United States Office of Water EPA-821-R-15-006

Environmental Protection Washington, DC 20460 September 2015 Agency



# Environmental Assessment

for the Effluent Limitations

Guidelines and Standards

for the Steam Electric Power Generating Point Source Category

# Environmental Assessment for the Effluent

Limitations Guidelines and Standards for the Steam Electric Power Generating Point Source Category

EPA-821-R-15-006

September 2015

U.S. Environmental Protection Agency Office of Water (4303T) Engineering and Analysis Division 1200 Pennsylvania Avenue, NW Washington, DC 20460Acknowledgements and Disclaimer

This report was prepared by the U.S. Envir onmental Protection Agency. Neither the United States Government nor any of its employees, contractors, subc ontractors, or their employees make any warrant, expressed or implied, or assume any legal liability or responsibility for any third party’s use of or the results of such use of any informati on, apparatus, product, or process discussed in this report, or repr esents that its use by such part y would not infrin ge on privately owned rights.Table of Contents

TABLE OF CONTENTS Page

A CRONYMS

.............................................................................................................................. ... VIII

G LOSSARY

.............................................................................................................................. ....... XI

S ECTION 1 I NTRODUCTION

.......................................................................................................... 1-1

S ECTION 2 B ACKGROUND AND S COPE

........................................................................................ 2-1

S ECTION 3 E NVIRONMENTAL A ND H UMAN H EALTH C ONCERNS

.............................................. 3-1

3.1 Types of Pollutants Discharged in Steam Electric Power Plant Wastewater

........... 3-2

3.1.1 Metals and Toxic Bioaccumulative Pollutants

............................................. 3-2

3.1.2 Nutrients

....................................................................................................... 3-9

3.1.3 TDS

............................................................................................................... 3-9

3.2 Loadings Associated with Steam El ectric Power Plant Wastewater

...................... 3-12

3.2.1 Annual Baseline Pollutant Loadings

.......................................................... 3-13

3.2.2 Comparison of Steam Electric Po wer Plant Loadings to Other

Industries

.................................................................................................... 3-15

3.2.3 Comparison of Steam Electric Powe r Plant Loadings to Publicly

Owned Treatment Works

........................................................................... 3-16

3.3 Environmental Impacts from Steam Elect ric Power Plant Wastewater

................. 3-20

3.3.1 Ecological Impacts

..................................................................................... 3-20

3.3.2 Human Health Effects

................................................................................ 3-27

3.3.3 Damage Cases and Other Document ed Surface Water Impacts

................ 3-28

3.3.4 Damage Cases and Other Docume nted Ground Water Impacts

................ 3-35

3.3.5 Potential for Impacts to Occur in Other Locations

..................................... 3-37

3.4 Discharge to Sensitive Environments

..................................................................... 3-38

3.4.1 Pollutant Loadings to the Great Lakes Watershed

..................................... 3-38

3.4.2 Pollutant Loadings to the Chesapeake Bay Watershed

.............................. 3-40

3.4.3 Proximity to Impair ed Waters

.................................................................... 3-42

3.4.4 Proximity to Fish Consumption Advisory Waters

..................................... 3-44

3.4.5 Proximity to Threatened and E ndangered Species Habitats

....................... 3-45

3.4.6 Proximity to Drinking Water Resources

.................................................... 3-46

3.5 Long Environmental Recovery Times A ssociated with Pollutants in Steam

Electric Power Plant Wastewater

............................................................................ 3-47

S ECTION 4 A SSESSMENT OF E XPOSURE P ATHWAYS

.................................................................. 4-1

4.1 Discharge and Leaching to Surface Waters

.............................................................. 4-2

4.1.1 Factors Controlling Environmental Impacts in Surface Waters

................... 4-2

4.1.2 Assessment of the Surface Water Exposure Pathway

.................................. 4-4

4.2 Leaching to Ground Water

....................................................................................... 4-7

4.2.1 Factors Controlling Environmental Impacts to Ground Water

.................... 4-7

4.2.2 Assessment of the Ground Water Exposure Pathway

................................ 4-12

4.3 Combustion Residual Surface Impoundment s as Attractive Nuisance

.................. 4-12

iTable of Contents

TABLE OF CONTENTS (Continued) Page

S ECTION 5 S URFACE W ATER M ODELING

................................................................................... 5-1

5.1 Immediate Receiving Water (IRW) Model

.............................................................. 5-1

5.1.1 Water Quality Module

.................................................................................. 5-3

5.1.2 Wildlife Module

........................................................................................... 5-8

5.1.3 Human Health Module

............................................................................... 5-10

5.2 Ecological Risk Modeling

...................................................................................... 5-12

S ECTION 6 C URRENT I MPACTS FROM S TEAM E LECTRIC P OWER G ENERATING
I NDUSTRY

......................................................................................................................... 6-1

6.1 Water Quality Impacts

.............................................................................................. 6-1

6.2 Wildlife Impacts

....................................................................................................... 6-3

6.2.1 Impacts to Wildlife Indicator Species

.......................................................... 6-3

6.2.2 Impacts to Fish and Waterfowl due to Dietary Selenium Exposure

............ 6-4

6.2.3 Impacts to Benthic Organisms

...................................................................... 6-6

6.3 Human Health Impacts

............................................................................................. 6-7

6.3.1 National-Scale Cohort Analysis

................................................................... 6-8

6.3.2 Environmental Justice Analysis

................................................................. 6-12

S ECTION 7 E NVIRONMENTAL I MPROVEMENTS U NDER THE F INAL R ULE

................................ 7-1

7.1 Pollutant Removals Under the Regulatory Options

.................................................. 7-5

7.2 Key Environmental Improvements

........................................................................... 7-9

7.2.1 Improvements in Water Quality Under the Final Rule

................................ 7-9

7.2.2 Reduced Threat to Wildlife Under the Final Rule

...................................... 7-13

7.2.3 Reduced Human Health Cancer Risk Under the Final Rule

...................... 7-15

7.2.4 Reduced Threat of Non-Cancer Human Health Effects Under the

Final Rule

................................................................................................... 7-15

7.2.5 Reduced Human Health Risk for Environmental Justice Analysis

............ 7-15

7.3 Pollutant-Specific Improvements

........................................................................... 7-16

7.3.1 Arsenic

........................................................................................................ 7-16

7.3.2 Mercury

...................................................................................................... 7-19

7.3.3 Selenium

..................................................................................................... 7-21

7.3.4 Cadmium

.................................................................................................... 7-25

7.3.5 Thallium

..................................................................................................... 7-25

7.4 Improvements to Sen sitive Environments

.................................... ... . . . .................. . 7-28

7.4.1 Impaired Waters

......................................................................................... 7-28

7.4.2 Threatened and Endangered Species

.......................................................... 7-31

7.4.3 Fish Advisory Waters

................................................................................. 7-31

7. 5 Improvements to Watersheds

........ . . . . . . . . . . . . . .......................... ........ ........ ................. . 7-31

7.6 Environmental and Human Health Improvements in Downstream Surface

Water

....................................................................................................................... 7 -34

7.7 Attractive Nuisances

............................................................................................... 7-37

7.8 Other Secondary Improvements

............................................................................. 7-37

7.9 Unresolved Drinking Water Impacts Due to Bromide Discharges

........................ 7-38

S ECTION 8 C ASE S TUDY M ODELING

........................................................................................... 8-1

8.1 Case Study Modeling Methodology

......................................................................... 8-2

iiTABLE OF CONTENTS (Continued) Table of Contents

Page

8.1.1 Selection of Case Study Loca tions for Modeling

......................................... 8-2

8.1.2 Scope and Technical Approach for Case Study Modeling

........................... 8-7

8.1.3 Development and Execution of WASP Models

......................................... 8-11

8.1.4 Use of WASP Water Qual ity Model Outputs

............................................. 8-13

8.1.5 Limitations of Case Study Modeling

.......................................................... 8-14

8.2 Quantified Environmental Impacts and Improvements from Case Study Modeling

................................................................................................................. 8-14

8.2.1 Black Creek Case Study

............................................................................. 8-15

8.2.2 Etowah River Case Study

........................................................................... 8-24

8.2.3 Lick Creek & White River Case Study

...................................................... 8-31

8.2.4 Ohio River Case Study

............................................................................... 8-41

8.2.5 Mississippi River Case Study

..................................................................... 8-47

8.2.6 Lake Sinclair Case Study

............................................................................ 8-52

8.3 Comparison of Case Study and IRW Modeling Results

........................................ 8-58

S ECTION 9 C ONCLUSIONS

........................................................................................................... 9-1

S ECTION 10 R EFERENCES

......................................................................................................... 10-1

Appendix A: Literature Re view Methodology and Results Appendix B: Proximity Analyses Supporting Tables Appendix C: Water Quality Module Methodology Appendix D: Wildlife Module Methodology Appendix E: Human Health Module Methodology Appendix F: Overview of Ecological Risk Modeling Se tup and Outputs Appendix G: Overview of Case Study Modeling Setup and Outputs Appendix H: Additional Model Results Appendix I: Analyses for Alternate Scenario with Clean Power Plan Appendix J: EA Loadings and TDD Loadings: Sensitivity Analysis

iiiList of Tables

LIST OF TABLES Page

Table 2-1. Steam Electric Power Plant Wastestreams Evaluated in the EA

................................ 2-2

Table 2-2. Number of Plants Evaluated in the EA

....................................................................... 2-4

Table 3-1. Key Metals and Toxic Bioaccumu lative Pollutants Found In Steam Electric

Power Plant Wastewater

.................................................................................................. 3-3

Table 3-2. Annual Baseline Pollutant Discha rges from Steam Electric Power Plants (Evaluated Wastestreams)

.............................................................................................. 3-14

Table 3-3. Pollutant Loadings for the Final 2010 Effluent Guidelines Planning Process: Top 10 Point Source Categories

.................................................................................... 3-15

Table 3-4. Comparison of Average Pollutant Lo adings in the Evaluated Wastestreams to an Average POTW

......................................................................................................... 3-18

Table 3-5. Estimated Number of POTW Equiva lents for Total Pollutant Loadings from

the Evaluated Wastestreams

.......................................................................................... 3-19

Table 3-6. Summary of Studies Evaluating Leth al Effects of Pollutants in Steam Electric

Power Plant Wastewater

................................................................................................ 3-25

Table 3-7. Median Lethal Concentrations (LC 50 ) for Pollutants in Steam Electric Power

Plant Wastewater

........................................................................................................... 3- 26

Table 3-8. Summary of Select Sites with Do cumented Surface Water Impacts from Steam

Electric Power Plant Wastewater

................................................................................... 3-30

Table 3-9. Number and Percentage of Immediate Receiving Waters Identified as

Sensitive Environments

................................................................................................. 3-38

Table 3-10. Pollutant Loadings to the Gr eat Lakes Watershed from the Evaluated

Wastestreams

................................................................................................................. 3-40

Table 3-11. Pollutant Loadings to the Ches apeake Bay Watershed from the Evaluated

Wastestreams

................................................................................................................. 3-41

Table 3-12. Number and Percen tage of Immediate Receivi ng Waters Classified as Impaired for a Pollutant Associated w ith the Evaluated Wastestreams

........................ 3-42

Table 3-13. Comparison of Numb er and Percentage of Steam Electric Power Plants

Located within 5 Miles of a Drinking Water Resource

................................................. 3-47

Table 4-1. Steam Electric Power Plant Wastew ater Environmental Pathways and Routes of Exposure Evaluated in the EA

..................................................................................... 4-2

Table 4-2. Receiving Water Types for Steam Electri c Power Plants Evaluated in the EA

......... 4-3

Table 4-3. Exceedances of MCLs in Leach ate Under Acidic, Neutral, and Basic

Conditions

.................................................................................................................... .... 4-9

Table 4-4. Range of Fly Ash and FGD Gyps um Total Content and Combustion Residual Leaching Test Results (Initial Screeni ng Concentrations) for Trace Metals

................. 4-11

Table 5-1. Pollutants Considered for Analysis in the Immediate Receiving Water Model

......... 5-5

ivList of Tables ( Continued ) List of Tables

Page

Table 6-1. Number and Percentage of Im mediate Receiving Waters with Estimated

Water Concentrations that Exceed the Wa ter Quality Criteria at Baseline

..................... 6-2

Table 6-2. Number and Percentage of Imme diate Receiving Waters That Exceed Wildlife Fish Consumption NEHCs for Minks and Eagles (by Waterbody Type) at

Baseline

...................................................................................................................... ...... 6-4

Table 6-3. Number and Percentage of Imme diate Receiving Waters That Exceed Wildlife Fish Consumption NEHCs for Minks and Eagles (by Pollutant) at Baseline

.................. 6-5

Table 6-4. Number and Percentage of Im mediate Receiving Waters with Sediment Pollutant Concentrations Exceeding CSCLs for Sediment Biota at Baseline

................. 6-7

Table 6-5. Number and Percentage of Imme diate Receiving Waters That Exceed Human Health Evaluation Criteria (Lifetime Excess Cancer Risk) for Inorganic Arsenic at

Baseline

...................................................................................................................... ...... 6-9

Table 6-6. Number and Percentage of Im mediate Receiving Waters That Exceed NonCancer Oral Reference Dose Values at Baseline

........................................................... 6-10

Table 6-7. Number and Percentage of Im mediate Receiving Waters That Exceed NonCancer Oral Reference Dose Values at Baseline by Pollutant

...................................... 6-11

Table 6-8. Comparison of T4 Fish Tissue Concen trations at Baseline to Fish Advisory Screening Values

........................................................................................................... 6-12

Table 6-9. Number and Percentage of Imme diate Receiving Waters That Exceed Human Health Evaluation Criteria (Lifetime Excess Cancer Risk) for Inorganic Arsenic at Baseline, by Race or Hispanic Origin

............................................................................ 6-13

Table 6-10. Number and Percen tage of Immediate Receiving Waters That Exceed NonCancer Oral Reference Dose Values at Ba seline, by Race or Hispanic Origin

............. 6-14

Table 7-1. Regulatory Options for the Wast estreams Evaluated in the EA

................................. 7-2

Table 7-2. Description of Environmental Improvem ents Associated with the Final Rule

.......... 7-3

Table 7-3. Steam Electric Power Generating In dustry Pollutant Removals for Metals, Bioaccumulative Pollutants, Nutrients, Chlorides, and TDS Under Regulatory Options

....................................................................................................................... ...... 7-7

Table 7-4. Steam Electric Power Generating Industry TWPE Removals for Metals, Bioaccumulative Pollutants, Nutrients, Chlorides, and TDS Under Regulatory Options

....................................................................................................................... ...... 7-8

Table 7-5. Key Environmental Improvements Under the Regulatory Options

......................... 7-11

Table 7-6. Number of Immediate Receiving Waters with Sediment Pollutant Concentrations Exceeding CSCLs for Se diment Biota Under the Regulatory Options

....................................................................................................................... .... 7-14

Table 7-7. Key Environmental Improvements for Arsenic Under the Regulatory Options

...... 7-17

Table 7-8. Key Environmental Improvements for Mercury Under the Regulatory Options

..... 7-20

vList of Tables ( Continued ) List of Tables

Page

Table 7-9. Key Environmental Improvement s for Selenium Under the Regulatory Options

....................................................................................................................... .... 7-23

Table 7-10. Key Environmental Improveme nts for Cadmium Under the Regulatory Options

....................................................................................................................... .... 7-26

Table 7-11. Key Environmental Improvement s for Thallium Under the Regulatory Options

....................................................................................................................... .... 7-27

Table 7-12. Pollutant Removals to Impair ed Waters by Impairment Type

............................... 7-29

Table 7-13. Pollutant Removals to the Gr eat Lakes Watershed Under the Regulatory Options

....................................................................................................................... .... 7-33

Table 7-14. Key Environmental Improvements for Downstream Waters Under the Regulatory Options

........................................................................................................ 7-3 5

Table 8-1. Locations Selected for Case Study Modeling

............................................................ 8-4

Table 8-2. Summary of Morrow Gene rating Site Operations

.................................................... 8-15

Table 8-3. Summary of Plant Bowen Operations

...................................................................... 8-25

Table 8-4. Summary of Petersburg Ge nerating Station Operations

.......................................... 8-32

Table 8-5. Summary of Bruce Mansfield Operations

................................................................ 8-42

Table 8-6. Summary of W.H. Sammis Operations

.................................................................... 8-42

Table 8-7. Summary of Rush Island Operations

........................................................................ 8-48

Table 8-8. Summary of Plant Har llee Branch Operations

......................................................... 8-53

viList of Figures List of Figures

Page

Figure 2-1. Locations and Counts of Immedi ate Receiving Waters in EA Scope and Modeling Analyses

.......................................................................................................... 2- 5

Figure 3-1. Location of Plants th at Directly Discharge the Evaluated Wastestreams to a Surface Water Impaired due to Mercury

....................................................................... 3-43

Figure 3-2. Location of Plants that Directly Discharge the Evaluated Wastestreams to a Surface Water Impaired due to Metals, Other than Mercury

......................................... 3-43

Figure 3-3. Location of Plants that Directly Discharge the Evaluated Wastestreams to a Surface Water Impaired due to Nutrients

...................................................................... 3-44

Figure 3-4. Location of Plants that Directly Discharge to a Surface Water with a Fish Consumption Advisory

.................................................................................................. 3-45

Figure 5-1. Overview of IRW Model

.......................................................................................... 5- 3

Figure 5-2. Water Quality Module: Pollutant Fate in the Waterbody

......................................... 5-7

Figure 5-3. Flowchart of Selenium Ecological Risk Model

...................................................... 5-15

Figure 8-1. Overview of Case Study Modeling Locations

.......................................................... 8-3

Figure 8-2. Black Creek WA SP Modeling Area

....................................................................... 8-16

Figure 8-3. Etowah River WASP Modeling Area

..................................................................... 8-26

Figure 8-4. Lick Creek and White River WASP Modeling Area

.............................................. 8-33

Figure 8

- 5

. Ohio River WA SP Modeling Area

......................................................................... 8-43

Figure 8- 6 . Mississippi R iv er WASP M odeling Area ...................

. . . ......................................... 8-49

Figure 8- 7 . Lake Sinclair WASP and EDFC Modeling Area

.............................. . . . . .................. 8-54

viiAcronyms



## ACRONYMS

ASTM American Society fo r Testing and Materials

ATSDR Agency for Toxic Substances and Disease Registry

BAF Bioaccumulation factor

BASINS Better Assessment Science In tegrating Point a nd Nonpoint Sources

BAT Best Available Technol ogy Economically Achievable

BCF Bioconcentration factor

BPT Best Practicable Control Technology Currently Available

CBI Confidential business information

CCR Coal combustion residuals

CFR Code of Federal Regulations

CSCL Chemical stressor concentration limit

CSF Cancer slope factor

CWA Clean Water Act

DBP Disinfection by-products

DCN Document control number

DMR Discharge monitoring report

DOE Department of Energy

EA Environmental assessment

EF Enrichment factors

EFDC Environmental Fluid Dynamics Code

ELGs Effluent Limitations Guidelines and Standards

EP Extraction procedure

EPA U.S. Environmental Protection Agency

ER Exposure-response
ESA Endangered Species Act

FGD Flue gas desulfurization

FGMC Flue gas mercury control

FR Federal Register

FWS U.S. Fish and Wildlife Service

IRIS Integrated Risk Information System

IRW Immediate receiving water

Kd

sw Suspended sediment-surface water partition coefficient

LADD Lifetime average daily dose

lbs/yr Pounds per year

LC 50 Median lethal concentration

LECR Lifetime excess cancer risk

viiiAcronyms

MCL Maximum contaminant level

MRL Minimal risk level

MGD Million gallons per day

mg/day Milligrams per day

mg/kg Milligrams per kilogram

mg/L Milligrams per liter

MW Megawatt
MWh Megawatt-hour

NEHC No effect hazard concentration

NHDPlus National Hydrography Dataset Plus

NOAA National Oceanic and A tmospheric Administration

NOAEL No-observed-adverse-effect level

NPDES National Pollutant Discharge Elimination System

NRWQC National Recommended Water Quality Criteria

NSPS New Source Performance Standards

NWIS National Water Information System

ORCR Office of Resource Conservation and Recovery

OSWER Office of Solid Waste and Emergency Response

PCB Polychlorinated biphenyls

POC Pollutant of concern

POTW Publicly owned treatment works

ppm Parts per million

PSES Pretreatment Standards for Existing Sources

PSNS Pretreatment Standards for New Sources

RCRA Resource Conservation and Recovery Act

RfD Reference dose
RIA Regulatory impact analysis

RSEI Risk-Screening Environmental Indicators

SDWA Safe Drinking Water Act

SQuiRT Screening Quick Reference Table

STORET EPA’s STOrage and RETrieval Data Warehouse

T3 Trophic level 3

T4 Trophic level 4

TC Toxicity characteristic

TCLP Toxicity characteris tic leaching procedure

TDD Technical Development Document

TDS Total dissolved solids

TEL Threshold effects level

ixAcronyms

TMDL Total maximum daily load

TOC Total organic carbon

TRI Toxics Release Inventory

TSS Total suspended solids

TTF Trophic transfer factor

TTHM Total trihalomethanes

TWF Toxic weighting factor

TWPE Toxic weighted pound equivalent

μ g/g Micrograms per gram

μ g/L Micrograms per liter

USGS United States Geological Survey

WASP Water Quality Analysis Simulation Program

WHO World Health Organization

WMA Wildlife Management Area

WQI Water quality index

xGlossary



## GLOSSARY

Acute – having a sudden onset or lasting a short tim e. An acute stimulus is severe enough to induce a response rapidly. The word acute can be used to define either the exposure or the response to an exposure (effect). Th e duration of an acute aquatic toxi city test is generally 4 days or less and mortality is th e response usually measured.

Aquifer – an underground formation or group of form ations in rocks and soils containing enough ground water to supply wells and springs.

Benthic – pertaining to the bottom (bed) of a waterbody.

Bioaccumulation – general term describing a process by which chemicals are taken up by an organism either directly from exposure to a contaminated medi um or by consumption of food containing the chemical, resulting in a net accumu lation of the chemical by an organism due to uptake from all routes of exposure.

Bioavailability – the ability of a particular contaminan t to be assimilated into the tissues of exposed organisms.

Biomagnification – result of the process of bioaccumu lation and biotransfer by which tissue concentrations of chemicals in organisms at one trophic level exceed tissue concentrations in organisms at the next lower trophic level in a food chain.

Bottom ash – the ash, including boiler slag, which set tles in the furnace or is dislodged from

furnace walls. Economizer ash is included when it is collected with bottom ash.

Chronic – involving a stimulus that is lingering or continues for a long time; often signifies periods from several weeks to years, depending on the reproductive life cycl e of the species. This

term can be used to define eith er the exposure or the response to an exposure (e ffect). Chronic exposures typically induce a biol ogical response of relatively slow progress and long duration.

Combustion residuals – solid wastes associated with comb ustion-related power plant processes, including fly and bottom ash from coal-, petr oleum coke-, or oil-fired units; flue gas desulfurization (FGD) solids; flue gas mercury control wastes; and other wastewater treatment

solids associated with steam elect ric power plant wastewater. In a ddition to the residuals that are associated with coal combustion, this also includes residuals a ssociated with the combustion of

other fossil fuels.

Combustion residual leachate – leachate from landfills or surface impoundments containing combustion residuals. Leachate is composed of liquid, including any suspended or dissolved constituents in the liquid, that has percolated through waste or other materials emplaced in a landfill, or that passes through the surface impoundment’s containment structure ( e.g. , bottom, dikes, berms). Combustion residual leachate incl udes seepage and/or leakage from a combustion residual landfill or impoundment unit. Combusti on residual leachate incl udes wastewater from landfills and surface impoundments located on non-adjoining property when under the operational control of the permitted facility.

xiGlossary

Criterion continuous concentration – an estimate of the highest c oncentration of a material in surface water to which an aquatic community can be exposed indefinitely (chronic exposure) without resulting in an unacceptable effect.

Criterion maximum concentration – an estimate of the highest concentration of a material in surface water to which an aquatic community can be exposed briefly (acute exposure) without resulting in an unacceptable effect.

Direct discharge – (a) Any addition of any “ pollutant” or combination of pollutants to “waters of the United States” from any “point source,” or (b) any addition of any pollutant or combination of pollutant to waters of the “contiguous zone” or the ocean from any point source other than a vessel or other floating craft which is being used as a means of transportation. This definition includes additions of pollutants into waters of the United States from: surface runoff which is collected or channeled by man; discharges thou gh pipes, sewers, or other conveyances owned by a State, municipality, or other person which do not lead to a tr eatment works; and discharges through pipes, sewers, or other c onveyances, leading into privately owned treatment works. This term does not include an addition of po llutants by any “indirect discharger.”

Edema – swelling caused by fluid in body tissues.

Effluent limitation – under Clean Water Act (CWA) sectio n 502(11), any restriction, including schedules of compliance, establ ished by a state or the Administ rator on quantities, rates, and concentrations of chemical, physical, biological, and other constituents which are discharged from point sources into navigabl e waters, the waters of the c ontiguous zone, or the ocean, including schedules of compliance.

Evaluated wastestreams – subset of steam electric power plant wastewaters evaluated in the environmental assessment (EA) and Benefits a nd Cost Analysis that includes FGD wastewater, fly ash transport water, bottom ash transport wa ter, and combustion resi dual leachate collected from landfills or surface impoundments.

Exposure – the contact or co-occurrence of a stressor w ith a receptor.

Flue gas desulfurization (FGD) wastewater – wastewater generated specifically from the wet FGD scrubber system that comes into contact with the flue gas or the FGD solids, including but not limited to, the blowdown or purge from th e FGD scrubber system, overflow or underflow from the solids separation process, FGD solids wash water, and the filtrate from the solids dewatering process. Wastewater generated fr om cleaning the FGD scrubber, cleaning FGD solids separation equipment, cleaning the FGD solids dewatering equipment, or that is collected in floor drains in the FGD process area is not considered FGD wastewater.

Flue gas mercury control (FGMC) wastewater – wastewater generated from an air pollution control system installed or operated for the pur pose of removing mercury from flue gas. This includes fly ash collection systems when the particulate control system follows sorbent injection or other controls to remove mercury from flue gas. FGD wastewater generated at plants using oxidizing agents to remove mercury in the FGD sy stem and not in a separate FGMC system is

not included in this definition.

xiiGlossary

Fly ash – the ash that is carried out of the furnace by a gas stream and collected by a capture device such as a mechanical pr ecipitator, electrostatic precipitator, and/or fabric filter.

Economizer ash is included in th is definition when it is collect ed with fly ash. Ash is not included in this definition when it is collected in wet scrubber air pollution control systems whose primary purpose is particulate removal.

Gasification wastewater – any wastewater generated at an in tegrated gasification combined cycle operation from the gasifier or the syngas cl eaning, combustion, and cooling processes. Gasification wastewater includes, but is not limited to the followi ng: sour/grey water; CO2/steam stripper wastewater; sulfur rec overy unit blowdown, and wastewat er resulting from slag handling or fly ash handling, particulate removal, halo gen removal, or trace organic removal. Air separation unit blowdown, noncontact cooling water, and runoff from fuel and/or byproduct piles are not considered gasification wastewater. Wastew ater that is collected intermittently in floor drains in the gasification process areas from leaks, spills and cleaning occurring during normal operation of the gasification operation is not considered gasi fication wastewater.

Ground water – water that is found in the saturate d part of the grou nd underneath the land

surface.

Hematological – pertaining to or em anating from blood cells.

Histopathological – pertaining to tissue changes.

Immediate receiving water – the segment of a receiving wate r where discharges from a point

source enter the surface water. The segment is defined by th e hydrographic dataset supporting the analysis ( e.g. , National Hydrography Dataset Plus, Version 1).

Impaired waters – a surface water is classified as a 303(d) impaired water when pollutant concentrations exceed water quality standards and the surface water can no longer meet its designated uses ( e.g. , drinking, recreation, a nd aquatic habitat).

Indirect discharge – wastewater discharged or othe rwise introduced to a publicly owned treatment works (POTW).

Invertebrates – animals without a bac kbone or spinal column; macroinvertebrates are invertebrates that can be seen without a micros cope (macro), such as aquatic insects, worms, clams, snails, and crustaceans.

Landfill – a disposal facility or part of a facility where solid waste, sludges, or other process residuals are placed in or on any natural or ma nmade formation in the earth for disposal and which is not a storage pile, a land treatment facility, a su rface impoundment, an underground injection well, a salt dome or salt bed forma tion, an underground mine, a cave, or a corrective action management unit.

Leachate – see combustion residual leachate

.

Lentic – pertaining to still or slow-moving water, such as lakes or ponds.

xiiiGlossary

Lethal – causing death by direct action.

Lotic – pertaining to flowing water, such as streams and rivers.

Median lethal c oncentration (LC 50 ) – a statistically or graphically estimated concentration that is expected to be lethal to 50 percent of a group of organi sms under specified conditions.

Mortality – death rate or proportion of deaths in a population.

Partition coefficient – the ratio of a pollutant concentratio n in one medium compared to another ( e.g. , dissolved in the water colu mn, sorbed to suspended sediment, and sorbed to benthic sediment in a receiving water).

Piscivorous – habitually feeds on fish.

Plant-receiving water – the combination of a steam elec tric power plant and the immediate receiving water into which evaluated wastes treams are discharged from that plant.

Point source – any discernable, confined, and discre te conveyance, includi ng but not limited to, any pipe, ditch, channel, tunnel, conduit, well, discrete fissure, container, rolling stock, concentrated animal feeding operation, or vessel or other floating craft fr om which pollutants are or may be discharged. The term does not include agricultural stormwater discharges or return flows from irrigated agricultu re. See CWA section 502(14), 33 U.S.C. 1362(14); 40 CFR §122.2.

Population – an aggregate of individuals of a speci es within a specified location in space and

time.

Publicly owned treatment works (POTW) – any device or system, owned by a state or municipality, used in the treatment (including recycling and reclam ation) of municipal sewage or industrial wastes of a liquid nature that is owned by a state or muni cipality. This includes sewers, pipes, or other conveyances only if they convey wastewater to a POTW providing treatment. See CWA section 212, 33 U.S.C. 1292; 40 CFR §§122.2, 403.3.

Receptor – the ecological or human entity exposed to a stressor.

Receiving water – surface waters into which treated wast e or untreated waste are discharged, including those portions of the surface water downstream from the point source.

Sediment – particulate material lying below water.

Sensitivity – in relation to toxic substances, organisms that are more sensitive exhibit adverse (toxic) effects at lower exposure levels than organisms that are less sensitive.

Steam electric power plant wastewater – wastewaters associated with or resulting from the combustion process, including ash transport water fr om coal-, petroleum coke-, or oil-fired units; air pollution contro l wastewater (e.g., FGD wastewater, FGMC wastewater, carbon capture wastewater); and leachate from landfills or surface impoundments containing combustion

residuals.

xivGlossary

Stressor – any physical, chemical, or biological entity that can induce an adverse response.

Sublethal – below the concentration that direct ly causes death. Exposure to sublethal concentrations of a substance can produce eff ects on behavior, biochemi cal, and/or physiological functions, and the structure of cel ls and tissues in organisms.

Surface water – all waters of the United States, includi ng rivers, streams, lakes, reservoirs, and

seas.

Teratogenic – able to disturb the growth and de velopment of an embryo or fetus.

Transport water – any wastewater that is used to c onvey fly ash, bottom ash, or economizer ash from the ash collection or storage equipment, or boiler, and has direct co ntact with the ash. Transport water does not include low volume, short duration disc harges of wastewater from minor leaks ( e.g. , leaks from valve packing, pipe flanges, or piping) or minor maintenance events ( e.g. , replacement of valves or pipe sections).

Trophic level – position of an organism in the food chain.

Toxic pollutants – as identified under the CWA, 65 pollutant s and classes of pollutants, of which 126 specific substances have been designated priority toxic pollu tants. See Appendix A to 40 CFR §423.

xvSection 1—Introduction



## SECTION 1
INTRODUCTION

The U.S. Environmental Protection Agency (EPA) is promulgating revised effluent limitations guidelines and standards (ELGs) fo r the Steam Electric Power Generating Point Source Category (40 CFR 423). In support of the development of the final rule, EPA conducted an environmental assessment (EA) to evaluate th e environmental impact of pollutant loadings released under current ( i.e. , baseline) discharge practices and assess the potential environmental improvement from pollutant loading removals under the final rule. 1

Based on evidence in the literature, documen ted damage cases, and modeled receiving water pollutant concentrations, it is clear that current steam electric power plant wastewater discharge practices impact the water quality in receiving waters, impact the wildlife in the surrounding environments, and pose a human health threat to nearby communities. Substantial evidence exists that metals ( e.g. , arsenic, cadmium, mercury, se lenium) from steam electric power plant wastewater discharges transfer fro m the aquatic environment to terrestrial food webs, indicating a potential for broader impact s to ecological system s by altering population diversity and community dynamics in the areas surrounding st eam electric power plants. Ecosystem recovery from exposure to pollutants in power plant wastewater discharges can be extremely slow, and even short periods of exposure ( e.g. , less than a year) can cause observable ecological impacts that last for years.

Steam electric power plants discharge wast ewater, which contains numerous pollutants, 2
into waterbodies used for recreation and can pr esent a threat to human health. Due to steam electric power plant wastewater di scharges, fish advisories have b een issued to protect the public from exposure to fish with elevated pollutant co ncentrations. Leaching of pollutants from surface impoundments and landfills containing combustion residuals is known to impact off-site ground water and drinking water wells at concentrat ions above maximum contaminant level (MCL) drinking water standards, posing a threat to human health. 3

In this report, EPA uses the term “steam electric power plant wastewater” to represent all combustion-related wastewaters that contain pol lutants covered by the revised steam electric ELGs. For the EA, EPA evaluated only a subset of the wastestreams: flue gas desulfurization (FGD) wastewater, fly ash transport water, bottom ash transport water, and combustion residual

1 The Clean Water Act does not require that EPA assess the water-related environmental impacts, or the benefits, of its ELGs, and EPA did not make its decision on the final steam electric ELGs based on the expected benefits of the rule. EPA does, however, inform itself of the benefits of its rule, as required by Executive Order 12866. See the Benefits and Cost Analysis for the Effluent Limitations Guidelines and Standards for the Steam Electric Power Generation Point Source Category (EPA-821-R-15-005).

2 The steam electric ELGs control the di scharge of pollutants to surface wa ters and do not specifically regulate

“wastewater.” To allow for more concise discussion in th is EA report, EPA occasionally refers to “wastewater” discharges and impacts without specifically referenc ing the pollutants in the wastewater discharges.

3 In this EA, EPA evaluated the threats to human health and the environment a ssociated with pollu tants leaching into ground water from surface impoundments and landfills containing combustion residuals. If these leached pollutants do not constitute the discharge of a pollutant to surface wate rs, then they are not contro lled under the steam electric ELGs. While the Coal Combustion Residuals (CCR) rulema king is the major controlling action for these pollutant releases to ground water, the ELGs co uld indirectly reduce impacts to ground water. These secondary improvements

are discussed in Section 7.8.

1-1Section 1—Introduction

leachate collected from landfill s or surface impoundments). The goal of the EA was to answer the following five questions regarding pollutant loadings from the evaluated wastestreams:

 What are the environmental concerns under current ( i.e. , baseline) discharge practices?

 What are the environmental and exposure pathways for steam electric power plant wastewater discharges to impact wate r quality, wildlife, and human health?

 What are the baseline environmental im pacts to water quality and wildlife?

 What are the impacts to human health from baseline discharges?

 What are the potential improvements to wa ter quality, wildlife, and human health

under the final rule?

The EA evaluated environmenta l concerns and potential e xposures (wildlif e and humans) to pollutants commonly found in wa stewater discharges from st eam electric power plants. EPA completed both qualitative and qu antitative analyses. Qualitative analyses included reviewing documented site impacts in literature and dama ge cases; assessing the pollutant loadings to receiving waters and sensitive environments; and reviewing the effects of pollutant exposure on ecological and human receptors. To quantify base line impacts and improvements under the final rule, EPA developed computer models to determ ine pollutant concentrations in the immediate and downstream receiving waters, pollutant concentr ations in fish tissue, and exposure doses to ecological and human receptors from fish consumption. EPA compared the values calculated by

the models to benchmarks to determine the exte nt of the environmental impacts nationwide. EPA also developed a model to determine the risk of reproductive impacts among fish and waterfowl that have been exposed, via their diet, to sele nium from steam electric power plant wastewater discharges.

This report presents the methodology and re sults of the qualitative and quantitative analyses performed to evaluate baseline disc harges from steam electric power plants and improvements under the final rule. The analyses presented in this re port incorporate some adjustments to current conditions in the indu stry. For example, these analyses account for publicly announced plans from the steam electric pow er generating industry to retire or modify steam electric generating units at specific power plants. These analyses also account for changes to the industry that are expect ed to occur as a result of th e recent CCR rulemaking by EPA’s Office of Solid Waste and Emergency Response (OSWER). These analyses, however, do not reflect changes in the industry that may occur as a result of the Clean Power Plan [Clean Air Act Section 111(d)]. 4

In addition to the EA, the final steam electric ELGs are supported by a number of reports including:

Regulatory Impact Analysis for Effluent Li mitations Guidelines and Standards for the Steam Electric Power Generation Point Source Category, Document No. EPA-821-R-15-004. This report presents a profile of the steam el ectric power generating in dustry, a summary of the

4 EPA completed a parallel set of quantitative EA analyses that reflect changes in the industry that may occur as a result of the Clean Power Plan. Appendix I provides the results of those analyses.

1-2Section 1—Introduction

costs and impacts associated with the regulatory options, and an assessmen t of the final rule’s impact on employment and small businesses.

Benefits and Cost Analysis for the Effluent Limitations Guidelines and Standards for the

Steam Electric Power Generation Point So urce Category (Benefits and Cost Analysis ),

Document No. EPA-821-R-15-005. Th is report summarizes the mone tary benefits and societal costs that result from implementation of the final rule.

Technical Development Document for Effluent Limitations Guidelines and Standards for the Steam Electric Power Generating Point Source Category (TDD) , Document No. EPA-821­ R-15-007. This report includes back ground on the final rule; appli cability and summary of the final rule; industry description; wastewater characteri zation and identification of pollutants of concern; treatment technologies and pollution prevention techniques; and documentation of EPA’s engineering analyses to suppo rt the final rule incl uding cost estimates, pollutant loadings, and non-water-quality impact assessment.

These reports are available in the public record for the final rule and on EPA’s website at http://water.epa.gov/scitech/was tetech/guide/steam_index.cfm

.

The ELGs for the Steam Electric Power Gene rating Point Source Category are based on data generated or obtained in accordance with EPA’s Quality Policy and Information Quality Guidelines. EPA’s quality assurance and quality control activities for this rulemaking include the development, approval, and implementation of Quality Assurance Project Plans for using environmental data generated or collected from all sampling and analyses, existing databases, and literature searches, and for developing any models that used environmental data. Unless otherwise stated within this document, EPA evaluated the data used and associated data analyses as described in these quality assurance documen ts to ensure they are of known and documented quality, meet EPA's requirements for objectivity, in tegrity, and utility, and are appropriate for the

intended use.

1-3Section 2—Background and Scope



## SECTION 2
BACKGROUND AND SCOPE

Many steam electric power plants use large

s urface impoundments to store and treat wastewaters. These impoundments are hydrologically connected to surface and

g round water. The final steam electric effluent limitations guidelines and standards (ELGs) apply to establishments whose generation of electricity is the predominant source of revenue or principal reason for operation, and whose generation results primarily from a process utilizing fossil-type fuels (coal, oil, or gas), fu el derived from fossil fuel ( e.g. , petroleum coke, synthesis gas), or nuclear fuel in conjunction with a thermal cycle using the steam water system as the thermodynamic medium. The final rule applies to discharges associated with both the combustion turbine and steam turbine portions of a combined cycle generating unit (see 40 CFR 423.10). EPA is revising or establishing best available technology economically achievable (BAT) limitations, new source performance sta ndards (NSPS), pretreatment standards for existing sources (PSES), and pretreatment standards for new sources (PSNS) that apply to certain discharges of seven wastestreams: flue gas desulfurization (FGD) wastewater, fly ash transport water, bottom ash transport water, combustion residual leachate, flue gas mercury control (FGMC) wastewater, gasification wastewater, and nonchemical metal cleaning wastes. See the Technical Development Document (TDD) (EPA-821-R-15-007) for more information on the rule applicab ility and defini tions, industry description, wastestreams and pollutants of concern, treatment technologies, baseline and regulatory option pollutant loadings, costs of implementing treatment technologies, and

revised standards.

As discussed in Section 1, EPA uses the term “steam electric power plantwastewater” to represent all combustionrelated wastewaters covered by the revised

steam electric ELGs. For the environmental assessment (EA), EPA evaluated only a subset of the wastestreams (see Table 2-1 below). 5

“Com bustion residuals” are the solid wastes associated with combustion-related power plant processes, including fly and bottom ash; FGD solids; FGMC wastes; and ot her wastewater treatment solids associated with steam electric power plant wastewater. Steam electric power plants generate solid residuals from fuel combustion and from emission control technologi es. These solid residuals include fly ash, bottom ash, and FGD solids. Plants remove these solid materials through both wet and dry handling methods. Dry handling typically involves transferring the solids to a storage silo or outdoor storage pile, to be either disposed of in a landfill or, depending on th e particular residual,

5 EPA evaluated technology options as sociated with FGMC wastewater, gasi fication wastewater, and nonchemical metal cleaning wastes as part of the regulatory options. However, no plants currently discharge FGMC wastewater, all existing gasification plants are operating the technology used as the basis for the regulatory option, and EPA will

continue to reserve BAT/NSPS/PSES/PS NS for nonchemical metal cleaning wa stes, as previously established regulations do. Therefore, EPA estimated zero compliance costs and zero pollutant reductions associated with these

wastestreams and did not include th ese three wastestreams in the EA.

2-1Section 2—Background and Scope

used to create beneficial by-produc ts such as wallboard or cement. However, many plants use wet handling systems, which transport the wastes to a surface impoundment ( e.g. , ash pond) using large quantities of water. For example, in wet systems, bottom ash collects at the bottom of the boiler in a water bath, and the water containing the bottom ash is then typically transported to a surface impoundment for storage and/or disposal. Fly ash may be handled similarly after it is collected from the particulate collection system . The slurry stream exiting wet FGD systems, which contains 10 to 20 percent FGD solids, is typically treated either in a surface impoundment or in an advanced wastewater treatment system, th en discharged to a rece iving stream or reused in other plant processes. Section 6 of the TDD describes the industry wastestreams in detail. Table 2-1 lists the specific wastestreams evaluated in the EA.

Table 2-1. Steam Electric Power Plant Wastestreams Evaluated in the EA

Evaluated Wastestream Description
Fly ash transport water Water used to convey the fly as h particles removed from the flue gas via a collection

system.

Untreated ash transport waters contain significant concentrations of total suspended solids (TSS) and metals, including arsenic, calcium, and titanium (see Section 6 of the TDD for further details). The effluent from surface impoundments generally contains low concentrations of TSS; however, metals are still present in the wastewater, predominantly in dissolved form.
Bottom ash transport water Water used to convey the bott om ash particles collected at the bottom of the boiler.

As noted above, untreated ash transport wate rs contain significant concentrations of

TSS and metals.

FGD wastewater Wastewater generated from a wet FGD scrubber system. Wet FGD systems are used to control sulfur dioxide (SO 2 ) emissions from the flue gas generated in the plant’s

boiler.

The pollutant concentrations in FGD wastewater vary from plant to plant depending on the coal type, the sorbent used, the materials of construction in the FGD system, the FGD system operation, the level of r ecycle within the absorber, and the air pollution control systems operated upstream of the FGD system. FGD wastewater contains significant concentrations of chlorides, total dissolved solids (TDS), nutrients, and metals, including bioaccumulativ e pollutants such as arsenic, mercury, and selenium (see Section 6 of the TDD for further details).

Combustion residual

leachate Collected liquid that has percolated through or drains from a landfill or a surface impoundment, where the steam electric power pl ant disposes of or stores a variety of wastes from the combustion process.

Leachate contains high concentration of me tals, such as boron, calcium, chloride, and sodium, similar to FGD wastewater s and ash transport water. The metal concentrations in the leachate are generally lower than those in FGD wastewater and ash transport water (see Section 6 of the TDD for further details).

2-2Section 2—Background and Scope

Surface impoundments accumulate high concentrations of toxic pollutants from fly ash transport water, bottom ash transport water,

and FGD wastewater. Surface impoundments act as a physical treatment process to remove particulate material from wastewater through gravitational settling. The wastew ater in surface impoundments can include one specific type of wastewater ( e.g. , fly ash transport water) or a combination of wastewaters ( e.g. , fly ash transport water and FGD wastewater). Additionally, plants may transfer wastewater streams from other operati ons into their on-site impoundments ( e.g. , cooling tower blowdown or metal cleaning wastes). The wastestreams sent to surface impoundments can also include coal pile runoff. Although coal pile runoff is

not the result of a com bustion process, it can contain many of the pollu tants present in steam electric power plant wastewater. Leachate or seepage may occur from surface impoundments or landfills containing combustion residuals. 6
Regardless of whether they use surface impoundmen ts or an advanced treatment system, steam electric power plants typically discharge wastewater into the natural environment where numerous studies have raised concern regardi ng the toxicity of these wastestreams [ERG, 2013a; NRC, 2006; Rowe et al ., 2002; U.S. EPA, 2014a through 2014e]. Previous regulations at 40 CFR 423 control pH and polychlorinated biphenyls (PCBs ) discharge from all wastestreams and TSS and oil and grease from ash transport waters a nd other “low volume wastes” that include air pollution control wastewater (see Section 1 of the TDD). Section 6 of the TDD discusses

wastewater characterization and sele ction of pollutants of concern.

Based on data EPA obtained from the 2010 Questionnaire for the Steam Electric Power Generating Effluent Guidelines (Steam Electric Survey), EPA es timates that 1,079 steam electric power plants are subject to the final rule (see Section 4 of the TDD). EPA limited the scope of the EA to those plants that both 1) discharge di rectly to surface waters and 2) will reduce their pollutant loadings as a result of the regulato ry options evaluated, based on EPA projections. Therefore, the EA scope excludes steam electric power plants that meet any of the following

criteria:

 Plants that do not discharge any of the wast estreams that are included in the final rule (even if the plant does gene rate and reuse the wastestream without discharging to surface waters).

 Plants that already comply with final rule or have plans to comply with the final rule prior to the date when the plants woul d have to meet the new limitations and

standards.

6 In this EA, EPA evaluated the threats to human health and the environment a ssociated with pollu tants leaching into ground water from surface impoundments and landfills containing combustion residuals. If these leached pollutants do not constitute the discharge of a pollutant to surface wate rs, then they are not contro lled under the steam electric ELGs. While the CCR rulemaking is the major controlling ac tion for these pollutant releases to ground water, the ELGs could indirectly reduce impacts to ground water. These secondary improvements are discussed in Section 7.8.

2-3Section 2—Background and Scope

 Plants that that have announced plans to retire steam generating units (that would otherwise be subject to the final rule) prior to the date that the plants would have to

meet the new limitations and standards.

 Plants that, based on EPA projections, will either convert to dry ash handling or

install tank-based FGD wastewater trea tment systems to comply with the CCR rulemaking.

 Plants that discharge only to public ly owned treatment works (POTWs).

In the EA, EPA evaluated the current im pact and potential improvement to the environment and human health from 195 plants that discharge directly to surface waters and that EPA projects will reduce pollutant loadings as a result of the re gulatory options evaluated. Table 2-2 presents the number of plants by discharge type (dir ect or indirect) included in the cost and loadings analysis presented in Sections 9 and 10 of the TDD.

Table 2-2. Number of Plants Evaluated in the EA

Plant Description Number of

Plants
Number of Plants in Scope of Final Rule
Plants that fall under the applicability of the final rule (40 CFR 423) 1,079
Cost and Loadings Analysis
Plants for which EPA calculated loadings in the cost and loadings analyses (see Sections 9 and 10 of the TDD) 202

Plants that discharge only to su rface waters (direct discharger) 191
Plants that discharge only to a POTW (indirect discharger) 7 Plants that discharge to surface waters and to a POTW (direct and indirect discharger) 4

Environmental Assessment
Plants evaluated in the EA (includes all direct dischargers) a 195
a – For the pollutant loadings and removals presented in this report, EPA included indirect dischargers to protect

confidential business information.

These 195 steam electric power plants discharg e to the 222 immediat e receiving waters illustrated in Figure 2-1 (some plants discharge to multiple receiving waters). The EA includes qualitative analysis of the pollu tant loadings in evaluated wast estreams discharged from these plants and the associated potential for environmen tal and human health imp acts. As discussed in Section 5, EPA developed and executed a na tional-scale immediate receiving water (IRW) model to perform further quantita tive modeling of the water qualit y, wildlife, and human health impacts associated with discharges from the ma jority of these plants. The IRW model, which excludes discharges to the Great Lakes and es tuaries, encompasses 188 steam electric power plants that discharge to 209 immediate receiving waters. As discussed in Section 8, EPA also performed more detailed case study modeling of discharges from six steam electric power plants. Figure 2-1 indicates the immedi ate receiving waters included in the IRW modeling and case study modeling scopes.

2-4Figure 2-1. Locations and Counts ofImmediate Receiving Waters in EA Scope and Modeling AnalysesSection 2—Background and Scope2-5Section 2—Background and Scope

EPA used the results from quantitative and qualitative assessments combined with the

literature review to evaluate a nd describe the environmental imp acts caused by the discharge of

the evaluated wastestreams. EPA organized the remainder of th is report into the following

sections:

 Section 3 describes the environmental c oncerns associated with the evaluated wastestreams, including a discussion of th e pollutants of concer n and a review of damage cases and other documented site im pacts showing negative impacts to surface water and ground water.

 Section 4 outlines how ecological and human receptors may be exposed to pollutants (i.e., environmental pathways), describes the factors that c ontrol environmental impacts for each pathway, and gives an overview of the methodology used to quantitatively evaluate the environmental and human health impacts.

 Section 5 presents the modeling performed to support the EA including an overview

of the national-scale IRW model and the ecological risk model.

 Section 6 presents the environmental and hum an health impacts based on qualitative review and quantitative assessments (mode ling of plant-specific discharges) of current (baseline) discharges.

 Section 7 presents the improvements to th e environment and human health estimated from the implementation of the regulatory options.

 Section 8 describes EPA’s cas e study modeling of discharges from six steam electric power plants, presents the environmental and human health impacts under baseline conditions, and discusses the modele d improvements under the final rule.

 Section 9 presents EPA’s conclusions on the environmental and human health improvements estimated under the final rule.

2-6Section 3—Environmental And Human Health Concerns



## SECTION 3
ENVIRONMENTAL AND HUM AN HEALTH CONCERNS

Current scientific literature indicates that st eam electric power plant wastewater is not a benign waste [NRC, 2006; Rowe et al ., 2002]. Many of the common pollutants ( e.g. , selenium, mercury, and arsenic) found in the evaluated wastestreams ( i.e. , fly ash and bottom ash transport water, flue gas desulfurization (FGD) wastewat er, and combustion residual leachate) present an increased ecological threat due to their tendency to persist in the environment and bioaccumulate in organisms. This often results in slow ecological recovery times following exposure. The toxic impacts of steam electric power plant wastewater discharges on surface waters have been well documented in studies of over 30 aquatic ecosyst ems receiving discharges from steam electric power plants. 7

Documented exceedances of drinking wate r maximum contaminant levels (MCLs) downstream of steam electric power plants and the issuance of fish advisories in re ceiving waters indicate an ongoing human health concern cause d by steam electric powe r plant wastewater discharges. EPA identified more than 30 docum ented cases where ground water contamination from surface impoundments extended beyond the plant boundaries, illustrating the threat to ground water drinking water sources [ERG, 2015m]. 8 In other damage cases, EPA documented locations where selenium in power plant wastewat er discharges resulted in fish consumption advisories being issued for surface waters.

The pollutants commonly discharged in the evaluated wastestreams cause environmental harm by contaminating surface water and ground water ( e.g. , selenium concentrations from steam electric power plants have resulted in fish k ills). After being released into the environment, pollutants can reside for a long time in the receiving waters, bi oaccumulating and binding with

the sediment. There is documented evidence of sl ow ecological recovery as a result of these pollutant discharges. Steam electric power plants also discharge to sensitive environments ( e.g. , impaired waters, waters under a fi sh consumption advisory, Great La kes, valuable estuaries, and drinking water sources). Some im pacts might not be realized for years due to the persistent and bioaccumulative nature of the pollutants releas ed. Based on EPA’s calculated baseline pollutant loadings, the total amount of toxic pollutants curr ently being released in wastewater discharges from steam electric power plants is significan t and raises concerns regarding the long-term impacts to aquatic organisms, wildlife, and hum ans that are exposed to these pollutants. For details on the pollutant loadings analysis, se e Section 10 of the Technical Development Document (TDD) (EPA-821-R-15-007).

This section details environmental concerns as sociated with wastewater discharges from steam electric power plants including change s in surface water quality and sediment contamination levels; changes in ground water qua lity and potential contamination of private

7 Sources include ATSDR, 1998a, 1998b and 1998c; Charlotte Observer, 2010; DOE, 1992; EIP, 2010a and 2010b;

Roe et al., 2005; Sorensen et al., 1983; Sorensen, 1988; Specht et al., 1984; and Vengosh et al., 2009.

8 In this EA, EPA evaluated the threats to human health and the environment a ssociated with pollu tants leaching into ground water from surface impoundments and landfills containing combustion residuals. If these leached pollutants do not constitute the discharge of a pollutant to surface wate rs, then they are not contro lled under the steam electric ELGs. While the Coal Combustion Residuals (CCR) rulema king is the major controlling action for these pollutant releases to ground water, the ELGs co uld indirectly reduce impacts to ground water. These secondary improvements

are discussed in Section 7.8.

3-1Section 3—Environmental And Human Health Concerns

drinking water wells; bioaccumulation of contamin ants in fish and aquatic life, fish eaten by piscivorous wildlife ( i.e. , fish-eating wildlife), and fish eaten by humans; and toxic effects on fish and aquatic life. The section is or ganized into the following subsections:

 Section 3.1: Types of pollutants discharged in steam electric power plant wastewater.

 Section 3.2: Pollutant loadings associated with steam electric pow er plant wastewater.

 Section 3.3: Environmental impacts from steam electric power plant wastewater, including ecological impacts, human hea lth effects, damage cases and other documented site impacts, and potential fo r impacts to occur in other locations.

 Section 3.4: Sensitive environm ents, including pollutant lo adings to the Great Lakes and Chesapeake Bay watersheds, impaired waters, waters issued fish advisories, threatened and endangered species ha bitats, and drinking water resources.

 Section 3.5: Long recovery times.

3.1 T YPES OF P OLLUTANTS D ISCHARGED IN S TEAM E LECTRIC P OWER P LANT
W ASTEWATER

This section provides an ove rview of the pollutants in steam electric power plant wastewater discharges that are frequently cited as affecting local wildlife or pose a threat to

human health. A number of variables can affect the composition of steam electric power plant wastewater, including fuel comp osition, type of combustion pr ocess, air pollution control technologies implemented, and management tec hniques used to dispos e of the wastewater [Carlson and Adriano, 1993]. In addition, comming ling steam electric power plant wastewater with other wastestreams from the plant in su rface impoundments can result in a chemically complex effluent that is rele ased to the environment [Rowe et al ., 2002]. To identify pollutants of concern for the final rule, EPA used the fo llowing sources of wast ewater characterization data: EPA’s field sampling program; data suppl ied by industry or me mbers of the public ( e.g., in questionnaire responses and public comments on the proposed rule); and various literature sources (see Section 6 of the TDD and the pream ble to the final rule for further details on pollutants of concern). Pollutants such as metals, nutrients, and total dissolved solids (TDS), including chloride and bromides, are the common pollutants found in stea m electric power plant

wastewater that have been associated with doc umented environmental impacts or could have the potential to cause environmental impacts based on the loadings and concentrations present in the

evaluated wastestreams.

3.1.1 Metals and Toxic Bioaccumulative Pollutants

Studies commonly cite metals and toxic bioaccumulative pollutants ( e.g., mercury and selenium) as the primary cause of ecological da mage following exposure to steam electric power plant wastewater [Rowe et al ., 1996; Lemly, 1997a; Hopkins et al ., 2000; Rowe et al ., 2002] (see Section 3.3.1). An important consideration in evaluating these pollu tants is their bioavailability– the ability of a particular contam inant to be assimilate d into the tissues of exposed organisms. A pollutant’s bioavailability is affected by the characteristics of both the pollutant and surrounding environment ( e.g. , temperature, pH, salinity, oxidation-reducti on (redox) potential, total organic content, suspended particulate content, and wate r velocity). Environmental conditions influence the tendency of a dissolved pollutant to remain in solution or precipitate out of solution, sorb to either organic or inorganic suspended matter in the water column, or sorb to the mixture of

3-2Section 3—Environmental And Human Health Concerns

materials ( e.g. , clays and humic matter) found in sedime nts [U.S. EPA, 2007a]. Pollutants that precipitate out of solution can b ecome concentrated in the sediments of a waterbody. Regardless, organisms will bioaccumulate pollutants either by consuming pollutant-enriched sediments and suspended particles, and/or by filtering ambi ent water containing dissolved pollutants.

Table 3-1 lists some of the common metals and toxic bioaccumulative pollutants found in steam electric power plant wastewater that have been associated with documented health and environmental impacts or could potentially caus e health and environmental impacts based on the loadings and concentrations present in the wast ewater. Table 3-1 is in tended to highlight the pollutants of concern in steam electric power plant wastewater that are associated with health and environmental impacts; it does not include all pol lutants that may cause adverse impacts. Metals and toxic bioaccumulative pollutants in steam elect ric power plant wastewater are present in both soluble ( i.e. , dissolved) and particulate ( i.e. , suspended) form. For example, EPA sampling data collected for FGD wastewater in support of th e steam electric ELGs shows that some pollutants such as arsenic are present mostly in particulate form while other pollutant s such as selenium and boron are present mostly in soluble form. The remainder of the section provides additional details on several key metals included in the environmental assessment (EA).

Table 3-1. Key Metals and Toxic Bioaccumula tive Pollutants Found In Steam Electric

Power Plant Wastewater

Pollutant Examples of Potential Health and Environmental Concerns

Aluminum Aluminum contamination can lead to the inability of fish to maintain the balance of their fluids and is associated with damage to amphibian eggs an d larvae, mostly in areas under acid stress. Human exposure to high concentrations has been linked to Alzheimer’s disease.

Arsenic a Arsenic contamination causes liver poisoning, developmental abnormalities, behavioral impairments, metabolic failure, reduced growth, and appetite loss in fish and is associated with an increased risk of the liver and bladder cancer in humans. Arsenic is also a potent endocrine disruptor at low, environmentally relevant levels. Non-cancer impacts to humans can include dermal, cardiovascular, and respiratory effects. Negative impacts can occur both after high-dose exposure and repeated lower-dose exposures. Chronic exposure via drinking water has been associated with excess incidence of miscarriages, stillbirths, preterm births, and low-birth weights.

Boron Boron can be toxic to vegetation and to wildlife at certain water concentrations and dietary levels. Human exposure to high concentrations can cause nausea, vomiting, and diarrhea.

Cadmium Cadmium contamination can lead to developmental impairments in wildlife and skeletal malformations in fish. Human exposure to high concentrations in drinking water and food can irritate the stomach, leading to vomiting and diarrh ea, and sometimes death. Chronic oral exposure via diet or drinking water to lower concentrations can lead to kidney damage and weakened bones.

Chromium b Chromium is not known to bioaccumulate in fish ; however, high concentr ations of chromium can damage gills, reduce growth, and alter metabolism in fish. Human exposure to high concentrations can cause gastrointestinal bleeding and lung problems.
Copper Copper contamination can lead to reproductive failure, gill damage, and reduced sense of smell in fish. Human exposure to high concentrations can cause nausea, vomiting, diarrhea, and liver and kidney damage.

Iron Iron contamination can reduce growth, increase susceptibility to injury and disease, and decrease egg hatchability in fish. Human exposure to high concentrations can cause metabolic changes and damage to the pancreas, liver, spleen, and heart.

Lead Lead contamination can delay embryonic development, suppress reproduction, and inhibit growth in fish. Human exposure to high concentrations in drinking water can cause serious damage to the brain, kidneys, nervous system, and red blood cells.

3-3Section 3—Environmental And Human Health Concerns

Table 3-1. Key Metals and Toxic Bioaccumula tive Pollutants Found In Steam Electric

Power Plant Wastewater

Pollutant Examples of Potential Health and Environmental Concerns
Manganese Manganese primarily accumulates in organism s lower in the food chai n such as phytoplankton, algae, mollusks, and some fish. Although high levels can be toxic to humans, manganese is not generally considered toxic when ingested. The most common impacts due to human exposure to high concentrations involve the nervous system.
Mercury c Once in the environment, mercury can convert into methylmercury, increasing the potential for bioaccumulation. Methylmercury contamination can reduce growth and reproductive success in fish and invertebrates. Human exposure at levels above the MCL for relatively short periods can result in kidney and brain damage. Fetuses, infants, and children are particularly susceptible to impaired neurological development from methylmercury exposure.

Nickel At low concentrations, nickel can inhibit the growth of microorganisms and algae. Nickel toxicity in fish and aquatic invertebrates varies among species and can damage the lungs, immune system, liver, and kidneys. Human exposure to high concentrations can cause gastrointestinal and kidney damage.

Selenium d Selenium readily bioaccumulates. Elevated concen trations have caused fish kills and numerous sublethal effects ( e.g. , organ damage, decreased growth rates, reproductive failure) to aquatic and terrestrial organisms. In humans, short-term expo sure at levels above the MCL can cause hair and fingernail changes, damage to the peripheral nerv ous system, and fatigue and irritability. Long-term exposure can damage the kidney, liver, and nervous and circulatory systems.

Thallium In humans, short-term exposure to thallium can lead to neurological symptoms, alopecia, gastrointestinal effects, and reproductive and developmental damage. Long-term exposures at levels above the MCL change blood chemistry and damage liver, kidney, intestinal and testicular tissues

and cause hair loss.

Vanadium Vanadium contamination can increase blood pressure and cause neurological effects in animals. There are very few reported cases of oral exposure to vanadium in humans; however, a few reported incidences documented diarrhea and stomach cramps. It also has been linked to the development of some neurological disorders and cardiovascular diseases.

Zinc Zinc contamination changes behavior, reduces oxygen supply, and impairs reproduction in fish. In humans, short-term exposure can cause nausea, vomiting, and stomach cramps. Long-term exposure can cause anemia.

a – Arsenic exists in two primary forms: arse nic III (arsenite) and arsenic V (arsenate).
b – Chromium exists in two primary forms: chromium III oxide and chromium VI (hexavalent chromium).
c – The EA evaluated two forms of mercury: total mercury and methylmercury.
d – Selenium exists in two primary forms: selenium IV (selenite) and selenium VI (selenate).

Selenium

Selenium is the most frequently cited pollutant associated with documented environmental impacts to ecological receptors fo llowing exposure to steam electric power plant wastewater [NRC, 2006]. The toxic potential of se lenium is related to its chemical form and solubility. The predominant chemical forms of se lenium in aquatic systems that receive steam electric power plant wastewater discharg es are selenite and selenate [Besser et al ., 1996]. The uptake of selenium by aquatic organisms is controlled by dissolved oxygen levels, hardness, pH, salinity, temperature, and the other chemical constituents present [NPS, 1997]. In alkaline conditions, selenite [Se(IV)] will oxidize in the presence of oxygen to become selenate [Se(VI)];

selenate is both stable and soluble and is the commonly found form of the chemical in alkaline

soils and waters. In acidic conditi ons, selenite is insoluble due to its tendency to bind to iron and aluminum oxides [WHO, 1987]. Organic forms of selenium are more bioavailable for uptake than selenate and selenite and may play an important role determining selenium toxicity in exposed aquatic organisms [Besser et al ., 1993; Rosetta and Knight, 1995].

3-4Toxic Pollutant Impacts to Ecological Receptors

 Selenium discharges have caused

numerous cases of fish kills and population decline due to reproductive impacts. Bioaccumulation can cause selenium-related environmental impacts to linger for years even after exposure to steam electric power plant wastewater

has ceased.

 Fish and invertebrates exposed to steam electric power plant wastewater have exhibited elevated mercury levels in their tissues and developed sublethal effects such as reduced growth and reproductive success.

 Elevated arsenic tissue concentrations are associated with several biological impacts such as liver tissue death, developmental abnormalities, and reduced growth. Section 3—Environmental And Human Health Concerns

The extent to which selenium is found in ecological receptors is affected by bioaccumulation, biomagnification, and maternal transfer. Bioaccumulation occurs when an organism absorbs a toxic substance through food and exposure to the environment at a faster rate than the body can remove the substance. The bioaccumulation of selenium is of particular concern due to its potential to impact higher trophic levels through biomagnification [Coughlan and Velte, 1989] and offspring thr ough maternal transfer [Hopkins et al ., 2006; Nagle et al

., 2001]. A laboratory study demonstrated that diet can be an important source of trace element exposure in aquatic snakes and pot entially other amphibians [Hopkins et al ., 2002]. Hopkins reported that the snakes accumulated significant concentrations of the trace elements, most notably selenium. This study also revealed that amphibian prey species are able to migrate

considerable distances and can ther efore be exposed to toxic levels of selenium even if they do

not inhabit a contaminated site. Because of bioaccumulation and biomagnification, seleniumrelated environmental impacts can linger for year s even after exposure to steam electric power plant wastewater has ceased [Rowe et al ., 2002].

Selenium-related impacts observed by scientists include lethal effects such as fish kills,

subleth al effects such as histopathological changes and damage to reproductive and developmental success, and the impacts of these effects on aquatic populations and communities. In a 1991 study, Sorensen found that dissolved selenium levels as low as 3 to 8 micrograms per liter ( μ g/L) in aquatic environm ents can be lifethreatening to fish [NPS, 1997]. Section 3.3.1 presents f urther details regarding the lethal and sublethal effects on aquatic organisms caused by selenium from steam electric power plant

wastewater.

In addition to ecological impacts, EPA

has docum ented numerous damage cases where selenium in steam electric power plant wastewater discharges resulted in fish consumption advisories be ing issued for surface waters and selenium MCLs being exceeded in ground water, suggesting that selenium

concentratio ns in power plant wastewater have the potential to impact human health [NRC, 2006; U.S. EPA, 2014a through 2014e]. Short-te rm exposure at levels above the MCL, 0.05 mg/L [U.S. EPA, 2009e], can cause hair and fi ngernail changes, damage to the peripheral nervous system, and fatigue and irritability in humans. Long-term exposure can damage the kidney, liver, and nervous a nd circulatory systems.

3-5Toxic Pollutant Impacts to Human Receptors

 Pregnant women exposed to mercury can pass the contaminant to their developing fetus, leading to possible mental retardation and damage to other parts of the nervous system.

 Inorganic arsenic is a carcinogen ( i.e. , causes cancer). Cadmium is a probable carcinogen.

 Human exposure to high concentrations of lead in drinking water can cause serious damage to the brain, kidneys, nervous system, and red blood cells, especially in

children. Section 3—Environmental And Human Health Concerns

Mercury

Mercury is a volatile metal and highly toxi c compound that represents an environmental

and human health threat even in small con centrations. One of the primary environmental concerns regarding mercury concentrations in steam electric power plant wastewater is the potential for methylmercury to form in combustion residual surface impoundments and constructed wetlands prior to discharge a nd in surface waters following discharge. Methylmercury is an organic form of mercury that readily bioaccumulates in fish and other organisms and is associated with high rates of reproductive failure [WHO, 1976]. Bacteria found in anaerobic conditions, such as those that may be present in sediments found on the bottom of combustion residual surface impoundments or in river sediments, convert mercury to methylmercury through a process called methyla tion [WHO, 1976]. Microbial methylation rates

increase in acidic and anoxic environments with high concentrations of organic matter. Sublethal effects from mercury e xposure include reduced growth and reproductiv e su ccess, metabolic changes, and abnormalities of the liver and kidneys. Human exposure at levels above the MCL, 0.002 mg/L [U.S. EPA, 2009e], for relatively short periods of time can result in kidney and brain damage. Pregnant women who are exposed to m ercury can pass the contaminant to their developing fetus, leading to possible mental retardation and damage to other parts of the nervous system [ATSDR, 1999]. Studies have documented fish and invertebrates exposed to mercury from steam electric power plant wastewater exhibiting elevated levels of mercury in their tissues and developing sublethal effects such as reduced growth and reproductive success [Rowe et al ., 2002].

Arsenic

Arsenic, like selenium , is of concern becaus e it is soluble in near-neutral pH and in alkaline conditions, which are co mmonly associated with steam el ectric power plant wastewater. As a soluble pollutant, arsenic leaches into gr ound water and is highly mobile. Arsenic is frequently observed at elevated concentratio ns at sites located dow nstream from combustion residual surface impoundments [NRC, 2006]. Inorganic arsenic, a carcinogen, is found in natural and drinking waters mainly as trivalent arsenite (As(III)) or pentavalent arsenate (As(V)) [WHO, 2001]. Both the arsenite and arsenate forms are highly soluble in water.

Arsenic is also of concern due to its tende ncy to bioaccumulate in aquatic communities and potentially impact higher-trophic-level orga nisms in the area. For example, studies have documented water snakes, which feed on fish and amphibians, with arsenic tissue concentrations higher than their prey [Rowe et al ., 2002]. Elevated arsenic tissue c oncentrations ar e associated with several biological impacts such as liver tissue death, developmental abnormalities, behavioral impairments, metabolic failure, reduced growth, and appetite loss [NRC, 2006; Rowe

et al ., 2002; U.S. EPA 2011f].

3-6Section 3—Environmental And Human Health Concerns

Humans are exposed to arse nic primarily by ingesting co ntaminated drinking water [WHO, 2001]. Humans are also ex posed to arsenic by consuming contaminated fish. Of greatest concern is inorganic arsenic, which can cause can cer in humans. Several studies have shown that most arsenic in fish is organi c and not harmful to humans. Inor ganic arsenic typically accounts for 4 percent or less of the total arsenic that accumulates in fish. 9 The highest potential exposure

is for individuals whose diet is high in fish and particular ly shellfish [U.S. EPA, 1997b].

As discussed in Section 3.3.4, EPA has documen ted several damage cases where arsenic levels exceeded drinking water standards in ground water near combustion residual surface impoundments [U.S. EPA, 2014b through 2014e]. Arseni c contamination of ground water at the levels documented represents a potential human heal th threat, if either the aquifer is used as a drinking water source or the ground water contaminates a downstream drinking water source.

Cadmium

The speciation and toxicity of cadmium in water depends on the water’s salinity, hardness, temperature, and organic content [WHO, 1992]. Cadmium tends to bioaccumulate readily in mollusks, soil invertebrates, and micr oorganisms. Due to its chemical similarity to calcium, it can also interfere with calcium up take in aquatic organisms, which can cause

sublethal effects in fish such as skeletal ma lformation. Divalent cadmium (Cd(II)) is the species most commonly found in an aquatic environmen t, but depending on the quality of the water,

cadmium can also occur as cad mium carbonate, hydroxi de, sulfite, sulfate, or chlorides.

EPA determined that cadmium is a prob able human carcinogen. Studies found lung cancer in humans and rats exposed to cadmium via inhalation. In humans, chronic low-level exposure to cadmium from contaminated air, dr inking water, or food can cause kidney failure. Chronic low-level exposure from contaminated dr inking water or food can also lead to fragile bones. Exposure via inhalation at high levels can damage lungs and exposure via food and drinking water can irritate the stomach, lead ing to vomiting and di arrhea [ATSDR, 2012].

Thallium

Thallium typically exists as the monovalent or trivalent thallium ion [WHO, 1996]. It is soluble in most waters and is readily available to aquatic life. Thallium can bioaccumulate in fish and vegetation in fresh and marine waters, as we ll as marine invertebrates, which suggests that thallium may be a potential threat to higher order organisms in vulnerable ecosystems [U.S. EPA, 2011a]. Studies in humans and animals indicate that thallium compounds are readily absorbed through ingestion of food and wa ter and maternal tr ansfer [WHO, 1996].

In humans, elevated thallium concentrati ons can lead to neur ological symptoms ( e.g. , weakness, sleep disorders, muscular problems), alopecia ( i.e. , loss of hair from the head and body), and gastrointestinal effects ( e.g. , diarrhea and vomiting). Long-term exposures at levels above the MCL, 0.002 mg/L [U.S. EPA, 2009e], lead to changes in blood chemistry, damage to liver, kidney, and intestinal and te sticular tissues, and hair loss. Thallium exposure can also cause reproductive and developmental damage [U.S. EPA, 2009a].

9 Based on a 1996 literature review of toxicity and exposure concerns related to arsenic in seafood prepared for U.S. EPA Region 10, inorganic arsenic comprised higher than four percent total arsenic for three species (shark, sturgeon, and sucker). Inorganic arsenic for all other species accounted for less than 4 pe rcent of the total arsenic [U.S. EPA, 1997b].

3-7Section 3—Environmental And Human Health Concerns

Lead

Neither metallic lead nor many of its common mineral forms are soluble in water, although it can be soluble in some acids or water with low pH; thus, lead is commonly present in precipitate form in water. Therefore, steam electric power plant wastewater may initially have high concentrations of lead, but later samp ling of the wastewater can show decreased concentrations because the lead settles out quick ly. Lead will accumulate in aquatic organisms, but depends on the species. Stud ies have shown lead to delay embryonic development, suppress reproduction, and inhibit growth rate among fish, crab, and severa l other aquatic organisms [U.S. EPA, 1984]. Human exposure to high concentrations of lead in drinking water can seriously damage the brain, kidneys, nervous system, a nd red blood cells, especially in children.

Boron

Boron is primarily found in the environmen t combined with oxygen in compounds called borates [ATSDR, 2010b]. Boron concentrations in North American waters are typically below

0.1 mg/L [WHO, 1998], although areas with natural boron-rich de posits may have ground water levels as high as 300 mg/L [ATSDR, 2010b]. Th e World Health Organization (WHO) suggests that the potential of adverse effects of boron on the aquatic eco system is low because the noeffect concentration (1 mg/L) is much greater than levels f ound in the ambient environment. Boron does not magnify through th e food chain, but does accumulat e in aquatic and terrestrial plants. While it is an essential micronutrient fo r higher plants, there is a small range between deficiency and toxicity in some plants. Studies of acute exposure in fish yielded toxicity values ranging from approximately 10 to 300 mg/L with rainbow trout and zebra fish being the most sensitive. Mallard duckling grow th was impacted at dietary le vels of 30 and 300 milligrams per kilogram (mg/kg), while survival was reduced at 1,000 mg/kg [WHO, 1998].

EPA has not set a numerical criterion unde r the National Recommended Water Quality Criteria (NRWQC) for aquatic lif e, but it has issued a narrative criterion of 0.75 mg/L for sensitive crops that rece ive long-term irrigation.

EPA has not set a NRWQC for human health. Very few human studies have examined health effects resulting from boron exposure through oral ingestion. However, one study documents nausea, vomiting, and diarrhea in an adult male who ingested 85 mg/kg of boron (30 g as boric acid) [ATSDR, 2010b]. In addition, animal experiments in dicate that boron in the form

of boric acid and borate affects reproductive and developmental pr ocesses at levels that are approximately 100 to 1,000 times greater than normal exposure levels, approximately 1.2 milligrams per day (mg/day) [WHO, 1998].

Manganese

In water, manganese tends to attach to particles or settle into the sediment [ATSDR, 2008b]. It occurs in both dissolved and suspended forms, depending on the water chemistry ( e.g. , pH) [WHO, 2011]. Manganese can bioaccumulate in lower organisms, such as phytoplankton, algae, mollusks, and some fish, but not in higher organisms. Studies suggest that biomagnification up the food chain is not significant [ATSDR, 2008b].

Due to a high bioaccumulation factor and conc entrations in mollusks, EPA established a criterion to protect c onsumers of marine mollusks—100 microgr ams per liter (μg/L) for marine

3-8Section 3—Environmental And Human Health Concerns

waters [U.S. EPA, 1986]. Although high levels can be toxic to humans, manganese is an essential nutrient required to maintain health and is generally not considered to be toxic when ingested [WHO, 2011]. EPA did not set a prim ary MCL for manganese in drinking water; however, EPA did set secondary (nonenforceab le) standards at 50 μg/L to minimize objectionable qualities in the drinking water that cau se laundry stains and objectionable tastes in beverages [U.S. EPA, 2009e].

3.1.2 Nutrients

Nutrients ( e.g. , phosphorus and nitrogen) are essential components for plants and animals to grow and develop; however, increased nutrient concentrations can upset the delicate balance of nutrient supply and demand required to maintain aquatic life in surface waters. For example, excess nutrients can cause low oxygen in surface waters (hypoxia) and harmful algal blooms. These are primarily problems for estuaries, such as the Chesapeake Bay, and coastal waters, such

as the Gulf of Mexico. Nutrient concentrations present in steam electric power plant wastewater are primarily attributed to the fuel compositi on and air pollution controls in the combustion

process.

Total nitrogen loadings from coal-fired power plants could potentially increase significantly in the future as air pollution limits become stricter and air pollution control use

increases. While wastewater from an individual steam electric power plant can have a relatively low nitrogen concentration the total nitrogen load ings from a single plant can be significant due to high wastewater discharge flow rates. Total nu trient loadings from multiple power plants are especially a concern for waterbodies that are nutrient-impaired or in watersheds that contribute to downstream nutrient problems. High nutrient loadings to surface waters can affect the ecological stability of freshwater and saltwat er aquatic systems. For example, excessive levels of nutrients can stimulate rapid growth of plants, algae, an d cyanobacteria on or near the waterbody surface, which in turn can obstruct sunlight penetrati on, increase turbidity, and decrease dissolved oxygen levels [U.S. EPA, 2015a]. These aquatic chan ges can potentially kill bottom-dwelling aquatic plants. Cyanobacterial blooms can also prod uce toxic secondary metabolites, known as cyanotoxins, that can have negative impacts to humans and wildlife that consume water contaminated with cyanobacteria. The presence of high levels of cyanotoxins in recreational and drinking water may cause fever, headaches, ab dominal pain, and other symptoms in humans. Severe human impacts include seizures, liver failur e, respiratory arrest, a nd (rarely) death [U.S. EPA, 2012d].

3.1.3 TDS

TDS, a reflection of water’s salinity level, is a measure of the amount of dissolved matter in water. TDS comprises primarily inorganic sa lts and dissolved metals, as well as a small amount of organic matter. Common inorganic salts found in TDS can include cations (positively charged ions), such as calcium, magnesium, pot assium, and sodium, and anions (negatively charged ions) such as carbonates, nitrates, bicarbonates, chlorides, and sulfates. TDS concentrations in steam electric power plants wastestreams include contributions from dissolved metals, chlorides, and bromides. Dissolved metals and other TDS constituents are found in wastewater particularly at acidic pH levels when they exhibit high solubilities. The specific

constituents in TDS in steam electric power plant wastewater cause the negative impacts.

3-9Section 3—Environmental And Human Health Concerns

Bromides

Bromide is the anion of bromine; it commonl y exists as salts with potassium and other cations, which are usually very soluble in water. In water, bromide reacts to form hydrobromic acid (HBr) and hypobromous (HOBr), bromous (HBrO 2 ), and bromic (HBrO 3 ) oxyacids. Bromide is commonly found in nature, with leve ls ranging from trace amounts to 0.5 mg/L in fresh water and levels ranging fr om 65 to over 80 mg/L in seawater. The bromide ion has a low degree of toxicity, and animal te sting suggests very low acute t oxicity upon oral administration [WHO, 2009].

While bromide itself is not t hought to be toxic at levels pr esent in the environment, its reaction with other constituents in water may be cause for concern now and into the future. The

bromide ion in water can form brominated disi nfection by-products (DBPs) when drinking water plants use certain processes including chlorination and ozonation to disinfect the incoming source water. Bromide can react with the ozone, fo rming bromates, or with chlorine or chlorinebased disinfectants used at dr inking water treatment plants, to form brominated and mixed chloro-bromo DBPs, such as trihalomethanes (THMs) or haloacetic acids (HAAs) [WHO, 2009]. EPA has set MCLs for the following DBPs in chlorinated water:

 0.010 mg/L for bromate due to increased cancer risk from long-term exposure.

 0.060 for HAAs due to increased cancer ri sk from long-term exposure HAAs include dichloroacetic acid, trichlor oacetic acid, chlor acetic acid, bromoacetic acid, and

dibromoacetic acid.

 0.080 mg/L for total trihalomethanes (TTHMs) due to increased cancer risk and liver, kidney, or central nervous system problem s from long-term exposure [U.S. EPA, 2009e]. TTHMs include the brominated trih alomethanes (bromodichloromethane, bromoform, dibromochloromethane) and ch loroform. MCL goals for the individual trihalomethanes include 0 (zero) for bromodichloromethane and bromoform.

Studies indicate that exposur e to THMs and other DBPs from chlorinated water are associated with human bladder cancer [Villanueva et al ., 2004; Cantor et al ., 2010]. Brominesubstituted DBPs are generally thought to have higher risks of cancer and other adverse human health effects compared to DBPs contai ning chlorine instead of bromine [Cantor et al ., 2010].

EPA has determined that bromodichloromethane a nd bromoform are likely to be carcinogenic to humans by all exposure routes and there is suggestive evidence of dibromocloromethane carcinogencity. Excess cancer risk (based on in creased risk to 1-in-a-million) occurs at concentrations above 0.001 mg/L for bromodichloromethane, 0.008 mg/L for bromoform, and 0.0008 mg/L for dibromochlormethane [U.S. EPA, 2005c].

DBP formation and the individual form of th e DBP are influenced by factors such as bromide ion concentration, pH of the source water, the disinfectant dose (ozone or chlorine), reaction or contact time, and organic matter c oncentration and reactiv ity [Liang and Singer, 2003; U.S. EPA, 2005c]. Studies have shown that higher bromide levels in source waters shift

the distribution of the TTHMs towa rds brominated species [Krasner et al. , 1989] and the types of

HAAs from chlorinated to brominated and mi xed chloro-bromo haloacetic acids [HellerGrossman, 1993; Cowman and Singer, 1996].

3-10Section 3—Environmental And Human Health Concerns

Under the Safe Drinking Water Act (SDWA), drinking water treatment plants must

reduce DBPs in their treated water and re duce exposure to customers. EPA conducted a nationwide survey that showed that br omide levels in s ource water above 400 μ g/L corresponded

with increased levels of DBPs in the treated water [Weinberg, 2002]. Due to increased bromide concentrations in surface water, drinking water treatment plants have found increased difficulty meeting regulatory limits on DBPs [U .S. EPA, 2012a; Handke, 2009; Fiske et al. , 2011; States et
al. , 2013; Wilson et al. , 2013]. In general, drinking water produced using surface water had higher concentrations of the DBPs than drinki ng water produced usi ng ground water [U.S. EPA, 2005c].

The city of Pittsburgh, in cooperation with the University of Pittsburgh, completed a multiyear study on the Allegheny Rive r to determine the major sources of bromide discharges, including coal-fired power plants. Typically, bromide concentrations are very low in the river,

but there are increased levels near industrial site s. The bromide concentration in the source water provided a linear correlation to bromination in the drinking wate r. At a concentration of 0.050 mg/L in the source water, 62 percent of the TT HMs were the three brominated trihalomethane species. At a concentration of 0.150 mg/L, 83 pe rcent of the TTHMs were the three brominated trihalomethane species [States et al. , 2013].

The California Urban Water Agencies (CUWA) evaluated costs associated with increased bromide levels in the source water for baseline and potential future DBP controls. CUWA developed virtual water treatment plants (WTPs) to represent their different source water areas and treatment needs, with virtual WTP design capacities ranging from 40 to 800 million gallons per day. To achieve potential future standards on currently regulated poll utants, including DBPs, CUWA estimated costs for capital improvement s and added annual operation and maintenance costs. On the low end, CUWA anticipated sp ending between $46 million to $923 million in capital improvements and $1 million to $59 milli on on annual operation and maintenance costs to each virtual WTP (costs vary based on the char acteristics of the virt ual WTP). On the high end, CUWA anticipated spending between $98 million and almost $2 billion in capital improvements and between $2 million and $127 million in annual operation and maintenance

costs for each virtua l WTP [CUWA, 2011].

Bromide is naturally present in coal at trace levels and becomes part of the flue gas air emissions following combustion at steam electri c power plants. Combusting coal with higher levels of bromide is known to improve removal of mercury from air emi ssions at steam electric power plants that operate wet FGD scrubbers. A ccordingly, steam electric power plant operators might add bromide-containing salts ( e.g. , calcium bromide) during coal combustion to improve mercury removal efficiency. The bromide- containing salts conve rt the mercury Hg 0 form into the more water soluble Hg 2+ form. Bromide is not ty pically removed from steam electric power plant wastewaters prior to discharge to surface waters. As discussed earlier, brom ides in surface waters can react with organic matter in the surface wate r to form DBPs at dr inking water treatment plants. A recent study identified fo ur drinking water treatment plan ts that experi enced increased levels of bromide in their source water, an d corresponding increases in the formation of brominated DBPs, after upstream steam electric power plants installed wet FGD scrubbers [McTigue et al. , 2014]. Bromide loadings into surface wa ters from coal-fired steam electric power plants could potentially increase in the futu re as more plant operators add bromide to help control mercury emissions.

3-11Pollutant Loadings: How Does the Steam Electric Power Generating Industry Compare?

EPA estimates that discharges from steam electric power plants alone contribute approximately one-third of the toxic weighted pound equivalent (TWPE) pollutant loadings to the environment among all industrial categories that report discharges under

NPDES p ermits. Section 3—Environmental And Human Health Concerns

Chlorides

Studies have found that combustion residual leachate reaching ground water has caused

chloride levels to exceed s econdary MCLs [NRC, 2006]. Chloride s contribute to the high TDS levels typical of steam electric power plant wa stewater, as do calcium and magnesium. Both chlorides and TDS levels affect the availability and toxicity of other steam electric power plant wastewater constituents, including metals. As TDS and chlorides levels fluctuate, so do the

amounts of other metals that dissolve due to solubility characteristics.

EPA recommends the following for chlorides: criterion maximum concentration of 860 mg/L (acute effects) and cr iterion continuous con centration of 230 mg/L (chronic effects) [U.S. EPA, 2009d]. Exceeding these ch lorides levels in wastewater discharges can be harmful to animals and plants in nonmarine surface waters a nd can disrupt ecosystem structure. It can also adversely affect biological wastewater treatme nt processes. Furtherm ore, excessively high chlorides concentrations in surface waters can impai r their use as source waters for potable water supplies. If sodium is the predominant cation pres ent, the water will have an unpleasant taste due

to the corrosive action of chloride ions.

3.2 L OADINGS A SSOCIATED WITH S TEAM E LECTRIC P OWER P LANT W ASTEWATER

As discussed above, the pollutants commonly found in steam electric power plant wastewater such as metals, nutrients, and TDS (including bromides and chlorides) can cause

considerable harm to su rface waters, aquatic life, wildlife, and human health. EPA estimated pollutant loadings for the steam electric power plant wastestreams evaluated and considered as part of the revision to the steam electric ELGs ( i.e. , FGD wastewater, fly ash transport water, bottom ash transport water, and combustion residual leachate). The total pollutant loadings for the evaluated wastestreams are significant, with these discharges accounting for over one-third of the toxic pollutant s reported to be discharged in industrial

National P ollutant Discharge Elimination System (NPDES) permits [ERG, 2015a]. EPA estimated the amount of pollutants ( i.e. , loadings) discharged by st eam electric power plants throughout the United States for the evaluated wa stestreams as almost 3 million toxic-weighted pound equivalents (TWPE) annually. 10 EPA uses TWFs as a way to better understand how treatment technologies and industry discharges compare to one another [U.S. EPA, 2012b]. Although EPA uses TWFs and the estimated TWPE as an indicator of a pollutant’s relative potential to cause harm, EPA does not use TWPE to represent actual aqua tic or human health impacts that may have occurred at specific loca tions due to these pollut ant loadings. To assess

10 To calculate the TWPE, EPA multiplies a mass loading of a pollutant in pounds per year (lb/yr) by a pollutantspecific weighting factor, called the toxic weighting factor (TWF), to derive a "toxic equivalent" loading (lbequivalent/yr), or TWPE. TWFs account for differences in toxicity across pollutants and allow mass loadings of different pollutants to be compared on the basis of their toxic potential. EPA has developed TWFs for more than 1,000 pollutants based on aquatic life and human health toxi city data, as well as physical/chemical property data [U.S. EPA, 2012b].

3-12Pollutant Loadings from Steam

Electric Power Plants Evaluated

Wastestreams

 2,210,000,000 pounds of pollutants

per year.

 2,680,000 pounds of TWPE per

year. Section 3—Environmental And Human Health Concerns

impacts to aquatic life or human health, EPA uses the amount of pollutant loadings discharged to the surface water and the resulting c oncentrations in the surface waters.

When coupled with the types of impacts associ ated with the pollutants, the magnitude of the loadings raises concern a bout the risks that th ese discharges present to the aquatic environment and the surrounding ecosystem. This section presents the annual baseline 11 pollutant loadings associated with the evaluated wastestrea ms and compares steam electric discharges to those of other industries to provide perspective on the magnitude of the loadings and subsequent potential impact these wastestreams pose to the environment.

3.2.1 Annual Baseline Pollutant Loadings

In support of the final rule, EPA estimated th e pollutant loadings discharged from steam electric power plants for the evaluated wastes treams, as described in Section 10 of the TDD. 12
Table 3-2 presents the baseline annual pollutantloadings discharged for select pollutants considered for analysis in the EA. 13 EPA presents these loadings in terms of pounds and TWPE and lists the TWF where applicable. The pollutant s with the highest annual TWPE discharges are manganese, cadmium, boron, thallium, mercury, se lenium, and arsenic. Although the total pounds discharged of arseni c, cadmium, mercury, and

thallium are lower than other pollutants, their relative toxicity (as represented by the TWF) results in a large TWPE. Other pollutants, such as boron and manganese, are relatively lo w in toxicity but have a high TWPE due to the fair ly high amount of these pollutants in steam electric power plant wastewater discharges. The high TWPE for selenium results from a combination of its quanti ty discharged in steam electric power plant wa stewaters and its TWF.

11 The analyses presented in this report incorporate some adjustments to current conditions in the industry. See

Section 1 for further details.

12 Prior to finalizing the rulemaking, EPA revised the datasets used to calculate pollutant loadings for bottom ash transport water and fly ash transport water. The final indust ry loadings calculated using these revised datasets are presented in the TDD. The total industry loadings presente d in Section 3.2 reflect the revised datasets. However, EPA did not rerun the EA models and other analyses to reflect the final loadings dataset. EA analyses used previously calculated version of the steam electric power plant pollutant loadings that were derived following the same methodology. The EA pollutant loadings are included in DCN SE05620. Pollutant-specific loadings and removals presented in this report are based on the previously calculated version. Appendix J presents the results of a sensitivity analysis that evaluated the potential for these loadings revisions to affect the EA analyses.

13 EPA selected the pollutants listed in Table 3-2 (which represent a subset of all steam electric pollutants of concern) for analysis in the EA based on the following f actors for each pollutant: presence of the pollutant in the evaluated wastestreams (see Table 2-1); documented elevated levels of the pollutant in surface waters or wildlife from exposure to steam electric powe r plant wastewater; and magnitude of the pollutant loadings to receiving

waters.

3-13Section 3—Environmental And Human Health Concerns

Table 3-2. Annual Baseline Pollutant Discharg es from Steam Electric Power Plants (Evaluated Wastestreams)

Pollutant a TWF b Annual Discharge, pounds (lbs) c Annual TWPE, pound-equivalent (lb-eq) c

Metals and Toxic Bioaccumulative Pollutants
Manganese 0.103 7,530,000 773,000

Cadmium 22.8 13,300 303,000

Boron 0.00834 31,300,000 261,000

Thallium 2.85 63,700 182,000
Mercury 110.0 1,490 164,000

Selenium 1.12 140,000 157,000

Arsenic 3.47 29,600 103,000

Aluminum 0.0647 1,410,000 91,500

Lead 2.24 19,700 44,100
Copper 0.623 31,200 19,500

Vanadium 0.280 66,000 18,500

Iron 0.00560 2,740,000 15,400

Nickel 0.109 120,000 13,100

Zinc 0.0469 174,000 8,160

Chromium VI 0.517 156 80.5

Nutrients
Total Nitrogen d Not applicable 16,900,000 Not applicable
Total Phosphorus Not applicable 214,000 Not applicable

Other

Chlorides 2.435 X 10 -5 930,000,000 22,600

Total dissolved solids Not applicable

Total Pollutants e 2,210,000,000 2,680,000

Sources: Abt, 2008; ERG, 2015a; ERG, 2015b; ERG, 2015f; U.S. EPA, 2012c.
Note: Numbers are rounded to three significant figures.
a – The list of pollutants included in this table is only a subset of pollutants included in the loadings analysis (see Section 10 of the TDD).
b – TWFs for the following metals apply to all metal compounds: arsenic, chromium, copper, lead, manganese, mercury, nickel, selenium, thallium, vanadium, and zi nc. EPA updated TWFs for arsenic, cadmium, copper, manganese, mercury, thallium, and vanadium for the steam electric ELGs pollutant loadings analysis.
c – These loadings reflect adjustments to current conditions in the industry. See Section 1 for further details. Data source for pollutant specific loadings is DCN SE05620.
d – Total nitrogen is the sum of total Kjeldahl nitrogen and nitrate/nitrite as N.
e – The totals represent the pollutant loadings in disc harges of the evaluated wa stestreams – specifically, FGD wastewater, fly ash transport wastewat er, bottom ash transport wastewater, an d combustion residual leachate (see Section 10 of the TDD). Loadings presented are based on the final loadings analysis presented in the TDD. The totals exclude loadings for pollutants not identified as POCs and for biochemical oxygen demand (BOD), chemical oxygen demand (COD), total organic carbon (TOC), total dissolved solids (TDS), and total suspended solids (TSS).

3-14Section 3—Environmental And Human Health Concerns

3.2.2 Comparison of Steam Electric Power Plant Loadings to Other Industries

The total TWPE discharges from the steam electric power genera ting industry are higher than the TWPEs estimated for many other industri es. As part of the Preliminary 2010 Effluent Guidelines Program Plan published on Octobe r 30, 2009 (74 FR 68599), EPA identified 10 point source categories, out of 56, th at represented the bulk of th e estimated toxic wastewater discharges (as measured by TWPE) from existin g industrial point source categories. EPA ranked each point source category by the amount of toxic pollutants in its discharges and identified the Steam Electric Power Generating Point Source Ca tegory (40 CFR 423) as the category with the highest TWPE. Table 3-3 presents the total TWPE estimated as part of the 2010 Effluent Guidelines Planning Process for the remaining nine point source categor ies with the highest TWPE [U.S. EPA, 2011d]. The TWPE estimate d for the 2010 Effluent Guidelines Planning Process includes pollutant loadings estimated fr om discharge monitoring reports (DMRs) and Toxic Release Inventory (TRI) reporting. Ther efore, the industry totals may include doublecounting of certain chemical discharges ( i.e. , a facility must report a chemical on both its DMR and its TRI reporting form).

Table 3-3. Pollutant Loadings for the Final 20 10 Effluent Guidelines Planning Process: Top 10 Point Source Categories

40 CFR Part Point Source Category Total TWPE a
(lb-eq/yr)

423 Steam Electric Power Generating 2,680000 b

430 Pulp, Paper, And Paperboard 1,030,000

419 Petroleum Refining 1,030,000

421 Nonferrous Metals Manufacturing 994,000

418 Fertilizer Manufacturing 826,000

414 Organic Chemicals, Plastics, And Synthetic Fibers 649,000

440 Ore Mining And Dressing 448,000

415 Inorganic Chemicals Manufacturing 299,000

444 Waste Combustors 254,000

410 Textile Mills 250,000

Source: U.S. EPA, 2011d.
a – Only TWPE totals for the steam electric power gene rating industry include updates to TWFs for arsenic, cadmium, copper, manganese, mercury, thallium, and vanadium. The TWPE for all other point source categories is estimated from DMRs and TRI reporting and may include double-counting of certain pollutant discharges ( i.e. , a facility must report a pollutant on both its DMR and its TRI reporting form). Loadings are rounded to three significant figures.
b –EPA calculated the steam electric power generating industry (40 CFR 423) discharges for the final rule as total 2,680,000 TWPE annually (see Section 10 of the TDD). These loadings reflect adjustments to current conditions in the industry. See Section 1 for further details.

EPA estimated that the total baseline TWPE from steam electric pow er plant wastewater

is almost three times the amount estimated fo r the pulp, paper, and paperboard industry, petroleum refining industry, a nd nonferrous metals manufactur ing (second, third, and fourth highest ranking), and it is over five times the TWPE for four of the six ot her industries identified as the top TWPE dischargers in the Final 2010 Effluent Guidelines Program Plan [U.S. EPA,

3-15Section 3—Environmental And Human Health Concerns

2011d]. 14 This suggests that the loadings from the s ubset of evaluated wast estreams represent a greater environmental concern within the context of all industrial dischargers across the United

States.

3.2.3 Comparison of Steam Electric Power Plant Loadings to Publicly Owned Treatment

Works

To provide additional perspective on the magn itude of the pollutant loadings from steam electric power plants, EPA compared loadings fo r the evaluated wastestreams to those of an average publicly owned treatment works (P OTW). EPA selected POTWs for comparison because, for point sources, POTWs and steam elect ric power plants dwarf all other point source discharges in terms of total TWPE of metals di scharged to waters in the United States [U.S. EPA, 2010c]. 15 In addition, the more than 16,000 POTWs are located across the United States and provide a common metric to us e for point source evaluations.

EPA calculated the average pollutant loadi ngs discharged from a typical POTW using EPA’s Effluent Guidelines Program Plan DMR database, DMRLoadsAnalysis2009_v02.mdb. EPA assumed that a typical POTW discharges wast ewater at a rate of 3 to 5 million gallons per day (MGD) 16 based on the number of fac ilities by discharge flow rate reported in Metcalf and Eddy, 2003 [ERG, 2015a]. EPA developed queries in the DMRLoadsAnalysis2009_v02.mdb to do the following: 1) select POTWs that discharg e between 3 and 5 MGD, and 2) calculate the average DMR loadings (in pounds and TWPE per year) for each pollutant [ERG, 2015a]. Table 3-4 compares the average steam electric pollutant loadings by wastestream 17 to the pollutant

14 Data sources for the other industry discharges include DMRs and TRI reports. EPA r ecognizes that the DMR and TRI data have limitations ( e.g. , only a subset of facilities and a subset of pollutants might be included in the estimated loadings); however, these are the most readily available data sets that represent discharges across the

United States.

15 Based on metal loadings (total TWPE) calculated by EPA’ s DMR Pollutant Loading Tool, 2010 data, by Standard Industrial Classification (SIC) code. The top two industries are SIC 4952 – Sewerage Systems ( i.e. , POTWs) and

SIC 4911 – Electrical Services. EPA’s DMR Po llutant Loading Tool is an online tool ( http://cfpub.epa.gov/dmr/ ) that calculates pollutant loadings from permit and DM R data from EPA’s Permit Compliance System (PCS) and Integrated Compliance Information Sy stem for the National Pollutant Di scharge Elimination System (ICISNPDES). The tool also ranks dischargers, industries, and watersheds based on pollutant mass and toxicity, and presents “top 10” lists to help users determine which fa cilities and industries are producing these discharges and which watersheds are impacted. Facilities report pollutant discharge monitoring data in their DMR as mass-based quantities ( e.g. , pounds per day) and/or concentrations ( e.g. , mg/L). The DMR Pollutant Loading Tool allows users to gather annual loadings data. For this EA, EPA reviewed the 2010 loadings reported in DMRs.

The use of the DMR data has its limitations. Only pollutants included in the facility’s NPDES permit are included in the PCS and ICIS-NPDES databases; ther efore, if a facility does not have me rcury limitations, mercury discharges from that facility will not be included in the total for indu strial discharges. States (or other permitting authority) have some discretion as to which data they make available (or enter) to PCS and ICIS-NPDES. For example, permitting authorities enter DMR and permit information for facilities that are considered major dischargers. However, they do not necessarily enter DMR or permit information into PC S for minor dischargers or facilities covered by a general permit.

16 For comparison, the average discharge flow rates for the evaluated wastestr eams are 0.45 MGD for FGD wastewater; 3.5 MGD for fly ash transport water; 2.1 MGD for bottom ash transport water; and 0.08-0.09 MGD for leachate [see Section 6 of the TDD].

17 EPA calculated the average pollutant lo adings for each wastestream by dividing the total pollutant loadings for the wastestream by the number of steam electric power plants discharging the wa stestream [ERG, 2015a].

3-16Section 3—Environmental And Human Health Concerns

loadings from an average POTW assumed to disc harge 3 to 5 MGD. The results of the analysis demonstrate the following:

 Average FGD wastewater discharges contain over 200 times more boron and manganese, over 75 times more selenium, and approximately 20 times more cadmium and nickel than average POTW discharges.

 Average fly ash transport water discharg es contain over 10 times more boron,

cadmium and thallium and over five times mo re arsenic, nickel, and selenium than average POTW discharges.

 Average bottom ash transport water discha rges contain 30 times more thallium; approximately 10 times more manganese and nickel; and five times more cadmium than average POTW discharges.

 Average combustion residual leachate wastew ater discharges c ontain more boron, iron, manganese, and selenium than average POTW discharges.

Nutrient loadings (total nitrogen and total phosphorus) from the average steam electric wastestreams are generally lower than the nutrient loadings from an average POTW. Total nitrogen loadings from an average FGD wastestream are approximately equal to those of an average POTW. Nitrogen loadings from average fly ash and bottom ash transport waters are less than the total nitrogen discharges from an average POTW (approximately 20 percent). The amount of total phosphorus discharged by an average POTW is over 20 times higher than that in the average fly ash transport water, bottom ash transport water discharges, and FGD

wastewater. EPA did not calculate nutrient loadings for combustion residual leachate.

For chlorides, EPA found that average

FGD wastewater di scharges contain approximately six times greater chlorides Loadings of the Evaluated Wastestreams Compared to POTWs

 FGD wastewater discharges contain:

- 200 times more manganese

- 200 times more boron

- 75 times more selenium

- 20 times more nickel

- 20 times more cadmium

 Bottom ash transport water discharges

contain 30 times more thallium and 10 times more manganese and nickel.

 Fly ash transport water discharges contain five times more arsenic, nickel, and selenium and 10 times more boron, cadmium, and thallium.

 Combustion residual leachate contains over

four times more boron and iron.

loadings than an average POTW discharge. The average discharges of fl y ash transport water, bottom ash transport water, and combustion resi dual leachate from a steam electric power plant

contain less chlorides than a t ypical POTW discharge (less than 10 percent). EPA’s DMR data did not include pollutant loadi ngs for TDS from POTWs; ther efore, EPA could not compare these pollutant loadings between steam electric and POTW discharges.

3-17Section 3—Environmental And Human Health ConcernsTable 3-4. Comparison of Average Pollutant Loadingsin the Evaluated Wastestreams to an Average POTWPollutantAverage Plant FGDWastewater Dischargea,bAverage Plant Fly AshTransport WaterDischargea,cAverage Plant BottomAsh Transport WaterDischargea,dAverage PlantCombustion ResidualLeachate Dischargea,eAverage POTWDischargea,fLoadings(lbs/yr)TWPE(lb-eq/yr)Loadings(lbs/yr)TWPE(lb-eq/yr)Loadings(lbs/yr)TWPE(lb-eq/yr)Loadings(lbs/yr)TWPE(lb-eq/yr)Loadings(lbs/yr)TWPE(lb-eq/yr)Aluminum1,53099.18,4905494,24027483754.13,590215Arsenic9.5433.13121,08066.523110.837.545.9159Boron334,0002,79017,9001492,19018.36,53054.51,54012.8Cadmium81.21,85047.71,09019.14352.8765.33.5480.6Chromium VI(g)(g)2.621.350.1360.070(g)(g)17.79.02Copper17.911.126316489.055.52.161.3415495.3Iron1,1506.425,14028.87,61042.610,40058.42,53014.2Lead5.7112.815234063.4142(g)(g)48.5109Manganese74,5007,65048649.94,77049079081.135436.1Mercury5.506057.858643.193510.29832.83,180350,000Nickel62067.618019.630132.713.11.4330.63.06Selenium1,4101,58013415032.436.331.235.018.520.7Thallium16.747.71373923028630.3380.9649.9428.2Vanadium20.85.8222061.711.43.21538151No dataNo dataZinc98346.173434.424711.659.12.7745318.1Total Nitrogen128,000--23,400--24,600--(g)--123,000--TotalPhosphorus457--864--715--(g)--17,800--Chlorides10,200,00024883,5002.0396,7002.35120,0002.931,610,00039.3TDS40,400,000--1,760,000--2,560,000--1,020,000--No data--Note: Numbers are rounded to three significant figures.a – TWPE presented in the table include updates to TWFs for arsenic, cadmium, copper, manganese,mercury, thallium, and vanadium.b – Average loadings based on 88 plants assumed to discharge FGD wastewater under baseline conditions [ERG, 2015a].c – Average loadings based on 50 plants assumed to discharge fly ash transport water under baseline conditions [ERG, 2015a].d – Average loadings based on 183 plants assumed to discharge bottom ash transport water under baseline conditions [ERG, 2015a].e – Average loadings based on 95 plants assumed to discharge combustion residual leachate under baseline conditions [ERG, 2015a].f – Average loadings based on average loadings calculated for POTWs discharging 3 to 5 MGD of wastewater (see DCN SE01961).g – EPA did not calculate loadings for this pollutant andwastestream. See the Costs andLoads Report (DCN SE05831).3-18Section 3—Environmental And Human Health Concerns

To provide additional perspective on the ma gnitude of the loadings, EPA calculated the equivalent number of typical POTWs that w ould discharge loadings equal to the 202 steam electric power plants 18 included in the baseline loadings analysis. Table 3-5 presents total pollutant loadings for the evaluated wastestream s (for the 202 plants) and the number of typical POTWs that would discharge equivalent loadings. The results demonstrate that the magnitude of the total loadings from 202 steam electric power pl ants is equivalent to a significantly larger number of typical POTWs for many of the pollutants commonl y known to cause environmental harm. For example, EPA estimated that the tota l loadings in discharg es of the evaluated wastestreams from these 202 plants are equivale nt to approximately 20,000 POTW discharges of boron and manganese; over 7,500 POTW discharges of selenium; over 6,000 POTW discharges of thallium; over 3,500 POTW discharges of ca dmium and nickel; over 1,000 POTW discharges of iron; and over 500 POTW discharges of arseni c and chlorides. This suggests that, for the evaluated wastestreams, 202 steam electric power pl ants contribute substan tial pollutant loadings

to the environment.

Table 3-5. Estimated Number of POTW Equivalen ts for Total Pollutant Loadings from the

Evaluated Wastestreams

Pollutant Annual Discharge pounds (lbs) Equivalent Number of Average

POTWs a

Aluminum 1,410,000 394

Arsenic 29,600 646

Boron 31,300,000 20,300

Cadmium 13,300 3,760

Chromium VI 156 8.81 Copper 31,200 203

Iron 2,740,000 1,080

Lead 19,700 406
Manganese 7,530,000 21,300
Mercury 1,490 <1

Nickel 120,000 3,920

Selenium 140,000 7,560

Thallium 63,700 6,410

Vanadium 66,000 No values for comparison

Zinc 174,000 384 Total Nitrogen 16,900,000 138 Total Phosphorus 214,000 12.0

Chlorides 930,000,000 578

TDS 4,210,000,000 No values for comparison

Source: ERG, 2015a.
Note: Numbers are rounded to three significant figures.
a – Equivalent number of POTWs is estimated by dividing the total annual pollutant loadings from the 202 steam electric power plants by the average POTW load ings presented in Table 3-4 for a 4-MGD POTW.

18 The count of 202 steam electric power plants includes se ven indirect dischargers that discharge wastewater to a POTW and do not discharge any of the evaluated wastes treams directly to surface wa ters. EPA included these indirect dischargers to protect confidential business information.

3-19Section 3—Environmental And Human Health Concerns

3.3 E NVIRONMENTAL I MPACTS FROM S TEAM E LECTRIC P OWER P LANT W ASTEWATER

EPA identified environmental impacts from EPA’s assessment of damage cases and literature sources (“other documented site im pacts”) caused by steam electric power plant

wastewater and combustion resi duals. EPA found over 150 steam elec tric power plants causing environmental impacts to surface water and gr ound water environments following exposure to steam electric power plant wastewater. Impact s identified in the damage cases and other documented site impacts include lethal and sublethal impacts on fish, impacts on the diversity and size of populations in the ecosystem, and impacts on drinki ng water quality. While these impacted sites are often assumed to be anomalies, mounting evidence indicates that the characteristics contributing to the documented impact ( e.g. , magnitude of the pollutant loadings, type of pollutant present, pl ant operations, and wastewater handling techniques) are common among steam electric power plant receiving water lo cations [Cherry et al ., 2000; NRC, 2006;

Rowe et al ., 2002].

Section 3.3.1 presents a qualitative discussion of the lethal and sublethal ecological effects of pollutants in steam electric power plant wastewater. Section 3.3.2 summarizes documented instances where steam electric power plant wastewater discharges have caused fish advisories or exceeded MCLs presenting a pot ential human health concern. Section 3.3.3 and Section 3.3.4 summarize the damage cases and ot her documented site impacts to surface water and ground water, respectively. Section 3.3.5 discusses the potenti al for these environmental impacts to occur at other locations.

3.3.1 Ecological Impacts

Documented ecological impacts associated w ith exposure to steam electric power plant wastewater include acute effects ( e.g. , fish kills) and chronic effects ( e.g. , malformations, and metabolic, hormonal, and behavioral disorder s) upon biota within the receiving water and surrounding environment. Effects have included re duced growth and reduced survival of aquatic organisms and changes to the local ha bitat [Carlson and Adriano, 1993; Rowe et al ., 2002].

This section provides examples of the lethal and sublethal effects on organisms exposed to steam electric power plant wastewater pollutants ( e.g. , arsenic, cadmium, chromium, copper, mercury, and selenium) in surface waters and se diment. Scientific studi es reported in the

literature included:

 Field studies in which organisms collect ed from known contaminated sites were compared to those collected from uncontaminated sites.

 Laboratory experiments in wh ich organisms intentionally exposed to steam electric power plant wastewater were compared to those unexposed.

Many of the scientific studies documented in the literature focused on selenium as a key pollutant of environmental concern within stea m electric power plant wa stewater. However, due to the complex nature of the wastewater, many studies evaluated the e nvironmental effects of metals in steam electric power pl ant wastewater in aggregate.

3-20Section 3—Environmental And Human Health Concerns

Lethal and Sublethal Effects of Selenium

Selenium can bioaccumulate to toxic levels in organisms inhabiti ng environments with low selenium concentrations. For example, Leml y conducted a field study that investigated the patterns of selenium biomagnification and toxic ity in aquatic organisms inhabiting a cooling

water reservoir that received effluent from a power plant’ s surface impoundment [Lemly, 1985a]. Throughout the study, selenium concentra tions in the reservoir averaged 10 μg/L; however, Lemly reported that fish tissue concentrations reached levels ranging from 500 to 4,000 times the average reservoir water selenium concen tration. The resu lts of the study indicated that the extent of selenium bioaccumulation depended on the trophic level of the fish present in the reservoir. Lemly observed that the selenium accumulation increased as the trophic level increased, which potentially correlated with the observed elimination of multiple higher-tropiclevel fish species. Therefore, these findings su ggest that—even at low concentration within a

surface water—selenium can accumulate and bioma gnify to toxic levels in aquatic organisms and pose a lethal threat to fish at the top of the trophic structure [Lemly, 1985a]. Predicting the impacts of selenium in aquatic ecosystems can be particularly challenging, because impacts to the ecosystem cannot be determined solely on the selenium concentration in the receiving water as demonstrated in this study.

Selenium discharges also impact species di versity in receiving wa ters. In 1977, two years after the initial operation of the Belews Creek Steam Station in North Carolina, the fish community inhabiting the plant’s cooling water re servoir (a lake) underwent rapid decline, and species diversity drastic ally altered [Lemly, 1985a]. Lemly observed that 17 of the 20 fish species originally present in the lake were eliminated after the power plant began operation, including all game species (temperate perch [ Percichthyidae ], true perch and pike perch [ Percidae ], and sunfish [ Centrarchidae ]). Lemly reported significant levels of selenium accumulation in the eliminated species and st atistically unchanged levels of selenium accumulation in the surviving species, relative to levels before the power plant began operation. Only three species maintained reproducing populat ions in the reservoir: one native species (mosquitofish) and two introduced non-native sp ecies of minnows (fathead minnows and red shiners) [Lemly, 1985a].

A number of scientific studies express con cern over selenium exposure within lakes and reservoirs where longer residence times allow fo r further bioaccumulation and a greater potential

to reach lethal concentrations. This is demonstrated by a series of major fish kills that occurred in

1978 and 1979 at Martin Creek Lake (Texas) due to the el evated concentrations of selenium in the water and fish tissue [U.S. EPA, 2014b]. In particular, studies conc luded that elevated selenium concentrations were likely the primary c ontributor to fish kills in lakes and reservoirs, decreasing population density a nd community diversity [Coughlan and Velte, 1989; Crutchfield, 2000b; Crutchfield and Ferguson, 2 000a; Cumbie and Van Horn, 1978].

The sublethal effects of selenium vary wide ly and can impact growth, reproduction, and survival of susceptible organisms. Scientists have demonstrated that various fish and amphibian species are sensitive to elevated selenium concen trations such as those found in steam electric power plant wastewater. In additi on to lethal effects described above, these fish and amphibian species have developed sublethal symptoms such as accumulation of selenium in tissue (histopathological effects) and in the blood (h ematological effects), re sulting in decreased

3-21Section 3—Environmental And Human Health Concerns

growth, changes in weight, abnormal morphol ogy, and reduced hatching success [Coughlan and Velte, 1989; Lemly, 1993; Sager and Colfield, 1984; Sorensen, 1988; Sorensen and Bauer, 1984a; Sorensen et al ., 1982, 1983, 1984b].

The literature indicates that the extent of selenium accumulation in fish tissue varies by species, and selenium accumulates most significan tly in the liver and reproductive tissues in most species [Baumann and Gi llespie, 1986; Sager and Colfie ld, 1984; Sorensen, 1988]. Other studies have reported accumulation in the skeletal muscle, kidneys, gills, and hearts of fish, resulting in pathological lesion s, morphological changes, increas ed organ weight, and decreased growth [Coughlan and Velte, 1989; Lemly, 2002; Sorensen and Bauer, 1984b]. Aquatic organisms exposed to steam electric power plant wastewater have exhibited elevated selenium concentrations in organs such as kidneys, liv er, and gonads, resulting in abnormalities that hinder growth and survival [Rowe et al ., 2002].

In addition, selenium is highly teratogenic ( i.e. , able to disturb the growth and development of an embryo or fe tus) and readily transferable from mother to egg [Chapman et al.

, 2009; Janz et al. , 2010; Lemly, 1997b; Maier and Kni ght, 1994]. Selenium is known to bioaccumulate in the reproductive organs of fish and amphibian species. In one study, ovarian selenium concentrations in bluegill fish were observed at levels 1,000 times greater than the surrounding surface water [Baumann and Gillespie, 1986]. Multiple studies have documented reproductive failure or diminished reproductive success in both fish and amphibians inhabiting ponds, lakes, and reservoirs contaminated with selenium from steam electric power plant wastewater discharges [Baumann and Gillespi e, 1986; Crutchfield, 2000b; Cumbie and Van Horn, 1978; Gillepsie et al ., 1986; Hopkins et al ., 2002; Nagle et al ., 2001]. For example, Hopkins et al . [2006] observed reduced hatching success, abnormal swimming, and abnormalities in the face and skull in the offspring of selenium-contaminated female toads. Field and captive feeding studies also show reproductive impairment (r educed hatchab ility of eggs) among waterfowl exposed to elevated levels of selenium [Adams et al. , 2003; Ohlendorf, 2003 and 2007; Beckon et al ., 2008; U.S. DOI, 1998; Smith et al ., 1998].

Histopathological effects ( i.e. , observable changes in tissue ), increased metabolic rate, and decreased growth rates are effects typicall y caused by contamination from steam electric power plant wastewater. Water and fish samples collected before and after the discharge of power plant wastewater from the surface impoundmen t to the Texas Utilities Martin Creek Lake found that selenium concentrations were significantly elevated in the reservoir and in fish livers, kidneys, and gonads. In 1984, Garrett and Inman repor ted that elevated selenium concentrations persisted in the livers and kidneys of several species of fish fo r up to 3 years after the power plant wastewater discharges ceased. Additiona lly, a 1988 study by Sorensen found that red ear sunfish native to the reservoir exhibited ovary abnormalities related to elevated selenium concentrations up to 8 years following an 8-month exposure to pow er plant wastewater discharges. Although the surface impoundment discharge was short-lived, many of the histopathological effects persisted for y ears after the discharge had ceased [Rowe et al ., 2002].

These sublethal effects of selenium, while no t directly resulting in the mortality of exposed aquatic wildlife, can ultimately cause the types of population-level impacts described under lethal impacts above. The available scie ntific evidence indicates that reproductive success—specifically, offspring mortality and seve re development abnormalities that affect the

3-22Section 3—Environmental And Human Health Concerns

ability of fish to swim, feed, and successfully avoid predation—is the critical assessment endpoint when evaluating the potential for sele nium exposure to result in population-level impacts to resident fish species.

For a summary of the impacts of selenium on surface water, refer to Table A-10 in Appendix A.

Lethal Effects of Other Pollutants

Scientific studies have confirmed that both acute and chronic expos ure to pollutants in steam electric power plant wastewater can be leth al to a wide range of aquatic organisms. For example, Guthrie and Cherry [1976] found that shrimp darters and salamanders were highly sensitive to acute exposures of steam electric power plant wastewater and experienced nearly 100 percent mortality following a five-day expos ure to power plant wastewater discharges.

Invertebrates and fish also evaluated in the stu dy were less sensitive to the acute exposure to power plant wastewater and reported lower ra tes of mortality [Guthrie and Cherry, 1976]. Chronic exposures to power plant wastewater are also of concern; however, studies show extreme differences in species sensitivity [Rowe et al ., 2002]. For example, juvenile chubsuckers (a benthic fish) exposed for 45 days to sedime nts, water, and food c ontaminated with power plant wastewater experienced a 75 percent mortality rate [Hopkins et al ., 2001]. In another study, bullfrogs exposed to sediment and water from a combustion residual surface impoundment for 34 days demonstrated an 87 percent mortality rate (which was 41 percent greater than the mortality rate of bullfrogs in cluded in control group) [Rowe et al ., 2002]. A third study reported no lethal effects for banded snakes exposed fo r 2 years to fish collected from combustion residual surface impoundments [Hopkins et al ., 2002].

Other studies examined lethal effects of sediments contaminated with combustion residuals. For example, eggs and hatchlings of fish and reptiles raised in contaminated sediment reported higher mortality rates (16 to 94 percent) than eggs and hatchlin gs from control groups [Hopkins et al ., 2000; Nagle et al ., 2001; Roe et al ., 2006; Rowe et al ., 1998a, 1998b, 2001; Snodgrass et al ., 2004]. Each of the studies observed elevat ed mortality rates in conjunction with higher concentrations of steam electri c power plant wastewater pollutants ( e.g. , arsenic, cadmium, chromium, copper, selenium) in the exposed sediment.

Three studies evaluated the le thal effects of specific pollutants in steam electric power plant wastewater on a va riety of organisms ( i.e. , insects, fish, and amphibians) and determined the median lethal concentration (LC 50 ) for each pollutant-org anism combination. LC 50 is the concentration expected to be lethal to 50 per cent of a group of organisms exposed for a given

time duration. Table 3-6 summarizes the result s from the three experiments and Table 3-7 presents the LC 50 concentrations reported in the studies. Overall, the LC 50 studies report speciesspecific differences, particularly among spec ies living downstream of fly ash surface impoundment discharges. The downstream species de veloped resistance to pollutants compared to those living in unpolluted ponds. Because the LC 50 concentrations were much higher than actual aquatic concentrations, there was no evidence in these experiments of acute lethal effects, though long-term (1 to 3 months) lethal effects could not be ruled out [Benson and Birge, 1985; Birge, 1978; Specht et al ., 1984].

3-23Section 3—Environmental And Human Health Concerns

Sublethal Effects of Other Pollutants

Although the majority of sublet hal effects documented in the literature primarily focus on selenium concentrations in steam electric power plant wastewater, several studies discussed the sublethal effects of other pollutants, such as arsenic, cadmium, chromium, copper, and lead [Rowe et al ., 2002]. Sublethal effects from exposure to pollutants other than selenium in power plant wastewater can include changes to morphology ( e.g. , fin erosion, oral deformities), behavior ( e.g. , swimming ability, ability to catch prey, ability to escape from predators), and metabolism that can negatively affect long-term survival. For example, a study of larval bullfrogs living in combustion residual surf ace impoundments found that more than 95 percent

of individuals had abnormal oral st ructures, such as the absence of grazing teet h or entire rows of teeth, which altered feeding habits and subseque ntly reduced growth rates in the affected bullfrogs [Rowe et al ., 1996]. In another study, tail malformations in larval bullfr ogs attributed to power plant wastewater expos ure caused abnormal swimming behavior, and the affected bullfrogs were preyed upon mo re frequently than bullfrogs from unpolluted sites [Raimondo et
al ., 1998].

Several studies have demonstr ated increased metabolic rates and decreased growth rates in aquatic organisms exposed to steam electri c power plant wastewater. Increased metabolism causes organisms to waste energy during normal me tabolic processes, whic h can affect growth. In a 1998 study by Rowe, grass shrimp caged in a surface impoundment for eight months experienced a 51 percent increase in standard me tabolic rate. Similarly, crayfish captured near the impoundment experienced increased metabolic ra tes and decreased growth rates—effects that were also observed in crayfish collected fr om unpolluted sites and e xposed to contaminated

sediments from the combustion residual surface impoundment [Rowe et al ., 2002].

3-24Section 3—Environmental And Human Health Concerns

Table 3-6. Summary of Studies E valuating Lethal Effects of

Pollutants in Steam Electric Power Plant Wastewater

Citation Studied Organism Test

Performed Trace Elements

Studied Summary of Results

Birge,

1978 Eggs from goldfish, trout,

and toads 7- to 28-day

lethal effects 22 elements Among the 22 elements tested, cadmium, chromium, mercury, nickel, lead, and silver were the most toxic to all three species, with most LC 50 being 0.1 milligrams per liter (mg/L) or less.

Benson and Birge,

1985 Minnows (fish) living in fly ash-polluted ponds in Kentucky compared to those living in uncontaminated ponds Acute (96­ hour) toxicity Cadmium
Copper

Zinc The study found a hi gher tolerance to cadmium and copper in the exposed fish compared to the fish from unpolluted ponds. However, both exposed and unexposed populations

exhibited similar tolerance to zinc. See

Table 3-7 for LC 50 values.

Specht et
al ., 1984 Insects (coleopterans, mayflies, and other insects) exposed to fly ash surface impoundment effluent from the Appalachian Power Plant in Giles County, Virginia, compared to those living in an uncontaminated pond Acute (96­ hour) toxicity Cadmium
Copper

Zinc The study observed a higher tolerance to pollutants in exposed insects compared to those living in unpolluted ponds. See Table 3-7 for LC 50 values.

3-25Section 3—Environmental And Human Health ConcernsTable 3-7. Median Lethal Concentrations (LC50) for Pollutants in Steam Electric Power Plant WastewaterPollutantLC50, mg/L7- to 28-Day Exposure96-Hour ExposureTrout[Birge, 1978]Goldfish[Birge, 1978]Toad[Birge, 1978]ExposedMinnows[Benson andBirge, 1985]ControlMinnows[Benson andBirge, 1985]Mayflies[Spechtet al.,1984]Other Insects[Spechtet al.,1984]Aluminum0.560.150.05Arsenic0.540.490.04Cadmium0.130.170.043.89a9.55b3.06a7.16b0.271.2-250Chromium0.180.660.03Cobalt0.470.810.05Copper0.095.20.040.36a0.41b0.21a0.39b0.180.03-8.3Lead0.181.660.04Mercury0.0050.120.001Nickel0.052.140.05Selenium4.188.780.09Silver0.010.030.01Vanadium0.164.60.25Zinc1.062.540.016.14a5.96b6.09a7.45b18.4418.2Acronyms: mg/L – milligrams per liter.Shaded cells indicate that the pollutant was not evaluated.a – Nominal water hardness of 100 mg/L calcium carbonate (CaCO3).b – Nominal water hardness of 250 mg/L calcium carbonate (CaCO3).3-26Section 3—Environmental And Human Health Concerns

3.3.2 Human Health Effects

Exposure to pollutants can cause noncancer effects in humans, including damage to the circulatory, respirator y, or digestive systems and neurological and developmental effects. Steam electric power plant wastewater includes toxic pollutants and known or suspected carcinogens ( e.g. , arsenic and cadmium). In the literature review, EPA identified potential human impacts from consuming fish in contaminated waters and from ingesting drinking water contaminat ed by pollutants from

combustion residuals. 19

During the late 1970s, three power plant cooling water reservoirs in Texas received discharges from surface impoundments containing elevated selenium levels, resulting in

a series of fish kills. The re servoirs included Brandy Branch Re servoir, located in Harrison County; Welsh Reservoir, located in Titus Count y; and Martin Creek Lake, located in Rusk County. Investigations at the reservoirs implicated elevated selenium levels in the fish tissue as the cause. In 1992, the Texas Department of Health issued a fish consumption advisory for the three reservoirs after determining that the level of selenium in fish could pose a potential health risk to humans, especially children 6 years or younger and pregnant women.

Ground water and drinking water supplies can be degraded by pollutants in steam electric power plant wastewater and combustion residu al leachate [Cross, 1981]. Combustion residual leachate can migrate from the site in the ground wa ter at concentrations that could contaminate public or private drinking water wells and surface waters, even years following disposal of combustion residuals [NRC, 2006], as exemplif ied in the following example. The Wisconsin Electric Power Company (WEPCO) plant in Port Washington, Wisconsin, had disposed of fly ash in a quarry for over 20 year s (1943-1971) at a depth of 40 to 60 feet, with some of the disposed ash below the water table. The disposal site is located in an upland area where downgradient ground water is used as a source of drinking water. The Wisconsin Department of Natural Resources was notified in January 1980 and November 1990 that elevated levels of sulfates, selenium, and boron were found in a pr ivate drinking water well located 250 feet downgradient from the coal-fired power plant waste disposal site. The imp acted private well was replaced with a deeper well to avoid furt her contamination [U.S. EPA, 2014c].

19 In this EA, EPA evaluated the threats to human health and the environment associat ed with pollutants leaching into ground water from surface impo undments and landfills containing combustion residuals. If these leached pollutants do not constitute the discharge of a pollutant to surface waters, then they are not controlled under the steam electric ELGs. While the CCR rulemaking is the ma jor controlling action for these pollutant releases to ground water, the ELGs could indirectly reduce impacts to ground water. These secondary improvements are

discussed in Section 7.8. N umerous damage cases show exceedances of drinking water standards at ground water and drinking water wells due to leachate from

nearb y impoundments and land f

ills.

3-27Section 3—Environmental And Human Health Concerns

As discussed in Section 3.3.4 and Appendix A, there have been documented exceedances of MCL drinking water standards at off-site ground water and dr inking water wells. Exceedances of MCLs in the ground water indicate potential human health impacts if the pollutants enter private drinking water wells. Section 3.3.4 outlines three documented instances where

combustion residual leachate contamination cause d impacts to private drinking water wells.

Drinking water standards can also be exceeded in surface waters. For example, Duke Energy's Riverbend Plant discharges surface im poundment effluent into Mountain Island Lake, which supplies drinking water to 700,000 peopl e. The county detected arsenic and zinc

concentrations above state standards in an area near the surface impoundment discharge pipe [ Charlotte Observer , 2010]. While most of the pollutants in the surface water would likely be reduced to safe levels during drinking water treatment, elevated levels of pollutants in source water can impact the effectiven ess of drinking water treatment processes and the ability of drinking water treatment plants to meet MCLs. Section 3.4.6 presents further details on drinking water resources near steam electric power plants.

3.3.3 Damage Cases and Other Documented Surface Water Impacts

Changes in surface water chemistry due to c ontamination from steam electric power plant wastewater can negatively impact all levels of an ecosystem, including lower food chain organisms, which affect the ecosystem’s food web; fish inhabiting the surface water; and wildlife and humans when they bathe in or drink the water. As described in earlier sections, pollutants in surface water can accumulate in aquatic organisms su ch as fish. When wildlife or humans ingest these aquatic organisms, they can be exposed to a higher dose of contamination than through direct exposure to the surface water. Docume nted surface water impacts associated with discharges of steam electric power plant wast ewater include damage to fish populations ( i.e.

, physiological and morphological abnormalities a nd various behavioral, reproductive, and developmental effects), decreased diversity in insect populations, and decline of aquatic macroinvertebrate popul ation. Impacts that

affect humans include exceedances of NRWQC, fish consumption advisories, and designation of surface waters as impaired (limiting recreational activities).

EPA’s damage case assessment found 26 proven damage case sites and 31 potential damage case sites with surface water impacts [U.S. EPA, 2014a through 2014e]. Including documented site impacts from the literature review, EPA identified impacts to surface waters at nearly 70 stea m electric power plants following exposure to wastewater (more than 140 documented site impacts) [ERG, 2015m]. Some of the documented impact sites are the same locations identified by EPA as damage case sites. Table 3-8 highlights several damage case and other documented impact sites where Some wastewater surface impoundments are located in, or near, large river floodplains.

F

ailure of the embankments of surface impoundments can release catastrophic amounts of pollutants into surrounding

ecosystems.

3-28Section 3—Environmental And Human Health Concerns

negative surface water impacts from steam electric pow er plant wastewater discharges have been studied. In most cases, negative impacts have b een studied and documented in multiple articles and reports. Tables A-6 and A-7 in Appendix A summarize the damage cases from combustion residual surface impoundments and landfills, respectively.

3-29Section 3—Environmental And Human Health ConcernsTable 3-8. Summary of Select Sites withDocumented Surface Water Impacts fromSteam Electric Power Plant WastewaterSite Name andLocationNumber ofDocuments thatDiscuss SurfaceWater Impactsat the SiteEPADamageCaseAssessmentSummary of Surface Water ImpactsBelews Lake,13ProvenIn 1970, Duke Power Company constructed Belews Lake as a cooling water reservoir to support the Belews CreekNCdamage case[U.S. EPA,2014b]Steam Station. Almost immediately after surface impoundment effluent began discharging into the lake, fishpopulations experienced morphological changes, reproductive failure, and eventually death. In 1985, the BelewsCreek Steam Station converted to a dry-ash transport system, ending the surface impoundment discharges to thelake. However, even 11 years afterthe discharges ceased, reproductive abnormalities persisted in the fishpopulations. Due to selenium concentrations, 16 of the 20populations originally present in the reservoir wereentirely eliminated, including all primary sport fish [Lemly, 1997a; U.S. EPA, 2014b].Brandy Branch1ProvenBrandy Branch Reservoir serves as a cooling water reservoir for Pirkey Power Plant. From 1986 to 1989, the TexasReservoir, TXdamage case[U.S. EPA,2014b]Parks and Wildlife Department's) reported increases in the selenium concentrations of the fish inhabiting thereceiving water. As a result, the Texas Department of Health issued a fish consumptionadvisory for the reservoir,because of the potential health impact dueto the levels of selenium in fish. Since the fish kills in the 1980s,Southwestern Electric Power Company has worked cooperatively to monitor fish tissue selenium concentrations,which have decreased since the late 1980s [ATSDR, 1998a].Euharlee Creek,GA1Provendamage case[U.S. EPA,2014b]On July 28, 2002, a sinkhole developed in the surface impoundment at theGeorgia Power Company in Cartersville,GA. The sinkhole expanded to 4 acres, and an estimated 2.25 million gallons of ash/water mixture was released to atributary of the Euharlee Creek. Approximately 80 tons ofash entered Euharlee Creek through a stormwater drainagepipe. This discharge deposited an ash blanket in the creek up to 8 inches deep over 1,850 square feet of the streambottom. Sampling at the ash discharge site found that concentrations of certain metals (arsenic, cadmium, chromium,copper, lead, mercury, and nickel) exceeded EPA RegionIV ecological sediment screening values (ESV'S)indicating a potential for adverse impacts to aquatic life. Sediment concentrations of arsenic measured 14 ppm dryweight–over five times the toxic threshold. Biological sampling indicated that benthic organisms in the tributary andash deposition zone of Euharlee Creek were either killed by contaminants or physically smothered. The resident fishcommunity, which consisted of at least 25 species, was displaced due to the irritation ofhigh turbidity in the ashplume as it moved through during the spill. One month afterthe spill, concentrations of selenium and cadmium wereelevated in crayfish, clams, mollusks,and insects at a Euharlee Creek sitedownstream from the ash deposit.3-30Section 3—Environmental And Human Health ConcernsTable 3-8. Summary of Select Sites withDocumented Surface Water Impacts fromSteam Electric Power Plant WastewaterSite Name andLocationNumber ofDocuments thatDiscuss SurfaceWater Impactsat the SiteEPADamageCaseAssessmentSummary of Surface Water ImpactsGibson Lake,IN4Provendamage case[U.S. EPA,2014b]Gibson Lake is a man-made, shallow impoundment thatreceives surface impoundment effluent from GibsonGenerating Station. Starting in 1986, least terns, an endangered species of migratory birds, began using the dike inGibson Lake as a nesting ground for breeding. To protect the birds from potential toxic exposure, the plant began acooperative program with the Indiana Department of Natural Resources to protect the nesting birds by creating anearby alternative habitat, known asCane Ridge Wildlife Management Area(WMA), which received water pumpedfrom Gibson Lake. In April 2007, Duke Energy closed access to the lake for recreational fishing due to elevatedselenium levels. A year later, the U.S. Fish and Wildlife Service (USFWS) became concerned about selenium levelsin the water and fish in the Cane Ridge WMA. The USFWSstopped the flow of water from Gibson Lake into CaneRidge, discouraged least terns from using the refuge, removed the contaminated fish, and plowed Cane Ridge toredistribute and bury the selenium in the soil. Subsequently, the USFWS stopped the flow of water from GibsonLake into Cane Ridge and piped water from Wabash River instead. Cane Ridge was restocked with fish to lure backmigratory birds. As of 2010, fish populations in Gibson Lake still had selenium levels above the toxic threshold[U.S. EPA, 2014b].Glen Lyn, VA5Provendamage case[U.S. EPA,2014b]Glen Lyn Plant discharged fly ash transport water from a surface impoundmentinto Adair Run, a tributary of theNew River. A 1984 study reported that the local insect diversity and density remained essentially the same upstream(reference site) and downstream of the surface impoundment when the impoundment was not close to capacity.However, as the settling impoundment reached its capacity,the insect density and diversity declined downstream.After closure of the surface impoundment, it took up to 10 months for the insect populations to recover [Spechtetal., 1984].Hyco Lake, NC8Provendamage case[U.S. EPA,2014b]Hyco Lake is a large cooling water reservoir that received effluent from a powerplant, including combustionresidual leachate and fly ash transport water discharges containing high levels of selenium. In 1981, a large-scale fishkill occurred in the reservoir, prompting numerous scientific studies to examine the extent and cause of theenvironmental damage. Multiple studies detected selenium concentrations in the water and tissue of fish inhabitingthe reservoir, while other trace elements were within normal concentrationranges. The selenium accumulated in thefish in the lake, impacting reproduction and causing declines in fish populations in the late 1970s and the 1980s. Afish consumption advisory was issued in 1988 for this lake due to selenium contamination.3-31Section 3—Environmental And Human Health ConcernsTable 3-8. Summary of Select Sites withDocumented Surface Water Impacts fromSteam Electric Power Plant WastewaterSite Name andLocationNumber ofDocuments thatDiscuss SurfaceWater Impactsat the SiteEPADamageCaseAssessmentSummary of Surface Water ImpactsMartin Creek8ProvenMartin Creek Lake is a cooling water reservoir that alsoreceives steam electric powerplant wastewater discharges.Lake, TXdamage case[U.S. EPA,2014b]In 1978 and 1979, a series of major fish kills occurred dueto the elevated concentrations of selenium in the waterand fish tissue. Numerous studies conducted throughout the 1980s documented histopathological and reproductivedamage in the fish populations inhabiting the lake. In addition, the studies determined that, even 8 years afterdischarge ceased, the overall health of the aquatic populationsnear the discharge site remained adversely affected bythe selenium pollution. In 1992, a fish consumption advisory was issued for the lake due to discharges from thesteam electric power plant [U.S. EPA, 2014b].McCoy Branch,TN3Provendamage case[U.S. EPA,2014b]In 1986, coal ash slurry discharges from the Department of Energy’s (DOE’s) Chestnut Ridge Y-12 power plant intoMcCoy Branch were found to contain elevated concentrations of trace elements, which violated the Tennessee WaterQuality Act. A 1992 report written by DOE documented bioaccumulation of contaminantsin fish tissues, decreaseddiversity in benthic macroinvertebrate communities, and increased fish mortality and abnormalities at the site [U.S.DOE, 1992].Mountain5Location notDuke Energy's Riverbend Plant discharges surface impoundment effluent into MountainIsland Lake, which suppliesIsland Lake,assesseddrinking water to 700,000 people. The county staff has detected arsenic and zinc concentrations above stateNCstandards in an area near the surface impoundment discharge pipe [Charlotte Observer, 2010]. The plant continuesto extensively monitor metal concentrations in MountainIsland Lake surrounding the point of discharge [NCDENR,2011].North CarolinaNot applicable,Location notA study of receiving waters (including lakes and rivers) for 10 steam electric power plants in North Carolina(Multiplemultiple sitesassessedevaluated the environmental and ecological impacts that wastewater discharges have on surface waters. The studyLocations)found that the receiving waters at the10 plants contain high levels of contaminants as a result of wastewaterdischarges. From the data collected between 2010 and 2012, contaminant levels at multiple surface waters exceededdrinking water standards and/or NRWQC. For example, arsenic concentrations at two outfalls were as high as 45μg/L and 92 μg/L, respectively (the drinking water MCL for arsenic is 10 μg/L). Whencompared to the upstreampollutant concentrations at the 10 North Carolina locations,data showed elevated levels of contaminants such asboron, chromium, selenium, bromine, arsenic, and thallium. Elevated pollutant concentrations were also found inlake sediments (arsenic and selenium) and pore water near lake bottoms (including manganese, arsenic, nickel, andbromine). The study found elevated levels of arsenic and selenium in fish tissues for two of the lakes (Hyco Lakeand Mayo Lake). A report on fish in Mayo Lake found deformities consistent with ingestion of high selenium levels[Ruhlet al., 2012].3-32Section 3—Environmental And Human Health ConcernsTable 3-8. Summary of Select Sites withDocumented Surface Water Impacts fromSteam Electric Power Plant WastewaterSite Name andLocationNumber ofDocuments thatDiscuss SurfaceWater Impactsat the SiteEPADamageCaseAssessmentSummary of Surface Water ImpactsRocky Run5ProvenRocky Run Creek, a tributaryof the Wisconsin River, receives effluentfrom Columbia Power Station’s surfaceCreek, WIdamage case[U.S. EPA,2014b]impoundments. After the power station began operation in 1975, the aquatic macroinvertebrate populations declinedin the area. Two studies conducted at this site concluded that population density decreased, not because of death dueto coal ash toxicity, but because the aquatic macroinvertebrate populations avoided the area due to sublethalalterations in the creek. Studies found increased TDS and total suspended solids (TSS), as well as a number of heavymetals, downstream from the discharge.Some species of macroinvertebrates were totally eliminated 4 months afterdischarges began.Savannah River23ProvenThe Savannah River Site, which is owned by DOE, is divided into several areas, based on production, land use, andSite, SCdamage case[U.S. EPA,2014b]other related characteristics. The D-area, a site utilizedby numerous ecologists to study the impacts of coal-firedpower plant waste, houses a coal-fired power plant that discharges ash intoa series of surface impoundments and aswamp that ultimately drains into the Savannah River. Numerous studies observed organisms within these habitatsaccumulated high concentrations of trace elements in their tissues and exhibited various physiological, behavioral,and developmental effects. Sediments, water, and biota in the disposal system have elevated concentrations of traceelements and heavy metals derived from bottom ash and fly ash deposited in the basins. The studies documentedseveral impacts to amphibians, reptiles, and fish, including five species of fish that have been eliminated.TVA’s6ProvenOn December 22, 2008, the retaining wall of a surfaceimpoundment at TVA’s Kingston Fossil Plant broke andKingston Fossildamage casereleased billions of gallons of coal ash slurry into the Emory, Clinch, and Tennessee Rivers. Tennessee DepartmentPlant, TN[U.S. EPA,2014b]of Environment and Conservation found exceedances of the more stringent criteria for chronic exposure of fish andaquatic life at least once in January 2009 for several metals (e.g., aluminum, cadmium, iron, and lead). Seven monthsafter the spill, all fish collected had concentrations ofselenium above a toxic threshold, and most were stillcontaminated at that level 14 months after the spill. Twenty-one months after the spill, a high percentage of fish werefound with lesions, deformities, and infections, all symptoms of extreme stress. In addition, studies have shownelevated levels of arsenic and mercury in sediments nearthe ash spill, as well as selenium levels exceeding the MCLin three wells underneath the Kingston’s coal ash disposalarea, ash processing area,and gypsum disposal facility[U.S. EPA, 2014b].3-33Section 3—Environmental And Human Health ConcernsTable 3-8. Summary of Select Sites withDocumented Surface Water Impacts fromSteam Electric Power Plant WastewaterSite Name andLocationNumber ofDocuments thatDiscuss SurfaceWater Impactsat the SiteEPADamageCaseAssessmentSummary of Surface Water ImpactsWelshReservoir, TX2Provendamage case[U.S. EPA,2014b]Welsh Reservoir serves as a cooling water reservoir for Welsh Power Plant. From 1986 to 1989, the Texas Park andWildlife Department reported increases in the selenium concentrations of the fish inhabiting the receiving water. Asa result, the Texas Department of Health (TDH) issued a fish consumption advisory for the reservoir because of thepotential health impact due to the levels of selenium in fish. In 1998, TDH collected 20 fish for reevaluation andobserved an average seleniumconcentration in the fish above the reported national averages. Therefore, the Agencyfor Toxic Substances and Disease Registry (ATSDR) concluded in a report that there was no clear indication of anoverall change in selenium fish tissue concentrations over the 12 years [ATSDR, 1998b].Sources: ATSDR, 1998a; ATSDR, 1998b;Charlotte Observer, 2010; ERG, 2013b; Lemly, 1997a; NCDENR, 2011; Ruhlet al., 2012; Spechtet al., 1984; U.S. DOE,1992; U.S. EPA, 2014b.3-34Section 3—Environmental And Human Health Concerns

3.3.4 Damage Cases and Other Documented Ground Water Impacts

Pollutants in combustion residuals can leach into ground water from surface impoundments and landfills at the site. Older surface impoundments and landfills are of particular concern because they were often built without liners and leacha te collection systems. Liners are typically made of s ynthetic material, asphalt, clay, or a composite of materials ( e.g. , synthetic and clay) and are designed to collect leachate and prevent ground water contamination.

Combustion residuals held in unlined surfac e impoundments can enter the subsurface and contaminate ground water. Pollutants in unlined landfills, used for the dry disposal of combustion residuals, can also leach as precipi tation flows through th e residuals pile and dissolves pollutants; the combustion residual leachate can eventually migrate into ground water. New plants are increasingly installing liner s in surface impoundme nts and landfills, but pollutants can also enter the ground water when liners fail or when a disposal site is situated such that natural ground water fluctuations come into contact with the disposed waste. Furthermore, state regulation on leachate coll ection systems and impermeable li ners is not uniform [EPRI, 1997; 65 FR 32214-32237, 2000].

Numerous damage cases and other documented site impacts demonstrate the toxic effects of steam electric power plant wastewater cont amination to ground water and the potential to impact off-site sources due to combustion residu al leachate migrating from landfills and surface impoundments (often unlined). EPA’s damage case assessment found 24 proven damage case sites and 110 potential damage case sites with ground water impacts [U.S . EPA, 2014a through 2014e]. EPA identified impacts to ground water qua lity caused by combusti on residual leachate from 140 steam electric power plants (more th an 130 documented site impacts) [ERG, 2015m]. Some of these documented site impacts are caused by ash contributions from multiple plants ( e.g. , a landfill that stores ash from multiple plan ts). EPA identified some of the documented impact sites as also being damage case sites. Th e majority of the damage cases and documented site impacts reported ground water pollutant leve ls in on-site wells a bove regulatory levels; however, only a portion of the cas es indicated off-site contamin ation. Documented impacts to off-site ground water resources may be lower due to long migration times within the subsurface

until the combustion residual leachate reaches a known monitoring point [NRC, 2006]. Further, the limited number of studies documenting off-s ite contamination might reflect less extensive monitoring of off-site ground water wells for evidence of impacts from combustion residual leachate, which suggests off-site impacts ma y be underrepresented in the documented ground water impacts [Cherry, 2000].

In surface impoundments, combustion residuals are in constant contact with water, allowing toxic pollutants to leach into and eventually contaminate ground water. From an environmental impact perspective, combusti on residual surface impoundments are generally considered less desirable than landfills for dispos al because they provide constant saturated or nearly saturated conditions and a relatively large hydraulic driving force to move combustion residual leachate into the subsurface [Theis and Gardner, 1990]. Table A-4 in Appendix A summarizes documented ground water damage cas es from combustion residual surface impoundments [U.S. EPA, 2014a through 2014e].

Although more desirable than surface im poundments, landfills pose their own ground

water contamination risks. If the landfills are not properly lined, the pollutants in combustion residuals can leach into the soil during precipitati on. In areas with acid ra in, the precipitation’s

3-35Section 3—Environmental And Human Health Concerns

low pH can accelerate the leaching of contam inants into ground water. In addition, heavy precipitation can not only acceler ate leaching, but also carry pol lutants in stormwater runoff, potentially contaminating ground water or su rface water resources [Andersen and Madsen, 1983]. Table A-5 in Appendix A summarizes doc umented ground water damage cases from combustion residual landfills [MDNRE, 2010; U.S. EPA, 2014a through 2014e].

While many damage cases document elevated po llutant levels in ground water wells, it is unclear how many of these are private drinking water wells (as opposed to monitoring wells). However, the fact that many sites reported MC L exceedances in ground water testing suggests that potential impacts to drinking water resources are a realistic concern. The following three damage cases are documented instances where uncollected combustion residual leachate contaminated ground water and resulted in impacts to private drinking water wells.

Constellation Ash Disposal at Waugh Chape l and Turner Pits – Anne Arundel County, Maryland

For over a decade, Constellation Energy Group (Constellation) supplied fly ash for structural fill at the B.B.S.S. Inc. (BBSS) sand and gravel mines in Anne Arundel County, Maryland. Fly ash from Constellation’s Brandon Shores and Wagner plants was used to reclaim portions of BBSS’s Turner Pit starting in 1995 a nd the Waugh Chapel Pit starting in 2000. In the fall of 2006, Anne Arundel County Health Depart ment officials documented concentrations of sulfate and metals ( i.e. , antimony, beryllium, cadmium, manganese, and nickel) exceeding the state’s screening criteria for potable aquifers in residential wells located downgradient from Waugh Chapel and Turner Pits [MDNR, 2007].

An independent study of the contamination conf irmed that the elevated concentrations of sulfate and metals observed in the wells directly resulted from precipitation infiltrating the fly ash deposited in the BBSS sand and gravel mines [MDNR, 2007]. In October 2007, the Maryland Department of the Environment (MDE) fined Constellation and BBSS $1 million for the ground water contamination and required the co mpanies to restore the local aquifer water quality [MDE, 2008]. In addition, Anne Arundel homeowners impacted by the contamination filed a class action lawsuit against Constellati on and were awarded a $45 million settlement. The settlement required Constellation to pay the co sts for converting 84 homes from well water to public water; cease future deliveries of new coal as h to the quarry; and to establish trust funds to compensate impacted property owners, enhanc e the neighborhood, and re mediate and restore a former quarry site [Schultz, 2008].

Gibson Generating Station Pl ant – Gibson County, Indiana

The Gibson Generating Station Plant has six unli ned surface impoundme nts (four surface impoundments and two settling/de cant basins) and a landfill for combustion residuals. The

landfill consists of a 94- acre older portion built in the late 1970s that is unlined and a 43-acre portion built in 2002 with a composite liner and leachate collection system. Additionally, the plant has a 400-acre landfill (South Landfill), permitted in 2005, which also has a composite liner and leachate collection system.

Samples from monitoring wells downgradient from the older landfill show high levels of arsenic, boron, iron, and manganese. Leaching from the landfill has contaminated 12 drinking

water wells in the hamlet of East Mount Carmel , Indiana, with boron, manganese, iron, sulfate,

3-36Section 3—Environmental And Human Health Concerns

sodium, and TDS. Sampling performed by Duke Energy in 2007 and by the Natural Resources

Defense Council in 2008 show dr inking water contamination from boron, iron, and manganese in at least nine off-site private re sidential wells [U.S. EPA, 2014b].

Ground Water Violations Near North Carolina Power Plants With Surface Impoundments – North Carolina

The North Carolina Department of Environm ent and Natural Resour ces reported groundwater contamination near combustion residual surface impoundments at all 14 of the state’s coalfired power plants. Duke Energy and Progress En ergy each own seven of the plants and perform ground water monitoring as required by the state. Manganese and lead conc entrations exceeded state ground water standards at all 14 locations and TDS and chromium concentrations exceeded

state standards at seven locations. Boron leve ls at six plants ex ceeded state ground water standards, and some plants ha d elevated levels of arsenic, selenium, thallium, antimony, chlorides, and nickel. The state and plants have not identified the source of the contamination but noted that the exceedances occurred at newly loca ted wells. Drilling the wells may have affected the concentration of naturally occurring elements such as lead and manganese [Ballard, 2012]. 20

3.3.5 Potential for Impacts to Occur in Other Locations

Key environmental characteristics that contributed to the impacts documented in Sections

3.3.3 and 3.3.4, such as chronic exposu re to large pollutant loadings, plants discharging to waters with long residence times, and unlined surface impoundments or landfills, are common at steam electric power plants. This suggests that th e impacts documented above indicate the greater potential threat that steam elect ric power plant wastewater discharges pose to the environment. Although substantial events such as fish kills are well documented, the extent to which more subtle damages, such as histopathological changes, morphological deformities, and damage to reproductive success, occur elsewhere is not know n due to the limited extent of monitoring

programs.

Some of the documented environmental imp acts discussed above occurred following discharges of steam electric power plant wastewater under normal operations. Although the actual amounts of pollutant loadi ngs discharged may vary among steam electric power plants, documented site impacts under normal operations do not indicate that th e pollutant loadings associated with the impacts are unusual for st eam electric power plants. This suggests that chronic exposure to typical steam electric power plant wastewater pollutant loadings can impact

the environment at other sites not documented in the literature.

The residence time of steam electric power pl ant wastewater pollutants in surface water is a major factor in determining the impact to the environment and th e length of the recovery time. Many documented impact sites are lent ic waterbodies such as lakes ( i.e. , still waters) where pollutants can reside for long periods of time. These types of surface waters are at particular risk to impacts from steam electric power plant wastew ater discharges. Steam electric power plants that discharge to a pond, lake, or reservoir may experience similar environmental effects as those observed in the documented impacts from analogous aquatic systems [ERG, 2015j].

20 EPA notes that the impacts reported at North Carolina plants have not been docu mented in a peer-reviewed literature source; however, the information shows that elev ated levels of metal contamination can occur near ash ponds.

3-37Section 3—Environmental And Human Health Concerns

3.4 D ISCHARGE TO S ENSITIVE E NVIRONMENTS

The pollutant loadings, ecological impacts, and human health concerns discussed in

Section 3.2 and Section 3.3 are also of concern due to the proximity of many steam electric power plants to sensitive environments where th e characteristics of steam electric power plant wastewater may impair water quality ( e.g. , 303(d)-listed waters and wate rs with fish advisories) or pose a threat to threatened and endangered species. 21 EPA identified the number of surface waters that receive discharges of the evaluated wastestreams and are located in close proximity to the following sensitive environments:

 Great Lakes watershed (Section 3.4.1).

 Chesapeake Bay watershed (Section 3.4.2).

 Impaired waters (Section 3.4.3).

 Fish consumption advisory waters (Section 3.4.4).

 Threatened and endangered spec ies habitats (Section 3.4.5).

 Drinking water resources (Section 3.4.6).

Table 3-9 summarizes the number and percentage of immediate receiving waters located

in sensitive environments.

Table 3-9. Number and Percentage of Immediate Receiving Waters Identified as Sensitive Environments

Sensitive Environment Number (Percentage) of Immediate Receiving Waters Identified a

Great Lakes watershed 25 (11%) Chesapeake Bay watershed 13 (6%) Impaired water 111 (50%) Surface water impaired for a subset of pollutants associated with the

evaluated wastestreams b 59 (27%)

Fish consumption advisory water 140 (63%) Surface water with a fish consump tion advisory for a subset of pollutants associated with the evaluated wastestreams c 93 (42%)

Drinking water resource within 5 miles 199 (90%)

a – For the sensitive environment proxim ity analysis, EPA evaluated 222 immedi ate receiving waters that receive discharges of the evaluated wastestreams [ERG, 2015c; ERG, 2015d].
b – Table B-1 in Appendix B contains a complete list of the impairment categories identified in EPA’s 303(d)­ listed waters and designates the subset of pollutants evaluated.
c – Table B-2 in Appendix B contains a complete list of the types of advisories identified under the sensitive environment proximity analysis, including pollutants that are not associated with the evaluated wastestreams.

3.4.1 Pollutant Loadings to the Great Lakes Watershed

The Great Lakes watershed includes hundreds of tributaries, thousands of smaller lakes, and extensive mineral deposits. The watershed pr ovides a unique habitat th at supports a wide range of flora and fauna, including over 200 globally rare plants and animals and more than 40 species found only in the Great Lakes watershed. Rare species include the white catspaw pearly mussel, the copper redhorse fis h, and the Kirtland’s wa rbler. The watershed provides a habitat

21 See the ERG memorandum “Proximity Analysis Methodology” (DCN SE04448) for a description of the methodology used to evaluate the proximity of st eam electric power plants to sensitive environments.

3-38Annual Discharges to the Great Lakes

Watershed from the Evaluated

Wastestreams

 1.15 million pounds of total nitrogen

 9,570 pounds of thallium

 8,730 pounds of zinc

 5,020 pounds of selenium

 2,170 pounds of arsenic

 1,900 pounds of lead Section 3—Environmental And Human Health Concerns

and food web for an estimated 180 species of native fish, including small- and large-mouth bass, muskellunge, northern pike, lake herring, whitefish, walleye, and lake trout [Great Lakes Restoration Initiative, 2010].

The Great Lakes provide humans with tr ansportation, power, and recreational opportunities including fishing and boating. Between the United States and Canada, the Great Lakes have more than 10,000 miles of coastl ine and 30,000 islands. The watershed is home to more than 30 million people. Recreational spen ding directly supports 107,000 jobs and nearly 250,000 jobs when secondary impacts are taken in to consideration [Gre at Lakes Restoration Initiative, 2010].

Environmental impacts documented in the Grea t Lakes are associated with a range of stressors, including toxic and nut rient pollutants, invasive speci es, and habitat degradation. EPA

and Environment Canada have focused their Great Lakes Binational Toxics Strategy on persistent toxic substances su ch as mercury [U.S. EPA and Environment Canada, 1997; Great Lakes Restoration Initiative, 2010] . Mercury is a concern in all of the Great Lakes due to its

bioaccumulation in fish and wild life and potential impacts on huma ns. For example, in a study of 65 hair samples from fish-eating and non-fish-ea ting women, average mercury concentrations in hair were significantly greater ( i.e. , 128 to 443 percent higher concentrat ion) for wom en who ate several meals of sport-caught fish from the Great

Lakes. EPA and Environment Canada have

docum ented a range of wildlife impacts from mercury in the Great Lakes such as an increase of physiological abnormalities in herring gulls [U.S. EPA and Environment Canada, 2009].

As part of the EA, EPA wanted to determine the extent of impacts to the Great Lakes watershed

that m ight be caused by di scharges of the evaluated wastestreams. The primary source of mercury in the Great Lakes watershed is atmospheric deposition from sources around the Great Lakes watershed ( e.g. , fuel combustion, incineration, and manufacturing) emitting approximatel y 70,000 pounds of mercury annually [Evers et al

., 2011]. When compared to atmospheric depositi on, mercury contributions from point source discharges are less of a concern. Due to the bi oaccumulative nature of mercury, EPA has placed strict controls ( e.g. , mixing zones are not allowed in permits ) to limit the total amount of mercury entering the Great Lakes watershe d. Monitoring within the Great Lakes watershed has indicated a decrease in mercury point source discharges , primarily because of implemented control strategies. EPA identified 23 st eam electric power plants disc harging to the Great Lakes watershed with the majority discharging to Lake Michigan (11 plants) and Lake Erie (6 plants) [ERG, 2015a]. In the Lake Erie Management Pla n, EPA identified steam electric discharges as contributing 57 percent of the mercury to Lake Erie from wastewater sources [U.S. EPA, 2008b].

The potential for bioaccumulative pollutant rete ntion in still or slow-moving water, such as the Great Lakes, is a particular concer n. Many pollutants in stea m electric power plant

wastewater can bioaccumulate in fish and then affect higher trophic le vels and terrestrial environments. Table 3-10 presents total pollutant loadings for the evaluated wastestreams discharging to the Great Lakes watershed.

3-39Section 3—Environmental And Human Health Concerns

Table 3-10. Pollutant Loadings to the Great Lakes Watershed from the Evaluated

Wastestreams

Pollutant Annual Discharge to the Great Lakes Watershed (lbs) Annual TWPE Discharge to the Great Lakes Watershed (lb-eq)

Arsenic 2,170 7,510

Boron 997,000 8,310

Cadmium 648 14,700

Chromium VI 0.548 0.283
Copper 2,550 1,590

Lead 1,900 4,250
Manganese 242,000 24,900
Mercury 82.8 9,110

Nickel 9,840 1,070

Selenium 5,020 5,630

Thallium 9,570 27,300

Zinc 8,730 409
Total Nitrogen 1,150,000

-- Total Phosphorus 23,100

-- Chlorides 31,900,000 778

Total Dissolved Solids 186,000,000

-- Source: ERG, 2015a. Note: Numbers are rounded to three significant figures.

3.4.2 Pollutant Loadings to the Chesapeake Bay Watershed

The Chesapeake Bay is the largest estuary in the United States and is a complex ecosystem that provides habita ts and food webs for diverse gr oups of animals and plants. A variety of fish either live in the Chesapeake Bay and its tributar ies year-round or visit its waters as they migrate along the East Coast. The Chesapeake Bay Watershed covers 64,000 square miles, with 11,684 miles of shorel ine, and includes areas in si x states: Delaware, Maryland, New York, Pennsylvania, Virginia, a nd West Virginia, plus Washi ngton, DC. The watershed includes approximately 284,000 acres of tidal wetlands that provi de critical habitats for fish, birds, crabs, and other species [Chesapeake Bay Program, 2015a and 2015b].

The Chesapeake Bay and its tributaries provide recreational and commercial opportunities, with more than 100,000 streams, creeks, and rivers in the watershed. Fishers commonly catch striped bass and white perch and seafood production from the Bay totals approximately 500 million pounds per year [Chesapeake Bay Program, 2015].

The Chesapeake Bay was the first estuary in

the nation to be selected for restoration as an integrated watershed and ecosystem. The watershed supports over 2,700 species of plants and animals, including 348 species of finfish and 173 species of shellfish. Other aquatic life includes algae, bay grasses, and other invertebrates. The watershed provides habitats for at least 29 species of waterfowl, with a population of near ly one million during the winter (representing Annual Discharges to the Chesapeake Bay from the Evaluated Wastestreams

 993,000 pounds of total nitrogen

 6,560 pounds of selenium

 5,830 pounds of zinc

 5,280 pounds of thallium 2,510 pounds of arsenic

3-40Section 3—Environmental And Human Health Concerns

approximately one-third of th e Atlantic Coast’s migrator y population) [Chesapeake Bay Program, 2015].

Most of the Chesapeake Bay and its tidal waters are listed as impaired for excess nitrogen, phosphorus, and sedime nt. These pollutants cause oxyge n-consuming algae blooms and

create “dead zones” where fish and shellfish cannot survive, bloc k sunlight that is needed for underwater grasses, and smother aqua tic life on the bottom of the Bay. To restore water quality in the Bay, EPA established Total Maximum Daily Load (TMDL) limits for the Chesapeake Bay watershed in December 2010. These limits are 186 million pounds of nitrogen, 12.5 million pounds of phosphorus, and 6.45 billion pounds of sediment each year, reducing the discharges to the watershed by 25 percent for nitrogen, 24 percent for phosphorus, and 20 percent for sediment. Pollutant loadings to the Chesapeake Bay watershed come from both point sources and nonpoint sources. Point sources include municipa l wastewater treatmen t facilities, industrial discharge facilities ( e.g. , steam electric power plants and concentrated animal feeding operations), NPDES permitted stormwater (m unicipal separate storm sewer systems (MS4) and construction and industrial sites) , and other sources. Nonpoint sour ces include agricultural land runoff, atmospheric deposition, fo rest land runoff, nonregulated st ormwater runoff, stream banks and tidal shorelines, tidal resu spension, the ocean, wildlife, and natural background [U.S. EPA, 2010d].

EPA identified nine steam electric power pl ants discharging to the Chesapeake Bay watershed and estimated that these plants disc harge almost one million pounds of nitrogen and over 16,000 pounds of phosphorus to the Bay annually [ERG, 2015a]. Table 3-11 presents the baseline pollutant loadings for the evaluated wastestreams.

Table 3-11. Pollutant Loadings to the Ches apeake Bay Watershed from the Evaluated

Wastestreams

Pollutant Annual Discharge to the Chesapeake Bay Watershed (lbs) Annual TWPE Discharge to the Chesapeake Bay Watershed (lb-eq)

Arsenic 2,510 8,720

Boron 1,390,000 11,600

Cadmium 513 11,700

Chromium VI 16.7 8.62
Copper 2,210 1,380

Lead 1,560 3,490
Manganese 148,000 15,200
Mercury 88.8 9,770

Nickel 5,280 575

Selenium 6,560 7,360

Thallium 5,280 15,100

Zinc 5,830 273
Total Nitrogen 993,000

-- Total Phosphorus 16,800

-- Chlorides 43,000,000 1,050

Total Dissolved Solids 186,000,000

-- Source: ERG, 2015a. Note: Numbers are rounded to three significant figures.

3-41Section 3—Environmental And Human Health Concerns

3.4.3 Proximity to Impaired Waters

A surface water is classified as a 303(d) impaired water when pollutant concentrations exceed water quality standards and the surface water can no longe r meet its designated uses ( e.g. , drinking, recreation, and aquatic habitat). Base d on that definition, half of the immediate receiving waters included in the EA are impaired waters. 22 EPA reviewed the identified 303(d) impairment categories and determined that approximately 27 percent of the immediate receiving waters are impaired for a pollutant associated with the evaluated wastestreams, as shown in Table 3-12. Figure 3-1, Fi gure 3-2, and Figure 3-3 illustrate the geographical location of plants that directly discharge wastewater to a water cl assified as impaired by high concentrations of mercury, metals (other than mercury), and nutrients.

Table 3-12. Number and Percentage of Imme diate Receiving Waters Classified as Impaired for a Pollutant Associated with the Evaluated Wastestreams

Pollutant Causing Impairment Number (Percentage) of Immediate Receiving Waters Identified a

Mercury 30 (14%)

Metals, other than mercury b 28 (13%)

Nutrients 19 (9%)

TDS, including chlorides 4 (2%)

Total for Any Pollutant c 70 (32%)

a – For the impaired waters proximity analysis, EPA evaluated 222 immedi ate receiving waters that receive discharges of the evaluated wastestreams [ERG, 2015c; ERG, 2015d].
b – The EPA impaired water database listed 28 immediate r eceiving waters as impaired based on the “metal, other than mercury” impairment category. Of those 28 immediate receiving waters, 13 receiving waters are also listed as impaired for one or more specific metals in the EA an alysis (arsenic, cadmium, chromium, copper, lead, manganese, selenium, and zinc). One additional i mmediate receiving water is impaired for boron (but not included in the “metals, other than mercur y” impairment category).
c – Total does not equal the sum of the immediate receiving waters listed in the table. Some immediate receiving waters are impaired for multiple pollutants.

22 Table B-1 in Appendix B lists the impairment categories identified under the sensitive environments proximity analysis, including pollutants that are not as sociated with the evaluated wastestreams.

3-42Figure 3-1. Location of Plants that Direct ly Discharge the Evaluated Wastestreams to a Surface Water Impaired due to Mercury

Figure 3-2. Location of Plants that Direct ly Discharge the Evaluated Wastestreams to a Surface Water Impaired due to Metals, Other than Mercury Section 3—Environmental And Human Health Concerns

3-43Figure 3-3. Location of Plants that Direct ly Discharge the Evaluated Wastestreams to a Surface Water Impaired due to Nutrients Section 3—Environmental And Human Health Concerns

3.4.4 Proximity to Fish Consumption Advisory Waters

States, territories, and authori zed tribes issu e fish consump tion advisories when pollutant

concentrations in fish tissue are considered unsafe for cons umption [U.S. EPA, 2011e]. EPA

determined that 140 of the imme diate receiving waters included in the EA (63 percent) are under fish consumption advisories; 93 of the immediate receiving waters (42 percent) are under an advisory for a pollutant associated with the evaluated wastestreams. 23 All of these 93 immediate receiving waters are under a fish consumption advisory for mercury and one of the receiving waters is also under a fish consumption advisory for lead. EPA also reviewed fish consumption advisories for arsenic, cadmium, and selenium but did not identify any immediate receiving waters under advisories for these pollutants. Figu re 3-4 illustrates the geographical location of plants that directly discharge steam electric power plant wastewater to surf ace waters with a fish consumption advisory for lead or mercury.

23 Table B-2 in Appendix B lists the types of advisori es identified under the sensitive environment proximity analysis, including pollutants that are not as sociated with the evaluated wastestreams.

3-44Figure 3-4. Location of Plants that Directly Discharge to a Surface Water with a Fish Consumption Advisory Section 3—Environmental And Human Health Concerns

3.4.5 Proximity to Threatened and Endangered Species Habitats

Under the Endangered Species Act (ESA), en dangered sp ecies are th ose in danger of extinction throughout all or a si gnificant portion of its range. Threatened species are those species that are likely to become endangered w ithin the foreseeable future. A species may be listed solely on the basis of their biological status and threats to their existence. The USFWS considers five factors for listing: 1) damage to, or destruction of, a species’ habitat; 2) overutilization of the species for commercial, recr eational, scientific, or education purposes; 3) disease or predation; 4) inadequacy of existin g protection; and 5) other natural or man-made

factors that affect the continue d existence of the species.

EPA evaluated the extent to which the estimated range and critical habitats of currently listed threatened and endangered species, or thos e in consideration for listing under the ESA (as of December 2014), overlap with surface waters that are potentially affected by the final rule. As

described in the Benefits a nd Cost Analysis (EPA-821-R-15- 005), these “affected areas” are receiving waters that do not meet water quality metrics recognized to cause harm in organisms under baseline conditions, but which do meet thes e metrics under the most stringent regulatory option EPA analyzed (Option E). EPA identified 138 threatened and endangered species whose habitats overlap with, or are located withi n, an “affected” surface water under baseline

conditions. 24

24 The habitat locations evaluated for this analysis in clude waters downstream fro m steam electric power plant discharges and reflect changes in the industry as a result of the Clean Power Plan [Clean Air Act Section 111(d)].

3-45Section 3—Environmental And Human Health Concerns

In addition, EPA assessed the vulnerability of each species identified to changes in water quality and developed the following categories:

 High vulnerability: species livi ng in aquatic habitats for several life history stages and/or species that obtain a majority of their food from aquatic sources.

 Moderate vulnerability: species living in a quatic habitats for one life history stage and/or species that obtain some of their food from aquatic sources.

 Low vulnerability: species whose habitats overlap bodies of water, but whose life history traits and food s ources are terrestrial.

EPA classified 54 percent of the species (75 of 138 species) with habitats located within an “affected” surface water as highly vulnerable to changes in water qu ality. The habitats of these highly vulnerable species overlap a total of 145 affected stream reaches. For further details on the threatened and endangered species analysis and results, see the Benefits and Cost Analysis (EPA-821-R-15-005).

3.4.6 Proximity to Drinking Water Resources

EPA also evaluated the potential for steam elect ric power plants to pose a threat to public sources of drinking water. A lthough many of the pollutants ( e.g. , selenium, mercury, arsenic, nitrates) in the evaluated wastes treams would likely be reduced to safe levels during drinking water treatment, these pollutants could potentially impact the effectiveness of the treatment processes, which could increase pub lic drinking water treatment costs. 25 EPA evaluated the proximity of steam electric power plants to th e following sensitive environments for drinking

water resources:

 Drinking water intakes – drinking water so urces that collect surface water through a public water system. Intakes are protected under the SDWA of 1974 and its 1986 and 1996 amendments, which require delegated states and tribes to perform routine testing to ensure that they meet state drinking water standards.

 Public wells – drinking water sources that collect ground water through a public water system. Public wells are protected under the SDWA, which requires delegated states and tribes to perform routine testing to ensure that they meet state drinking

water standards.

 Sole-source aquifers – drinking water sources that supply at least 50 percent of the drinking water consumed in the area overlyi ng the aquifer. These areas can have no reasonably available alterna tive drinking water source(s) if the aquifer were to

become contaminated.

Table 3-13 summarizes the number and percenta ges of plants included in the nationalscale proximity analysis that are located with in five miles of the evaluated drinking water resources. The table also presents the number of drinking water resources that are located within this five-mile buffer zone. For example, 67 steam electric power plants are located within 5 miles

25 For more information on drinking water treatment processes used to reduce or eliminate metals commonly

detected in the evaluated wastestreams from steam elec tric power plants, see the ERG memorandum “Drinking Water Treatment Technologies that Can Reduce Metal and Selenium Concentrations Associated with Discharges from Steam Electric Power Plants” (DCN SE02154).

3-46Section 3—Environmental And Human Health Concerns

of a drinking water system intake or drinking water reservoir. Within 5 miles of these 67 plants are 113 drinking water system intakes or reservoirs.

Table 3-13. Comparison of Number and Perce ntage of Steam Electric Power Plants Located within 5 Miles of a Drinking Water Resource

Type of Drinking Water

Resource Number of Drinking Water

Resources within 5 Miles of a Steam

Electric Power Plant Number (Percentage) of Steam

Electric Power Plants

Located within 5 Miles of a Drinking Water Resource a

Intakes and reservoirs 113 67 (33%)

Public wells b 2,057 157 (81%) Sole-source aquifers 8 7 (4%)

Sources: ERG, 2015c; ERG, 2015d
a – For the drinking water resource proximity analysis, EP A evaluated 222 immediate receiving waters that receive discharges of the evaluated wastestreams from 195 steam electric power plants.
b – Counts include two springs and 29 wellheads.

3.5 L ONG E NVIRONMENTAL R ECOVERY T IMES A SSOCIATED WITH P OLLUTANTS IN S TEAM
E LECTRIC P OWER P LANT W ASTEWATER

Recovery of the environment from exposure to steam electric power plant wastewater is affected by continued cycling of contaminants within the ecosystem, bioaccumulation, and the potential alterations to ecologi cal processes, such as population and community dynamics in the surrounding ecosystems. The ability of aquatic and adjacent terrestrial environments to recover from even short periods of exposure to steam electric power plant wa stewater depends on the distance from discharge, the pollutant concentr ations, pollutant reside nce time, and the time elapsed since exposure. In particular, accu mulation of metals a nd other bioacummulative pollutants in sediments can slow recovery of aquatic systems following exposure to power plant wastewater due to the pot ential for resuspension in the water column and for benthic organisms to provide a pathway for exposure long after power plant wastewater discharges have ended. For example, Lemly [1985a, 1997a, 1999] documented that benthic pa thways can continue to provide toxic doses of se lenium to wildlife even 10 years after water column selenium

concentrations are below levels of concern. Ruhl

et al. [2012] documented elevated levels of power plant wastewater pollutant s (including arsenic and selenium) in pore water, even in cases where the

water column concentrations are not elevated. This study found that arseni c is retained in lake sediments and pore water through a cycle of adsorption and desorption, likely in response to seasonal changes in the lake water chemistry [Ruhl et al. , 2012]. Short Exposures to Steam Electric Power Plant Wastewater Can Equate to Lasting Ecological Effects

In Martin Creek Lake, ecological effects persisted for at least 8 years following 8 months of fly ash discharges into the lake.

Ash pond discharges to Belews Lake in

North Carolina resulted in elevated levels of arsenic, selenium, and zinc in the water and impacts to fish populations. Even 11 years after discharges ceased, selenium levels in the sediments still posed a risk to wildlife that feed on benthic organisms.

As discussed in Section 3.1, many of the pollutants in steam electric power plant wastewater ( e.g. , arsenic, mercury, selenium) readily bioaccumulate in exposed biota. The

3-47Section 3—Environmental And Human Health Concerns

bioaccumulation of these pollutants is of particular concern due to their impact on higher trophic levels, local terrestrial environm ents, and transient species, in addition to the aquatic organisms directly exposed to the wastew ater. Aquatic systems with long residence times and potential contamination with bioaccumulative pollutants ofte n experience persistent environmental effects following exposure to steam elect ric power plant wastewater.

Population decline attributed to exposure to steam electric power plant wastewater can alter the structure of aquatic communities and cause cascading effects within the food web that result in long-term impacts to ecosystem dynamics [Rowe et al ., 2002]. Reductions in organism survival rates from abnormalities caused by exposur e to power plant wastewater and alterations in interspecies relationships, su ch as declining abundance or quality of pr ey, can delay ecosystem recovery until key organisms within the food web return to levels prior to power plant wastewater exposure. In a 1980 study of a creek in Wisconsin, fungal decomposition of detritus was limited due to the effects of power plant wastewater. As a result, the benthic invertebrate population, which graze on detrital material, declined as did benthic fish that prey upon small invertebrates because of the reduced available resources [Magnuson et al.

, 1980].

Belews Lake, a 1,500-hectare cooling reservoir constructed to support the Belews Creek Steam Station in Stokes County, North Carolina, is a well-documented site that highlights the effects that steam electric power plant wastewater can have on fish populations and the subsequent long recovery time. In 1970, Duke Energy began monitoring the fish populations in Belews Lake prior to any discharges of steam electric power plant wastewater. From 1974 to 1985, Duke Energy di scharged surface impoundment effluent into Belews Lake. Almost immediately after these di scharges began, rapid a nd dramatic changes in the fish populations were observed [Leml y, 1993]. By 1975, morphological abnormalities ( e.g. , partial fin loss, head deformities, cataracts) were reported for all 19 fish species monitored in the lake. Within 2 years after surface impoundment e ffluent was released in to the lake, several species stopped reproducing, leav ing only four sp ecies by 1978 ( i.e. , 4 years after discharges began). Water samples collected in the lake repor ted elevated levels of arsenic, selenium, and zinc. Large predatory fish were so me of the first species to die out completely, due to the lethal and sublethal effects of exposur e to surface impoundment effluent . Because a top predator was gone, some fish that exhibited developmental a bnormalities were able to survive, despite their otherwise high susceptibility to predation [Lem ly, 1993]. The study eventually correlated the observed fish abnormalities with high selenium whole-body concentrations, and identified the planktonic community as the key source of sele nium to the impacted fish. In 1985, the Belews Creek Steam Station switched to disposing of the coal ash in a dry landfill and ended the surface impoundment discharges to the la ke. In a 1997 study, Lemly determin ed that there was evidence that the lake was recovering; however, even 11 y ears after the discharges ceased, selenium levels in the sediments still posed a risk to wildlife that feed on benthic organisms. Lemly also Studies have linked historical discharges of

s elenium from the Belews Creek Steam Station with persistent ecological impacts in the plant’s cooling reservoir.

3-48Section 3—Environmental And Human Health Concerns

observed that despite th e reduction in the selenium concentr ation in fish ova ries, reproductive abnormalities remained persistent, highlighting th e long ecological recovery time observed in

Belews Lake.

In addition to population density effects, the diversity of species in the communities in both field and experimental studies exposed to st eam electric power plant wastewater has altered, which can further prolong ecosystem recovery [Benson and Birge, 1985; Guthrie and Cherry, 1976; Rowe et al ., 2001; Specht et al ., 1984]. In a study of fish populations in Martin Creek Lake following a short 8-month period in whic h the lake received fly ash surface impoundment discharges, both planktivorous ( i.e. , diet primarily consists of plankton) and carnivorous ( i.e.

, diet primarily consists of meat) fish populatio ns were severely reduced [Garrett and Inman, 1984]. Three years after the effluent release was halted, planktivorous fish populations remained extremely low, while carnivorous fish populations had nearly recovered. Ca rnivorous fish have a more diverse diet than plankti vorous fish and therefore benefite d from an increase in food availability as the aquatic system recovered; ho wever, the size of carnivorous fish in the lake suggested that surviving adults continued to ha ve reproductive impairments [Garrett and Inman, 1984]. Sorensen (1988) documented that ecological im pacts in the lake remained evident even up to 8 years after the 8-month exposure to fly ash transport water disc harges, with sunfish populations continuing to exhibit tissue damage to the liver, kidneys, gills, and ovaries and impaired overall reproductive health. Fish samples taken in 1996 and 1997 showed that the selenium concentration (2.3 parts per million (ppm ) average for all sample fish) remained well above the national average range of between 0.1 and 1.5 ppm [ATSDR, 1998a].

3-49Section 4—Assessment of Exposure Pathways



## SECTION 4
ASSESSMENT OF EXPOSURE PATHWAYS

An exposure pathway is defined as the r oute a pollutant takes from its source ( e.g. , combustion residual surface impoundments) to its endpoint ( e.g. , a surface water), and how receptors ( e.g. , fish, wildlife, or people) can come into contact with it. E xposure pathways are typically described in term s of five components:

 Source of contamination ( e.g. , steam electric power plant wastewater).

 Environmental pathway—the environmental medium or transport mechanism that moves the pollutant away from the source through the environment ( e.g. , discharges to surface waters).

 Point of exposure—the place ( e.g. , private drinking water well) where receptors ( e.g. , people) come into contact with a poll utant from the source of contamination.

 Route of exposure—the way ( e.g. , ingestion, skin contact) receptors come into contact with the pollutant.

 Receptor population—the aquatic life, wildli fe, or people exposed to the pollutant.

The exposure pathway plays an important role in determining the potential effects of steam electric power plant wastewater on the environment. For example, the physical and chemical characteristics of receiving waters can affect the fate and transport of pollutants from combustion residual surface impoundments to the environment and ultimately impact how the pollutants interact with the biological community.

EPA identified four primary exposure pathways of concern for steam electric power plant wastewater enteri ng the environment: 1) discharges entering surface waters, 2)

uncollected combustion residual leachate infiltrating through soil to nearby surface water, 3) uncollected combustion residual leachat e entering ground water, and 4) direct contact with steam electric power plant wastewater stored in surface impoundments. This section

describes the factors that contro l the magnitude of impacts to wa ter quality, wild life, and human health associated with exposur e to steam electric power plant discharges and presents an overview of EPA’s environmental assessment (EA) of the steam electric power generating industry, in which EPA evaluated the national-scale effects of pow er plant wastewater pollutants on the environment. Table 4-1 presents the envi ronmental pathways, routes of exposure, and environmental concerns identified during the lit erature review and the types of analyses conducted to determine the impacts under ba seline conditions and regulatory options. P ollutants from steam electric power plant wastewater stored in surface impoundments can reach receptor populations (such as wildlife or

p eople) through various exposure pathways.

4-1Section 4—Assessment of Exposure Pathways

Table 4-1. Steam Electric Power Plant Wastewater Environmental Pathways and Routes of Exposure Evaluated in the EA

Environmental Pathway Route of Exposure Environmental Concern Analysis to Determine Environmental Impact

Steam electric power plant wastewater discharges to surface

waters Direct contact with

surface water Toxic effects on aquatic organisms a Water quality impacts analysis (quantitative) –

see Section 4.1.2 Ingestion of surface water Degradation of surface water quality used as intake to drinking water plants

Direct contact with

sediment Toxic effects on benthic organisms Wildlife impacts analysis (quantitative) –

see Section 4.1.2 Consumption of aquatic organisms Bioaccumulation of contaminants and resulting

toxic effects on wildlife

Toxic effects on humans consuming contaminated

fish Human health impacts analysis (quantitative) –

see Section 4.1.2

Uncollected combustion residual leachate infiltration to nearby

surface waters from combustion residual surface impoundment or

landfill Direct contact with

surface water or sediment Toxic effects on humans and aquatic wildlife Ground water quality impacts analysis (qualitative) – see

Section 4.2.2

Uncollected combustion residual leachate entering ground water

from combustion residual surface impoundment or landfill Ingestion of ground water Changes in ground water quality

Contaminated private drinking water wells

Combustion residual surface impoundment Direct contact with or ingestion of surface water Toxic effects on wildlif e Attractive nuisances analysis (qualitative) –

see Section 4.3 Bioaccumulation of

contaminants in wildlife

a – The term “toxic effects” refers to impacts upon ex posure, ingestion, inhalation, or assimilation into any organism, either directly from the environment or indirectly by ingestion through food chains. These effects can include death, disease, behavioral abnormalities, cancer, genetic mutations, physiological malfunctions (including malfunctions in reproduction), or physical deformations, in receptors ( e.g. , aquatic organisms, wildlife, humans) or their offspring.

4.1 D ISCHARGE AND L EACHING TO S URFACE W ATERS

Steam electric power plants commonly discharg e wastewater directly to surface waters following storage and treatment ( e.g. , particulate settling) in su rface impoundments. In addition to effluent discharges, uncollected combustion re sidual leachate can migrate through the soil and

into the surface water. Section 4.2 further di scusses the impacts of uncollected combustion

residual leachate.

4.1.1 Factors Controlling Environmental Impacts in Surface Waters

One of the primary factors c ontrolling the environmental impact of steam electric power plant wastewater on surface waters is the reside nce time of the pollutants once they enter an

4-2Section 4—Assessment of Exposure Pathways

aquatic system. Residence times are often determin ed by the flow rate of the receiving water and type of ecosystem it supports. The potential for pollutant retention in lentic aquatic systems ( i.e.

, still or slow-moving water, such as lakes or ponds) and the creati on of hot spots in lotic aquatic systems ( i.e. , flowing water, such as streams and ri vers) are of particular concern when bioaccumulative pollutants are present. Many of the pollutants in steam electric power plant wastewater discharges bioaccumulate, complica ting estimates of potential impacts in surface waters because the pollutants can affect higher trophic levels, loca l terrestrial environments, and transient species, in addition to the aquatic or ganisms directly exposed to the wastewater.

Based on industry responses to EPA’s 2010 Questionnaire for the Steam Electric Power Generating Effluent Guideline (Steam Electric Survey), 26 EPA determined that 18 percent of the 222 receiving waters included in th e scope of the EA, all of whic h receive steam electric power plant wastewater discharges, are lentic systems such as lakes, ponds, reservoirs, and estuaries (Table 4-2). The majority of ecological studie s on the impact of power plant wastewater in aquatic environments have focused on lentic systems [Rowe et al ., 2002]. In le ntic aquatic systems, the hydraulic residence time, or the amount of time it takes for th e water in the aquatic system to be replaced by inflowing streams or precipitation is relativel y long, allowing pollutants to build up over time and making these systems mo re vulnerable to impacts from power plant wastewater. In addition, aquatic organisms are lim ited in their ability to avoid areas of high pollutant concentrations and are restricted to the food supply available only within the waterbody.

Table 4-2. Receiving Water Types for Steam El ectric Power Plants E valuated in the EA

Receiving Water Type Number (Percentage) of Immediate Receiving Waters a

River/Stream 183 (82%)

Lake/Pond/Reservoir 26 (12%)

Great Lakes 11 (5%)

Estuary and others (bay) 2 (1%)

Total Receiving Waters 222 (100%)

Source: ERG, 2015d.
a – The EA encompasses a total of 222 immediate receivi ng waters and loadings fr om 195 steam electric power plants (some of which discharge to multiple receiving waters). The imme diate receiving wa ter (IRW) model, which excludes the Great Lakes and estuaries, encomp asses a total of 209 immedi ate receiving waters and loadings from 188 steam electric power plants.

Based on responses to EPA’s Steam Electric Su rvey, EPA determined that 82 percent of aquatic environments that receive discharges of the evaluated wastestreams are lotic systems such as rivers and streams [ERG, 2015j]. Lotic systems dilute discharges more quickly than lentic systems. The moving water in lotic sy stems also provides a transport mechanism to disperse pollutants greater distances from the power plant, and enable s aquatic organisms to move away from the areas contaminated by steam electric power plant discharges [Rowe et al

.,

26 Results presented in this report are based on plant re sponses to the Steam Electric Survey, which represent 2009 data. However, the analyses presented in this report incorporate some adjustments to current conditions in the industry. See Section 1 for further details.

4-3Section 4—Assessment of Exposure Pathways

2002]. Although power plant wastewater discharges into a lotic system can distribute pollutants across a greater spatial area, changes in flow velocity may result in the concentration of pollutants at a single loca tion further downstream [Rowe et al ., 2002]. For example, power plant wastewater discharged to a ri ver may encounter areas of sl ower moving water downstream where pollutants would fall out of suspension and concentrate in a limited area. These pockets of higher pollutant concentrations, or hot spots, could be vulnerable to continued resuspension as stream velocities are affected by rainfall, resu lting in the aquatic organisms being exposed to pollutants over much longer periods of time [Lemly, 1997a; Rowe et al ., 2002].

4.1.2 Assessment of the Surface Water Exposure Pathway

EPA developed and executed models to quan tify the water quality, wildlife, and human health impacts resulting from discharges of th e evaluated wastestreams to surface waters. These models consist of the following: 1) a national- scale IRW model that ev aluates the discharges from 186 steam electric power plants and focu ses on impacts within the immediate surface

water 27 where discharges occur, and 2) case study models that perform more sophisticated and extensive modeling of selected waterbodies that receive, or are downstream from, steam electric power plant wastewater discharg es. Section 5 describes the IRW model and Section 8 describes the case study models. In addition, as part of the benefits and co st analysis, EPA also evaluated

surface water concentrations downstream from steam electric discharges using EPA’s RiskScreening Environmental Indicators (RSEI) model; see the Benefits and Cost Analysis (EPA821-R-15-005).

The remainder of this section discusses the scope of EPA’s environmental assessment of the steam electric power gene rating industry in terms of ev aluated pollutants, evaluated waterbody types, and evaluated environmental impacts.

Evaluated Pollutants

The EA quantitative analyses focused on th e environmental impacts associated with discharges of toxic, bioaccumulative pollutants to surface waters. A key factor in determining the pollutants to include in the quantitative analyses was the potential for pollutant loadings to be diluted in the receiving waters following discharge. For example, EPA determined that the rivers

and streams included in the IRW model had a me dian average annual flow of 2,808 cubic feet per second (cfs) and that 57 percent had an aver age annual flow greater than 1,000 cfs. Due to the potential for dilution, EPA focused the quan titative analyses on pollutants where the total mass loadings and not the concentration are crit ical factors in determining the potential for environmental impact. Section 5.1.2 lists the pollu tants selected for quantitative analyses and how they were selected.

27 The length of the immediate receivi ng water, as represented in the na tional-scale IRW model, ranges from between 1 to 5 miles from the steam electric power plant outfall. See the ERG memorandum “Water Quality Module: Plant and Receiving Water Characteristics” (DCN SE04513) for details on the immediate discharge zone and length of stream reach represented.

4-4Section 4—Assessment of Exposure Pathways

The EA quantitative analyses did not focu s on water quality impacts associated with discharges of nutrien ts (total nitrogen and total phosphorus). 28 While discharges of large amounts

of nutrients to surface waters can cause environmental problems ( e.g. , eutrophication), EPA focused the EA quantitative analyses on 10 toxic pollutants that can bioaccumulate in fish and impact wildlife and human receptors via fish c onsumption. Additionally, nutrient-related impacts tend to be site-specific dependi ng on environmental factors ( e.g. , water-body temperature, the limiting nutrient in the system, algal species in the waterbody, and availability of oxygen in the water).

While the EA quantitative analyses did not address nutrient-related impacts, EPA did include nutrient loadings in the Benefits and Cost Analysis. EPA estimated total nitrogen and total phosphorus concentrations in receiving waters using dilution equations as input values to analyze benefits related to improvements in water quality. EPA used the SPARROW (SPAtially Referenced Regressions On Waters hed attributes) model to provide baseline concentrations, as well as concentrations under each regulatory opti on. EPA used these concentrations to develop subindices for a water quality index (WQI), a value that translates water quality measurements, gathered for multiple parameters that represent various aspects of water quality, into a single numerical indicator. Total nitrogen and total phosphorous are only two of the subindices included in the WQI; the others are di ssolved oxygen, biochemical oxygen demand, fecal coliform, total suspended solids (TSS), and heavy metals. EPA then used the WQI as a basis for calculating a willingness to pay for an increase in water quality as a result of the different regulatory options. See the Benefits and Cost Analysis for further details on the analysis and the

results.

EPA identified total dissolved solids (TDS) and chlorides as the pollutants with the largest loadings under baseline conditions (s ee Table 3-2); however , EPA did not perform quantitative analyses of these pollutants fo r several reasons. TDS from the evaluated wastestreams consists largely of dissolved metals that are already captured in the analysis. Therefore, estimates of potential environmen tal impacts from TDS would double-count many of the environmental impacts and potential impr ovements assessed. Chlorides lack partition coefficient data (which are necessary for the wa ter quality modeling performed in this EA) and

have limited numeric threshold cr iteria data for comparison.

Evaluated Waterbody Types

In selecting the appropriate methodologies fo r the quantitative analys es, EPA considered the types of receiving waters commonly impact ed by steam electric power plants and the pollutants typically found in the evaluated wastes treams. The IRW model and the selected case study models quantify the environmental risks with in rivers/streams and la kes/ponds (including reservoirs), based on the determ ination that 94 percent of the final outfall receiving water designations fell within these two categories.

The EA quantitative analyses did not evaluate pollutant concentrations in the Great Lakes and estuarine systems, which represented 6 percent of all final outfall receiving waters. The

28 EPA evaluated the nutrient impacts to the Great Lakes and Chesapeake Bay systems from a total mass loadings perspective, discussed in Section 3.4.

4-5Section 4—Assessment of Exposure Pathways

specific hydrodynamics and scale of the analysis required to appropriately model and quantify receiving water concentrations in the Great Lake s and estuarine systems are more complex than

the IRW model. 29 In selecting the receivi ng waters to evaluate in the case study analyses, EPA focused primarily on rivers and streams based on the following: 1) the determination that 82 percent of the final outfall receiving water desi gnations fell within this category, and 2) the relative simplicity of the hydrodynamics in rive r and stream case study models. This allowed EPA to develop and execute a larg er set of case studie s. EPA also develope d one case study to represent the impacts of steam electric discharges to a lake. Refer to Sec tion 8 for discussion of the receiving waters selected for case study analyses.

Evaluated Environmental Impacts

EPA focused the evaluation of environmental impacts on four key areas resulting from discharges of harmful pollutants to surface waters (rivers, streams, lakes, ponds, and reservoirs):

 Water Quality Impacts: Potential toxic e ffects to aquatic life based on changes in surface water quality—specifically, exceedan ces of the acute and chronic National Recommended Water Quality Criteria (N RWQC) for freshwat er aquatic life.

 Wildlife Impacts: Potential toxic effects on benthic organisms based on changes in sediment quality within surface waters —specifically, exceedances of chemical

stressor concentration limits (CSCL) for sediment biota.

 Wildlife Impacts: Bioaccumulaton of contaminants and potential toxic effects on wildlife from consuming contaminated aquatic organisms, specifically:

- Risk of adverse reproductive impacts in fi sh and waterfowl that consume aquatic organisms with elevated levels of seleni um (as determined by the ecological risk modeling methodology descri bed in Section 5.2).

- Potential risk of reduced reproduction ra tes in piscivorous wildlife, based on

exceedances of no effect hazard co ncentration (NEHC) benchmarks.

 Human Health Impacts: Potential toxic e ffects to human health from consuming contaminated fish and water, specifically:

- Exceedances of the human health NRWQC based on two standards: 1) standard for the consumption of water and organism s and 2) standard for the consumption of organisms.

- Exceedances of drinking water maximu m contaminant levels (MCLs). Although MCLs apply to drinking water produced by public water systems and not surface waters themselves, EPA identified immedi ate receiving waters that exceeded a MCL as an indication of the degradati on of the overall water quality following exposure to the evaluated wastestreams.

29 EPA evaluated the impacts to the Great Lakes and Chesapeake Bay systems from a total mass loadings perspective, discussed in Section 3.4. See the ERG me morandum “Site-Specific Estuary Dilution Analysis” (DCN SE02152) for details on EPA’s initial screening analysis of the modeled receiving water concentrations in the Great Lakes and estuary systems compared to water quality benchmarks.

4-6Section 4—Assessment of Exposure Pathways

- Risk of cancer and non-cancer threats ( e.g. , reproductive or ne urological impacts) due to consuming fish caught from contaminated receiving waters.

4.2 L EACHING TO G ROUND W ATER

Combustion residual landfills and surface impoundments can impact local ground water through leaching. 30 Once in ground water, pollutants can migrate from the site and contaminate public or private drinking water wells and su rface waters [NRC, 2006]. Contamination of drinking water wells is of particular concern be cause more than one-third of the U.S. population relies on ground water for drinki ng water. According to the U.S. Geological Survey (USGS), one in every five samples of ground water used as a source for drinking contains at least one

contaminant at a level of concer n for human health [USGS, 2015].

The fate of pollutants that leach from com bustion residuals to ground water is controlled by many biological and geochemical ( e.g. , adsorption, desorption, and precipitation reactions with aquifer materials) processes that can vary over large spatial and temporal scales [NRC, 2006]. This section describes th e pollutant concentrations, chemical characteristics ( e.g. , solubility, leachability, persistence, and mobility), and fate and transport processes that influence the potential environmental impact of unc ollected combustion residual leachate.

4.2.1 Factors Controlling Environmental Impacts to Ground Water

Environmental impacts to ground water are dete rmined by the pollutant concentrations in

the combustion residual leachate and the rate of pollutant transport in the ground water. The pollutant concentrations in the combustion residual leachate depe nd on factors such as

characteristics of the combusti on residuals, site conditions ( e.g. , rainfall amount and pH of the pore water in the surface impoundment or landf ill), and combustion residual residence time in the surface impoundment or landfill. 31 The rate of pollutant trans port in ground water depends on factors such as the biogeochemical characteristics of the subsurface ( e.g. , soil pH and oxidationreduction potentials), local rates of ground wate r recharge, and unsaturat ed and saturated ground

water flow velocities.

Pollutant Concentrations in Combustion Residual Leachate

Combustion residual characteristics in clude the mineralogy of the waste ( e.g. , lime, gypsum, iron, and aluminum oxide content) and po llutant solubility in the pore water. The mobility of pollutants may be a ltered due to changes in pH, car bon and chloride content, and

interaction with other wastes from steam electric power plants [Thorneloe et.al. , 2010]. The waste mineralogy can vary based on the chemical composition in the fuel source ( e.g. , the

30 In this EA, EPA evaluated the threats to human health and the environment associat ed with pollutants leaching into ground water from surface impo undments and landfills containing combustion residuals. If these leached pollutants do not constitute the discharge of a pollutant to surface waters, then they are not controlled under the

steam electric ELGs. While the Coal Combustion Residua ls (CCR) rulemaking is the major controlling action for these pollutant releases to ground water, the ELGs coul d indirectly reduce impacts to ground water. These secondary improvements are discussed in Section 7.8.

31 Leaching experiments indicate that the chemistry of leac hates is based on both the chemical composition of the waste and other factors such as site conditions [Thorneloe et al., 2010]. Thorneloe [2010] specifically looked at fly ash and bottom ash waste from coal-fired power plants.

4-7Section 4—Assessment of Exposure Pathways

specific coal seam and geographic location of the mine) and operational characteristics at the plant. Many laboratory investigations have exam ined the solubility characteristics of various pollutants associated with fly ash [Prasad et al ., 1996; Thorneloe et.al. , 2010]. The results of these investigations largely depend on multiple f actors, and they tend to be more applicable qualitatively rather than quantitatively ( e.g. , results from investigations can be used to determine the likelihood of a pollutant to dissolve in the combustion residual leachate, but not the amount). Concentrations of inorganic pollutants derived from calcium , sodium, magnesium, potassium, iron, sulfur, and carbon are relatively high in a queous solution of fly ash because of their high total concentrations in the ash [Prasad et al ., 1996].

The pH level of pore water in surface impoundments can stro ngly influence the concentration of pollutants in leachate from impoundments to ground water. The pH of the pore water is a dominant factor in the leaching of pollutants from unlined surface impoundments and landfills. Because most pollutants in combustion

residuals exhibit weak acidic or weak basic behavior in aqueous solution, the pore water pH strongly influences the concentrations of pollutants in the combustion residual leachate. Steam electric power plants generate combustion residuals in high-temperature processes, and many acids and acidic precursors ( e.g. , carbon dioxide, hydrogen sulfide, hydrochloric acid) are volatilized prior to waste collection. Therefore, combustion residuals typically yield an alkaline reaction in water, but acidic reacti ons have also been observed [Theis and Gardner, 1990]. Acidic pore water allows pollutants from the combustion residuals to remain in solution, in creasing their mobility and the potential for ground water contamination. The results of a study of three power plants in Turkey indicated that combustion residuals in the deeper layers of landfills and on the bottoms of the surface impoundments may continue to leach if the pH value drops in the surrounding environment [Baba and Kaya, 2004]. 32

Table 4-3 presents data collected by EPA’ s Steam Electric Survey regarding pollutant

concentrations in the combustion residual leachate under acidic, ne utral, and basic (or alkaline)

conditions. Arsenic exceeded its MCL for more th an 60 percent of the samples in both acidic and basic combustion residual leachate. Similarly, the majority of manganese samples exceeded its secondary MCL under all pH conditions, with 95 percent of the samples exceeding the MCL in

32 This conclusion was based on a comparison of ash extraction procedures used. The study examined how the concentration of trace elements in the ash can vary base d on the procedure used, comp aring the EPA-developed EP (extraction procedure) and its replacement method, TCLP (toxicity characteristic leaching procedure), and the ASTM (American Society for Testing and Materials) Method D-3987. A comparis on of the results revealed that the ASTM procedure indicated much lower dissolved metal c oncentrations than the EP and TCLP procedures. These results indicate that pH is an important parameter affecti ng the leaching rate of metals from ash deposits. The lower pH values in the EP and TCLP methods increase the leachi ng rate of inorganic constitu ents of fly ash and bottom ash [Fleming et al. , 1996].

4-8Section 4—Assessment of Exposure Pathways

acidic conditions. Selenium had varying concentra tions under all pH conditions, but exceeded its MCL more frequently under basic conditions. Overal l, the results support the conclusion that pH levels influence the concentrations of pollu tants in the combustion residual leachate.

Table 4-3. Exceedances of MCLs in Leacha te Under Acidic, Neutral, and Basic

Conditions

Pollutant MCL (mg/L) Total Number of Samples Percentage of Total Samples Exceeding MCL

Acidic Neutral Basic Acidic Neutral Basic

Arsenic 0. 01 21 64 90 62 % 30% 71%

Boro n 7 a 21 64 91 14 % 31% 31%

Cadmium 0. 005 21 63 90 29 % 3% 29%

Chromium 0

. 1 21 64 90 0% 0% 18 % Copp er 1.3 21 64 91 0% 0% 0%

Lead 0.015 21 62 86 5% 0% 2%

M anganese 0. 05 b 21 64 89 95 % 81% 54%

Mercur y 0.002 21 64 89 5% 16 % 8%

Nickel No MCL 21 64 87 NC NC NC

Sel enium 0. 05 21 64 90 14 % 17% 31%

Thalliu m 0.002 21 62 86 52 % 10% 14%

Zinc 5 b 21 63 86 0% 0% 0%

Sou rce: ERG, 2015d.
Acronyms: mg/L (milligrams per liter); MCL (Maximum contaminant level); NC (not calculated; no MCL for comparison).

Note: Data are for untreated leachate co llected in leachate collection systems at steam electric landfills and surface impoundments.
a – The drinking water equivalent level, used for noncarcinogenic endpoints, is listed rather than the MCL.
b – MCL is a secondary (nonenforceable) standard.

In addition to the pH of the pore water, amounts of precipitation can affect pollutant concentrations in the combustion residual leachate. Although landfills are dry disposal sites, rainfall and frozen precipitation infiltrate through the waste, dissolving pollutants that can then

leach from the landfill. Landfills in drier climates generate less combustion residual leachate than

landfills in wetter climates.

The last factor affecting pollutant concentr ations in the combustion residual leachate is the combustion residual residence time in the surface impoundment or landfill. In a study of metals (calcium, copper, iron, lead, magnesi um, manganese, potassium , sodium, and zinc) leaching from fly ash and bottom ash, all polluta nts decreased in concentration with time of leaching, except for calcium, whic h released at a constant rate [Kopsick and Angino, 1981]. The most commonly noted leachate release curve is an initial flush curve, where the highest concentrations of pollutants are released as the leachate initially forms, with rapidly decreasing concentrations over time. Therefore, active surface impoundments receiving fresh combustion residuals will produce a leachate with elevated con centrations of pollutants that have a greater potential to contaminate drinking water source s and surface waters. Mo st inactive surface impoundments where pollutants have initially already leached from the combustion residuals

4-9Section 4—Assessment of Exposure Pathways

should produce a leachate with decreasing concen trations of pollutants [Kopsick and Angino, 1981].

Thorneloe et al . [2010] studied the leaching behavior of coal combustion residuals in landfills, performing tests using a range of pH conditions and liqui d-solid ratios expected during management via landfills or beneficial use. Comb ustion residual leachate concentrations for most pollutants were variable over a ra nge of coal types, plant configurations, and combustion residual types ( i.e. , fly ash or flue gas desulfurization (F GD) gypsum). The study showed significantly different leaching results (liquid-solid partitioni ng [equilibrium] as a function of pH) for similar combustion residual types and plants. The variabili ty in pollutant leaching results was several orders of magnitude higher than the variability in the pollutant concentrations in the combustion residuals; this indicates that the pollutant

concentrations alone cannot predict the leaching of metals, as noted above. Table 4-4 presents pollutant concentrations in combustion residual samples across a pH range of 5.4 to 12.4 and the range of pollutant

concentrations in the combustion residual

leachate. The table also includes indicator values for each pollutant: toxicity characteristic (TC) values for Resource Conservation and Recovery Act (RCRA) hazardous waste regulatory determination and drinking water MCLs for combustion residual leachate concentrations. As shown in the table,

the maximum combustion residual leachate pollutant concentrations:

 Exceed the TC values for RCRA hazardous wast e determinations for arsenic, barium

, chrom ium, and selenium (in fly ash).

 Exceed the TC values for RCRA hazardous wa ste determinations for selenium (in FGD gypsu m ).

 Exceed the MCLs for nine metals (in fly ash and FGD gypsum): antimony, arseni c, barium (fly ash only), boron, cadmium, chromium, molybdenum, selenium, and

thallium.

The higher pollutant concentrations in the co mbustion residual leachate indicate greater mobility of the pollutant from the solid/slurry re sidual to the liquid phase. The concentration of the pollutants in the combustion residual leachate can be hundreds to thousands of times greater

than the MCL. Most surface impoundments are unlined, allowing pollutants to infiltrate into ground water and eventually into surface waters.

4-10Section 4—Assessment of Exposure Pathways

Table 4-4. Range of Fly Ash and FGD Gypsum Total Content and Combustion Residual Leaching Test Results (Initial Screen ing Concentrations) for Trace Metals

Pollutant Range of Combustion

Residual Content Range of Leaching Test

Results: Concentration in the

Combustion Residual

Leachate Indicator Values

Fly Ash (mg/kg) FGD Gypsum (mg/kg) Fly Ash (μg/L) FGD Gypsum

(μg/L) TC Value for

Hazardous Waste Designation (μg/L) Drinking

Water

MCL (μg/L)
Antimony 3. 0-14 0.14-8.2 <0.3-11,000 <0.3-330

-- 6

Arseni c 17-510 0.95-10 0.32-18,000 0.32-1,2 00 5 ,0 00 1 0

Barium 50 -7,000 2.4-67 50-670,000 30-560 100,000 2,000

Boro n NA NA 210-270,000 12-270,000

-- 7,000 a

Cadmium 0. 3-1.8 0.11-0.61 <0.1-320 <0.2-240 1,000 5

Chromium 66-210 1.2-20 <0.3-7,300 <0.3-240 5,000 100
Mercury 0. 1-1.5 0.01-3.1 <0.01-0.50 <0.01-0.66 200 2
Molybdenum 6.9-77 1.1-12 <0.5-130,000 0.36-1,900

-- 200 a

Selenium 1. 1-210 2.3-46 5.7-29,000 3.6-16,000 1,000 50

Thalliu m 0.72-13 0.24-2.3 <0.3-790 <0.3-1,100

-- 2

Source: T horneloe et al ., 2010.

Acronyms: Acronyms: MCL (maximum contaminant level) ; mg/kg (milligrams per kilogram); TC (Toxicity Characteristics); μg/L (micrograms per liter); NA (Not Available).

a – The drinking water equivalent level, used for noncarcinogenic endpoints, is listed rather than the MCL.

Transporting Pollutants in the Ground Water

Predicting the movement of combustion resi dual pollutants in ground water can be challenging due to the wide range of biogeochemical characteristic s between sites and within a given site. Pollutant transport times can vary, an d combustion residual pollutants can take many years to reach local drinking water wells and su rface waters [NRC, 2006]. For example, in the damage case at the Virginia Power Yorktown Po wer Station Chisman Creek Disposal Site in Yorktown, Virginia, fly ash had be en disposed of in abandoned, un lined sand and gravel pits at the site for almost 20 years, from 1957 to 1974 . However, ground water contamination was not discovered until 1980, when nearby shallow resident ial wells became contaminated with nickel and vanadium. Sampling also showed elevated leve ls of other heavy metals and toxic pollutants: arsenic, beryllium, chromium, copper, mol ybdenum, and selenium [U.S. EPA, 2014b].

Natural mechanisms, such as soil buffering capacity, attenuation of trace pollutants in certain soil types, amount of organic matter, a nd low soil permeability, can limit the transport of combustion residual pollutants in the subsurface environment. The mobility of pollutants in the subsurface strongly depends on soil-specific charact eristics. Soil can have a buffering influence over the leachate by raising or lo wering the pH. As noted previousl y, the solubility of most trace pollutants (the notable exceptions being arsenic and selenium) tends to decrease with increased pH ( i.e. , alkaline conditions). In general, trace polluta nts are less mobile in alkaline soils because the pollutants will precip itate and/or adsorb onto hydrous ir on and aluminum oxides. Theis and Richter [1979] attempted to assess the factors in fluencing the attenuati on of trace metals in

4-11Section 4—Assessment of Exposure Pathways

soil/ground water. Results show that the major sol ubility control for cadmium, nickel, and zinc is adsorption by iron and manganese oxides while ch romium, copper, and lead are controlled by precipitation. In some cases, particles in leac hate may seal a surface impoundment or landfill, reducing the amount of leachate ente ring the ground water. Simsiman et al . [1987] and Kopsick and Angino [1981] both reported evidence of so me sealing and reduced permeability of combustion residual surface impoundments, reducing seepage.

4.2.2 Assessment of the Ground Water Exposure Pathway

The EA focused on the discharges of toxic, bioaccumulative pollutants to surface waters

from the evaluated wastestreams. While Sec tion 3.3 provides qualitati ve discussion of ground water impacts based on a review of damage cases and other documented site impacts, the EA did not quantify the environmental and human health impacts resulting from pollutants leaching into the ground water from combustion residual su rface impoundments and landfills. Additionally, the models used for this EA did not consider pollutant loadings to surface waters caused by combustion residual pollutants migrating through th e soil and into surfa ce waters, even though this may be occurring at many of the plants. As shown in Tables A-4 and A-5 in Appendix A, several damage cases have documented impacts to surface waters due to ground water

contamination from combustion residual surf ace impoundments and landfills. The EA may

therefore underestimate the number of cases wher e water quality standards are being exceeded in immediate receiving waters (see Section 6).

On April 17, 2015, EPA published a RCRA rule that regulates the disposal of CCRs from steam electric power plants (80 FR 21302). As part of the final CCR rulemaking, EPA’s Office of Solid Waste and Emergency Response (OSW ER) evaluated ground water contamination

associated with combustion residuals in su rface impoundments and landfills. The ground water impact analysis for the CCR rule identified and qua ntified human health risk s to private drinking water wells due to potential ground water contamination from current CCR management practices. The analysis determined that human h ealth risks were primarily from exposures to arsenic and molybdenum in ground water used as a source of drinking water. EPA identified

additional human health risks fr om exposures to boron, cadmium , cobalt, fluoride, mercury, lithium, and thallium in ground wate r used as drinking water at ce rtain sites based on the CCR disposal practices. Refer to the Regulatory Impact Analysis: EPA’s 2015 RCRA Final Rule Regulating Coal Combustion Resi dual (CCR) Landfills and Surface Impoundments at Coal-Fired Electric Utility Power Plants (EPA-HQ-RCRA -2009-0640-12034) for the results of the nationalscale analysis of ground water impacts.

4.3 C OMBUSTION R ESIDUAL S URFACE I MPOUNDMENTS AS A TTRACTIVE N UISANCE

An “attractive nuisance” is an area or habita t that attracts wildlife and is contaminated with pollutants at concentrati ons high enough to potentially harm exposed organisms. Two methods of handling steam electric power plant wastewater, surface impoundments and constructed wetlands, are classi fied as lentic systems suppor ting aquatic vegetation and organisms. These methods have been known to attrac t wildlife from other terrestrial habitats and

therefore can be considered attractive nuisa nces. As an attractiv e nuisance, a surface impoundment can impact local wildlife as well as transient species that might rely on them during critical reproduction periods such as seasonal breeding events [Rowe et al ., 2002].

4-12Section 4—Assessment of Exposure Pathways

Exposure to steam electric power plant wastewater during sensitive life cycle events is a concern given that it has been associated with complete reproductive failure in various vertebrate species [Cumbie and Van Horn, 1978; Gillespie and Baumann, 1986; Lemly, 1997a; Pruitt, 2000].

Organisms that frequent attractive nuisance s ites at steam electric power plants, such as surface impoundments, risk exposure to elevated pollutant concentrations. Several studies have

shown that terrestrial fauna nesting near combustion residu al surface impoundments can have higher levels of arsenic, cadmium, chromium, lead, mercury, selenium, strontium, and vanadium than the same species at reference sites [Bryan et al ., 2003; Burger et al ., 2002; Hopkins et al

., 1997, 1998, 2000, 2006; Nagle et al ., 2001; Rattner et al ., 2006]. Table A-8 in Appendix A summarizes documented examples of impacts to w ildlife associated with attractive nuisances at steam electric power plants.

In several of these instances, histopathological effects ( i.e. , changes in pollutant tissue concentrations) were observed. For example, bi rds nesting near a com bustion residual surface impoundment produced eggs with higher selenium concentrations than eggs found at the reference site. Although egg selenium concentrations near combustion residual surface impoundments exceeded thresholds that signify adverse effects on reproduction, the study did not observe any reduction in reproductive success [Bryan et al ., 2003]. In a study conducted by Hopkins et al . [1998],

sediment from a contaminated combustion residual surface impoundment had arsenic levels more than 100 times higher than the

levels found in reference site sediments. Adult toads captured in the contaminated surface impoundment reported a sevenfold difference

in arsenic levels between those from reference sites [Hopkins et al ., 1998]. Although the
study did not measure any indicators of

reduced survival or re productive success in the toads, the results indicate that exposure to combustion residual surface impoundments are a potential threat [Hopkins et al ., 1998]. Surface impoundments and constructed

wetlands can act as at tractive nuisances by attracting wildlife and exposing them to elevated pollutant levels.

Multiple studies have linked attractive nuisance areas at steam electric power plants to diminished reproductive success. Field studies have documented adverse effects on reproduction for turtles and toads living near selenium -laden combustion residual surface impoundments [Hopkins et al ., 2006; Nagle et al ., 2001]. In another study, an interior least tern (Sternula antillarum), an endangered migratory bird, began nesti ng at Gibson Lake, an artificial shallow pond that receives combustion residual surf ace impoundment effluent from the Gibson Generating Station in Indiana. Within severa l years, nearby combustion residual surface impoundments at the Gibson Generati ng Station were also attracting nesting least terns, placing these sensitive species in direct contact with steam electric power plant wastewater. To address the attractive nuisance problem presented by th e surface impoundments, the Gibson Generating Station began a cooperative program with the I ndiana Department of Natural Resources to

4-13Section 4—Assessment of Exposure Pathways

protect the nesting birds by crea ting a nearby alternative hab itat known as the Cane Ridge Wildlife Management Area (WMA) [Pruitt, 2000] . Cane Ridge WMA received water from Gibson Lake and, in 2008, the U.S. Fish and W ildlife Service became con cerned about selenium levels in the water and fish present in th e Cane Ridge WMA [USFWS , 2008]. Accordingly, the bottom of Cane Ridge was plowed to redistribute and bury the selenium in the soil and the water flowing from Gibson Lake into Cane Ridge was stopped and replaced with water piped from the Wabash River. Duke Energy paid to stock the Cane Ridge WM A ponds with fathead minnows to lure back migratory birds. As of June 2009, avocet s, dunlins, black terns, Forster’s terns, Caspian terns, and 50 endangered least terns have returned to Cane Ridge [USFWS, 2012].

Other well-documented cases of attractive nuisance settings with characteristics ( e.g. , elevated concentrations of specific pollutants) si milar to those associated with steam electric power plants provide further support that comb ustion residual surface impoundments have the potential to pose a threat to wildlife. For exam ple, exposed organisms in attractive nuisance settings affected by urban and ag ricultural wastes have exhibited elevated tissue concentrations of pollutants, with some organisms experienci ng a combination of reproductive or sublethal effects that adversely impact th eir survival [Clark, 1987; Hofer et al ., 2010; King et al ., 1994;

Ohlendorf et al ., 1986, 1988a, 1988b, 1989, 1990; Tsipoura et al ., 2008]. Although these examples do not directly relate to steam electr ic power plants, they highlight the potential dangers of attractive nuisances and ability for pollutants to bioaccumulate in the surrounding wildlife [Ohlendorf et al ., 1986, 1989, 1990]. Table A-9 in Appe ndix A summarizes documented examples of impacts to wildlife a ssociated with attractive nuisances that are not specific to steam electric power plants.

4-14Section 5—Surface Water Modeling



## SECTION 5
SURFACE WATER MODELING

Based on the documented environmental imp acts discussed in the literature, EPA identified several key environmental and human health concerns and pathways of exposure to evaluate in the environmental assessment (EA). Environmental concerns include degradation of surface water, sediment, and ground water qual ity; toxic effects on aquatic and benthic organisms; bioaccumulation of contaminants and re sultant toxic effects on wildlife; toxic effects on humans consuming contaminated fish; and contamination of drinking water resources.

EPA focused its quantitative analyses on disc harges of the evaluated wastestreams to surface water – one of the primary exposure pathways of concern discussed in Section 4. To quantify baseline impacts and improvements under the final steam electric effluent limitations guidelines and standards (ELGs), EPA developed models to determine pollutant concentrations in the immediate receiving waters, pollutant concen trations in fish tissue, and exposure doses to ecological and human receptors from consuming a quatic organisms. This section describes the immediate receiving water (IRW) m odel and the ecological risk mode l used in developing this EA. Section 8 describes the development and execution of case study models using EPA’s Water Quality Analysis Simulation Program (WASP) to supplement the results of the IRW model.

5.1 I MMEDIATE R ECEIVING W ATER (IRW) M ODEL

EPA developed the IRW model 33 to quantify the environmental impacts to surface waters, wildlife, and human health from the wa stestreams evaluated for the regulatory options. As part of this national assessment, EPA de termined impacts in the immediate surface water where steam electric power generating industry di scharges occur, between 1 and 5 miles from the outfall depending on the stream reach. 34 As part of the benefits and cost analysis, EPA also

evaluated surface water concentrat ions downstream from steam electric discharges using EPA’s Risk-Screening Environmental Indicators (RSEI) model; see the Benefits and Cost Analysis (EPA-821-R-15-005). The IRW model framework focused on four key areas of impacts:

 Impacts to aquatic life based on reduction in water quality from discharges of the

evaluated wastestreams.

 Impacts to aquatic life based on reduction in sediment quality from discharges of the

evaluated wastestreams.

 Impacts to wildlife from the bioaccumulati on of contaminants in aquatic organisms and fish, including piscivorous (fish-eating) wildlife.

 Impacts to human health from consuming contaminated fish.

33 The IRW model is the same model that EPA used for the national-scale analyses in s upport of the proposed ELGs. EPA assigned the “IRW model” label to help distinguish the national-scale model from the case study models developed in support of the final ELGs.

34 See the ERG memorandum “Water Quality Module: Plan t and Receiving Water Characteristics” (DCN SE04513) for details on the immediate discharge zone and length of stream reach represented.

5-1Section 5—Surface Water Modeling

As discussed in Section 4.1.2, EPA considered the type of receiv ing waters commonly impacted by steam electric power plants and the pollutants typically found in the evaluated wastestreams in selecting the appropriate met hodologies for the quantitative analysis. The IRW model quantified the envi ronmental risks within rivers/str eams and lakes/ponds/reservoirs, and evaluated impacts from 10 toxic, bioaccumulative pollutants: arsenic, cadmium, copper, hexavalent chromium (chromium VI), lead, merc ury, nickel, selenium, th allium, and zinc. EPA’s

IRW model includes three interrelated modules:

 Water quality module—calculates immediate-receiving-water-specific pollutant concentrations in the water column and sediment and evaluates the impacts that receiving water concentrations pose to aquatic life and human health.

 Wildlife module—evaluates the impact that sediment concentrations pose to aquatic life, calculates the pollutant concentrations in exposed fi sh populations, and evaluates the potential adverse effects to minks and eagles from consuming fish.

 Human health module—calculates non-cancer and cancer risks to human populations from consuming fish.

Additionally, EPA used the selenium output s from the IRW water quality module to

evaluate the risks to fish and waterfowl that co nsume aquatic organisms with elevated levels of selenium (see Section 5.2). This ecological risk analysis expands on the results of the IRW

wildlife module described in this section.

The IRW water quality module us es plant-specific input data (plant-specific pollutant loadings and cooling water flow rate), 35 surface-water-specific characteristic data ( e.g. , receiving water flow rate, lake volume), and repr esentative environmental parameters ( e.g. , partition coefficients) to quantify the environmental imp acts of the evaluated wastestreams to surface waters. The module calculates pollu tant concentrations in the su rface water and sediment. These concentrations are inputs to the IRW wildlife m odule, which calculates the bioaccumulation of pollutants in fish tissue and determines impact s to wildlife. The fish tissue concentration

calculated in the IRW wildlife m odule becomes an input to the IR W human health module. This section provides overviews of each module. Appendices C thr ough E describe the IRW model equations, input data, and assumed environmental parameters in further detail. The appendices

also describe the limitations and assumptions of the IRW model.

Figure 5-1 provides an overview of the IRW model inputs and the connections among the three modules to support EPA’s national-scale modeling framework.

35 EPA calculated annual pollutant loadings for the evaluated wastestreams and excluded any pollutants discharged with other wastewaters ( e.g. , coal pile runoff). EPA incorporated cooling water flow rates into the IRW water quality module on a site-by-site basis. EPA assumed no pol lutant loadings were associated with cooling water discharges to surface waters and used cooling water flow rates only to evaluate dilution effects.

5-2Figure 5-1. Overview of IRW Model Section 5—Surface Water Modeling

5.1.1 Water Quality Module

EPA selected the stea dy-state equilibrium -partitioning model described in EPA’s Methodology for Assessing Health Risks Associ ated with Indirect Exposure to Combustor

Emissions (EPA 600-R-98-137) for the IRW water quality module. This selection was based on three factors: 1) the model’s ability to repres ent pollutants in the aquatic environment; 2) the model’s complexity, which EPA judged to be appropriate for a national-scale evaluation; 36 and 3) the level of previous Agency and extern al peer reviews performed on the modeling methodology. An equilibrium-partitioning model assu mes that dissolved and sorbed pollutants in a receiving water will quickly atta in equilibrium in the immediate vicinity of the discharge point because they dissolve or sorb in the surface water faster than they can be transported or dispersed

outside that area. The model also assumes that the equilibrium state for each pollutant can be represented by a partition coefficient that divides the total mass of a pollutant in the waterbody into four compartments:

 Constituents dissolved in the water column.

 Constituents sorbed onto suspende d solids in the water column.

36 For a national-scale environmental asse ssment of over 200 receiving waters, da ta limitations inhibit the feasibility of using more complex fate and transport receiving water models (dynamic or hydrodynamic) to estimate surface

water concentrations.

5-3Section 5—Surface Water Modeling

 Constituents sorbed onto sediments at the bottom of the waterbody.

 Constituents dissolved in pore water in the sediments at the bottom of the waterbody.

Table 5-1 lists the pollutants commonly found in the evaluated wast estreams with known environmental impacts (see Section 3.1, Table 3-1). EPA selected a subset of these pollutants for the water quality model based on the following criteria:

 The pollutant is known to be presen t in the evaluated wastestreams ( i.e. , identified as a pollutant of concern).

 Scientific literature documents elevated leve ls observed in surface waters or wildlife from exposure to steam electric power plant wastewater.

 Partition coefficient data are available for the water quality model.

 Benchmarks are available to evaluate potenti al threats to wildli fe or human health.

For the immediate receiving water quality analysis, EPA modeled 10 of the pollutants shown in Table 5-1: arsenic, cadmium, chromium VI, copper, lead, merc ury, nickel, selenium, thallium, and zinc.

5-4Section 5—Surface Water ModelingTable 5-1. Pollutants Considered for Analysisin the Immediate Receiving Water ModelPollutantPOCaLiteratureReviewbPartitionCoefficientcNRWQCdMaximum ContaminantLevel (MCL)WildlifeBenchmarkeHuman HealthBenchmarkfIncluded inModeling AnalysisgAluminumArsenichBoronCadmiumChromiumiCopperIronLeadManganeseMercuryjNickelSeleniumkThalliumVanadiumZinca – A check mark indicates that the pollutantis a pollutant of concern (POC) for oneor more of the evaluated wastestreams (see Section 6 of the TechnicalDevelopment Document (TDD) (EPA-821-R-15-007)).b – Literature review identified documented cases of elevated pollutant levels in surface watersor wildlife near steam electric power plants [ERG, 2013b; ERG,2015m].c – Partition coefficients for modeling analysis identified in U.S. EPA, 1999, and U.S. EPA, 2005a.d – National Recommended Water Quality Criteria (NRWQC) are available at http://water.epa.gov/scitech/swguidance/standards/current/index.cfm.e – No effect hazard concentration (NEHC) identified in USGS, 2008, for minks and bald eagles.f – Reference dose (RfD) identified in EPA’s Integrated Risk Information System (IRIS) for all pollutants except copper and thallium (available athttp://www.epa.gov/iris/);RfD forcopper is the intermediate oral minimal risklevel (MRL) [ATSDR, 2010a]; and RfD for thallium is the value for thalliumchloride provided in U.S. EPA, 2010a. Cancer slope factor forarsenic identified in EPA’s Integrated Risk Information System (IRIS) database [2011].g – Pollutant is included in the quantitative modeling analysis discussed in this section.h – Arsenic exists in two primary forms: arsenic III (arsenite) and arsenic V (arsenate). A check mark indicates that total arsenic, arsenite, and/or arsenatesatisfied the criterion in the table header.i – Chromium exists in two primary forms: chromium III and chromium VI. A check mark indicates that total chromium and/or chromium VI satisfied thecriterion in the table header.j – A check mark indicates that mercury and/or methylmercury satisfied the criterion in the table header.k – Selenium exists in two primary forms: selenium IV (selenite) and selenium VI (selenate). Acheck mark indicates that totalselenium, selenite, and/or selenatesatisfied the criterion in the table header.5-5Section 5—Surface Water Modeling

EPA developed the IRW water quality mo dule in Microsoft AccessTM using the equilibrium-partition equations presented in A ppendix C. The IRW water quality module is a mathematical model used to represent the part itioning of pollutants th rough the surface water after the wastestream has been discharged. Th e module output provides site-specific pollutant

concentrations in the wa ter column (total, dissolved, and su spended) and sediment for 188 steam electric power plants located across the United States that discharge to a river or stream or to a lake, pond, or reservoir. Figure 5- 2 depicts the pollutant concentr ations calculated in the IRW water quality module. EPA implemented this mode ling approach through the following steps:

1. Characterize the immediate rece iving water characteristics ( e.g. , depth of water column, depth of waterbody, receiving wa ter width, and flow independent mixing value) using site-specific inputs. See th e ERG memorandum “Water Quality Module: Plant and Receiving Water Char acteristics” (DCN SE04513).

2. Using the immediate receiving water char acteristics, determine the fraction of pollutant in the benthic sediment and in the water column and determine fraction of pollutant in the water column that is dissolved.

3. Using the immediate receiving water char acteristics and assumed input values,

calculate the water column volatilization ra te constant, for volatile pollutants only ( i.e. , mercury).

4. Calculate the water concentration dissipati on rate (zero for nonvol atile pollutants).

5. Based on site-specific pollutant loadings (converting annual loadi ngs to an average daily loading), cooling water flow rates (for a subset of plants), and immediate receiving water characteristics, calculate the total pollutant concentrations ( e.g. , total arsenic) in the immediate receiving water, including the concentration in the water

column and in the benthic sediment.

6. Calculate the concentration of dissolved pollu tant in the water column. Section 10 of the TDD details the pollut ant loadings methodology; th e ERG memorandum “Water Quality Module: Plant and Receiving Water Characteristics” (DCN SE004513) describes the use of cooling water flow rates. Note that the pollutant loadings included in the module do not represent th e total pollutant lo adings from steam electric power plants; several wastestreams were not evaluated ( e.g. , stormwater runoff, metal cleaning wastes, coal pile runoff). In addition, the module uses an annual average discharge rate, assumi ng no seasonal or daily variation.

7. Quantify the number of sites that exceed the NRWQC and drinking water maximum contaminant levels (MCLs) to evaluate th e potential exposure of ecological receptors ( i.e. , aquatic biota) and human receptors to toxic pollutants in the environment from

the evaluated wastestreams.

5-6Source: Adapted from U.S. EPA, 1998b.
Figure 5-2. Water Quality Module: Po llutant Fate in the Waterbody Section 5—Surface Water Modeling

As an indic ator of potential impacts, EP A compared the immediate receiving water concentrations (under base line and regulatory options) to the following NRWQCs:

 Freshwater acute and chr onic aquatic life NRWQC.

 Human health NRWQC for the consum ption of water and organisms.

 Human health NRWQC for the consumption of organisms.

EPA also compared immediate receiving wate r concentrations to drinking water MCLs. EPA identified immediate receiving waters that exceeded a NRWQC or MCL as an indication of the degradation of the overall water quality fo llowing exposure to the evaluated wastestreams. Section 6.3 summarizes the NRWQC and MCL ex ceedances under baseline pollutant loadings. Section 7.2 presents the perc ent reduction in number of imme diate receiving waters that potentially impact water quality under the final rule.

As with any modeling, EPA recognizes that model limitations exist and certain assumptions need to be made. EPA used aver age annual pollutant loadings and normalized effluent flow rates, which do not take into account temporal variability ( e.g. , variable plant operating schedules, storm flows, low-flow events, catastrophic events). The IRW water quality module does not account for ambient background pollutant concentrations or contributions from other point and nonpoint sources, an d assumes a constant flow rate in the receiving water based on the annual average reported in National Hy drography Dataset Plus (NHDPlus). Appendix C discusses these and additional module-specific limitations and assumptions and Section 6 and

5-7Section 5—Surface Water Modeling

Section 7 present the results of the IRW wa ter quality module under baseline and regulatory options.

5.1.2 Wildlife Module

As shown in Figure 5-1, the IRW wildlife module builds off the IRW water quality module by using the calculated immediate receivi ng water and sediment concentrations to calculate pollutant concen trations in fish populations exposed to the evaluated wastestreams and to assess the potential to impact w ildlife for the following categories:

 Impact to aquatic organisms from cont act with sediment contaminated by the evaluated wastestreams. To do this, the m odel quantifies the number of sites with potential exposure of ecological receptors ( i.e. , sediment biota) to the pollutant in the

environment.

 Impact to piscivorous wildlife ( i.e. , wildlife that habitually feeds on fish) from consuming fish impacted by the evaluated wastestreams. To do this, the model quantifies the number of sites with pot ential exposure of ecological receptors ( i.e.

, piscivorous wildlife) to the po llutant in the environment.

EPA developed the wildlife model in Microsoft Access TM to calculate pollutant concentrations in fish populations exposed to the evaluated wastestreams and estimate daily contaminant dose for wildlife receptors ( i.e. , minks and eagles) using equations presented in Appendix D. EPA determined potential impacts to wildlife by comparing the concentration in the contaminated media ( i.e. , water, sediment, or fish) to concentrations known to be protective of negative impacts ( i.e. , benchmark). Benchmarks, which are pollutant- and endpoint-specific and sometimes are species-specific, are an expressi on of the concentration level in contaminated media that is protective against a specific endpoint ( e.g. , mortality). Endpoints frequently reflected in benchmark values include sublethal effects ( e.g. , reduced reproduction, neurological effects) and lethal effects. EPA implement ed the wildlife modeling approach through the following steps:

1. Compare the concentration of the contaminant in benthic sediment to the benchmark

for sediment biota.

2. Calculate the pollutant concentration in fish for trophic level th ree (T3) or trophic level four (T4), 37 using the calculated pollutant concentration in the water column and the bioaccumulation factor (BAF) or bioconcentration factor (BCF). 38 For mercury, calculate the concentration of methylmercur y in the fish. See A ppendix D for details

on the IRW wildlife module and calculation of methylmercury concentration in fish.

3. Compare the concentration of the contaminant in the fish to the wildlife benchmarks for ecological receptors ( i.e. , mink and eagle).

37 T3 fish ( e.g. , carp, smelt, perch, catfish, sucker, bullhead, saug er) are those that primar ily consume invertebrates and plankton, while T4 fish ( e.g. , salmon, trout, walleye, bass) are those that primarily consume other fish.

38 BCFs are more appropriate for use with pollutants where th e primary pathway entering fish tissue is via the water, whereas BAFs are more approp riate for pollutants where the primary pathway entering fish tissue is through a food source (takes into account both water and diet). Wh ere available, EPA used pollutant-specific BAFs.

5-8Section 5—Surface Water Modeling

4. Compare the baseline and re gulatory option results ( i.e. , number of sites with potential exposure of ecological receptors to concentrations above protective benchmarks).

Adverse Effects to Aquatic Organi sms from Contact with Sediment

EPA compared the concentration in the bent hic sediment to benchmarks protective of benthic organisms. EPA used th reshold effects level (TEL) benc hmarks provided in the National Oceanic and Atmospheric Administration ( NOAA) 2008 Screening Quic k Reference Tables (SQuiRTs), referred to as the chemical stressor concentration limit (CSCL), for the sediment biota adverse impacts analysis. The CSCL is a chemical-specific media concentration that is protective of ecological receptors of concern. Th e CSCL benchmark is species-specific, but can be used to represent a community of organisms, such as amphibians or fish. Usually the most sensitive (or lowest) CSCL for a species is us ed to represent the co mmunity. Table D-1 in Appendix D presents the benchmarks used for se diment exposure analysis. Section 6.2 discusses the results of this analysis for baseline pollutant loadings.

Assessment of Pollutant Bioconcentration in Fish

EPA calculated fish tissue concentrations ba sed on the following: 1) total water column concentrations ( i.e. , dissolved plus sorbed) calculated in the IRW water quality module, and 2) trophic-level-specific BAFs or BCFs. BAFs a nd BCFs are based on field and laboratory study results compiled to develop a single factor or ratio for estimating the amount of pollutant transferred into fish tissue at a given trophic level ( i.e. , rank in the food chain) based on the pollutant concentration in the waterbody. EPA estim ated fish tissue concentrations in milligrams per kilogram (mg/kg) for T3 and T4 fish to account for the variability in fish likely consumed by both wildlife and human receptors included in the IRW model.

Although using the total water column concentr ation in the bioaccumulation analysis may overestimate the level of pollutants in the fish, it provides for a more environmentally protective estimate of risk in the subsequent human health model because it assumes that all pollutants within the waterbody (bot h dissolved and sorbed) are bioava ilable to the exposed fish. The exception to this methodology is mercury, wher e EPA based the fish tissue concentration

calculation on the dissolved con centration of methylmercury in the waterbody [U.S. EPA, 2005b]. Appendix D presents the BCFs and model equations for the anal ysis of pollutant

bioconcentration in fish tissue fo r T3 and T4 fish. EPA used the fish tissue concentrations to evaluate impacts to piscivorous wildlife (see next section) and impacts to human health receptors (see Section 5.1.3).

Impact to Piscivorous Wildlife

EPA based the piscivorous wildlife impact analysis on the methodology outlined in the 2008 U.S. Geological Survey (USGS) study Environmental Contaminant s in Freshwater Fish and Their Risk to Piscivorous Wildlife Based on a National Monitoring Program . The study examined the impacts to minks and eagles from eating contaminated fish. Minks and eagles are commonly used in ecological risk assessments as indicator species for potential impacts to fisheating mammals and birds in areas contaminated with bioaccumulative pollutants [USGS, 2008]. Minks and eagles are appropriate receptors for the steam electric power plant wildlife impact

5-9Section 5—Surface Water Modeling

analysis because their habitats sp an most of the country and their diet largel y consists of adult fish from the two trophic levels ( i.e. , T3 and T4 fish) included in the IRW wildlife module. According to the literature [U.S. EPA, 1998a], minks consume mostly T3 fish, while eagles consume mostly T4 fish. EPA evaluated the pote ntial adverse effects to minks and eagles for nine pollutants commonly found in the wastestreams of interest : arsenic, cadmium, chromium, copper, mercury, nickel, lead, selenium, and zinc. 39 The USGS method [USGS, 2008] is a wildlife impact analysis using NOAELs (no-observe d-adverse-effect levels ), which were derived from adult dietary exposure or tissue con centration studies based primarily on reproductive endpoints. The study calculated a NEHC benchm ark, which is based on the NOAEL, the food consumption rate, and/or the biomagnification f actor of each receptor. The report states that piscivorous wildlife may be at an elevated risk for reduced reproduction rates if the measured pollutant concentration in fish exceeds the NE HC. Therefore, EPA compared the mink-specific and eagle-specific NEHC values from the USGS study with the T3 and T4 fish tissue concentrations, respectively, to identify potential adverse impacts to the ecological receptors. In the piscivorous wildlife analysis, a benchmark exceedance indicates that piscivorous mammals or birds exposed to fish in the immediate receivi ng water of interest are at an elevated risk for reduced reproduction rates or other health effects.

Table D-3 in Appendix D presen ts the NEHC values used to evaluate potential adverse

effects to wildlife. The text of Appendix D presents the equations used to compare model outputs to benchmarks (NEHCs), along with model-specifi c limitations and assump tions. The results of

the IRW wildlife module under baseline conditions a nd the final rule are included in Section 6 and Section 7, respectively.

5.1.3 Human Health Module

As shown in Figure 5-1, the IRW human h ealth module builds off the IRW wildlife module, using the calculated T3 and T4 fish tissue concentrations. Its pur pose is to evaluate the cancer risk and potential to cause non-cancer hea lth effects from consuming fish within the following age and consumption categories:

 Child recreational fishers (six coho rts covering different age ranges). 40

 Child subsistence fishers (six coho rts covering differe nt age ranges).

 Adult recreational fishers.

 Adult subsistence fishers.

In addition, EPA evaluated potential impact s to different race populations using these same cohorts as part of its envi ronmental justice analysis. See the Regulatory Impact Analysis for the Effluent Limitations Guidelines and Standar ds for the Steam Electric Power Generating Point Source Category (RIA) (EPA-821-R-15-004).

39 Because there are no benchmarks fo r chromium VI or methylmercury, EP A used the total chromium and total mercury benchmarks, respectively, which ma y underestimate the risk to wildlife.

40 The child cohort age rang es correspond to the ranges provided in the 2008 Child-Specific Exposure Factors

Handbook ( EPA-600-R-06-096F ) for body weights.

5-10Section 5—Surface Water Modeling

EPA developed the IRW human hea lth module in Microsoft Access TM to estimate the daily pollutant doses for human receptors as a resu lt of eating T3 and T4 contaminated fish. EPA used a mathematical model to estimate the potential threats to human receptors from pollutant exposure. EPA estimated the average concentrati on of pollutants in a fish fillet consumed by humans based on a consumption diet of 36 percen t T3 and 64 percent T4 fish (see Appendix E).

The IRW human health module then calculate s the daily dose of pollutants from fish consumption for each cohort included in the anal ysis. EPA varied the fish consumption rate based on the specific cohort using two factors: 1) t ype of fisher (recreational or subsistence) and 2) age (adult and six child cohorts). EPA first ev aluated human health impacts based on type of fisher and age of cohort using national-level co nsumption rates. For th e environmental justice analysis, EPA determined fish consumption ra tes using the race population in addition to the other two factors. See Appendix E for further de tails. Using the fish consumption rate, EPA determined an average daily pollutant dose for each human cohort evaluated. Table E-2 in Appendix E presents the cohorts included in the IRW human health module and the corresponding fish consumption rates used in the module. EPA implemented the human health modeling approach throu gh the following steps:

1. Calculate the pollutant concentration in a fish fillet.

2. Calculate the average daily dose of pollutant from fish consumption by each receptor cohort (used for comparison to reference dose [RfD] values).

3. Calculate the lifetime average daily dose (LADD) for carcinogenic pollutants only, by each receptor cohort (used to determine cancer risk).

4. Calculate the lifetime excess cancer risk ( LECR) for carcinogenic pollutants only, by each receptor cohort, using the LADD.

5. Compare the exposure doses of human recep tor cohorts to appropriate benchmarks (RfD and selected cancer benchmark: 1-in-a-million).

6. Compare the baseline and regulatory option results: reduction in the number of immediate receiving waters with exposure doses from consuming fish that pose a potential threat to human receptors.

Non-Cancer Threat to Human Receptors

EPA evaluated the non-cancer threat ( e.g. , reproductive or neurological impacts) to each cohort by comparing the pollutant-s pecific average daily dose values for fish consumption to the corresponding RfDs. EPA evaluated non-cancer risks for the following pollutants: inorganic arsenic, 41 cadmium, chromium VI, copper, methylmercury, nickel, selenium, thallium, and zinc. Table E-3 in Appendix E presents the RfD values used in the non-cancer threat analysis. RfD values are an expression of the consumption dos e that is protective against a specific endpoint.

41 For this analysis, EPA used only the concentration of inorganic arsenic for the human health impact assessment. Based on the literature review, arsenic in fish is mostly in the organic form and is not considered harmful. The

wildlife model calculates a total arsenic fish tissue concentra tion. To convert this number to inorganic arsenic, EPA assumed that 4 percent of the total arsenic is inorganic based on EPA’s 1997 document Arsenic and Fish Consumption (EPA-822-R-97-003). The 1997 document reported that the inorganic arsenic concentration in fish is between 0.4 and 4 percent of the total arseni c accumulating in fish [U.S. EPA, 1997b].

5-11Section 5—Surface Water Modeling

Endpoints frequently reflected in RfDs in clude various immunological, reproductive, neurological, and other non-cancer effects. In the IRW human hea lth module, when the RfD is exceeded, it indicates a potential threat to humans for the endpoint associated with the RfD. For example, exceeding the RfD for selenium indicates that the exposure dose from fish consumption can cause non-cancer health effects, such as selenium-induced liver dy sfunction or selenosis (hair or nail loss, morphological changes of the nails, etc.) [U.S. EPA, 2011c].

Cancer Risk to Human Receptors

Arsenic is the only pollutant included in the IRW model for which EPA has derived a cancer slope factor fo r ingestion exposures. 42 The IRW human health module calculates the LADD for each receptor cohort base d on an exposure duration ( i.e. , length of time a receptor is in contact with the carcinogen) averaged over a lifetime ( i.e. , 70 years). For this analysis, EPA assumed the exposure duration to be equal to th e number of years represented by each cohort. Using these exposure durations is appropriate for screening-level estimates of cancer risk and for comparing changes between base line and regula tory options. 43 The model then multiplies the LADD by the cancer slope factor to calculate the LECR from arsenic. LECR is an estimate of the increase in cancer risk resulting from an exposure ( i.e. , consumption of contaminated fish). EPA used the benchmark value for evaluating cancer risk of 1-in-a-million people. Therefore, a calculated LECR greater than 1 × 10 -6 indicates an increased cancer risk for humans that consume fish exposed to discharg es of evaluated wastestreams.

5.2 E COLOGICAL R ISK M ODELING

Selenium bioaccumulation in aquatic organism s occurs primarily from ingesting food rather than through direct exposure to disso lved selenium in the water column [Fan et al ., 2002;

Ohlendorf et al ., 1986; Saiki and Lowe, 1987; Presser and Ohlendorf, 1987; Luoma et al ., 1992;

Presser et al ., 1994; Chapman et al ., 2009]. Unlike other bioaccumulative contaminants such as mercury, the single largest step in selenium accumulation in aquatic environments occurs in aquatic organisms at the base of the food web; algae, particulates, and microorganisms can accumulate selenium to levels far greater th an the concentration in the water column. Bioaccumulation and transfer through aquatic f ood webs constitute the major selenium exposure pathway in aquatic ecosystems.

Macrophytes, algae, phytoplankton, zooplankto n, and macroinvertebrates at the base of the food web easily bioaccumulate selenite and selenate and incorporate selenium in tissues as selenomethionine, an organo-selenide . This selenomethionine is then released back to the water

42 Although EPA determined that lead and lead co mpounds can be “reasonably anticipated to be human carcinogens,” no numeric value has been determined to qu antify the cancer risk. As st ated on the IRIS website, “quantifying lead’s cancer risk involves many uncertainties, some of which may be unique to lead. Age, health, nutritional state, body burden, and exposure duration influence the absorption, release, and excretion of lead. In addition, current knowledge of lead pharmacokinetics indicat es that an estimate derived by standard procedures would not truly describe the potential risk. Thus, the Carcinogen Assessment Group recommends that a numerical estimate not be used.” (See http://w ww.epa.gov/iris/subst/0277.htm#reforal.)

43 To completely assess risk to an individual, EPA recommends that risks should be calculated by integrating exposures throughout all life stages ( i.e. , adding multiple cohort risks from screening analysis). For example, the exposure duration may be equal to the length of time a person lives in an area [U.S. EPA, 2011b].

5-12Section 5—Surface Water Modeling

column as these plants and organisms die or are consumed [U.S. EPA, 2014f]. In general, selenium concentrations in particulates ( e.g. , sediment, detritus, and primary producers such as algae and biofilm) are 100 to 500 times higher th an dissolved concentrations in selenatedominated environments such as streams and ri vers. Where selenite or organo-selenide is proportionately more abundant, such as in lakes, wetlands, some estuaries, and oceans, the ratio can be much higher (1,000 to 10,000 times higher than dissolved concentrations). This variability of particulate concentrations relative to dissolved concentr ations across different aquatic environments makes it difficult to develop a simp le relationship between the concentration of

selenium in water and the concentration of se lenium in organisms [Presser and Luoma, 2010].

The scientific community has devoted signifi cant effort to understanding the mechanisms of selenium bioaccumulation. The preferred a pproach, as described in Presser and Luoma [2010], accounts for the variability in particulat e concentrations descri bed above by applying site-specific enrichment factors (E Fs) that represent the ratio of the concentration of selenium at the base of the food web ( i.e. , particulates) to the dissolved concentration in water. Subsequent bioaccumulation by aquatic organisms is descri bed through a series of empirically derived, species-specific trophic transfer factors (TTFs) that link the selenium concentrations in particulates and invertebrates to higher trophic-level organisms su ch as fish and birds. TTFs can be derived from laboratory expe riments or from field data. TTFs differ from traditional BCFs (described in Section 5.1.2) in that they are the ratio of the selenium concentration in each animal to the selenium concentration in its food, wher eas BCFs represent the ratio of the selenium

concentration in an animal to the selenium con centration in the water of its environment. Using TTFs therefore more accurately predicts seleni um bioaccumulation in aquatic organisms because it accounts for the significant role of dietary exposure.

Selenium toxicity among exposed fish and bird s primarily is transferred to the eggs and demonstrated via subsequent reproductive effect s. Many studies and expert panels have shown that reproductive effects, linked to egg-ovary selenium concentr ations, are of greatest concern and likely have led to observed reductions in sensitive fish sp ecies populations in waterbodies having excessive selenium concentrations [Chapman et al ., 2009].

EPA developed and applied a probabilistic ecological risk model, based on the bioaccumulation concepts described above, to as sess the risk of adverse reproductive impacts among fish and birds exposed to selenium in water bodies that receive discha rges of the evaluated wastestreams. Figure 5-3 provides a general sche matic of the approach, which follows these general steps:

1. Apply a distribution of site-s pecific EFs (with separate di stributions for lentic and lotic systems) to the predicted dissolved selenium concentration from the IRW water quality module, resu lting in a distribution of predicted selenium concentrations in particulates and pr imary producers for each receiving water.

2. Apply a TTF distribution for invertebrates (TTF invert ) to the outputs from Step 1, resulting in a distri bution of predicted selenium c oncentrations in invertebrates that inhabit each receiving water.

3. To predict the bioaccumulation a nd reproductive risk among fish:

5-13Section 5—Surface Water Modeling

a. Apply a TTF distribution for fish (TTF fish ) to the outputs from Step 2, resulting in a distri bution of predicted selenium concentrations in the eggs

and ovaries of fish that inhabit each receiving water (some of the TTFs incorporate tissue conversion factors to translate the outputs from whole body or muscle concentrations into fish egg-ovary concentrations).

b. Apply an exposure-respons e function for fish (ER fish ) to the outputs from Step 3a, resulting in a distribution s howing the probability of a decline in reproductive success across exposed fish populations.

4. To predict the bioaccumulation and repr oductive risk among birds (specifically, mallards):

a. Apply a TTF distribution for mallards (TTF mallard ) to the outputs from Step 2, resulting in a distribution of predic ted selenium concentrations in the eggs of mallards that forage and/ or breed in each receiving water.

b. Apply an exposure-response function for mallards (ER mallard ) to the outputs from Step 4a, resulting in a di stribution showing the probability of a decline in reproductive success ac ross exposed mallard populations.

This modeling approach is consistent with th e approach taken in de veloping the External Peer Review Draft Aquatic Life Ambient Wate r Quality Criterion for Selenium – Freshwater [U.S. EPA, 2014f] (referred to as th e external peer review draft se lenium criterion) and is based on the same data sets and studies for EF, TTF invert , TTF fish , and ER fish . For this EA, EPA expanded the model to in clude data sets for TTF mallard and ER mallard and to include several additional data sets and studies for EF, TTF invert , TTF fish , and ER fish that were eventually incorporated into the Draft Aquatic Life Am bient Water Quality Criterion for Selenium

– Freshwater [U.S. EPA, 2015b].

5-14Figure 5-3. Flowchart of Sele nium Ecological Risk Model Section 5—Surface Water Modeling

5-15Section 5—Surface Water Modeling

Detailed information for some of the factors that influence selenium bioaccumulation at a particular site, such as the form of selenium in the environment ( e.g. , selenate, selenite, and organo-selenide) and the structure of the aqua tic food web, is not available across the 209 immediate receiving waters modeled in this EA . The ecological risk model accounts for these unknowns by applying distributions of EFs and TTFs based on data representing a wide variety

of lentic and lotic waterbodies a nd freshwater invertebrate and fish species, rather than relying on a single statistical measure ( e.g. , mean or median) for those parameters. This approach

accounts for the variabili ty across aquatic systems and cap tures the full range of food web constructs that could occur in these receiving waters.

The remainder of this section further discu sses EPA’s development of the EFs, TTFs, and ER functions in the ecological risk model and use of those functions to calculate risk of adverse reproductive effects (performed using Oracle Cr ystal Ball software). Appendix F provides additional details regarding data sources, data acceptance criteria, statistical methods, and assumptions and limitations of the ecological risk model.

Enrichment Factors

EPA compiled a database of empirical measur ements of selenium concentration (water, sediment, biofilm, algae, phytoplankton, and detritus) from relevant field studies across a range of aquatic systems. EPA then calculated EFs for a set of aquatic systems and applied statistical methods to distinguish categories with similar bi oaccumulation characteristics, consistent with the approach followed in developing the external peer review draft seleni um criterion [U.S. EPA, 2014f]. The key factor distinguishing EFs across syst ems is whether the data were collected from lentic systems ( e.g. , lakes, reservoirs, and ponds) or lotic systems ( e.g. , rivers, creeks, and streams). Therefore, the EPA deve loped EF distributions separately for lentic and lotic systems.

This effort produced EF distributions fo r both systems that are well described by lognormal distributions with means (standard deviati ons) of 1,738 (2,499) 44 for lentic systems and 692 (787) for lotic systems.

Trophic Transfer Factors for Invertebrates and Fish

EPA compiled a database of empirical measurements of selenium concentration in particulates, invertebrates, and fish from re levant field studies. EPA arranged the data by developing data pairs representing the concentrati on in the consumer organism (invertebrate or fish) and the concentration in the consumed materi al or lower-trophic-level organism (particulate or invertebrate). The ratio betw een these two values defines the TTF for the consumer organism. EPA limited these data pairs to measurements collected from the same aquatic site. EPA further limited the data pairs by excluding measurements of material or lower-trophic-level organisms deemed unlikely to be ingested by the high er-trophic-level organism. Many of the fish

concentration measurements required a further conversion to the concentration of selenium in eggs, requiring a whole-body-to-egg/ovary conve rsion factor. This factor (egg/ovary concentration = whole body concentration × 1.9) is based on paired measurements from

44 The EF incorporates a multiplier of 1,000. A mean EF of 1,738 for lentic systems indi cates that, on average, the concentration of selenium at the base of the food web is 1.738 times greater than the dissolved concentration in

water.

5-16Section 5—Surface Water Modeling

individual fish and is consistent with the value used to develop the external peer review draft selenium criterion [U.S. EPA, 2014f].

This effort resulted in a TTF invert distribution with a mean (standard deviation) of 2.84 (2.49) and a TTF fish distribution with a mean (sta ndard deviation) of 1.6 (1.08).

Trophic Transfer Factors for Mallards

EPA selected the mallard ( Anas platyrhynchos ) as the representative bird species for the ecological risk analysis. The mallard has been ex tensively evaluated in bo th field and laboratory studies and has been shown to be relatively sensitive to selenium. Mallards are ubiquitous, occurring in every state at specific times during the year, and are the species with the highest probability of being found at any of the 209 mode led receiving waters. Dabbling ducks such as mallards contribute important ecosystem services, such as transferring eggs and seeds of aquatic organisms between isolated wetlands and main taining the biodiversity of other organisms [Bengtsson et al. , 2014; Green and Elmberg, 2014].

Based on a review of Ohlendorf [2003], EPA deve loped a database of field measurements of mallards and their likely food so urces, expressed as a ratio of me asured egg concentrations to dietary concentrations. Many studies across a wide variety of species have shown that selenium concentrations in bird eggs range from roughly equal to or three or four times the concentrations

in the diet of the female at the time of e gg-laying [Ohlendorf and Heinz, 2011]. The resulting

TTF mallard distribution is best described by a triangular distribution, with a lik eliest value of 2.5, a minimum value of 0.4, and a maximum value of 4.1.

Exposure-Response Function for Fish

Larval mortality and repr oductive teratogenesis ( i.e. , deformities in offspring) from maternal transfer of selenium to eggs re present the most sensitive endpoints in fish. Deformities in fish that affect feeding or respiration can be lethal shortly after hatching. Deformities that are not directly lethal, but that distort the spine and fins, can affect larval survival by reducing swimming ability and overall fitness. EPA therefore selected larval mortality and deformities as the target endpoints for this analysis.

This approach is consistent with the approach taken to develop the external peer review draft selenium criterion, and used the same extensively peer-reviewed exposure-response function ( i.e., curve) as was used in that analysis [U.S. EPA, 2014f]. Appendix F provides the exposure-response function for fis h, which translates the modeled egg-ovary concentration into the probability of adverse reproductive effects.

Exposure-Response Function for Mallards

To derive the exposure-response function for mallards, EPA used the same set of six progressive studies us ed to develop the TTF mallard distribution [Ohlendorf, 2003]. This approach ensures consistency in the predicted bioaccumulation and reproductive response across different selenium exposure levels.

5-17Section 5—Surface Water Modeling

The mallard exposure-response function in Ohlendorf [2003] is based on a regression meta-analysis of six different laboratory studies th at evaluated the effect of selenium on mallard egg hatchability [Heinz et al., 1987, 1989; Heinz and Hoffman, 1996, 1998; Stanley et al., 1994, 1996]. This function formed the basis of the wate r quality criterion adopted by the Utah Water Quality Board for Lake Gilbert, and underwent peer review by EPA Region 8. For this analysis, EPA fit a logistic curve to the combined, control normalized data from the six mallard studies. Appendix F provides the resulting expos ure-response function for mallards.

Calculation of Reproductive Risk

In this analysis, risk is defined as the probability of a percentage reduction in reproductive capacity based on larval mortality and deformity in fish and hatching success in mallards. For any given exposure concentration to selenium predicted fro m the EF-TTF model, the exposure-response function provides the probabi lity of the effect occurring, termed a joint probability model.

The EF-TTF models provide the predicted ex posure distributions in fish and mallard eggs. For each concentration, the probability of exposure occurring is compared to the probability of effect at that exposure level. Th e resulting functions provide the probability of larval mortality and deformities in fish and hatching failure in mallards.

5-18Section 6—Current Impacts from Steam Electric Power Generating Industry



## SECTION 6
CURRENT IMPACTS FROM STEAM ELECTRIC POWER
GENERATING INDUSTRY

EPA developed the immediate receiving wate r (IRW) model and ecological risk model described in Section 5 to quantify the current national-scale environmen tal impacts of direct surface water discharges of the evaluated wastestreams ( i.e. , flue gas desulfurization (FGD) wastewater, fly ash transport water, bottom ash transport water, and combustion residual leachate) from steam electric power plants. This section presents the baseline results of the modeled pollutant concentrations in surface waters and fish tissue and their potential impacts to aquatic life, wildlife, and human health.

6.1 W ATER Q UALITY I MPACTS

The quality of a surface water is defined by its chemical, physical, and biological characteristics and is measured to evaluate a water’s potential to harm aquatic life and human health. EPA assessed the quality of surface waters that receiv e discharges of the evaluated wastestreams by comparing estimated pollutant c oncentrations in the water column to the National Recommended Water Quality Criter ia (NRWQC) and drinking water maximum contaminant levels (MCLs). Based on the modeli ng results for surface wa ter quality impacts, approximately 62 percent of the lakes, ponds, and re servoirs (16 out of 26) and 43 percent of the rivers and streams (78 out of 183) that receive discharges of th e evaluated wastestreams have estimated pollutant concentrations that exceed these water quality benchmarks and may have quantifiably impaired water quality due to th ose discharges. Based on the modeling results, human health criteria exceedances are more pr evalent among the immediate receiving waters than aquatic life criteria exceedances. Approxi mately 17 to 45 percent of the immediate receiving waters had modeled pollutant concentr ations that exceed a human health criterion, while approximately 4 to 17 percent of the imme diate receiving waters had modeled pollutant concentrations that exceed an aquatic life criterion. The difference between exceedances for human health and aquatic life crite ria is due to the human health criteria for arsenic and thallium, which are significantly lower than the aquatic life criteria for most of the modeled pollutants.

Due to data limitations at the national scale, EPA did not include other pollutant sources ( e.g. , naturally -occurring pollutants, nonpoint s ource discharges, or other point source discharges) in the IRW model. Quantified excee dances estimated by the IRW model represent environmental impacts due entirely to the pollutant loadings in discharges of the evaluated wastestreams from steam electric power plants. Tabl e 6-1 presents the number and percentage of immediate receiving waters with estimated pollutant concentrations that exceed each water quality criterion under baseline conditions.

EPA identified arsenic, thallium, cadmium, and selenium as the primary pollutants contributing to the water quality exceedances, as shown in Table 6-1. Humans are primarily at risk for exposure to arsenic and thallium. Out of the 209 modeled immediate receiving waters:

 94 exceed the human health NRWQC for the consumption of arsenic-contaminated water and organisms (0.018 micrograms per liter (μg/L)).

6-1Section 6—Current Impacts from Steam Electric Power Generating Industry

 65 exceed the arsenic NRWQC for consumption of organisms only (0.14 μg/L).

 49 exceed the human health NRWQC for the consumption of thallium-contaminated water and organisms (0.24 μg/L).

 45 exceed the thallium NRWQC for consump tion of organisms only (0.47 μg/L).

Therefore, humans consuming water and/or organisms inhabiting these waters are more at risk of arsenic-related effects (skin damage, cardiovascular disease, and cancer in the skin, lungs, bladder, and kidney) and thallium-related e ffects (changes in blood chemistry; damage to liver, kidney, and intestinal and testicular tissues; hair loss; and reproductive and developmental damage).

Aquatic organisms are primarily at risk due to exposure to cadmium and selenium. Estimated pollutant concentrations in approximately 15 percent of the immediate receiving waters (29 and 33 out of 209, respectively) exceed the aquatic life criterion for chronic exposure

to cadmium- and selenium-contaminated waters (0.25 and 5 μg/L, respectively). Therefore, aquatic organisms inhabiting thes e waters are under a greater thre at for cadmium-related effects (tissue damage and organ abnormalities) and selenium-related effects (reproductive failure, deformities, reduced growth, increased metabolic ra tes, and death). Sublethal and lethal impacts from chronic selenium exposure are frequently ci ted in literature. For more information on these impacts, refer to Section 3.1.1.

Table 6-1. Number and Percentage of Imme diate Receiving Waters with Estimated

Water Concentrations that Exceed th e Water Quality Criteria at Baseline

Evaluation Criterion Number of Immediate Receiving Waters Exceeding a

Criterion a

Number of

Rivers and

Streams Number of Lakes, Ponds,

and

Reservoirs Total Immediate Receiving

Waters b

Number Exceeding Percentage Exceeding
Aquatic

Life

Criteria Freshwater Acute NRWQC 9 0 9 4%

Freshwater Chronic NRWQC 30 5 35 17%

Human

Health

Criteria Human Health Water and Organism NRWQC 78 16 94 45%

Human Health Organism Only NRWQC 55 11 66 32%

Drinking Water MCL 31 5 36 17%
Total Number of Unique Immediate Receiving Waters c 78 16 94 45%

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i.

Acronyms: NRWQC (National Recommended Water Quality Criteria); MCL (maximum contaminant level).

a – The EA encompasses a total of 222 immediate receivi ng waters and loadings fr om 195 steam electric power plants (some of which discharge to mu ltiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receiving waters (183 rivers and streams; 26 lakes, ponds, and reservoirs) and loadings from 18 8 steam electric power plants.

b – These values are the sum and percentage of rivers , streams, lakes, ponds, and reservoirs impacted.

c – This represents the number of unique immediate receiving waters th at exceeded at least one criterion.

6-2Section 6—Current Impacts from Steam Electric Power Generating Industry

Table H-1 in Appendix H presents additional details on the number and percentage of immediate receiving waters that are exceeding each water quality criter ion by pollutant. For

more detailed information on the modeled im mediate receiving water concentrations under baseline conditions, see Figures H-1 to H-10 and Tables H-2 to H-11 in Appendix H.

6.2 W ILDLIFE I MPACTS

As part of the national-scale wildlife impact s analysis, EPA assessed the impacts of the evaluated wastestreams on the following categories:

 Impacts to wildlife indicator species ( i.e. , mink and eagle) due to consuming contaminated fish (using the wild life component of the IRW model).

 Impacts to fish and waterfowl due to dietary exposure and trophic transfer of selenium (using the ecological risk model in combination with the water quality component of the IRW model).

 Impacts to benthic organisms due to contac t with contaminated sediment (using the wildlife component of the IRW model).

The results of these analyses are described in the following sections.

6.2.1 Impacts to Wildlife Indicator Species

As described in Section 5.1.2, EPA assessed th e potential impact to piscivorous wildlife from the evaluated wastestreams by modeling fish tissue pollutant concentr ations and comparing

these concentrations to no eff ect hazard concentrations (NEHC) for minks and eagles developed by the U.S. Geological Survey (USGS). Based on the estimated fish tissue concentrations, approximately 34 percent (71 out of 209) and 28 percent (58 out of 209) of the immediate receiving waters pose a poten tial threat to eagles and mi nks, respectively, through the consumption of contaminated fish. This resu lt demonstrates that estimated pollutant concentrations in fish that inhabit receiving waters immediately downstream from steam electric power plant wastewater discharg es pose a potential reproductive threat to surrounding minks and eagles and indicates the potential broader impact s that steam electric power plant wastewater discharges may pose to the greater environmen t as pollutants transfer from the aquatic environment and begin to accumulate in terrestrial food webs.

As expected, based on documented environmen tal impacts, modeling results indicate that pollutant concentrations in fish inhabiting lakes, ponds, and reservoirs are more likely to exceed the NEHC benchmarks than polluta nt concentrations in fish inha biting rivers and streams. The estimated fish tissue pollutant c oncentrations pose a potential reproductive threat to minks and eagles in approximately 46 percent of modeled lakes, ponds, and reservoirs (12 out of 26) and in 32 percent of rivers and streams (59 out of 183) that were evalua ted. These results are expected, since fish populations inhabiting lake environments cannot travel to uncontaminated waters and therefore continue to bioaccumulate pollutants.

Table 6-2 presents the number and percentage of immediate receiving waters that exceed the USGS wildlife fish consump tion NEHC for minks and eagles.

6-3Section 6—Current Impacts from Steam Electric Power Generating Industry

Table 6-2. Number and Percentage of Immediat e Receiving Waters That Exceed Wildlife Fish Consumption NEHCs for Minks and E agles (by Waterbody Type) at Baseline

Evaluation Criterion Number of

Rivers and

Streams Number of Lakes, Ponds,

and Reservoirs Total Receiving Waters a,b

Number Exceeding Percentage Exceeding
Mink fish consumption NEHC 47 11 58 28%
Eagle fish consumption NEHC 59 12 71 34%
Total Number of Unique Immediate Receiving Waters c 59 12 71 34%

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i.

Acronyms: NEHC (No Effect Hazard Concentration).

a – The EA encompasses a total of 222 immediate receivi ng waters and loadings fr om 195 steam electric power plants (some of which discharge to mu ltiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receiving waters (183 rivers and streams; 26 lakes, ponds, and reservoirs) and loadings from 18 8 steam electric power plants.

b – These values are the sum and percentage of rivers , streams, lakes, ponds, and reservoirs impacted.

c – This represents the number of unique immediate receiving waters that exceed a criterion.

The pollutants found to present the greatest threat to minks and eagles from fish consumption were mercury and selenium. The mode led concentrations of mercury in fish tissue

exceeded the NEHC benchmarks for minks and eagles in 26 and 34 percent of the modeled immediate receiving waters, respectively. Approxim ately 20 percent of the immediate receiving

waters contained fish with m odeled selenium concentrations exceeding a fish consumption NEHC benchmark for minks and eagles.

Table 6-3 presents the number and percentage of immediate receiving waters that exceed a USGS wildlife fish consumption NEHC for minks and eagles by pollutant.

6.2.2 Impacts to Fish and Waterfowl due to Dietary Selenium Exposure

As discussed in Section 5.2, EPA expanded upon the piscivorous wildlife benchmark analysis to include ecological risk modeling of the reproductiv e risks among fish and waterfowl that consume aquatic organisms contaminated with elevated levels of selenium. Selenium is of particular concern in aquatic environments because it can accumula te in sediment and biomagnify to toxic levels in fish inhabiting selenium-contaminat ed waters (even at relatively low concentrations), potentially eliminating piscivorous (fish-eating) wildlife higher in the food chain [Ohlendorf et al ., 1988a]. Impacts to fish populations are well document ed in the literature [Garrett and Inman, 1984; Lemly, 1985a; Sorensen et al ., 1982]. While exposed fish populations may not experience lethal impacts, the sublet hal damage to their reproductive systems can eventually impact the survivabili ty of fish populations near st eam electric power plants. The documented impacts at Belews Lake illustrate this is especially an issue in lakes, ponds, and reservoirs, where healthy fish populations cannot migrate and seek out alternative food sources. Decreased fish populations may cause cascading e ffects within the food web that can adversely affect other organisms in the ecosystem.

6-4Section 6—Current Impacts from Steam Electric Power Generating Industry

Table 6-3. Number and Percentage of Immediat e Receiving Waters That Exceed Wildlife Fish Consumption NEHCs for Minks a nd Eagles (by Pollutant) at Baseline

Pollutant Mink Eagle

Fish Consumption

NEHC (μg/g) a Immediate Receiving

Waters Fish Consumption

NEHC (μg/g) a Immediate Receiving

Waters

Number Exceeding b Percentage Exceeding Number Exceeding b Percentage Exceeding

Arsenic 7.65 0 0% 22.4 0 0%

Cadmium 5.66 6 3% 14.7 4 2%

Chromium VI 17.7 c 0 0% 26.6 c 0 0%
Copper 41.2 1 <1% 40.5 1 <1%

Lead 34.6 1 <1% 16.3 2 1%
Mercury 0.37 55 26% 0.5 71 34%

Nickel 12.5 0 0% 67.1 0 0%

Selenium 1.13 42 20% 4 42 20%

Thallium ID NC NC ID NC NC

Zinc 904 1 <1% 145 5 2%

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i.

Acronyms: ID (Insufficient data; no benchmarks were iden tified in the wildlife analysis for thallium); NC (Not calculated); NEHC (No Effect Hazard Con centration); μg/g (micrograms/gram).

a – The wildlife fish consumption NEHC represents the maximum pollutant concentration in the fish that will result in no observable adverse effects in wildlife ( i.e. , minks or eagles) [USGS, 2008].

b – The EA encompasses a total of 222 immediate receivi ng waters and loadings fr om 195 steam electric power plants (some of which discharge to mu ltiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receiving waters (183 rivers and streams; 26 lakes, ponds, and reservoirs) and loadings from 18 8 steam electric power plants.

c – An NEHC benchmark is not available for chromium VI; therefore, EPA used the total chromium benchmark.

The results of the ecological risk mode l indicate that, under baseline conditions, discharges of selenium from steam electric power pl ants elevate the risk of adverse reproductive impacts among fish and mallards that inhabit, fora ge, or breed in the imme diate receiving waters. These reproductive impacts include larval morta lity and deformities among fish and reduced egg hatchability among mallards.

The ecological risk modeling results indicat e that 15 percent of the lakes, ponds, and reservoirs (four out of 26) and 11 percent of the rivers and streams (20 out of 183) that receive discharges of the evaluated wastestreams pres ent an elevated risk of negative reproductive impacts to fish. For mallards, th e counts are slightly higher, with 19 percen t of the lakes, ponds, and reservoirs (five out of 26) a nd 14 percent of the rivers and streams (26 out of 183) presenting these risks. These results support the conclusion th at lentic systems, which have higher potential for pollutant retention due to longer residence ti mes, are more likely to experience ecological impacts due to discharges from steam electric power plants.

The results described above represent those immediate recei ving waters whose median modeled egg/ovary concentration is predicted to impact repr oduction among at least 10 percent of the exposed fish or mallard population. As described below, however, ad justing these criteria reveals additional perspective re garding the prevalence of immedi ate receiving waters that may be causing reproductive impacts due to selenium exposure.

6-5Section 6—Current Impacts from Steam Electric Power Generating Industry

Selecting the 90 th percentile modeled egg/ovary concentration, meaning there is a 10 percent probability that the egg/ovary concentrati ons are greater than the selected concentration, reveals that 20 percent of the immediate receiving waters (42 out of 209) present reproductive risks to at least 10 percent of the exposed fish population. The re sults for mallard s (21 percent) are very similar. These counts ar e considerably higher than the results obtained using the median modeled egg/ovary concentrati on, indicating the potential for more widespread ecological impacts among those waterbodies and food webs that tend to experience higher bioaccumulation

of selenium.

The results of the ecological risk model i ndicate that sublethal effects from dietary exposure to selenium (from disc harges of the evaluated wast estreams) can lead to hidden population-level effects among exposed fish an d waterfowl by reducing reproductive success.

The results for mallards illustrate the broader effects throughout the f ood web that can result from exposure to waterbodies co ntaminated with selenium. Thes e results also indicate that impacts to aquatic-dependent wildlife are not li mited to piscivorous wildlife such as mink and eagles.

The ecological risk model accounts only for th ose reproductive effects associated with exposure to selenium. There might be more imme diate receiving waters whose pollutant levels result in elevated reproductive risk because they contain other pollutants at concentrations that

are harmful to wildlife.

For more information on the potential enviro nmental impacts from selenium exposure,

refer to the selenium discussion in Section 3.1. For more detailed information on baseline modeled fish tissue concentrations in the immediate receiving water for selenium and other pollutants evaluated in the EA, see Figures H-11 to H-21 and Tables H-12 to H-22 in Appendix H.

6.2.3 Impacts to Benthic Organisms

EPA also assessed the potential impact to wild life exposed to sediments in surface waters that receive discharges of the evaluated wastestreams by comparing estimated pollutant

concentrations in the sediment to chemical st ressor concentration limit (CSCL) benchmarks for sediment biota published by MacDonald, et. al. (2000) in Archives of Environmental Contamination and Toxicology . Table 6-4 presents the number and percentage of immediate receiving waters with sediment pollutant conc entrations that exceed a CSCL. EPA calculated that 22 percent of rivers and streams (40 out of 183) and 35 percent of lakes, ponds, and reservoirs (9 out of 26) had es timated sediment pollutant concen trations that may be toxic to

wildlife.

Benthic organisms are at risk primarily due to exposure to mercury, nickel, and cadmium. Estimated sediment pollutant concentrations in 13 to 23 percent of the immediate receiving waters (27 to 49 out of 209) exceed the sediment biota CSCL benchmarks for exposure to cadmium-contaminated, nickel-contaminated, and mercury-contaminated waters. Therefore, benthic organisms inhabiting these waters are under a greater threat for sublethal effects such as skeletal malformation and reduced growth and reproductive success. For more information on these impacts, refer to Section 3.1.1.

6-6Section 6—Current Impacts from Steam Electric Power Generating Industry

As expected, based on documented environmen tal impacts, modeling results indicate that pollutant concentrations in the benthic sediment in lakes, ponds and reservoirs are more likely to

exceed the sediment biota CSCL benchmarks th an pollutant concentrations in the benthic sediment of rivers and streams. Several publica tions in the literature confirm that sediment impacts are more likely to occur in lakes where pollutants can accumulate in sediments over time [Hopkins et al ., 2000, 2003; Lemly, 1997a].

Table 6-4. Number and Percentage of Imme diate Receiving Waters with Sediment Pollutant Concentrations Exceeding CS CLs for Sediment Biota at Baseline

Pollutant Sediment

Benchmark

(mg/kg) Number of Immediate Receiving Waters Exceeding CSCLs for

Sediment Biota

Rivers and

Streams Lakes, Ponds,

and Reservoirs Total Immediate Receiving

Waters

Number a Percent

Arsenic 5.90 7 0 7 3%

Cadmium 0.596 22 5 27 13%

Chromium VI b 37.3 0 0 0 0% Copper 35.7 6 1 7 3%

Lead 35 5 1 6 3% Mercury 0.174 40 9 49 23%

Nickel 18.0 29 5 34 16%

Selenium ID NC NC NC NC

Thallium ID NC NC NC NC

Zinc 123 14 1 15 7% Total Number of Unique Immediate Receiving Waters 40 9 49 23%

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i.

Acronyms: CSCL (Chemical stressor concentration limit); ID (Insufficient data; no benchmarks were identified); NC (Not calculated).a – The EA encompasses a total of 222 immediate receiving waters and loadings from 195 steam electric power plants (some of which discharge to multiple r eceiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receiving waters (183 rivers and streams; 26 lakes, ponds, and reservoirs) and loadings from 188 steam electric power plants.

b – No benchmark for chromium VI. EPA used the total chromium benchmark, which may underestimate the impact

to wildlife.

6.3 H UMAN H EALTH I MPACTS

In addition to assessing water quality impact s on human health as discussed in Section 3.3.2, EPA expanded the analysis to evaluate hu man health impacts from consuming fish in immediate receiving waters downstream from disc harges of the evaluated wastestreams. The purpose of this analysis was to evaluate the broader bioaccumul ative effects of pollutants in steam electric power plant discharges to see whet her average daily doses of pollutants from fish consumption could potentially exceed human health thresholds where water concentrations may not indicate an issue. EPA evaluated multiple human cohorts ( i.e. , recreational and subsistence fishers, children and adults) by calculating the average daily dose of pollutants from fish consumption using the estimated fi sh tissue concentrations calcula ted in the model. EPA varied the fish consumption rate of each cohort (based on age) to determine the average and long-term daily doses for each pollutant. EPA calculated th e lifetime excess cancer risk (LECR) based on

6-7Section 6—Current Impacts from Steam Electric Power Generating Industry

estimated fish tissue concentra tions of inorganic arsenic an d calculated non-cancer threats by comparing the average daily doses to threshold va lues for all pollutants with published reference doses. EPA first evaluated human health impacts ba sed on type of fisher and age of cohort using national-level consumption rates. For the environmental justice analysis, EPA determined fish consumption rates using the race population in a ddition to the other two factors. For more information on how EPA identified potential imp acts to human receptors, see Section 5.1.3 and Appendix E.

The human health module presents the risk results for each age group individually to allow for further manipulation in the benefits analysis. The true cancer risk to a child would depend on the amount of time the child consumed fish from locations downstream from steam electric power plant discharges. For example, the cancer risk for a 6-year-old child who was born and raised in the same place would be the sum of the LECRs from the 1 to <2 years, 2 to <3 years, and 3 to <6 years cohort groups.

A limitation of the national-scale IRW modeli ng that may underestimate the cancer risk is the use of an average annual pollutant loading rate as the basis for the risk estimation; as described earlier, the model doe s not consider the potential for pollutants to accumulate over

time in the environment. The model estimates a minimal cancer risk from consuming fish in lakes, ponds, and reservoirs that receive discharges of the ev aluated wastestreams. The cancer risk is likely greater in a lake, where fish are limited in their food sources and can bioaccumulate pollutants over a longer exposure period than is represented in the model.

6.3.1 National-Scale Cohort Analysis

Table 6-5 presents the number and percentage of immediate receiving waters where the

estimated LECR for the national-scale human rece ptor exceeds the select ed threshold, 1-in-amillion cancer risk for arsenic. Inorganic arsenic concentrations in fish result in an estimated cancer risk greater than 1-in-a-m illion to adult subsistence fishers in approximately 12 percent of the immediate receiving waters (25 out of 209) a nd to adult recreational fi shers in approximately 6 percent of the immediate receiving waters (12 out of 209). Cancer risks for the child cohorts are lower, with LECRs exceeding the cancer risk threshold in 2 to 4 percent of the immediate receiving waters. Even given the limitations of the modeling framew ork discussed in Section 6.3, the inorganic arsenic concentrations in fish can pose a cancer risk to adult subsistence fishers in 12 percent of the lakes and to adult recreational fishers in 8 percent of the lakes.

6-8Section 6—Current Impacts from Steam Electric Power Generating Industry

Table 6-5. Number and Percentage of Immedi ate Receiving Waters That Exceed Human Health Evaluation Criteria (Lifetime Exce ss Cancer Risk) for Inorganic Arsenic at

Baseline

Receptor Cohort Exposure

Duration (Years) Number of Immediate Receiving Waters Where

Lifetime Excess Cancer Ri sk Exceeds 1-in-a-Million a,b

Number of

Rivers and

Streams Number of Lakes, Ponds,

and Reservoirs Total Receiving Waters c

Number Exceeding Percentage Exceeding

Child

recreational

fisher 1 to <2 years 1 4 0 4 2%
2 to <3 years 1 4 0 4 2%
3 to <6 years 3 6 0 6 3%
6 to <11 years 5 6 0 6 3%
11 to <16 years 5 6 0 6 3%
16 to <21 years 5 6 0 6 3%

Adult recreational fisher 49 10 2 12 6%

Child

subsistence

fisher 1 to <2 years 1 6 0 6 3%
2 to <3 years 1 6 0 6 3%
3 to <6 years 3 7 0 7 3%
6 to <11 years 5 8 1 9 4%
11 to <16 years 5 6 0 6 3%
16 to <21 years 5 6 0 6 3%

Adult subsistence fisher 49 22 3 25 12%

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i.

a – The EA encompasses a total of 222 immediate receivi ng waters and loadings fr om 195 steam electric power plants (some of which discharge to mu ltiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receiving waters (183 rivers and streams; 26 lakes, ponds, and reservoirs) and loadings from 18 8 steam electric power plants.

b – Inorganic arsenic cancer slope factor of 1.5 per milligrams per kilogram (mg/kg) per day.

c – These values are the sum and percentage of rivers , streams, lakes, ponds, and reservoirs impacted.

Based on the estimated fish tissue concentra tions and average daily pollutant doses by cohort, subsistence fishers (adul ts and children) have the great est threat for non-cancer health effects. This is because the average daily doses (for one or more pollutant) exceed the oral reference dose values in 49 to 56 percent of the immediate receiving waters, depending on the age group evaluated. Recreational fishers (adult or ch ild) have less of a thr eat, with average daily doses exceeding oral reference doses in 41 to 48 percent of the immediate receiving waters. These results suggest that fish downstream from discharges of th e evaluated wastestreams pose a non-cancer health threat to surrounding fish er populations. Given the modeling limitations described above, these results may underest imate these non-cancer health impacts.

Table 6-6 presents the number and percentage of immediate receiving waters where the average daily dose of one or more pollutant ex ceeds an oral referen ce dose for non-carcinogens.

6-9Section 6—Current Impacts from Steam Electric Power Generating Industry

Table 6-6. Number and Percentage of Immediate Receiving Waters

That Exceed Non-Cancer Oral Reference Dose Values at Baseline

Receptor Cohort Exposure

Duration (Years) Number of Immediate Receiving Waters where Estimated Exposure Doses Exceed Non- Cancer Reference Doses a

Number of

Rivers and

Streams Number of Lakes, Ponds,

and Reservoirs Total Receiving Waters b

Number Exceeding Percentage Exceeding

Child

recreational

fisher 1 to <2 years 1 82 18 100 48%
2 to <3 years 1 82 18 100 48%
3 to <6 years 3 80 18 98 47%
6 to <11 years 5 76 16 92 44%
11 to <16 years 5 72 14 86 41%
16 to <21 years 5 72 14 86 41%

Adult recreational fisher 49 72 14 86 41%

Child

subsistence

fisher 1 to <2 years 1 98 20 118 56%
2 to <3 years 1 98 20 118 56%
3 to <6 years 3 92 19 111 53%
6 to <11 years 5 87 19 106 51%
11 to <16 years 5 84 18 102 49%
16 to <21 years 5 84 18 102 49%

Adult subsistence fisher 49 85 18 103 49%

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i.

a – The EA encompasses a total of 222 immediate receivi ng waters and loadings fr om 195 steam electric power plants (some of which discharge to mu ltiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receiving waters (183 rivers and streams; 26 lakes, ponds, and reservoirs) and loadings from 18 8 steam electric power plants.

b – These values are the sum and percentage of rivers , streams, lakes, ponds, and reservoirs impacted.

According to the exposure doses calculated fr om the estimated fish tissue concentrations, methylmercury poses the greatest threat to caus e non-cancer health effects in humans from fish consumption. Mercury concentrations in fi sh pose a non-cancer threat to humans in approximately 52 percent of the immediate rece iving waters. Therefore, humans who consume fish inhabiting these waters are at risk for developing mercury-relate d effects, which could include neurological symptoms ( e.g. , affecting fine motor func tion, language skills, verbal memory) and cardiovascular disease if expos ed at high enough doses. In addition, thallium concentrations in fish pose a non-cancer thre at to humans in approximately 45 percent of immediate receiving waters. 45 Therefore, humans who consume thallium-contaminated fish inhabiting these waters are more likely to develop neurological symptoms ( e.g. , weakness, sleep disorders, muscular problems), alopecia ( i.e. , loss of hair from the head and body), and gastrointestinal effects ( e.g. , diarrhea and vomiting).

Table 6-7 presents the number and percenta ge of immediate receiving waters where average daily doses exceed an oral re ference dose for non-carcinogens by pollutant.

45 EPA used the chronic oral exposure value cited in U.S. EPA, 2010a for thallium chloride as the reference dose.

6-10Section 6—Current Impacts from Steam Electric Power Generating Industry

Table 6-7. Number and Percentage of Imme diate Receiving Waters That Exceed NonCancer Oral Reference Dose Values at Baseline by Pollutant

Pollutant Oral

Reference Dose

(mg/kg/day) Number of Immediate Receiving Waters where Estimated Exposure Doses Exceed Non- Cancer Reference Doses a

Number Exceeding Percentage Exceeding
Inorganic arsenic 0.0003 b 3 1%

Cadmium 0.001 b 32 15%

Chromium VI 0.003 b 0 0%
Copper 0.01 c 6 3%

Lead ID NC NC
Mercury (as methylmercury) 0.0001 b 109 52%
Nickel (soluble salts) 0.02 b 0 0%

Selenium 0.005 b 55 26%
Thallium (soluble salts) 0.00001 d 94 45%

Zinc 0.3 b 9 4%

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i.

Acronyms: NC (Not calculated); ID (Insufficient data ; there is no current reference dose for lead).

a – The EA encompasses a total of 222 immediate receivi ng waters and loadings fr om 195 steam electric power plants (some of which discharge to mu ltiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receiving waters (183 rivers and streams; 26 lakes, ponds, and reservoirs) and loadings from 18 8 steam electric power plants.

b – U.S. EPA, 2011c.

c – ATSDR, 2010a.

d – U.S. EPA, 2010a.

States, territories, and authorized tribes have the primary responsibility to protect residents from the health risks of consuming contaminated noncommercially caught fish. They inform the general population, incl uding recreational and subsistence fishers, typically by issuing advisories that notify the public that chemical contamination found in local fish may present a public health hazard.

EPA modeled concentrations in T4 fish tissu e and compared them to fish consumption advisory screening values to a ssess the potential for discharges of the evaluated wastestreams to

cause or contribute to fish advisories and pose a human hea lth hazard. Based on the modeling results, up to 48 percent of the immediate rece iving waters evaluated may contain fish with

contamination levels that coul d trigger advisories for recrea tional and subsistence fishers. Mercury and selenium are the pollutants most lik ely to exceed screening values. This result indicates that steam electric power plants are contributing to th e already widespread concentrations of mercury and sele nium in fish throughout the country.

Table 6-8 presents the number and percentage of immediate receiving waters where the

modeled T4 fish tissue concentrations exceed sc reening values used for fish advisories.

6-11Section 6—Current Impacts from Steam Electric Power Generating Industry

Table 6-8. Comparison of T4 Fish Tissue Concentrations at Baseline to Fish Advisory Screening Values

Pollutant Recreational Fishers Subsistence Fishers
Screening Value (ppm) a Number Exceeding b Percentage Exceeding Screening Value (ppm) a Number Exceeding b Percentage Exceeding
Inorganic arsenic (noncarcinogen) 1.2 0 0% 0.147 3 1%

Inorganic arsenic (carcinogen) 0.026 4 2% 0.00327 9 4%

Cadmium 4.0 8 4% 0.491 22 11%
Mercury (as methylmercury) 0.4 76 36% 0.049 101 48%

Selenium 20 22 11% 2.457 46 22%

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i.

Acronyms: ppm (parts per million).

a – Screening values are defined as concentrations of target analytes in fish or shellfish tissue that are of potential public health concern and that are used as threshold values against which levels of contamination in similar tissue

collected from the ambient environment can be compared. Exceedance of these sc reening values indicates that more intensive site-specific monitoring and/or evaluation of human health risk should be conducted [U.S. EPA, 2000a, Table 5-3].

b – The EA encompasses a total of 222 immediate receivi ng waters and loadings fr om 195 steam electric power plants (some of which discharge to mu ltiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receiving waters (183 rivers and streams; 26 lakes, ponds, and reservoirs) and loadings from 18 8 steam electric power plants.

6.3.2 Environmental Justice Analysis

As part of the EA, EPA evaluated whether the impacts from steam electric power plant wastewater discharges dispropor tionately impact minority groups. This environmental justice (EJ) analysis included looking at impacts based on race or Hispanic origin. Table 6-9 presents the number and percentage of immediate recei ving waters where the estimated LECR for the human receptor exceeds the selected threshold, 1-in-a-million cancer risk for arsenic. Inorganic

arsenic concentrations in fish result in an es timated cancer risk greater than 1-in-a-million to adult subsistence, minority fishers in approximately 12 to 15 per cent of the immediate receiving waters (26 to 32 out of 209) and to adult recreati onal fishers in approximately 7 to 9 percent of the immediate receiving waters (14 to 19 out of 209). Cancer risks for the child cohorts are lower. The estimated cancer risk among adult minor ity fishers is higher than the risk among adult nonminority fishers (especi ally among the recreational fisher population).

6-12Section 6—Current Impacts from Steam Electric Power Generating Industry

Table 6-9. Number and Percentage of Immedi ate Receiving Waters That Exceed Human Health Evaluation Criteria (Lifetime Exce ss Cancer Risk) for Inorganic Arsenic at Baseline, by Race or Hispanic Origin

Receptor Race or Hispanic Origin Number of Immediate Receiving Waters Where

Lifetime Excess Cancer Ri sk Exceeds 1-in-a-Million a,b

1 to <2

years 2 to <3

years 3 to <6

years 6 to <11

years 11 to <16

years 16 to <21

years Adult

Recreational Non-Hispanic White 3 3 4 6 6 6 1 2

Non-His panic Black 3 3 5 6 6 6 1 4

Mexican-Am erican 4 4 6 6 6 6 1 8

Othe r Hispanic 4 4 6 6 6 6 1 6

Ot her, including Multiple Races 4 4 6 6 6 6 1 9

Sub sistence Non-Hispanic White 4 4 6 7 7 7 2 5

Non-His panic Black 5 5 6 7 7 7 2 6

Mexican-Am erican 6 6 6 8 8 8 2 8

Othe r Hispanic 6 6 6 7 7 7 2 8

Ot her, including Multiple Races 6 6 7 10 10 10 32

Sou rces: ERG, 2015d; ERG, 2015h; ERG, 2015i.

a – The EA encompasses a total of 222 immediate receivi ng waters and loadings fr om 195 steam electric power plants (some of which discharge to mu ltiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receiving waters (183 rivers and streams; 26 lakes, ponds, and reservoirs) and loadings from 18 8 steam electric power plants.

b – Inorganic arsenic cancer slope factor of 1.5 per milligrams per kilogram (mg/kg) per day.

Based on the estimated fish tissue concentra tions and average daily pollutant doses by cohort, subsistence fishers (adul ts and children) have the great est threat for non-cancer health effects. This is because the average daily doses (for one or more pollutant) exceed the oral reference dose values in 49 to 56 percent of the immediate receiving waters, depending on the age group evaluated. Recreational fishers (adult or ch ild) have less of a thr eat, with average daily doses exceeding oral reference doses in 41 to 48 percent of the immediate receiving waters. These results suggest that fish downstream from discharges of th e evaluated wastestreams pose a non-cancer health threat to surrounding fish er populations. Given the modeling limitations described above, these results may underest imate these non-cancer health impacts.

Table 6-10 presents the number and percentage of immediat e receiving waters where the average daily dose of one or more pollutant ex ceeds an oral referen ce dose for non-carcinogens.

6-13Section 6—Current Impacts from Steam Electric Power Generating IndustryTable 6-10. Number and Percentage of Immediate Receiving WatersThat Exceed Non-Cancer Oral Reference Dose Values atBaseline, by Race or Hispanic OriginReceptorRace or Hispanic OriginNumber of Immediate Receiving Waters Where Pollutant Exceeds a Non-Cancer Reference DoseaInorganicArsenicCadmiumCopperMercurybSeleniumThalliumcZincRecreational,Child FisherNon-Hispanic White0 (0%)10 (5%)3 (1%)81 (39%)32 (15%)55 (26%)4 (2%)Non-Hispanic Black0 (0%)12 (6%)4 (2%)84 (40%)33 (16%)58 (28%)4 (2%)Mexican-American0 (0%)14 (7%)4 (2%)86 (41%)33 (16%)63 (30%)4 (2%)Other Hispanic0 (0%)13 (6%)4 (2%)84 (40%)33 (16%)60 (29%)4 (2%)Other, including Multiple Races0 (0%)14 (7%)4 (2%)88 (42%)34 (16%)63 (30%)4 (2%)Subsistence,Child FisherNon-Hispanic White3 (1%)21 (10%)5 (2%)98 (47%)42 (20%)76 (36%)5 (2%)Non-Hispanic Black3 (1%)22 (11%)5 (2%)98 (47%)43 (21%)78 (37%)5 (2%)Mexican-American3 (1%)25 (12%)6 (3%)100 (48%)46 (22%)79 (38%)6 (3%)Other Hispanic3 (1%)25 (12%)5 (2%)100 (48%)46 (22%)79 (38%)6 (3%)Other, including Multiple Races3 (1%)29 (14%)6 (3%)104 (50%)48 (23%)89 (43%)6 (3%)Recreational,Adult FisherNon-Hispanic White0 (0%)10 (5%)3 (1%)81 (39%)32 (15%)55 (26%)4 (2%)Non-Hispanic Black0 (0%)12 (6%)4 (2%)84 (40%)33 (16%)58 (28%)4 (2%)Mexican-American0 (0%)14 (7%)4 (2%)86 (41%)33 (16%)63 (30%)4 (2%)Other Hispanic0 (0%)13 (6%)4 (2%)84 (40%)33 (16%)60 (29%)4 (2%)Other, including Multiple Races0 (0%)14 (7%)4 (2%)88 (42%)34 (16%)63 (30%)4 (2%)Subsistence,Adult FisherNon-Hispanic White3 (1%)21 (10%)5 (2%)98 (47%)42 (20%)76 (36%)5 (2%)Non-Hispanic Black3 (1%)22 (11%)5 (2%)98 (47%)43 (21%)78 (37%)5 (2%)Mexican-American3 (1%)25 (12%)6 (3%)100 (48%)46 (22%)79 (38%)6 (3%)Other Hispanic3 (1%)25 (12%)5 (2%)100 (48%)46 (22%)79 (38%)6 (3%)Other, including Multiple Races3 (1%)29 (14%)6 (3%)104 (50%)48 (23%)89 (43%)6 (3%)Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i.a – The EA encompasses a total of 222 immediate receiving waters and loadings from 195 steam electric power plants (some of which discharge to multiplereceiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receivingwaters (183 rivers andstreams; 26 lakes, ponds, and reservoirs) andloadings from 188 steam electric power plants.b – Mercury, as methylmercury.c – Reference dose based on thallium (soluble salts).6-14Section 7—Environmental Improvements Under the Final Rule



## SECTION 7
ENVIRONMENTAL IMPROVEMENTS UNDER
THE FINAL RULE

In Section 6, EPA presented the environmen tal impacts to surface water quality, wildlife,

and human health estimated with EPA’s immedi ate receiving water (IRW) model and ecological risk model resulting from baseline discharges of the evaluated wastestreams. Under the final steam electric effluent limitations guidelines a nd standards (ELGs), EPA evaluated six regulatory options (Options A, B, C, D, E, and F). As pa rt of this quantitative environmental assessment (EA), EPA evaluated the environmental improvement s associated with the reduction in pollutant loadings from the evaluated wastestreams ( i.e. , flue gas desulfurizati on (FGD) wastewater, fly ash transport water, bottom ash transport water, and combustion residual leachate) under Options A, B, C, D, and E, described in Table 7-1. 46

In the remainder of this document, EPA presents the results only for Options A through E for existing sources. During development of the fina l rule, EPA decided not to base the final rule on Option F for existing sources due primarily to the high cost of that Option, particularly in light of the costs associated with other rule makings expected to impact the steam electric industry (see Section VIII.C.1 of the preamble). As a result, EPA chose not to conduct particular analyses for Option F to the same extent that it did for some of the other options considered. Section 8 of the Technical Development Document (TDD) (EPA-821-R-15-007) details the technology options for all wastes treams evaluated under each regulat ory option for the final rule. As described in Section 8 of the TDD, EPA se lected Option D as the technology basis for the best available technology economically achievab le (BAT) and for pretreatment standards for existing sources (PSES). See Section 12 of the TDD for further information on the limitations and standards of the final rule. This section pr esents the improvements to surface water quality, wildlife, and human health under the final rule as quantified by EPA’s IRW model and ecological risk model.

Based on the quantitative and qualitative analys es performed for the EA, EPA estimated that a variety of environmental improvements would result from the pollu tant loading removals associated with the regulatory options. In particular, the EA evaluated the following: 1) improvements in water quality, 2) reduction in thre ats to wildlife, 3) reduction in human health cancer risks, 4) reduction in threats for non- cancer human health e ffects, and 5) other unquantified environmental improvements. Tabl e 7-2 lists the quantified and unquantified environmental improvements estimated to result from the final rule’s regulatory options and designates which quantified improvements were mone tized in the benefits analysis described in

the Benefits and Cost An alysis (EPA-821-R-15-005).

46 In addition to the wastestreams listed in Table 7-1, EP A evaluated technology options associated with flue gas mercury control (FGMC) wastewater, ga sification wastewater, and nonchemical metal cleaning wastes as part of the regulatory options. However, no plants currently disc harge FGMC wastewater, all existing gasification plants are operating the technology used as the basis for the regulatory option, and EPA will continue to reserve BAT/NSPS/PSES/PSNS for nonchemical metal cleaning wastes, as previously established regulations do. Therefore, EPA estimated zero complia nce costs and zero pollutant reductions associated with these wastestreams

and did not include these three wastestreams in the EA.

7-1Section 7—Environmental Improvements Under the Final Rule

Table 7-1. Regulatory Options for the Wastestreams Evaluated in the EA

Evaluated

Wastestream a Option

A Option

B Option

C Option

D Option

E

FGD wastewater Chemical precipitation Chemical precipitation + biological

treatment Chemical precipitation + biological

treatment Chemical precipitation + biological

treatment Chemical precipitation + biological

treatment Fly ash transport

water Dry handling Dry handling Dry handling Dry handling Dry handling

Bottom ash

transport water Impoundment (equal to BPT) Impoundment (equal to BPT) Dry handling/ closed loop (for units >400 MW); impoundment (equal to BPT) for

units ≤ 400 MW Dry handling/ closed loop Dry handling/ closed loop

Combustion

residual leachate Impoundment (equal to BPT) Impoundment (equal to BPT) Impoundment (equal to BPT) Impoundment (equal to BPT) Chemical precipitation

Acronyms: BPT (Best practicable control techno logy currently available); MW (Megawatt).

a – The evaluated wastestreams and regulatory options listed in the table are a subset of regulatory options for the

steam electric ELGs. See Section 8 of the TDD for the full list of regulatory options.

7-2Section 7—Environmental Improvements Under the Final Rule

Table 7-2. Description of Environmental Improvements

Associated with the Final Rule

Assessment

Category Description of Environmental Improvement Improvement Quantified Improvement

Monetized More Information

Water Quality Reduced number of immediate receiving waters exceeding an acute or chronic aquatic life NRWQC  Section 7.2

Section 7.3

Reduced number of immediate receiving waters exceeding a human health NRWQC  Section 7.2

Section 7.3

Reduced number of immediate receiving waters exceeding MCLs  Section 7.2

Section 7.3
Increased aesthetic benefits, such as enhancement of adjoining site amenities ( e.g. , residing, working, traveling, and owning property near water)   Benefits and Cost Analysis a

Improved water-based recreation, including swimming, fishing, boating, and near-water activities from improved water quality   Benefits and Cost Analysis a

Improved quality of source water used for drinking, irrigation, and

industrial use Qualitative Discussion (Benefits and Cost Analysis)
Increased property values from water quality improvements Qualitative Discussion (Benefits and Cost Analysis)
Increased tourism and participation in

water-based recreation Qualitative Discussion (Benefits and Cost Analysis)
Pollutant removals to impaired

waters  Section 7.4

Pollutant removals to the Great Lakes and Chesapeake Bay  Section 7. 5

Pol lutant removals of toxic contaminants, chlorides, and TDS to receiving waters  Section 7.1

Nutrient removals to receiving waters

  Section 7.1 and

Benefits and Cost Analysis a

Reduced risk of surface impoundment failures   Benefits and Cost Analysis a

Reduced sediment contamination Qualitative Discussion (Benefits and Cost Analysis)
Increased availability of ground

water resources   Benefits and Cost Analysis a

7-3Section 7—Environmental Improvements Under the Final Rule

Table 7-2. Description of Environmental Improvements

Associated with the Final Rule

Assessment

Category Description of Environmental Improvement Improvement Quantified Improvement

Monetized More Information

Wildlife Reduced exposure among minks to pollutants that bioaccumulate in fish  Section 7.2

Section 7.3
Reduced exposure among eagles to pollutants that bioaccumulate in fish  Section 7.2

Section 7.3

Reduced selenium concentrations in

fish and waterfowl and associated reduced reproductive risk  Section 7.2

Section 7.3

Improved aquatic and wildlife habitat and improved protection of threatened and endangered species   Section 7.4 and

Benefits and Cost Analysis a
Improved commercial fisheries yield due to aquatic habitat improvement Qualitative Discussion (Benefits and Cost Analysis)
Enhanced existence, option, and bequest values from improved ecosystem health   Benefits and Cost Analysis a

Reduced risks to aquatic life from exposure to steam electric pollutants  Benefits and Cost Analysis a
Reduced exposure to pollutants

associated with the wastestreams of concern in surface impoundments

that serve as attractive nuisances Qualitative Discussion (Section 7.7)

Human

Health Reduced exposure to non-cancer pollutants for recreational and

subsistence fishers  Section 7.2

Section 7.3

Benefits and Cost Analysis a

Reduced cancer risk in recreational

and subsistence fishers   Section 7.2

Section 7.3

Benefits and Cost Analysis a

Reduced incidences of cardiovascular

disease from reduced arsenic and lead

exposure   Benefits and Cost Analysis a

Reduced adverse health effects from reduced in-utero mercury exposure from maternal fish consumption   Benefits and Cost Analysis a

Reduced IQ loss and specialized

education from reduced childhood exposure to lead from fish consumption   Benefits and Cost Analysis a

Reduced adult mortality from air pollutant emissions   Benefits and Cost Analysis a
Avoided climate change impacts

from carbon dioxide emissions   Benefits and Cost Analysis a
Reduced exposure to pollutants from

recreational water uses Qualitative Discussion (Benefits and Cost Analysis)

7-4Section 7—Environmental Improvements Under the Final Rule

Table 7-2. Description of Environmental Improvements

Associated with the Final Rule

Assessment

Category Description of Environmental Improvement Improvement Quantified Improvement

Monetized More Information
Reduced injury associated with impoundment failures Qualitative Discussion (Benefits and Cost Analysis)

Reduced number of immediate receiving waters exceeding fish consumption advisory screening

values  Section 7.4

Acronyms: MCL (maximum contaminant level); NRWQC (National Recommended Wate r Quality Criteria); TDS (total dissolved solids).

a – The Benefits and Cost Analysis quantifies and monetizes individual environmental improvements for Options A, B, C, D, and E. See Benefits an d Cost Analysis for more detail.

7.1 P OLLUTANT R EMOVALS U NDER THE R EGULATORY O PTIO NS

EPA estimates that the regulatory options w ould significantly reduce pollutant loadings to receiving waters for the 10 pollutants modele d in the EA and for other pollutants that can adversely affect surface waters, such as boron, ma nganese, nutrients, chlorides, and TDS. Table 7-3 and Table 7-4 present the pollutant removals under the regulatory options for the evaluated

wastestreams.

Under the final rule (Option D), EPA estimat es that pollutant loadings from existing sources will decrease by over 95 percent for copper, lead, mercury, nickel, selenium, thallium, and zinc and over 90 percent for arsenic and cadm ium. In turn, these pollutant removals will reduce the negative impacts on th e environment as well as th e potential exposure of these contaminants to ecological and human receptors . The selenium removals will significantly improve the water quality around the steam elect ric power plant discha rge locations. Mercury removals will improve human health as mercury has been linked to decreased IQs in children whose pregnant mothers have been e xposed to mercury by consuming fish.

Manganese and boron, while not ge nerally considered toxic at levels seen in the aquatic environment, have the highest and third highest toxic-weight ed pound equivalents (TWPEs), respectively, under baseline conditions for polluta nts evaluated in the EA (see Section 3.2). As discussed in Section 3, boron can negatively impact fish and duc ks and manganese can be toxic to humans at high levels. Under the final rule, the pollutant loadings for manganese and boron will decrease by 80 and 15 percent, respectively.

As discussed in Section 3, nutrients ( i.e. , nitrogen and phosphorus) in excess quantities can adversely affect surface waters by causi ng oxygen-consuming harmful algae blooms and creating “dead zones” where fish and shellfis h cannot survive. Under the final rule, EPA calculated that nitrogen loadings will decrease by 16.8 million pounds per year (99 percent) and phosphorus loadings will decrease by 174,000 pounds per year (81 percent). The nutrient removals will improve hypoxic areas ( i.e. , low-oxygen surface waters) such as the Chesapeake Bay and the Gulf of Mexico (via reduced loadings to th e Mississippi River Basin).

7-5Section 7—Environmental Improvements Under the Final Rule

Excess chlorides levels in wastewater discharg es can be harmful to animals and plants in nonmarine surface waters and can disrupt ecosys tem structure. Under the final rule, annual chlorides loadings to surface waters will decrease by 21.8 million pounds (two percent).

The pollutant parameter, TDS, comprises diss olved solids such as chloride and metals. Under the final rule, EPA calculated that annual TD S loadings to surface waters will decrease by more than 1.32 billion pounds (31 pe rcent). This decrease is at least partially due to the reduction in total and dissolved metals discharged to receiving waters. 47

47 EPA’s estimated TDS removals do not account for additional removals that may be achieved as a result of steam electric power plants opting to particip ate in the voluntary incentives program, in which they would be subject to effluent limitations based on evaporation technology, including for TDS.

7-6Section 7—Environmental Improvements Under the Final Rule

Table 7-3. Steam Electric Power Generating Industry Pollutant Removals for Metals, Bioaccumulative Pollutants, Nutrients, Chlo rides, and TDS Under Regulatory Options

Pollutant Pollutant Removals, lbs/yr (Percent Reduction) a

Option A Option B Option C Option D Option E

Arsenic 15,700
(53%) 15,700
(53%) 23,200
(78%) 27,900
(94%) 28,500
(96%)

Boron 4,230,000
(14%) 4,230,000
(14%) 4,480,000
(14%) 4,630,000
(15%) 4,630,000
(15%)

Cadmium 9,020
(68%) 9,020
(68%) 11,200
(84%) 12,500
(94%) 12,600
(95%)

Chromium VI 131
(84%) 131
(84%) 147
(95%) 156
(>99%) 156
(>99%)

Copper 14,300
(46%) 14,300
(46%) 24,300
(78%) 30,500
(98%) 30,600
(98%)

Lead 7,670
(39%) 7,670
(39%) 14,800
(75%) 19,200
(98%) 19,200
(98%)

Manganese 5,120,000
(68%) 5,120,000
(68%) 5,650,000
(75%) 5,990,000
(80%) 5,990,000
(80%)

Mercury 858
(58%) 868
(58%) 1,230
(83%) 1,450
(97%) 1,470
(99%)

Nickel 62,300
(52%) 62,600
(52%) 96,200
(80%) 117,000
(98%) 118,000
(99%)

Selenium 29,300
(21%) 130,000
(93%) 134,000
(96%) 136,000
(97%) 136,000
(97%)

Thallium 7,180
(11%) 7,180
(11%) 40,900
(64%) 62,300
(98%) 62,300
(98%)

Zinc 120,000
(69%) 120,000
(69%) 148,000
(85%) 166,000
(95%) 169,000
(97%)

Nitrogen, total b 1,980,000
(12%) 12,300,000
(73%) 15,100,000
(89%) 16,800,000
(99%) 16,800,000
(99%)

Phosphorus, total 43,100
(20%) 43,100
(20%) 123,000
(57%) 174,000
(81%) 174,000
(81%)

Chlorides 4,160,000
(<1%) 4,160,000
(<1%) 14,900,000
(2%) 21,800,000
(2%) 21,800,000
(2%)

TDS 849,000,000
(20%) 849,000,000
(20%) 1,130,000,000
(27%) 1,320,000,000
(31%) 1,320,000,000
(31%)

Source: ERG, 2015a.
Acronyms: TDS (Total Dissolved Solids); lbs/yr (pounds per year).
Note: Pollutant removals are rounded to three significant figures.
a – .>0 to 15 percent reduction; 16 to 30 percent reduction; 31 to 45 percent reduction; 46 to 60 percent reduction ; >60 percent reduction

. b – Total nitrogen loadings are the sum of total Kj eldahl nitrogen and nitrate/nitrite as N loadin gs.

7-7Section 7—Environmental Improvements Under the Final Rule

Table 7-4. Steam Electric Power Generati ng Industry TWPE Removals for Metals, Bioaccumulative Pollutants, Nutrients, Chlo rides, and TDS Under Regulatory Options

Pollutant Pollutant Removals, TWPE/year (Percent Reduction) a

Option A Option B Option C Option D Option E

Arsenic 54,600
(53%) 54,600
(53%) 80,400
(78%) 96,700
(94%) 98,900
(96%)

Boron 35,300
(13%) 35,300
(13%) 37,300
(14%) 38,600
(15%) 38,600
(15%)

Cadmium 205,000
(68%) 205,000
(68%) 254,000
(84%) 285,000
(94%) 287,000
(95%)

Chromium VI 6\7.5
(84%) 67.5
(84%) 76.1
(94%) 80.4
(>99%) 80.4
(>99%)

Copper 8,890
(46%) 8,890
(46%) 15,100
(78%) 19,000
(98%) 19,100
(98%)

Lead 17,200
(39%) 17,200
(39%) 33,100
(75%) 43,100
(98%) 43,100
(98%)

Manganese 526,000
(68%) 526,000
(68%) 580,000
(75%) 615,000
(80%) 615,000
(80%)

Mercury 94,400
(58%) 95,500
(58%) 136,000
(83%) 160,000
(97%) 162,000
(99%)

Nickel 6,790
(52%) 6,820
(52%) 10,500
(80%) 12,800
(98%) 12,900
(99%)

Selenium 32,900
(21%) 146,000
(93%) 150,000
(96%) 152,000
(97%) 152,000
(97%)

Thallium 20,500
(11%) 20,500
(11%) 117,000
(64%) 178,000
(98%) 178,000
(98%)

Zinc 5,650
(69%) 5,650
(69%) 6,950
(85%) 7,770
(95%) 7,940
(97%)
Nitrogen, total N/A N/A N/A N/A N/A

Pho sphorus, total N/A N/A N/A N/A N/A

Ch lorides 101
(<1%) 101
(<1%) 364
(2%) 531
(2%) 531
(2%)

TDS N/A N/A N/A N/A N/A

Source: ER G, 2015a. Acronyms: TDS (Total Dissolved Solids); TWPE (Toxic Weighted Pound Equivalents). Note: Pollutant removals are rounded to three significant figures. N/A – The TWPE/year is not provided for total nitr ogen, total phosphorus, and TDS because EPA has not established a toxic weighting factor (TWF) for these pollutants.
a – >0 to 15 percent reduction; 16 to 30 percent reduction; 31 to 45 percent reduction; 46 to 60 percent reduction ; >60 percent reduction

.

7-8Section 7—Environmental Improvements Under the Final Rule

7.2 K EY E NVIRONMENTAL I MPROVEMENTS

As part of this EA, EPA conducted mo deling of the expected environmental improvements under Options A through E. EPA estimates the environmental improvements under Option F, which were not modeled, to be in crementally greater than those under Option E based on the pollutant reductions calculated.

Table 7-5 summarizes the key environmen tal improvements within the immediate receiving waters due to the pol lutant removals unde r the final rule (O ption D) and other evaluated regulatory options. The numbers of immediate receiving waters with water quality, wildlife, and human health exceedances would:

 Decrease under Options A and B by no more than 33 percent, with most exceedances being reduced by less than 15 percent.

 Decrease under Option C by 17 to 56 percent, with most exceedances being reduced by less than 40 percent.

 Decrease under Option D by 45 to 83 percent, with most exceedances being reduced by at least 56 percent.

 Decrease under Option E by 51 to 84 percent, with most exceedances being reduced by at least 61 percent.

The final rule (Option D) will substantiall y improve water qualit y, wildlife, and human health. Under the final rule, EPA estimates that:

 Receiving water exceedances of the NRWQC will decrease by 45 to 67 percent.

 Receiving water exceedances of the MCL benc hmarks will decrease by 83 percent.

 The number of receiving waters with fish tissue concentrations exceeding the no effect hazard concentration (NEHC) for se lenium for eagles and minks will decrease by 63 and 62 percent, respectively.

 Human exposures via fish consumption to pollutants with the potential to cause noncancer health effects will decrease by up to 56 percent.

 Human exposures to pollutants that presen t a cancer risk will decrease by up to 75

percent.

Results for the final rule are discussed in further detail in the sections following Table

7-5.

7.2.1 Improvements in Water Quality Under the Final Rule

EPA estimates that pollutant removals to surface waters associated with the final rule will significantly improve water quality by reduci ng exceedances of the NRWQC and MCLs by up to 83 percent. The largest reductions in NRWQC exceed ances are attributed to reduced loadings of cadmium, selenium, arsenic, and thallium. Due to the substantial pollutant removals, EPA projects that aquatic organisms will be less susceptible to chronic impacts such as:

7-9Section 7—Environmental Improvements Under the Final Rule

 Skeletal malformations;

 Organ damage;

 Developmental abnormalities;

 Behavioral impairments;

 Reproductive failure;

 Metabolic failure;

 Neurological effects;

 Gastrointestinal effects; and

 Fish kills. 48

EPA estimates that up to 45 percent of the 209 evaluate d immediate receiving waters currently exceed NRWQC for the protection of human health, primarily due to arsenic and

thallium. EPA estimates that these arsenic an d thallium removals will lower the number of immediate receiving waters that exceed NRWQC designed to protec t public health by 45 to 50 percent. By reducing MCL exceedances by 83 percent, the final rule will improve the quality of source water available to drinking water treatment plants downstream from steam electric power plants.

In addition to reducing NRWQC and MCL ex ceedances, the final rule will quantifiably improve overall water quality – in the immediate receiving waters and downstream from steam electric power plants. EPA calculates that, on aver age, receiving water c oncentrations of the 10 toxic, bioaccumulative pollutants evaluate d in the EA will decrease by 57 percent.

48 Impacts documented in ATSDR, 2008a; Coughlan and Velte, 1989; Lemly, 1985b; Nagle et al ., 2001; NRC, 2006; Rowe et al ., 2002; U.S. EPA, 2009a; and U.S. EPA, 2011f.

7-10Section 7—Environmental Improvements Under the Final RuleTable 7-5. Key Environmental Improvements Under the Regulatory OptionsEvaluation BenchmarkModeled Immediate ReceivingWaters Exceeding BenchmarkUnder Baseline ConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the RegulatoryOptionsbNumberPercentageOption AOption BOption COption DOption EWater Quality ResultsFreshwater Acute NRWQC94%6(33%)6(33%)6(33%)3(67%)2(78%)Freshwater Chronic NRWQC3517%34(3%)27(23%)21(40%)17(51%)17(51%)Human Health Water and Organism NRWQC9445%90(4%)90(4%)69(27%)52(45%)43(54%)Human Health Organism Only NRWQC6632%62(6%)62(6%)46(30%)33(50%)26(61%)Drinking Water MCL3617%34(6%)33(8%)16(56%)6(83%)6(83%)Wildlife ResultsFish Ingestion NEHC for Minks5828%57(2%)51(12%)32(45%)22(62%)21(64%)Fish Ingestion NEHC for Eagles7134%65(8%)61(14%)44(38%)26(63%)23(68%)Human Health Results—Non-CancerNon-Cancer Reference Dose for Child(recreational)1004892(8%)90(10%)68(32%)47(53%)38(62%)Non-Cancer Reference Dose for Adult(recreational)8641%77(10%)74(14%)56(35%)38(56%)28(67%)Non-Cancer Reference Dose for Child(subsistence)11856%107(9%)104(12%)79(33%)52(56%)46(61%)Non-Cancer Reference Dose for Adult(subsistence)10349%94(9%)93(10%)71(31%)49(52%)39(62%)7-11Section 7—Environmental Improvements Under the Final RuleTable 7-5. Key Environmental Improvements Under the Regulatory OptionsEvaluation BenchmarkModeled Immediate ReceivingWaters Exceeding BenchmarkUnder Baseline ConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the RegulatoryOptionsbNumberPercentageOption AOption BOption COption DOption EHuman Health Results—CancerArsenic Cancer Risk for Child (recreational)63%5(17%)5(17%)5(17%)2(67%)2(67%)Arsenic Cancer Risk for Adult (recreational)126%9(25%)9(25%)6(50%)3(75%)2(83%)Arsenic Cancer Risk forChild (subsistence)84%7(13%)7(13%)6(25%)3(63%)2(75%)Arsenic Cancer Risk for Adult (subsistence)2512%23(8%)23(8%)15(40%)11(56%)4(84%)Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (maximum contaminant level); NEHC (No Effect Hazard Concentration); NRWQC (National Recommended Water Quality Criteria).a – The EA encompasses a total of 222 immediate receiving waters and loadings from 195 steam electric power plants (some of which discharge to multiplereceiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receivingwaters (183 rivers andstreams; 26 lakes, ponds, and reservoirs) andloadings from 188 steam electric power plants.b –>0 to 15 percent reduction; 16 to 30 percent reduction; 31 to 45 percent reduction;46 to 60 percent reduction;>60 percent reduction.7-12Section 7—Environmental Improvements Under the Final Rule

7.2.2 Reduced Threat to Wildlif e Under the Final Rule

In the EA, EPA evaluated multiple threats to wildlife, including impacts to wildlife indicator species by consuming contaminated fish; impacts to fish and waterfowl due to dietary exposure to selenium; and exposure of benthic a quatic organisms to contaminated sediments. The combination of lethal and sublethal effects ( e.g. , changes to morphology, behavior, and metabolism) of exposure to steam electric power plant wastewater can cause cascading effects through the food web.

As discussed in Section 7.2.1, the number of immediate receivi ng waters that can potentially pose an acute or chronic threat to wildlife will decrease under the final rule, improving wildlife populations and communities surrounding steam electric power plants ( e.g. , reduced impacts to population density and species diversity as discussed in Section 3). EPA estimates that average fish tissue concentrations of the pollutants evaluated in the EA will decrease by an average of 57 percent. EPA projects that these lower pollutant concentrations will significantly improve the health of fish populat ions and the quality of fish available for consumption by both humans and wildlife near steam electric power plants.

Based on the threats to minks and eagles fr om consuming fish contaminated by steam electric power plant wastewater, pollutants can bi oaccumulate and impact higher order species in the food chain. Under the final rule, EPA estimates that exceedances of the NEHC for eagles and minks will decrease by approximately 70 percent. See Section 7.3.3 for discussion of the reduced risk of adverse reproductive e ffects among aquatic wildlife (fis h and mallards) resulting from dietary exposure to selenium.

EPA estimates that pollutant removals to surface waters associated with the final rule will decrease the exposure of aquatic organisms to pollutants in the sediment, as shown in Table 7-6. As discussed in Section 6.2.3, benthic organisms are at risk primarily due to exposure to mercury, nickel, and cadmium. Under the final rule , the number of immediate receiving waters with pollutant concentration in the sediment above chemical stressor concentration limits (CSCL) will decrease by over 60 percent.

7-13Section 7—Environmental Improvements Under the Final RuleTable 7-6. Number of Immediate Receiving Waters with Sediment Pollutant Concentrations Exceeding CSCLs forSediment Biota Under the Regulatory OptionsPollutantModeled ImmediateReceiving WatersExceeding CSCLs UnderBaseline ConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the Regulatory OptionsbOption AOption BOption COption DOption EArsenic7(3%)6(14%)6(14%)6(14%)3(57%)2(71%)Cadmium27(13%)21(22%)21(22%)14(48%)10(63%)8(70%)Chromium VIc0(0%)0(N/A)0(N/A)0(N/A)0(N/A)0(N/A)Copper7(3%)5(29%)5(29%)5(29%)2(71%)2(71%)Lead6(3%)4(33%)4(33%)4(33%)1(83%)1(83%)Mercury49(23%)45(8%)44(10%)26(47%)19(61%)7(86%)Nickel34(16%)28(18%)28(18%)16(53%)11(68%)4(88%)SeleniumNCNCNCNCNCNCThalliumNCNCNCNCNCNCZinc15(7%)9(40%)9(40%)9(40%)6(60%)2(87%)Total49(23%)45(8%)44(10%)27(45%)20(59%)8(84%)Source: ERG, 2015d;ERG, 2015h; ERG, 2015i.Acronyms: CSCL (Chemical stressor concentration limit); N/A (Not Applicable, no exceedances at baseline conditions to compare option results); NC (Notcalculated; no benchmark for comparison).a – The EA encompasses a total of 222 immediate receiving waters and loadings from 195 steam electric power plants (some of which discharge to multiplereceiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receivingwaters (183 rivers andstreams; 26 lakes, ponds, and reservoirs) andloadings from 188 steam electric power plants.b – >0 to 15 percent reduction; 16 to 30 percent reduction; 31 to 45 percent reduction;46 to 60 percent reduction;>60 percent reduction.c – EPA used the total chromium benchmark for this analysis.7-14Section 7—Environmental Improvements Under the Final Rule

7.2.3 Reduced Human Health Cancer Risk Under the Final Rule

Under baseline conditions, EP A estimates that 25 immediate receiving waters (12 percent) could contain fish contaminated with in organic arsenic that pres ent cancer risks above

the 1-in-a-million threshol d for the most sensitive, national-s cale cohort. EPA cal culates that the number of immediate receiving waters whose fish exceed this cancer risk threshold will decrease by at least 56 percent for all nationa l-scale cohorts under the final rule.

7.2.4 Reduced Threat of Non-Cancer Human Health Effects Under the Final Rule

Chronic exposure to toxic, bi oaccumulative pollutants in steam electric power plant wastewater can potentially compromise neurological and developmental functions and affect the circulatory, respiratory, and digestive systems of exposed populations. EPA estimates that the number of immediate receiving waters whose fish pose non-cancer health risks will decrease by at least 52 percent for all natio nal-scale cohorts under the final rule. As discussed in Section 7.2.2, EPA found that the pollutant concentrations in fish tissue will decrease, improving the quality of fish available to recreational and subsistence fish ers and subsequently loweringexposures to toxic, bioaccumulative pollutants and the potential for humans to develop noncancer health effects ( e.g. , nausea, abdominal pain, sleep di sorders, muscular problems, and cardiovascular disease).

The pollutants that cause the potential fo r non-cancer health effects are selenium, cadmium, mercury (as methylmercury), and, to a le sser degree, thallium. EPA calculates that the

final rule will decrease the numbe r of immediate receiving waters with fish that, if consumed,

would exceed the reference doses for th ese pollutants, by the following amounts:

 Selenium: decrease by at least 51 pe rcent for all nati onal-scale cohorts.

 Cadmium: decrease by at least 53 pe rcent for all national-scale cohorts.

 Methylmercury: decrease by at least 52 pe rcent for all national-scale cohorts.

 Thallium: decrease by at least 62 pe rcent for all national-scale cohorts.

Although the EA did not direct ly assess the potential non-can cer health effects posed by lead, 49 the final rule will lower th e total annual loadings of lead to the environment by 19,000 pounds (98 percent), thus reducing the potential threat of hypertensi on, coronary heart disease, and impaired cognitive function in exposed populat ions. For children in particular, lead exposure can cause additional negative impacts, such as hyperactivity, behavi oral and attention difficulties, delayed mental development, and motor and perceptual skill deficits. The benefits to

adults and children from the reduced lead discha rges are discussed in the Benefits and Cost Analysis.

7.2.5 Reduced Human Health Risk for Environmental Justice Analysis

As discussed in Section 6.3.2, EPA evaluated th e impacts that steam electric power plant discharges have on environmental justice (EJ) c ohorts in addition to the national-scale cohorts. Under baseline conditions, EPA estimates that 32 immediate receiving wate rs (15 percent) could

49 Currently, there is no reference dose for lead—there is no safe level for ingestion of lead (see EPA’s Integrated Risk Information System (IRIS) website: http://www.epa.gov/IRIS/).

7-15Section 7—Environmental Improvements Under the Final Rule

contain fish contaminated with inorganic arsenic that presen t cancer risks above the 1-in-amillion threshold for the most sensitive minorit y cohort. EPA estimates that the number of immediate receiving waters whose fish exceed this cancer risk threshold will decrease by at least 46 percent for the average recreational fisher mi nority cohort and at least 51 percent for the average subsistence fisher minor ity cohort under the final rule. 50 These improvements are similar to those for non-minority recreation al and subsistence fisher cohor ts (at least 33 and 50 percent, respectively) under the final rule.

EPA estimates that the number of immedi ate receiving waters whose fish pose noncancer health risks will decrease by 56 percent for all recreationa l fisher minority cohorts and 53 percent for all subsiste nce fisher minority cohorts under the final rule. These improvements are similar to those for non-minority recreational and subsistence fisher cohorts (56 and 52 percent, respectively) under the final rule. The pollutants that cause the potential for non-cancer health effects are selenium, cadmium, mercury (as methyl mercury), and, to a lesser degree, thallium.

7.3 P OLLUTANT -S PECIFIC I MPROVEMENTS

EPA identified several key pollutants ( i.e. , arsenic, mercury, selenium, cadmium, and thallium) whose pollutant removals would prim arily be responsible for the improvements in water quality, wildlife, and human health attributed to the final rule. This section highlights the environmental improvements associat ed with these five pollutants.

7.3.1 Arsenic

Under the final rule, EPA estimates 27,900 pounds per year of arsenic removals from steam electric power plant discharges – a 94 per cent reduction in annual lo adings. The final rule

will decrease the number of immediate receiv ing waters exceeding human health NRWQC for arsenic by up to 49 percent. The arsenic rem ovals will reduce negative effects on aquatic organisms, such as liver tissue death, developmental abnormalities, behavioral impairments, metabolic failure, growth reduction, and appetite loss [NRC, 2006; Rowe et al ., 2002; U.S. EPA, 2011f]. As a result, the final rule will decr ease human exposure to arsenic through fish consumption and thus lower the potential for e xposed populations to develop arsenic-related

cancer and non-cancer health effects such as derm al, cardiovascular, and respiratory effects. The

final rule will decrease the number of immediat e receiving waters exceeding the human health cancer risk threshold for arsenic by up to 75 per cent, depending on the evaluated cohort. Table 7-7 presents the key environmental improvement s resulting from arsenic removals under the regulatory options evaluated in the EA.

EPA did not see a reduction in the number of immediate receiving waters exceeding the arsenic NEHCs for minks or eagles because ther e are no exceedances modeled at baseline. The final rule, however, will still reduce the bioaccumulation of arse nic in the food web.

50 These values represent the average percentage improveme nts across the four race populations that comprise the minority cohorts.

7-16Section 7—Environmental Improvements Under the Final RuleTable 7-7. Key Environmental Improvements for Arsenic Under the Regulatory OptionsEvaluation BenchmarkModeled ImmediateReceiving Waters ExceedingBenchmark Under BaselineConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the Regulatory OptionsbNumberPercentageOption AOption BOption COption DOption EWater Quality ResultsFreshwater Acute NRWQC31%2(33%)2(33%)2(33%)2(33%)1(67%)Freshwater Chronic NRWQC42%3(25%)3(25%)3(25%)2(50%)1(75%)Human Health Water and OrganismNRWQC9445%90(4%)90(4%)69(27%)52(45%)43(54%)Human Health Organism Only NRWQC6531%61(6%)61(6%)45(31%)33(49%)26(60%)Drinking Water MCL126%9(25%)9(25%)6(50%)3(75%)2(83%)Wildlife ResultsFish Ingestion NEHC for Minks00%0(N/A)0(N/A)0(N/A)0(N/A)0(N/A)Fish Ingestion NEHC for Eagles00%0(N/A)0(N/A)0(N/A)0(N/A)0(N/A)Human Health Results—Non-CancerNon-Cancer Reference Dose for Child(recreational)21%1(50%)1(50%)1(50%)1(50%)0(100%)Non-Cancer Reference Dose for Adult(recreational)00%0(N/A)0(N/A)0(N/A)0(N/A)0(N/A)Non-Cancer Reference Dose for Child(subsistence)31%2(33%)2(33%)2(33%)2(33%)1(67%)Non-Cancer Reference Dose for Adult(subsistence)31%2(33%)2(33%)2(33%)2(33%)1(67%)7-17Section 7—Environmental Improvements Under the Final RuleTable 7-7. Key Environmental Improvements for Arsenic Under the Regulatory OptionsEvaluation BenchmarkModeled ImmediateReceiving Waters ExceedingBenchmark Under BaselineConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the Regulatory OptionsbNumberPercentageOption AOption BOption COption DOption EHuman Health Results—CancerArsenic Cancer Risk for Child(recreational)63%5(17%)5(17%)5(17%)2(67%)2(67%)Arsenic Cancer Risk for Adult(recreational)126%9(25%)9(25%)6(50%)3(75%)2(83%)Arsenic Cancer Risk for Child(subsistence)84%7(13%)7(13%)6(25%)3(63%)2(75%)Arsenic Cancer Risk for Adult(subsistence)2512%23(8%)23(8%)15(40%)11(56%)4(84%)Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (Maximum contaminant level); N/A (Not Applicable, no exceedances atbaseline conditions tocompare option results); NEHC (No EffectHazard Concentration); NRWQC (NationalRecommended Water Quality Criteria).a – The EA encompasses a total of 222 immediate receiving waters and loadings from 195 steam electric power plants (some of which discharge to multiplereceiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receivingwaters (183 rivers andstreams; 26 lakes, ponds, and reservoirs) andloadings from 188 steam electric power plants.b – >0 to 15 percent reduction; 16 to 30 percent reduction; 31 to 45 percent reduction;46 to 60 percent reduction;>60 percent reduction.7-18Section 7—Environmental Improvements Under the Final Rule

7.3.2 Mercury

Under the final rule, EPA estimates 1,450 pounds per year of mercury removals from steam electric power plant discharges – a 97 per cent reduction in annual loadings. As discussed in Section 6.2, estimated fish tissue concentratio ns for mercury (and selenium) exceed levels that can affect reproduction in exposed mink and eagle populations. EPA estimates that the final rule will decrease the number of immediate receiving wa ters with fish tissue concentrations that exceed the mercury NEHC for eagles and minks by 62 and 64 percent, respectively. These reductions also represent the potential improve ment in exposure to mercury above effects

thresholds in other wildlife that co nsume fish from these receiving waters.

Under baseline pollutant loadings, EPA estimates that fish methylmercury concentrations pose a non-cancer threat to subsistence fisher s and recreational fish ers in up to 52 and 46 percent, respectively, of i mmediate receiving waters. EPA calculates that fish tissue concentrations of methylmercury will decrease under the final rule and, as a result, the number of immediate receiving waters with exposure do ses from fish consumption that exceed the methylmercury reference dose will decrease by up to 57 percent. Because there are over 80 addressed by this final rule discharge to receiving waters that are under a fish advisory for mercury (see Section 3.4.4), the final rule will re duce mercury loadings to those receiving waters (see Section 7.4). Table 7-8 presents the key environmental improvements resulting from mercury removals under the regulatory options.

7-19Section 7—Environmental Improvements Under the Final RuleTable 7-8. Key Environmental Improvements for Mercury Under the Regulatory OptionsEvaluation BenchmarkModeled ImmediateReceiving Waters ExceedingBenchmark Under BaselineConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the Regulatory OptionsbNumberPercentageOption AOption BOption COption DOption EWater Quality ResultsFreshwater Acute NRWQC10%0(100%)0(100%)0(100%)0(100%)0(100%)Freshwater Chronic NRWQC10%0(100%)0(100%)0(100%)0(100%)0(100%)Human Health Water and OrganismNRWQCNo benchmark for comparisonN/AN/AN/AN/AN/AHuman Health Organism Only NRWQCNo benchmark for comparisonN/AN/AN/AN/AN/ADrinking Water MCL52%4(20%)4(20%)4(20%)2(60%)1(80%)Wildlife ResultsFish Ingestion NEHC for Minks5526%50(9%)49(11%)30(45%)20(64%)8(85%)Fish Ingestion NEHC for Eagles7134%61(14%)61(14%)44(38%)27(62%)18(75%)Human Health Results—Non-CancerNon-Cancer Reference Dose for Child(recreational)9646%87(9%)84(13%)63(34%)44(54%)35(64%)Non-Cancer Reference Dose for Adult(recreational)8239%71(13%)69(16%)52(37%)35(57%)24(71%)Non-Cancer Reference Dose for Child(subsistence)10952%97(11%)96(12%)75(31%)52(52%)46(58%)Non-Cancer Reference Dose for Adult(subsistence)9947%89(10%)87(12%)66(33%)46(54%)36(64%)Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (Maximum contaminant level); N/A (Not Applicable, no exceedances atbaseline conditions tocompare option results); NEHC (No EffectHazard Concentration); NRWQC (NationalRecommended Water Quality Criteria).a – The EA encompasses a total of 222 immediate receiving waters and loadings from 195 steam electric power plants (some of which discharge to multiplereceiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receivingwaters (183 rivers andstreams; 26 lakes, ponds, and reservoirs) andloadings from 188 steam electric power plants.b – >0 to 15 percent reduction; 16 to 30 percent reduction; 31 to 45 percent reduction;46 to 60 percent reduction;>60 percent reduction.7-20Selenium is known to cause fish deformities at high levels, such as these from Belews Lake,

N C. Section 7—Environmental Improvements Under the Final Rule

7.3.3 Selenium

Under the final rule, EPA estimates 136,000 pounds per year of selenium removals from steam electric power plant discharges – a 97 per cent reduction in annual loadings. Selenium is one of the primary pollutants identified in the literature and by EPA as causing documented environmental impacts to fish and wildlife fr om steam electric power plant discharges. EPA estimates that immediate receiving water concentr ations of total selenium will decrease under the final rule by 71 percent on averag e, decreasing the amount of sele nium that would bioaccumulate or persist in the aquatic environment. Under th e final rule, the number of immediate receiving waters exceeding chronic aquatic life NRWQC will decrease by 55 percent and the number of immediate receiving waters exceeding a drinking water MCL for selenium will decrease by 75

percent.

Reducing selenium loadings and subsequent bioaccumulation will decrease by 52 percent the number of immediate receiving waters with fish tissue concentrations exceeding the NEHC for selenium for both eagles and minks. These reductions also represent the potential health improvements in other wildlife that consume fish from these receiving waters, as well as the potential decrease in bioaccumulation of toxic pollutants in the broader food web near steam electric power plants.

The results of the ecological risk model further support these pred icted redu ctions in the bioaccumulative impact of selenium throughout the food web. Under the final rule, the ecological

risk m odeling results indicate that:

 The risk of negative reproductive impacts am ong fish and/or mallards will be reduced to less than one percent in each of the 26 modeled lentic immediate receiving waters.

 The number of immediate receiving waters th at present a risk of reproductive impacts among at least 10 percent of the exposed population will be reduced by 67 percent (for fish) and 61 percent (for mallards).

 The number of immediate receiving waters th at present a risk of reproductive impacts among at least 50 percent of the exposed population will be reduced by 70 percent (for fish) and 74 percent (for mallards).

These results are based on the median modeled egg/ovary selenium concentration in exposed fish and mallards. Use of the 90 th percentile modeled egg/ ovary concentration, which results in a higher predicted risk of reproductiv e impacts, shows similar improvements under the

final rule:

7-21Section 7—Environmental Improvements Under the Final Rule

 The risk of negative reproductive impacts among fish will be reduced to less than one percent in all but one of the 26 modele d lentic immediate receiving waters.

 The number of immediate receiving waters th at present a risk of reproductive impacts among at least 10 percent of the exposed population will be reduced by 55 percent (for fish) and 52 percent (for mallards). Under the final rule, none of the lentic immediate receiving waters will pose this reproductive risk to fish or mallards.

 The number of immediate receiving waters th at present a risk of reproductive impacts among at least 50 percent of the exposed population will be reduced by 53 percent (for fish) and 59 percent (for mallards).

Under the final rule, EPA estimates that fish selenium concentra tions that pose a noncancer threat to subsistence fishers and recrea tional fishers will decrease in up to 53 and 56 percent of immediate receiving wa ters, respectively. This reduc es the risk of developing noncancer health effects associated with selenium, su ch as pulmonary edema and lesions of the lung; cardiovascular effects such as tachycardia; ga strointestinal effects including nausea, vomiting, diarrhea, and abdominal pain; e ffects on the liver; and neurologi cal effects such as aches, irritability, chills, and tremors [U.S. EPA, 200 0b]. Table 7-9 presents the key environmental improvements resulting from selenium removals under the regulatory options.

7-22Section 7—Environmental Improvements Under the Final RuleTable 7-9. Key Environmental Improvements for Selenium Under the Regulatory OptionsEvaluation BenchmarkModeled ImmediateReceiving Waters ExceedingBenchmark Under BaselineConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the Regulatory OptionsbNumberPercentageOption AOption BOption COption DOption EWater Quality ResultsFreshwater Acute NRWQCNo benchmark for comparisonN/AN/AN/AN/AN/AFreshwater Chronic NRWQCd3316%30(9%)20(39%)18(45%)15(55%)15(55%)Human Health Water and OrganismNRWQC84%7(13%)3(63%)3(63%)2(75%)2(75%)Human Health Organism Only NRWQC10%1(0%)1(0%)1(0%)1(0%)1(0%)Drinking Water MCL126%10(17%)5(58%)5(58%)3(75%)3(75%)Wildlife ResultsFish Ingestion NEHC for Minks4220%40(5%)29(31%)23(45%)20(52%)20(52%)Fish Ingestion NEHC for Eagles4220%40(5%)29(31%)23(45%)20(52%)20(52%)Negative Reproductive Effects in Fishc2411%19(21%)10(58%)10(58%)8(67%)8(67%)Negative Reproductive Effects inMallardsc3115%26(16%)16(48%)14(55%)12(61%)12(61%)7-23Section 7—Environmental Improvements Under the Final RuleTable 7-9. Key Environmental Improvements for Selenium Under the Regulatory OptionsEvaluation BenchmarkModeled ImmediateReceiving Waters ExceedingBenchmark Under BaselineConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the Regulatory OptionsbNumberPercentageOption AOption BOption COption DOption EHuman Health Results—Non-CancerNon-Cancer Reference Dose for Child(recreational)4120%39(5%)29(29%)23(44%)20(51%)20(51%)Non-Cancer Reference Dose for Adult(recreational)3215%29(9%)18(44%)17(47%)14(56%)14(56%)Non-Cancer Reference Dose for Child(subsistence)5526%51(7%)39(29%)33(40%)27(51%)27(51%)Non-Cancer Reference Dose for Adult(subsistence)4321%40(7%)30(30%)23(47%)20(53%)20(53%)Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (Maximum contaminant level); N/A (Not Applicable, no exceedances atbaseline conditions tocompare option results); NEHC (No EffectHazard Concentration); NRWQC (NationalRecommended Water Quality Criteria).a – The EA encompasses a total of 222 immediate receiving waters and loadings from 195 steam electric power plants (some of which discharge to multiplereceiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receivingwaters (183 rivers andstreams; 26 lakes, ponds, and reservoirs) andloadings from 188 steam electric power plants.b – >0 to 15 percent reduction; 16 to 30 percent reduction; 31 to 45 percent reduction;46 to 60 percent reduction;>60 percent reduction.c – These rows indicate the numberof immediate receiving waters whose median modeled egg/ovary concentration is predicted to result in reproductive impactsamong at least 10 percent of the exposed fish or mallard population, as determined using the ecological risk model.d – The EA analyses use the EPA recommended water quality criteria for selenium in the water column of 5 μg/L -- in effect at the time of the modeling done,both for the proposed rule in 2012, and the final rule in 2015. EPA used this criterion in its modeling for the final rule to allow for consistent comparisonsbetween the modeling done for the proposed rule and that done for the final rule. All modeling was done prior to EPA publishingnew final draft criteria forselenium on July 27, 2015. The new final draft criteria, which EPA now recommends, of 3.1 μg/L in freshwater flowing systems (rivers, streams) and 1.2 μg/L inlakes and reservoirs, are lower than the criteria EPA used in these analyses. Had EPA conducted the modeling with these new recommended criteria, it wouldhave resulted in slightly greater estimated impacts (more exceedances of the new selenium criteria)than that revealed using the old criteria. As a result, thiswould have led to slightly greater potential improvements due to control of selenium discharges under the final rule. Therefore, the estimates of the modeledselenium impacts, and potential improvements of the final ELG, are conservative and tend, if anything, to underestimate both the impacts and the benefits.7-24Section 7—Environmental Improvements Under the Final Rule

7.3.4 Cadmium

Under the final rule, EPA estimates 9,020 pounds per year of cadmium removals from steam electric power plant discharges – a 68 per cent reduction in annual loadings. At baseline conditions, discharges of cadmium are the second largest toxic-we ighted pollutant discharges from the steam electric power generating indust ry among those pollutants evaluated in the EA (see Section 3.2). The final rule will decrease th e number of immediate r eceiving waters that exceed acute and chronic NRWQC by up to 67 a nd 59 percent, respectively. The number of immediate receiving waters with fish tissue con centrations that exceed NEHCs for minks and eagles will decrease by 67 and 50 percent, resp ectively. Under the final rule, the number of immediate receiving waters with fish containing cadmium concentrations that pose a risk of noncancer health effects will decrease by 53 to 70 percent, depending on the cohort. Table 7-10 presents the key environmental improvements resulting from cadmium removals under the regulatory options.

7.3.5 Thallium

Under the final rule, EPA estimates 62,300 pounds per year of thallium removals from steam electric power plant discharges – a 98 percent reduction in annual loadings. EPA estimates

that the final rule will decrease the number of immediate receiving waters exceeding human health NRWQC and MCLs for thallium by up to 85 pe rcent. Under the final rule, the number of immediate receiving waters with fish containing thallium concentrations that can potentially cause non-cancer health effects in humans ( e.g. , neurological symptoms, alopecia, gastrointestinal effects, and reproductive and developmental damage) wi ll decrease by up to 69 percent, depending on the cohort. Table 7-11 presents the key environmental improvements resulting from thallium removals under the regulatory options.

7-25Section 7—Environmental Improvements Under the Final RuleTable 7-10. Key Environmental Improvements for Cadmium Under the Regulatory OptionsEvaluation BenchmarkModeled ImmediateReceiving Waters ExceedingBenchmark Under BaselineConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the Regulatory OptionsbNumberPercentageOption AOption BOption COption DOption EWater Quality ResultsFreshwater Acute NRWQC94%6(33%)6(33%)6(33%)3(67%)2(78%)Freshwater Chronic NRWQC2914%23(21%)23(21%)16(45%)12(59%)9(69%)Human Health Water and OrganismNRWQCNo benchmark for comparisonN/AN/AN/AN/AN/AHuman Health Organism Only NRWQCNo benchmark for comparisonN/AN/AN/AN/AN/ADrinking Water MCL115%7(36%)7(36%)6(45%)3(73%)2(82%)Wildlife ResultsFish Ingestion NEHC for Minks63%5(17%)5(17%)5(17%)2(67%)2(67%)Fish Ingestion NEHC for Eagles42%3(25%)3(25%)3(25%)2(50%)2(50%)Human Health Results—Non-CancerNon-Cancer Reference Dose for Child(recreational)168%12(25%)12(25%)9(44%)5(69%)3(81%)Non-Cancer Reference Dose for Adult(recreational)105%7(30%)7(30%)6(40%)3(70%)2(80%)Non-Cancer Reference Dose for Child(subsistence)3215%26(19%)26(19%)19(41%)15(53%)10(69%)Non-Cancer Reference Dose for Adult(subsistence)2211%17(23%)17(23%)11(50%)7(68%)4(82%)Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (Maximum contaminant level); N/A (Not Applicable, no exceedances atbaseline conditions tocompare option results); NEHC (No EffectHazard Concentration); NRWQC (NationalRecommended Water Quality Criteria).a – The EA encompasses a total of 222 immediate receiving waters and loadings from 195 steam electric power plants (some of which discharge to multiplereceiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receivingwaters (183 rivers andstreams; 26 lakes, ponds, and reservoirs) andloadings from 188 steam electric power plants.b – >0 to 15 percent reduction; 16 to 30 percent reduction; 31 to 45 percent reduction;46 to 60 percent reduction;>60 percent reduction.7-26Section 7—Environmental Improvements Under the Final RuleTable 7-11. Key Environmental Improvements for Thallium Under the Regulatory OptionsEvaluation BenchmarkModeled ImmediateReceiving Waters ExceedingBenchmark Under BaselineConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the Regulatory OptionsbNumberPercentageOption AOption BOption COption DOption EWater Quality ResultsFreshwater Acute NRWQCNo benchmark for comparisonN/AN/AN/AN/AN/AFreshwater Chronic NRWQCNo benchmark for comparisonN/AN/AN/AN/AN/AHuman Health Water and OrganismNRWQC4923%46(6%)46(6%)27(45%)13(73%)13(73%)Human Health Organism Only NRWQC4522%42(7%)42(7%)23(49%)8(82%)8(82%)Drinking Water MCL3416%32(6%)32(6%)15(56%)5(85%)5(85%)Wildlife ResultsFish Ingestion NEHC for MinksNo benchmark for comparisonN/AN/AN/AN/AN/AFish Ingestion NEHC for EaglesNo benchmark for comparisonN/AN/AN/AN/AN/AHuman Health Results—Non-CancerNon-Cancer Reference Dose for Child(recreational)7435%73(1%)73(1%)46(38%)27(64%)27(64%)Non-Cancer Reference Dose for Adult(recreational)5426%51(6%)51(6%)31(43%)17(69%)17(69%)Non-Cancer Reference Dose for Child(subsistence)9445%90(4%)90(4%)63(33%)35(63%)35(63%)Non-Cancer Reference Dose for Adult(subsistence)7737%76(1%)76(1%)49(36%)29(62%)29(62%)Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (Maximum contaminant level); N/A (Not Applicable, no exceedances atbaseline conditions tocompare option results); NEHC (No EffectHazard Concentration); NRWQC (NationalRecommended Water Quality Criteria).a – The EA encompasses a total of 222 immediate receiving waters and loadings from 195 steam electric power plants (some of which discharge to multiplereceiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 209 immediate receivingwaters (183 rivers andstreams; 26 lakes, ponds, and reservoirs) andloadings from 188 steam electric power plants.b – >0 to 15 percent reduction; 16 to 30 percent reduction; 31 to 45 percent reduction;46 to 60 percent reduction;>60 percent reduction.7-27Section 7—Environmental Improvements Under the Final Rule

7.4 I MPROVEMENTS TO S ENSITIVE E NVIRONMENTS

As discussed in Section 3.4, EPA evaluate d pollutant discharges to sensitive environments ( i.e.

, impaired waters, threatened and endangered species, and fish consumption advisory waters) and sensitive watersheds (the Great Lakes and Chesapeake Bay). The purpose was to assess if steam electric power plants discharge to receiv ing waters with existing

im pairments or fish advisories and assess if di s ch arges of the evaluated wastestreams increase

stres s on threatened and endange red species. This section pres ents EPA’s estimated pollutant removals under five regulatory options to the evaluated sensitive environments.

The final rule will decrease pollutant loadings to sensitive en vironments, which will help impaired waters to recover; decrease the bioacc um ulation of toxic pollutants in fish, thereby

r educing the number of fish advisories; and re duce stress on threatened and endangered species

and sensitive watersheds such as C h esapeake Bay and the Great Lakes (see Section 7.5)

.

7.4.1 Impaired Waters

EPA determined that 59 of the immediate rece iving waters are 303(d)-listed waterbodies,

d esignated as impaired for one or more pol lutants found in the evaluated wastestreams. 51

Mercury (30 immediate receiving waters), nutrients (19 immediate receiving waters), and phosphorus (11 imm ediate receiving waters) are the most frequently identified impairment

catego ries among the surface waters that directly receive the evaluated wastestreams. Table 7-12

p r esents the pollutant removals to impaired waters (by impairment category) as a result of the

r egulatory options.

Under the fi nal rule, EPA estimates the following pollutant removals:

 Mercury removals of 168 pounds per year to mercury-impaired waters (decrease of 99 percent).

 Phosphorus removals of 4,100 pounds per year to nutrient-impaired waters (decrease of 78 percent).

 Nitrogen removals of 471,000 pounds per year to nutrient-impaired waters (decrease of 96 percent).

 Pollutant removals to receiving waters impa ired for a metal (except mercury) include 4,100 pounds per year of arsenic (decrease of 95 percent); 1,770 pounds per year of cadmium (decrease of 93 pe rcent); 2,630 pounds per year of lead (d ecrease of 97 percent); 21,500 pounds per year of seleni um (decrease of 97 percent); and 7,130 pounds per year of thallium (decrease of 97 percent). 52

51 The count of impaired waters excludes the general im pairment category “metals (not mercury)” and includes receiving waters impaired for arsenic, boron, cadmium, chromium, copper, lead, ma nganese, mercury, selenium, zinc, phosphorous, nutrients, TDS, or chlorides.

52 EPA presents pollutant loadings and removals for meta ls, other than mercury, for immediate receiving waters designated as impaired for the general impairment category “metals (not mercury)” to protect confidential business

information. See all results in Table 7-12.

7-28Section 7—Environmental Improvements Under the Final RuleTable 7-12. Pollutant Removals to Impaired Waters by Impairment TypeImpairmentType/Number ofReceiving WatersbPollutantBaselineLoadings(lbs/yr)Pollutant Removals (lbs/yr) toImpaired Waters Under the Regulatory Options (PercentReduction)aOption AOption BOption COption DOption EMercury-Impaired Receiving Waters30Mercury17089.790.2139168169(53%)(53%)(81%)(99%)(99%)Metals (Not Mercury)-Impaired Receiving Waters28Arsenic4,3202,8002,8003,6904,1104,160(65%)(65%)(85%)(95%)(96%)Boron4,900,000316,000316,000349,000361,000361,000(6%)(6%)(7%)(7%)(7%)Cadmium1,9001,3801,3801,6501,7701,780(73%)(73%)(87%)(93%)(94%)ChromiumVI27.223.423.426.927.227.2(86%)(86%)(99%)(>99%)(>99%)Copper4,4202,4902,4903,7904,3204,320(56%)(56%)(86%)(98%)(98%)Lead2,7001,3601,3602,2402,6302,630(50%)(50%)(83%)(97%)(97%)Manganese1,080,000718,000718,000780,000810,000810,000(66%)(66%)(72%)(75%)(75%)Nickel15,6009,2709,32013,30015,20015,300(59%)(60%)(85%)(97%)(98%)Selenium22,1003,32020,90021,30021,50021,500(15%)(94%)(96%)(97%)(97%)Thallium7,3301,2601,2605,2207,1307,130(17%)(17%)(71%)(97%)(97%)Zinc24,70018,60018,60021,90023,50023,800(75%)(75%)(89%)(95%)(96%)7-29Section 7—Environmental Improvements Under the Final RuleTable 7-12. Pollutant Removals to Impaired Waters by Impairment TypeImpairmentType/Number ofReceiving WatersbPollutantBaselineLoadings(lbs/yr)Pollutant Removals (lbs/yr) toImpaired Waters Under the Regulatory Options (PercentReduction)aOption AOption BOption COption DOption ENutrient-Impaired Receiving Waters19TotalNitrogen492,0007,250341,000395,000471,000471,000(1%)(69%)(80%)(96%)(96%)TotalPhosphorous5,2804064061,9304,0904,090(8%)(8%)(37%)(78%)(78%)TDS and Chlorides-Impaired Receiving Waters4ChloridesCBICBICBICBICBICBITDSCBICBICBICBICBICBISource: ERG, 2015c.Acronyms: CBI (Confidential business information); lbs/yr (pounds per year).Note: Loadings and pollutant reductions are rounded to three significant figures.a – >0 to 15 percent reduction; 16 to 30 percent reduction; 31 to 45 percent reduction;46 to 60 percent reduction;>60 percent reduction.b – For the impaired waters proximity analysis, EPA evaluated 222 immediate receiving waters that receive discharges of the evaluated wastestreams.c – The EPA impaired water database listed 28immediate receiving waters as impaired based on the “metal, other than mercury” impairment category. Of those28 immediate receiving waters, 13 receivingwaters are also listed as impaired for one or more specific metals (arsenic, cadmium, chromium, copper, lead,manganese, selenium, and zinc). One additional immediate receivingwater is impaired for boron (but not included in the “metals, other than mercury”impairment category).d – Total phosphorous and total nitrogen loadings are presented with this impairmentcategory. Total nitrogen loadings are thesum of total Kjeldahl nitrogen andnitrate/nitrite as N loadings.7-30Section 7—Environmental Improvements Under the Final Rule

7.4.2 Threatened and Endangered Species

As discussed in Section 3.4.5, EPA identifi ed 138 threatened a n d endangered species whose habitats overlap with, or are located w ithin, surface waters that exceeded NRWQC for the protection of aquatic life under baseline conditions. 53 To assess the potential improvements to threatened and endangered species under the final rule, EPA initially selected only those species identified as highly vulnerable to changes in water quality (75 of the 138 species) for evaluation. EPA further excluded species from the analysis ba sed on the following criteria: the species is already p resumed extinct, species habitat is unlikely to be affected by discharges of the evaluated wastestreams ( e.g. , isolated headwaters), species listing status is due to habitat destruction

u n r elated to steam electric power plant discharges ( e.g. , damming, stream channelization), and

o ther criteria. Based on the analysis, EPA identified 15 species out of the 75 that are highly

v ulnerable to changes in water quality and whose recovery may be enhanced by the final rule. Four of these 15 species inhabit waters that wi ll no longer exceed NRWQ C fo r the protection of aquatic life following implementation of the fina l rule. The species may therefore experience increases in population growth ra tes as a result of the final ru le. See the Benefits and Cost Analysis for further details on the methodology a nd results of EPA’s thr eatened and endangered species analysis.

7.4.3 Fish Advisory Waters

States, territories, and authorized tribes issue fish advisories to notify the public ( including recreational and subsistence fishers) of waterbodies containing fish with elevated and potentially unhealthy contamina tion levels. Mercury is the most common pollutant found in steam electric power plant wastewater for which fish advisories are issued to the surface waters

that receive the evaluated wastes treams (see Section 3.4.4). EPA det ermined that 88 of the 222 immediate receiving waters include d in the EA are under a fish advisory for mercury. Under the final rule, the number of immediate receiv ing waters with fish that exceed EPA’s mercury screening value for recreational fishers (based on steam electric power plant discharges only) will decrease by 63 percent, thereby reducing the potential threat to human health from consuming contaminated fish.

7. 5 I MPROVEMENTS TO W ATERSHEDS

As discussed in Section 3.4, both the Great La kes and Chesapeake Bay watersheds have a history of receiving pollutant discharges that ne gatively affect water quality, wildlife, and human health. Both are well-studied, sensitive environments that ar e affected by pollutants commonly

f o und in steam electric power plant wastewater. Mercury is one of the primary po llutants of concern in the Great Lakes, 54 and nutrients are the primary pollu tants of focus in the Chesapeake Bay.

EPA identified 23 steam electric power plants that discharge into the Great Lakes watershed. Table 7-13 presents the pollutant reducti ons to the Great Lake s watershed under the

53 The habitat locations evaluated for this analysis in clude waters downstream fro m steam electric power plant discharges and reflect changes in the industry as a result of the Clean Power Plan [Clean Air Act Section 111(d)].

54 One of the main environmental pathways for mercury in the Great Lakes is from atmospheric deposition, which is not in the scope of the final rule.

7-31Section 7—Environmental Improvements Under the Final Rule

regulatory options considered by EPA. Under the final rule , EPA estimates the following pollutant removals to the Great Lakes watershed:

 2,070 pounds of arsenic annually (96 percent reduction).

 612 pounds of cadmium annually (95 percent reduction).

 1,880 pounds of lead annually (99 percent reduction).

 80.6 pounds of mercury annually (97 percent reduction).

 4,800 pounds of selenium annually (96 percent reduction).

 9,510 pounds of thallium annually (99 percent reduction).

 1.15 million pounds of total nitrogen annually (>99 percent reduction).

 21,800 pounds of total phosphorus annua lly (94 percent reduction).

EPA identified nine steam electric power plan ts that discharge to the Chesapeake Bay watershed. Under the final rule, EPA estimates the following pollutant removals to the Chesapeake Bay watershed:

 2,430 pounds of arsenic annually (97 percent reduction).

 476 pounds of cadmium annually (93 percent reduction).

 1,540 pounds of lead annually (99 percent reduction).

 87.1 pounds of mercury annually (98 percent reduction).

 6,380 pounds of selenium annually (97 percent reduction).

 5,220 pounds of thallium annually (99 percent reduction).

 990,000 pounds of total nitrogen annu ally (>99 percent reduction).

 14,900 pounds of total phosphorus annua lly (89 percent reduction).

7-32Section 7—Environmental Improvements Under the Final RuleTable 7-13. Pollutant Removals to the Great Lakes Watershed Under the Regulatory OptionsPollutantBaseline Loadingsto the GreatLakes Watershed(lbs/yr)Pollutant Removals (lbs/yr) to Great Lakes Watershed Under the Regulatory Options(Percent Reduction)aOption AOption BOption COption DOption EArsenic2,17047.5 (2%)47.5 (2%)513 (24%)2,070 (96%)2,130 (98%)Boron997,0009,190 (1%)9,190 (1%)22,600 (2%)66,800 (7%)66,800 (7%)Cadmium64853.6 (8%)53.6 (8%)183 (28%)612 (95%)623 (96%)Chromium VI0.5480.471 (86%)0.471 (86%)0.548 (>99%)0.548 (>99%)0.548 (>99%)Copper2,55034.5 (1%)34.5 (1%)608 (24%)2,510 (99%)2,520 (99%)Lead1,90019.4 (1%)19.4 (1%)449 (24%)1,880 (99%)1,880 (99%)Manganese242,00035,500 (15%)35,500 (15%)70,500 (29%)188,000 (77%)188,000 (77%)Mercury82.84.56 (6%)4.91 (6%)22.6 (27%)80.6 (97%)82.2 (99%)Nickel9,840402 (4%)413 (4%)2,550 (26%)9,720 (99%)9,790 (99%)Selenium5,020126 (3%)3,780 (75%)4,010 (80%)4,800 (96%)4,800 (96%)Thallium9,57023.5 (<1%)23.5 (<1%)2,200 (23%)9,510 (95%)9,510 (99%)Zinc8,730658 (8%)658 (8%)2,410 (28%)8,270 (95%)8,600 (99%)Nitrogen, totalb1,150,0002,420 (<1%)380,000 (33%)556,000 (48%)1,150,000 (>99%)1,150,000 (>99%)Phosphorus, total23,100135 (1%)135 (1%)5,110 (22%)21,800 (94%)21,800 (94%)Chlorides31,900,00011,400 (<1%)11,400 (<1%)698,000 (2%)3,000,000 (9%)3,000,000 (9%)TDS186,000,0003,890,000 (2%)3,890,000 (2%)22,300,000 (12%)83,900,000 (45%)83,900,000 (45%)Source: ERG, 2015a; ERG, 2015c.Acronyms: lbs/yr (pounds per year).Note: Loadings and pollutant removals are rounded to three significant figures.a – >0 to 15 percent reduction; 16 to 30 percent reduction; 31 to 45 percent reduction;46 to 60 percent reduction;>60 percent reduction.b – Total nitrogen loadings are the sum of total Kjeldahl nitrogen and nitrate/nitrite as N loadings.7-33Section 7—Environmental Improvements Under the Final Rule

7.6 E NVIRONMENTAL AND H UMAN H EALTH I MPROVEMENTS IN D OWNSTREAM S URFACE
W ATER

EPA estimates that the environmental and hum an health improvements in the immediate receiving waters expected from the final rule will translate into considerable improvements in water quality further downstream from steam el ectric power plant discharges. EPA calculated downstream receiving water pollutant concentrations using EPA’s Risk-Screening Environmental Indicators (RSEI) model 55 and compared these concentrations to the same NRWQC and MCL water quality benchmarks used in the IRW model national-scale analysis. EPA also evaluated the wildlife (mink and eagle NEHC benchmarks) and human health (cancer and non-cancer) improvements in downstream surf ace waters using a simplified version of the IRW model national-scale analysis. This appr oach involved calculating the water pollutant

concentrations that would result in exceedance s if used as inputs to the wildlife and human

health modules in the IRW mode l; EPA then compared the downstr eam receiving water pollutant

concentrations in RSEI to these “threshold” co ncentrations to identify the downstream reaches

that would have at least one ex ceedance of a particular wildli fe or human health benchmark. 56
EPA used this approach to estimate the extent (in river miles) of environmental and human health impacts in downstream surface waters under baseline conditions and the improvements under the modeled regulatory options (Options A, B, C, D, a nd E). Table 7-14 presents the results of this downstream analysis.

Based on the results of the downstream mode ling, thousands of downstream river miles are impacted by steam electric power plant discharges. Pollutant concentrations exceed NRWQC for human health (water and organism) in 4,400 river miles downstream from immediate receiving waters. However, under the final rule, this drops by 2,390 river miles (54 percent). The

final rule reduces the number of downstream exceedances for each of the NRWQCs and MCLs evaluated. This reduction improves the water qual ity and aquatic habitats available to wildlife and human populations located outside of the immedi ate vicinity of steam electric power plants. In addition, pollutant removals under the final rule also reduce impacts to wildlife that rely on downstream aquatic habitats as a food source. Up to 1,040 miles of su rface waters downstream from steam electric power plant discharges will no longer contain fi sh populations th at exceed an NEHC benchmark for minks or eagles. The fina l rule also decreases potential exposure of humans to pollutants that can cau se non-cancer health effects from consumption of contaminated fish in up to 5,470 river miles. These results demonstrate that steam electric power plant discharges are impacting surface waters beyo nd the immediate receiving waters. Pollutant removals associated with the final rule will substantially improve the environmental and human health for communities beyond the area immediately surrounding steam electric power plants.

55 EPA used pollutant loadings discharged to each recei ving reach by steam electric power plants to estimate

concentrations in downstream reaches. The RSEI model us es a simple dilution and first-order decay equation to calculate receiving water concentrations (metals are treated as conservative substances). The RSEI model assumes that the plant’s annual discharge is released at a constant rate throughout the year. In addition, EPA included pollutant loadings from EPA’s Toxics Release Inventory (TR I) database for other industries to represent background pollutant concentrations in the downstream receiving waters. For furt her details on the RSEI model methodology and assumptions, see the Benefits and Cost Analysis.

56 See the ERG memorandum “Downstream EA Modeling Methodology and Supporting Documentation” (DCN SE04455) regarding the calculation of these water pollutant concentration thresholds.

7-34Section 7—Environmental Improvements Under the Final RuleTable 7-14. Key Environmental Improvements for Downstream Waters Under the Regulatory OptionsEvaluation CriteriaNumber of RiverMiles ExceedingCriteria UnderBaseline ConditionsNumber of River-Miles Exceeding Criteria(Percent Reduction from Baseline Conditions) Under the Regulatory OptionsaOption AOption BOption COption DOption EWater Quality ResultsFreshwater Acute NRWQC417396(5%)396(5%)394(5%)390(7%)390(7%)Freshwater ChronicNRWQC628612(3%)569(9%)547(13%)518(18%)518(18%)Human Health Water andOrganism NRWQC4,4003,670(17%)3,670(17%)2,620(40%)2,010(54%)1,760(60%)Human Health Organism-onlyNRWQC1,5601,300(16%)1,300(16%)1,070(31%)782(50%)713(54%)Drinking WaterMCL759731(4%)726(4%)630(17%)487(36%)487(36%)Wildlife ResultsFish Ingestion NEHC for Minks1,180917(23%)892(25%)723(39%)527(56%)504(57%)Fish Ingestion NEHC for Eagles2,0001,730(13%)1,720(14%)1,390(30%)959(52%)901(55%)Human Health Results—Non-CancerNon-cancer reference dose forchild (recreational)6,3504,900(23%)4,890(23%)3,130(51%)2,310(64%)2,150(66%)Non-cancer reference dose foradult (recreational)3,7602,960(21%)2,950(21%)2,050(46%)1,470(61%)1,380(63%)Non-cancer reference dose forchild (subsistence)10,1008,380(17%)8,350(17%)6,150(39%)4,630(54%)4,240(58%)Non-cancer reference dose foradult (subsistence)7,1105,580(22%)5,570(22%)3,720(48%)2,770(61%)2,540(64%)7-35Section 7—Environmental Improvements Under the Final RuleTable 7-14. Key Environmental Improvements for Downstream Waters Under the Regulatory OptionsEvaluation CriteriaNumber of RiverMiles ExceedingCriteria UnderBaseline ConditionsNumber of River-Miles Exceeding Criteria(Percent Reduction from Baseline Conditions) Under the Regulatory OptionsaOption AOption BOption COption DOption EHuman Health Results—CancerCancer risk for child(recreational)231216(7%)216(7%)211(9%)210(9%)207(10%)Cancer risk for adult(recreational)286263(8%)263(8%)251(12%)246(14%)245(14%)Cancer risk for child(subsistence)262241(8%)241(8%)239(9%)235(10%)231(12%)Cancer risk for adult(subsistence)446383(14%)383(14%)358(20%)328(27%)304(32%)Source: ERG, 2015i; ERG, 2015l.Note: River miles are rounded to three significant figures.a – >0 to 15 percent reduction; 16 to 30 percent reduction; 31 to 45 percent reduction;46 to 60 percent reduction;>60 percent reduction.b – EPA evaluated a total of 73,000 river-miles in the downstream receiving water analysis for toxic, bioaccumulative pollutants. Downstream receiving waterconcentrations are calculated until one of three conditions occurs: 1) the discharge travels 300 kilometers (km) downstream; 2)the discharge travels downstreamfor a week; or 3) the concentration reaches 1 x 10-9milligrams per liter (mg/L).7-36Section 7—Environmental Improvements Under the Final Rule

7.7 A TTRACTIVE N UISANCES

EPA projects that the final rule will also decrease the environmental impact to wildlife exposed to pollutants through direct contac t with surface impoundments and constructed wetlands at steam electric power plants. Multiple studi es show that wildlife living near steam electric surface impoundments exhibit elevated levels of arsenic, cadmium, chromium, lead, mercury, selenium, strontium, and vanadium [Burger et al ., 2002; Bryan et al ., 2003; Hopkins et
al ., 1997, 1998, 2000, 2002, 2006; Nagle et al ., 2001; Rattner et al ., 2006]. Multiple studies have linked attractive nuisance areas at steam electric power plants to diminished reproduction [Hopkins et al ., 2002, 2006; Nagle et al ., 2001]. While the final rule does not control pollutants within surface impoundments or constructed wetlands prior to their discharge to surface waters,

EPA estimates that the final rule will decreas e pollutant loadings to these waterbodies ( e.g. , through plants converting to dry handling their fl y ash). These pollutant removals will decrease the exposure of wildlife populations to toxic pollutants and decrea se the threat that combustion residual surface impoundments pose to surrounding wildlife.

7.8 O THER S ECONDARY I MPROVEMENTS

In addition to the improvements discussed ab ove, other secondary, or ancillary, other resources will see improvements that are associated directly or indirectly with the final rule. Pollutant removals not only improve water quality in surface waters but e nhances their aesthetic ( e.g. , by improving clarity and decreasing odor a nd discoloration). Cleaner surface water improves the source of drinking water for both surface water treatment plants and wells that are influenced by surface water; water used for irri gation; and water used for industrial uses (less contaminants). Recreational benefits from wate r quality improvements include more enjoyment from swimming, fishing, and boating and potentia lly increased revenue from more people partaking of recreational activities. The final rule may also reduce economic impacts such as clean-up and treatment costs for contaminati on or impoundment failures, reduced injury associated with surface impoundment failures, re duced water usage, redu ced potential for algal blooms, and decreased air emissions.

The Benefits and Cost Analysis monetizes benefits of implementing the final rule (increased aesthetics, recreational improvements, increa sed availability of ground water resources, reduced risk of surface impoundment failures, and air quality improvements). In addition, the document also qualitatively discusse s improvements to the quality of source water for drinking, irrigation, and indus trial use; quantity and quality of recreational opportunities; improved commercial fisheries yields; increas ed property values; and reduced sediment contamination within receiving waters.

While the final rule does not control pollu tants leaching to ground water from surface impoundments and landfills containing combustion residuals, EPA estimates that the final rule will decrease pollutant loadings to surface impoundments ( e.g. , through plants converting to dry handling their fly ash). These po llutant removals will decrease pollutants leaching from combustion residual surface impoundments to ground water and decrease the potential human health impacts associated with exposure to contaminated drinking water wells (see Section 3.3.4). EPA, however, did not quantify or mone tize the benefits associated with this improvement to ground water quality.

7-37Section 7—Environmental Improvements Under the Final Rule

7.9 U NRESOLVED D RINKING W ATER I MPACTS D UE TO B ROMIDE D ISCHARGES

As discussed in Section 3.1.3, bromide in water can form brominated disinfection byproducts (DBPs), some potentially carcinogenic, when drinking water plants use certain processes including chlorination and ozonation to disinfect th e incoming source water. The national effluent limitations guidelines and stan dards under the final rule (regulatory Option D) do not directly control TDS levels (including bromides) in FGD wa stewater discharges from all steam electric power plants. 57 Coal-fired steam electric power plants can discharge bromide due to its natural presence in coal (w hich is released when burned and/ or captured in particulates by baghouses and FGD controls) or through bromide add ition to flue gas control processes to reduce mercury emissions. Steam electric power plant di scharges occur close to more than 100 public drinking water intakes on rivers and other wate rbodies and there is evidence that bromide discharges are already having adverse effects on the quality of drinking water sources.

While bromide itself is not t hought to be toxic at levels pr esent in the environment, its reaction with other constituents in water may be of concern now and into the future. Drinking

water utilities should be concerned about bromides affecting drinking water sources, as bromide loadings into surface waters could potentially in crease in the future as more coal-fired steam electric power plant operators add bromide to help control mercur y emissions. Although EPA decided not to finalize BAT requirements based on evaporation for treating FGD wastewater at all steam electric power plants in the final rule, eva poration technology is pot entially available and may be appropriate for achie ving water quality-based efflue nt limitations, depending on sitespecific conditions, where drinking wate r supplies need to be protected.

57 They do, however, directly control TDS in cases wher e steam electric power plants opt into the voluntary incentives program, in which they would be subject to effluent limitations based on evaporation technology.

7-38Section 8—Case Study Modeling



## SECTION 8
CASE STUDY MODELING

EPA developed dynamic water quality models of selected case study locations to supplement the water quality component of the national-scale immediate receiving water (IRW) model. EPA performed the case study modeling to provide additional re solution regarding the baseline impacts and the expected environm ental and human health improvements under the final rule, while encompassing a broader temporal and spatial scope than what is included in the IRW model. The case study models also valida te and provide additional perspective on the

results of the IRW model for those waterbod ies included in both models. The case study modeling improves upon the IRW model in the following ways:

 Accounts for long-term pollutant loadings from steam electric power plants (under

both baseline conditions and th e final rule) and estimates the resultant accumulation of pollutants within the water column a nd sediments of the receiving water. These models can more accurately assess baselin e pollutant concentrations and the time frame and magnitude of environmental impr ovements associated with the final rule.

 Accounts for fluctuations in receiving water flow rates by using daily stream flow monitoring data instead of one annual average flow rate for the receiving water. This approach better reflects the va rying influence of dilution (or lack thereof) within the receiving water during high-fl ow and low-flow conditions.

 Accounts for pollutant transport and accumula tion within receiving water reaches that are downstream from the discharge location. This approach can more accurately estimate the river distance showing envir onmental impacts unde r baseline conditions and improvements under the final rule. 58

 Accounts for pollutant contributions fr om other point, nonpoint, and background sources, to the extent practical, using av ailable data sources . Incorporating nonsteam-electric pollutant sources and availa ble water quality data provides a more complete illustration of the compounding impacts of background pollutant concentrations, steam electric power plant po llutant loadings, and other point source dischargers.

This section describes EPA’s methodology for developing and running the case study models (Section 8.1); presents th e results of the case study models for the selected case study locations (Section 8.2); and compares the ca se study and IRW model results (Section 8.3).

58 The case study downstream modeling described in this section is separate from the downstream modeling EPA performed using the Risk-Screening Environmental Indicators (RSEI) model and the SPARROW (SPAtially Referenced Regressions On Watershed attributes) model. EPA used the national-scale RSEI and SPARROW models to quantify changes in water quality in support of the benefits analysis for the final rule. See the Benefits and Cost Analysis for the Effluent Limitations Guidelines and Standards for the Steam Electric Power Generating Point Source Category (EPA-821-R-15-005).

8-1Section 8—Case Study Modeling

8.1 C ASE S TUDY M ODELING M ETHODOLOGY

The case studies use EPA’s Water Quality Analysis Simulation Program (WASP), a dynamic compartment-modeling program for aquatic systems that simulates pollutant fate and transport within both the water column and the benthic sediment. The WASP model helps users interpret and predict wa ter quality responses to natural phenomena and man-made pollution for various pollutant management decisions. EPA’s a pproach also relies on U.S. Geological Survey (USGS) daily stream flow data downloade d through EPA’s Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) interface to provide input time series flow

data for use in the WASP model.

This section is organized as follows:

 Section 8.1.1 discusses EPA’s approach for selecting case study locations ( i.e. , steam electric power plants and receiving wa ters) for case study m odeling, including the differences in selection criteria for lotic, lentic, and estuarine water systems.

 Section 8.1.2 summarizes the scope and general technical approach for the case study modeling, including the selection of polluta nts and wastestreams for modeling; the

data sources evaluated for non-steam-electri c pollutant contributi ons; and approaches for modeling pollutant levels before and af ter the assumed final rule compliance date.

 Section 8.1.3 explains the development and execution of the case study models using WASP. Appendix G provides additional information regarding the specific input parameters ( e.g. , background pollutant concentrations, USGS time series flow data) and model settings ( e.g. , solids transport parameters) for each of the WASP models. For additional documentation regarding the selection and calculation of the input parameters and settings, refer to the ERG memorandum, “Technical Approach for Case Study Water Quality Modeling of Aquatic Systems in Support of the Final Steam Electric Power Generating Industr y Environmental Assessment” (DCN SE05570) ( Case Study Water Quality Modeling Memorandum ).

 Section 8.1.4 describes the use of the case study model outputs to determine impacts to aquatic life based on changes in water quality; impacts to a quatic life based on changes in sediment quality; impacts to wildlife from consuming contaminated aquatic organisms; and impacts to human health from consuming contaminated fish.

 Section 8.1.5 lists some of th e limitations and assumptions involved with EPA’s case study modeling.

8.1.1 Selection of Case Study Locations for Modeling

To select locations for detailed case study modeling, EPA developed site-selection criteria to identify a collection of steam electri c power plants and receiving waters that, when evaluated as a group:

 Represent a reasonable cross-section of the ra nge of receiving waters evaluated in the environmental assessment (EA).

 Illustrate pollutant removals across th e regulatory options evaluated by EPA.

8-2Figure 8-1. Overview of Case Study Modeling Locations Section 8—Case Study Modeling

 Encompass discharges of all four wastestreams evaluated in the EA.

 Demonstrate pollutant loadings that are re presentative of those discharged by steam electric power plants evaluated in the EA ( i.e. , discharges are typical of steam electric power plants and not outlier values).

EPA evaluated 195 steam electric power plants that discharge directly to aquatic systems

with lotic characteri stics (rivers and streams), lentic charac teristics (lakes, ponds, and reservoirs), or that are estuarine systems. Through the site-selection process described below, EPA identified six representative case study locations (five lo tic sites and one lentic site) that capture improvements across multiple regulatory options, re present all four evaluated wastestreams (flue gas desulfurization (FGD) wastewater, fly ash tr ansport water, bottom ash transport water, and combustion residual leachate), a nd represent both lentic and lotic aquatic environments. Figure 8-1 and Table 8-1 present the si x receiving waters that EPA se lected for case study modeling.

8-3Section 8—Case Study ModelingTable 8-1. Locations Selected for Case Study ModelingCase StudyLocationWaterbodyTypeSteam ElectricPower Plant(s)ModeledEvaluated Wastestreams DischargedRegulatory OptionsDemonstrating RemovalsModelLength(rivermiles)ModelingPeriodaFGDFly AshBottomAshLeachateABCDBlack Creek,MSLoticR.D. Morrow Sr.Generating Site971982-2036(55 years)Etowah River,GALoticPlant Bowen351982-2032(51 years)Lick Creek &White River, INLoticPetersburgGenerating Station531986-2034(49 years)Ohio River,PA/WV/OHLoticBruce MansfieldPlant & W.H.Sammis Plant441982-2036(55 years)MississippiRiver, MO/ILLoticRush Islandb651982-2036(55 years)Lake Sinclair,GALenticPlant HarlleeBranchcN/A2012-2025(14 years)Acronym: FGD (flue gas desulfurization); N/A (Not applicable).a – The modeling periods start at 1982 (the year of the last revision to the steam electric effluent limitations guidelines andstandards (ELGs) or the date ofinstallation of the most recent generatingunit impacted by the final rule (if after 1982). The duration of the modeling periodis influenced by the available timeperiods covered by USGS time series flow data and by the assumed date upon which the steam electric power plant would achieve the limitations under the finalrule, as determined based on the plant’s National PollutantDischarge Elimination System (NPDES) permitting cycle.b – EPA identified another steam electric power plant, Meramec, that discharges upstream of the Rush Island plant. EPA incorporated the pollutant loadings ofthe Meramec plant to account for the upstream pollutant contributions. EPA did not evaluate the water quality, wildlife, or human health impacts associated withdischarges from the Meramec plant because this plant was not selected using the case study selection methodology described in this section.c – This steam electric power plant has decertified and retired all of its steam electric generating units. EPA selected this plant to represent the potential impactsof discharges of the evaluated wastestreams to lentic waterbodies because it meets all of the case study selection criteria.8-4Section 8—Case Study Modeling

Selection of Lotic Case Study Locations

To select lotic receiving waters to model us ing WASP, EPA reviewed all combinations of steam electric power plants and th eir receiving waters evaluated in the EA for factors that would negatively influence the ability to use WASP for case study water quality modeling or the ability to discuss the case study modeli ng results in a public document. EPA completed an assessment using industry res ponses to the 2010 Questionnaire for the Stea m Electric Power Generating Effluent Guidelines (the Steam Electric Survey), EPA’ s BASINS tool, Na tional Hydrography Dataset Plus (NHDPlus Version 1) hydrography layers, and USGS National Water Information System (NWIS) data sources to identify and elimin ate the lotic receiving waters that met one or more of the following criteria from c onsideration for case study modeling:

 Confidential Business Information (CBI) . EPA identified and eliminated steam electric power plants with CBI claims on disc harge flow rate data for any of the four

evaluated wastestreams. EPA eliminated thes e plants as potentia l case study locations because CBI data, including modeled water concentrations based on CBI data, cannot be discussed in a public document such as this EA report.

 Stream gage flow data . EPA identified and eliminated receiving waters that lack sufficient stream gage flow data. Availabil ity of a long-term, c ontinuous stream flow record for both the receiving water bei ng modeled and any significant downstream tributaries was a major factor in selecting case study locations because these data are needed to construct the hydrodynamics in WASP. The primary considerations when reviewing the sufficiency of stream gage flow data for use in WASP were the following:

- Location of USGS stream gage stations (the ideal location is within the vicinity of the immediate receiving water being evalua ted, plus additional locations within the model area).

- A continuous stream flow record coveri ng a time period that matches or exceeds the length of the de sired modeling period.

- Age of the stream gage flow data (data se ts without data from within the previous 30 years were considered potentially unrep resentative of current flow conditions).

 Downstream waterbody characteristics . WASP’s ability to accurately model water quality using USGS stream gage flow data can be affected by flow control structures

such as dams that affect the linear flow a nd circulation of water, and thus influence the transport of pollutants. EPA identifie d and eliminated receiving waters whose

downstream waterbodies exhibit these charac teristics, unless the areas of concern were sufficiently downstream to allow for modeling of a reasonable distance ( i.e. , at least 25 miles) before encount ering the area of concern.

 Influence by other point source disc hargers that coul d not be modeled . EPA identified receiving waters that could be significantly influenced by discharges from other point sources (including other steam electric pow er plants) and eval uated whether those point sources would meet the criteria listed above for case study modeling. If EPA determined that a receiving water would be significantly influenced by other point source discharges that could not be modeled ( e.g. , an upstream steam electric power

8-5Section 8—Case Study Modeling

plant exercising CBI claims) or represen ted in the model by STORET monitoring data (see Section 8.1.3), EPA eliminated th e receiving water from consideration. If EPA deemed the pollutant loadings from the other point source discharges to be insignificant compared to the steam electri c power plant pollutant loadings being evaluated, EPA included the receiving water in the analysis. 59

Next, EPA assessed the representativeness of the steam electric power plants and receiving waters that were not eliminated base d on the criteria above. EPA selected the receiving water flow rate, magnitude of pollutant loadin gs from the evaluated wastestreams, and water column concentrations output ca lculated based on these values as the primary factors in determining whether it considered a particular receiving water representative. EPA reviewed the average annual flow rates (as defined in NHDPlu s Version 1), baseline loadings of the modeled pollutants, and water column con centrations output from the IR W model of each of the steam electric power plants and receiving waters that were not eliminated after application of the acceptance criteria. EPA assessed how each plant and receiving water compared to the general population in the EA and eliminated plant and receiving water combinations that did not reasonably represent typical conditions. From the population of lotic receiving waters that EPA

determined would be suitable for WASP modeli ng and representative of typical pollutant loadings from discharges of th e evaluated wastestreams, the Agency selected a collection that, when evaluated as a group, demonstrated pollut ant removals across all modeled regulatory options and all four evaluated wastestreams. As a result, EPA identified five case study locations as the best candidates for modeling as part of a representative set of st eam electric power plants that discharge to lotic systems. The selected cas e study locations are further described in Section

8.2. 60 Additional information about EPA’s methodology for selecting plants and receiving waters that are representative and suitable for WA SP modeling is further described in the Case Study Water Quality Modeling Memorandum (DCN SE05570).

Selection of Lentic and Estuarine Case Study Locations

Water quality modeling of lentic systems (l akes, ponds, and reservoirs) or estuarine systems involves more complex hydrodynamics that would not be adequately represented by stream gage flow data. Modeling steam electric power plants that discharge to lentic or estuarine systems requires using existing EPA-developed WASP models (or more specifically, the underlying hydrodynamic data) for the specific wa terbodies of intere st. Accordingly, EPA considered the availability of existing models a primary factor in selecting lentic and estuarine systems for case study wa ter quality modeling.

59 EPA considered receiving water flow rate, distance betw een outfalls, and relative magnitude of pollutant loadings when assessing whether the discharges from upstream or downstream plants or point sources could significantly affect the water quality modeling results for the selected case study location. EPA applied best professional judgment using these criteria, but did not apply numeric thresholds.

60 Because of the level of effort requir ed to design, execute, and evaluate the outputs for case study modeling, EPA did not complete case study modeling for all candidates that met all acceptance criteria and were determined to be representative. EPA used best professional judgment in determination of which five case study locations were the best candidates for modeling and represent a reasonable cross-section of the range of receiving waters evaluated in

the EA.

8-6Section 8—Case Study Modeling

EPA identified one preexisting WASP model for a lake (Lake Sinclair, GA) that receives steam electric power plant discharges from Geor gia Power Company’s Plant Harllee Branch. As of April 16, 2015, this plant has dece rtified and retired all four of its coal-fired generating units.

Based on a review of the water concentration ou tputs generated by the IRW model in support of the proposed ELGs (which were developed prior to the announcement of plans to retire Plant Harllee Branch), EPA determined that Lake Sinc lair remains a representative illustration of

lentic waterbodies that receive di scharges of the evaluated wastes treams. As discussed in Section 3, pollutant loadings to lentic systems often mo re strongly affect wate r quality and ecosystem health (compared to lotic systems) due to the longer reside nce times and associated long-term accumulation of pollutants in these systems. Acco rdingly, and despite the retirement of Plant Harllee Branch, EPA proceeded with case study modeling of Lake Sinclair to represent the potential impacts of steam electric power plant discharges on lentic wa terbodies (including the 26 lake, pond, and reservoir receiving waters evaluated in this EA) and the potential environmental improvements under the final rule in other lentic wate rbodies that receive discharges of the eval uated wastestreams.

EPA also identified one preexisting wate r WASP model for an estuary (Hillsborough Bay, FL) that receives steam elect ric power plant discharges. However, due to the hydrologic complexity of the model, and b ecause estuarine systems represen t less than 2 percent of the receiving waters evaluated in the EA, EPA elect ed to develop only freshwater river and lake WASP models for this case study analysis. Addi tionally, the ecological risk modeling approach

described in Section 5.2 is based on selenium bioaccumulation within freshwater environments and would not be appropriate to apply to estuar ine or marine aquatic sy stems, which would limit EPA’s ability to analyze the ecological effects for the estuarine case study.

8.1.2 Scope and Technical Approach for Case Study Modeling

This section describes the scope and techni cal approach used for EPA’s detailed case study modeling, including the selection of pollutant s and wastestreams eval uated, the inclusion of other point and nonpoint sour ces, the development of a histor ical baseline for the case study location, and the prediction of de creased water and sediment pollu tant concentrations under the regulatory options evaluate d for the final rule.

Selection of Pollutants for Modeling

EPA approached the case study modeling with the goal of modeling the same 10 pollutants included in the IRW model, which are listed in Secti on 5.1. As describe d later in this section, however, EPA was unable to perfor m case study modeling for chromium VI and mercury. EPA performed case study water quality modeling for the following eight pollutants (or

“toxicants” as defined in th e WASP model), which were also included in the IRW model:

 Arsenic (As).

 Cadmium (Cd).

 Copper (Cu).

 Lead (Pb).

 Nickel (Ni).

 Selenium (Se).

8-7Section 8—Case Study Modeling

 Thallium (Tl).

 Zinc (Zn).

These pollutants can be modeled using th e Simple Toxicant module within WASP. Similar to the water quality module of the IR W model, the Simple Toxicant module applies pollutant-specific partition coefficients to estimate the degree to which pollutants in the water

column will adsorb to benthic sediments a nd suspended solids. Unlike the IRW model, the Simple Toxicant module does not incorporate separate partition coefficients to define the benthic sediment/pore water equilibrium and the suspended sediment/water column equilibrium. Therefore, EPA selected only th e suspended sediment-water (Kd

sw ) partition coefficient for each pollutant (see Table C-4 in Appendix C).

EPA also considered using WASP to perfor m water quality modeling for chromium VI and mercury. These pollutants, however, requir e using more data-inten sive modules within WASP. Accurately modeling chromium VI requi res using the META4 m odule within WASP to accurately predict pollutant speciation and depends on the availability of extensive site-specific monitoring data. Modeling mercury (and methylme rcury, a bioaccumulative organic form of mercury) requires using the MERC7 module w ithin WASP to account for transformation processes such as methylation. Using the more data -intensive modules requir es site-specific data

that were not available for all locations.

Evaluated Wastestreams

The case study models quantified the water qua lity impacts resulting from discharges of

the same four evaluated wastestreams included in the IRW model:

 Fly ash transport water.

 Bottom ash transport water.

 FGD wastewater.

 Combustion residual leachate.

As with the IRW model, EPA performe d the WASP water quality modeling using average daily pollutant loadings derived from average annual pollutant loadings and normalized effluent flow rates. This assumption of a static loadings rate does no t account for temporal variability in the loadings to receiving waters due to factors such as variable plant operating schedules, storm flows, low-flow events, and catastrophic events.

Inclusion of Other Point and Nonpoint Sources

Accounting for pollutant contributions fr om non-steam-electric point sources and nonpoint sources, to the extent practical using av ailable data, can improve the accuracy of the case study water quality models. EPA identified the following data sources that provide pollutant loadings and/or concentration data for these othe r sources potentially affe cting water quality in the case study location:

 Discharge Monitoring Reports (DMR) . Point source discharger s are required to report certain wastewater monitoring data through the submittal of DMRs. However, they are required to report only for the pollutants that are listed in the facility’s National

8-8Section 8—Case Study Modeling

Pollutant Discharge Elimination System (NPDES) permit. 61 EPA evaluated 2011 pollutant loadings data for direct dischargers includi ng publicly owned treatment works (POTWs) and industrial facilities.

 Toxics Release Inventory (TRI) . TRI collects facility-reported estimates of wastewater loadings data for both direct a nd indirect dischargers. The TRI database does not include loadings from facilities w ith total annual chemical releases of less than 500 pounds and incorporat es assumptions regarding plants with annual releases of less than 1,000 pounds. The point source loadi ngs from smaller facilities, therefore, may not be well represented in the TRI database. 62 EPA evaluated 2011 pollutant loadings data for industrial f acilities with indirect discha rges of a modeled pollutant. EPA also evaluated TRI direct pollutant loadings data for these facilities and pollutants if the facilities are not also requi red to report this pollutant in their DMRs (to avoid double-counting direct discharges).

 STORET Monitoring Data. EPA’s STORET database is a repository for water quality, biological, and physical data compiled from many data sources and locations throughout the country. The STORET database contains water qua lity and sediment quality monitoring data for all eight mode led pollutants and othe r input parameters for WASP including total organic carbon (T OC) and total suspended solids (TSS).

EPA reviewed these publicly available data sources to identify pollutant contributions from non-steam-electric point sources and nonpoint sources that may imp act the case study water quality model. EPA also used available STORET monitoring data to help calibrate the modeled outputs. For additional documentation regarding EPA’s collection and use of these data, refer to

the Case Study Water Quality Modeling Memorandum (DCN SE05570).

Modeling of Pollutant Loadings Prior to the Final Rule

EPA developed and executed WASP models (as described in Section 8.1.3) for the selected case study locations to predict the ba seline accumulation of pollutants in the receiving water and sediment leading up to implementation of the final rule.

The modeling periods start at 1982 (the year of the last revision to the steam electric ELGs) or the date of installation of the most recent generating unit impacted by this rulemaking (if after 1982), and extend to the assumed compliance date. 63 If the available stream gage flow

61 In addition, states (or other permitting authorities) have some discretion as to which data they make available (or enter) to the national database ( i.e. , Permit Compliance System (PCS) and Integrated Compliance Information System for the National Pollutant Discharge Eliminat ion System (ICIS-NPDES)). For example, permitting authorities enter DMR and permit information for facilities that are considered major dischargers. However, they do not necessarily enter DMR or permit information into PC S for minor dischargers or facilities covered by a general permit.

62 Other limitations of the data collected in TRI include the following: small establishments are not required to report, nor are facilities that do not meet reporting thre sholds; releases reported are based on estimates, not measurements; certain chemicals are reported as a class, not as individual compounds; facilities are identified by

North American Industrial Classification System (NAICS) code, not point source category; and TRI requires facilities to only report certain chemicals and therefore all pollutants discharged from a facility may not be captured.

63 For each steam electric power plant in the case study mo deling, EPA assumed a plant-specific date, derived from the plant’s permitting cycle, that the plant would achieve the limitation under the final rule.

8-9Section 8—Case Study Modeling

data did not cover the desired modeling pe riod, EPA extrapolated the available data, incorporating another partial cycl e of the flow data to reach the total desired modeling period.

Historical pollutant loadings data for the ev aluated wastestreams a nd non-steam-electric point sources are very limited and difficult to obtain, so EPA used Steam Electric Survey data (representing plant operations in 2009), STORET monitori ng data, and 2011 TRI and DMR loadings data as a representative set of disc harge conditions. EPA acknowledges that these data may not reflect the actual pollutant loadings ov er the entire modeling period; however, they represent an appropriate estimati on of annual pollutant loadings and how discharges may affect individual aquatic systems over time.

For each case study location, EPA assumed that the annual, historical pollutant loadings associated with fly ash transport water, botto m ash transport water, and combustion residual leachate discharges were equal to the base line pollutant loadings calculated for these wastestreams ( i.e. , the same annual pollutant loadings used to represen t baseline conditions in the national-scale IRW model). The impoundment and di scharge of these wastestreams has been a standard technique prac ticed since before 1982. EPA did not attempt to determine whether a modeled plant had historical discharges of an ev aluated wastestream that are not represented in the baseline pollutant loadings. For example, fo r a plant that does not have fly ash transport water pollutant loadings under baseline conditions, EPA did not attempt to determine whether the plant had historical discharges of fly as h transport water.

In estimating the annual, historical pollutant loadings associated with FGD wastewater,

EPA accounted for the fact that steam electric power plants may have installed FGD systems after the start of the modeling period. EPA used the FGD system installation dates, based on industry responses to the Steam Electric Surv ey, to determine how to incorporate FGD wastewater pollutant loadings into the case study model. If a plant installed multiple FGD systems during the modeling period, EPA assumed that the annual, historical FGD wastewater pollutant loadings associated with each individual system were proportional to that system’s flow rate contribution compared to the total FGD wast ewater flow rate under baseline conditions. The procedure for calculating and incorporating the proportional loadings for each FGD system is

further described in the Case Study Water Quality Modeling Memorandum (DCN SE05570).

EPA accounted for pollutant load ings from non-steam-electri c point sources within the modeling boundary by using 2011 TRI and DMR data. EPA assumed that the annual, historical pollutant loadings for these point sources th roughout the modeling peri od were equal to the pollutant loadings reported in the 2011 TRI and DMR data sets. To account for contributions from nonpoint sources, EPA evaluated STORET water quality monitoring data collected upstream of the modeling boundary. The Agency used these monitoring data to represent the pollutant contributions from all point, nonpoi nt, and background sources upstream of the monitoring location, potentially avoiding the need to collect TR I and DMR pollutant loadings data and perform WASP modeling of t hose upstream or tributary reaches. The Case Study Water Quality Modeling Memorandum (DCN SE05570) further discusses how EPA incorporated DMR pollutant loadings data, TRI po llutant loadings data, and STOR ET monitoring data into the WASP water quality models.

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The results of this baseline modeling prov ided initial receiving water and sediment concentrations for modeling discharges after the assumed compliance date, discussed in the following section.

Modeling of Pollutant Loadi ngs Under the Final Rule

EPA developed and executed WASP water qual ity models (as described in Section 8.1.3) for the selected case study locations to predic t the decreases of receiving water and sediment pollutant concentrations (relative to baseline conditions) following impl ementation of the final

rule.

EPA executed separate models for continued baseline pollutant lo adings and regulatory option pollutant loadings (Options A through D) 64 . These modeling peri ods started at the assumed compliance date, as determined by each steam electric power plant’s permitting cycle, and continued for at least 10 years after the a ssumed compliance date. EPA used the pollutant loadings calculated under the regulatory options to represent the annual st eam electric pollutant loadings for each year of the period following implementation of the final rule. EPA assumed that the pollutant contributions from non-steam-electric point sources (based on TRI and DMR data) and from nonpoint sources (based on STOR ET monitoring data) would remain constant and would be equal to those used to model the period leading up to implementation of the final

rule.

8.1.3 Development and Execution of WASP Models

EPA built each case study model using the BASINS setup tool for WASP, known as the WASP Model Builder, which allows the user to open WASP directly from the BASINS interface. As described in Section 8.1.2, EPA’s approach used the Simple Toxicant module within WASP for the eight modeled pollutants. The Simple Toxicant module puts stretches of the modeled receiving water into segments based on the hydrologic characteristics. The WASP

model calculates the water column and benthic pollutant concentrations using user-defined parameters and default assumption values. The pr ocess described in this section is based on using WASP Version 7.52 and BASINS Version 4.1. Both represent the most current versions available for EPA’s analysis.

EPA followed the general approach describe d below in developing the WASP models for each of the lotic case study locations:

 WASP calculates receiving water and se diment concentrati ons by dividing the waterbody into segments and performing cal culations for each segment. EPA used

NHDPlus Flowlines as the basis for defi ning waterbody segments. To maintain reasonable model runtimes and reduce system instability, EPA further refined these segments by combining short segments suchthat the flow time through each segment is at least a tenth of a day. In some cases, segment travel times were shorter than the

64 Case study modeling omitted Option E because EPA determined that the additional pollutant removals for Option E are only marginally better than Option D. Under Opti on E, only R.D. Morrow Generating Station and W.H. Sammis plant would have additional removals.

8-11Section 8—Case Study Modeling

desired minimum because the segment wa s located between an upstream and downstream tributary of some significance.

 EPA used USGS stream gage flow data to represent inflows at the upstream end of the case study location, as well as any signifi cant tributary with a USGS stream gage station. In all cases, EPA scaled the stre am gage flow data to account for the difference in drainage area between the actu al gage location and the point where the contributing flow enters the model.

 For those tributaries without available USGS stream gage flow data for the simulation period, EPA set the flow rate equal to th e average annual flow rate as per NHDPlus

Version 1.

 To simplify the geographic extent of th e modeling area, EPA did not model any

tributaries with mean annual flow rates of less than 5 cubic feet per second (cfs) as per NHDPlus Version 1.

 EPA used stream gage flow data from the actual time period ( e.g. , 1982 – 2014) to represent the baseline flow rate in the m odeling area. EPA reused the historical flow data to the extent necessary to comple te the modeling period through the assumed compliance date ( e.g. , 2015 – 2020), preferentially selecting flow data from periods that excluded years of partic ularly high or low flow rates. Then EPA reused the

historical flow data to represent the peri od through the end of the model run ( e.g. , 2020 – 2036). This approach ensured that th e modeling periods before and after the assumed compliance date were based on similar flow data.

 To represent non-steam-electric point s ources within the modeling area, EPA assigned the TRI and DMR pollutant loadings to the stream reach (as represented in NHDPlus Version 1) that was closest to the location of the point source.

 EPA used STORET monitoring data, where available, to represent pollutant contributions flowing into the modeling ar ea from upstream point sources, nonpoint sources, and background sources. Prior to incorporation into the WASP model, EPA converted the pollutant concentrations to mass loadings (for all pollutants except TOC and TSS) using the annua l average flow rate for th e stream segment where the sample was collected (as represented in NHD Plus Version 1). This approach ensured that the modeled pollutant c oncentrations flowing into th e modeling area would vary with changes in the stream flow rate.

 To define initial concentrations for th e organic solids, sands, and silts/fines parameters, EPA used TOC and TSS c oncentrations derived from STORET monitoring data collected within the modeling area.

 EPA calibrated the WASP water quality mode ls by modifying the solids transport input parameters until the modeled pollutant concentrations in the benthic segments closely matched the sediment concentrati ons derived from STORET monitoring data.

The existing WASP model used for Lake Sinc lair already divides the waterbody into segments and an existing Environmental Flui d Dynamics Code (EFDC) model provides hydrodynamics for the lentic system. Using an existing model of a lentic system was a reasonable approach to investig ate the regulatory options wit hout developing a detailed model

8-12Section 8—Case Study Modeling

from scratch. However, this approach does limit the modeling period to the period simulated in the existing EFDC model. Other than these diffe rences, the approach fo r developing the WASP model for the lentic system was similar to th e approach described above for lotic systems.

EPA developed the WASP water quality models (for both lotic and le ntic systems) to provide output data for pollutant concentration (total, dissolved, and sorbed) in the water column and benthic segments on a daily ou tput time step. The WASP mode ls generate these outputs for both the immediate receiving water and every dow nstream segment. As described in Section 8.1.2, EPA then executed the models to represent conditions before and after implementation of

the final rule.

Appendix G provides additional information re garding the specific input parameters ( e.g. , background pollutant concentrations, USGS tim e series flow data) and model settings ( e.g. , solids transport parameters) for each of th e WASP water quality models. For additional documentation regarding the use or bypassing of specific WASP model fe atures, incorporating stream gage flow and pollutant loadings data, a nd default settings and assumptions, refer to the Case Study Water Quality Modeling Memorandum (DCN SE05570).

8.1.4 Use of WASP Water Quality Model Outputs

For each modeled segment, EPA used the water column and benthic sediment pollutant concentration outputs (for baselin e and Option D, both from the WASP model run representing the time period after the assumed compliance date) to perform the following environmental and human health analyses:

 EPA compared the modeled pollutant concen trations in the water column (daily outputs) to the water qualit y benchmarks listed in Table C-7 of Appendix C and calculated the frequency of exceedances over the entire modeling period ( i.e. , the percentage of days that have a modeled exceedance).

 EPA compared the modeled pollu tant concentrations in th e benthic sediment (daily outputs) to the sediment biota chemical stressor concentration limit (CSCL) benchmarks listed in Table D-2 of Appe ndix D and calculated the frequency of exceedances over the entire modeling period ( i.e. , the percentage of days with a modeled exceedance).

 EPA compared the modeled pollutant concen trations in the water column (averaged over the entire modeling period) to the water pollutant concentrations that would result in exceedances if used as inputs to the wildlife and human health modules in the IRW model (as described in Section 7.6).

For the Black Creek case study, which had relatively high concentrations of selenium compared to the other selected case studies, EPA also performed ecological risk modeling following the methodology described in Section 5.2.

Using the WASP water quality outputs in these analyses allowed EPA to evaluate, with greater focus and accuracy, the potential for additional environmental and human health impacts that were not reflected in the IRW model outputs. These included impacts associated with peak pollutant concentrations during low-flow pe riods; long-term accumulation of pollutants in

8-13Section 8—Case Study Modeling

benthic sediment; impacts in downstream receivi ng waters; and pollutant contributions from

non-steam-electric sources.

8.1.5 Limitations of Case Study Modeling

The results of the case study models are intende d to illustrate the types and magnitudes of environmental impacts that are likely to have occurred, and which may c ontinue to occur, in surface waters that receive discharges of the ev aluated wastestreams from steam electric power plants. Similarly, the case study modeling results provide valuable information regarding the relative magnitude of water quality improvement s predicted for each of the regulatory options.

In developing the case study models, EPA fo und it necessary to incorporate several assumptions that simplified the modeling approach while introduci ng uncertainty into the model results. For example, due to a lack of data regarding temporal variability in point source loadings, EPA assumed that the pollutant loadi ngs from steam electric power plants and other point sources are st atic loadings ( i.e. , a constant daily average load ing rate). This approach does not account for temporal variabilit y in the loadings to receiving waters due to factors such as variable plant operating schedules , storm flows, low-flow events , and catastrophic events. In actuality, steam electric power plants and other point sources could adjust wastewater discharge rates based on stream flow conditions or other considerations. For instance, a plant could reduce discharges during periods of low flow in th e receiving water and incr ease discharges during periods of high flow, resulting in surface water con centrations that differ from what is predicted by the case study model. These assumptions infl uence the relationship between modeled and

actual surface water concentrations at specific locations and times.

Appendix G further discusses the limitations and assumptions made in developing the case study models and describes in more deta il the development of each case study model, including input parameters ( e.g. , pollutant loadings) and model settings. Refer to the Case Study Water Quality Mode ling Memorandum (DCN SE05570) for discussi on of EPA’s technical approach and data acceptance criteria to inco rporate DMR, TRI, and STORET monitoring data.

8.2 Q UANTIFIED E NVIRONMENTAL I MPACTS AND I MPROVEMENTS FROM C ASE S TUDY
M ODELING

As described in Section 8.1.1, EPA identified si x representative case study locations that would capture the types of impact s to surface waters associated with steam electric power plant discharges, capture the improvements expected ac ross the regulatory options, represent the four wastestreams evaluated in the EA, and represent both lentic and lotic systems. Figure 8-1 and Table 8-1 present the six receiving waters that EPA selected for case study modeling.

Section 8.2 introduces each of the six selected case study locations and presents the scope, inputs, and modeling results. For each case study, EPA presents:

 Potential impacts to aquatic life, wildlife, and human health under baseline conditions;

 Improvements to aquatic life, wildlife, a nd human health following compliance with the final rule; and

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 Comparison of the case study and IRW model results for the ca se study location.

Although EPA modeled the expected environmental improvements under Options A through D, this section primarily presents th e water quality, wildlife, and human health improvements under the final rule (Option D). Appendix G of this re port includes figures illustrating the water column concentrations out put for the immediate receiving water both for baseline conditions and following compliance with the final rule, for those modeled pollutants that exceed one or more water quality benchm arks based on modeling results. These figures present the National Recommended Water Quality Criteria (NRWQC) and Maximum contaminant level (MCL) benchmarks for the modeled pollutant and the steady-state water

column concentration results from the IRW mode l. Appendix G also includes the average total

water column concentration for each of the modeled pollutants in WASP model segments downstream of the modeled case study plants.

8.2.1 Black Creek Case Study

Black Creek flows south-southeast through southern Mississippi from Hattiesburg through the De Soto National Forest until it conver ges with the Pascagoula River. Black Creek is Mississippi’s only designated National Wild and Scenic River (for 21 miles) under the National Wild and Scenic Rivers System Act. South Mississippi Electric Power Association’s R.D. Morrow, Sr. (Morrow) Generating Site (Plant ID 1185) is a 400-mega watt (MW) coal-fired power plant operating alongside Black Creek n ear Purvis, Mississippi. Morrow’s two standalone steam turbine generating units repor ted producing more than 2,000,000 megawatt-hours (MWh) of electricity in 2009. Based on data obt ained from the Steam Electric Survey, Morrow Generating Site discharges F GD wastewater, bottom ash tran sport water, and combustion residual leachate directly into Black Creek. Tabl e 8-2 contains some general information on the two steam electric generating units at Morrow Generating Site.

Table 8-2. Summary of Morrow Generating Site Operations

SE Unit Fuel Capacity (MW) Fly Ash Bottom Ash FGD (Year Installed)

1 Bituminous coal and

No. 2 fuel oil 200 Dry conveyed Wet handled to impoundment Wet system (1978)

2 Bituminous coal and

No. 2 fuel oil 200 Dry conveyed Wet handled to impoundment Wet system (1978)

Source: ERG, 2015j.

Acronyms: FGD (Flue gas desulfurization) ; MW (Megawatt); SE (steam electric).

Modeling Area

The Black Creek WASP model encompasses a 95-mile reach of Black Creek, extending from the Morrow Generating Site discharge outfa ll on Black Creek to the confluence of Black Creek and Red Creek. The immediate receiving wate r that Morrow Generating Site discharges to is approximately 1.6 miles long, as defined in th e WASP model. This mo deling area includes the 21-mile span of the waterway, from Moody’s Landing to Fairley Bridge Landing, that is

8-15Figure 8-2. Black Creek WASP Modeling Area Section 8—Case Study Modeling

protected under the National Wild and Scenic River Systems Ac t. Figure 8-2 illustrates the

location and extent of the Black Creek WASP model.

Identified Point Sources and Background Concentrations

As discussed below, EPA reviewed availa ble pollutant loadings (DMR and TRI) and monitoring data (STORET) for potential incorporation into th e Black Creek WASP model to represent pollutant contributions from backgr ound and non-steam-electric point sources, and for use in calibrating the model results.

 Upstream pollutant contributions . EPA did not identify sufficient STORET monitoring data to represent pollutant c ontributions from upstream of the MorrowGenerating Site immediate receiving water. EPA did not identify any upstream nonsteam-electric point sources with loadings for the eight modeled pollutants. EPA therefore assumed pollutant concentrations of zero within the water column at the upstream boundary of the modeling area.

 Downstream pollutant contributions . EPA incorporated STORET data from eight monitoring stations to represent the polluta nt contributions flow ing into the modeling

8-16Section 8—Case Study Modeling

area downstream of the Morrow Generati ng Site immediate receiving water ( i.e.

, tributaries flowing into Black Creek). EP A did not identify any non-steam-electric point sources whose pollutant loadings would significantly influence the model results in the downstream modeling area.

 Monitoring data within the modeling area. EPA compiled STORET data from two monitoring stations located within the mode ling area and used these data to calibrate

the WASP model.

Modeling Period

The modeling period starts in 1982 (the year of the last revision to the steam electric ELGs) and extends through 2036, covering a peri od of 55 years. Based on Morrow Generating Site’s NPDES permitting cycle, EPA assumes that the plant will achieve the limitations under the final rule by 2019.

Modeling Results - Water Quality

Under baseline conditions, the modeled pollu tant concentrations in the immediate receiving water and downstream reaches exceed the NRWQC water quality benchmarks for four modeled pollutants, indicating that pollutant loadings from the Morrow Generating Site may quantifiably reduce water quality in the modele d portions of Black Creek. The reduced water quality is primarily attributed to arsenic, cad mium, selenium, and thallium. Intervals of higher pollutant concentrations occur dur ing periods of low flow in Black Creek for all eight modeled pollutants.

The baseline modeled pollutant concentrations exceed human health criteria primarily for arsenic, thallium, and selenium, as discussed below:

 Arsenic concentrations in the immediate receiving water exceed the water quality benchmark for consumption of water a nd organisms (0.018 micrograms per liter (μg/L)) for 99 percent of the modeling period. These exceedances continue downstream, generally at a reduced fre quency, throughout the entire 95-mile-long modeling area downstream of the plant.

 Arsenic concentrations in the immediate re ceiving water also exceed the higher water quality benchmark for consumption of orga nisms only (0.14 μg/L) for 16 percent of the modeling period. These exceedances continue downstream, at a reduced frequency, throughout the entire 95-mile-long modeling area downstream of the plant.

 Thallium concentrations in the immediat e receiving water exceed the water quality benchmark for consumption of water and organisms (0.24 μg/L) for 17 percent of the modeling period. These exceedances continue downstream, at a reduced frequency, throughout the entire 95-mile-long modeli ng area downstream of the plant.

 Thallium concentrations in the immediate receiving water also exceed the higher water quality benchmark for consumption of organisms only (0.47 μg/L) for 1 percent of the modeling period. These exceedan ces continue downstream throughout the entire 95-mile-long modeling area downstrea m of the plant. The frequency of

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exceedances downstream ranges from less than 1 percent to 3 percent of the modeling period.

 On rare occasions (less than 1 percent of the modeling period), selenium

concentrations in reaches downstream of the immediate receiving water exceed the water quality benchmark for consumption of water and organisms (170 μg/L). These

exceedances occur in 5.3 miles of the mode ling area downstream of the plant and up to 88 miles downstream of the plant.

These case study modeling results indicate that, under baseline conditions, humans consuming water and/or organism s inhabiting these modeled portions of Black Creek could be at an elevated risk of the negativ e effects associated with oral exposure to these pollutants (see Section 3.1.1).

Aquatic organisms may be at risk for expos ure to cadmium and selenium under baseline conditions, as discussed below:

 Cadmium concentrations in the immediate receiving water exceed the freshwater aquatic life criteria for ch ronic exposure (0.25 μg/L) fo r 39 percent of the modeling period. These exceedances continue downstr eam, at a reduced frequency, throughout 28 miles of the modeling area downstream of the plant.

 Selenium concentrations in the immediat e receiving water exceed the freshwater aquatic life criteria for ch ronic exposure (5.0 μg/L) for 43 percent of the modeling period. These exceedances continue downs tream throughout the entire 95-mile-long modeling area downstream of the plant. The frequency of exceedances downstream ranges from 2 percent to 51 pe rcent of the modeling period.

These case study modeling results indicate that, under baseline conditions, aquatic organisms inhabiting these modeled portions of Black Creek could be at an elevated risk of the negative effects associated w ith oral exposure to these pollutants (see Section 3.1.1).

Under baseline conditions, the modeled pollu tant concentrations in the immediate receiving water and downstream reaches o ccasionally exceed the MCL drinking water benchmarks for three modeled pollutants. The base line modeled pollutant concentrations exceed drinking water criteria for cad mium, selenium, and thallium, as discussed below:

 On rare occasions (less than 1 percent of the modeling period), cadmium concentrations in the immediate receiving water exceed the MCL benchmark (5 μg/L). These exceedances co ntinue downstream throughout the entire 95- mile-long modeling area downstream of the plant. The frequency of exceedances downstream ranges from less than 1 percent to 5 percent of the modeling period.

 On rare occasions (less than 1 percent of the modeling period), selenium concentrations in the immediate receiving water exceed the MCL benchmark (50 μg/L). These exceedances continue downstream, generally at a reduced frequency, in 93 miles of the modeling area downstream of the plant.

 On rare occasions (less than 1 per cent of the modeling period), thallium

concentrations in downstream reaches of the modeling area exceed the MCL (2

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μg/L). These exceedances occur in 8.9 mile s of the modeling area downstream of the plant and up to 92 miles dow nstream of the plant.

Modeling results do not indicate any exceedances of NRWQC or MCL criteria for the other modeled pollutants (copper, nickel, lead, and zinc). Appendix G of this report includes figures that illustrate the water column pollutant concentration output for the immediate receiving water for arsenic, cadmium, selenium, and thallium. These figures also present the NRWQC and MCL benchmarks for the pollutant and the steady-state water column pollutant concentrations predic ted by the IRW model.

The final rule modeling results show signi ficantly decreased concentrations of all modeled pollutants in the immediate receiving wa ter, which will greatly improve water quality. These pollutant removals result in fewer exceedances of NRWQC and MCL benchmarks compared to those estimated in the baseline modeling. Case study mode ling results for Black Creek reveal the following water qual ity improvements under the final rule:

 For arsenic:

- Exceedances of the human health water quality benchmark for consumption of water and organisms reduce in frequency from 99 percent to 94 percent of the modeling period in the immediate receiving water. Additionally, the exceedances of this benchmark reduce in frequency in all remaining sections of the downstream modeling area follo wing compliance with the final rule. Despite the

continued exceedances of this human h ealth criteria, reducing the pollutant concentrations in the water column may decrease the risk to humans consuming contaminated water and organisms.

- Exceedances of the human health water quality benchmark for consumption of organisms reduce in frequency from 16 percent to 6 percent of the modeling period in the immediate receiving water. Additionally, the exceedances of this benchmark reduce in frequency in all remaining sections of the downstream modeling area following compliance with the final rule. Despite the continued exceedances of this human health criteria, reducing the pollutant concentrations in the water column may decrease the ri sk to humans consuming contaminated organisms.

 For cadmium:

- Exceedances of the aquatic life water qua lity criteria for chronic impacts are eliminated throughout the entire modeling area.

- Exceedances of the MCL benchmark are eliminated throughout the entire modeling area.

 For selenium:

- Exceedances of the human health water quality benchmark for consumption of water and organisms are eliminated throughout the entire modeling area.

- Exceedances of the MCL benchmark are eliminated throughout the entire modeling area.

8-19Section 8—Case Study Modeling

- Exceedances of the aquatic life water qua lity criteria for chronic impacts are eliminated in 13 miles of the modeling area, including the immediate receiving

water. The exceedances of this benchmar k reduce in frequency to less than 4 percent in all remaining sections of the downstream modeling area following compliance with the final rule. Most of these exceedances occur within the first year following compliance with the final rule (due to the gradua l recovery of the system following the pollutant loading removals). Despite the continued exceedances of these human health criteria, reducing the pollutant concentrations in the water column may decrease risk to humans consuming contaminated water and/or organisms.

 For thallium:

- Exceedances of the MCL benchmark are eliminated throughout the entire modeling area.

- Exceedances of the human health water quality benchmark for consumption of water and organisms reduce in frequency from 17 percent to less than 1 percent of the modeling period in the immediate receiving water. Additionally, the

exceedances of this benchmark reduce in fr equency in all remaining sections of the downstream modeling area following comp liance with the final rule. Despite

the continued exceedances of this human health criteria, reducing the pollutant concentrations in the water column may decrease the risk to humans consuming contaminated water and organisms.

- Exceedances of the human health water quality benchmark for consumption of organisms are eliminated in 6.2 mile s of the modeling area, including the immediate receiving water. Additionally, the exceedances of these benchmarks reduce in frequency in all remaining s ections of the downstream modeling area following compliance with the final rule . Despite the continued exceedances of this human health criteria, reducing the pollutant concentrations in the water column may decrease risk to humans consuming contaminated organisms.

Modeling Results – Wildlife

EPA assessed the potential threat to piscivorous wildlife from the evaluated wastestreams by modeling the average pollutant concentrations in the water column and comparing these to the concentrations that would trigger exceedances of no effect hazard concentrations (NEHC) for minks and eagles developed by the USGS. Unde r baseline conditions, Bl ack Creek may pose a risk to minks and eagles that consume fish contaminated with selenium. The average modeled

selenium concentrations in 90 miles of the Black Creek modeling area are greater than the

concentration that would translate to NEHC exceedances for minks and eagles, demonstrating that the fish inhabiting these por tions of Black Creek may pose a potential reproductive threat to

terrestrial food webs.

EPA also assessed the potential impact to wild life exposed to sediments in surface waters by comparing estimated pollutant concentrations in the sediment to sediment biota CSCL benchmarks. Modeling results demonstrate that cadmium concentrations in the upper benthic sediment of the immediate receiving water ex ceed the CSCL criteria (0.596 mg/kg) during 36

8-20Section 8—Case Study Modeling

percent of the modeling period. Th ese exceedances conti nue downstream for 36 miles of the total modeling area.

Ecological risk modeling results indicate that baseline selenium loadings also present an elevated risk of widespread negative reproduc tive impacts (larval mortality and deformities) among fish that inhabit the immediate receiving water of Black Creek. The results illustrate the significant increase in risk that can result from minor variations in selenium bioaccumulation patterns and toxicity responses within the organisms that inhabit a particular waterbody. Specifically:

 The median (50 th percentile) of the model out puts indicates that selenium concentrations in the fish eggs and ovari es would cause reproductive impacts in less than 1 percent of the exposed fish population.

 However, there is a 35 per cent probability that these concentra tions are high enough to cause reproductive impacts in more than 30 percent of the expos ed fish population.

 There is a 25 percent probability that th ese concentrations ar e high enough to cause reproductive impacts in more than 80 percent of the exposed fish population.

Ecological risk modeling results also indicate an elevated risk of widespread negative reproductive impacts (hatching failure) among mallard s that forage or br eed in the immediate receiving water of Black Creek. Specifically:

 There is a 50 percent probability that seleni um concentrations in the mallard eggs are high enough to cause reproductive impacts in at least 9 percent of the exposed mallard population.

 There is a 35 percent probability that th ese concentrations ar e high enough to cause reproductive impacts in more than 20 pe rcent of the exposed mallard population.

 There is a 10 percent probability that th ese concentrations ar e high enough to cause reproductive impacts in more than 70 percent of the exposed mallard population.

Elevated risks of reproductive impacts to fish and mallards continue downstream from the immediate receiving water. Ecological risk m odeling results indicate that the entire 95-mile modeled length of Black Creek has selenium concen trations that lead to a 10 percent or greater probability of negative reproductive impacts among at least 17 percent of the exposed fish or mallard populations. Additionally, several downstr eam segments of Black Creek (totaling 29 miles) have selenium concentrations that lead to a 25 percent or greater probability of negative reproductive impacts among at least 10 percen t of the exposed mallard population.

The case study modeling results demonstrate that the final rule will significantly reduce pollutant concentrations and the associated impacts to wildlife that inhabit Black Creek. The

final rule will eliminate selenium exceedances of the NEHC benchmarks for minks and eagles in

all modeled reaches of Black Creek. The final rule will also eliminate CSCL benchmark

exceedances for cadmium in 27 miles of the m odeling area, including the immediate receiving

water. The exceedances of this benchmark reduce in frequency to 3 percent or less in all remaining sections of the downstream modeling area following compliance with the final rule. Most of these remaining exceedances occur within the first year following compliance with the

8-21Section 8—Case Study Modeling

final rule. Ecological risk modeling results also indicate that the fina l rule will eliminate the risk of selenium-related adverse reproductive imp acts among exposed fish and mallards in all modeled reaches of Black Creek ( i.e. , the risk to fish and mallards is less than 0.1 percent at the

95 th percentile egg/ovary concentration).

Modeling Results – Human Health

EPA evaluated the potential threat to human receptors due to consumption of

contaminated fish from Black Creek. EPA modele d the average pollutant concentrations in the water column and compared these to the concentra tions that would trigger exceedances of either the non-cancer reference dose or the 1-in-a-million lifetime excess cancer risk (LECR). Under baseline conditions, the average water column concentration of arsenic throughout the modelingarea downstream of the plant does not result in an estimated cancer risk greater than 1-in-amillion for any of the national-scale cohorts. See Appendix E for details on the human health

module of the IRW model and national-scale cohorts.

Based on the average pollutant concentra tions in the water column under baseline conditions, cadmium, selenium, and thallium pose the greatest threat to ca use non-cancer health

effects in humans from fish c onsumption, as discussed below:

 Average thallium concentrations in the wa ter column throughout the entire 95-milelong modeling area are greater than the c oncentration that would translate to

exceedance of the reference doses for at l east one child subsistence fisher cohort (with all child subsistence cohorts impacted by 59 or more miles of the modeling area downstream of the plant), while the concentr ations in 90 miles of the modeling area are high enough to trigger exceedance of the reference dose for adult subsistence fishers. Additionally, the average thallium concentrations in 59 miles of the modeling area are high enough to trigger exceedance of the reference dose for at least one child

recreational fisher cohort.

 Average selenium concentrations in the water column throughout the entire 95-milelong modeling area are greater than the c oncentration that would translate to

exceedance of the reference dose for the adult subsistence fisher cohorts and at least

one child subsistence fisher cohort (with all ch ild subsistence cohor ts impacted by 90 or more miles). Additionall y, the average selenium con centrations are high enough to trigger exceedances of the reference doses for adult recreational fishers and at least

one child recreational fisher cohort in 13 miles and 90 miles of the modeling area, respectively.

 Average cadmium concentrations in the wa ter column in 38 miles of the modeling area are greater than the concentration th at would translate to exceedance of the

reference dose for at least one child subsistence fisher cohort.

Therefore, humans who consume cadmium-, se lenium-, or thallium-contaminated fish inhabiting these waters may be at greater ri sk for developing the negative health effects associated with these pollutants, which are discussed in Section 3.1.1.

8-22Section 8—Case Study Modeling

The modeling results demonstrate significan t reductions in average water column concentrations of cadmium, selenium, and thal lium under the final rule, which would reduce average cadmium and selenium concentrations e nough to eliminate the risk for non-cancer health effects for all cohorts throughout the entire mode ling area. These loadings reductions would also reduce the thallium concentrations enough to elim inate the risk for non-cancer health effects for

adult subsistence and child recr eational fishers. While the case study model continues to show average thallium concentrations that may pose non-cancer health e ffects for at least one child subsistence cohort, the total ar ea of impact is reduced by up to 37 miles (with some child

subsistence cohort non-cancer ri sks being eliminated throughout the entire modeling period downstream of the plant).

Interpretation of Black Creek Results

Case study modeling results for Black Creek indicate greater water quality, wildlife, and human health impacts to the im mediate receiving water under baseline conditions than predicted by the IRW model. Case study modeling results fo r Black Creek also dem onstrate water quality

benchmark exceedances and risks to wildlife and humans sustaining beyond Morrow Generating Site’s immediate receiving water. In some inst ances, the average water column concentrations can increase in some portions of the downstream modeling area, posing a greater threat to humans, aquatic organisms, and terrestrial ecosystems. This phenomenon is most pronounced for modeled pollutants with the la rgest partition coefficients ( i.e. , lead, zinc, cadmium, and copper) suggesting that sediment transport has significant influence in this small receiving water. Under baseline conditions, significant water quality, wildlife, and human health impacts are identified in the modeled area corresponding with 21-mile span of the waterway that is protected under the National Wild and Scenic River Systems Act.

Ecological risk modeling results for the Black Creek case study indicate that the risk of negative reproductive effects among fish and malla rds exposed to selenium may be significantly greater than predicted using wa ter quality outputs from the IR W model. Use of the case study water quality outputs, which include extended periods of elevated selenium concentrations that

are not reflected in the IRW m odel outputs, reveals the potenti al for widespread ecological impacts among wildlife that inhabit, forage, or br eed in the immediate r eceiving water of Black

Creek and its downstream waters.

The USGS stream gage flow data used in the case study model indicate that flow rates in Black Creek are typically lower than the annual av erage flow rate used in the IRW model, while greatly exceeding the annual average flow rate during occasional high-flow events. During the frequent periods of below-average flow, the po llutant concentrations in the modeling area quickly climb to levels associated with nega tive impacts to fish, wildlife, and humans.

The exceedances identified in the Black Creek WASP model are based solely on discharges of the evaluated wastestreams from the steam electric power plant because EPA did not identify any STORET monitori ng data or point sources sugge sting any other sources were contributing pollutant discharges to the mode ling area. The Black Cr eek WASP model may be underestimating the pollutant concentrations actually present if there are other discharges that were not captured in the DMR and TRI data sets . Under the final rule, case study modeling of

Black Creek indicates that th e waterbody will exhibit fewer exceedances of water quality

8-23Section 8—Case Study Modeling

benchmarks; will no longer pose reproductive risks to higher trophic-level w ildlife; will pose less risk to benthic organisms; and will pose less ri sk to humans consuming fish. The extent of improvements identified by the case study model is greater than what was projected by the IRW model. The decrease of the average pollutant concentrations within the immediate receiving water occurs very quickly after compliance with the final rule; however, some downstream reaches of the modeling area take up to a year to reach equilibrium.

8.2.2 Etowah River Case Study

The Etowah River is a 164-mile-long waterway north of Atlanta, Georgia. The river flows west-southwest from Amicalola Creek, the primary tributary, to Ro me, Georgia, where it

meets the Oostanaula River and forms the Coosa River at their confluence. Once estimated to have 91 native fish species, the Etowah watershed is biologically one of th e richest river systems in North America. Eight imperiled fish species, three of which are federally listed as endangered or threatened, are known to inhabit the Etowah watershed, and five mollusk species are believed to have been decimated [Etowah Aquatic Habitat Conservation Plan, 2015].

The Etowah River serves as a source of cooling water for, and receives steam electric wastewater discharges from, Southern Company’s Plant Bowen (Plant ID 2244), located in Cartersville, Georgia. In commercial operation since 1975, Plant Bowen is bordered on two sides by the Etowah River and Euharlee

Creek. Plant Bowen’s f our stand-alone steam turbine generating units have a total nameplatecapacity of 3,499 MW. As the nation’s ninthlargest power plant in net ge neration of electricity, Plant Bowen reported producing almost 23,000,000 MWh of electricity in 2009 [Georgia Po wer, 2014]. Based on data EPA obtained in responses to the Steam Electric Survey, Plan t Bowen discharges two of the evaluated wastestreams, FGD wastewater and bottom ash tran sport water, directly to the Etowah River. Table 8-3 contains general info rmation on the four steam elect ric generating units at Plant

Bowen.

In estimating the historical pollutant loadi ngs associated with Plant Bowen’s four FGD systems, EPA incorporated the pollutant loadings from FGD wastewater as the systems were installed, between 2008 and 2011. EPA did not mode l any FGD wastewater pollutant loadings before the installation of Plant Bowen’s first FGD system. Georgia Power Company’s Plant Bowen

8-24Section 8—Case Study Modeling

Table 8-3. Summary of Plant Bowen Operations

SE Unit Fuel Capacity (MW) Fly Ash Bottom Ash FGD (Year Installed)

1 Bituminous coal and

No. 2 fuel oil 806 Dry conveyed Wet handled to impoundment Wet system (2010)

2 Bituminous coal and

No. 2 fuel oil 789 Dry conveyed Wet handled to impoundment Wet system (2009)

3 Bituminous coal and

No. 2 fuel oil 952 Dry conveyed Wet handled to impoundment Wet system (2008)

4 Bituminous coal and

No. 2 fuel oil 952 Dry conveyed Wet handled to impoundment Wet system (2008)

Source: ERG, 2015j.

Acronyms: FGD (Flue gas desulfurization) ; MW (Megawatt); SE (steam electric).

Modeling Area

The Etowah River WASP model encompasses a 35-mile segment of the Etowah River, extending from the immediate re ceiving water to the confluence of the Etowah River and Silver Creek. The immediate receiving water to which Plant Bowen discharges is approximately 3.6 miles long, as defined in the WASP model. Figure 8-3 illustrates the loca tion and extent of the

Etowah River WASP model.

8-25Figure 8-3. Etowah River WASP Modeling Area Section 8—Case Study Modeling

Identified Point Sources and Background Concentrations

As discussed below, EPA reviewed availa ble pollutant loadings (DMR and TRI) and monitoring data (STORET) for pot entia l incorporation into the Etowah River WASP model to represent pollutant contributions from backgr ound and non-steam-electric point sources, and for use in calibrating the model results.

 Upstream pollutant contributions . EPA incorporated STORET data from four monitoring stations to represent the polluta nt contributions from upstream of the Plant Bowen immediate receiving water. EPA also identified two upstream non-steamelectric point sources whose pollutant load ings (from DMR and TRI data sets) could influence the model results; however, EPA as sumed that the STORET data from the four monitoring stations (which encompa ss all of the modeled pollutants except for selenium) adequately reflect the pollutant contributions from ups tream point sources. Therefore, EPA did not incorporate pollu tant loadings from the two identified upstream non-steam-electric point sources.

8-26Section 8—Case Study Modeling

 Downstream pollutant contributions . EPA incorporated STORET data from 10 monitoring stations to represent the po llutant concentrations flowing into the modeling area downstream of the Plant Bowen immediate receiving water ( i.e.

, tributaries flowing into the Etowah Ri ver). EPA did not id entify any non-steamelectric point sources whose pollutant lo adings would significantly influence the model results in the downstream modeling area.

 Monitoring data within the modeling area . EPA compiled STORET data from six monitoring stations located within the mode ling area and used these data to calibrate

the WASP model.

The contributions of arsenic, cadmium, coppe r, lead, and thallium from upstream sources have a much greater influence on the modeled pollu tant concentrations in the Etowah River than the pollutant loadings from Plant Bowen. The cont ributions of nickel and zinc from upstream sources also strongly influence the modeled pollu tant concentrations in the Etowah River.

The Etowah River case study model did not account for the documented surface water impacts from Plant Bowen that are discussed in Section 3.3.3. In 2002, a sinkhole developed in the surface impoundment at Plant Bowen that released 2.25 million gallons of ash/water mixture, estimated to contain 80 tons of ash, to Euharlee Creek, which immediately flows into the Etowah River [U.S. EPA, 2014b]. Additionally, an extreme rainfall event in 2008 caused a dry ash stockpile to collapse, depositing approximately tw o tons of ash in Euharlee Creek. The surface water quality impacts resulting from these events ar e not reflected in this model; therefore, the case study modeling could under-represent the act ual baseline impacts of Plant Bowen on the

Etowah River.

Modeling Period

The modeling period starts in 1982 (the year of the last revision to the steam electric ELGs) and extends through 2032, covering a period of 51 years. Based on Plant Bowen’s NPDES permitting cycle, EPA assumes that the plant will achieve the limitations under the final rule by 2021.

Modeling Results – Water Quality

Under baseline conditions, the modeled pollu tant concentrations in the immediate receiving water and downstream reaches exceed the NRWQC water quality benchmarks for five modeled pollutants, indicating th at pollutant loadings from Pl ant Bowen may contribute to a quantifiable reduction in water quality in the mode led portions of the Etowah River. The reduced water quality is primarily attributed to arsenic, cadmium, selenium, thallium, and lead.

The baseline modeled water concentrations exceed human health criteria primarily for arsenic and thallium, as discussed below:

 Arsenic concentrations in the immediate receiving water exceed the water quality benchmark for consumption of water and organisms (0.018 μg/L) for the entire modeling period. These exceedances continue downstream, at the same frequency, throughout the entire 35-mile-long modeli ng area downstream of the plant.

8-27Section 8—Case Study Modeling

 Arsenic concentrations in the immediate re ceiving water also exceed the higher water quality benchmark for consumption of or ganisms only (0.14 μg/L) for the entire modeling period. These exceedances continue downstream, at the same frequency, throughout the entire 35-mile-long modeli ng area downstream of the plant.

 Thallium concentrations in the immediat e receiving water exceed the water quality benchmarks for consumption of water and organisms (0.24 μg/L) for more than 99 percent of the modeling period. These ex ceedances continue downstream, at an increased frequency, throughout the entire 35-mile-long modeling area downstream of the plant.

 Thallium concentrations in the immediate receiving water also exceed the higher water quality benchmark for consumpti on of organisms only (0.47 μg/L) for 90 percent of the modeling period. These ex ceedances continue downstream, at an increased frequency, throughout the entire 35-mile-long modeling area downstream of the plant.

These case study modeling results indicate that, under baseline conditions, humans consuming water and/or organisms inhabiting th ese modeled portions of the Etowah River may be more at risk of the negative effects associated with oral exposure to ar senic and thallium (see Section 3.1.1).

Aquatic organisms may be at risk for expos ure to cadmium and selenium under baseline conditions, specifically:

 Cadmium concentrations in the immediate receiving water exceed the freshwater aquatic life criteria for ch ronic exposure (0.25 μg/L) fo r 52 percent of the modeling period. These exceedances continue downstream throughout the 35-mile-long modeling area downstream of the plant. The frequency of exceedances downstream ranges from 33 percent to 55 pe rcent of the modeling period.

 On rare occasions (less than 1 percent of the modeling period), selenium

concentrations in downstream reaches of the modeling area exce ed the freshwater aquatic life criteria for chronic exposure (5 μg/L). These exceedances occur in 4.7 miles of the downstream modeling area downs tream of the plant and up to 35 miles downstream of the plant.

These modeling results indicate that, under baseline conditions, aquatic organisms residing in the portions of the Etowah River with modeled exceedances may be more at risk to negative impacts from chronic expo sure to cadmium and selenium.

Under baseline conditions, the modeled pollu tant concentrations in the immediate receiving water and downstream reaches exceed the MCL drinking water benchmarks for four modeled pollutants. The baseline modeled pollu tant concentrations exceed drinking water criteria for thallium, arsenic, cadmi um and lead as discussed below:

 Thallium concentrations in the immedi ate receiving water exceed the MCL benchmark (2 μg/L) for 29 percent of the modeling period. These exceedances

8-28Section 8—Case Study Modeling

continue downstream, at a reduced fre quency, throughout the entire 35-mile-long modeling area downstream of the plant.

 On rare occasions (less than 1 percent of the modeling period), arsenic concentrations in the immediate receiving water exceed the MCL benchmark (10 μg/L). These exceedances do not occur beyond the 3.6-mile-long immediate receiving water.

 On rare occasions (less than 1 percent of the modeling period), cadmium concentrations in downstream reaches of the modeling area exceed the MCL benchmark (5 μg/L). These exceedances occur in 5.1 miles of the downstream modeling area downstream of the plant and up to 35 miles downstream of the plant.

 On rare occasions (less than 1 percent of th e modeling period), lead concentrations in downstream reaches of the modeling area exceed the MCL benchmark (15 μg/L).

These exceedances occur in 5.1 miles of the downstream modeling area downstream of the plant and up to 35 miles downstream of the plant.

Modeling results do not indicate any exceedances of NRWQC or MCL criteria for the other modeled pollutants (copper, nickel, and zinc ). Appendix G of this report includes figures that illustrate the water column pollutant conc entration output for the immediate receiving water for arsenic, cadmium, selenium, and thallium. These figures also present the NRWQC and MCL benchmarks for the pollutant and the steady-st ate water column pollutant concentrations predicted by th e IRW model.

The final rule modeling results show a signifi cant reduction in selenium concentrations and moderately decreased concentrations of cadmi um, nickel, and zinc within the Etowah River, which will improve water quality. These pollutant removals result in fewer exceedances of NRWQC and MCL benchmarks compared to thos e estimated in the baseline modeling. Case study modeling results for the Etowah River re veal the following water quality improvements

under the final rule:

 Exceedances of the cadmium aquatic life wa ter quality criteria for chronic impacts reduce in frequency (by 13 percent) in th e immediate receiving water. Additionally,

the exceedances of these benchmarks reduce in frequency in all remaining sections of the downstream modeling area following co mpliance with the final rule. Despite continued exceedances of these aquatic life criteria, reduc ing the pollutant concentrations in the water column may decrea se the risk to aquatic life in the Etowah

River.

 Exceedances of the selenium aquatic life wate r quality criteria for chronic impacts are eliminated throughout the entire modeling area.

While case study modeling results conti nue to show exceedances for NRWQC

benchmark exceedances of arsenic and thallium and MCL benchmark exceedances of arsenic, cadmium, lead, and thallium, the final rule will reduce loading contributi ons of these pollutants

from Plant Bowen.

8-29Section 8—Case Study Modeling

Modeling Results – Wildlife

Based on the average pollutant concentra tions in the water column under baseline conditions, the modeled portion of the Etowah Ri ver does not exceed the concentrations that

would translate to NEHC exceedances and does not pose a risk to minks and eagles that consume contaminated fish. Despite the modeling not bei ng able to quantify any improvements to minks and eagles under the final rule, the pollutant loading removals will decrease bioaccumulation of toxic pollutants in the terrestrial food chains.

Modeling results do not indicate that there are any pollutant concentrations in the upper

benthic sediment that exceed CSCL benchmarks of for any of the eight modeled pollutants; therefore, the Etowah River does not pose a th reat to benthic organisms in contact with contaminated sediment. Despite the modeling no t being able to quantify any improvements to benthic organisms under the fina l rule, the pollutant loading removals will decrease the concentrations of toxic pollutant s in benthic sediment and decrea se the exposure of organisms to these pollutants.

Modeling Results – Human Health

EPA modeled the average pollutant concentrations in the water column and compared

these to the concentrations th at would trigger exceedances of either the non-cancer reference

dose or the 1-in-a-million lifetime excess cancer risk (LECR). Under baseline conditions, the average water column concentration of arseni c in the immediate receiving water over the modeling period results in an estimated cancer risk greater than 1-in-a-million for adult

subsistence fishers. These exceedances do not occur beyond the 3.6-mile-long immediate receiving water. Therefore, adults who frequen tly consume arsenic-contaminated fish inhabiting the immediate receiving water may be at grea ter risks for development of cancer. Modeling

results demonstrate no reduction in the cancer risk from inorgani c arsenic under the final rule.

Based on the average pollutant concentra tions in the water column under baseline conditions, selenium and thallium pose the greatest threat to cause non-cancer health effects in humans from fish consumption, as discussed below:

 Average selenium concentrations in the im mediate receiving wate r are greater than

the concentrations that woul d translate to exceedance of the reference doses for the child (younger than 11 years old) subsiste nce fisher cohorts. The average selenium concentrations throughout the entire 35-mile-long modeli ng area downstream of the plant are greater than the concentration that would translate to an exceedance of the

reference dose for least one child subsistence cohort.

 Average thallium concentrations in the wa ter column throughout the entire 35-milelong modeling area downstream of the plant ar e greater than the concentrations that

would translate to exceedance of the reference doses for adult and children

recreational and subsisten ce fishers (all national-scal e cohorts evaluated).

Therefore, humans who consume selenium- or thallium-contaminated fish inhabiting the modeled area of the Etowah River may be at greater risk for devel oping the negative health effects associated with these pollutant s, which are discussed in Section 3.1.1.

8-30Section 8—Case Study Modeling

The final rule modeling results demonstrat e significant reductions in selenium concentrations in the Etowah River, which will eliminate selenium exceedances of the noncancer health effects reference dose for all cohort s. While the modeling results continue to show

thallium water concentrations th at would translate to exceedan ces of the non-cancer health effects reference dose, the final rule will redu ce thallium loading cont ributions from Plant

Bowen.

Interpretation of Etowah River Results

Case study modeling results fo r the Etowah River indicate greater water quality and human health impacts than predicted by the IR W model (IRW modeling resu lts did not indicate any quantifiable impacts in the immediate rece iving water of Plant Bowen). By accounting for background pollutant contributions from upstream sources and othe r boundaries (for all modeled pollutants except selenium), case study modeling pr edicts higher pollutant concentrations under baseline conditions. For arsenic and thallium, a nd to a lesser extent cadmium, the projected exceedances are driven by the background concentrations flowing into the Etowah River modeling area. Plant Bowen’s discharges of the evaluated wastestreams may be further impairing the degraded waterway.

Case study modeling results for the Etowah River also demonstrate water quality

benchmark exceedances and risks to humans oc cur beyond Plant Bowen’s immediate receiving water. In some instances, the average water colu mn concentrations can increase in some portions of the downstream modeling area, posing a greater threat to humans and aquatic life. This phenomenon is most pronounced for modeled polluta nts with the largest partition coefficients ( i.e. , lead, zinc, cadmium, and copper), suggesti ng that sediment transport has moderate

influence in the Etowah River.

Case study modeling of the Etow ah River indicates that, unde r the final rule, the Etowah River will exhibit fewer exceedances of water quali ty benchmarks and pose less risk to humans consuming fish that inhabit these waters. The improvements identified by the case study model are more extensive than what was projected by the IRW model. This is due in part to the greater water quality and human healthimpacts under base line conditions, which created additional opportunities for modeled improvements, and in part to the identified improvements in

downstream reaches of the Etowah River that were not evaluated as part of the IRW model. The average pollutant concentrations throughout the entire modeling area reduce promptly after compliance with the final rule.

8.2.3 Lick Creek & White River Case Study

The White River is a two-forked river that primarily flows southwest through central and southern Indiana. The two forks, the West Fork and the East Fork, are nearly equal in size when they converge in Daviess Country, just north of Petersburg, Indiana. From this confluence, the White River flows west-southwest for 50 river-miles until it joins the Wabash River at the

Illinois-Indiana state border. Located on the banks of the lower White River, Indianapolis Power & Light’s (IPL) Petersburg Generating Station (Plant ID 3997) has four stand-alone steam turbine units with a nameplate capacity of 1,864 MW. Th e plant reported that these four coalfired generating units produced more than 12,000,000 MWh of electricity in 2009 in the Steam

8-31Section 8—Case Study Modeling

Electricity Survey. Petersburg Generating Station also operates three minor oil-burning internal combustion units, which are exempt from the re quirements of the final rule. Based on data obtained in responses to the Steam Electric Surve y, this power plant discharges FGD wastewater and bottom ash transpor t water. Table 8-4contains general information on the four coalfired generating units at Petersburg Generating

Station.

In estimating the hi storical pollutant loadings associated with Petersburg Generating Station’s four FGD systems, EPA incorporated the pollutant loadings from FGD wastewater as the systems were inst alled, between 1977 and 1996. EPA included the pollu tant loadings from the FGD systems on units 3 and 4 at the start of the historical modeling period (1986).

Table 8-4. Summary of Petersburg Generating Station Operations IPL’s Petersburg Generating Station

SE Unit Fuel Capacity (MW) Fly Ash a Bottom Ash FGD (Year Installed)

1 Subbituminous coal

and No. 2 fuel oil 255 Dry conveyed Wet handled to impoundment Wet system (05/1996)

2 Subbituminous coal

and No. 2 fuel oil 445 Dry conveyed Wet handled to impoundment Wet system (05/1996)

3 Subbituminous coal

and No. 2 fuel oil 580 Dry conveyed Wet handled to impoundment Wet system (11/1977)

4 Subbituminous coal

and No. 2 fuel oil 584 Dry conveyed Wet handled to impoundment Wet system (04/1986)

Source: ERG, 2015j.

Acronyms: FGD (Flue gas desulfurization) ; MW (Megawatt); SE (steam electric).

a – Based on EPA projections, Petersburg Generating Statio n will convert to dry ash handling to comply with the CCR rulemaking.

Modeling Area

Based on data obtained in responses to the Steam Electric Survey, Petersburg Generating Station discharges FGD wastewater and bottom as h transport water to Lick Creek, a 1.8-milelong tributary emptying into the White River. The White River WASP model encompasses Lick Creek and a 52-mile reach of the White River, 49 miles of which is downstream of Lick Creek. The immediate receiving water, Lick Creek, is the first of three upstream modeling boundaries for this WASP model. The other upstream mode l boundaries are on the West Fork White River and East Fork White River approximately one m ile upstream of their c onfluence. EPA extended the modeling area upstream of Lick Creek to capture and incorpor ate available STORET monitoring data as further de scribed below. The Lick Creek and White River WASP model ends

8-32Figure 8-4. Lick Creek and Whit e River WASP Modeling Area Section 8—Case Study Modeling

at the confluence of the White River with the Wabash River. Figure 8-4 illustrates the location

and extent of the White River WASP model.

Identified Point Sources and Background Concentrations

As discussed below, EPA reviewed availa ble pollutant loadings (DMR and TRI) and monitoring data (STORET) for potential inco rporation into the Lick Creek and White River WASP model to represent pollu tant contributions from background and non-steam-electric point sources, and for use in calibrating the model results.

 Upstream pollutant contributions (Lick Creek) . EPA did not identify sufficient STORET monitoring data to represent pollu tant contributions from upstream of the Petersburg Generating Station immediate re ceiving water (Lick Creek). EPA did not identify any upstream non-steam-electric poin t sources with load ings for the eight modeled pollutants on Lick Creek. EPA ther efore assumed pollutant concentrations

of zero within the water column at th e upstream boundary of the modeling area.

 Upstream pollutant contributions (West Fork White River) . EPA incorporated STORET data from three monitoring stations to represent the pollutant contributions

8-33Section 8—Case Study Modeling

from upstream on the west fork of the White River. EPA also identified three upstream non-steam-electric point sources w hose pollutant loadings (from DMR and TRI data sets) could influence the model results; however, EPA assumed that the STORET monitoring data (which include all of the modeled pollutants except for thallium) adequately reflect the pollutant contributions from upstream point sources. Similarly, EPA identified that a steam elect ric power plant, Ed wardsport Generating Station (Plant ID 8544), has historically di scharged to the west fork of the White River 30 miles upstream of the start boundary. Edwardsport Generating Station discontinued operation of all steam electric generating uni ts in 2011 to construct a new integrated gasification combined cy cle power plant. EPA assumed that the STORET monitoring data adequately reflect the pollutant contributions from this point source. Therefore, EPA did not incor porate pollutant loadings from the three identified upstream non-steam-electric poi nt sources or Edwa rdsport Generating

Station into the WASP model.

 Upstream pollutant contributions (East Fork White River) . EPA incorporated STORET data from one monitoring station to represent the pollu tant contributions from upstream on the east fork of the White River. EPA also id entified one upstream non-steam-electric point source whose polluta nt loadings (from DMR and TRI data sets) could influence the model results; however, EPA assumed that the STORET monitoring data (which include all of the modeled pollutants) adequately reflect the pollutant contributions from upstream point sources. Therefore, EPA did not incorporate pollutant loadings from this identified upstream non-steam-electric point

source in the WASP model.

 Downstream pollutant contributions . EPA incorporated STORET data from four monitoring stations to represent the po llutant concentrations flowing into the modeling area downstream of the Petersburg Generating Station immediate receiving water, Lick Creek ( i.e. , tributaries flowing into the White River). EPA did identify one non-steam-electric point source that di scharges one or more of the modeled pollutants within the modeling area. EPA inco rporated the pollutant loadings from the

identified non-steam-electric point source into the model.

 Monitoring data within the modeling area. EPA compiled STORET data from 12 monitoring stations located within the mode ling area and used these data to calibrate

the WASP model.

The contributions of arsenic, cadmium, coppe r, nickel, lead, and zinc from upstream sources have a much greater influence on the m odeled pollutant concentr ations in White River than the pollutant loadings fr om Petersburg Generating Station.

Due to the lack of pollutant loadings da ta, the White River cas e study model did not account for the ground water impacts from Peters burg Generating Station associated with the damage case listed in Appendix A. In 1997, the catastrophi c release of coal combustion residuals degraded the quality of ground water and surface water around the plant.

The White River case study model does not acc ount for pollutant loadings from Hoosier Energy’s Frank E. Ratts (Ratts) Generating St ation (Plant ID 2314), a 232-MW steam electric power plant located less than a mile downstr eam of Petersburg Generating Station. Based on

8-34Section 8—Case Study Modeling

information obtained in responses to the St eam Electric Survey, Ratts Generating Station discharged one or more of the evaluated wastestr eams directly to the White River. This plant, however, has publicly announced plans to retire all of its steam gene rating units prior to implementation of the final rule. EPA therefor e excluded pollutant loadings from the Ratts Generating Station so that the changes in pollu tant loadings during the modeling period, and the associated environmental improvements, reflect only those attributable to the final rule.

Modeling Period

The modeling period starts in 1986 (the year the last generating unit at Petersburg Generating Station began operati ng) and extends through 2034, covering a period of 49 years. Based on Petersburg Generating Station’s NPDES permitting cycle, EPA assumes that the plant will achieve the limitations under the final rule by 2019.

Modeling Results – Water Quality

Under baseline conditions, the modeled pollutant concentrations in Lick Creek, the immediate receiving water exceed NRWQC wate r quality benchmarks for five modeled pollutants, indicating that pollutant loadings from the Petersburg Generating Station may quantifiably reduce water quality in the modeled portions of Lick Creek. Additionally, the modeled pollutant concentrations in portions of the White River downstream of Lick Creek exceed NRWQC water quality benchmarks for four of the modeled pollutant s, indicating that the water quality downstream of Lick Creek may also be reduced by the pollutant loadings form Petersburg Generating Station.

The baseline modeled pollutant concentrations exceed human health criteria primarily for arsenic, thallium, and selenium, as discussed below:

 Arsenic concentrations in Lick Creek exceed the water quality benchmark for consumption of water and organisms (0.018 μg/L) for the entire modeling period. These exceedances continue downstream in the White River, at the same frequency, throughout the entire 50-mile-long modeli ng area downstream of the plant.

 Arsenic concentrations in Lick Creek also exceed the higher water quality benchmark for consumption of organisms only (0.14 μg /L) for the entire modeling period. These

exceedances continue downstream in the White River, generally at the same frequency, throughout the entire 50-mile-long modeling area downstream of the plant.

 Thallium concentrations in Lick Creek exceed the water quality benchmarks for consumption of water and organisms (0.24 μg/L) for the entire modeling period. These exceedances continue downstream in the White River, at a much lower frequency (less than 2 percent of the m odeling period), throughoutthe entire 50-milelong modeling area downstream of the plant.

 Thallium concentrations in Lick Creek also exceed the higher water quality benchmark for consumption of organisms only (0.47 μg/L) for the entire modeling period. On rare occasions (less than 1 pe rcent of the modeling period), thallium

concentrations in reaches downstream in the White River also exceed this benchmark.

8-35Section 8—Case Study Modeling

These downstream exceedances occur in 26 miles of the modeling area downstream of the plant and up to 31 miles downstream of the plant.

 On rare occasions (less than 1 percent of the modeling period), selenium

concentrations in Lick Creek exceed the wa ter quality benchmark for consumption of water and organisms (170 μg/L). These ex ceedances do not occu r downstream after

the confluence of the Lick Creek and White River.

These case study modeling results indicate that, under baseline conditions, humans consuming water and/or organi sms inhabiting these modeled por tions of Lick Creek and the White River may be more at risk of the negative effects associat ed with oral exposure to these pollutants (see Section 3.1.1).

Aquatic organisms may be at risk for expos ure to copper, seleni um, and cadmium under baseline conditions, as discussed below:

 Copper concentrations in Lick Creek exceed the freshwater aquatic life criteria for chronic exposure (9.0 μg/L) for 45 percent of the modeling period. These

exceedances do not occur downstream after th e confluence of the Lick Creek and

White River.

 Copper concentrations in Lick Creek also ex ceed the higher freshwater aquatic life criteria for acute exposure (13 μg/L) fo r 25 percent of the modeling period. These

exceedances do not occur downstream after th e confluence of the Lick Creek and

White River.

 Selenium concentrations in Lick Creek exceed the freshwater aqua tic life criteria for chronic exposure (5.0 μg/L) for 99 percent of the modeling period. On rare occasions (less than 1 percent of the modeling period ), selenium concentrations in reaches

downstream in the White River also ex ceed this benchmark. These downstream exceedances occur in 21 miles of the modeling area downstream of the plant and up to 32 miles downstream of the plant.

 Cadmium concentrations in Lick Creek exceed the freshwater aquatic life criteria for chronic exposure (0.25 μg/L) for 86 percent of the modeling period. On rare occasions (less than 1 percent of the m odeling period), cadmium concentrations in

reaches downstream in the White Rive r also exceed this benchmark. These

downstream exceedances occur in 18 miles of the modeling area downstream of the plant.

These modeling results indicate that, under baseline conditions, aquatic organisms residing in the portions of Lick Creek and th e White River with modeled exceedances may be more at risk to negative impacts from chroni c exposure to cadmium and selenium. Additionally, the copper loadings from Petersburg Generating St ation may pose a threat from chronic or acute

exposure.

Under baseline conditions, the modeled pollu tant concentrations in Lick Creek and

downstream reaches in the White River exceed the MCL drinking water benchmarks for five

8-36Section 8—Case Study Modeling

modeled pollutants. The baseline modeled pollu tant concentrations exceed drinking water criteria for thallium, selenium, arsenic, lead, and cadmium as discussed below:

 Thallium concentrations in Lick Creek ex ceed the MCL benchmark (2 μg/L) for 96 percent of the modeling peri od. These exceedances do not occur downstream after the

confluence of the Lick Creek and White River.

 Selenium concentrations in Lick Creek exceed the MCL benchmark (50 μg/L) for 38 percent of the modeling peri od. These exceedances do not occur downstream after the

confluence of the Lick Creek and White River.

 Arsenic concentrations in Lick Creek ex ceed the MCL benchmark (10 μg/L) for 34 percent of the modeling peri od. These exceedances occur in 8.0 miles of the modeling area downstream of the plant and up to 35 miles downstream of the plant.

 On rare occasions (less than 1 percent of th e modeling period), lead concentrations in Lick Creek exceed the MCL benchmark (15 μg/L). These exceedances continue to

occur downstream in 24 miles of the White River as far as the end of the model (50 miles downstream of the plant discharge).

 On rare occasions (less than 1 percent of the modeling period), cadmium

concentrations in Lick Creek exceed the MCL benchmark (0.25 μg/L). These

exceedances do not occur downstream after th e confluence of the Lick Creek and

White River.

Modeling results do not indica te any exceedances of NRWQC or MCL criteria for nickel or zinc. Appendix G of this repor t includes figures that illustrate the water column pollutant concentration output for the im mediate receiving water for ar senic, cadmium, copper, lead, selenium, and thallium. These figures also present the NRWQC and MCL benchmarks for the pollutant and the steady-state water column pollutant concentrations predicted by the IRW

model.

The final rule modeling results show signi ficantly decreased concentrations of all modeled pollutants in the immediate receiving wa ter (Lick Creek), which will greatly improve water quality. The final modeling results also demonstrate that the reduction of pollutant loadings from Petersburg Generating Station will significantly reduce the concentrations of selenium and thallium in the White River, downs tream of Lick Creek. These pollutant removals result in fewer exceedances of NRWQC and MCL benchmarks compared to those estimated in the baseline modeling. Case study modeling results for Lick Creek and the White River reveal the following water quality improvements under the final rule:

 For arsenic:

- Exceedances of the MCL benchmark are e liminated in Lick Creek. Despite the continued exceedances of this benchmark, at the same frequency, downstream in the White River, reducing the pollutant concentrations in the water column may

decrease the human health risk.

- Exceedances of the human health water quality benchmark for consumption of organisms reduce in frequency from 100 percent to 87 percent of the modeling

8-37Section 8—Case Study Modeling

period in Lick Creek. Despite the conti nued exceedances of this human health criteria, at the same frequency, downstr eam in the White River, reducing the pollutant concentrations in the water co lumn may decrease the risk to humans consuming contaminated organisms.

 For cadmium:

- Exceedances of the aquatic life water qua lity criteria for chronic impacts are eliminated throughout the entire modeling area.

- Exceedances of the MCL benchmark (obser ved only in Lick Creek under baseline conditions) are eliminated througho ut the entire modeling area.

 For copper:

- Exceedances of the aquatic life water qua lity criteria for chronic and acute impacts (observed only in Lick Creek unde r baseline conditions ) are eliminated throughout the entire modeling area.

 For lead:

- Exceedances of the MCL benchmark are e liminated in Lick Creek. Despite the continued exceedances of this benchmark, at the same frequency, downstream in the White River, reducing the pollutant concentrations in the water column may

decrease the human health risk.

 For selenium:

- Exceedances of the aquatic life water qua lity criteria for chronic impacts are eliminated throughout the entire modeling area.

- Exceedances of the human health water quality benchmark for consumption of water and organisms (observed only in Li ck Creek under baseline conditions) are eliminated throughout the entire modeling area.

- Exceedances of the MCL benchmark (obser ved only in Lick Creek under baseline conditions) are eliminated througho ut the entire modeling area.

 For thallium:

- Exceedances of the MCL benchmark reduce in frequency from 96 percent to less than 1 percent of the modeling period in Lick Creek.

- Exceedances of the human health water quality benchmark for consumption of water and organisms reduce in frequency from 100 percent to 84 percent of the modeling period in Lick Creek. Exceedances of this benchmark are eliminated through the modeling area downs tream of the immediate receiving water (after the confluence of the Lick Creek and White River).

- Exceedances of the human health water quality benchmark for consumption of organisms reduce in frequency from 100 percent to 61 percent of the modeling period in Lick Creek. Exceedances of this benchmark are eliminated through the modeling area downstream of the immediate receiving water (after the confluence of the Lick Creek and White River).

8-38Section 8—Case Study Modeling

The final rule modeling results demonstrate that, due to background concentrations of arsenic from upstream sources, there will still be exceedances of the human health water quality benchmark for consumption of water and or ganisms throughout the entire modeling area downstream of the plant; however, the final rule will reduce the arsenic loadings that the Petersburg Generating Station c ontributes to th e White River.

Modeling Results – Wildlife

Under baseline conditions, Lick Creek may pos e a risk to minks and eagles that consume fish contaminated with selenium. The average modeled selenium concentration in Lick Creek is more than 18 times greater than the concentratio n that would translate to NEHC exceedances for minks and eagles, demonstrating that this portion of the immediate receiving water may pose a potential reproductive threat to terrestrial food webs. The water concentrations downstream after

the confluence of the Lick Creek and White River do not pose a threat to these indicator species.

Modeling results indicate that on rare occasions (less than 1 percent of the modeling period), nickel concentrations in benthic sediment downstream reaches exceed the CSCL benchmark (18 mg/kg). These exceedances occu r in 3.0 miles of the modeling area downstream of the plant and up to 35 miles downstream of the plant.

The case study modeling results demonstrate that the final rule will significantly reduce pollutant concentrations and the associated impact s to wildlife that inhabit Lick Creek. The final

rule will eliminate selenium exceedances of the NEHC benchmarks for minks and eagles in all modeled reaches of Lick Creek. Despite th e modeling not being ab le to quantify any improvements to benthic organisms under the fina l rule, the pollutant loading removals will decrease the concentrations of toxic pollutants in benthic sediment and decrease the exposure of organisms to these pollutants.

Modeling Results – Human Health

EPA modeled the average pollutant concentrations in the water column and compared

these to the concentrations th at would trigger exceedances of either the non-cancer reference

dose or the 1-in-a-million LECR. Under base line conditions, the average water column

concentration of arsenic in the immediate receiving water over th e modeling period results in an estimated cancer risk of approximately 3-in-a-million for adult subsistence fishers. Therefore, adults who frequently consume arsenic-contamin ated fish inhabiting the immediate receiving water may be at greater risks for development of cancer.

Based on the average pollutant concentra tions in the water column under baseline conditions, cadmium, selenium, and thallium pose the greatest threat to ca use non-cancer health

effects in humans from fish c onsumption, as discussed below:

 Average thallium concentrations in Lick Creek are significantly greater than the

concentrations that would translate to ex ceedances of the reference doses for adult

and children recreational and subsisten ce fishers (all national-scale cohorts evaluated), with some cohorts potentially being exposed to concentrations more than

200 times the reference dose. The water concentrations downstream after the

8-39Section 8—Case Study Modeling

confluence of the Lick Creek and White Ri ver do not pose a threat to any of the

evaluated cohorts.

 Average selenium concentrations in Lick Cr eek are greater than th e concentration that

would translate to exceedances of the reference doses for adult and children recreational and subsistence fishers (all na tional-scale cohorts evaluated). The water

concentrations downstream after the conflu ence of the Lick Creek and White River do not pose a threat to any of the evaluated cohorts.

 Average cadmium concentrations in Lick Creek are greater than the concentration

that would translate to exceedances of the reference doses for the child (younger than 11 years old) subsistence fisher cohorts. The water concentrations downstream after

the confluence of the Lick Creek and White Ri ver do not pose a threat to any of the

evaluated cohorts.

Therefore, humans who consume thallium-, selenium-, or cadmium-contaminated fish inhabiting Lick Creek may be at gr eater risk for developing the nega tive health effects associated with these pollutants, which are discussed in Section 3.1.1.

The final rule modeling results demonstrate significant reductions in selenium and cadmium concentrations in Lick Creek, whic h will eliminate exceedances of the non-cancer

health effects reference dose for all cohorts fo r these pollutants. While the modeling results

continue to show thallium water concentrations that would translate to exceedances of the noncancer health effects reference doses for all cohort s, the final rule will reduce the magnitude of the human health impacts and reduce thallium lo ading contributions from Petersburg Generating

Station.

Interpretation of Lick Creek and White River Results

Case study modeling results for Lick Creek in dicate that there are severe water quality, wildlife, and human health impacts in Lick Cr eek. Case study modeling of Lick Creek reveals more exceedances of water quality and human h ealth benchmarks than the IRW model; however, the IRW model predicts more imp acts to benthic organisms than the case study modeling results.

The exceedances identified in Lick Creek are based solely on discharges of the evaluated wastestreams from Petersburg Generating Statio n because EPA did not identify any STORET monitoring data or point sources suggesting a ny other sources were contributing pollutant discharges on this small tributary.

The pollutant loadings discharged by Peters burg Generating Stati on contribute to the overall concentrations in the White River, along with other upstream sources. Case study modeling indicates that some of the water quality impacts identified in Lick Creek for arsenic, cadmium, selenium, thallium, and lead can occur in the White River, far downstream of where Lick Creek flows into it. For thallium, thes e downstream impacts are solely caused by the discharges of the evaluated wastestreams from the plant because EPA did not identify any other sources of thallium within the modeling period. For arsenic and lead, the projected exceedances are driven by the background concentrations fl owing into the White River modeling area. Pollutant loadings from Petersburg Generating Station may be further impairing the degraded waterway for arsenic and lead. For lead and zinc , the average water column concentrations are

8-40Section 8—Case Study Modeling

highest downstream in the White River, indicating that pollutants with high partition coefficients may pose a greater threat to humans and aquatic lif e in the White River than in Lick Creek. The case study modeling results suggest th at while high concentrations of toxic pollutants may dilute once Lick Creek empties into the White River, there are still impacts downstream that are not captured by the IRW model.

Under the final rule, case study modeling of Lick Creek and the White River indicate that both these waterbodies will exhibit fewer exceedances of water quality benchmarks. Additionally, Lick Creek will no longer pose reproducti ve risks to higher trophic-level wildlife and will pose less risk to humans consuming fi sh for cancer and non-cancer impacts. Case study modeling predicts more water quality improveme nts in the modeling area than the IRW model. This is due in part to the greater water quality impacts under baseline conditions, which created additional opportunities for modeled improvements, and in part to the id entified improvements in

downstream reaches of the White Ri ver that were not evaluated as part of the IRW model. Case study modeling predict fewer human health impr ovements than the IRW model. The average pollutant concentrations throughout the entire modeling area reduce promptly after compliance

with the final rule.

8.2.4 Ohio River Case Study

The 948-mile Ohio River flows westward from Pittsburgh, Pennsylvania, to Cairo, Illinois, where it meets the Mississippi Ri ver. According to 2013 TRI reporting, 23 million pounds of chemicals were discharged into the Ohio River, more than any other surface water in the TRI database [U.S. EPA, 2013a]. EPA iden tified that 24 steam el ectric power plants evaluated in the EA discharge one or more of the evaluated wastestreams to the Ohio River or to

tributaries that flow into the Ohio River in under five miles. FirstEne rgy Corp. (FirstEnergy) owns and operates several of the coal-fired power plants that discharge to the Ohio River.

The Bruce Mansfield plant (Plant ID 2269) is FirstEnergy’s largest co al-fired power plant by nameplate capacity. The plant is located in Sh ippingport, Pennsylvania, along the Ohio River, approximately 25 miles northwest of Pittsburgh. This plant operates three stand-alone steam turbines, each with a nameplate capacity of 914 MW. These three generating units have a total capacity of 2,741 MW and report ed producing approximately 19,000,000 MWh of electricity in 2009 [ERG, 2015j]. The Bruce Mansfield plant di scharges FGD wastewater and bottom ash transport water directly to the Ohio River fr om the Little Blue Run surface impoundment, which straddles the border of Pennsylva nia and West Virginia. Table 8- 5 contains general information

about the three coal-fired generating units at the Bruce Mansfield plant.

Located along the Ohio River in Stratton, Ohi o, FirstEnergy’s W.H. Sammis plant (Plant ID 103) is the largest coal-fired power plant in Ohio. W.H. Sa mmis Plant’s seven stand-alone steam turbine generating units have a total na meplate capacity of 2,460 MW. Based on data EPA obtained in responses to the Steam Electric Surv ey, the W.H. Sammis plant reported generating more than 9,500,000 MWh of energy with these seven coal-fired generating units in 2009. The

W.H. Sammis plant discharges three of the evaluated wastestreams (FGD wastewater, bottom ash transport water, and combustion residual leach ate) directly to the Ohio River. Table 8-6 contains general information about each of the se ven steam electric generating units at the W.H. Sammis plant.

8-41Section 8—Case Study Modeling

Table 8-5. Summary of Bruce Mansfield Operations

SE Unit Fuel Capacity (MW) Fly Ash Bottom Ash FGD (Year Installed)

1 Bituminous coal and 914 Wet scrubber a Wet handled to Wet system

No. 2 fuel oil impoundment (1975)

2 Bituminous coal and 914 Wet scrubber a Wet handled to Wet system

No. 2 fuel oil impoundment (1977)

3 Bituminous coal and 914 Dry conveyed Wet handled to Wet system

No. 2 fuel oil impoundment (1980)

Source: ERG, 2015j.
Acronyms: FGD (Flue gas desulfurization) ; MW (Megawatt); SE (steam electric).
a – EPA does not consider the ash collected by venturi-ty pe wet scrubbers as fly ash, and therefore, the water generated by these systems is not considered fly ash transport water.

Table 8-6. Summary of W.H. Sammis Operations

SE Unit Fuel Capacity (MW) Fly Ash Bottom Ash FGD (Year Installed)

1 Bituminous coal, subbituminous coal,

and No. 2 fuel oil 190 Dry conveyed Wet handled to impoundment Wet system (2010)

2 Bituminous coal, subbituminous coal,

and No. 2 fuel oil 190 Dry conveyed Wet handled to impoundment Wet system (2010)

3 Bituminous coal, subbituminous coal,

and No. 2 fuel oil 190 Dry conveyed Wet handled to impoundment Wet system (2010)

4 Bituminous coal, subbituminous coal,

and No. 2 fuel oil 190 Dry conveyed Wet handled to impoundment Wet system (2010)

5 Bituminous coal, subbituminous coal,

and No. 2 fuel oil 334 Dry conveyed Wet handled to impoundment Wet system (2010)

6 Bituminous coal, subbituminous coal,

and No. 2 fuel oil 680 Dry conveyed Wet handled to impoundment Wet system (2010)

7 Bituminous coal, subbituminous coal,

and No. 2 fuel oil 680 Dry conveyed Wet handled to impoundment Wet system (2010)

Source: ERG, 2015j.

Acronyms: FGD (Flue gas desulfurization) ; MW (Megawatt); SE (steam electric).

In estimating the historical pollutant loadin gs associated with W.H. Sammis’ three FGD systems, EPA incorporated the pollutant loadin gs for FGD wastewater as the systems were installed, between March a nd May 2010. EPA did not model a ny FGD wastewater pollutant loadings in the model prior to the installati on of W.H. Sammis plant’s first FGD system.

8-42Figure 8- 5 . Ohio River WASP Modeling Area Section 8—Case Study Modeling

Modeling Area

The Ohio River WASP model encompasses a 49-mile-long reach of the Ohio River, 37

miles of which is downstream o f o n e or both of th e two modeled steam electric p ower plant immediate receiving water s. Located furthest ups tream, the Bruce Mansfield plant discharges

ap proximately 12 miles downstream of the start of the mo deling area. The immediate receiving water that the Bruce Mansfield pl ant discharges to is approximately 3.3 miles long, as defin ed in

th e WASP model. W.H. Sammis plant discharges 13 miles downstream of the Bruce Mansfield

p lan t’ s immediate receiving water. The immedi ate receiving water that W.H. Sammis plant

d ischarges to is approximately 3.4 miles long, as defined in the WASP model. The modeling area ends just upstream of the discha r ges from anoth er steam electric power plan t, the Cardinal plant ( Plant ID 3265). EPA did not model the p ollu tant loadings from th e Cardinal plan t because of

C B I claims on one or more of th e ev aluated wastestream flow ra tes. Figur e 8- 5 illustrates the

location and extent of the Ohio River WASP model.

8-43Section 8—Case Study Modeling

Identified Point Sources and Background Concentrations

As discussed below, EPA reviewed availa ble pollutant loadings (DMR and TRI) and monitoring data (STORET) for potential incorporation into the Ohio River WASP model to represent pollutant contributions from backgr ound and non-steam-electric point sources, and for use in calibrating the model results.

 Upstream pollutant contributions . EPA identified many upstream non-steamelectric point sources whose pollutant loadings could influence the model results. EPA identified STORET data from one monitoring station on the Ohio River (approximately 28 river-miles upstream of Bruce Mansfield plant’s immediate receiving water). EPA incorporated the mon itoring data (which encompass five of the modeled pollutants) to represent the pollutant contributions flowing into the modeling area. EPA identified additional STORET monitoring data from one station on a tributary to the Ohio River; EPA incorporated these data to represent pollutant contributions flowing in from that tribut ary. EPA also incorporated the pollutant loadings, based on DMR and TRI data, from seven non-steam-electric point sources upstream of the Bruce Mansfield plant’s imme diate receiving water to account for the pollutant contributions not capture d by the STORET monitoring data.

 Downstream pollutant contributions . EPA incorporated STORET data from eight monitoring stations to represent TSS concen trations flowing into the modeling area downstream of both steam electric power plant immediate receiving waters ( i.e.

, tributaries flowing into the Ohio River). These monitoring stations all represent one tributary that flows into the Ohio River near the downstream end of the modeling

area. EPA identified 29 non-steam-electric point sources whose pollutant loadings

could influence the model results downstream of th e Bruce Mansfield plant immediate receiving water and incorporated these pollutant loadings into the Ohio

River WASP model.

 Monitoring data within the modeling area. EPA compiled STORET data from seven monitoring stations located within the modeling area and us ed these data to

calibrate the WASP model.

The contributions of copper, lead, nick el, and zinc from upstream sources are significantly greater than the pollutant loadings from the Bruce Mansfield and W.H. Sammis plants.

The Ohio River case study model did not account for the documented surface water and ground water impacts from Bruce Mansfield or Little Blue Run that are listed in Appendix A. In 1993, a catastrophic release of steam electric power plant wastewater compromised the quality of ground water and surface water around the Bruce Mansfield plant and Little Blue Run impoundment. Due to the lack of pollutant loadings data, surface water quality impacts resulting

from this event are not reflec ted in this model; therefore, the case study modeling could underrepresent the actual ba seline impacts of the Br uce Mansfield plant on the Ohio River.

8-44Section 8—Case Study Modeling

Modeling Period

The modeling period starts in 1982 (year of the last revision to the steam electric ELGs) and extends through 2036, covering a period of 55 years. Based on their NPDES permitting cycles, EPA assumes that the Bruce Mansfiel d and W.H. Sammis plants will achieve the limitations under the final rule by 2020 and 2021, respectively. EPA focused the assessment of the improvements under the final rule on the period after the 2021 assumed compliance date.

Modeling Results – Water Quality

Under baseline conditions, th e modeled pollutant concentra tions in the modeled portion

of the Ohio River exceed a human health NRWQC water quality benchmark for one modeled pollutant (arsenic), indicating that arsenic loadin gs from the two steam electric power plants may contribute to a quantifiable reduction in water quality in the modeled portions of the Ohio River.

Arsenic concentrations in 33 miles of the mode ling area downstream of the Bruce Mansfield plant exceed the human health water quality benchmark for consumption of water and organisms (0.018 μg/L). These exceedances begin several m iles downstream of the Bruce Mansfield plant due to the pollutant loadings from a non-steam-electric point s ource. This area of exceedances continues downstream of the W.H. Sammis pl ant for 24 miles (including the W.H. Sammis plant’s immediate receiving water) and exceeds the arsenic benchmark during 30 percent of the modeling period. In some portions of the modeling area, the fr equency of these exceedances

increases due to arsenic contri butions from other non-steam-el ectric point sources. These case study modeling results indicate that, under baseli ne conditions, humans consuming water and/or organisms inhabiting these modeled portions of th e Ohio River may be more at risk of the negative effects associated with oral exposure to arsenic (see Section 3.1.1). On rare occasions (less than 1 percent of the m odeling period), the modeled pollu tant concentrations exceed the MCL drinking water benchmark for one pollutant (l ead), indicating that lead loadings from the two steam electric power plants may contribute to a quantifiable reduction in water quality in the modeled portions of the Ohio River. These rare lead exceedances occur in 15 miles of the modeling area downstream of the Bruce Mansfield plant, of which 13 mile s are also downstream of the W.H. Sammis plant (including the immediate receiving water).

Modeling results do not indicate any exceedan ces of human health NRWQC criteria for the other modeled pollutants (cadmium, copper, ni ckel, selenium, thallium, and zinc) and do not indicate any exceedances of aquatic life NRWQC or MCL criteria for any of the eight modeled pollutants. Appendix G of this report includes figur es that illustrate the water column pollutant concentration output for the immediate receiving water for arsenic and lead. These figures also present the NRWQC and MCL benchmarks for the pollutant and the steady-state water column pollutant concentrations pred icted by the IRW model.

The final rule modeling results show significantly decreased concentrations of four of the modeled pollutants (arsenic, cadmium, selenium, and thallium) in the modeled portion of the Ohio River, which will improve water quality. Th ese pollutant removals result in less frequent exceedances of human health NRWQC benchmarks compared to those estimated in the baseline modeling. Arsenic exceedances of human health water quality benchmarks for consumption of water and organisms reduce in frequency from 30 percent to 6 percent of the modeling period in the W.H. Sammis plant’s immediate receiving water. Additionally, the exceedances of these

8-45Section 8—Case Study Modeling

benchmarks reduce in frequency in all remain ing sections of the downstream modeling area following compliance with the final rule. Despite the continued exceedances of the arsenic

human health criteria and the lead MCL benchmar k, reducing the pollutant concentrations in the water column may decrease the risk to humans.

Modeling Results – Wildlife

Based on the average pollutant concentra tions in the water column under baseline conditions, the modeled portion of the Ohio River does not exceed the concentrations that would translate to NEHC exceedances and does not pose a risk to minks and eagles that consume contaminated fish. Despite the modeling not bei ng able to quantify any improvements to minks and eagles under the final rule, the pollutant loading removals will decrease bioaccumulation of toxic pollutants in the terrestrial food chains.

Modeling results do not indicate that there are any pollutant concentrations in the upper benthic sediment that exceed CSCL benchmarks for any of the eight modeled pollutants; therefore, the modeled portion of the Ohio River does not pose a threat to benthic organisms in contact with contaminated sediment. Despite the modeling not being able to quantify any improvements to benthic organisms under the fina l rule, the pollutant loading removals will decrease the concentrations of toxic pollutants in benthic sediment and decrease the exposure of organisms to these pollutants.

Modeling Results – Human Health

Under baseline conditions, the average concentr ation of arsenic in fish over the modeling period does not result in an estimated cancer risk greater than 1-in-a-million for any of the

national-scale cohorts.

Based on the average pollutant concentra tions in the water column under baseline conditions, thallium poses the grea test threat to cause non-cancer health effects in humans from fish consumption. Average thallium concentrat ions in the W.H. Sammis plant’s immediate receiving water are greater than the concentrat ion that would translate to exceedances of the reference doses for the child (younger than 11 y ears old) subsistence fisher cohorts. Average

thallium concentrations in 24 miles of the m odeling area downstream of the W.H. Sammis plant are high enough to trigger exceed ances of the reference dose for at least one subsistence cohort. Therefore, humans who consume fish inhabiti ng these waters may be at greater risk for developing the negative health eff ects associated with thallium, which are discussed in Section

3.1.1.

The final rule modeling results demonstr ate significant reductions in thallium, eliminating thallium exceedances of the non-cancer health effects reference dose throughout the entire modeling area.

Interpretation of Ohio River Results

Case study modeling results for the Ohio Rive r indicate greater water quality and human health impacts under baseline conditions than predicted by the IRW model. The impacts identified in the Ohio River by case study mode ling are more extensive than the IRW model

8-46Section 8—Case Study Modeling

because EPA has accounted for pollutant contribu tions from upstream on the Ohio River, other waterways flowing into the Ohio River, and non -steam electric point sources. Modeled alone, the Bruce Mansfield plant and W.H. Sammis plant would not caus e any quantifiable impacts over the modeling period; however the modeled potion of the Ohio Ri ver is heavily industrialized. EPA identified 34 non-steam electric point sources that discharge one or more of the modeled pollutants and report to DMR or TRI. The pollu tant contributions from the Bruce Mansfield plant, W.H. Sammis plant, and these other non- steam electric point sources modeled accumulate in the waterbody, increasing the overall water column concentrations to a degree that adversely affects water quality and human health. EP A identified exceedances of human health benchmarks that indicate that consuming water and/or organisms from the modeled portion of the Ohio River, including th e W.H. Sammis plant’s immediate receiving water and areas downstream, can cause health problems related to arsenic, lead, or thallium. The Ohio River case study model results exemplify th at, by not accounting for non-st eam-electric point sources discharging to the same waterbodies as steam electric power plants, the IRW model may be under-representing the total number of receiving waters with impacts that are caused, in part, by pollutant contributions from the steam electric power genera ting industry. The case modeling results also suggest that the discharges of th e evaluated wastestreams from Bruce Mansfield plant and W.H. Sammis plant may be fu rther impairing the degraded waterway.

Case study modeling of the Ohio River indicates that, under th e final rule, the Ohio River will exhibit less frequent exceedances of water quality benchmarks and will eliminate risk to humans consuming fish that inhabit these waters. The huma n health non-cancer impacts and improvements under the final rule are solely caused by the re duction in steam electric plant pollutant loadings (there are no other input s ources of thallium in the Ohio River WASP model).The improvements identifie d by the case study model are more extensive than what was projected by the IRW model for e ither of Bruce Mansfield plant or W.H. Sammis plant. This is due in part to the greater water quality and human health impacts under baseline conditions, which created additional opportunities for modeled improvements, and in part to the identified improvements in downstream reaches of the Ohio Ri ver that were not evaluated as part of the IRW model. The average pollutant concentratio ns throughout the enti re modeling area reduce within a year after compliance with the final rule.

8.2.5 Mississippi River Case Study

The Mississippi River watershed is the larg est in North America, covering about 40 percent of the lower 48 states. The 190-mile stretch of the Mississippi River between the confluence with the Missouri River at St. Louis, Missouri, and the confluence with the Ohio River at Cairo, Illinois, is known as the Middle Mississippi River. South of St. Louis along this stretch of the river, Ameren Corporation operates the Rush Is land steam electric power plant (Plant ID 5038) on the we st bank of the Mississippi River. The Rush Island plant operates two stand-alone steam turbine units with a namepl ate capacity of 670 MW eac h. Together, these two coal-fired generating units have a capacity of 1,340 MW and reported producing over 8,500,000 MWh of electricity in 2009 in the Steam Electric Survey. The Rush Island plant discharges fly

ash and bottom ash trans port water directly to the Mississipp i River. Table 8-7 contains general information on the two coal-fired units at the Rush Island plant.

8-47Section 8—Case Study Modeling

Table 8-7. Summary of Rush Island Operations

SE Unit Fuel Capacity (MW) Fly Ash Bottom Ash FGD (Year Installed)

1 Subbituminous coal

and No. 2 fuel oil 670 Dry conveyance & wet handled to impoundment Wet handled to impoundment No FGD system

2 Subbituminous coal

and No. 2 fuel oil 670 Dry conveyance & wet handled to impoundment Wet handled to impoundment No FGD system

Source: ERG, 2015j.
Acronyms: FGD (Flue gas desulfurization) ; MW (Megawatt); SE (steam electric).

Modeling Area

Th e Mississippi River WASP model encompasses a 46-mile-lo ng reach of the Mississippi River, 23 miles o f which is downstream of the Rush Island plan t immediate

r eceiving water. The model has two start boundaries that ar e on the Meramec River and Mississippi River shortly upstream of their co nf luence. The immediate r eceiv ing water that the

R u sh Island plant dischar g es to is approximately 1.5 miles long, as defined in the WASP model.

Th is model ends at the co nfluence of the Mi ssissippi River and Kaskas kia River. Fig u r e 8- 6 illustrates the location and extent of the Mississippi R iver WASP model.

Identified Point Sources and Background Concentrations

As discussed below, EPA reviewed availa ble pollutant loadings (DMR and TRI) and monitoring data (STORET) f or potential incorp oration into the Missi ssippi River WASP model to represent pollutant contribu tions from background and non-steam -electric point sources, and for use in calibrating the model results.

 Upstream pollutant contributions from non-steam-electric point sources . EPA identified several upstream non-steam-elect ric point sources whose loadings could

influence the model results. EPA therefore extended the modeling area upstream to model these point sources and incorporate upstream monitoring data. EPA identified STORET data from four monitoring statio ns on the Mississippi River prior to the confluence with the Meramec River (approxi mately 24 river-miles upstream of Rush Island’s immediate receiving water). EPA in corporated the monito ring data (which encompass all of the modeled pollutants excep t for thallium) to represent the pollutant contributions in the Mississippi River prio r to where it converge s with the Meramec River. EPA assumed that the monitoring data adequately reflect the pollutant contributions from upstream of this confluence. EPA incorporated the pollutant loadings from three non-steam-electric poi nt sources downstream of the convergence to account for the pollutant contributions not captured by the STORET monitoring

data.

 Upstream pollutant contributions from steam electric sources . EPA identified one steam electric power plant, Ameren’s Mera mec plant (Plant ID 1435), whose loadings

could influence the model results at the Rush Island immediate receiving water and other downstream locations. EPA incorporated the loadings from the Meramec plant

into the extended Mississi ppi River model, as disc ussed further below.

8-48Fig ure 8- 6 . Mississippi River WASP Modeling Area Section 8—Case Study Modeling

 Downstream pollutant contributions . EPA incorporated STORET data from two monitoring stations to repres ent pollutant concentrations flowing into the modeling area downstream of the Rush Island immediate receiving water ( i.e. , tributaries flowing into the Mississippi River). EPA di d not identify any non-steam-electric point sources whose pollutant loadings would significantly influence the model results in the downstream modeling area.

 Monitoring data within the modeling area . EPA compiled STORET data from four monitoring stations located within the mode ling area and used these data to calibrate

the WASP model.

The Meramec plant discharges approximately 24 river miles upstream of the Rush Island plant’s immediate receiving wate r. EPA did not identify STORET monitoring data between the two plants to represent the pollutant concentrat ions from the Meramec plant; therefore, EPA incorporated the pollutant loadings from the Me ramec plant (as calculated for this rulemaking) into the Mississippi River model. The Meramec plant operates four coal-fired generating units with a total nameplate capacity of 923 MW. A ll pollutant loadings from the evaluated wastestreams are from bottom ash transport water. EPA assumed that the Meramec plant will

8-49Section 8—Case Study Modeling

comply with the standards of the final rule by 2019. EPA did not evalua te the water quality, wildlife, or human health impacts associated wi th discharges from the Meramec plant because this plant did not meet the cas e study location selection criter ia described in Section 8.1.1. EPA incorporated the loadings from Meramec plan t solely to account for the upstream pollutant contributions flowing into the Rush Island plant’s immediate receiving water from upstream,

under baseline conditions and the final rule.

The contributions of arsenic, cadmium, c opper, lead, nickel, and zinc from upstream sources are significantly greater than the pollu tant loadings from the Rush Island plant.

Modeling Period

The modeling period starts in 1982 (year of the last revision to the steam electric ELGs) and extends through 2036, covering a period of 55 years. Based on their NPDES permitting cycles, EPA assumes that the Meramec and Rush Island plants will achieve the limitations under the final rule by 2019 and 2023, respectively. For th e Rush Island plant’s immediate receiving water and downstream reaches, EPA focused th e assessment of the baseline impacts and improvements under the final rule on the peri od after the 2023 assumed compliance date.

Modeling Results – Water Quality

Under baseline conditions, the modeled pollu tant concentrations in the Rush Island plant’s immediate receiving water and downstrea m reaches exceed human health NRWQC water quality benchmarks for one modeled pollutant (a rsenic), indicating that loadings from Rush Island may contribute to a quantif iable reduction in water quality in the modeled portions of the Mississippi River. Arsenic concen trations in the Rush Island plant’s immediate receiving water exceed the human health water quality benchm ark for consumption of water and organisms (0.018 μg/L) and the human health water qualit y benchmark for consumption organisms (0.14 μg/L) for the entire modeling period. These ex ceedances continue downstream, at the same frequency, throughout the entire 23-mile-long modeli ng area downstream of the plant. The case study modeling results indicate that, under baseli ne conditions, humans consuming water and/or organisms that inhabit these modeled portions of th e Mississippi River may be more at risk of the negative effects associated with oral exposure to arsenic (see Section 3.1.1).

Modeling results do not indicate any exceed ances of human health NRWQC benchmarks for the other modeled pollutants (cadmium, copper, nickel, lead, selenium, th allium, and zinc). In addition, modeling results do not indicate any exceedances of aquatic life NRWQC or MCL criteria for any of the eight mode led pollutants. Appendix G of this report includes figures that illustrate the water column pollutant concentra tion output for the immediate receiving water for arsenic. This figure also presents the NRWQC and MCL benchmarks for the pollutant and the steady-state water column pollutant concen trations predicted by the IRW model.

The final rule modeling continues to show human health NRWQC benchmark

exceedances for arsenic within th e Mississippi River due to additi onal arsenic contributions from other sources ( i.e. , Mississippi River background concentr ations and non-steam electric point sources). However, under the final rule, both th e Meramec and Rush Island plants will no longer

8-50Section 8—Case Study Modeling

discharge any of the evaluated wastestreams and will therefore no longer contribute to the arsenic or lead impairment of the Mississippi River.

Modeling Results – Wildlife

Based on the average pollutant concentra tions in the water column under baseline conditions, the modeled portion of the Mississippi River does not ex ceed the concentrations that

would translate to NEHC exceedances and does not pose a risk to minks and eagles that consume contaminated fish. Despite the modeling not bei ng able to quantify any improvements to minks and eagles under the final rule, the pollutant loading removals will decrease bioaccumulation of toxic pollutants in the terrestrial food chains.

Modeling results do not indicate that there are any pollutant concentrations in the upper

benthic sediment that exceed CSCL benchmarks of for any of the eight modeled pollutants; therefore, the modeled portion of the Mississippi River does not pose a threat to benthic organisms in contact with contaminated sedi ment. Despite the modeling not being able to quantify any improvements to benthic organism s under the final rule, the pollutant loading removals will decrease the concentrations of toxic pollutants in benthic sediment and decrease the exposure of organisms to these pollutants.

Modeling Results – Human Health

EPA modeled the average pollutant concentrations in the water column and compared

these to the concentrations th at would trigger exceedances of either the non-cancer reference

dose or the 1-in-a-million LECR. Under base line conditions, the average water column concentration of arsenic throughout the modeling ar ea downstream of the plant results in an estimated cancer risk greater than 1-in-a-million for adult subsistence fishers. Therefore, humans

who consume arsenic-contaminated fish inhab iting the immediate receiving water may be at greater risks for development of cancer. Modeling results demonstrate no reduction in the cancer risk from inorganic arse nic under the final rule.

Under baseline conditions, the average polluta nt concentrations over the modeling period does not pose the threat to cause non-cancer health effects for adult and children recreational and subsistence fishers (all nationa l-scale cohorts evaluated).

Interpretation of Mississippi River Results

Case study modeling results for the Mississipp i River indicate great er water quality and human health impacts under baseline conditions than predicted by the IRW model. By accounting for pollutant contributions from background and upstream sources, the case study model predicts higher pollutant concentrations under base line conditions. For arsenic, the projected exceedances are driven by the pollutant contributions entering the Mississippi River upstream of the Rush Island plant. Alone, the steam electric discharges of the evaluated wastestreams would not cause any quantifiable impact s, which is consistent with the IRW model results; however, the pollutant loadings from the Rush Island plant may be further exacerbating the impairment of the degraded waterway.

8-51Section 8—Case Study Modeling

The case study modeling of the Mississippi Rive r indicates that, under the final rule, it will continue to exceed all of the water qual ity and human health benchmarks observed at baseline, with little to no reducti on in frequency. Under the final rule, the Rush Island plant will no longer discharge any fly ash or bottom ash tran sport water. After compliance with the final rule, the modeled steam electric power plants will no longer contribute to th e impairment of the Mississippi River and the overall magnitude of the pollutant concentrations in the aquatic system

will decrease.

8.2.6 Lake Sinclair Case Study

Lake Sinclair is a reservoir located in centr al Georgia. The lake was created in 1953 when the waters of the Oconee River were dammed by Georgia Power, a subs idiary of Southern Company, to create a hydroelect ric generating stati on. Georgia Power also owns and operates Plant Harllee Branch (Plant ID 5762), a steam elect ric power plant situated on the northern shore

of Lake Sinclair. Based on 2009 da ta obtained in responses to th e Steam Electric Survey, Plant Harllee Branch operated four coal -fired generating units with a total nameplate capacity of 1,750 MW and produced more than 6,800,000 MWh of el ectricity in 2009. As of April 16, 2015 (the date by which the plant would be required to co mply with the U.S. EPA’s Clean Power Plan [Clean Air Act Section 111(d)]), this plant has d ecertified and retired all f our of its coal-fired generating units. Georgia Power cited several factor s, including the cost to comply with existing and future environmental regulations, recent and future economic conditions, and lower natural gas prices, in the decision to close the plant. Plant Harllee Branch disc harged FGD wastewater, fly ash transport water, and bot tom ash transport water directly to Lake Sinclair. Table 8-8 contains general information on the four coal-fired units at Rush Island Plant.

Despite the retirement of all coal-fired genera ting units at this plant, EPA proceeded with case study modeling of Lake Sinc lair to represent the potenti al impacts of steam electric discharges on lentic waterbodie s (including the 26 lake, pond, a nd reservoir receiving waters evaluated in this EA) and the potential enviro nmental improvements that could reasonably be expected under the final rule in other lentic waterbodies that receive discharg es of the evaluated

wastestreams. EPA did not include Plant Harll ee Branch or Lake Sinclair in the other quantitative and qualitative analyses in this EA for the final rule ( e.g. , the IRW model).

In estimating the historical pollutant loadings associated with Plant Harllee Branch, EPA incorporated the loadings only from generating unit IDs 3 and 4 because generating unit IDs 1 and 2 were flagged for retirement at the time of the proposed revised ELGs. EPA incorporated the loadings with the FGD wastewater as the sy stems were installed (sta rting in 2013). EPA did not model any FGD wastestream loadings in the hist orical model prior to the installation of Plant Harllee Branch’s first FGD system.

8-52Section 8—Case Study Modeling

Table 8-8. Summary of Plant Harllee Branch Operations

SE Unit Fuel Capacity (MW) Fly Ash Bottom Ash FGD (Year Installed)

1 a Bituminous coal and

No. 2 fuel oil 299 Wet handled to impoundment Wet handled to impoundment Wet system (2014)

2 a Bituminous coal and

No. 2 fuel oil 359 Wet handled to impoundment Wet handled to impoundment Wet system (2014)

3 Bituminous coal and

No. 2 fuel oil 544 Wet handled to impoundment Wet handled to impoundment Wet system (2013)

4 Bituminous coal and

No. 2 fuel oil 544 Wet handled to impoundment Wet handled to impoundment Wet system (2013)

Source: ERG, 2015j.

Acronyms: FGD (Flue gas desulfurization) ; MW (Megawatt); SE (steam electric).

a – EPA did not model any pollutant loadings associated with these generating units.

Modeling Area

As discussed in Section 8.1.1, EPA relied upon the availability of existin g models to

p erform case study modeling of lentic systems: an existing WASP model th at divided the waterbody into segments and EFDC model th at provided hydrodynamics and simulated the aquatic system in three dimensions. The EFDC m od el uses stretch o r sigma vertical coordinates

and Cartesian coordinates to represent the physical character istics of Lake Sin clair.

Th e th r ee- d imensional EFDC model, whic h p rovides the hydrodynamic foundation for the WASP model, divides the waterbody into 1

, 2 3 5 segments; each segment represents a unique

lo cation and stratum within Lake Sinclair

. Th e model accounts for a total volu me o f approximately 340 millio n cubic meters. In contrast to the WASP models that EPA d eveloped to

mo d el lotic systems, the Lake Sinclair model is not set up to quantify the po llutant concentrations in the benthic sediment; theref ore, EPA was unable to assess whether pollutant accumulation in the sediment was occurring ov er prolonged discharge periods. Figu re 8- 7

illustrates the location and ex tent of the Lake Sinclair modeling area.

8-53Section 8—Case Study Modeling

Figure 8- 7 . Lake Sinclair WA SP and EDFC Modeling Area

Identified Point Sources and Background Concentrations

As discussed below, EPA reviewed availa ble pollutant loadings (DMR and TRI) and monitoring data (STORET) for poten tial incorpo ration into the Lake Sinclair water quality model to represent pollutant contribu tions from background and non-steam -electric point sources, and for use in validating and calibrating the model results.

 Upstream pollutant contributions. EPA incorporated STORET data from three monitoring stations to repr esent TOC and TSS contributions from upstream of Lake

Sinclair on the Oconee River. EPA did not identify sufficient STORET monitoring data to represent the pollutant contributi ons of the eight modeled pollutants or any upstream non-steam-electric point sources with loadings for the eight modeled pollutants. EPA therefore assumed pollutant concentrations of zero within the water column flowing into Lake Si nclair from the Oconee River.

 Other pollutant contributions . EPA incorporated STORET data from 15 monitoring stations to represent the modeled pollutant s, TOC, and TSS concentrations flowing

into Lake Sinclair from other streams. EPA did not identify any non-steam-electric

8-54Section 8—Case Study Modeling

point sources whose pollutant loadings would significantly influence the model

results.

 Monitoring data within the modeling area. EPA compiled STORET data from six monitoring stations located within the mode ling area and used these data to calibrate the Lake Sinclair water quality model.

The pollutant concentrations entering the modeling area for arsenic, copper, lead, and thallium which EPA calculated using monitoring data, are much greater than the pollutant loadings from Lake Sinclair plant. The con centrations entering the modeling area for cadmium, nickel, and zinc also strongl y influence the model outputs.

Modeling Period

As discussed earlier in this section, EPA adopted the preexisting Lake Sinclair EFDC model. The preexisting model was designed with seven years of hydrodynamic and flow input, limiting the length of the period EPA could mode l. Based on Plant Harllee Branch’s NPDES permitting cycle, EPA assumed that the plant woul d have achieved the limitations under the final rule by 2019 if it continued to operate. Th e modeling period begins in February 2012 (approximately seven years before the assumed compliance date) and extends through November 2025 (approximately seven years afte r the assumed compliance date).

Modeling Results – Water Quality

EPA selected three portions of Lake Sinclair to eval uate the modeled pollutant concentrations: 1) the immediate receiving water (a 720,000-cubic-mete r cell of the lake); 2) the average of all segments in the r each of the lake where Plant Har llee Branch discharges, including subsurface water segments (hereafte r referred to as the “receiving br anch”), and 3) the average of all segments included in the Lake Sinclair model, including subsurface water segments (hereafter referred to as the “entire modeling area”).

Under baseline conditions, the modeled pollu tant concentrations in Lake Sinclair, including the immediate receiving water and th e receiving reach, exceed NRWQC water quality benchmarks for three modeled pollutants, indicati ng that pollutant loadings from Plant Harllee Branch may quantifiably reduce wa ter quality in the modeled por tions of Lake Sinclair. The reduced water quality is primarily attribut ed to arsenic, cadmium, and thallium.

The baseline modeled pollutant concentrations exceed human health criteria primarily for arsenic and thallium, as discussed below:

 Arsenic concentrations exceed the water qua lity benchmark for consumption of water and organisms (0.018 μg/L):

- In the immediate receiving wate r for the entire modeling period.

- In all modeled segments of the receiving branch for more than 99 percent of the modeling period.

- In 97 percent of the entire modeling area for 10 percent or more of the modeling period.

8-55Section 8—Case Study Modeling

 Arsenic concentrations also exceed th e higher water quality benchmark for consumption of organisms (0.14 μg/L):

- In five of the six modeled segments of th e receiving branch for up to 19 percent of the modeling period.

- In 54 percent of the entire modeling area for 10 percent or more of the modeling period.

 Thallium concentrations exceed the water quality benchmark for consumption of water and organisms (0.24 μg/L):

- In three of the six modeled segments of th e receiving branch for up to 6 percent of the modeling period.

- In 14 percent of the entire modeling area for 10 percent or more of the modeling period.

 Thallium concentrations also exceed the higher water quality benchmark for consumption of organisms (0.47 μg/L):

- In two of the six modeled segments of th e receiving branch for less than 1 percent of the modeling period.

- In 11 percent of the entire modeling area for 10 percent or more of the modeling period.

The case study modeling results indicate th at, under baseline conditions, humans consuming water and/or organisms that inhabit these modeled porti ons of Lake Sinclair may be more at risk of the negative effects associated with oral exposure to arsenic and thallium (see Section 3.1.1).

Aquatic organisms may be at risk for e xposure to cadmium under baseline conditions. Specifically, cadmium concentrations exceed the fr eshwater aquatic life criteria for chronic exposure (0.25 μg/L) in 4 percen t of the entire modeling area fo r 10 percent or more of the modeling period. These case stud y modeling results indicate that , under baseline conditions, aquatic organisms inhabiting these m odeled portions of Lake Sinclair could be at an elevated risk of the negative effects associated with oral exposure to cadmium (see Section 3.1.1).

Under baseline conditions, the modeled polluta nt concentrations in Lake Sinclair occasionally exceed the MCL drinking water benchmarks for two of the modeled pollutants (arsenic and thallium), as discussed below:

 Arsenic concentrations exceed the MCL drinking water criteria (10 μg/L) in less than 1 percent of the segments for 10 perc ent or more of the modeling period.

 Thallium concentrations exceed the MCL dri nking water criteria (2 μg/L) in 5 percent of the segments for 10 percent or more of the modeling period.

Modeling results do not indicate any exceedances of NRWQC or MCL criteria for the other modeled pollutants (copper, lead, nickel, se lenium, and zinc). Appendix G of this report includes figures that illustrate the average water column pollutant concentration output for the

8-56Section 8—Case Study Modeling

entire lake for arsenic, cadmium, and thallium . These figures also present the NRWQC and MCL benchmarks for the pollutant and the steady-st ate water column pollutant concentrations predicted by th e IRW model.

The final rule modeling results show significantly decreased average concentrations of two of the modeled pollutants (n ickel and selenium) in the mode led portion of Lake Sinclair. Case study modeling results for Lake Sinclair re veal the water quality improvements for arsenic under the final rule. Specifically, arsenic exceed ances of the human health NRWQC benchmark for consumption of water and organisms reduce in frequency from the entire modeling period to 23 percent of the modeling period in the immediate receiving wa ter and reduce from above 99 percent of the modeling period to as low as 23 percent of the modeling period in the receiving branch. Additionally, slightly less (2 percent of the modeling area) of Lake Sinclair will exceed

this benchmark under the final rule. Arsenic ex ceedances of the higher human health NRWQC benchmark for consumption of organisms also reduce throughout the entire lake as 12 percent less of the modeling area exceed this benchmar k for more than 10 percent of the modeling period.

While the modeling results demonstrate co ntinuing arsenic, cadmium, and thallium exceedances of NRWQC and MCL benchmarks in the receiving reach and the entire modeling area, the pollutant loading contri butions to the lake would be reduced under the final rule (if

Plant Harllee Branch did not retire all generating units).

Modeling Results – Wildlife

For the analysis of wildlife impacts and im provements, EPA assumed that aquatic life travel freely throughout Lake Sincla ir and do not confine themselves within particular segments of the lake. EPA calculated the average fish tissue concentrations of all segments within the Lake Sinclair model ( i.e. , entire modeling area) for purposes of the wildlife assessment.

Based on the average pollutant concentra tions in the water column under baseline conditions, the modeled portion of Lake Sinclair does not exceed the concentrations that would translate to NEHC exceedances and does not pose a risk to minks and eagles that consume contaminated fish. Despite the modeling not bei ng able to quantify any improvements to minks and eagles under the final rule, the pollutant loading removals will decrease bioaccumulation of toxic pollutants in the terrestria l food chains (if Plant Harllee Br anch did not retire all generating units).

The Lake Sinclair EFDC model is not set up to qua ntify the pollutant concentrations in the benthic sediment; therefore, EPA was unable to assess whether polluta nt concentrations in the sediment exceeded CSCL benchmarks and pose a threat to benthic organisms.

Modeling Results – Human Health

For the analysis of human health impacts a nd improvements, EPA also assumed that fish travel freely throughout Lake Sincla ir and do not confine themselves within particular segments of the lake. EPA calculated the average fish tissue concentrations of all segments within the Lake Sinclair model ( i.e. , entire modeling area) for purposes of the human health assessment.

8-57Section 8—Case Study Modeling

Under baseline conditions, th e average water column concen tration of arsenic in Lake Sinclair over the modeling period does not result in an estimated cancer riskgreater than 1-in-amillion for any of the national-scale cohorts.

Based on the average pollutant concentra tions in the water column under baseline conditions, thallium poses the grea test threat to cause non-cancer health effects in humans from fish consumption. Average thallium concentrati ons in the water column of the entire Lake Sinclair modeling area are greate r than the concentrations that would translate to exceedance of

the reference doses for adult and children recrea tional and subsistence fishers (all national-scale cohorts evaluated). Therefore, humans who cons ume thallium-contaminated fish inhabiting the modeled area of Lake Sinclair may be at greate r risk for developing the negative health effects associated with these pollutants, which are discussed in Section 3.1.1.

While the modeling results continue to show thallium water concentrations that would

translate to exceedances of the non-cancer health e ffects reference dose, the final rule will reduce thallium loading contributions from Plant Harllee Branch (if Plant Harllee Branch did not retire all generating units).

Interpretation of Lake Sinclair Results

The case study modeling results indicate that the water qualit y impacts are greater in the receiving branch (closest portion of the lake to the Plant Harllee Branch discharge) of Lake Sinclair compared to the rest of the lake. EP A identified that the receiving branch of Lake

Sinclair also exhibited more quantifiable improvements ( i.e. , reduced NRWQC and MCL benchmark exceedances) under the final rule than the average of all Lake Sinclair model segments. Despite the model not indicating any wildlife or human health impacts in Lake Sinclair, the reduction of pollutant loadings under the final rule would lessen the contribution of steam electric power plant discharges on the entire aquatic and te rrestrial ecosystems.

8.3 C OMPARISON OF C ASE S TUDY AND IRW M ODELING R ESULTS

In general, the case study m odeling results from the six case study models support the

overall conclusions of the IRW model.

Case study modeling of smaller receiving wate rs, such as Black Creek and Lick Creek, indicate that more severe water quality, wildlife, and human health impacts are occurring at baseline conditions than the IRW model predicted. Since flow rates in small receiving waters fluctuate significantly, the case study modeling demonstrates im pacts that can occur during periods when the flow is lower than the annual average used in the IRW model. During the frequent periods of low flow in smaller rivers and streams, th e case study modeling shows that pollutant concentrations quickly climb to levels that will negatively aff ect fish, wildlife, and

humans. The Black Creek and Lick Creek case study model also sugge sts the potential for additional improvements under the final rule than the IRW model predicts. Case study modeling therefore indicates that small receiving waters w ith highly variable flow rates may benefit from

the final rule more than th e IRW model results suggest.

The case study modeling also demonstrates th at the impacts from steam electric power plant discharges can propagate much further downstream than the immediate receiving water

8-58Section 8—Case Study Modeling

used in the IRW modeling. In four of the six case study models, results illustrate that the pollutant loadings from steam electric power plan t discharges of the evaluated wastestreams may contribute to water quality impacts up to 95 miles downstream of the plant discharge. These additional impacts, as well as additional improvement s under the final rule, are not represented in the IRW modeling results.

Additionally, case study modeli ng of smaller water bodies revealed that downstream reaches may be heavily influenced by the sedi ment transport and exhi bit much higher water

column concentrations than the immediate receiv ing water. In the Black Creek, Etowah River, and White River results, “hot spots” with high er pollutant concentrations were observed and posed a greater risk to humans, aquatic life, and te rrestrial food chains than reaches closer to the steam electric power plants.

EPA performed one case study model of a repres entative lentic receiving water to assess the potential impact on similar lakes or rese rvoirs that receive steam electric power plant discharges of the evaluated wastestreams. Case study modeling of Lake Sinclair showed that impacts are occurring in the lake, and these are more severe in the imme diate area of the steam electric discharge as compared to the la ke average. The water quality improvements demonstrated by the reduced exceedances of water quality benchmarks indicate that other lentic receiving waters may also exhibit similar improvements. Although the case study modeling of Lake Sinclair was unable to qua ntify the accumulation of pollutant concentrations in benthic sediment, lower concentrations of pollutants un der the final rule shoul d reduce pollutant longterm accumulation and consequential resuspension.

Each of the case study models demonstrated at least one exceedance of a water quality, wildlife, or human health benchmark for a mode led pollutant discharged from stream electric power plants. Under the final rule, the steam elect ric power plant(s) will contribute a reduced loading of the pollutant(s), thereby improving water quality in these receiving waters. As demonstrated by the Black Creek, Etowah River, Lick Creek and White River, Ohio River, and Lake Sinclair case study mode ling results, pollutant removals will result in quantifiable improvements through reduced exceedan ces of environmental benchmarks.

8-59Section 9—Conclusions



## SECTION 9
CONCLUSIONS

Based on evidence in the literature, dama ge cases, other documented impacts, and modeled receiving water pollutant concentrations, it is clear that current wastewater discharge practices at steam electric power plants are im pacting the surrounding aquatic and terrestrial environments and pose a human health threat to nearby communities. EPA estimates that discharges from steam electric power plants c ontribute over one-third of the toxic-weighted pollutant loadings of the combined discharges of all industrial categorie s currently required to report discharges to U.S. waters. These discharg es add large quantities of toxic bioaccumulative pollutants ( e.g. , selenium, arsenic, and mercury) to the aquatic environment. Substantial evidence exists that pollutants from steam electric power pl ant wastewater discharges are transferring from the aquatic environment to terres trial food webs; this indicates the potential for broader impacts to ecological systems by altering population di versity and community dynamics in the areas surrounding steam electric power plants. Ecosyste m recovery from exposure to steam electric power plant wastewater discharg es can be extremely slow and even short periods of exposure ( e.g. , less than a year) can cause observable ecologi cal impacts that last for years. The strong bioaccumulative properties and long residence time s of pollutants in imme diate receiving waters

reinforce the threat of these wastes to the local environment, and many of the impacts may not be fully realized for years to come.

In addition, EPA’s modeling demonstrates that pollutant loadings from discharges of the evaluated wastestreams are imp acting areas beyond the immediat e receiving waters and pose a threat to wildlife and human popul ations in thousands of rive r-miles downstream from steam electric power plants under current discharge pr actices. Furthermore, EP A predicts that the recently promulgated Clean Air Act requirements ( i.e. , Clean Power Plan) and other state and local regulations may lead to a dditional air pollution controls (a nd resulting wastestreams) that will increase the pollutant loadings to surface wa ters in the future. These additional pollutant loadings above current baseline conditions will increase the number of immediate receiving waters exceeding water quality, wildlife, a nd human health benchmarks in the future. 65

Steam electric power plants discharge wastewat er into waterbodies used for recreation, and these discharges can present a potential threat to human health. Documented fish kills have resulted in states issuing fish advisories to prot ect the public from exposure to fish with elevated pollutant concentrations in recreational waters that receive these discha rges. Combustion residual leachate from surface impoundments and landfills is known to impact off-site ground water and drinking water wells at concentrations above Maximum contaminant level (MCL) drinking water standards and pose a potential threat to human health.

65 The analyses presented in this report incorporate some adjustments to current conditions in the industry. For example, these analyses account for pub licly announced plans from the steam electric power generating industry to retire or modify steam electric generating units at specifi c power plants. These analyses also account for changes to the industry that are expected to occur as a result of the recent Coal Combustion Residuals (CCR) rulemaking by EPA’s Office of Solid Waste and Emergency Response (OSWER). These analyses, however, do not reflect changes in the industry that may occur as a result of the proposed Clean Power Plan [Clean Air Act section 111(d)].

9-1Section 9—Conclusions

The final steam electric effluent limitations guidelines and standards (ELGs) will result in quantifiable improvements in ecological and hu man health by reducing immediate receiving water pollutant concentrations , on average, by 57 percent. 66 The final rule will result in the following environmental improvements as estimat ed by the national-scale immediate receiving water (IRW) model:

 A 51 to 67 percent reduction in the number of immediate receiving waters exceeding National Recommended Water Quality Crit eria (NRWQC) for the protection of aquatic life.

 A 45 to 50 percent reduction in the number of immediate receiving waters exceeding an NRWQC for the protection of human health.

 A 63 to 64 percent reduction in the numbe r of immediate receiving waters that support fish whose tissue pollutant concen trations exceed benchmarks for the protection of piscivorou s wildlife (represented by minks and eagles).

 A 61 to 67 percent reduction in the numbe r of immediate receiving waters where selenium contamination in the food web presents reproductive risks 67 to aquatic wildlife (represented by fish and mallards).

 A 56 to 75 percent reduction in the numbe r of immediate receiving waters that support fish whose tissue pollutant concen trations pose a cancer risk to exposed populations.

 A 52 to 56 percent reduction in the numbe r of immediate receiving waters that support fish whose tissue pollutant concentr ations pose a risk of non-cancer health effects in exposed populations.

The results of th e case study modeling for selected plan ts and receiving waters indicate that the environmental and human health impact s associated with stea m electric power plant discharges, and the corresponding improvements under the final rule, could be even more extensive than those predicted by the IRW model. Case study modeling re sults demonstrate that the impacts from steam electric power plant di scharges of the evaluated wastestreams can propagate much further downstream of the immedi ate receiving water. While the steam electric power plant discharges may not cause these impacts in isolat ion, case study modeling reveals that the discharges contribute to the further im pairment of such waterways. Case study modeling results identified a larger increase in baseline impacts and improvements under the final rule in small receiving waters with variable flow than la rger receiving waters. The analyses presented in the environmental assessment (EA) focus on qua ntifying the environmental improvements within rivers and lakes from post-compliance pollutant removals for metals, bioaccumulative pollutants,

and nutrients.

66 Reductions apply to the subset of pollutants evaluated in the environmental assessment ( i.e. , arsenic, cadmium, chromium VI, copper, lead, mercury, nickel, selenium, thallium, and zinc).

67 For this statistic, reproductive risk is indicated by a 50-percent (or higher) probability that adverse reproductive effects will occur in at least 10 percent of the exposed population of fish and mallards.

9-2Section 9—Conclusions

While extensive, the environmental improvements quantified above do not encompass the full range that will result from the final rule, such as the following improvements that are not quantified (or have only limited analysis) in this EA:

 Reducing the loadings of bioaccumulative pollutants to the broader ecosystem, decreasing long-term exposures a nd sublethal ecological effects.

 Reducing sublethal chronic effects of toxic pollutants on aquatic life not captured by the NRWQC.

 Reducing loadings of pollutants for which EPA did not perform water quality modeling in support of the EA ( e.g. , boron, manganese, aluminum, vanadium, and iron).

 Mitigating impacts to aquatic and aquatic-d ependent wildlife population diversity and community structures. 68

 Reducing wildlife exposure to pollutants through direct contact with combustion residual impoundments and constructed wetlands built as treatment systems at steam electric power plants.

 Reducing water withdrawals from surface wa ters and aquifers, leading to greater availability of groundwater supplies fo r alternative uses and reducing fish impingement and entrainment mortality due to surface water intake structures.

 Reducing the potential of harmful algal blooms to form.

Data limitations prevented EPA from appropriately modeling the scale and complexity of the ecosystem processes potentially impacted by steam electric power plant wastewater and therefore did not fully quantify the improvements listed above. However, damage cases and other documented impacts in the literature reinforce that these impacts are common in the environments surrounding steam electric power plants and fully support the conclusion that pollutant removals will improve overall environmental

and wildlife health.

Although the EA quantifies some impacts to wildlife that consume fish contaminated with pollutants from steam electric power plant wastewater, it does not capture the full range of exposure pathways th rough which bioaccumulative pollutants can enter the surrounding food web. Wildlife can encounter bioaccumulative pollutants from steam electric power plant wastewater discha rges through direct exposure, drinking water, consuming

68 EPA did evaluate impacts to aquatic and aquatic-dependent wildlife from selenium contamination as part of the ecological risk modeling. EPA did not quantify impacts that might occur due to other pollutant contamination. A s surface impoundments accumulate fly ash, bottom ash and flue gas desulfurization

s ludges, they can begin to fill up and lose their treatment capability.

9-3Section 9—Conclusions

contaminated vegetation, and consuming contamin ated prey other than fish. Therefore, the quantified improvements underestimate the complete loadings of bioaccumulative pollutants that can impact wildlife in the eco system. EPA did quantify improvements to aquatic and aquaticdependent wildlife due to redu ced selenium exposure via the food web. The reduced selenium loadings under the final rule will significantly re duce the risk of negative reproductive effects to

wildlife in waterbodies that recei ve discharges from steam electr ic power plants. In addition to the improvements resulting from reduced sele nium loadings, EPA estimates that the postcompliance pollutant removals under the final rule will lower the total amount of bioaccumulative pollutants entering the food web in immediate receiving waters and downstream

waters.

EPA estimates that pollutant removals will also decrease sublethal e ffects associated with many of the pollutants in steam electric power plant wastewater that may not be captured by comparisons with NRWQC for aquatic life. Well- documented studies suggest that organisms in aquatic environments near steam electric power pl ants exhibit chronic effects such as changes in metabolic rates, decreased growth rates, changes in morphology ( e.g. , fin erosion, oral deformities), and changes in behavior ( e.g. , decreased ability to swim, catch prey, or escape from predators) that can negatively a ffect long-term survival [Raimondo et al ., 1998; Rowe et al

., 1996, 2002]. However, these effects are not fully qua ntified in the EA due to data limitations, and therefore improvements to wildlife health and survival from the final rule may be underestimated. Reduced organism survival rates from chronic effects such as abnormalities can alter interspecies relationships ( e.g. , declines in the abundance or quality of prey) and prolong ecosystem recovery. EPA was unable to quantif y changes to aquatic and wildlife population diversity and community dynamics ; however, population effects ( i.e. , decline in nu mber and type of organisms present) attributed to exposure to steam electric power plant wastewater are well documented in the literature [Lemly, 1985a; Garrett and Inman, 1984; Sorensen et al ., 1982]. Changes in aquatic populations can alter th e structure of aquatic communities and cause cascading effects within the food web that have long-term impacts to ecosystem dynamics. EPA estimates that post-compliance pollutant removals associated with the final rule will lower the stressors that can alter population and comm unity dynamics and will improve the overall function of ecosystems surrounding steam electric power plants.

9-4Section 10—References



## SECTION 10
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10-11Section 10—References

U.S. EPA. 2000b. Selenium Compounds (websi te). (January). Available online at: http://www.epa.gov/ttn/atw/hlthef/selenium.html . DCN SE01923.

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U.S. EPA. 2005c. Drinking Water Criteria Document for Brominated Trihalomethanes. EPA

822-R-05-011. Office of Water. Wash ington, DC. (November 15). DCN SE06443.

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10-12Section 10—References

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U.S. EPA, 2011c. Integrated Ri sk Information System (IRIS)

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DC. DCN SE04457.

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10-13Section 10—References

U.S. EPA. 2014g. Human and Ecological Risk Assessmen t of Coal Combustion Residuals

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10-14Section 10—References

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10-15