 2 is assigned a circular boundary around provided water
system centroids based on a statistical model trained on explicit water service boundary data.
14 This is compared to the 2019 and 2023 analyses which used counties and ZIP codes, respectively, to determine
the demographic and socioeconomic characteristics of the population served.
15 For the ACS, the Census Bureau determines poverty status by comparing annual income to a set of dollar values,
called poverty thresholds, that vary by family size, number of children, and the age of the householder.
16 The racial/ethnic categories are based on available fish consumption data as well as the breakout of ethnic/racial
populations in Census data, which distinguishes racial groups within Hispanic and non-Hispanic categories. The
groups are: African American (non-Hispanic), Asian (non-Hispanic), Native Hawaiian or Pacific Islander (non-
Hispanic), American Indian or Alaska Native (non-Hispanic), Other (non-Hispanic), and Hispanic or Latino.
20
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Section 3—Nationwide Proximity Analysis
Table 3. Socioeconomic Characteristics of Populations Served by Potentially Affected PWS, Compared to the National Average
Socioeconomic Characteristics of Populations in Service Areas of Affected PWS
State
Number of
Potentially
Affected PWS
Population
Served3
Percent
Below
Poverty
Level
Percent
African-
American
(Non-
Hispanic)
Percent Asian
(Non-
Hispanic)
Percent Native
Hawaiian/Pacific
Islander (Non-
Hispanic)
Percent American
Indian/Alaska
Native (Non-
Hispanic)
Percent
Other(Non-
Hispanic)
Percent
Hispanic/Latino
AL
51
1,243,009
14.4%
21.2%
1.3%
0.0%
0.4%
3.2%
6.4%
AR
18
20,567
16.5%
0.4%
0.2%
0.1%
1.9%
3.3%
2.7%
DE
1
231,114
12.0%
24.8%
5.2%
0.0%
0.1%
3.4%
11.9%
FL
7
429,167
9.5%
5.6%
1.8%
0.0%
0.2%
2.3%
10.6%
GA
16
706,206
18.0%
31.0%
1.9%
0.1%
0.1%
3.2%
11.5%
IA
12
155,987
13.9%
3.6%
1.0%
0.3%
0.2%
2.8%
9.6%
IL
86
759,693
13.4%
17.8%
1.4%
0.0%
0.1%
3.7%
4.4%
IN
4
192,275
15.7%
10.5%
1.4%
0.2%
0.0%
3.3%
2.9%
KS
21
781,859
9.2%
5.0%
4.6%
0.0%
0.6%
3.7%
7.8%
KY
54
1,774,744
16.9%
16.2%
2.1%
0.0%
0.1%
3.5%
4.9%
LA
4
89,699
17.5%
25.8%
2.0%
0.0%
0.4%
3.0%
7.8%
MA
12
397,487
11.5%
3.9%
9.7%
0.0%
0.1%
2.7%
26.3%
MD
20
2,140,060
16.8%
47.9%
4.5%
0.0%
0.2%
3.8%
6.4%
Ml
99
3,426,543
17.0%
28.5%
4.6%
0.0%
0.2%
3.6%
5.5%
MN
11
1,055,600
14.8%
15.7%
10.4%
0.0%
0.7%
5.1%
8.9%
MO
52
2,658,501
9.3%
17.4%
6.0%
0.1%
0.2%
3.5%
5.1%
MS
2
1,490
19.4%
27.8%
2.7%
0.0%
0.0%
3.3%
8.2%
NC
38
1,514,192
10.8%
27.9%
5.4%
0.0%
0.2%
3.4%
11.9%
ND
13
33,722
8.1%
1.0%
0.8%
0.1%
3.2%
1.8%
3.4%
NE
13
569,432
15.3%
15.4%
4.4%
0.0%
0.5%
4.2%
12.5%
NH
3
103,592
7.1%
1.6%
3.6%
0.0%
0.1%
3.1%
10.7%
OH
30
1,229,857
17.9%
22.3%
2.0%
0.0%
0.0%
3.8%
3.9%
OK
48
828,052
13.6%
8.8%
3.2%
0.1%
6.8%
8.3%
12.1%
PA
93
4,033,477
10.3%
11.7%
4.1%
0.0%
0.1%
3.4%
4.7%
SC
72
1,496,142
14.6%
27.7%
1.9%
0.2%
0.2%
3.1%
6.1%
SD
45
43,674
14.6%
1.5%
1.9%
0.0%
19.6%
2.0%
3.2%
TN
43
2,116,969
11.4%
14.5%
2.8%
0.1%
0.1%
3.7%
7.2%
TX
1
23,170
14.6%
5.6%
5.8%
0.0%
0.1%
2.3%
16.0%
21
-------
Section 3—Nationwide Proximity Analysis
Table 3. Socioeconomic Characteristics of Populations Served by Potentially Affected PWS, Compared to the National Average
Socioeconomic Characteristics of Populations in Service Areas of Affected PWS
State
Number of
Potentially
Affected PWS
Population
Served3
Percent
Below
Poverty
Level
Percent
African-
American
(Non-
Hispanic)
Percent Asian
(Non-
Hispanic)
Percent Native
Hawaiian/Pacific
Islander (Non-
Hispanic)
Percent American
Indian/Alaska
Native (Non-
Hispanic)
Percent
Other(Non-
Hispanic)
Percent
Hispanic/Latino
VA
23
828,925
11.0%
26.5%
5.3%
0.1%
0.2%
5.0%
8.2%
WV
24
289,810
20.0%
4.6%
1.8%
0.0%
0.1%
3.8%
2.1%
TOTAL
916
29,175,015
United
States
12.9%
12.1%
5.6%
0.2%
0.6%
3.5%
19.2%
Source: U.S. EPA Analysis, 2024.
Notes:
a. The affected population is based on the total population served reported by SDWIS for affected PWSs within each state
22
-------
Section 3—Nationwide Proximity Analysis
As Table 3 shows, more than 29 million people across 30 states are served by PWSs potentially affected
by the estimated changes in source water quality under the regulatory options. Of the 30 states with
affected PWS, 19 serve CBGs with higher proportions of low-income populations, 17 serve CBGs with
higher proportions of African American (non-Hispanic) populations, and 11 serve CBGs with higher
proportions of Other (non-Hispanic) populations compared to the national average. Fewer than five of
the states serve CBGs with higher proportions of American Indian or Alaska Native (non-Hispanic), Native
Hawaiian or Pacific Islander (non-Hispanic), and Hispanic or Latino populations compared to the national
average.
Table 4 and Table 5 summarize the estimated Tribal area population potentially affected by changes in
drinking water quality as a result of steam electric power plant discharges. The analysis intersected the
geographic boundaries of national Tribal lands with the service area boundaries of affected PWSs. This
was then overlaid with CBGs. This analysis compares the socioeconomic characteristics of the affected
Tribal areas to the averages of the states where the Tribal lands are located, the national average of the
rural population of the United States, and the overall national average of the United States.
23
-------
Section 3—Nationwide Proximity Analysis
Table 4. Percent of Population in Tribal Areas with an Affected PWS Identifying as Low-Income Compared to Their Respective State, National Rural, and
National Average
States with
Total Population
Percent Low-Income Population
Tribal Area
Affected Tribal
Areas
Affected
Population3
Total for Tribal
Area
State(s)
Population
Tribal Area
State Average
Poarch Creek Reservation and Off-
AL
9,930
440
4,876,863
8.2%
15.8%
Reservation Trust Land
Lake Traverse Reservation and Off-
SD
230
11,409
881,785
27.9%
12.5%
Reservation Trust Land
Standing Rock Reservation
SD, ND
7,745
7,974
1,655,129
29.9%
11.6%
Prairie Band of Potawatomi Nation
KS
2,500
1,475
2,932,099
11.1%
11.5%
Reservation
Cherokee OTSA
OK
638,430
513,176
3,948,136
16.0%
15.2%
CreekOTSA
OK
692,049
809,447
3,948,136
14.3%
15.2%
Osage Reservation
OK
511,302
46,140
3,948,136
16.7%
15.2%
Choctaw OTSA
OK
1,075
226,644
3,948,136
20.1%
15.2%
United States - Rural
12.3%
United States
12.9%
Source: U.S. EPA analysis, 2024.
Notes:
|a. The affected population is based on the population served by the PWS. In some cases, the PWS serves both the tribal area and surrounding service areas.
24
-------
Section 3—Nationwide Proximity Analysis
Table 5. Percent of Population in Tribal Areas with an Affected PWS Identifying as a Racial or Ethnic Minority Compared to Their Respective State, National
Rural, and National Average
Tribal Area
States
Total Population
Percent African
American
(Non-Hispanic)
Percent Asian
(Non-Hispanic)
Percent Native
Hawaiian /
Pacific Islander
(Non-Hispanic)
Percent
American
Indian/Alaska
Native (Non-
Hispanic)
Percent Other
(Non-Hispanic)
Percent
Hispanic/Latino
Affected
Pop.3
Tribal
Area
State(s)
Pop.
Tribal
State
Averag
e (Avg.)
Tribal
State
Avg.
Tribal
State
Avg.
Tribal
State
Avg.
Tribal
State
Avg.
Tribal
State
Avg.
Poarch Creek
Reservation and
Off-Reservation
Trust Land
AL
9,930
440
4,876,863
0.4%
26.3%
0.0%
1.4%
0.0%
0.0%
0.0%
0.3%
9.7%
2.5%
0.0%
4.5%
Lake Traverse
Reservation and
Off-Reservation
Trust Land
SD
230
11,409
881,785
0.0%
2.1%
0.3%
1.4%
0.0%
0.1%
44.9%
8.0%
1.9%
3.3%
1.7%
4.3%
Standing Rock
Reservation
SD,
ND
7,745
7,974
1,655,129
0.0%
2.6%
0.0%
1.5%
0.0%
0.1%
90.7%
6.5%
1.2%
3.2%
0.1%
4.2%
Prairie Band of
Potawatomi
Nation
Reservation
KS
2,500
1,475
2,932,099
0.2%
5.4%
0.5%
3.0%
0.1%
0.1%
26.2%
0.5%
7.6%
3.9%
9.4%
12.3%
Cherokee OTSA
OK
638,430
513,176
3,948,136
10.7%
7.1%
3.0%
2.2%
0.1%
0.2%
7.3%
7.2%
8.2%
7.9%
13.5%
11.2%
CreekOTSA
OK
692,049
809,447
3,948,136
10.5%
7.1%
3.5%
2.2%
0.1%
0.2%
5.0%
7.2%
7.9%
7.9%
13.4%
11.2%
Osage
Reservation
OK
511,302
46,140
3,948,136
12.7%
7.1%
3.3%
2.2%
0.1%
0.2%
5.0%
7.2%
7.9%
7.9%
15.1%
11.2%
Choctaw OTSA
OK
1,075
226,644
3,948,136
1.1%
7.1%
0.5%
2.2%
0.0%
0.2%
18.2%
7.2%
11.9%
7.9%
2.7%
11.2%
United States - F
Sural
6.3%
0.7%
0.1%
1.8%
2.8%
7.4%
United States
12.1%
5.6%
0.2%
0.6%
3.5%
19.2%
Source: U.S. EPA analysis, 2024.
Notes:
a. The affected population is based on the population served by the PWS. In some cases, the PWS serves both the tribal area and surrounding service areas.
25
-------
Section 3—Nationwide Proximity Analysis
As shown in Table 4, affected Tribal areas consistently have higher proportions of people who are below
the poverty level compared to both the overall and rural national averages as well as the state averages,
with the exception of the Prairie Band of Potawatomi Nation Reservation. As shown in Table 5, affected
Tribal areas have higher proportions of people who belong to some minority racial/ethnic categories
other than American Indian/Alaska Native (non-Hispanic) compared to state and national averages. In
particular, the Poarch Creek Reservation and Off-Reservation Trust Land has nearly three times the
proportion of people who identify as "Other (non-Hispanic)" than the state and national averages.
3.3 Socioeconomic Characteristics of Populations Affected by Changes in
Exposure to Pollutants in Downstream Surface Waters
Lastly, EPA evaluated the socioeconomic characteristics of communities within 50 miles17 of reaches
affected by steam electric plant discharges, including both reaches that receive discharges from steam
electric power plants and downstream reaches.18 To assess the socioeconomic characteristics of these
communities, EPA collected 2017 to 2021 population-specific ACS data (U.S. Census Bureau, 2022a) on:
• The percent of the population below the poverty threshold,19 referred to as "low-income population"
in this analysis.
• The population categorized in various racial/ethnic groups representing people of color.20
EPA compared the socioeconomic characteristics of these areas to national averages. EJ concerns may
exist in areas where the percent of the population that is low-income and/or people of color (including
specific racial or ethnic categories) is higher than the national average.
EPA conducted this analysis for communities affected by changes in pollutant loadings modeled for two
periods: Period 1 and Period 2. Period 1 covers the years 2025 through 2029, when the universe of steam
electric power plants would transition from current (baseline) treatment practices to practices that
achieve the revised limitations, whereas Period 2 covers the years 2030 through 2049, when the full
universe of plants is projected to employ treatment practices that achieve the revised limitations. The
Benefit Cost Analysis (BCA) document provides additional details on the estimated loading reductions for
the two periods (U.S. EPA, 2024a). Given that the results of the proximity analysis show similar water
quality improvement and distributions in socioeconomic characteristics among affected communities in
Period 1 and Period 2, with only differences in magnitude, results are only presented and discussed for
Period 2 (Table 6 through Table 8).21
17 See the 2024 BCA for an explanation of why a 50-mile radius was used to estimate the potentially affected
population.
18 The analysis defines "communities in proximity to reaches" as the aggregate populations residing in CBGs within
50 miles of all reaches within 300 km of steam electric power plant outfalls with nonzero loadings, which includes
approximately 112.5 million people as of 2021. This analysis provides total population and does not adjust for the
fraction of this population that consumes self-caught fish.
19 For the ACS, the Census Bureau determines poverty status by comparing annual income to a set of dollar values,
called poverty thresholds, that vary by family size, number of children, and the age of the householder.
20 The racial/ethnic categories are based on available fish consumption data as well as the breakout of ethnic/racial
populations in Census data, which distinguishes racial groups within Hispanic and non-Hispanic categories. The
groups are: African American (non-Hispanic), Asian (non-Hispanic), Native Hawaiian or Pacific Islander (non-
Hispanic), American Indian or Alaska Native (non-Hispanic), Other (non-Hispanic), and Hispanic or Latino.
21 Results for Period 1 can be found in Appendix A.
26
-------
Section 3—Nationwide Proximity Analysis
Table 6. Percent of the Population Living Within 50 Miles of an Affected Downstream Reach with Modeled Concentrations of Selected Pollutants Under the
Regulatory Options Compared to the National Average (Period 2)
Pollutant
Changes in
Number of Downstream Reaches3
Percent Low-Income Population
Concentrations
Option A
Option B
Option C
Option A
Option B
Option C
Antimony
Decreases'11
10,777
10,803
10,868
12.85%
12.85%
12.85%
No changes
91
65
0
11.92%
11.48%
0.00%
Arsenic
Decreases
10,777
10,803
10,868
12.85%
12.85%
12.84%
No changes
262
236
171
12.53%
12.43%
12.79%
Cadmium
Decreases
10,777
10,803
10,868
12.85%
12.85%
12.84%
No changes
262
236
171
12.53%
12.43%
12.79%
Cyanide3
Decreases
3,667
3,667
4,107
13.53%
13.53%
13.48%
No changes
440
440
0
13.13%
13.13%
0.00%
Lead3
Decreases
6,723
6,723
6,743
12.45%
12.45%
12.45%
No changes
652
652
632
12.99%
12.99%
12.99%
Manganese
Decreases
10,777
10,803
10,868
12.85%
12.85%
12.84%
No changes
262
236
171
12.53%
12.43%
12.79%
Mercury
Decreases
10,777
10,803
10,868
12.85%
12.85%
12.84%
No changes
262
236
171
12.53%
12.43%
12.79%
Thallium
Decreases
10,777
10,803
10,868
12.85%
12.85%
12.84%
No changes
262
236
171
12.53%
12.43%
12.79%
United States
12.90%
Isoi/rce: U.S. EPA Analysis, 2024.
Notes:
a. Not all steam electric plants discharge cyanide and lead. The associated socioeconomic characteristic information is only for the set of reaches with non-zero loadings for those pollutants
(4,107 and 6,743 reaches for cyanide and lead, respectively, compared to 10,868 reaches for other pollutants).
b. Under the regulatory options, the largest change in the concentration of the pollutants analyzed is a decrease in Manganese of 0.361 mg/L. Given the small range of pollutant changes
|observed-zero mg/L to -0.361 mg/L, EPA generalized these changes as "decreases" for each pollutant for ease of comprehension.
27
-------
Section 3—Nationwide Proximity Analysis
Table 7. Percent of the Population Living Within 50 Miles of an Affected Downstream Reach with Modeled Concentrations of Selected Pollutants Under the
Regulatory Options Identifying as a Racial or Ethnic Minority Compared to the National Average (Period 2)
Pollutant
Changes in
Concentrations
Number of Downstream
Reaches3
Percent African American
Percent American Indian/
Alaska Native
Percent Asian
Option A Option B Option C
Option A Option B Option C
Option A Option B Option C
Option A Option B Option C
Antimony
Decreases6
10,777
10,803
10,868
15.52%
15.53%
15.48%
0.41%
0.41%
0.41%
3.66%
3.66%
3.65%
No changes
91
65
0
9.31%
5.66%
0.00%
0.08%
0.05%
0.00%
1.73%
1.77%
0.00%
Arsenic
Decreases
10,777
10,803
10,868
15.49%
15.51%
15.45%
0.41%
0.41%
0.41%
3.68%
3.68%
3.67%
No changes
262
236
171
13.98%
13.19%
16.04%
0.13%
0.13%
0.16%
2.07%
2.09%
2.22%
Cadmium
Decreases
10,777
10,803
10,868
15.49%
15.51%
15.45%
0.41%
0.41%
0.41%
3.68%
3.68%
3.67%
No changes
262
236
171
13.98%
13.19%
16.04%
0.13%
0.13%
0.16%
2.07%
2.09%
2.22%
Cyanided
Decreases
3,667
3,667
4,107
17.10%
17.10%
18.06%
0.21%
0.21%
0.21%
3.39%
3.39%
3.33%
No changes
440
440
0
24.99%
24.99%
0.00%
0.20%
0.20%
0.00%
2.93%
2.93%
0.00%
Lead a
Decreases
6,723
6,723
6,743
14.56%
14.56%
14.61%
0.53%
0.53%
0.53%
3.83%
3.83%
3.82%
No changes
652
652
632
14.36%
14.36%
13.94%
0.18%
0.18%
0.18%
4.62%
4.62%
4.71%
Manganese
Decreases
10,777
10,803
10,868
15.49%
15.51%
15.45%
0.41%
0.41%
0.41%
3.68%
3.68%
3.67%
No changes
262
236
171
13.98%
13.19%
16.04%
0.13%
0.13%
0.16%
2.07%
2.09%
2.22%
Mercury
Decreases
10,777
10,803
10,868
15.49%
15.51%
15.45%
0.41%
0.41%
0.41%
3.68%
3.68%
3.67%
No changes
262
236
171
13.98%
13.19%
16.04%
0.13%
0.13%
0.16%
2.07%
2.09%
2.22%
Thallium
Decreases
10,777
10,803
10,868
15.49%
15.51%
15.45%
0.41%
0.41%
0.41%
3.68%
3.68%
3.67%
No changes
262
236
171
13.98%
13.19%
16.04%
0.13%
0.13%
0.16%
2.07%
2.09%
2.22%
United States
12.10%
0.60%
5.60%
Source: U.S. EPA Analysis, 2024.
Notes:
a. Not all of the steam electric plants are estimated to discharge cyanide and lead. The associated socioeconomic characteristic information is only for the set of reaches with non-zero loadings
for those pollutants (4,107 and 6,743 reaches for cyanide and lead, respectively, compared to 10,868 reaches for other pollutants).
b. Under the regulatory options, the largest change in the concentration of the pollutants analyzed is a decrease in manganese of 0.361 mg/L. Given the small range of pollutant changes observed
(zero mg/L to -0.361 mg/L), EPA generalized these changes as "decreases" for each pollutant for ease of presentation.
28
-------
Section 3—Nationwide Proximity Analysis
Table 8. Percent of the Population Living Within 50 Miles of an Affected Downstream Reach with Modeled Concentrations of Selected Pollutants Under the
Regulatory Options Identifying as a Racial or Ethnic Minority Compared to the National Average (Period 2)
Pollutant
Changes in
Concentrations
Number of Downstream
Reaches3
Percent Native Hawaiian/
Pacific Islander
Percent Other (Non-Hispanic)
Percent Hispanic/Latino
Option A Option B Option C
Option A Option B Option C
Option A Option B Option C
Option A Option B Option C
Antimony
Decreases111
10,777
10,803
10,868
0.07%
0.07%
0.07%
3.27%
3.27%
3.27%
11.61%
11.60%
11.55%
No changes
91
65
0
0.03%
0.02%
0.00%
2.82%
2.82%
0.00%
2.20%
1.76%
0.00%
Arsenic
Decreases
10,777
10,803
10,868
0.07%
0.07%
0.07%
3.27%
3.27%
3.27%
11.67%
11.66%
11.61%
No changes
262
236
171
0.06%
0.05%
0.07%
3.59%
3.62%
3.92%
5.21%
5.22%
6.53%
Cadmium
Decreases
10,777
10,803
10,868
0.07%
0.07%
0.07%
3.27%
3.27%
3.27%
11.67%
11.66%
11.61%
No changes
262
236
171
0.06%
0.05%
0.07%
3.59%
3.62%
3.92%
5.21%
5.22%
6.53%
Cyanidea
Decreases
3,667
3,667
4,107
0.05%
0.05%
0.05%
3.11%
3.11%
3.11%
10.71%
10.71%
10.36%
No changes
440
440
0
0.06%
0.06%
0.00%
3.09%
3.09%
0.00%
7.78%
7.78%
0.00%
Lea da
Decreases
6,723
6,723
6,743
0.06%
0.06%
0.06%
3.42%
3.42%
3.42%
9.12%
9.12%
9.11%
No changes
652
652
632
0.05%
0.05%
0.05%
3.01%
3.01%
3.01%
18.36%
18.36%
18.76%
Manganese
Decreases
10,777
10,803
10,868
0.07%
0.07%
0.07%
3.27%
3.27%
3.27%
11.67%
11.66%
11.61%
No changes
262
236
171
0.06%
0.05%
0.07%
3.59%
3.62%
3.92%
5.21%
5.22%
6.53%
Mercury
Decreases
10,777
10,803
10,868
0.07%
0.07%
0.07%
3.27%
3.27%
3.27%
11.67%
11.66%
11.61%
No changes
262
236
171
0.06%
0.05%
0.07%
3.59%
3.62%
3.92%
5.21%
5.22%
6.53%
Thallium
Decreases
10,777
10,803
10,868
0.07%
0.07%
0.07%
3.27%
3.27%
3.27%
11.67%
11.66%
11.61%
No changes
262
236
171
0.06%
0.05%
0.07%
3.59%
3.62%
3.92%
5.21%
5.22%
6.53%
United States
0.20%
3.50%
19.20%
Source: U.S. EPA Analysis, 2024.
Notes:
a. Not all steam electric plants are estimated to discharge cyanide and lead. The associated socioeconomic characteristic information is only for the set of reaches with non-zero loadings for those
pollutants (4,107 and 6,743 reaches for cyanide and lead, respectively, compared to 10,868 reaches for other pollutants).
b. Under the regulatory options, the largest change in the concentration of the pollutants analyzed is a decrease in manganese of 0.361 mg/L. Given the small range of pollutant changes
observed (zero mg/L to -0.361 mg/L), EPA generalized these changes as "decreases" for each pollutant for ease of comprehension.
29
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Section 3—Nationwide Proximity Analysis
As shown in Table 7, communities living near the majority of reaches (regardless of the associated water
quality change under the regulatory options) have a larger proportion of populations identified as African
American (non-Hispanic) than the national average. As shown in Table 7 and Table 8, all of the reaches
(regardless of the associated water quality change under the regulatory options) have a smaller
proportion of people who identify as Asian (non-Hispanic), people who identify as American Indian or
Alaska Native (non-Hispanic), people who identify as Native Hawaiian or Pacific Islander (non-Hispanic),
and people who identify as Hispanic or Latino than national averages. In the majority of cases, reaches
also have a smaller proportion of low-income population and population that identify as Other (non-
Hispanic) than the national average. However, for certain pollutants, the reaches have larger than
average proportions of the population for the previously mentioned demographics. For cyanide and lead,
communities living near affected reaches (regardless of the associated water quality change under the
regulatory options) have a larger proportion of low-income population than the national average. For
arsenic, cadmium, manganese, mercury, and thallium, communities living near affected reaches
(regardless of the associated water quality change under the regulatory options) have a larger proportion
of population that identify as Other (non-Hispanic) than the national average.
3.4 Key Findings
The results of EPA's power plant proximity analysis indicate that, similar to the findings of the literature
review, steam electric power plants are differentially located in low-income or minority communities. The
analysis shows that communities located within one and three miles of a steam electric power plant have
larger proportions of people identified as American Indian or Alaska Native (non-Hispanic), Other (non-
Hispanic]), and low-income than the average community when compared to the national average.
Additionally, the PWS and downstream proximity analyses indicate that, like the literature review
suggests, population groups of concern may experience differential impacts from pollutants discharged
by steam electric power plants. The PWS analysis shows that populations served by potentially affected
PWSs have larger proportions of people identified as low-income, African American (non-Hispanic),
American Indian or Alaska Native (non-Hispanic), and Other (non-Hispanic) than the average community
in the United States. Focusing on PWSs serving tribal areas, PWSs were found to serve areas with larger
proportions of people identified as low-income and racial and ethnic groups other than American Indian
or Alaska Native (non-Hispanic) than the average community in the states where the Tribal lands are
located, the average community United States overall, and the average community in the rural United
States. Furthermore, the downstream analysis shows that the majority of downstream reaches of
receiving waters of steam electric power plants have communities living within 50 miles with larger
proportions of people identified as low-income, African American (non-Hispanic), and Other (non-
Hispanic) than the average community in the United States.
30
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4. Analysis of the Distribution of Pollutant Exposures
For the final rule, EPA evaluated the distribution of pollutant exposures and health effects among all
communities potentially affected under the baseline and each of the regulatory options. EPA conducted
this analysis for each of the relevant pathways of exposure to pollutants from steam electric power
plants: air (only analyzes Option B), surface water, and drinking water.
The objectives of this analysis were to determine:
• Whether, through each exposure pathway, under the baseline, communities with identified potential
EJ concerns experience differential, and potentially disproportionate, and adverse pollutant
exposures and/or health effects compared to communities with no identified potential EJ concerns.
• Whether differential, and potentially disproportionate, and adverse pollutant exposures and health
effects experienced by communities with potential EJ concerns are expected to be mitigated,
exacerbated, or created by each of the regulatory options.
The results of these analyses are presented and discussed in this section.
4.1 Baseline and Regulatory Options
This analysis evaluates three regulatory options, labelled A through C in increasing order of stringency, as
shown in Table 9. With this action, EPA is finalizing limits based on Option B.
All three options include the same technology basis for FGD wastewater (zero discharge systems) and BA
transport water (dry handling and closed-loop systems), while incrementally increasing controls on CRL
and legacy wastewater and removing certain subcategories as one moves from Option A to Option C.
In estimating changes under each option, EPA compares projected pollutant discharges to those which
would occur under the baseline, which reflects applicable requirements (in absence of the rule) of the
2020 rule (85 FR 64650).
4.1.1 FGD Wastewater
Under all three main options, EPA would require zero discharge of FGD wastewater based on zero-
discharge technologies and retain the 2020 FGD wastewater limitations and standards as an interim step
toward achievement of zero discharge requirements.
Under all three options, EPA would also eliminate the BAT and PSES subcategorizations for high FGD flow
facilities and low-utilization electric generating units (LUEGUs). Option A and Option B would also create a
subcategory for EGUs that will permanently cease coal combustion no later than December 31, 2034, and
instead of zero discharge would require discharges from these facilities to meet the 2020 rule limitations
as included in their CWA permit. This subcategory modifies the proposed early adopters subcategory.
Under Option C, EPA would not finalize a subcategory for those planning to cease coal combustion by
December 31, 2034. Note that, for all three options, EPA would retain the subcategory for electric
generating units (EGUs) permanently ceasing coal combustion by 2028.
4.1.2 BA Transport Water
Under all three main options, EPA would require zero discharge of BA transport water based on dry-
handling or closed-loop systems and retain the 2020 BA transport water limitations and standards as an
interim step toward achievement of zero discharge requirements.
For all three options, EPA would also eliminate the BAT and PSES subcategorizations for LUEGUs. Option A
and Option B would also create a subcategory for EGUs that will permanently cease coal combustion no
later than December 31, 2034, and instead would require discharges from these facilities to meet the
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Section 4—Analysis of the Distribution of Pollutant Exposures
2020 rule limitations as permitted. Under Option C, EPA would not finalize this subcategory. Note that,
for all three options, EPA would retain the subcategory for EGUs permanently ceasing coal combustion by
2028.
4.1.3 CRL
Under Option A, EPA would establish BAT limitations and PSES for mercury and arsenic based on chemical
precipitation treatment. Under Option B and Option C, BAT limitations and PSES would be zero discharge
and EPA would establish BAT limitations and PSES for mercury and arsenic based on chemical
precipitation for discharges of CRL through groundwater deemed by the permitting authority, on a case-
by-case basis, to be functionally equivalent direct discharges. Option A and Option B would also create a
subcategory for EGUs that would permanently cease coal combustion no later than December 31, 2034,
and instead would leave these discharges subject to case-by-case BPJ decision-making until permanent
cessation of coal combustion and then would subject the discharges to mercury and arsenic limitations
based on chemical precipitation. Under Option C, EPA would not finalize this subcategory.
4.1.4 Legacy Wastewater
Under Option A, EPA would not specify a nationwide technology basis for BAT/PSES applicable to legacy
wastewater at this time and such limitations would be derived on a site-specific basis by the permitting
authorities, using their BPJ. Under Option B and Option C, EPA would establish a subcategory for
discharges of legacy wastewater discharged from surface impoundments commencing closure after 60
days following the rule publication. For such discharges, EPA would establish mercury and arsenic
limitations based on chemical precipitation.
Table 9. Regulatory Options Analyzed for the Final Rule
Technology Basis for BAT/PSES Regulatory Options3
Wastestream
Subcategory
2020 Rule
(Baseline)
Option A
Option B
(Final Rule)
Option C
FGD
Wastewater
N/A
CP + Bio
ZLD
ZLD
ZLD
EGUs permanently ceasing the
combustion of coal by 2028
SI
SI
SI
SI
EGUs permanently ceasing the
combustion of coal by 2034
NS
2020 rule
limitations as
permitted
2020 rule
limitations as
permitted
NS
High FGD Flow Facilities or LUEGUs
CP
NS
NS
NS
BA Transport
Water
N/A
HRR
Dry-handling
or closed-
loop systems
Dry-handling
or closed-
loop systems
Dry-handling
or closed-
loop systems
EGUs permanently ceasing the
combustion of coal by 2028
SI
SI
SI
SI
EGUs permanently ceasing the
combustion of coal by 2034
NS
2020 rule
limitations as
permitted
2020 rule
limitations as
permitted
NS
LUEGUs
BMP Plan
NS
NS
NS
CRL
N/A
BPJ
CP
ZLD
ZLD
Discharges of unmanaged CRL
N/A
NS
CP
CP
EGUs permanently ceasing the
combustion of coal by 2034
N/A
Reserving for
best
professional
judgement;
Reserving for
best
professional
judgement;
NS
32
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 9. Regulatory Options Analyzed for the Final Rule
Technology Basis for BAT/PSES Regulatory Options3
Wastestream
Subcategory
2020 Rule
(Baseline)
Option A
Option B
(Final Rule)
Option C
CP after
closure
CP after
closure
Legacy
Wastewater
N/A
N/A
Reserving for
best
professional
judgement
Reserving for
best
professional
judgement
Reserving for
best
professional
judgement
Legacy wastewater discharged
from surface impoundments
commencing closure after [X date]
N/A
NS
CP
CP
Abbreviations: BMP = Best Management Practice; CP = Chemical Precipitation; HRR = High Recycle Rate Systems; SI = Surface
Impoundment; ZLD = Zero Liquid Discharge; NS = Not subcategorized (default technology basis applies); NA = Not applicable
Notes
a. See Technical Development Document (TDD) for a description of these technologies (U.S. EPA, 2024e).
Source: U.S. EPA Analysis, 2024
The analyses described in the following sections focus on loadings associated with three main
wastestreams: FGD wastewater, BA transport water, and CRL.
Legacy wastewater discharges and loading reductions achieved by the legacy wastewater limits in the
final rule would occur only as plants close and dewater their existing ponds. Given the uncertainty on
when plants may do so, EPA estimated no loading reductions during the period of analysis when modeling
pollutant loadings and resulting exposure and health effects. Similarly, certain plants could be required to
treat CRL discharged from landfills, surface impoundments, or other features via groundwater to meet
the limits in the final rule. These limits would apply only in cases where a permitting authority deems, on
a case-by-case basis, that the discharge is functionally equivalent to a direct discharge and requires a
permit. Because these discharges are uncertain, EPA did not include CRL loads discharged to surface
waters via groundwater when modeling pollutant loadings and resulting exposure and health effects.
4.2 Analysis of Exposures to Air Pollutants from Steam Electric Power Plants
EPA analyzed air pollutant exposures22 across all communities potentially affected by the final rule to
evaluate whether communities with EJ concerns experience differential, and potentially disproportionate,
and adverse exposures, compared to relevant comparison population groups, under the baseline and the
final rule. The analysis focuses on PM2.5 and ozone exposures23 from emissions from the steam electric
power plants regulated under the final rule. EPA's approach to this analysis considered the provisions of
the final rule, as well as the nature of known and potential exposures and impacts. As the final rule
regulates steam electric power plants across the U.S., which typically have tall stacks and thus disperse
emissions over large distances, it was appropriate to conduct a national-scale distributional analysis of
PM2.5 and ozone exposures. Using modeled baseline and policy PM2.5 and ozone air quality surfaces, EPA
22 The term "exposure" is used here to describe estimated PM2.5and ozone concentrations, not individual dosage.
23 Air quality surfaces used to estimate exposures are based on 12-kilometer x 12-kilometer grids. More information
on air quality modeling can be found in Chapter 8 of the BCA (U.S. Environmental Protection Agency. (2024a).
Benefit and Cost Analysis for Supplemental Effluent Limitations Guidelines and Standards for the Steam Electric
Power Generating Point Source Category. (821-R-24-006).).
33
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Section 4—Analysis of the Distribution of Pollutant Exposures
analyzed changes in PM2.5 and ozone concentrations resulting from the emission changes projected by
the Integrated Planning Model (IPM)24 to occur under the final rule as compared to the baseline,
characterizing average and distributional exposures both prior to and following implementation in 2030.
Population characteristics considered in the distributional analysis were race, ethnicity, educational
attainment, poverty status, linguistic isolation, age, and sex (Table 10).25
Table 10. Population Characteristics Included in the Ozone and PM2.5 Distributional Analyses
Demographic
Characteristics
Description
Race
Asian; American Indian; Black; White
Ethnicity
Hispanic; Non-Hispanic
Educational Attainment
Over age 24 with/without a high school diploma
Poverty Status
Above /below 200% of the poverty line; Above/below the poverty line
Linguistic Isolation
Speaks/does not speak English "very well or better"; Speaks/does not speak English
less than "well or better"
Age
Children (0-17); Adults (18-64); Older Adults (65-99)
Sex
Female; Male
Important caveats of this analysis include:
• PM2.5 and ozone concentration changes associated with the final rule are relatively small in
magnitude. As a result, the potential for the final rule to mitigate or exacerbate existing disparities
among demographic groups is small.
• Although several future years were assessed for health benefits associated with this final rulemaking,
there was variability in high year-to-year PM2.5 and ozone concentration change across modeled
future years. Only 2030 is analyzed for air pollutant distributional implications because 2030 is the
24 As discussed in greater detail in U.S. Environmental Protection Agency. (2018). Documentation for EPA's Power
Sector Modeling Platform v6 Using the Integrated Planning Model. 1200 Pennsylvania Avenue, NW, Washington D.C.
20460, IPM is a comprehensive electricity market optimization model that can evaluate the impacts of regulatory
actions affecting the power sector within the context of regional constraints such as environmental, demand, and
other operational constraints. It uses a long-term dynamic linear programming framework that simulates the
dispatch of generating capacity to achieve a demand-supply equilibrium on a seasonal basis and by region. The
model computes optimal capacity that combines short-term dispatch decisions with long-term investment
decisions. IPM runs under the assumption that electricity demand must be met and maintains a consistent
expectation of future load. IPM outputs include the air emissions resulting from the simulated generation mix. Refer
to the Regulatory Impact Analysis (RIA) report for more details on the IPM model runs (U.S. Environmental
Protection Agency. (2024c). Regulatory Impact Analysis for Supplemental Effluent Limitations Guidelines and
Standards for the Steam Electric Power Generating Point Source Category. (821-R-24-007).).
25 Population projections stratified by race/ethnicity, age, and sex are based on economic forecasting models
developed by Woods & Poole. (2015). Complete Demographic Database, https://www.woodsandpoole.com/. The
Woods and Poole database contains county-level projections of population by age, sex, and race out to 2050,
relative to a baseline using the 2010 Census data. Population projections for all U.S. counties are determined
simultaneously to consider patterns of economic growth and migration. County-level estimates of population
percentages within the poverty status and educational attainment groups were derived from 2015 to 2019 five-year
average ACS estimates. More information can be found in Appendix J of the BenMAP-CE user's manual
(https://www.epa.gov/benmap/benmap-ce-manual-and-appendices).
34
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Section 4—Analysis of the Distribution of Pollutant Exposures
nearest future year in which all affected steam electric power plants are expected to be in
compliance with the final rule.26
4.2.1 Analysis of Changes in Air Quality Across Affected Areas of the Contiguous U.S.
As IPM predicts, the final rule will lead to both decreases and increases in emissions in 2030. Given this,
to characterize changes in emissions of PM2.5 and ozone across the contiguous United States, EPA
grouped affected areas into those where air quality does not change, improves, or worsens as a result of
the final rule. As air quality changes associated with the final rule were estimated to be small, EPA used a
cutoff of changes in concentrations that were at least a ten-thousandth of each pollutant's 2023 National
Ambient Air Quality Standard (NAAQS) (+/- 0.007 ppb of ozone and 0.0012 |ag/m3 of PM2.5) to define
"changing" air quality.
In 2030, 365 million people are predicted to live in the contiguous United States. Applying the groupings
and definition of changing air quality, the results of the IPM analysis show that, under the final rule,
approximately 60 percent and 50 percent of the U.S. population, respectively, resides in areas predicted
to experience changes in ozone and PM2.5 concentrations compared to the baseline (Figure 1). In the
areas where air quality changes are predicted under the final rule, 91 percent (202.5 million) and
83 percent (140.8 million) of the population, respectively, is predicted to experience air quality
improvements for ozone and PM2.5 compared to the baseline (Figure 1). Additionally, in the areas where
air quality changes are predicted under the final rule, 9 percent (20.5 million) and 16 percent
(27.3 million) of the population, respectively, is predicted to experience worsening air quality for ozone
and PM2.5 compared to the baseline (Figure 1). EPA notes that ozone and PM2.5 changes under the final
rule in areas experiencing worsening air quality are predicted to be small compared to the baseline,
averaging approximately 0.06 ppb for ozone and 0.00 |ag/m3 for PM2.5. Additionally, while increases in
PM2.5 concentrations under the final rule are predicted for a nontrivial number of people in 2030, EPA
notes that increases in PM2.5 concentrations in later modeled future year scenarios not included in this
analysis (2035, 2040, 2045, and 2050) occur in substantially fewer areas.
Area Ozone orPM
Contiguous U.S. Ozone
PM2.5
Not Changing Ozone
PM2.5
Changing Ozone
PM2.5
Improving Ozone
PM2.5
Worsening Ozone
PM2.5
ll
OM 50 M 100M 1S0M 200M 2S0M 3COM 350M
Population Count
Figure 1. Number of People in the Contiguous U.S. Residing in Areas with Not Changing, Changing,
Improving, and Worsening Modeled Ozone and PM2.5 Concentrations in 2030
26 This differs from the analyses performed in the RIA which use 2035 as the compliance year.
35
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Section 4—Analysis of the Distribution of Pollutant Exposures
4.2.2 Distribution of Ozone Exposures in Communities with Predicted Changes in Air Quality
For areas with predicted changes in ozone concentrations under the final rule, EPA conducted a
distributional analysis to determine whether population groups of concern experience differential, and
potentially disproportionate, and adverse exposures to ozone relative to their relevant comparison
population groups under the baseline and whether such differential exposures among population groups
of concern are mitigated, exacerbated, or created under the final rule.
As described in Chapter 8 of the BCA, higher ozone exposure is associated with a wide range of adverse
health effects, including premature mortality; respiratory effects, including increases in hospital
admissions and emergency room visits, asthma onset and symptom exacerbation, allergic rhinitis (hay
fever) symptoms; cardiovascular and nervous system effects; and reproductive and developmental
effects (U.S. EPA, 2024a). Thus, reducing exposure to ozone can provide both health and economic
benefits, whose significance may depend on socioeconomic factors (e.g., susceptibility or vulnerability
according to income or race/ethnicity, access to healthcare).
Figure 2 is a map of the areas with predicted changes in ozone concentrations under the final rule in
2030. The map shows areas in which the warm season (April - September) MDA8 ozone concentrations
improve (shown in blue) or worsen (shown in red) - by at least +/- 0.007 ppb - under the final rule.
Improving
Worsening
Figure 2. Map of 12-km Grid Cells with Modeled Changes in MDAS Warm Season Ozone
Concentrations Improving or Worsening by at Least +/-0.007 ppb in 2030
In areas shown as having predicted improvements in air quality in 2030, decreases in ozone are driven by
the net reduction in regional NOxemissions from the steam electric power generating sector as a result of
the final rule. In areas shown as having predicted worsening air quality in 2030, increases in ozone are the
result of a relatively small number of sources with predicted increases in NO. emissions under the final
rule due to IPM-projected changes in the future dispatch of certain electricity generation units after
promulgation of the final rule.
36
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Section 4—Analysis of the Distribution of Pollutant Exposures
Comparing the baseline concentrations of MDA8 ozone in areas with predicted changing ozone
concentrations under the final rule to the baseline concentrations of MDA8 ozone in areas with no
predicted change in ozone concentrations, EPA found that areas not affected by ozone changes from the
final rule have, on average, higher baseline MDA8 ozone concentrations (Figure 3). Additionally, the areas
expected to experience worsening ozone concentrations under the final rule have lower baseline average
ozone concentrations than any other group (Figure 3). As the population in areas with changing ozone
concentrations under the final rule is nearly identical to the population in areas with improving ozone
concentrations under the final rule, the two dots are next to one another in Figure 3.
9 Contiguous U.S.
350M-
300M-
250M-
c
o
^ Changing
Reference £ 2Q0M.
O Improving
(0-99) |
a
150M-
Not Changing Q
100M-
50M-
OM
^Worsening
38 39 40 41 42 43
Ozone (ppb)
Figure 3. Baseline MDA8 Ozone Concentrations and Population Counts in Areas with Not Changing,
Changing, Improving, and Worsening Modeled Ozone Concentrations in 2030.
To determine whether disparities in exposure were present under the baseline and whether they were
mitigated, exacerbated, or created by the final rule, EPA modeled average baseline warm season MDA8
ozone concentrations and MDA8 ozone concentration changes under the final rule across population
groups of concern compared to the overall reference group (labeled "Reference [0-99]") and their
relevant comparison groups (e.g., White [non-Hispanic] for racial or ethnic groups). Different areas, air
quality scenarios, and methods of showing results are presented across the columns in Table ll27. More
information on the columns in Table 11 can be found in Table 12.
27 Numbers in Table 11 extend two and three places beyond the decimal point due to the small magnitude of air
quality changes; this is not intended to convey confidence in EPA's ability to estimate air quality exposures to that
level of exactness.
37
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 11. Modeled MDA8 Ozone Concentrations (ppb) Across Area Categories and Selected Population Groups in 2030
Population
Groups
Reference
Population (Ages)
<2 g> = £ |
¦— CUD qj
in = 60 < E
>. c (0c=-= u •-
u .E cUf.E := >
:= M "Jlo u6" too o o
o r- ^ r- m i_ r* £_
< £ •*
> M 60 M
c < 60 <
QJ ^
~ u .E e .E .e .E
ai>=> c>u>
IA « « r « «
™ >w l/l w VI U w u ^ u . n u
O E .E (B . „ B (O i- Q.1- U >- o? >-
o_ to u u 5?(c coo. .a. .a. .a.
. -C -?OB24; HS or more)
40.01
40.00
0.02
0.04
38.23
38.20
0.02
0.06
38.28
38.25
0.03
0.09
37.66
37.72
-0.06
-0.15
Less educated (>24; no HS)
40.70
40.69
0.01
0.03
38.17
38.15
0.02
0.06
38.25
38.22
0.03
0.08
37.56
37.61
-0.06
-0.15
>200% of the poverty line (0-99)
Poverty
Status
40.19
40.18
0.02
0.04
38.33
38.31
0.02
0.06
38.39
38.36
0.03
0.09
37.67
37.73
-0.06
-0.15
<200% of the poverty line (0-99)
40.20
40.18
0.01
0.03
38.05
38.03
0.02
0.06
38.09
38.06
0.03
0.08
37.65
37.71
-0.06
-0.15
>Poverty line (0-99)
40.19
40.18
0.02
0.04
38.27
38.25
0.02
0.06
38.33
38.30
0.03
0.09
37.67
37.72
-0.06
-0.15
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 12. Additional Information on the Column Headers Used in Table 11 and Table 13
Area Category
Description
1. Contiguous U.S.
Baseline
Average exposure burden under the baseline scenario averaged across the population
in the entire contiguous U.S.
2. Contiguous U.S.
Policy
Average exposure burden under the policy scenario averaged across the population in
the entire contiguous U.S.
3. Changes in
Contiguous U.S.
Average exposure changes when moving from the baseline to the policy scenario
averaged across the population in the entire contiguous U.S.
4. % Change in
Contiguous U.S.
Average exposure changes as a percent of baseline exposure when moving from the
baseline to the policy scenario averaged across the population in the entire contiguous
U.S.
5. Baseline Areas
Changing
Average exposure burden under the baseline scenario averaged across the population
experiencing a change of at least 1/10,000th of the 2023 NAAQS
6. Policy Areas
Changing
Average exposure burden under the policy scenario averaged across the population
experiencing a change of at least 1/10,000th of the 2023 NAAQS
7. Changes in Policy
Areas Changing
Average exposure changes when moving from the baseline to the policy scenario
averaged across the population experiencing an air quality change of at least 1/10,000th
of the 2023 NAAQS
8. % Changes in
Changing Areas
Average exposure changes as a percent of baseline exposure when moving from the
baseline to the policy scenario averaged across the population experiencing an air
quality change of at least 1/10,000th of the 2023 NAAQS
9. Baseline Areas
Improving
Average exposure burden under the baseline scenario averaged across the population
experiencing an air quality improvement of at least 1/10,000th of the 2023 NAAQS
10. Policy Areas
Improving
Average exposure burden under the policy scenario averaged across the population
experiencing an air quality improvement of at least 1/10,000th of the 2023 NAAQS
11. Changes in
Improving Areas
Average exposure changes when moving from the baseline to the policy scenario
averaged across the population experiencing an air quality improvement of at least
1/10,000th of the 2023 NAAQS
12. % Changes in
Improving Areas
Average exposure changes as a percent of baseline exposure when moving from the
baseline to the policy scenario averaged across the population experiencing an air
quality improvement of at least 1/10,000th of the 2023 NAAQS
13. Baseline Areas
Worsening
Average exposure burden under the baseline scenario averaged across the population
experiencing an air quality worsening of at least 1/10,000th of the 2023 NAAQS
14. Policy Areas
Worsening
Average exposure burden under the policy scenario averaged across the population
experiencing an air quality worsening of at least 1/10,000th of the 2023 NAAQS
15. Changes in
Worsening Areas
Average exposure changes when moving from the baseline to the policy scenario
averaged across the population experiencing an air quality worsening of at least
1/10,000th of the 2023 NAAQS
16. % Changes in
Worsening Areas
Average exposure changes as a percent of baseline exposure when moving from the
baseline to the policy scenario averaged across the population experiencing an air
quality worsening of at least 1/10,000th of the 2023 NAAQS
17. Areas Not
Changing
Average exposure burden under the areas not changing or changing by less than
1/10,000th of the 2023 NAAQS
Based on the results of the analysis, EPA determined that the final rule leads to small changes in MDA8
ozone concentrations. Across the contiguous United States, the average total warm-season MDA8 ozone
concentrations under the baseline and final rule (shown in columns 1 and 2 in Table 11) are similar when
averaged across the lower 48 states. The absolute magnitude of these changes is less than 0.06 ppb, or
about a 0.1-0.2 percent change from baseline concentrations, as shown in the first and second gray-
39
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Section 4—Analysis of the Distribution of Pollutant Exposures
shaded columns in Table 11. Columns 5-8 in the table show MDA8 concentrations in changing areas,
which includes both areas in which MDA8 ozone concentrations improve (shown in columns 9-12) and
areas in which they worsen (shown in columns 13-16).28 Column 17 shows MDA8 ozone concentrations
by population group in the areas that are not affected by the final rule.
Given that baseline MDA8 ozone concentrations for the final rule are similar to those for other recent
rulemakings (e.g., the regulatory impact analysis [RIA] for the proposed federal implementation plan on
ozone transport for the 2015 ozone NAAQS (U.S. EPA, 2022) and areas changing can be more
meaningfully discussed by directly addressing improving and worsening areas, columns 1-8 in Table 11
are not discussed in detail here.29
Although there are differences in baseline exposures across population groups and area categories, the
absolute and relative changes across population groups of concern in improving and worsening areas
under the final rule are similar (shown in columns 11-12 and 15-16 in Table 11). This suggests that MDA8
ozone exposure disparities are not created, exacerbated, or mitigated under the final rule as compared to
the baseline.
To further evaluate distributional impacts, EPA evaluated differences in MDA8 ozone exposures across
the various population groups of concern compared to their relevant comparison groups. Figure 4 shows
the results. For total exposures (columns 1, 2, 4, 5, 7, 8, 10, 11, and 13 in the figure), colored lines to the
right and left of the black line indicate differentially high and low exposures in the population group of
concern relative to the comparison group. For exposure changes (columns 3, 6, 9, and 12), colored lines
to the right and left of the black line indicate differentially large and small exposure reductions in the
population group of concern relative to the comparison group.
28 In other EJ and benefits assessments, air quality improvements have been shown as positive numbers. In keeping
with this precedent, worsening air quality concentrations are presented as negative numbers here.
29 For a discussion, see the Regulatory Impacts Analysis for the Proposed Federal Implementation Plan Addressing
Regional Ozone Transport for the 2015 Ozone NAAQS (U.S. Environmental Protection Agency. (2022). Regulatory
Impact Analysis for Proposed Federal Implementation Plan Addressing Regional Ozone Transport for the 2015 Ozone
National Ambient Air Quality Standard. (EPA-452/D-22-001). Retrieved from
https://www.epa.gov/system/files/documents/2022-03/transport_ria_proposal_fip_2015_ozone_naaqs_2022-
02.pdf)
40
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Section 4—Analysis of the Distribution of Pollutant Exposures
Population
Groups
1. Contiguous 2. Contiguous
U.S. Baseline U.S. Policy
3. Changes in | 4. Baseline 5. Policy 6. Changes in 7. Baseline
Contiguous Areas Areas Areas Areas
U.S. Changing Changing Changing Improving
8.Policy Areas
Improving
9. Changes in 10. Baseline 11. Policy
Improving Areas Areas
Areas Worsening Worsening
12. Changes
in Worsening '
Areas
13. Areas Not
Changing
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0 20 40 60 0 20 40 60 0.00 0.05 |0 20 40 0 20 40
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0.0 0.1 0 20 40 0 20 40 0.00 0.05 0 20 40 0 20 40 -0.01 0 20 40 60
Ozone (ppb) Ozone (ppb) Ozone (ppb) Ozone (ppb) Ozorte (ppb) Ozone (ppb) Ozone (ppb) Ozone (ppb)
Figure 4. Distribution of Modeled MDA8 Ozone Concentrations Across Area Categories and Selected Population Groups in 2030
41
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Section 4—Analysis of the Distribution of Pollutant Exposures
4.2.3 Distribution ofPM2.s Exposures in Communities with Predicted Changes in Air Quality
In areas with predicted changes in PM2.5 concentrations under the final rule, EPA conducted a
distributional analysis to determine whether population groups of concern experience differential, and
potentially disproportionate, and adverse exposures to annual average PM2.5 concentrations as compared
to their relevant comparison groups under the baseline and whether such differential exposures among
communities with EJ concerns are mitigated, exacerbated, or created under the final rule.
As described in Chapter 8 of the BCA, higher PM2.5 exposure is associated with a wide range of adverse
health effects, including:
• Premature mortality.
• Cardiovascular effects such as heart attacks, strokes, and increased hospital admissions or emergency
department visits due to cardiovascular problems.
• Respiratory effects, including hospital admissions or emergency department visits, and onset or
exacerbation of asthma symptoms, lung cancer, and allergic rhinitis (hay fever) symptoms.
• Alzheimer's disease.
• Parkinson's disease.
• Other nervous system effects (e.g., autism, cognitive decline, dementia).
• Metabolic effects (e.g., diabetes).
• Reproductive and developmental effects (e.g., low birth weight, pre-term births).
• Cancer, mutagenicity, and genotoxicity effects. (U.S. EPA, 2024a)
Thus, reducing exposure to PM2.5 provides both health and economic benefits on populations, with the
significance of the benefits depending on socioeconomic factors (e.g., susceptibility or vulnerability
among subgroups according to income or race/ethnicity, access to healthcare). Figure 5 is a map of the
areas with predicted changes in average annual PM2.5 concentrations under the final rule in 2030. The
map shows areas in which the average annual PM2.5 concentrations improve (shown in blue) or worsen
(shown in red)-by at least +/- 0.0012 |ag/m3 under the final rule.
42
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Section 4—Analysis of the Distribution of Pollutant Exposures
Figure 5. Map of 12-km Grid Cells with Modeled Changes in Average Annual PM2.5 Concentrations
Improving or Worsening by at Least +/-0.0012 pg/m3 in 2030
EPA found that changes in PM2.5 emissions are driven by changes in the types of steam EGUs that are
being dispatched in any given future year. In certain out-years, higher-emitting units may be dispatched
to meet generation needs, which could result in PM-m, emissions increases in those particular years.
Figure 6 shows the average annual baseline PM2.5 concentrations for the areas in the contiguous United
States that are affected by the final rule.
350M-
^ Contiguous U.S.
300M-
Reference
(0-99)
Population
25QM-
200M-
150M-
100M-
50M-
QM
£ Changing
Q Improving
Not Changing £
Worsening A
1 1 1
6.7 6.8 6.9
1 1 1 1 1 1
7.0 7.1 7.2 7.3 7.4
PM;.5 (ng/m3)
Figure 6. Baseline Average Annual PM2.5 Concentrations and Population Counts in Areas with Not
Changing, Changing, Improving, and Worsening Modeled PM2.5 concentrations in 2030
43
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Section 4—Analysis of the Distribution of Pollutant Exposures
Comparing baseline average annual PM2.5 concentrations in areas with predicted change in PM2.5
concentrations under the final rule to baseline average annual PM2.5 concentrations in areas with no
predicted change in PM2.5 concentrations under the baseline, EPA found that, as with MDA8 ozone
concentrations, the baseline average annual PM2.5 concentrations in areas with no predicted change were
higher than in areas with a predicted change. Unlike with MDA8 ozone concentrations, areas predicted to
experience not changing or worsening PM2.5 concentrations under the final rule had higher baseline
average annual PM2.5 concentrations than all other area categories analyzed. However, EPA notes that
very few areas are predicted to have increased average annual PM2.5 concentrations due to the final rule
in modeled future years after 2030. Additionally, average annual PM2.5 concentration increases in these
areas are very small and round to 0.00 |ag/m3. To determine whether differential exposures among
population groups of concern were present under the baseline and whether they were mitigated,
exacerbated, or created by the final rule, EPA modeled baseline annual average PM2.5 concentrations and
concentration changes across various population groups of concern. Table 13 presents the results. It is
organized in the same way as Table 11, with rows for population groups and columns for areas, air quality
scenarios, and methods.30
30 Numbers in Table 13 extend two and three places beyond the decimal point due to the small magnitude of air
quality changes; this is not intended to convey confidence in EPA's ability to estimate air quality exposures to that
level of exactness.
44
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 13. Modeled Average Annual PM2.5 Concentrations3 (ng/m3) Across Area Categories and Selected Population Groups in 2030b
Population
Groups
_ to J
= => ¦; => <
Population (Ages)
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Reference (0-99)
7.11
7.11
0.00
0.01
6.77
6.77
0.00
0.03
6.67
6.66
0.00
0.04
7.33
7.33
0.00
-0.03
7.41
Race
White (0-99)
7.02
7.02
0.00
0.01
6.65
6.65
0.00
0.03
6.54
6.54
0.00
0.04
7.21
7.21
0.00
-0.03
7.33
American Indian (0-99)
6.66
6.66
0.00
0.01
6.49
6.49
0.00
0.03
6.38
6.38
0.00
0.04
7.39
7.39
0.00
-0.03
6.74
Asian (0-99)
7.69
7.69
0.00
0.01
7.15
7.15
0.00
0.03
7.05
7.05
0.00
0.04
7.82
7.82
0.00
-0.02
8.07
Black (0-99)
7.35
7.35
0.00
0.02
7.19
7.19
0.00
0.03
7.08
7.08
0.00
0.04
7.73
7.73
0.00
-0.02
7.56
Ethnicity
Non-Hispanic (0-99)
6.89
6.89
0.00
0.01
6.73
6.73
0.00
0.03
6.63
6.62
0.00
0.04
7.28
7.29
0.00
-0.03
7.05
Hispanic (0-99)
7.91
7.91
0.00
0.01
6.98
6.98
0.00
0.03
6.87
6.86
0.00
0.04
7.60
7.60
0.00
-0.02
8.36
Educational
Attainment
More educated (>24; HS or more)
7.02
7.02
0.00
0.01
6.74
6.74
0.00
0.03
6.64
6.63
0.00
0.04
7.31
7.31
0.00
-0.03
7.26
Less educated (>24; no HS)
7.45
7.45
0.00
0.01
6.86
6.86
0.00
0.03
6.76
6.75
0.00
0.04
7.35
7.35
0.00
-0.03
7.87
Poverty
Status
>200% of the poverty line (0-99)
7.05
7.05
0.00
0.01
6.74
6.74
0.00
0.03
6.64
6.64
0.00
0.04
7.31
7.31
0.00
-0.03
7.32
<200% of the poverty line (0-99)
7.25
7.25
0.00
0.01
6.84
6.84
0.00
0.03
6.73
6.73
0.00
0.04
7.38
7.38
0.00
-0.03
7.58
>Poverty line (0-99)
7.08
7.08
0.00
0.01
6.75
6.75
0.00
0.03
6.64
6.64
0.00
0.04
7.32
7.32
0.00
-0.03
7.37
-------
Section 4—Analysis of the Distribution of Pollutant Exposures
Based on the results of the analysis, EPA determined that the final rule would lead to small average
annual PM2.5 concentration improvements. Average total annual PM2.5 concentrations across the entire
contiguous U.S. under the baseline and the final rule (columns 1 and 2 in Table 13) are similar when
averaged across the lower 48 states. The absolute magnitude of these changes is very small and rounds
to 0.00 |ag/m3, with estimated changes less than a 0.03 percent change from baseline concentrations, as
shown in Table 13. Columns 5-8 in the table show average annual PM2.5 concentrations in areas with
predicted changes under the final rule, which includes both areas in which average annual PM2.5
concentrations improve (columns 9-12) or worsen (columns 13-16).31 Column 17 shows average annual
PM2.5 concentrations by population group in areas not affected by the final rule. Because average annual
PM2.5 concentrations in the baseline for the final rule are similar to those in other recent rulemakings
(e.g., the RIA for the Reconsideration of the NAAQS for PM) and areas changing can be more meaningfully
discussed by directly considering improving and worsening areas, columns 1-8 in Table 13 are not
discussed in detail here. As with MDA8 ozone concentrations, EPA found that there are differences in
baseline average annual PM2.5 exposures across population groups and area categories (Table 13). Also,
as with MDA8 ozone, absolute and relative changes in average annual PM2.5 exposures across population
groups in improving and worsening areas are similar (columns 11-12 and 15-16 in Table 13). This suggests
that average annual PM2.5 exposure disparities are not created, exacerbated, or mitigated under the final
rule compared to the baseline. To further evaluate distributional impacts, EPA evaluated differences in
average annual PM2.5 exposures between the various population groups of concern and their relevant
comparison groups. Figure 7 presents the results. Colored lines to the right and left of the black line of
total exposure distributions (columns 1, 2, 4, 5, 7, 8, 10, 11, and 13) indicate differentially high and low
exposures in the population group of concern compared to the comparison group. Colored lines to the
right and left of the black line of exposure changes (columns 3, 6, 9, and 12 in Figure 7) indicate
differentially large and small exposure reductions in the population group of concerns compared to the
comparison group.
31 In other distributional and benefits assessments, air quality improvements have been shown as positive numbers.
In keeping with this precedent, worsening air quality concentrations are presented as negative numbers here.
46
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Section 4—Analysis of the Distribution of Pollutant Exposures
Population
Groups
1. Contiguous 2. Contiguous
U.S. Baseline U.S. Policy
7. Baseline _ „ . 9. Changes in 10. Baseline
8.Policy Areas
Areas . Improving Areas
Improving * *
Improving Areas Worsening
11. Policy
Areas
Worsening
12. Changes
in Worsening
Areas
13. Areas Not
Changing
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PMj.5 (ng/m3) PMj.s (|ig/m3) PMj.5 fag/m3) PM;., (ng/rn3) PM2.S (ng/m3) PMj.s (ng/m5) PM2,5 (ng/m3) PM2.S (ng/m3) PMj.5 (pg/m3) PM2.S ((ig/m3) PMj.s (pg/m5) PM?.S (ng/m3) PM;.5 (ng/m3)
Figure 7. Distribution of Modeled Average Annual PM2.5 Concentrations Across Area Categories and Selected Population Groups in 2030
47
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Section 4—Analysis of the Distribution of Pollutant Exposures
4.2.4 Key Findings
The results of EPA's distributional analysis of air quality impacts indicates that, under the baseline,
average annual PM2.5 and MDA8 ozone exposures are differentially higher among certain population
groups of concern relative to their relevant comparison groups (columns 1, 4, 7, 10, and 13 in Figure 4
and Figure 7). While the regulatory analysis estimating changes in average annual PM2.5 and MDA8 ozone
exposures shows increases and decreases in pollutant emissions across regions of the United States
under the final rule, these changes overall are small and do not change the distribution of air quality
impacts observed under the baseline. Therefore, EPA concludes that the air quality changes resulting
from the final rule are not expected to mitigate or exacerbate distributional disparities present under the
baseline.
4.3 Surface Water
In addition to air emissions, EPA evaluated the distribution of pollutant loadings and the environmental
and human health effects of wastewater discharges from steam electric power plants into surface waters.
EPA analyzed these impacts in the immediate and downstream reaches of surface waters receiving
wastewater discharges. The following sections provide an overview of EPA's methodology for quantifying
these impacts and discuss the distribution of these impacts among all affected communities.
4.3.1 Immediate Receiving Waters
The term "immediate receiving water" is used to describe a reach of a surface water where a discharge of
wastewater occurs.32 To evaluate impacts within immediate receiving waters, EPA used the Immediate
Receiving Water (IRW) Model which quantitatively assesses potential water quality, wildlife, and human
health impacts from estimated pollutant loadings from steam electric power plant discharges.
The IRW Model evaluates water quality impacts by calculating annual average total and dissolved
pollutant concentrations33 in the water column and sediment of immediate receiving waters. It then
compares these concentrations to specific water quality criteria values-National Recommended Water
Quality Criteria (NRWQC) and MCLs-to assess potential impacts to wildlife and human health. To evaluate
potential impacts to wildlife, the model uses the annual average pollutant concentrations in the
immediate receiving water to estimate bioaccumulation of pollutants in fish tissue of trophic level34 3 (T3)
and trophic level 4 (T4) fish.35 The model then compares these results to benchmark values-threshold
effect concentration (TEC) and no effect hazard concentration (NEHC)-to evaluate potential impacts on
exposed sediment biota and piscivorous wildlife36 that consume T3 and T4 fish, respectively. Estimated
32 The length of the immediate receiving water, as defined in the National Hydrography Dataset Plus (NHDPIus)
Version 2. See the 2024 EA for more details.
33 The pollutants modeled were arsenic, cadmium, copper, lead, mercury, nickel, selenium, thallium, and zinc.
34 A trophic level is a sequential stage in a food chain, i.e., producers (Tl), primary consumers (T2), secondary
consumers (T3), tertiary consumers (T4), and quaternary consumers (T5).
35 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 (U.S. EPA,
2020).
36 The IRW Model uses minks and eagles to represent impacts to piscivorous wildlife because they live in most of the
United Sates and their diets primarily consist of T3 and T4 fish, respectively. Referencing Hinck, J. E., Schmitt, C. J.,
Chojnacki, K. A., & Tillitt, D. E. (2009). Environmental Contaminants in Freshwater Fish and Their Risk to Piscivorous
Wildlife Based on A National Monitoring Program. Environmental Monitoring and Assessment, 152, 469-494.
https://doi.Org/https://doi.org/10.1007/sl0661-008-0331-5 , the 2015 EA states that, "Minks and eagles are
commonly used in ecological risk assessments as indicator species for potential impacts to fish-eating mammals and
birds in areas contaminated with bioaccumulative pollutants (USGS, 2008)." (U.S. Environmental Protection Agency.
48
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Section 4—Analysis of the Distribution of Pollutant Exposures
fish tissue concentrations are also used to assess human health impacts-non-cancer and cancer risks - to
human populations from consuming fish that are caught in contaminated receiving waters.37 For a more
detailed discussion of the IRW Model see the 2024 EA.
EPA used the IRW Model to evaluate these impacts from steam electric power plant discharges for 114
immediate receiving waters receiving pollutant loadings from 112 plants. The results of the analyses are
presented under baseline conditions and for each of the regulatory options. Information on the
socioeconomic characteristics38 of affected communities is included with the results from the model to
evaluate the distribution of impacts (relative to the baseline) under the final rule.
4.3.1.1 Distribution of Water Quality Impacts
Using the IRW Model, EPA compared immediate-receiving-water-specific pollutant concentrations in the
water column and sediment to benchmark values for NRWQC and MCLs. The benchmarks used for each
pollutant were the freshwater acute NRWQC, freshwater chronic NRWQC, human health water and
organism NRWQC, human health organism only NRWQC, and drinking water MCL. The comparison of
pollutant concentrations to these benchmarks enabled EPA to evaluate the potential for adverse impacts
to wildlife and human health for each immediate receiving water. For more information on the
methodology EPA used to evaluate water quality impacts, see the 2024 EA and section 4.2.1 of the 2020
EA (U.S. EPA, 2020; 2024b).
Table 14 presents the results of the IRW Model's analysis of water quality impacts. Under the baseline
and regulatory options, the table shows the socioeconomic characteristics of communities impacted by
immediate receiving waters exceeding pollutant-specific benchmark values, compared to the
socioeconomic characteristics of communities impacted by immediate receiving waters without
exceedances. This was done to assess whether, under the baseline, communities impacted by immediate
receiving waters with pollutant-specific benchmark exceedances have larger populations of low-income
individuals and people of color than impacted communities where immediate receiving waters do not
have exceedances, and whether this distribution changes under the regulatory options.
(2015a). Environmental Assessment for the Effluent Limitations Guidelines and Standards for the Steam Electric
Power Generating Point Source Category. (EPA 821-R-15-006).)
37 Non-cancer risks are evaluated for all pollutants based on a reference dose (RfD) that represents a dose that is in
general protective of human health, as opposed to a dose associated with a specific health endpoint. Cancer risks
are calculated only for arsenic, which has a cancer slope factor identified in EPA's Integrated Risk Information
System (IRIS). See Appendix E of the 2020 EA (U.S. Environmental Protection Agency. (2020). Supplemental
Environmental Assessment for Revisions to the Effluent Limitations Guidelines and Standards for the Steam Electric
Power Generating Point Source Category.).
38 To analyze the socioeconomic characteristics of communities expected to be impacted by pollutant loadings in
immediate receiving waters of steam electric power plants, EPA used the five-year (2017 to 2021) population
estimates from the U.S. Census Bureau's ACS dataset. EPA evaluated the percent of the affected population that is
low-income, defined in the ACS as the percent of the population below the poverty threshold. EPA also evaluated
the demographic characteristic of impacted communities across minority racial and ethnic categories included in the
ACS data. These racial and ethnic categories include: African American (non-Hispanic); Asian (non-Hispanic); Native
Hawaiian/Pacific Islander (non-Hispanic); American Indian/Alaska Native (non-Hispanic); Other non-Hispanic;
Hispanic/Latino.
49
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 14. Immediate Receiving Water Community Demographics by Water Quality Benchmark Exceedances under Baseline and the Regulatory Options
National
Baseline
Option A
Option B
Option C
Average
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Percent Low-Income
12.9%
6.1%
6.1%
7.9%
5.7%
7.5%
5.9%
5.4%
6.1%
Percent African American
(non-Hispanic)
12.1%
14.5%
7.2%
16.9%
7.8%
22.6%
7.7%
11.0%
9.4%
Percent American
0.6%
Indian/Alaska Native (non-
2.2%
1.2%
3.2%
1.1%
4.9%
1.1%
1.0%
1.5%
Hispanic)
Percent Asian (non-Hispanic)
5.6%
3.8%
0.9%
0.8%
2.0%
0.5%
1.9%
0.4%
1.8%
Percent Native
0.2%
Hawaiian/Pacific Islander
0.1%
0.1%
0.1%
0.1%
0.2%
0.1%
0.1%
0.1%
(non-Hispanic)
Percent Other (non-
Hispanic)
3.5%
1.5%
1.1%
1.2%
1.2%
1.1%
1.2%
1.0%
1.2%
Percent Hispanic/Latino
19.2%
7.9%
3.5%
4.3%
5.0%
5.3%
4.8%
4.5%
4.9%
Total Population
333,000,000
99,834
221,017
57,812
263,039
37,219
283,632
14,976
305,875
Count of IRW
38
76
28
86
14
100
7
107
Isoi/rce: U.S. EPA. 2024. IRW Model Results and Demographic Comparison for the EJ Analysis.
Abbreviations: IRW (immediate receiving water).
a -EPA compared pollutant concentrations in the receiving water attributed to steam electric power plant discharges to pollutant-specific water quality benchmarks to determine exceedances.
Evaluated benchmarks include freshwater acute, freshwater chronic, human health water and organism, and human health organism only National Recommended Water Quality Criteria (NRWQC);
and drinking water maximum contaminant levels (MCLs). Evaluated pollutants include arsenic, cadmium, copper, lead, mercury, nickel, selenium, thallium, and zinc. See the 2024 EA for more details
|on the analysis.
50
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Section 4—Analysis of the Distribution of Pollutant Exposures
Under the baseline, in communities near immediate receiving waters with pollutant-specific benchmark
exceedances, the percent of the population identified as African American (non-Hispanic) and American
Indian or Alaska Native (non-Hispanic) are above the national average and greater than in communities
near immediate receiving waters with no exceedances (Table 14). Additionally, in communities near
immediate receiving waters with exceedances, the percent of the population identified as Asian (non-
Hispanic), Other (non-Hispanic), and Hispanic or Latino is greater than in communities near immediate
receiving waters with no exceedances (Table 14). These results suggest that there are potential EJ
concerns under the baseline.
The results of the analysis of the regulatory options show that all options reduce the number of
immediate receiving waters with pollutant-specific benchmark exceedances and the people affected by
these exceedances compared to the baseline across all population groups of concern, helping to mitigate
potential EJ concerns observed under the baseline. Option C generates the largest reductions (Table 14).
The improvements estimated under the Option A and Option B accrue at a higher rate to some
population groups of concern than other groups, resulting in the remaining immediate receiving waters
with exceedances being concentrated among those other groups. Under Option C, the estimated
improvements accrue proportionally among all population groups of concern as the percent of the
population identified as one of these groups in communities with immediate receiving waters with
exceedances is below the national average (except for those identified as American Indian or Alaska
Native [non-Hispanic]) and the percent of the population in communities near immediate receiving
waters with no exceedances (except for those identified as African American [non-Hispanic]) (Table 14).
Improvements under Option A accrue at a higher rate among people identified as Asian (non-Hispanic),
Other (non-Hispanic) and Hispanic or Latino, reducing their representation relative to the baseline in
communities near the remaining immediate receiving waters with exceedances under Option A. The
percent of the population identified as one of these demographic groups in communities near immediate
receiving waters with exceedances decreases to less than the percent of the population in communities
near immediate receiving waters with no exceedances (Table 14). The improvements under Option A
accrue at a higher rate among people identified as low-income, African American (non-Hispanic), and
American Indian or Alaska Native (non-Hispanic) in communities near immediate receiving waters with
exceedances, increasing their representation relative to the baseline in communities near the remaining
immediate receiving waters with exceedances under Option A (Table 14). The percent of the population
identified as low-income in communities near immediate receiving waters with exceedances increases to
become greater than the percent of the of the population identified as low-income in communities near
immediate receiving waters without exceedances. Additionally, the percent of the population identified
as African American (non-Hispanic) or American Indian or Alaska Native (non-Hispanic) increases relative
to the baseline and remains greater than the national average and the percent of the population
identified as African American (non-Hispanic) or American Indian Alaska Native (non-Hispanic) in
communities near immediate receiving waters with no exceedances.
Improvements under Option B accrue at a higher rate among people identified as Asian (non-Hispanic),
Other (non-Hispanic), and Hispanic or Latino, reducing their representation relative to the baseline in
communities near the remaining immediate receiving waters with exceedances under Option B (Table
14). The percent of the population identified as one of these demographic groups in communities near
immediate receiving waters decreases to less than the percent of the population in communities near
immediate receiving waters with no exceedances. A decrease is also observed for the percent of the
population identified as Hispanic or Latino, although it remains greater than in communities near
immediate receiving waters with no exceedances. The improvements estimated under Option B accrue at
a lower rate among people identified as low-income, African American (non-Hispanic), American Indian or
Alaska Native (non-Hispanic), and Native Hawaiian or Pacific Islander (non-Hispanic) in communities near
immediate receiving waters with exceedances, increasing their representation relative to the baseline in
communities near the remaining immediate receiving waters with exceedances under Option B (Table
14). The percent of the population identified as low-income or Native Hawaiian or Pacific Islander (non-
Hispanic) in communities near immediate receiving waters with exceedances increases to become
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Section 4—Analysis of the Distribution of Pollutant Exposures
greater than the percent of the population identified as low-income or Native Hawaiian or Pacific Islander
(non-Hispanic) in communities near immediate receiving waters with no exceedances. Additionally, the
percent of the population identified as African American (non-Hispanic) or American Indian or Alaska
Native (non-Hispanic) increases relative to the baseline and remains greater than the national average
and the percent of the population identified as African American (non-Hispanic) or American Indian
Alaska Native (non-Hispanic) in communities near immediate receiving waters with no exceedances.
4.3.1.1.1 Distribution of Wildlife Impacts
Once the water quality impacts were assessed, EPA used the IRW Model to evaluate potential wildlife
impacts in immediate receiving waters. The IRW Model performs two types of analyses to evaluate
potential wildlife impacts. The first is an analysis that compares pollution concentration in sediment of
immediate receiving waters to TECs for sediment biota. For the second analysis, the IRW Model calculates
the bioaccumulation of pollutants in T3 and T4 fish tissue and compares the fish tissue concentrations to
NEHCs for minks and eagles. EPA uses the results of the two analyses to evaluate potential impacts on
wildlife from pollutant discharges to the immediate receiving waters. For more information on the
methodology EPA used to evaluate wildlife impacts see the 2024 EA and section 4.2.2 of the 2020 EA
(U.S. EPA, 2020; 2024b).
The following tables present the results of the analyses on impacts to sediment biota, mink, and eagles.
Table 15 through Table 17 present the socioeconomic characteristics of communities with immediate
receiving waters with and without sediment pollutant concentrations that exceed the TEC for sediment
biota, fish tissue concentrations that exceed the NEHC for mink, and fish tissue concentrations that
exceed the NEHC for eagles, respectively, under the baseline and regulatory options. This was done to
assess whether, under the baseline, communities impacted by immediate receiving waters with TEC and
NEHC exceedances have larger populations of low-income people individuals and people of color than
impacted communities where immediate receiving waters do not have exceedances, and whether this
distribution changes under the final rule.
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 15. Immediate Receiving Water Community Demographics by Sediment Benchmark Exceedances under Baseline and the Regulatory
Options
National
Baseline
Option A
Option B
Option C
Average
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Percent Low-Income
12.9%
7.4%
5.9%
7.4%
5.9%
6.9%
6.0%
4.6%
6.2%
Percent African
12.1%
17.6%
8.0%
17.6%
8.0%
26.1%
7.9%
18.9%
9.0%
American (non-
Hispanic)
Percent American
0.6%
3.8%
1.1%
3.8%
1.1%
6.3%
1.1%
0.9%
1.5%
Indian/Alaska Native
(non-Hispanic)
Percent Asian (non-
5.6%
0.8%
2.0%
0.8%
2.0%
0.4%
1.9%
0.3%
1.9%
Hispanic)
Percent Native
0.2%
0.1%
0.1%
0.1%
0.1%
0.2%
0.1%
0.1%
0.1%
Hawaiian/Pacific
lslander(non-
Hispanic)
Percent Other (non-
3.5%
1.2%
1.2%
1.2%
1.2%
1.1%
1.2%
1.1%
1.2%
Hispanic)
Percent
19.2%
3.2%
5.2%
3.2%
5.2%
3.8%
5.0%
4.3%
4.9%
Hispanic/Latino
Total Population
333,000,000
47,972
272,879
47,972
272,879
28,233
292,618
15,715
305,136
Count of IRW
24
90
24
90
11
103
7
107
Isoi/rce: U.S. EPA. 2024. IRW Model Results and Demographic Comparison for the EJ Analysis.
Abbreviations: IRW (immediate receiving water).
a -EPA compared pollutant concentrations in the receiving water sediment attributed to steam electric power plant discharges to pollutant-specific threshold effect concentrations
(TECs) for sediment biota to determine exceedances. Evaluated pollutants include arsenic, cadmium, copper, lead, mercury, nickel, selenium, and zinc. See the 2024 EA for more
|details on the analysis.
53
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 16. Immediate Receiving Water Community Demographics NEHC Exceedances for Eagles (Ingesting T4 Fish) under Baseline and the
Regulatory Options
National
Baseline
Option A
Option B
Option C
Average
IRW with
Exceedances3
IRW without
Exceedances3
IRW with
Exceedances3
IRW without
Exceedances3
IRW with
Exceedances3
IRW without
Exceedances3
IRW with
Exceedances3
IRW
without
Exceedanc
es3
Percent Low-Income
12.9%
7.8%
5.8%
6.9%
6.0%
6.0%
6.1%
4.9%
6.1%
Percent African
12.1%
16.6%
8.4%
11.8%
9.2%
11.8%
9.4%
13.3%
9.3%
American (non-
Hispanic)
Percent American
0.6%
4.3%
1.1%
6.1%
1.1%
12.5%
1.0%
1.1%
1.5%
Indian/Alaska Native
(non-Hispanic)
Percent Asian (non-
Hispanic)
5.6%
0.8%
1.9%
1.0%
1.9%
0.3%
1.8%
0.4%
1.8%
Percent Native
Hawaiian/Pacific
lslander(non-
Hispanic)
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
Percent Other (non-
Hispanic)
3.5%
1.2%
1.2%
1.5%
1.2%
1.0%
1.2%
1.1%
1.2%
Percent
Hispanic/Latino
19.2%
3.4%
5.1%
3.8%
5.0%
4.9%
4.9%
5.2%
4.9%
Total Population
333,000,000
42,042
278,809
28,968
291,883
13,996
306,855
12,349
308,502
Count of IRW
22
92
17
97
6
108
5
109
Isoi/rce: U.S. EPA. 2024. IRW Model Results and Demographic Comparison for the EJ Analysis.
Abbreviations: IRW (immediate receiving water); NEHC (no effect hazard concentrations); T4 (trophic level 4).
a -EPA compared fish tissue concentrations (T4) in the receiving water attributed to steam electric power plant discharges to pollutant-specific no effect hazard concentrations
(NEHCs) for eagles (ingesting T4 fish) to determine exceedances. Evaluated pollutants include arsenic, cadmium, copper, lead, mercury, nickel, selenium, and zinc. See the 2024 EAfor
more details on the analysis.
Note: EPA did not identify an NEHC value for methylmercury. EPA compared the modeled methylmercury concentrations to the total mercury NEHC, which may underestimate the
impact to wildlife.
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 17. Immediate Receiving Water Community Demographics NEHC Exceedances for Mink (Ingesting T3 Fish) under Baseline and the
Regulatory Options
National
Baseline
Option A
Option B
Option C
Average
IRW with
Exceedances3
IRW without
Exceedances3
IRW with
Exceedances3
IRW without
Exceedances3
IRW with
Exceedances3
IRW without
Exceedances3
IRW with
Exceedances3
IRW without
Exceedances3
Percent Low-Income
12.9%
7.3%
6.0%
7.3%
6.0%
6.0%
6.1%
4.9%
6.1%
Percent African
12.1%
7.8%
9.6%
7.8%
9.6%
11.8%
9.4%
13.3%
9.3%
American (non-
Hispanic)
Percent American
0.6%
6.7%
1.1%
6.7%
1.1%
12.5%
1.0%
1.1%
1.5%
Indian/Alaska Native
(non-Hispanic)
Percent Asian (non-
Hispanic)
5.6%
1.1%
1.8%
1.1%
1.8%
0.3%
1.8%
0.4%
1.8%
Percent Native
Hawaiian/Pacific
lslander(non-
Hispanic)
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
Percent Other (non-
Hispanic)
3.5%
1.5%
1.2%
1.5%
1.2%
1.0%
1.2%
1.1%
1.2%
Percent
Hispanic/Latino
19.2%
4.1%
5.0%
4.1%
5.0%
4.9%
4.9%
5.2%
4.9%
Total Population
333,000,000
26,447
294,404
26,447
294,404
13,996
306,855
12,349
308,502
Count of IRW
16
98
16
98
6
108
5
109
Isoi/rce: U.S. EPA. 2024. IRW Model Results and Demographic Comparison for the EJ Analysis.
Abbreviations: IRW (immediate receiving water); NEHC (no effect hazard concentrations); T3 (trophic level 3).
a -EPA compared fish tissue concentrations (T3) in the receiving water attributed to steam electric power plant discharges to pollutant-specific no effect hazard concentrations
(NEHCs) for minks (ingesting T3 fish) to determine exceedances. Evaluated pollutants include arsenic, cadmium, copper, lead, mercury, nickel, selenium, and zinc. See the 2024 EA for
more details on the analysis.
Note: EPA did not identify an NEHC value for methylmercury. EPA compared the modeled methylmercury concentrations to the total mercury NEHC, which may underestimate the
impact to wildlife.
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Section 4—Analysis of the Distribution of Pollutant Exposures
Across the sediment biota, eagle, and mink wildlife analyses, under the baseline, the percent of the
population identified as low-income, African American (non-Hispanic), American Indian or Alaska Native
(non-Hispanic), or Other (non-Hispanic) in communities near immediate receiving waters with pollutant-
specific benchmark exceedances is greater than the national average and/or the percent of the
population in communities near immediate receiving waters with no exceedances (Table 15-Table 17).
These results suggest that there are potential EJ concerns under the baseline.
The results of the analysis of regulatory options show that across the sediment biota, eagle, and mink
wildlife analyses, none of the options increase the number of immediate receiving waters with pollutant-
specific benchmark exceedances for sediment biota, eagle, and mink and the people affected by these
exceedances compared to the baseline across all population groups of concern, helping to mitigate
potential EJ concerns observed under the baseline (Table 15-Table 17).Option C generates the greatest
reduction in the number of immediate receiving waters with exceedances and the people affected by
these exceedances relative to the baseline (Table 15-Table 17).
Option A
In the sediment biota and mink wildlife analyses, under Option A, there is no change in the number of
immediate receiving waters with exceedances and the population potentially affected by these
exceedances relative to the baseline (Table 15 and Table 17).
For the eagle wildlife analysis, the improvements under Option A accrue at a higher rate among people
identified as low-income or African American (non-Hispanic), reducing their representation relative to the
baseline in communities near the remaining immediate receiving waters with exceedances under Option
A (Table 16). The percent of the population identified as low-income in communities with immediate
receiving waters with exceedances decreases, although it remains greater than the percent of the
population identified as low-income in communities near immediate receiving waters with no
exceedances. The percent of the population identified as African American (non-Hispanic) in communities
with immediate receiving waters with exceedances decreases so that it falls below the national average,
although it remains greater than the percent of the population identified as African American (non-
Hispanic) in communities with immediate receiving waters with no exceedances. The improvements
under Option A accrue at a lower rate to people identified as American Indian or Alaska Native (non-
Hispanic) and Other (non-Hispanic), increasing their representation relative to the baseline in
communities near the remaining immediate receiving waters with exceedances under Option A (Table
16). The percent of the population identified as American Indian or Alaska Native (non-Hispanic) increases
relative to the baseline and remains greater than the national average and the percent of the population
identified as American Indian or Alaska Native (non-Hispanic) in communities near immediate receiving
waters with no exceedances. The percent of the populations identified as Other (non-Hispanic) increases
relative to the baseline and becomes greater than the percent of the population identified as Other (non-
Hispanic) in communities near immediate receiving waters with no exceedances.
Option B
In the sediment biota wildlife analysis, the improvements under Option B accrue at a higher rate among
people identified as low-income in communities near immediate receiving waters with exceedances,
reducing their representation relative to the baseline in communities near the remaining immediate
receiving waters with exceedances under Option B (Table 15). The percent of the population identified as
low-income decreases relative to the baseline although it remains greater than the percent of the
population identified as low-income in communities near immediate receiving waters with no
exceedances. The improvements estimated under Option B accrue at a lower rate to people identified as
African American (non-Hispanic) or American Indian or Alaska Native (non-Hispanic) in communities near
immediate receiving waters with exceedances, increasing their representation relative to the baseline in
communities near the remaining immediate receiving waters with exceedances under Option B (Table
15). The percent of the population identified as African American (non-Hispanic) or American Indian
Alaska Native (non-Hispanic) increases relative to the baseline and remains greater than the national
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Section 4—Analysis of the Distribution of Pollutant Exposures
average and the percent of the population identified as African American (non-Hispanic) or American
Indian Alaska Native (non-Hispanic) in communities near immediate receiving waters with no
exceedances.
For the eagle wildlife analysis, the improvements under Option B accrue at a higher rate among people
identified as low-income or African American (non-Hispanic) in communities near immediate receiving
waters with exceedances, reducing their representation relative to the baseline in communities near the
remaining immediate receiving waters with exceedances under Option B (Table 16). The percent of the
population identified as low-income decreases relative to the baseline and becomes less than the percent
of the population identified as low-income in communities near immediate receiving waters with no
exceedances. The percent of the population identified as African American (non-Hispanic) also decreases
relative to the baseline and becomes less than the national average, although it remains greater than in
communities near immediate receiving waters with no exceedances. The improvements estimated under
Option B accrue at a lower rate to people identified as American Indian or Alaska Native (non-Hispanic) in
communities near immediate receiving waters with exceedances, increasing their representation relative
to the baseline in communities near the remaining immediate receiving waters with exceedances under
Option B (Table 16). The percent of the population identified as American Indian or Alaska Native (non-
Hispanic) increases relative to the baseline and remains greater than the national average and the
percent of the population identified as American Indian or Alaska Native (non-Hispanic) in communities
near immediate receiving waters with no exceedances.
In the mink wildlife analysis, the improvements under Option B accrue at a higher rate among people
identified as low-income or Other (non-Hispanic) in communities near immediate receiving waters with
exceedances, reducing their representation relative to the baseline in communities near the remaining
immediate receiving waters with exceedances under Option B (Table 17). The percent of the population
identified as low-income or Other (non-Hispanic) decreases relative to the baseline and becomes less
than the percent of the population identified as low-income or Other (non-Hispanic) in communities near
immediate receiving waters with no exceedances. The improvements estimated under Option B accrue at
a lower rate among people identified as African American (non-Hispanic) or American Indian or Alaska
Native (non-Hispanic), increasing their representation relative to the baseline in communities near the
remaining immediate receiving waters with exceedances under Option B (Table 17). The percent of the
population identified as African American (non-Hispanic) increases relative to the baseline and remains
greater than the percent of the population identified as African American (non-Hispanic) in communities
near immediate receiving waters without exceedances. The percent of the population identified as
American Indian or Alaska Native (non-Hispanic) also increases relative to the baseline and remains
greater than the national average and the percent of the population identified as American Indian or
Alaska Native (non-Hispanic) in communities near immediate receiving waters with no exceedances.
Option C
In the sediment biota wildlife analysis, improvements under Option C accrue at a higher rate among
people identified as low-income or American Indian or Alaska Native (non-Hispanic) in communities near
immediate receiving waters with exceedances, reducing their representation relative to the baseline in
communities near the remaining receiving waters with exceedances under Option C (Table 15). Both the
percent of the population identified as low-income and the percent of the population identified as
American Indian or Alaska Native (non-Hispanic) decrease relative to the baseline and become less than
the percent of the population identified as low-income or American Indian or Alaska Native (non-
Hispanic) in communities near immediate receiving waters with no exceedances, although the percent of
the population identified as American Indian or Alaska Native (non-Hispanic) remains greater than the
national average. The improvements estimated under Option C accrue at a lower rate among people
identified as African American (non-Hispanic) in communities near immediate receiving waters with
exceedances, increasing their representation relative to the baseline in communities near the remaining
immediate receiving waters with exceedances under Option C (Table 15). The percent of the population
identified as African American (non-Hispanic) increases relative to the baseline and remains greater than
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Section 4—Analysis of the Distribution of Pollutant Exposures
the national average and the percent of the population identified as African American (non-Hispanic) in
communities near immediate receiving waters with no exceedances.
For the eagle wildlife analysis, improvements under Option C accrue at a higher rate among people
identified as low-income, African American (non-Hispanic), or American Indian or Alaska Native (non-
Hispanic) in communities near immediate receiving waters with exceedances, reducing their
representations relative to the baseline in communities near the remaining receiving waters with
exceedances under Option C (Table 16). The percent of the population identified as low-income or
American Indian or Alaska Native (non-Hispanic) decreases relative to the baseline and becomes less than
the percent of the population identified as low-income or American Indian or Alaska Native (non-
Hispanic) in communities near immediate receiving waters with no exceedances, although the percent of
the population identified as American Indian or Alaska Native (non-Hispanic) remains greater than the
national average. The percent of the population identified as African American (non-Hispanic) decreases
relative to the baseline but remains greater than the national average and the percent of the population
identified as African American (non-Hispanic) in communities near immediate receiving waters with no
exceedances. The improvements estimated under Option C accrue at a lower rate among people
identified as Hispanic or Latino in communities near immediate receiving waters with exceedances,
increasing their representation relative to the baseline in communities near the remaining immediate
receiving waters with exceedances under Option C (Table 16). The percent of the population identified as
Hispanic or Latino increases relative to the baseline and becomes greater than the percent of the
population identified as Hispanic or Latino in communities near immediate receiving waters with no
exceedances.
In the mink wildlife analysis, the improvements under Option C accrue at a higher rate among people
identified as low-income, American Indian or Alaska Native (non-Hispanic), or Other (non-Hispanic) in
communities near immediate receiving waters with exceedances, reducing their representation relative
to the baseline in communities near the remaining receiving waters with exceedances under Option C
(Table 17). The percent of the population identified as low-income, American Indian or Alaska Native
(non-Hispanic), and Other (non-Hispanic) decreases relative the baseline and becomes less than the
percent of the population identified as one of these demographic groups in communities near immediate
receiving waters with no exceedances, although the percent of the population identified as American
Indian or Alaska Native (non-Hispanic) remains greater than the national average. The improvements
estimated under Option C accrue at a lower rate among people identified as African American (non-
Hispanic) in communities near immediate receiving waters with exceedances, increasing their
representation relative to the baseline in communities near the remaining immediate receiving waters
with exceedances under Option C (Table 17). The percent of the population identified as African
American (non-Hispanic) increases relative to the baseline and becomes greater than the national
average and remains greater than the percent of the population identified as this demographic group in
communities near immediate receiving waters with no exceedances.
4.3.1.1.2 Distribution of Human Health Impacts
After impacts to wildlife were evaluated, EPA used the fish tissue concentrations calculated by the IRW
Model to assess non-cancer and cancer risks to human populations from consuming fish caught in
contaminated immediate receiving waters. Non-cancer and cancer risks are calculated for four human
cohorts: child recreational, adult recreational, child subsistence, and adult subsistence. For more
information on the methodology EPA used to evaluate human health impacts, see the 2024 EA and
section 4.2.3 of the 2020 EA (U.S. EPA, 2020; 2024b).
Non-cancer human health risks are evaluated by comparing the cohort- and pollutant-specific daily intake
of a pollutant from fish ingestion—expressed as an average daily dose (mg/kg/day)— to cohort- and
pollutant-specific oral reference doses (RfDs). Based on these factors, in each cohort, a hazard quotient
(HQ) value is calculated for each immediate receiving water by dividing the average daily dose by the
RfDs. If an immediate receiving water has an HQ greater than one (1.0), EPA identifies it as having an
exceedance of a non-cancer human health risk.
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Section 4—Analysis of the Distribution of Pollutant Exposures
EPA evaluated cancer human health risks from arsenic by estimating a lifetime average daily dose (LADD)
and a corresponding lifetime excess cancer risk (LECR) for each cohort. EPA then compared the LECR to a
benchmark of one-in-a-million (1.00 x 106). LECRs are calculated for each immediate receiving water. If
an immediate receiving water has an LECR greater than 1.00 x 10''6, EPA identified it as having an LECR
exceedance.
Table 18 and Table 19 show the results from the distributional analysis of the IRW Model's estimated
non-cancer and cancer health impacts under the baseline and regulatory options for each cohort. This
was done to determine whether, for each cohort, communities with immediate receiving waters with
exceedances have a larger proportion of population groups of concern.
Table 18 presents the socioeconomic characteristics of communities with immediate receiving waters
with and without HQs greater than one.
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 18. Immediate Receiving Water Community Demographics by Oral RfD Exceedances under Baseline and the Regulatory Options, organized
by Life Stage and Consumer Cohort
National
Baseline
Option A
Option B
Option C
Average
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Child, Recreational Fisher
Percent Low-Income
12.9%
7.5%
5.8%
7.7%
5.9%
7.8%
6.0%
4.9%
6.1%
Percent African
12.1%
15.7%
8.2%
17.3%
8.3%
22.2%
8.5%
12.5%
9.3%
American (non-
Hispanic)
Percent American
0.6%
3.3%
1.1%
4.5%
1.1%
7.6%
1.0%
1.1%
1.5%
Indian/Alaska Native
(non-Hispanic)
Percent Asian (non-
5.6%
0.9%
2.0%
0.9%
1.9%
0.4%
1.9%
0.4%
1.8%
Hispanic)
Percent Native
0.2%
0.2%
0.1%
0.2%
0.1%
0.3%
0.1%
0.1%
0.1%
Hawaiian/Pacific
Islander (non-
Hispanic)
Percent Other (non-
3.5%
1.1%
1.3%
1.3%
1.2%
0.9%
1.3%
1.1%
1.2%
Hispanic)
Percent
19.2%
4.3%
5.0%
3.7%
5.1%
4.4%
4.9%
5.0%
4.9%
Hispanic/Latino
Total Population
333,000,000
55,285
265,566
40,284
280,567
23,522
297,329
13,194
307,657
Count of IRW
28
86
22
92
9
105
6
108
Adult, Recreational Fisher
Percent Low-Income
12.9%
7.4%
5.8%
6.8%
6.0%
5.2%
6.1%
3.9%
6.2%
Percent African
12.1%
16.0%
8.2%
11.0%
9.3%
8.9%
9.5%
10.2%
9.4%
American (non-
Hispanic)
Percent American
0.6%
3.5%
1.1%
5.8%
1.1%
13.5%
1.0%
0.7%
1.5%
Indian/Alaska Native
(non-Hispanic)
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 18. Immediate Receiving Water Community Demographics by Oral RfD Exceedances under Baseline and the Regulatory Options, organized
by Life Stage and Consumer Cohort
National
Baseline
Option A
Option B
Option C
Average
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Percent Asian (non-
5.6%
0.9%
1.9%
1.0%
1.9%
0.4%
1.8%
0.4%
1.8%
Hispanic)
Percent Native
0.2%
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
Hawaiian/Pacific
Islander (non-
Hispanic)
Percent Other (non-
3.5%
1.2%
1.2%
1.4%
1.2%
1.1%
1.2%
1.3%
1.2%
Hispanic)
Percent
19.2%
4.4%
5.0%
3.7%
5.0%
5.2%
4.9%
5.6%
4.9%
Hispanic/Latino
Total Population
333,000,000
52,429
268,422
30,873
289,978
12,471
308,380
10,824
310,027
Count of IRW
26
88
18
96
6
108
5
109
Child, Subsistence Fisher
Percent Low-Income
12.9%
6.3%
6.0%
7.4%
5.8%
7.4%
5.9%
5.3%
6.1%
Percent African
12.1%
15.9%
6.8%
15.2%
8.2%
21.5%
7.8%
9.7%
9.5%
American (non-
Hispanic)
Percent American
0.6%
2.2%
1.2%
3.3%
1.1%
4.7%
1.1%
0.9%
1.6%
Indian/Alaska Native
(non-Hispanic)
Percent Asian (non-
5.6%
3.7%
1.0%
0.1%
2.0%
0.5%
2.0%
0.3%
1.9%
Hispanic)
Percent Native
0.2%
0.1%
0.1%
0.1%
0.1%
0.2%
0.1%
0.1%
0.1%
Hawaiian/Pacific
Islander (non-
Hispanic)
Percent Other (non-
3.5%
1.9%
1.0%
1.1%
1.2%
1.1%
1.2%
0.9%
1.2%
Hispanic)
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 18. Immediate Receiving Water Community Demographics by Oral RfD Exceedances under Baseline and the Regulatory Options, organized
by Life Stage and Consumer Cohort
National
Baseline
Option A
Option B
Option C
Average
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Percent
19.2%
8.9%
3.2%
4.2%
5.1%
5.1%
4.9%
4.1%
4.9%
Hispanic/Latino
Total Population
333,000,000
94,751
226,100
58,368
262,483
39,124
281,727
16,881
303,970
Count of IRW
39
75
28
86
15
99
8
106
Adult, Subsistence Fisher
Percent Low-Income
12.9%
7.8%
5.7%
7.7%
5.8%
7.8%
6.0%
4.9%
6.1%
Percent African
12.1%
15.2%
8.1%
15.9%
8.4%
22.2%
8.5%
12.5%
9.3%
American (non-
Hispanic)
Percent American
0.6%
3.2%
1.1%
4.1%
1.1%
7.6%
1.0%
1.1%
1.5%
Indian/Alaska Native
(non-Hispanic)
Percent Asian (non-
5.6%
0.8%
2.0%
0.8%
1.9%
0.4%
1.9%
0.4%
1.8%
Hispanic)
Percent Native
0.2%
0.1%
0.1%
0.1%
0.1%
0.3%
0.1%
0.1%
0.1%
Hawaiian/Pacific
Islander (non-
Hispanic)
Percent Other (non-
3.5%
1.2%
1.2%
1.2%
1.2%
1.0%
1.2%
1.1%
1.2%
Hispanic)
Percent
19.2%
5.2%
4.8%
3.3%
5.1%
4.4%
4.9%
5.0%
4.9%
Hispanic/Latino
Total Population
333,000,000
62,762
258,089
43,947
276,904
23,522
297,329
13,194
307,657
Count of IRW
31
83
23
91
9
105
6
108
Isoi/rce: U.S. EPA. 2024. IRW Model Results and Demographic Comparison for the EJ Analysis.
Abbreviations: IRW (immediate receiving water); RfD (reference dose).
a -EPA compared the human health cohort's daily intake of a pollutant from ingesting fish from the receiving water to pollutant-specific oral reference doses (RfDs) to determine
exceedances. Evaluated pollutants include arsenic (inorganic), cadmium, copper, mercury (as methylmercury), nickel, selenium, and zinc. See the 2024 EAfor more details on the
[analysis.
62
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Section 4—Analysis of the Distribution of Pollutant Exposures
Child Recreational Consumption
Under the baseline, the percent of the population identified as low-income, African American (non-
Hispanic), American Indian or Alaska Native (non-Hispanic), or Native Hawaiian or Pacific Islander (non-
Hispanic) children in communities near immediate receiving waters with non-cancer HQs greater than
one is greaterthan the national average and the percent of the population of children identified as one of
these demographic groups in communities near immediate receiving waters without non-cancer HQs
greater than one (Table 18). These results suggests that there are potential EJ concerns under the
baseline.
The results of the analysis of regulatory options show that all options reduce the number of immediate
receiving waters with non-cancer HQs greater than one and the population of children affected by these
HQ exceedances compared to the baseline, helping to mitigate potential EJ concerns observed under the
baseline (Table 18). Option C generates the largest reductions (Table 18).
Improvements under Option A accrue at a lower rate among children identified as low-income, African
American (non-Hispanic), American Indian or Alaska Native (non-Hispanic), or Native Hawaiian or Pacific
Islander (non-Hispanic) in communities near immediate receiving waters with non-cancer HQs greater
than one, increasing their representation relative to the baseline in communities near the remaining
immediate receiving waters with non-cancer HQs greater than one under Option A (Table 18). The
percent of the population of children identified as low-income or Native Hawaiian or Pacific (Islander
(non-Hispanic) increases relative to the baseline and remains greater than the percent of the population
of children identified as one of these demographic groups in communities near immediate receiving
waters without non-cancer HQs greater than one. The percent of the population of children identified as
African American (non-Hispanic) or American Indian or Alaska Native (non-Hispanic) increases relative to
the baseline and remains greater than the national average and the percent of the population of children
identified as one of these demographic groups in communities near immediate receiving waters without
non-cancer HQs greater than one.
Improvements under Option B accrue at a lower rate among children identified as low-income, African
American (non-Hispanic), American Indian or Alaska Native (non-Hispanic), or Native Hawaiian or Pacific
Islander (non-Hispanic) in communities near immediate receiving waters with non-cancer HQs greater
than one, increasing their representation relative to the baseline in communities near their remaining
immediate receiving waters with non-cancer HQs greater than one under Option B (Table 18). The
percent of the population of children identified as low-income increases relative to the baseline and
remains greater than the percent of the population identified as this demographic group in communities
near immediate receiving waters without non-cancer HQs greater than one. The percent of the
population of children identified as Native Hawaiian Pacific Islander (non-Hispanic) increases relative to
the baseline and becomes greater than the national average and remains greater than the percent of the
population of children identified as this demographic group in communities near immediate receiving
waters without non-cancer HQs greater than one. Lastly, the percent of the population of children
identified as African American (non-Hispanic) or American Indian or Alaska Native (non-Hispanic)
increases relative to the baseline and remains greater than the national average and the percent of the
population identified as one of these demographic groups in communities near immediate receiving
waters without non-cancer HQs greater than one.
Improvements under Option C accrue at a higher rate among children identified as low-income, African
American (non-Hispanic), American Indian or Alaska Native (non-Hispanic), or Native Hawaiian or Pacific
Islander (non-Hispanic) in communities near immediate receiving waters with non-cancer HQs greater
than one, reducing their representation relative to the baseline in communities near the remaining
immediate receiving waters with non-cancer HQs greater than one under Option C (Table 18). The
percent of the population of children identified as one of these demographic groups decreases relative to
the baseline, although the percent of the population of children identified as African American (non-
Hispanic) or American Indian or Alaska Native (non-Hispanic) remain greaterthan the national average
63
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Section 4—Analysis of the Distribution of Pollutant Exposures
and the percent of the population of children identified as African American (non-Hispanic) or American
Indian or Alaska Native (non-Hispanic) in communities near immediate receiving waters without non-
cancer HQs greater than one. The improvements estimated under Option C accrue at a lower rate to
children identified as Hispanic or Latino, increasing their representation relative to the baseline in
communities near the remaining immediate receiving waters with non-cancer HQs greater than one
under Option C (Table 18). The percent of the population of children identified as this demographic group
increases relative to the baseline and becomes greater than the percent of the population identified as
Hispanic or Latino in communities near immediate receiving waters without non-cancer HQs greater than
one.
Adult Recreational Consumption
Under the baseline, the percent of the population identified as low-income, African American (non-
Hispanic), American Indian or Alaska Native (non-Hispanic), or Native Hawaiian or Pacific Islander (non-
Hispanic) adults in communities near immediate receiving waters with non-cancer HQs greater than one
is greater than the national average and/or the percent of the population of adults identified as one of
these demographic groups in communities near immediate receiving waters without non-cancer HQs
greater than one (Table 18). This suggests that there are potential EJ concerns under the baseline. The
results of the analysis of regulatory options show that all options reduce the number of immediate
receiving waters with non-cancer HQs greater than one and the population of adults affected by these
HQ exceedances compared to the baseline across all population groups of concern, helping to mitigate
potential EJ concerns observed under the baseline (Table 18). Option C generates the largest reductions
(Table 18).
Improvements under Option A accrue at a higher rate to adults identified as low-income, African
American (non-Hispanic), or Native Hawaiian or Pacific Islander (non-Hispanic) in communities near
immediate receiving waters with non-cancer HQs greater than one, reducing their representation relative
to the baseline in communities near the remaining immediate receiving waters with non-cancer HQs
greater than one under Option A (Table 18). The percent of the population of adults identified as low-
income decreases relative to the baseline, although it remains greater than the percent of the population
of adults identified as this demographic group in communities near immediate receiving waters without
non-cancer HQs greater than one. The percent of the population of adults identified as African American
(non-Hispanic) decreases relative to the baseline and becomes less than the national average but remains
greater than the percent of the population of adults identified as this demographic groups in
communities near immediate receiving waters without non-cancer HQs greater than one. Lastly, the
percent of the population of adults identified as Native Hawaiian or Pacific Islander (non-Hispanic)
decreases relative to the baseline and becomes less than the percent of the population of adults
identified as this demographic group in communities near immediate receiving waters without non-
cancer HQs greater than one. The improvements estimated under Option A accrue at a lower rate to
adults identified as American Indian or Alaska Native (non-Hispanic) and Other (non-Hispanic), increasing
their representation relative to the baseline in communities near the remaining immediate receiving
waters with non-cancer HQs greater than one under Option A (Table 18). The percent of the population
of adults identified as American Indian or Alaska Native (non-Hispanic) increases relative to the baseline
and remains greaterthan the national average and the percent of the population of adults identified as
this demographic group in communities near immediate receiving waters without non-cancer HQs
greater than one. The percent of the population of adults identified as Other (non-Hispanic) also
increases relative to the baseline and becomes greater than the percent of the population of adults
identified as Other(non-Hispanic) in communities near immediate receiving waters without non-cancer
HQs greater than one.
Improvements under Option B accrue at a higher rate to adults identified as low-income, African
American (non-Hispanic), and Native Hawaiian or Pacific Islander (non-Hispanic) in communities near
immediate receiving waters with non-cancer HQs greater than one, reducing their representation relative
to the baseline in communities near the remaining immediate receiving waters with non-cancer HQs
64
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Section 4—Analysis of the Distribution of Pollutant Exposures
greater than one under Option B. Both the percent of the adult population identified as low-income or
Native Hawaiian or Pacific Islander (non-Hispanic) decreases relative to the baseline and becomes less
than the percent of the adult population identified as these demographic groups in communities near
immediate receiving waters without non-cancer HQs greater than one. Additionally, the percent of the
adult population identified as African American (non-Hispanic) decreases relative to the baseline and
becomes less than the national average and the percent of the adult population identified as this
demographic group in communities near immediate receiving waters without non-cancer HQs greater
than one. The improvements estimated under Option B accrue at a lower rate to adults identified as
American Indian or Alaska Native (non-Hispanic) or Hispanic or Latino, increasing their representation
relative to the baseline in communities near the remaining immediate receiving waters with non-cancer
HQs greater than one under Option B (Table 18). The percent of the adult population identified as
American Indian or Alaska Native (non-Hispanic) increases relative to the baseline and remains greater
than the national average and the percent of the adult population identified as this demographic group in
communities near immediate receiving waters without non-cancer HQs greater than one. The percent of
the adult population identified as Hispanic or Latino increases relative to the baseline and becomes
greater than the percent of the adult population identified as Hispanic or Latino in communities near
immediate receiving waters without non-cancer HQs greater than one.
Improvements under Option C accrue at a higher rate to adults identified as low-income, African
American (non-Hispanic), American Indian or Alaska Native (non-Hispanic), or Native Hawaiian or Pacific
Islander (non-Hispanic) in communities near immediate receiving waters with non-cancer HQs greater
than one, reducing their representation relative to the baseline in communities near the remaining
immediate receiving waters with non-cancer HQs greater than one under Option C (Table 18). The
percent of the adult population identified as low-income or Native Hawaiian or Pacific Islander (non-
Hispanic) decreases relative to the baseline and becomes less than the percent of the adult population
identified as one of these demographic groups in communities near immediate receiving waters without
non-cancer HQs greater than one. The percent of the adult population identified as African American
(non-Hispanic) or American Indian or Alaska Native (non-Hispanic) decreases relative to the baseline but
remains greater than the national average and the percent of the adult population identified as one of
these demographic groups in communities near immediate receiving waters without non-cancer HQs
greater than one. The improvements estimated under Option C accrue at a lower rate to adults identified
as Other (non-Hispanic) or Hispanic or Latino, increasing their representation relative to the baseline in
communities near the remaining immediate receiving waters with non-cancer HQs greater than one
under Option C (Table 18). The percent of the adult population identified as Other (non-Hispanic) or
Hispanic or Latino increases relative to the baseline and becomes greater than the percent of the adult
population identified as one of these demographic groups in communities near immediate receiving
waters without non-cancer HQ exceedances.
Child Subsistence Consumption
Under the baseline, the percent of the population identified as low-income, African American (non-
Hispanic), American Indian or Alaska Native (non-Hispanic), Asian (non-Hispanic), Other (non-Hispanic), or
Hispanic or Latino children in communities near immediate receiving waters with non-cancer HQs greater
than one is greater than the national average and/or the percent of the population of children identified
as one of these demographic groups in communities near immediate receiving waters without non-
cancer HQs greater than one (Table 18). This suggests that there are potential EJ concerns under the
baseline.
The results of the analysis of regulatory options show that all options reduce the number of immediate
receiving waters with non-cancer HQs greater than one and the number of children affected by these HQ
exceedances compared to the baseline across all population groups of concerns, helping to mitigate
potential EJ concerns observed under the baseline (Table 18). Option C generates the largest reductions
(Table 18).
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Section 4—Analysis of the Distribution of Pollutant Exposures
Improvements under Option A accrue at a higher rate to children identified as African American (non-
Hispanic), Asian (non-Hispanic), Other (non-Hispanic), and Hispanic or Latino in communities near
immediate receiving waters with non-cancer HQs greater than one, reducing their representation relative
to the baseline in communities near the remaining immediate receiving waters with non-cancer HQs
greater than one under Option A (Table 18). The percent of the population of children identified as Asian
(non-Hispanic), Other (non-Hispanic), and Hispanic or Latino decreases relative to the baseline and
becomes less than the percent of the population of children identified as one of these demographic
groups in communities near immediate receiving waters without non-cancer HQs greater than one. The
percent of the population of children identified as African American (non-Hispanic) decreases relative to
the baseline but remains greater than the national average and the percent of the population of children
identified as African American (non-Hispanic) in communities near immediate receiving waters without
non-cancer HQs greater than one. The improvements estimated under Option A accrue at a lower rate to
children identified as low-income or American Indian or Alaska Native (non-Hispanic), increasing their
representation relative to the baseline in communities near the remaining immediate receiving waters
with non-cancer HQs greater than one under Option A (Table 18). The percent of the population of
children identified as low-income increases relative to the baseline and remains greater than the percent
of the population of children identified as low-income in communities near immediate receiving waters
without non-cancer HQs greater than one. Lastly, the percent of the population of children identified as
American Indian or Alaska Native (non-Hispanic) increases relative to the baseline and remains greater
than the national average and the percent of the population of children identified as this demographic
groups in communities near immediate receiving waters without non-cancer HQs greater than one.
Improvements under Option B accrue at a higher rate to children identified as Asian (non-Hispanic), Other
(non-Hispanic), and Hispanic or Latino in communities near immediate receiving waters with non-cancer
HQs greater than one, reducing their representation relative to the baseline in communities near the
remaining immediate receiving waters with non-cancer HQs greater than one under Option B (Table 18).
The percent of the population of children identified as Asian (non-Hispanic) or Other (non-Hispanic)
decreases relative to the baseline and becomes less than the percent of the population of children
identified as one of these demographic groups in communities near immediate receiving waters without
non-cancer HQs greater than one. The percent of the population of children identified as Hispanic or
Latino also decreases but remains greater than the percent of the population of children identified as
Hispanic or Latino in communities near immediate receiving waters without non-cancer HQs greater than
one. The improvements estimated under Option B accrue at a lower rate to children identified as low-
income, African American (non-Hispanic), American Indian or Alaska Native (non-Hispanic), or Native
Hawaiian or Pacific Islander (non-Hispanic), increasing their representation relative to the baseline in
communities near the remaining immediate receiving waters with non-cancer HQs greater than one
under Option B (Table 18). The percent of the population of children identified as low-income or Native
Hawaiian or Pacific Islander (non-Hispanic) increases relative to the baseline and remains greater than
and becomes greater than the percent of the population of children identified as low-income or Native
Hawaiian or Pacific Islander (non-Hispanic) in communities near immediate receiving waters without non-
cancer HQs greater than one, respectively. The percent of the population of children identified as African
American (non-Hispanic) or American Indian or Alaska Native (non-Hispanic) increases relative to the
baseline and remains greater than the national average and the percent of the population of children
identified as one of these demographic groups in communities near immediate receiving waters without
non-cancer HQs greater than one.
Improvements under Option C accrue at a higher rate to children identified as low-income, African
American (non-Hispanic), American Indian or Alaska Native (non-Hispanic), Asian (non-Hispanic), Other
(non-Hispanic), or Hispanic or Latino in communities near immediate receiving waters with non-cancer
HQs greater than one, reducing their representation relative to the baseline in communities near the
remaining immediate receiving waters with non-cancer HQs greater than one under Option C (Table 18).
The percent of the population of children identified as low-income, Asian (non-Hispanic), Other (non-
Hispanic), or Hispanic or Latino decreases relative to the baseline and becomes less than the percent of
the population of children identified as one of these demographic groups in communities near immediate
66
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Section 4—Analysis of the Distribution of Pollutant Exposures
receiving waters without non-cancer HQ greater than one. The percent of the population of children
identified as African American (non-Hispanic) decreases relative to the baseline and becomes less than
the national average but remains greater than the percent of the population of children identified as
African American (non-Hispanic) in communities near immediate receiving waters without non-cancer
HQs greaterthan one. Lastly, the percent of the population of children identified as American Indian or
Alaska Native (non-Hispanic) decreases relative to the baseline to become less than the percent of the
population of children identified as this demographic group in communities near immediate receiving
waters without non-cancer HQs greater than one but remains greater than the national average.
Adult Subsistence Consumption
Under the baseline, the percent of the population identified as low-income, African American (non-
Hispanic), American Indian or Alaska Native (non-Hispanic), or Hispanic or Latino adults in communities
near immediate receiving waters with non-cancer HQs greater than one is greater than the national
average and/or the percent of the population of adults identified as one of these demographic groups in
communities near immediate receiving waters without non-cancer HQs greater than one (Table 18). This
suggests that there are potential EJ concerns under the baseline.
The results of the analysis of regulatory options show that all options reduce the number of immediate
receiving waters with non-cancer HQs greater than one and the number of adults affected by these HQ
exceedances compared to the baseline across all population groups of concern, helping to mitigate
potential EJ concerns observed under the baseline (Table 18). Option C generates the largest reductions
(Table 18).
Improvements under Option A accrue at a higher rate to adults identified as low-income or Hispanic or
Latino in communities near immediate receiving waters with non-cancer HQs greater than one, reducing
their representation relative to the baseline in communities near the remaining immediate receiving
waters with non-cancer HQs greater than one under Option A (Table 18). The percent of the adult
population identified as low-income or Hispanic or Latino decreases relative to the baseline. The percent
of the adult population identified as Hispanic or Latino becomes less than the percent of the adult
population identified as Hispanic or Latino in communities near immediate receiving waters without non-
cancer HQs greater than one, while the percent of the adult population identified as low-income remains
greater than the percent of the adult population identified as low-income in communities near immediate
receiving waters without non-cancer HQs greater than one. Improvements estimated under Option A
accrue at a lower rate to adults identified as African American (non-Hispanic) or American Indian or
Alaska Native (non-Hispanic), increasing their representation relative to the baseline in communities near
the remaining immediate receiving waters with non-cancer HQs greater than one under Option A (Table
20). The percent of the adult population identified as African American (non-Hispanic) or American Indian
or Alaska Native (non-Hispanic) increases relative to the baseline and remains greater than the national
average and the percent of the adult population identified as one of the demographic groups in
communities near immediate receiving waters without non-cancer HQs greater than one.
Improvements under Option B accrue at a higher rate to adults identified as Hispanic or Latino in
communities near immediate receiving waters with non-cancer HQs greater than one, reducing their
representation relative to the baseline in communities near the remaining immediate receiving waters
with non-cancer HQs greater than one under Option B (Table 18). The percent of the adult population
identified as Hispanic or Latino decreases relative to the baseline and becomes less than the percent of
the adult population identified as Hispanic or Latino in communities near immediate receiving waters
without non-cancer HQs greater than one. The improvements estimated under Option B accrue at a
lower rate to adults identified as African American (non-Hispanic), American Indian or Alaska Native (non-
Hispanic), or Native Hawaiian or Pacific Islander (non-Hispanic), increasing their representation relative to
the baseline in communities near the remaining immediate receiving waters with non-cancer HQs greater
than one under Option B (Table 18). The percent of the adult population identified as African American
(non-Hispanic) or American Indian or Alaska Native (non-Hispanic) increases relative to the baseline and
remains greater than the national average and the percent of the adult population identified as one of
67
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Section 4—Analysis of the Distribution of Pollutant Exposures
these demographic groups in communities near immediate receiving waters without non-cancer HQs
greater than one. The percent of the adult population identified as Native Hawaiian or Pacific Islander
(non-Hispanic) increases relative to the baseline and becomes greater than the national average and the
percent of the adult population identified as this demographic group in communities near immediate
receiving waters without non-cancer HQs greater than one.
Improvements under Option C accrue at a higher rate to adults identified as low-income, African
American (non-Hispanic), American Indian or Alaska Native (non-Hispanic), or Hispanic or Latino in
communities near immediate receiving waters with non-cancer HQs greater than one, reducing their
representation relative to the baseline in communities near the remaining immediate receiving waters
with non-cancer HQs greater than one under Option C (Table 18). The percent of the adult population
identified as low-income decreases relative to the baseline to become less than the percent of the adult
population identified as low-income in communities near immediate receiving waters without non-cancer
HQs greater than one. The percent of the adult population identified as Hispanic or Latino decreases
relative to the baseline but remains greater than the percent of the adult population identified as
Hispanic or Latino in communities near immediate receiving waters without non-cancer HQs greater than
one. The percent of the adult population identified as African American (non-Hispanic) also decreases
relative to the baseline and becomes less than the national average but remains greater than the percent
of the adult population identified as this demographic group in communities near immediate receiving
waters without non-cancer HQs greater than one. Lastly, the percent of the adult population identified as
American Indian or Alaska Native (non-Hispanic) decreases relative to the baseline but remains greater
than the national average and the percent of the adult population identified as this demographic groups
in communities near immediate receiving waters without non-cancer HQs greater than one.
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 19. Immediate Receiving Water Community Demographics by Lifetime Excess Cancer Risk (LECR) Exceedances Above 1.00 x 10-6 for
Arsenic under Baseline and the Regulatory Options, organized by Life Stage and Consumer Cohort
National
Baseline
Option A
Option B
Option C
Average
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances
Exceedances3
Exceedances3
Adult, Recreational Fisher
Percent Low-Income
12.9%
11.2%
6.0%
3.2%
6.1%
3.2%
6.1%
3.2%
6.1%
Percent African
12.1%
0.1%
9.7%
0%
9.6%
0%
9.6%
0%
9.6%
American (non-
Hispanic)
Percent American
0.6%
23.7%
1.0%
1.0%
1.5%
1.0%
1.5%
1.0%
1.5%
Indian/Alaska Native
(non-Hispanic)
Percent Asian (non-
5.6%
0%
1.8%
0%
1.8%
0%
1.8%
0%
1.8%
Hispanic)
Percent Native
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
0.1%
Hawaiian/Pacific
lslander(non-
Hispanic)
Percent Other (non-
3.5%
1.1%
1.2%
2.1%
1.2%
2.1%
1.2%
2.1%
1.2%
Hispanic)
Percent
19.2%
3.1%
4.9%
4.7%
4.9%
4.7%
4.9%
4.7%
4.9%
Hispanic/Latino
Total Population
333,000,000
6,973
313,878
3,763
317,088
3,763
317,088
3,763
317,088
Count of IRW
4
110
2
112
2
112
2
112
Child, Subsistence Fisher
Percent Low-Income
12.9%
10.3%
6.0%
3.2%
6.1%
5.3%
6.1%
5.3%
6.1%
Percent African
12.1%
0%
9.6%
0%
9.6%
0%
9.5%
0%
9.5%
American (non-
Hispanic)
Percent American
0.6%
0.7%
1.5%
1.0%
1.5%
0%
1.5%
0%
1.5%
Indian/Alaska Native
(non-Hispanic)
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 19. Immediate Receiving Water Community Demographics by Lifetime Excess Cancer Risk (LECR) Exceedances Above 1.00 x 10-6 for
Arsenic under Baseline and the Regulatory Options, organized by Life Stage and Consumer Cohort
National
Baseline
Option A
Option B
Option C
Average
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
IRW with
IRW without
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances3
Exceedances
Exceedances3
Exceedances3
Percent Asian (non-
5.6%
0%
1.8%
0%
1.8%
0%
1.8%
0%
1.8%
Hispanic)
Percent Native
0.2%
0.2%
0.1%
0.1%
0.1%
0%
0.1%
0%
0.1%
Hawaiian/Pacific
lslander(non-
Hispanic)
Percent Other (non-
3.5%
1.5%
1.2%
2.1%
1.2%
0%
1.2%
0%
1.2%
Hispanic)
Percent
19.2%
3.3%
4.9%
4.7%
4.9%
3.9%
4.9%
3.9%
4.9%
Hispanic/Latino
Total Population
333,000,000
5,326
315,525
3,763
317,088
1,237
319,614
1,237
319,614
Count of IRW
3
111
2
112
1
113
1
113
Adult, Subsistence Fisher
Percent Low-Income
12.9%
8.1%
6.0%
10.3%
6.0%
3.2%
6.1%
3.2%
6.1%
Percent African
12.1%
2.8%
9.8%
0%
9.6%
0%
9.6%
0%
9.6%
American (non-
Hispanic)
Percent American
0.6%
11.3%
1.0%
0.7%
1.5%
1.0%
1.5%
1.0%
1.5%
Indian/Alaska Native
(non-Hispanic)
Percent Asian (non-
5.6%
1.6%
1.8%
0%
1.8%
0%
1.8%
0%
1.8%
Hispanic)
Percent Native
0.2%
0.1%
0.1%
0.2%
0.1%
0.1%
0.1%
0.1%
0.1%
Hawaiian/Pacific
lslander(non-
Hispanic)
Percent Other (non-
3.5%
2.2%
1.2%
1.5%
1.2%
2.1%
1.2%
2.1%
1.2%
Hispanic)
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 19. Immediate Receiving Water Community Demographics by Lifetime Excess Cancer Risk (LECR) Exceedances Above 1.00 x 10-6 for
Arsenic under Baseline and the Regulatory Options, organized by Life Stage and Consumer Cohort
National
Baseline
Option A
Option B
Option C
Average
IRW with
Exceedances3
IRW without
Exceedances3
IRW with
Exceedances3
IRW without
Exceedances3
IRW with
Exceedances3
IRW without
Exceedances
IRW with
Exceedances3
IRW without
Exceedances3
Percent
Hispanic/Latino
19.2%
4.1%
4.9%
3.3%
4.9%
4.7%
4.9%
4.7%
4.9%
Total Population
333,000,000
14,767
306,084
5,326
315,525
3,763
317,088
3,763
317,088
Count of IRW
9
105
3
111
2
112
2
112
Isoi/rce: U.S. EPA. 2024. IRW Model Results and Demographic Comparison for the EJ Analysis.
Abbreviations: IRW (immediate receiving water); LECR (lifetime excess cancer risk); NA (not applicable).
a -EPA compared the human health cohort's lifetime average daily dose of the pollutant (i.e., arsenic) from fish ingestion (multiplied by the cancer slope factor) to the LECR of one-
in-a-million to determine exceedances. See the 2024 EA for more details on the analysis.
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Section 4—Analysis of the Distribution of Pollutant Exposures
Adult Recreational Consumption
Under the baseline, the percent of the population identified as low-income or American Indian or Alaska
Native (non-Hispanic) adults in communities near immediate receiving waters with arsenic LECR
exceedances than the national average and/or the percent of the population of adults identified as one of
these demographic groups in communities near immediate receiving waters without arsenic LECR
exceedances (Table 19). This suggests that there are potential EJ concerns under the baseline.
The results of the analysis show that all of the regulatory options reduce the number of immediate
receiving waters with arsenic LECR exceedances and the number of adults affected by these exceedances
relative to the baseline across all population groups of concern, helping to mitigate potential EJ concerns
observed under the baseline (Table 19). Options A, B, and C all result in the same number of reductions in
immediate receiving waters with exceedances (Table 19).
Improvements under Options A, B, and C accrue at a higher rate to adults identified as low-income,
African American (non-Hispanic), or American Indian or Alaska Native (non-Hispanic) in communities near
immediate receiving waters with exceedances, reducing their representation relative to the baseline in
communities near the remaining immediate receiving waters with exceedances under Options A, B, and C
(Table 19). The percent of the adult population identified as low-income decreases relative to the
baseline and becomes less than the percent of the adult population identified as low-income in
communities near immediate receiving waters without exceedances. The percent of the adult population
identified as African American (non-Hispanic) or American Indian or Alaska Native (non-Hispanic) also
decreases relative to the baseline and becomes less than the national average and the percent of the
adult population identified as one of these demographic groups in communities near immediate receiving
waters without exceedances. The improvements estimated under Options A, B, and C accrue at a lower
rate to adults identified as Other (non-Hispanic), increasing their representation relative to the baseline in
communities near the remaining immediate receiving waters with exceedances under Option A, B, and C
(Table 19). The percent of the adult population identified as Other (non-Hispanic) increases relative to the
baseline and becomes greater than the percent of the adult population identified as this demographic
group in communities near immediate receiving waters without exceedances.
Child Subsistence Consumption
Under the baseline, the percent of the population identified as low-income, American Indian or Alaska
Native (non-Hispanic), Other (non-Hispanic), or Native Hawaiian or Pacific Islander (non-Hispanic) children
in communities near immediate receiving waters with arsenic LECR exceedances is greater than the
national average and/or the percent of the population of children identified as one of these demographic
groups in communities near immediate receiving waters without arsenic LECR exceedances (Table 19).
This suggests that there are potential EJ concerns under the baseline.
The results of the analysis show that all of the regulatory options reduce the number of immediate
receiving waters with arsenic LECR exceedances and the number of children affected by these
exceedances relative to the baseline across all population groups of concern, helping to mitigate potential
EJ concerns observed under the baseline (Table 19). Options B and C result in the most reductions in
immediate receiving waters with exceedances (Table 19).
Improvements under Option A accrue at a higher rate to children identified as low-income or Native
Hawaiian or Pacific Islander (non-Hispanic) in communities near immediate receiving waters with
exceedances, reducing their representation relative to the baseline in communities near the remaining
immediate receiving waters with exceedances under Option A (Table 19). The percent of the population
of children identified as both of these demographic groups decreases relative to the baseline and
becomes less than the percent of the population of children identified as one of these demographic
groups in communities near immediate receiving waters without exceedances. The improvements
estimated under Option A accrue at a lower rate to children identified as American Indian or Alaska
Native (non-Hispanic) and Other (non-Hispanic), increasing their representation relative to the baseline in
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Section 4—Analysis of the Distribution of Pollutant Exposures
communities near the immediate receiving waters with exceedances under Option A (Table 19). The
percent of the population of children identified as American Indian or Alaskan Native (non-Hispanic)
increases relative to the baseline and remains greater than the national average. The percent of the
population of children identified as Other (non-Hispanic) increases relative to the baseline and remains
greater than the percent of the population of children identified as this demographic group in
communities near immediate receiving waters without exceedances.
Improvements under Options B and C accrue at a higher rate to children identified as low-income,
American Indian or Alaska Native (non-Hispanic), Other (non-Hispanic), or Native Hawaiian or Pacific
Islander (non-Hispanic) in communities near immediate receiving waters with exceedances, reducing
their representation relative to the baseline in the communities near remaining immediate receiving
waters with exceedances under Options B and C (Table 19). The percent of the population of children
identified as one of these demographic groups decreases relative to the baseline and becomes less than
the national average and/or the percent of the population of children identified as one of these
demographic groups in communities near immediate receiving waters without exceedances.
Adult Subsistence Consumption
Under the baseline, the percent of the population identified as low-income, American Indian or Alaska
Native (non-Hispanic) or Other (non-Hispanic) in communities near immediate receiving waters with
arsenic LECR exceedances is greater than the national average and/or the percent of the adult population
identified as one of these demographic groups in communities near immediate receiving waters without
arsenic LECR exceedances (Table 19). This suggests that there are potential EJ concerns under the
baseline. The results of the analysis of regulatory options show that all options reduce the number of
immediate receiving waters with arsenic LECR exceedances and the number of adults affected by these
exceedances compared to the baseline across all population groups of concern, helping to mitigate
potential EJ concerns observed under the baseline (Table 19). Options B and C generate the largest
reductions (Table 19).
Improvements under Option A accrue at a higher rate to adults identified as American Indian or Alaska
Native (non-Hispanic), or Other (non-Hispanic) in communities near immediate receiving waters with
exceedances, reducing their representation relative to the baseline in communities near the remaining
immediate receiving waters with exceedances under Option A (Table 19). The percent of the adult
population identified as American Indian or Alaska Native (non-Hispanic) decreases relative to the
baseline to become less than the national average and the percent of the adult population identified as
this demographic group in communities near immediate receiving waters without exceedances. The
percent of the adult population identified as Other (non-Hispanic) decreases relative to the baseline but
remains greater than the percent of the adult population identified as Other (non-Hispanic) in
communities near immediate receiving waters without exceedances. The improvements estimated under
Option A accrue at a lower rate to adults identified as low-income or Native Hawaiian or Pacific Islander
(non-Hispanic), increasing their representation relative to the baseline in communities near the remaining
immediate receiving waters with exceedances under Option A (Table 19). The percent of the adult
population identified as low-income increases relative to the baseline and remains greater than the
percent of the population identified as low-income in communities near immediate receiving waters
without exceedances. The percent of the adult population identified as Native Hawaiian or Pacific Islander
(non-Hispanic) also increases relative to the baseline and becomes greater than the percent of the adult
population identified as this demographic group in communities near immediate receiving waters without
exceedances.
Improvements under Options B and C accrue at a higher rate to adults identified as low-income,
American Indian or Alaska Native (non-Hispanic), Other (non-Hispanic) or Hispanic or Latino in
communities near immediate receiving waters with exceedances, reducing their representation relative
to the baseline in communities near the remaining immediate receiving waters with exceedances under
Option B and C (Table 19). The percent of the adult population identified as low-income decreases
relative to the baseline and becomes less than the percent of the adult population identified as low-
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Section 4—Analysis of the Distribution of Pollutant Exposures
income in communities near immediate receiving waters without exceedances. The percent of the adult
population identified as Other (non-Hispanic) decreases relative to the baseline but remains greater than
the percent of the adult population identified as Other (non-Hispanic) in communities near immediate
receiving waters without exceedances. The percent of the adult population identified as American Indian
or Alaska Native (non-Hispanic) also decreases relative to the baseline and becomes less than the percent
of the adult population identified as American Indian or Alaska Native (non-Hispanic) in communities near
immediate receiving waters without exceedances but remains greater than the national average. Lastly,
while the percent of the adult population identified as Hispanic or Latino increases relative to the
baseline, it remains less than the percent of the population identified as Hispanic or Latino in
communities near immediate receiving waters without exceedances.
4.3.1.1.3 Key Conclusions
Based on the results of the distributional analyses of water quality, wildlife, and human health impacts,
EPA determined that under the baseline distributional disparities were most often observed among
affected African American (non-Hispanic) or American Indian or Alaska Native (non-Hispanic) populations
when comparing the percent of the population affected in communities with immediate receiving waters
benchmark exceedances to the national average and to communities with immediate receiving waters
without benchmark exceedances. This, along with distributional disparities observed under the baseline
for other population groups of concern, indicates the presence of potential EJ concerns under the
baseline across the three analyses. Analyzing the regulatory options across the analyses, EPA found that
all the regulatory options reduced the amount of immediate receiving waters with benchmark
exceedances and the population affected by these exceedances, with Option C often generating the
largest reductions. The improvements estimated under the regulatory options accrue at different rates
depending on the population group of concern. Due to disparities under the baseline, population groups
of concern that experience improvements at a less than proportional rate were found to be represented
to a greater extent in communities near the remaining immediate receiving waters with benchmark
exceedances relative to the baseline.
4.3.2 Downstream Surface Waters
Following the approach used for the 2023 proposed rule, EPA used the D-FATE model to estimate the
concentrations of pollutants in downstream reaches of surface waters receiving steam electric power
plant discharges to support the analysis of the benefits for the final rule. EPA used these concentrations
to estimate fish tissue pollutant concentrations39 under the baseline and regulatory options. For more
information on the D-FATE model and the analysis of downstream pollutant and fish tissue
concentrations, see the BCA (U.S. EPA, 2024a).
EPA used the modeled fish tissue concentrations as inputs to evaluate human health risks to populations
consuming self-caught fish, because the Agency expects recreational and subsistence fishers (and their
household members) who consume fish caught in the downstream reaches of receiving waters of steam
electric power plant discharges to be affected by changes in fish tissue pollutant concentrations. EPA
evaluated the human health effects of exposure to three pollutants known to accumulate in fish tissue
among relevant cohorts under the baseline and regulatory options from 2025 to 2049:
• Lead exposure from fish consumption: This analysis evaluated two health endpoints from lead
exposure through recreational and subsistence fish consumption: (1) potential neurological and
cognitive impacts to children (ages 0-7) in terms of avoided intelligence quotient (IQ) point losses
from exposure to lead through recreational and subsistence fish consumption, and (2) avoided
cardiovascular disease (CVD) premature mortality in adults (ages 40-80).
39 As described in Section 4.4, EPA also used D-FATE to estimate changes in pollutant concentrations in source
waters.
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Section 4—Analysis of the Distribution of Pollutant Exposures
• Mercury exposure from fish consumption: This analysis evaluated potential neurological and
cognitive impacts to infants exposed to mercury in utero due to maternal fish consumption in terms
of avoided IQ point losses.
• Arsenic exposure from fish consumption: This analysis evaluated potential cancer risk impacts to
adults, expressed as avoided cancer cases.
As part of these analyses, EPA disaggregated health effects within cohorts by racial and ethnic population
group (White, Black, Hispanic, Asian, American Indian and Alaska Native, Other40) and by income group
(above the poverty line or below the poverty line). EPA did this to facilitate an evaluation of the
distribution of health effects within and among these groups to determine where there are differential,
and potentially disproportionate, and adverse health impacts to population groups of concern under the
baseline and regulatory options. The results of the analysis are discussed below.
4.3.2.1 Distribution of Health Impacts Among Children Exposed to Lead through Fish Consumption
As detailed in the BCA, the total avoided IQ point losses for children exposed to lead are very small,
approximately one IQ point across the entire exposed population of 1,555,558 children and under all
regulatory options (see Table 5-4 in U.S. EPA, 2024a). Given this, EPA determined that reporting small
fractional changes across racial and ethnic population groups or by income group would not be
informative. However, EPA expects children of color, low-income, and Indigenous peoples to receive
shares of the avoided IQ point losses benefits proportional to their exposure.
4.3.2.2 Distribution of Health Impacts Among Adults Exposed to Lead through Fish Consumption
As detailed in the BCA, the total number of avoided CVD deaths for all adults (age 40-80) in the scope of
the analysis across the timeframe of the analysis ranges from 0.42 avoided CVD deaths to 1.13 avoided
CVD deaths (see Table 5-7 in U.S. EPA, 2024a). Therefore, EPA determined that reporting small fractional
changes across racial and ethnic population groups or by income group would not be informative.
However, EPA expects adults of color, low-income, and Indigenous populations to receive shares of the
CVD premature mortality risk reduction proportional to their exposure.
4.3.2.3 Distribution of Health Impacts Among Infants Exposed to Mercury Through Fish
Consumption
As detailed in the BCA, the total number of avoided IQ point losses for the estimated 201,850 infants
exposed to mercury in utero from maternal fish consumption ranges from 1,190 under Option A to 1,393
under Option C (see Table 5-8 in U.S. EPA, 2024a). Table 20 presents the estimated distribution of the
total IQ point losses under the baseline and the avoided IQ point losses under each regulatory option, for
infants of subsistence and recreational fish consumers, by race and ethnic population group.
40 The "Other" category includes populations that identify as Native Hawaiian and Other Pacific Islander, some other
race alone, and two or more races, based on 2021 American Community Survey data (U.S. Census Bureau. (2022a).
American Community Survey (ACS), https://www.census.gov/programs-surveys/acs ).
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 20. Modeled Total IQ Point Losses Under the Baseline and Avoided IQ Point Losses under the Regulatory Options Among Infants of
Subsistence and Recreational Fish Consumers Exposed to Mercury in Utero, by Racial or Ethnic Population Group
Cohort Group
Race/Ethnic Group
Exposed Population3
Baseline Total IQ
Points Losses'5
Avoided IQ Point Losses
(% Across Cohort Group)
Option A Option B Option C
Subsistence
White (non-Hispanic)
7,944 (61.3%)
50,271 (53.5%)
125 (62.5%)
145 (62.8%)
146 (62.7%)
African American (non-Hispanic)
2,270 (17.5%)
15,864 (16.9%)
26 (13.2%)
30 (13.2%)
31 (13.3%)
Asian (non-Hispanic)
452 (3.5%)
5,408 (5.8%)
8 (4.0%)
9 (4.0%)
9 (4.0%)
American Indian and Alaska Native
(non-Hispanic)
48 (0.4%)
574 (0.6%)
1 (0.7%)
2 (0.7%)
2 (0.7%)
Other (non-Hispanic)
452 (3.5%)
5,410 (5.8%)
12 (5.8%)
14 (5.9%)
14 (5.9%)
Hispanic
1,796 (13.9%)
16,492 (17.5%)
27 (13.7%)
31 (13.4%)
31 (13.5%)
Recreational
White (non-Hispanic)
115,766 (61.3%)
258,337 (55.6%)
641 (64.7%)
745 (65.0%)
752 (64.9%)
African American (non-Hispanic)
33,085 (17.5%)
84,768 (18.2%)
141 (14.2%)
163 (14.2%)
165 (14.3%)
Asian (non-Hispanic)
6,582 (3.5%)
21,015 (4.5%)
31 (3.2%)
36 (3.1%)
36 (3.1%)
American Indian and Alaska Native
(non-Hispanic)
699 (0.4%)
2,229 (0.5%)
6 (0.6%)
6 (0.5%)
7 (0.6%)
Other (non-Hispanic)
6,580 (3.5%)
21,025 (4.5%)
45 (4.6%)
53 (4.6%)
53 (4.6%)
Hispanic
26,176 (13.9%)
77,157 (16.6%)
127 (12.9%)
144 (12.5%)
146 (12.6%)
Total
201,850
575,042
1,190
1,377
1,393
Source: U.S. EPA analysis, 2024.
Notes:
The exposed population for each racial/ethnic population group is presented as the number of infants exposed and (in parenthesis) the number of infants exposed as a share of the
entire cohort.
The baseline total IQ point losses for each racial/ethnic population group are presented as the total number of IQ point losses and (in parenthesis) the total number of IQ point
losses as a share of the total number of IQ point losses for the entire cohort.
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Section 4—Analysis of the Distribution of Pollutant Exposures
The results of the distributional analysis of neurological and cognitive health impacts among both infants
of mothers who are subsistence and recreational fish consumers indicates potential EJ concerns under
the baseline in terms of differential and adverse impacts to infants of mothers in population groups of
concern, compared to the White population group. Although the regulatory options generate
improvements relative to the baseline in terms of avoided IQ point losses, these improvements are small
and do not substantially change the differential baseline IQ points among infants of mother who are
subsistence and recreational fish consumers. (Table 20).
When evaluating results for the infants of mothers in the subsistence fish consumer cohort under the
baseline, a comparison of each population group's share of the cohort's total IQ point losses compared to
its share of the cohort's total exposed population shows that Hispanic, Asian (non-Hispanic), American
Indian and Alaska Native (non-Hispanic), and Other (non-Hispanic) infants' share of IQ point losses is
larger than their share of the exposed population. African American (non-Hispanic) infants' share of IQ
point losses is smaller than their share of the exposed population, with 0.6 percent less of a share of the
IQ point losses. White infants had a smaller share of IQ point losses compared to their share of the
exposed population, with 7.8 percent less of a share of the IQ point losses. The results for infants of
mothers in the recreational fish consumer cohort under the baseline shows that, for each population
group of concern, infants' share of IQ point losses is larger than their share of the exposed population.
White infants' share of IQ point losses is smaller than their share of the exposed population by 5.7
percent.
Examining the impact of the regulatory options on avoided IQ point losses among infants in the various
racial and ethnic population groups showed that for both infants of mothers in the subsistence and
recreational fish consumer cohorts, all of the regulatory options result in avoided IQ point losses,
compared to the baseline, across the racial/ethnic groups, with Option C resulting in the largest combined
avoided IQ point losses. Across all regulatory options, for infants of mothers who are subsistence
consumers, all people of color experiencing disparities under the baseline receive a share of avoided IQ
point losses that is greater than their share of the exposed population, except for Hispanic infants.
Additionally, for infants of mothers who are child recreational consumers, only American Indian or Alaska
Native (non-Hispanic) infants and Other (non-Hispanic) infants receive a share of avoided IQ point losses
that is greater than their share of the exposed population across all regulatory options. For infants of
color that experience improvements under the regulatory options in terms of avoided IQ point losses,
these improvements are small and do not substantially change the differential baseline IQ points
observed among infants under the baseline. Table 21 presents the total IQ points under the baseline and
change in avoided IQ point losses under each of the regulatory options for infants of mothers who are
subsistence and recreational fish consumers, by income group (below the poverty line or not below the
poverty line).
Table 21. Modeled Total IQ Point Losses Under the Baseline and Avoided IQ Point Losses under the
Regulatory Options Among Infants of Subsistence and Recreational Fish Consumers Exposed to
Mercury in Utero, by Income Group
Cohort Group
Income Group
Exposed
Population3
Baseline Total IQ
Point Losses'5
Option A
Option B
Option C
Child
Subsistence
Below the Poverty
Line
1,891 (14.6%)
13,925 (14.8%)
34 (16.9%)
39 (16.9%)
39 (16.9%)
Not Below the
Poverty Line
11,070 (85.4%)
80,094 (85.2%)
166 (83.1%)
192 (83.1%)
194(83.1%)
Child
Recreation
Below the Poverty
Line
27,565 (14.6%)
68,967 (14.8%)
167 (16.9%)
194(16.9%)
196 (16.9%)
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 21. Modeled Total IQ Point Losses Under the Baseline and Avoided IQ Point Losses under the
Regulatory Options Among Infants of Subsistence and Recreational Fish Consumers Exposed to
Mercury in Utero, by Income Group
Cohort Group
Income Group
Exposed
Population3
Baseline Total IQ
Point Losses'5
Option A
Option B
Option C
Not Below the
Poverty Line
161,324(85.4%)
395,565 (85.2%)
823 (83.1%)
953 (83.1%)
964(83.1%)
Source: U.S. EPA analysis, 2024.
Notes:
The exposed population for each income group is presented as the number of infants exposed and (in parenthesis) the number
of infants exposed as a share of the total exposed population for the entire cohort.
The baseline total IQ points for each income group are presented as the total number of IQ points and (in parenthesis) the total
number of IQ points as a share of the total number of IQ points for the entire cohort.
The results of the distributional analysis of neurological and cognitive health impacts among both infants
of mothers who are subsistence and recreational fish consumers indicate potential EJ concerns under the
baseline in terms of differential and adverse impacts to infants below the poverty line compared to those
not below the poverty line. Although the regulatory options generate improvements relative to the
baseline in terms of avoided IQ point losses, these improvements are small and do not substantially
change the differential baseline exposures among infants of mother who are subsistence and recreational
fish consumers.(Table 21).
The results for the infants of mothers in the subsistence and recreational fish consumer cohorts under
the baseline show that infants below the poverty line have a larger share of IQ point losses compared to
their share of the exposed population, while infants not below the poverty line have a smaller share of IQ
point losses compared to their share of the exposed population by 0.2 and 0.3 percent, respectively
(Table 21).
Examining the impact of the regulatory options on avoided IQ point losses by income group shows that
for both infants of mothers in the subsistence and recreational fish consumers cohorts, all of the
regulatory options result in avoided IQ point losses for both infants below the poverty line and infants not
below the poverty line, compared to the baseline (Table 21). Additionally, while under each of the
regulatory options infants not below the poverty line had the greatest avoided IQ point losses in absolute
terms, the regulatory options resulted in a slightly larger share of IQ point losses avoided for infants
below the poverty line, compared to the baseline (Table 21). Of the regulatory options, Option C resulted
in the largest combined avoided IQ point losses among infants, compared to the baseline (Table 21). For
infants below the poverty line that experience improvements under the regulatory options in terms of
avoided IQ point losses, these improvements are small and do not substantially change the differential
baseline IQ points observed among infants under the baseline.
4.3.2.4 Distribution of Health Impacts Among Adults Exposed to Arsenic Through Fish Consumption
As detailed in the BCA, the changes in the annual number of skin cancer cases associated with
consumption offish contaminated with arsenic from steam electric power plant discharges are negligible
(see Section 5.6 in U.S. EPA, 2024a). Therefore, EPA excluded the distributional analysis of the annual
changes in skin cancer cases because the resulting impacts would be reported as very small fractions of
cases, which EPA concluded would not be informative. However, EPA expects adults of color, low-income
adults, and Indigenous adults to receive shares of the reduced skin cancer cases benefits proportional to
their exposure.
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Section 4—Analysis of the Distribution of Pollutant Exposures
4.3.2.5 Key Findings
The results of EPA's analysis of human health impacts resulting from exposures among fish consumers to
lead, mercury, and arsenic in downstream surface waters produced informative distributional results only
for the analysis of IQ point losses under the baseline and changes in avoided IQ point losses under the
regulatory options for infants exposed to mercury in utero through maternal recreational and subsistence
fish consumption. This analysis showed potential EJ concerns in the baseline in terms of differential, and
potentially disproportionate, and adverse impacts to infants of color and infants below the poverty line
relative to White infants and infants not below the poverty line, respectively. For infants of mothers in
both cohorts, under all of the regulatory options, increases in avoided IQ point losses were estimated
relative to the baseline across all racial or ethnic groups and income groups, with Option C generating the
greatest combined increases in avoided IQ point losses. Despite these estimated increases in avoided IQ
point losses for infants, the improvements EPA estimated under the regulatory options are small and do
not substantially change the differential baseline IQ points observed among infants under the baseline.
Although distributional analyses were not performed, for all human health endpoints related to lead and
arsenic exposures from fish consumption, across population groups of concern and fish consumers, EPA
expects low-income and Indigenous children and adults, as well as children and adults of color to receive
shares of reduced adverse health impact benefits proportional to their exposure under all the regulatory
options.
4.4 Drinking Water
Along with the pollutants evaluated in the surface water analysis, EPA also analyzed changes in bromide
loadings from steam electric power plant discharges of FGD wastewater and BA transport water. The
presence of bromide in surface water is not considered to pose a risk to human health as the bromide ion
has a low degree of toxicity, but as surface waters transport bromide discharges downstream to drinking
water treatment facility intakes, bromide can be drawn into the treatment systems and undergo chemical
changes that can potentially pose risks to human health through drinking water.41,42 Of particular concern
to EPA is bromide's contribution to the formation of brominated disinfection byproducts (DBPs) during
disinfection processes that occur as part of standard drinking water treatment. When surface water
containing bromide is disinfected using chlorine a chemical change occurs which produces hypobromite
(BrO~) which reacts with organic matter in the water to produce brominated and mixed chloro-bromo
41 Halogens discharged by steam electric plants include both bromide and iodine, but EPA quantified only effects
associated with brominated DBPs. In vitro toxicology studies with bacteria and mammalian cells have documented
evidence of genotoxic (including mutagenic), cytotoxic, tumorigenic, and developmental toxicity properties of
iodinated DBPs, but the available data are insufficient at this time to determine the extent of iodinated DBP's
contribution to adverse human health effects from exposure to treated drinking water.
42 EPA acknowledges that other pollutants discharged by steam electric power plants to surface waters (e.g., lead,
mercury, and arsenic) may affect the quality of water used for public drinking water systems. The pollutants may not
be removed adequately during treatment at a drinking water treatment plant and people may then be exposed to
such harmful pollutants through ingestion, as well as inhalation and dermal absorption (e.g., showering, bathing).
Public drinking water supplies are subject to legally enforceable MCLs, which specify the highest level of a pollutant
that is allowed in drinking water, established by EPA. The MCL is based on the MCL Goal (MCLG), which is the level
of a contaminant in drinking water below which there is no known or expected risk to human health. EPA sets the
MCL as close to the MCLG as possible, with consideration for the best available treatment technologies and costs. In
analyzing the human health benefits of the regulatory options, EPA assumes that treated water meets applicable
MCLs in the baseline. To assess potential for changes in health risk from exposure to arsenic, lead, and thallium in
drinking water, EPA estimated changes in pollutant levels in source waters downstream from steam electric power
plants under each regulatory option. The results of this analysis are presented in Section 4.3.2.3 of the BCA (U.S.
Environmental Protection Agency. (2024a). Benefit and Cost Analysis for Supplemental Effluent Limitations
Guidelines and Standards for the Steam Electric Power Generating Point Source Category. (821-R-24-006).).
Additionally, a distributional analysis using these results is presented in Section 9.2.
79
-------
Section 4—Analysis of the Distribution of Pollutant Exposures
DBPs, including total trihalomethanes (referred to as TTHM). There is evidence that exposure to TTHM
through drinking water is linked to the incidence of bladder cancer. For more information on bromide
loadings from steam electric power plants, the formation of brominated and mixed chloro-bromo DBPs,
and associated human health impacts see Section 4 of the BCA (U.S. EPA, 2024a).
Based on this understanding of potential human health risks related to exposure to TTHM through
drinking water, EPA evaluated the distribution of TTHM underthe regulatory options in communities
served by drinking water systems identified as intaking water directly or indirectly (i.e., purchasing water
from a system that intakes directly) from surface waters affected by bromide discharges from steam
electric power plants. Additionally, EPA analyzed the distribution of health impacts, specifically incidence
of bladder cancer, under the regulatory options in these communities. These analyses were performed to
determine whether potential EJ concerns related to exposures to TTHM and bladder cancer incidence
exist under the regulatory options. The following sections discuss the results of these analyses.
4.4.1 Distribution of TTHM Exposures Among Affected Communities
To evaluate the distribution of TTHM exposures among communities served by drinking water systems,
EPA first estimated bromide concentrations in downstream surface waters identified as receiving FGD
wastewater and BA transport water discharges from steam electric power plants under the baseline and
regulatory options using the D-FATE model. Regulatory options A and B are estimated to result in the
same bromide loading reductions, whereas bromide loading reductions are slightly higher under
Option C.
EPA then used information from the SDWIS dataset to determine what PWS downstream of the steam
electric power plants would be affected based on whether they directly or indirectly intake source water
from an identified downstream surface water receiving bromide discharges from a plant. Combining PWS
information from SDWIS with reach-level bromide concentrations modeled in D-FATE, EPA calculated
system-level changes in bromide concentrations in the source waters under each of the regulatory
options. Using research estimating changes in TTHM levels as a function of changes in bromide levels, EPA
used the system-level changes in bromide concentrations under each of the regulatory options to
estimate TTHM concentration changes. Finally, EPA estimated population exposures to changes in TTHM
concentrations using information on the service area of each system. For a more detailed discussion of
EPA methodology for estimating TTHM exposures, see Section 4 of the BCA (U.S. EPA, 2024a).
Table 22 presents the results of this analysis. As noted above, bromide loading changes are the same for
regulatory options A and B and therefore the results for these two options are the same. Given the
number of systems that EPA identified as being potentially affected by bromide discharges, changes in
TTHM concentrations are presented at the state level. EPA calculated the state-level changes in TTHM
concentrations presented in Table 22 by weighting the modeled changes in TTHM concentrations under
each of the regulatory options across all affected PWSs in each state based on the population served.
Table 22 is divided into two sections, states with affected PWSs that have estimated non-zero changes in
TTHM concentrations under the regulatory options and states with affected PWSs that have no estimated
changes in TTHM concentration under the regulatory options. For states with non-zero changes in TTHM
concentrations, the results are presented from greatest to least based on the change calculated for
Option C. Information on changes in TTHM concentrations under each of the regulatory options is
combined with information on socioeconomic characteristics of the population served in each state by
affected PWSs collected from the U.S. Census Bureau's 2017 to 2021 ACS dataset to assess distributional
impacts.
80
-------
Section 4—Analysis of the Distribution of Pollutant Exposures
Table 22. Modeled Changes in TTHM Concentrations Under the Regulatory Options Among Potentially Affected Drinking Water Systems, by State
Percent
Percent
Percent
Option A and
Option C
# Potentially
Affected PWS
Population
Served
Percent
African
Percent
Asian a
Native
American
Percent
Other3
Percent
Option B
State
Low-
Income'
Americ
ana
Hawaiian/
Pacific
Islander
Indian /
Alaska
Native a
Hispanic/
Latino9
ATTHM
(Hg/L)b
PWS
(#)
ATTHM
(Hg/L)b
PWS
(#)
States with Estimated Changes in TTHM Concentrations
KS
21
781,859
9.2%
5.0%
4.6%
0.0%
0.6%
3.7%
7.8%
-0.959
21
-0.959
21
ND
13
33,722
8.1%
1.0%
0.8%
0.1%
3.2%
1.8%
3.4%
-0.734
11
-0.734
11
SD
45
43,674
14.6%
1.5%
1.9%
0.0%
19.6%
2.0%
3.2%
-0.709
44
-0.709
44
AL
51
1,243,009
14.4%
21.2%
1.3%
0.0%
0.4%
3.2%
6.4%
-0.701
26
-0.701
26
IN
4
192,275
15.7%
10.5%
1.4%
0.2%
0.0%
3.3%
2.9%
-0.641
4
-0.641
4
NE
13
569,432
15.3%
15.4%
4.4%
0.0%
0.5%
4.2%
12.5%
-0.521
13
-0.521
13
KY
54
1,774,744
16.9%
16.2%
2.1%
0.0%
0.1%
3.5%
4.9%
-0.325
27
-0.325
27
IA
12
155,987
13.9%
3.6%
1.0%
0.3%
0.2%
2.8%
9.6%
-0.252
10
-0.252
10
MO
52
2,658,501
9.3%
17.4%
6.0%
0.1%
0.2%
3.5%
5.1%
-0.248
48
-0.248
48
OH
30
1,229,857
17.9%
22.3%
2.0%
0.0%
0.0%
3.8%
3.9%
-0.161
30
-0.161
30
WV
24
289,810
20.0%
4.6%
1.8%
0.0%
0.1%
3.8%
2.1%
-0.134
24
-0.134
24
IL
86
759,693
13.4%
17.8%
1.4%
0.0%
0.1%
3.7%
4.4%
-0.092
33
-0.092
33
GA
16
706,206
18.0%
31.0%
1.9%
0.1%
0.1%
3.2%
11.5%
-0.081
5
-0.081
5
NC
38
1,514,192
10.8%
27.9%
5.4%
0.0%
0.2%
3.4%
11.9%
-0.020
38
-0.072
38
VA
23
828,925
11.0%
26.5%
5.3%
0.1%
0.2%
5.0%
8.2%
-0.050
23
-0.061
23
PA
93
4,033,477
10.3%
11.7%
4.1%
0.0%
0.1%
3.4%
4.7%
-0.059
41
-0.059
41
SC
72
1,496,142
14.6%
27.7%
1.9%
0.2%
0.2%
3.1%
6.1%
0.000
34
-0.016
34
MA
12
397,487
11.5%
3.9%
9.7%
0.0%
0.1%
2.7%
26.3%
-0.003
12
-0.003
12
MN
11
1,055,600
14.8%
15.7%
10.4%
0.0%
0.7%
5.1%
8.9%
-0.002
11
-0.002
11
States with No Estimated Changes in TTHM Concentrations
AR
18
20,567
16.5%
0.4%
0.2%
0.1%
1.9%
3.3%
2.7%
0.000
0
0.000
0
DE
1
231,114
12.0%
24.8%
5.2%
0.0%
0.1%
3.4%
11.9%
0.000
0
0.000
0
FL
7
429,167
9.5%
5.6%
1.8%
0.0%
0.2%
2.3%
10.6%
0.000
0
0.000
0
LA
4
89,699
17.5%
25.8%
2.0%
0.0%
0.4%
3.0%
7.8%
0.000
0
0.000
0
MD
20
2,140,060
16.8%
47.9%
4.5%
0.0%
0.2%
3.8%
6.4%
0.000
10
0.000
10
Ml
99
3,426,543
17.0%
28.5%
4.6%
0.0%
0.2%
3.6%
5.5%
0.000
0
0.000
0
81
-------
Section 4—Analysis of the Distribution of Pollutant Exposures
Table 22. Modeled Changes in TTHM Concentrations Under the Regulatory Options Among Potentially Affected Drinking Water Systems, by State
Percent
Percent
Percent
Option A and
Option C
# Potentially
Affected PWS
Population
Served
Percent
African
Percent
Asian a
Native
American
Percent
Other3
Percent
Option B
State
Low-
Income'
Americ
ana
Hawaiian/
Pacific
Islander
Indian /
Alaska
Native a
Hispanic/
Latino9
ATTHM
(Hg/L)b
PWS
(#)
ATTHM
(Hg/L)b
PWS
(#)
MS
2
1,490
19.4%
27.8%
2.7%
0.0%
0.0%
3.3%
8.2%
0.000
0
0.000
0
NH
3
103,592
7.1%
1.6%
3.6%
0.0%
0.1%
3.1%
10.7%
0.000
0
0.000
0
OK
48
828,052
13.6%
8.8%
3.2%
0.1%
6.8%
8.3%
12.1%
0.000
26
0.000
26
TN
43
2,116,969
11.4%
14.5%
2.8%
0.1%
0.1%
3.7%
7.2%
0.000
30
0.000
30
TX
1
23,170
14.6%
5.6%
5.8%
0.0%
0.1%
2.3%
16.0%
0.000
0
0.000
0
Total
916
29,175,015
521
521
US
12.9%
12.1%
5.6%
0.2%
0.6%
3.5%
19.2%
Isoi/rce: U.S. EPA analysis, 2024.
Notes:
a. Socioeconomic characteristics are population-weighted to reflect differences in populations served by potentia
1 ly affected PWS within each state, as well as characteristics of different CBGs
intersected by the PWS service areas. Each racial and ethnic category besides Hispanic or Latino represent the subset of the race and ethnicity that is identified as "non-Hispanic".
b. This column shows the average change in TTHM concentrations (in ug/L) under each of the regulatory options across PWS in each state. The change in TTHM concentration was weighted by the
| populations of the potential
ly affected PWS in each state.
82
-------
Section 4—Analysis of the Distribution of Pollutant Exposures
EPA's analysis shows that, across all states and affected systems, all three regulatory options are
estimated to reduce the concentration of TTHM in drinking water, with Option C generating the greatest
combined reductions (Table 22). As shown in Table 22, under all regulatory options, reductions in TTHM
concentrations are estimated for 521 systems in 19 states, with a median change in TTHM concentration
of -0.06 |ag/L (Table 22). Of these 19 states, 18 have populations served by affected systems where the
percent of the population for at least one population group of concern is above the national average.
Within these 18 states, the majority (approximately 75 percent) are states with two or more population
groups of concern above the national average. This is similar to the nine states with at least one
population group of concern above the national average and with affected PWSs that have no estimated
changes in TTHM concentrations under the regulatory options, with the majority (approximately 85
percent) of states having two or more population groups of concern above the national average. For the
four states which have one population group of concern above the national average, the median change
in TTHM concentrations observed under Option A and Option B is -0.59|ag/L and under Option C the
change is -0.60|ag/L. Across eleven states which have two population groups of concern above the
national average, the median change in TTHM concentrations observed under all regulatory options
is -0.23|ag/L. Lastly, for six states with three or more population groups of concern above the national
average, the median change in TTHM concentrations observed under all regulatory options is -0.13|ag/L.
4.4.2 Distribution of Bladder Cancer Cases and Deaths Among Affected Communities
To model the relationship between estimated changes in lifetime TTHM exposures and bladder cancer
cases, EPA used a life table approach which estimates age-specific changes in bladder cancer probability
and models subsequent bladder cancer mortality. The life table approach enables quantification of
complex regulatory scenarios that involve variable pollutant changes over time. For this analysis, EPA
assumed that the population affected by estimated changes in bromide discharges from steam electric
power plants is exposed to baseline TTHM concentrations before implementation of the revised ELGs
(before 2025) and to alternative TTHM concentrations from 2025-2049 to be consistent with the
framework for evaluating costs and benefits. Therefore, EPA modeled changes in bladder cancer health
outcomes resulting from changes in TTHM exposures from 2025-2049. Recognizing that changes in
cancer incidence can occur long after exposure, associated changes in bladder cancer incidence were
modeled through 2125, though for only the changes attributable to changes in TTHM exposure estimated
in the 2025-2049 timeframe. Using available data on bladder cancer incidence and mortality and modeled
relationships between changes in TTHM concentrations and changes in lifetime bladder cancer risk, EPA
calculated changes in bladder cancer incidence and mortality under the regulatory options. For a more
detailed discussion of EPA's methodology for estimating bladder cancer incidence and mortality, see
Section 4 of the BCA (U.S. EPA, 2024a).
Table 23 and Table 24 present the results of this analysis by summarizing the distribution of avoided
cancer cases and avoided cancer deaths, respectively. Given the number of systems that EPA identified as
being potentially affected by changes in bromide discharges, changes in bladder cancer incidence and
mortality are presented at the state level. Table 23 and Table 24 are divided into two sections, states with
affected PWSs that have estimated non-zero changes in total bladder cancer cases avoided or total excess
bladder cancer deaths avoided under the regulatory options and states with affected PWSs that have no
estimated changes in total bladder cancer cases avoided or total excess bladder cancer deaths avoided
under the regulatory options. For states with non-zero changes in total bladder cancer cases avoided or
total excess bladder cancer deaths avoided, the results are presented from greatest to least based on the
change calculated for Option C. Similar to the analysis of changes in TTHM concentrations in Table 22,
EPA combined information on changes in bladder cancer incidence and mortality under each of the
regulatory options with information on socioeconomic characteristics of the exposed populations
collected from the U.S. Census Bureau's 2017 to 2021 ACS dataset to assess distributional impacts.
83
-------
Section 4—Analysis of the Distribution of Pollutant Exposures
Table 23. Modeled Changes in Total Bladder Cancer Cases Avoided Under the Regulatory Options Among Potentially Affected Drinking Water Systems, by
State
#
Potentially
Affected
PWS
Percent
Low-
Income
a
Percent
African-
American
a
Percent
Percent
Option A and Option B
Option C
State
Population
Served
Percent
Asian3
Native
Hawaiian/
Pacific
Islander3
American
Indian/
Alaska
Native3
Percent
Other3
Percent
Hispanic/
Latino3
Cases
Avoided
(#)b
PWS
(#)
Cases
Avoided
(#)b
PWS
(#)
States with Estimated Changes in Total B
adder Cancer Cases Avoided
AL
51
1,243,009
14.4%
21.2%
1.3%
0.0%
0.4%
3.2%
6.4%
20.6
20
20.6
20
KS
21
781,859
9.2%
5.0%
4.6%
0.0%
0.6%
3.7%
7.8%
17.8
21
17.8
21
MO
52
2,658,501
9.3%
17.4%
6.0%
0.1%
0.2%
3.5%
5.1%
15.8
48
15.8
48
KY
54
1,774,744
16.9%
16.2%
2.1%
0.0%
0.1%
3.5%
4.9%
14.7
27
14.7
27
NE
13
569,432
15.3%
15.4%
4.4%
0.0%
0.5%
4.2%
12.5%
7.2
13
7.2
13
NC
38
1,514,192
10.8%
27.9%
5.4%
0.0%
0.2%
3.4%
11.9%
0.9
38
5.8
38
PA
93
4,033,477
10.3%
11.7%
4.1%
0.0%
0.1%
3.4%
4.7%
5.0
36
5.0
36
OH
30
1,229,857
17.9%
22.3%
2.0%
0.0%
0.0%
3.8%
3.9%
4.9
30
4.9
30
IN
4
192,275
15.7%
10.5%
1.4%
0.2%
0.0%
3.3%
2.9%
3.1
4
3.1
4
IL
86
759,693
13.4%
17.8%
1.4%
0.0%
0.1%
3.7%
4.4%
1.6
33
1.6
33
VA
23
828,925
11.0%
26.5%
5.3%
0.1%
0.2%
5.0%
8.2%
1.2
23
1.5
23
GA
16
706,206
18.0%
31.0%
1.9%
0.1%
0.1%
3.2%
11.5%
1.4
2
1.4
2
SC
72
1,496,142
14.6%
27.7%
1.9%
0.2%
0.2%
3.1%
6.1%
0.0
32
1.3
32
IA
12
155,987
13.9%
3.6%
1.0%
0.3%
0.2%
2.8%
9.6%
0.9
10
0.9
10
WV
24
289,810
20.0%
4.6%
1.8%
0.0%
0.1%
3.8%
2.1%
0.9
24
0.9
24
ND
13
33,722
8.1%
1.0%
0.8%
0.1%
3.2%
1.8%
3.4%
0.6
11
0.6
11
SD
45
43,674
14.6%
1.5%
1.9%
0.0%
19.6%
2.0%
3.2%
0.6
43
0.6
43
MN
11
1,055,600
14.8%
15.7%
10.4%
0.0%
0.7%
5.1%
8.9%
0.1
11
0.1
11
States with No Estimated Changes in Total Bladder Cancer Cases Avoided
AR
18
20,567
16.5%
0.4%
0.2%
0.1%
1.9%
3.3%
2.7%
0.0
0
0.0
0
DE
1
231,114
12.0%
24.8%
5.2%
0.0%
0.1%
3.4%
11.9%
0.0
0
0.0
0
FL
7
429,167
9.5%
5.6%
1.8%
0.0%
0.2%
2.3%
10.6%
0.0
0
0.0
0
LA
4
89,699
17.5%
25.8%
2.0%
0.0%
0.4%
3.0%
7.8%
0.0
0
0.0
0
MA
12
397,487
11.5%
3.9%
9.7%
0.0%
0.1%
2.7%
26.3%
0.0
12
0.0
12
MD
20
2,140,060
16.8%
47.9%
4.5%
0.0%
0.2%
3.8%
6.4%
0.0
5
0.0
5
Ml
99
3,426,543
17.0%
28.5%
4.6%
0.0%
0.2%
3.6%
5.5%
0.0
0
0.0
0
84
-------
Section 4—Analysis of the Distribution of Pollutant Exposures
Table 23. Modeled Changes in Total Bladder Cancer Cases Avoided Under the Regulatory Options Among Potentially Affected Drinking Water Systems, by
State
#
Potentially
Affected
PWS
Percent
Low-
Income
a
Percent
African-
American
a
Percent
Percent
Option A and Option B
Option C
State
Population
Served
Percent
Asian3
Native
Hawaiian/
Pacific
Islander3
American
Indian/
Alaska
Native3
Percent
Other3
Percent
Hispanic/
Latino3
Cases
Avoided
(#)b
PWS
(#)
Cases
Avoided
(#)b
PWS
(#)
MS
2
1,490
19.4%
27.8%
2.7%
0.0%
0.0%
3.3%
8.2%
0.0
0
0.0
0
NH
3
103,592
7.1%
1.6%
3.6%
0.0%
0.1%
3.1%
10.7%
0.0
0
0.0
0
OK
48
828,052
13.6%
8.8%
3.2%
0.1%
6.8%
8.3%
12.1%
0.0
25
0.0
25
TN
43
2,116,969
11.4%
14.5%
2.8%
0.1%
0.1%
3.7%
7.2%
0.0
28
0.0
28
TX
1
23,170
14.6%
5.6%
5.8%
0.0%
0.1%
2.3%
16.0%
0.0
0
0.0
0
Total
916
29,175,015
97.4
496
103.8
496
Total
916
29,175,015
97.4
496
103.8
496
US
12.9%
12.1%
5.6%
0.2%
0.6%
3.5%
19.2%
Isoi/rce: U.S. EPA analysis, 2024.
Notes:
a. Socioeconomic characteristics are population-weighted to reflect differences in populations served by potentially affected PWS within each state, as well as characteristics of different CBGs
intersected by the PWS service areas. Each racial and ethnic category besides Hispanic or Latino represent the subset of the race and ethnicity that is identified as "non-Hispanic".
|b. This column shows the total number of bladder cancer cases avoided under each of the regulatory options over the period of analysis.
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 24. Modeled Changes in Total Excess Bladder Cancer Deaths Avoided Under the Regulatory Options Among Potentially Affected Drinking Water
Systems, by State
s
tate
if
Potentially
Affected
PWS
Population
Served
Percent
Low-
Income3
Percent
African-
American3
Percent
Asian3
Native
Hawaiian/
Pacific
Islander3
American
Indian/
Alaska
Native3
Percent
Other3
Percent
Hispanic/
Latino3
Deaths
Avoided (#)b
PWS (#)
Deaths
Avoided
(#)b
PWS (#)
States with Changes in Total Excess Bladder Cancer Deaths Avoided
AL
51
1,243,009
14.4%
21.2%
1.3%
0.0%
0.4%
3.2%
6.4%
5.8
20
5.8
20
KS
21
781,859
9.2%
5.0%
4.6%
0.0%
0.6%
3.7%
7.8%
5.0
21
5.0
21
MO
52
2,658,501
9.3%
17.4%
6.0%
0.1%
0.2%
3.5%
5.1%
4.4
48
4.4
48
KY
54
1,774,744
16.9%
16.2%
2.1%
0.0%
0.1%
3.5%
4.9%
4.2
27
4.2
27
NE
13
569,432
15.3%
15.4%
4.4%
0.0%
0.5%
4.2%
12.5%
2.0
13
2.0
13
NC
38
1,514,192
10.8%
27.9%
5.4%
0.0%
0.2%
3.4%
11.9%
0.3
38
1.7
38
OH
30
1,229,857
17.9%
22.3%
2.0%
0.0%
0.0%
3.8%
3.9%
1.4
30
1.4
30
PA
93
4,033,477
10.3%
11.7%
4.1%
0.0%
0.1%
3.4%
4.7%
1.4
36
1.4
36
IN
4
192,275
15.7%
10.5%
1.4%
0.2%
0.0%
3.3%
2.9%
0.9
4
0.9
4
IL
86
759,693
13.4%
17.8%
1.4%
0.0%
0.1%
3.7%
4.4%
0.5
33
0.5
33
GA
16
706,206
18.0%
31.0%
1.9%
0.1%
0.1%
3.2%
11.5%
0.4
2
0.4
2
SC
72
1,496,142
14.6%
27.7%
1.9%
0.2%
0.2%
3.1%
6.1%
0.0
32
0.4
32
VA
23
828,925
11.0%
26.5%
5.3%
0.1%
0.2%
5.0%
8.2%
0.3
23
0.4
23
IA
12
155,987
13.9%
3.6%
1.0%
0.3%
0.2%
2.8%
9.6%
0.3
10
0.3
10
WV
24
289,810
20.0%
4.6%
1.8%
0.0%
0.1%
3.8%
2.1%
0.3
24
0.3
24
ND
13
33,722
8.1%
1.0%
0.8%
0.1%
3.2%
1.8%
3.4%
0.2
11
0.2
11
SD
45
43,674
14.6%
1.5%
1.9%
0.0%
19.6%
2.0%
3.2%
0.2
43
0.2
43
States with No Changes in Total Excess Blad
der Cancer Deaths Avoided |
AR
18
20,567
16.5%
0.4%
0.2%
0.1%
1.9%
3.3%
2.7%
0.0
0
0.0
0
DE
1
231,114
12.0%
24.8%
5.2%
0.0%
0.1%
3.4%
11.9%
0.0
0
0.0
0
FL
7
429,167
9.5%
5.6%
1.8%
0.0%
0.2%
2.3%
10.6%
0.0
0
0.0
0
LA
4
89,699
17.5%
25.8%
2.0%
0.0%
0.4%
3.0%
7.8%
0.0
0
0.0
0
MA
12
397,487
11.5%
3.9%
9.7%
0.0%
0.1%
2.7%
26.3%
0.0
12
0.0
12
MD
20
2,140,060
16.8%
47.9%
4.5%
0.0%
0.2%
3.8%
6.4%
0.0
5
0.0
5
Ml
99
3,426,543
17.0%
28.5%
4.6%
0.0%
0.2%
3.6%
5.5%
0.0
0
0.0
0
MN
11
1,055,600
14.8%
15.7%
10.4%
0.0%
0.7%
5.1%
8.9%
0.0
11
0.0
11
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Section 4—Analysis of the Distribution of Pollutant Exposures
Table 24. Modeled Changes in Total Excess Bladder Cancer Deaths Avoided Under the Regulatory Options Among Potentially Affected Drinking Water
Systems, by State
#
Potentially
Affected
PWS
Percent
Percent
Option A and Option B
Option C
State
Population
Served
Percent
Low-
Income3
Percent
African-
American3
Percent
Asian3
Native
Hawaiian/
Pacific
American
Indian/
Alaska
Percent
Other3
Percent
Hispanic/
Latino3
Deaths
Avoided (#)b
PWS (#)
Deaths
Avoided
(#)b
PWS (#)
Islander3
Native3
MS
2
1,490
19.4%
27.8%
2.7%
0.0%
0.0%
3.3%
8.2%
0.0
0
0.0
0
NH
3
103,592
7.1%
1.6%
3.6%
0.0%
0.1%
3.1%
10.7%
0.0
0
0.0
0
OK
48
828,052
13.6%
8.8%
3.2%
0.1%
6.8%
8.3%
12.1%
0.0
25
0.0
25
TN
43
2,116,969
11.4%
14.5%
2.8%
0.1%
0.1%
3.7%
7.2%
0.0
28
0.0
28
TX
1
23,170
14.6%
5.6%
5.8%
0.0%
0.1%
2.3%
16.0%
0.0
0
0.0
0
Total
916
29,175,015
27.5
496
29.3
496
US
12.9%
12.1%
5.6%
0.2%
0.6%
3.5%
19.2%
1 Source: U.S. EPA analysis, 2024.
Notes:
a. Socioeconomic characteristics are population-weighted to reflect differences in populations served by potentially affected PWS within each state, as well as characteristics of different CBGs
intersected by the PWS service areas. Each racial and ethnic category besides Hispanic or Latino represent the subset of the race and ethnicity that is identified as "non-Hispanic".
| b. This column shows the total number of excess bladder cancer deaths avoided under each of the regulatory options over the period of analysis.
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Section 4—Analysis of the Distribution of Pollutant Exposures
EPA's analysis shows that all three regulatory options result in avoided bladder cancer cases over the
period of analysis (Table 23). Under all options, EPA estimates avoided bladder cancer cases in 18 states
across 496 PWS, with a median change of 0.75 cases avoided under Option C. Option A or Option B result
in a total of 97 cases avoided, while Option C results in 104 cases avoided. Of the 18 states with avoided
bladder cancer cases, 17 have populations served by affected systems where the percent of the
population for at least one population group of concern is above the national average. Within these 17
states, the majority (approximately 75 percent) are states with two or more population groups of concern
above the national average. This is similar to the 10 states with at least one population group of concern
above the national average and no estimated changes in total bladder cancer cases avoided under the
regulatory options, with the majority (approximately 90 percent) of state having two or more population
groups of concern above the national average.
Based on the results summarized in Table 23, states that have populations served by affected systems
where the percent of the population for one population group of concern is above the national average
have a median number of avoided bladder cancer cases of about two cases under Option A or Option B
and four cases under Option C. States that have populations served by affected systems where the
percent of the population for two population groups of concern is above the national average have a
median number of avoided bladder cancer cases of about one case under all three options. States that
have populations served by affected systems where the percent of the population for three or more
population groups of concern is above the national average have a median number of avoided bladder
cancer cases of about one case under all regulatory options.
Similarly, EPA's analysis shows that, across all states, all of the regulatory options result in avoided excess
bladder cancer deaths (Table 24). Under all regulatory options, EPA estimated avoided bladder cancer
deaths in 17 states across 496 PWS, with a median change of 0.25 avoided bladder cancer deaths. Of the
17 states with avoided bladder cancer deaths, 16 have populations served by affected systems where the
percent of the population for at least one population group of concern is above the national average.
Within these 16 states, the majority (approximately 75 percent) are states with two or more population
groups of concern above the national average. This is similar to the 11 states with at least one population
group of concern above the national average and no estimated changes in total bladder cancer deaths
avoided under the regulatory options, with the majority (approximately 90 percent) of states having two
or more population groups of concern above the national average (Table 24).
Based on the results summarized in Table 24, states that have populations served by affected systems
where the percent of the population for one population group of concern is above the national average
have a median number of avoided excess bladder cancer deaths of about 0.6 deaths under Option A or
Option B and 1.3 deaths under Option C. States that have populations served by affected systems where
the percent of the population for two population groups of concern is above the national average have a
median number of avoided excess bladder cancer deaths of about 0.3 deaths under Option A or Option B
and 0.4 deaths under Option C. States that have populations served by affected systems where the
percent of the population for three or more population groups of concern is above the national average
have a median number of avoided excess bladder cancer deaths of about 0.2 deaths under all regulatory
options.
4.4.3 Key Findings
The results of EPA's analysis of changes in TTHM concentrations and resulting changes in bladder cancer
cases and deaths from consuming drinking water with TTHM, shows that all three regulatory options
reduce TTHM concentrations and reduce the incidence of bladder cancer cases and excess bladder cancer
deaths in states with affected drinking water systems. Of the regulatory options evaluated, across the
analyses and states with affected systems, Option C results in the greatest improvements. Across the
analyses, under each of the regulatory options, the majority of states with affected systems serve
populations with at least one population group of concern above the national average, with the largest
proportion of these states having two or more population groups of concern above the national average.
Analyzing the distribution of changes across the analyses and regulatory options, EPA finds that states
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Section 4—Analysis of the Distribution of Pollutant Exposures
with affected systems serving populations with one population group of concern above the national
average experience the largest median changes in TTHM concentrations and avoided bladder cancer
cases and excess bladder cancer deaths than states serving populations with two and three or more
population groups of concern above the national average, respectively. Despite this, the median changes
in states with one, two, or three or more population groups of concern above the national average is
greater than median change estimated across all states for each of the analyses. While the magnitude of
the median change observed across the analyses decrease in communities with one, two, or three or
more population groups of concern above the national average, EPA finds that this is not due to there
being smaller reductions in TTHM concentrations and avoided bladder cancer cases and excess bladder
cancer deaths, but rather that these states generally have more systems experiencing smaller changes.
Given that the analysis focused on changes under the regulatory options, EPA is not able to draw
conclusions with respect to how the regulatory options contribute to addressing any differential, and
potentially disproportionate, and adverse exposures to TTHM and the incidence of bladder cancer cases
and deaths among population groups of concern in the baseline.
4.5 Cumulative Risks
In previous Steam Electric EAs, EPA focused on assessing potential impacts to human health caused by
individual pollutants present in steam electric power plant wastewater discharges. As indicated by the
results of the human health effects in the immediate receiving water distributional analysis (section 4.2),
communities can be exposed to multiple pollutants from steam electric power plant discharges, the
effects of which may not be fully captured when analyzing impacts on the basis of an individual pollutant.
Therefore, for the proposed rule, EPA expanded the individual pollutant assessment to include a further
evaluation of potential impacts to human health from mixtures of pollutants present in steam electric
power plant discharges. As shown in the EJA for the proposed rule, EPA only identified a handful of
immediate receiving waters with exceedances of pollutant mixture- and human health-specific Hazard
Indices (His), with changes under the proposed regulatory options that were too small to substantially
change baseline distributional disparities. For the final rule, EPA's analysis of cumulative risks produced
similar results under the baseline and the regulatory options. Therefore, EPA determined it would not be
informative to conduct a distributional analysis of cumulative risks. For more information on the results of
EPA's cumulative risk analysis for the final rule, see the 2024 EA and U.S. EPA (2024).
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Section 5—Analysis of the Distribution of Benefits and Costs of the Final Rule
5. Analysis of the Distribution of Benefits and Costs of the
Final Rule
In addition to evaluating the distribution of exposures and health impacts, EPA examined the distribution
of incremental benefits and costs of the regulatory options. The Office of Management and Budget
(OMB) Circular A-4 (2023) defines "distributional effects" as "how the benefits and the costs of a
regulatory action are ultimately experienced across the population and economy, divided up in various
ways (e.g., income groups, race or ethnicity, sex, gender, sexual orientation, disability, occupation, or
geography; or relevant categories for firms, including firm size and industrial sector)." (p. 61) As discussed
below, EPA research demonstrates that climate change impacts associated with greenhouse gas (GHG)
emissions disparately accrue to minority and low-income populations and expects that the final rule could
benefit these populations to a greater degree due to estimate reductions in GHGs under the regulatory
options. However, other benefits and costs evaluated under the final rule may not have substantial
impacts distributionally.
5.1 Benefits
EPA began its evaluation of the final rule's distributional effects with an assessment of the categories of
benefits. For the final rule (Option B), approximately 99 percent of the benefits accrue from reductions in
air pollution due to estimated shifts in electric generation resulting from the incremental costs of the final
rule on coal steam electricity generating units. Furthermore, these air benefits are comprised of
approximately a 3-to-l ratio of conventional air pollutants health benefits to GHG benefits. Thus, while
EPA evaluated a number of exposures and endpoints for differential impacts, as discussed above, for
purposes of evaluating the distributional effects of the final rule, the Agency focuses on these two benefit
categories for further evaluation.43
5.1.1 GHG Benefits
In 2009, under the Endangerment and Cause or Contribute Findings for Greenhouse Gases Under Section
202(a) of the Clean Air Act ("Endangerment Finding"), the Administrator considered how climate change
threatens the health and welfare of the U.S. population (U.S. EPA, 2009). As part of that consideration,
the Administrator also considered risks to minority and low-income individuals and communities, finding
that certain parts of the U.S. population may be especially vulnerable based on their characteristics or
circumstances. These groups include economically and socially disadvantaged communities; individuals at
vulnerable lifestages, such as the elderly, the very young, and pregnant or nursing women; those already
in poor health or with comorbidities; the disabled; those experiencing homelessness, mental illness, or
substance abuse; and/or Indigenous or people of color dependent on one or limited resources for
subsistence due to factors including but not limited to geography, access, and mobility.
Scientific assessment and agency reports produced over the past decade by the United States Global
Change Research Program (USGCRP), the Intergovernmental Panel on Climate Change (IPCC), and the
National Academies of Science, Engineering, and Medicine (NASEM) add more evidence that the impacts
of climate change raise EJ concerns (IPCC, 2018; National Academies of Sciences, 2017; National Research
Council, 2011; Oppenheimer et al., 2014; Porter et al., 2014; Smith et al., 2014; USGCRP, 2016, 2018).
These reports conclude that poorer communities or communities of color can be especially vulnerable to
climate change impacts because they tend to have limited adaptive capacities and are more dependent
on climate-sensitive resources such as local water and food supplies or have less access to social and
43 EPA acknowledges that while the assessment of benefits under Option B show that nearly all the benefits
associated with the final rule can be attributed to benefits from reductions in air pollution, benefits associated with
other potential impacts from the rule that EPA did not quantify, like changes in housing prices, could also have
distributional impacts across affected populations.
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Section 5—Analysis of the Distribution of Benefits and Costs of the Final Rule
information resources. Some communities of color, specifically populations defined jointly by ethnic or
racial characteristics and geographic location, may be uniquely vulnerable to climate change health
impacts in the U.S.. In particular, the 2016 scientific assessment on the Impacts of Climate Change on
Human Health found with high confidence that vulnerabilities are place-and time-specific, lifestages and
ages are linked to immediate and future health impacts, and social determinants of health are linked to
greater extent and severity of climate change-related health impacts.
5.1.1.1 Effects on Specific Population Groups of Concern
Socioeconomic and educational factors affect the likelihood of an individual being exposed to negative
impacts of climate change. Individuals living in socially and economically disadvantaged communities,
such as those living at or below the poverty line or those who are experiencing homelessness or social
isolation, are at greater risk of health effects from climate change. This is also true with respect to people
at vulnerable lifestages, specifically women who are pre-and perinatal, or are nursing; in utero fetuses;
children at all stages of development; and the elderly. Per the Fourth National Climate Assessment
(NCA4), "Climate change affects human health by altering exposures to heat waves, floods, droughts, and
other extreme events; vector-, food-and waterborne infectious diseases; changes in the quality and safety
of air, food, and water; and stresses to mental health and well-being" (Ebi et al., 2018). Many health
conditions such as cardiovascular or respiratory illness and other health impacts are associated with and
exacerbated by an increase in GHGs and climate change outcomes, which is problematic as these
diseases occur at higher rates within vulnerable communities. Importantly, negative public health
outcomes include those that are physical in nature, as well as mental, emotional, social, and economic.
To this end, as well, the scientific assessment literature-including the aforementioned USGCRP, IPCC, and
NASEM reports-demonstrates that there are myriad ways in which these populations may be affected at
the individual and community levels. Individuals face differential exposure to criteria pollutants, in part
due to the proximity of highways, trains, factories, and other major sources of pollutant-emitting sources
to less-affluent residential areas. Outdoor workers, such as construction or utility crews and agricultural
laborers, who frequently are comprised of already at-risk groups, are exposed to poor air quality and
extreme temperatures without relief. U.S. EPA (2021) projected that individuals who are low-income or
who do not have a high school diploma are 25 percent more likely to live in areas with the greatest losses
of labor hours due to extreme temperatures. Low-income individuals or those without high school
diplomas are 15 percent more likely to live in areas that are projected to see the greatest increases in
childhood asthma diagnoses, due to climate change-driven increases to particulate air pollution.
Furthermore, individuals within population groups of concern face greater housing, clean water, and food
insecurity and bear disproportionate economic impacts and health burdens associated with climate
change effects. They have less or limited access to healthcare and affordable, adequate health or
homeowner insurance. Finally, resiliency and adaptation are more difficult for economically
disadvantaged communities: they have less liquidity, individually and collectively, to move or to make the
types of infrastructure or policy changes to limit or reduce the hazards they face. They frequently are less
able to self-advocate for resources that would otherwise aid in building resilience and hazard reduction
and mitigation. Further findings of U.S. EPA (2021) include findings that the following groups are more
likely than their reference population to currently live in areas with:
• The highest increases in childhood asthma diagnoses from climate-driven changes in PM2.5 (low-
income, Black and African American, Hispanic and Latino, and Asian populations);
• The highest percentage of land lost to inundation (low-income, American Indian and Alaska Native
populations);
• The highest increases in mortality rates due to climate-driven changes in extreme temperatures (low-
income and Black and African American populations);
• The highest rates of labor hour losses for weather-exposed workers due to extreme temperatures
(low-income, Black and African American, American Indian and Alaska Native, Hispanic and Latino,
and Pacific Islander populations);
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Section 5—Analysis of the Distribution of Benefits and Costs of the Final Rule
• The highest increases in traffic delays associated with high-tide flooding (low-income, Hispanic and
Latino, Asian, and Pacific Islander populations); and
• The highest damages from inland flooding (Pacific Islander populations).
It is important to examine ways in which socially and physiologically vulnerable groups are exposed to,
and experience threats posed by climate change. The assessment literature cited in EPA's 2009 and 2016
Endangerment Findings, as well as Impacts of Climate Change on Human Health (USGCRP, 2016),
concluded that certain populations and life stages, including children and older individuals, are more
vulnerable to climate-related health effects. The assessment literature produced from 2016 to the
present strengthens these conclusions by providing more detailed findings regarding related
vulnerabilities and the projected impacts youth may experience. These assessments-including the NCA4
Ebi et al., 2018 and The Impacts of Climate Change on Human Health in the United States (USGCRP,
2016)-describe how children's unique physiological and developmental factors contribute to making
them particularly vulnerable to climate change. Impacts to children are expected from heat waves, air
pollution, infectious and waterborne illnesses, and mental health effects resulting from extreme weather
events. In addition, children are among those especially susceptible to allergens, as well as health effects
associated with heat waves, storms, and floods. Additional health concerns may arise in low-income
households, especially those with children, if climate change reduces food availability and increases
prices, leading to food insecurity within households.
Present research demonstrates that exposures and vulnerabilities to climate change impacts are a
product of a complex set of racial, ethnic, and age demographics; and geographic, sociocultural, and
economic factors. Individuals may experience hazards in aggregate or individually; they also may have
one, some, or multiple of the vulnerabilities considered. The Impacts of Climate Change on Human Health
(USGCRP, 2016) found that some people of color, low-income groups, people with limited English
proficiency, and certain immigrant groups (especially those who are undocumented) live with many of
the factors that contribute to their vulnerability to the health impacts of climate change. While difficult to
isolate from related socioeconomic factors, race appears to be an important factor in vulnerability to
climate-related stress, with elevated risks for mortality from high temperatures reported for Black or
African American individuals compared to White individuals after controlling for factors such as air
conditioning use. Some research has found that race or ethnicity alone, more than other individual
demographic and socioeconomic characteristics, may play a significant role in determining one's risk of
experiencing harm as a result of climate change. This includes estimates that Black Americans are
40 percent more likely than non-Black individuals to live in areas of the U.S. experiencing the highest
projected increases in mortality rates due to changes in extreme temperatures (under a scenario of 2°C of
global warming). Additionally, Hispanic and Latino individuals in weather-exposed industries were found
to be 43 percent more likely to currently live in areas with the highest projected labor hour losses due to
extreme temperatures (U.S. EPA, 2021). Moreover, people of color are differentially exposed to air
pollution based on where they live, and potentially disproportionately vulnerable due to higher baseline
prevalence of underlying diseases such as asthma, so climate exacerbations of air pollution are expected
to have potentially disproportionate effects on these communities.
Indeed, Indigenous communities possess unique vulnerabilities to climate change, particularly those
impacted by degradation of natural and cultural resources within established reservation boundaries and
threats to traditional subsistence lifestyles. Indigenous communities whose health, economic well-being,
and cultural traditions depend upon the natural environment will likely be affected by the degradation of
ecosystem goods and services associated with climate change. EPA found that American Indian and
Alaska Native individuals are 48 percent more likely than individuals not identifying as such to currently
live in areas where the highest percentage of land is projected to be inundated due to sea level rise
(under a scenario of 50cm of global sea level rise). Asian-Americans are 23 percent more likely to live in
coastal areas projected to see the highest increases in traffic delays due to high-tide flooding on
roadways (U.S. EPA, 2021). The Fifth Assessment Report of the Intergovernmental Panel on Climate
Change (IPCC AR5) indicates that losses of customs and historical knowledge may cause communities to
be less resilient or adaptable (Porter et al., 2014). The NCA4 noted that while Indigenous peoples are
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Section 5—Analysis of the Distribution of Benefits and Costs of the Final Rule
diverse and will be impacted by the climate changes universal to all Americans, there are several ways in
which climate change uniquely threatens Indigenous peoples' livelihoods and economies (Jantarasami et
al., 2018).
In addition, there can be institutional barriers to their management of water, land, and other natural
resources that could impede adaptive measures. For example, Indigenous agriculture in the Southwest is
already being adversely affected by changing patterns of flooding, drought, dust storms, and rising
temperatures leading to increased soil erosion, irrigation water demand, and decreased crop quality and
herd sizes. The Confederated Tribes of the Umatilla Indian Reservation in the Northwest have identified
climate risks to salmon, elk, deer, roots, and huckleberry habitat. Housing and sanitary water supply
infrastructure are vulnerable to disruption from extreme precipitation events.
The NCA4 noted that Indigenous peoples often have differentially higher rates of asthma, cardiovascular
disease, Alzheimer's, diabetes, and obesity, which can all contribute to increased vulnerability to climate-
driven extreme heat and air pollution events Jantarasami et al., 2018. These factors also may be
exacerbated by stressful situations, such as extreme weather events, wildfires, and other circumstances
(Jantarasami et al., 2018).
The NCA4 and IPCC AR5 also highlighted several impacts specific to Alaska Indigenous peoples
(Jantarasami et al., 2018; Porter et al., 2014). Coastal erosion and permafrost thaw will lead to more
coastal erosion, exacerbated risks of winter travel, and damage to buildings, roads, and other
infrastructure-these impacts on archaeological sites, structures, and objects that will lead to a loss of
cultural heritage for Alaska's Indigenous people. In terms of food security, the NCA4 discussed reductions
in suitable ice conditions for hunting, warmer temperatures impairing the use of traditional ice cellars for
food storage, and declining shellfish populations due to warming and acidification Jantarasami et al.,
2018. While the NCA4 also noted that climate change provided more opportunity to hunt from boats
later in the fall season or earlier in the spring, the assessment found that the net impact was an overall
decrease in food security (Jantarasami et al., 2018).
In addition, the U.S. Pacific Islands and the Indigenous communities that live there are also uniquely
vulnerable to the effects of climate change due to their remote location and geographic isolation. They
rely on the land, ocean, and natural resources for their livelihoods, but face challenges in obtaining
energy and food supplies that need to be shipped in at high costs. As a result, they face higher energy
costs than the rest of the nation and depend on imported fossil fuels for electricity generation and diesel.
These challenges exacerbate the climate impacts that the Pacific Islands are experiencing. The NCA4
notes that Indigenous peoples of the Pacific are threatened by rising sea levels, diminishing freshwater
availability, and negative effects to ecosystem services that threaten these individuals' health and well-
being (Jantarasami et al., 2018).
EPA notes that the changes in GHGs attributable to the regulatory options are small compared to
worldwide emissions. Nevertheless, the overall findings of these above-mentioned peer-reviewed
evaluations demonstrate that actions that reduce GHG emissions are likely to reduce impacts on
vulnerable communities, including people of color and low-income populations.
5.1.2 Conventional Air Pollutant Health Benefits
The current EPA modeling methodology for conventional air pollutants results in benefits that are
proportional to exposures. In other words, the distributional findings of air pollutant exposures discussed
above are the same findings EPA has for this benefit category: exposure and health benefit improvements
and degradations attributable to this proposal will be proportionately experienced by all demographic
populations evaluated. However, there are several important nuances and caveats to this conclusion
owing to differences in vulnerability and health outcomes across population subgroups. For example,
there is some information suggesting that the same PM2.5 exposure reduction will reduce the hazard of
mortality more so in Black populations than in White populations (U.S. EPA, 2019b, 2022b). In addition,
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Section 5—Analysis of the Distribution of Benefits and Costs of the Final Rule
demographic-stratified information relating PM2.5 and ozone to other health effects and valuation
estimates is currently lacking.
5.2 Costs
Energy provides many services to households that are necessary for a basic standard of living. The
regulatory requirements will obligate steam electric plants to incur costs to install effluent controls, which
may impact the supply and prices of electricity, specifically residential electricity. This section discusses
how consumers can be affected by potential energy market impacts and characterizes how energy
burdens vary across the income and for different racial or ethnic groups. The goal of this section is to
highlight which populations may be most vulnerable to potential energy market effects caused by
regulatory impacts on the steam electric power sector. In addressing these vulnerabilities, energy
poverty, insecurity, and access are important concepts in the discussion of energy burden. Energy
insecurity is when households lack certainty that they will be able to afford their energy bills. Energy
poverty is when households lack sufficient energy to meet their needs. Finally, energy access barriers are
present when households lack access to affordable, reliable energy.
Energy poverty, insecurity, and access barriers are persistent problems facing many households across
the United States. Low-income households and households of color are particularly vulnerable when
energy prices increase. Although these households consume less energy, it tends to represent a larger
share of their budgets. Drehobl, Ross and Ayala (2020) find that low-income, Black, Hispanic, Native
American, and older adult households have disproportionally higher energy burdens than the average
household. Lyubich (2020) finds that Black households spend more on residential energy than White
households after controlling for income, household size, city, and homeowner status. Reames (2016)
finds that home heating energy efficiency is lower for census blocks in Kansas City, Missouri with a
greater percentage of households in poverty, higher percentage of y heads-of-household of color, lower
median incomes, and a higher share of adults without a high school diploma. He attributes the higher fuel
poverty vulnerability among Black and Hispanic households to racial segregation.
To investigate potential distributional impacts of higher electricity and fuel prices, EPA collected 2022
expenditure and income data stratified by pre-tax income quintiles and race from the Consumer
Expenditure Survey (CES) from the U.S. Bureau of Labor Statistics. EPA combined expenditures in the
following four categories to approximate "energy expenditures": (1) Natural gas, (2) Electricity, (3) Fuel oil
and other fuels, and (4) Gasoline, other fuels, and motor oil (transportation). The first three categories
are residential energy expenditures, and the fourth category represents transportation energy
expenditures. These categories are assumed to potentially experience price impacts due to regulatory
costs affecting the steam electric power sector, though EPA expects impacts to be minimal. EPA examines
energy expenditures, the ratio of household energy expenditures to total household expenditures, and
the ratio of household energy expenditures to after-tax income across income quintiles and racial and
ethnic groups. It is important to note that energy burden is sensitive to what energy services and
expenditures are included and how income is defined (e.g., whether transfer payments or taxes are
included in income calculation).
Table 25. Energy Expenditures by Quintiles of Income before Taxes, 2022
All
Lowest
20%
Second
20%
Third
20%
Fourth
20%
Highest
20%
Average income after taxes
$83,195
$16,337
$39,300
$63,676
$99,891
$196,794
Average annual expenditures
$72,967
$32,612
$47,657
$61,950
$81,957
$140,654
Natural gas
$535
$320
$444
$503
$598
$809
Electricity
$1,683
$1,205
$1,527
$1,664
$1,835
$2,185
Fuel oil and other fuels
$160
$66
$104
$135
$192
$305
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Section 5—Analysis of the Distribution of Benefits and Costs of the Final Rule
Table 25. Energy Expenditures by Quintiles of Income before Taxes, 2022
All
Lowest
20%
Second
20%
Third
20%
Fourth
20%
Highest
20%
Gasoline, other fuels, and motor oil
(transportation)
$3,120
$1,553
$2,360
$3,166
$3,919
$4,601
Total expenditures on energy
$5,498
$3,144
$4,435
$5,468
$6,544
$7,900
Energy expenditures as share of total
expenditures
7.5%
9.6%
9.3%
8.8%
8.0%
5.6%
Energy expenditures as share of income
6.6%
19.2%
11.3%
8.6%
6.6%
4.0%
Quintile's share of all energy expenditures
11.4%
16.1%
19.9%
23.8%
28.7%
Source: U.S. Bureau of Labor Statistics (2023)
Note: Income includes wages, self-employment income, Social Security and retirement payments, interest, dividends, rental
income and other property income, public assistance, unemployment and workers' compensation, veterans' benefits, and
regular contributions for support.
The data in Table 25 indicate that the highest income group consumes the most energy and spends the
most per household, but energy expenditures represent a smaller percentage of their total expenditures
and a smaller percentage of their income than the lowest income quintile. The lowest income quintile
accounted for 11.4 percent of energy expenditures, while the highest quintile accounted for almost
29 percent. However, energy expenditures as a share of total household expenditures were 9.6 percent
for the lowest income quintile and 5.6 percent for the highest income quintile. For energy expenditures
as a share of average after-tax income, the distribution is more unequal, ranging from 19.2 percent for
the lowest income quintile to 4.0 percent for the highest income quintile. This means the lowest income
households are spending over five times more of their income on energy than the highest income
households. The highest income quintile spent about $7,900 per household on energy and had an
average after-tax income of $196,000 in 2022 while the lowest income quintile spent about $3,144 per
household on energy and had $16,000 of after-tax income. Thus, lower income households consume less
energy than higher income households, but their energy expenditures account for a higher share of total
household expenditures on average and a higher share of after-tax income compared to higher income
households.
Table 26 summarizes average demographics by income quintile. Households in the lowest income quintile
are more than twice as likely to be Black than households in the highest income quintile. The higher
income groups also tend to be less likely to be Hispanic than the lower income groups.
Table 26. Demographics by Quintiles of Income before Taxes, 2022
All
Lowest
20%
Second
20%
Third
20%
Fourth
20%
Highest
20%
Black
13%
17%
15%
13%
11%
9%
White, Asian, and all other races
87%
83%
85%
87%
89%
91%
Hispanic or Latino
15%
16%
17%
17%
14%
10%
Not Hispanic or Latino
85%
84%
83%
83%
86%
90%
Source: U.S. Bureau of Labor Statistics (2023)
Table 27 and Table 28 show household energy expenditures by race and ethnicity. Black households'
energy expenditures represent a higher share of their total expenditures than for households of other
races, although their energy expenditures are lower. Hispanic households' energy expenditures comprise
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Section 5—Analysis of the Distribution of Benefits and Costs of the Final Rule
a larger share of their total expenditures than non-Hispanic households, although they spend slightly
more per household on energy than non-Hispanic households. For Black households, energy expenditures
were about $3,700 in 2019 and accounted for about 8 percent of total expenditures and 7 percent of
after-tax income. For White and other non-Black households, energy expenditures accounted for about
6.4 percent of total expenditures and 5.7 percent of after-tax income, though they spent more on energy
($4,200 per household). For Hispanic households, energy expenditures were about $4,200 in 2019 and
accounted for about 8 percent of total expenditures and 7 percent of after-tax income. These numbers
are higher than for non-Hispanic households, whose energy expenditures accounted for about 6.3
percent of total expenditures and 5.6 percent of after-tax income, although non-Hispanic households
spent less on energy per household at $4,100.
Table 27. Energy Expenditures by Race, 2022
All
Consumer
Units
White,
White and
Asian, and
All other
Races
All other
Races(not
Asian)
Asian
Black
Number of consumer units
132,242
114,554
108,246
6,308
17,688
(thousands)
Income before taxes
$82,852
$86,743
$85,417
$109,492
$57,649
Income after taxes
$71,487
$74,436
$73,341
$93,221
$52,389
Average annual expenditures
$63,036
$65,446
$64,981
$73,433
$47,230
Natural gas
$416
$417
$413
$481
$409
Electricity
$1,472
$1,479
$1,496
$1,192
$1,424
Fuel oil and other fuels
$113
$123
$127
$42
$52
Gasoline, other fuels, and motor oil
$2,094
$2,141
$2,146
$2,042
$1,794
(transportation)
Energy expenditures
$4,095
$4,160
$4,182
$3,757
$3,679
Energy expenditures as share of total
6.5%
6.4%
6.4%
5.1%
7.8%
expenditures
Energy expenditures as share of
5.7%
5.6%
5.7%
4.0%
7.0%
income
Group's share of energy expenditures
100%
88%
84%
4%
12%
Source: U.S. Bureau of Labor Statistics (2023)
Note: Income includes wages, self-employment income, Social Security and retirement payments, interest, dividends, rental
income and other property income, public assistance, unemployment and workers' compensation, veterans' benefits, and
| regular contributions for support.
Table 28. Energy Expenditures by Race or Ethnicity, 2022
All
Consumer
Units
Hispanic
Non-
Hispanic
Non-
Hispanic
White,
other
Races
Non-
Hispanic
Black
Number of consumer units (thousands)
132,242
17,921
114,321
96,992
17,328
Income before taxes
$82,852
$64,577
$85,717
$90,734
$57,632
Income after taxes
$71,487
$60,235
$73,251
$76,983
$52,366
Average annual expenditures
$63,036
$54,734
$64,350
$67,370
$47,213
Natural gas
$416
$371
$423
$426
$407
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Section 5—Analysis of the Distribution of Benefits and Costs of the Final Rule
Table 28. Energy Expenditures by Race or Ethnicity, 2022
All
Consumer
Units
Hispanic
Non-
Hispanic
Non-
Hispanic
White,
other
Races
Non-
Hispanic
Black
Electricity
$1,472
$1,433
$1,478
$1,487
$1,426
Fuel oil and other fuels
$113
$31
$126
$139
$51
Gasoline, other fuels, and motor oil
(transportation)
$2,094
$2,438
$2,040
$2,083
$1,798
Energy expenditures
$4,095
$4,273
$4,067
$4,135
$3,682
Energy expenditures as share of total
expenditures
6.5%
7.8%
6.3%
6.1%
7.8%
Energy expenditures as share of income
5.7%
7.1%
5.6%
5.4%
7.0%
Group's share of energy expenditures
100%
14%
86%
74%
12%
Source: U.S. Bureau of Labor Statistics (2023)
Note: Income includes wages, self-employment income, Social Security and retirement payments, interest, dividends, rental
income and other property income, public assistance, unemployment and workers' compensation, veterans' benefits, and
regular contributions for support.
The CES data summarized in this section highlight the higher energy burdens experienced by low-income,
Black, and Hispanic households under baseline conditions. The proposed rule may increase energy prices,
which could exacerbate existing inequalities in energy burden.
EPA assessed the potential electricity price impacts of the proposed ELG on household electricity costs
assuming, as a worst-case scenario, that utilities may pass on all compliance costs to ratepayers. This
analysis, which is detailed in Chapter 7 of the RIA (U.S. EPA, 2024c), suggests very small potential changes
in electricity costs as a result of the final rule. At the national level, upper bound average compliance
costs per residential households for Option B are $3.14 per year. These costs vary across North American
Electric Reliability Corporation (NERC)44 regions (see Figure 8), however, with average compliance costs
per residential households ranging from $0.19 per year in Northeast Power Coordinating Council (NPCC)
to $5.44 per year in SERC Reliability Corporation (SERC). EPA also looked at the distribution of the
potential increases in household electricity costs across types of systems as characterized by the
ownership type of each plant (e.g., utility, municipal, cooperative). This analysis found that residential
consumers served by cooperatives may see the greatest average increase, between $6.73 and $19.26 per
year, assuming cooperatives pass on all compliance costs to ratepayers.
As described above, lower-income households spend less, in the absolute, on energy than do higher-
income households, but energy expenditures represent a larger share of their income. Therefore,
electricity price increases tend to have a relatively larger effect on lower-income households, compared
to higher-income households. While the incremental burden relative to income is not distributionally
neutral, i.e., any increase would affect lower-income households to a greater extent than higher-income
households, the final rule is expected to have a very small impact in the absolute across all regions
analyzed. The potential price increases across regions under the upper bound cost scenario represent
between less than 0.1 percent and 0.2 percent of energy expenditures for all income, race groups, and
income quintiles. These same increases represent between less than 0.1 percent and 0.5 percent of just
L NERC regions include Midwest Reliability Organization (MRO), Northeast Power Coordinating Council (NPCC),
Reliability First Corporation (RF), SERC Reliability Corporation (SERC), Western Electricity Coordinating Council
(WECC), Texas Reliability Entity (TRE), Alaska Systems Coordinating Council (ASCC), and Flawaii Coordinating
Council (FHICC). Compliance costs are zero in both the ASCC and FHICC regions.
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Section 5—Analysis of the Distribution of Benefits and Costs of the Final Rule
electricity expenditures. Furthermore, these small impacts may be further moderated by existing pricing
structures.
Figure 8. Range of Estimated Average Annual Compliance Costs of the Proposed Rule (Option B) per
Residential Household under the Lower and Upper Bound Cost Scenarios, by NERC Region
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6. Limitations and Uncertainties
Table 29 through Table 35 summarize the limitations and uncertainties of EPA's distributional analysis and
their potential effects on the analysis.
As discussed in Section 4.1, the analysis of pollutant exposure focuses on the three principal
wastestreams from steam electric power plants: FGD wastewater, BA transport water and CRL. The
analysis does not account for legacy wastewater discharges or CRL discharged from landfills, surface
impoundments, or other features via groundwater, which a permitting authority may deem, on a case-by-
case basis, to be functionally equivalent to a direct discharge. This omission has an uncertain effect on the
distributional effects of the rule as it would depend on the geographical distribution of the loads and
changes thereof under the regulatory options.
Table 29. Limitations and Uncertainties of EPA's Nationwide Proximity Analysis
Uncertainty/Limitation
Effect on
Notes
Analysis
EPA used independent one-mile and three-
mile buffers around steam electric plant
locations to identify potentially affected
populations.
Uncertain
A CBG may overlap with the buffer areas of
multiple steam electric plants. As a result,
some individuals may be double counted
when generating associated statistics. This
limitation only affects around 2 percent of
CBGs that fall within the buffer areas.
EPA used proximity to the steam electric
power plants or waters receiving FGD
wastewater, BA transport water and CRL
discharges to identify potentially affected
populations.
Uncertain
Steam electric power plants may also affect
populations living near landfills receiving
CCRs or waters receiving CRL via
groundwater. To the extent that these
impacts occur away from the locations
included in the analysis, the number of
people and socioeconomic characteristics of
affected populations may be different than
reported in Section 3.
For some systems lacking data in the
Hydroshare Community Water Systems
Service Boundaries (CWSSB) dataset
(SimpleLab EPIC, 2022), EPA relied on the zip
code reported for the system in the SDWIS
dataset to define the service area.
Uncertain
The zip codes reported in the SDWIS
dataset represent the zip codes associated
with the location of the system, which may
not in all cases accurately represent the zip
code(s) served by the system.
-------
Section 6—Limitations and Uncertainties
Table 30. Limitations and Uncertainties of EPA's Distributional Analysis of Air Impacts
Uncertainty/Limitation
Effect on
Analysis
Notes
EPA used population projections from the
Woods and Poole dataset to analyze the
distribution of PM2.5 and ozone exposures
among various population groups.
Uncertain
There is uncertainty in the population
projections generated in the Woods & Poole
(2015) dataset.
The Woods and Poole database contains
county-level projections of population by age,
sex, and race out to 2050, relative to a baseline
using the 2010 Census data. Population
projections for each county are determined
simultaneously with every other county in the
U.S to consider patterns of economic growth
and migration.
Underlying the population projections are
forecasted variables such as income,
employment, and population. Each of these
forecasts require many assumptions:
economy-wide modeling to project income
and employment, net migration rates based on
employment opportunities and taking into
account fertility and mortality, and the
estimation of age/sex/race distributions at the
county-level based on historical rates of
mortality, fertility, and migration. To the extent
these patterns and assumptions have changed
since the population projections were
estimated, and to the extent that these
patterns and assumptions may change in the
future, we would expect the projections of
future population would be different than
those used in this analysis.
The baseline does not account for several
pending regulatory actions and newly enacted
statutory provisions.
Uncertain
The pending regulatory actions not included in
the baseline include regulatory actions that
EPA is proposing for the near terms and
impacts of the Inflation Reduction Act.
EPA used two air pollutant metrics, MDA8
(ppb) and average annual PM2.5 concentrations
(|ig/m3) which are used to evaluate longer-
term exposures that have been linked to
adverse health effects.
Uncertain
The analysis does not evaluate distributional
disparities in other potentially health-relevant
metrics like shorter-term exposures to ozone
and PM2.5.
EPA's analysis was limited to assessing
distributional disparities in PIVh.sand ozone
exposures
Uncertain
The analysis did not extend to assess
distributional disparities in health effects from
PM2.5 and ozone exposures given the relatively
small changes in PIVh.sand ozone
concentrations resulting from Option 3 and
additional uncertainties associated with
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Section 6—Limitations and Uncertainties
Table 30. Limitations and Uncertainties of EPA's Distributional Analysis of Air Impacts
Uncertainty/Limitation
Effect on
Analysis
Notes
estimating health effects stratified by
population group and valuing those effects.
Table 31. Limitations and Uncertainties of EPA's Distributional Analysis of Immediate Receiving
Water Impacts
Uncertainty/Limitation
Effect on
Analysis
Notes
IRW modeling is based on annual-
average pollutant loadings from the
evaluated wastestreams at steam
electric power plants and annual-
average flow rates within the immediate
receiving waters and does not consider
temporal variability or potential for
pollutants to accumulate in the
environment over extended discharge
periods covering multiple years.
Underestimate
Uncertain effect regarding water quality
distributional analysis.
Likely underestimated effects for impacts to
wildlife and human health impacts due to long-
term accumulation.
Pollutant loading estimates are based on
average pollutant concentrations, not
site-specific data.
Uncertain
Likely results in overestimate of benchmark
exceedances for some immediate receiving
waters and underestimate of benchmark
exceedances at other immediate receiving
waters.
Modeling does not take into
consideration pollutant speciation within
the receiving stream.
Overestimate
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).
National-scale modeling assumptions
that: (1) Do not include site-specific
details or detailed modeling of pollutants
within the receiving water, (2) are used
to estimate pollutant concentrations in
the fish tissue and to evaluate wildlife
impacts, and (3) Are used to estimate
human exposure impacts.
Uncertain
(1) See the 2020 EA for details (U.S. EPA, 2020).
An example of this can be found in Exhibit E
which details input provided by community
members in Florida regarding reverse tidal
flows contributing to pollutant loadings from
the local steam electric power plant
contaminating a local river.
(2) See Appendix D of the 2023 EA for details
(U.S. EPA, 2023a).
(3) Individual exposure factors, such as
ingestion rate, body weight, and exposure
duration, are variable due to physical
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Section 6—Limitations and Uncertainties
Table 31. Limitations and Uncertainties of EPA's Distributional Analysis of Immediate Receiving
Water Impacts
Uncertainty/Limitation
Effect on
Analysis
Notes
characteristics, activities, and behavior of the
individual.
Does not take into account ambient
background pollutant concentrations or
contributions from other point and
nonpoint sources and other
wastestreams that may be discharged
from the steam electric power plant.
Underestimate
EPA's pollutant loadings analysis and IRW
Model runs specifically evaluate the changes in
pollutant loadings that result from the
regulatory options considered under the
proposed supplemental rule. Pollutant loadings
from other wastestreams at steam electric
power plants are assumed to remain the same
under baseline and option scenarios and are
therefore not considered in the analysis.
Because of this approach, the modeling likely
underestimates the number and magnitude of
benchmark value exceedances at baseline and
under the regulatory options, which
contributes to uncertainty in the number of
environmental and human health
improvements or impacts under the proposed
rule and evaluated regulatory options relative
to baseline.
Does not consider cumulative risks
across exposure pathways for ecological
receptors and subsistence and
recreational fishers.
Underestimate
Because many of the pollutants considered in
this analysis are bioaccumulative in nature, the
model considers only ingestion of the food
source (fish), because it is likely that the dose
from the food source is far greater than the
dose from water ingestion or direct contact
with receiving waters.
The diet of the ecological receptors
consists entirely offish inhabiting the
immediate receiving water and that all
fish consumed by subsistence and
recreational fishers (excluding two weeks
per year) are caught in the immediate
receiving water.
Overestimate
This assumption potentially overestimates the
annual-average daily dose of the pollutants,
particularly for recreational fishers. The
proportion offish 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).
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Section 6—Limitations and Uncertainties
Table 32. Limitations and Uncertainties of EPA's Distributional Analysis of Downstream Surface
Water Impacts
Uncertainty/Limitation
Effect on
Analysis
Notes
The IEUBK model does not capture very
small changes.
Negligible
The analysis of human health effects from
reductions in lead exposure uses the
Integrated Exposure Uptake Biokinetic
(IEUBK) model geometric mean blood lead
(BLL) values for each cohort in each CBG
under the baseline and the regulatory
options. The IEUBK model processes daily
intake to two decimal places (|ig/day),and is
not sensitive to some small changes
between the baseline and regulatory
options. As estimated reductions in adverse
health effects are driven by very small
changes across large populations, this
aspect of the model contributes to potential
underestimation of the lead-related health
effects in children in the different
subgroups.
EPA estimated that all fishers travel up to 50
miles.
Uncertain
Certain subpopulations {e.g., low-income
and subsistence fishers) may tend to fish
closer to home. To the extent that these
people fish predominantly from waters
receiving discharges from steam electric
power plants, they may be exposed to
relatively higher concentrations of
pollutants. Conversely, people who live
farther from steam electric power plants
may predominantly fish from waters not
affected by pollutants in steam electric
power plant discharges and be exposed to
relatively lower concentrations of pollutants.
As data are not available on the share of the
fishing population that practices subsistence
fishing, EPA assumed that, uniformly across
the population {i.e., no distinction between
race and ethnicity, income, or other
factors), five percent of people who fish
practice subsistence fishing. This is based on
the assumed 95th percentile fish
consumption rate for this population in
EPA's Exposure Factors Handbook (U.S. EPA,
2011).
Underestimate
Subsistence fishers may represent a
relatively larger share of subpopulations of
interest for potential EJ concerns. This could
increase inequities in the baseline and affect
the extent to which the regulatory options
may mitigate these inequities.
EPA applied uniform fishing participation
rates and catch and release practices across
the entire population.
Uncertain
Differences in behavior across
socioeconomic groups may result in a
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Section 6—Limitations and Uncertainties
Table 32. Limitations and Uncertainties of EPA's Distributional Analysis of Downstream Surface
Water Impacts
Uncertainty/Limitation
Effect on
Analysis
Notes
different distribution of baseline and
regulatory option impacts.
Table 33. Limitations and Uncertainties of EPA's Distributional Analysis of Drinking Water Impacts
Uncertainty/Limitation
Effect on
Analysis
Notes
EPA's analysis of the distribution of drinking
water impacts focuses on the changes in
TTHM concentrations, bladder cancer cases,
and excess bladder cancer deaths across
drinking water systems under each of the
regulatory options.
Uncertain
EPA's analysis does not quantify the
baseline distribution of TTHM
concentrations, bladder cancer cases, and
excess bladder cancer deaths across
drinking water systems, but instead focuses
on the change resulting from the regulatory
options. The analysis does not provide
insight into any existing distributional
disparities in the baseline, such as poorer
communities being less able to afford
treatment system upgrades to mitigate
TTHM formation, leading to higher levels of
TTHM concentrations and incidence of
bladder cancer cases and deaths-among
populations served by affected drinking
water systems.
Table 34. Limitations and Uncertainties of EPA's Distributional Analysis of Cumulative Risks
Uncertainty/Limitation
EPA estimated the distribution of
cumulative risks across human health
endpoints for only mixtures of pollutants
discharged to surface waters from the
evaluated wastestreams included in the
steam electric supplemental rule.
Effect on
Analysis
Underestimate
Notes
The analysis did not extend to pollutant
loadings from other wastestreams present
at steam electric power plants or
contributions from other point or nonpoint
sources. EPA's pollutant loadings analysis
and cumulative impacts modeling runs
specifically evaluate the changes in
pollutant loadings that result from the
regulatory options considered under the
proposed supplemental rule. Pollutant
loadings from other wastestreams at steam
electric power plants are assumed to
remain the same under baseline and option
scenarios and are not considered in the
analysis. Therefore, the pollutant loadings
considered in the analysis are an
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Section 6—Limitations and Uncertainties
Table 34. Limitations and Uncertainties of EPA's Distributional Analysis of Cumulative Risks
Uncertainty/Limitation
Effect on
Analysis
Notes
underestimate of the total potential
cumulative risk across human health
endpoints posed by steam electric
discharges to the environment.
Exposure concentrations for all pollutants
except lead in the cumulative risk analysis
are based only on steam electric power
plant discharges and do not reflect other
potential pollutant sources in the vicinity.
Underestimate
The cumulative risk analysis did not consider
pollutant loadings emitted from other
sources near the affected communities.
Lead blood concentrations used in the
cumulative analysis were the exception. The
IEUBK model, used to estimate lead blood
concentrations, considered lead
contributions from soil, dust, air, and water,
in addition to lead contributions from fish
consumption from waters that receive
discharges of the evaluated wastestreams.
During public meetings held by EPA with
communities with EJ concerns, participants
often cited multiple sources of pollution in
their communities in addition to the local
plants that were of concern. This suggests a
potential underestimation of distributional
disparities in cumulative risks among
affected communities.
EPA limited the cumulative risks assessment
across human health endpoints for only
mixtures of pollutants with a published
Interaction Profile.
Underestimate
EPA identified only five pollutants {i.e.,
arsenic, cadmium, lead, methylmercury, and
zinc) in the IRW Model with published
ATSDR Interaction Profiles. EPA did not
estimate cumulative risks across human
health endpoints for mixtures of the
remaining four pollutants in the IRW Model.
There may be additional mixtures of
concern that result in cumulative impacts to
communities not represented in the
analysis.
Results from the analysis are limited to the
distribution of cumulative risks across
human health endpoints for only child
cohorts under the age of 11 years old.
Underestimate
Lead is included in all three pollutant
mixtures evaluated in the cumulative risk
analysis. The IEUBK model only determines
blood lead concentrations for children
under the age of seven years old. Therefore,
the cumulative risk analysis for the
methylmercury-lead and lead-zinc mixtures
are limited to child cohorts under the age of
11 years old (based on crosswalk of age
groups). Arsenic-lead-cadmium mixtures
may also be limited to the under 11 years
old child cohorts if arsenic or cadmium
105
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Section 6—Limitations and Uncertainties
Table 34. Limitations and Uncertainties of EPA's Distributional Analysis of Cumulative Risks
Uncertainty/Limitation
Effect on
Analysis
Notes
endpoint-specific HQ values are not greater
than or equal to 0.1.
Table 35. Limitations and Uncertainties of EPA's Distributional Analysis of Costs and Benefits
Uncertainty/Limitation
Effect on Analysis
Notes
EPA's analysis of benefits focused on a
subset of benefits from the proposed
regulation, e.g., benefits from air pollution
reductions from steam electric power
plants.
Underestimation
EPA's benefits analysis did not value
potential additional benefits resulting
from the proposed rule. For example, in
EPA's public meetings, community
members discussed predominantly using
bottled water for drinking water and
everyday household activities given their
concerns about pollutants in their drinking
water from steam electric power plants
and emphasized the high cost of doing so.
EPA's analysis of benefits from the
proposed rule evaluated benefits for the
time period 2025-2049.
Underestimate
EPA's analysis did not calculate benefits to
affected populations from the proposed
rule after 2049, and therefore may not
capture longer-term effects on economic
disparities that may exist under the
baseline. For example, in EPA's public
meetings, community members noted
long-term economic losses in their
communities due to water pollution from
steam electric power plants damaging key
industries like recreational tourism.
Improvements in water quality in these
communities as a result of the proposed
rule, therefore, may have long-term
benefits from reducing averting behaviors
and restoring livelihoods in that may not
be fully captured in the benefits analysis.
EPA's analysis of the distribution of costs
focused on evaluating the distribution of
the changes in household electricity prices
under the proposed rule.
Underestimate
EPA's analysis of the distribution of costs
did not capture other costs with potential
disparities that may be incurred by
affected communities as a result of the
proposed rule.
EPA's distributional analysis of benefits and
costs qualitatively discusses potential
differences in apportionment of costs and
benefits among population groups of
concern.
Uncertain
EPA was not able to quantitatively analyze
the apportionment of costs and benefits
among population groups of concern
given the lack of information about how
different costs and benefits may be
incurred across population groups. For
example, there is uncertainty about how
106
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Section 6—Limitations and Uncertainties
Table 35. Limitations and Uncertainties of EPA's Distributional Analysis of Costs and Benefits
Uncertainty/Limitation
Effect on Analysis
Notes
to value benefits from air quality
improvements across various racial/ethnic
groups.
107
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7. Conclusions
Overall, EPA's EJ analysis showed that the extent to which the technologies steam electric power plants
implement to control wastewater discharges will reduce differential baseline exposures for low-income
populations and people of color in affected communities to pollutants in wastewater and resulting human
impacts varies. In particular, benefits associated with improvements to water quality, wildlife, and human
health resulting from reductions in pollutants in surface water will accrue to some low-income
populations and people of color at a higher rate under some or all of the regulatory options. Benefits
associated with drinking water will accrue to people of color and low-income populations at a higher rate
under the final rule. Remaining exposures, impacts, costs, and benefits analyzed either accrue at a higher
rate to populations which are not people of color or low-income, accrue proportionately to all
populations, or are small enough that EPA could not conclude whether changes in disproportionate
impacts would occur. While the changes in GHGs attributable to the final rule are small compared to
worldwide emissions, findings from peer-reviewed evaluations demonstrate that actions that reduce GHG
emissions are also likely to reduce climate-related impacts on vulnerable communities, including low-
income communities and communities of color.
-------
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112
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APPENDIX A: Results from the Proximity Analysis of Downstream Surface
Waters
This section of the appendix presents the results of the nationwide proximity analysis EPA conducted to
assess the socioeconomic characteristics of communities living in proximity (within 50 miles) of a
downstream surface water receiving discharges from steam electric power plants. The socioeconomic
results presented are for Period 1 which covers the years 2025 through 2029 when the universe of plants
would transition from current (baseline) treatment practices to practices that achieve the revised effluent
limits.
-------
APPENDIX A—Results from the Proximity Analysis of Downstream Surface Waters
Table A-l. Percent of the Population Living within 50 Miles of an Affected Downstream Reach with Modeled Concentrations of Selected Pollutants under the
Regulatory Options Identifying as Low-Income Compared to the National Average (Period 1)
Pollutant
Changes in
Percentage of Reaches
Percent Low-Income
Concentrations
Option A
Option B
Option C
Option A
Option B
Option C
Antimony
Decreases
87.2%
87.7%
88.3%
12.6%
12.6%
12.6%
No changes
11.3%
10.7%
10.1%
14.6%
14.6%
14.8%
Arsenic
Decreases
87.2%
87.7%
88.3%
12.6%
12.6%
12.6%
No changes
12.8%
12.3%
11.7%
14.4%
14.4%
14.5%
Cadmium
Decreases
87.2%
87.7%
88.3%
12.6%
12.6%
12.6%
No changes
12.8%
12.3%
11.7%
14.4%
14.4%
14.5%
Cyanide(a)
Decreases
31.3%
31.3%
35.1%
13.6%
13.6%
13.6%
No changes
5.9%
5.9%
2.1%
13.1%
13.1%
13.2%
Lead(a)
Decreases
56.8%
56.8%
56.8%
12.2%
12.2%
12.2%
No changes
10.0%
10.0%
10.0%
13.6%
13.6%
13.6%
Manganese
Decreases
87.2%
87.7%
88.3%
12.6%
12.6%
12.6%
No changes
12.8%
12.3%
11.7%
14.4%
14.4%
14.5%
Mercury
Decreases
87.2%
87.7%
88.3%
12.6%
12.6%
12.6%
No changes
12.8%
12.3%
11.7%
14.4%
14.4%
14.5%
Thallium
Decreases
87.2%
87.7%
88.3%
12.6%
12.6%
12.6%
No changes
12.8%
12.3%
11.7%
14.4%
14.4%
14.5%
United States
12.9%
Source: U.S. EPA analysis, 2024
Notes:
Not all of the steam electric plants discharged cyanide and lead. The associated socioeconomic characteristic information is only for the set of reaches with non-zero loadings for those pollutants.
A-l
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APPENDIX A—Results from the Proximity Analysis of Downstream Surface Waters
Table A-2. Percent of the Population Living within 50 Miles of an Affected Downstream Reach with Modeled Concentrations of Selected Pollutants under the
Regulatory Options Identifying as a Racial or Ethnic Minority Compared to the National Average (Period 1)
Pollutant
Changes in
Percent of Reaches
Percent African American
Percent Asian
Percent Native
Hawaiian/Pacific Islander
Concentrations
Option A
Option B
Option C
Option A
Option B
Option
C
Option
A
Option
B
Option
C
Option
A
Option
B
Option
C
Antimony
Decreases
87.2%
87.7%
88.3%
15.1%
15.2%
15.1%
3.8%
3.8%
3.8%
0.1%
0.1%
0.1%
No changes
11.3%
10.7%
10.1%
18.4%
18.2%
18.9%
2.6%
2.6%
2.6%
0.1%
0.1%
0.1%
Arsenic
Decreases
87.2%
87.7%
88.3%
15.1%
15.1%
15.1%
3.8%
3.8%
3.8%
0.1%
0.1%
0.1%
No changes
12.8%
12.3%
11.7%
18.1%
18.0%
18.5%
2.5%
2.5%
2.6%
0.1%
0.1%
0.1%
Cadmium
Decreases
87.2%
87.7%
88.3%
15.1%
15.1%
15.1%
3.8%
3.8%
3.8%
0.1%
0.1%
0.1%
No changes
12.8%
12.3%
11.7%
18.1%
18.0%
18.5%
2.5%
2.5%
2.6%
0.1%
0.1%
0.1%
Cyanide(a)
Decreases
31.3%
31.3%
35.1%
18.1%
18.1%
19.1%
2.7%
2.7%
2.7%
0.1%
0.1%
0.1%
No changes
5.9%
5.9%
2.1%
18.0%
18.0%
14.0%
4.7%
4.7%
5.7%
0.0%
0.0%
0.0%
Lead(a)
Decreases
56.8%
56.8%
56.8%
14.1%
14.1%
14.1%
3.7%
3.7%
3.7%
0.1%
0.1%
0.1%
No changes
10.0%
10.0%
10.0%
16.1%
16.1%
16.1%
4.6%
4.6%
4.6%
0.1%
0.1%
0.1%
Manganese
Decreases
87.2%
87.7%
88.3%
15.1%
15.1%
15.1%
3.8%
3.8%
3.8%
0.1%
0.1%
0.1%
No changes
12.8%
12.3%
11.7%
18.1%
18.0%
18.5%
2.5%
2.5%
2.6%
0.1%
0.1%
0.1%
Mercury
Decreases
87.2%
87.7%
88.3%
15.1%
15.1%
15.1%
3.8%
3.8%
3.8%
0.1%
0.1%
0.1%
No changes
12.8%
12.3%
11.7%
18.1%
18.0%
18.5%
2.5%
2.5%
2.6%
0.1%
0.1%
0.1%
Thallium
Decreases
87.2%
87.7%
88.3%
15.1%
15.1%
15.1%
3.8%
3.8%
3.8%
0.1%
0.1%
0.1%
No changes
12.8%
12.3%
11.7%
18.1%
18.0%
18.5%
2.5%
2.5%
2.6%
0.1%
0.1%
0.1%
United States
12.1%
5.6%
0.2%
Source: U.S. EPA analysis, 2024
Notes:
Not all of the steam electric plants discharged cyanide and lead. The associated socioeconomic characteristic information is only for the set of reaches with non-zero loadings for those pollutants.
A-2
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APPENDIX A—Results from the Proximity Analysis of Downstream Surface Waters
Table A-3. Percent of the Population Living within 50 Miles of an Affected Downstream Reach with Modeled Concentrations of Selected Pollutants under the
Regulatory Options Identifying as a Racial or Ethnic Minority Compared to the National Average (Period 1)
Pollutant
Changes in
Concentration
s
Percent of Reaches
Percent American
Indian/Alaska Native
Percent Other non-Hispanic
Percent Hispanic/Latino
Option A
Option
B
Option
C
Option
A
Option B
Option
C
Option
A
Option B
Option
C
Option
A
Option B
Option C
Antimony
Decreases
87.2%
87.7%
88.3%
0.4%
0.4%
0.4%
3.3%
3.3%
3.3%
10.9%
10.9%
10.9%
No changes
11.3%
10.7%
10.1%
0.2%
0.2%
0.2%
2.9%
2.9%
2.9%
16.9%
17.1%
17.9%
Arsenic
Decreases
87.2%
87.7%
88.3%
0.4%
0.4%
0.4%
3.3%
3.3%
3.3%
11.0%
11.0%
10.9%
No changes
12.8%
12.3%
11.7%
0.2%
0.2%
0.2%
3.0%
3.0%
3.0%
15.6%
15.8%
16.4%
Cadmium
Decreases
87.2%
87.7%
88.3%
0.4%
0.4%
0.4%
3.3%
3.3%
3.3%
11.0%
11.0%
10.9%
No changes
12.8%
12.3%
11.7%
0.2%
0.2%
0.2%
3.0%
3.0%
3.0%
15.6%
15.8%
16.4%
Cyanide(a)
Decreases
31.3%
31.3%
35.1%
0.2%
0.2%
0.2%
3.2%
3.2%
3.2%
6.5%
6.5%
6.7%
No changes
5.9%
5.9%
2.1%
0.1%
0.1%
0.1%
2.9%
2.9%
2.8%
18.6%
18.6%
24.7%
Lead(a)
Decreases
56.8%
56.8%
56.8%
0.5%
0.5%
0.5%
3.4%
3.4%
3.4%
7.2%
7.2%
7.2%
No changes
10.0%
10.0%
10.0%
0.4%
0.4%
0.4%
3.2%
3.2%
3.2%
20.7%
20.7%
20.7%
Manganes
e
Decreases
87.2%
87.7%
88.3%
0.4%
0.4%
0.4%
3.3%
3.3%
3.3%
11.0%
11.0%
10.9%
No changes
12.8%
12.3%
11.7%
0.2%
0.2%
0.2%
3.0%
3.0%
3.0%
15.6%
15.8%
16.4%
Mercury
Decreases
87.2%
87.7%
88.3%
0.4%
0.4%
0.4%
3.3%
3.3%
3.3%
11.0%
11.0%
10.9%
No changes
12.8%
12.3%
11.7%
0.2%
0.2%
0.2%
3.0%
3.0%
3.0%
15.6%
15.8%
16.4%
Thallium
Decreases
87.2%
87.7%
88.3%
0.4%
0.4%
0.4%
3.3%
3.3%
3.3%
11.0%
11.0%
10.9%
No changes
12.8%
12.3%
11.7%
0.2%
0.2%
0.2%
3.0%
3.0%
3.0%
15.6%
15.8%
16.4%
United States
0.6%
3.5%
19.2%
Source: U.S. EPA analysis, 2024
Notes:
Not all of the steam electric plants discharged cyanide and lead. The associated socioeconomic characteristic information is only for the set of reaches with non-zero loadings for those pollutants.
A-3
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