Appendix A— Literature Review Methodology and Results 

APPENDIX A 

LITERATURE REVIEW METHODOLOGY AND RESULTS 

This appendix presents the methodology, resources, and summary results for the literature 

review. The U.S. Environmental Protection Agency (EPA) used the keyword list in Table A-1 to 

identify peer-reviewed journal articles that document environmental and human health impacts 

caused by steam electric power plant discharges of the evaluated wastestreams. The literature

search focused on information regarding impacts caused by pollutants of concern for the steam

electric power generating industry (e.g., toxic bioaccumulative pollutants such as mercury and 

selenium, metals such as arsenic and lead, and nutrients) in the discharges. EPA also searched for 

environmental assessments, impact studies, and related documents from state and federal 

governments. 

In addition, the literature search involved collecting information from newspapers, 

environmental groups, industry organizations, and other non-peer-reviewed information sources. 

These sources are considered to be “gray literature” and are not acceptable forms of formal 

documentation of environmental impact events. However, these literature sources can provide

useful information for identifying potential areas of concern. Often, an environmental event is 

reported in gray literature sources before it is well documented in peer-reviewed journals or 

government reports. EPA used gray literature to help highlight areas of interest and facilitate 

additional searches of peer-reviewed journals for more detailed information on the impacted area.

EPA used several different search engines to broaden the range of reference materials 

represented in the results. The Agency searched the following search engines in the order 

presented, using the keyword list in Table A-1: 

 Scirus – A comprehensive science-specific search engine that provides access to a large 

database of scientific, technical, and medical journals. 

 Science Direct – An online library that features full text journals from Elsevier, 

Academic Press, and other scholarly publishers. 

 Ingenta – A scholarly research database that provides access to a large collection of

academic and professional research articles.

 Google Scholar – A search engine used to find other articles that cited previously 

identified references as well as perform a general search of scholarly literature, 

including peer-reviewed papers, theses, books, abstracts, and articles from academic 

publishers, professional societies, preprint repositories, and universities and other 

scholarly organizations. 

 Google – A search engine used to perform a general search of information readily 

available on the Internet.

A-1 
 

Appendix A— Literature Review Methodology and Results 

Table A-1. Keyword Search Terms for Environmental Impacts from

Steam Electric Power Plants

Category Keyword

Ash pond 

Discharge

Lake 

Landfill 

Leachate

Leaks

Lotic system

Plume 

Pond 

Power plant 

General Terms Receiving water 

River 

Sediment 

Steam electric

Stream 

Surface waters

Water

Wastewater 

Water pollution 

Water quality

Waste management

Wastewater discharges

Algal blooms

Attractive nuisance 

Background levels/concentrations

Bioaccumulation 

Biomagnification

Biomagnify

Contamination 

Environmental impact

Environmental Terms Environmental assessment 

Eutrophication

Fish 

Fish consumption advisory

Fish kill 

Fish mortality

Fish recovery 

Hot Spot

Toxicity

Wildlife 

Arsenic

Arsenate

Pollutants of Concern Arsenite 

Boron 

Boric Acid 

A-2 
 

Appendix A— Literature Review Methodology and Results 

Table A-1. Keyword Search Terms for Environmental Impacts from

Steam Electric Power Plants

Category Keyword

Chloride(s)

Chromium

Magnesium

Mercury 

Metals

Methylmercury 

Nitrate 

Nitrogen 

Selenium

Selenate 

Selenite 

Sulfate

Coal 

Fuel Source Terms Coal combustion by-products

Coal combustion residues

Oil 

Cancer 

Carcinogen 

Carcinogenic 

Human Health Terms Drinking water

Health effects

Human health

Toxicity

Case study 

Other Terms Damage case assessment 

Environmental impacts 

Environmental aspects

To perform the literature search, EPA paired each fuel source term (see Table A-1) with at 

least one keyword to focus the search results. Although EPA used multiple fuel source terms, the 

environmental impacts from the steam electric power generating industry are documented most 

commonly for coal-fired power plants. EPA used best professional judgment to create multiple 

keyword combinations to further focus the literature search.

In addition to the key word combinations and search engines described above, EPA used 

the following supplemental methods to identify more articles for the targeted topic areas: 

 Reviewed references cited in previously identified published literature for additional 

documented cases of environmental impact. 

 Searched the Agency for Toxic Substances and Disease Registry’s (ATSDR) website 

for public health assessments and health consultations with information on the case 

study sites referenced in Dr. Christopher Rowe’s literature review paper published in

2002 [Rowe et al., 2002]. 

A-3 
 

Appendix A— Literature Review Methodology and Results 

 Searched for case studies of attractive nuisances unrelated to the steam electric power 

generating industry using the search engines described above. 

 Reviewed EPA’s December 2014 Coal Combustion Residuals (CCR) Damage Cases 

Database and supporting compendiums [U.S. EPA, 2014a; U.S. EPA, 2014b; U.S. 

EPA, 2014c; U.S. EPA, 2014d; U.S. EPA, 2014e]1 and Michigan’s Department of 

Natural Resources and Environment (MDNRE’s) Docket Comments (see Table A-3

for a full list of references).

 Searched magazines related to the steam electric industry and newspapers for articles 

documenting additional environmental impacts. 

EPA created a database for the literature review that documents the identified literature and 

summarizes key information. EPA finalized the primary literature review on November 24, 2010; 

however, the database also includes literature identified after the primary search efforts were 

completed [ERG, 2013b]. EPA created a second database to summarize the damage cases and 

other documented site impacts [ERG, 2015m]. 

The following tables in Appendix A summarize information EPA gathered from the 

literature review: 

 Table A-2. Summary of Literature Review Results by Information Source. 

 Table A-3. Summary of Damage Cases and Other Documented Site Impacts to Surface 

Water and Ground Water from Steam Electric Power Plant Discharges. 

 Table A-4. Summary of Documented Ground Water Damage Cases from Surface

Impoundments. 

 Table A-5. Summary of Documented Ground Water Damage Cases from Landfills.

 Table A-6. Summary of Documented Surface Water Damage Cases from Surface 

Impoundments. 

 Table A-7. Summary of Documented Surface Water Damage Cases from Landfills.

 Table A-8. Summary of Attractive Nuisances Related to Steam Electric Power Plants. 

 Table A-9. Summary of Attractive Nuisances Unrelated to Steam Electric Power 

Plants. 

 Table A-10. Summary of Selenium Concentrations in the Environment and Organisms 

Experiencing Adverse Effects. 

Table A-2 highlights the results of the literature search, including documents identified by 

keyword searches and relevant documents identified from supplemental methods. During the 

period following completion of the literature review and the associated database, EPA obtained 

additional documents (e.g., through public comments and informal searches) that supported 

development of the final steam electric effluent limitations guidelines and standards (ELGs). EPA 

1

 These 2014 references are updates to EPA’s September 18, 2012 review of damage cases which were primarily

identified in EPA’s Damage Case Assessment Report; Environmental Integrity Project’s (EIP’s) Out of Control:

Mounting Damages From Coal Ash; and EIP’s In Harm’s Way: Lack of Federal Coal Ash Regulations Endangers 

Americans and Their Environment. 

A-4 
 

Appendix A— Literature Review Methodology and Results 

incorporated relevant information from the additional literature in the EA report and in the other

tables included in this Appendix. 

Table A-3 summarizes the number of documented site impacts to surface water and ground 

water identified during the literature search and organized by steam electric power plant. Table A4 and Table A-5 summarize the damage cases to ground water from combustion residuals surface 

impoundments and landfills, respectively. Table A-6 and Table A-7 summarize the damage cases 

to surface water from combustion residuals surface impoundments and landfills, respectively.

Table A-8 and Table A-9 summarize attractive nuisances identified during the literature search,

related and unrelated to steam electric power plants, respectively. Table A-10 presents selenium 

concentrations in the environment that are documented in the literature as causing sublethal and 

lethal effects to organisms. 

A-5 
 

 

 

 

 

Appendix A— Literature Review Methodology and Results 

Table A-2. Summary of Literature Review Results by Information Source 

Source Type

Number of Documents

Identified

Number of Documents

Reviewed f

Number of Documents that 

Discussed Environmental 

and Human Health Impacts 

Peer-Reviewed Literature a

 151 128 117 

Government Publication b 53 47 32

University Research c

 13 12 9

Gray Literature d 18 16 14

Industry Publication e

 4 3 3 

Total 239 206 175 

Source: ERG, 2013b. 

a – Peer-reviewed literature consists of journal articles that undergo a formal review process prior to publishing. 

b – Government publications are documents affiliated with state or federal government agencies. 

c – University research includes finalized dissertations and theses, as well as papers published on behalf of a 

university or presented at a conference. 

d – Gray literature includes documents that are subjected to a less stringent review process (e.g., newspaper articles, 

environmental group publications).

e – Industry publications include documents prepared by or for industry-affiliated entities. 

f – EPA did not review several documents as part of the formal literature review either because EPA was unable to

acquire the full text of the document for review or because once the full text document was obtained a preliminary

review determined the document was not appropriate for inclusion in the literature review. 

A-6 
Appendix A— Literature Review 

Table A-3. Summary of Surface Water and Ground Water Impacts Reported in Damage Cases and Othe

from Steam Electric Power Plant Discharges

Plant Name

Number of Damage Cases 

and Other Literature that 

Document 

Surface Water Impacts a

N

an

G

A.B. Brown Generating Station, Southern Indiana Gas and Electric Company (SIGECO) (IN) 0 Allen Fossil Plant Tennessee Valley Authority (TVA) (TN) 0 Allen Steam Generating Plant, Duke Power (NC) 1 Alma Station, Dairyland Power (WI) 0 Asheville Plant, Progress Energy (NC) 2 

B.C. Cobb Power Plant, Consumers Energy (MI) 0 

Bailly Generating Station, Northern Indiana Public Service Company (NIPSCO) (IN) 0 Belews Creek Steam Station, Duke Energy (NC) 14 Belle River Power Plant, Detroit Edison Company (MI) 1 Big Bend Station, Tampa Electric Company (FL) 1 

Big Cajun 2 Power Plant, NRG Energy/Louisiana Generating, LLC (LA) 0 

Brandon Shores, Constellation Energy (MD) 0 

Brayton Point Station, Dominion (MA) 0 Bruce Mansfield Power Plant, First Energy (PA) 1 

Buck Steam Station, Duke Energy (NC) 1 

Bull Run Steam Plant, Tennessee Valley Authority (TVA) (TN) 1 C.D. McIntosh, Jr. Power Plant, City of Lakeland (FL) 0 

C.R. Huntley Generating Station, NRG Energy (NY) 0 

Canadys Plant, South Carolina Electric & Gas (SCE&E) (SC) 0 

Cape Fear Steam Plant, Progress Energy (NC) 0 Cardinal Plant, American Electric Power (AEP) (OH) 1 

Cargill Salt Power Plant, Cargill (MI) 1 Cayuga Generating Station, Duke Energy (NY) 1 Chalk Point Generating Station, Mirant (MD) 1 Chesapeake Energy Facility, Dominion Power (VA) 1 

A-7 
Appendix A— Literature Review 

Table A-3. Summary of Surface Water and Ground Water Impacts Reported in Damage Cases and Othe

from Steam Electric Power Plant Discharges

Plant Name

Number of Damage Cases 

and Other Literature that 

Document 

Surface Water Impacts a

N

an

G

Cholla Steam Electric Generating Station, Arizona Public Service Company (AZ) 0 Christ Power Plant, Gulf Power (Southern Company) (FL) 0 

Clifty Creek Station, Indiana Kentucky Electric Company (IKEC) (IN) 0 

Clinch River Plant, American Electric Power (AEP)/Appalachian Power (VA) 1 

Coal Creek Station, Cooperative Power Association/United Power (ND) 0 

Coffeen Power Station, Ameren (IL) 0 

Colbert Fossil Plant, Tennessee Valley Authority (TVA) (AL) 0 Coleto Creek Power Station, International Power (TX) 0 

Colstrip Power Plant, PPL Montana (MT) 0 

Columbia Electric Generating Station (WI) 5 

Columbia Energy Center, Alliant Energy (WI) 1 Conesville Power Plant, American Electric Power (AEP) (OH) 0 

Cross Generating Station, Santee Cooper/South Carolina Public Service Authority (SCPSA) (SC) 0 Cumberland Steam Plant, Tennessee Valley Authority (TVA) (TN) 1 Curtis Stanton Energy Center, Orlando Utility Commission (FL) 1 

Dallman Station, City Water, Light and Power (IL) 0 Dan River Steam Station, Duke Energy (NC) 2 Danskammer Generating Station, Dynegy (NY) 0 D-Area Coal-Fired Power Plant, Savannah River Site (SRS) (SC) 24 

Dave Johnston Power Plant (WY) 1 Dickerson Generating Station, Mirant (MD) 1 

Dolet Hills Power Station, Central Louisiana Electric Co-Op (CLECO) Power, LLC (LA) 0 

Duck Creek Station, Central Illinois Light Company (IL) 0 Dunkirk Generating Station, NRG Energy (NY) 0 

E.J. Stoneman Generating Station, Dairyland Power Cooperative (WI) 0 

A-8 
Appendix A— Literature Review 

Table A-3. Summary of Surface Water and Ground Water Impacts Reported in Damage Cases and Othe

from Steam Electric Power Plant Discharges

Plant Name

Number of Damage Cases 

and Other Literature that 

Document 

Surface Water Impacts a

N

an

G

East Bend Generating Station, Cinergy (KY) 0 

Eckert Station, Lansing Board of Water & Light (MI) 0 

Edgewater Generating Station, Alliant Energy (WI) 0 

Elizabethtown Power Plant, North Carolina Power Holdings (NC) 0 

Elrama Power Plant, Reliant Energy (PA) 1 

Erickson Station, Lansing Board of Water & Light (MI) 0 

Fair Station, Central Iowa Power Cooperative (IA) 0 Fayette Power Project, Lower Colorado River Authority (TX) 0 Flint Creek Power Plant, American Electric Power (AEP)/South West Electric Power Company(SWEPCO) (AR) 1 Gallatin Fossil Plant, Tennessee Valley Authority (TVA) (TN) 0 General James M. Gavin Power Plant, American Electric Power/Ohio Power Company (OH) 1 George Neal Station North, Berkshire Hathaway/MidAmerican Energy Company (IA) 0 George Neal Station South, Berkshire Hathaway/MidAmerican Energy Company (IA) 0 Gibson Generating Station, Duke Energy (IN) 5 

Glen Lyn Plant, American Electric Power (AEP)/Appalachian Power (VA) 6 Grainger Generating Station, Santee Cooper/South Carolina Public Service Authority (SCPSA) (SC) 1 Greenidge Generation Plant, AES (NY) 0 Harbor Beach Power Plant, Detroit Edison Company (MI) 1 Hatfield's Ferry Power Station, Allegheny Energy (PA) 1 Havana Power Plant, Illinois Power Company (IL) 0 

Hennepin Power Station, Illinois Power Company (IL) 0 

Herbert A. Wagner, Constellation Energy (MD) 0 

Hickling Generation Plant, AES (NY) 0 

Hopewell Power Station, Dominion Power (VA) 0 

A-9 
Appendix A— Literature Review 

Table A-3. Summary of Surface Water and Ground Water Impacts Reported in Damage Cases and Othe

from Steam Electric Power Plant Discharges

Plant Name

Number of Damage Cases 

and Other Literature that 

Document 

Surface Water Impacts a

N

an

G

Hunlock Power Station, UGI Development Company (PA) 0 Hutsonville Power Station, Central Illinois Public Service Company (IL) 0 

Independence Steam Station, Entergy/Arkansas Power and Light (AR) 0 Indian River Generating Station, NRG Energy (DE) 1 J.H. Campbell Power Plant, Consumers Energy (MI) 1 

J.R. Whiting Generating Plant, CMS/Consumers Energy (MI) 1 

Jennison Generation Plant, AES (NY) 0 John Amos Plant, American Electric Power (AEP)/Appalachian Power (WV) 1 

John H. Warden Generating Station, Integrys (MI) 1 

John Sevier Fossil Plant, Tennessee Valley Authority (TVA) (TN) 1 

Johnsonville Fossil Plant, Tennessee Valley Authority (TVA) (TN) 2 Joliet Generating Station 9, Midwest Generation (IL) 0 Joppa Steam Plant, Ameren (Electric Energy) (IL) 0 Karn/Weadock Generating Facility, Consumer Energy (MI) 0 

Kenansville Plant, Green Power Energy Holdings (NC) 0 Kingston Fossil Plant, Tennessee Valley Authority (TVA) (TN) 7 Lansing Smith Plant, Florida Power and Light (FL) 0 

Lee Steam Plant, Progress Energy (NC) 0 

Leland Olds Station, Basin Electric Power Cooperative (ND) 0 Lumberton Power Plant, North Carolina Power Holdings (NC) 0 Marion Plant, Southern Illinois Power Cooperative (IL) 1 Marshall Steam Station, Duke Energy (NC) 1 Martin Lake Steam Station, Texas Utilities Electric Service Company (TX) 9 Martin's Creek Power Plant, PPL (PA) 1 

Marysville Power Plant, Detroit Edison Company (MI) 1 

A-10 
Appendix A— Literature Review 

Table A-3. Summary of Surface Water and Ground Water Impacts Reported in Damage Cases and Othe

from Steam Electric Power Plant Discharges

Plant Name

Number of Damage Cases 

and Other Literature that 

Document 

Surface Water Impacts a

N

an

G

Mayo Steam Station, Progress Energy (NC) 1 

McMeekin Station, SCANA/South Carolina Electric & Gas Company (SCE&G) (SC) 0 Mendosa Power Station, Ameren Energy Generating Company, (IL) 0 

Merom Generating Station, Hoosier Energy (IN) 1 

Miamiview Landfill, Cincinnati Gas & Electric Company (OH) b 0 

Michigan City Generating Station, Northern Indiana Public Service Company (NIPSCO) (IN) 0 

Mill Creek Plant, E ON U.S./Louisville Gas & Electric (LG&E) (KY) 0 

Mitchell Power Station, Allegheny Energy (PA) 0 

Montville Generating Station, NRG Energy/Montville Power, LLC (CT) 1 

Morgantown Generating Station, Mirant (MD) 2 

Muskingum River Plant, American Electric Power (AEP)/ Ohio Power Company (OH) 0 

Nelson Dewey Generating Station, Alliant Energy (WI) 0 

Northeastern Station, American Electric Power/Public Service Company Oklahoma (OK) 0 Oak Creek Power Plant, Wisconsin Energy (WE Energies (WE))/Wisconsin Electric Power Company (WI) 1 Oak Ridge Y-12 Plant, Department of Energy (TN) 4 Paradise Fossil Plant, Tennessee Valley Authority (TVA) (KY) 0 

Parish Generating Station, NRG Energy/Texas Genco II (TX) 0 Pearl Station, Prairie Power Inc./Soyland Power Coop (IL) 0 

Petersburg Generating Station, Indianapolis Power & Light (IN) 0 

Phillips Power Plant, Duquesne Light Company (PA) 1 

Pirkey Power Plant, Southwestern Electric Power Company (SWEPCO) (TX) 2 Plant Bowen, Georgia Power (GA) 1 Port Washington Facility, Wisconsin Electric Power Company (WEPCO) (WI) 0 

Portland Generating Station, RRI Energy (PA) 1 

A-11 
Appendix A— Literature Review 

Table A-3. Summary of Surface Water and Ground Water Impacts Reported in Damage Cases and Othe

from Steam Electric Power Plant Discharges

Plant Name

Number of Damage Cases 

and Other Literature that 

Document 

Surface Water Impacts a

N

an

G

Powerton Plant, Commonwealth Edison (IL) 1 Prairie Creek Station, Interstate Power and Light (Alliant) (IA) 0 

Presque Isle Power Plant, WE Energies (WE) (MI) 0 Pulliam Power Plant, Wisconsin Public Service Corp. (WI) 0 

R.M. Heskett Station, Montana-Dakota Utilities (ND) 0 R.M. Schahfer Generating Station (IN) 0 

Reid Gardner Generating Facility, Nevada Energy (NV) 1 

Riverbend Steam Station, Duke Energy (NC) 4 Rock River Generating Station, Alliant Energy (WI) 0 Rocky Mount Power Plant (NC) 0 Rodemacher Power Station, Central Louisiana Electric Co-Op (CLECO) Power, LLC (LA) 0 

Roxboro Plant, Progress Energy (NC) 8 Salem Harbor Station, Dominion (MA) 0 

SCANA Williams Station (SC) 1 Seminole Generating Station, Seminole Electric Cooperative (FL) 1 Seward Generating Station, RRI Energy (PA) 1 

Shawnee Fossil Plant, Tennessee Valley Authority (TVA) (KY) 1 Sheldon Station, Nebraska Public Power District (NE) 0 Sherburne County (Sherco) Generating Plant, Xcel Energy/Southern Minnesota Municipal PowerAgency (MN) 0 Shiras, Marquette Board of Light & Power (MI) 0 

Spurlock Station, Eastern Kentucky Power Cooperative (KY) 0 Sutton Steam Plant, Progress Energy (NC) 1 Unnamed Plant 1c 1 

A-12 
Appendix A— Literature Review 

Table A-3. Summary of Surface Water and Ground Water Impacts Reported in Damage Cases and Othe

from Steam Electric Power Plant Discharges

Plant Name

Number of Damage Cases 

and Other Literature that 

Document 

Surface Water Impacts a

N

an

G

Unnamed Plant 2 c 1 

Unnamed Plant 3 c 1 Unnamed Plant 4 c 1 Urquhart Station, South Carolina Electric & Gas Company (SGE&E) (SC) 0 

Valley Power Plant, Wisconsin Energy (WI) 0 

Venice Power Station, Union Electric Company/Ameren Energy/AmerenUE (IL) 0 

Vermillion Power Station, Illinois Power (IL) 0 W.C. Beckjord Station, Duke Energy (formerly Cinergy) (OH) 0 

W.J. Neal Station, Basin Electric Power Cooperative (ND) 1 Wateree Station, SCE&G (SC) 1 Waukegan Generating Station, Midwest Generation (Edison International) (IL) 0 

Welsh Power Plant, Southwestern Electric Power Company (SWEPCO) (TX) 3 Westover Generation Plant, AES (NY) 0 Widows Creek Fossil Plant, Tennessee Valley Authority (TVA) (AL) 0 

Winyah Generating Station, Santee Cooper/South Carolina Public Service Authority (SCPSA) (SC) 0 

Wood River Power Station, Illinois Power Company (IL) 0 

Yorktown Power Station, Virginia Electric Power and Power Company (VEPCO) (VA) 0 Total 152 

Source: ERG, 2015m; U.S. EPA, 2014a through 2014e.a – One case study or damage case may document impacts to both ground water and surface water. b – The damage case source did not specifically identify the plant name; therefore, EPA used the name of the damage case.c – EPA was unable to identify the steam electric power plant associated with this documented impact. For the purpose of counting the these impacts were assumed to be associated with a plant not already identified elsewhere in this table.

A-13 
Appendix A— Literature Review 

Table A-4. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Pow

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

MCL b

Exceeded Federal/ 

State WQC/ 

Standards b

Grou

Impac

W

Allen Fossil Plant Tennessee Valley Authority (TVA) (TN)

Pond/Impoundment Arsenic, Manganese, TDS X

Allen Steam Generating Plant,Duke Power (NC)

Pond/Impoundment Manganese, Iron, pH, Nitrate, 

Nickel

X 

Alma Off-site Fly Ash Landfill, Dairyland Power (WI)

Pond/Impoundment Sulfate, Manganese, Boron,

Selenium, Cadmium

Asheville Steam Electric Plant, Pond/Impoundment Boron, Chromium, Iron, X X Progress Energy (NC) Manganese, Thallium, Nitrate, 

Sulfate, pH, TDS, Cadmium,Arsenic, Antimony

Bailly Generating Station, Northern Indiana Public Service Company (NIPSCO) (IN)

Pond/Impoundment, Landfill 

Arsenic, Cadmium X

Bangor Quarry Ash DisposalSite, Portland Generating Station,RRI Energy (PA) 

Pond/Impoundment, Landfill 

Selenium, Boron, Cadmium,Hexavalent Chromium, Iron, Manganese, Sulfate, TDS, Aluminum, Fluoride

X X

BC Cobb, Consumers Energy(MI)

Pond/Impoundment Boron, Lithium, Manganese,

Sulfate, Ammonia 

X 

Belews Creek Steam Station, Pond/Impoundment, Selenium, Arsenic, Boron, X X 

Duke Energy (NC) Landfill Cadmium, Iron, Lead, 

Manganese, Nitrate, Sulfate, pH, Bromide 

Big Bend Station, Tampa Electric Company (FL) 

Pond/Impoundment, Landfill 

Arsenic, Aluminum, Boron,Chloride, Fluoride, Iron, Manganese, Molybdenum,Sulfate, Sodium, Thallium, TDS 

X 

Big Cajun 2 Power Plant, NRG Energy/Louisiana Generating,LLC (LA) 

Pond/Impoundment Selenium, TDS, Barium, Arsenic X

A-14 
Appendix A— Literature Review 

Table A-4. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Pow

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

MCL b

Exceeded Federal/ 

State WQC/ 

Standards b

Grou

Impac

W

Brandywine Coal Ash Landfill, Mirant Mid-Atlantic LLC (MD)

Pond/Impoundment, Landfill 

Selenium, Cadmium, Lead, Manganese, Iron, Aluminum, Sulfate, TDS, Chloride

X X 

Bull Run Steam Plant, Tennessee Pond/Impoundment Aluminum, Cadmium, Iron, X 

Valley Authority (TVA) (TN) Sulfate, Arsenic, Cobalt, Calcium,

Manganese, Molybdenum, Boron, Nickel

C.D. McIntosh, Jr. Power Plant, City of Lakeland (FL)

Pond/Impoundment, Landfill 

Selenium, Arsenic, Cadmium,Lead, Manganese, Vanadium, Nitrate, Iron, Sulfate, TDS, pH 

X 

C.R. Huntley Flyash Landfill (NY)

Pond/Impoundment, Landfill 

Arsenic, Iron, Manganese,Sulfate, TDS, Cadmium, Barium, Lead, TSS 

X X

Canadys Plant, South Carolina Electric & Gas (SCE&E) (SC)

Pond/Impoundment Arsenic, Nickel, Selenium X 

Cape Fear Steam Plant, Progress Energy (NC)

Pond/Impoundment Lead, Chromium, Boron, Iron, 

Manganese, Sulfate, Selenium

X X

Cardinal Fly Ash Reservoir (FAR) 1 and 2, American Electric Power (AEP) (OH)

Pond/Impoundment, Landfill 

Arsenic, Boron, Molybdenum X X 

Cayuga Coal Ash Disposal Pond/Impoundment, Selenium, Arsenic, Boron, X X 

Landfill, AES (NY) Landfill Cadmium, Lead, TDS, 

Aluminum, Manganese, Sulfate, Barium, Sodium, Iron,Chromium, Zinc

Cholla Steam Electric Generating Station, Arizona Public Service Company (AZ) 

Pond/Impoundment Sulfate, TDS, Chloride, Fluoride X

A-15 
Appendix A— Literature Review 

Table A-4. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Pow

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

MCL b

Exceeded Federal/ 

State WQC/ 

Standards b

Grou

Impac

W

Clifty Creek Station, Indiana Kentucky Electric Company (IKEC) (IN)

Pond/Impoundment, Landfill 

Boron, Manganese, Iron, Sulfate, Magnesium

X 

Coal Creek Station Surface Impoundments, CooperativePower Association/United Power(ND)

Pond/Impoundment Selenium, Arsenic, Sulfate,

Chloride, Boron, Chromium, Iron, Sodium, TDS

X 

Colbert Fossil Plant, Tennessee Pond/Impoundment, Cadmium, Antimony, Arsenic, X Valley Authority (TVA) (AL) Landfill Lead, Nitrate, Aluminum, Iron, 

Manganese, Boron, Molybdenum, Cobalt, Lithium, Sulfate, Chromium

Coleto Creek Power Station,International Power (TX) 

Pond/Impoundment Arsenic, Lead, Boron, Cobalt,

Nickel, Vanadium

X 

Colstrip Power Plant, PPL Montana (MT)

Pond/Impoundment, Landfill 

Selenium, Boron, Sulfate, TDS,Molybdenum, Arsenic, Chloride 

X 

Cross Generating Station, Santee Cooper/South Carolina PublicService Authority (SCPSA) (SC) 

Pond/Impoundment, Landfill 

Arsenic, Cadmium, Chromium, Sodium, Sulfate, Iron, Aluminum, Chloride, TDS 

X 

Cumberland Steam Plant, Tennessee Valley Authority (TVA) (TN) 

Pond/Impoundment, Landfill 

Selenium, Arsenic, Aluminum, Boron, Chloride, Iron, Manganese, Sulfate, TDS, Vanadium

X X

Curtis Stanton Energy Center,Orlando Utility Commission (FL) 

Pond/Impoundment, Landfill 

Aluminum, Chloride, Iron,Manganese, Sodium, Sulfate,TDS, Vanadium, pH 

X 

Dallman Station Ash and FGD Ponds, City Water, Light andPower (IL)

Pond/Impoundment, Landfill 

Arsenic, Chromium, Sodium, Boron, Manganese, Iron, Sulfate, TDS

X 

A-16 
Appendix A— Literature Review 

Table A-4. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Pow

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

MCL b

Exceeded Federal/ 

State WQC/ 

Standards b

Grou

Impac

W

Dan River Steam Station, DukeEnergy (NC)

Pond/Impoundment, Landfill 

Chromium, Iron, Lead, Manganese, Silver, Sulfate, Arsenic, Antimony, Boron, TDS,pH

X X

Dave Johnston Power Plant (WY)

Pond/Impoundment, Landfill 

Cadmium, Manganese, Sulfate, Boron 

X 

Dolet Hills Power Station, Central Louisiana Electric Co-Op (CLECO) Power, LLC (LA)

Pond/Impoundment, Landfill 

Selenium, Arsenic, Lead,Chloride, TDS, Sulfate, Iron, pH 

X 

Duck Creek Station, CentralIllinois Light Company (IL)

Pond/Impoundment Sulfate, TDS, Chloride, 

Manganese, Iron, Boron

E.J. Stoneman Generating Station, Dairyland Power Cooperative (WI) 

Pond/Impoundment Cadmium, Chromium, Sulfate, 

Manganese, Iron, Zinc, Boron, Barium

X 

Edgewater 1-4 Ash Disposal Site, Alliant (formerly WisconsinPower & Light) (WI) 

Pond/Impoundment, Landfill 

Boron, Sulfate, Iron, Chloride, TDS, Arsenic, Selenium

X 

Fayette Power Project (SamSeymour), Lower Colorado River Authority (TX)

Pond/Impoundment, Landfill 

Selenium, Aluminum, Chloride, Cobalt, Manganese,Molybdenum, Sulfate, TDS, Vanadium

X 

Flint Creek Power Plant, American Electric Power (AEP)/South West Electric Power Company (SWEPCO)(AR)

Pond/Impoundment, Landfill 

Selenium, Barium, Cadmium,Chromium, Iron, Lead, Manganese, pH, Silver, Sulfate, TDS

X X

Fly Ash Landfill, Coffeen/White Pond/Impoundment, Sulfate, TDS, Manganese, X 

& Brewer Trucking (IL) Landfill Cadmium, Chromium, Thallium, 

Beryllium, Boron, Nickel, Barium, Iron, Zinc, Aluminum, Sodium

A-17 
Appendix A— Literature Review 

Table A-4. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Pow

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

MCL b

Exceeded Federal/ 

State WQC/ 

Standards b

Grou

Impac

W

Gallatin Fossil Plant, Tennessee Pond/Impoundment Boron, Beryllium, Cadmium, X 

Valley Authority (TVA) (TN) Iron, Manganese, Nickel, Sulfate, 

TDS, Arsenic, Mercury, Vanadium, Cobalt

General James M. Gavin Power Plant, American Electric Power/Ohio Power Company(OH)

Pond/Impoundment, Landfill 

Arsenic, Barium, Cadmium,Lead, Molybdenum, Sulfate, TDS, Aluminum, Copper, Nickel, Zinc, Manganese, Chloride

X X 

George Neal Station North Landfill, Berkshire Hathaway/MidAmerican EnergyCompany (IA) 

Landfill, Pond/Impoundment

Iron, Manganese, Sulfate, Arsenic X 

Gibson Generating Station, DukeEnergy (IN) 

Pond/Impoundment, Landfill, Cooling Reservoir 

Selenium, Arsenic, Boron,Manganese, Iron, Sodium

X X 

Grainger Generating Station, Santee Cooper/South CarolinaPublic Service Authority (SCPSA) (SC) 

Pond/Impoundment Arsenic, pH X

Havana Power Plant, Illinois Power Company (IL) 

Pond/Impoundment Manganese, Sulfate, Boron

Hennepin Power Station, Illinois Power Company (IL) 

Pond/Impoundment, Landfill 

Sulfate, TDS, Boron, Iron, Manganese

X 

Hunlock Power Station, UGI Development Company (PA)

Pond/Impoundment Arsenic, Iron, Manganese X 

Hutsonville Power Station, Central Illinois Public Service Company (IL)

Pond/Impoundment Sulfate, TDS, Manganese, Boron

A-18 
Appendix A— Literature Review 

Table A-4. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Pow

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

MCL b

Exceeded Federal/ 

State WQC/ 

Standards b

Grou

Impac

W

Independence Steam Station, Entergy/Arkansas Power andLight (AR)

Pond/Impoundment, Landfill 

Cadmium, Iron, Lead, Manganese, pH, Sulfate, TDS, Arsenic, Chlorine 

X 

J.H. Campbell, Consumers Energy (MI)

Pond/Impoundment pH, Antimony, Boron, Cadmium,

Chromium, Iron, Lead, Selenium, Vanadium, Aluminum, Nickel, Thallium, Manganese, Zinc

X X

John Sevier Fossil Plant, Tennessee Valley Authority (TVA) (TN) 

Pond/Impoundment Arsenic, Aluminum, Cadmium,

Manganese, Boron, Strontium,Sulfate, Selenium, HexavalentChromium

X X 

Johnsonville Fossil Plant, Tennessee Valley Authority (TVA) (TN) 

Pond/Impoundment, Landfill 

Arsenic, Aluminum, Boron,Cadmium, Chromium, TDS, Iron, Lead, Manganese, Molybdenum, Sulfate, Cobalt 

X X 

Joppa Steam Plant Ash Ponds,Ameren (Electric Energy) (IL) 

Pond/Impoundment Lead, Chromium, Cobalt, Boron,

Manganese, Sulfate, Iron, TDS 

X 

Karn/Weadock Generating Facility, Consumer Energy (MI) 

Pond/Impoundment, Landfill 

 Arsenic, Boron, Lithium, X 

Kingston Fossil Plant, Tennessee Valley Authority (TVA) (TN)

Pond/Impoundment Arsenic, Selenium, Manganese, 

Cobalt, Aluminum, Ammonia, Thallium, Iron 

X X 

Lansing Smith Plant, Florida Pond/Impoundment Aluminum, Cadmium, Chloride, X 

Power and Light (FL) Chromium, Fluoride, Sulfate,

Manganese, Iron, Radium-226, Radium-228, TDS, Sodium

Lee Steam Plant, Progress Energy (NC)

Pond/Impoundment Arsenic, Lead, Boron,

Manganese, Iron, Chromium, pH

X 

Leland Olds Station, Basin Electric Power Cooperative (ND) 

Pond/Impoundment Arsenic, Boron, Lead, Sulfate X

A-19 
Appendix A— Literature Review 

Table A-4. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Pow

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

MCL b

Exceeded Federal/ 

State WQC/ 

Standards b

Grou

Impac

W

Lincoln Stone Quarry Landfill, Joliet Generating Station 29, Midwest Generation (IL) 

Pond/Impoundment Antimony, Manganese, Sulfate, 

Chloride, TDS 

X 

Lincoln Stone Quarry Landfill, Pond/Impoundment, Arsenic, Ammonia, Boron, X 

Joliet Generating Station 9, Landfill Molybdenum, pH, Sulfate, TDS,Midwest Generation (IL) Barium, Copper, Selenium, 

Cadmium 

Little Blue Run Surface Pond/Impoundment Selenium, Arsenic, Aluminum, X X 

Impoundment, Bruce Mansfield Antimony, Barium, Boron, Power Plant, First Energy (PA) Cadmium, Calcium, Chloride, 

Hexavalent Chromium, Fluoride, Iron, Lead, Manganese, pH, Sodium, Sulfate, TDS, TSS,Thallium, Turbidity

Mahoney Landfill, PowertonPlant, Commonwealth Edison(IL)

Pond/Impoundment, Landfill 

Arsenic, Selenium, Chromium, TDS, Cadmium, Lead, Nitrate, Iron, Manganese, Sulfate, Boron,

X 

Marion Plant, Southern Illinois Power Cooperative (IL)

Pond/Impoundment, Landfill 

Boron, Cadmium, Iron,Aluminum, TDS, Sulfate

X X 

McMeekin Station,SCANA/South Carolina Electric & Gas Company (SCE&G) (SC)

Pond/Impoundment, Landfill 

Chromium, Lead, Sulfate, Iron, TDS

X 

Mendosa Power Station AshPonds, Ameren Energy Generating Company, (IL)

Pond/Impoundment Arsenic, Boron, Manganese, 

Chromium (?), Sulfate, TDS 

X X

Michigan City Site (IN) Pond/Impoundment Arsenic, Lead X

Mill Creek Plant, E ON U.S./Louisville Gas & Electric (LG&E) (KY)

Pond/Impoundment, Landfill 

Arsenic, Chloride, Sulfate, TDS X 

A-20 
Appendix A— Literature Review 

Table A-4. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Pow

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

MCL b

Exceeded Federal/ 

State WQC/ 

Standards b

Grou

Impac

W

Mitchell Power Station,Allegheny Energy (PA)

Pond/Impoundment, Landfill 

Arsenic, Boron, Iron, Molybdenum, Manganese, Nickel 

X 

Montville Generating Station, NRG Energy/Montville Power, LLC (CT)

Pond/Impoundment Arsenic, Beryllium, Cadmium, 

Copper, Iron, Lead, Manganese, Nickel, pH, Zinc

X X 

Morgantown Generating Station, Faulkner Off-site Disposal Facility (MD) 

Pond/Impoundment, Landfill 

Iron, pH, Cadmium, Aluminum, Chloride, Manganese, Sulfate,TDS, Copper, Lead, Selenium 

X X 

Muskingum River Plant, American Electric Power (AEP)/ Ohio Power Company (OH)

Pond/Impoundment Barium, Iron, Sulfate X 

Nelson Dewey Ash Disposal Facility, Alliant (formerly Wisconsin Power & Light) (WI) 

Pond/Impoundment Selenium, Arsenic, Sulfate,

Boron, Fluoride, Cadmium (?),Iron

Northeastern Station AshLandfill, American Electric Power/Public Service Company Oklahoma (OK)

Landfill, Pond/Impoundment

Selenium, Arsenic, Barium, Chromium, Lead, Vanadium, Thallium, Sulfate, pH 

X 

Oak Ridge Y-12 Plant, ChestnutRidge Operable Unit 2, Oak Ridge Reservation, Departmentof Energy (TN)

Pond/Impoundment Selenium, Arsenic, Aluminum, 

Iron, Zinc, Manganese, Thallium(?)

X 

Paradise Fossil Plant, Tennessee Valley Authority (TVA) (KY) 

Pond/Impoundment Arsenic, Boron, Chromium, 

Copper, Manganese

X 

Parish Generating Station, NRG Energy/Texas Genco II (TX) 

Pond/Impoundment, Landfill 

Arsenic, Selenium, Barium, Boron, Chromium, Cobalt,Manganese, Molybdenum, Sulfate 

X 

Pearl Station, Prairie Power Inc./Soyland Power Coop (IL)

Pond/Impoundment Arsenic, Chromium, Boron,

Manganese, Sulfate, Chlorine,Iron, TDS, Lead, Boron 

X 

A-21 
Appendix A— Literature Review 

Table A-4. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Pow

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

MCL b

Exceeded Federal/ 

State WQC/ 

Standards b

Grou

Impac

W

Phillips Power Plant Landfill, Duquesne Light Company (PA)

Pond/Impoundment, Landfill 

TDS, Chloride, Fluoride, Manganese, Aluminum, Arsenic 

X X 

Prairie Creek Generating Station Ash Landfill, Interstate Power and Light (Alliant) (IA) 

Pond/Impoundment, Landfill 

Arsenic, Boron, Manganese, Sulfate, Iron 

X X

R.M. Schahfer Generating Station (IN)

Landfill, Pond/Impoundment

Sulfate, Iron, Manganese,Molybdenum, Chlorine, Sodium, Boron 

Reid Gardner Generating Pond/Impoundment, Selenium, Arsenic, Chloride, X X 

Facility, Nevada Energy (NV) Landfill Sulfate, TDS, Nitrate, Boron, 

Chromium, Manganese, Magnesium, Molybdenum,Sodium, Vanadium, Titanium, Barium, Iron, Aluminum

Rock River Ash DisposalFacility, Alliant (formerly Wisconsin Power & Light) (WI) 

Pond/Impoundment Mercury, Arsenic, Sulfate, Iron,

Selenium, Boron, TDS

X 

Rodemacher Power Station, Central Louisiana Electric Co-Op (CLECO) Power, LLC (LA)

Pond/Impoundment, Landfill 

Arsenic, Lead, pH, TDS, Chloride, Sulfate 

X 

Seminole Generating Station, Seminole Electric Cooperative (FL)

Pond/Impoundment, Landfill 

Arsenic, Chloride, Chlorine,Sulfate, Iron, TDS, Boron, Aluminum, Lead, Sodium

X X 

Seward Generating Station, RRIEnergy (PA) 

Pond/Impoundment, Landfill 

Selenium, Arsenic, Aluminum, Antimony, Cadmium, Chloride, Chromium, Iron, Lead, Manganese, Nickel, pH, Sulfate, TDS, Zinc, 

X X 

A-22 
Appendix A— Literature Review 

Table A-4. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Pow

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

MCL b

Exceeded Federal/ 

State WQC/ 

Standards b

Grou

Impac

W

Shawnee Fossil Plant, Tennessee Pond/Impoundment, Selenium, Arsenic, Boron, pH, X Valley Authority (TVA) (KY) Landfill Sulfate, TDS, Beryllium, Cobalt, 

Nickel, Molybdenum, Manganese, Vanadium

Sherburne County (Sherco)Generating Plant, Xcel Energy/Southern Minnesota Municipal Power Agency (MN)

Pond/Impoundment, Landfill 

Arsenic, Cadmium, Lead, Sulfate, Selenium, Boron

X 

Spurlock Station, Eastern Kentucky Power Cooperative(KY)

Pond/Impoundment, Landfill 

Arsenic, Sulfate, TDS X 

Sutton Steam Plant, ProgressEnergy (NC)

Pond/Impoundment Arsenic, Boron, Manganese, Iron,

Thallium, Selenium, Antimony, Lead, Sulfate, TDS 

X X 

Urquhart Station, South Carolina Electric & Gas Company (SGE&E) (SC)

Pond/Impoundment, Landfill 

Arsenic, Nickel X

Venice Power Station Ash Ponds, Union Electric Company/Ameren Energy/AmerenUE (IL)

Pond/Impoundment Arsenic, Boron, Cadmium, Iron, 

Manganese, TDS

X X 

Vermillion Power Station, Illinois Power (IL)

Pond/Impoundment Sulfate, TDS, Boron, Iron, 

Manganese, Chloride

W.C. Beckjord Station, Duke Energy (formerly Cinergy) (OH)

Pond/Impoundment Selenium, Sulfate X

W.J. Neal Station Surface Impoundment, Basin Electric Power Cooperative (ND) 

Pond/Impoundment Selenium, Arsenic, Chromium, 

Cadmium, Lead, Zinc, Aluminum 

X 

Wateree Station, SCE&G (SC) Pond/Impoundment, 

Landfill 

Arsenic, Chromium, Cadmium,Lead, Iron 

X X 

A-23 
Appendix A— Literature Review 

Table A-4. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Pow

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

MCL b

Exceeded Federal/ 

State WQC/ 

Standards b

Grou

Impac

W

Waukegan Generating Station Ash Ponds, Midwest Generation (Edison International) (IL)

Pond/Impoundment, Landfill 

Arsenic, Antimony, Boron,Manganese, Sulfate, TDS, Iron

X X

Weber Ash Disposal Site, AES Creative Resources (NY) 

Pond/Impoundment, Landfill 

Sulfate, TDS, Manganese, Iron,Aluminum, pH

X 

Westland Disposal Site, Dickerson Generating Station, Mirant (MD)

Pond/Impoundment, Landfill 

Selenium, Arsenic, Barium, Chromium, Cobalt, Copper, Iron,Zinc, Sulfate, Chlorine, Hardness,TDS, Aluminum 

X X 

Widows Creek Fossil Plant, Tennessee Valley Authority (TVA) (AL) 

Pond/Impoundment Lead, Cobalt, Boron, Iron, 

Manganese, Aluminum, Sulfate 

X 

Winyah Generating Station,Santee Cooper/South CarolinaPublic Service Authority (SCPSA) (SC) 

Pond/Impoundment Arsenic, Chromium, Sulfate, Iron, 

Chloride

X X

Wood River Power Station,Illinois Power Company (IL)

Pond/Impoundment Sulfate, TDS, Chloride, 

Manganese, Iron, Boron

Yorktown Power Station,Chisman Creek Disposal Site, Virginia Electric Power and Power Company (VEPCO) (VA) 

Pond/Impoundment, Landfill 

Sulfate, Nickel, Vanadium, Selenium

X 

Sources: ERG, 2015m; U.S. EPA, 2012e (DCN SE01966); U.S. EPA, 2013b; U.S. EPA, 2014a through 2014e. 

Acronyms: FGD (Flue Gas Desulfurization); MCL (Maximum Contaminant Level); TDS (Total Dissolved Solids); WQC (Water Qualia – The term “ash” was used when the impact case study source did not identify the type of ash present at the waste management unit. b – An “X” indicates that one or more of the pollutants listed exceeded MCLs or federal/state WQC/standards. c – An “X” indicates that the ground water contaminated the surface water with one or more of the pollutants listed.d – An “X” indicates that the ground water contaminated a source outside the plant property boundaries. 

A-24 
Appendix A— Literature Review 

Table A-5. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Powe

Damage Case Site

Type of

Waste in 

Landfill a Pollutants of Concern 

Exceeded 

MCL b

Exceeded 

Federal/ State

WQC/ 

Standards b

Gr

Sur

A.B. Brown Generating Station,Southern Indiana Gas and ElectricCompany (SIGECO) (IN)

FGD Arsenic, Sodium, Boron, Sulfate, TDS, 

Chloride, pH 

X 

Alma On-site Fly Ash Landfill, Dairyland Power (WI)

Fly Ash Sulfate, Manganese 

Bailly Generating Station, NorthernIndiana Public Service Company (NIPSCO) (IN)

Ash Arsenic, Cadmium X

Bangor Quarry Ash Disposal Site, Portland Generating Station, RRIEnergy (PA) 

Bottom Ash,Fly Ash, Other

Selenium, Boron, Cadmium, HexavalentChromium, Iron, Manganese, Sulfate, TDS, Aluminum, Fluoride

X X

Battlefield Golf Club, Chesapeake Energy Facility, Dominion Power (VA)

Fly Ash Arsenic, Cadmium, Chromium, Copper,

Lead, Manganese, Thallium, Zinc, Vanadium, Iron, Boron, Aluminum

X 

BBSS Sand and Gravel Quarries, Constellation Energy (MD) 

Fly Ash, Bottom Ash 

Arsenic, Selenium, Aluminum, Cadmium,Thallium, Manganese, Sulfate, Beryllium,Lead, Nickel 

X 

Belews Creek Steam Station, Duke Energy (NC)

Fly Ash, FGD 

Selenium, Arsenic, Boron, Cadmium,Iron, Lead, Manganese, Nitrate, Sulfate, pH, Bromide 

X X 

Big Bend Station, Tampa Electric Company (FL) 

Bottom Ash,Fly Ash, FGD, Other

Arsenic, Aluminum, Boron, Chloride, Fluoride, Iron, Manganese, Molybdenum,Sulfate, Sodium, Thallium, TDS 

X 

Brandywine Coal Ash Landfill, Mirant Mid-Atlantic LLC (MD)

Bottom Ash,Fly Ash 

Selenium, Cadmium, Lead, Manganese,Iron, Aluminum, Sulfate, TDS, Chloride

X X 

C.D. McIntosh, Jr. Power Plant, City of Lakeland (FL)

Ash, FGD Selenium, Arsenic, Cadmium, Lead, 

Manganese, Vanadium, Nitrate, Iron, Sulfate, TDS, pH 

X 

A-25 
Appendix A— Literature Review 

Table A-5. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Powe

Damage Case Site

Type of

Waste in 

Landfill a Pollutants of Concern 

Exceeded 

MCL b

Exceeded 

Federal/ State

WQC/ 

Standards b

Gr

Sur

C.R. Huntley Flyash Landfill (NY) Bottom Ash,

Fly Ash, Other 

Arsenic, Iron, Manganese, Sulfate, TDS, Cadmium, Barium, Lead, TSS 

X X

Cardinal Fly Ash Reservoir (FAR) 1 and 2, American Electric Power (AEP) (OH)

Bottom Ash,Fly Ash, FGD 

Arsenic, Boron, Molybdenum X X 

Cayuga Coal Ash Disposal Landfill, AES (NY)

Bottom Ash,Fly Ash, Other

Selenium, Arsenic, Boron, Cadmium,Lead, TDS, Aluminum, Manganese, Sulfate, Barium, Sodium, Iron, Chromium, Zinc

X X 

CCW Landfill, Trans-Ash, Inc. (TN) Bottom Ash,

Fly Ash 

Mercury, Iron, Boron, Sulfate, Arsenic, Chromium, Lead 

X 

Cedar-Sauk Landfill, WisconsinElectric Power Company (WEPCO) (WI)

Fly Ash, Bottom Ash 

Selenium, Sulfate, Boron X

Clifty Creek Station, Indiana Kentucky Electric Company (IKEC)(IN)

Fly Ash, Other

Boron, Manganese, Iron, Sulfate, Magnesium

X 

Coal Ash Pit #3, Sheldon Station,Nebraska Public Power District (NE)

Fly Ash Selenium, Sulfate X 

Coal Combustion Waste Landfill, Merom Generating Station, Hoosier Energy (IN) 

Fly Ash, Bottom Ash 

Barium, Chromium, Cadmium, Lead, Sulfate, Chloride, Sodium

X 

Colbert Fossil Plant, Tennessee Bottom Ash, Cadmium, Antimony, Arsenic, Lead, X Valley Authority (TVA) (AL) Fly Ash, 

Other

Nitrate, Aluminum, Iron, Manganese, Boron, Molybdenum, Cobalt, Lithium,Sulfate, Chromium 

Colstrip Power Plant, PPL Montana (MT)

Bottom Ash,Fly Ash, FGD 

Selenium, Boron, Sulfate, TDS,Molybdenum, Arsenic, Chloride 

X 

A-26 
Appendix A— Literature Review 

Table A-5. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Powe

Damage Case Site

Type of

Waste in 

Landfill a Pollutants of Concern 

Exceeded 

MCL b

Exceeded 

Federal/ State

WQC/ 

Standards b

Gr

Sur

Conesville Fixed FGD Sludge Landfill, American Electric Power (AEP) (OH)

Fly Ash, FGD 

Arsenic, Cadmium, Chromium, Calcium,Magnesium, TDS, Sulfate, Iron, Selenium

X 

Crist Plant Ash Landfill, Gulf Power (Southern Company) (FL) 

Fly ash,Bottom Ash,FGD 

Arsenic, Cadmium, Manganese, Chromium, Sodium, Sulfate, Aluminum, Chlorine, Iron, pH, TDS

X 

Cross Generating Station, Santee Cooper/South Carolina PublicService Authority (SCPSA) (SC) 

Bottom Ash,FGD 

Arsenic, Cadmium, Chromium, Sodium, Sulfate, Iron, Aluminum, Chloride, TDS

X 

Cumberland Steam Plant, Tennessee Valley Authority (TVA) (TN)

Bottom Ash,Fly Ash, FGD 

Selenium, Arsenic, Aluminum, Boron,Chloride, Iron, Manganese, Sulfate, TDS, Vanadium

X X

Curtis Stanton Energy Center,Orlando Utility Commission (FL) 

Bottom Ash,Other

Aluminum, Chloride, Iron, Manganese, Sodium, Sulfate, TDS, Vanadium, pH

 X 

Dallman Station Ash and FGD Ponds, City Water, Light and Power (IL)

Ash, FGD Arsenic, Chromium, Sodium, Boron,

Manganese, Iron, Sulfate, TDS

X 

Dan River Steam Station, DukeEnergy (NC)

Bottom Ash,Fly Ash, Other

Chromium, Iron, Lead, Manganese,Silver, Sulfate, Arsenic, Antimony, Boron, TDS, pH 

X X

Danskammer Waste ManagementFacility, Central Hudson Gas and Electric Corporation (NY) 

Ash Sulfate, Sulfide, TDS, Turbidity, Iron,

Magnesium, Manganese, Sodium, Boron,pH

Dave Johnston Power Plant (WY) Fly Ash Cadmium, Manganese, Sulfate, Boron X Dolet Hills Power Station, Central Louisiana Electric Co-Op (CLECO) Power, LLC (LA)

Bottom Ash,Fly Ash, FGD, Other

Selenium, Arsenic, Lead, Chloride, TDS,Sulfate, Iron, pH 

X 

East Bend Scrubber Sludge Landfill, Cinergy (KY) 

FGD TDS, Iron, Sulfate, Manganese, Chloride

A-27 
Appendix A— Literature Review 

Table A-5. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Powe

Damage Case Site

Type of

Waste in 

Landfill a Pollutants of Concern 

Exceeded 

MCL b

Exceeded 

Federal/ State

WQC/ 

Standards b

Gr

Sur

Edgewater 1-4 Ash Disposal Site, Alliant (formerly Wisconsin Power & Light) (WI) 

Ash Boron, Sulfate, Iron, Chloride, TDS, 

Arsenic, Selenium

X 

Fair Station Ash Landfill, Central Iowa Power Cooperative (IA) 

Ash Selenium, Manganese, Sulfate, Iron X 

Fayette Power Project (SamSeymour), Lower Colorado River Authority (TX)

Bottom Ash,Fly Ash, FGD, Other

Selenium, Aluminum, Chloride, Cobalt,Manganese, Molybdenum, Sulfate, TDS, Vanadium

X 

Fern Valley Landfill, Orion Power Holdings, Inc. (a subsidiary of RRIEnergy) (PA) 

Fly Ash Selenium, Aluminum, Boron, Chloride,

Sulfate, TDS 

X X 

Flint Creek Power Plant, American Electric Power (AEP)/South West Electric Power Company (SWEPCO) (AR)

Bottom Ash,Fly Ash, Other

Selenium, Barium, Cadmium, Chromium, Iron, Lead, Manganese, pH, Silver, Sulfate, TDS 

X X

Fly Ash Landfill, Coffeen/White & Brewer Trucking (IL)

Fly Ash, FGD, BottomAsh

Sulfate, TDS, Manganese, Cadmium,Chromium, Thallium, Beryllium, Boron,Nickel, Barium, Iron, Zinc, Aluminum, Sodium

X 

Fly Ash Landfill, Don Frame Trucking, Inc. (NY)

Bottom Ash,Fly Ash, Other

Lead, Sulfate, TDS, Manganese, Iron X 

General James M. Gavin Power Plant, American Electric Power/Ohio Power Company (OH) 

Bottom Ash,Fly Ash, FGD, Other

Arsenic, Barium, Cadmium, Lead, Molybdenum, Sulfate, TDS, Aluminum, Copper, Nickel, Zinc, Manganese, Chloride

X X 

George Neal Station North Landfill, Berkshire Hathaway/MidAmericanEnergy Company (IA) 

Fly Ash Iron, Manganese, Sulfate, Arsenic X 

A-28 
Appendix A— Literature Review 

Table A-5. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Powe

Damage Case Site

Type of

Waste in 

Landfill a Pollutants of Concern 

Exceeded 

MCL b

Exceeded 

Federal/ State

WQC/ 

Standards b

Gr

Sur

George Neal Station South Ash Monofill, Berkshire Hathaway/MidAmerican EnergyCompany (IA) 

Bottom Ash,Fly Ash 

Selenium, Arsenic, Barium, Zinc, Iron, Manganese, Sulfate 

X 

Gibson Generating Station, DukeEnergy (IN) 

Bottom Ash,Fly Ash 

Selenium, Arsenic, Boron, Manganese, Iron, Sodium

X X 

Hatfield's Ferry Power Station,Allegheny Energy (PA)

Bottom Ash,Fly Ash, FGD 

Arsenic, Aluminum, Boron, Chromium, Manganese, Molybdenum, Thallium,TDS, Sulfate, Selenium 

X X 

Hennepin Power Station, Illinois Power Company (IL) 

Fly Ash Sulfate, TDS, Boron, Iron, Manganese X

Highway 59 Landfill, Wisconsin Electric Power Company (WEPCO) (WI)

Bottom Ash,Fly Ash 

Selenium, Sulfate, Boron, Manganese, Chloride, Iron, Arsenic, Molybdenum,TDS

 X 

Independence Steam Station, Entergy/Arkansas Power and Light(AR)

Bottom Ash,Fly Ash, Other

Cadmium, Iron, Lead, Manganese, pH,Sulfate, TDS, Arsenic, Chlorine 

X 

Indian River Generating Station,NRG Energy (DE)

Ash Selenium, Mercury, Arsenic, Aluminum, 

Barium, Cadmium, Chromium, Copper,Lead, Nickel, Thallium, Zinc, Iron, Manganese

X X 

John Warden Ash Site (MI) Ash, Other Boron, Lithium Johnsonville Fossil Plant, Tennessee Valley Authority (TVA) (TN)

Bottom Ash,Fly Ash 

Arsenic, Aluminum, Boron, Cadmium,Chromium, TDS, Iron, Lead, Manganese, Molybdenum, Sulfate, Cobalt 

X X 

K.R. Rezendes South Main Street Ash Landfill, Salem Harbor and Brayton Point Plants, Pacific Gas and Electric (PG&E) (MA)

Ash Selenium, Arsenic (?) X

A-29 
Appendix A— Literature Review 

Table A-5. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Powe

Damage Case Site

Type of

Waste in 

Landfill a Pollutants of Concern 

Exceeded 

MCL b

Exceeded 

Federal/ State

WQC/ 

Standards b

Gr

Sur

Karn/Weadock Generating Facility, Consumer Energy (MI)

Ash, Fly Ash, BottomAsh

 Arsenic, Boron, Lithium, X 

Lincoln Stone Quarry Landfill, JolietGenerating Station 9, MidwestGeneration (IL)

Ash Arsenic, Ammonia, Boron, Molybdenum,

pH, Sulfate, TDS, Barium, Copper, Selenium, Cadmium

X 

Mahoney Landfill, Powerton Plant, Commonwealth Edison (IL) 

Bottom Ash,Fly Ash, Other

Arsenic, Selenium, Chromium, TDS, Cadmium, Lead, Nitrate, Iron, Manganese, Sulfate, Boron,

X 

Marion Plant, Southern Illinois Power Cooperative (IL)

Bottom Ash,Fly Ash, FGD 

Boron, Cadmium, Iron, Aluminum, TDS, Sulfate

X X 

McMeekin Station, SCANA/South Carolina Electric & Gas Company (SCE&G) (SC) 

Ash Chromium, Lead, Sulfate, Iron, TDS X 

Miamiview Landfill, Cincinnati Gas & Electric Company (OH) 

FGD Sulfate, Manganese

Mill Creek Plant, E ON U.S./Louisville Gas & Electric (LG&E) (KY)

Bottom Ash,Fly Ash, FGD, Other

Arsenic, Chloride, Sulfate, TDS X 

Mitchell Power Station, Allegheny Energy (PA) 

Bottom Ash,Fly Ash 

Arsenic, Boron, Iron, Molybdenum, Manganese, Nickel

X 

Morgantown Generating Station, Faulkner Off-site Disposal Facility (MD)

Bottom Ash,Fly Ash, Other

Iron, pH, Cadmium, Aluminum, Chloride, Manganese, Sulfate, TDS, Copper, Lead, Selenium

X X 

Muscatine County Landfill (IA) Ash Selenium, Sulfate X 

Muskegon County Type III Landfill (MI)

Fly Ash Boron, Manganese X 

North Lansing Landfill, Lansing Board of Water & Light (MI)

Ash, Other Selenium, Boron, Lithium, Manganese, 

Sulfate, Lead

X 

A-30 
Appendix A— Literature Review 

Table A-5. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Powe

Damage Case Site

Type of

Waste in 

Landfill a Pollutants of Concern 

Exceeded 

MCL b

Exceeded 

Federal/ State

WQC/ 

Standards b

Gr

Sur

Northeastern Station Ash Landfill, American Electric Power/Public Service Company Oklahoma (OK) 

Bottom Ash,Fly Ash 

Selenium, Arsenic, Barium, Chromium, Lead, Vanadium, Thallium, Sulfate, pH 

X 

Parish Generating Station, NRG Energy/Texas Genco II (TX) 

Fly Ash, Bottom Ash,FGD (EmergencyOnly)

Arsenic, Selenium, Barium, Boron, Chromium, Cobalt, Manganese, Molybdenum, Sulfate 

X 

Petersburg Generating Station,Indianapolis Power & Light (IN) 

Not Specified Sulfate, TDS X 

Phillips Power Plant Landfill, Duquesne Light Company (PA)

Ash, FGD TDS, Chloride, Fluoride, Manganese, 

Aluminum, Arsenic

X X 

Pine Hill Landfill, Marquette Boardof Light & Power (MI) 

Fly Ash Boron, Lithium, Sodium X 

Port Washington Facility, WisconsinElectric Power Company (WEPCO) (WI)

Bottom Ash,Fly Ash 

Selenium, Boron, Sulfate 

Prairie Creek Generating Station Ash Landfill, Interstate Power and Light (Alliant) (IA) 

Ash Arsenic, Boron, Manganese, Sulfate, Iron X X 

Presque Isle Power Plant, WEEnergies (WE) (MI) 

Bottom Ash,Fly Ash 

Boron, Molybdenum, Selenium, Sodium, Sulfate, Lithium 

X 

Pulliam Ash Disposal Site, Wisconsin Power Supply Company (WPSC) (WI) 

Bottom Ash,Fly Ash 

Sulfate, Manganese, Iron, Boron, Zinc,Aluminum, Chlorine, TDS, pH

R.M. Heskett Station, MontanaDakota Utilities (ND) Ash Sulfate, Boron, Cadmium, Selenium, Nitrate X 

R.M. Schahfer Generating Station (IN)

 Ash, FGD Sulfate, Iron, Manganese, Molybdenum,

Chlorine, Sodium, Boron

A-31 
Appendix A— Literature Review 

Table A-5. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Powe

Damage Case Site

Type of

Waste in 

Landfill a Pollutants of Concern 

Exceeded 

MCL b

Exceeded 

Federal/ State

WQC/ 

Standards b

Gr

Sur

Range Road Landfill, Detroit Edison(MI)

Ash Boron, Lithium, Manganese X 

Reid Gardner Generating Facility, Nevada Energy (NV)

Fly Ash, FGD 

Selenium, Arsenic, Chloride, Sulfate, TDS, Nitrate, Boron, Chromium, Manganese, Magnesium, Molybdenum, Sodium, Vanadium, Titanium, Barium, Iron, Aluminum 

X X 

Rodemacher Power Station, CentralLouisiana Electric Co-Op (CLECO) Power, LLC (LA)

Bottom Ash,Fly Ash, Other

Arsenic, Lead, pH, TDS, Chloride, Sulfate X 

Seminole Generating Station, Seminole Electric Cooperative (FL)

Fly Ash, FGD, Other

Arsenic, Chloride, Chlorine, Sulfate, Iron,TDS, Boron, Aluminum, Lead, Sodium

X X 

Seward Generating Station, RRIEnergy (PA) 

Ash, Other Selenium, Arsenic, Aluminum, Antimony, 

Cadmium, Chloride, Chromium, Iron,Lead, Manganese, Nickel, pH, Sulfate, TDS, Zinc, 

X X 

Shawnee Fossil Plant, Tennessee Valley Authority (TVA) (KY) 

Bottom Ash,Fly Ash 

Selenium, Arsenic, Boron, pH, Sulfate, TDS, Beryllium, Cobalt, Nickel, Molybdenum, Manganese, Vanadium

X 

Sherburne County (Sherco) Bottom Ash, Arsenic, Cadmium, Lead, Sulfate, X 

Generating Plant, Xcel Fly Ash, Selenium, BoronEnergy/Southern Minnesota FGD Municipal Power Agency (MN)Spurlock Station, Eastern KentuckyPower Cooperative (KY) 

Bottom Ash,Fly Ash, FGD 

Arsenic, Sulfate, TDS X 

Swift Creek Structural Fill, ReUse Technology, Inc./ Full Circle Solutions (NC) 

Fly Ash Arsenic, Lead, Sulfate X X 

A-32 
Appendix A— Literature Review 

Table A-5. Summary of Ground Water Impacts Reported in Damage Cases from Steam Electric Powe

Damage Case Site

Type of

Waste in 

Landfill a Pollutants of Concern 

Exceeded 

MCL b

Exceeded 

Federal/ State

WQC/ 

Standards b

Gr

Sur

Urquhart Station, South Carolina Electric & Gas Company (SGE&E) (SC)

Fly Ash, Bottom Ash,Other

Arsenic, Nickel X

Wateree Station, SCE&G (SC) Bottom Ash,

Fly Ash, FGD 

Arsenic, Chromium, Cadmium, Lead, Iron X X 

Waukegan Generating Station AshPonds, Midwest Generation (Edison International) (IL) 

Ash Arsenic, Antimony, Boron, Manganese,

Sulfate, TDS, Iron 

X X

Weber Ash Disposal Site, AES Creative Resources (NY) 

Ash Sulfate, TDS, Manganese, Iron,

Aluminum, pH

X 

Westland Disposal Site, DickersonGenerating Station, Mirant (MD)

Fly Ash Selenium, Arsenic, Barium, Chromium, 

Cobalt, Copper, Iron, Zinc, Sulfate, Chlorine, Hardness, TDS, Aluminum

X X 

Yard 520 Landfill Site (Brown's Landfill),Northern Indiana Public Service Company (NIPSCO) (IN) 

Fly Ash, Other

Arsenic, Manganese, Boron,Molybdenum, Lead, Selenium, Iron, Sulfate, Ammonium

X 

Yorktown Power Station, ChismanCreek Disposal Site, Virginia Electric Power and Power Company (VEPCO) (VA)

Fly Ash Sulfate, Nickel, Vanadium, Selenium X

Sources: ERG, 2015m; U.S. EPA, 2012e (DCN SE01966); U.S. EPA, 2013b; U.S. EPA, 2014a through 2014e. Acronyms: FGD (Flue Gas Desulfurization); MCL (Maximum Contaminant Level); TDS (Total Dissolved Solids); WQC (Water Qualia – The term “ash” was used when the impact case study source did not identify the type of ash present at the waste management unit. b – An “X” indicates that one or more of the pollutants listed exceeded MCLs or federal/state WQC/standards. c – An “X” indicates that the ground water contaminated the surface water with one or more of the pollutants listed.d – An “X” indicates that the ground water contaminated a source outside the plant property boundaries. 

A-33 
Appendix A— Literature Review 

Table A-6. Summary of Surface Water Impacts Reported in Damage Cases from Steam Electric Powe

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

Federal/State 

WQC/Standards b 

Issued a Fish 

Consumption 

Advisory c

Impac

from Gr

Conta

Asheville Steam Electric Plant, Progress Energy(NC)

Pond/Impoundment Boron, Chromium, Iron,

Manganese, Thallium, Nitrate, Sulfate, pH, TDS, Cadmium,Arsenic, Antimony

X 

Bangor Quarry Ash Disposal Site, PortlandGenerating Station, RRI Energy (PA) 

Pond/Impoundment, Landfill 

Selenium, Boron, Cadmium,Hexavalent Chromium, Iron, Manganese, Sulfate, TDS, Aluminum, Fluoride

X 

Belews Creek SteamStation, Duke Energy(NC)

Pond/Impoundment, Landfill 

Selenium, Arsenic, Boron,Cadmium, Iron, Lead, Manganese,Nitrate, Sulfate, pH, Bromide

X 

Big Bend Station, Tampa Pond/Impoundment, Arsenic, Aluminum, Boron, 

Electric Company (FL) Landfill Chloride, Fluoride, Iron, 

Manganese, Molybdenum, Sulfate, Sodium, Thallium, TDS 

Brandywine Coal AshLandfill, Mirant MidAtlantic LLC (MD) 

Pond/Impoundment, Landfill 

Selenium, Cadmium, Lead, Manganese, Iron, Aluminum, Sulfate, TDS, Chloride

X 

Bull Run Steam Plant, Pond/Impoundment Aluminum, Cadmium, Iron, Sulfate, 

Tennessee Valley Arsenic, Cobalt, Calcium,Authority (TVA) (TN) Manganese, Molybdenum, Boron, 

Nickel

Cardinal Fly AshReservoir (FAR) 1 and 2,American Electric Power (AEP) (OH)

Pond/Impoundment, Landfill 

Arsenic, Boron, Molybdenum X 

Cayuga Coal AshDisposal Landfill, AES (NY)

Pond/Impoundment, Landfill 

Selenium, Arsenic, Boron,Cadmium, Lead, TDS, Aluminum, Manganese, Sulfate, Barium, Sodium, Iron, Chromium, Zinc

X 

A-34 
Appendix A— Literature Review 

Table A-6. Summary of Surface Water Impacts Reported in Damage Cases from Steam Electric Powe

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

Federal/State 

WQC/Standards b 

Issued a Fish 

Consumption 

Advisory c

Impac

from Gr

Conta

Clinch River Plant, American Electric Power (AEP)/Appalachian Power (VA) 

Pond/Impoundment Aluminum, pH, Copper X 

Columbia Energy Center, Alliant Energy (WI) 

Pond/Impoundment, Landfill 

Cadmium, Copper, Barium, Aluminum, Iron, Zinc, Arsenic, Selenium, Lead, Manganese

X 

Cumberland Steam Plant, Tennessee Valley Authority (TVA) (TN)

Pond/Impoundment, Landfill 

Selenium, Arsenic, Aluminum, Boron, Chloride, Iron, Manganese, Sulfate, TDS, Vanadium

X 

Curtis Stanton EnergyCenter, Orlando Utility Commission (FL)

Pond/Impoundment, Landfill 

Aluminum, Chloride, Iron,Manganese, Sodium, Sulfate, TDS,Vanadium, pH

X 

Dan River Steam Station, Duke Energy (NC)

Pond/Impoundment Arsenic, Copper, Iron, Aluminum X X

Dave Johnston Power Plant (WY) 

Pond/Impoundment, Landfill 

Cadmium, Manganese, Sulfate, Boron 

Flint Creek Power Plant, American Electric Power (AEP)/South West Electric Power Company (SWEPCO) (AR) 

Pond/Impoundment, Landfill 

Selenium, Barium, Cadmium,Chromium, Iron, Lead, Manganese,pH, Silver, Sulfate, TDS 

X 

General James M. Gavin Pond/Impoundment, Arsenic, Barium, Cadmium, Lead, X 

Power Plant, American Landfill Molybdenum, Sulfate, TDS, 

Electric Power/Ohio Aluminum, Copper, Nickel, Zinc, Power Company (OH) Manganese, ChlorideGibson Generating Station, Duke Energy(IN)

Pond/Impoundment, Landfill, Cooling Reservoir 

Selenium, Arsenic, Boron,Manganese, Iron, Sodium

X 

A-35 
Appendix A— Literature Review 

Table A-6. Summary of Surface Water Impacts Reported in Damage Cases from Steam Electric Powe

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

Federal/State 

WQC/Standards b 

Issued a Fish 

Consumption 

Advisory c

Impac

from Gr

Conta

Glen Lyn Plant,American Electric Power (AEP)/Appalachian Power (VA) 

Pond/Impoundment Selenium, Cadmium, Copper,

Chromium, Zinc, pH, Nickel

X 

Grainger GeneratingStation, SanteeCooper/South Carolina Public Service Authority (SCPSA) (SC) 

Pond/Impoundment Arsenic, pH

J.H. Campbell, Pond/Impoundment pH, Antimony, Boron, Cadmium, X 

Consumers Energy (MI) Chromium, Iron, Lead, Selenium, 

Vanadium, Aluminum, Nickel, Thallium, Manganese, Zinc

J.R. Whiting GeneratingPlant, CMS/Consumers Energy (MI)

Pond/Impoundment Selenium, Arsenic, Cobalt, Nickel, 

Bromine, Chromium

John Sevier Fossil Plant, Pond/Impoundment Arsenic, Aluminum, Cadmium, X 

Tennessee Valley Manganese, Boron, Strontium,Authority (TVA) (TN) Sulfate, Selenium, Hexavalent

Chromium

Johnsonville Fossil Plant, Pond/Impoundment, Arsenic, Aluminum, Boron, X 

Tennessee Valley Landfill Cadmium, Chromium, TDS, Iron, 

Authority (TVA) (TN) Lead, Manganese, Molybdenum, 

Sulfate, Cobalt 

Kingston Fossil Plant, Tennessee Valley Authority (TVA) (TN)

Pond/Impoundment Arsenic, Selenium, Manganese, 

Cobalt, Aluminum, Ammonia, Thallium, Iron 

X X 

A-36 
Appendix A— Literature Review 

Table A-6. Summary of Surface Water Impacts Reported in Damage Cases from Steam Electric Powe

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

Federal/State 

WQC/Standards b 

Issued a Fish 

Consumption 

Advisory c

Impac

from Gr

Conta

Little Blue Run Surface Pond/Impoundment Selenium, Arsenic, Aluminum, X 

Impoundment, Bruce Antimony, Barium, Boron, Mansfield Power Plant, Cadmium, Calcium, Chloride, First Energy (PA) Hexavalent Chromium, Fluoride, 

Iron, Lead, Manganese, pH, Sodium, Sulfate, TDS, TSS,Thallium, Turbidity

Little Scary Creek Fly Ash Impoundment, JohnAmos Plant, American Electric Power (AEP)/Appalachian Power (WV) 

Pond/Impoundment Selenium, Mercury, Arsenic, 

Copper 

X 

Mahoney Landfill, Powerton Plant,Commonwealth Edison(IL)

Pond/Impoundment, Landfill 

Arsenic, Selenium, Chromium, TDS, Cadmium, Lead, Nitrate, Iron, Manganese, Sulfate, Boron,

Marion Plant, SouthernIllinois Power Cooperative (IL) 

Pond/Impoundment, Landfill 

Boron, Cadmium, Iron, Aluminum, TDS, Sulfate

X 

Martin's Creek Power Plant, PPL (PA) 

Pond/Impoundment Arsenic, Selenium, Lead, 

Aluminum, Copper, Chromium, Iron

X 

Montville Generating Station, NRG Energy/Montville Power, LLC (CT)

Pond/Impoundment Arsenic, Beryllium, Cadmium, 

Copper, Iron, Lead, Manganese, Nickel, pH, Zinc

X 

Morgantown GeneratingStation, Faulkner Off-siteDisposal Facility (MD) 

Pond/Impoundment, Landfill 

Iron, pH, Cadmium, Aluminum, Chloride, Manganese, Sulfate, TDS, Copper, Lead, Selenium

X 

A-37 
Appendix A— Literature Review 

Table A-6. Summary of Surface Water Impacts Reported in Damage Cases from Steam Electric Powe

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

Federal/State 

WQC/Standards b 

Issued a Fish 

Consumption 

Advisory c

Impac

from Gr

Conta

Oak Ridge Y-12 Plant, Chestnut Ridge Operable Unit 2, Oak RidgeReservation, Departmentof Energy (TN)

Pond/Impoundment Selenium, Arsenic, Aluminum, Iron,

Zinc, Manganese, Thallium (?) 

Phillips Power Plant Landfill, Duquesne LightCompany (PA) 

Pond/Impoundment, Landfill 

TDS, Chloride, Fluoride, Manganese, Aluminum, Arsenic 

X 

Plant Bowen, Georgia Power (GA) 

Pond/Impoundment Arsenic, Cadmium, Chromium, 

Lead, Mercury, Nickel, Copper 

X 

Reid Gardner Generating Facility, Nevada Energy(NV)

Pond/Impoundment, Landfill 

Selenium, Arsenic, Chloride,Sulfate, TDS, Nitrate, Boron, Chromium, Manganese, Magnesium, Molybdenum, Sodium, Vanadium, Titanium, Barium, Iron,Aluminum

X 

Savannah River Site, DArea, Department ofEnergy (SC) 

Pond/Impoundment Cadmium, Chromium, Copper, 

Mercury, Selenium, Zinc, Iron, Aluminum

X 

Seminole GeneratingStation, Seminole Electric Cooperative (FL) 

Pond/Impoundment, Landfill 

Arsenic, Chloride, Chlorine, Sulfate,Iron, TDS, Boron, Aluminum, Lead, Sodium

X 

Seward Generating Pond/Impoundment, Selenium, Arsenic, Aluminum, X 

Station, RRI Energy (PA) Landfill Antimony, Cadmium, Chloride, 

Chromium, Iron, Lead, Manganese,Nickel, pH, Sulfate, TDS, Zinc, 

Shawnee Fossil Plant, Pond/Impoundment, Selenium, Arsenic, Boron, pH, 

Tennessee Valley Landfill Sulfate, TDS, Beryllium, Cobalt, 

Authority (TVA) (KY) Nickel, Molybdenum, Manganese,

Vanadium

A-38 
Appendix A— Literature Review 

Table A-6. Summary of Surface Water Impacts Reported in Damage Cases from Steam Electric Powe

Impoundments

Damage Case Site

Type of Waste in 

Impoundment a Pollutants of Concern 

Exceeded 

Federal/State 

WQC/Standards b 

Issued a Fish 

Consumption 

Advisory c

Impac

from Gr

Conta

Sutton Steam Plant, Progress Energy (NC) 

Pond/Impoundment Arsenic, Boron, Manganese, Iron,

Thallium, Selenium, Antimony, Lead, Sulfate, TDS 

X 

W.J. Neal Station Surface Impoundment, Basin Electric Power Cooperative (ND) 

Pond/Impoundment Selenium, Arsenic, Chromium, 

Cadmium, Lead, Zinc, Aluminum

Wateree Station, SCE&G (SC)

Pond/Impoundment, Landfill 

Arsenic, Chromium, Cadmium,Lead, Iron 

X 

Westland Disposal Site, Dickerson GeneratingStation, Mirant (MD)

Pond/Impoundment, Landfill 

Selenium, Arsenic, Barium, Chromium, Cobalt, Copper, Iron,Zinc, Sulfate, Chlorine, Hardness,TDS, Aluminum 

X 

Sources: ERG, 2015m; U.S. EPA, 2012e (DCN SE01966); U.S. EPA, 2013b; U.S. EPA, 2014a through 2014e. Acronyms: FGD (Flue Gas Desulfurization); TDS (Total Dissolved Solids); TOC (Total Organic Carbon); TOH (Total Organic HydrocSuspended Solids); WQC (Water Quality Criteria). a – The term “ash” was used when the impact case study source did not identify the type of ash present at the waste management unit. b – An “X” indicates that one or more of the pollutants listed exceeded federal/state WQC/standards. c – An “X” indicates that the contaminated surface water was issued a fish consumption advisory. d – An “X” indicates that the ground water contaminated the surface water with one or more of the pollutants listed.

e – An “X” indicates that the surface water contaminated a source outside the plant property boundaries. 

A-39 
Appendix A— Literature Review 

Table A-7. Summary of Surface Water Impacts Reported in Damage Cases from Steam Electric Powe

Damage Case Site

Type of

Waste in 

Landfill a Pollutants of Concern 

Exceeded 

Federal/ State

WQC/ 

Standards b

Issued a Fish 

Consumption 

Advisory c

Impa

from 

Conta

Bangor Quarry Ash DisposalSite, Portland GeneratingStation, RRI Energy (PA)

Bottom Ash,Fly Ash, Other 

Selenium, Boron, Cadmium, HexavalentChromium, Iron, Manganese, Sulfate, TDS, Aluminum, Fluoride

X 

Battlefield Golf Club, Chesapeake Energy Facility, Dominion Power (VA)

Fly Ash Arsenic, Cadmium, Chromium, Copper,

Lead, Manganese, Thallium, Zinc, Vanadium, Iron, Boron, Aluminum

Belews Creek Steam Station, Duke Energy (NC)

Fly Ash, FGD Selenium, Arsenic, Boron, Cadmium,

Iron, Lead, Manganese, Nitrate, Sulfate, pH, Bromide 

X 

Big Bend Station, Tampa Electric Company (FL) 

Bottom Ash,Fly Ash, FGD,Other

Arsenic, Aluminum, Boron, Chloride, Fluoride, Iron, Manganese, Molybdenum,Sulfate, Sodium, Thallium, TDS 

Brandywine Coal AshLandfill, Mirant MidAtlantic LLC (MD) 

Bottom Ash,Fly Ash 

Selenium, Cadmium, Lead, Manganese,Iron, Aluminum, Sulfate, TDS, Chloride

X 

Cardinal Fly Ash Reservoir (FAR) 1 and 2, American Electric Power (AEP) (OH)

Bottom Ash,Fly Ash, FGD 

Arsenic, Boron, Molybdenum X 

Cayuga Coal Ash Disposal Bottom Ash, Selenium, Arsenic, Boron, Cadmium, X 

Landfill, AES (NY) Fly Ash, Other Lead, TDS, Aluminum, Manganese, 

Sulfate, Barium, Sodium, Iron, Chromium, Zinc

CCW Landfill, Trans-Ash,Inc. (TN)

Bottom Ash,Fly Ash 

Mercury, Iron, Boron, Sulfate, Arsenic, Chromium, Lead 

Coal Combustion Waste Landfill, Merom Generating Station, Hoosier Energy (IN)

Fly Ash, Bottom Ash 

Barium, Chromium, Cadmium, Lead, Sulfate, Chloride, Sodium

Columbia Energy Center, Alliant Energy (WI) 

Bottom Ash,Fly Ash 

Cadmium, Copper, Barium, Aluminum, Iron, Zinc, Arsenic, Selenium, Lead, Manganese

X 

A-40 
Appendix A— Literature Review 

Table A-7. Summary of Surface Water Impacts Reported in Damage Cases from Steam Electric Powe

Damage Case Site

Type of

Waste in 

Landfill a Pollutants of Concern 

Exceeded 

Federal/ State

WQC/ 

Standards b

Issued a Fish 

Consumption 

Advisory c

Impa

from 

Conta

Cumberland Steam Plant, Tennessee Valley Authority (TVA) (TN) 

Bottom Ash,Fly Ash, FGD 

Selenium, Arsenic, Aluminum, Boron,Chloride, Iron, Manganese, Sulfate, TDS, Vanadium

X 

Curtis Stanton EnergyCenter, Orlando Utility Commission (FL)

Bottom Ash,Other

Aluminum, Chloride, Iron, Manganese, Sodium, Sulfate, TDS, Vanadium, pH

X 

Dave Johnston Power Plant (WY)

Fly Ash Cadmium, Manganese, Sulfate, Boron

Fern Valley Landfill, OrionPower Holdings, Inc. (asubsidiary of RRI Energy) (PA)

Fly Ash Selenium, Aluminum, Boron, Chloride,

Sulfate, TDS 

X 

Flint Creek Power Plant, American Electric Power (AEP)/South West Electric Power Company (SWEPCO)(AR)

Bottom Ash,Fly Ash, Other 

Selenium, Barium, Cadmium, Chromium, Iron, Lead, Manganese, pH, Silver, Sulfate, TDS 

X 

General James M. Gavin Power Plant, American Electric Power/Ohio Power Company (OH) 

Bottom Ash,Fly Ash, FGD,Other

Arsenic, Barium, Cadmium, Lead, Molybdenum, Sulfate, TDS, Aluminum, Copper, Nickel, Zinc, Manganese, Chloride

X 

Gibson Generating Station,Duke Energy (IN)

Bottom Ash,Fly Ash 

Selenium, Arsenic, Boron, Manganese, Iron, Sodium

X 

Hatfield's Ferry Power Station, Allegheny Energy(PA)

Bottom Ash,Fly Ash, FGD 

Arsenic, Aluminum, Boron, Chromium, Manganese, Molybdenum, Thallium,TDS, Sulfate, Selenium 

X 

Indian River Generating Ash Selenium, Mercury, Arsenic, Aluminum, X 

Station, NRG Energy (DE) Barium, Cadmium, Chromium, Copper,

Lead, Nickel, Thallium, Zinc, Iron, Manganese

A-41 
Appendix A— Literature Review 

Table A-7. Summary of Surface Water Impacts Reported in Damage Cases from Steam Electric Powe

Damage Case Site

Type of

Waste in 

Landfill a Pollutants of Concern 

Exceeded 

Federal/ State

WQC/ 

Standards b

Issued a Fish 

Consumption 

Advisory c

Impa

from 

Conta

John Warden Ash Site (MI) Ash, Other Boron, Lithium Johnsonville Fossil Plant, Tennessee Valley Authority (TVA) (TN) 

Bottom Ash,Fly Ash 

Arsenic, Aluminum, Boron, Cadmium,Chromium, TDS, Iron, Lead, Manganese, Molybdenum, Sulfate, Cobalt 

X 

Mahoney Landfill, PowertonPlant, Commonwealth Edison (IL) 

Bottom Ash,Fly Ash, Other 

Arsenic, Selenium, Chromium, TDS, Cadmium, Lead, Nitrate, Iron, Manganese, Sulfate, Boron,

Marion Plant, SouthernIllinois Power Cooperative (IL)

Bottom Ash,Fly Ash, FGD 

Boron, Cadmium, Iron, Aluminum, TDS, Sulfate

X 

Morgantown GeneratingStation, Faulkner Off-siteDisposal Facility (MD) 

Bottom Ash,Fly Ash, Other 

Iron, pH, Cadmium, Aluminum, Chloride, Manganese, Sulfate, TDS, Copper, Lead, Selenium

X 

Oak Creek Power Plant,Wisconsin Energy (WE Energies (WE))/Wisconsin Electric Power Company (WI)

Bottom Ash,Fly Ash, FGD,Other

Arsenic, Chromium, TCE, Diesel Fuel X 

Phillips Power Plant Landfill, Duquesne LightCompany (PA) 

Ash, FGD TDS, Chloride, Fluoride, Manganese, 

Aluminum, Arsenic

X 

Range Road Landfill, DetroitEdison (MI) 

Ash Boron, Lithium, Manganese X 

Reid Gardner Generating Facility, Nevada Energy(NV)

Fly Ash, FGD Selenium, Arsenic, Chloride, Sulfate, 

TDS, Nitrate, Boron, Chromium, Manganese, Magnesium, Molybdenum, Sodium, Vanadium, Titanium, Barium, Iron, Aluminum 

X 

A-42 
Appendix A— Literature Review 

Table A-7. Summary of Surface Water Impacts Reported in Damage Cases from Steam Electric Powe

Damage Case Site

Type of

Waste in 

Landfill a Pollutants of Concern 

Exceeded 

Federal/ State

WQC/ 

Standards b

Issued a Fish 

Consumption 

Advisory c

Impa

from 

Conta

Seminole GeneratingStation, Seminole Electric Cooperative (FL) 

Fly Ash, FGD,Other

Arsenic, Chloride, Chlorine, Sulfate, Iron,TDS, Boron, Aluminum, Lead, Sodium

X 

Seward Generating Station,RRI Energy (PA) 

Ash, Other Selenium, Arsenic, Aluminum, 

Antimony, Cadmium, Chloride, Chromium, Iron, Lead, Manganese,Nickel, pH, Sulfate, TDS, Zinc, 

X 

Shawnee Fossil Plant,Tennessee Valley Authority (TVA) (KY)

Bottom Ash,Fly Ash 

Selenium, Arsenic, Boron, pH, Sulfate, TDS, Beryllium, Cobalt, Nickel, Molybdenum, Manganese, Vanadium

Wateree Station, SCE&G Bottom Ash, Arsenic, Chromium, Cadmium, Lead, X 

(SC) Fly Ash, FGD IronWestland Disposal Site, Dickerson GeneratingStation, Mirant (MD)

Fly Ash Selenium, Arsenic, Barium, Chromium, 

Cobalt, Copper, Iron, Zinc, Sulfate, Chlorine, Hardness, TDS, Aluminum

X 

Sources: ERG, 2015m; U.S. EPA, 2012e (DCN SE01966); U.S. EPA, 2013b; U.S. EPA, 2014a through 2014e. Acronyms: FGD (Flue Gas Desulfurization); TDS (Total Dissolved Solids); TOC (Total Organic Carbon); TOH (Total Organic HydrocSuspended Solids); WQC (Water Quality Criteria). a – The term “ash” was used when the impact case study source did not identify the type of ash present at the waste management unit. b – An “X” indicates that one or more of the pollutants listed exceeded federal/state WQC/standards. c – An “X” indicates that the contaminated surface water was issued a fish consumption advisory. d – An “X” indicates that the ground water contaminated the surface water with one or more of the pollutants listed.

e – An “X” indicates that the surface water contaminated a source outside the plant property boundaries. 

A-43 
Appendix A— Literature Review 

Table A-8. Summary of Attractive Nuisances Related to Steam Electric Power Plants

Species

Attractive Nuisance

Site Description

Pollutant Concentrations 

in the Environment or

Diet

Pollutant Concentrations 

in the Organism 

(μg/g) Observed Effects Stud

Common Grackles (Quiscalus quiscala) 

Nested in closeproximity to a coal-fired power plant’s fly ash pond. 

Not measured in study Eggs = 5.9 selenium Histopathological Field 

Raccoons(Procyon lotor) 

Lived in close proximity to a coal-fired power plant’s ash pond.

Not measured in study  Heart = 2.8 arsenic 

 Kidney = 3.2 cadmium,

0.43 strontium

 Muscle = 0.95 chromium Liver = 0.34 lead, 1.5 

mercury 

Histopathological Field 

Interior Least Tern(Sterna antillarum) 

Nested on a dike in a coal-fired power plant’sash pond. 

Not measured in study Not observed in study Not observed in study Field 

Southern Toads (Bufo terrestris) 

 Inhabited an ash 

basin and nearbyswamp. 

 Reference (control) 

site organisms weretransferred to contaminated locations. 

Not measured in study Not measured in study Elevated 

corticosterone and testosterone levels 

Outdomesoc

Southern Toads (Bufo terrestris) 

 Inhabited an ash pond

and nearby swamp. 

 Reference site 

organisms were transferred to contaminated locations. 

Pond sediment = 39.64 μg/g arsenic, 4.38 μg/gselenium

Adult males = 1.58 arsenic, 17.40 selenium

Histopathological Outdo

mesoc

A-44 
Appendix A— Literature Review 

Table A-8. Summary of Attractive Nuisances Related to Steam Electric Power Plants

Species

Attractive Nuisance

Site Description

Pollutant Concentrations 

in the Environment or

Diet

Pollutant Concentrations 

in the Organism 

(μg/g) Observed Effects Stud

Larval Bullfrogs(Rana catesbeiana) 

Inhabited bottom ash ponds near a coal-fired power plant.

Pond sediment = 49.39 μg/g arsenic, 0.72 μg/gcadmium, 23.85 μg/g chromium, 84.72 μg/gcopper, 6.11 μg/g selenium, 106.39 μg/g strontium,45.83 μg/g vanadium

Whole body concentration= 33.10 arsenic, 5.47cadmium, 18.25 chromium, 116.72 copper, 20.25 selenium, 39.89 strontium,17.32 vanadium

 Morphological  Decreased

swimming speeds

Field 

Eastern NarrowMouth Toads (Gastrophryne carolinensis)

Inhabited a seleniumladen site located near a coal-fired power plant.

 Site water = 3.93 μg/L 

selenium

 Soil = 38.25 μg/L 

selenium

 Lab water = 0.28 μg/L

selenium

 Females = 42.40 

selenium

 Eggs = 43.96 selenium

 Reproductive Histopathological 

Outdomesco

Barn Swallow (Hirundo rustica) 

Nested near a seleniumladen pond associated with a coal-fired power plant.

Not provided in the literature 

Eggs = 2.8 selenium Histopathological Field 

Slider Turtles (Trachemys scripta) 

 Inhabited a seleniumladen basin that

receives fly ash transport water near a coal-fired power plant.

 Eggs were incubated 

in ash-contaminated soil. 

Ash-contaminated soil = 2.56 μg/g selenium

Adult Females = 37.18 (mean concentration), selenium

Reproductive Outdo

mesco

Canada Geese(Branta Canadensis) 

Inhabited pens near a vanadium-laden ash pond associated with anoil-fired power plant

Site water = 467,000 μg/L vanadium

 Liver = 57.3 vanadium Kidney = 226 vanadium

 Lethal  Histopathological 

Outdomesoc

Acronyms: μg/g (Micrograms per Grams); μg/L (Micrograms per Liters). 

A-45 
Appendix A— Literature Review 

Table A-9. Summary of Attractive Nuisances Unrelated to Steam Electric Power Plants

Site Name, Location, and 

Contamination Source Organism Affected Documented Effects

Trace Pollutant Concentrati

(ppm) 

Kesterson Reservoir, CA Agricultural Runoff 

California Vole (Microtus californicus) 

Mean selenium concentrations in livers were significantly elevated. 

Liver = 119 selenium 

Kesterson Reservoir, CA Agricultural Runoff 

American Coot (Fulica americana), 

Mallard (Anas platyrhynchos) 

Mean selenium concentrations in bird eggs and livers were elevated; organisms exhibited severe reproductivefailure and deformities.

 Eggs = 2.2 – 110 selenium Liver = 19 – 130 selenium Water = 300,000 selenium

Kesterson Reservoir, CA Agricultural Runoff 

Pied-Billed Grebes (Podilymbuspodiceps),Common Moorhen (Gallinula chloropus),Black-Necked Stilts (Himantopusmexicanus) 

Selenium concentrations in livers were 10 times those found in nearby controlareas; organisms exhibited severelesions and embryonic deformities. 

 Liver = 94.4 selenium Water = 300,000 selenium

Kesterson Reservoir, CA Agricultural Runoff 

Gopher Snakes (Pituophis melanoleucus), Bullfrogs (Rana catesbeiana) 

Selenium concentrations in snake andfrog livers were significantly elevated. 

 Snake liver = 11.1 selenium Frog liver = 45.0 selenium

Kesterson Reservoir, CA Agricultural Runoff 

Eared Grebe (podiceps nigricollis), Mallard (Anas platyrhynchos),Cinnamon Teal (Anas cyanoptera),Gadwall (Anas strepera), American Coot (Fulica americana), 

Killdeer (Charadrius vociferous),Black-Necked Stilt (Himantopusmexicanus),American Avocet (Recurvirostraamericana)

Hatchlings exhibited mortality, deformity, and lack of embryonicdevelopment.

Water = 300 selenium 

Kesterson Reservoir, CA Agricultural Runoff 

Mosquitofish (Gambusiaaffinis), American Coot (Fulica americana), 

Ducks (Anas spp.)

Selenium concentrations in livers, kidneys, and muscles were elevated; organisms exhibited reduced bodyweight.

 Fish = 120 – 140 selenium Coot liver = 76.7 selenium Duck liver = 25.2 selenium

Liberty State Park, NJIndustrial and Urban Activities 

House Wren (troglodytes aedon),

American Robin (Turdus migratorus) 

Lead, arsenic, chromium, copper, and iron concentrations in bird feathers were elevated. 

Feather = 4,200 lead; 1,000chromium; 6,200 copper; 600 arsenic

A-46 
Appendix A— Literature Review 

Table A-9. Summary of Attractive Nuisances Unrelated to Steam Electric Power Plants

Site Name, Location, and 

Contamination Source Organism Affected Documented Effects

Trace Pollutant Concentrati

(ppm) 

Meadowlands, NJIndustrial and Urban Activities 

Red-winged blackbird (agelaius

phoeniceus), marsh wrens (Cistothorus palustris), tree swallow 

(Tachycineta bicolor) 

Lead and chromium concentrations inblood were elevated; mercury and chromium concentrations in eggs were elevated. 

 Swallow blood = 0.94 lead; 

1.03 chromium

 Wren eggs = 0.2 mercury Blackbird eggs = 0.12

chromium

Acronym: ppm (parts per million).

A-47 
Appendix A— Literature Review 

Table A-10. Summary of Selenium Concentrations in the Environment and Organisms Experiencing A

Plant Name Species

Route of Selenium 

Exposure 

Selenium 

Concentrations in the 

Environment (μg/L) 

or Diet (μg/g)

Selenium 

Concentrations in the 

Organism (μg/g) Observed Effects 

S

W

Belews CreekSteam Station, Duke Energy(NC)

Striped bass (Morone saxatilis) 

Consumed a selenium-laden diet by eating red shiners collected from a site receiving coal ash pond sluice water. 

Red Shiners = 9.6 μg/g (average wholebody concentration), wet 

Skeletal muscle = 3.8 (higher average concentration), wet

ModifiedbehaviorDecreased growth Histopathological Lethal 

La(re

Largemouth bass (Micropterus salmoides) a 

Pomoxis spp. 

Inhabited a selenium-laden cooling water reservoirreceiving both fly ash and bottom ash pond effluentfrom a coal-fired power plant.

Site water d = 10 μg/L Biomass e = 0.1 – 1.0 

(mean) 

Lethal Reproductive

Fie(re

Lepomis spp. b Body = 41.0 – 77.1

(54.6 mean concentration), wet

Lealurus spp. c Body = 0.31 – 15.5

(6.32 mean concentration), wet

Largemouth bass (Micropterus salmoides)

Inhabited a selenium-laden cooling water reservoirreceiving effluent from the coal ash pond. 

Ash effluent = 100­200 μg/LSite water = 10 μg/L

Visceral tissue = 40+ (highest mean concentration), wet

Lethal Fie

(re

Green sunfish (Lepomis cyanellus) 

Inhabited a selenium-laden lake receiving coal fly ash sluice water. 

Site water = 13 μg/L Sediment = 5 – 14μg/g, dry

Liver = 21.4, wet Skeletal muscle = 12.9, wet Hematocrit = 33, wet

Histopathological Hematological 

Fie(la

D-Area CoalFired Power Plant, Savannah River Site (SRS) (SC) 

Banded water snakes (Nerodia fasciata) 

Consumed a selenium-laden diet by eating prey collected from a contaminated site located near a coal-fired power plant.

Prey items f = 22.7 

μg/g (geometric least squared mean), dry 

Gonads = 17.64 (female), 19.06 (male)Kidney = 25.38 (female), 32.04 (male)Liver = 24.08 (female), 24.22 (male)

ReproductiveHistopathological 

La(nosp

A-48 
Appendix A— Literature Review 

Table A-10. Summary of Selenium Concentrations in the Environment and Organisms Experiencing A

Plant Name Species

Route of Selenium 

Exposure 

Selenium 

Concentrations in the 

Environment (μg/L) 

or Diet (μg/g)

Selenium 

Concentrations in the 

Organism (μg/g) Observed Effects 

S

W

Eastern narrowmouth toads (Gastrophryne carolinensis)

Inhabited a selenium-laden site located near a coal-firedpower plant.

Site water = 3.93 μg/L Soil = 8.25 μg/LLab water = 0.28 μg/L

Females = 42.40 Eggs = 43.96 

ReproductiveHistopathological 

Oume(corespo

Slider turtles (Trachemysscripta) 

Inhabited a selenium-laden pond receiving sluiced fly ash near a coal-fired power plant.Eggs were incubated in ashcontaminated soil. 

Ash-contaminated soil = 2.56 μg/g, dry

Adult females = 37.18 (mean concentration), dry

Reproductive Ou

me(corespo

Roxboro Plant, Progress Energy (NC)

Largemouth bass (Micropterus salmoides) 

Inhabited a selenium-laden cooling water reservoirreceiving ash pond effluent from a coal-fired power plant.

Not provided in the literature. 

Carcass = 2.86 (mean, female), 2.63 (mean, male)Gonad = 4.40 (mean, female), 2.38 (mean, male)

ReproductiveHistopathological

Fie(re

Bluegill (Lepomis macrochirus) 

Carcass = 2.74 (mean, female), 4.64 (mean, male)Gonad = 4.63 (mean, female), 3.35 (mean, male)

Bluegill (Lepomis macrochirus) 

Inhabited a selenium-laden reservoir receiving coal ash pond effluent.

Not provided in the literature 

Not provided in the literature 

Lethal Fie

(re

Green sunfish h

(Lepomis cyanellus)

Inhabited a selenium-laden reservoir receiving coal ash pond effluent.

Site water i = 7 – 14

μg/L 

Biomass j = 2,744 – 

3,793 (mean) 

Lethal Reproductive

Fie(re

A-49 
Appendix A— Literature Review 

Table A-10. Summary of Selenium Concentrations in the Environment and Organisms Experiencing A

Plant Name Species

Route of Selenium 

Exposure 

Selenium 

Concentrations in the 

Environment (μg/L) 

or Diet (μg/g)

Selenium 

Concentrations in the 

Organism (μg/g) Observed Effects 

S

W

Bluegill (Lepomis macrochirus) 

Inhabited a selenium-laden cooling water reservoir of a coal-fired power plant. 

Site water k = 9 – 12

μg/L 

Testes = 4.37 (mean concentration) Ovaries = 6.96 (meanconcentration) 

Reproductive La

(re

Bluegill l

(Lepomis macrochirus) 

Inhabited a selenium-laden cooling water reservoir of a coal-fired power plant. 

Site water = <10–20 μg/L 

Liver = 34 (mean concentration), wetGonad = 12.1 (mean, female), 5.4 (mean, male), wet Muscle = 13 (mean concentration), wet

Histopathological Fie

(re

Largemouth bass 

m (Micropterus

salmoides) 

Liver = 10.2 (meanconcentration), wetGonad = 10.3 (mean, female), wet Muscle = 6.7 (mean concentration), wet

Martin LakeSteam Station, Texas Utilities Electric Service Company (TX) 

Green sunfish (Lepomis cyanellus) 

Inhabited a selenium-laden lake receiving coal fly ash, scrubber sludge, and coal bottom ash.

Not provided in the literature 

Hepatopancreas = 1.31– 9.30, wet

Histopathological Fie

(la

Redear sunfish (Lepomis microlophus) 

Hepatopancreas = 2.8– 11.03, wet

Redear sunfish (Lepomis microlophus) 

Inhabited a selenium-laden lake receiving coal fly ash, scrubber sludge, and coal bottom ash.

Not provided in the literature 

Liver = 20 Histopathological Fie

(la

A-50 
Appendix A— Literature Review 

Table A-10. Summary of Selenium Concentrations in the Environment and Organisms Experiencing A

Plant Name Species

Route of Selenium 

Exposure 

Selenium 

Concentrations in the 

Environment (μg/L) 

or Diet (μg/g)

Selenium 

Concentrations in the 

Organism (μg/g) Observed Effects 

S

W

Redear sunfish (Lepomis microlophus) 

Inhabited a selenium-laden lake receiving coal ash pond wastewater. 

Not provided in the literature 

Hepatopancreas = 8.4– 27.2 μg/LKidney = 11.4 – 115.7 μg/L Ovaries = 0 – 5.9 μg/L Testes = 0 – 54.2 μg/L 

Increased weightloss 

Fie(la

Redear sunfish (Lepomis microlophus) 

Inhabited a selenium-laden lake located near a coalfired power plant. 

Not provided in the literature 

Liver = 7.63 (meanconcentration) 

Histopathological Reproductive

Fie(la

Acronyms: kg/ha (kilogram per hectacre); μg/L (micrograms per liter); μg/g (micrograms per gram). a – Multiple fish species were studied; however, as presented by the report, the largemouth bass and pomoxis spp. had the lowest documen

concentrations. b – Multiple fish species were studied; however, as presented by the report, the Lepomis spp. had the highest documented selenium skeleta

c – Multiple fish species were studied; however, as presented by the report, the Letalurus spp. had the lowest documented selenium body c

d – This selenium concentration is dissolved. e – This concentration is measured in the units kg/ha. The range of selenium concentrations was reported annually from 1982 to 1989, befopower plant converted to dry ash handling. Both fish species had the same range of selenium concentrations.f – The banded water snakes were fed weekly combinations of previously frozen prey items inhabiting the coal ash-contaminated site. g – The data used in this study were census data collected from routine biological monitoring undertaken by the steam electric power planth – Multiple fish species were studied; however, as presented by the report, the green sunfish had the highest documented selenium biomasi – These are the selenium water concentrations detected prior to the conversion to a dry fly ash handling system. j – This concentration is measured in the units kg/ha. The range of selenium concentrations was reported annually from 1982 to 1989, befopower plant converted to dry ash handling.k – This concentration was not measured for this study but was reported in a previous study conducted at the same site. l – Multiple fish species were studied; however, as presented by the report, the bluegills had the highest documented selenium liver tissue cm – Multiple fish species were studied; however, as presented by the report, the largemouth bass had the lowest documented selenium live

A-51 
 

 

 

 

Appendix B—Proximity Analyses Supporting Tables 

APPENDIX B 

PROXIMITY ANALYSES SUPPORTING TABLES 

Table B-1. Immediate Receiving Waters 303(d) Impairments Listing 

Cause Group Name Cause Name

Found in 

Combustion

Wastewater

Evaluated in

the EA

Algal Growth Algal Growth

Algal Growth Chlorophyll-A 

Cause Unknown Cause Unknown 

Cause Unknown - Impaired Biota Benthic Macroinvertebrates

Bioassessments 

Cause Unknown - Impaired Biota Fish Bioassessments 

Dioxins 2,3,7,8-Tetrachlorodibenzo-P-Dioxin

(Only)

Dioxins Dioxin

Dioxins Dioxins

Fish Consumption Advisory Fish Consumption Advisory

Flow Alteration(s) Flow Alteration(s) 

Habitat Alterations Habitat Alterations

Mercury Fish Consumption Advisory - Mercury  

Mercury Mercury  

Mercury Mercury In Fish Tissue  

Metals (Other Than Mercury) Aluminum  

Metals (Other Than Mercury) Arsenic  

Metals (Other Than Mercury) Cadmium  

Metals (Other Than Mercury) Chromium, Total  

Metals (Other Than Mercury) Copper  

Metals (Other Than Mercury) Iron  

Metals (Other Than Mercury) Lead  

Metals (Other Than Mercury) Manganese  

Metals (Other Than Mercury) Metals (Other Than Mercury)  

Metals (Other Than Mercury) Selenium  

Metals (Other Than Mercury) Silver  

Metals (Other Than Mercury) Zinc  

Noxious Aquatic Plants Macrophytes 

Nutrients Eutrophication  

Nutrients Nitrogen, Total  

Nutrients Nutrient/Eutrophication Biological

Indicators

 

Nutrients Nutrients  

Nutrients Phosphorus  

Nutrients Phosphorus, Total  

B-1 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Appendix B—Proximity Analyses Supporting Tables 

Table B-1. Immediate Receiving Waters 303(d) Impairments Listing 

Cause Group Name Cause Name

Found in 

Combustion

Wastewater

Evaluated in

the EA

Oil And Grease Oil 

Oil And Grease Oil And Grease 

Organic Enrichment/Oxygen 

Depletion Dissolved Oxygen 

Organic Enrichment/Oxygen 

Depletion Dissolved Oxygen Saturation 

Pathogens Bacteria 

Pathogens Coliforms

Pathogens Enterococcus Bacteria 

Pathogens Escherichia Coli (E. Coli) 

Pathogens Fecal Coliform 

Pathogens Indicator Bacteria 

Pathogens Pathogens

Pesticides Atrazine

Pesticides Chlordane 

Pesticides Chlorpyrifos

Pesticides DDD

Pesticides DDE

Pesticides DDT

Pesticides Dieldrin

Pesticides Mirex

Pesticides Organochlorine Pesticides 

pH/Acidity/Caustic Conditions pH 

pH/Acidity/Caustic Conditions pH, Low 

Polychlorinated Biphenyls (PCBs) Fish Consumption Advisory - PCBs

Polychlorinated Biphenyls (PCBs) PCBs In Fish Tissue 

Polychlorinated Biphenyls (PCBs) Polychlorinated Biphenyls (PCBs) 

Salinity/Total Dissolved 

Solids/Chlorides/Sulfates Salinity/Total Dissolved Solids/Chlorides  

Salinity/Total Dissolved 

Solids/Chlorides/Sulfates Total Dissolved Solids (TDS)  

Sediment Sedimentation/Siltation 

Sediment Siltation 

Sediment Solids (Suspended/Bedload) 

Sediment Suspended Sediment 

Taste, Color, And Odor Taste and Odor 

Temperature Temperature

Toxic Inorganics Boron  

Toxic Organics Polycyclic Aromatic Hydrocarbons (PAHs) 

(Aquatic Ecosystems) 

B-2 
 

 

Appendix B—Proximity Analyses Supporting Tables 

Table B-1. Immediate Receiving Waters 303(d) Impairments Listing 

Cause Group Name Cause Name

Found in 

Combustion

Wastewater

Evaluated in

the EA

Turbidity Total Suspended Solids (TSS) 

Turbidity Turbidity 

Source: U.S. EPA, 2014i. National 303(d) Listed Impaired Waters National Hydrography Data (NHD) Indexed 

Dataset. Reach Address Database (RAD). Extracted on August 4. Available online at: 

http://www.epa.gov/waters/data/downloads.html. DCN SE04544. 

Note: 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, and aquatic

habitat). In even-numbered years, states submit their lists of impaired waters (known as the “303(d) list”) to EPA. 

These state-submitted, Geographic Information System (GIS) datasets are collected by EPA and indexed to the 

National Hydrography Dataset (NHDPlus) at 1:100K resolution (i.e., 303(d) impaired waters proximity database).

For this EA, EPA reviewed the 303(d) impaired waters proximity database to identify steam electric power plant 

immediate receiving waters identified as impaired for a pollutant associated with the evaluated wastestreams (i.e., 

FGD wastewater, fly ash transport water, bottom ash transport water, and combustion residual leachate).

B-3 
 

 

 

Appendix B—Proximity Analyses Supporting Tables 

Table B-2. Immediate Receiving Waters Fish Consumption Advisory Listing

Pollutant Found in Combustion Wastewater Evaluated in the EA

Chlordane 

Chlorinated pesticides 

DDT

Dieldrin

Dioxin

Lead  

Mercury  

Mirex 

Not Specified 

PCBs (Total) 

Perfluorooctane sulfonate 

Toxaphene 

Source: U.S. EPA, 2014h. National Fish Consumption Advisories NHD Indexed Dataset. RAD. Extracted on July 7.

Available online at: http://epamap32.epa.gov/radims/. DCN SE04545. 

B-4 
Appendix C—Water Quality Module Methodology

APPENDIX C 

WATER QUALITY MODULE METHODOLOGY 

This appendix presents the model equations, input variables, pollutant benchmarks, and 

methodology limitations/assumptions for the immediate receiving water (IRW) model water

quality module.

The IRW water quality module equations are organized by the methodology for

nonvolatile pollutants (i.e., arsenic, cadmium, chromium (VI), copper, lead, nickel, selenium, 

thallium, and zinc) and volatile pollutants (i.e., mercury). EPA used the equations to calculate 

total and dissolved pollutant concentrations in receiving waters and total pollutant concentrations

in sediment within the immediate discharge zone. Model input requirements for the equations 

presented in Appendix C can be divided into four major categories: 1) input variable described 

by another equation; 2) site-specific input variable; 3) model assumption variable; and 4) sitespecific assumption variable based on predetermined data. The following tables in Appendix C 

describe the input requirements and data sources used in the water quality module: 

 Table C-1. Site-Specific Model Input Variables. 

 Table C-2. Model Assumption Input Variables. 

 Table C-3. Site-Specific Assumption Input Variables. 

 Table C-4. Surface Water Partition Coefficients.

 Table C-5. Total Suspended Solids (TSS) Concentrations in Surface Waters.

 Table C-6. Regional Surface Water Temperatures. 

 Table C-7. National Recommended Water Quality Criteria (NRWQC) and Drinking

Water Maximum Contaminant Level (MCL) Benchmarks. 

EPA calculated pollutant loadings from the evaluated wastestreams as part of its 

engineering analysis (see Section 10 of the Technical Development Document for the Effluent 

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

Category (TDD) [EPA 821-R-15-007]). The IRW water quality module performs calculations on 

a per immediate-receiving-water basis. For steam electric power plants that discharge to multiple 

receiving waters, EPA divided the plant-specific pollutant loadings accordingly among the 

receiving waters based on water diagrams provided in the Questionnaire for the Steam Electric 

Power Generating Effluent Guidelines (Steam Electric Survey) responses. EPA used the IRW 

model to evaluate the environmental impacts from 188 steam electric power plants in the 

receiving water quantitative analysis (209 unique immediate receiving waters).

EPA modeled chromium (VI) in the water quality module, but did not take into 

consideration arsenic or mercury speciation. EPA included assumptions of pollutant speciation 

for arsenic and mercury as appropriate in the subsequent wildlife and human health modules (see 

Appendix D and Appendix E, respectively). EPA used total selenium loadings in the water 

quality module; however, due to the partition coefficients available, EPA assumed the dominant

form of selenium in the receiving water was selenate (i.e., selenium (VI)). Although selenium 

speciation likely occurs within combustion residual surface impoundments prior to discharge, 

C-1 
	 	 	 	 	 	 	 	

Appendix C—Water Quality Module Methodology

EPA selected the selenate partition coefficient because it is expected to be the predominant form

present in well-oxygenated alkaline surface waters and the rate of conversion between selenate 

and selenite (i.e., selenium (IV)) is reported to be slow in most natural waters [U.S. EPA, 2004]. 

IRW Model: Water Quality Module Equations 

EPA calculated the nonvolatile pollutant concentrations for the following compartments 

within the receiving water: 

Total pollutant concentration in water column (Cwc); 

Dissolved pollutant concentration in water column (Cdw); and 

Total pollutant concentration in sediment (Cbs). 

EPA used the equations presented below to calculate receiving water concentrations for 

arsenic, cadmium, chromium (VI), copper, lead, mercury, nickel, selenium, thallium, and zinc.

EQUATION C-1

Ltotal CwTot, Rivers = ሺQcool + Q ሻ	× fwater + Kwt× Vriver river

Where: 

CwTot,Rivers = Total pollutant concentration in the 

waterbody (water and sediment) in rivers and 

streams from pollutant loading (grams per 

cubic meter [g/m3

] or milligrams per liter 

[mg/L]) 

Output from Equation C-1 

Ltotal = Average pollutant loading from steam 

effluent (grams per day [g/day]) 

Site-specific value from

engineering analysis, 

based on annual average 

(see Table C-1) 

Qcool = Total cooling water effluent flow (cubic 

meters per day [m3

/day])

Site-specific value from

engineering analysis 

(see Table C-1) 

Qriver = Receiving water average annual flow 

(m3

/day) 

Site-specific value from

NHD Plus 

(see Table C-1) 

fwater = Fraction of total waterbody pollutant 

concentration in water column (unitless)

Output from 

Equation C-6

Kwt = Water concentration dissipation rate constant

(1/day) 

Output from Equation 

C-10 

Vriver = Flow independent mixing volume for rivers 

and streams (m3

) 

Output from 

Equation C-11

C-2 
	 	 	 	 	 	

	 	 	 	 	 	

Appendix C—Water Quality Module Methodology

EQUATION C-2

Ltotal CwTot, Lake = ሺQୡ୭୭୪ + Qlakeሻ	× fwater + Kwt× Vlake

Where: 

CwTot, Lake = Total pollutant concentration in the waterbody 

(water and sediment) in lakes, ponds, and 

reservoirs from pollutant loading (g/m3 or 

mg/L) 

Output from Equation C-2 

Ltotal = Average pollutant loading from steam effluent 

(g/day) 

Site-specific value from

engineering analysis, based 

on annual average 

(see Table C-1) 

Qcool = Total cooling water effluent flow (m3

/day) Site-specific value from

engineering analysis 

(see Table C-1) 

Qlake = Average annual flow exiting the lake, pond, or 

reservoir (m3

/day)

Site-specific value from

NHD Plus 

(see Table C-1) 

fwater = Fraction of total waterbody pollutant 

concentration in water column (unitless)

Output from 

Equation C-6

Kwt = Water concentration dissipation rate constant

(1/day) 

Output from Equation C-10 

Vlake = Flow independent mixing volume for lakes, 

ponds, and reservoirs (m3) 

Output from Equation C-12

EQUATION C-3

dz Cwc = fwater × Cwtot (Rivers or Lakes) ×

dw

Where: 

Cwc = Total pollutant concentration in water column

(mg/L) 

Output from Equation C-3 

fwater = Fraction of total waterbody pollutant 

concentration in water column (unitless)

Output from 

Equation C-6

CwTot 

(Rivers or

Lakes)

= Total pollutant concentration in the waterbody 

(water and sediment) from pollutant loading 

(g/m3

 or mg/L) 

Output from Equation C-1 

or Equation C-2 

C-3 
 

	 	 	 	 	 	

	 	 	 	

Appendix C—Water Quality Module Methodology

dz 

(Rivers or

Lakes)

= Depth of the waterbody (meters [m]) River or stream: output 

from Equation C-9 

Lake, pond, or reservoir: 

site-specific value (see 

Table C-1) 

dw 

(Rivers or

Lakes)

= Depth of water column (m) River or stream: output 

from

Equation C-7

Lake, pond, or reservoir: 

site-specific value (see 

Table C-1) 

EQUATION C-4

1

Cdw = Cwc ൬ ൰ 1 + Kdsw × TSS × 0.000001

Where: 

Cdw = Dissolved pollutant concentration in water 

(mg/L) 

Output from 

Equation C-4 

Cwc = Total pollutant concentration in water column

(mg/L) 

Output from Equation C-3 

Kdsw = Suspended sediment-surface water partition 

coefficient (milliliters per gram [mL/g]) 

Model assumption value 

(see Table C-2 and Table 

C-4) 

TSS = Total suspended solids (mg/L) Site-specific assumption 

value (see Table C-3 and

Table C-5) 

0.000001 = Conversion factor (L/mL)(g/mg) Conversion factor 

EQUATION C-5

dz Cbs = fBenth × Cwtot (Rivers or Lakes) ×

db

Where: 

Cbs = Total pollutant concentration in sediment 

(mg/L) 

Output from Equation C-5 

fBenth = Fraction of total waterbody pollutant 

concentration in benthic sediment (unitless) 

Output from 

Equation C-15

CwTot 

(Rivers or

Lakes)

= Total pollutant concentration in the waterbody 

(water and sediment) from pollutant loading 

(g/m3 or mg/L) 

Output from Equation C-1 

or 

Equation C-2 

C-4 
	 	

	 	 	 	 	 	 	 	

	 	 	 	 	 	 	 	 	 	 	 	 	 	 	

 

Appendix C—Water Quality Module Methodology

dz 

(Rivers or

= Depth of the waterbody (m) River or stream: output 

from Equation C-9 

Lakes)

Lake, pond, or reservoir: 

site-specific value (see 

Table C-1) 

db 

(Rivers or

Lakes)

= Depth of upper benthic sediment layer (m) Model assumption value of 

0.03 m

(see Table C-2) 

EQUATION C-6

dw ሾ1 + ሺKdsw × TSS × 0.000001ሻሿ × dz fwater = dw db ቈሾ1 + ሺKdsw × TSS × 0.000001ሻሿ × ቉ + ൤ሺbsp + Kdbs × bscሻ × ൨ dz dz 

Where: 

fwater = Fraction of total waterbody pollutant 

concentration in water column (unitless) 

Output from 

Equation C-6

Kdsw = Suspended sediment-surface water 

partition coefficient (mL/g) 

Model assumption value 

(see Table C-2 and Table C-4) 

TSS = Total suspended solids (mg/L) Site-specific assumption value 

(see Table C-3 and Table C-5) 

0.000001 = Conversion factor (L/mL)(g/mg) Conversion factor 

dw 

(Rivers or

Lakes)

= Depth of water column (m) River or stream: output from

Equation C-7

Lake, pond, or reservoir: 

site-specific value (see Table 

C-1) 

dz 

(Rivers or

Lakes)

= Depth of the waterbody (m) River or stream: output from

Equation C-9 

Lake, pond, or reservoir: 

site-specific value (see Table 

C-1) 

bsp = Bed sediment porosity (cubic centimeter 

per cubic centimeter [cm3/cm3]) 

Model assumption value of 0.6 

cm3/cm3 

(see Table C-2) 

Kdbs = Bottom sediment-pore water partition 

coefficient (mL/g) 

Model assumption value 

(see Table C-2 and Table C-4) 

C-5 
	 	 	 	

	 	 	 	 	

Appendix C—Water Quality Module Methodology

bsc = Bed sediment particle concentration (gram

per cubic centimeter [g/cm3]) or (kilogram

per liter [kg/L]) 

Model assumption value of 1 

g/cm3 

(see Table C-2) 

db = Depth of upper benthic layer (m) Model assumption value of 

0.03 m

(see Table C-2) 

EQUATION C-7

dw = Qriver 

v × Width

Where: 

dw, river = Depth of water column (m) Output from 

Equation C-7

Qriver = Receiving water average annual flow 

(m3/s) 

Site-specific value from NHD 

Plus 

(see Table C-1) 

v = Receiving water velocity (m/s) Site-specific value from NHD 

Plus 

(see Table C-1) 

Width river = Receiving water width (m) Output from Equation C-8 

EQUATION C-8

Width 0.4559

river = 5.1867 × Qriver 

Where: 

Widthriver = Receiving water width (m) Output from Equation C-8 

Qriver = Receiving water average annual flow 

(m3/s) 

Site-specific value from NHD 

Plus 

(see Table C-1) 

EQUATION C-9

dz, river = db + dw, river

Where: 

dz, river = Depth of the waterbody (m) Output from Equation C-9 

db = Depth of upper benthic sediment layer (m) Model assumption value 0.03 

m 

(see Table C-2) 

C-6 
	 	 	 	 	 	 	 	 	 	 	 	 	 	 	

Appendix C—Water Quality Module Methodology

dw, river = Depth of water column (m) Output from 

Equation C-7

EQUATION C-10

Kwt = ሺfwater × kswሻ + ሺfbenth × ksedሻ + ሺfwater× kvolሻ + ሺfbenth × Kbሻ

Where: 

Kwt = Water concentration dissipation rate 

constant (1/day) for nonvolatile pollutants 

(see Equation C-16 for volatile pollutants) 

Output from Equation C-10 

fwater = Fraction of total waterbody pollutant 

concentration in water column (unitless)

Output from 

Equation C-6

ksw = Degradation rate for water column (1/day) Model assumption value of 

0/day 

(see Table C-2) 

fbenth = Fraction of total waterbody pollutant 

concentration in benthic sediment 

(unitless) 

Output from 

Equation C-15

ksed = Degradation rate for sediment (1/day) Model assumption value of 

0/day 

(see Table C-2) 

kvol = Water column volatilization loss rate 

constant (1/day) 

Model assumption value of 

0/day 

(see Table C-2) 

Kb = Benthic burial rate (1/day) Output from 

Equation C-14

EQUATION C-11

Vriver = Widthriver × Len × dz,river

Where: 

Vriver = Flow independent mixing volume for 

rivers and streams (m3) 

Output from 

Equation C-11

Widthriver = Receiving water width (m) Output from Equation C-8 

Len = Length of stream reach (m) Site-specific value from NHD 

Plus 

(see Table C-1) 

dz, river = Depth of the waterbody (m) Output from Equation C-9 

C-7 
	 	 	 	 	 	 	

	 	

Appendix C—Water Quality Module Methodology

EQUATION C-12

Vlake = Area × dz,lake

Where: 

Vlake = Flow independent mixing volume for 

lakes, ponds, and reservoirs (m3

) 

Output from 

Equation C-12

Area = Surface area of the lake (m) Site-specific value from NHD 

Plus 

(see Table C-1) 

dz,lake = Depth of the lake (m) Site-specific value 

(see Table C-1) 

EQUATION C-13

fd = 1 

1 + Kdsw× TSS × 0.000001

Where: 

fd = Dissolved fraction in water (unitless) Output from 

Equation C-13

Kdsw = Suspended sediment-surface water 

partition coefficient (mL/g) 

Model assumption value 

(see Table C-2 and Table C-4) 

TSS = Total suspended solids (mg/L) Site-specific assumption value 

(see Table C-3 and Table C-5) 

0.000001 = Conversion factor (L/mL)(g/mg) Conversion factor 

EQUATION C-14

Kb = fbenth × 

WB 

db

Where: 

Kb = Benthic burial rate (1/day) Output from 

Equation C-14

fbenth = Fraction of total waterbody pollutant 

concentration in benthic sediment 

(unitless) 

Output from 

Equation C-15

WB = Rate of burial (m/day) Model assumption value of 0 

m/day (see Table C-2) 

C-8 
	 	 	 	 	 	

	 	 	 	 	 	 	 	 	 	 	 	 	 	

 

Appendix C—Water Quality Module Methodology

db = Depth of upper benthic sediment layer (m) Model assumption value of 

0.03 m (see Table C-2) 

EQUATION C-15

db ሺbsp + Kdbs × bscሻ × dz fBenth = dw db ቈሾ1 + ሺKdsw × TSS × 0.000001ሻሿ × ቉ + ൤ሺbsp + Kdbs × bscሻ × ൨ dz dz 

Where: 

fbenth = Fraction of total waterbody pollutant 

concentration in benthic sediment 

(unitless) 

Output from 

Equation C-15

bsp = Bed sediment porosity (cm3/cm3) Model assumption value of 0.6 

cm3

/cm3 

(see Table C-2) 

Kdbs = Bottom sediment-pore water partition 

coefficient (mL/g) 

Model assumption value 

(see Table C-2 and Table C-4) 

bsc = Bed sediment particle concentration 

(g/cm3

) or (kg/L) 

Model assumption value of 1 

g/cm3 

(see Table C-2) 

db = Depth of upper benthic sediment layer (m) Model assumption value of 

0.03 m

(see Table C-2) 

dz = Depth of the waterbody (m) Output from Equation C-9 

Kdsw = Suspended sediment-surface water 

partition coefficient (mL/g) 

Model assumption value 

(see Table C-2 and Table C-4) 

TSS = Total suspended solids (mg/L) Site-specific assumption value

(see Table C-3 and Table C-5) 

0.000001 = Conversion factor (L/mL)(g/mg) Conversion factor 

dw 

(Rivers or

Lakes)

= Depth of water column (m) River or stream: output from

Equation C-7

Lake, pond, or reservoir: 

site-specific value (see Table 

C-1) 

EPA calculated the volatile pollutant concentrations in each of the three compartments

within the receiving water by building off the equations used to calculate nonvolatile pollutant

concentrations. The water concentration dissipation rate constant, Kwt, in Equation C-10 was 

replaced with a Kwt,volatile factor (see Equation C-16) that takes into account volatilization loss 

C-9 
	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	 	

	 	 	 	

Appendix C—Water Quality Module Methodology

(kvol). EPA used the equations presented below in combination with the preceding equations to

calculate receiving water concentrations for mercury only. 

EQUATION C-16

Kwt, volatile = ሺfwater × kswሻ + ሺfbenth × ksedሻ + ሺfwater × fd × kvolሻ + ሺfbenth × Kbሻ

Where: 

Kwt, volatile = Water concentration dissipation rate 

constant (1/day) 

Output from Equation C-16 

fwater = Fraction of total waterbody pollutant 

concentration in water column (unitless) 

Output from 

Equation C-6

ksw = Degradation rate for water column (1/day) Model assumption value of 

0/day 

(see Table C-2) 

fbenth = Fraction of total waterbody pollutant 

concentration in benthic sediment 

(unitless) 

Output from 

Equation C-15

ksed = Degradation rate for sediment (1/day) Model assumption value of 

0/day 

(see Table C-2) 

fd = Dissolved fraction in water (unitless) Output from 

Equation C-13

kvol = Water column volatilization loss rate 

constant (1/day) 

Output from 

Equation C-17

Kb = Benthic burial rate (1/day) Output from 

Equation C-14

EQUATION C-17

Kv × fd kvol = dw

Where: 

kvol = Water column volatilization loss rate 

constant (1/day) 

Output from 

Equation C-17

Kv = Diffusion transfer rate (m/day) Output from 

Equation C-18

fd = Dissolved fraction in water (unitless) Output from 

Equation C-13

C-10 
 

	 	

	 	

 

 

Appendix C—Water Quality Module Methodology

dw = Depth of water column (m) River or stream: output from

(Rivers or Equation C-7

Lakes)

Lake, pond, or reservoir: 

site-specific value (see Table 

C-1) 

EQUATION C-18

Where: 

Kv = 1 

ቀ 1 

KL 

ቁ + ൮ 1 

Kg × ቀ HLC 

R × Tw 

ቁ

൲

θwater 

ሺTw-Thicሻ

Kv = Diffusion transfer rate (m/day) Output from 

Equation C-18

Θwater = Temperature correction (unitless) Model assumption value of 

1.026 

(see Table C-2) 

Tw = Temperature of the waterbody (degrees 

Kelvin [°K]) 

River or stream: site-specific 

assumption value 

(see Table C-3 and Table C-6) 

Lake, pond, or reservoir: 

model assumption value (see 

Table C-3 and Table C-6) 

Thlc = Temperature of HLC (°K) Default model value of 298°K 

(see Table C-2) 

KL 

(Rivers or

Lakes)

= Liquid-phase transfer coefficient (m/day) River or stream: output from

Equation C-19 

Lake, pond, or reservoir: 

output from Equation C-21 

Kg 

(Rivers or

Lakes)

= Gas-phase transfer coefficient (m/day) River or stream:

model assumption value of 

100 m/day 

(see Table C-2) 

Lake, pond, or reservoir: 

output from

Equation C-23 

C-11 
 

	 	 	 	 	 	 	 	 	

	 	

 

Appendix C—Water Quality Module Methodology

HLC = Henry's Law Constant (atm-m3/mole) 1 Known value of 0.0113 atmm3

/mol 

(see Table C-2) 

R = Universal gas constant (atm-m3

/°K-mole) Known value of 0.00008205 

atm-m3/°K-mole 

(see Table C-2) 

EQUATION C-19

ඨ10-4 × Dw × v

KL(Rivers) = × 86,400 dz

Where: 

KL(Rivers) = Liquid-phase transfer coefficient (m/day) Output from 

Equation C-19 

Dw = Diffusivity of the pollutant in water 

(square centimeter per second [cm2/s])

Output from 

Equation C-20 

v = Receiving water velocity (m/s) 

Site-specific value from NHD 

Plus 

(see Table C-1) 

dz,river = Depth of waterbody (m) Output from Equation C-9 

86,400 = Conversion factor (s/day) Conversion factor 

EQUATION C-20

Dw = 22×10-5 

MW2 3⁄

Where: 

Dw = Diffusivity of the pollutant in water 

(cm2

/s) 

Output from 

Equation C-20 

MW = Molecular weight (grams per mole 

[g/mol]) 

Known value of 200.59 g/mol 

for mercury

(see Table C-2) 

1

 Units for Henry’s Law Constant are atmospheres of absolute pressure (atm) per cubic meter (m3) per mole (mol).

C-12 
	 	 		 	 	 	 	 	 	 	

	 	

Appendix C—Water Quality Module Methodology

EQUATION C-21

× ቆ

k0.33 

a KLሺLakesሻ = ඥCd × w10 × ඨ

ρ

λ2 ቇ	 × Scw 

-0.67 × 86,400

ρw

Where: 

KL(Lakes) = Liquid-phase transfer coefficient (m/day) Output from Equation C-21 

Cd = Drag coefficient (unitless) Model assumption value of 

0.0011 

(see Table C-2) 

W10 = Wind velocity 10 meters above water 

surface (m/s) 

Site-specific assumption value 

(see Table C-3) 

ρa = Density of air corresponding to water 

temperature (g/cm3) 

Model assumption value of 

0.0012 g/cm3

(see Table C-2) 

ρw = Density of water corresponding to water 

temperature (g/cm3) 

Model assumption value of 1 

g/cm3

(see Table C-2) 

k = Von Karman’s constant (unitless) Known value of 0.4 

(see Table C-2) 

λ2 = Dimensionless viscous sublayer thickness 

(unitless) 

Model assumption value of 4 

(see Table C-2) 

Scw = Water Schmidt number (dimensionless) Output from 

Equation C-22

86,400 = Conversion factor (s/day) Conversion factor 

EQUATION C-22

μw Scw = ρw× Dw

Where: 

Scw = Water Schmidt number (dimensionless) Output from 

Equation C-22 

μw = Viscosity of water corresponding to water 

temperature (g/cm-s) 

Model assumption value of 

0.0169 g/cm-s 

(see Table C-2) 

ρw = Density of water corresponding to water 

temperature (g/cm3

) 

Model assumption value of 1 

g/cm3

(see Table C-2) 

Dw = Diffusivity of the pollutant in water 

(cm2

/s) 

Output from 

Equation C-20 

C-13 
	 	 	 	 	 	 	

	 	 	 	 	 	

Appendix C—Water Quality Module Methodology

EQUATION C-23

Kg(Lakes) = ඥCd × W10 × ቆ

k0.33ቇ × Sca 

-0.67 × 86,400 λ2 

Where: 

Kg(lakes) = Gas-phase transfer coefficient (m/day) Output from 

Equation C-23 

Cd = Drag coefficient (unitless) Model assumption value of 

0.0011 

(see Table C-2) 

W10 = Wind velocity 10 meters above water 

surface (m/s) 

Site-specific assumption value 

(see Table C-3) 

k = Von Karman’s constant (unitless) Known value of 0.4 

(see Table C-2)

λ2 = Dimensionless viscous sublayer thickness 

(unitless) 

Model assumption value of 4 

(see Table C-2) 

Sca = Air Schmidt number (dimensionless) Output from 

Equation C-24 

86,400 = Conversion factor (s/day) Conversion factor 

EQUATION C-24

ሺ1.32 + 0.009Taሻ × 105 

Sca = 1.9

⁄ MW2 3

Where: 

Sca = Air Schmidt number (dimensionless) Output from 

Equation C-24 

Ta = Air temperature °K Site-specific assumption value 

(see Table C-3) 

MW = Molecular weight (g/mol) Known value of 200.59 g/mol 

for mercury

(see Table C-2) 

EPA calculated the potential water quality impacts to aquatic life and humans by

comparing the pollutant concentration in the water column (Cwc or Cdw, depending on the 

benchmark) to the water quality benchmarks presented in Table C-7. 

C-14 
 

 

 

 

 

Appendix C—Water Quality Module Methodology

IRW Model: Water Quality Module Inputs 

Table C-1. Site-Specific Input Variables 

Input 

Variable Input Category and Description Data Source

Ltotal Plant-specific effluent characteristic

Total waterbody loading 

EPA estimated the pollutant discharge loadings using the 

methodology presented in Section 10 of the TDD.

Qcool Plant-specific effluent characteristic

Total cooling water effluent flow 

by receiving water 

EPA determined the estimated cooling water flow for each plant 

by outfall based an assessment of industry survey results using

the methodology outlined in Water Quality Module: Plant and

Receiving Water Characteristics [ERG, 2015e].

Qriver Receiving water characteristic for 

rivers and streams 

Waterbody annual flow

EPA extracted average annual flow values from the NHD Plus

dataset using the methodology outlined in Water Quality 

Module: Plant and Receiving Water Characteristics [ERG,

2015e]. The NHD Plus dataset includes estimated mean annual 

flow values for each stream reach within the network using the 

Vogel Method [Vogel et al., 1999] and the Unit Runoff Method. 

v Receiving water characteristic for 

rivers and streams 

Receiving water velocity 

EPA extracted average annual velocity values from the NHD 

Plus dataset using the methodology outlined in Water Quality 

Module: Plant and Receiving Water Characteristics [ERG,

2015e]. The NHD Plus dataset includes estimated mean annual 

velocity values for each stream reach within the network using 

the Jobson Method [Jobson, 1996] and the estimated mean

annual flow values. 

Len Receiving water characteristic for 

rivers and streams 

Length of stream reach 

EPA estimated the stream reach length based on outfall 

locations using the methodology described in Water Quality 

Module: Plant and Receiving Water Characteristics [ERG,

2015e]. 

Qlake Receiving water characteristic for 

lakes, ponds, and reservoirs 

Average discharge flow exiting the 

lake/pond system

EPA extracted average annual flow values from the NHD Plus

dataset using the methodology outlined in Water Quality 

Module: Plant and Receiving Water Characteristics [ERG,

2015e]. The NHD Plus dataset includes estimated mean annual 

flow values for the stream reach exiting the lake using the 

Vogel Method [Vogel et al., 1999] and the Unit Runoff Method. 

Area Receiving water characteristic for 

lakes, ponds, and reservoirs 

Surface area of the lake, pond, or 

reservoir 

EPA estimated the lake surface area based on NHD Plus data or

site-specific sources as described in Water Quality Module: 

Plant and Receiving Water Characteristics [ERG, 2015e]. 

dz,lake Receiving water characteristic for 

lakes, ponds, and reservoirs 

Depth of the lake, pond, or

reservoir 

EPA estimated the depth of the lake, pond, or reservoir based on 

site-specific data as described in Water Quality Module: Plant 

and Receiving Water Characteristics [ERG, 2015e]. 

dw,lake Receiving water characteristic for 

lakes, ponds, and reservoirs 

Depth of the water column

EPA estimated the depth of the lake, pond, or reservoir based on 

site-specific data as described in Water Quality Module: Plant 

and Receiving Water Characteristics [ERG, 2015e]. 

C-15 
 

 

 

 

 

 

 

Appendix C—Water Quality Module Methodology

Table C-2. Model Assumption Input Variables and Known Variables 

Input Variable Description 

Assumed/ 

Known

Value Assumption Rationale/Data Source

bsp Bed sediment porosity 0.6 cm3

/cm3 Bed sediment porosity is the volume of water per 

volume of benthic space with typical values 

ranging between 0.8 and 0.4 [U.S. EPA, 1998b].

EPA selected an average value to use for this input 

variable.

bsc Bed sediment particle

concentration 

1 g/cm3 Bed sediment particle concentrations typically

range between 0.5 to 1.5 g/cm3 [U.S. EPA, 1998d]. 

EPA selected an average value to use for this input 

variable.

db Depth of upper benthic layer 0.03 m The upper benthic layer variable represents the 

portion of the bed in equilibrium with the water 

column. Typical values can range from 0.01 to

0.05 m [U.S. EPA, 1998b]. EPA selected an

average value to use for this input variable. 

ksw Degradation rate for water 

column

0/day EPA assumed no loss from pollutant degradation 

in the water column, as an environmentally 

conservative assumption. 

kvol Water column volatilization

loss rate constant

0/day EPA selected a volatilization rate of 0 for 

nonvolatile pollutants (i.e., all pollutants except

mercury).

ksed Degradation rate for 

sediment 

0/day EPA assumed no loss from pollutant degradation 

in the sediment, as an environmentally 

conservative assumption. 

WB Rate of burial 0/day EPA assumed no pollutant loss from burial within

the waterbody sediments, as an environmentally

conservative assumption. 

Θwater Temperature correction 1.026 

(unitless) 

EPA selected the temperature correction factor 

based on the value provided in U.S. EPA, 1998b. 

Kg(Rivers) Gas phase transfer 

coefficient for rivers or 

streams 

36,500 m/yr

(100 m/day)

EPA selected the gas phase transfer coefficient for 

rivers and streams based on the value provided in

U.S. EPA, 1998b. 

R Ideal gas constant 0.00008205

atm-m3

/ 

K-mole 

The ideal gas constant is a known chemical 

constant. 

Cd Drag coefficient 0.0011 

(unitless) 

EPA selected the drag coefficient based on the 

value provided in U.S. EPA, 1998b. 

ρa Density of air corresponding 

to water temperature 

0.0012 g/cm3 EPA selected the density of air corresponding to 

water temperature based on the value provided in

U.S. EPA, 2005b. 

ρw Density of water 

corresponding to water 

temperature

1 g/cm3 EPA selected the density of water corresponding to

water temperature based on the value provided in

U.S. EPA, 2005b. 

k Von Karman’s constant 0.4

(unitless) 

The von Karman constant is a known

dimensionless constant used to describe the

velocity profile of a turbulent fluid flow near a 

boundary. 

C-16 
 

 

 

 

 

 

Appendix C—Water Quality Module Methodology

Table C-2. Model Assumption Input Variables and Known Variables 

Input Variable Description 

Assumed/ 

Known

Value Assumption Rationale/Data Source

Kdsw Suspended sediment- surface

water partition coefficient 

Table C-4 The suspended sediment partition coefficient

describes the partitioning of a pollutant between

sorbing material, in this case suspended sediment

and surface water. EPA identified U.S. EPA, 

2005a as the primary source for the pollutantspecific suspended sediment partition coefficients. 

Kdbs Bottom sediment-pore water 

partition coefficient 

Table C-4 The bottom sediment partition coefficient 

describes the partitioning of a pollutant between

sorbing material, in this case bottom sediment and

pore water. EPA identified U.S. EPA, 2005a as the 

primary source for the pollutant-specific bed

sediment partition coefficients. 

λ2 Dimensionless viscous 

sublayer thickness 

4 

(unitless) 

EPA selected the viscous sublayer thickness value 

based on the value provided in U.S. EPA, 2005b.

μw Viscosity of water 

corresponding to water 

temperature

0.0169 g/cms EPA selected the viscosity of water value based on

the value provided in U.S. EPA, 2005b. 

HLC Henry’s Law Constant 0.0113

atm-m3

/mol 

Henry’s Law Constant is used in

Equation C-18 to estimate the receiving water 

concentration for volatile pollutants. Mercury is 

the only volatile pollutant included in the IRW 

model. Therefore, the assumed model default value

is set to Henry’s Law Constant for mercury at 298

°K.

Thlc Temperature of Henry’s Law 

Constant

298 °K The value 298 °K is the standard temperature value

provided for Henry’s Law Constant.

MW Molecular weight 200.59 g/mol Molecular weight is used in

Equation C-20 and 

Equation C-24 to estimate the receiving water 

concentration for volatile pollutants. Mercury is 

the only volatile pollutant included in the IRW 

model. Therefore, the assumed model default value

is set to the molecular weight for mercury. 

Table C-3. Site-Specific Assumption Input Variables 

Input Variable Description 

Assumed 

Value Data Source

TSS Total suspended solids Table C-5 EPA used the geometric mean of the regional and

national TSS concentrations determined as part of 

the Human and Ecological Risk Assessment of

Coal Combustion Residuals [U.S. EPA, 2014g].

C-17 
 

Appendix C—Water Quality Module Methodology

Table C-3. Site-Specific Assumption Input Variables 

Input Variable Description 

Assumed 

Value Data Source

W10 Wind velocity 10 m above

the water surface 

Table C-1 National Climatic Data Center national mean

annual wind speed GIS coverage (downloaded 

05/12/2011 from

http://hurricane.ncdc.noaa.gov/cgibin/climaps/climaps.pl?directive=quick_search&s 

ubrnum). EPA selected, as an environmentally 

conservative estimate, the lower of the wind speed 

range values for the analysis. 

Ta Air temperature Table C-2 National Climatic Data Center national mean

annual temperature GIS coverage (downloaded 

05/12/2011 from

http://hurricane.ncdc.noaa.gov/cgibin/climaps/climaps.pl?directive=quick_search&s 

ubrnum). EPA selected, as an environmentally 

conservative estimate, the lower of the air 

temperature range values for the analysis. 

Tw Temperature of the surface

water

Table C-6 EPA used the regional surface temperatures 

determined as part of the Human and Ecological

Risk Assessment of Coal Combustion Residuals

[U.S. EPA, 2014g]. 

Figure C-1. National Climatic Data Center National Mean Annual Wind Speed 

C-18 
 

Appendix C—Water Quality Module Methodology

Figure C-2. National Climatic Data Center National Mean Annual Temperature 

Table C-4. Partition Coefficients

Pollutant 

Suspended SedimentWater Partition 

Coefficient (Kdsw) 

(mL/g)

Bottom Sediment-Pore

Water Partition 

Coefficient (Kdbs) 

(mL/g)

Arsenic 7,900 250

Cadmium 79,000 2,000 

Chromium (VI) 16,000 50

Copper 50,000 3,200 

Lead 500,000 40,000 

Mercury (II) 200,000 79,000 

Nickel 20,000 7,900 

Selenium (IV) 25,000 4,000 

Thallium 13,000 20

Zinc 100,000 13,000 

Source: U.S. EPA, 2005a.

C-19 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Appendix C—Water Quality Module Methodology

Table C-5. TSS Concentrations in Surface Waters 

Hydrologic 

Region a

Number of 

Measurements 

Number of 

Annual Medians 

Annual Median TSS (mg/L) 

(log triangular distribution) 

Min Max 

Geometric 

Mean

Weighted 

Geometric 

Mean

1 9,007 33 3.2 40 8 6 

2 47,202 38 10 316 32 40

3 43,395 36 6.3 79 25 25

4 29,577 37 6.3 794 25 25

5 39,900 38 4 100 25 25

6 4,137 28 5 316 16 20

7 34,494 37 32 1,585 63 100 

8 46,231 38 50 316 158 126 

9 3,254 35 13 3,162 32 63

10 62,791 38 10 398 126 126 

11 48,969 38 25 794 200 126 

12 7,280 35 40 1,995 79 126

13 13,974 37 32 79,433 200 398 

14 26,699 38 16 5,012 158 251 

15 9,162 37 20 19,953 200 398 

16 19,965 33 4 2,512 16 25

17 173,136 37 2 316 6 10

18 42,022 37 13 398 63 50

Lakes 

(national) 4,360 99 1 398 25 25

Source: U.S. EPA, 2010b; Legacy STORET database.

a – For rivers and streams, EPA used the geometric mean TSS concentration for the corresponding hydrogeologic 

region. For lakes, ponds, and reservoirs, EPA used a national geometric mean. 

Table C-6. Regional Surface Water Temperatures

Hydrologic Region Climate 

Surface Water 

Temperature (°C) 

Surface Water 

Temperature (°K) 

1 North 14 (Northern Median) 287

2 North 16 289

3 South 21 294

4 North 14 287

5 North 17 290

6 South 18 291

7 North 15 288

8 South 20 293

9 North 10 283

10 North 13 286

C-20 
 

 

 

 

 

 

 

Appendix C—Water Quality Module Methodology

Table C-6. Regional Surface Water Temperatures

Hydrologic Region Climate 

Surface Water 

Temperature (°C) 

Surface Water 

Temperature (°K) 

11 South 17 290

12 South 21 294

13 South 17 (Southern Median) 290 

14 South 9 282 

15 South 17 290

16 South 9 282 

17 North 14 (Northern Median) 287

18 South 15 288

Source: U.S. EPA, 2010b; Legacy STORET database.

Table C-7. NRWQC and MCL Benchmarks 

Pollutant 

FW Acute

NRWQC 

Benchmark a,b

(mg/L)

FW Chronic 

NRWQC 

Benchmark a,b

(mg/L)

HH WO

NRWQC 

Benchmark a,b 

(mg/L)

HH O

NRWQC 

Benchmark a,b

(mg/L)

MCL

Benchmark a,c 

(mg/L)

Arsenic 0.34 (d) 0.15 (d) 0.000018 (f) 0.00014 (f) 0.01

Cadmium 0.002 (d) 0.00025 (d) -- -- 0.005

Chromium (VI) 0.016 (d) 0.011 (d) -- -- 0.1 (g)

Copper 0.013 (d,e) 0.009 (d,e) 1.3 -- 1.3 (Action 

Level); 1.0 (h)

Lead 0.065 (d) 0.0025 (d) -- -- 0.015 (Action

Level) 

Mercury 0.0014 (d) 0.00077 (d) -- -- 0.002 (f) 

Nickel 0.47 (d) 0.052 (d) 0.61 4.6 -

Selenium -- 0.005 0.17 4.2 0.05

Thallium -- -- 0.00024 0.00047 0.002 

Zinc 0.12 (d) 0.12 (d) 7.4 26 5 (h)

Acronyms: MCL (Maximum Contaminant Level); NRWQC (National Recommended Water Quality Criteria). 

a – “--” designates instances where a benchmark does not exist for the pollutant or the benchmark is a secondary

standard. 

b – National Recommended Water Quality Criteria. Washington, D.C. [U.S. EPA, 2009d]. Pollutant concentrations

were compared to the freshwater (FW) acute and chronic NRWQC and the human health (HH) water and organisms 

(WO) and organisms only (O) NRWQC.

c – National Primary Drinking Water Regulations. EPA 816-F-09-004. May. Washington, D.C. [U.S. EPA, 2009e].

d – Benchmark is expressed in terms of the dissolved pollutant in the water column. 

e – The 2009 NRWQC for copper are calculated using the biotic ligand model; therefore, there is no national value.

For this analysis, EPA used the 2002 NRWQC values [U.S. EPA, 2002]. 

f – Benchmark is for inorganic form of pollutant. 

g – MCL is for total chromium.

h – Secondary (nonenforceable) drinking water standard.

C-21 
Appendix C—Water Quality Module Methodology

IRW Model: Water Quality Module Methodology Limitations and Assumptions 

The limitations and assumptions in the IRW water quality module are as follows: 

 The module is based on annual-average pollutant loadings, normalized effluent flow 

rates from the steam electric power plants, and annual-average flow rates within the 

immediate receiving waters. The module does not consider temporal variability (e.g.,

seasonal differences, storm flows, low-flow events, catastrophic events). The result of

this limitation on the water quality module outputs is unknown. 

 The module represents only the waterbody concentration within the immediate

discharge zone (i.e., approximately 1 to 10 kilometers [km] from the outfall) and does 

not calculate pollutant concentrations in downstream waters. This limitation results in 

a potential underestimation of the extent of surface waters with environmental and 

human health impacts under baseline conditions and improvements under the

regulatory options. 

 The module does not take into consideration pollutant speciation within the receiving 

stream. This limitation is particularly relevant to the wildlife impact analysis as many 

of the ecological impacts are tied to a specific pollutant species. For example, 

inorganic arsenic is typically more toxic to aquatic life than organic arsenic. This

limitation results in a potential overestimation of the number of immediate receiving

waters with exceedances of water quality benchmarks for inorganic forms of the 

pollutant (e.g., the human health NRWQCs for arsenic). 

 The module assumes that equilibrium is quickly attained within the waterbody 

following discharge and is consistently maintained between the water column and

surficial bed sediments. This assumption is especially significant regarding pollutant

equilibrium within lakes, ponds, and reservoirs. The module equations presented in 

Appendix C do not take into consideration the effects of currents, inversion, or 

temperature variations within the water column, but assume that the entire mass of the 

lake, pond, or reservoir is at equilibrium. As a result, the module outputs do not 

reflect the potential spatial and temporal variability of pollutant concentrations within 

the immediate receiving water, and potentially underestimate the existence of isolated 

“hot spots” of elevated pollutant concentrations. The module does not account for the

accumulation of pollutant concentrations in bottom sediments and pore water that 

occur over prolonged discharge periods. 

 The module assumes that pollutants dissolved or sorbed within the water column and 

bottom sediments can be described by a partition coefficient. EPA used a single 

partition coefficient to characterize the pollutant in the immediate receiving waters. 

The partition coefficient in a specific waterbody will be influenced by geochemical 

parameters (e.g., pH and presence of particulate organic matter and other sorbing 

material). EPA used a mean or median value for the partition coefficients (central 

tendency of Kd values) based on data gathered from published sources, statistical 

analysis of retrieved data, geochemical modeling, and expert judgment [U.S. EPA, 

2005a]. The result of this assumption on the water quality module outputs is unknown 

because of unknown site-specific factors.

C-22 
Appendix C—Water Quality Module Methodology

 The module assumes that pollutants sorbed to bottom sediments are considered a net 

loss from the water column. This assumes that bottom sediments are not resuspended 

and deposited further downstream, but remain within the immediate discharge zone 

and do not further contribute to the dissolved or suspended sediment concentrations 

within the water column. This assumption results in a potential overestimation of 

pollutant concentrations within the benthic sediments and a potential underestimation 

of pollutant concentrations within the water column and downstream reaches. 

 The module assumes a pollutant burial rate of zero within benthic sediment. This is 

an environmentally protective assumption that might overestimate impacts to

sediment receptors to some degree. The burial rate constant is a function of the 

deposition of sediments from the water column to the upper bed and accounts for the 

soil eroding into a waterbody becoming bottom sediment rather than suspended 

sediment. The rate of burial used for each segment of a waterbody may be difficult to

obtain [U.S. EPA, 1998b]. EPA had neither measured values nor the data to 

determine burial rates for each immediate receiving water. The pollutants with more 

than 10 percent immediate receiving waters showing impacts to sediment receptors

include cadmium, mercury, and nickel (see Table 6-4). This assumption results in a 

potential overestimation of impacts in the benthic sediment. 

 The module does not take into account ambient background pollutant concentrations 

or contributions from other point and nonpoint sources. Also, the pollutant loadings 

included in the module are not representative of the total pollutant loadings from

steam electric power plants, as there are several waste streams that are not included in 

the analysis (e.g., stormwater runoff, metal cleaning wastes, coal pile runoff).

Because of this approach, the module potentially underestimates the number and 

magnitude of benchmark exceedances at baseline and under the regulatory options.

The module also potentially underestimates the number of environmental and human 

health improvements under the regulatory options (i.e., a higher number of 

exceedances under baseline conditions creates additional opportunities for 

improvement under the regulatory options). The results of EPA’s case study 

modeling, which does take into account ambient background pollutant concentrations

and contributions from other point and nonpoint sources, support this assessment of 

the water quality module’s limitations (see Section 8). 

C-23 
 

Appendix D—Wildlife Module Methodology

APPENDIX D 

WILDLIFE MODULE METHODOLOGY 

This appendix presents the model equations, input variables, pollutant benchmarks, and 

methodology limitations/assumptions for the immediate receiving water (IRW) model wildlife

module. Wildlife impacts include the following ecological receptors: 

 Aquatic and sediment organisms (amphibians, fish, invertebrates) in direct contact with

receiving water and/or sediment in the immediate discharge zone of steam electric 

power plants. 

 Wildlife (minks and eagles)1 that consume fish from receiving waters in the immediate 

discharge zone of steam electric power plants.

EPA estimated pollutant concentrations in the immediate receiving water and sediment

using the IRW model water quality module (see Appendix C). The wildlife module uses these 

concentrations as inputs. 

Model input requirements for the equations presented in Appendix D can be divided into 

four major categories: 1) input variable described by another equation; 2) site-specific input

variable; 3) model assumption variable; and 4) pollutant-specific variable. The following tables in 

Appendix D describe the input requirements and data sources used in the wildlife module and 

impacts analysis: 

 Table D-1. Chemical Stressor Concentration Limits (CSCLs) for Sediment Biota. 

 Table D-2. Bioconcentration Factors (BCFs) and Bioaccumulation Factors (BAFs) for 

Trophic Level 3 (T3) and Trophic Level 4 (T4) Fish. 

 Table D-3. No Effect Hazard Concentration (NEHC) Benchmarks for Minks and Bald 

Eagles. 

IRW Model: Wildlife Module Equations, Input Variables, and Impact Analysis 

Impact to Aquatic Life Receptors from Direct Contact with Sediment. EPA determined the

potential negative impact to aquatic organisms from direct contact with the sediment in immediate

receiving waters by comparing the pollutant concentration in the sediment (Cbs from the water

quality module) to the CSCL benchmarks for sediment biota listed in Table D-1. The wildlife

module expresses this comparison as a hazard quotient (HQ). An HQ of higher than one (i.e., 

pollutant concentration exceeds benchmark) indicates a potential impact to the exposed organism. 

EPA used Equation D-1 to calculate the HQ for sediment biota. 

1

 EPA selected minks and eagles to represent national-scale impacts from steam electric power plants because their 

habitats cover the entire United States (i.e., can be used for a national assessment). 

D-1 
	 	

	 	 	 	

	 	 	 	 	 	

Appendix D—Wildlife Module Methodology

EQUATION D-1

Cbs HQsed = CSCLsed

Where: 

HQsed = Hazard quotient for contact with sediment Output from Equation D-1 

Cbs = Total pollutant concentration in sediment 

(milligrams per liter [mg/L]) 

Water quality module output 

Equation C-5 

CSCLsed = Ecological benchmark for sediment 

(milligrams per kilograms [mg/kg]) 

Receptor-specific benchmark 

(see Table D-1) 

Adverse Effects to Piscivorous Wildlife. EPA determined the potential negative impact to 

piscivorous wildlife (i.e., wildlife that consume fish) from the ingestion of contaminated fish by 

calculating fish tissue concentrations and comparing these concentrations to ecological

benchmarks. Equation D-2 calculates pollutant concentrations in fish for the evaluated pollutants,

except for mercury. Because the more toxic form of mercury is methylmercury, EPA used 

Equation D-3 for this pollutant [U.S. EPA, 2005b]. Equation D-3 estimates the concentration of 

methylmercury in fish tissue, as opposed to total mercury. 

EQUATION D-2

CfishT = Cwc × BCFT

EQUATION D-3

CfishT = ሺ0.15 × Cdwሻ × BCFT

Where: 

CfishT = Pollutant concentration in fish (wet weight), 

where T represents trophic level T3 or T4 

(mg/kg) 

Output from Equation D-2 or 

Equation D-3 

Cwc = Total pollutant concentration in water (mg/L) Water quality module output 

Equation C-3 

Cdw = Dissolved pollutant concentration in water 

(mg/L) 

Water quality module output 

Equation C-4 

0.15 = Fraction of dissolved total mercury as 

dissolved methylmercury (unitless) 

Model assumption value [U.S. 

EPA, 2005b] 

BCFT = Bioconcentration factor or bioaccumulation 

factor for specified trophic level (liters per 

kilogram [L/kg]) 

Pollutant-specific value

(see Table D-2) 

EPA compared the calculated T3 fish tissue concentration to the ecological benchmark for

minks and the calculated T4 fish tissue concentration to the ecological benchmark for eagles. EPA 

selected NEHC benchmarks for minks and eagles (Table D-3) as the ecological benchmarks for

piscivorous wildlife. The wildlife module expresses this comparison as an HQ. EPA used Equation 

D-4 to calculate HQ values for arsenic, cadmium, chromium (VI), copper, lead, mercury (as 

methylmercury), nickel, selenium, thallium, and zinc. 

D-2 
	 	

 

Appendix D—Wildlife Module Methodology

EQUATION D-4

CfishT HQI = NEHC

Where: 

HQI = Hazard quotient for ingestion of fish Output from Equation D-4 

CfishT = Pollutant concentration in fish (wet weight), 

where T represents trophic level T3 or T4 

(mg/kg) 

Output from Equation D-2 or 

Equation D-3 

NEHC = No effect hazard concentration (μg/g) Receptor- and pollutantspecific (see Table D-3) 

Table D-1. CSCL Benchmarks for Sediment Biota a

Pollutant in Wildlife 

Impact Assessment 

CSCL Benchmark

Value (mg/kg) Notes 

Arsenic 5.90

Cadmium 0.596

Chromium (VI) 37.3 No benchmark for chromium VI. EPA used the total chromium

benchmark, which may underestimate the impact to wildlife.

Copper 35.7 

Lead 35

Mercury 0.174 EPA compares the mercury, not methylmercury, concentration in

the sediment to the benchmark.

Nickel 18.0 

Selenium None identified EPA could not complete the analysis for this pollutant – no

benchmark for comparison. Thallium None identified 

Zinc 123

Source: MacDonald, D.D.; C. G. Ingersoll; and T. A. Berger. Development and Evaluation of Consensus-Based 

Sediment Quality Guidelines for Freshwater Ecosystems. Archives of Environmental Contamination and 

Toxicology 2000, 39(1)20 (as cited in NOAA, 2008).

a – The benchmarks used for the analysis are threshold effect levels (TELs).

D-3 
 

 

 

 

 

 

 

 

 

 

 

 

 

Appendix D—Wildlife Module Methodology

Table D-2. Bioconcentration Factors (BCFs) and Bioaccumulation Factors (BAFs) for 

Trophic Level 3 (T3) and Trophic Level 4 (T4) Fish

Pollutant BCF or BAF 

Factor for Trophic 

Level 3 (T3) Fish 

(L/kg)

Factor for Trophic 

Level 4 (T4) Fish 

(L/kg) Source

Arsenic BCF 4.00E+00 4.00E+00 Barrows et al., 1980 

Cadmium BCF 2.70E+02 2.70E+02 Kumada et al., 1972 

Chromium (VI) BCF 6.00E-01 6.00E-01 Stephan, 1993

Copper a BCF 3.60E+01 3.60E+01 U.S. EPA, 1980 

Lead BAF 4.60E+01 4.60E+01 Stephan, 1993

Methylmercury BAF 1.60E+06 6.80E+06 U.S. EPA, 1997a 

Nickel b BCF 0.8 0.8 Stephan, 1993

Selenium BAF 4.90E+02 1.70E+03 Lemly, 1985a

Thallium BCF 3.40E+01 1.30E+02 Barrows et al., 1980

and Stephan, 1993 

Zinc BCF 3.50E+02 3.50E+02 Murphy et al., 1978 

a – BCF not specific to a particular trophic level; applies to fish consumed by humans.

b – Nickel (soluble salts).

Table D-3. NEHC Benchmarks for Mink and Bald Eagles 

Pollutant in 

Wildlife Impact 

Assessment 

NEHC Benchmark 

Value for Mink

(T3 Fish) (μg/g)

NEHC Benchmark 

Value for Eagle 

(T4 Fish) (μg/g) Notes

Arsenic 7.65 22.4

Cadmium 5.66 14.7

Chromium (VI) 17.7 26.6 No benchmark for chromium VI. EPA used the 

total chromium benchmark, which may

underestimate the impact to wildlife. 

Copper 41.2 40.5

Lead 34.6 16.3

Methylmercury 0.37 0.5 No benchmark for methylmercury. EPA used the

total mercury benchmark, which may

underestimate the impact to wildlife. 

Nickel, 12.5 67.1 

Selenium 1.13 4

Thallium None identified None identified EPA could not complete the analysis for this 

pollutant – no benchmark for comparison.

Zinc 904 145 

Source: USGS, 2008. 

D-4 
 

Appendix D—Wildlife Module Methodology

IRW Model: Wildlife Module Methodology Limitations and Assumptions 

EPA was required to make assumptions about various inputs, resulting in limitations with 

respect to the wildlife module output and interpretation. Variability occurs from heterogeneous 

characteristics, such as body weight differences within a population or the contaminant levels in 

the environment. Uncertainty represents a lack of knowledge about factors such as the adverse 

effects from exposure to pollutants. The assumptions and limitations of the wildlife module include 

the following: 

 Additive Risks Across Pathways. The wildlife module does not consider additive risks 

across pathways. For example, the modeled impacts to wildlife from ingesting

contaminated fish do not consider the risk from direct contact with surface water. The 

receptors chosen for the wildlife ingestion model, minks and eagles, do not spend large 

amounts of time in contact with the surface water; therefore, not including the impact

of direct contact with surface water should only minimally underestimate the impacts. 

In addition, the wildlife module does not consider the impact from water ingestion. 

Because many of the pollutants considered in this analysis are bioaccumulative in 

nature, the model considers only ingestion of the food source since it is likely the dose 

from the food source dominates the dose from water ingestion. 

 Use of BCFs and BAFs. Where available, EPA used BAFs to represent the 

accumulation of pollutants in fish tissue (e.g., for selenium and methylmercury). 

Otherwise, EPA used BCFs, which do not account for accumulation of pollutants via 

the food web. For certain pollutants, exposure via the aquatic food web can be more 

significant than exposure via ingestion of water.2

 The result of this limitation on the 

wildlife module output for those pollutants that use a BCF is an under-representation 

of pollutant bioaccumulation in fish tissue where exposure via the aquatic food web is

significant. However, BCFs are useful in a screening-level assessment and appropriate 

for a national-level environmental assessment (EA) where site-specific data are not 

available and collection of site-specific data is not viable. The limitation of using a 

single, national-level BAF/BCF is unknown due to site-specific considerations.

 Receptor Populations Evaluated. EPA considered the limitations and made multiple

assumptions in choosing receptor populations to evaluate. First, EPA assumed that,

because this is a national model, the receptor species and receiving water occur together

(i.e., all receiving waters evaluated in the wildlife module are habitat for the receptor 

species even though that may not always be the case). In addition, due to the scope of 

the project, EPA considered a limited number of species for use as receptors. For the 

wildlife receptors, EPA chose minks and eagles due to their national distribution and 

data available to conduct the analysis [USGS, 2008]. By choosing a limited number of 

species, the wildlife module inherently excludes the impacts to critical assessment 

endpoints such as threatened and endangered species. EPA attempts to address this 

2

 EPA Office of Water Health and Ecological Criteria Division agrees that all the routes (e.g., food, sediment, and 

water) by which fish and shellfish are exposed to highly bioaccumulative pollutants may be important in

determining the accumulation in fish tissue and the subsequent transfer to human receptors. In addition, EPA agrees 

that distributions of BAFs/BCFs may be better than single BAFs/BCFs because they account for changes in

bioaccumulation/bioconcentration rates at different water concentrations. EPA is working to develop BAF/BCF

distributions for several pollutants to better represent the bioaccumulation in aquatic organisms.

D-5 
Appendix D—Wildlife Module Methodology

limitation in the impact assessment by presenting a proximity analysis of steam electric

power plants to habitats of threatened and endangered species (see Section 3.4.5 of this 

report) and an evaluation of the ecological risk to aquatic organisms and avian receptors 

from selenium contamination (see Section 5.2 of this report). 

 Wildlife Receptor Diet. To provide an environmentally protective estimate of dietary 

pollutant exposure, the wildlife module assumes that the diet of adult minks and bald 

eagles consists entirely of fish inhabiting the immediate receiving waters. EPA believes 

this assumption is reasonable based on the following two factors: 1) It is possible that 

in some habitats the dietary composition for both minks and eagles consists largely of 

fish and EPA aims to be protective of wildlife across all habitats. For example, studies 

have shown dietary composition as high as 75 and 85 percent fish for bald eagles and

minks, respectively [U.S. EPA, 1993]. In addition, it is likely that the other organisms

consumed by minks and eagles are also contaminated with the pollutants of concern

and are unaccounted for in the model; and 2) With respect to home ranges, the case 

study water quality modeling results (see Section 8) demonstrate that pollutants

discharged from steam electric power plants can continue to occur at elevated levels

downstream from the immediate receiving waters, contaminating fish outside of 

immediate receiving waters and resulting in additional potential for pollutant exposure 

among piscivorous wildlife. Overall, however, this assumption likely results in a 

potential overestimation of exposure to the modeled species. 

 Bioavailability and Speciation of Pollutants. The IRW model assumes that all forms 

of a pollutant are equally bioavailable to ecological receptors. Therefore, data inputs 

for the wildlife module include total pollutant concentration in the water column (i.e., 

dissolved plus particles sorbed to suspended sediment) or sediment concentration for 

all pollutants analyzed, except where noted. In addition, some pollutant forms are more

toxic to organisms, such as various forms of arsenic. While different forms of arsenic

exist in the water column, it is not possible to determine the percentages of each due to 

the complexities of the chemistry of a particular waterbody. Because of bioavailability 

and pollutant speciation assumptions made for the wildlife impact assessment, the 

impact to receptors may be over- or underestimated. 

 Indirect Ecological Effects. The wildlife module does not consider indirect ecological 

effects, such as depletion of food sources. Such indirect effects are difficult to assess 

and are thought to have minimal impact on some wildlife species because the impacted 

receiving water is only a small portion of the species’ habitat. In addition, many species 

will move into other areas in search of prey if food sources in their current habitat 

decline.

 Full Mixing Effects for Receiving Water. The water quality module assumes that the 

receiving waterbody is fully mixed. In reality, the water in lakes might stratify, 

especially if they are deep enough. Chemical speciation, mostly based on pH, varies by 

strata; for example, if the hypolimnion (i.e., lowest stratum of a lake) has a much lower

pH than the epilimnion (i.e., upper stratum), the concentration or speciation of many 

pollutants may vary between the two layers. Therefore, bottom-dwelling organisms 

would be exposed to different species and concentrations of pollutants. Due to the

complexity of these relationships and necessity for site-specific data, none of the impact 

analyses considered stratification of receiving waters. The result of this limitation on

the wildlife module outputs is unknown. 

D-6 
Appendix D—Wildlife Module Methodology

 Multiple Pollutant Exposures. According to EPA’s Steam Electric Power Generating 

Point Source Category: Final Detailed Study Report [U.S. EPA, 2009b], receptors will 

be exposed to multiple constituents simultaneously. However, the wildlife module 

examines the impact of individual pollutants to receptors and does not take into account 

how the interaction of multiple pollutants impacts the receptors. For example, EPA did 

not consider the impact of mercury on the uptake or toxicity of selenium. There is 

evidence in the literature that these two compounds interact with each other in the 

environment and may decrease the level of impact of each pollutant on a receptor;

conversely, the interaction of other pollutants may increase the impact to a receptor. 

However, because benchmarks are based on the toxicity of individual chemicals, and 

the relationships between chemicals are complex, it is beyond the scope of this analysis 

to include the effects of multiple pollutant interactions on receptors.

 Ecological Benchmarks. EPA used ecological benchmarks as described above to 

determine impacts to aquatic organisms from direct contact with contaminated 

sediment. The benchmarks represent threshold effect levels TELs. If an organism

ingests chemical concentration above the TEL, some effect (or response) will be 

produced. If the concentration ingested is below the TEL, no effect (or response) will 

occur. The TEL represents the concentration of a chemical that would result in “no 

effect,” therefore the results presented in EA report are a more environmentally

protective impact estimate [USGS, 2008]. 

D-7 
Appendix E—Human Health Module Methodology

APPENDIX E 

HUMAN HEALTH MODULE METHODOLOGY 

This appendix presents the model equations, input variables, benchmarks, and 

methodology limitations/assumptions for the immediate receiving water (IRW) model human 

health module. Human health impacts include the following receptor groups: 

 Child cohorts (recreational) that consume fish exposed to pollutants as a result of 

discharges from steam electric power plants. 

 Child cohorts (subsistence) that consume fish exposed to pollutants as a result of 

discharges from steam electric power plants. 

 Adult cohorts (recreational) that consume fish exposed to pollutants as a result of 

discharges from steam electric power plants. 

 Adult cohorts (subsistence) that consume fish exposed to pollutants as a result of

discharges from steam electric power plants. 

In addition to the national-scale cohorts evaluated as part of the environmental assessment 

(EA), EPA also estimated annual-average daily dose of pollutants for human receptors based on 

race and Hispanic origin as an environmental justice analysis.

EPA estimated pollutant concentrations in fish tissue using the IRW model wildlife module 

(see Appendix D). The human health module uses these concentrations as inputs. 

Model input requirements for the equations presented in Appendix E can be divided into 

five major categories: 1) input variable described by another equation; 2) site-specific input

variable; 3) model assumption variable; 4) receptor cohort-specific variable; and 5) pollutantspecific variable. The following tables in Appendix E describe the input requirements and data 

sources used in the human health module: 

 Table E-1. Calculation of Consumption Ratio for Trophic Level 3 (FT3) and Trophic 

Level 4 (FT4) Fish.

 Table E-2. Model Assumption Input Variables for the Human Health Module.

 Table E-3. Receptor Cohort-Specific Input Variables for the Human Health Module.

 Table E-4. Environmental Justice Analysis: Receptor Cohort-Specific Consumption 

Rate by Race or Hispanic Origin for the Human Health Module. 

 Table E-5. Pollutant-Specific Input Variables in the Human Health Module. 

IRW Model: Human Health Module Equations 

EPA estimated the pollutant concentrations in fish fillets consumed by humans (i.e., dose) 

using an assumed consumption ratio of T3 and T4 fish and site-specific pollutant concentrations

in fish. For each cohort, EPA calculated the average daily dose (ADD) of the pollutant from eating 

fish and compared this ADD to non-cancer human health benchmarks (i.e., reference doses 

[RfDs]). The human health module expresses this comparison as a hazard quotient (HQ). An HQ 

of higher than one (i.e., pollutant dosage exceeds benchmark) indicates a potential non-cancer 

E-1 
	 	 	 	 	

Appendix E—Human Health Module Methodology

threat to the human cohort. EPA also calculated a lifetime average daily dose (LADD) and a 

corresponding lifetime excess cancer risk (LECR) for each cohort. This study used the 1-in-amillion cancer risk benchmark as an acceptable risk threshold when evaluating exposures

associated with fish consumption. 

EPA used the equations presented below to calculate the pollutant concentration in the fish 

fillet; the ADD for arsenic, cadmium, chromium (VI), copper, lead, mercury, nickel, selenium, 

thallium, and zinc; the associated non-cancer threat HQ; and the LADD and LECR values for 

arsenic.

EQUATION E-1 

Cfish_fillet = FT3 × CfishT3F + FT4 × CfishT4F

Where: 

Cfish_fillet = Average fish fillet concentration ingested by 

humans (milligrams per kilograms [mg/kg]) 

Output from Equation E-1 

CfishT3F = Concentration of contaminant in fish at 

trophic level 3 (mg/kg) 

Site-specific wildlife module 

output Equation D-2 and 

Equation D-3 

CfishT4F = Concentration of contaminant in fish at 

trophic level 4 (mg/kg) 

Site-specific wildlife module 

output Equation D-2 and 

Equation D-3 

FT3 = Fraction of trophic level 3 fish intake 

(unitless) 

Model assumption value of 

0.36 (see calculation below) 

FT4 = Fraction of trophic level 4 fish intake 

(unitless) 

Model assumption value of 

0.64 (see calculation below) 

To determine the fraction of T3 and T4 fish intake for human cohorts, EPA started with 

the data presented in the 2011 Emissions Factor Handbook, Table 10-74 [U.S. EPA, 2011b]. EPA 

then completed the following analysis: 

1. Assigned trophic levels to fish if not already listed in the table. 

2. Totaled the quantities of fish consumed by trophic level. 

3. Determined fraction of fish consumed at each trophic level.

Table E-1 documents the data and analysis performed. EPA chose to use the factors for

fish intake that corresponded to rivers and streams; this is the most common receiving water source 

in the IRW model. 

E-2 
 

 

 

 

 

 

 

 

 

 

Appendix E—Human Health Module Methodology

Table E-1. Calculation of Consumption Ratio for Trophic Level 3 (FT3) and Trophic Level 4 

(FT4) Fish

Species

Trophic 

Level 

Ice Fishing Lakes and Ponds Rivers and Streams

Count of 

Fish 

Consumed 

Mass 

Consumed

(kg)

Count of 

Fish 

Consumed 

Mass 

Consumed

(kg)

Count of 

Fish 

Consumed

Mass 

Consumed

(kg)

Landlocked salmon 4 832 290 928 340 305 120 

Atlantic salmon 4 3 1.1 33 9.9 17 11

Togue (Lake trout) 4 483 200 459 160 33 2.7 

Brook trout 4 1,309 100 3,294 210 10,185 420 

Brown trout 4 275 54 375 56 338 23

Yellow perch 3 235 9.1 1,649 52 188 7.4

White perch 3 2,544 160 6,540 380 3,013 180 

Bass (Smallmouth and 

largemouth)

4 474 120 73 5.9 787 130 

Pickerel 3 1,091 180 553 91 303 45

Lake whitefish 3 111 20 558 13 55 2.7

Hornpout (Catfish and 

bullheads) 

3 47 8.2 1,291 100 180 7.8 

Bottom fish (Suckers,

carp and sturgeon) 

3 50 81 62 22 100 6.7

Chub 3 0 0 252 35 219 130 

Smelt 3 7,808 150 428 4.9 4,269 37

Other 4 201 210 90 110 54 45

 TOTALS 15,463 1,583 16,587 1,590 20,046 1,168 

Totals by Trophic Level

T3 Total 11,886 608 11,333 698 8,327 417 

T4 Total 3376 765.1 5162 781.8 11665 751.7 

Calculation of Factors by Trophic Level

T3 Factor 0.77 0.38 0.68 0.44 0.42 0.36

T4 Factor 0.22 0.48 0.31 0.49 0.58 0.64

Source: U.S. EPA, 2011b. 

Bold indicates factors selected for the human health model.

Equation E-2 calculates the ADD, which is the daily intake of the contaminant from fish 

ingestion. Based on a literature review (including EPA and Agency for Toxic Substances and 

Disease Registry (ATSDR) references), arsenic in fish is mostly in the organic form and not 

harmful to humans. The inorganic form of arsenic is harmful to humans; EPA’s 1997 document, 

Arsenic and Fish Consumption, reported the inorganic arsenic concentration in fish is between 0.4 

– 4 percent of the total arsenic accumulating in fish. EPA estimated the inorganic arsenic 

E-3 
		 	 	

	 	

 

Appendix E—Human Health Module Methodology

concentration in fish by assuming 4 percent of the total arsenic is inorganic. EPA used the

inorganic arsenic concentration in fish to determine human health impacts. The human health

model multiplies the Cfish_fillet concentration by 4 percent for arsenic (converting concentration 

from total to inorganic).

Equation E-3 calculates the LADD, based on the ADD. Arsenic is the only carcinogenic 

pollutant included in the EA. The model calculates the LADD of arsenic for each child cohort (six

recreational and six subsistence) and for each adult cohort (one recreational and one subsistence). 

EPA assumed the exposure durations (ED) for use in the LADD calculation are equal to the length 

of time in that cohort range. EPA selected an exposure frequency of 350 days per year, assuming 

residents take an average of two weeks of vacation away from their homes each year.

Equation E-4 calculates the non-cancer HQ, based on the ADD.

Equation E-5 calculates the LECR for inorganic arsenic, based on the LADD.

EQUATION E-2 

Cfish_fillet × CRfish × Ffish ADD	= 1,000 × BW

Where: 

ADD = Daily dose of pollutant from fish ingestion 

(mg/kg BW/day) 

Output from Equation E-2 

Cfish_fillet = Average fish fillet concentration ingested by 

humans (mg/kg) 

Output from Equation E-1 

CRfish = Consumption rate of fish (g ww/day) Receptor cohort-specific 

value (see Table E-3 and 

Table E-4) 

Ffish = Fraction of fish intake from contaminated 

source 

Model assumption value of 1 

1,000 = Conversion factor (grams per kilograms 

[g/kg]) 

Conversion factor 

BW = Body weight (kg) Receptor cohort-specific 

value (see Table E-3) 

E-4 
	 	 	 	 	

	 	

	 	

Appendix E—Human Health Module Methodology

EQUATION E-3 

ADD	× ED × EF 

LADD = AT × 365

Where: 

LADD = Lifetime average daily dose (mg/kg BW/day) Output from 

Equation E-3 

ADD = Daily dose of pollutant from fish ingestion 

(mg/kg BW/day) 

Output from Equation E-2 

ED = Exposure duration for oral ingestion (yr) Receptor cohort-specific 

value (assumed value) 

(see Table E-3) 

EF = Exposure frequency (days/yr) Model assumption value of 

350 

AT = Averaging time (yr) Model assumption value of 70 

[U.S. EPA, 2011b] 

365 = Conversion factor (days/yr) 

EQUATION E-4 

HQ = ADD

RfD

Where: 

HQ = Hazard quotient Output from Equation E-4 

ADD = Daily dose of pollutant from fish ingestion 

(mg/kg BW/day) 

Output from Equation E-2 

RfD = Non-cancer reference dose (mg/kg BW/day) Pollutant-specific value 

(see Table E-5) 

EQUATION E-5 

LECR = LADD × CSF

Where: 

LECR = Lifetime excess cancer risk Output from Equation E-5 

LADD = Lifetime average daily dose (mg/kg BW/d) Output from 

Equation E-3 

CSF = Cancer slope factor (mg/kg BW/day)-1 Pollutant-specific value

(see Table E-5) 

E-5 
 

 

 

 

Appendix E—Human Health Module Methodology

IRW Model: Human Health Module Inputs and Benchmarks 

Table E-2. Model Assumption Input Variables for the Human Health Module 

Input 

Variable Description 

Assumed 

Value Assumption Rationale/Data Source

FT3 Fraction of trophic level 3 fish intake 0.36 U.S. EPA, 2011b 

FT4 Fraction of trophic level 4 fish intake 0.64 U.S. EPA, 2011b 

Ffish Fraction of fish intake from

contaminated source 

1 EPA assumed that all fish consumed by the

receptor is from the contaminated surface water. 

EF Exposure frequency (days/yr) 350 EPA assumed that the fisher travels away from

home for 15 days per year and does not eat fish

from contaminated surface water during that

period. 

AT Averaging time (yr) 70 U.S. EPA, 2011b 

For the EA and benefits analyses,1 EPA focused on human exposure to contaminated fish 

for recreational and subsistence fishers. Recreational fishers are non-commercial, non-subsistence 

fishers and are more vulnerable to pollutant exposure by intake of contaminated fish from a 

specific waterbody compared to the general population. Subsistence fishers are individuals who 

consume fresh caught fish as a major food source. Intake rates for subsistence fishers are generally 

higher than for the general population, and subsistence fishers are more vulnerable to pollutant 

exposure by intake of contaminated fish from a specific waterbody compared to both recreational 

fishers and the general population. Because of the focus of human exposure to a subset of the

general population that more frequently consume local fish, EPA selected fish consumption rates 

from studies based on “consumer only” data. Consumer-only fish consumption rates are the 

average intake rates across only those individuals that consumed fish and shellfish during the 

survey time period. See the memorandum “Fish Consumption Rates Used in the Environmental 

Assessment Human Health Module” for further details [ERG, 2015g]. 

The human health module calculates annual-average daily doses of pollutants for

recreational and subsistence fishers and does not calculate the annual-average daily doses of 

pollutants for the general population. In its benefits analysis (see the Benefits and Cost Analysis), 

EPA only evaluates impacts to a subset of the population living near the immediate and 

downstream receiving waters. 

The EPA document, Methodology for Deriving Ambient Water Quality Criteria for the 

Protection of Human Health (Table 5-1) determined protective fish intake rates using the following

percentiles by fisher type: 1) general population and recreational fisher: 90th percentile of per capita

data and 2) subsistence fisher: 99th percentile of per capita data [U.S. EPA, 2000c]. The document

does not provide guidance on which percentiles to use for consumer-only fish intake rates. 

Therefore, EPA used best professional judgment and using the following percentiles by fisher type: 

1) recreational fisher: mean of consumer-only data and 2) subsistence fisher: 95th percentile of 

consumer-only data. 

1

 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) (Benefits and Cost Analysis). 

E-6 
 

 

 

Appendix E—Human Health Module Methodology

Table E-3. Receptor Cohort-Specific Input Variables for the Human Health Module 

Receptor Cohort a

Body Weight 

(kg) a

Consumption 

Rate (g/kg-day) b 

Consumption 

Rate (g/day) b

Exposure 

Duration (years) 

Child

Recreational 

Fisher 

1 to <2 years 11.4 1.60 18.2 1

2 to <3 years 13.8 1.60 22.1 1

3 to <6 years 18.6 1.30 24.2 3

6 to <11 years 31.8 1.10 35.0 5

11 to <16 years 56.8 0.660 37.5 5

16 to <21 years 71.6 0.660 47.3 5

Child

Subsistence 

Fisher 

1 to <2 years 11.4 4.90 55.9 1

2 to <3 years 13.8 4.90 67.6 1

3 to <6 years 18.6 3.60 67.0 3

6 to <11 years 31.8 2.90 92.2 5

11 to <16 years 56.8 1.70 96.6 5

16 to <21 years 71.6 1.70 121.7 5

Adult Recreational Fisher c

 80 0.665 53.2 49

Adult Subsistence Fisher c

 80 2.05 164 49

Sources: U.S. EPA, 2008a; U.S. EPA, 2011b. 

Acronyms: g/day (grams per day); g/kg-day (grams per kilogram body weight per day); kg (kilograms).

a – The child cohort age ranges correspond to the ranges provided in the 2008 Child-Specific Exposure Factor

Handbook (EFH) for body weights [U.S. EPA, 2008a].

b – EPA determined consumption rates for child cohorts using data from Table 10-1 (Recommend Per Capita and 

Consumer-Only Values for Fish Intake) for finfish consumption [U.S. EPA, 2011b]. EPA used consumer-only fish

consumption rates: mean values for recreational fishers and 95th percentile values for subsistence fishers. EPA 

converted the listed consumption rate (g/kg-day) to g/day by multiplying by mean body weight for each cohort as 

listed in U.S. EPA, 2008b [ERG, 2015g]. Fish intake rates provided in the reference [U.S. EPA, 2011b] are 

recommended for the consumer-only population; the selection of consumption rates for exposure assessment

purposes may vary depending on the exposure scenarios being evaluated.

c – Table 10-1[U.S. EPA, 2011b] presented multiple adult groups. EPA used the average fish consumption rate for

age groups “21 to <50 years” and “50+ years” to calculate a single adult cohort fish consumption rate. 

E-7 
Appendix E—Human H

Table E-4. Environmental Justice Analysis: Receptor Cohort-Specific Input Consumption Rate by Race or His

Human Health Module 

Receptor Race or Hispanic Origin 

CRfish, 

g/kg-day 

(All ages) a

Consumption Rate (CRfish), g/day, by Cohort 

1 to <2

years

2 to <3

years

3 to <6

years

6 to <11 

years

11 to <16 

years

Recreational

Non-Hispanic White 0.67 7.64 9.25 12.5 21.3 38.1 

Non-Hispanic Black 0.77 8.78 10.6 14.3 24.5 43.7 

Mexican-American 0.93 10.6 12.8 17.3 29.6 52.8 

Other Hispanic 0.82 9.35 11.3 15.3 26.1 46.6 

Other, including Multiple Races 0.96 10.9 13.2 17.9 30.5 54.5 

Subsistence 

Non-Hispanic White 1.9 21.7 26.2 35.3 60.4 108 

Non-Hispanic Black 2.1 23.9 29.0 39.1 66.8 119 

Mexican-American 2.8 31.9 38.6 52.1 89.0 159 

Other Hispanic c 2.7 30.8 37.3 50.2 85.9 153 

Other, including Multiple Races c 3.6 41.0 49.7 67.0 114 204 

Source: U.S. EPA, 2011b. Acronyms: CRfish (consumption rate); g/day (grams per day); g/kg-day (grams per kilogram body weight per day)

a – For recreational fishers, EPA used the mean, consumer-only fish consumption rate for finfish (excludes shellfish). For subsistence fishers, EP

percentile, consumer-only fish consumption rate for finfish (excludes shellfish). See Table 10-8 of U.S. EPA, 2011b. b – Consumption rates provided as single value by race and Hispanic origin (as g/kg-day). EPA multiplied these values by cohort-specific body 

E-3, to calculate a cohort-specific consumption rate in g/day. Numbers presented as three significant digits. c – Consumption rates for this race or Hispanic origin are less statistically reliable due to the comparatively smaller data set. 

E-8 
 

 

 

 

 

Appendix E—Human Health Module Methodology

Table E-5. Pollutant-Specific Benchmarks for the Human Health Module 

Pollutant in Human Health 

Impact Assessment 

RfD

 (mg/kg-day) 

CSF 

(mg/kg-day) -1 Notes a

Arsenic, inorganic 3.00E-04 1.50E+00 RfD and CSF for drinking water ingestion

Cadmium, total 1.00E-03 RfD for food consumption

Chromium (VI) 3.00E-03 RfD for drinking water ingestion

Copper 1.00E-02 Used the intermediate oral minimal risk

level (MRL) as the reference dose 

[ATSDR, 2010a] 

Lead, total None available 

Methylmercury 1.00E-04 RfD for fish consumption only

Nickel, total 2.00E-02 RfD for soluble salts; used for food

consumption 

Selenium, total 5.00E-03 RfD for food consumption

Thallium, total 1.00E-05 Used value cited in U.S. EPA, 2010a for 

thallium chloride as the reference dose; 

used for chronic oral exposure

Zinc, total 3.00E-01 RfD for food consumption

Acronyms: mg/kg-day (milligrams per kilogram body weight per day)

a – References include ATSDR, 2010a for copper; U.S. EPA, 2010a for thallium, and U.S. EPA, 2011c for all other 

pollutants. 

IRW Model: Human Health Module Limitations and Assumptions

The human health module limitations and assumptions include the following: 

 Additive Risks Across Pathways. The human health module does not consider additive 

risks across pathways. For example, the module assumes that the human population 

consuming the fish is not also ingesting contaminated drinking water. Exposures from 

fish consumption and drinking water are likely to occur over different time frames

(because of ground water travel) and may involve different receptors (e.g., a resident 

near a receiving water exposed to ground water contamination may not be a recreational 

fisher). Similarly, the module assumes that these populations are not coming in direct 

contact with contaminated surface water or sediment through recreation. Based on 

these assumptions, the model may underestimate total risk to human health from 

combustion wastewater. 

 Bioavailability and Speciation of Pollutants. The assumptions listed for the wildlife

module in Appendix D apply to pollutant concentrations modeled in fish and therefore 

affect the human health impact assessment. 

 Full Mixing Effects for Receiving Water. The assumptions listed for the wildlife 

module in Appendix D apply to pollutant concentrations modeled in fish and therefore 

affect the human health impact assessment. 

 Multiple Pollutant Exposures. According to previous analyses and literature reviewed

[U.S. EPA, 2009b], people who ingest fish from impacted waters will be exposed to 

E-9 
 

Appendix E—Human Health Module Methodology

multiple pollutants from the wastestreams evaluated. However, the module evaluates 

each pollutant individually. Such an approach does not account for interactive effects

that might be associated with exposures to mixtures. For example, some pollutants may 

have a higher risk when consumed together because of their interaction, whereas other 

pollutants may have less impact on human health when consumed together. Due to the 

complexity of these interactions and because benchmarks are based on the toxicity of

individual pollutants, it is not possible to examine these synergistic effects in this

analysis. Based on this limitation, risks of pollutants may be over- or underestimated. 

 Sources of Consumed Fish. The human health module assumes that all of the fish 

consumed by recreational and subsistence fishers is caught from the immediate 

receiving water, except during a two-week time period once per year. This assumption 

potentially overestimates the annual-average daily dose of the pollutants for these 

receptors, particularly for recreational fishers. The proportion of fish eaten by an

individual from local surface waters will vary (e.g., consumption rate estimates in

studies might include seafood purchased from a grocery store and not locally caught).2

 Human Exposure Factors. Individual exposure factors, such as ingestion rate, body 

weight, and exposure duration, are variable due to the physical characteristics, 

activities, and behavior of the individual. EPA used the most current data regarding 

exposure assumptions, and these values represent EPA’s current guidance on exposure 

data [U.S. EPA, 2008a; U.S. EPA, 2011b]. 

 Human Health Benchmarks. Uncertainties generally associated with human health 

benchmarks are discussed in detail in EPA’s Guidelines for Carcinogen Risk 

Assessment [U.S. EPA, 2005c] and Integrated Risk Information System (IRIS) [U.S. 

EPA, 2011c]. IRIS defines the RfD as “an estimate (with uncertainty spanning perhaps 

an order of magnitude) of a daily oral exposure to the human population (including 

sensitive subgroups) that is likely to be without an appreciable threat of deleterious 

effects during a lifetime.” RfDs are typically based on an assumption of lifetime 

exposure and may not be appropriate when applied to less-than-lifetime exposure 

situations [U.S. EPA, 2011c]. The cancer slope factor is an estimate of the human

cancer risk per milligram of chemical per kilogram body weight per day. To calculate 

the LADD used for the cancer risk assessment, EPA used the time in the cohort group 

(i.e., 1, 3, or 5 years depending on child cohort and 49 years for adult cohort) as the

ED. The ED is the length of time exposure occurs at the concentration. This analysis 

may over- or under-estimate the cancer risk if exposure is shorter than or longer than 

the ED, respectively. LADDs are appropriate when developing screening-level 

estimates; however, EPA recommends calculating that risk by integrating exposures or 

risks through all life stages (e.g., chronic exposure for a child may occur across cohorts) 

[U.S. EPA, 2011b].

2

 For the benefits analysis, EPA further defined the affected population (i.e., individuals potentially exposed to

steam electric power plant pollutants via consumption of contaminated fish) as recreational and subsistence fishers 

who fish reaches that are affected by steam electric power plant discharges (including immediate receiving waters 

and downstream reaches), as well as their household members. EPA estimated the number of people who are likely 

to fish affected reaches based on typical travel distances to a fishing site, presence of substitute fishing locations, 

data on the locations and status of fish consumption advisories for affected reaches, and information on anglers’ 

awareness and adherence to those advisories. See the Benefits and Cost Analysis. 

E-10 
 

Appendix F—Overview of Ecological Risk Modeling Setup and Outputs 

APPENDIX F 

OVERVIEW OF ECOLOGICAL RISK MODELING SETUP

AND OUTPUTS 

This appendix summarizes the inputs, outputs, and methodology limitations/assumptions

for the ecological risk modeling that EPA used to evaluate reproductive risks associated with

dietary exposure to selenium. EPA performed ecological risk modeling for two sets of water 

quality outputs: 

 Dissolved selenium concentrations in the immediate receiving waters of all modeled 

steam electric power plants, based on the outputs from the water quality module of the 

national-scale immediate receiving water (IRW) model (see Appendix C). 

 Dissolved selenium concentrations in the immediate receiving water and downstream

reaches of Black Creek, Mississippi, based on the outputs from the Black Creek case

study water quality model (see Appendix G). 

Model input requirements for the ecological risk model can be divided into four major 

categories: 1) dissolved selenium concentrations; 2) site-specific enrichment factors (EFs), which 

represent the ratio of the concentration of selenium at the base of the food web (i.e., particulates) 

to the dissolved concentration in water; 3) species-specific trophic transfer factors (TTFs), which 

describe subsequent bioaccumulation by higher trophic-level aquatic organisms such as fish and 

birds; and 4) exposure-response (ER) functions, which translate the modeled selenium 

concentrations in fish and birds into the associated reduction in reproductive success.

The ecological risk modeling methodology is described in Section 5.2 of the EA report. 

This modeling approach is consistent with the approach taken in developing the Draft Aquatic Life 

Ambient Water Quality Criterion for Selenium – Freshwater [U.S. EPA, 2014f] (referred to as the 

draft selenium criterion) and is based on the same data sets and studies for EF, TTFinvert, TTFfish, 

and ERfish. For this EA, EPA expanded the model to include data sets for TTFmallard and ERmallard. 

The following sections describe these inputs and their sources; summarize the ecological 

risk modeling results; and discuss the limitations and assumptions associated with this modeling.

Dissolved Selenium Concentrations

As described above, the dissolved selenium concentrations for the national-scale and case 

study ecological risk models are derived from the IRW water quality module and the Black Creek 

case study water quality model, respectively. Dissolved selenium concentrations used in the 

national-scale ecological risk model are provided in DCN SE04612.1

 Dissolved selenium

concentrations used in the case study ecological risk model are provided in DCN SE04615. Prior 

to use as inputs for the Black Creek case study ecological risk model, EPA calculated three-month 

rolling averages of the dissolved selenium concentration output from the Black Creek case study 

water quality model. This resulted in one average concentration for each calendar month 

1

 EPA removed identifying information, such as the immediate receiving water name and the steam electric power 

plant name, from this reference to prevent disclosure of confidential business information (CBI). 

F-1 
 

 

Appendix F—Overview of Ecological Risk Modeling Setup and Outputs 

throughout the entire modeling period after the assumed compliance date for the Morrow 

Generating Site (2019-2036). Use of a three-month rolling average avoided the calculation of 

significantly elevated reproductive risks in response to short-term (e.g., daily or weekly) 

fluctuations in the dissolved selenium concentration. 

Enrichment Factors

As discussed in Section 5.2 of the EA report, the EFs used in the ecological risk modeling 

effort are consistent with those used in developing the draft selenium criterion [U.S. EPA, 2014f]. 

This effort produced EF distributions for lentic systems (e.g., lakes, reservoirs, and ponds) and 

lotic systems (e.g., rivers, creeks, and streams). These distributions are well described by 

lognormal distributions with means (standard deviations) of 1,738 (2,499)2 for lentic systems and

692 (787) for lotic systems. These EF distributions are illustrated in Figure F-1 and Figure F-2. 

Trophic Transfer Factors 

As discussed in Section 5.2 of the EA report, the TTFs used to represent selenium

bioaccumulation in invertebrates and fish in the national-scale ecological risk model are also

consistent with those used in developing the draft selenium criterion [U.S. EPA, 2014f]. This

resulted in a TTFinvert distribution with a mean (standard deviation) of 2.84 (2.49)3

 and a TTFfish

distribution with a mean (standard deviation) of 1.6 (1.08). These TTF distributions are illustrated 

in Figure F-1. 

Based on a review of Ohlendorf [2003], EPA developed a TTF distribution for mallards. 

The resulting TTFmallard distribution is best described by a triangular distribution, with a likeliest 

value of 2.5, a minimum value of 0.4, and a maximum value of 4.1. This TTF distribution is

illustrated in Figure F-1.

For the Black Creek case study ecological risk model, EPA refined the TTFinvert and TTFfish 

datasets to include only invertebrate and fish species that are representative of those collected

during surveys of Black Creek and other nearby rivers and streams as part of EPA’s National 

Aquatic Resource Survey (NARS). This resulted in smaller distributions that are more likely to 

reflect bioaccumulation patterns within the species that actually inhabit Black Creek. These TTF 

distributions are illustrated in Figure F-2. 

Exposure Response Functions 

To estimate the risk of negative reproductive effects among fish, EPA used the same

extensively peer-reviewed ER function (i.e., curve) as was used in the draft selenium criterion

[U.S. EPA, 2014f]. This ER function is illustrated in Figure F-3. 

2

 The EF for a given waterbody is the ratio of the concentration of selenium at the base of the food web (i.e., 

particulates) to the dissolved concentration in water, multiplied by 1,000. A mean EF of 1,738 for lentic systems 

indicates 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. 

3

 The TTF for a given trophic level is the ratio of the concentration in the organism to the concentration in the 

consumed material or lower-trophic-level organism. A mean TTF of 2.84 for invertebrates indicates that, on

average, the concentration of selenium in the tissues of invertebrates is 2.84 times greater than the concentration in 

particulates consumed by invertebrates.

F-2 
Appendix F—Overview of Ecological Risk Modeling Setup and Outputs 

To develop the ER function for mallards, EPA fit a logistic curve to the combined, control 

normalized data from six different laboratory studies that 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 ER function is illustrated in Figure F-4. 

F-3 
Figure F-1. Input EF and TTF Distributions for National-Scale Ecological Risk Model – 

Baseline and Final Rule (Option D)
 

Appendix F—Overview of Ecological Risk Modeling Setup and Outputs 

F-4 
 

Figure F-2. Input EF, TTF, and Dissolved Selenium Distributions for Morrow Generating 

Site Immediate Receiving Water (Black Creek Case Study) Ecological Risk Model – 

Baseline and Final Rule (Option D) 

Appendix F—Overview of Ecological Risk Modeling Setup and Outputs 

F-5 
Proportion Fully N ormal 

-.2 0 .2 .4 .6 .8 1.0 1.2 1.4 1.6 1.8 

0 

.1 

.2 

.3 

.4 

.5 

.6 

.7 

.8 

.9 

1.0 

L og(mg Se/kg egg dw in fish) 

Figure F-3. Exposure-Response Function for Fish Reproductive Success 

1.1 

1.0 

Proportion Succesfully Hatched 

.9 

.8 

.7 

.6 

.5 

.4 

.3 

.2 

.1 

0 

-.5 0 .5 1.0 1.5 2.0 

L og (mg Se/kg egg) in mallard 

Figure F-4. Exposure-Response Function for Mallard Egg Hatchability 

Appendix F—Overview of Ecological Risk Modeling Setup and Outputs 

F-6 
Appendix F—Overview of Ecological Risk Modeling Setup and Outputs 

Ecological Risk Model Outputs 

Table F-1 and Table F-2 summarize the results of the national-scale ecological risk model 

for fish under baseline conditions and the final rule, respectively. 

Table F-3 and Table F-4 summarize the results of the national-scale ecological risk model 

for mallards under baseline conditions and the final rule, respectively. 

Table F-5 and Table F-6 summarize the results of the case study ecological risk model for 

birds and mallards, respectively, under baseline conditions. Under the final rule, none of the 

modeled stream segments resulted in a modeled risk of greater than 0.1 percent for either fish or 

mallards. 

F-7 
Appendix F—Overview of Ecological Risk Modeling Setup and Outputs 

Table F-1. Number (and Percentage) of Receiving Waters in National-Scale Ecological Risk

Model with Selenium-Driven Reproductive Effects in Fish – Baseline 

Percentile a Lake b River b Total b

1 Percent of Fish Population Experiencing Negative Reproductive Effects

10th: 0 (0%) 14 (7.7%) 14 (6.7%)

25th: 2 (7.7%) 17 (9.3%) 19 (9.1%)

Median: 4 (15%) 24 (13%) 28 (13%)

75th: 6 (23%) 32 (17%) 38 (18%)

90th: 8 (31%) 36 (20%) 44 (21%)

95th: 8 (31%) 42 (23%) 50 (24%)

10 Percent of Fish Population Experiencing Negative Reproductive Effects

10th: 0 (0%) 12 (6.6%) 12 (5.7%)

25th: 1 (3.8%) 14 (7.7%) 15 (7.2%)

Median: 4 (15%) 20 (11%) 24 (11%)

75th: 6 (23%) 29 (16%) 35 (17%)

90th: 7 (27%) 35 (19%) 42 (20%)

95th: 8 (31%) 39 (21%) 47 (22%)

50 Percent of Fish Population Experiencing Negative Reproductive Effects

10th: 0 (0%) 10 (5.5%) 10 (4.8%)

25th: 0 (0%) 14 (7.7%) 14 (6.7%)

Median: 3 (12%) 17 (9.3%) 20 (9.6%)

75th: 5 (19%) 27 (15%) 32 (15%)

90th: 6 (23%) 34 (19%) 40 (19%)

95th: 8 (31%) 35 (19%) 43 (21%)

75 Percent of Fish Population Experiencing Negative Reproductive Effects

10th: 0 (0%) 10 (5.5%) 10 (4.8%)

25th: 0 (0%) 14 (7.7%) 14 (6.7%)

Median: 3 (12%) 17 (9.3%) 20 (9.6%)

75th: 5 (19%) 26 (14%) 31 (15%)

90th: 6 (23%) 31 (17%) 37 (18%)

95th: 7 (27%) 34 (19%) 41 (20%)

90 Percent of Fish Population Experiencing Negative Reproductive Effects

10th: 0 (0%) 9 (4.9%) 9 (4.3%)

25th: 0 (0%) 13 (7.1%) 13 (6.2%)

Median: 2 (7.7%) 17 (9.3%) 19 (9.1%)

75th: 5 (19%) 22 (12%) 27 (13%)

90th: 6 (23%) 29 (16%) 35 (17%)

95th: 6 (23%) 34 (19%) 40 (19%)

Notes: 

a – Percentile refers to the risk percentile. For example, values in the 90th percentile row indicate the numbers of

receiving waters whose selenium concentrations are high enough to result in a 10 percent probability of the indicated 

reproductive effect. 

b – The national-scale ecological risk model 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. 

F-8 
Appendix F—Overview of Ecological Risk Modeling Setup and Outputs 

Table F-2. Number (and Percentage) of Receiving Waters in National-Scale Ecological Risk

Model with Selenium-Driven Reproductive Effects in Fish – Final Rule (Option D) 

Percentile a Lake b River b Total b

1 Percent of Fish Population Experiencing Negative Reproductive Effects 

10th: 0 (0%) 3 (1.6%) 3 (1.4%)

25th: 0 (0%) 5 (2.7%) 5 (2.4%)

Median: 0 (0%) 11 (6%) 11 (5.3%)

75th: 0 (0%) 16 (8.7%) 16 (7.7%)

90th: 1 (3.8%) 21 (11%) 22 (11%)

95th: 1 (3.8%) 25 (14%) 26 (12%)

10 Percent of Fish Population Experiencing Negative Reproductive Effects 

10th: 0 (0%) 3 (1.6%) 3 (1.4%)

25th: 0 (0%) 3 (1.6%) 3 (1.4%)

Median: 0 (0%) 8 (4.4%) 8 (3.8%)

75th: 0 (0%) 15 (8.2%) 15 (7.2%)

90th: 0 (0%) 19 (10%) 19 (9.1%)

95th: 1 (3.8%) 23 (13%) 24 (11%)

50 Percent of Fish Population Experiencing Negative Reproductive Effects 

10th: 0 (0%) 3 (1.6%) 3 (1.4%)

25th: 0 (0%) 3 (1.6%) 3 (1.4%)

Median: 0 (0%) 6 (3.3%) 6 (2.9%)

75th: 0 (0%) 12 (6.6%) 12 (5.7%)

90th: 0 (0%) 19 (10%) 19 (9.1%)

95th: 0 (0%) 20 (11%) 20 (9.6%)

75 Percent of Fish Population Experiencing Negative Reproductive Effects 

10th: 0 (0%) 2 (1.1%) 2 (0.96%)

25th: 0 (0%) 3 (1.6%) 3 (1.4%)

Median: 0 (0%) 5 (2.7%) 5 (2.4%)

75th: 0 (0%) 9 (4.9%) 9 (4.3%)

90th: 0 (0%) 15 (8.2%) 15 (7.2%)

95th: 0 (0%) 19 (10%) 19 (9.1%)

90 Percent of Fish Population Experiencing Negative Reproductive Effects 

10th: 0 (0%) 2 (1.1%) 2 (0.96%)

25th: 0 (0%) 3 (1.6%) 3 (1.4%)

Median: 0 (0%) 4 (2.2%) 4 (1.9%)

75th: 0 (0%) 9 (4.9%) 9 (4.3%)

90th: 0 (0%) 15 (8.2%) 15 (7.2%)

95th: 0 (0%) 19 (10%) 19 (9.1%)

Notes: 

a – Percentile refers to the risk percentile. For example, values in the 90th percentile row indicate the numbers of

receiving waters whose selenium concentrations are high enough to result in a 10 percent probability of the indicated 

reproductive effect. 

b – The national-scale ecological risk model 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. 

F-9 
 

 

 

 

Appendix F—Overview of Ecological Risk Modeling Setup and Outputs 

Table F-3. Number (and Percentage) of Receiving Waters in National-Scale Ecological Risk

Model with Selenium-Driven Reproductive Effects in Mallards – Baseline 

Percentile a Lake b River b Total b

1 Percent of Mallard Population Experiencing Hatching Failure

10th: 3 (12%) 18 (9.8%) 21 (10%)

25th: 5 (19%) 26 (14%) 31 (15%)

Median: 6 (23%) 34 (19%) 40 (19%)

75th: 8 (31%) 38 (21%) 46 (22%)

90th: 9 (35%) 47 (26%) 56 (27%)

95th: 13 (50%) 52 (28%) 65 (31%)

10 Percent of Mallard Population Experiencing Hatching Failure

10th: 0 (0%) 14 (7.7%) 14 (6.7%)

25th: 3 (12%) 17 (9.3%) 20 (9.6%)

Median: 5 (19%) 26 (14%) 31 (15%)

75th: 6 (23%) 32 (17%) 38 (18%)

90th: 8 (31%) 36 (20%) 44 (21%)

95th: 8 (31%) 42 (23%) 50 (24%)

50 Percent of Mallard Population Experiencing Hatching Failure

10th: 0 (0%) 10 (5.5%) 10 (4.8%)

25th: 0 (0%) 13 (7.1%) 13 (6.2%)

Median: 2 (7.7%) 17 (9.3%) 19 (9.1%)

75th: 4 (15%) 22 (12%) 26 (12%)

90th: 6 (23%) 28 (15%) 34 (16%)

95th: 6 (23%) 34 (19%) 40 (19%)

75 Percent of Mallard Population Experiencing Hatching Failure

10th: 0 (0%) 7 (3.8%) 7 (3.3%)

25th: 0 (0%) 10 (5.5%) 10 (4.8%)

Median: 0 (0%) 14 (7.7%) 14 (6.7%)

75th: 3 (12%) 17 (9.3%) 20 (9.6%)

90th: 5 (19%) 22 (12%) 27 (13%)

95th: 6 (23%) 27 (15%) 33 (16%)

90 Percent of Mallard Population Experiencing Hatching Failure

10th: 0 (0%) 3 (1.6%) 3 (1.4%)

25th: 0 (0%) 8 (4.4%) 8 (3.8%)

Median: 0 (0%) 12 (6.6%) 12 (5.7%)

75th: 1 (3.8%) 14 (7.7%) 15 (7.2%)

90th: 4 (15%) 18 (9.8%) 22 (11%)

95th: 5 (19%) 22 (12%) 27 (13%)

Notes: 

a – Percentile refers to the risk percentile. For example, values in the 90th percentile row indicate the numbers of

receiving waters whose selenium concentrations are high enough to result in a 10 percent probability of the indicated 

reproductive effect. 

b – The national-scale ecological risk model 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. 

F-10 
 

 

 

 

Appendix F—Overview of Ecological Risk Modeling Setup and Outputs 

Table F-4. Number (and Percentage) of Receiving Waters in National-Scale Ecological Risk

Model with Selenium-Driven Reproductive Effects in Mallards – Final Rule (Option D) 

Percentile a Lake b River b Total b

1 Percent of Mallard Population Experiencing Hatching Failure

10th: 0 (0%) 7 (3.8%) 7 (3.3%)

25th: 0 (0%) 12 (6.6%) 12 (5.7%)

Median: 0 (0%) 19 (10%) 19 (9.1%)

75th: 0 (0%) 23 (13%) 23 (11%)

90th: 0 (0%) 26 (14%) 26 (12%)

95th: 2 (7.7%) 26 (14%) 28 (13%)

10 Percent of Mallard Population Experiencing Hatching Failure

10th: 0 (0%) 3 (1.6%) 3 (1.4%)

25th: 0 (0%) 6 (3.3%) 6 (2.9%)

Median: 0 (0%) 12 (6.6%) 12 (5.7%)

75th: 0 (0%) 17 (9.3%) 17 (8.1%)

90th: 0 (0%) 21 (11%) 21 (10%)

95th: 0 (0%) 25 (14%) 25 (12%)

50 Percent of Mallard Population Experiencing Hatching Failure

10th: 0 (0%) 3 (1.6%) 3 (1.4%)

25th: 0 (0%) 3 (1.6%) 3 (1.4%)

Median: 0 (0%) 5 (2.7%) 5 (2.4%)

75th: 0 (0%) 9 (4.9%) 9 (4.3%)

90th: 0 (0%) 14 (7.7%) 14 (6.7%)

95th: 0 (0%) 18 (9.8%) 18 (8.6%)

75 Percent of Mallard Population Experiencing Hatching Failure

10th: 0 (0%) 2 (1.1%) 2 (0.96%)

25th: 0 (0%) 3 (1.6%) 3 (1.4%)

Median: 0 (0%) 3 (1.6%) 3 (1.4%)

75th: 0 (0%) 6 (3.3%) 6 (2.9%)

90th: 0 (0%) 9 (4.9%) 9 (4.3%)

95th: 0 (0%) 13 (7.1%) 13 (6.2%)

90 Percent of Mallard Population Experiencing Hatching Failure

10th: 0 (0%) 1 (0.55%) 1 (0.48%)

25th: 0 (0%) 2 (1.1%) 2 (0.96%)

Median: 0 (0%) 3 (1.6%) 3 (1.4%)

75th: 0 (0%) 3 (1.6%) 3 (1.4%)

90th: 0 (0%) 6 (3.3%) 6 (2.9%)

95th: 0 (0%) 9 (4.9%) 9 (4.3%)

Notes: 

a – Percentile refers to the risk percentile. For example, values in the 90th percentile row indicate the numbers of

receiving waters whose selenium concentrations are high enough to result in a 10 percent probability of the indicated 

reproductive effect. 

b – The national-scale ecological risk model 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. 

F-11 
Appendix F— Overview of Ecological Risk M

Table F-5. Risk of Selenium-Driven Reproductive Effects in Fish Downstream from Morrow Generating 

Receiving Water (Black Creek Case Study) – Baseline 

Percentile a

Black Creek WASP Model Segment ID b,c

39 38 37 36 35 34 33 32 31 30 29 

10th: <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% 

25th: <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% 

Median: 0.381% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% 

75th: 83.0% 17.8% 18.9% 8.00% 6.25% 3.46% 5.70% 8.80% <0.1% <0.1% <0.1% 

90th: >99.9% 98.7% 98.3% 94.6% 93.4% 87.7% 95.2% 94.4% 40.8% 36.3% 20.5% 

95th: >99.9% >99.9% >99.9% >99.9% >99.9% 99.8% >99.9% >99.9% 94.2% 92.8% 80.6% 

26 25 24 23 22 21 20 19 18 17 16 

10th: <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% 

25th: <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% 

Median: <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% 

75th: 1.11% 0.226% 2.42% 2.39% 2.14% 1.82% 1.81% 2.41% 0.723% 0.330% 0.345% 

90th: 80.9% 57.1% 86.5% 87.8% 83.9% 80.1% 81.0% 84.1% 73.4% 66.5% 64.6% 

95th: 99.7% 97.8% 99.8% 99.7% 99.7% 99.5% 99.6% 99.7% 99.1% 98.9% 98.7% 

13 12 11 10 9 8 7 6 5 4 3 

10th: <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% 

25th: <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% 

Median: <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% 

75th: 0.237% 0.273% 0.266% 0.993% 0.509% 0.303% 0.312% 0.273% 0.313% 0.375% 0.375% 

90th: 57.9% 60.3% 59.2% 72.3% 66.7% 59.1% 59.7% 56.3% 58.4% 63.1% 63.1% 

95th: 97.6% 98.5% 97.9% 98.9% 97.8% 97.5% 97.8% 97.8% 97.4% 98.4% 98.4% 

Note: Percentages are rounded to three significant figures. a – Percentile refers to the risk percentile. For example, based on the values in the 75th percentile row for Segment 39, there is a 25 percenconcentrations in fish eggs/ovaries are high enough to cause negative reproductive effects in 83 percent of the exposed fish population inha

Black Creek. b – Segment 39 is the immediate receiving water for Morrow Generating Site. Segment 1 is farthest downstream from the immediate receiv

segments comprise a total of 95 miles of Black Creek.

c – >0 to 5 percent risk; 5 to 35 percent risk; 35 to 65 percent risk; 65 to 95 percent risk; >95 percent risk.

F-12 
Appendix F— Overview of Ecological Risk M

Table F-6. Risk of Selenium-Driven Reproductive Effects in Mallards Downstream from Morrow Generati

Receiving Water (Black Creek Case Study) – Baseline 

Percentile a

Black Creek WASP Model Segment ID b,c

39 38 37 36 35 34 33 32 31 30 29 

10th: <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% 

25th: 0.872% 0.268% 0.253% 0.153% 0.155% 0.139% 0.117% 0.167% <0.1% <0.1% <0.1% 

Median: 9.18% 3.46% 3.21% 2.33% 2.27% 1.90% 1.92% 2.33% 0.463% 0.451% 0.298% 

75th: 37.3% 19.4% 18.6% 15.0% 14.8% 12.6% 13.7% 14.6% 5.33% 4.81% 3.57% 

90th: 71.1% 49.5% 47.4% 41.4% 40.5% 38.3% 40.5% 41.6% 22.1% 21.2% 17.6% 95th: 86.1% 68.0% 66.7% 60.5% 58.6% 57.2% 59.7% 60.6% 38.4% 37.2% 33.2% 

26 25 24 23 22 21 20 19 18 17 16 

10th: <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% 

25th: <0.1% 0.11% 0.109% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% 

Median: 1.14% 1.66% 1.53% 1.51% 1.57% 1.12% 1.12% 1.55% 1.12% 0.911% 0.698% 

75th: 9.46% 11.5% 11.2% 11.5% 10.9% 10.0% 10.7% 10.9% 9.28% 7.76% 7.53% 

90th: 33.2% 35.3% 35.6% 36.0% 34.5% 32.9% 33.5% 33.9% 31.1% 27.2% 27.4% 95th: 53.1% 53.7% 54.7% 55.3% 53.5% 52.5% 51.2% 52.4% 50.2% 44.9% 44.9% 

13 12 11 10 9 8 7 6 5 4 3 

10th: <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% 

25th: <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% <0.1% 

Median: 0.698% 0.698% 0.698% 1.09% 0.986% 0.750% 0.750% 0.75% 0.789% 0.750% 0.898% 

75th: 7.20% 7.12% 6.63% 8.59% 7.89% 7.35% 7.42% 7.17% 7.21% 7.03% 7.65% 

90th: 25.5% 26.1% 25.4% 31.0% 26.8% 26.5% 26.0% 25.9% 26.9% 26.1% 27.0% 95th: 44.3% 44.4% 44.2% 48.6% 45.7% 44.3% 43.4% 43.6% 44.9% 43.6% 44.8% 

Note: Percentages are rounded to three significant figures. a – Percentile refers to the risk percentile. For example, based on the values in the 75th percentile row for Segment 39, there is a 25 percenconcentrations in mallard eggs are high enough to cause negative reproductive effects in 37.3 percent of the exposed mallard population inBlack Creek. b – Segment 39 is the immediate receiving water for Morrow Generating Site. Segment 1 is farthest downstream from the immediate receiv

segments comprise a total of 95 miles of Black Creek.

c – >0 to 5 percent risk; 5 to 35 percent risk; 35 to 65 percent risk; 65 to 95 percent risk; >95 percent risk. 

F-13 
 

Appendix F— Overview of Ecological Risk Modeling Setup and Outputs

Ecological Risk Model Methodology Limitations and Assumptions

The limitations and assumptions of the ecological risk modeling methodology include the 

following: 

 Water Quality Inputs. The assumptions listed for the IRW model water quality module 

in Appendix C apply to the dissolved selenium concentrations that support the nationalscale ecological risk model. The assumptions listed for the case study water quality 

model in Appendix G apply to the Black Creek case study ecological risk model. As

discussed in Section 8 of the EA report, the case study models do incorporate available 

data regarding background pollutant concentrations and pollutant loading contributions 

from non-steam-electric point sources. For the Black Creek case study, however, EPA 

did not identify sufficient STORET monitoring data to represent upstream pollutant 

contributions, and did not identify any upstream non-steam-electric point sources with 

loadings for the modeled pollutants. EPA therefore assumed pollutant concentrations

of zero within the water column at the upstream boundary of the modeling area. This 

results in a potential underestimation of dissolved selenium concentrations (and the 

associated risk of negative reproductive effects among fish and mallards) within the 

Black Creek modeling area. 

 Receptor Populations Evaluated. EPA assumed that the receptor species and receiving 

water occur together (i.e., all receiving waters evaluated in the national-scale and case

study ecological risk models are habitat for fish and mallards even though that may not

always be the case). This results in a potential overestimation of the number of 

immediate receiving waters whose elevated selenium concentrations are causing 

negative reproductive impacts among exposed fish and mallards. 

 Species Represented by Exposure-Response Functions. EPA used exposure-response 

functions that are based on vetted functions from the literature for brown trout 

(representative of fish) and mallard (representative of avian). Brown trout are amongst

the most sensitive fish species to selenium [U.S. EPA, 2014f]. EPA selected the mallard 

as the representative avian species, which may not reflect potential impacts to other 

species that consume primarily fish rather than invertebrates, and that may show 

differential sensitivity. The literature suggests that mallards are among the most

sensitive bird species to selenium [Chapman et al., 2009]. Therefore, use of these 

exposure-response functions results in an environmentally protective estimate of 

reproductive risk among the fish and avian species found at any given waterbody. 

 Multiple Pollutant Exposures. According to EPA’s Steam Electric Power Generating 

Point Source Category: Final Detailed Study Report [U.S. EPA, 2009b], receptors will 

be exposed to multiple constituents simultaneously. However, the ecological risk

model examines the impact of only selenium to receptors and does not take into account 

how the interaction of multiple pollutants impacts the receptors. For example, EPA did 

not consider the impact of mercury on the uptake or toxicity of selenium. There is 

evidence in the literature that these two compounds interact with each other in the 

environment and may decrease the level of impact of selenium on a receptor;4

conversely, the interaction of other pollutants may increase the impact to a receptor. It 

4

 In a notable but unexplained exception to this general rule, Heinz and Hoffman (1998) found that selenium and

mercury interact to create additive or synergistic toxic effects in mallard embryos. 

F-14 
Appendix F— Overview of Ecological Risk Modeling Setup and Outputs

is beyond the scope of this analysis to include the effects of multiple pollutant

interactions on receptors; however, the consideration of only selenium-driven impacts

in this analysis likely results in an underestimation of the overall negative reproductive 

impacts among fish and mallards resulting from exposure to the variety of pollutants in 

steam electric power plant wastewater discharges. 

 Composition of Fish and Mallard Diet. In this analysis, EPA assumed that mallard

diets consisted entirely of invertebrates, which potentially overestimates the dietary 

intake of selenium (because invertebrates tend to bioaccumulate selenium to a higher 

degree than submerged aquatic vegetation, another component of mallard diets). EPA 

also assumed that the diets of fish and mallards consisted entirely of aquatic organisms

that inhabit the modeled waterbodies. These assumptions result in an environmentally 

protective estimation of dietary selenium uptake if fish and mallards also consume

organisms from other waterbodies that are not contaminated with selenium. 

F-15 
Appendix G—Overview of Case Study Modeling Setup and Outputs 

APPENDIX G 

OVERVIEW OF CASE STUDY MODELING 

SETUP AND OUTPUTS 

This appendix presents additional information about the model development, input

variables, pollutant benchmarks, and methodology limitations/assumptions applicable to case 

study modeling performed using EPA’s Water Quality Analysis Simulation Program (WASP). 

This appendix also presents additional information regarding the site-specific design, site-specific 

input parameters (e.g., background pollutant concentrations, U.S. Geological Survey (USGS) time

series flow data, steam electric power plant pollutant loadings), and model settings (e.g., solids 

constants and sediment transport parameters) for each of the WASP models. For additional 

documentation regarding the selection of case study locations, development of the case study 

models, and outputs produced by the WASP models, 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 Industry Environmental Assessment” (DCN SE05570) (Case 

Study Water Quality Modeling Memorandum). 

CASE STUDY MODEL SETUP – ALL MODELS

This section of the appendix focuses on the development of the case study models, 

including the limitations/assumptions, input parameters, and methodologies that are applicable to 

all of the case study models. 

Model Development & Input Variables 

WASP Model Default Parameters. The Simple Toxicant module within WASP groups 

reaches of the modeled receiving water (i.e., the individual COMIDs as defined in NHDPlus

Version 1) into segments based on the hydrologic characteristics. The WASP model calculates the 

water column and benthic pollutant concentrations of the eight modeled pollutants using userdefined parameters and default assumption values. Table G-1 presents the WASP default

parameters and values that EPA used for all the case study models. 

Benthic Sediment Depth. All of the case study models are designed with two layers of 

segments representing the upper and lower benthic sediment layer, except for the Lake Sinclair

model where benthic layers are not simulated. For each model, the depth of the upper and lower 

benthic sediment layers are 0.03m and 0.25m, respectively. 

Pollutant Partition Coefficients & Densities. The Simple Toxicant module within WASP 

applies pollutant-specific partition coefficients to estimate the degree to which pollutants in the

water column will adsorb to benthic sediments and suspended solids. EPA selected the suspended 

sediment-water (Kdsw) partition coefficient for each of the eight modeled pollutants. Refer to Table 

C-4 in Appendix C of the Environmental Assessment for the Effluent Limitations Guidelines and

Standards for the Steam Electric Power Generating Point Source Category (EPA-861-R-15-006), 

hereafter referred to as the “EA Report,” for the suspended sediment water partition coefficients 

used for each modeled pollutant. Additionally, the Simple Toxicant module requires the user to

input a density for each modeled pollutant. Table G-2 presents the density values EPA used for 

each pollutant, based on published values from literature.

G-1 
 

 

 

 

 

 

 

 

 

 

 

Appendix G—Overview of Case Study Modeling Setup and Outputs

Table G-1. Solids Constants and Sediment Transport Parameters – All Models

Input Parameter Description Value Used Units

Silts and Fines Density WASP default density for silts/fines 2.650 g/cm3

Sand Density WASP default density for sand 2.650 g/cm3

Organic Solids Density WASP default density for organic solids 1.350 g/cm3

fcritcoh

Critical cohesive sediment fraction; above which 

sediment bed acts cohesively 0.200 (fraction) 

vRCohMult Shear stress multiplier for cohesive resuspension 2.500 g/m2

/sec

vRCohExp Shear stress exponent for cohesive resuspension 2.500 (unitless) 

vRNonCohEx Shear stress exponent for noncohesive resuspension 1.500 (unitless) 

D50_silt Particle diameter for silt 0.025 mm 

D50_sand Particle diameter for sand 0.250 mm 

D50_POM Particle diameter for organic solids 0.012 mm

vDexp_silt Shear stress exponent for silt deposition 1.000 (unitless) 

vD_exp_san Shear stress exponent for sand deposition 1.000 (unitless) 

vD_exp_POM Shear stress exponent for organic solids deposition 1.000 (unitless) 

TAUcritcoh a Critical shear stress for erosion of cohesive bed 3.500 or 5.000 N/m2

TAU_cD1_si b

Lower critical shear stress for silt; below which

deposition is maximum 3.500 or 5.000 N/m2

TAU_cD2_si b

Upper critical shear stress for sand; above which 

deposition is zero 7.000 or 10.000 N/m2

TAU_cD1_sa

Lower critical shear stress for sand; below which

deposition is maximum 4.000 N/m2

TAU_cD2_sa

Upper critical shear stress for sand; above which 

deposition is zero 5.000 N/m2

TAU_cD1_PO b

Lower critical shear stress for organic solids; below 

which deposition is maximum 3.500 or 5.000 N/m2

TAU_cD2_PO b

Upper critical shear stress for organic solids; above

which deposition is zero 7.000 or 10.000 N/m2

Acronyms: g/cm3 (grams per cubic centimeter); g/m2/sec (grams per square meter per second); mm (millimeter); 

N/m2

 (newton per square meter)

a – The value of this input parameter varies the critical sheer stress values for sediment transport. The value 

specified for this parameter, which can be set between 0.5 and 8.0 N/m2

, was determined as a result of calibration 

performed for each case study model. EPA determined that for all WASP models except for the Mississippi River 

site, a value of 3.5 N/m2

 was reasonable and resulted in modeled solids output comparable to the actual monitoring

data results. For the Mississippi River WASP model, a value of 5.0 N/m2 was deemed more appropriate based on 

model calibration. 

b – WASP uses default values for these input parameters based on the value specified for ‘TAUcritcoh.’

G-2 
 

 

Appendix G—Overview of Case Study Modeling Setup and Outputs

Table G-2. Pollutant Densities - All Models

Pollutant Density

(g/cm3

)

Arsenic 5.75

Cadmium 8.70

Copper 8.96

Lead 11.34 

Nickel 8.91 

Selenium 4.80

Thallium 11.85 

Zinc 7.14

Organic Solids, Sands, and Silts/Fines. To define initial concentrations for the organic 

solids, sands, and silts/fines parameters, EPA used total organic carbon (TOC) and total suspended

solids (TSS) concentrations derived from STORET monitoring data collected within the WASP 

modeling area. EPA calculated the concentrations of organic solids (OS), sands, and silts/fines 

using Equation G-1, Error! Reference source not found. Equation G-2, and Equation G-3 below. 

G-3 
 

 

 

Appendix G—Overview of Case Study Modeling Setup and Outputs

EQUATION G-1 

Cos = TOC	× fos

EQUATION G-2 

Csand = ሺTSS	‐	Cosሻ	× fsand

EQUATION G-3 

Csf = ሺTSS	‐	Cosሻ	× fsf

Where: 

Cos = Initial concentration of organic solids 

(mg/L) 

Output from Equation G-1

Csand = Initial concentration of sands (mg/L) Output from Equation G-2

Csf = Initial concentration of silts/fines (mg/L) Output from Equation G-3

TOC = Total organic carbon (mg/L) Site-specific value derived from

STORET monitoring data 

TSS = Total suspended solids (mg/L) Site-specific value derived from

STORET monitoring data 

fos = Fraction of total organic carbon that is 

organic solids (unitless) 

Model assumption value of 0.5 

fsand = Fraction of total suspended solids 

composed of sands 

Model assumption value of 0.05 

fsf = Fraction of total suspended solids 

composed of silts/fines

Model assumption value of 0.95 

Calibration of Sediment Transport Parameters. The concentrations of the modeled 

pollutants are influenced by sediment transport; therefore, EPA calibrated specific sediment 

transport parameters where possible. EPA calibrated the model outputs by manipulating one 

sediment transport parameter, ‘Critical Shear Stress for Erosion of Cohesive Bed’ (defined as 

‘TAUcritcoh’ in WASP), until the modeled TSS concentrations in the water column segments 

(represented by the sum of organic matter, sands, and silts/fines) closely matched the available 

TSS STORET monitoring data. The ‘Critical Shear Stress for Erosion of Cohesive Bed’ value used 

for each case study model is presented in the case study model-specific sections of this appendix.1

Calibration of Initial Concentration of Sediment in Benthic Segments. In some cases, the 

initial concentration of sediment in the benthic segments was adjusted during the calibration

process, as very large spikes in total solids concentration were sometimes observed during high 

1

 If EPA observed a significant difference between the modeled TSS concentrations and actual observed TSS 

concentrations, the sediment transport calibration values were given further review; however, those differences, 

when they occurred, were often attributable to the pollutant contributions flowing in from the model boundaries. 

G-4 
 

 

 

Appendix G—Overview of Case Study Modeling Setup and Outputs

flow events near the beginning of the simulation period. These large spikes were an indication that 

too much sediment was present in the modeled benthic segments at the start of the simulation,

indicating that calibration of the sediment concentration was necessary. Where monitored pollutant 

data were available, the total concentration of pollutant was plotted alongside the actual observed 

results from STORET monitoring data as another check in the calibration process. The initial 

concentrations of the organic solids, sands, and silts/fines in the benthic sediment used for each 

case study model are presented in the case study model-specific sections of this appendix. 

Steam Electric Power Plant Pollutant Loadings. EPA calculated pollutant loadings from 

the evaluated wastestreams as part of its engineering analysis (see Section 10 of the Technical 

Development Document for the Effluent Limitations Guidelines and Standards for the Steam 

Electric Power Generating Point Source Category (TDD) [EPA 821-R-15-007]). The baseline and 

regulatory option pollutant loadings used for each case study are presented in the case study modelspecific sections of this appendix. The Case Study Water Quality Modeling Memorandum further 

describes the methodology for calculating and incorporating steam electric power plant loadings 

data into the WASP models.

Non-Steam Electric Loadings. EPA incorporated pollutant loadings and/or concentrations 

data from Discharge Monitoring Reports (DMR), the Toxics Release Inventory (TRI), and EPA’s

STORET monitoring database to represent pollutant contributions from non-steam-electric point 

sources and nonpoint sources that may impact the case study water quality model. EPA 

incorporated pollutant loadings data from DMR and TRI data for each of the eight pollutants to

account for the pollutant contributions within the modeling area. STORET monitoring data were 

incorporated to account for contributions upstream of the modeling boundaries and for use in 

calibration. For the modeled pollutants (not including TOC and TSS), EPA converted the average

concentration or annual load to a daily mass loading.2

 Each case study model-specific section of 

this appendix presents the non-steam electric pollutant loadings incorporated into the model. The

Case Study Water Quality Modeling Memorandum further describes the methodology for 

collecting, assessing, and incorporating DMR and TRI pollutant loadings data into the WASP 

models. 

WASP Output Analysis Methodology 

The WASP models generate output data for pollutant concentration (total, dissolved, and 

sorbed) in each water column and benthic segment on a daily output time step. For the purposes 

of assessing the baseline impacts and the improvements under the final rule, EPA used the baseline 

and regulatory option WASP model outputs from the period after the steam electric power plant’s

assumed compliance date.3

 Using this period of water quality output ensures that the baseline and 

regulatory option analyses are both based on the same underlying flow data, meaning that the 

differences in modeled pollutant concentrations are solely attributable to the pollutant loading

reductions under the final rule. 

2

 EPA converted the average concentration calculated from the STORET monitoring data to a mass loading using 

the average annual flow rate for the stream reach represented by the monitoring station(s). 

3

 For case studies with pollutant loadings from multiple steam electric power plants (Ohio River and Mississippi

River), EPA used the later of the two assumed compliance dates. 

G-5 
 

 

 

Appendix G—Overview of Case Study Modeling Setup and Outputs

Water Quality Assessment. The WASP models generate daily pollutant concentrations in

the water column of all water column segments within the models. EPA quantified the water

quality impacts as the percent of days where the water column concentration, total or dissolved, 

exceed the National Recommended Water Quality Criteria (NRWQC) or Maximum Contaminant 

Level (MCL) benchmarks listed in Table C-7 in Appendix C. EPA also quantified the total river

miles exhibiting exceedances and the distance downstream of the steam electric power plant(s) 

that showed any exceedances of these benchmarks at any point during the modeling period.

Wildlife Assessment. The WASP models generate daily pollutant concentrations in the 

upper and lower benthic sediment segments within the models. EPA quantified the impact to 

benthic organisms as the percent of days where the total sediment concentration in the upper 

benthic segments exceed the Chemical Stressor Concentration Limit (CSCL) benchmarks for 

sediment biota listed in Table D-1 in Appendix D. EPA also quantified the total number of river 

miles exhibiting exceedances and the distance downstream of the steam electric power plant(s) 

that showed any exceedances of these CSCLs at any point during the modeling period.

EPA calculated the annual average pollutant concentrations in the water column (averaged 

over the entire modeling period) of all water column segments. To determine negative impacts to 

piscivorous wildlife (i.e., wildlife that consume fish) from the ingestion of contaminated fish, EPA 

compared the calculated annual average water column concentrations to “threshold” water 

concentrations that would result in exceedances of no effect hazard concentrations (NEHCs) for 

minks and eagles developed by the USGS.4

 Since minks are estimated to have a four-year life 

expectancy, EPA completed this analysis using four-year rolling average water concentration

values. EPA quantified the total river miles with NEHC exceedances and how far downstream of 

the plant these impacts are observed.

Refer to Appendix F regarding the methodology for performing ecological risk modeling 

using water quality outputs from the Black Creek WASP model.

Human Health Assessment. EPA calculated the annual average pollutant concentrations in

the water column (averaged over the entire modeling period) of all water column segments. To 

determine negative impacts to human receptors from the ingestion of contaminated fish, EPA 

compared the calculated annual average concentrations to “threshold” water concentrations that 

would trigger exceedances of either the non-cancer reference dose or the 1-in-a-million lifetime 

excess cancer risk (LECR) benchmark for selected cohorts.5

 EPA quantified the total river miles

with LECR benchmark exceedances and how far downstream of the plant these impacts are 

observed. 

Case Study Modeling Methodology Limitations and Assumptions

The case study modeling methodology shares the following limitations and assumptions 

with the IRW model water quality module (see Appendix C for further discussion): 

4

 Refer to the memorandum “Downstream EA Modeling Methodology and Supporting Documentation” (DCN

SE04455) for the water column concentrations that result in exceedances of the NEHC benchmarks. 

5

 Refer to the memorandum “Downstream EA Modeling Methodology and Supporting Documentation” (DCN

SE04455) for the water column concentrations that result in exceedances of the non-cancer reference doses or LECR 

benchmark for selected cohorts. 

G-6 
Appendix G—Overview of Case Study Modeling Setup and Outputs 

 The models are based on annual-average pollutant loadings and normalized flow rates 

from the steam electric power plants. Unlike the water quality module, however, the 

case study models do account for temporal variability in the receiving water flow 

rates.

 The models do not take into consideration pollutant speciation within the receiving 

stream. 

 The models assume that pollutants dissolved or sorbed within the water column and 

bottom sediments can be described by a single partition coefficient. 

 The pollutant loadings included in the models are not representative of the total 

pollutant loadings from steam electric power plants, as there are several waste 

streams that are not included in the analysis (e.g., stormwater runoff, metal cleaning 

wastes, coal pile runoff). Unlike the water quality module, however, the case study 

models do take into account ambient background pollutant concentrations and 

contributions from other point and nonpoint sources. 

In addition to the above, the case study modeling methodology incorporates the following 

limitations and assumptions: 

 The models assume that pollutant contributions from background sources and other 

point and nonpoint sources are constant over the entire modeling period. This 

assumption reduces the variability in modeled pollutant concentrations over time and 

results in a potential underestimation of periods with elevated pollutant 

concentrations above benchmark levels (under both baseline conditions and the 

regulatory options). 

 The models incorporate DMR and TRI loadings data to represent other point source 

dischargers. In DMR, facilities are required to report loadings only for the pollutants 

that are listed in the facility’s National Pollutant Discharge Elimination System

(NPDES) permit. This limitation results in a potential underestimation of the pollutant 

loadings from point sources that discharge a modeled pollutant but are not required to

report wastewater monitoring data as part of their NPDES permit. TRI collects 

facility-reported estimates of wastewater loadings data for both direct and indirect 

dischargers. The TRI releases database does not include loadings from facilities with 

total annual chemical releases of less than 500 lbs and incorporates assumptions 

regarding plants with annual releases of less than 1,000 lbs. This limitation results in 

a potential underestimation of pollutant loadings from smaller point sources. 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 thresholds; 

releases reported are based on estimates, not measurements; certain chemicals are 

reported as a class, not as individual compounds; facilities are identified by NAICS 

code, not point source category; and TRI requires facilities to report only certain 

chemicals, therefore all pollutants discharged from a facility may not be captured. 

The effect of these limitations on the case study model outputs is unknown. 

 In cases where STORET monitoring data results are reported as below the 

quantitation limit, EPA assumed the result was equal to one-half the low-level 

analytical method detection limit for purposes of averaging the monitoring data 

results. The effect of this assumption on the case study model outputs is unknown and 

G-7 
Appendix G—Overview of Case Study Modeling Setup and Outputs 

depends on whether actual background concentrations at the time and location of 

monitoring were higher or lower than the assumed concentration. 

 The models assume that stream flow conditions throughout the modeling period can 

be represented by selected ranges of historical stream flow data. The effect of this 

assumption on the case study model outputs is unknown and depends on whether 

actual stream flow rates are higher or lower than those used in the models. 

 For each steam electric power plant, EPA assumed a plant-specific date (derived from

the plant’s permitting cycle) upon which the plant would achieve compliance with the 

final rule. The selection of the assumed compliance date influences the timing of

when the modeled baseline impacts and improvements under the final rule would 

occur, but does not affect the magnitude of these impacts and improvements. 

 By incorporating wildlife, human health, and ecological risk analyses, the models 

incorporate all of the limitations and assumptions described for those analyses (see 

Appendices D, E, and F). 

G-8 
Appendix G—Overview of Case Study Modeling Setup and Outputs 

CASE STUDY MODEL SETUPS AND OUTPUTS – BLACK CREEK, MS 

This section presents information regarding the site-specific design, site-specific input 

parameters (e.g., background pollutant concentrations, USGS time series flow data), model

settings (e.g., sediment transport parameters), and case study modeling results for the Black Creek 

case study model. 

Model Development & Input Variables 

WASP Model Design. The Black Creek WASP model starts at the R.D. Morrow, Sr.

(Morrow) Generating Site’s immediate receiving water (COMID 18104316), as defined by the 

IRW model, and extends approximately 95 miles downstream to just upstream of where Big Black 

Creek converges with Red Creek (COMID 18106998). 

The Black Creek WASP model consists of 174 modeled segments. Segment IDs 1-39 

represent the surface water of Black Creek with Segment ID 1 being the most downstream segment

and Segment ID 39 being the most upstream segment and immediate receiving water. The 

remaining model segments represent tributary surface waters (Segment IDs 40-58), the upper 

benthic layers (Segment IDs 59-116), and the lower benthic layers (Segment IDs 117-174). Figure 

G-1 illustrates the segmentation of the Black Creek WASP model.

The modeling period starts in 1982 (the year of the last revision to the steam electric ELGs)

and extends through 2036, covering a period 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. 

Incorporation of Flow Data. EPA used USGS stream flow data from one USGS stream

gage to represent inflow at the upstream end of the modeling area of the Black Creek WASP 

model. EPA scaled the Black Creek stream gage data from Gage ID 02479130 to account for the 

difference in drainage area between the actual gage location and the point where the contributing

flows enter the modeling area.

EPA used USGS stream flow data from one USGS stream gage to represent inflow from 

Cypress Creek, a significant tributary to the Black Creek WASP modeling area. EPA scaled the 

Cypress Creek stream gage data from Gage ID 0247155 to account for the difference in drainage 

area between the actual gage location and the point where the contributing flows enter the

modeling area. 

Figure G-1 illustrates the two stream flow gages from which EPA incorporated USGS 

stream flow data. Table G-3 presents additional information about the two stream gages and the 

time period covered in the stream flow data record at each. Table G-4 presents how EPA

incorporated the stream flow data from these stream gages into the model to complete a full record

of flow data for the entire modeling period. For all other local inflows, EPA used the mean annual 

flow defined in NHDPlus Version 1. 

G-9 
 

Figure G-1. Geographic Extent and Segmentation – Black Creek WASP Model 

Appendix G—Overview of Case Study Modeling Setup and Outputs

Model Input Variables. Table G-5 presents the pollutant loadings modeled from Morrow 

Generating Plant at the evaluated wastestream level, both at baseline and after the plant achieves

the limitations under the final rule. EPA did not identify any point sources with 2011 DMR or TRI 

loadings which would impact the Black Creek case study model. 

Table G-6 presents the pollutant contributions flowing into the Black Creek WASP model 

boundaries calculated using available STORET monitoring data. 

Table G-7 presents the initial concentrations for the organic solids, sands, and silts/fines 

values derived from STORET monitoring data collected. For tributaries where STORET 

monitoring data were not available, EPA assumed the average boundary concentration from all 

tributaries entering the modeling area. Based on the average of STORET data available within the 

model, EPA calculated the initial concentrations of organic solids, sands, and silts/fines in the 

water column segments were 3.43 mg/L, 0.78 mg/L, and 14.74 mg/L, respectively. 

EPA calibrated the model outputs by manipulating the sediment transport parameters until 

the modeled concentrations in the benthic segments closely matched the available sediment 

concentration monitoring data derived from STORET. Table G-8 presents the sediment transport

parameters resulting from EPA’s calibration effort. EPA assumed the initial concentrations of 

organic solids, sands, and silts/fines in the benthic segments were equal to 10,000 mg/L each. 

G-10 
 

 

 

 

Appendix G—Overview of Case Study Modeling Setup and Outputs

Model Results

Case study modeling of Black Creek revealed water quality benchmark exceedances in the 

immediate receiving water and/or in downstream segments for arsenic, cadmium, selenium, and 

thallium. Figure G-2, Figure G-3, and Figure G-4 illustrate the water concentration outputs for 

these pollutants in the immediate receiving water before and after the assumed compliance date 

for the final rule.6

Case study modeling of Black Creek revealed that average water column concentrations of 

three pollutants (cadmium, selenium, and thallium) in the immediate receiving water and/or

downstream segments would trigger exceedances of wildlife and/or human health benchmarks. 

Table G-9 and Table G-10 illustrate the average modeled pollutant concentration in each water 

column segment downstream of Morrow Generating Site (including the immediate receiving

water) for baseline and following compliance with the final rule, respectively. Table G-11 and 

Table G-12 present the total miles with average water column concentrations translating to 

exceedances of these benchmarks for baseline and under the final rule, respectively.

Refer to Appendix F regarding the results of ecological risk modeling using water quality 

outputs from the Black Creek WASP model. 

6

 To improve clarity, Figure G-2, Figure G-3, and Figure G-4 present the baseline water column concentrations

leading up to the assumed compliance date of Morrow Generating Station. All analyses of the WASP model outputs

were performed on the baseline output after the assumed compliance date.

G-11 
Appendix G—Overview of Case Study M

Table G-3. USGS Stream Gages with Flow Data Used in Black Creek WASP Model 

Gage ID USGS Gage Location Stream Flow Record Period Cumulative Drainage Area Represented by Gage (sq km) Model Boundary Cumulative Dr

Area at Mo

Boundary (sq 

2479130 Black Creek near Brooklyn, MS Full Record from 10/01/1970 - 04/14/2014 929 Black Creek 379 

2479155 Cypress Creek near Janice, MS Full Record from 10/01/1966 - 04/15/2014 138 Cypress Creek 158 

Acronyms: USGS (U.S. Geological Survey).

Table G-4. Stream Flow Data Periods – Black Creek WASP Model 

Modeling Period Corresponding Stream Flow Data Period 

Black Creek (Gage ID 2479130)

01/01/1982 - 09/30/2013 01/01/1982 - 09/30/2013 

10/01/2013 – 12/31/2020 10/01/2005 – 12/31/2012

01/01/1998 - 09/30/2029 01/01/1982 - 09/30/2013 

10/01/2029 – 12/31/2036 10/01/2005 – 12/31/2012

Cypress Creek (Gage ID 2479155)

01/01/1982 - 09/30/2013 01/01/1982 - 09/30/2013 

10/01/2013 – 12/31/2020 10/01/2005 – 12/31/2012

01/01/1998 - 09/30/2029 01/01/1982 - 09/30/2013 

10/01/2029 – 12/31/2036 10/01/2005 – 12/31/2012

G-12 
Appendix G—Overview of Case Study M

Table G-5. Pollutant Loadings - Morrow Generating Site 

Wastestream Pollutant Loadings (g/day) 

As Cd Cu Ni Pb Se 

Baseline a

FGD Wastewater 6.87 101.88 19.68 794.50 4.22 1,057.22 

Fly Ash Transport Water -- -­

-­ --

-­

-­ --

 Bottom Ash Transport Water 3.68 1.02 4.50 16.93 3.39 1.87 

 Combustion Residual Leachate 6.29 1.66 1.24 7.61 -- 18.19 

Total 16.84 104.56 25.42 819.03 7.61 1,077.27 

Final Rule b

 FGD Wastewater 5.28 3.81 3.42 5.70 3.07 5.18 

Fly Ash Transport Water -- -­

-­ --

-­

-­ --

Bottom Ash Transport Water -- -­

-­ --

-­

-­ --

 Combustion Residual Leachate 6.29 1.66 1.24 7.61 -- 18.19 

 Total 11.57 5.47 4.66 13.32 3.07 23.37 

Acronyms: FGD (flue gas desulfurization). a – The baseline pollutant loadings are modeled throughout the entire modeling period (from 01/01/1982 through 12/31/2036).b – The final rule pollutant loadings are modeled only after the assumed compliance date (from 01/01/2019 through 12/31/2036).

G-13 
Appendix G—Overview of Case Study M

Table G-6. Pollutant Contributions from STORET Monitoring Data – Black Creek WASP M

Model Boundary Model Boundary COMID Station ID(s) (lat, long) Parameter Average Concentration (μg/L)a 

Clear Creek 18104458 NLA06608-2010 (31.20,-89.30) TOC 4,420.00 

Little Black Creek 18104706 PA361 (31.09,-89.49)

TOC 7,400.00 

TSS 4,642.86 

Big Creek c 18104940 PA043 (31.07,-89.27)

TOC 10,000.00 

TSS 7,000.00 

Big Creek c 18104992 PA240 (31.07,-89.17) PA360 (31.14,-89.24) TOC 10,333.33 

TSS 4,666.67 

Cypress Creek 18108034 OWW04440-HBN8 (31.02,-89.01) PA056 (31.03,-89.02) TSS 10,000.00 

TOC 18,000.00 

Hickory Creek 18106316 112D33 (30.97,-88.97) TOC 3,000.00 

Acronyms: TOC (Total Organic Carbon); TSS (Total Suspended Solids).a –Where more than one monitoring station located on the same tributary system reported acceptable results for the same pollutant, EPA cathe weighted average concentration across the monitoring stations (weighted by number of samples at each station). b – For the modeled pollutants (not including TOC and TSS), EPA converted the average concentration to a mass loading using the averagstream reach represented by the monitoring station(s). c – There are two distinct tributary systems that are identified as “Big Creek” in the National Hydrography Dataset Plus (NHDPlus Version 

G-14 
Appendix G—Overview of Case Study M

Table G-7. Organic Solids, Sands, and Silts/Fines Inputs – Black Creek WASP Model

Model Boundary Model Boundary COMID Organic Solids Concentration (mg/L)a Sands Concentration (mg/L)b Silts/

Black Creek d 18104316 3.43 0.78 

Clear Creek 18104458 2.21 * 

Little Black Creek 18104706 3.70 0.23 

Big Creek e 18104940 5.00 0.35 

Big Creek e 18104992 5.17 0.23 

Cypress Creek 18108034 5.00 0.90 

Hickory Creek 18106316 1.50 * 

All Other Inflows f N/A 3.76 0.43 

Acronyms: N/A (Not Applicable).* – No TSS results available. The ‘All Other Inflows’ concentration was used in this scenario.a – The organic solids concentration was calculated using Equation G-1and the STORET monitoring data presented in Table G-6.

b – The sands concentration was calculated using Equation G-2 and the STORET monitoring data presented in Table G-6.c – The silts/fines concentration was calculated using Equation G-3 and the STORET monitoring data presented in Table G-6.

d – The organic solids, sands, and silts/fines concentrations presented for this segment were used as the initial surface water conditions.e – There are two distinct tributary systems that are identified as “Big Creek” in the National Hydrography Dataset Plus (NHDPlus Version 

f – For tributaries where boundary concentrations from STORET monitoring data were not available, EPA assumed the average boundary tributaries entering the modeling area.

G-15
Appendix G—Overview of Case Study M

Table G-8. Sediment Transport Parameters – Black Creek WASP Model

Input Parameter Value Used Units

TAUcritcoh 3.5 N/m2

TAU_cD1_si a 3.5 N/

m2

TAU_cD2_si a 7.

0 N/

m2

TAU_cD1_PO a 3.5 N/

m2

TAU_cD2_PO a 7.

0 N/

m2

Note: Table G-1 presents additional solids constants and sediment transport parameters that are used in each of the case study models. a – This parameter is a WASP model default based on the value of the ‘TAUcritcoh’ parameter. 

G-16
Appendix G—Overview of Case Study M

Figure G-2. Modeled Concentrations in Black Creek Water Column at Morrow Generating Site Immediat

(Total Cadmium, Dissolved Cadmium) 

G-17
Appendix G—Overview of Case Study M

Figure G-3. Modeled Concentrations in Black Creek Water Column at Morrow Generating Site Immediat

(Total Arsenic, Total Thallium)

G-18 
Appendix G—Overview of Case Study M

Figure G-4. Modeled Concentrations in Black Creek Water Column at Morrow Generating Site Immediat

(Total Selenium) 

G-19 
Appendix G—Overview of Case Study M

Table G-9. Average Water Column Concentrations Downstream of Morrow Generating Site at B

Segment Data Average Total Water Column Concentration over Mo

Segment ID Segment Name Segment Length (mi) Distance Downstream (mi) As Cd Cu Pb Ni Se 

39 Black Creek/ IRW 1.64 1.64 0.0833 0.6045 0.1407 0.0498 4.2330 5.6

38 Black Creek 1.44 3.08 0.0543 0.4095 0.0942 0.0346 2.7890 3.7

37 Black Creek 2.23 5.31 0.0521 0.3172 0.0774 0.0226 2.5298 3.3

36 Black Creek 2.68 7.99 0.0445 0.2883 0.0693 0.0218 2.2009 2.9

35 Black Creek 0.93 8.92 0.0450 0.3114 0.0735 0.0249 2.2628 3.0

34 Black Creek 2.10 11.01 0.0420 0.2960 0.0696 0.0240 2.1255 2.8

33 Black Creek 1.89 12.90 0.0483 0.6251 0.1220 0.0625 3.0284 4.2

32 Black Creek 1.68 14.58 0.0476 0.6712 0.1307 0.0694 3.1224 4.4

31 Black Creek 1.84 16.43 0.0313 0.5851 0.1074 0.0619 2.3412 3.4

30 Black Creek 1.48 17.90 0.0282 0.3999 0.0783 0.0400 1.8857 2.6

29 Black Creek 1.44 19.35 0.0241 0.3275 0.0650 0.0324 1.5902 2.2

28 Black Creek 2.64 21.99 0.0396 0.9409 0.1816 0.1095 3.4735 5.2

27 Black Creek 2.09 24.08 0.0364 0.7642 0.1489 0.0866 3.0067 4.4

26 Black Creek 2.66 26.74 0.0348 0.6855 0.1344 0.0764 2.7946 4.1

25 Black Creek 1.31 28.05 0.0398 1.1003 0.2131 0.1383 3.8927 5.9

24 Black Creek 1.07 29.12 0.0413 1.2014 0.2311 0.1532 4.1371 6.3

23 Black Creek 2.86 31.98 0.0425 1.3070 0.2498 0.1688 4.3820 6.7

22 Black Creek 3.02 35.00 0.0425 1.3056 0.2499 0.1690 4.3861 6.8

21 Black Creek 1.59 36.59 0.0382 1.1168 0.2147 0.1431 3.8483 5.9

20 Black Creek 2.50 39.09 0.0396 1.2133 0.2319 0.1569 4.0771 6.3

19 Black Creek 1.98 41.07 0.0399 1.2327 0.2352 0.1596 4.1222 6.3

18 Black Creek 4.21 45.29 0.0349 1.1106 0.2114 0.1451 3.6660 5.7

17 Black Creek 2.62 47.91 0.0315 0.9820 0.1872 0.1276 3.2730 5.0

16 Black Creek 2.75 50.66 0.0299 0.9354 0.1780 0.1218 3.1087 4.8

15 Black Creek 2.09 52.75 0.0309 1.0301 0.1945 0.1357 3.3126 5.1

G-20 
Appendix G—Overview of Case Study M

Table G-9. Average Water Column Concentrations Downstream of Morrow Generating Site at B

Segment Data Average Total Water Column Concentration over Mo

Segment ID Segment Name Segment Length (mi) Distance Downstream (mi) As Cd Cu Pb Ni Se 

14 Black Creek 4.55 57.30 0.0305 1.0067 0.1903 0.1325 3.2498 5.0

13 Black Creek 2.35 59.65 0.0300 0.9822 0.1860 0.1290 3.1903 4.9

12 Black Creek 2.14 61.79 0.0194 0.2514 0.0569 0.0208 1.4524 2.0

11 Black Creek 2.01 63.80 0.0192 0.2467 0.0558 0.0211 1.4283 2.0

10 Black Creek 4.00 67.80 0.0269 0.5034 0.1033 0.0565 2.2124 3.2

9 Black Creek 1.80 69.61 0.0282 0.6248 0.1242 0.0747 2.4762 3.6

8 Black Creek 3.50 73.10 0.0265 0.5620 0.1125 0.0662 2.2782 3.3

7 Black Creek 3.02 76.12 0.0261 0.5480 0.1099 0.0642 2.2346 3.3

6 Black Creek 3.33 79.45 0.0261 0.5551 0.1109 0.0650 2.2472 3.3

5 Black Creek 3.16 82.61 0.0260 0.5475 0.1096 0.0639 2.2301 3.3

4 Black Creek 3.36 85.97 0.0263 0.5658 0.1129 0.0666 2.2768 3.3

3 Black Creek 1.90 87.87 0.0248 0.4646 0.0947 0.0517 2.0354 2.9

2 Black Creek 3.66 91.54 0.0241 0.4279 0.0877 0.0462 1.9406 2.8

1 Black Creek/ End 3.85 95.38 0.0247 0.4799 0.0943 0.0492 2.0362 2.9

Acronyms: IRW (Immediate receiving water). a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modelin

compliance date. 

G-21 
Appendix G—Overview of Case Study M

Table G-10. Average Water Column Concentrations Downstream of Morrow Generating Site Unde

Segment Data Average Total Water Column Concentration over Mo

Segment ID Segment Name Segment Length (mi) Distance Downstream (mi) As Cd Cu Pb Ni Se 

39 Black Creek/ IRW 1.64 1.64 0.0575 0.0322 0.0261 0.0204 0.0702 0.12

38 Black Creek 1.44 3.08 0.0375 0.0218 0.0175 0.0141 0.0464 0.0

37 Black Creek 2.23 5.31 0.0360 0.0169 0.0144 0.0092 0.0419 0.07

36 Black Creek 2.68 7.99 0.0308 0.0153 0.0129 0.0089 0.0366 0.0

35 Black Creek 0.93 8.92 0.0311 0.0166 0.0136 0.0102 0.0378 0.0

34 Black Creek 2.10 11.01 0.0290 0.0158 0.0129 0.0098 0.0355 0.0

33 Black Creek 1.89 12.90 0.0335 0.0532 0.0273 0.0274 0.1016 0.17

32 Black Creek 1.68 14.58 0.0330 0.0545 0.0286 0.0301 0.0972 0.17

31 Black Creek 1.84 16.43 0.0217 0.0469 0.0233 0.0269 0.0778 0.13

30 Black Creek 1.48 17.90 0.0196 0.0335 0.0171 0.0174 0.0635 0.1

29 Black Creek 1.44 19.35 0.0167 0.0274 0.0142 0.0140 0.0534 0.09

28 Black Creek 2.64 21.99 0.0272 0.0639 0.0358 0.0460 0.0916 0.17

27 Black Creek 2.09 24.08 0.0249 0.0536 0.0300 0.0366 0.0823 0.15

26 Black Creek 2.66 26.74 0.0239 0.0491 0.0274 0.0323 0.0784 0.14

25 Black Creek 1.31 28.05 0.0279 0.1061 0.0442 0.0607 0.1996 0.34

24 Black Creek 1.07 29.12 0.0289 0.1205 0.0486 0.0675 0.2233 0.3

23 Black Creek 2.86 31.98 0.0298 0.1339 0.0530 0.0746 0.2437 0.42

22 Black Creek 3.02 35.00 0.0298 0.1349 0.0534 0.0748 0.2467 0.43

21 Black Creek 1.59 36.59 0.0268 0.1214 0.0469 0.0639 0.2291 0.39

20 Black Creek 2.50 39.09 0.0278 0.1276 0.0500 0.0697 0.2351 0.40

19 Black Creek 1.98 41.07 0.0280 0.1291 0.0507 0.0709 0.2370 0.4

18 Black Creek 4.21 45.29 0.0245 0.1176 0.0458 0.0643 0.2143 0.37

17 Black Creek 2.62 47.91 0.0221 0.1029 0.0404 0.0565 0.1881 0.32

G-22 
Appendix G—Overview of Case Study M

Table G-10. Average Water Column Concentrations Downstream of Morrow Generating Site Unde

Segment Data Average Total Water Column Concentration over Mo

Segment ID Segment Name Segment Length (mi) Distance Downstream (mi) As Cd Cu Pb Ni Se 

16 Black Creek 2.75 50.66 0.0209 0.0988 0.0386 0.0540 0.1821 0.3

15 Black Creek 2.09 52.75 0.0217 0.1092 0.0422 0.0602 0.1951 0.34

14 Black Creek 4.55 57.30 0.0214 0.1085 0.0416 0.0590 0.1937 0.34

13 Black Creek 2.35 59.65 0.0210 0.1068 0.0408 0.0574 0.1921 0.3

12 Black Creek 2.14 61.79 0.0136 0.0236 0.0118 0.0090 0.0729 0.1

11 Black Creek 2.01 63.80 0.0134 0.0232 0.0116 0.0095 0.0716 0.1

10 Black Creek 4.00 67.80 0.0187 0.0514 0.0223 0.0249 0.1231 0.20

9 Black Creek 1.80 69.61 0.0197 0.0652 0.0271 0.0330 0.1485 0.24

8 Black Creek 3.50 73.10 0.0185 0.0585 0.0245 0.0291 0.1352 0.22

7 Black Creek 3.02 76.12 0.0182 0.0571 0.0240 0.0282 0.1322 0.2

6 Black Creek 3.33 79.45 0.0183 0.0580 0.0242 0.0286 0.1333 0.22

5 Black Creek 3.16 82.61 0.0182 0.0568 0.0239 0.0281 0.1314 0.2

4 Black Creek 3.36 85.97 0.0184 0.0582 0.0245 0.0292 0.1329 0.22

3 Black Creek 1.90 87.87 0.0173 0.0510 0.0211 0.0228 0.1250 0.20

2 Black Creek 3.66 91.54 0.0169 0.0469 0.0195 0.0204 0.1196 0.19

1 Black Creek/ End 3.85 95.38 0.0173 0.0497 0.0208 0.0217 0.1233 0.19

Acronyms: IRW (Immediate receiving water). a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modelin

compliance date. 

G-23 
Appendix G—Overview of Case Study M

Table G-11. Total Miles of Black Creek with Wildlife And Human Health Impacts at Basel

Wildlife & Human Health Impact Thresholds

Total Miles with Average Water Column Concentration Translating to W

Benchmark Exceedances (mi) 

As Cd Cu Pb Ni Se 

WL - NEHC, T3 (mink) 0.00 0.00 0.00 0.00 0.00 89.79 

WL - NEHC, T4 (eagle) 0.00 0.00 0.00 0.00 0.00 89.79 

HH - Non-Cancer Adult Subsistence 0.00 0.00 0.00 No RfD 0.00 95.38 

HH - Non-Cancer Adult Recreational 0.00 0.00 0.00 No RfD 0.00 12.75 

HH - Non-Cancer Child Subsistence (1 to <2 y.o.) a 0.00 37.64 0.00 No RfD 0.00 95.38 

HH - Non-Cancer Child Subsistence (16 to <21 y.o) b 0.00 0.00 0.00 No RfD 0.00 89.79 

HH - Non-Cancer Child Recreational (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 89.79 HH - Non-Cancer Child Recreational (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 11.43 HH - Cancer Adult Subsistence 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Adult Recreational 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (6 to <11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (6 to 11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR 

Acronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration); Rfd (Reference dose); LECR (Lifetime excess caa – This row represents the most sensitive child fisher cohort. b – This row represents the least sensitive child fisher cohort. 

G-24 
Appendix G—Overview of Case Study M

Table G-12. Total Miles of Black Creek with Wildlife And Human Health Impacts Under Fina

Wildlife and Human Health Impact Thresholds 

Total Miles with Average Water Column Concentration Translating to W

Benchmark Exceedances (mi) 

As Cd Cu Pb Ni Se 

WL - NEHC, T3 (mink) 0.00 0.00 0.00 0.00 0.00 0.00 

WL - NEHC, T4 (eagle) 0.00 0.00 0.00 0.00 0.00 0.00 

HH - Non-Cancer Adult Subsistence 0.00 0.00 0.00 No RfD 0.00 0.00 

HH - Non-Cancer Adult Recreational 0.00 0.00 0.00 No RfD 0.00 0.00 

HH - Non-Cancer Child Subsistence (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 0.00 

HH - Non-Cancer Child Subsistence (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Cancer Adult Subsistence 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Adult Recreational 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (6 to <11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (6 to 11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR 

Acronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration); Rfd (Reference dose); LECR (Lifetime excess caa – This row represents the most sensitive child fisher cohort. b – This row represents the least sensitive child fisher cohort. 

G-25 
Appendix G—Overview of Case Study Modeling Setup and Outputs 

CASE STUDY MODEL SETUPS AND OUTPUTS – ETOWAH RIVER, GA 

This section presents information regarding the site-specific design, site-specific input 

parameters (e.g., background pollutant concentrations, USGS time series flow data), model

settings (e.g., sediment transport parameters), and case study modeling results for the Etowah 

River case study model. 

Model Development & Input Variables 

WASP Model Design. The Etowah River WASP model starts at Plant Bowen’s immediate

receiving water (COMID 6499098), as defined by the IRW model, and extends approximately 35 

miles downstream to just upstream of where the Etowah River converges with Silver Creek 

(COMID 6500350). 

The Etowah River WASP model consists of 96 modeled segments. Segment IDs 1-18 

represent the surface water of the Etowah River with Segment ID 1 being the most downstream 

segment and Segment ID 18 being the most upstream segment and immediate receiving water. The 

remaining model segments represent tributary surface waters (Segment IDs 19-32), the upper 

benthic layers (Segment IDs 33-64), and the lower benthic layers (Segment IDs 65-96). Figure

G-5 illustrates the segmentation of the Etowah River WASP model. 

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. 

Incorporation of Flow Data. EPA used USGS stream flow data from one USGS stream

gage to represent inflow at the upstream end of the modeling area of the Etowah River WASP 

model. EPA scaled the Etowah River stream gage data from Gage ID 02395000 to account for the 

difference in drainage area between the actual gage location and the point where the contributing

flows enter the modeling area.

EPA used USGS stream flow data from one USGS stream gage to represent inflow from 

Two Run Creek, a significant tributary to the Etowah River WASP modeling area. EPA scaled the 

Two Run Creek stream gage data from Gage ID 02395120 to account for the difference in drainage

area between the actual gage location and the point where the contributing flows enter the

modeling area. 

Figure G-5 illustrates the two stream flow gages from which EPA incorporated USGS 

stream flow data. Table G-13 presents additional information about the two stream gages and the 

time period covered in the stream flow data record at each. Table G-14 presents how EPA 

incorporated the stream flow data from these stream gages into the model to complete a full record

of flow data for the entire modeling period. For all other local inflows, EPA used the mean annual 

flow defined in NHDPlus Version 1. 

G-26 
 

Figure G-5. Geographic Extent and Segmentation – Etowah River WASP Model 

Appendix G—Overview of Case Study Modeling Setup and Outputs

Model Input Variables. Table G-15 presents the pollutant loadings modeled from Plant 

Bowen at the evaluated wastestream level, both at baseline and after the plant achieves the 

limitations under the final rule. EPA did not identify any point sources with 2011 DMR or TRI 

loadings which would impact the Etowah River case study model and could not be accounted for 

using STORET monitoring data. 

Table G-16 presents the pollutant contributions flowing into the Etowah River WASP 

model boundaries calculated using available STORET monitoring data. 

Table G-17 presents the initial concentrations for the organic solids, sands, and silts/fines 

values derived from STORET monitoring data collected. For tributaries where STORET 

monitoring data were not available, EPA assumed the average boundary concentration from all 

tributaries entering the modeling area. Based on the average of STORET data available within the 

model, EPA calculated the initial concentrations of organic solids, sands, and silts/fines in the 

water column segments were 2.56 mg/L, 0.90 mg/L, and 17.19 mg/L, respectively. 

EPA calibrated the model outputs by manipulating the sediment transport parameters until 

the modeled concentrations in the benthic segments closely matched the available sediment 

concentration monitoring data derived from STORET. Table G-18 presents the sediment transport 

parameters resulting from EPA’s calibration effort. EPA assumed the initial concentrations of 

organic solids, sands, and silts/fines in the benthic segments were equal to 500 mg/L each.

G-27 
 

 

 

 

Appendix G—Overview of Case Study Modeling Setup and Outputs

Model Results

Case study modeling of the Etowah River revealed water quality benchmark exceedances 

in the immediate receiving water and/or in downstream segments for arsenic, cadmium, selenium, 

and thallium.7

 Figure G-6 and Figure G-7 illustrate the water concentration outputs for these 

pollutants in the immediate receiving water before and after the assumed compliance date for the 

final rule.8

Case study modeling of the Etowah River revealed that average water column

concentrations of three pollutants (arsenic, selenium, and thallium) in the immediate receiving 

water and/or downstream segments would trigger exceedances of human health benchmarks. Table 

G-19 and Table G-20 illustrate the average modeled pollutant concentration in each water column

segment downstream of Plant Bowen (including the immediate receiving water) for baseline and

following compliance with the final rule, respectively. Table G-21 and Table G-22 present the total 

miles with average water column concentrations translating to exceedances of these benchmarks 

for baseline and under the final rule, respectively. 

7

 Case study modeling also revealed isolated downstream exceedances of water quality benchmarks for lead. 

8

 To improve clarity, Figure G-6 and Figure G-7 present the baseline water column concentrations leading up to the 

assumed compliance date of Plant Bowen. All analyses of the WASP model outputs were performed on the baseline 

output after the assumed compliance date.

G-28 
Appendix G—Overview of Case Study M

Table G-13. USGS Stream Gages with Flow Data Used in Etowah River WASP Model 

Gage ID USGS Gage Location Stream Flow Record Period Cumulative Drainage Area Represented by Gage (sq km) Model Boundary Cumulative Dr

Area at Mo

Boundary (sq 

02395000 Etowah River near Kingston, GA 

Partial Record from

07/18/2928 – 09/30/2013

(Missing Data between 

10/24/1995 – 10/01/2008)

4,239 Etowah River 3,683 

02395120 Two Run Creek near Kingston, GA Full Record from 05/02/1980 – 09/30/2013 85 Two Run Creek 130 

Acronyms: USGS (U.S. Geological Survey).

Table G-14. Stream Flow Data Periods – Etowah River WASP Model 

Modeling Period Corresponding Stream Flow Data Period 

Etowah River (Gage ID 02395000) 

01/01/1982 - 10/23/1995 01/01/1982 - 10/23/1995 

10/24/1995 - 09/30/2008 10/24/1967 - 09/30/1980 

10/01/2008 - 9/30/2013 10/01/2008 - 9/30/2013

10/01/2013 – 12/31/2020 10/01/2005 – 12/31/2012

01/01/1994 - 10/23/2007 01/01/1982 - 10/23/1995 10/24/2007 - 09/30/2020 10/24/1967 - 09/30/1980 

10/01/2020 - 9/30/2025 10/01/2008 - 9/30/2013

10/01/2025 – 12/31/2032 10/01/2005 – 12/31/2012

Two Run Creek (Gage ID 02395120)

01/01/1982 - 09/30/2013 01/01/1982 - 09/30/2013 

10/01/2013 – 12/31/2020 10/01/2005 – 12/31/2012

01/01/1994 - 09/30/2025 01/01/1982 - 09/30/2013 

10/01/2025 – 12/31/2032 10/01/2005 – 12/31/2012

G-29 
Appendix G—Overview of Case Study M

Table G-15. Pollutant Loadings – Plant Bowen

Wastestream Pollutant Loadings (g/day) 

As Cd Cu Ni Pb Se 

Baseline a

 FGD Wastewater c 27.56 408.74 78.96 3187.42 16.93 4241.43 

Fly Ash Transport Water -- -­

-­ --

-­

-­ --

 Bottom Ash Transport Water 13.79 3.81 16.86 63.46 12.69 6.99  Combustion Residual Leachate -- -- -- -- -- -- 

 Total 41.35 412.55 95.82 3,250.88 29.62 4,248.42 Final Rule b

FGD Wastewater 21.18 15.28 13.71 22.89 12.31 20.77 

Fly Ash Transport Water -- -­

-­ --

-­

-­ --

Bottom Ash Transport Water -- -­

-­ --

-­

-­ --

 Combustion Residual Leachate -- -- -- -- -- -- 

Total 21.18 15.28 13.71 22.89 12.31 20.77 

Acronyms: FGD (flue gas desulfurization). a – The baseline pollutant loadings are modeled throughout the entire modeling period (from 01/01/1982 through 12/31/2032).b – The final rule pollutant loadings are modeled only after the assumed compliance date (from 01/01/2021 through 12/31/2032).c - In estimating the historical pollutant loadings associated with Plant Bowen’s four FGD systems, EPA incorporated the pollutant loadingas the systems were installed, between 2008 and 2011. EPA did not model any FGD wastewater pollutant loadings before the installation osystem. 

G-30 
Appendix G—Overview of Case Study M

Table G-16. Pollutant Contributions from STORET Monitoring Data – Etowah River WASP 

Model Boundary Model Boundary COMID Station ID(s) (lat, long) Parameter Average Concentration (μg/L)a M

Etowah River 6499098 

14310011 (34.15,-84.77) 

1404130102 (34.15,-84.77) 1404130103 (34.15,-84.77) 1404130105 (34.12,-84.82) 

As -- 

Cd -- Cu -- 

Ni -- 

Pb -- 

Tl -- 

Zn -- 

TOC 3,531.41 

TSS 8,775.41 

Euharlee Creek 6497752 1404140704 (34.13,-84.94) 1404140701 (34.12,-84.95) 

Pb -- 

TOC 6,734.53 

TSS 16,323.08 

Two Run Creek 6497374 14340201 (34.22,-84.97) 

As -- 

Cd -- 

Cu -- 

Ni -- 

Pb -- 

Tl -- 

Zn -- 

TOC 7,996.03 

TSS 12,847.83 

Connesena Creek 6497306 1404150501 (34.24,-84.97) 

TOC 4,191.06 

TSS 4,640.00 

Toms Creek 6499778 1404160201 (34.26,-84.99) TOC 9,465.83 

G-31 
Appendix G—Overview of Case Study M

Table G-16. Pollutant Contributions from STORET Monitoring Data – Etowah River WASP 

Model Boundary Model Boundary COMID Station ID(s) (lat, long) Parameter Average Concentration (μg/L)a M

Spring Creek 6499820 1404160301 (34.21,-85.07) 14340991 (34.21,-85.07) 

As -- 

Cd -- 

Cu -- 

Ni -- 

Pb -- 

Tl -- 

Zn -- 

TOC 8,526.71 

TSS 14,434.78 

Dykes Creek 6499782 1404160401 (34.25,-85.08) 1404160402 (34.26,-85.09) TOC 2,350.53 

TSS 3,661.11 

Acronyms: TOC (Total Organic Carbon); TSS (Total Suspended Solids).a –Where more than one monitoring station located on the same tributary system reported acceptable results for the same pollutant, EPA cathe weighted average concentration across the monitoring stations (weighted by number of samples at each station). b – For the modeled pollutants (not including TOC and TSS), EPA converted the average concentration to a mass loading using the averagstream reach represented by the monitoring station(s). 

G-32 
Appendix G—Overview of Case Study M

Table G-17. Organic Solids, Sands, and Silts/Fines Inputs – Etowah River WASP Model

Model Boundary Model Boundary COMID Organic Solids Concentration (mg/L)a Sands Concentration (mg/L)b Silts/

Etowah River 6499098 1.77 0.44 

Euharlee Creek 6497752 3.37 0.82 

Two Run Creek 6497374 4.00 0.64 

Connesena Creek 6497306 2.10 0.23 

Toms Creek 6499778 4.73 * 

Spring Creek 6499820 4.26 0.72 

Dykes Creek 6499782 1.18 0.18 

All Other Inflows d N/A 3.06 0.51 

Acronyms: N/A (Not Applicable).* – No TSS results available. The ‘All Other Inflows’ concentration was used in this scenario. a – The organic solids concentration was calculated using Equation G-1 and the STORET monitoring data presented in Table G-16.b – The sands concentration was calculated using Equation G-2 and the STORET monitoring data presented in Table G-16.c – The silts/fines concentration was calculated using Equation G-3 and the STORET monitoring data presented in Table G-16. 

d – For tributaries where boundary concentrations from STORET monitoring data were not available, EPA assumed the average boundary 

tributaries entering the modeling area. 

Table G-18. Sediment Transport Parameters – Etowah River WASP Model

Input Parameter Value Used Units

TAUcritcoh 3.5 N/m2

TAU_cD1_sia 3.5 N/m2TAU_cD2_sia 7.0 N/m2

TAU_cD1_POa 3.5 N/m2TAU_cD2_POa 7.0 N/m2

Note: Table G-1 presents additional solids constants and sediment transport parameters that are used in each of the case study models. a – This parameter is a WASP model default based on the value of the ‘TAUcritcoh’ parameter. 

G-33 
Appendix G—Overview of Case Study M

Figure G-6. Modeled Concentrations in Etowah River Water Column at Plant Bowen Immediate Receiv

(Total Arsenic, Total Thallium)

G-34 
Appendix G—Overview of Case Study M

Figure G-7. Modeled Concentrations in Etowah River Water Column at Plant Bowen Immediate Rec

(Dissolved Cadmium, Total Selenium)

G-35 
Appendix G—Overview of Case Study M

Table G-19. Average Water Column Concentrations Downstream of Plant Bowen at Baseli

Segment Data Average Total Water Column Concentration over Mo

Segment 

ID Segment Name

Segment 

Length 

(mi)

Distance 

Downstrea 

m (mi) 

As Cd Cu Pb Ni Se 

18 Etowah River / IRW 3.61 3.61 3.5521 0.5095 1.6421 0.6667 2.0928 1.42

17 Etowah River 1.48 5.09 2.5373 0.3532 1.1484 0.5990 1.4836 1.00

16 Etowah River 1.42 6.51 2.4625 0.3077 1.0395 0.4300 1.4091 0.94

15 Etowah River 0.58 7.10 2.4351 0.2988 1.0163 0.4017 1.3887 0.93

14 Etowah River 1.20 8.29 2.3959 0.2871 0.9850 0.3660 1.3601 0.91

13 Etowah River 3.69 11.99 2.4026 0.3190 1.0550 0.4924 1.3918 0.93

12 Etowah River 1.09 13.08 2.3771 0.3115 1.0354 0.4681 1.3739 0.92

11 Etowah River 1.29 14.36 2.3582 0.2976 1.0034 0.4155 1.3538 0.91

10 Etowah River 0.37 14.74 2.4742 0.3076 1.0550 0.4226 1.3632 0.88

9 Etowah River 2.95 17.69 2.4181 0.3033 1.0363 0.4246 1.3339 0.87

8 Etowah River 2.70 20.39 2.7308 0.5530 1.6659 1.3016 1.7191 1.16

7 Etowah River 0.90 21.29 2.6890 0.5256 1.5999 1.1982 1.6785 1.13

6 Etowah River 1.26 22.55 2.6458 0.4943 1.5239 1.0827 1.6334 1.10

5 Etowah River 2.82 25.38 2.6189 0.4847 1.4972 1.0559 1.6113 1.08

4 Etowah River 2.19 27.57 2.7324 0.6494 1.8852 1.7094 1.7807 1.20

3 Etowah River 2.48 30.05 2.6886 0.6536 1.8873 1.7431 1.7639 1.19

2 Etowah River 1.89 31.94 2.6892 0.6629 1.9009 1.7746 1.7696 1.20

1 Etowah River / End 2.81 34.75 2.6554 0.6282 1.8203 1.6351 1.7279 1.17

Acronyms: IRW (Immediate receiving water). 

a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modelin

compliance date. 

G-36 
Appendix G—Overview of Case Study M

Table G-20. Average Water Column Concentrations Downstream of Plant Bowen Under Fina

Segment Data Average Total Water Column Concentration over Mo

Segment 

ID Segment Name

Segment 

Length 

(mi)

Distance 

Downstream 

(mi)

As Cd Cu Pb Ni Se 

18 Etowah River/IRW 3.61 3.61 3.5450 0.3900 1.6162 0.6624 0.9963 0.017 Etowah River 1.48 5.09 2.5322 0.2704 1.1302 0.5960 0.7063 0.0

16 Etowah River 1.42 6.51 2.4576 0.2355 1.0231 0.4278 0.6709 0.0

15 Etowah River 0.58 7.10 2.4302 0.2287 1.0003 0.3998 0.6611 0.0

14 Etowah River 1.20 8.29 2.3911 0.2197 0.9695 0.3642 0.6475 0.0

13 Etowah River 3.69 11.99 2.3978 0.2442 1.0384 0.4900 0.6627 0.0

12 Etowah River 1.09 13.08 2.3723 0.2385 1.0191 0.4657 0.6542 0.0

11 Etowah River 1.29 14.36 2.3534 0.2278 0.9876 0.4134 0.6446 0.0

10 Etowah River 0.37 14.74 2.3036 0.2401 1.0396 0.4206 0.6706 0.0

9 Etowah River 2.95 17.69 2.2517 0.2368 1.0212 0.4227 0.6560 0.0

8 Etowah River 2.70 20.39 2.5377 0.4328 1.6418 1.2965 0.8479 0.0

7 Etowah River 0.90 21.29 2.4979 0.4113 1.5768 1.1935 0.8280 0.0

6 Etowah River 1.26 22.55 2.4579 0.3866 1.5019 1.0785 0.8056 0.0

5 Etowah River 2.82 25.38 2.4331 0.3791 1.4753 1.0525 0.7947 0.0

4 Etowah River 2.19 27.57 2.4324 0.5100 1.8580 1.7033 0.8992 0.0

3 Etowah River 2.48 30.05 2.3930 0.5134 1.8602 1.7368 0.8908 0.0

2 Etowah River 1.89 31.94 2.3926 0.5197 1.8754 1.7578 0.8939 0.0

1 Etowah River/End 2.81 34.75 2.3624 0.4923 1.7955 1.6212 0.8728 0.0

Acronyms: IRW (Immediate receiving water). a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modelin

compliance date. 

G-37 
Appendix G—Overview of Case Study M

Table G-21. Total Miles of Etowah River with Wildlife And Human Health Impacts at Base

Wildlife and Human Health Impact Thresholds 

Total Miles with Average Water Column Concentration Translating to Wi

Benchmark Exceedances (mi) 

As Cd Cu Pb Ni Se 

WL - NEHC, T3 (mink) 0.00 0.00 0.00 0.00 0.00 0.00 

WL - NEHC, T4 (eagle) 0.00 0.00 0.00 0.00 0.00 0.00 

HH - Non-Cancer Adult Subsistence 0.00 0.00 0.00 No RfD 0.00 0.00 

HH - Non-Cancer Adult Recreational 0.00 0.00 0.00 No RfD 0.00 0.00 

HH - Non-Cancer Child Subsistence (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 34.75 

HH - Non-Cancer Child Subsistence (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Cancer Adult Subsistence 3.61 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Adult Recreational 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (6 to <11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (6 to 11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR 

Acronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration); Rfd (Reference dose); LECR (Lifetime excess caa – This row represents the most sensitive child fisher cohort. b – This row represents the least sensitive child fisher cohort. 

G-38 
Appendix G—Overview of Case Study M

Table G-22. Total Miles of Etowah River with Wildlife And Human Health Impacts Under Fin

Wildlife and Human Health Impact Thresholds 

Total Miles with Average Water Column Concentration Translating to Wi

Benchmark Exceedances (mi) 

As Cd Cu Pb Ni Se 

WL - NEHC, T3 (mink) 0.00 0.00 0.00 0.00 0.00 0.00 WL - NEHC, T4 (eagle) 0.00 0.00 0.00 0.00 0.00 0.00 HH - Non-Cancer Adult Subsistence 0.00 0.00 0.00 No RfD 0.00 0.00 

HH - Non-Cancer Adult Recreational 0.00 0.00 0.00 No RfD 0.00 0.00 

HH - Non-Cancer Child Subsistence (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 0.00 

HH - Non-Cancer Child Subsistence (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Cancer Adult Subsistence 3.61 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Adult Recreational 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (6 to <11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (6 to 11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR 

Acronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration); Rfd (Reference dose); LECR (Lifetime excess caa – This row represents the most sensitive child fisher cohort. b – This row represents the least sensitive child fisher cohort. 

G-39 
Appendix G—Overview of Case Study Modeling Setup and Outputs 

CASE STUDY MODEL SETUPS AND OUTPUTS – LICK CREEK & WHITE RIVER, IN 

This section presents information regarding the site-specific design, site-specific input 

parameters (e.g., background pollutant concentrations, USGS time series flow data), model

settings (e.g., sediment transport parameters), and case study modeling results for the Lick Creek 

and White River case study model. 

Model Development & Input Variables 

WASP Model Design. The Lick Creek and White River WASP model starts at the

convergence of the West Fork White River (COMID 18471042) and the East Fork White River 

(COMID 18446060). The model extends approximately 52 miles downstream to just upstream of 

where the White River converges with the Wabash River (COMID 18471318). Petersburg 

Generating Station’s immediate receiving water, Lick Creek (COMID 18471122) is approximately 

3 miles downstream of the confluence of the East Fork and West Fork of the White River. 

The Lick Creek and White River WASP model consists of 78 modeled segments. Segment

IDs 1-19 represent the surface water of the White River with Segment ID 1 being the most 

downstream segment, Segment ID 19 being the West Fork White River, and Segment 18 being the 

East Fork White River. Lick Creek, the immediate receiving water, is represented as Segment 76 

and intersects the White River between Segment 16 and Segment 17. The remaining model

segments represent tributary surface waters (Segment IDs 20-25), the upper benthic layers

(Segment IDs 26-50 & 77), and the lower benthic layers (Segment IDs 51-75 & 78). Figure G-8 

illustrates the segmentation of the Etowah River WASP model.

The modeling period starts in 1986 (the year the last generating unit at Petersburg 

Generating Station began operating) 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. 

Incorporation of Flow Data. EPA used USGS stream flow data from one USGS stream

gage to represent inflow at the upstream end of the modeling area of the Lick Creek and White 

River WASP model. EPA scaled the White River stream gage data from Gage ID 033740000 to 

account for the difference in drainage area between the actual gage location and the point where

the contributing flows enter the modeling area at the East Fork White River and West Fork White 

River modeling boundaries. 

No USGS stream flow data were available on Lick Creek; therefore, EPA used stream flow 

data from one USGS stream gage on nearby Kessinger Ditch as a surrogate stream to represent 

inflow from Lick Creek. EPA scaled the Kessinger Ditch stream gage data from Gage ID 03360895 

to produce a dataset with an average annual flow rate that closely approximates that of Lick Creek, 

as defined by NHDPlus Version 1. 

Figure G-8 illustrates the two stream flow gages from which EPA incorporated USGS 

stream flow data. Table G-23 presents additional information about the two stream gages and the 

time period covered in the stream flow data record at each. Table G-24 presents how EPA 

incorporated the stream flow data from these stream gages into the model to complete a full record

of flow data for the entire modeling period. For all other local inflows, EPA used the mean annual 

flow defined in NHDPlus Version 1. 

G-40 
 

Figure G-8. Geographic Extent and Segmentation – Lick Creek & White River WASP 

Model 

Appendix G—Overview of Case Study Modeling Setup and Outputs

Model Input Variables. Table G-25 presents the pollutant loadings modeled from

Petersburg Generating Station at the evaluated wastestream level, both at baseline and after the

plant achieves the limitations under the final rule. 

Table G-26 presents the pollutant loadings modeled from non-steam electric point sources

with 2011 DMR or TRI loadings which would impact the Lick Creek and White River case study 

model. 

Table G-27 presents the pollutant contributions flowing into the Lick Creek and White 

River WASP model boundaries calculated using available STORET monitoring data. 

Table G-28 presents the initial concentrations for the organic solids, sands, and silts/fines 

values derived from STORET monitoring data collected. For tributaries where STORET 

monitoring data were not available, EPA assumed the average boundary concentration from all 

tributaries entering the modeling area. Based on the average of STORET data available within the 

model, EPA calculated the initial concentrations of organic solids, sands, and silts/fines in the 

water column segments were 1.99 mg/L, 4.70 mg/L, and 89.24 mg/L, respectively. 

EPA calibrated the model outputs by manipulating the sediment transport parameters until 

the modeled concentrations in the benthic segments closely matched the available sediment 

concentration monitoring data derived from STORET. Table G-29 presents the sediment transport 

parameters resulting from EPA’s calibration effort. EPA assumed the initial concentrations of 

organic solids, sands, and silts/fines in the benthic segments were equal to 500 mg/L each.

G-41 
 

 

Appendix G—Overview of Case Study Modeling Setup and Outputs

Model Results

Case study modeling of Lick Creek and the White River revealed water quality benchmark 

exceedances in the immediate receiving water and/or in downstream segments for arsenic, 

cadmium, copper, lead, selenium, and thallium. Figure G-9, Figure G-10, Figure G-11, and Figure 

G-12 illustrate the water concentration outputs for these pollutants in the immediate receiving 

water before and after the assumed compliance date for the final rule.9

Case study modeling of Lick Creek and the White River revealed that average water 

column concentrations of four pollutants (arsenic, cadmium, selenium, and thallium) in the 

immediate receiving water and/or downstream segments would trigger exceedances of wildlife

and/or human health benchmarks. Table G-30 and Table G-31 illustrate the average modeled 

pollutant concentration in each water column segment downstream of Petersburg Generating

Station (including the immediate receiving water) for baseline and following compliance with the 

final rule, respectively. Table G-32 and Table G-33 present the total miles with average water 

column concentrations translating to exceedances of these benchmarks for baseline and under the 

final rule, respectively. 

9

 To improve clarity, Figure G-9, Figure G-10, Figure G-11, and Figure G-12 present the baseline water column

concentrations leading up to the assumed compliance date of Petersburg Generating Station. All analyses of the 

WASP model outputs were performed on the baseline output after the assumed compliance date.

G-42 
Appendix G—Overview of Case Study M

Table G-23. USGS Stream Gages with Flow Data Used in Lick Creek and White River WASP 

Gage ID USGS Gage Location Stream Flow Record Period Cumulative Drainage Area Represented by Gage (sq km) Model Boundary Cumulative Dra

Area at Mod

Boundary (sq 

3374000 White River near Petersburg, IN Full Record from 04/01/1928 - 12/11/2013 28,825 West Fork White River 13,923 

3374000 White River near Petersburg, IN Full Record from 04/01/1928 - 12/11/2013 28,825 East Fork White River 14,880 

3360895 

Kessinger Ditch 

near Monroe City, 

IN

Full Record from 10/01/1992 

- 9/30/1998 64.27 a Lick Creek 4.46 b 

Acronyms: USGS (U.S. Geological Survey).a – This value represents the mean annual flow (in cfs), as defined by NHDPlus Version 1, at gage ID 3360895.b – This value represents the mean annual flow (in cfs), as defined by NHDPlus Version 1, of the Lick Creek immediate receiving water.

c – This value represents the scale factor determined by the dividend of the mean annual flow of at gage ID 3360895 and the Lick Creek im

G-43 
Appendix G—Overview of Case Study M

Table G-24. Stream Flow Data Periods – Lick Creek and White River WASP 

Model 

Modeling Period Corresponding Stream Flow Data Period 

White River (Gage ID 3374000) 

01/01/1986 - 12/11/2013 01/01/1986 - 12/11/2013 

12/12/2013 – 12/31/2018 12/12/2005 – 12/31/2010

01/01/2002 - 12/11/2029 01/01/1986 - 12/11/2013 

12/12/2029 – 12/31/2034 12/12/2005 – 12/31/2010

Kessinger Ditch (Gage ID 3360895)

01/01/1986 - 9/30/1986 01/01/1998 - 09/30/1998 10/01/1986 - 9/30/1992 10/01/1992 - 09/30/1998 10/01/1992 - 9/30/1998 10/01/1992 - 09/30/1998 10/01/1998 - 9/30/2004 10/01/1992 - 09/30/1998 10/01/2004 - 9/30/2010 10/01/1992 - 09/30/1998 10/01/2010 - 9/30/2016 10/01/1992 - 09/30/1998 

10/01/2016 - 12/31/2018 10/01/1992 - 12/31/1994 

01/01/2002 - 9/30/2002 01/01/1998 - 09/30/1998 10/01/2002 - 9/30/2008 10/01/1992 - 09/30/1998 10/01/2008 - 9/30/2014 10/01/1992 - 09/30/1998 10/01/2014 - 9/30/2020 10/01/1992 - 09/30/1998 10/01/2020 - 9/30/2026 10/01/1992 - 09/30/1998 10/01/2026 - 9/30/2032 10/01/1992 - 09/30/1998 

10/01/2032 - 12/31/2034 10/01/1992 - 12/31/1994 

G-44 
Appendix G—Overview of Case Study M

Table G-25. Pollutant Loadings – Petersburg Generating Station

Wastestream Pollutant Loadings (g/day) 

As Cd Cu Ni Pb Se 

Baseline a

 FGD Wastewater c 2.86 2.07 1.85 4.47 1.66 455.14 

Fly Ash Transport Water -- -­

-­ --

-­

-­ --

 Bottom Ash Transport Water 49.78 25.34 174.33 150.96 79.01 5.40 

 Combustion Residual Leachate -- -- -- -- -- -- 

Total 52.64 27.40 176.18 155.43 80.67 460.54 

Final Rule b

FGD Wastewater 2.86 2.07 1.85 3.09 1.66 2.81 

Fly Ash Transport Water -- -­

-­ --

-­

-­ --

Bottom Ash Transport Water -- -­

-­ --

-­

-­ --

 Combustion Residual Leachate -- -- -- -- -- -- 

Total 2.86 2.07 1.85 3.09 1.66 2.81 

Acronyms: FGD (flue gas desulfurization). a – The baseline pollutant loadings are modeled throughout the entire modeling period (from 01/01/1986 through 12/31/2034).b – The final rule pollutant loadings are modeled only after the assumed compliance date (from 01/01/2019 through 12/31/2034).c – In estimating the historical pollutant loadings associated with Petersburg Generating Station’s four FGD systems, EPA incorporated the 

FGD wastewater as the systems were installed, between 1977 and 1996. The pollutant loadings associated with FGD systems installed befomodeling period (01/01/1986) are incorporated at the beginning or the model. 

G-45 
Appendix G—Overview of Case Study M

Table G-26. Pollutant Contributions from Non-Steam Electric Point Sources – Lick Creek and White Riv

Facility Name Model COMID City Location (lat, long) Parameter Average Da

Cu 

Pride Mine S-321 a 18471050 (White River) Monroe City (38.54,-87.27) Ni 

Zn 

a – EPA identified that this industrial facility is a direct discharger with 2011 DMR loadings. 

Table G-27. Pollutant Contributions from STORET Monitoring Data – Lick Creek and White River 

Model Boundary Model Boundary COMID Station ID(s) (lat, long) Parameter Average Concentration (μg/L)a 

West Fork White 

River 18471042 

10947 (38.56,-87.24) 

2719 (38.56,-87.24) 

WWL090-0028 (35.55,-87.24)

As -- 

Cu -- 

Ni -- 

Pb -- 

Zn -- 

TOC 5,104.00 

TSS 104,000.00 

East Fork White 

River 18446060 2619 (38.54,-87.22) 

As -- 

Cd -- 

Cu -- 

Ni -- 

Pb -- 

Zn -- 

TOC 3,475.43 

TSS 62,087.96 

G-46 
Appendix G—Overview of Case Study M

Table G-27. Pollutant Contributions from STORET Monitoring Data – Lick Creek and White River 

Model Boundary Model Boundary COMID Station ID(s) (lat, long) Parameter Average Concentration (μg/L)a 

Conger Creek 18471078 

2511 (38.52,-87.45) 2513 (38.51,-87.45) 

WWL100-0002 (38.51,-87.44)

Cu -- 

Pb -- 

Zn -- 

TOC 5,700.00 

TSS 95,200.00 

Upper River 

Deshee 18471082 2512 (38.52,-87.53) 

Pb -- 

Zn -- 

TOC 3,120.00 

TSS 18,600.00 

Acronyms: TOC (Total Organic Carbon); TSS (Total Suspended Solids).a –Where more than one monitoring station located on the same tributary system reported acceptable results for the same pollutant, EPA cathe weighted average concentration across the monitoring stations (weighted by number of samples at each station). b – For the modeled pollutants (not including TOC and TSS), EPA converted the average concentration to a mass loading using the averagstream reach represented by the monitoring station(s). 

G-47 
Appendix G—Overview of Case Study M

Table G-28. Organic Solids, Sands, and Silts/Fines Inputs – Lick Creek and White River WASP 

Model Boundary Model Boundary COMID Organic Solids Concentration (mg/L)a Sands Concentration (mg/L)b Silts/

West Fork White River 18471042 2.55 5.20 

East Fork White River 18446060 1.74 3.10 

Conger Creek 18471078 2.85 4.76 

Upper River Deshee 18471082 1.56 0.93 

All Other Inflows d N/A 2.17 3.50 

Acronyms: N/A (Not Applicable).a – The organic solids concentration was calculated using Equation G-1 and the STORET monitoring data presented in Table G-27.b – The sands concentration was calculated using Equation G-2 and the STORET monitoring data presented in Table G-27.c – The silts/fines concentration was calculated using Equation G-3 and the STORET monitoring data presented in Table G-27. 

d – For tributaries where boundary concentrations from STORET monitoring data were not available, EPA assumed the average boundary 

tributaries entering the modeling area. 

Table G-29. Sediment Transport Parameters – Lick Creek and White River WASP Mode

Input Parameter Value Used Units

TAUcritcoh 3.5 N/m2

TAU_cD1_sia 3.5 N/m2TAU_cD2_sia 7.0 N/m2

TAU_cD1_POa 3.5 N/m2TAU_cD2_POa 7.0 N/m2

Note: Table G-1 presents additional solids constants and sediment transport parameters that are used in each of the case study models. a – This parameter is a WASP model default based on the value of the ‘TAUcritcoh’ parameter. 

G-48 
Appendix G—Overview of Case Study M

Figure G-9. Modeled Concentrations in Lick Creek Water Column at Petersburg Generating Station Imm

Water (Total Cadmium, Dissolved Cadmium) 

G-49 
Appendix G—Overview of Case Study M

Figure G-10. Modeled Concentrations in Lick Creek Water Column at Petersburg Generating Station Imm

Water (Total Selenium, Dissolved Copper) 

G-50 
Appendix G—Overview of Case Study M

Figure G-11. Modeled Concentrations in Lick Creek Water Column at Petersburg Generating Station Imm

Water (Total Arsenic, Total Thallium) 

G-51 
Appendix G—Overview of Case Study M

Figure G-12. Modeled Concentrations in Lick Creek Water Column at Petersburg Generating Station Imm

Water (Total Lead) 

G-52 
Appendix G—Overview of Case Study M

Table G-30. Average Water Column Concentrations Downstream of Petersburg Generating Station 

Segment Data Average Total Water Column Concentration over Mo

Segment ID Segment Name Segment Length (mi) Distance Downstream (mi) As Cd Cu Pb Ni Se 

76 Lick Creek / IRW 1.82 1.82 7.8099 1.4260 12.1623 2.2256 17.0962 43.0

16 White River 2.53 4.35 2.1741 0.0169 3.9202 1.4878 7.9745 0.0

15 White River 3.64 7.99 1.9842 0.0130 3.1428 1.0360 6.8940 0.0

14 White River 3.39 11.38 1.8988 0.0108 2.7187 0.7764 6.3429 0.0

13 White River 3.39 14.77 1.8498 0.0096 2.4878 0.6399 6.0350 0.0

12 White River 3.39 18.17 1.8294 0.0090 2.3642 0.5643 5.8819 0.0

11 White River 4.43 22.59 1.9038 0.0165 3.4944 1.4571 6.9169 0.0

10 White River 1.78 24.37 1.8990 0.0197 4.0254 1.8743 7.2995 0.0

9 White River 3.88 28.26 1.9106 0.0187 3.8692 1.7404 7.2015 0.0

8 White River 3.22 31.48 2.8165 0.0657 11.7204 7.8841 15.3397 0.0

7 White River 2.97 34.45 2.9378 0.0572 10.4477 6.5913 14.7231 0.0

6 White River 2.97 37.42 2.6471 0.0521 9.4987 6.0681 13.2868 0.0

5 White River 2.97 40.39 2.5550 0.0494 9.0307 5.7329 12.7097 0.0

4 White River 2.97 43.36 2.4986 0.0474 8.6786 5.4787 12.3055 0.0

3 White River 2.97 46.33 2.4569 0.0457 8.3900 5.2645 11.9847 0.0

2 White River 2.97 49.30 2.4265 0.0443 8.1520 5.0746 11.7264 0.0

1 White River / End 1.17 50.47 2.4061 0.0455 8.3071 5.2341 11.7954 0.0

Acronyms: IRW (Immediate receiving water). a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modelin

compliance date. 

G-53 
Appendix G—Overview of Case Study M

Table G-31. Average Water Column Concentrations Downstream of Petersburg Generating Station Un

Segment Data Average Total Water Column Concentration over Mo

Segment ID Segment Name

Segment 

Length 

(mi)

Distance 

Downstream 

(mi)

As Cd Cu Pb Ni Se 

76 Lick Creek / IRW 1.82 1.82 0.4306 0.1093 0.7301 0.0469 1.2803 0.2

16 White River 2.53 4.35 2.1711 0.0159 3.9132 1.4855 7.9669 0.0

15 White River 3.64 7.99 1.9815 0.0123 3.1377 1.0346 6.8877 0.0

14 White River 3.39 11.38 1.8962 0.0103 2.7144 0.7754 6.3372 0.0

13 White River 3.39 14.77 1.8473 0.0092 2.4838 0.6392 6.0295 0.0

12 White River 3.39 18.17 1.8269 0.0086 2.3604 0.5636 5.8767 0.0

11 White River 4.43 22.59 1.9010 0.0156 3.4867 1.4556 6.9088 0.0

10 White River 1.78 24.37 1.8961 0.0185 4.0157 1.8722 7.2905 0.0

9 White River 3.88 28.26 1.9077 0.0176 3.8599 1.7386 7.1928 0.0

8 White River 3.22 31.48 2.8120 0.0608 11.6855 7.8735 15.3177 0.0

7 White River 2.97 34.45 2.9331 0.0530 10.4162 6.5828 14.7021 0.0

6 White River 2.97 37.42 2.6430 0.0484 9.4716 6.0604 13.2683 0.0

5 White River 2.97 40.39 2.5510 0.0459 9.0055 5.7261 12.6922 0.0

4 White River 2.97 43.36 2.4948 0.0440 8.6545 5.4724 12.2886 0.0

3 White River 2.97 46.33 2.4531 0.0425 8.3679 5.2585 11.9682 0.0

2 White River 2.97 49.30 2.4228 0.0411 8.1243 5.0689 11.7104 0.0

1 White River / End 1.17 50.47 2.4024 0.0421 8.2818 5.2278 11.7788 0.0

Acronyms: IRW (Immediate receiving water). 

a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modelin

compliance date. 

G-54 
Appendix G—Overview of Case Study M

Table G-32. Total Miles of Lick Creek and White River with Wildlife And Human Health Impacts 

Wildlife and Human Health Impact Thresholds 

Total Miles with Average Water Column Concentration Translating to Wi

Benchmark Exceedances (mi) 

As Cd Cu Pb Ni Se 

WL - NEHC, T3 (mink) 0.00 0.00 0.00 0.00 0.00 1.82 

WL - NEHC, T4 (eagle) 0.00 0.00 0.00 0.00 0.00 1.82 

HH - Non-Cancer Adult Subsistence 0.00 0.00 0.00 No RfD 0.00 1.82 

HH - Non-Cancer Adult Recreational 0.00 0.00 0.00 No RfD 0.00 1.82 

HH - Non-Cancer Child Subsistence (1 to <2 y.o.) a 0.00 1.82 0.00 No RfD 0.00 1.82 

HH - Non-Cancer Child Subsistence (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 1.82 HH - Non-Cancer Child Recreational (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 1.82 HH - Non-Cancer Child Recreational (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 1.82 HH - Cancer Adult Subsistence 1.82 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Adult Recreational 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (6 to <11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (6 to 11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR 

Acronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration); Rfd (Reference dose); LECR (Lifetime excess caa – This row represents the most sensitive child fisher cohort. b – This row represents the least sensitive child fisher cohort. 

G-55 
Appendix G—Overview of Case Study M

Table G-33. Total Miles of Lick Creek and White River with Wildlife And Human Health Impacts Un

Wildlife and Human Health Impact Thresholds 

Total Miles with Average Water Column Concentration Translating to Wi

Benchmark Exceedances (mi) 

As Cd Cu Pb Ni Se 

WL - NEHC, T3 (mink) 0.00 0.00 0.00 0.00 0.00 0.00 WL - NEHC, T4 (eagle) 0.00 0.00 0.00 0.00 0.00 0.00 HH - Non-Cancer Adult Subsistence 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Adult Recreational 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Subsistence (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 0.00 

HH - Non-Cancer Child Subsistence (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Cancer Adult Subsistence 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Adult Recreational 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (6 to <11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (6 to 11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR 

Acronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration); Rfd (Reference dose); LECR (Lifetime excess caa – This row represents the most sensitive child fisher cohort. b – This row represents the least sensitive child fisher cohort. 

G-56 
Appendix G—Overview of Case Study Modeling Setup and Outputs 

CASE STUDY MODEL SETUPS AND OUTPUTS – OHIO RIVER, PA/WV/OH 

This section presents information regarding the site-specific design, site-specific input 

parameters (e.g., background pollutant concentrations, USGS time series flow data), model

settings (e.g., sediment transport parameters), and case study modeling results for the Ohio River 

case study model. 

Model Development & Input Variables 

WASP Model Design. The Ohio River WASP model starts approximately 12 miles

upstream of the first steam electric power plant immediate receiving water at COMID 3821033.

There are two coal-fired plants modeled in the Ohio River WASP simulation. The upstream plant, 

Bruce Mansfield plant, discharges to the Ohio River (COMID 3821113) from a large surface

impoundment named Little Blue Run. Approximately 13 miles downstream of this immediate

receiving water is the W.H. Sammis plant immediate receiving water (COMID 3821343). Ending 

just upstream of the Cardinal Plant immediate receiving water, the entire Ohio River WASP model 

is 49 miles long. 

The Ohio River WASP model consists of 84 modeled segments. Segment IDs 1-17 

represent the surface water of the Ohio River with Segment ID 1 being the most downstream 

segment and Segment ID 17 being the most upstream segment. The immediate receiving waters 

of the Bruce Mansfield plant and the W.H. Sammis plant are located at Segment ID 13 and 9, 

respectively. The remaining model segments represent tributary surface waters (Segment IDs 18­

28), the upper benthic layers (Segment IDs 29-56), and the lower benthic layers (Segment IDs 57­

84). Figure G-13 illustrates the segmentation of the Ohio River WASP model.

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 Bruce Mansfield 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 for W.H. Sammis Plant. 

Incorporation of Flow Data. EPA used USGS stream flow data from one USGS stream

gage to represent inflow at the upstream end of the modeling area of the Ohio River WASP model. 

EPA scaled the Ohio River stream gage data from Gage ID 03086000 to account for the difference 

in drainage area between the actual gage location and the point where the contributing flows enter 

the modeling area.

EPA used USGS stream flow data from three USGS stream gages to represent inflow from 

three tributaries to the Ohio River WASP modeling area, as described below: 

 EPA scaled the Little Beaver Creek stream gage data from Gage ID 03109500 to 

account for the difference in drainage area between the actual gage location and the 

point where the contributing flows enter the modeling area. 

 EPA scaled the Yellow Creek stream gage data from Gage ID 03110000 to account 

for the difference in drainage area between the actual gage location and the point 

where the contributing flows enter the modeling area.

G-57 
 

Figure G-13. Geographic Extent and Segmentation – Ohio River WASP Model 

Appendix G—Overview of Case Study Modeling Setup and Outputs

 EPA scaled the Raccoon Creek stream gage data from Gage ID 03108000 to account 

for the difference in drainage area between the actual gage location and the point 

where the contributing flows enter the modeling area.

Figure G-13 illustrates the two stream flow gages from which EPA incorporated USGS 

stream flow data. Table G-34 presents additional information about the four stream gages and the 

time period covered in the stream flow data record at each. Table G-35 presents how EPA 

incorporated the stream flow data from these stream gages into the model to complete a full 

record of flow data for the entire modeling period. For all other local inflows, EPA used the 

mean annual flow defined in NHDPlus Version 1. 

Model Input Variables. Table G-36 presents the pollutant loadings modeled from Bruce 

Mansfield plant at the evaluated wastestream level, both at baseline and after the plant achieves 

the limitations under the final rule. Table G-37 presents the pollutant loadings modeled from W.H. 

Sammis plant at the evaluated wastestream level, both at baseline and after the plant achieves the 

limitations under the final rule. 

Table G-38 presents the pollutant loadings modeled from non-steam electric point sources

with 2011 DMR or TRI loadings which would impact the Ohio River case study model. 

Table G-39 presents the pollutant contributions flowing into the Ohio River WASP model 

boundaries calculated using available STORET monitoring data. 

G-58 
 

 

Appendix G—Overview of Case Study Modeling Setup and Outputs

Table G-40 presents the initial concentrations for the organic solids, sands, and silts/fines 

values derived from STORET monitoring data collected. For tributaries where STORET 

monitoring data were not available, EPA assumed the average boundary concentration from all 

tributaries entering the modeling area. Based on the average of STORET data available within the 

model, EPA calculated the initial concentrations of organic solids, sands, and silts/fines in the 

water column segments were 1.36 mg/L, 0.57 mg/L, and 10.85 mg/L, respectively. 

EPA calibrated the model outputs by manipulating the sediment transport parameters until 

the modeled concentrations in the benthic segments closely matched the available sediment 

concentration monitoring data derived from STORET. Table G-41 presents the sediment transport 

parameters resulting from EPA’s calibration effort. EPA assumed the initial concentrations of 

organic solids, sands, and silts/fines in the benthic segments were equal to 100 mg/L each.

Model Results

Case study modeling of the Ohio River revealed water quality benchmark exceedances in 

the W.H. Sammis plant immediate receiving water and/or in downstream segments for arsenic and 

lead. Figure G-14 illustrates the water concentration outputs for these pollutants in the immediate 

receiving water before and after the assumed compliance date for the final rule.10

Case study modeling of the Ohio River revealed that average water column concentrations

of thallium in the W.H. Sammis plant immediate receiving water and/or downstream segments

would trigger exceedances of human health benchmarks. Figure G-15 illustrates the water 

concentration outputs for thallium in the W.H. Sammis plant immediate receiving water before 

and after the assumed compliance date for the final rule. Table G-42 and Table G-43 illustrate the 

average modeled pollutant concentration in each water column segment downstream of Bruce 

Mansfield plant (including the Bruce Mansfield plant immediate receiving water) for baseline and

following compliance with the final rule, respectively. Table G-44 and Table G-45 present the total 

miles with average water column concentrations translating to exceedances of these benchmarks 

for baseline and under the final rule, respectively. 

10 To improve clarity, Figure G-14 and Figure G-15 present the baseline water column concentrations leading up to

the assumed compliance date of Bruce Mansfield plant and W.H. Sammis plant. All analyses of the WASP model 

outputs were performed on the baseline output after the assumed compliance date.

G-59 
Appendix G—Overview of Case Study M

Table G-34. USGS Stream Gages with Flow Data Used in Ohio River WASP Model 

Gage ID USGS Gage Location Stream Flow Record Period Cumulative Drainage Area Represented by Gage (sq km) Model Boundary Cumulative Dr

Area at Mo

Boundary (sq 

3086000 Ohio River near Sewickley, PA Full Record from 01/01/1982 - 09/30/2013 50,475 Ohio River 58,947 

3109500 Little Beaver Creek Full Record from 01/01/1982 - 09/30/2013 1,286 Little Beaver Creek 1,345 

3110000 Yellow Creek Full Record from 01/01/1982 - 09/30/2013 382 Yellow Creek 612 

3108000 Raccoon Creek Full Record from 01/01/1982 - 09/30/2013 464 Raccoon Creek 477 

Acronyms: USGS (U.S. Geological Survey).

G-60 
Appendix G—Overview of Case Study M

Table G-35. Stream Flow Data Periods – Ohio River WASP Model 

Modeling Period Corresponding Stream Flow Data Period 

Ohio River (Gage ID 3086000) 

01/01/1982 - 09/30/2013 01/01/1982 - 09/30/2013 

10/01/2013 – 12/31/2020 10/01/2005 – 12/31/2012

01/01/1998 - 09/30/2029 01/01/1982 - 09/30/2013 

10/01/2029 – 12/31/2036 10/01/2005 – 12/31/2012

Little Beaver Creek (Gage ID 3109500) 

01/01/1982 - 09/30/2013 01/01/1982 - 09/30/2013 

10/01/2013 – 12/31/2020 10/01/2005 – 12/31/2012

01/01/1998 - 09/30/2029 01/01/1982 - 09/30/2013 

10/01/2029 – 12/31/2036 10/01/2005 – 12/31/2012

Yellow Creek (Gage ID 3110000)

01/01/1982 - 09/30/2013 01/01/1982 - 09/30/2013 

10/01/2013 – 12/31/2020 10/01/2005 – 12/31/2012

01/01/1998 - 09/30/2029 01/01/1982 - 09/30/2013 

10/01/2029 – 12/31/2036 10/01/2005 – 12/31/2012

Raccoon Creek (Gage ID 3108000) 

01/01/1982 - 09/30/2013 01/01/1982 - 09/30/2013 

10/01/2013 – 12/31/2020 10/01/2005 – 12/31/2012

01/01/1998 - 09/30/2029 01/01/1982 - 09/30/2013 

10/01/2029 – 12/31/2036 10/01/2005 – 12/31/2012

G-61 
Appendix G—Overview of Case Study M

Table G-36. Pollutant Loadings – Bruce Mansfield Plant

Wastestream Pollutant Loadings (g/day) 

As Cd Cu Ni Pb Se 

Baseline a

 FGD Wastewater 29.09 431.42 83.34 3,364.27 17.87 4,476.75 

Fly Ash Transport Water -- -­

-­ --

-­

-­ --

 Bottom Ash Transport Water 50.21 13.86 61.38 231.01 46.21 25.46 

 Combustion Residual Leachate -- -- -- -- -- -- 

 Total 79.30 445.28 144.72 3,595.28 64.08 4,502.21 Final Rule b

 FGD Wastewater 22.35 16.13 14.48 24.16 12.99 21.93 

Fly Ash Transport Water -- -­

-­ --

-­

-­ --

Bottom Ash Transport Water -- -­

-­ --

-­

-­ --

 Combustion Residual Leachate -- -- -- -- -- -- 

 Total 22.35 16.13 14.48 24.16 12.99 21.93 

Acronyms: FGD (flue gas desulfurization). a – The baseline pollutant loadings are modeled throughout the entire modeling period (from 01/01/1982 through 12/31/2036).b – The final rule pollutant loadings are modeled only after the assumed compliance date (from 01/01/2021 through 12/31/2036).

G-62 
Appendix G—Overview of Case Study M

Table G-37. Pollutant Loadings – W.H. Sammis Plant

Wastestream Pollutant Loadings (g/day) 

As Cd Cu Ni Pb Se 

Baseline a

 FGD Wastewater c 5.82 4.20 3.77 9.09 3.38 925.46 

Fly Ash Transport Water -- -­

-­ --

-­

-­ --

 Bottom Ash Transport Water 353.61 97.59 432.31 1,626.99 325.44 179.30 

 Combustion Residual Leachate 2.34 0.62 0.46 2.83 - 6.75  Total 361.77 102.41 436.54 1,638.91 328.82 1,111.51 

Final Rule b

 FGD Wastewater 5.82 4.20 3.77 6.29 3.38 5.71 

Fly Ash Transport Water -- -­

-­ --

-­

-­ --

Bottom Ash Transport Water -- -­

-­ --

-­

-­ --

 Combustion Residual Leachate 2.34 0.62 0.46 2.83 - 6.75 

 Total 8.16 4.82 4.23 9.12 3.38 12.46 

Acronyms: FGD (flue gas desulfurization). a – The baseline pollutant loadings are modeled from 01/01/1982 through 12/31/2036.b – The final rule pollutant loadings are modeled from 01/01/2021 through 12/31/2036.c - In estimating the historical pollutant loadings associated with W.H. Sammis plant’s three FGD systems, EPA incorporated the pollutant wastewater as the systems were installed, between March and May 2010. EPA did not model any FGD wastewater pollutant loadings befor

Sammis plant’s first FGD system.

G-63 
Appendix G—Overview of Case Study M

Table G-38. Pollutant Contributions from Non-Steam Electric Point Sources –Ohio River WASP 

Facility Name Model COMID City, State Location (lat, long) Parameter A

City of Chester a 3821165 (Ohio River) Chester, WV (40.61,-80.57)

Cu 

Pb 

Zn 

East Liverpool WWTP a 3821167 (Ohio River) East Liverpool, OH (40.62,-80.58) Cu 

Zn 

Town of Newell a 3821149 (Ohio River) Newell, WV (40.62,-80.61) 

Cu 

Pb 

Zn 

Wellsville STP a 3821273 (Ohio River) Wellsville, OH (40.60,-80.66) 

Cu 

Pb 

Zn 

Hancock County PSD a 3821301 (Ohio River) New Cumberland, WV (40.58,-80.66) Cu 

Pb 

Hancock County PSD WWTP a 3821355 (Ohio River) New Cumberland, WV (40.51,-80.62) 

Cu 

Pb 

Zn 

City of New Cumberland a 3824147 (Ohio River) New Cumberland, WV (40.49,-80.60) 

Cu 

Pb 

Zn 

Toronto WWTP a 3824175 (Ohio River) Toronto, OH (40.50,-80.61) Zn 

G-64 
Appendix G—Overview of Case Study M

Table G-38. Pollutant Contributions from Non-Steam Electric Point Sources –Ohio River WASP 

Facility Name Model COMID City, State Location (lat, long) Parameter A

City of Weirton a 3824185 (Ohio River) Weirton, WV (40.38,-80.61)

As 

Cd Cu 

Ni 

Pb 

Zn 

City of Steubenville, Wastewater 

Treatment Plant a

3824195 

(Ohio River) Steubenville, OH (40.36,-80.61) 

Cu 

Zn 

City of Follansbee a 3824211 (Ohio River) Follansbee, WV (40.32,-80.60) 

As 

Cd Cu 

Ni 

Pb 

Zn 

Mingo Junction WTP a 19453097 (Cross Creek) Mingo Junction, OH (40.31,-80.61) Cu 

City of Wellsburg a 19453103 (Ohio River) Wellsburg, WV (40.27,80.62) 

As 

Cd Cu 

Ni 

Pb 

Zn 

CBS Beaver Groundwater 

Remediation b

3821033 

(Two Mile Run) Beaver, PA (40.69,-80.31) Zn 

G-65 
Appendix G—Overview of Case Study M

Table G-38. Pollutant Contributions from Non-Steam Electric Point Sources –Ohio River WASP 

Facility Name Model COMID City, State Location (lat, long) Parameter A

Horsehead Corp Monaca Smelter b 3821033 (Ohio River) Monaca, PA (40.67,-80.34) 

As 

Cd Cu 

Pb 

Se 

Zn 

BASF Monaca Plant b 3821039 (Ohio River) Monaca, PA (40.66,-80.35) Zn 

Lyondell Chem Beaver Valley b 3821057 (Ohio River) Monaca, PA (40.66,-80.36) 

Cu 

Ni 

Pb 

Zn 

Allegheny Technologies Midland

Plant b

3821109 

(Ohio River) Midland, PA (40.64,-80.47) Ni 

Heritage-WTI Inc. b 3821157 (Ohio River) East Liverpool, OH (40.63,-80.55) 

As 

Cd 

Cu 

Ni 

Pb 

Zn 

Homer Laughlin China Co b 3821149 (Ohio River) Newell, WV (40.62,-80.61) 

Cd 

Ni 

Pb 

Se 

Zn 

G-66 
Appendix G—Overview of Case Study M

Table G-38. Pollutant Contributions from Non-Steam Electric Point Sources –Ohio River WASP 

Facility Name Model COMID City, State Location (lat, long) Parameter A

Ergon West Virginia Inc b 3821189 (Ohio River) Newell, WV (40.61,-80.63) 

As 

Cu 

Zn 

Marsh Bellofram Corporation b 3821301 (Ohio River) Newell, WV (40.58,-80.65) 

Cu 

Ni 

Pb 

Zn 

Mountaineer Park Incorporated b 3821301 (Ohio River) Chester, WV (40.57,-80.65)

Cu 

Pb 

Zn 

Titanium Metals Corp b 3824175 (Ohio River) Toronto, OH (40.45,-80.61) Cu 

Zn 

Mittal Steel USA Weirton Inc b 3824175 (Ohio River) Weirton, WV (40.43,-80.60)

Cu 

Ni 

Pb 

Se 

Zn 

Severstal Wheeling Inc - 

Steubenville Plant b

3824211 

(Ohio River) Steubenville, OH (40.35,-80.61) Zn 

Severstal Wheeling Inc - 

Follansbee b

3824211 

(Ohio River) Follansbee, WV (40.35,-80.61) 

As 

Cd 

Cu 

Ni 

Pb 

Se 

Zn 

G-67 
Appendix G—Overview of Case Study M

Table G-38. Pollutant Contributions from Non-Steam Electric Point Sources –Ohio River WASP 

Facility Name Model COMID City, State Location (lat, long) Parameter A

RG Steel Wheeling LLC Beech 

Bottom Plant b

3824211 

(Ohio River) Beech Bottom, WV (40.35,-80.61) 

As 

Cu 

Ni 

Pb 

Se 

Zn 

Koppers Follansbee Tar Plant b 3824211 (Ohio River) Follansbee, WV (40.34,-80.61) 

As 

Se 

Zn 

Wheeling-Nisshin b 3824211 (Ohio River) Follansbee, WV (40.33,-80.60) Pb 

Zn 

Wheeling Pittsburgh Steel 

Steubenville South Mingo b

3824211 

(Ohio River) Mingo Junction, OH (40.32,-80.60)

Cu 

Zn 

NGC Industries LLC A Subsidiary

c

3821097 

(Ohio River) Shippingport, PA (40.63,-80.42) Pb 

Whemco-Steel Castings Inc c 3821109 (Ohio River) Midland, PA (40.63,-80.45) Ni 

Mittal Steel USA Weirton Inc c 3824175 (Ohio River) Weirton, WV (40.42,-80.60)

Cu 

Ni 

Pb 

Zn 

a – EPA identified that this publicly operated treatment works (POTW) facility is a direct discharger with 2011 DMR loadings. b - EPA identified that this industrial facility is a direct discharger with 2011 DMR loadings. c - EPA identified that this facility is a direct discharger with 2011 TRI loadings. 

G-68 
Appendix G—Overview of Case Study M

Table G-39. Pollutant Contributions from STORET Monitoring Data – Ohio River WASP M

Model Boundary Model Boundary COMID Station ID(s) (lat, long) Parameter Average Concentration (μg/L)a 

Ohio River 3821033 WQN0902 (40.53,-80.19)

Cu -- 

Ni -- 

Pb -- 

Zn -- 

TOC 2,426.67 

TSS 21,434.78 

Raccoon Creek 3821043 WQN0903 (40.63,-80.34) 

Cu -- 

Ni -- 

Pb -- 

Zn -- 

TOC 2,232.63 

TSS 16,893.62 

Buffalo Creek 19453099 

O-092-0004 (40.26,-80.55) O-092-0003 (40.25,-80.59) O-092-0001 (40.24,-80.59) O-092-0012 (40.23,-80.52) O-092-0006 (40.20,-80.60) O-092-0002 (40.20,-80.56) O-092-0007 (40.19,-80.55) O-092-0008 (40.16,-80.53) 

TSS 10,333.33 

Acronyms: TOC (Total Organic Carbon); TSS (Total Suspended Solids).a –Where more than one monitoring station located on the same tributary system reported acceptable results for the same pollutant, EPA cathe weighted average concentration across the monitoring stations (weighted by number of samples at each station). b – For the modeled pollutants (not including TOC and TSS), EPA converted the average concentration to a mass loading using the averagstream reach represented by the monitoring station(s). 

G-69 
Appendix G—Overview of Case Study M

Table G-40. Organic Solids, Sands, and Silts/Fines Inputs – Ohio River WASP Model

Model Boundary Model Boundary COMID Organic Solids Concentration (mg/L)a Sands Concentration (mg/L)b Silts/

Ohio River 3821033 1.21 1.07 

Raccoon Creek 3821043 1.12 0.84 

Buffalo Creek 3821043 * 0.52 e 

All Other Inflows d N/A 1.16 0.81 

Acronyms: N/A (Not Applicable).* – No TOC results available. The ‘All Other Inflows’ concentration was used in this scenario. a – The organic solids concentration was calculated using Equation G-1 and the STORET monitoring data presented in Table G-39.b – The sands concentration was calculated using Equation G-2 and the STORET monitoring data presented in Table G-39.c – The silts/fines concentration was calculated using Equation G-3 and the STORET monitoring data presented in Table G-39. 

d – For tributaries where boundary concentrations from STORET monitoring data were not available, EPA assumed the average boundary 

tributaries entering the modeling area. e – These concentrations were calculated using the ‘All Other Inflows’ concentration.

Table G-41. Sediment Transport Parameters – Ohio River WASP Model

Input Parameter Value Used Units

TAUcritcoh 3.5 N/m2

TAU_cD1_sia 3.5 N/m2TAU_cD2_sia 7.0 N/m2

TAU_cD1_POa 3.5 N/m2TAU_cD2_POa 7.0 N/m2

Note: Table G-1 presents additional solids constants and sediment transport parameters that are used in each of the case study models. a – This parameter is a WASP model default based on the value of the ‘TAUcritcoh’ parameter. 

G-70 
Appendix G—Overview of Case Study M

Figure G-14. Modeled Concentrations in Ohio River Water Column at W.H. Sammis Plant Immediate R

(Total Arsenic, Total Lead) 

G-71 
Appendix G—Overview of Case Study M

Figure G-15. Modeled Concentrations in Ohio River Water Column at W.H. Sammis Plant Immediate R

(Total Thallium) 

G-72 
Appendix G—Overview of Case Study M

Table G-42. Average Water Column Concentrations Downstream of Bruce Mansfield Plant at B

Segment Data Average Total Water Column Concentration over Mo

Segment 

ID Segment Name

Segment 

Length 

(mi)

Distance 

Downstream 

(mi)

As Cd Cu Pb Ni Se 

13

Ohio River / MansfieldIRW 3.31 3.31 0.0020 0.0082 2.6416 0.6965 2.4564 0.08

12 Ohio River 3.71 7.02 0.0083 0.0094 2.8186 0.8586 2.4577 0.08

11 Ohio River 3.26 10.29 0.0083 0.0111 3.1227 0.9913 2.5719 0.09

10 Ohio River 2.40 12.69 0.0093 0.0145 3.9276 1.4032 3.0175 0.11

9 Ohio River / Sammis IRW 3.43 16.12 0.0158 0.0165 3.8615 1.4652 2.8946 0.12

8 Ohio River 3.88 20.00 0.0165 0.0147 3.6063 1.1281 2.9481 0.12

7 Ohio River 3.45 23.45 0.0157 0.0127 3.2123 0.9050 2.7435 0.12

6 Ohio River 1.76 25.21 0.0155 0.0121 3.0856 0.8119 2.6984 0.12

5 Ohio River 1.33 26.54 0.0157 0.0120 3.0046 0.7527 2.6689 0.11

4 Ohio River 2.02 28.56 0.0156 0.0117 2.9513 0.7228 2.6419 0.11

3 Ohio River 3.08 31.64 0.0209 0.0182 3.1309 0.8725 2.7427 0.18

2 Ohio River 3.06 34.70 0.0202 0.0183 3.0956 0.9017 2.6655 0.18

1 Ohio River / End 1.85 36.55 0.0285 0.0195 3.1928 0.9529 2.6998 0.18

Acronyms: IRW (Immediate receiving water). a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modelin

compliance date. 

G-73 
Appendix G—Overview of Case Study M

Table G-43. Average Water Column Concentrations Downstream of Bruce Mansfield Plant Under 

Segment Data Average Total Water Column Concentration over Mo

Segment 

ID Segment Name

Segment 

Length 

(mi)

Distance 

Downstream 

(mi)

As Cd Cu Pb Ni Se 

13

Ohio River / MansfieldIRW 3.31 3.31 0.0008 0.0011 2.6393 0.6959 2.3863 0.0

12 Ohio River 3.71 7.02 0.0072 0.0013 2.8161 0.8577 2.3875 0.0

11 Ohio River 3.26 10.29 0.0071 0.0016 3.1199 0.9900 2.4986 0.0

10 Ohio River 2.40 12.69 0.0080 0.0020 3.9241 1.4013 2.9313 0.0

9 Ohio River / Sammis IRW 3.43 16.12 0.0076 0.0021 3.8493 1.4561 2.7809 0.0

8 Ohio River 3.88 20.00 0.0080 0.0019 3.5949 1.1213 2.8337 0.0

7 Ohio River 3.45 23.45 0.0076 0.0016 3.2019 0.8995 2.6370 0.0

6 Ohio River 1.76 25.21 0.0075 0.0016 3.0756 0.8069 2.5936 0.0

5 Ohio River 1.33 26.54 0.0077 0.0018 2.9948 0.7481 2.5653 0.0

4 Ohio River 2.02 28.56 0.0077 0.0018 2.9417 0.7183 2.5393 0.0

3 Ohio River 3.08 31.64 0.0130 0.0075 3.1209 0.8674 2.6388 0.0

2 Ohio River 3.06 34.70 0.0125 0.0076 3.0855 0.8961 2.5642 0.0

1 Ohio River / End 1.85 36.55 0.0208 0.0084 3.1826 0.9468 2.5974 0.0

Acronyms: IRW (Immediate receiving water). a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modelin

compliance date. 

G-74 
Appendix G—Overview of Case Study M

Table G-44. Total Miles of Ohio River with Wildlife And Human Health Impacts at Baseli

Wildlife and Human Health Impact Thresholds 

Total Miles with Average Water Column Concentration Translating to Wi

Benchmark Exceedances (mi) 

As Cd Cu Pb Ni Se 

WL - NEHC, T3 (mink) 0.00 0.00 0.00 0.00 0.00 0.00 WL - NEHC, T4 (eagle) 0.00 0.00 0.00 0.00 0.00 0.00 HH - Non-Cancer Adult Subsistence 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Adult Recreational 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Subsistence (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 0.00 

HH - Non-Cancer Child Subsistence (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Cancer Adult Subsistence 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Adult Recreational 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (6 to <11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (6 to 11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR 

Acronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration); Rfd (Reference dose); LECR (Lifetime excess caa – This row represents the most sensitive child fisher cohort. b – This row represents the least sensitive child fisher cohort. 

G-75 
Appendix G—Overview of Case Study M

Table G-45. Total Miles of Ohio River with Wildlife And Human Health Impacts Under Final 

Wildlife and Human Health Impact Thresholds 

Total Miles with Average Water Column Concentration Translating to Wi

Benchmark Exceedances (mi) 

As Cd Cu Pb Ni Se 

WL - NEHC, T3 (mink) 0.00 0.00 0.00 0.00 0.00 0.00 WL - NEHC, T4 (eagle) 0.00 0.00 0.00 0.00 0.00 0.00 HH - Non-Cancer Adult Subsistence 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Adult Recreational 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Subsistence (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 0.00 

HH - Non-Cancer Child Subsistence (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Cancer Adult Subsistence 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Adult Recreational 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (6 to <11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (6 to 11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR 

Acronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration); Rfd (Reference dose); LECR (Lifetime excess caa – This row represents the most sensitive child fisher cohort. b – This row represents the least sensitive child fisher cohort. 

G-76 
Appendix G—Overview of Case Study Modeling Setup and Outputs 

CASE STUDY MODEL SETUPS AND OUTPUTS – MISSISSIPPI RIVER, MO/IL 

This section presents information regarding the site-specific design, site-specific input 

parameters (e.g., background pollutant concentrations, USGS time series flow data), model

settings (e.g., sediment transport parameters), and case study modeling results for the Mississippi

River case study model. 

Model Development & Input Variables 

WASP Model Design. The Mississippi River WASP model encompasses a 46-mile-long 

reach of the Mississippi River, 23 miles of which is downstream of the Rush Island plant 

immediate receiving water (COMID 3629181). The model has two start boundaries that are on the 

Meramec River (COMID 5052703) and Mississippi River (COMID 3629071) shortly upstream of 

their confluence. This model ends at the confluence of the Mississippi River and Kaskaskia River 

(COMID 5089872). 

The Mississippi River WASP model consists of 90 modeled segments. Segment IDs 1-16 

represent the surface water of the Ohio River with Segment ID 1 being the most downstream 

segment and Segment ID 16 being the most upstream segment. The Meramec River start boundary, 

which is also the Meramec plant’s immediate receiving water (COMID 5052703), is represented

by Segment ID 17. The immediate receiving water of the Rush Island is located at Segment ID 9. 

The remaining model segments represent tributary surface waters (Segment IDs 18-30), the upper 

benthic layers (Segment IDs 31-60), and the lower benthic layers (Segment IDs 61-90). Figure

G-16 illustrates the segmentation of the Mississippi River WASP model. 

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 the Rush Island plant’s immediate receiving water and 

downstream reaches, EPA focused the assessment of the baseline impacts and improvements under

the final rule on the period after the 2023 assumed compliance date for the Rush Island plant. 

Incorporation of Flow Data. EPA used USGS stream flow data from one USGS stream

gage to represent inflow at the upstream end of the modeling area of the Mississippi River WASP 

model. EPA scaled the Mississippi River stream gage data from Gage ID 07010000 to account for 

the difference in drainage area between the actual gage location and the point where the

contributing flows enter the modeling area. 

EPA used USGS stream flow data from one other USGS stream gages to represent inflow 

from the Meramec River, a tributary to the Mississippi River WASP modeling area. EPA scaled

the Meramec River stream gage data from Gage ID 07019000 to account for the difference in 

drainage area between the actual gage location and the point where the contributing flows enter 

the modeling area.

Figure G-16 illustrates the two stream flow gages from which EPA incorporated USGS 

stream flow data. Table G-46 presents additional information about the four stream gages and the 

time period covered in the stream flow data record at each. Table G-47 presents how EPA 

incorporated the stream flow data from these stream gages into the model to complete a full record

G-77 
 

Figure G-16. Geographic Extent and Segmentation – Mississippi River WASP Model 

Appendix G—Overview of Case Study Modeling Setup and Outputs

of flow data for the entire modeling period. For all other local inflows, EPA used the mean annual 

flow defined in NHDPlus Version 1. 

Model Input Variables. Table G-48 presents the pollutant loadings modeled from Bruce 

Meramec plant at the evaluated wastestream level, both at baseline and after the plant achieves the 

limitations under the final rule. Table G-49 presents the pollutant loadings modeled from Rush 

Island plant at the evaluated wastestream level, both at baseline and after the plant achieves the 

limitations under the final rule. 

Table G-50 presents the pollutant loadings modeled from non-steam electric point sources

with 2011 DMR or TRI loadings which would impact the Mississippi River case study model. 

Table G-51 presents the pollutant contributions flowing into the Mississippi River WASP 

model boundaries calculated using available STORET monitoring data. 

Table G-52 presents the initial concentrations for the organic solids, sands, and silts/fines 

values derived from STORET monitoring data collected. For tributaries where STORET 

monitoring data were not available, EPA assumed the average boundary concentration from all 

tributaries entering the modeling area. Based on the average of STORET data available within the 

model, EPA calculated the initial concentrations of organic solids, sands, and silts/fines in the 

water column segments were 2.74 mg/L, 2.73 mg/L, and 51.94 mg/L, respectively. 

EPA calibrated the model outputs by manipulating the sediment transport parameters until 

the modeled concentrations in the benthic segments closely matched the available sediment 

G-78 
 

 

 

Appendix G—Overview of Case Study Modeling Setup and Outputs

concentration monitoring data derived from STORET. Table G-53 presents the sediment transport 

parameters resulting from EPA’s calibration effort. EPA assumed the initial concentrations of 

organic solids, sands, and silts/fines in the benthic segments were equal to 100 mg/L each.

Model Results

Case study modeling of the Mississippi River revealed water quality benchmark 

exceedances in the immediate receiving water and/or in downstream segments for arsenic. Figure 

G-17 illustrates the water concentration outputs for arsenic in the Rush Island plant immediate 

receiving water before and after the assumed compliance date for the final rule.11

Case study modeling of the Mississippi River revealed that average water column 

concentrations of arsenic in the Rush Island plant’s immediate receiving water and/or downstream 

segments would trigger exceedances of human health benchmarks. Table G-54 and Table G-55

illustrate the average modeled pollutant concentration in each water column segment downstream

of the Rush Island plant (including the immediate receiving water) for baseline and following 

compliance with the final rule, respectively. Table G-56 and Table G-57 present the total miles 

with average water column concentrations translating to exceedances of these benchmarks for

baseline and under the final rule, respectively. 

11 To improve clarity, Figure G-17 presents the baseline water column concentrations leading up to the assumed

compliance date of Rush Island plant. All analyses of the WASP model outputs were performed on the baseline

output after the assumed compliance date.

G-79 
Appendix G—Overview of Case Study M

Table G-46. USGS Stream Gages with Flow Data Used in Mississippi River WASP Mode

Gage ID USGS Gage Location Stream Flow Record Period Cumulative Drainage Area Represented by Gage (sq km) Model Boundary Cumulative Dr

Area at Mo

Boundary (sq 

7010000 Mississippi River near St. Louis, MO Full Record from 01/01/1880 - 11/19/2014 1,668,452 Mississippi River 1,667,867 

7019000 Meramec River near Eureka, MO Full Record from 10/01/1903 - 02/04/2015 9,811 Meramec River 10,264 

Acronyms: USGS (U.S. Geological Survey).

Table G-47. Stream Flow Data Periods – Mississippi River WASP Model 

Modeling Period Corresponding Stream Flow Data Period 

Mississippi River (Gage ID 7010000)

01/01/1982 - 09/30/2014 01/01/1982 - 09/30/2014 

10/01/2014 – 12/31/2020 10/01/2002 – 12/31/2008

01/01/1998 - 09/30/2030 01/01/1982 - 09/30/2014 

10/01/2030 – 12/31/2036 10/01/2002 – 12/31/2008

Meramec River (Gage ID 7019000)

01/01/1982 - 09/30/2014 01/01/1982 - 09/30/2014 

10/01/2014 – 12/31/2020 10/01/2002 – 12/31/2008

01/01/1998 - 09/30/2030 01/01/1982 - 09/30/2014 

10/01/2030 – 12/31/2036 10/01/2002 – 12/31/2008

G-80 
Appendix G—Overview of Case Study M

Table G-48. Pollutant Loadings – Meramec Plant 

Wastestream Pollutant Loadings (g/day) 

As Cd Cu Ni Pb Se 

Baseline a

FGD Wastewater -- -­

-­ --

-­

-­ --

Fly Ash Transport Water -- -­

-­ --

-­

-­ --

 Bottom Ash Transport Water 425.25 117.36 519.89 1,956.61 391.37 215.63  Combustion Residual Leachate -- -- -- -- -- -- 

 Total 425.25 117.36 519.89 1,956.61 391.37 215.63 

Final Rule b

FGD Wastewater -- -­

-­ --

-­

-­ --

Fly Ash Transport Water -- -­

-­ --

-­

-­ --

Bottom Ash Transport Water -- -­

-­ --

-­

-­ --

 Combustion Residual Leachate -- -- -- -- -- -- 

 Total -- -­

-­ --

-­

-­ --

Acronyms: FGD (flue gas desulfurization). a – The baseline pollutant loadings are modeled throughout the entire modeling period (from 01/01/1982 through 12/31/2036).b – The final rule pollutant loadings are modeled only after the assumed compliance date (from 01/01/2019 through 12/31/2036).

G-81 
Appendix G—Overview of Case Study M

Table G-49. Pollutant Loadings – Rush Island Plant 

Wastestream Pollutant Loadings (g/day) 

As Cd Cu Ni Pb Se 

Baseline a

FGD Wastewater -- -­

-­ --

-­

-­ --

 Fly Ash Transport Water 2,617.69 338.24 1,490.40 1,152.47 1,054.61 1,171.40  Bottom Ash Transport Water 109.07 55.52 381.96 330.76 173.11 11.83 

 Combustion Residual Leachate -- -- -- -- -- -- 

 Total 2,726.76 393.76 1,872.36 1,483.22 1,227.72 1,183.23 

Final Rule b

FGD Wastewater -- -­

-­ --

-­

-­ --

Fly Ash Transport Water -- -­

-­ --

-­

-­ --

Bottom Ash Transport Water -- -­

-­ --

-­

-­ --

 Combustion Residual Leachate -- -- -- -- -- -- 

 Total -- -­

-­ --

-­

-­ --

Acronyms: FGD (flue gas desulfurization). a – The baseline pollutant loadings are modeled from 01/01/1982 through 12/31/2022.b – The final rule pollutant loadings are modeled from 01/01/2023 through 12/31/2036.

G-82 
Appendix G—Overview of Case Study M

Table G-50. Pollutant Contributions from Non-Steam Electric Point Sources – Mississippi River W

Facility Name Model COMID City, State Location (lat, long) Parameter Average Da

MSD Meramec Treatment 

Plant a

3629071 

(Mississippi River) St. Louis, MO (38.39,-90.34) 

As 

Cd Cu 

Ni 

Pb 

Zn 

Doe Run Co Herculaneum

Smelter b

3629127 

(Mississippi River) Herculaneum, MO (38.26,-90.38) 

Cd Cu 

Pb 

Zn 

Doe Run Co Herculaneum

Smelter c

3634867 d

(Joachim Creek) Herculaneum, MO (38.26,-90.38) 

As 

Cd Cu 

Ni 

Pb 

Zn 

a – EPA identified that this publicly operated treatment works (POTW) facility is a direct discharger with 2011 DMR loadings. b - EPA identified that this industrial facility is a direct discharger with 2011 DMR loadings. c - EPA identified that this facility is also an indirect discharger with 2011 TRI loadings. d – These pollutant loadings for Doe Run Co Herculaneum are indirectly discharged to Joachim Creek via the Herculaneum Sewer District 

G-83 
Appendix G—Overview of Case Study M

Table G-51. Pollutant Contributions from STORET Monitoring Data – Mississippi River WASP 

Model Boundary Model Boundary COMID Station ID(s) (lat, long) Parameter Average Concentration (μg/L)a 

Mississippi River 3629071 

1707.02/3.7 (38.43,-90.29)

GRW04449-331 (38.41,-90.32)

J-36 (38.40,-90.32) 

1707.03/41.0 (38.36,-90.36)

As -- 

Cd -- Cu -- 

Ni -- 

Pb -- 

Zn -- 

TSS 220,098.26 

TOC 5,298.95 

Maeystown Creek 3629179 JD-02 (38.21,-90.26) 

As -- 

Cd -- 

Cu -- 

Ni -- 

Pb -- 

Zn -- 

TOC 3,928.00 

TSS 43,000.00 

South Gabouri

Creek 3630453 1707.02/121/0.9/1.5 (37.97,-90.06) TSS 5,000.00 

Acronyms: TOC (Total Organic Carbon); TSS (Total Suspended Solids).a –Where more than one monitoring station located on the same tributary system reported acceptable results for the same pollutant, EPA cathe weighted average concentration across the monitoring stations (weighted by number of samples at each station). b – For the modeled pollutants (not including TOC and TSS), EPA converted the average concentration to a mass loading using the averagstream reach represented by the monitoring station(s). 

G-84 
Appendix G—Overview of Case Study M

Table G-52. Organic Solids, Sands, and Silts/Fines Inputs – Mississippi River WASP Mod

Model Boundary Model Boundary COMID Organic Solids Concentration (mg/L)a Sands Concentration (mg/L)b Silts/

Mississippi River 3629071 2.65 11.00 

Maeystown Creek 3629179 1.96 2.15 

South Gabouri Creek 3630453 * 0.25 e 

All Other Inflows d N/A 2.31 4.47 

Acronyms: N/A (Not Applicable).* – No TOC results available. The ‘All Other Inflows’ concentration was used in this scenario. a – The organic solids concentration was calculated using Equation G-1 and the STORET monitoring data presented in Table G-51.b – The sands concentration was calculated using Equation G-2 and the STORET monitoring data presented in Table G-51.c – The silts/fines concentration was calculated using Equation G-3 and the STORET monitoring data presented in Table G-51. 

d – For tributaries where boundary concentrations from STORET monitoring data were not available, EPA assumed the average boundary 

tributaries entering the modeling area. e – These concentrations were calculated using the ‘All Other Inflows’ concentration.

Table G-53. Sediment Transport Parameters – Mississippi River WASP Model

Input Parameter Value Used Units

TAUcritcoh 5.0 N/m2

TAU_cD1_sia 5.0 N/m2TAU_cD2_sia 10.0 N/m2

TAU_cD1_POa 5.0 N/m2TAU_cD2_POa 10.0 N/m2

Note: Table G-1 presents additional solids constants and sediment transport parameters that are used in each of the case study models. a – This parameter is a WASP model default based on the value of the ‘TAUcritcoh’ parameter. 

G-85 
Appendix G—Overview of Case Study M

Figure G-17. Modeled Concentrations in Mississippi River Water Column at Rush Island Plant Immediat

(Total Arsenic) 

G-86 
Appendix G—Overview of Case Study M

Table G-54. Average Water Column Concentrations Downstream of Rush Island Plant at Bas

Segment Data Average Total Water Column Concentration over Mo

Segment 

ID Segment Name

Segment 

Length 

(mi)

Distance 

Downstream 

(mi)

As Cd Cu Pb Ni Se 

9 Mississippi River / Rush Island IRW 1.48 1.48 3.2912 0.1287 3.5878 3.5149 8.7116 0.00

8 Mississippi River 2.69 4.17 4.0944 0.1237 3.5546 3.2102 9.5052 0.00

7 Mississippi River 4.33 8.49 3.0972 0.1171 3.2754 3.1789 8.0477 0.00

6 Mississippi River 2.21 10.70 3.1050 0.1174 3.2833 3.1859 8.0684 0.00

5 Mississippi River 1.25 11.95 3.1057 0.1174 3.2834 3.1858 8.0693 0.00

4 Mississippi River 2.93 14.88 3.1055 0.1173 3.2816 3.1835 8.0667 0.00

3 Mississippi River 1.40 16.27 3.1065 0.1173 3.2819 3.1834 8.0682 0.00

2 Mississippi River 1.92 18.19 3.1078 0.1173 3.2820 3.1831 8.0699 0.00

1 Mississippi River / End 5.06 23.25 3.1123 0.1173 3.2832 3.1830 8.0766 0.00

Acronyms: IRW (Immediate receiving water). a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modelin

compliance date. 

G-87 
Appendix G—Overview of Case Study M

Table G-55. Average Water Column Concentrations Downstream of Rush Island Plant Under Fi

Segment Data Average Total Water Column Concentration over Mo

Segment 

ID Segment Name

Segment 

Length 

(mi)

Distance 

Downstream 

(mi)

As Cd Cu Pb Ni Se 

9 Mississippi River / Rush Island IRW 1.48 1.48 3.2833 0.1275 3.5819 3.5109 8.7034 0.0

8 Mississippi River 2.69 4.17 4.0847 0.1225 3.5488 3.2066 9.4964 0.0

7 Mississippi River 4.33 8.49 3.0898 0.1159 3.2700 3.1753 8.0402 0.0

6 Mississippi River 2.21 10.70 3.0976 0.1162 3.2779 3.1823 8.0609 0.0

5 Mississippi River 1.25 11.95 3.0984 0.1162 3.2780 3.1822 8.0618 0.0

4 Mississippi River 2.93 14.88 3.0982 0.1161 3.2763 3.1799 8.0592 0.0

3 Mississippi River 1.40 16.27 3.0992 0.1162 3.2765 3.1798 8.0607 0.0

2 Mississippi River 1.92 18.19 3.1004 0.1162 3.2767 3.1795 8.0624 0.0

1 Mississippi River / End 5.06 23.25 3.1049 0.1162 3.2779 3.1795 8.0691 0.0

Acronyms: IRW (Immediate receiving water). a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modelin

compliance date. 

G-88 
Appendix G—Overview of Case Study M

Table G-56. Total Miles of Mississippi River with Wildlife And Human Health Impacts at Ba

Wildlife and Human Health Impact Thresholds 

Total Miles with Average Water Column Concentration Translating to W

Benchmark Exceedances (mi) 

As Cd Cu Pb Ni Se 

WL - NEHC, T3 (mink) 0.00 0.00 0.00 0.00 0.00 0.00 

WL - NEHC, T4 (eagle) 0.00 0.00 0.00 0.00 0.00 0.00 

HH - Non-Cancer Adult Subsistence 0.00 0.00 0.00 No RfD 0.00 0.00 

HH - Non-Cancer Adult Recreational 0.00 0.00 0.00 No RfD 0.00 0.00 

HH - Non-Cancer Child Subsistence (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 0.00 

HH - Non-Cancer Child Subsistence (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Cancer Adult Subsistence 23.25 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Adult Recreational 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (6 to <11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (6 to 11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR 

Acronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration); Rfd (Reference dose); LECR (Lifetime excess caa – This row represents the most sensitive child fisher cohort. b – This row represents the least sensitive child fisher cohort. 

G-89 
Appendix G—Overview of Case Study M

Table G-57. Total Miles of Mississippi River with Wildlife And Human Health Impacts Under Fi

Wildlife and Human Health Impact Thresholds 

Total Miles with Average Water Column Concentration Translating to Wi

Benchmark Exceedances (mi) 

As Cd Cu Pb Ni Se 

WL - NEHC, T3 (mink) 0.00 0.00 0.00 0.00 0.00 0.00 WL - NEHC, T4 (eagle) 0.00 0.00 0.00 0.00 0.00 0.00 HH - Non-Cancer Adult Subsistence 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Adult Recreational 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Subsistence (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 0.00 

HH - Non-Cancer Child Subsistence (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (1 to <2 y.o.) a 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Non-Cancer Child Recreational (16 to <21 y.o.) b 0.00 0.00 0.00 No RfD 0.00 0.00 HH - Cancer Adult Subsistence 23.25 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Adult Recreational 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (6 to <11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR 

HH - Cancer Child Subsistence (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (6 to 11 y.o.) a 0.00 No LECR No LECR No LECR No LECR No LECR HH - Cancer Child Recreational (1 to <2 y.o.) b 0.00 No LECR No LECR No LECR No LECR No LECR 

Acronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration); Rfd (Reference dose); LECR (Lifetime excess caa – This row represents the most sensitive child fisher cohort. b – This row represents the least sensitive child fisher cohort. 

G-90 
 

 

 

Appendix G—Overview of Case Study Modeling Setup and Outputs

CASE STUDY MODEL SETUPS AND OUTPUTS – LAKE SINCLAIR, GA 

This section presents information regarding the site-specific design, site-specific input 

parameters (e.g., background pollutant concentrations, EFDC model flow data), model settings 

(e.g., sediment transport parameters), and case study modeling results for the Lake Sinclair case

study model. 

Model Development & Input Variables 

WASP Model Design. As discussed in Section 8.1.1 of the EA Report, EPA relied on the 

availability of an existing water quality model to perform case study modeling of Lake Sinclair. 

In contrast to the lotic case study models, the Lake Sinclair WASP model relies on Environmental 

Fluid Dynamics Code (EFDC) hydrodynamics to simulate the aquatic system in three

dimensions.12 The scope of the Lake Sinclair WASP model is limited by the boundaries of the preexisting EFDC hydrodynamics. The modeling area encompasses the main body of Lake Sinclair, 

from Wallace Dam to Sinclair Dam, and the major tributaries feeding into the Lake.

The three-dimensional EFDC model, which provides the hydrodynamic foundation for the

WASP model, divides the waterbody into 1,235 segments. Each segment represents a unique 

location and stratum within Lake Sinclair. The EFDC model uses stretch or sigma vertical 

coordinates and Cartesian coordinates to represent the physical characteristics of Lake Sinclair. 

Plant Harllee Branch’s immediate receiving water is identified by the coordinate code I=30 J=32 

K=5, where each coordinate represents the position on x, y, and z axes, respectively. The Lake 

Sinclair model does not have any segments representing benthic sediment. The model accounts for 

a total volume of approximately 340 million cubic meters.

As discussed earlier in this section, EPA adopted the preexisting Lake Sinclair EFDC 

model. The pre-existing model was designed with seven years of hydrodynamic and flow input, 

limiting the length of the period EPA could model. Based on Plant Harllee Branch’s NPDES 

permitting cycle, EPA assumed that the plant would have achieved the limitations under the final 

rule by 2019, if it continued to operate. The modeling period begins in February 2012 

(approximately seven years before the assumed compliance date) and extends through November 

2025 (approximately seven years after the assumed compliance date). 

Incorporation of Flow Data. EPA did not incorporate any USGS flow data into the Lake 

Sinclair WASP model. Instead, EPA used the seven years of hydrodynamic and flow input 

integrated into the EFDC model. Table G-58 presents how the EFDC hydrodynamic data were 

incorporated into the model to complete a full record of flow data for the entire modeling period. 

Model Input Variables. As discussed in Section 8.2.6 of the EA Report, Plant Harllee 

Branch retired all of coal-fired generating units in April 2015. Despite the retirement of this plant, 

EPA proceeded with case study modeling of Lake Sinclair to represent the potential impacts of 

steam electric discharges on lentic waterbodies. Table G-59 presents the pollutant loadings

modeled from Plant Harllee Branch at the evaluated wastestream level, both at baseline and after 

12 The Black Creek, Etowah River, Lick Creek and White River, Ohio River, and Mississippi River case study

models relied on NHDPlus Version 1 hydrodynamics for simulating lotic aquatic systems. 

G-91 
 

 

 

Appendix G—Overview of Case Study Modeling Setup and Outputs

the plant achieves the limitations under the final rule.13 EPA did not identify any point sources 

with 2011 DMR or TRI loadings which would impact the Lake Sinclair case study model. 

Table G-60 presents the pollutant contributions flowing into the Lake Sinclair WASP 

model boundaries calculated using available STORET monitoring data. 

Table G-61 presents the initial concentrations for the organic solids, sands, and silts/fines 

values derived from STORET monitoring data collected. For tributaries where STORET 

monitoring data were not available, EPA assumed the average boundary concentration from all 

tributaries entering the modeling area. Based on the average of STORET data available within the 

model, EPA calculated the initial concentrations of organic solids, sands, and silts/fines in the 

water column segments were 1.91 mg/L, 0.20 mg/L, and 3.85 mg/L, respectively. 

Model Results

Case study modeling of Lake Sinclair revealed water quality benchmark exceedances in 

the immediate receiving water and neighboring segments for arsenic and thallium. Figure G-18 

illustrates the water concentration outputs averaged for all model segments before and after the 

assumed compliance date for the final rule.14 Case study modeling also revealed frequent (more 

than 50 percent of the modeling period) water quality benchmark exceedances of three pollutants 

(arsenic, cadmium, and thallium) in some segments of Lake Sinclair. 

Case study modeling of the Lake Sinclair revealed that the average water column

concentrations of thallium of all segments in the WASP model would trigger exceedances of

human health benchmarks. 

13 EPA calculated pollutant loadings at the wastestream level for Plant Harllee Branch using the same loadings 

methodology that EPA used for other plants in the loadings analyses. EPA did not include Plant Harllee Branch or

Lake Sinclair in the other quantitative and qualitative analyses in this EA for the final rule (e.g., the IRW model).

14 To improve clarity, Figure G-18 presents the baseline water column concentrations leading up to the assumed

compliance date of Plant Harllee Branch. All analyses of the WASP model outputs were performed on the baseline

output after the assumed compliance date.

G-92 
Appendix G—Overview of Case Study M

Table G-58. Stream Flow Data Periods – Lake Sinclair WASP Model 

Modeling Period Corresponding Stream Flow Data Period 

Lake Sinclair (EFDC Hydrodynamic Model)

02/01/2012 – 12/31/2018 2/1/2001 – 12/31/2007 01/01/2019 – 11/30/2025 2/1/2001 – 12/31/2007 

G-93 
Appendix G—Overview of Case Study M

Table G-59. Pollutant Loadings – Plant Harllee Branch

Wastestream Pollutant Loadings (g/day) 

As Cd Cu Ni Pb Se 

Baseline a

 FGD Wastewater c 35.18 521.69 100.78 4,068.20 21.61 5,413.46 

 Fly Ash Transport Water 44.28 12.01 97.91 55.28 39.77 14.80 

 Bottom Ash Transport Water 22.29 6.15 27.25 102.56 20.52 11.30 

 Combustion Residual Leachate -- -- -- -- -- -- 

 Total 101.75 539.85 225.94 4,226.04 81.90 5,439.56 Final Rule b

 FGD Wastewater 27.03 19.50 17.50 29.21 15.71 26.51 

Fly Ash Transport Water -- -­

-­ --

-­

-­ --

Bottom Ash Transport Water -- -­

-­ --

-­

-­ --

 Combustion Residual Leachate -- -- -- -- -- -- 

 Total 27.03 19.50 17.50 29.21 15.71 26.51 

Acronyms: FGD (flue gas desulfurization). Note: Plant Harllee Branch has retired all coal-fired generating units. EPA calculated pollutant loadings at the wastestream level for Plant H

same loadings methodology that EPA used for other plants in the loadings analyses. EPA did not include Plant Harllee Branch in the other qualitative analyses in this EA for the final rule (e.g., the IRW model).a – The baseline pollutant loadings are modeled throughout the entire modeling period (from 02/01/2012 through 11/30/2025).b – The final rule pollutant loadings are modeled only after the assumed compliance date (from 01/01/2019 through 11/30/2025).c - In estimating the historical pollutant loadings associated with Plant Harllee Branch’s FGD systems, EPA incorporated the pollutant load

wastewater when the system was installed in 2013. EPA did not model any FGD wastewater pollutant loadings before the installation of Pl

system. 

G-94 
Appendix G—Overview of Case Study M

Table G-60. Pollutant Contributions from STORET Monitoring Data – Lake Sinclair WASP M

Model Boundary Model Boundary COMID Station ID(s) (lat, long) Parameter Average Concentration (μg/L)a 

Oconee River 1057503 

0301100602 (33.35,-83.16) 

3038901 (33.35,-83.16)

0301100603 (33.33,-83.14) 

TOC 3,818.44 

TSS 6,941.46 

Crooked Creek 1056407 0301180202 (33.32,-83.28) 

TOC 7,124.62 

TSS 18,992.31 

Rooty Creek 1057629 

0301180301 (33.32,-83.27) 

3040101 (33.32,-83.37)

0301180302 (33.29,-83.35) 

3040501 (33.29,-83.25)

As -- 

Cd -- 

Cu -- 

Ni -- 

Pb -- 

Tl -- 

Zn -- 

TOC 5,347.26 

TSS 11,635.71 

Little River 1057681 

3042001 (33.30,-83.42)

0301150301 (33.29,-83.43) 0301150302 (33.29,-83.43) 

3041701 (33.31,-83.44)

0301150102 (33.31,-83.44) 

As -- 

Cd -- 

Cu -- 

Ni -- 

Pb -- 

Tl -- 

Zn -- 

TOC 4,960.21 

TSS 15,576.92 

G-95 
Appendix G—Overview of Case Study M

Table G-60. Pollutant Contributions from STORET Monitoring Data – Lake Sinclair WASP M

Model Boundary Model Boundary COMID Station ID(s) (lat, long) Parameter Average Concentration (μg/L)a 

Murder Creek 1057679 

0301160703 (33.27,-83.48) 

3043401 (33.25,-83.48)

0301160701 (33.25,-83.48) 

As -- 

Cd -- 

Cu -- 

Ni -- 

Pb -- 

Tl -- 

Zn -- 

TOC 2,773.47 

TSS 21,383.33 

Big Cedar Creek 1056893 3043801 (33.19,-83.44) 0301170401 (33.19,-83.44) 

As -- 

Cd -- 

Cu -- 

Ni -- 

Pb -- 

Tl -- 

Zn -- 

TOC 3,407.30 

TSS 20,223.08 

Acronyms: TOC (Total Organic Carbon); TSS (Total Suspended Solids).a –Where more than one monitoring station located on the same tributary system reported acceptable results for the same pollutant, EPA cathe weighted average concentration across the monitoring stations (weighted by number of samples at each station). b – For the modeled pollutants (not including TOC and TSS), EPA converted the average concentration to a mass loading using the averagstream reach represented by the monitoring station(s). 

G-96 
Appendix G—Overview of Case Study M

Table G-61. Organic Solids, Sands, and Silts/Fines Inputs – Lake Sinclair WASP Model

Model Boundary Model Boundary COMID Organic Solids Concentration (mg/L)a Sands Concentration (mg/L)b Silts/

Oconee River 1057503 1.91 0.35 

Crooked Creek 1056407 3.56 0.95 

Rooty Creek 1057629 2.67 0.58 

Little River 1057681 2.48 0.78 

Murder Creek 1057679 1.39 1.07 

Big Cedar Creek 1056893 1.70 1.01 

All Other Inflows d N/A 2.29 0.79 

Acronyms: N/A (Not Applicable).a – The organic solids concentration was calculated using Equation G-1 and the STORET monitoring data presented in Table G-60.b – The sands concentration was calculated using Equation G-2 and the STORET monitoring data presented in Table G-60.c – The silts/fines concentration was calculated using Equation G-3 and the STORET monitoring data presented in Table G-60. 

d – For tributaries where boundary concentrations from STORET monitoring data were not available, EPA assumed the average boundary 

tributaries entering the modeling area. 

Table G-62. Sediment Transport Parameters – Lake Sinclair WASP Model

Input Parameter Value Used Units

TAUcritcoh 3.5 N/m2

TAU_cD1_sia 3.5 N/m2TAU_cD2_sia 7.0 N/m2

TAU_cD1_POa 3.5 N/m2TAU_cD2_POa 7.0 N/m2

Note: Table G-1 presents additional solids constants and sediment transport parameters that are used in each of the case study models. a – This parameter is a WASP model default based on the value of the ‘TAUcritcoh’ parameter. 

G-97 
Appendix G—Overview of Case Study M

Figure G-18. Average Modeled Concentrations in All Segments in Lake Sinclair WASP Model (Total Arsen

G-98 
 

 

 

 

 

 

 

 

 

 

Appendix H—Additional Model Results 

APPENDIX H 

ADDITIONAL MODEL RESULTS 

Table H-1. Number and Percentage of Immediate Receiving Waters that Exceeded a 

Criterion by Pollutant and Criteria Type at Baseline Pollutant Loadings 

Pollutant 

Number of Immediate Receiving Waters that Exceeded a Criterion a

Freshwater 

Acute 

NRWQC

Freshwater 

Chronic 

NRWQC

Human 

Health 

Water and 

Organism 

NRWQC

Human 

Health 

Organism 

Only 

NRWQC

Drinking

Water 

MCL

Total Receiving Waters b 

Number

Exceeding 

Percentage

Exceeding 

Arsenic 3 (c) 4 (c) 94 (d) 65 (d) 12 94 45%

Cadmium 9 (c) 29 (c) No

criterion

No

criterion 11 29 14%

Chromium VI 0 (c) 0 (c) No

criterion

No

criterion 0 (e) 0 0%

Copper 6 (c) 7 (c) 0 No

criterion

0 (f); 

1 (g) 7 3%

Lead 0 (c) 5 (c) No

criterion

No

criterion 7 (f) 7 3%

Mercury 1 (c) 1 (c) No

criterion

No

criterion 5 (d) 5 2%

Nickel 2 (c) 8 (c) 4 0 No

criterion 8 4%

Selenium No criterion 33 8 1 12 33 16%

Thallium No criterion No criterion 49 45 34 49 23% 

Zinc 4 (c) 4 (c) 1 0 1 (g) 4 2%

Source: ERG, 2015d; ERG, 2015h. 

Acronyms: MCL (Maximum Contaminant Level); NRWQC (National Recommended Water Quality Criteria). 

a – A total of 209 immediate receiving waters (183 rivers and streams; 26 lakes, ponds, and reservoirs) were

included in the water quality model. Table C-7 presents the criteria used for the analysis. 

b – These values are the sum and percentage of rivers, streams, lakes, ponds, and reservoirs impacted. 

c – NRWQC is expressed in terms of the dissolved pollutant in the water column. 

d – NRWQC or MCL is for inorganic form of metal. For the benchmark comparison, EPA used the total pollutant

concentration in the water column. This might overestimate the number of exceedances. 

e – MCL is for total chromium.

f - MCL used for comparison is the drinking water action level. 

g – MCL used for comparison is a secondary (nonenforceable) drinking water standard. 

H-1
 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015h. 

0 

10 

20 

30 

40 

50 

60

Number of Immediate Receiving Waters 

Total Arsenic Concentration in Receiving Water (mg/L) 

Figure H-1. Baseline Total Arsenic Concentration in the 

Immediate Receiving Water 

Table H-2. Total Arsenic Concentration (mg/L) in the Immediate Receiving Water by 

Percentile 

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 3.45E-08 2.07E-08 2.07E-08 0 0 0

25th 9.61E-07 6.28E-07 6.28E-07 1.21E-07 0 0

50th 7.88E-06 5.49E-06 5.49E-06 2.82E-06 3.62E-07 1.93E-07

75th 0.001 4.40E-04 4.40E-04 9.23E-05 1.62E-05 9.68E-06

95th 0.016 0.008 0.008 0.006 0.003 9.76E-04

Max 1.86 1.86 1.86 1.86 1.86 1.13

Source: ERG, 2015d; ERG, 2015h. 

H-2
 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015h. 

0 

10 

20 

30 

40 

50 

60

Number of Immediate Receiving Waters 

Total Cadmium Concentration in Receiving Water (mg/L) 

Figure H-2. Baseline Total Cadmium Concentration in the 

Immediate Receiving Water 

Table H-3. Total Cadmium Concentration (mg/L) in the Immediate Receiving Water by 

Percentile 

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 1.43E-08 1.04E-08 1.04E-08 0 0 0

25th 5.10E-07 2.25E-07 2.25E-07 5.15E-08 0 0

50th 5.15E-06 2.10E-06 2.10E-06 9.87E-07 1.54E-07 1.36E-07

75th 1.75E-04 1.22E-04 1.22E-04 3.66E-05 8.42E-06 6.99E-06

95th 0.005 0.003 0.003 0.002 0.001 7.04E-04

Max 0.490 0.490 0.490 0.490 0.490 0.204 

Source: ERG, 2015d; ERG, 2015h. 

H-3
 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015h. 

Table H-4. Chromium VI Concentration (mg/L) in the Immediate Receiving Water by 

Percentile 

0 

20 

40 

60 

80 

100 

120 

140 

160 

Number of Immeidate Receiving Waters 

Chromium VI Concentration in Receiving Water (mg/L) 

Figure H-3. Chromium VI Concentration in the Immediate 

Receiving Water 

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 0 0 0 0 0 0 

25th 0 0 0 0 0 0 

50th 0 0 0 0 0 0 

75th 0 0 0 0 0 0 

95th 5.38E-06 1.33E-06 1.33E-06 7.87E-08 0 0

Max 0.019 0.013 0.013 0.013 0.013 0.013 

Source: ERG, 2015d; ERG, 2015h. 

H-4
 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015h. 

0 

10 

20 

30 

40 

50 

60

Number of Immediate Receiving Waters 

Total Copper Concentration in Receiving Water (mg/L) 

Figure H-4. Baseline Total Copper Concentration in the 

Immediate Receiving Water 

Table H-5. Total Copper Concentration (mg/L) in the Immediate Receiving Water by 

Percentile 

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 1.64E-08 1.01E-08 1.01E-08 0 0 0

25th 8.86E-07 5.37E-07 5.37E-07 7.86E-08 0 0

50th 8.30E-06 6.27E-06 6.27E-06 1.57E-06 1.33E-07 1.21E-07

75th 2.81E-04 2.33E-04 2.33E-04 4.21E-05 7.10E-06 6.27E-06

95th 0.015 0.009 0.009 0.002 0.001 6.32E-04

Max 1.15 0.778 0.778 0.778 0.778 0.778

Source: ERG, 2015d; ERG, 2015h. 

H-5
 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015h.

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

50

Number of Immediate Receiving Waters 

Total Lead Concentration in Receiving Water (mg/L) 

Figure H-5. Baseline Total Lead Concentration in the 

Immediate Receiving Water 

Table H-6. Total Lead Concentration (mg/L) in the Immediate Receiving Water by 

Percentile 

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 1.41E-09 0 0 0 0 0 

25th 4.47E-07 2.22E-07 2.22E-07 1.36E-09 0 0

50th 3.61E-06 2.91E-06 2.91E-06 3.65E-07 2.65E-09 2.65E-09

75th 7.65E-05 6.98E-05 6.98E-05 5.99E-06 4.47E-07 4.47E-07

95th 0.009 0.007 0.007 0.001 7.22E-05 7.22E-05

Max 0.757 0.510 0.510 0.510 0.510 0.510 

Source: ERG, 2015d; ERG, 2015h. 

H-6
 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015h. 

0 

10 

20 

30 

40 

50 

60 

70 

80

Number of Immediate Receiving Waters 

Total Mercury Concentration in Receiving Water (mg/L) 

Figure H-6. Baseline Total Mercury Concentration in the 

Immediate Receiving Water 

Table H-7. Total Mercury Concentration (mg/L) in the Immediate Receiving Water by 

Percentile 

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 1.70E-09 5.32E-10 3.94E-10 0 0 0

25th 4.50E-08 2.29E-08 1.86E-08 1.86E-09 0 0

50th 3.56E-07 1.79E-07 1.77E-07 6.24E-08 4.20E-09 2.32E-09

75th 1.68E-05 1.34E-05 1.28E-05 2.31E-06 2.14E-07 1.05E-07

95th 0.001 2.62E-04 2.58E-04 1.15E-04 4.17E-05 8.96E-06

Max 0.056 0.020 0.020 0.020 0.020 0.020 

Source: ERG, 2015d; ERG, 2015h. 

H-7
 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015h. 

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

50

Number of Immediate Receiving Waters 

Total Nickel Concentration in Receiving Water (mg/L) 

Figure H-7. Baseline Total Nickel Concentration in the 

Immediate Receiving Water 

Table H-8. Total Nickel Concentration (mg/L) in the Immediate Receiving Water by 

Percentile 

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 7.14E-08 4.16E-08 3.00E-08 0 0 0

25th 3.31E-06 1.31E-06 1.11E-06 1.86E-07 0 0

50th 3.34E-05 1.81E-05 1.81E-05 4.58E-06 4.17E-07 2.47E-07

75th 0.001 0.001 0.001 1.37E-04 1.62E-05 1.05E-05

95th 0.049 0.034 0.033 0.008 0.004 0.002

Max 2.25 2.25 2.25 2.25 2.25 0.616

Source: ERG, 2015d; ERG, 2015h. 

H-8
 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015h. 

Table H-9. Total Selenium Concentration (mg/L) in the Immediate Receiving Water by 

Percentile 

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

50

Number of Immediate Receiving Waters 

Total Selenium Concentration in Receiving Water (mg/L) 

Figure H-8. Baseline Total Selenium Concentration in the 

Immediate Receiving Water 

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 9.12E-08 3.84E-08 2.05E-08 0 0 0

25th 2.74E-06 2.46E-06 5.01E-07 1.19E-07 0 0

50th 5.46E-05 3.67E-05 5.30E-06 2.35E-06 3.82E-07 3.82E-07

75th 0.001 0.001 3.08E-04 9.68E-05 2.61E-05 2.61E-05

95th 0.064 0.040 0.017 0.013 0.010 0.010

Max 5.38 5.38 5.38 5.38 5.38 5.38

Source: ERG, 2015d; ERG, 2015h. 

H-9
  

 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015h.

0 

10 

20 

30 

40 

50 

60

Number of Immediate Receiving Waters 

Total Thallium Concentration in Receiving Water (mg/L) 

Figure H-9. Baseline Total Thallium Concentration in the 

Immediate Receiving Water 

Table H-10. Total Thallium Concentration (mg/L) in the Immediate Receiving Water by 

Percentile 

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 1.09E-08 5.95E-09 5.95E-09 0 0 0

25th 1.31E-06 7.82E-07 7.82E-07 6.08E-08 0 0

50th 1.49E-05 1.20E-05 1.20E-05 2.33E-06 1.89E-07 1.89E-07

75th 1.91E-04 1.54E-04 1.54E-04 3.71E-05 5.87E-06 5.87E-06

95th 0.035 0.033 0.033 0.004 3.42E-04 3.42E-04

Max 1.75 1.75 1.75 1.75 0.591 0.591

Source: ERG, 2015d; ERG, 2015h. 

H-10
 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015h. 

0 

10 

20 

30 

40 

50 

60

Number of Immediate Receiving Waters 

Total Zinc Concentration in Receiving Water (mg/L) 

Figure H-10. Baseline Total Zinc Concentration in the 

Immediate Receiving Water 

Table H-11. Total Zinc Concentration (mg/L) in the Immediate Receiving Water by 

Percentile 

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 2.07E-07 9.14E-08 9.14E-08 0 0 0

25th 5.40E-06 2.43E-06 2.43E-06 4.67E-07 0 0

50th 6.37E-05 2.12E-05 2.12E-05 1.10E-05 1.44E-06 7.84E-07

75th 0.002 0.002 0.002 4.11E-04 7.72E-05 3.54E-05

95th 0.081 0.039 0.039 0.032 0.019 0.003

Max 10.2 10.2 10.2 10.2 10.2 1.43

Source: ERG, 2015d; ERG, 2015h. 

H-11
 

 

 

 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015i.

0 

10 

20 

30 

40 

50 

60

Number of Immediate Receiving Waters 

Total Arsenic Concentration in Fish Tissue (mg/kg) 

Figure H-11. Baseline Total Arsenic Concentration in 

Trophic Level 3 and Trophic Level 4 Fish Tissue in the 

Immediate Receiving Water a 

a – The wildlife module applies the same total arsenic bioconcentration factors (BCFs) for both trophic level 3 (T3)

and trophic level 4 (T4) fish (see Appendix D). Therefore, the estimated concentrations presented here are identical 

for both trophic levels.

Table H-12. Total Arsenic Concentration (mg/kg) in Fish Tissue (Trophic Level 3 & 

Trophic Level 4) by Percentile a

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 1.38E-07 8.28E-08 8.28E-08 0 0 0

25th 3.85E-06 2.51E-06 2.51E-06 4.86E-07 0 0

50th 3.15E-05 2.20E-05 2.20E-05 1.13E-05 1.45E-06 7.71E-07

75th 0.002 0.002 0.002 3.69E-04 6.49E-05 3.87E-05

95th 0.062 0.032 0.032 0.024 0.014 0.004

Max 7.45 7.45 7.45 7.45 7.45 4.53

Source: ERG, 2015d; ERG, 2015i.

a – The wildlife module applies the same total BCFs for both trophic level 3 (T3) and trophic level 4 (T4) fish (see 

Appendix D). Therefore, the estimated concentrations presented here are identical for both trophic levels.

H-12
 

     

 

 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015i.

0 

10 

20 

30 

40 

50 

60

Number of Immediate Receiving Waters 

Total Cadmium Concentration in Fish Tissue (mg/kg) 

Figure H-12. Baseline Total Cadmium Concentration in 

Trophic Level 3 and Trophic Level 4 Fish Tissue in the 

Immediate Receiving Water a 

a – The wildlife module applies the same total cadmium BCFs for both T3 and T4 fish (see Appendix DError!

Reference source not found.). Therefore, the estimated concentrations presented here are identical for both 

trophic levels. 

Table H-13. Total Cadmium Concentration (mg/kg) in Fish Tissue (Trophic Level 3 & 

Trophic Level 4) by Percentile a

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 3.85E-06 2.81E-06 2.81E-06 0 0 0

25th 1.38E-04 6.08E-05 6.08E-05 1.39E-05 0 0

50th 0.001 5.67E-04 5.67E-04 2.66E-04 4.17E-05 3.67E-05

75th 0.047 0.033 0.033 0.010 0.002 0.002

95th 1.40 0.738 0.738 0.505 0.332 0.190

Max 132 132 132 132 132 55.1 

Source: ERG, 2015d; ERG, 2015i.

a – The wildlife module applies the same total cadmium BCFs for both trophic level 3 (T3) and trophic level 4 (T4)

fish (see Appendix D). Therefore, the estimated concentrations presented here are identical for both trophic levels.

H-13
 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015i.

0 

50 

100 

150 

200 

250 

Number of Immediate Receiving Waters 

Chromium VI Concentration in Fish Tissue (mg/kg) 

Figure H-13. Baseline Chromium VI Concentration in 

Trophic Level 3 and Trophic Level 4 Fish Tissue in the 

Immediate Receiving Water a 

a – BCFs for chromium VI are not available; EPA used the total chromium BCF values. The wildlife module applies 

the same total chromium BCFs for both T3 and T4 fish (see Appendix D). Therefore, the estimated concentrations

presented here are identical for both trophic levels.

Table H-14. Chromium VI Concentration (mg/kg) in Fish Tissue (Trophic Level 3 & 

Trophic Level 4) by Percentile a

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 0 0 0 0 0 0 

25th 0 0 0 0 0 0 

50th 0 0 0 0 0 0 

75th 0 0 0 0 0 0 

95th 3.67E-07 5.18E-08 5.18E-08 3.91E-09 0 0

Max 0.011 0.008 0.008 0.008 0.008 0.008 

Source: ERG, 2015d; ERG, 2015i.

a – The wildlife module applies the same total chromium BCFs for both trophic level 3 (T3) and trophic level 4 (T4)

fish (see Appendix D). Therefore, the estimated concentrations presented here are identical for both trophic levels.

H-14
 

 

 

 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015i.

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

50

Number of Immediate Receiving Waters 

Total Copper Concentration in Fish Tissue (mg/kg) 

Figure H-14. Total Copper Concentration in Trophic Level 3 

and Trophic Level 4 Fish Tissue in the Immediate Receiving 

Water a 

a – The wildlife module applies the same total copper BCFs for both T3 and T4 fish (see Appendix D). 

Therefore, the estimated concentrations presented here are identical for both trophic levels. 

Table H-15. Total Copper Concentration (mg/kg) in Fish Tissue (Trophic Level 3 & 

Trophic Level 4) by Percentile a

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 5.89E-07 3.65E-07 3.65E-07 0 0 0

25th 3.19E-05 1.93E-05 1.93E-05 2.83E-06 0 0

50th 2.99E-04 2.26E-04 2.26E-04 5.66E-05 4.78E-06 4.36E-06

75th 0.010 0.008 0.008 0.002 2.56E-04 2.26E-04

95th 0.540 0.340 0.340 0.072 0.036 0.023

Max 41.5 28.0 28.0 28.0 28.0 28.0

Source: ERG, 2015d; ERG, 2015i.

a – The wildlife module applies the same total copper BCFs for both trophic level 3 (T3) and trophic level 4 (T4)

fish (see Appendix D). Therefore, the estimated concentrations presented here are identical for both trophic levels.

H-15
 

 

 

 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015i.

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

50

Number of Immediate Receiving Waters 

Total Lead Concentration in Fish Tissue (mg/kg) 

Figure H-15. Total Lead Concentration in Trophic Level 3 

and Trophic Level 4 Fish Tissue in the Immediate Receiving 

Water a 

a – The wildlife module applies the same total lead BCFs for both T3 and T4 fish (see Appendix D). Therefore, the

estimated concentrations presented here are identical for both trophic levels. 

Table H-16. Total Lead Concentration (mg/kg) in Fish Tissue (Trophic Level 3 & 

Trophic Level 4) by Percentile a

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 0 0 0 0 0 0 

25th 2.12E-06 7.94E-07 7.94E-07 0 0 0

50th 7.01E-05 4.95E-05 4.95E-05 5.57E-06 0 0

75th 0.001 0.001 0.001 1.83E-04 1.03E-05 1.03E-05

95th 0.343 0.319 0.319 0.047 0.002 0.002

Max 34.8 23.5 23.5 23.5 23.5 23.5

Source: ERG, 2015d; ERG, 2015i.

a – The wildlife module applies the same total lead BCFs for both trophic level 3 (T3) and trophic level 4 (T4) fish

(see Appendix D). Therefore, the estimated concentrations presented here are identical for both trophic levels.

H-16
 

 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015i.

0 

10 

20 

30 

40 

50 

60

Number of Immediate Receiving Waters 

Methylmercury Concentration in Fish Tissue (mg/kg) 

Figure H-16. Methylmercury Concentration in Trophic Level 

3 Fish Tissue in the Immediate Receiving Water 

Table H-17. Methylmercury Concentration (mg/kg) in Fish Tissue (Trophic Level 3) by 

Percentile a

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 2.86E-05 1.63E-05 9.58E-06 0 0 0

25th 0.001 8.10E-04 4.69E-04 5.71E-05 0 0

50th 0.010 0.005 0.005 0.001 1.76E-04 9.28E-05

75th 0.455 0.314 0.279 0.045 0.006 0.004

95th 16.826 9.42 9.42 2.66 1.43 0.230 

Max 414.6 183 183 183 183 183 

Source: ERG, 2015d; ERG, 2015i.

a – EPA calculated methylmercury fish tissue concentrations using bioaccumulation factors which do not fully 

account for the complexity of biogeochemical reactions that can occur within an aquatic environment and result in 

lower bioaccumulation rates of mercury in fish. For example, fish are known to bioaccumulate mercury at lower

rates when exposed to surface waters with high selenium concentrations. In addition, bioaccumulation factors do not 

account for a maximum limit a fish could accumulate before a lethal concentration is reached. To address the 

outliers in mercury fish tissue concentrations, EPA compared fish tissue concentrations to site-specific data available 

in the national fish advisory database and established calibration factors to lower the outlier values. Fish tissue 

concentrations presented in the figure and table above represent the uncalibrated values calculated by the wildlife 

model. For further details on the methodology for selecting calibration factors see ERG memorandum “EA Model 

Validation and Calibration” (DCN SE04454). 

H-17
 

 

 

 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015i.

0 

10 

20 

30 

40 

50 

60

Number of Immediate Receiving Waters 

Methylmercury Concentration in Fish Tissue (mg/kg) 

Figure H-17. Methylmercury Concentration in Trophic Level 

4 Fish Tissue in the Immediate Receiving Water 

Table H-18. Methylmercury Concentration (mg/kg) in Fish Tissue (Trophic Level 4) by 

Percentile a

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 1.21E-04 6.91E-05 4.07E-05 0 0 0

25th 0.005 0.003 0.002 2.43E-04 0 0

50th 0.044 0.021 0.020 0.006 7.48E-04 3.94E-04

75th 1.93 1.33 1.19 0.190 0.027 0.017

95th 71.5 40.1 40.1 11.3 6.07 0.976

Max 1,762 779 779 779 779 779 

Source: ERG, 2015d; ERG, 2015i.

a – EPA calculated methylmercury fish tissue concentrations using bioaccumulation factors which do not fully 

account for the complexity of biogeochemical reactions that can occur within an aquatic environment and result in 

lower bioaccumulation rates of mercury in fish. For example, fish are known to bioaccumulate mercury at lower

rates when exposed to surface waters with high selenium concentrations. In addition, bioaccumulation factors do not 

account for a maximum limit a fish could accumulate before a lethal concentration is reached. To address the 

outliers in mercury fish tissue concentrations, EPA compared fish tissue concentrations to site-specific data available 

in the national fish advisory database and established calibration factors to lower the outlier values. Fish tissue 

concentrations presented in the figure and table above represent the uncalibrated values calculated by the wildlife 

model. For further details on the methodology for selecting calibration factors see ERG memorandum “EA Model 

Validation and Calibration” (DCN SE04454). 

H-18
 

 

 

 

 

 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015i.

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

50

Number of Immediate Receiving Waters 

Total Nickel Concentration in Fish Tissue (mg/kg) 

Figure H-18. Total Nickel Concentration in Trophic Level 3 

and Trophic Level 4 Fish Tissue in the Immediate Receiving 

Water a 

a – The wildlife module applies the same total nickel BCFs for both T3 and T4 fish (see Appendix D). Therefore,

the estimated concentrations presented here are identical for both trophic levels.

Table H-19. Total Nickel Concentration (mg/kg) in Fish Tissue (Trophic Level 3 & 

Trophic Level 4) by Percentile a

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 5.71E-08 3.33E-08 2.40E-08 0 0 0

25th 2.65E-06 1.05E-06 8.88E-07 1.49E-07 0 0

50th 2.67E-05 1.44E-05 1.44E-05 3.66E-06 3.34E-07 1.98E-07

75th 0.001 0.001 0.001 1.09E-04 1.30E-05 8.37E-06

95th 0.040 0.027 0.027 0.007 0.003 0.001

Max 1.80 1.80 1.80 1.80 1.80 0.493

Source: ERG, 2015d; ERG, 2015i.

a – The wildlife module applies the same total nickel BCFs for both trophic level 3 (T3) and trophic level 4 (T4) fish

(see Appendix D). Therefore, the estimated concentrations presented here are identical for both trophic levels.

H-19
 

 

 

 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015i.

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

50

Number of Immediate Receiving Waters 

Total Selenium Concentration in Fish Tissue (mg/kg) 

Figure H-19. Total Selenium Concentration in Trophic Level 

3 Fish Tissue in the Immediate Receiving Water 

Table H-20. Total Selenium Concentration (mg/kg) in Fish Tissue (Trophic Level 3) by 

Percentile 

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 4.47E-05 1.88E-05 1.01E-05 0 0 0

25th 0.001 0.001 2.45E-04 5.83E-05 0 0

50th 0.027 0.018 0.003 0.001 1.87E-04 1.87E-04

75th 0.428 0.374 0.151 0.047 0.013 0.013

95th 31.6 19.5 8.12 6.55 4.86 4.86

Max 2,638 2,638 2,638 2,638 2,638 2,638

Source: ERG, 2015d; ERG, 2015i.

H-20
 

 

 

 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015i.

0 

5 

10 

15 

20 

25 

30 

35 

40 

45

Number of Immediate Receiving Waters 

Total Selenium Concentration in Fish Tissue (mg/kg) 

Figure H-20. Total Selenium Concentration in Trophic Level 

4 Fish Tissue in the Immediate Receiving Water 

Table H-21. Total Selenium Concentration (mg/kg) in Fish Tissue (Trophic Level 4) by 

Percentile 

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 1.55E-04 6.54E-05 3.49E-05 0 0 0

25th 0.005 0.004 8.51E-04 2.02E-04 0 0

50th 0.093 0.062 0.009 0.004 6.50E-04 6.50E-04

75th 1.48 1.30 0.523 0.165 0.044 0.044

95th 110 67.5 28.2 22.7 16.9 16.9

Max 9,151 9,151 9,151 9,151 9,151 9,151

Source: ERG, 2015d; ERG, 2015i.

H-21
 

 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015i.

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

50

Number of Immediate Receiving Waters 

Total Thallium Concentration in Fish Tissue (mg/kg) 

Figure H-21. Total Thallium Concentration in Trophic Level 

3 Fish Tissue in the Immediate Receiving Water 

Table H-22. Total Thallium Concentration (mg/kg) in Fish Tissue (Trophic Level 3) by 

Percentile 

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 3.70E-07 2.02E-07 2.02E-07 0 0 0

25th 4.46E-05 2.66E-05 2.66E-05 2.07E-06 0 0

50th 5.05E-04 4.07E-04 4.07E-04 7.91E-05 6.43E-06 6.43E-06

75th 0.006 0.005 0.005 0.001 2.00E-04 2.00E-04

95th 1.20 1.13 1.13 0.131 0.012 0.012

Max 59.6 59.6 59.6 59.6 20.1 20.1

Source: ERG, 2015d; ERG, 2015i.

H-22
 

 

 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015i.

0 

5 

10 

15 

20 

25 

30 

35 

40 

45 

50

Number of Immediate Receiving Waters 

Total Thallium Concentration in Fish Tissue (mg/kg) 

Figure H-22. Total Thallium Concentration in Trophic Level 

4 Fish Tissue in the Immediate Receiving Water 

Table H-23. Total Thallium Concentration (mg/kg) in Fish Tissue (Trophic Level 4) by 

Percentile 

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 1.41E-06 7.74E-07 7.74E-07 0 0 0

25th 1.70E-04 1.02E-04 1.02E-04 7.90E-06 0 0

50th 0.002 0.002 0.002 3.02E-04 2.46E-05 2.46E-05

75th 0.025 0.020 0.020 0.005 7.63E-04 7.63E-04

95th 4.58 4.31 4.31 0.500 0.044 0.044

Max 228 228 228 228 76.8 76.8 

Source: ERG, 2015d; ERG, 2015i.

H-23
 

 

 

 

 

 

 

 

Appendix H—Additional Model Results 

Source: ERG, 2015d; ERG, 2015i.

0 

10 

20 

30 

40 

50 

60

Number of Immediate Receiving Waters 

Total Zinc Concentration in Fish Tissue (mg/kg) 

Figure H-23. Total Zinc Concentration in Trophic Level 3 

and Trophic Level 4 Fish Tissue in the Immediate Receiving 

Water a 

a – The wildlife module applies the same total zinc BCFs for both T3 and T4 fish (see Appendix D). Therefore, the

estimated concentrations presented here are identical for both trophic levels. 

Table H-24. Total Zinc Concentration (mg/kg) in Fish Tissue (Trophic Level 3 & 

Trophic Level 4) by Percentile a

Percentile

Scenario

Baseline Option A Option B Option C Option D Option E

5th 7.25E-05 3.20E-05 3.20E-05 0 0 0

25th 0.002 8.50E-04 8.50E-04 1.63E-04 0 0

50th 0.022 0.007 0.007 0.004 5.04E-04 2.74E-04

75th 0.809 0.687 0.687 0.144 0.027 0.012

95th 28.4 13.6 13.6 11.0 6.59 1.17

Max 3,576 3,576 3,576 3,576 3,576 501 

Source: ERG, 2015d; ERG, 2015i.

a – The wildlife module applies the same total zinc BCFs for both trophic level 3 (T3) and trophic level 4 (T4) fish

(see Appendix D). Therefore, the estimated concentrations presented here are identical for both trophic levels.

H-24
 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

APPENDIX I 

ANALYSIS FOR ALTERNATE SCENARIO WITH CLEAN 

POWER PLAN 

As discussed in Section 1, the environmental assessment (EA) report presents the 

methodology and results of the qualitative and quantitative analyses performed to evaluate

baseline discharges from steam electric power plants and improvements under the final steam 

electric effluent limitations guidelines and standards (ELGs). The analyses presented in the 

report incorporate some adjustments to current conditions in the industry. The analyses in the 

report, 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)] (CPP). This appendix presents the results of EPA’s 

quantitative EA analysis that does reflect changes in the industry that may occur as a result of the 

CPP. Table I-1 presents the number of plants included in this alternate scenario analysis 

compared to those in the EA report. 

Table I-1. Number of Plants Evaluated in the EA Alternate Scenario Analysis Compared to 

the EA Report

Plant Description 

Number of Plants 

in EA Report 

Number of Plants 

in Alternate 

Scenario Analysis

Number of Plants in Scope of Final Rule

Plants that fall under the applicability of the final rule (40 CFR 423) 1,079 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) 

202 151 

Plants that discharge only to surface waters (direct discharger) 191 145 

Plants that discharge only to a POTW (indirect discharger) 7 3 

Plants that discharge to surface waters and to a POTW (direct and 

indirect discharger)

4 3 

Environmental Assessment

Plants evaluated in the EA (includes all direct dischargers)a

 195 148 

Acronyms: CFR (Code of Federal Regulations); POTW (publicly owned treatment works); TDD (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) 

a – For the pollutant loadings and removals presented in this appendix, EPA included indirect dischargers to protect

confidential business information.

The 148 steam electric power plants in the EA alternate scenario analysis discharge to the 

172 immediate receiving waters illustrated in Figure I-1 (some plants discharge to multiple 

receiving waters). Table I-2 presents the count of receiving water types for the 172 immediate 

receiving waters.

I-1
Figure I-1. Locations and Counts of Immediate Receiving Waters in EA Scope and Modeling Ana

Appendix I—Analysis for Alternate Scena

I-2
 

 

 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-2. Receiving Water Types for Steam Electric Power Plants 

Evaluated in the EA 

Receiving Water Type

Number (Percentage) of Immediate

Receiving Waters in the Alternate Scenario 

Analysis a

River/Stream 144 (84%)

Lake/Pond/Reservoir 19 (11%)

Great Lakes 8 (5%)

Estuary 1 (<1%)

Total Receiving Waters 172 (100%)

Source: ERG, 2015d. 

a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 

steam electric power plants (some of which discharge to multiple receiving waters). The immediate receiving 

water (IRW) model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immediate 

receiving waters and loadings from 143 steam electric power plants. 

EPA evaluated the annual baseline pollutant discharges of the evaluated wastestreams

from steam electric power plants reflecting changes in the industry that may occur as a result of

the CPP. Table I-3 presents the annual pollutant loadings in pounds and toxic-weighted pound 

equivalents (TWPE).1,2 Table I-4 compares pollutant discharges, as TWPE, from the steam 

electric power generating industry to discharges from the other top ten discharging point source 

categories, as estimated by EPA for the 2010 Effluent Guidelines Planning Process [U.S. EPA, 

2011d]. 

1

 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 toxicity data, as well as physical/chemical property data 

[U.S. EPA, 2012b]. 

2

 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 industry loadings calculated using these revised datasets are 

presented in the TDD. The total industry loadings presented in Appendix I 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 SE05622. 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. 

I-3
 

 

 

 

 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-3. Annual Baseline Pollutant Discharges 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 6,320,000 649,000

Cadmium 22.8 10,900 249,000 

Boron 0.00834 24,600,000 205,000 

Mercury 110.0 1,180 129,000

Selenium 1.12 113,000 127,000

Thallium 2.85 43,900 125,000 

Arsenic 3.47 22,200 77,100 

Aluminum 0.0647 1,070,000 69,400 

Lead 2.24 14,600 32,700 

Vanadium 0.280 55,600 15,600 

Copper 0.623 24,000 15,000 

Iron 0.00560 2,110,000 11,800 

Nickel 0.109 94,200 10,300 

Zinc 0.0469 145,000 6,800 

Chromium VI 0.517 119 61.4 

Nutrients

Total Nitrogen d Not applicable 13,100,000 Not applicable 

Total Phosphorus Not applicable 154,000 Not applicable 

Other

Chlorides 2.435 X 10-5 722,000,000 17,600 

Total dissolved solids Not applicable 3,290,000,000 Not applicable 

Total Pollutants e 1,700,000,000 2,140,000 

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 Technical Development Document (TDD) (EPA-821-R-15-007). 

b – TWFs for the following metals apply to all metal compounds: arsenic, chromium, copper, lead, manganese, 

mercury, nickel, selenium, thallium, vanadium, and zinc. 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 to account for publicly announced plans 

from the steam electric power generating industry to retire or modify steam electric generating units at specific 

power plants; 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); and changes to the 

industry that are expected to occur as a result of the CPP. Data source for pollutant specific loadings is DCN 

SE05622. 

d – Total nitrogen is the sum of total Kjeldahl nitrogen and nitrate/nitrite as N. 

e – The totals represent the pollutant loadings in discharges of the evaluated wastestreams – specifically, flue gas 

desulfurization (FGD) wastewater, fly ash transport wastewater, bottom ash transport wastewater, and 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 pollutants of concern (POCs) and for 

biochemical oxygen demand (BOD), chemical oxygen demand (COD), total organic carbon (TOC), total dissolved

solids (TDS), and total suspended solids (TSS). 

I-4
 

 

 

 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-4. Pollutant Loadings for the Final 2010 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 2,140,000 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. 

Note: Numbers are rounded to three significant figures. 

a – Only TWPE totals for the steam electric power generating 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 discharge monitoring reports (DMRs) and Toxic Release Inventory (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). 

b –EPA calculated the steam electric power generating industry (40 CFR 423) discharges for the alternate scenario

analysis as total of 2,140,000 TWPE annually (see Section 10 of the TDD). 

EPA estimated that the total alternate scenario analysis TWPE from steam electric power

plant wastewater (see Table I-4) is over two times the amount estimated for the pulp, paper, and 

paperboard industry; petroleum refining industry; and nonferrous metals manufacturing (second, 

third, and fourth highest ranking), and it is over five times the TWPE for four of the six other 

industries identified as the top TWPE dischargers in the Final 2010 Effluent Guidelines Program

Plan [U.S. EPA, 2011d].3

To provide additional perspective on the magnitude of the pollutant loadings from steam 

electric power plants in the alternate scenario analysis, EPA compared loadings for the evaluated 

wastestreams to those of an average publicly owned treatment works (POTW). Table I-5 

compares the average steam electric pollutant loadings by wastestream4 to the pollutant loadings

from an average POTW assumed to discharge 3 to 5 MGD. EPA also calculated the equivalent 

number of typical POTWs that would discharge loadings equal to the 151 steam electric power 

plants5

 included in the alternate scenario analysis. Table I-6 presents total pollutant loadings for 

3

 Data sources for the other industry discharges include DMRs and TRI reports. EPA recognizes 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. 

4

 EPA calculated the average pollutant loadings for each wastestream by dividing the total pollutant loadings for the

wastestream by the number of steam electric power plants discharging the wastestream [ERG, 2015a].

5

 The count of 151 steam electric power plants includes three indirect dischargers that discharge wastewater to a

POTW and do not discharge any of the evaluated wastestreams directly to surface waters. EPA included these

indirect dischargers to protect confidential business information.

I-5
Appendix I—Analysis for Alternate Scenario with Clean Power Plan

the evaluated wastestreams (for the 151 plants) and the number of typical POTWs that would 

discharge equivalent loadings. 

I-6
Appendix I—Analysis for Alternate Scena

Table I-5. Comparison of Average Pollutant Loadings in the Evaluated Wastestreams to an Aver

Pollutant 

Average Plant FGD 

Wastewater Discharge a,b

Average Plant Fly Ash 

Transport Water 

Discharge a,c

Average Plant Bottom 

Ash Transport Water

Discharge a,d

Average Plant 

Combustion Residual 

Leachate Discharge a,e

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) 

Aluminum 1,720 111 9,010 583 3,880 251 988 63.9 

Arsenic 9.68 33.6 310 1,080 61.1 212 12.7 44.2 

Boron 333,000 2,780 19,800 166 2,060 17.2 7,700 64.2 

Cadmium 91.7 2,090 49.2 1,120 17.7 403 3.39 77.2 

Chromium VI (g) (g) 2.48 1.28 0.145 0.0750 (g) (g) 

Copper 19.6 12.2 282 176 83.0 51.7 2.55 1.59 

Iron 1,270 7.10 5,740 32.1 6,960 39.0 12,200 68.5 

Lead 5.82 13.0 157 351 58.6 131 (g) (g) Manganese 81,800 8,400 522 53.6 4,340 446 933 95.8 

Mercury 6.24 687 7.76 854 3.04 334 0.351 38.7 

Nickel 701 76.4 188 20.5 275 30.0 15.4 1.68 

Selenium 1,470 1,640 132 148 29.5 33.1 36.7 41.2 

Thallium 17.0 48.6 134 384 276 789 0.399 1.14 

Vanadium 21.0 5.87 209 58.5 12.2 3.42 631 177 Zinc 1,110 52.3 814 38.2 227 10.6 69.8 3.27 

Total Nitrogen 132,000 -- 25,000 -- 22,500 -- (g) -- 

Total Phosphorus 453 -- 849 -- 657 -- (g) -- 

Chlorides 10,100,000 246 84,600 2.06 88,500 2.16 142,000 3.45 TDS 40,800,000 -- 1,870,000 -- 2,340,000 -- 1,200,000 -- 

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 vanadiumb – Average loadings based on 69 plants assumed to discharge FGD wastewater under baseline conditions [ERG, 2015a]. c – Average loadings based on 40 plants assumed to discharge fly ash transport water under baseline conditions [ERG, 2015a]. d – Average loadings based on 135 plants assumed to discharge bottom ash transport water under baseline conditions [ERG, 2015a]. e – Average loadings based on 70 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 and wastestream. See the Costs and Loads Report (DCN SE05831). 

I-7
 

 

 

 

 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-6. Estimated Number of POTW Equivalents for Total Pollutant Loadings from the 

Evaluated Wastestreams 

Pollutant 

Annual Discharge

pounds (lbs) a

Equivalent Number of Average

POTWs b

Aluminum 1,070,000 299

Arsenic 22,200 484 

Boron 24,600,000 16,000 

Cadmium 10,900 3,090 

Chromium VI 119 6.72

Copper 24,000 156 

Iron 2,110,000 835

Lead 14,600 301 

Manganese 6,320,000 17,800 

Mercury 1,180 0.370 

Nickel 94,200 3,080 

Selenium 113,000 6,110

Thallium 43,900 4,410 

Vanadium 55,600 No values for comparison

Zinc 145,000 320

Total Nitrogen 13,100,000 107 

Total Phosphorus 154,000 8.65

Chlorides 722,000,000 448 

TDS 3,290,000,000 No values for comparison

Source: ERG, 2015a. 

Note: Numbers are rounded to three significant figures. 

a – Annual discharge based on pollutant discharges from 151 steam electric power plants, including three indirect

dischargers.

b – Equivalent number of POTWs is estimated by dividing the total annual pollutant loadings from the 151 steam

electric power plants by the average POTW loadings presented in Table I-5 for a 4-MGD POTW.

I-8
 

 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

EPA identified the number of surface waters that receive discharges of the evaluated 

wastestreams and are located in close proximity to sensitive environments. Table I-7 summarizes

the number and percentage of immediate receiving waters in the alternate scenario analysis that 

are located in sensitive environments. 

Table I-7. Number and Percentage of Immediate 

Receiving Waters Identified as Sensitive Environments

Sensitive Environment 

Number (Percentage) of Immediate

Receiving Waters Identified a

Great Lakes watershed 15 (9%)

Chesapeake Bay watershed 11 (6%)

Impaired water 91 (53%)

Surface water impaired for a subset of pollutants associated with the 

evaluated wastestreams b 45 (26%)

Fish consumption advisory water 116 (67%)

Surface water with a fish consumption advisory for a subset of 

pollutants associated with the evaluated wastestreams c 79 (46%)

Drinking water resource within 5 miles 152 (88%)

a – For the sensitive environment proximity analysis, EPA evaluated 172 immediate 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. 

d – The values presented in Section 3.4.5 of the report are based on an analysis of habitat locations that reflect

changes in the industry as a result of the CPP. 

Table I-8 and Table I-9 present the pollutant loadings to the Great Lakes watershed and 

the Chesapeake Bay watershed, respectively, accounting for changes in the industry baseline as a 

result of the CPP. Table I-10 presents the number of immediate receiving waters classified as

impaired in the alternate scenario analysis.

Based on a review of immediate receiving waters that reflect changes in the industry as a 

result of the CPP, EPA determined that 116 immediate receiving waters (67 percent) are under 

fish consumption advisories; 79 of the immediate receiving waters (46 percent) are under an 

advisory for a pollutant associated with the evaluated wastestreams.6 All of these 79 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. 

The results of the threatened and endangered species analysis presented in Section 3.4.5 

already account for changes in the industry as a result of the CPP. Table I-11 presents the 

number of steam electric power plants located within five miles of a drinking water resource and 

the number of drinking water resources located within five miles of a steam electric power plant.

6

 Table B-2 in Appendix B lists the types of advisories identified under the sensitive environment proximity

analysis, including advisories for pollutants that are not associated with the evaluated wastestreams.

I-9
 

 

 

 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-8. Pollutant Loadings to the Great Lakes Watershed from the Evaluated 

Wastestreams a

Pollutant 

Annual Discharge to the Great Lakes 

Watershed (lbs) 

Annual TWPE Discharge to the 

Great Lakes Watershed (lb-eq) 

Arsenic 1,030 3,590

Boron 760,000 6,340 

Cadmium 286 6,520

Chromium VI 0.548 0.283

Copper 1,170 728 

Lead 869 1,950 

Manganese 112,000 11,500 

Mercury 37.5 4,130 

Nickel 4,310 470 

Selenium 3,540 3,960

Thallium 4,320 12,300 

Zinc 3,860 181

Total Nitrogen 646,000 --

Total Phosphorus 10,900 --

Chlorides 24,100,000 587 

Total Dissolved Solids 116,000,000 --

Source: ERG, 2015a. 

Note: Numbers are rounded to three significant figures. 

a – Pollutant loadings based on 14 steam electric power plants discharging to 15 immediate receiving waters in the 

Great Lakes watershed.

I-10
 

 

 

 

 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-9. Pollutant Loadings to the Chesapeake Bay Watershed from the Evaluated 

Wastestreams a

Pollutant 

Annual Discharge to the Chesapeake

Bay Watershed (lbs) 

Annual TWPE Discharge to the 

Chesapeake Bay Watershed (lb-eq) 

Arsenic 680 2,360

Boron 1,080,000 9,000

Cadmium 199 4,530 

Chromium VI 0 0 

Copper 765 477 

Lead 571 1,280 

Manganese 106,000 10,900 

Mercury 24.4 2,690 

Nickel 2,880 313 

Selenium 4,710 5,290

Thallium 2,880 8,210 

Zinc 2,630 123

Total Nitrogen 670,000 --

Total Phosphorus 7,920 --

Chlorides 34,200,000 832 

Total Dissolved Solids 139,000,000 --

Source: ERG, 2015a. 

Note: Numbers are rounded to three significant figures. 

a – Pollutant loadings based on seven steam electric power plants discharging to 11 immediate receiving waters in 

the Chesapeake Bay watershed. 

Table I-10. Number and Percentage of Immediate 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 21 (12%) 

Metals, other than mercury b 24 (14%)

Nutrients 15 (9%)

TDS, including chlorides 2 (1%)

Total for Any Pollutant c 56 (33%)

a – For the impaired waters proximity analysis, EPA evaluated 172 immediate receiving waters that receive 

discharges of the evaluated wastestreams [ERG, 2015c; ERG, 2015d].

b – The EPA impaired water database listed 24 immediate receiving waters as impaired based on the “metal, other 

than mercury” impairment category. Of those 24 immediate receiving waters, 13 receiving waters are also listed as

impaired for one or more specific metals in the EA analysis (arsenic, cadmium, manganese, selenium, and zinc). 

One additional immediate receiving water is impaired for boron (but not included in the “metals, other than 

mercury” 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. 

I-11
Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-11. Comparison of Number and Percentage 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 87 52 (35%)

Public wells b 1,530 116 (78%)

Sole-source aquifers 5 5 (3%)

Sources: ERG, 2015c; ERG, 2015d. 

a – For the drinking water resource proximity analysis, EPA evaluated 172 immediate receiving waters that receive

discharges of the evaluated wastestreams from 148 steam electric power plants.

b – Counts include two springs and 29 wellheads.

Current impacts from the steam electric power generating industry under the alternate 

scenario analysis include water quality impacts (Table I-12); wildlife impacts (Table I-13 and

Table I-14); impacts to benthic organisms (Table I-15); human health impacts to national-scale

cohorts representing recreational and subsistence fishers (Table I-16 through Table I-19); and 

human health impacts to cohorts representing recreational and subsistence fishers by race or

Hispanic origin (Table I-20 and Table I-21, respectively). 

The ecological risk modeling results under the alternate scenario analysis indicate that 16 

percent of the lakes, ponds, and reservoirs (3 out of 19) and 13 percent of the rivers and streams

(18 out of 144) that receive discharges of the evaluated wastestreams present an elevated risk of

negative reproductive impacts to fish. For mallards, the counts are slightly higher, with the same

number of lakes, ponds, and reservoirs and 15 percent of the rivers and streams (22 out of 144) 

presenting these risks. 

Selecting the 90th percentile modeled egg/ovary concentration, meaning there is a 10 

percent probability that the egg/ovary concentrations are greater than the selected concentration,

reveals that 19 percent of the immediate receiving waters (31 out of 163) present reproductive 

risks to at least 10 percent of the exposed fish population. The results for mallards (20 percent) 

are very similar. These counts are considerably higher than the results obtained using the median 

modeled egg/ovary concentration, indicating the potential for more widespread ecological 

impacts among those waterbodies and food webs that tend to experience higher bioaccumulation 

of selenium. 

I-12
Table I-12. Number and Percentage of Immediate Receiving Waters with Estimated 

Water Concentrations that Exceed the Water Quality Criteria

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 7 0 7 4%

Freshwater Chronic NRWQC 25 3 28 17%

Human 

Health

Criteria 

Human Health Water and

Organism NRWQC 61 12 73 45%

Human Health Organism Only

NRWQC 44 7 51 31%

Drinking Water MCL 25 4 29 18%

Total Number of Unique Immediate 

Receiving Waters c 61 12 73 45%

 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i. 

Acronyms: NRWQC (National Recommended Water Quality Criteria); MCL (maximum contaminant level). 

a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 

steam electric power plants (some of which discharge to multiple receiving waters). The IRW model, which 

excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving waters (144 rivers and 

streams; 19 lakes, ponds, and reservoirs) and loadings from 143 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 exceeded at least one criterion. 

Table I-13. Number and Percentage of Immediate Receiving Waters That Exceed Wildlife 

Fish Consumption NEHCs for Minks and Eagles (by Waterbody Type) 

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 38 8 46 28%

Eagle fish consumption NEHC 48 8 56 34%

Total Number of Unique

Immediate Receiving Waters c 48 8 56 34%

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i

Acronyms: NEHC (No Effect Hazard Concentration). 

a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 

steam electric power plants (some of which discharge to multiple receiving waters). The IRW model, which 

excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving waters (144 rivers and 

streams; 19 lakes, ponds, and reservoirs) and loadings from 143 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. 

I-13
 

 

 

 

 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-14. Number and Percentage of Immediate Receiving Waters That Exceed 

Wildlife Fish Consumption NEHCs for Minks and Eagles (by Pollutant) 

Pollutant 

Mink Eagle

Fish 

Consumption

NEHC

(ug/g) a

Immediate Receiving 

Waters

Fish 

Consumption

NEHC

(ug/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 5 3% 14.7 4 2%

Chromium VI 17.7 c

 0 0% 26.6 c 0 0%

Copper 41.2 0 0% 40.5 0 0%

Lead 34.6 0 0% 16.3 2 1%

Mercury 0.37 43 26% 0.5 55 34%

Nickel 12.5 0 0% 67.1 0 0%

Selenium 1.13 33 20% 4 33 20%

Thallium ID NC NC ID NC NC 

Zinc 904 1 1% 145 4 2%

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i. 

Acronyms: ID (Insufficient data; no benchmarks were identified in the wildlife analysis for thallium); NC (Not

calculated); NEHC (No Effect Hazard Concentration); ug/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 alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 

steam electric power plants (some of which discharge to multiple receiving waters). The IRW model, which 

excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving waters and loadings from

143 steam electric power plants. 

c – An NEHC benchmark is not available for chromium VI; therefore, EPA used the total chromium benchmark.

I-14
 

 

 

 

 

 

 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-15. Number and Percentage of Immediate Receiving Waters with Sediment 

Pollutant Concentrations Exceeding TELs for Sediment Biota

Pollutant 

Sediment 

Benchmark 

(mg/kg)

Number of Immediate Receiving Waters Exceeding TELs for Sediment 

Biota 

Rivers and 

Streams

Lakes, Ponds,

and Reservoirs

Total Immediate Receiving 

Waters

Number a Percent 

Arsenic 5.90 5 0 5 3%

Cadmium 0.596 19 3 22 13%

Chromium VI b 37.3 0 0 0 0%

Copper 35.7 4 1 5 3%

Lead 35 3 1 4 2%

Mercury 0.174 33 7 40 25% 

Nickel 18.0 24 3 27 17%

Selenium ID NC NC NC NC 

Thallium ID NC NC NC NC 

Zinc 123 12 1 13 8%

Total Number of Unique 

Immediate Receiving Waters 33 7 40 25%

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i. 

Acronyms: ID (Insufficient data; no benchmarks were identified); NC (Not calculated).

a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 

steam electric power plants (some of which discharge to multiple receiving waters). The IRW model, which 

excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving waters (144 rivers and 

streams; 19 lakes, ponds, and reservoirs) and loadings from 143 steam electric power plants. 

b – No benchmark for chromium VI. EPA used the total chromium benchmark, which may underestimate the impact

to wildlife. 

I-15
 

 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-16. Number and Percentage of Immediate Receiving Waters That Exceed Human 

Health Evaluation Criteria (Lifetime Excess Cancer Risk) for Inorganic Arsenic 

Receptor Cohort

Exposure 

Duration 

(Years)

Number of Immediate Receiving Waters Where

Lifetime Excess Cancer Risk 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 4 0 4 2%

6 to <11 years 5 4 0 4 2%

11 to <16 years 5 4 0 4 2%

16 to <21 years 5 4 0 4 2%

Adult recreational fisher 49 7 2 9 6%

Child

subsistence 

fisher

1 to <2 years 1 4 0 4 2%

2 to <3 years 1 4 0 4 2%

3 to <6 years 3 5 0 5 3%

6 to <11 years 5 6 0 6 4%

11 to <16 years 5 4 0 4 2%

16 to <21 years 5 4 0 4 2%

Adult subsistence fisher 49 19 2 21 13%

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i. 

a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 

steam electric power plants (some of which discharge to multiple receiving waters). The IRW model, which 

excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving waters (144 rivers and 

streams; 19 lakes, ponds, and reservoirs) and loadings from 143 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. 

I-16
 

 

 

 

 

 

 

 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-17. Number and Percentage of Immediate Receiving Waters 

That Exceed Non-Cancer Oral Reference Dose Values 

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 62 13 75 46%

2 to <3 years 1 62 13 75 46%

3 to <6 years 3 61 13 74 45%

6 to <11 years 5 60 12 72 44%

11 to <16 years 5 57 10 67 41%

16 to <21 years 5 57 10 67 41%

Adult recreational fisher 49 57 10 67 41%

Child

subsistence 

fisher

1 to <2 years 1 76 14 90 55%

2 to <3 years 1 76 14 90 55%

3 to <6 years 3 70 14 84 52%

6 to <11 years 5 67 14 81 50%

11 to <16 years 5 63 13 76 47%

16 to <21 years 5 63 13 76 47%

Adult subsistence fisher 49 65 13 78 48%

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i. 

a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 

steam electric power plants (some of which discharge to multiple receiving waters). The IRW model, which 

excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving waters (144 rivers and 

streams; 19 lakes, ponds, and reservoirs) and loadings from 143 steam electric power plants. 

b – These values are the sum and percentage of rivers, streams, lakes, ponds, and reservoirs impacted. 

I-17
 

 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-18. Number and Percentage of Immediate 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 2%

Cadmium 0.001 b

 27 17%

Chromium VI 0.003 b

 0 0%

Copper 0.01 c

 4 2%

Lead ID NC NC 

Mercury (as methylmercury) 0.0001 b

 84 52%

Nickel (soluble salts) 0.02 b

 0 0%

Selenium 0.005 b

 41 25%

Thallium (soluble salts) 0.00001 d

 72 44%

Zinc 0.3 b

 7 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 alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 

steam electric power plants (some of which discharge to multiple receiving waters). The IRW model, which 

excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving waters and loadings from

143 steam electric power plants. 

b – U.S. EPA, 2011c.

c – ATSDR, 2010a. 

d – U.S. EPA, 2010a.

I-18
 

 

 

 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-19. Comparison of T4 Fish Tissue Concentrations 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 2%

Inorganic arsenic 

(carcinogen) 0.026 4 2% 0.00327 7 4%

Cadmium 4.0 6 4% 0.491 18 11%

Mercury (as 

methylmercury) 0.4 58 36% 0.049 77 47%

Selenium 20 19 12% 2.457 36 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 screening 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 alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 

steam electric power plants (some of which discharge to multiple receiving waters). The IRW model, which 

excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving waters and loadings from

143 steam electric power plants. 

I-19
 

 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-20. Number and Percentage of Immediate Receiving Waters That Exceed Human 

Health Evaluation Criteria (Lifetime Excess Cancer Risk) for Inorganic Arsenic, by Race 

or Hispanic Origin 

Receptor

Race or Hispanic 

Origin 

Number of Immediate Receiving Waters Where

Lifetime Excess Cancer Risk 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 4 4 4 9 

Non-Hispanic Black 3 3 4 4 4 4 11

Mexican-American 4 4 4 4 4 4 14

Other Hispanic 4 4 4 4 4 4 13

Other, including 

Multiple Races 

4 4 4 4 4 4 15

Subsistence 

Non-Hispanic White 4 4 4 5 5 5 21

Non-Hispanic Black 4 4 4 5 5 5 22

Mexican-American 4 4 4 6 6 6 23

Other Hispanic 4 4 4 5 5 5 23

Other, including 

Multiple Races 

4 4 5 7 7 7 26

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i. 

a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 

steam electric power plants (some of which discharge to multiple receiving waters). The IRW model, which 

excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving waters and loadings from

143 steam electric power plants. 

b – Inorganic arsenic cancer slope factor of 1.5 per milligrams per kilogram (mg/kg) per day.

I-20
Appendix I—Analysis for Alternate Scena

Table I-21. Number and Percentage of Immediate Receiving Waters That Exceed Non-Cancer Oral Refer

Race or Hispanic Origin 

Receptor Race or Hispanic Origin 

Number of Immediate Receiving Waters Where Pollutant Exceeds a Non-

Inorganic 

Arsenic Cadmium Copper Mercury b Selenium T

Recreational, 

Child Fisher 

Non-Hispanic White 0 (0%) 8 (5%) 3 (2%) 63 (39%) 26 (16%) 

Non-Hispanic Black 0 (0%) 9 (6%) 4 (2%) 64 (39%) 27 (17%) 

Mexican-American 0 (0%) 11 (7%) 4 (2%) 66 (40%) 27 (17%) 

Other Hispanic 0 (0%) 10 (6%) 4 (2%) 64 (39%) 27 (17%) 

Other, including Multiple Races 0 (0%) 11 (7%) 4 (2%) 68 (42%) 28 (17%) 

Subsistence, Child Fisher 

Non-Hispanic White 0 (0%) 8 (5%) 3 (2%) 63 (39%) 26 (16%) 

Non-Hispanic Black 0 (0%) 9 (6%) 4 (2%) 64 (39%) 27 (17%) 

Mexican-American 0 (0%) 11 (7%) 4 (2%) 66 (40%) 27 (17%) 

Other Hispanic 0 (0%) 10 (6%) 4 (2%) 64 (39%) 27 (17%) 

Other, including Multiple Races 0 (0%) 11 (7%) 4 (2%) 68 (42%) 28 (17%) 

Recreational, 

Adult Fisher 

Non-Hispanic White 3 (2%) 17(10%) 4 (2%) 74 (45%) 33 (20%) 

Non-Hispanic Black 3 (2%) 18 (11%) 4 (2%) 74 (45%) 34 (21%) 

Mexican-American 3 (2%) 20 (12%) 4 (2%) 76 (47%) 36 (22%) 

Other Hispanic 3 (2%) 20 (12%) 4 (2%) 76 (47%) 36 (22%) 

Other, including Multiple Races 3 (2%) 24 (15%) 4 (2%) 79 (48%) 38 (23%) 

Subsistence, 

Adult Fisher 

Non-Hispanic White 3 (2%) 17(10%) 4 (2%) 74 (45%) 33 (20%) 

Non-Hispanic Black 3 (2%) 18 (11%) 4 (2%) 74 (45%) 34 (21%) 

Mexican-American 3 (2%) 20 (12%) 4 (2%) 76 (47%) 36 (22%) 

Other Hispanic 3 (2%) 20 (12%) 4 (2%) 76 (47%) 36 (22%) 

Other, including Multiple Races 3 (2%) 24 (15%) 4 (2%) 79 (48%) 38 (23%) 

Sources: ERG, 2015d; ERG, 2015h; ERG, 2015i. a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 steam electric power 

discharge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immand loadings from 143 steam electric power plants. b – Mercury, as methylmercury. c – Reference dose based on thallium (soluble salts). 

I-21
 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

EPA evaluated environmental improvements as a result of the regulatory options,

reflecting changes in the industry as a result of the CPP. Table I-22 and Table I-23 present 

pollutant removals under the regulatory options. 

Table I-22. Steam Electric Power Generating Industry Pollutant Removals for Metals, 

Bioaccumulative Pollutants, Nutrients, Chlorides, and TDS Under Regulatory Options 

Pollutant 

Pollutant Removals, lbs/yr (Percent Reduction) a

Option A Option B Option C Option D Option E

Arsenic 12,500 

(56%)

12,500 

(56%)

18,500 

(83%)

20,700 

(93%)

21,300 

(96%)

Boron 3,150,000

(13%)

3,150,000

(13%)

3,350,000

(14%)

3,420,000

(14%)

3,420,000

(14%)

Cadmium 7,900

(72%)

7,900

(72%)

9,650

(88%)

10,300 

(94%)

10,400 

(95%)

Chromium VI 99.1

(83%)

99.1

(83%)

115 

(96%)

119 

(>99%)

119 

(>99%)

Copper 12,200 

(51%)

12,200 

(51%)

20,500 

(85%)

23,400 

(98%)

23,500 

(98%)

Lead 6,340

(43%)

6,340

(43%)

12,100 

(83%)

14,200 

(98%)

14,200 

(98%)

Manganese 4,520,000

(72%)

4,520,000

(72%)

4,950,000

(78%)

5,110,000

(81%)

5,110,000

(81%)

Mercury 728 

(62%)

736 

(63%)

1,040

(89%)

1,140

(97%)

1,160

(99%)

Nickel 55,100 

(58%)

55,300 

(59%)

82,300 

(87%)

92,400 

(98%)

93,100 

(99%)

Selenium 24,100 

(21%)

106,000

(94%)

109,000

(96%)

110,000

(97%)

110,000

(97%)

Thallium 5,640

(13%)

5,640

(13%)

32,700 

(74%)

42,800 

(98%)

42,800 

(98%)

Zinc 107,000

(74%)

107,000

(74%)

130,000

(89%)

138,000

(95%)

141,000

(97%)

Nitrogen, total b 1,590,000

(12%)

10,000,000 

(76%)

12,200,000 

(93%)

13,100,000 

(99%)

13,100,000 

(99%)

Phosphorus, total 33,900 

(22%)

33,900 

(22%)

98,300 

(64%)

122,000

(79%)

122,000

(79%)

Chlorides 3,380,000

(<1%)

3,380,000

(<1%)

12,000,000 

(2%)

15,300,000 

(2%)

15,300,000 

(2%)

TDS 684,000,000 

(21%)

684,000,000 

(21%)

913,000,000 

(28%)

999,000,000 

(30%)

999,000,000 

(30%)

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 Kjeldahl nitrogen and nitrate/nitrite as N loadings. 

I-22
10,0 00,000 12,200, 000 13,10 0,000 13,10 0,000

10,0 00,000 12,200, 000 13,10 0,000 13,10 0,000

10,0 00,000 12,200, 000 13,10 0,000 13,10 0,000

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-23. Steam Electric Power Generating Industry TWPE Removals for Metals, 

Bioaccumulative Pollutants, Nutrients, Chlorides, and TDS Under Regulatory Options 

Pollutant 

Pollutant Removals, TWPE/year (Percent Reduction) a

Option A Option B Option C Option D Option E

Arsenic 43,400 

(56%)

43,400 

(56%)

64,200 

(83%)

71,900 

(93%)

73,900 

(96%)

Boron 26,200 

(13%)

26,200 

(13%)

28,000 

(14%)

28,600 

(14%)

28,600 

(14%)

Cadmium 180,000

(72%)

180,000

(72%)

220,000

(88%)

234,000

(94%)

236,000

(95%)

Chromium VI 51.2

(83%)

51.2

(83%)

59.2

(96%)

61.3

(>99%)

61.3

(>99%)

Copper 7,630

(51%)

7,630

(51%)

12,800 

(85%)

14,600 

(98%)

14,600 

(98%)

Lead 14,200 

(43%)

14,200 

(43%)

27,200 

(83%)

31,900 

(98%)

31,900 

(98%)

Manganese 464,000

(72%)

464,000

(72%)

508,000

(78%)

524,000

(81%)

524,000

(81%)

Mercury 80,100 

(62%)

80,900 

(63%)

115,000

(89%)

126,000

(97%)

128,000

(99%)

Nickel 6,000

(58%)

6,020

(59%)

8,970

(87%)

10,100 

(98%)

10,100 

(99%)

Selenium 27,000 

(21%)

119,000

(94%)

122,000

(96%)

123,000

(97%)

123,000

(97%)

Thallium 16,100 

(13%)

16,100 

(13%)

93,300 

(74%)

122,000

(98%)

122,000

(98%)

Zinc 5,040

(74%)

5,040

(74%)

6,090

(89%)

6,470

(95%)

6,630

(97%)

Nitrogen, total N/A N/A N/A N/A N/A 

Phosphorus, 

total N/A N/A N/A N/A N/A 

Chlorides 82.2

(<1%)

82.2

(<1%)

293 

(2%)

372 

(2%)

372 

(2%)

TDS N/A N/A N/A N/A N/A 

Source: ERG, 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 nitrogen, 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. 

Table I-24 presents key environmental improvements as a result of the regulatory options 

and reflecting changes in the industry as a result of the CPP. Table I-25 shows environmental 

improvements for benthic organisms. Key environmental improvements based on reduced 

discharges of arsenic, mercury, selenium, cadmium, and thallium are included in Table I-26 

through Table I-30. 

I-23
Appendix I—Analysis for Alternate Scena

Table I-24. Key Environmental Improvements Under the Regulatory Options 

Evaluation Benchmark

Modeled Immediate Receiving 

Waters Exceeding Benchmark 

Under Baseline Conditions a

Number of Immediate Receiving Waters E

(Percent Reduction from Baseline Condition

Options b

Number Percentage Option A Option B Option C 

Water Quality Results Freshwater Acute NRWQC 7 4% 5 

(29%)

5 

(29%)

5 

(29%)

Freshwater Chronic NRWQC 28 17% 27

(4%)

22

(21%)

18

(36%)

Human Health Water and Organism NRWQC 73 45% 70

(4%)

70

(4%)

55

(25%)

Human Health Organism Only NRWQC 51 31% 48

(6%)

48

(6%)

36

29%)

Drinking Water MCL 29 18% 27

(7%)

26

(10%)

12

(59%)

Wildlife Results Fish Ingestion NEHC for Minks 46 28% 46

(0%)

41

(11%)

25

(46%)

Fish Ingestion NEHC for Eagles 56 34% 52

(7%)

48

(14%)

34

(39%)

Human Health Results—Non-Cancer Non-Cancer Reference Dose for Child (recreational)

75 46% 69

(8%)

67

(11%)

51

(32%)

Non-Cancer Reference Dose for Adult (recreational)

67 41% 60

(10%)

58

(13%)

44

(34%)

Non-Cancer Reference Dose for Child (subsistence) 

90 55% 81

(10%)

79

(12%)

59

(34%)

Non-Cancer Reference Dose for Adult (subsistence) 

78 48% 72

(8%)

71

(9%)

54

(31%)

I-24
Appendix I—Analysis for Alternate Scena

Table I-24. Key Environmental Improvements Under the Regulatory Options 

Evaluation Benchmark

Modeled Immediate Receiving 

Waters Exceeding Benchmark 

Under Baseline Conditions a

Number of Immediate Receiving Waters E

(Percent Reduction from Baseline Condition

Options b

Number Percentage Option A Option B Option C 

Human Health Results—Cancer Arsenic Cancer Risk for Child (recreational)

4 2% 3 

(25%)

3 

(25%)

3 

(25%)

Arsenic Cancer Risk for Adult (recreational) 9 6% 7 

(22%)

7 

(22%)

5 

(44%)

Arsenic Cancer Risk for Child (subsistence) 6 4% 6 

(0%)

6 

(0%)

 5 

(17%)

Arsenic Cancer Risk for Adult (subsistence) 21 13% 19

(10%)

19

(10%)

13

(38%)

Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (maximum contaminant level); NEHC (No Effect Hazard Concentration); NRWQC (National Recommended Water Q

a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 steam electric power 

discharge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immand loadings from 143 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 reductio

I-25
Appendix I—Analysis for Alternate Scena

Table I-25. Number of Immediate Receiving Waters with Sediment Pollutant Concentrations Exceeding T

Biota Under the Regulatory Options

Pollutant 

Modeled Immediate

Receiving Waters 

Exceeding CSCLs Under

Baseline Conditions a

Number of Immediate Receiving Waters Exceeding Benchm

(Percent Reduction from Baseline Conditions) Under the Regulator

Option A Option B Option C Option D 

Arsenic 5 (3%) 4 (20%) 4 (20%) 4 (20%) 3 (40%) 

Cadmium 22 (13%) 17 (23%) 17 (23%) 12 (45%) 10 (55%) 

Chromium VI c 0 (0%) 0 (N/A) 0 (N/A) 0 (N/A) 0 (N/A) 

Copper 5 (3%) 4 (20%) 4 (20%) 4 (20%) 2 (60%) 

Lead 4 (2%) 3 (25%) 3 (25%) 3 (25%) 1 (75%) 

Mercury 40 (25%) 36 (10%) 35 (13%) 20 (50%) 16 (60%) 

Nickel 27 (17%) 22 (19%) 22 (19%) 12 (56%) 10 (63%) 

Selenium NC NC NC NC NC 

Thallium NC NC NC NC NC Zinc 13 (8%) 7 (46%) 7 (46%) 7 (46%) 6 (54%) 

Total 40

(25%) 

36

(10%) 

35

(13%) 

21

(48%) 

17

(58%) 

Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: CSCL (Chemical stressor concentration limit); N/A (Not Applicable, no exceedances at baseline conditions to compare opti

calculated; no benchmark for comparison).a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 steam electric power 

discharge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immand loadings from 143 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. 

I-26
Appendix I—Analysis for Alternate Scena

Table I-26. Key Environmental Improvements for Arsenic Under the Regulatory Optio

Evaluation Benchmark

Modeled Immediate

Receiving Waters Exceeding 

Benchmark Under Baseline 

Conditions a

Number of Immediate Receiving Waters Exce

(Percent Reduction from Baseline Conditions) U

Options b

Number Percentage Option A Option B Option C Op

Water Quality Results Freshwater Acute NRWQC 3 2% 2 

(33%)

2 

(33%)

2 

(33%)

(

Freshwater Chronic NRWQC 4 2% 3 

(25%)

3 

(25%)

3 

(25%)

(

Human Health Water and OrganismNRWQC

73 45% 70

(4%)

70

(4%)

55

(25%)

(

Human Health Organism Only NRWQC 51 31% 48

(6%)

48

(6%)

36

(29%)

(

Drinking Water MCL 9 6% 7 

(22%)

 7 

(22%)

5 

(44%)

(

Wildlife Results Fish Ingestion NEHC for Minks

0 0%

0

(N/A)

0 

(N/A)

0 

(N/A)

(

Fish Ingestion NEHC for Eagles 

0 0%

0

(N/A)

0 

(N/A)

0 

(N/A)

(

Human Health Results—Non-Cancer Non-Cancer Reference Dose for Child (recreational)

2 1% 1 

(50%)

1 

(50%)

1 

(50%)

(

Non-Cancer Reference Dose for Adult (recreational)

0 0% 0 

(N/A)

0 

(N/A)

0 

(N/A)

(

Non-Cancer Reference Dose for Child (subsistence) 

3 2% 2 

(33%)

2 

(33%)

2 

(33%)

(

Non-Cancer Reference Dose for Adult (subsistence) 

3 2% 2 

(33%)

2 

(33%)

2 

(33%)

(

I-27
Appendix I—Analysis for Alternate Scena

Table I-26. Key Environmental Improvements for Arsenic Under the Regulatory Optio

Evaluation Benchmark

Modeled Immediate

Receiving Waters Exceeding 

Benchmark Under Baseline 

Conditions a

Number of Immediate Receiving Waters Exce

(Percent Reduction from Baseline Conditions) U

Options b

Number Percentage Option A Option B Option C Op

Human Health Results—Cancer Arsenic Cancer Risk for Child(recreational)

4 2% 3 

(25%)

3 

(25%)

3 

(25%)

(

Arsenic Cancer Risk for Adult(recreational)

9 6% 7 

(22%)

7 

(22%)

5 

(44%)

(

Arsenic Cancer Risk for Child(subsistence) 

6 4% 6 

(0%)

6 

(0%)

5 

(17%)

(

Arsenic Cancer Risk for Adult(subsistence) 

21 13% 19

(10%)

19

(10%)

13

(38%)

(

Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (Maximum contaminant level); N/A (Not Applicable, no exceedances at baseline conditions to compare option resultHazard Concentration); NRWQC (National Recommended Water Quality Criteria). a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 steam electric power 

discharge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immand loadings from 143 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

I-28
Appendix I—Analysis for Alternate Scena

Table I-27. Key Environmental Improvements for Mercury Under the Regulatory Optio

Evaluation Benchmark

Modeled Immediate Receiving Waters 

Exceeding Benchmark Under Baseline 

Conditions a

Number of Immediate Receiving 

Benchmark

(Percent Reduction from Baseline C

Regulatory Optio

Number Percentage Option A Option B Option C 

Water Quality Results Freshwater Acute NRWQC 0 0% 0 

(N/A)

0 

(N/A)

0 

(N/A)

Freshwater Chronic NRWQC 1 1% 0 

(100%) 

0 

(100%) 

0 

(100%) 

Human Health Water and Organism NRWQC No benchmark for comparison N/A N/A N/A Human Health Organism Only NRWQC No benchmark for comparison N/A N/A N/A Drinking Water MCL

4 2%

4

(0%)

4 

(0%)

4 

(0%)

Wildlife Results Fish Ingestion NEHC for Minks 43 26% 40

(7%)

39

(9%)

23

(47%)

Fish Ingestion NEHC for Eagles 55 34% 48

(13%)

48

(13%)

34

(38%)

Human Health Results—Non-Cancer Non-Cancer Reference Dose for Child (recreational)

72 44% 65

(10%)

62

(14%)

46

(36%)

Non-Cancer Reference Dose for Adult (recreational)

64 39% 55

(14%)

54

(16%)

41

(36%)

Non-Cancer Reference Dose for Child (subsistence) 

84 52% 74

(12%)

73

(13%)

55

(35%)

Non-Cancer Reference Dose for Adult (subsistence) 

75 46% 68

(9%)

66

(12%)

49

(35%)

Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (Maximum contaminant level); N/A (Not Applicable, no exceedances at baseline conditions to compare option results

Hazard Concentration); NRWQC (National Recommended Water Quality Criteria). a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 steam electric power 

discharge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immand loadings from 143 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

I-29
Appendix I—Analysis for Alternate Scena

Table I-28. Key Environmental Improvements for Selenium Under the Regulatory Optio

Evaluation Benchmark

Modeled Immediate

Receiving Waters Exceeding 

Benchmark Under Baseline 

Conditions a

Number of Immediate Receiving Waters Exce

(Percent Reduction from Baseline Conditions) U

Options b

Number Percentage Option A Option B Option C Op

Water Quality Results Freshwater Acute NRWQC No benchmark for comparison N/A N/A N/A 

Freshwater Chronic NRWQC 27 17% 25

(7%)

17

(37%)

16

(41%)

(

Human Health Water and OrganismNRWQC

8 5% 7 

(13%)

3 

(63%)

3 

(63%)

(

Human Health Organism Only NRWQC 1 1% 1

(0%)

1 

(0%)

1 

(0%)

Drinking Water MCL 10 6% 9 

(10%)

4 

(60%)

4 

(60%)

(

Wildlife Results Fish Ingestion NEHC for Minks 33 20% 32

(3%)

23

(30%)

19

(42%)

(

Fish Ingestion NEHC for Eagles 33 20% 32

(3%)

23

(30%)

19

(42%)

(

Negative Reproductive Effects in Fish c 21 13% 17

(19%)

9 

(57%)

9 

(57%)

(

Negative Reproductive Effects inMallards c

25 15% 21

(16%)

13

(48%)

12

(52%)

(

I-30
Appendix I—Analysis for Alternate Scena

Table I-28. Key Environmental Improvements for Selenium Under the Regulatory Optio

Evaluation Benchmark

Modeled Immediate

Receiving Waters Exceeding 

Benchmark Under Baseline 

Conditions a

Number of Immediate Receiving Waters Exce

(Percent Reduction from Baseline Conditions) U

Options b

Number Percentage Option A Option B Option C Op

Human Health Results—Non-Cancer Non-Cancer Reference Dose for Child (recreational)

33 20% 32

(3%)

23

(30%)

19

(42%)

(

Non-Cancer Reference Dose for Adult (recreational)

26 16% 23

(12%)

14

(46%)

14

(46%)

(

Non-Cancer Reference Dose for Child (subsistence) 

41 25% 39

(5%)

31

(24%)

28

(32%)

(

Non-Cancer Reference Dose for Adult (subsistence) 

34 21% 32

(6%)

23

(32%)

19

(44%)

(

Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (Maximum contaminant level); N/A (Not Applicable, no exceedances at baseline conditions to compare option resultHazard Concentration); NRWQC (National Recommended Water Quality Criteria). a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 steam electric power 

discharge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immand loadings from 143 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 number of immediate receiving waters whose median modeled egg/ovary concentration is predicted to resu

among at least 10 percent of the exposed fish or mallard population, as determined using the ecological risk model.

I-31
Appendix I—Analysis for Alternate Scena

Table I-29. Key Environmental Improvements for Cadmium Under the Regulatory Opti

Evaluation Benchmark

Modeled Immediate Receiving Waters Exceeding Benchmark 

Under Baseline Conditions a

Number of Immediate Receiving Waters E

(Percent Reduction from Baseline Conditions

Options b

Number Percentage Option A Option B Option C O

Water Quality Results Freshwater Acute NRWQC 7 4% 4 

(43%)

4 

(43%)

4 

(43%)

Freshwater Chronic NRWQC 23 14% 18

(22%)

18

(22%)

13

(43%)

Human Health Water and Organism NRWQC No benchmark for comparison N/A N/A N/A 

Human Health Organism Only NRWQC No benchmark for comparison N/A N/A N/A 

Drinking Water MCL 8 5% 6 

(25%)

6 

(25%)

5 

(38%)

Wildlife Results Fish Ingestion NEHC for Minks 5 3% 4 

(20%)

4 

(20%)

4 

(20%)

Fish Ingestion NEHC for Eagles 

4 2% 3 

(25%)

3 

(25%)

3 

(25%)

Human Health Results—Non-Cancer Non-Cancer Reference Dose for Child (recreational)

13 8% 9 

(31%)

9 

(31%)

7 

(46%)

Non-Cancer Reference Dose for Adult (recreational)

8 5% 6 

(25%)

6 

(25%)

5 

(38%)

Non-Cancer Reference Dose for Child (subsistence) 

27 17% 22

(19%)

22

(19%)

17

(37%)

Non-Cancer Reference Dose for Adult (subsistence) 

18 11% 13

(28%)

13

(28%)

9 

(50%)

Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (Maximum contaminant level); N/A (Not Applicable, no exceedances at baseline conditions to compare option resultsHazard Concentration); NRWQC (National Recommended Water Quality Criteria). a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 steam electric power 

discharge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immand loadings from 143 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

I-32
Appendix I—Analysis for Alternate Scena

Table I-30. Key Environmental Improvements for Thallium Under the Regulatory Optio

Evaluation Benchmark

Modeled Immediate

Receiving Waters Exceeding 

Benchmark Under Baseline 

Conditions a

Number of Immediate Receiving Waters Excee

(Percent Reduction from Baseline Conditions) Under 

Number Percentage Option A Option B Option C Op

Water Quality Results Freshwater Acute NRWQC No benchmark for comparison N/A N/A N/A 

Freshwater Chronic NRWQC No benchmark for comparison N/A N/A N/A 

Human Health Water and OrganismNRWQC

39 24% 36

(8%)

36

(8%)

22

(44%)

(

Human Health Organism Only NRWQC 35 21% 32

(9%)

32

(9%)

18

(49%)

(

Drinking Water MCL 27 17% 25

(7%)

25

(7%)

11

(59%)

(

Wildlife Results Fish Ingestion NEHC for Minks No benchmark for comparison N/A N/A N/A 

Fish Ingestion NEHC for Eagles No benchmark for comparison N/A N/A N/A 

Human Health Results—Non-Cancer Non-Cancer Reference Dose for Child (recreational)

55 34% 54

(2%)

54

(2%)

36

(35%)

(

Non-Cancer Reference Dose for Adult (recreational)

43 26% 41

(5%)

41

(5%)

26

(40%)

(

Non-Cancer Reference Dose for Child (subsistence) 

72 44% 69

(4%)

69

(4%)

47

(35%)

(

Non-Cancer Reference Dose for Adult (subsistence) 

58 36% 58

 (0%) 

58

 (0%) 

39

(33%)

(

Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (Maximum contaminant level); N/A (Not Applicable, no exceedances at baseline conditions to compare option resultsHazard Concentration); NRWQC (National Recommended Water Quality Criteria). a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 steam electric power 

discharge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immand loadings from 143 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

I-33
 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Under the alternate scenario analysis, EPA evaluated environmental improvements to 

sensitive waters as a result of the regulatory options and reflecting changes in the industry as a 

result of the CPP. EPA determined that 91 of the immediate receiving waters are 303(d)-listed 

waterbodies, designated as impaired for one or more pollutants found in the evaluated 

wastestreams.7 Table I-31 presents the pollutant removals to impaired waters under the 

regulatory options. 

EPA determined that 79 of the 172 immediate receiving waters included in the alternate 

scenario analysis are under a fish advisory for mercury. Under the final rule, the number of

immediate receiving waters with fish that exceed EPA’s mercury screening value for recreational 

fishers (based on steam electric power plant discharges only) will decrease by 59 percent, 

thereby reducing the potential threat to human health from consuming contaminated fish. 

Under the alternate scenario analysis, EPA identified 14 steam electric power plants that 

discharge into the Great Lakes watershed. Table I-32 presents the pollutant removals to the Great 

Lakes watershed under the regulatory options considered by EPA. 

Under the alternate scenario analysis, EPA identified seven steam electric power plants 

that discharge to the Chesapeake Bay watershed. Under the final rule, EPA estimates the

following pollutant removals to the Chesapeake Bay watershed: 

 603 pounds of arsenic annually (89 percent reduction). 

 167 pounds of cadmium annually (84 percent reduction). 

 555 pounds of lead annually (97 percent reduction). 

 22.8 pounds of mercury annually (93 percent reduction). 

 4,550 pounds of selenium annually (96 percent reduction). 

 2,830 pounds of thallium annually (98 percent reduction). 

 667,000 pounds of total nitrogen annually (>99 percent reduction). 

 6,450 pounds of total phosphorus annually (81 percent reduction). 

Finally, EPA evaluated the improvements to downstream receiving waters. Table I-33

presents the number of river miles impacted by steam electric power plant discharges at baseline 

and under the regulatory options for the alternate scenario analysis. The table also presents the 

percent reduction in number of impacted river miles. 

7

 The count of impaired waters excludes the general impairment category “metals (not mercury)” and includes receiving waters 

impaired for arsenic, boron, cadmium, chromium, copper, lead, manganese, mercury, selenium, zinc, phosphorous, nutrients, 

TDS, or chlorides. 

I-34
Appendix I—Analysis for Alternate Scena

Table I-31. Pollutant Removals to Impaired Waters by Impairment Type 

Impairment 

Type/Number of 

Receiving Waters b Pollutant 

Baseline 

Loadings

(lbs/yr)

Pollutant Removals (lbs/yr) to Impaired Waters Under the Regula

Reduction) a

Option A Option B Option C Option 

Mercury-Impaired Receiving Waters

21 Mercury 123 52.3 52.6 100 123 

(42%) (43%) (81%) (99%) 

Metals (Not Mercury)-Impaired Receiving Waters

24

Arsenic 4,020 2,660 2,660 3,540 3,830 

(66%) (66%) (88%) (95%) 

Boron 4,420,000 312,000 312,000 344,000 353,000 

(7%) (7%) (8%) (8%) 

Cadmium 1,810 1,360 1,360 1,630 1,710 

(75%) (75%) (90%) (94%) 

Chromium

VI 25.6 22.0 22.0 25.5 25.6 

(86%) (86%) (>99%) (>99%

Copper 4,150 2,410 2,410 3,690 4,060 

(58%) (58%) (89%) (98%) 

Lead 2,500 1,300 1,300 2,170 2,440 

(52%) (52%) (87%) (98%) 

Manganese 1,030,000 718,000 718,000 778,000 800,000 

(70%) (70%) (76%) (78%) 

Nickel 14,700 9,210 9,250 13,200 14,500 

(62%) (63%) (89%) (99%) 

Selenium 20,000 3,250 19,100 19,500 19,700 

(16%) (95%) (98%) (98%) 

Thallium 6,620 1,190 1,190 5,070 6,450 

(18%) (18%) (77%) (97%) 

Zinc 23,600 18,400 18,400 21,700 22,800 

(78%) (78%) (92%) (96%) 

I-35
Appendix I—Analysis for Alternate Scena

Table I-31. Pollutant Removals to Impaired Waters by Impairment Type 

Impairment 

Type/Number of 

Receiving Waters b Pollutant 

Baseline 

Loadings

(lbs/yr)

Pollutant Removals (lbs/yr) to Impaired Waters Under the Regula

Reduction) a

Option A Option B Option C Option 

Nutrient-Impaired Receiving Waters

15

Total 

Nitrogen 242,000 0 (0%) 158,000 212,000 241,000 

(65%) (87%) (99%) 

Total 

Phosphorous 2,870 0 (0%) 0 (0%) 1,520 2,330 

(53%) (81%) 

TDS and Chlorides-Impaired Receiving Waters

2 

Chlorides CBI CBI CBI CBI CBI 

TDS CBI CBI CBI CBI CBI 

Source: ERG, 2015c. Acronyms: CBI (Confidential business information); 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 – For the impaired waters proximity analysis, EPA evaluated 172 immediate receiving waters that receive discharges of the evaluated 

c – The EPA impaired water database listed 24 immediate receiving waters as impaired based on the “metal, other than mercury” impai

24 immediate receiving waters, 13 receiving waters are also listed as impaired for one or more specific metals (arsenic, cadmium, mangzinc). One additional immediate receiving water is impaired for boron (but not included in the “metals, other than mercury” impairmen

d – Total phosphorous and total nitrogen loadings are presented with this impairment category. Total nitrogen loadings are the sum of t

nitrate/nitrite as N loadings. 

I-36
 

 

Appendix I—Analysis for Alternate Scenario with Clean Power Plan

Table I-32. Pollutant Removals to the Great Lakes Watershed Under the Regulatory 

Options

Pollutant 

Baseline 

Loadings to

the Great 

Lakes 

Watershed 

(lbs/yr)

Pollutant Removals (lbs/yr) to Great Lakes Watershed Under the Regulatory 

Options (Percent Reduction) a

Option A Option B Option C Option D Option E

Arsenic 1,030 46.7 (5%) 46.7 (5%) 509 (49%) 955 (92%) 1,000 (97%)

Boron 760,000 1,380 (<1%) 1,380 (<1%) 14,700 (2%) 27,300 (4%) 27,300 (4%) 

Cadmium 286 6.03 (2%) 6.03 (2%) 134 (47%) 257 (90%) 266 (93%)

Chromium

VI 0.548 0.471 (86%) 0.471 (86%) 0.548 (>99%) 0.548 (>99%) 0.548 (>99%) 

Copper 1,170 26.6 (2%) 26.6 (2%) 596 (51%) 1,140 (98%) 1,150 (98%)

Lead 869 18.8 (2%) 18.8 (2%) 446 (51%) 856 (99%) 856 (99%)

Manganese 112,000 47.3 (<1%) 47.3 (<1%) 34,700 (31%) 68,300 (61%) 68,300 (61%)

Mercury 37.5 1.20 (3%) 1.48 (4%) 19.1 (51%) 35.7 (95%) 37.1 (99%)

Nickel 4,310 20.6 (<1%) 29.3 (1%) 2,150 (50%) 4,210 (98%) 4,260 (99%)

Selenium 3,540 20.9 (1%) 2,890 (82%) 3,120 (88%) 3,350 (95%) 3,350 (95%)

Thallium 4,320 21.8 (1%) 21.8 (1%) 2,190 (51%) 4,280 (99%) 4,280 (99%)

Zinc 3,860 55.5 (1%) 55.5 (1%) 1,790 (46%) 3,470 (90%) 3,760 (97%)

Nitrogen, 

total b 646,000 2,420 (<1%) 299,000

(46%)

474,000

(73%)

643,000

(>99%)

643,000

(>99%)

Phosphorus, 

total 10,900 135 (1%) 135 (1%) 5,080 (47%) 9,850 (91%) 9,850 (91%)

Chlorides 24,100,000 11,400 (<1%) 11,400 (<1%) 693,000 (3%) 1,350,000

(6%)

1,350,000

(6%)

TDS 116,000,000 187,000

(<1%)

187,000

(<1%)

18,400,000

(16%)

36,100,000

(31%)

36,100,000

(31%)

Source: ERG, 2015a; ERG, 2015c. 

Acronyms: lbs/yr (pounds per year); TDS (total dissolved solids).

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. 

I-37
Appendix I—Analysis for Alternate Scena

Table I-33. Key Environmental Improvements for Downstream Waters Under the Regulatory 

Evaluation Criteria

Number of RiverMiles Exceeding 

Criteria Under 

Baseline Conditions 

Number of River-Miles Exceeding Criteria 

(Percent Reduction from Baseline Conditions) Under the Reg

Option A Option B Option C Option 

Water Quality Results Freshwater Acute NRWQC 412 395 

(4%)

395 

(4%)

393 

(5%)

388 

(6%)

Freshwater Chronic NRWQC

605 592 

(2%)

560 

(8%)

542 

(10%)

514 

(15%

Human Health Water andOrganism NRWQC

4,050 3,390

(16%)

3,390

(16%)

2,480

(39%)

1,930

(52%

Human Health Organism-onlyNRWQC

1,500 1,230

(18%)

1,230

(18%)

1,030

(31%)

781 

(48%

Drinking WaterMCL 

751 725 

(3%)

720 

(4%)

629 

(16%)

487 

(35%

Wildlife Results Fish Ingestion NEHC for Minks 1,070 893 

(17%)

862 

(19%)

720 

(33%)

524 

(51%

Fish Ingestion NEHC for Eagles 1,870 1,580

(15%)

1,560

(16%)

1,260

(32%)

957 

(49%

Human Health Results—Non-Cancer Non-cancer reference dose forchild (recreational) 

5,800 4,380

(24%)

4,380

(25%)

2,890

(50%)

2,250

(61%

Non-cancer reference dose foradult (recreational) 

3,420 2,830

(17%)

2,820

(17%)

1,960

(43%)

1,430

(58%

Non-cancer reference dose forchild (subsistence) 

9,240 7,790

(16%)

7,760

(16%)

5,520

(40%)

4,490

(51%

Non-cancer reference dose foradult (subsistence) 

6,540 5,050

(23%)

5,050

(23%)

3,330

(49%)

2,620

(60%

I-38
Appendix I—Analysis for Alternate Scena

Table I-33. Key Environmental Improvements for Downstream Waters Under the Regulatory 

Evaluation Criteria

Number of RiverMiles Exceeding 

Criteria Under 

Baseline Conditions 

Number of River-Miles Exceeding Criteria 

(Percent Reduction from Baseline Conditions) Under the Reg

Option A Option B Option C Option 

Human Health Results—Cancer Cancer risk for child (recreational)

227 216 

(5%)

216 

(5%)

211 

(7%)

210 

(8%)

Cancer risk for adult (recreational)

286 263 

(8%)

263 

(8%)

251 

(12%)

246 

(14%

Cancer risk for child (subsistence) 

262 241 

(8%)

241 

(8%)

239 

(9%)

235 

(10%

Cancer risk for adult (subsistence) 

414 375 

(9%)

375 

(9%)

355 

(14%)

328 

(21%

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 72,100 river-miles in the downstream receiving water analysis for toxic, bioaccumulative pollutants. Down

concentrations are calculated until one of three conditions occurs: 1) the discharge travels 300 kilometers (km) downstream; 2) the disc

for a week; or 3) the concentration reaches 1 x 10-9 milligrams per liter (mg/L). 

I-39
Appendix J —EA Loadings and TDD Loadings: Sensitivity Analysis 

APPENDIX J 

EA LOADINGS AND TDD LOADINGS: SENSITIVITY

ANALYSIS 

As discussed in Section 3, the analyses presented in the environmental assessment (EA) 

report are based on loadings datasets that differ from those that are summarized in the 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 

appendix presents a sensitivity analysis that evaluates the difference between the two pollutant

loadings datasets (the “EA loadings” and the “TDD loadings”) and estimates the change in counts

of environmental exceedances that would have resulted from use of the TDD loadings dataset. The

analyses in this section reflect changes in the industry that may occur as a result of the Clean Power 

Plan [Clean Air Act Section 111(d)] (CPP). 

Table J-1 quantifies the difference in baseline loadings between the EA loadings and TDD 

loadings for each of the ten pollutants that are modeled in the EA analyses. 

Impacts to Exceedances across All Pollutants

To estimate the influence that using the TDD loadings would have on the overall counts of 

exceedances identified in the EA Report, EPA took the following steps: 

1. EPA determined how many immediate receiving waters had exceedances that were 

due, in part or in whole, to selenium, thallium, or chromium VI. Because the EA 

loadings for these pollutants are equal to (or, in the case of selenium, slightly greater 

than) the corresponding TDD loadings, each immediate receiving water in this group 

would have had exceedances if EPA had used the TDD loadings. 

2. Of the remaining receiving waters with exceedances, EPA determined how many had

exceedances that were due, in part or in whole, to arsenic (whose loadings are 9.4

percent lower using the TDD loadings). By assuming that the difference in loadings

would result in an equal change in the count of exceedances, EPA assumed that use of

the TDD loadings would have resulted in 9.4 percent fewer exceedances among this

group of immediate receiving waters. 

3. Of the remaining receiving waters with exceedances, EPA determined how many had

exceedances that were due, in part or in whole, to zinc (whose loadings are 14 percent 

lower in the TDD loadings). By assuming that the difference in loadings would result 

in an equal change in the count of exceedances, EPA assumed that use of the TDD 

loadings would have resulted in 14 percent fewer exceedances among this group of 

immediate receiving waters.

4. EPA repeated this process for the remaining modeled pollutants (in order of increasing 

change between the EA loadings and TDD loadings) until all immediate receiving 

waters with exceedances were taken into account. 

Table J-2 presents the results of this analysis, which demonstrates that use of the TDD 

loadings in place of the EA loadings would have only minimal effect on the overall counts of 

J-1
Appendix J —EA Loadings and TDD Loadings: Sensitivity Analysis 

exceedances identified by the immediate receiving water (IRW) model. The benchmark

exceedances that would be most affected by use of the TDD loadings are exceedances of chemical

stressor concentration limits (CSCLs) for sediment biota. Exceedances of this benchmark under 

baseline conditions would be approximately 4 percentage points lower (41 percent versus 45 

percent) based on use of the TDD loadings instead of the EA loadings. All other benchmark 

exceedances change by 2 percentage points or less. 

This analysis assumes a linear relationship between a loadings reduction and a change in 

exceedances for that pollutant. As discussed below, however, this assumption likely overestimates

the effect of a loadings change on the count of exceedances.

Impacts to Individual Pollutant Exceedances

Table I-22 in Appendix I presents the industry-wide pollutant-specific removals under the 

regulatory options (reflecting changes in the industry as a result of the CPP). Table I-25 through 

Table I-30 present the pollutant-specific environmental improvements under the regulatory 

options. A comparison of the values in these tables indicates that an industry-wide pollutant 

loading reduction of x under the regulatory options usually results in a reduction in benchmark 

exceedances of less than x. For example, looking at Option A: 

 Cadmium: Loadings reduced by 72 percent; exceedances reduced by approximately 19 

to 43 percent. 

 Mercury: Loadings reduced by 62 percent; exceedances reduced by approximately 7 to 

14 percent. 

 Arsenic: Loadings reduced by 56 percent; exceedances reduced by approximately 4 to 

33 percent. 

 Selenium: Loadings reduced by 21 percent; exceedances reduced by approximately 3 

to 19 percent. 

 Thallium: Loadings reduced by 13 percent; exceedances reduced by approximately 0 

to 9 percent. 

This suggests that the use of the TDD loadings instead of the EA loadings would have a 

less-than-linear effect on the number of exceedances in the EA for each pollutant. Based on this 

observation, EPA estimates that use of the TDD loadings would result in the following 

approximate effects in the baseline counts of pollutant-specific exceedances identified using the 

EA loadings: 

 Selenium, thallium, and chromium VI: No decrease in exceedances.

 Arsenic, zinc, mercury: Approximately 10 percent fewer exceedances. 

 Cadmium, copper, and nickel: Approximately 20 percent fewer exceedances.

 Lead: Approximately 25 percent fewer exceedances.

J-2
Appendix J —EA Loadings and TDD Loa

Table J-1. Comparison of Annual Baseline Pollutant Discharges from Steam Electric Power Plants 

Wastestreams), EA Loadings versus TDD Loadings 

Pollutant 

Baseline Loadings Option D Removals Option D 

EA Version 

(lbs/yr)

TDD 

Version 

(lbs/yr)

Percent Change

EA Version 

(lbs/yr)

TDD 

Version 

(lbs/yr)

Percent Change

EA Version 

(%) 

V

Arsenic 22,200 20,100 -9.4% 20,700 18,700 -10% 93% 

Cadmium 10,900 8,290 -24% 10,300 7,660 -26% 94% 

Chromium (VI) 119 119 0% 119 119 0% 100% Copper 24,000 16,400 -32% 23,400 15,800 -33% 98% 

Lead 14,600 7,670 -47% 14,200 7,340 -48% 98% 

Mercury 1,180 992 -16% 1,150 961 -16% 97% 

Nickel 94,200 61,900 -34% 92,400 60,200 -35% 98% 

Selenium 113,000 115,000 1.4% 110,000 111,000 1.4% 97% 

Thallium 43,900 43,900 0% 42,800 42,800 0.0% 98% 

Zinc 145,000 124,000 -14% 138,000 117,000 -15% 95% 

Source: ERG, 2015o. Note: Loadings and pollutant removals are rounded to three significant figures. Percentages are rounded to two significant figures.

J-3
 

 

 

Appendix J —EA Loadings and TDD Loadings: Sensitivity Analysis 

Table J-2. Comparison of Modeled Baseline Exceedances (Using EA Loadings) and 

Approximated Baseline Exceedances (Using TDD Loadings) 

Evaluation Benchmark

Baseline Exceedances in 

Appendix I

(EA Loadings Version) 

Baseline Approximated 

Exceedances

(TDD Loadings Version)

Number a Percentage Number a Percentage

Freshwater Acute NRWQC 7 4% 5.85 4% 

Freshwater Chronic NRWQC 28 17% 27.8 17% 

Human Health Water and Organism

NRWQC

73 45% 69.8 43% 

Human Health Organism Only NRWQC 51 31% 49.5 30% 

Drinking Water MCL 29 18% 29.0 18% 

Fish Ingestion NEHC for Minks 46 28% 44.0 27% 

Fish Ingestion NEHC for Eagles 56 34% 52.4 32% 

CSCLs for Sediment Biota 40 25% 34.2 21% 

Negative Reproductive Effects in Fish

from Selenium b

21 13% 21.0 13% 

Negative Reproductive Effects in

Mallards from Selenium b

25 15% 25.0 15% 

Non-Cancer Reference Dose for Child 

(recreational)

75 46% 72.7 45% 

Non-Cancer Reference Dose for Adult 

(recreational)

67 41% 64.2 39% 

Non-Cancer Reference Dose for Child 

(subsistence) 

90 55% 87.8 54% 

Non-Cancer Reference Dose for Adult 

(subsistence) 

78 48% 75.7 46% 

Source: ERG, 2015o. 

Acronyms: CSCL (Chemical stressor concentration limit); MCL (Maximum contaminant level); NEHC (No Effect 

Hazard Concentration); NRWQC (National Recommended Water Quality Criteria). 

a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 

steam electric power plants (some of which discharge to multiple receiving waters). The IRW model, which 

excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving waters and loadings from

143 steam electric power plants. 

b – These rows indicate the number of immediate receiving waters whose median modeled egg/ovary concentration 

is predicted to result in reproductive impacts among at least 10 percent of the exposed fish or mallard population, as

determined using the ecological risk model. 

J-4