# Appendix A— Literature Review Methodology and Results



# APPENDIX A

LITERATURE REVIEW METHODOLOGY AND RESULTS

This appendix presents the methodology, resource s, 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 nutr ients) in the discharges. EPA also searched for

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

governments.

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

environmental groups, industry or ganizations, and other non-peer-r eviewed information sources.

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

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

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

reported in gray literatu re sources before it is well documen ted in peer-reviewed journals or

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

additional searches of peer-revie wed journals for more detailed in formation 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 keyw ord list in Table A-1:

 

# Scirus – A comprehensive science-specific sear ch engine that provides access to a large

database of scientific, tec hnical, and medical journals.

 

# Science Direct – An online library that f eatures 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. A lthough 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 furthe r focus the literature search.

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

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

 

# Reviewed references cited in previously identified published liter ature 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 c onsultations with information on the case

study sites referenced in Dr. Christopher Ro we’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 sear ch engines described above.

 

# Reviewed EPA’s December 2014 Coal Comb ustion 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 el ectric 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 summar ize information EPA gathered from the

literature review:

 

# Table A-2. Summary of L iterature 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 Do cumented Ground Water Dama ge Cases from Surface

Impoundments.

 

# Table A-5. Summary of Do cumented Ground Water Damage Cases from Landfills.

 

# Table A-6. Summary of Do cumented Surface Water Damage Cases from Surface

Impoundments.

 

# Table A-7. Summary of Docu mented 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 Nuisan ces Unrelated to Steam Electric Power

Plants.

 

# Table A-10. Summary of Selenium Concentra tions in the Environment and Organisms

Experiencing Adverse Effects.

Table A-2 highlights the results of the literatu re search, including doc uments identified by

keyword searches and relevant documents id entified from supplemental methods. During the

period following completion of the literature revi ew 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 a nd 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 Cas e 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 additi onal literature in the EA report and in the other

tables included in this Appendix.

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

water identified during the literature search an d 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 summari ze attractive nuisances identified during the literature search,

related and unrelated to steam el ectric power plants, respectivel y. Table A-10 presents selenium

concentrations in the environment that are docum ented 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 Re view 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 affiliate d with state or federal government agencies.

c – University research includes finalized dissertations an d 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 fo rmal 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-6Appendix A— Literature Review Methodology and ResultsTable A-3. Summary of Surface Water and Ground Water ImpactsReported in Damage Cases and Other Documented Sitesfrom Steam Electric Power Plant DischargesPlant NameNumber of Damage Casesand Other Literature thatDocumentSurface Water ImpactsaNumber of Damage Casesand Other Literature thatDocumentGround Water ImpactsaA.B. Brown Generating Station, Southern Indiana Gas and Electric Company (SIGECO) (IN)01Allen Fossil Plant Tennessee Valley Authority (TVA) (TN)01Allen Steam Generating Plant, Duke Power (NC)11Alma Station, Dairyland Power (WI)02Asheville Plant, Progress Energy (NC)21B.C. Cobb Power Plant, Consumers Energy (MI)02Bailly Generating Station, Northern IndianaPublic Service Company (NIPSCO) (IN)02Belews Creek Steam Station, Duke Energy (NC)141Belle River Power Plant, Detroit Edison Company (MI)11Big Bend Station, Tampa Electric Company (FL)11Big Cajun 2 Power Plant, NRG Energy/Louisiana Generating, LLC (LA)01Brandon Shores, Constellation Energy (MD)01Brayton Point Station, Dominion (MA)01Bruce Mansfield Power Plant,First Energy (PA)11Buck Steam Station, Duke Energy (NC)10Bull Run Steam Plant, Tennessee Valley Authority (TVA) (TN)11C.D. McIntosh, Jr. Power Plant, City of Lakeland (FL)01C.R. Huntley Generating Station, NRG Energy (NY)01Canadys Plant, South Carolina Electric & Gas (SCE&E) (SC)01Cape Fear Steam Plant, Progress Energy (NC)01Cardinal Plant, American Electric Power (AEP) (OH)11Cargill Salt Power Plant, Cargill (MI)11Cayuga Generating Station, Duke Energy (NY)11Chalk Point Generating Station, Mirant (MD)11Chesapeake Energy Facility, Dominion Power (VA)12A-7Appendix A— Literature Review Methodology and ResultsTable A-3. Summary of Surface Water and Ground Water ImpactsReported in Damage Cases and Other Documented Sitesfrom Steam Electric Power Plant DischargesPlant NameNumber of Damage Casesand Other Literature thatDocumentSurface Water ImpactsaNumber of Damage Casesand Other Literature thatDocumentGround Water ImpactsaCholla Steam Electric Generating Station, Arizona Public Service Company (AZ)01Christ Power Plant, Gulf Power (Southern Company) (FL)01Clifty Creek Station, Indiana Kentucky Electric Company (IKEC) (IN)01Clinch River Plant, American ElectricPower (AEP)/Appalachian Power (VA)10Coal Creek Station, Cooperative Power Association/United Power (ND)01Coffeen Power Station, Ameren (IL)01Colbert Fossil Plant, TennesseeValley Authority (TVA) (AL)01Coleto Creek Power Station, International Power (TX)01Colstrip Power Plant, PPL Montana (MT)01Columbia Electric Generating Station (WI)50Columbia Energy Center, Alliant Energy (WI)10Conesville Power Plant, AmericanElectric Power (AEP) (OH)01Cross Generating Station, Santee Cooper/South Carolina Public Service Authority (SCPSA) (SC)01Cumberland Steam Plant, TennesseeValley Authority (TVA) (TN)11Curtis Stanton Energy Center,Orlando Utility Commission (FL)11Dallman Station, City Water, Light and Power (IL)01Dan River Steam Station, Duke Energy (NC)21Danskammer Generating Station, Dynegy (NY)01D-Area Coal-Fired Power Plant, Savannah River Site (SRS) (SC)240Dave Johnston Power Plant (WY)11Dickerson Generating Station, Mirant (MD)11Dolet Hills Power Station, Central Louisiana Electric Co-Op (CLECO) Power, LLC (LA)01Duck Creek Station, Central Illinois Light Company (IL)01Dunkirk Generating Station, NRG Energy (NY)01E.J. Stoneman Generating Station, Dairyland Power Cooperative (WI)01A-8Appendix A— Literature Review Methodology and ResultsTable A-3. Summary of Surface Water and Ground Water ImpactsReported in Damage Cases and Other Documented Sitesfrom Steam Electric Power Plant DischargesPlant NameNumber of Damage Casesand Other Literature thatDocumentSurface Water ImpactsaNumber of Damage Casesand Other Literature thatDocumentGround Water ImpactsaEast Bend Generating Station, Cinergy (KY)01Eckert Station, Lansing Board of Water & Light (MI)01Edgewater Generating Station, Alliant Energy (WI)01Elizabethtown Power Plant, NorthCarolina Power Holdings (NC)01Elrama Power Plant, Reliant Energy (PA)11Erickson Station, Lansing Board of Water & Light (MI)01Fair Station, Central Iowa Power Cooperative (IA)02Fayette Power Project, Lower Colorado River Authority (TX)01Flint Creek Power Plant, American Electric Power (AEP)/South West Electric Power Company(SWEPCO) (AR)11Gallatin Fossil Plant, TennesseeValley Authority (TVA) (TN)01General James M. Gavin Power Plant, AmericanElectric Power/Ohio Power Company (OH)11George Neal Station North, Berkshire Hathaway/MidAmerican Energy Company (IA)01George Neal Station South, Berkshire Hathaway/MidAmerican Energy Company (IA)01Gibson Generating Station, Duke Energy (IN)51Glen Lyn Plant, American Electric Power (AEP)/Appalachian Power (VA)60Grainger Generating Station, SanteeCooper/South Carolina Public Service Authority (SCPSA) (SC)11Greenidge Generation Plant, AES (NY)01Harbor Beach Power Plant, Detroit Edison Company (MI)11Hatfield's Ferry Power Station, Allegheny Energy (PA)11Havana Power Plant, Illinois Power Company (IL)01Hennepin Power Station, Illinois Power Company (IL)01Herbert A. Wagner, Constellation Energy (MD)01Hickling Generation Plant, AES (NY)01Hopewell Power Station, Dominion Power (VA)01A-9Appendix A— Literature Review Methodology and ResultsTable A-3. Summary of Surface Water and Ground Water ImpactsReported in Damage Cases and Other Documented Sitesfrom Steam Electric Power Plant DischargesPlant NameNumber of Damage Casesand Other Literature thatDocumentSurface Water ImpactsaNumber of Damage Casesand Other Literature thatDocumentGround Water ImpactsaHunlock Power Station, UGI Development Company (PA)01Hutsonville Power Station, Central Illinois Public Service Company (IL)01Independence Steam Station, Entergy/Arkansas Power and Light (AR)01Indian River Generating Station, NRG Energy (DE)11J.H. Campbell Power Plant, Consumers Energy (MI)11J.R. Whiting Generating Plant, CMS/Consumers Energy (MI)10Jennison Generation Plant, AES (NY)01John Amos Plant, American ElectricPower (AEP)/Appalachian Power (WV)10John H. Warden Generating Station, Integrys (MI)11John Sevier Fossil Plant, Tennessee Valley Authority (TVA) (TN)11Johnsonville Fossil Plant, TennesseeValley Authority (TVA) (TN)22Joliet Generating Station 9, Midwest Generation (IL)02Joppa Steam Plant, Ameren(Electric Energy) (IL)01Karn/Weadock Generating Facility,Consumer Energy (MI)01Kenansville Plant, Green Power Energy Holdings (NC)01Kingston Fossil Plant, Tennessee Valley Authority (TVA) (TN)71Lansing Smith Plant, Florida Power and Light (FL)01Lee Steam Plant, Progress Energy (NC)01Leland Olds Station, Basin Electric Power Cooperative (ND)01Lumberton Power Plant, North Carolina Power Holdings (NC)01Marion Plant, Southern Illinois Power Cooperative (IL)11Marshall Steam Station, Duke Energy (NC)10Martin Lake Steam Station, Texas Utilities Electric Service Company (TX)90Martin's Creek Power Plant, PPL (PA)10Marysville Power Plant, Detroit Edison Company (MI)11A-10Appendix A— Literature Review Methodology and ResultsTable A-3. Summary of Surface Water and Ground Water ImpactsReported in Damage Cases and Other Documented Sitesfrom Steam Electric Power Plant DischargesPlant NameNumber of Damage Casesand Other Literature thatDocumentSurface Water ImpactsaNumber of Damage Casesand Other Literature thatDocumentGround Water ImpactsaMayo Steam Station, Progress Energy (NC)10McMeekin Station, SCANA/South CarolinaElectric & Gas Company (SCE&G) (SC)01Mendosa Power Station, Ameren Energy Generating Company, (IL)01Merom Generating Station, Hoosier Energy (IN)11Miamiview Landfill, Cincinnati Gas & Electric Company (OH)b01Michigan City Generating Station, Northern Indiana Public Service Company (NIPSCO) (IN)01Mill Creek Plant, E ON U.S./Louisville Gas & Electric (LG&E) (KY)01Mitchell Power Station, Allegheny Energy (PA)01Montville Generating Station, NRG Energy/Montville Power, LLC (CT)11Morgantown Generating Station, Mirant (MD)22Muskingum River Plant, American Electric Power (AEP)/ Ohio Power Company (OH)01Nelson Dewey Generating Station, Alliant Energy (WI)01Northeastern Station, American Electric Power/Public Service Company Oklahoma (OK)01Oak Creek Power Plant, Wisconsin Energy (WE Energies (WE))/Wisconsin Electric PowerCompany (WI)10Oak Ridge Y-12 Plant, Department of Energy (TN)41Paradise Fossil Plant, Tennessee Valley Authority (TVA) (KY)01Parish Generating Station, NRG Energy/Texas Genco II (TX)01Pearl Station, Prairie Power Inc./Soyland Power Coop (IL)01Petersburg Generating Station, Indianapolis Power & Light (IN)01Phillips Power Plant, Duquesne Light Company (PA)11Pirkey Power Plant, Southwestern Electric Power Company (SWEPCO) (TX)20Plant Bowen, Georgia Power (GA)10Port Washington Facility, Wisconsin Electric Power Company (WEPCO) (WI)02Portland Generating Station, RRI Energy (PA)11A-11Appendix A— Literature Review Methodology and ResultsTable A-3. Summary of Surface Water and Ground Water ImpactsReported in Damage Cases and Other Documented Sitesfrom Steam Electric Power Plant DischargesPlant NameNumber of Damage Casesand Other Literature thatDocumentSurface Water ImpactsaNumber of Damage Casesand Other Literature thatDocumentGround Water ImpactsaPowerton Plant, Commonwealth Edison (IL)11Prairie Creek Station, InterstatePower and Light (Alliant) (IA)01Presque Isle Power Plant, WE Energies (WE) (MI)01Pulliam Power Plant, Wisconsin Public Service Corp. (WI)01R.M. Heskett Station, Montana-Dakota Utilities (ND)01R.M. Schahfer Generating Station (IN)01Reid Gardner Generating Facility, Nevada Energy (NV)11Riverbend Steam Station, Duke Energy (NC)40Rock River Generating Station, Alliant Energy (WI)01Rocky Mount Power Plant (NC)01Rodemacher Power Station, Central LouisianaElectric Co-Op (CLECO) Power, LLC (LA)01Roxboro Plant, Progress Energy (NC)80Salem Harbor Station, Dominion (MA)01SCANA Williams Station (SC)10Seminole Generating Station, Seminole Electric Cooperative (FL)11Seward Generating Station, RRI Energy (PA)11Shawnee Fossil Plant, Tennessee Valley Authority (TVA) (KY)11Sheldon Station, Nebraska Public Power District (NE)01Sherburne County (Sherco) Generating Plant, Xcel Energy/Southern Minnesota Municipal PowerAgency (MN)01Shiras, Marquette Board of Light & Power (MI)01Spurlock Station, Eastern Kentucky Power Cooperative (KY)01Sutton Steam Plant, Progress Energy (NC)11Unnamed Plant 1c10A-12Appendix A— Literature Review Methodology and ResultsTable A-3. Summary of Surface Water and Ground Water ImpactsReported in Damage Cases and Other Documented Sitesfrom Steam Electric Power Plant DischargesPlant NameNumber of Damage Casesand Other Literature thatDocumentSurface Water ImpactsaNumber of Damage Casesand Other Literature thatDocumentGround Water ImpactsaUnnamed Plant 2c10Unnamed Plant 3c10Unnamed Plant 4c10Urquhart Station, South Carolina Electric & Gas Company (SGE&E) (SC)01Valley Power Plant, Wisconsin Energy (WI)01Venice Power Station, Union Electric Company/Ameren Energy/AmerenUE (IL)01Vermillion Power Station, Illinois Power (IL)01W.C. Beckjord Station, Duke Energy (formerly Cinergy) (OH)01W.J. Neal Station, Basin Electric Power Cooperative (ND)11Wateree Station, SCE&G (SC)11Waukegan Generating Station, Midwest Generation (Edison International) (IL)01Welsh Power Plant, Southwestern Electric Power Company (SWEPCO) (TX)30Westover Generation Plant, AES (NY)01Widows Creek Fossil Plant, Tennessee Valley Authority (TVA) (AL)01Winyah Generating Station, Santee Cooper/South Carolina Public Service Authority (SCPSA) (SC)01Wood River Power Station, Illinois Power Company (IL)01Yorktown Power Station, Virginia Electric Power and Power Company (VEPCO) (VA)01Total152149Source: 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 unique number of plants,these impacts were assumed to be associated with aplant not already identified elsewhere in this table.A-13Appendix A— Literature Review Methodology and ResultsTable A-4. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededMCLbExceeded Federal/State WQC/StandardsbGround WaterImpacted SurfaceWaterscImpactedOff-SiteSourcedAllen Fossil Plant TennesseeValley Authority (TVA) (TN)Pond/ImpoundmentArsenic, Manganese, TDSXAllen Steam Generating Plant,Duke Power (NC)Pond/ImpoundmentManganese, Iron, pH, Nitrate,NickelXAlma Off-site Fly Ash Landfill,Dairyland Power (WI)Pond/ImpoundmentSulfate, Manganese, Boron,Selenium, CadmiumAsheville Steam Electric Plant,Pond/ImpoundmentBoron, Chromium, Iron,XXXProgress Energy (NC)Manganese, Thallium, Nitrate,Sulfate, pH, TDS, Cadmium,Arsenic, AntimonyBailly Generating Station,Northern Indiana Public ServiceCompany (NIPSCO) (IN)Pond/Impoundment,LandfillArsenic, CadmiumXBangor Quarry Ash DisposalSite, Portland Generating Station,RRI Energy (PA)Pond/Impoundment,LandfillSelenium, Boron, Cadmium,Hexavalent Chromium, Iron,Manganese, Sulfate, TDS,Aluminum, FluorideXXBC Cobb, Consumers Energy(MI)Pond/ImpoundmentBoron, Lithium, Manganese,Sulfate, AmmoniaXBelews Creek Steam Station,Pond/Impoundment,Selenium, Arsenic, Boron,XXXXDuke Energy (NC)LandfillCadmium, Iron, Lead,Manganese, Nitrate, Sulfate, pH,BromideBig Bend Station, Tampa ElectricCompany (FL)Pond/Impoundment,LandfillArsenic, Aluminum, Boron,Chloride, Fluoride, Iron,Manganese, Molybdenum,Sulfate, Sodium, Thallium, TDSXXXBig Cajun 2 Power Plant, NRGEnergy/Louisiana Generating,LLC (LA)Pond/ImpoundmentSelenium, TDS, Barium, ArsenicXA-14Appendix A— Literature Review Methodology and ResultsTable A-4. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededMCLbExceeded Federal/State WQC/StandardsbGround WaterImpacted SurfaceWaterscImpactedOff-SiteSourcedBrandywine Coal Ash Landfill,Mirant Mid-Atlantic LLC (MD)Pond/Impoundment,LandfillSelenium, Cadmium, Lead,Manganese, Iron, Aluminum,Sulfate, TDS, ChlorideXXXBull Run Steam Plant, TennesseePond/ImpoundmentAluminum, Cadmium, Iron,XValley Authority (TVA) (TN)Sulfate, Arsenic, Cobalt, Calcium,Manganese, Molybdenum, Boron,NickelC.D. McIntosh, Jr. Power Plant,City of Lakeland (FL)Pond/Impoundment,LandfillSelenium, Arsenic, Cadmium,Lead, Manganese, Vanadium,Nitrate, Iron, Sulfate, TDS, pHXC.R. Huntley Flyash Landfill(NY)Pond/Impoundment,LandfillArsenic, Iron, Manganese,Sulfate, TDS, Cadmium, Barium,Lead, TSSXXCanadys Plant, South CarolinaElectric & Gas (SCE&E) (SC)Pond/ImpoundmentArsenic, Nickel, SeleniumXXCape Fear Steam Plant, ProgressEnergy (NC)Pond/ImpoundmentLead, Chromium, Boron, Iron,Manganese, Sulfate, SeleniumXXCardinal Fly Ash Reservoir(FAR) 1 and 2, AmericanElectric Power (AEP) (OH)Pond/Impoundment,LandfillArsenic, Boron, MolybdenumXXCayuga Coal Ash DisposalPond/Impoundment,Selenium, Arsenic, Boron,XXXXLandfill, AES (NY)LandfillCadmium, Lead, TDS,Aluminum, Manganese, Sulfate,Barium, Sodium, Iron,Chromium, ZincCholla Steam Electric GeneratingStation, Arizona Public ServiceCompany (AZ)Pond/ImpoundmentSulfate, TDS, Chloride, FluorideXA-15Appendix A— Literature Review Methodology and ResultsTable A-4. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededMCLbExceeded Federal/State WQC/StandardsbGround WaterImpacted SurfaceWaterscImpactedOff-SiteSourcedClifty Creek Station, IndianaKentucky Electric Company(IKEC) (IN)Pond/Impoundment,LandfillBoron, Manganese, Iron, Sulfate,MagnesiumXCoal Creek Station SurfaceImpoundments, CooperativePower Association/United Power(ND)Pond/ImpoundmentSelenium, Arsenic, Sulfate,Chloride, Boron, Chromium, Iron,Sodium, TDSXColbert Fossil Plant, TennesseePond/Impoundment,Cadmium, Antimony, Arsenic,XValley Authority (TVA) (AL)LandfillLead, Nitrate, Aluminum, Iron,Manganese, Boron, Molybdenum,Cobalt, Lithium, Sulfate,ChromiumColeto Creek Power Station,International Power (TX)Pond/ImpoundmentArsenic, Lead, Boron, Cobalt,Nickel, VanadiumXColstrip Power Plant, PPLMontana (MT)Pond/Impoundment,LandfillSelenium, Boron, Sulfate, TDS,Molybdenum, Arsenic, ChlorideXXCross Generating Station, SanteeCooper/South Carolina PublicService Authority (SCPSA) (SC)Pond/Impoundment,LandfillArsenic, Cadmium, Chromium,Sodium, Sulfate, Iron, Aluminum,Chloride, TDSXCumberland Steam Plant,Tennessee Valley Authority(TVA) (TN)Pond/Impoundment,LandfillSelenium, Arsenic, Aluminum,Boron, Chloride, Iron,Manganese, Sulfate, TDS,VanadiumXXCurtis Stanton Energy Center,Orlando Utility Commission (FL)Pond/Impoundment,LandfillAluminum, Chloride, Iron,Manganese, Sodium, Sulfate,TDS, Vanadium, pHXDallman Station Ash and FGDPonds, City Water, Light andPower (IL)Pond/Impoundment,LandfillArsenic, Chromium, Sodium,Boron, Manganese, Iron, Sulfate,TDSXA-16Appendix A— Literature Review Methodology and ResultsTable A-4. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededMCLbExceeded Federal/State WQC/StandardsbGround WaterImpacted SurfaceWaterscImpactedOff-SiteSourcedDan River Steam Station, DukeEnergy (NC)Pond/Impoundment,LandfillChromium, Iron, Lead,Manganese, Silver, Sulfate,Arsenic, Antimony, Boron, TDS,pHXXDave Johnston Power Plant(WY)Pond/Impoundment,LandfillCadmium, Manganese, Sulfate,BoronXDolet Hills Power Station,Central Louisiana Electric Co-Op(CLECO) Power, LLC (LA)Pond/Impoundment,LandfillSelenium, Arsenic, Lead,Chloride, TDS, Sulfate, Iron, pHXDuck Creek Station, CentralIllinois Light Company (IL)Pond/ImpoundmentSulfate, TDS, Chloride,Manganese, Iron, BoronE.J. Stoneman GeneratingStation, Dairyland PowerCooperative (WI)Pond/ImpoundmentCadmium, Chromium, Sulfate,Manganese, Iron, Zinc, Boron,BariumXXEdgewater 1-4 Ash Disposal Site,Alliant (formerly WisconsinPower & Light) (WI)Pond/Impoundment,LandfillBoron, Sulfate, Iron, Chloride,TDS, Arsenic, SeleniumXXFayette Power Project (SamSeymour), Lower Colorado RiverAuthority (TX)Pond/Impoundment,LandfillSelenium, Aluminum, Chloride,Cobalt, Manganese,Molybdenum, Sulfate, TDS,VanadiumXFlint Creek Power Plant,American Electric Power(AEP)/South West ElectricPower Company (SWEPCO)(AR)Pond/Impoundment,LandfillSelenium, Barium, Cadmium,Chromium, Iron, Lead,Manganese, pH, Silver, Sulfate,TDSXXFly Ash Landfill, Coffeen/WhitePond/Impoundment,Sulfate, TDS, Manganese,X& Brewer Trucking (IL)LandfillCadmium, Chromium, Thallium,Beryllium, Boron, Nickel,Barium, Iron, Zinc, Aluminum,SodiumA-17Appendix A— Literature Review Methodology and ResultsTable A-4. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededMCLbExceeded Federal/State WQC/StandardsbGround WaterImpacted SurfaceWaterscImpactedOff-SiteSourcedGallatin Fossil Plant, TennesseePond/ImpoundmentBoron, Beryllium, Cadmium,XValley Authority (TVA) (TN)Iron, Manganese, Nickel, Sulfate,TDS, Arsenic, Mercury,Vanadium, CobaltGeneral James M. Gavin PowerPlant, American ElectricPower/Ohio Power Company(OH)Pond/Impoundment,LandfillArsenic, Barium, Cadmium,Lead, Molybdenum, Sulfate,TDS, Aluminum, Copper, Nickel,Zinc, Manganese, ChlorideXXXGeorge Neal Station NorthLandfill, BerkshireHathaway/MidAmerican EnergyCompany (IA)Landfill,Pond/ImpoundmentIron, Manganese, Sulfate, ArsenicXXGibson Generating Station, DukeEnergy (IN)Pond/Impoundment,Landfill, CoolingReservoirSelenium, Arsenic, Boron,Manganese, Iron, SodiumXXXGrainger Generating Station,Santee Cooper/South CarolinaPublic Service Authority(SCPSA) (SC)Pond/ImpoundmentArsenic, pHXHavana Power Plant, IllinoisPower Company (IL)Pond/ImpoundmentManganese, Sulfate, BoronHennepin Power Station, IllinoisPower Company (IL)Pond/Impoundment,LandfillSulfate, TDS, Boron, Iron,ManganeseXHunlock Power Station, UGIDevelopment Company (PA)Pond/ImpoundmentArsenic, Iron, ManganeseXXHutsonville Power Station,Central Illinois Public ServiceCompany (IL)Pond/ImpoundmentSulfate, TDS, Manganese, BoronA-18Appendix A— Literature Review Methodology and ResultsTable A-4. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededMCLbExceeded Federal/State WQC/StandardsbGround WaterImpacted SurfaceWaterscImpactedOff-SiteSourcedIndependence Steam Station,Entergy/Arkansas Power andLight (AR)Pond/Impoundment,LandfillCadmium, Iron, Lead,Manganese, pH, Sulfate, TDS,Arsenic, ChlorineXXJ.H. Campbell, ConsumersEnergy (MI)Pond/ImpoundmentpH, Antimony, Boron, Cadmium,Chromium, Iron, Lead, Selenium,Vanadium, Aluminum, Nickel,Thallium, Manganese, ZincXXJohn Sevier Fossil Plant,Tennessee Valley Authority(TVA) (TN)Pond/ImpoundmentArsenic, Aluminum, Cadmium,Manganese, Boron, Strontium,Sulfate, Selenium, HexavalentChromiumXXXXJohnsonville Fossil Plant,Tennessee Valley Authority(TVA) (TN)Pond/Impoundment,LandfillArsenic, Aluminum, Boron,Cadmium, Chromium, TDS, Iron,Lead, Manganese, Molybdenum,Sulfate, CobaltXXXXJoppa Steam Plant Ash Ponds,Ameren (Electric Energy) (IL)Pond/ImpoundmentLead, Chromium, Cobalt, Boron,Manganese, Sulfate, Iron, TDSXKarn/Weadock GeneratingFacility, Consumer Energy (MI)Pond/Impoundment,LandfillArsenic, Boron, Lithium,XXKingston Fossil Plant, TennesseeValley Authority (TVA) (TN)Pond/ImpoundmentArsenic, Selenium, Manganese,Cobalt, Aluminum, Ammonia,Thallium, IronXXXLansing Smith Plant, FloridaPond/ImpoundmentAluminum, Cadmium, Chloride,XPower and Light (FL)Chromium, Fluoride, Sulfate,Manganese, Iron, Radium-226,Radium-228, TDS, SodiumLee Steam Plant, ProgressEnergy (NC)Pond/ImpoundmentArsenic, Lead, Boron,Manganese, Iron, Chromium, pHXXLeland Olds Station, BasinElectric Power Cooperative (ND)Pond/ImpoundmentArsenic, Boron, Lead, SulfateXA-19Appendix A— Literature Review Methodology and ResultsTable A-4. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededMCLbExceeded Federal/State WQC/StandardsbGround WaterImpacted SurfaceWaterscImpactedOff-SiteSourcedLincoln Stone Quarry Landfill,Joliet Generating Station 29,Midwest Generation (IL)Pond/ImpoundmentAntimony, Manganese, Sulfate,Chloride, TDSXLincoln Stone Quarry Landfill,Pond/Impoundment,Arsenic, Ammonia, Boron,XXJoliet Generating Station 9,LandfillMolybdenum, pH, Sulfate, TDS,Midwest Generation (IL)Barium, Copper, Selenium,CadmiumLittle Blue Run SurfacePond/ImpoundmentSelenium, Arsenic, Aluminum,XXXImpoundment, Bruce MansfieldAntimony, Barium, Boron,Power Plant, First Energy (PA)Cadmium, Calcium, Chloride,Hexavalent Chromium, Fluoride,Iron, Lead, Manganese, pH,Sodium, Sulfate, TDS, TSS,Thallium, TurbidityMahoney Landfill, PowertonPlant, Commonwealth Edison(IL)Pond/Impoundment,LandfillArsenic, Selenium, Chromium,TDS, Cadmium, Lead, Nitrate,Iron, Manganese, Sulfate, Boron,XMarion Plant, Southern IllinoisPower Cooperative (IL)Pond/Impoundment,LandfillBoron, Cadmium, Iron,Aluminum, TDS, SulfateXXXXMcMeekin Station,SCANA/South Carolina Electric& Gas Company (SCE&G) (SC)Pond/Impoundment,LandfillChromium, Lead, Sulfate, Iron,TDSXMendosa Power Station AshPonds, Ameren EnergyGenerating Company, (IL)Pond/ImpoundmentArsenic, Boron, Manganese,Chromium (?), Sulfate, TDSXXMichigan City Site (IN)Pond/ImpoundmentArsenic, LeadXMill Creek Plant, E ONU.S./Louisville Gas & Electric(LG&E) (KY)Pond/Impoundment,LandfillArsenic, Chloride, Sulfate, TDSXA-20Appendix A— Literature Review Methodology and ResultsTable A-4. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededMCLbExceeded Federal/State WQC/StandardsbGround WaterImpacted SurfaceWaterscImpactedOff-SiteSourcedMitchell Power Station,Allegheny Energy (PA)Pond/Impoundment,LandfillArsenic, Boron, Iron,Molybdenum, Manganese, NickelXXMontville Generating Station,NRG Energy/Montville Power,LLC (CT)Pond/ImpoundmentArsenic, Beryllium, Cadmium,Copper, Iron, Lead, Manganese,Nickel, pH, ZincXXXMorgantown Generating Station,Faulkner Off-site DisposalFacility (MD)Pond/Impoundment,LandfillIron, pH, Cadmium, Aluminum,Chloride, Manganese, Sulfate,TDS, Copper, Lead, SeleniumXXXXMuskingum River Plant,American Electric Power (AEP)/Ohio Power Company (OH)Pond/ImpoundmentBarium, Iron, SulfateXXNelson Dewey Ash DisposalFacility, Alliant (formerlyWisconsin Power & Light) (WI)Pond/ImpoundmentSelenium, Arsenic, Sulfate,Boron, Fluoride, Cadmium (?),IronNortheastern Station AshLandfill, American ElectricPower/Public Service CompanyOklahoma (OK)Landfill,Pond/ImpoundmentSelenium, Arsenic, Barium,Chromium, Lead, Vanadium,Thallium, Sulfate, pHXXXOak Ridge Y-12 Plant, ChestnutRidge Operable Unit 2, OakRidge Reservation, Departmentof Energy (TN)Pond/ImpoundmentSelenium, Arsenic, Aluminum,Iron, Zinc, Manganese, Thallium(?)XXParadise Fossil Plant, TennesseeValley Authority (TVA) (KY)Pond/ImpoundmentArsenic, Boron, Chromium,Copper, ManganeseXParish Generating Station, NRGEnergy/Texas Genco II (TX)Pond/Impoundment,LandfillArsenic, Selenium, Barium,Boron, Chromium, Cobalt,Manganese, Molybdenum, SulfateXPearl Station, Prairie PowerInc./Soyland Power Coop (IL)Pond/ImpoundmentArsenic, Chromium, Boron,Manganese, Sulfate, Chlorine,Iron, TDS, Lead, BoronXA-21Appendix A— Literature Review Methodology and ResultsTable A-4. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededMCLbExceeded Federal/State WQC/StandardsbGround WaterImpacted SurfaceWaterscImpactedOff-SiteSourcedPhillips Power Plant Landfill,Duquesne Light Company (PA)Pond/Impoundment,LandfillTDS, Chloride, Fluoride,Manganese, Aluminum, ArsenicXXXXPrairie Creek Generating StationAsh Landfill, Interstate Powerand Light (Alliant) (IA)Pond/Impoundment,LandfillArsenic, Boron, Manganese,Sulfate, IronXXR.M. Schahfer GeneratingStation (IN)Landfill,Pond/ImpoundmentSulfate, Iron, Manganese,Molybdenum, Chlorine, Sodium,BoronReid Gardner GeneratingPond/Impoundment,Selenium, Arsenic, Chloride,XXXXFacility, Nevada Energy (NV)LandfillSulfate, TDS, Nitrate, Boron,Chromium, Manganese,Magnesium, Molybdenum,Sodium, Vanadium, Titanium,Barium, Iron, AluminumRock River Ash DisposalFacility, Alliant (formerlyWisconsin Power & Light) (WI)Pond/ImpoundmentMercury, Arsenic, Sulfate, Iron,Selenium, Boron, TDSXRodemacher Power Station,Central Louisiana Electric Co-Op(CLECO) Power, LLC (LA)Pond/Impoundment,LandfillArsenic, Lead, pH, TDS,Chloride, SulfateXSeminole Generating Station,Seminole Electric Cooperative(FL)Pond/Impoundment,LandfillArsenic, Chloride, Chlorine,Sulfate, Iron, TDS, Boron,Aluminum, Lead, SodiumXXXSeward Generating Station, RRIEnergy (PA)Pond/Impoundment,LandfillSelenium, Arsenic, Aluminum,Antimony, Cadmium, Chloride,Chromium, Iron, Lead,Manganese, Nickel, pH, Sulfate,TDS, Zinc,XXXA-22Appendix A— Literature Review Methodology and ResultsTable A-4. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededMCLbExceeded Federal/State WQC/StandardsbGround WaterImpacted SurfaceWaterscImpactedOff-SiteSourcedShawnee Fossil Plant, TennesseePond/Impoundment,Selenium, Arsenic, Boron, pH,XXXValley Authority (TVA) (KY)LandfillSulfate, TDS, Beryllium, Cobalt,Nickel, Molybdenum,Manganese, VanadiumSherburne County (Sherco)Generating Plant, XcelEnergy/Southern MinnesotaMunicipal Power Agency (MN)Pond/Impoundment,LandfillArsenic, Cadmium, Lead, Sulfate,Selenium, BoronXSpurlock Station, EasternKentucky Power Cooperative(KY)Pond/Impoundment,LandfillArsenic, Sulfate, TDSXXSutton Steam Plant, ProgressEnergy (NC)Pond/ImpoundmentArsenic, Boron, Manganese, Iron,Thallium, Selenium, Antimony,Lead, Sulfate, TDSXXXUrquhart Station, South CarolinaElectric & Gas Company(SGE&E) (SC)Pond/Impoundment,LandfillArsenic, NickelXVenice Power Station Ash Ponds,Union Electric Company/AmerenEnergy/AmerenUE (IL)Pond/ImpoundmentArsenic, Boron, Cadmium, Iron,Manganese, TDSXXXVermillion Power Station,Illinois Power (IL)Pond/ImpoundmentSulfate, TDS, Boron, Iron,Manganese, ChlorideW.C. Beckjord Station, DukeEnergy (formerly Cinergy) (OH)Pond/ImpoundmentSelenium, SulfateXW.J. Neal Station SurfaceImpoundment, Basin ElectricPower Cooperative (ND)Pond/ImpoundmentSelenium, Arsenic, Chromium,Cadmium, Lead, Zinc, AluminumXXXWateree Station, SCE&G (SC)Pond/Impoundment,LandfillArsenic, Chromium, Cadmium,Lead, IronXXXA-23Appendix A— Literature Review Methodology and ResultsTable A-4. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededMCLbExceeded Federal/State WQC/StandardsbGround WaterImpacted SurfaceWaterscImpactedOff-SiteSourcedWaukegan Generating StationAsh Ponds, Midwest Generation(Edison International) (IL)Pond/Impoundment,LandfillArsenic, Antimony, Boron,Manganese, Sulfate, TDS, IronXXWeber Ash Disposal Site, AESCreative Resources (NY)Pond/Impoundment,LandfillSulfate, TDS, Manganese, Iron,Aluminum, pHXWestland Disposal Site,Dickerson Generating Station,Mirant (MD)Pond/Impoundment,LandfillSelenium, Arsenic, Barium,Chromium, Cobalt, Copper, Iron,Zinc, Sulfate, Chlorine, Hardness,TDS, AluminumXXXWidows Creek Fossil Plant,Tennessee Valley Authority(TVA) (AL)Pond/ImpoundmentLead, Cobalt, Boron, Iron,Manganese, Aluminum, SulfateXWinyah Generating Station,Santee Cooper/South CarolinaPublic Service Authority(SCPSA) (SC)Pond/ImpoundmentArsenic, Chromium, Sulfate, Iron,ChlorideXXWood River Power Station,Illinois Power Company (IL)Pond/ImpoundmentSulfate, TDS, Chloride,Manganese, Iron, BoronYorktown Power Station,Chisman Creek Disposal Site,Virginia Electric Power andPower Company (VEPCO) (VA)Pond/Impoundment,LandfillSulfate, Nickel, Vanadium,SeleniumXSources: 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 DissolvedSolids); 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 managementunit.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 withone or more of the pollutants listed.d – An “X” indicates that the ground water contaminated a source outside theplant property boundaries.A-24Appendix A— Literature Review Methodology and ResultsTable A-5. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant LandfillsDamage Case SiteType ofWaste inLandfillaPollutants of ConcernExceededMCLbExceededFederal/ StateWQC/StandardsbGround WaterImpactedSurface WaterscImpactedOff-SiteSourcedA.B. Brown Generating Station,Southern Indiana Gas and ElectricCompany (SIGECO) (IN)FGDArsenic, Sodium, Boron, Sulfate, TDS,Chloride, pHXAlma On-site Fly Ash Landfill,Dairyland Power (WI)Fly AshSulfate, ManganeseBailly Generating Station, NorthernIndiana Public Service Company(NIPSCO) (IN)AshArsenic, CadmiumXBangor Quarry Ash Disposal Site,Portland Generating Station, RRIEnergy (PA)Bottom Ash,Fly Ash,OtherSelenium, Boron, Cadmium, HexavalentChromium, Iron, Manganese, Sulfate,TDS, Aluminum, FluorideXXBattlefield Golf Club, ChesapeakeEnergy Facility, Dominion Power(VA)Fly AshArsenic, Cadmium, Chromium, Copper,Lead, Manganese, Thallium, Zinc,Vanadium, Iron, Boron, AluminumXBBSS Sand and Gravel Quarries,Constellation Energy (MD)Fly Ash,Bottom AshArsenic, Selenium, Aluminum, Cadmium,Thallium, Manganese, Sulfate, Beryllium,Lead, NickelXXBelews Creek Steam Station, DukeEnergy (NC)Fly Ash,FGDSelenium, Arsenic, Boron, Cadmium,Iron, Lead, Manganese, Nitrate, Sulfate,pH, BromideXXXXBig Bend Station, Tampa ElectricCompany (FL)Bottom Ash,Fly Ash,FGD, OtherArsenic, Aluminum, Boron, Chloride,Fluoride, Iron, Manganese, Molybdenum,Sulfate, Sodium, Thallium, TDSXXXBrandywine Coal Ash Landfill,Mirant Mid-Atlantic LLC (MD)Bottom Ash,Fly AshSelenium, Cadmium, Lead, Manganese,Iron, Aluminum, Sulfate, TDS, ChlorideXXXC.D. McIntosh, Jr. Power Plant, Cityof Lakeland (FL)Ash, FGDSelenium, Arsenic, Cadmium, Lead,Manganese, Vanadium, Nitrate, Iron,Sulfate, TDS, pHXA-25Appendix A— Literature Review Methodology and ResultsTable A-5. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant LandfillsDamage Case SiteType ofWaste inLandfillaPollutants of ConcernExceededMCLbExceededFederal/ StateWQC/StandardsbGround WaterImpactedSurface WaterscImpactedOff-SiteSourcedC.R. Huntley Flyash Landfill (NY)Bottom Ash,Fly Ash,OtherArsenic, Iron, Manganese, Sulfate, TDS,Cadmium, Barium, Lead, TSSXXCardinal Fly Ash Reservoir (FAR) 1and 2, American Electric Power(AEP) (OH)Bottom Ash,Fly Ash,FGDArsenic, Boron, MolybdenumXXCayuga Coal Ash Disposal Landfill,AES (NY)Bottom Ash,Fly Ash,OtherSelenium, Arsenic, Boron, Cadmium,Lead, TDS, Aluminum, Manganese,Sulfate, Barium, Sodium, Iron,Chromium, ZincXXXXCCW Landfill, Trans-Ash,Inc. (TN)Bottom Ash,Fly AshMercury, Iron, Boron, Sulfate, Arsenic,Chromium, LeadXXCedar-Sauk Landfill, WisconsinElectric Power Company (WEPCO)(WI)Fly Ash,Bottom AshSelenium, Sulfate, BoronXClifty Creek Station, IndianaKentucky Electric Company (IKEC)(IN)Fly Ash,OtherBoron, Manganese, Iron, Sulfate,MagnesiumXCoal Ash Pit #3, Sheldon Station,Nebraska Public Power District (NE)Fly AshSelenium, SulfateXXCoal Combustion Waste Landfill,Merom Generating Station, HoosierEnergy (IN)Fly Ash,Bottom AshBarium, Chromium, Cadmium, Lead,Sulfate, Chloride, SodiumXColbert Fossil Plant, TennesseeBottom Ash,Cadmium, Antimony, Arsenic, Lead,XValley Authority (TVA) (AL)Fly Ash,OtherNitrate, Aluminum, Iron, Manganese,Boron, Molybdenum, Cobalt, Lithium,Sulfate, ChromiumColstrip Power Plant, PPL Montana(MT)Bottom Ash,Fly Ash,FGDSelenium, Boron, Sulfate, TDS,Molybdenum, Arsenic, ChlorideXXA-26Appendix A— Literature Review Methodology and ResultsTable A-5. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant LandfillsDamage Case SiteType ofWaste inLandfillaPollutants of ConcernExceededMCLbExceededFederal/ StateWQC/StandardsbGround WaterImpactedSurface WaterscImpactedOff-SiteSourcedConesville Fixed FGD SludgeLandfill, American Electric Power(AEP) (OH)Fly Ash,FGDArsenic, Cadmium, Chromium, Calcium,Magnesium, TDS, Sulfate, Iron, SeleniumXCrist Plant Ash Landfill, Gulf Power(Southern Company) (FL)Fly ash,Bottom Ash,FGDArsenic, Cadmium, Manganese,Chromium, Sodium, Sulfate, Aluminum,Chlorine, Iron, pH, TDSXCross Generating Station, SanteeCooper/South Carolina PublicService Authority (SCPSA) (SC)Bottom Ash,FGDArsenic, Cadmium, Chromium, Sodium,Sulfate, Iron, Aluminum, Chloride, TDSXCumberland Steam Plant, TennesseeValley Authority (TVA) (TN)Bottom Ash,Fly Ash,FGDSelenium, Arsenic, Aluminum, Boron,Chloride, Iron, Manganese, Sulfate, TDS,VanadiumXXCurtis Stanton Energy Center,Orlando Utility Commission (FL)Bottom Ash,OtherAluminum, Chloride, Iron, Manganese,Sodium, Sulfate, TDS, Vanadium, pHXDallman Station Ash and FGDPonds, City Water, Light and Power(IL)Ash, FGDArsenic, Chromium, Sodium, Boron,Manganese, Iron, Sulfate, TDSXDan River Steam Station, DukeEnergy (NC)Bottom Ash,Fly Ash,OtherChromium, Iron, Lead, Manganese,Silver, Sulfate, Arsenic, Antimony,Boron, TDS, pHXXDanskammer Waste ManagementFacility, Central Hudson Gas andElectric Corporation (NY)AshSulfate, Sulfide, TDS, Turbidity, Iron,Magnesium, Manganese, Sodium, Boron,pHDave Johnston Power Plant (WY)Fly AshCadmium, Manganese, Sulfate, BoronXDolet Hills Power Station, CentralLouisiana Electric Co-Op (CLECO)Power, LLC (LA)Bottom Ash,Fly Ash,FGD, OtherSelenium, Arsenic, Lead, Chloride, TDS,Sulfate, Iron, pHXEast Bend Scrubber Sludge Landfill,Cinergy (KY)FGDTDS, Iron, Sulfate, Manganese, ChlorideA-27Appendix A— Literature Review Methodology and ResultsTable A-5. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant LandfillsDamage Case SiteType ofWaste inLandfillaPollutants of ConcernExceededMCLbExceededFederal/ StateWQC/StandardsbGround WaterImpactedSurface WaterscImpactedOff-SiteSourcedEdgewater 1-4 Ash Disposal Site,Alliant (formerly Wisconsin Power &Light) (WI)AshBoron, Sulfate, Iron, Chloride, TDS,Arsenic, SeleniumXXFair Station Ash Landfill, CentralIowa Power Cooperative (IA)AshSelenium, Manganese, Sulfate, IronXFayette Power Project (SamSeymour), Lower Colorado RiverAuthority (TX)Bottom Ash,Fly Ash,FGD, OtherSelenium, Aluminum, Chloride, Cobalt,Manganese, Molybdenum, Sulfate, TDS,VanadiumXFern Valley Landfill, Orion PowerHoldings, Inc. (a subsidiary of RRIEnergy) (PA)Fly AshSelenium, Aluminum, Boron, Chloride,Sulfate, TDSXXXXFlint Creek Power Plant, AmericanElectric Power (AEP)/South WestElectric Power Company (SWEPCO)(AR)Bottom Ash,Fly Ash,OtherSelenium, Barium, Cadmium, Chromium,Iron, Lead, Manganese, pH, Silver,Sulfate, TDSXXFly Ash Landfill, Coffeen/White &Brewer Trucking (IL)Fly Ash,FGD, BottomAshSulfate, TDS, Manganese, Cadmium,Chromium, Thallium, Beryllium, Boron,Nickel, Barium, Iron, Zinc, Aluminum,SodiumXFly Ash Landfill, Don FrameTrucking, Inc. (NY)Bottom Ash,Fly Ash,OtherLead, Sulfate, TDS, Manganese, IronXGeneral James M. Gavin PowerPlant, American Electric Power/OhioPower Company (OH)Bottom Ash,Fly Ash,FGD, OtherArsenic, Barium, Cadmium, Lead,Molybdenum, Sulfate, TDS, Aluminum,Copper, Nickel, Zinc, Manganese,ChlorideXXXGeorge Neal Station North Landfill,Berkshire Hathaway/MidAmericanEnergy Company (IA)Fly AshIron, Manganese, Sulfate, ArsenicXXA-28Appendix A— Literature Review Methodology and ResultsTable A-5. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant LandfillsDamage Case SiteType ofWaste inLandfillaPollutants of ConcernExceededMCLbExceededFederal/ StateWQC/StandardsbGround WaterImpactedSurface WaterscImpactedOff-SiteSourcedGeorge Neal Station South AshMonofill, BerkshireHathaway/MidAmerican EnergyCompany (IA)Bottom Ash,Fly AshSelenium, Arsenic, Barium, Zinc, Iron,Manganese, SulfateXGibson Generating Station, DukeEnergy (IN)Bottom Ash,Fly AshSelenium, Arsenic, Boron, Manganese,Iron, SodiumXXXHatfield's Ferry Power Station,Allegheny Energy (PA)Bottom Ash,Fly Ash,FGDArsenic, Aluminum, Boron, Chromium,Manganese, Molybdenum, Thallium,TDS, Sulfate, SeleniumXXXHennepin Power Station, IllinoisPower Company (IL)Fly AshSulfate, TDS, Boron, Iron, ManganeseXHighway 59 Landfill, WisconsinElectric Power Company (WEPCO)(WI)Bottom Ash,Fly AshSelenium, Sulfate, Boron, Manganese,Chloride, Iron, Arsenic, Molybdenum,TDSXXIndependence Steam Station,Entergy/Arkansas Power and Light(AR)Bottom Ash,Fly Ash,OtherCadmium, Iron, Lead, Manganese, pH,Sulfate, TDS, Arsenic, ChlorineXXIndian River Generating Station,NRG Energy (DE)AshSelenium, Mercury, Arsenic, Aluminum,Barium, Cadmium, Chromium, Copper,Lead, Nickel, Thallium, Zinc, Iron,ManganeseXXXJohn Warden Ash Site (MI)Ash, OtherBoron, LithiumJohnsonville Fossil Plant, TennesseeValley Authority (TVA) (TN)Bottom Ash,Fly AshArsenic, Aluminum, Boron, Cadmium,Chromium, TDS, Iron, Lead, Manganese,Molybdenum, Sulfate, CobaltXXXXK.R. Rezendes South Main StreetAsh Landfill, Salem Harbor andBrayton Point Plants, Pacific Gas andElectric (PG&E) (MA)AshSelenium, Arsenic (?)XA-29Appendix A— Literature Review Methodology and ResultsTable A-5. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant LandfillsDamage Case SiteType ofWaste inLandfillaPollutants of ConcernExceededMCLbExceededFederal/ StateWQC/StandardsbGround WaterImpactedSurface WaterscImpactedOff-SiteSourcedKarn/Weadock Generating Facility,Consumer Energy (MI)Ash, FlyAsh, BottomAshArsenic, Boron, Lithium,XXLincoln Stone Quarry Landfill, JolietGenerating Station 9, MidwestGeneration (IL)AshArsenic, Ammonia, Boron, Molybdenum,pH, Sulfate, TDS, Barium, Copper,Selenium, CadmiumXXMahoney Landfill, Powerton Plant,Commonwealth Edison (IL)Bottom Ash,Fly Ash,OtherArsenic, Selenium, Chromium, TDS,Cadmium, Lead, Nitrate, Iron,Manganese, Sulfate, Boron,XMarion Plant, Southern IllinoisPower Cooperative (IL)Bottom Ash,Fly Ash,FGDBoron, Cadmium, Iron, Aluminum, TDS,SulfateXXXXMcMeekin Station, SCANA/SouthCarolina Electric & Gas Company(SCE&G) (SC)AshChromium, Lead, Sulfate, Iron, TDSXMiamiview Landfill, Cincinnati Gas& Electric Company (OH)FGDSulfate, ManganeseMill Creek Plant, E ONU.S./Louisville Gas & Electric(LG&E) (KY)Bottom Ash,Fly Ash,FGD, OtherArsenic, Chloride, Sulfate, TDSXMitchell Power Station, AlleghenyEnergy (PA)Bottom Ash,Fly AshArsenic, Boron, Iron, Molybdenum,Manganese, NickelXXMorgantown Generating Station,Faulkner Off-site Disposal Facility(MD)Bottom Ash,Fly Ash,OtherIron, pH, Cadmium, Aluminum, Chloride,Manganese, Sulfate, TDS, Copper, Lead,SeleniumXXXXMuscatine County Landfill (IA)AshSelenium, SulfateXMuskegon County Type III Landfill(MI)Fly AshBoron, ManganeseXNorth Lansing Landfill, LansingBoard of Water & Light (MI)Ash, OtherSelenium, Boron, Lithium, Manganese,Sulfate, LeadXA-30Appendix A— Literature Review Methodology and ResultsTable A-5. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant LandfillsDamage Case SiteType ofWaste inLandfillaPollutants of ConcernExceededMCLbExceededFederal/ StateWQC/StandardsbGround WaterImpactedSurface WaterscImpactedOff-SiteSourcedNortheastern Station Ash Landfill,American Electric Power/PublicService CompanyOklahoma (OK)Bottom Ash,Fly AshSelenium, Arsenic, Barium, Chromium,Lead, Vanadium, Thallium, Sulfate, pHXXXParish Generating Station, NRGEnergy/Texas Genco II (TX)Fly Ash,Bottom Ash,FGD(EmergencyOnly)Arsenic, Selenium, Barium, Boron,Chromium, Cobalt, Manganese,Molybdenum, SulfateXPetersburg Generating Station,Indianapolis Power & Light (IN)Not SpecifiedSulfate, TDSXPhillips Power Plant Landfill,Duquesne Light Company (PA)Ash, FGDTDS, Chloride, Fluoride, Manganese,Aluminum, ArsenicXXXXPine Hill Landfill, Marquette Boardof Light & Power (MI)Fly AshBoron, Lithium, SodiumXPort Washington Facility, WisconsinElectric Power Company (WEPCO)(WI)Bottom Ash,Fly AshSelenium, Boron, SulfateXPrairie Creek Generating Station AshLandfill, Interstate Power and Light(Alliant) (IA)AshArsenic, Boron, Manganese, Sulfate, IronXXPresque Isle Power Plant, WEEnergies (WE) (MI)Bottom Ash,Fly AshBoron, Molybdenum, Selenium, Sodium,Sulfate, LithiumXPulliam Ash Disposal Site,Wisconsin Power Supply Company(WPSC) (WI)Bottom Ash,Fly AshSulfate, Manganese,Iron, Boron, Zinc,Aluminum, Chlorine, TDS, pHR.M. Heskett Station, MontanaDakota Utilities (ND)AshSulfate, Boron, Cadmium, Selenium,NitrateXR.M. Schahfer Generating Station(IN)Ash, FGDSulfate, Iron, Manganese, Molybdenum,Chlorine, Sodium, BoronA-31Appendix A— Literature Review Methodology and ResultsTable A-5. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant LandfillsDamage Case SiteType ofWaste inLandfillaPollutants of ConcernExceededMCLbExceededFederal/ StateWQC/StandardsbGround WaterImpactedSurface WaterscImpactedOff-SiteSourcedRange Road Landfill, Detroit Edison(MI)AshBoron, Lithium, ManganeseXXReid Gardner Generating Facility,Nevada Energy (NV)Fly Ash,FGDSelenium, Arsenic, Chloride, Sulfate,TDS, Nitrate, Boron, Chromium,Manganese, Magnesium, Molybdenum,Sodium, Vanadium, Titanium, Barium,Iron, AluminumXXXXRodemacher Power Station, CentralLouisiana Electric Co-Op (CLECO)Power, LLC (LA)Bottom Ash,Fly Ash,OtherArsenic, Lead, pH, TDS, Chloride, SulfateXSeminole Generating Station,Seminole Electric Cooperative (FL)Fly Ash,FGD, OtherArsenic, Chloride, Chlorine, Sulfate, Iron,TDS, Boron, Aluminum, Lead, SodiumXXXSeward Generating Station, RRIEnergy (PA)Ash, OtherSelenium, Arsenic, Aluminum, Antimony,Cadmium, Chloride, Chromium, Iron,Lead, Manganese, Nickel, pH, Sulfate,TDS, Zinc,XXXShawnee Fossil Plant, TennesseeValley Authority (TVA) (KY)Bottom Ash,Fly AshSelenium, Arsenic, Boron, pH, Sulfate,TDS, Beryllium, Cobalt, Nickel,Molybdenum, Manganese, VanadiumXXXSherburne County (Sherco)Bottom Ash,Arsenic, Cadmium, Lead, Sulfate,XGenerating Plant, XcelFly Ash,Selenium, BoronEnergy/Southern MinnesotaFGDMunicipal Power Agency (MN)Spurlock Station, Eastern KentuckyPower Cooperative (KY)Bottom Ash,Fly Ash,FGDArsenic, Sulfate, TDSXXSwift Creek Structural Fill, ReUseTechnology, Inc./ Full CircleSolutions (NC)Fly AshArsenic, Lead, SulfateXXXA-32Appendix A— Literature Review Methodology and ResultsTable A-5. Summary of Ground Water Impacts Reported inDamage Cases from Steam Electric Power Plant LandfillsDamage Case SiteType ofWaste inLandfillaPollutants of ConcernExceededMCLbExceededFederal/ StateWQC/StandardsbGround WaterImpactedSurface WaterscImpactedOff-SiteSourcedUrquhart Station, South CarolinaElectric & Gas Company (SGE&E)(SC)Fly Ash,Bottom Ash,OtherArsenic, NickelXWateree Station, SCE&G (SC)Bottom Ash,Fly Ash,FGDArsenic, Chromium, Cadmium, Lead, IronXXXWaukegan Generating Station AshPonds, Midwest Generation (EdisonInternational) (IL)AshArsenic, Antimony, Boron, Manganese,Sulfate, TDS, IronXXWeber Ash Disposal Site, AESCreative Resources (NY)AshSulfate, TDS, Manganese, Iron,Aluminum, pHXWestland Disposal Site, DickersonGenerating Station, Mirant (MD)Fly AshSelenium, Arsenic, Barium, Chromium,Cobalt, Copper, Iron, Zinc, Sulfate,Chlorine, Hardness, TDS, AluminumXXXYard 520 Landfill Site (Brown'sLandfill),NorthernIndiana PublicService Company (NIPSCO) (IN)Fly Ash,OtherArsenic, Manganese, Boron,Molybdenum, Lead, Selenium, Iron,Sulfate, AmmoniumXXYorktown Power Station, ChismanCreek Disposal Site, Virginia ElectricPower and Power Company(VEPCO) (VA)Fly AshSulfate, Nickel, Vanadium, SeleniumXSources: 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 DissolvedSolids); 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 managementunit.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 withone or more of the pollutants listed.d – An “X” indicates that the ground water contaminated a source outside the plant property boundaries.A-33Appendix A— Literature Review Methodology and ResultsTable A-6. Summary of Surface Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededFederal/StateWQC/StandardsbIssued a FishConsumptionAdvisorycImpact Resultedfrom Ground WaterContaminationdImpactedOff-SiteSourceeAsheville Steam ElectricPlant, Progress Energy(NC)Pond/ImpoundmentBoron, Chromium, Iron,Manganese, Thallium, Nitrate,Sulfate, pH, TDS, Cadmium,Arsenic, AntimonyXXBangor Quarry AshDisposal Site, PortlandGenerating Station, RRIEnergy (PA)Pond/Impoundment,LandfillSelenium, Boron, Cadmium,Hexavalent Chromium, Iron,Manganese, Sulfate, TDS,Aluminum, FluorideXBelews Creek SteamStation, Duke Energy(NC)Pond/Impoundment,LandfillSelenium, Arsenic, Boron,Cadmium, Iron, Lead, Manganese,Nitrate, Sulfate, pH, BromideXXXBig Bend Station, TampaPond/Impoundment,Arsenic, Aluminum, Boron,XXElectric Company (FL)LandfillChloride, Fluoride, Iron,Manganese, Molybdenum, Sulfate,Sodium, Thallium, TDSBrandywine Coal AshLandfill, Mirant MidAtlantic LLC (MD)Pond/Impoundment,LandfillSelenium, Cadmium, Lead,Manganese, Iron, Aluminum,Sulfate, TDS, ChlorideXXBull Run Steam Plant,Pond/ImpoundmentAluminum, Cadmium, Iron, Sulfate,Tennessee ValleyArsenic, Cobalt, Calcium,Authority (TVA) (TN)Manganese, Molybdenum, Boron,NickelCardinal Fly AshReservoir (FAR) 1 and 2,American Electric Power(AEP) (OH)Pond/Impoundment,LandfillArsenic, Boron, MolybdenumXCayuga Coal AshDisposal Landfill, AES(NY)Pond/Impoundment,LandfillSelenium, Arsenic, Boron,Cadmium, Lead, TDS, Aluminum,Manganese, Sulfate, Barium,Sodium, Iron, Chromium, ZincXXXA-34Appendix A— Literature Review Methodology and ResultsTable A-6. Summary of Surface Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededFederal/StateWQC/StandardsbIssued a FishConsumptionAdvisorycImpact Resultedfrom Ground WaterContaminationdImpactedOff-SiteSourceeClinch River Plant,American Electric Power(AEP)/AppalachianPower (VA)Pond/ImpoundmentAluminum, pH, CopperXXColumbia Energy Center,Alliant Energy (WI)Pond/Impoundment,LandfillCadmium, Copper, Barium,Aluminum, Iron, Zinc, Arsenic,Selenium, Lead, ManganeseXXCumberland Steam Plant,Tennessee ValleyAuthority (TVA) (TN)Pond/Impoundment,LandfillSelenium, Arsenic, Aluminum,Boron, Chloride, Iron, Manganese,Sulfate, TDS, VanadiumXCurtis Stanton EnergyCenter, Orlando UtilityCommission (FL)Pond/Impoundment,LandfillAluminum, Chloride, Iron,Manganese, Sodium, Sulfate, TDS,Vanadium, pHXDan River Steam Station,Duke Energy (NC)Pond/ImpoundmentArsenic, Copper, Iron, AluminumXXDave Johnston PowerPlant (WY)Pond/Impoundment,LandfillCadmium, Manganese, Sulfate,BoronFlint Creek Power Plant,American Electric Power(AEP)/South WestElectric Power Company(SWEPCO) (AR)Pond/Impoundment,LandfillSelenium, Barium, Cadmium,Chromium, Iron, Lead, Manganese,pH, Silver, Sulfate, TDSXGeneral James M. GavinPond/Impoundment,Arsenic, Barium, Cadmium, Lead,XXPower Plant, AmericanLandfillMolybdenum, Sulfate, TDS,Electric Power/OhioAluminum, Copper, Nickel, Zinc,Power Company (OH)Manganese, ChlorideGibson GeneratingStation, Duke Energy(IN)Pond/Impoundment,Landfill, CoolingReservoirSelenium, Arsenic, Boron,Manganese, Iron, SodiumXXA-35Appendix A— Literature Review Methodology and ResultsTable A-6. Summary of Surface Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededFederal/StateWQC/StandardsbIssued a FishConsumptionAdvisorycImpact Resultedfrom Ground WaterContaminationdImpactedOff-SiteSourceeGlen Lyn Plant,American Electric Power(AEP)/AppalachianPower (VA)Pond/ImpoundmentSelenium, Cadmium, Copper,Chromium, Zinc, pH, NickelXXGrainger GeneratingStation, SanteeCooper/South CarolinaPublic Service Authority(SCPSA) (SC)Pond/ImpoundmentArsenic, pHJ.H. Campbell,Pond/ImpoundmentpH, Antimony, Boron, Cadmium,XConsumers Energy (MI)Chromium, Iron, Lead, Selenium,Vanadium, Aluminum, Nickel,Thallium, Manganese, ZincJ.R. Whiting GeneratingPlant, CMS/ConsumersEnergy (MI)Pond/ImpoundmentSelenium, Arsenic, Cobalt, Nickel,Bromine, ChromiumJohn Sevier Fossil Plant,Pond/ImpoundmentArsenic, Aluminum, Cadmium,XXXTennessee ValleyManganese, Boron, Strontium,Authority (TVA) (TN)Sulfate, Selenium, HexavalentChromiumJohnsonville Fossil Plant,Pond/Impoundment,Arsenic, Aluminum, Boron,XXXTennessee ValleyLandfillCadmium, Chromium, TDS, Iron,Authority (TVA) (TN)Lead, Manganese, Molybdenum,Sulfate, CobaltKingston Fossil Plant,Tennessee ValleyAuthority (TVA) (TN)Pond/ImpoundmentArsenic, Selenium, Manganese,Cobalt, Aluminum, Ammonia,Thallium, IronXXXA-36Appendix A— Literature Review Methodology and ResultsTable A-6. Summary of Surface Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededFederal/StateWQC/StandardsbIssued a FishConsumptionAdvisorycImpact Resultedfrom Ground WaterContaminationdImpactedOff-SiteSourceeLittle Blue Run SurfacePond/ImpoundmentSelenium, Arsenic, Aluminum,XXImpoundment, BruceAntimony, Barium, Boron,Mansfield Power Plant,Cadmium, Calcium, Chloride,First Energy (PA)Hexavalent Chromium, Fluoride,Iron, Lead, Manganese, pH,Sodium, Sulfate, TDS, TSS,Thallium, TurbidityLittle Scary Creek FlyAsh Impoundment, JohnAmos Plant, AmericanElectric Power(AEP)/AppalachianPower (WV)Pond/ImpoundmentSelenium, Mercury, Arsenic,CopperXMahoney Landfill,Powerton Plant,Commonwealth Edison(IL)Pond/Impoundment,LandfillArsenic, Selenium, Chromium,TDS, Cadmium, Lead, Nitrate, Iron,Manganese, Sulfate, Boron,Marion Plant, SouthernIllinois PowerCooperative (IL)Pond/Impoundment,LandfillBoron, Cadmium, Iron, Aluminum,TDS, SulfateXXXMartin's Creek PowerPlant, PPL (PA)Pond/ImpoundmentArsenic, Selenium, Lead,Aluminum, Copper, Chromium,IronXXMontville GeneratingStation, NRGEnergy/Montville Power,LLC (CT)Pond/ImpoundmentArsenic, Beryllium, Cadmium,Copper, Iron, Lead, Manganese,Nickel, pH, ZincXXMorgantown GeneratingStation, Faulkner Off-siteDisposal Facility (MD)Pond/Impoundment,LandfillIron, pH, Cadmium, Aluminum,Chloride, Manganese, Sulfate, TDS,Copper, Lead, SeleniumXXXA-37Appendix A— Literature Review Methodology and ResultsTable A-6. Summary of Surface Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededFederal/StateWQC/StandardsbIssued a FishConsumptionAdvisorycImpact Resultedfrom Ground WaterContaminationdImpactedOff-SiteSourceeOak Ridge Y-12 Plant,Chestnut Ridge OperableUnit 2, Oak RidgeReservation, Departmentof Energy (TN)Pond/ImpoundmentSelenium, Arsenic, Aluminum, Iron,Zinc, Manganese, Thallium (?)XPhillips Power PlantLandfill, Duquesne LightCompany (PA)Pond/Impoundment,LandfillTDS, Chloride, Fluoride,Manganese, Aluminum, ArsenicXXXPlant Bowen, GeorgiaPower (GA)Pond/ImpoundmentArsenic, Cadmium, Chromium,Lead, Mercury, Nickel, CopperXXReid Gardner GeneratingFacility, Nevada Energy(NV)Pond/Impoundment,LandfillSelenium, Arsenic, Chloride,Sulfate, TDS, Nitrate, Boron,Chromium, Manganese,Magnesium, Molybdenum, Sodium,Vanadium, Titanium, Barium, Iron,AluminumXXXSavannah River Site, DArea, Department ofEnergy (SC)Pond/ImpoundmentCadmium, Chromium, Copper,Mercury, Selenium, Zinc, Iron,AluminumXSeminole GeneratingStation, SeminoleElectric Cooperative (FL)Pond/Impoundment,LandfillArsenic, Chloride, Chlorine, Sulfate,Iron, TDS, Boron, Aluminum, Lead,SodiumXXSeward GeneratingPond/Impoundment,Selenium, Arsenic, Aluminum,XXStation, RRI Energy (PA)LandfillAntimony, Cadmium, Chloride,Chromium, Iron, Lead, Manganese,Nickel, pH, Sulfate, TDS, Zinc,Shawnee Fossil Plant,Pond/Impoundment,Selenium, Arsenic, Boron, pH,XXTennessee ValleyLandfillSulfate, TDS, Beryllium, Cobalt,Authority (TVA) (KY)Nickel, Molybdenum, Manganese,VanadiumA-38Appendix A— Literature Review Methodology and ResultsTable A-6. Summary of Surface Water Impacts Reported inDamage Cases from Steam Electric Power Plant SurfaceImpoundmentsDamage Case SiteType of Waste inImpoundmentaPollutants of ConcernExceededFederal/StateWQC/StandardsbIssued a FishConsumptionAdvisorycImpact Resultedfrom Ground WaterContaminationdImpactedOff-SiteSourceeSutton Steam Plant,Progress Energy (NC)Pond/ImpoundmentArsenic, Boron, Manganese, Iron,Thallium, Selenium, Antimony,Lead, Sulfate, TDSXXW.J. Neal Station SurfaceImpoundment, BasinElectric PowerCooperative (ND)Pond/ImpoundmentSelenium, Arsenic, Chromium,Cadmium, Lead, Zinc, AluminumXXWateree Station, SCE&G(SC)Pond/Impoundment,LandfillArsenic, Chromium, Cadmium,Lead, IronXXWestland Disposal Site,Dickerson GeneratingStation, Mirant (MD)Pond/Impoundment,LandfillSelenium, Arsenic, Barium,Chromium, Cobalt, Copper, Iron,Zinc, Sulfate, Chlorine, Hardness,TDS, AluminumXXSources: 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 Hydrocarbons); TSS (TotalSuspended 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 managementunit.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 withone or more of the pollutants listed.e – An “X” indicates that the surface water contaminated a source outside the plant property boundaries.A-39Appendix A— Literature Review Methodology and ResultsTable A-7. Summary of Surface Water Impacts Reported in Damage Cases from Steam Electric Power Plant LandfillsDamage Case SiteType ofWaste inLandfillaPollutants of ConcernExceededFederal/ StateWQC/StandardsbIssued a FishConsumptionAdvisorycImpact Resultedfrom GroundWaterContaminationdImpactedOff-SiteSourceeBangor Quarry Ash DisposalSite, Portland GeneratingStation, RRI Energy (PA)Bottom Ash,Fly Ash, OtherSelenium, Boron, Cadmium, HexavalentChromium, Iron, Manganese, Sulfate,TDS, Aluminum, FluorideXBattlefield Golf Club,Chesapeake Energy Facility,Dominion Power (VA)Fly AshArsenic, Cadmium, Chromium, Copper,Lead, Manganese, Thallium, Zinc,Vanadium, Iron, Boron, AluminumBelews Creek Steam Station,Duke Energy (NC)Fly Ash, FGDSelenium, Arsenic, Boron, Cadmium,Iron, Lead, Manganese, Nitrate, Sulfate,pH, BromideXXXBig Bend Station, TampaElectric Company (FL)Bottom Ash,Fly Ash, FGD,OtherArsenic, Aluminum, Boron, Chloride,Fluoride, Iron, Manganese, Molybdenum,Sulfate, Sodium, Thallium, TDSXXBrandywine Coal AshLandfill, Mirant MidAtlantic LLC (MD)Bottom Ash,Fly AshSelenium, Cadmium, Lead, Manganese,Iron, Aluminum, Sulfate, TDS, ChlorideXXCardinal Fly Ash Reservoir(FAR) 1 and 2, AmericanElectric Power (AEP) (OH)Bottom Ash,Fly Ash, FGDArsenic, Boron, MolybdenumXCayuga Coal Ash DisposalBottom Ash,Selenium, Arsenic, Boron, Cadmium,XXXLandfill, AES (NY)Fly Ash, OtherLead, TDS, Aluminum, Manganese,Sulfate, Barium, Sodium, Iron,Chromium, ZincCCW Landfill, Trans-Ash,Inc. (TN)Bottom Ash,Fly AshMercury, Iron, Boron, Sulfate, Arsenic,Chromium, LeadXCoal Combustion WasteLandfill, Merom GeneratingStation, Hoosier Energy (IN)Fly Ash,Bottom AshBarium, Chromium, Cadmium, Lead,Sulfate, Chloride, SodiumColumbia Energy Center,Alliant Energy (WI)Bottom Ash,Fly AshCadmium, Copper, Barium, Aluminum,Iron, Zinc, Arsenic, Selenium, Lead,ManganeseXXA-40Appendix A— Literature Review Methodology and ResultsTable A-7. Summary of Surface Water Impacts Reported in Damage Cases from Steam Electric Power Plant LandfillsDamage Case SiteType ofWaste inLandfillaPollutants of ConcernExceededFederal/ StateWQC/StandardsbIssued a FishConsumptionAdvisorycImpact Resultedfrom GroundWaterContaminationdImpactedOff-SiteSourceeCumberland Steam Plant,Tennessee Valley Authority(TVA) (TN)Bottom Ash,Fly Ash, FGDSelenium, Arsenic, Aluminum, Boron,Chloride, Iron, Manganese, Sulfate, TDS,VanadiumXCurtis Stanton EnergyCenter, Orlando UtilityCommission (FL)Bottom Ash,OtherAluminum, Chloride, Iron, Manganese,Sodium, Sulfate, TDS, Vanadium, pHXDave Johnston Power Plant(WY)Fly AshCadmium, Manganese, Sulfate, BoronFern Valley Landfill, OrionPower Holdings, Inc. (asubsidiary of RRI Energy)(PA)Fly AshSelenium, Aluminum, Boron, Chloride,Sulfate, TDSXXXFlint Creek Power Plant,American Electric Power(AEP)/South West ElectricPower Company (SWEPCO)(AR)Bottom Ash,Fly Ash, OtherSelenium, Barium, Cadmium, Chromium,Iron, Lead, Manganese, pH, Silver,Sulfate, TDSXGeneral James M. GavinPower Plant, AmericanElectric Power/Ohio PowerCompany (OH)Bottom Ash,Fly Ash, FGD,OtherArsenic, Barium, Cadmium, Lead,Molybdenum, Sulfate, TDS, Aluminum,Copper, Nickel, Zinc, Manganese,ChlorideXXGibson Generating Station,Duke Energy (IN)Bottom Ash,Fly AshSelenium, Arsenic, Boron, Manganese,Iron, SodiumXXHatfield's Ferry PowerStation, Allegheny Energy(PA)Bottom Ash,Fly Ash, FGDArsenic, Aluminum, Boron, Chromium,Manganese, Molybdenum, Thallium,TDS, Sulfate, SeleniumXXIndian River GeneratingAshSelenium, Mercury, Arsenic, Aluminum,XXStation, NRG Energy (DE)Barium, Cadmium, Chromium, Copper,Lead, Nickel, Thallium, Zinc, Iron,ManganeseA-41Appendix A— Literature Review Methodology and ResultsTable A-7. Summary of Surface Water Impacts Reported in Damage Cases from Steam Electric Power Plant LandfillsDamage Case SiteType ofWaste inLandfillaPollutants of ConcernExceededFederal/ StateWQC/StandardsbIssued a FishConsumptionAdvisorycImpact Resultedfrom GroundWaterContaminationdImpactedOff-SiteSourceeJohn Warden Ash Site (MI)Ash, OtherBoron, LithiumJohnsonville Fossil Plant,Tennessee Valley Authority(TVA) (TN)Bottom Ash,Fly AshArsenic, Aluminum, Boron, Cadmium,Chromium, TDS, Iron, Lead, Manganese,Molybdenum, Sulfate, CobaltXXXMahoney Landfill, PowertonPlant, CommonwealthEdison (IL)Bottom Ash,Fly Ash, OtherArsenic, Selenium, Chromium, TDS,Cadmium, Lead, Nitrate, Iron,Manganese, Sulfate, Boron,Marion Plant, SouthernIllinois Power Cooperative(IL)Bottom Ash,Fly Ash, FGDBoron, Cadmium, Iron, Aluminum, TDS,SulfateXXXMorgantown GeneratingStation, Faulkner Off-siteDisposal Facility (MD)Bottom Ash,Fly Ash, OtherIron, pH, Cadmium, Aluminum,Chloride, Manganese, Sulfate, TDS,Copper, Lead, SeleniumXXXOak Creek Power Plant,Wisconsin Energy (WEEnergies (WE))/WisconsinElectric Power Company(WI)Bottom Ash,Fly Ash, FGD,OtherArsenic, Chromium, TCE, Diesel FuelXXPhillips Power PlantLandfill, Duquesne LightCompany (PA)Ash, FGDTDS, Chloride, Fluoride, Manganese,Aluminum, ArsenicXXXRange Road Landfill, DetroitEdison (MI)AshBoron, Lithium, ManganeseXXReid Gardner GeneratingFacility, Nevada Energy(NV)Fly Ash, FGDSelenium, Arsenic, Chloride, Sulfate,TDS, Nitrate, Boron, Chromium,Manganese, Magnesium, Molybdenum,Sodium, Vanadium, Titanium, Barium,Iron, AluminumXXXA-42Appendix A— Literature Review Methodology and ResultsTable A-7. Summary of Surface Water Impacts Reported in Damage Cases from Steam Electric Power Plant LandfillsDamage Case SiteType ofWaste inLandfillaPollutants of ConcernExceededFederal/ StateWQC/StandardsbIssued a FishConsumptionAdvisorycImpact Resultedfrom GroundWaterContaminationdImpactedOff-SiteSourceeSeminole GeneratingStation, Seminole ElectricCooperative (FL)Fly Ash, FGD,OtherArsenic, Chloride, Chlorine, Sulfate, Iron,TDS, Boron, Aluminum, Lead, SodiumXXSeward Generating Station,RRI Energy (PA)Ash, OtherSelenium, Arsenic, Aluminum,Antimony, Cadmium, Chloride,Chromium, Iron, Lead, Manganese,Nickel, pH, Sulfate, TDS, Zinc,XXShawnee Fossil Plant,Tennessee Valley Authority(TVA) (KY)Bottom Ash,Fly AshSelenium, Arsenic, Boron, pH, Sulfate,TDS, Beryllium, Cobalt, Nickel,Molybdenum, Manganese, VanadiumXXWateree Station, SCE&GBottom Ash,Arsenic, Chromium, Cadmium, Lead,XX(SC)Fly Ash, FGDIronWestland Disposal Site,Dickerson GeneratingStation, Mirant (MD)Fly AshSelenium, Arsenic, Barium, Chromium,Cobalt, Copper, Iron, Zinc, Sulfate,Chlorine, Hardness, TDS, AluminumXXSources: 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 Hydrocarbons); TSS (TotalSuspended 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 managementunit.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 withone or more of the pollutants listed.e – An “X” indicates that the surface water contaminated a source outside theplant property boundaries.A-43Appendix A— Literature Review Methodology and ResultsTable A-8. Summary of Attractive NuisancesRelated to Steam Electric Power PlantsSpeciesAttractive NuisanceSite DescriptionPollutant Concentrationsin the Environment orDietPollutant Concentrationsin the Organism(μg/g)Observed EffectsStudy TypeCitationCommon Grackles(Quiscalus quiscala)Nested in closeproximity to a coal-firedpower plant’s fly ashpond.Not measured in studyEggs = 5.9 seleniumHistopathologicalFieldBryanet al.,2003Raccoons(Procyon lotor)Lived in close proximityto a coal-fired powerplant’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, 1.5mercuryHistopathologicalFieldBurgeret al.,2002Interior Least Tern(Sterna antillarum)Nested on a dike in acoal-fired power plant’sash pond.Not measured in studyNot observed in studyNot observed in studyFieldPruitt, 2000and DukeEnergy, 2007Southern Toads(Bufo terrestris)Inhabited an ashbasin and nearbyswamp.Reference (control)site organisms weretransferred tocontaminatedlocations.Not measured in studyNot measured in studyElevatedcorticosterone andtestosterone levelsOutdoormesocosmHopkinset al.,1997Southern Toads(Bufo terrestris)Inhabited an ash pondand nearby swamp.Reference siteorganisms weretransferred tocontaminatedlocations.Pond sediment = 39.64μg/g arsenic, 4.38 μg/gseleniumAdult males = 1.58 arsenic,17.40 seleniumHistopathologicalOutdoormesocosmHopkinset al.,1998A-44Appendix A— Literature Review Methodology and ResultsTable A-8. Summary of Attractive NuisancesRelated to Steam Electric Power PlantsSpeciesAttractive NuisanceSite DescriptionPollutant Concentrationsin the Environment orDietPollutant Concentrationsin the Organism(μg/g)Observed EffectsStudy TypeCitationLarval Bullfrogs(Rana catesbeiana)Inhabited bottom ashponds near a coal-firedpower plant.Pond sediment = 49.39μg/g arsenic, 0.72 μg/gcadmium, 23.85 μg/gchromium, 84.72 μg/gcopper, 6.11 μg/g selenium,106.39 μg/g strontium,45.83 μg/g vanadiumWhole body concentration= 33.10 arsenic, 5.47cadmium, 18.25 chromium,116.72 copper, 20.25selenium, 39.89 strontium,17.32 vanadiumMorphologicalDecreasedswimming speedsFieldHopkinset al.,2000Eastern NarrowMouth Toads(Gastrophrynecarolinensis)Inhabited a seleniumladen site located near acoal-fired power plant.Site water = 3.93 μg/LseleniumSoil = 38.25 μg/LseleniumLab water = 0.28 μg/LseleniumFemales = 42.40seleniumEggs = 43.96 seleniumReproductiveHistopathologicalOutdoormescosmHopkinset al.,2006Barn Swallow(Hirundo rustica)Nested near a seleniumladen pond associatedwith a coal-fired powerplant.Not provided in theliteratureEggs = 2.8 seleniumHistopathologicalFieldKinget al.,1994Slider Turtles(Trachemys scripta)Inhabited a seleniumladen basin thatreceives fly ashtransport water near acoal-fired powerplant.Eggs were incubatedin ash-contaminatedsoil.Ash-contaminated soil =2.56 μg/g seleniumAdult Females = 37.18(mean concentration),seleniumReproductiveOutdoormescosmNagleet al.,2001Canada Geese(Branta Canadensis)Inhabited pens near avanadium-laden ashpond associated with anoil-fired power plantSite water = 467,000 μg/LvanadiumLiver = 57.3 vanadiumKidney = 226 vanadiumLethalHistopathologicalOutdoormesocosmRattneret al.,2006Acronyms: μg/g (Micrograms per Grams); μg/L (Micrograms per Liters).A-45Appendix A— Literature Review Methodology and ResultsTable A-9. Summary of Attractive NuisancesUnrelated to Steam Electric Power PlantsSite Name, Location, andContamination SourceOrganism AffectedDocumented EffectsTrace Pollutant Concentrations(ppm)CitationKesterson Reservoir, CAAgricultural RunoffCalifornia Vole (Microtuscalifornicus)Mean selenium concentrations in liverswere significantly elevated.Liver = 119 seleniumClarket al., 1987Kesterson Reservoir, CAAgricultural RunoffAmerican Coot (Fulica americana),Mallard (Anas platyrhynchos)Mean selenium concentrations in birdeggs and livers were elevated;organisms exhibited severe reproductivefailure and deformities.Eggs = 2.2 – 110 seleniumLiver = 19 – 130 seleniumWater = 300,000 seleniumOhlendorfet al.,1986Kesterson Reservoir, CAAgricultural RunoffPied-Billed Grebes (Podilymbuspodiceps),Common Moorhen (Gallinulachloropus),Black-Necked Stilts (Himantopusmexicanus)Selenium concentrations in livers were10 times those found in nearby controlareas; organisms exhibited severelesions and embryonic deformities.Liver = 94.4 seleniumWater = 300,000 seleniumOhlendorfet al.,1988aKesterson Reservoir, CAAgricultural RunoffGopher Snakes (Pituophismelanoleucus), Bullfrogs (Ranacatesbeiana)Selenium concentrations in snake andfrog livers were significantly elevated.Snake liver = 11.1 seleniumFrog liver = 45.0 seleniumOhlendorfet al.,1988bKesterson Reservoir, CAAgricultural RunoffEared 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 seleniumOhlendorfet al.,1989Kesterson Reservoir, CAAgricultural RunoffMosquitofish (Gambusiaaffinis),American Coot (Fulica americana),Ducks (Anasspp.)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 seleniumOhlendorfet al.,1990Liberty State Park, NJIndustrial and UrbanActivitiesHouse Wren (troglodytes aedon),American Robin (Turdusmigratorus)Lead, arsenic, chromium, copper, andiron concentrations in bird feathers wereelevated.Feather = 4,200 lead; 1,000chromium; 6,200 copper; 600arsenicHoferet al., 2010A-46Appendix A— Literature Review Methodology and ResultsTable A-9. Summary of Attractive NuisancesUnrelated to Steam Electric Power PlantsSite Name, Location, andContamination SourceOrganism AffectedDocumented EffectsTrace Pollutant Concentrations(ppm)CitationMeadowlands, NJIndustrial and UrbanActivitiesRed-winged blackbird (agelaiusphoeniceus), marsh wrens(Cistothorus palustris), tree swallow(Tachycineta bicolor)Lead and chromium concentrations inblood were elevated; mercury andchromium concentrations in eggs wereelevated.Swallow blood = 0.94 lead;1.03 chromiumWren eggs = 0.2 mercuryBlackbird eggs = 0.12chromiumTsipouraet al., 2008Acronym: ppm (parts per million).A-47Appendix A— Literature Review Methodology and ResultsTable A-10. Summary of Selenium Concentrations in the Environment and Organisms Experiencing Adverse EffectsPlant NameSpeciesRoute of SeleniumExposureSeleniumConcentrations in theEnvironment (μg/L)or Diet (μg/g)SeleniumConcentrations in theOrganism (μg/g)Observed EffectsStudy Type(SurfaceWater Type)CitationBelews CreekSteam Station,Duke Energy(NC)Striped bass(Moronesaxatilis)Consumed a selenium-ladendiet by eating red shinerscollected from a sitereceiving coal ash pondsluice water.Red Shiners = 9.6μg/g (average wholebody concentration),wetSkeletal muscle = 3.8(higher averageconcentration), wetModifiedbehaviorDecreased growthHistopathologicalLethalLaboratory(reservoir)Coughlanand Velte,1989Largemouth bass(Micropterussalmoides)aPomoxis spp.Inhabited a selenium-ladencooling water reservoirreceiving both fly ash andbottom ash pond effluentfrom a coal-fired powerplant.Site waterd= 10 μg/LBiomasse= 0.1 – 1.0(mean)LethalReproductiveField(reservoir)Cumbie andVan Horn,1978Lepomis spp.bBody = 41.0 – 77.1(54.6 meanconcentration), wetLealurus spp.cBody = 0.31 – 15.5(6.32 meanconcentration), wetLargemouth bass(Micropterussalmoides)Inhabited a selenium-ladencooling water reservoirreceiving effluent from thecoal ash pond.Ash effluent = 100­200 μg/LSite water = 10μg/LVisceral tissue = 40+(highest meanconcentration), wetLethalField(reservoir)Lemly,1985aGreen sunfish(Lepomiscyanellus)Inhabited a selenium-ladenlake receiving coal fly ashsluice water.Site water = 13 μg/LSediment = 5 – 14μg/g, dryLiver = 21.4, wetSkeletal muscle =12.9, wetHematocrit = 33, wetHistopathologicalHematologicalField(lake)Sorensenetal., 1984bD-Area CoalFired PowerPlant,SavannahRiver Site(SRS) (SC)Banded watersnakes(Nerodiafasciata)Consumed a selenium-ladendiet by eating prey collectedfrom a contaminated sitelocated near a coal-firedpower plant.Prey itemsf= 22.7μg/g (geometric leastsquared mean), dryGonads = 17.64(female), 19.06 (male)Kidney = 25.38(female), 32.04 (male)Liver = 24.08(female), 24.22 (male)ReproductiveHistopathologicalLaboratory(notspecified)Hopkinsetal., 2002A-48Appendix A— Literature Review Methodology and ResultsTable A-10. Summary of Selenium Concentrations in the Environment and Organisms Experiencing Adverse EffectsPlant NameSpeciesRoute of SeleniumExposureSeleniumConcentrations in theEnvironment (μg/L)or Diet (μg/g)SeleniumConcentrations in theOrganism (μg/g)Observed EffectsStudy Type(SurfaceWater Type)CitationEastern narrowmouth toads(Gastrophrynecarolinensis)Inhabited a selenium-ladensite located near a coal-firedpower plant.Site water = 3.93 μg/LSoil = 8.25 μg/LLab water = 0.28 μg/LFemales = 42.40Eggs = 43.96ReproductiveHistopathologicalOutdoormescosm(combustionresidualspond)Hopkinsetal., 2006Slider turtles(Trachemysscripta)Inhabited a selenium-ladenpond receiving sluiced flyash near a coal-fired powerplant.Eggs were incubated in ashcontaminated soil.Ash-contaminated soil= 2.56 μg/g, dryAdult females = 37.18(mean concentration),dryReproductiveOutdoormescosm(combustionresidualspond)Nagleet al.,2001Roxboro Plant,ProgressEnergy (NC)Largemouth bass(Micropterussalmoides)Inhabited a selenium-ladencooling water reservoirreceiving ash pond effluentfrom a coal-fired powerplant.Not provided in theliterature.Carcass = 2.86 (mean,female), 2.63 (mean,male)Gonad = 4.40 (mean,female), 2.38 (mean,male)ReproductiveHistopathologicalField(reservoir)BaumannandGillespie,1986Bluegill(Lepomismacrochirus)Carcass = 2.74 (mean,female), 4.64 (mean,male)Gonad = 4.63 (mean,female), 3.35 (mean,male)Bluegill(Lepomismacrochirus)Inhabited a selenium-ladenreservoir receiving coal ashpond effluent.Not provided in theliteratureNot provided in theliteratureLethalField(reservoir)gCrutchfieldandFerguson,2000aGreen sunfishh(Lepomiscyanellus)Inhabited a selenium-ladenreservoir receiving coal ashpond effluent.Site wateri= 7 – 14μg/LBiomassj= 2,744 –3,793 (mean)LethalReproductiveField(reservoir)Crutchfield,2000bA-49Appendix A— Literature Review Methodology and ResultsTable A-10. Summary of Selenium Concentrations in the Environment and Organisms Experiencing Adverse EffectsPlant NameSpeciesRoute of SeleniumExposureSeleniumConcentrations in theEnvironment (μg/L)or Diet (μg/g)SeleniumConcentrations in theOrganism (μg/g)Observed EffectsStudy Type(SurfaceWater Type)CitationBluegill(Lepomismacrochirus)Inhabited a selenium-ladencooling water reservoir of acoal-fired power plant.Site waterk= 9 – 12μg/LTestes = 4.37 (meanconcentration)Ovaries = 6.96 (meanconcentration)ReproductiveLaboratory(reservoir)Gillepsieetal., 1986Bluegilll(Lepomismacrochirus)Inhabited a selenium-ladencooling water reservoir of acoal-fired power plant.Site water = <10–20μg/LLiver = 34 (meanconcentration), wetGonad = 12.1 (mean,female), 5.4 (mean,male), wetMuscle = 13 (meanconcentration), wetHistopathologicalField(reservoir)Sager andColfield,1984Largemouth bassm(Micropterussalmoides)Liver = 10.2 (meanconcentration), wetGonad = 10.3 (mean,female), wetMuscle = 6.7 (meanconcentration), wetMartin LakeSteam Station,Texas UtilitiesElectricServiceCompany (TX)Green sunfish(Lepomiscyanellus)Inhabited a selenium-ladenlake receiving coal fly ash,scrubber sludge, and coalbottom ash.Not provided in theliteratureHepatopancreas = 1.31– 9.30, wetHistopathologicalField(lake)Sorensenetal., 1982Redear sunfish(Lepomismicrolophus)Hepatopancreas = 2.8– 11.03, wetRedear sunfish(Lepomismicrolophus)Inhabited a selenium-ladenlake receiving coal fly ash,scrubber sludge, and coalbottom ash.Not provided in theliteratureLiver = 20HistopathologicalField(lake)Sorensenetal., 1983A-50Appendix A— Literature Review Methodology and ResultsTable A-10. Summary of Selenium Concentrations in the Environment and Organisms Experiencing Adverse EffectsPlant NameSpeciesRoute of SeleniumExposureSeleniumConcentrations in theEnvironment (μg/L)or Diet (μg/g)SeleniumConcentrations in theOrganism (μg/g)Observed EffectsStudy Type(SurfaceWater Type)CitationRedear sunfish(Lepomismicrolophus)Inhabited a selenium-ladenlake receiving coal ash pondwastewater.Not provided in theliteratureHepatopancreas = 8.4– 27.2 μg/LKidney = 11.4 – 115.7μg/LOvaries = 0 – 5.9 μg/LTestes = 0 – 54.2 μg/LIncreased weightlossField(lake)Sorensenand Bauer,1984aRedear sunfish(Lepomismicrolophus)Inhabited a selenium-ladenlake located near a coalfired power plant.Not provided in theliteratureLiver = 7.63 (meanconcentration)HistopathologicalReproductiveField(lake)Sorensen,1988Acronyms: kg/ha (kilogram per hectacre); μg/L (micrograms per liter); μg/g (micrograms per gram).a – Multiple fish species were studied; however, aspresented by the report, the largemouth bass andpomoxis spp.had the lowest documented selenium biomassconcentrations.b – Multiple fish species were studied; however, as presented by the report, theLepomis spp.had the highest documented selenium skeletal muscle concentrations.c – Multiple fish species were studied; however, as presented by the report, theLetalurus spp.had the lowest documented selenium body concentrations.d – This selenium concentration is dissolved.e – This concentration is measured in the units kg/ha. The rangeof selenium concentrations was reported annually from 1982 to1989, before the steam electricpower 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 electricpower plant.h – Multiple fish species were studied; however, as presented bythe report, the green sunfish had the highest documented selenium biomass concentrations.i – These are the selenium water concentrations detectedprior 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 to1989, before the steam electricpower 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 seleniumliver tissue concentration.m – Multiple fish species were studied; however, as presented bythe report, the largemouth bass had the lowest documented selenium liver tissue concentration.A-51

# Appendix B—Proximity Analyses Supporting Tables



# APPENDIX B

PROXIMITY ANALYSES SUPPORTING TABLES

Table B-1. Immediate Receiving Wat ers 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 Wat ers 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) Po lychlorinated 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 Wat ers 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). Ex tracted 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 concentra tions 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 Info rmation 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 imme diate 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 concen trations in receiving waters and total pollutant concentrations

in sediment within the immedi ate 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-speci fic input variable; 3) model assumption variable; and 4) sitespecific assumption variable based on predetermi ned 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 Assump tion Input Variables.

 

# Table C-3. Site-Specific A ssumption 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 Qu ality 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 Secti on 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 provide d 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 fr om 188 steam electric power plants in the

receiving water quantitativ e 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. EP A included assumptions of pollutant speciation

for arsenic and mercury as approp riate in the subseque nt wildlife and human health modules (see

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

quality module; however, due to the partition coe fficients 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 resi dual surface impoundments prior to discharge,

C-1

# Appendix C—Water Quality Module Methodology



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

present in well-oxygenated alkaline surface waters and the rate of convers ion 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 po llutant concentrations for the following compartments

within the receiving water:

Total pollutant concentration in water column (C

wc 

# );

Dissolved pollutant concentration in water column (C dw 

# ); and

Total pollutant concentr ation in sediment (C bs 

# ).

EPA used the equations presented below to ca lculate receiving water concentrations for

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

E QUATION 

# C-1

L total 

# Cw Tot, Rivers 

# = ሺ Q

cool 

# + Q ሻ × f

water 

# + K

wt 

# × V river river



# Where:

Cw Tot,Rivers 

# = Total pollutant concentration in the

waterbody (water and sediment) in rivers and

streams from pollutant loading (grams per

cubic meter [g/m 3 

# ] or milligrams per liter

[mg/L]) Output from Equation C-1

L total 

# = 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)

Q cool 

# = Total cooling water effluent flow (cubic

meters per day [m 3 

# /day]) Site-specific value from

engineering analysis

(see Table C-1)

Q river 

# = Receiving water average annual flow

(m 3 

# /day) Site-specific value from

NHD Plus

(see Table C-1)

f water 

# = Fraction of total waterbody pollutant

concentration in water column (unitless) Output from

Equation C-6

K

wt 

# = Water concentration di ssipation rate constant

(1/day) Output from Equation

C-10

V river 

# = Flow independent mixing volume for rivers

and streams (m 3 

# ) Output from

Equation C-11

C-2

# Appendix C—Water Quality Module Methodology



# E QUATION 

# C-2

L total 

# Cw Tot, Lake 

# = ሺQ ୡ୭୭୪ 

# + Q

lake 

# ሻ × f

water 

# + K

wt 

# × V lake



# Where:

Cw Tot, Lake 

# = Total pollutant concen tration in the waterbody

(water and sediment) in lakes, ponds, and

reservoirs from pollutant loading (g/m 3 

# or

mg/L) Output from Equation C-2

L total 

# = Average pollutant loading from steam effluent

(g/day) Site-specific value from

engineering analysis, based

on annual average

(see Table C-1)

Q cool 

# = Total cooling water effluent flow (m 3 

# /day) Site-specific value from

engineering analysis

(see Table C-1)

Q lake 

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

reservoir (m 3 

# /day) Site-specific value from

NHD Plus

(see Table C-1)

f water 

# = Fraction of total waterbody pollutant

concentration in water column (unitless) Output from

Equation C-6

K

wt 

# = Water concentration di ssipation rate constant

(1/day) Output from Equation C-10

V lake 

# = Flow independent mixing volume for lakes,

ponds, and reservoirs (m 3 

# ) Output from Equation C-12

E QUATION 

# C-3

d

z 

# C

wc 

# = f

water 

# × Cw tot (Rivers or Lakes) 

# × d

w 

# Where:

C

wc 

# = Total pollutant concentration in water column

(mg/L) Output from Equation C-3

f water 

# = Fraction of total waterbody pollutant

concentration in water column (unitless) Output from

Equation C-6

Cw Tot

(Rivers or

Lakes) 

# = Total pollutant concen tration in the waterbody

(water and sediment) fr om pollutant loading

(g/m 3 

# or mg/L) Output from Equation C-1

or Equation C-2

C-3

# Appendix C—Water Quality Module Methodology



# d

z

(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)

d

w

(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)

E QUATION 

# C-4

1

C dw 

# = C

wc 

# ൬ ൰

1 + Kd

sw 

# × TSS × 0.000001

Where:

C dw 

# = Dissolved pollutant concentration in water

(mg/L) Output from

Equation C-4

C

wc 

# = Total pollutant concentration in water column

(mg/L) Output from Equation C-3

Kd

sw 

# = 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

E QUATION 

# C-5

d

z 

# C bs 

# = f Benth 

# × Cw tot (Rivers or Lakes) 

# × d b



# Where:

C bs 

# = Total pollutant con centration in sediment

(mg/L) Output from Equation C-5

f Benth 

# = Fraction of total waterbody pollutant

concentration in benthic sediment (unitless) Output from

Equation C-15

Cw Tot

(Rivers or

Lakes) 

# = Total pollutant concen tration in the waterbody

(water and sediment) fr om pollutant loading

(g/m 3 

# or mg/L) Output from Equation C-1

or

Equation C-2

C-4

# Appendix C—Water Quality Module Methodology



# d

z

(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)

d

b

(Rivers or

Lakes) 

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

0.03 m

(see Table C-2)

E QUATION 

# C-6

d

w 

# ሾ 1 + ሺ Kd

sw 

# × TSS × 0.000001 ሻሿ × d

z 

# f

water 

# = d

w 

# d b 

# ቈ ሾ 1 + ሺ Kd

sw 

# × TSS × 0.000001 ሻሿ × ቉

+ ൤ ሺ bsp + Kd bs 

# × bsc ሻ × ൨

d

z 

# d

z



# Where:

f water 

# = Fraction of total waterbody pollutant

concentration in water column (unitless) Output from

Equation C-6

Kd

sw 

# = 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

d

w

(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)

d

z

(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 [cm 3 

# /cm 3 

# ]) Model assumption value of 0.6

cm 3 

# /cm 3



# (see Table C-2)

Kd bs 

# = 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/cm 3 

# ]) or (kilogram

per liter [kg/L]) Model assumption value of 1

g/cm 3



# (see Table C-2)

d

b 

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

0.03 m

(see Table C-2)

E QUATION 

# C-7

d

w 

# = Q

river



# v × Width

Where:

d w, river 

# = Depth of water column (m) Output from

Equation C-7

Q river 

# = Receiving water average annual flow

(m 3 

# /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

E QUATION 

# C-8

0.4559 

# Width river 

# = 5.1867 × Q

river



# Where:

Width river 

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

Q river 

# = Receiving water average annual flow

(m 3 

# /s) Site-specific value from NHD

Plus

(see Table C-1)

E QUATION 

# C-9

d z, river 

# = d b 

# + d w, river



# Where:

d z, river 

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

d

b 

# = 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



# d w, river 

# = Depth of water column (m) Output from

Equation C-7

E QUATION 

# C-10

K

wt 

# = ሺ f

water 

# × k

sw 

# ሻ + ሺ f benth 

# × k sed 

# ሻ + ሺ f

water 

# × k vol 

# ሻ + ሺ f benth 

# × K b 

# ሻ

Where:

K

wt 

# = Water concentration dissipation rate

constant (1/day) for nonvolatile pollutants

(see Equation C-16 for volatile pollutants) Output from Equation C-10

f water 

# = Fraction of total waterbody pollutant

concentration in water column (unitless) Output from

Equation C-6

k

sw 

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

0/day

(see Table C-2)

f benth 

# = Fraction of total waterbody pollutant

concentration in benthic sediment

(unitless) Output from

Equation C-15

k sed 

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

0/day

(see Table C-2)

k

vol 

# = Water column volatilization loss rate

constant (1/day) Model assumption value of

0/day

(see Table C-2)

K

b 

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

Equation C-14

E QUATION 

# C-11

V river 

# = Width river 

# × Len × d z,river



# Where:

V river 

# = Flow independent mixing volume for

rivers and streams (m 3 

# ) Output from

Equation C-11

Width river 

# = 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)

d z, river 

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

C-7

# Appendix C—Water Quality Module Methodology



# E QUATION 

# C-12

V lake 

# = Area × d z,lake



# Where:

V lake 

# = Flow independent mixing volume for

lakes, ponds, and reservoirs (m 3 

# ) Output from

Equation C-12

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

Plus

(see Table C-1)

d z,lake 

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

(see Table C-1)

E QUATION 

# C-13

f d 

# = 1

1 + Kd

sw 

# × TSS × 0.000001

Where:

f d 

# = Dissolved fraction in wate r (unitless) Output from

Equation C-13

Kd

sw 

# = 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

E QUATION 

# C-14

K b 

# = f benth 

# × WB

d

b



# Where:

K

b 

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

Equation C-14

f benth 

# = 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



# d

b 

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

0.03 m (see Table C-2)

E QUATION 

# C-15

d b 

# ሺ bsp + Kd bs 

# × bsc ሻ × d

z 

# f Benth 

# = d

w 

# d b 

# ቈ ሾ 1 + ሺ Kd

sw 

# × TSS × 0.000001 ሻሿ × ቉

+ ൤ ሺ bsp + Kd bs 

# × bsc ሻ × ൨

d

z 

# d

z



# Where:

f benth 

# = Fraction of total waterbody pollutant

concentration in benthic sediment

(unitless) Output from

Equation C-15

bsp = Bed sediment porosity (cm 3 

# /cm 3 

# ) Model assumption value of 0.6

cm 3 

# /cm 3



# (see Table C-2)

Kd bs 

# = 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/cm 3 

# ) or (kg/L) Model assumption value of 1

g/cm 3



# (see Table C-2)

d

b 

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

0.03 m

(see Table C-2)

d

z 

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

Kd

sw 

# = 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

d

w

(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 concentr ations 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, K wt 

# , in Equation C-10 was

replaced with a K wt,volatile 

# factor (see Equation C-16) that takes into account volatilization loss

C-9

# Appendix C—Water Quality Module Methodology



# (k

vol 

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

calculate receiving water con centrations for mercury only.

E QUATION 

# C-16

K

wt, volatile 

# = ሺ f

water 

# × k

sw 

# ሻ + ሺ f benth 

# × k sed 

# ሻ + ሺ f

water 

# × f d 

# × k vol 

# ሻ + ሺ f benth 

# × K b 

# ሻ

Where:

K

wt, volatile 

# = Water concentration dissipation rate

constant (1/day) Output from Equation C-16

f water 

# = Fraction of total waterbody pollutant

concentration in water column (unitless) Output from

Equation C-6

k

sw 

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

0/day

(see Table C-2)

f benth 

# = Fraction of total waterbody pollutant

concentration in benthic sediment

(unitless) Output from

Equation C-15

k sed 

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

0/day

(see Table C-2)

f d 

# = Dissolved fraction in water (unitless) Output from

Equation C-13

k

vol 

# = Water column volatilization loss rate

constant (1/day) Output from

Equation C-17

K

b 

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

Equation C-14

E QUATION 

# C-17

K

v 

# × f d 

# k

vol 

# = d

w 

# Where:

k

vol 

# = Water column volatilization loss rate

constant (1/day) Output from

Equation C-17

K

v 

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

Equation C-18

f d 

# = Dissolved fraction in water (unitless) Output from

Equation C-13

C-10

# Appendix C—Water Quality Module Methodology



# d

w 

# = 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)

E QUATION 

# C-18

Where: K

v 

# = 1

ቀ 1

K L 

# ቁ + ൮

1

K

g 

# × ቀ HLC

R × T

w 

# ቁ ൲ θ

water ሺ T

w 

# -T hic 

# ሻ



# K

v 

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

Equation C-18

Θ water 

# = Temperature correction (unitle ss) Model assumption value of

1.026

(see Table C-2)

T

w 

# = 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)

T hlc 

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

(see Table C-2)

K L

(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

K g

(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-m 3 

# /mole) 1 

# Known value of 0.0113 atmm 3 

# /mol

(see Table C-2)

R = Universal gas constant (atm-m 3 

# /°K-mole) Known value of 0.00008205

atm-m 3 

# /°K-mole

(see Table C-2)

E QUATION 

# C-19 ඨ

10 -4 

# × D

w 

# × v K L(Rivers) 

# = × 86,400 d

z



# Where:

K L(Rivers) 

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

Equation C-19

D

w 

# = Diffusivity of the pollutant in water

(square centimeter per second [cm 2 

# /s]) Output from

Equation C-20

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

Plus

(see Table C-1)

d z,river 

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

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

E QUATION 

# C-20

D

w 

# = 22×10 -5



# MW 2 3 ⁄



# Where:

D

w 

# = Diffusivity of the pollutant in water

(cm 2 

# /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 (m 3 

# ) per mole (mol).



# C-12

# Appendix C—Water Quality Module Methodology



# E QUATION 

# C-21

× ቆ k 0.33

a 

# K L ሺ Lakes ሻ 

# = ඥ C d 

# × w 10 

# × ඨ ρ

λ 2 

# ቇ

× Sc

w -0.67 

# × 86,400

ρ

w



# Where:

K L(Lakes) 

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

C d 

# = Drag coefficient (unitles s) Model assumption value of

0.0011

(see Table C-2)

W 10 

# = Wind velocity 10 meters above water

surface (m/s) Site-specific assumption value

(see Table C-3)

ρ a 

# = Density of air corresponding to water

temperature (g/cm 3 

# ) Model assumption value of

0.0012 g/cm 3



# (see Table C-2)

ρ w 

# = Density of water corresponding to water

temperature (g/cm 3 

# ) Model assumption value of 1

g/cm 3



# (see Table C-2)

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

(see Table C-2)

λ 2 

# = Dimensionless viscous sublayer thickness

(unitless) Model assumption value of 4

(see Table C-2)

Sc

w 

# = Water Schmidt number (dimensionless) Output from

Equation C-22

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

E QUATION 

# C-22

μ

w 

# Sc

w 

# = ρ × D

w w 

# Where:

Sc

w 

# = Water Schmidt number (dimensionless) Output from

Equation C-22

μ w 

# = Viscosity of water corresponding to water

temperature (g/cm-s) Model assumption value of

0.0169 g/cm-s

(see Table C-2)

ρ w 

# = Density of water corresponding to water

temperature (g/cm 3 

# ) Model assumption value of 1

g/cm 3



# (see Table C-2)

D

w 

# = Diffusivity of the pollutant in water

(cm 2 

# /s) Output from

Equation C-20

C-13

# Appendix C—Water Quality Module Methodology



# E QUATION 

# C-23

K g(Lakes) 

# = ඥ C d 

# × W 10 

# × ቆ k 0.33 

# ቇ

× Sc

a -0.67 

# × 86,400 λ 2



# Where:

K g(lakes) 

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

Equation C-23

C d 

# = Drag coefficient (unitles s) Model assumption value of

0.0011

(see Table C-2)

W 10 

# = 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)

λ 2 

# = Dimensionless viscous sublayer thickness

(unitless) Model assumption value of 4

(see Table C-2)

Sc

a 

# = Air Schmidt number (dimensionless) Output from

Equation C-24

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

E QUATION 

# C-24

ሺ 1.32 + 0.009T

a 

# ሻ × 10 5



# Sc

a 

# = 1.9

⁄ 

# MW 2 3



# Where:

Sc

a 

# = Air Schmidt number (dimensionless) Output from

Equation C-24

T

a 

# = Air temperature °K Site-specific assumption value

(see Table C-3)

MW = Molecular weight (g/m ol) 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 (C

wc 

# or C dw 

# , depending on the

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

C-14

# Appendix C—Water Quality Module Methodology



# IRW Model: Water Quality Module Inputs

Table C-1. Site-Speci fic Input Variables

Input

Variable Input Category and Description Data Source

L total 

# Plant-specific effluent characteristic

Total waterbody loading EPA estimated the pollutant discharge loadings using the

methodology presented in Section 10 of the TDD.

Q cool 

# 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].

Q river 

# Receiving water characteristic for

rivers and streams

Waterbody annual flow EPA extracted average annual fl ow 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 ve locity 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].

Q lake 

# Receiving water characteristic for

lakes, ponds, and reservoirs

Average discharge flow exiting the

lake/pond system EPA extracted average annual fl ow 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].

d z,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 b ased on

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

and Receiving Water Characteristics [ERG, 2015e].

d w,lake 

# Receiving water characteristic for

lakes, ponds, and reservoirs

Depth of the water column EPA estimated the depth of the lake, pond, or reservoir b ased 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 cm 3 

# /cm 3 

# 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/cm 3 

# Bed sediment particle concentrations typically

range between 0.5 to 1.5 g/cm 3 

# [U.S. EPA, 1998d].

EPA selected an average value to use for this input

variable.

d b 

# 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.

k

sw 

# Degradation rate for water

column 0/day EPA assumed no loss from pollutant degradation

in the water column, as an environmentally

conservative assumption.

k vol 

# Water column volatilization

loss rate constant 0/day EPA selected a volatilization rate of 0 for

nonvolatile pollutants ( i.e. , all pollutants except

mercury).

k sed 

# 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.

Θ

water 

# Temperature correction 1.026

(unitless) EPA selected the temper ature correction factor

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

K g(Rivers) 

# Gas phase transfer

coefficient for rivers or

streams 36,500 m/yr

(100 m/day) EPA selected the gas phase transfer coefficient for

rivers and streams based on the value provided in

U.S. EPA, 1998b.

R

Ideal gas constant 0.00008205

atm-m 3 

# /

K-mole The ideal gas constant is a known chemical

constant.

C d



# Drag coefficient 0.0011

(unitless) EPA selected the drag coefficient based on the

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

ρ a 

# Density of air corresponding

to water temperature 0.0012 g/cm 3 

# EPA selected the density of air corresponding to

water temperature based on the value provided in

U.S. EPA, 2005b.

ρ w 

# Density of water

corresponding to water

temperature 1 g/cm 3 

# 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

Kd

sw 

# 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 so urce for the pollutantspecific suspended sediment partition coefficients.

Kd bs 

# 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.

λ 2 

# Dimensionless viscous

sublayer thickness 4

(unitless) EPA selected the viscous sublayer thickness value

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

μ w 

# 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-m 3 

# /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.

T hlc 

# Temperature of Henry’s Law

Constant 298 °K The value 298 °K is th e 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 A ssumption 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 A ssumption Input Variables

Input Variable Description Assumed

Value Data Source

W 10 

# 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.

T

a 

# 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.

T

w 

# 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 Ce nter National Mean Annual Wind Speed

C-18

# Appendix C—Water Quality Module Methodology



# Figure C-2. National Climatic Data Ce nter National Mean Annual Temperature

Table C-4. Partition Coefficients

Pollutant Suspended SedimentWater Partition

Coefficient (Kd

sw 

# )

(mL/g) Bottom Sediment-Pore

Water Partition

Coefficient (Kd bs 

# )

(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 concentratio n 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

Cadmium0.002 (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); NRWQ C (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 (F W) 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 bio tic ligand model; therefore, th ere 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 Metho dology Limitations and Assumptions

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

 

# The module is based on annual-average pollu tant 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 flow s, 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 spec iation within the receiving

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

of the ecological impacts are tied to a sp ecific 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 reserv oirs. The module equations presented in

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

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

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

reflect the potential spatial and temporal vari ability of pollutant c oncentrations within

the immediate receiving water, and potentiall y underestimate the ex istence of isolated

“hot spots” of elevated pollutant concen trations. 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 th e water column and

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

partition coefficient to charac terize 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 va lue for the partition coefficients (central

tendency of K d 

# values) based on data gathered fr om published sources, statistical

analysis of retrieved data, geochemical modeling, and expert judgment [U.S. EPA,

2005a]. The result of this assumption on th e 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 rema in 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 benthi c sediments and a potential underestimation

of pollutant concentrations within th e 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 co lumn 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 va lues nor the data to

determine burial rates for each immediate re ceiving water. The pollutants with more

than 10 percent immediate r eceiving 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 nonpoi nt sources. Also, the pollutant loadings

included in the module are not representativ e of the total pollutant loadings from

steam electric power plants, as there are seve ral 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 ambi ent 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 immedi ate receiving water (IRW) model wildlife

module. Wildlife impact s include the following ecological receptors:

 

# Aquatic and sediment organisms (amphibians, fi sh, invertebrates) in direct contact with

receiving water and/or sediment in the im mediate discharge zone of steam electric

power plants.

 

# Wildlife (minks and eagles) 1 

# that consume fish from recei ving waters in the immediate

discharge zone of steam electric power plants.

EPA estimated pollutant concen trations in the immediate re ceiving water and sediment

using the IRW model water quality module (see Appendix C). Th e wildlife module uses these

concentrations as inputs.

Model input requirements for the equations pr esented in Appendix D can be divided into

four major categories: 1) input variable described by another e quation; 2) site-specific input

variable; 3) model assumption vari able; and 4) pollutant-specific va riable. The following tables in

Appendix D describe the input re quirements and data sources us ed in the wild life module and

impacts analysis:

 

# Table D-1. Chemical Stressor Concentrati on Limits (CSCLs) for Sediment Biota.

 

# Table D-2. Bioconcentration Factors (BCFs) and Bioaccumulation Factors (BAFs) for

Trophic Level 3 (T3) and Tr ophic 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 fr om Direct Contact with Sediment . EPA determined the

potential negative impact to aqua tic organisms from direct contact with the sedime nt in immediate

receiving waters by comparing the polluta nt concentration in the sediment (C bs 

# from the water

quality module) to the CSCL benc hmarks 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) indicat es a potential impact to the exposed organism.

EPA used Equation D-1 to calcula te the HQ for sediment biota.

1 

# EPA selected minks and eagles to represent national-scal e 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



# E QUATION 

# D-1

C bs 

# HQ

sed 

# = CSCL sed



# Where:

HQ sed 

# = Hazard quotient for contact with sediment Output from Equation D-1

C bs 

# = Total pollutant con centration in sediment

(milligrams per liter [mg/L]) Water quality module output

Equation C-5

CSCL sed 

# = 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 th e ingestion of contaminated fish by

calculating fish tissue concentr ations and comparing these c oncentrations 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 met hylmercury, 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.

E QUATION 

# D-2

C fishT 

# = C

wc 

# × BCF T



# E QUATION 

# D-3

C fishT 

# = ሺ 0.15 × C dw 

# ሻ × BCF T



# Where:

C fishT 

# = 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

C

wc 

# = Total pollutant concentration in wa ter (mg/L) Water quality module output

Equation C-3

C dw 

# = 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]

BCF T 

# = Bioconcentration fact or 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 c oncentration to the ecological benchmark for

minks and the calculated T4 fish tissue concentra tion 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 expresse s this comparison as an HQ. EPA used Equation

D-4 to calculate HQ values for arsenic, cadmi um, chromium (VI), copper, lead, mercury (as

methylmercury), nickel, sele nium, thallium, and zinc.

D-2

# Appendix D—Wildlife Module Methodology



# E QUATION 

# D-4

C fishT 

# HQ

I 

# = NEHC

Where:

HQ I 

# = Hazard quotient for ingestion of fish Output from Equation D-4

C fishT 

# = 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 Benchmar ks 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 Ecosys tems. 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 Method ology Limitations and Assumptions

EPA was required to make assumptions about va rious inputs, resulti ng in limitations with

respect to the wildlife module output and interpretation. Variab ility occurs from heterogeneous

characteristics, such as body wei ght differences within a populati on 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 assumpti ons 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 modele d impacts to wildlife from ingesting

contaminated fish do not consider the risk fr om direct contact with surface water. The

receptors chosen for the wild life ingestion model, minks a nd eagles, do not spend large

amounts of time in contact with the surface wa ter; therefore, not including the impact

of direct contact with surface water shoul d 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 th at 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 assessmen t (EA) where site-specific data are not

available and collection of site-specific da ta is not viable. Th e 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 recepto r species and receiving water occur together

( i.e. , all receiving waters evalua ted 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 eag les due to their nati onal distribution and

data available to conduct the analysis [U SGS, 2008]. By choosing a limited number of

species, the wildlife module inherently excl udes 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 Cr iteria 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 tissu e and the subsequent transfer to human receptors. In addition, EPA agrees

that distributions of BAFs/BCFs may be better than si ngle BAFs/BCFs because they account for changes in

bioaccumulation/bioconcentration rates at different wate r concentrations. EPA is working to develop BAF/BCF

distributions for several pollutants to better repr esent the bioaccumulation in aquatic organisms.



# D-5

# Appendix D—Wildlife Module Methodology



# limitation in the impact assessment by presenti ng a proximity analysis of steam electric

power plants to habitats of threatened and endangered sp ecies (see Section 3.4.5 of this

report) and an evaluation of the ecological ri sk to aquatic organisms and avian receptors

from selenium contamination (s ee Section 5.2 of this report).

 

# Wildlife Receptor Diet . To provide an environmentall y protective estimate of dietary

pollutant exposure, the wildlif e 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 fo llowing two factors: 1) It is possible that

in some habitats the dietary composition fo r both minks and eagles consists largely of

fish and EPA aims to be protective of wild life 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 additi on, it is likely that the other organisms

consumed by minks and eagles are also cont aminated 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 S ection 8) demonstrate that pollutants

discharged from steam electric power plants can continue to occur at elevated levels

downstream from the immediate receiving wa ters, 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 polluta nt concentration in the water column ( i.e.

, dissolved plus particles sorbed to suspende d 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 part icular waterbody. Because of bioavailability

and pollutant speciation assu mptions 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 e ffects are difficult to assess

and are thought to have mini mal 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 r eality, 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 concentr ation 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 relationshi ps and necessity for site-speci fic data, none of the impact

analyses considered stratification of receivi ng 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 im pacts the receptors. For example, EPA did

not consider the impact of mercury on the uptake or toxicity of selenium. There is

evidence in the literatu re that these two compounds inte ract 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 th e toxicity of individual chemicals, and

the relationships between chemicals are comp lex, 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 fr om direct contact with contaminated

sediment. The benchmarks represent thres hold effect levels TELs. If an organism

ingests chemical concentra tion 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 resu lts 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 variable s, benchmarks, and

methodology limitations/assumptions for the imme diate receiving water (IRW) model human

health module. Human health impacts include the following receptor groups:

 

# Child cohorts (recreational) that consume fi sh exposed to pollutants as a result of

discharges from steam electric power plants.

 

# Child cohorts (subsistence) that consume fi sh exposed to pollutants as a result of

discharges from steam electric power plants.

 

# Adult cohorts (recreational) that consume fi sh exposed to pollutants as a result of

discharges from steam electric power plants.

 

# Adult cohorts (subsistence) that consume fi sh exposed to pollutants as a result of

discharges from steam electric power plants.

In addition to the national-scale cohorts evalua ted as part of the e nvironmental assessment

(EA), EPA also estimated annual-average daily dos e 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 concentr ations as inputs.

Model input requirements for the equations pr esented in Appendix E can be divided into

five major categories: 1) input variable described by another e quation; 2) site -specific input

variable; 3) model assumption variable; 4) recept or cohort-specific vari able; and 5) pollutantspecific variable. The following tables in Appendi x E describe the input requirements and data

sources used in the human health module:

 

# Table E-1. Calculation of Consum ption Ratio for Trophic Level 3 (F T3 

# ) and Trophic

Level 4 (F T4 

# ) Fish.

 

# Table E-2. Model Assumption Input Vari ables 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-Spec ific Consumption

Rate by Race or Hispanic Origin for the Human Health Module.

 

# Table E-5. Pollutant-Specific Input Vari ables 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 rati o of T3 and T4 fish and site-s pecific pollutant concentrations

in fish. For each cohort, EPA calculated the aver age daily dose (ADD) of th e pollutant from eating

fish and compared this ADD to n on-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 benchm ark) indicates a potential non-cancer

E-1

# Appendix E—Human Health Module Methodology



# threat to the human cohort. EPA also calcula ted 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 presente d 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 associ ated non-cancer threat HQ; an d the LADD and LECR values for

arsenic.

E QUATION 

# E-1

C fish_fillet 

# = F T3 

# × C fishT3F 

# + F T4 

# × C fishT4F



# Where:

C fish_fillet 

# = Average fish fillet concentration ingested by

humans (milligrams per kilograms [mg/kg]) Output from Equation E-1

C fishT3F 

# = Concentration of contaminant in fish at

trophic level 3 (mg/kg) Site-specific wildlife module

output Equation D-2 and

Equation D-3

C fishT4F 

# = Concentration of contaminant in fish at

trophic level 4 (mg/kg) Site-specific wildlife module

output Equation D-2 and

Equation D-3

F T3 

# = Fraction of trophic level 3 fish intake

(unitless) Model assumption value of

0.36 (see calculation below)

F T4 

# = 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 F actor 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 stream s; 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 Consumpt ion Ratio for Trophic Level 3 (F T3 

# ) and Trophic Level 4

(F T4 

# ) 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 da ily intake of the c ontaminant from fish

ingestion. Based on a literature review (including EPA and Agen cy 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 arse nic is harmful to humans; EPA’s 1997 document,

Arsenic and Fish Consumption , reported the inorganic arsenic c oncentration 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 heal th impacts. The human health

model multiplies the C fish_fillet 

# concentration by 4 pe rcent for arsenic (converting concentration

from total to inorganic).

Equation E-3 calculates the LADD, based on th e ADD. Arsenic is th e 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 ar e equal to the length

of time in that cohort range. EPA selected an ex posure 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 i norganic arsenic, based on the LADD.

E QUATION 

# E-2

C fish_fillet 

# × CR fish 

# × F fish 

# ADD

= 1,000 × BW

Where:

ADD = Daily dose of pollutant from fish ingestion

(mg/kg BW/day) Output from Equation E-2

C fish_fillet 

# = Average fish fillet concentration ingested by

humans (mg/kg) Output from Equation E-1

CR fish 

# = Consumption rate of fish (g ww/day) Receptor cohort-specific

value (see Table E-3 and

Table E-4)

F fish 

# = 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



# E QUATION 

# 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 inge stion (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)

E QUATION 

# 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)

E QUATION 

# 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 Mo dule Inputs and Benchmarks

Table E-2. Model Assumption Input Va riables for the Human Health Module

Input

Variable Description Assumed

Value Assumption Rationale/Data Source

F T3 

# Fraction of trophic level 3 fish intake 0.36 U.S. EPA, 2011b

F T4 

# Fraction of trophic level 4 fish intake 0.64 U.S. EPA, 2011b

F fish 

# Fraction of fish intake from

contaminated source 1 EPA assumed that all fish consumed by the

receptor is from the cont aminated surface water.

EF Exposure frequency (days/yr) 350 EPA assu med 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. Recrea tional fishers are non-commercial, non-subsistence

fishers and are more vulnerable to pollutant e xposure 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 ma jor food source. Intake rates for subsistence fishers are generally

higher than for the general population, and subsiste nce fishers are more vulnerable to pollutant

exposure by intake of co ntaminated fish from a specific wa terbody compared to both recreational

fishers and the general population. Because of th e focus of human exposure to a subset of the

general population that more frequently consume lo cal fish, EPA selected fish consumption rates

from studies based on “consumer only” data. Consumer-only fi sh 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 C onsumption 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 no t calculate the annual-av erage 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 fi sh intake rates using the following

percentiles by fisher type: 1) genera l population and recrea tional fisher: 90 th 

# percentile of per capita

data and 2) subsistence fisher: 99 th 

# 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 an d using the following percentiles by fisher type:

1) recreational fisher: mean of consumer-only data and 2) subsistence fisher: 95 th 

# 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 cal culate a single adult cohort fish consumption rate.



# E-7Appendix E—Human Health Module MethodologyTable E-4. Environmental Justice Analysis:Receptor Cohort-Specific Input Consumption Rate by Race or Hispanic Origin for theHuman Health ModuleReceptorRace or Hispanic OriginCRfish,g/kg-day(All ages)aConsumption Rate (CRfish), g/day, by Cohortb1 to <2years2 to <3years3 to <6years6 to <11years11 to <16years16 to <21yearsAdultRecreationalNon-Hispanic White0.677.649.2512.521.338.14853.6Non-Hispanic Black0.778.7810.614.324.543.755.161.6Mexican-American0.9310.612.817.329.652.866.674.4Other Hispanic0.829.3511.315.326.146.658.765.6Other, including Multiple Races0.9610.913.217.930.554.568.776.8SubsistenceNon-Hispanic White1.921.726.235.360.4108136152Non-Hispanic Black2.123.929.039.166.8119150168Mexican-American2.831.938.652.189.0159200224Other Hispanicc2.730.837.350.285.9153193216Other, including Multiple Racesc3.641.049.767.0114204258288Source: 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, EPA used the 95thpercentile, 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 weights, as listed in TableE-3, to calculate a cohort-specific consumption rate ing/day. Numbers presented asthree significant digits.c – Consumption rates for this race or Hispanic origin are less statistically reliabledue to the comparatively smaller data set.E-8

# Appendix E—Human Health Module Methodology



# Table E-5. Pollutant-Specific Benchm arks 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 c ontaminated drinking water. Exposures from

fish consumption and drinking water are like ly 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 wa ter 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 underestim ate 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 conc entrations 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 conc entrations 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 fr om 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 appro ach 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 interact ions 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 assu mes 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-avera ge daily dose of the pollutants for these

receptors, particularly for recreational fi shers. The proportion of fish eaten by an

individual from local su rface 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 re present EPA’s current guidance on exposure

data [U.S. EPA, 2008a; U.S. EPA, 2011b].

 

# Human Health Benchmarks. Uncertainties generally asso ciated with human health

benchmarks are discusse d in detail in EPA’s Guidelines for Carcinogen Risk

Assessment [U.S. EPA, 2005c] and Integrated Ri sk Information System (IRIS) [U.S.

EPA, 2011c]. IRIS defines the RfD as “an es timate (with uncertainty spanning perhaps

an order of magnitude) of a daily oral exposure to the human population (including

sensitive subgroups) that is lik ely to be without an appreciable threat of deleterious

effects during a lifetime.” RfDs are typi cally based on an assumption of lifetime

exposure and may not be appropriate when applied to less-th an-lifetime exposure

situations [U.S. EPA, 2011c]. The cancer sl ope factor is an estimate of the human

cancer risk per milligram of ch emical per kilogram body weight per day. To calculate

the LADD used for the cancer risk assessmen t, 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 co ncentration. This analysis

may over- or under-estimate the cancer risk if exposure is shorter than or longer than

the ED, respectively. LADDs are appropria te when developing screening-level

estimates; however, EPA recommends calculati ng 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 co ntaminated fish) as recreatio nal 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 memb ers. EPA estimated the numb er of people who are likely

to fish affected reaches based on typi cal travel distances to a fishing site, presence of substitute fishing locations,

data on the locations and status of fi sh consumption advisories for affected reaches, and information on anglers’

awareness and adherence to those advisori es. 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 eco logical 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 out puts from the water quality module of the

national-scale immediate receiving water (IRW) model (see Appendix C).

 

# Dissolved selenium concentrations in th e immediate receiving water and downstream

reaches of Black Creek, Mississippi, base d 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 enrichme nt 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) spec ies-specific trophic transf er factors (TTFs), which

describe subsequent bioaccumulation by higher trophi c-level aquatic organisms such as fish and

birds; and 4) exposure-response (ER) functions, which tran slate the modeled selenium

concentrations in fish and birds into the associated reduction in reproductive success.

The ecological risk modeling methodology is de scribed in Section 5.2 of the EA report.

This modeling approach is consistent with the appr oach taken in developing the Draft Aquatic Life

Ambient Water Quality Criterion for Selenium – Freshwater [U.S. EP A, 2014f] (referred to as the

draft selenium criterion) and is based on th e same data sets and studies for EF, TTF invert 

# , TTF fish



# , and ER fish 

# . For this EA, EPA expanded the m odel to include data sets for TTF mallard 

# and ER mallard



# .

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 c oncentrations for the national-scale and case

study ecological risk models are derived from th e IRW water quality module and the Black Creek

case study water quality model, respectively. Disso lved selenium concentrations used in the

national-scale ecologica l risk model are provided in DCN SE04612. 1 

# Dissolved selenium

concentrations used in the cas e study ecological risk model ar e provided in DCN SE04615. Prior

to use as inputs for the Black Creek case study ec ological risk model, EPA calculated three-month

rolling averages of the dissolved selenium con centration output from the Black Creek case study

water quality model. This resulted in one av erage concentration for each calendar month

1 

# EPA removed identifying information, such as the immediate receiving wa ter name and the steam electric power

plant name, from this reference to prevent disclo sure of confidential business information (CBI).



# F-1

# Appendix F—Overview of Ecological Risk Modeling Setup and Outputs



# throughout the entire modeling pe riod after the assumed comp liance date for the Morrow

Generating Site (2019-2036). Use of a three-month rolling averag e avoided the calculation of

significantly elevated reproductive ri sks 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 develo ping 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). Thes e 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 repor t, 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 dr aft selenium criterion [U.S. EPA, 2014f]. This

resulted in a TTF invert 

# distribution with a mean (s tandard deviation) of 2.84 (2.49) 3 

# and a TTF fish



# 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 de veloped a TTF distribution for mallards.

The resulting TTF mallard 

# distribution is best de scribed by a triangular dist ribution, with a likeliest

value of 2.5, a minimum value of 0.4, and a maxi mum 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 TTF invert 

# and TTF fish 

# datasets to include only inverteb rate and fish species that are re presentative 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 illu strated 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 th e draft selenium criterion

[U.S. EPA, 2014f]. This ER functi on 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 concentra tion 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 co ncentration in the organism to the concentration in the

consumed material or lower-trophic-l evel organism. A mean TTF of 2.84 for invertebrates indicates that, on

average, the concentration of selenium in the tissues of in vertebrates 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 f it a logistic curve to the combined, control

normalized data from six different laboratory studies that evalua ted 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 i llustrated in Figure F-4.

F-3

# Figure F-1. Input EF and TTF Di stributions for National-Sca le 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 Sele nium Distributions for Morrow Generating

Site Immediate Receiving Water (Black C reek Case Study) Ecological Risk Model –

Baseline and Final Rule (Option D) Appendix F—Overview of Ecological Risk Modeling Setup and Outputs



# F-5Proportion 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

1.0Proportion 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 Functi on 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 summari ze 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 summari ze 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 summari ze the results of the case stu dy 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 per cent 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 Reproduc tive Effects in Fish – Baseline

Percentile a 

# Lake b 

# River b 

# Total b



# 1 Percent of Fish Population Experiencing Negative Reproductive Effects

10 th 

# : 0 (0%) 14 (7.7%) 14 (6.7%)

25 th 

# : 2 (7.7%) 17 (9.3%) 19 (9.1%)

Median: 4 (15%) 24 (13%) 28 (13%)

75 th 

# : 6 (23%) 32 (17%) 38 (18%)

90 th 

# : 8 (31%) 36 (20%) 44 (21%)

95 th 

# : 8 (31%) 42 (23%) 50 (24%)

10 Percent of Fish Population Experiencing Negative Reproductive Effects

10 th 

# : 0 (0%) 12 (6.6%) 12 (5.7%)

25 th 

# : 1 (3.8%) 14 (7.7%) 15 (7.2%)

Median: 4 (15%) 20 (11%) 24 (11%)

75 th 

# : 6 (23%) 29 (16%) 35 (17%)

90 th 

# : 7 (27%) 35 (19%) 42 (20%)

95 th 

# : 8 (31%) 39 (21%) 47 (22%)

50 Percent of Fish Population Experiencing Negative Reproductive Effects

10 th 

# : 0 (0%) 10 (5.5%) 10 (4.8%)

25 th 

# : 0 (0%) 14 (7.7%) 14 (6.7%)

Median: 3 (12%) 17 (9.3%) 20 (9.6%)

75 th 

# : 5 (19%) 27 (15%) 32 (15%)

90 th 

# : 6 (23%) 34 (19%) 40 (19%)

95 th 

# : 8 (31%) 35 (19%) 43 (21%)

75 Percent of Fish Population Experiencing Negative Reproductive Effects

10 th 

# : 0 (0%) 10 (5.5%) 10 (4.8%)

25 th 

# : 0 (0%) 14 (7.7%) 14 (6.7%)

Median: 3 (12%) 17 (9.3%) 20 (9.6%)

75 th 

# : 5 (19%) 26 (14%) 31 (15%)

90 th 

# : 6 (23%) 31 (17%) 37 (18%)

95 th 

# : 7 (27%) 34 (19%) 41 (20%)

90 Percent of Fish Population Experiencing Negative Reproductive Effects

10 th 

# : 0 (0%) 9 (4.9%) 9 (4.3%)

25 th 

# : 0 (0%) 13 (7.1%) 13 (6.2%)

Median: 2 (7.7%) 17 (9.3%) 19 (9.1%)

75 th 

# : 5 (19%) 22 (12%) 27 (13%)

90 th 

# : 6 (23%) 29 (16%) 35 (17%)

95 th 

# : 6 (23%) 34 (19%) 40 (19%)

Notes:

a – Percentile refers to the risk percentile. For example, values in the 90 th 

# percentile row indicate the numbers of

receiving waters whose selenium concentr ations are high enough to result in a 10 percent probability of the indicated

reproductive effect.

b – The national-scale ecological risk model encompasses a to tal 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 Ef fects in Fish – Final Rule (Option D)

Percentile a 

# Lake b 

# River b 

# Total b



# 1 Percent of Fish Population Experiencing Negative Reproductive Effects

10 th 

# : 0 (0%) 3 (1.6%) 3 (1.4%)

25 th 

# : 0 (0%) 5 (2.7%) 5 (2.4%)

Median: 0 (0%) 11 (6%) 11 (5.3%)

75 th 

# : 0 (0%) 16 (8.7%) 16 (7.7%)

90 th 

# : 1 (3.8%) 21 (11%) 22 (11%)

95 th 

# : 1 (3.8%) 25 (14%) 26 (12%)

10 Percent of Fish Population Experiencing Negative Reproductive Effects

10 th 

# : 0 (0%) 3 (1.6%) 3 (1.4%)

25 th 

# : 0 (0%) 3 (1.6%) 3 (1.4%)

Median: 0 (0%) 8 (4.4%) 8 (3.8%)

75 th 

# : 0 (0%) 15 (8.2%) 15 (7.2%)

90 th 

# : 0 (0%) 19 (10%) 19 (9.1%)

95 th 

# : 1 (3.8%) 23 (13%) 24 (11%)

50 Percent of Fish Population Experiencing Negative Reproductive Effects

10 th 

# : 0 (0%) 3 (1.6%) 3 (1.4%)

25 th 

# : 0 (0%) 3 (1.6%) 3 (1.4%)

Median: 0 (0%) 6 (3.3%) 6 (2.9%)

75 th 

# : 0 (0%) 12 (6.6%) 12 (5.7%)

90 th 

# : 0 (0%) 19 (10%) 19 (9.1%)

95 th 

# : 0 (0%) 20 (11%) 20 (9.6%)

75 Percent of Fish Population Experiencing Negative Reproductive Effects

10 th 

# : 0 (0%) 2 (1.1%) 2 (0.96%)

25 th 

# : 0 (0%) 3 (1.6%) 3 (1.4%)

Median: 0 (0%) 5 (2.7%) 5 (2.4%)

75 th 

# : 0 (0%) 9 (4.9%) 9 (4.3%)

90 th 

# : 0 (0%) 15 (8.2%) 15 (7.2%)

95 th 

# : 0 (0%) 19 (10%) 19 (9.1%)

90 Percent of Fish Population Experiencing Negative Reproductive Effects

10 th 

# : 0 (0%) 2 (1.1%) 2 (0.96%)

25 th 

# : 0 (0%) 3 (1.6%) 3 (1.4%)

Median: 0 (0%) 4 (2.2%) 4 (1.9%)

75 th 

# : 0 (0%) 9 (4.9%) 9 (4.3%)

90 th 

# : 0 (0%) 15 (8.2%) 15 (7.2%)

95 th 

# : 0 (0%) 19 (10%) 19 (9.1%)

Notes:

a – Percentile refers to the risk percentile. For example, values in the 90 th 

# percentile row indicate the numbers of

receiving waters whose selenium concentr ations are high enough to result in a 10 percent probability of the indicated

reproductive effect.

b – The national-scale ecological risk model encompasses a to tal 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 Reproducti ve Effects in Mallards – Baseline

Percentile a 

# Lake b 

# River b 

# Total b



# 1 Percent of Mallard Population Experiencing Hatching Failure

10 th 

# : 3 (12%) 18 (9.8%) 21 (10%)

25 th 

# : 5 (19%) 26 (14%) 31 (15%)

Median: 6 (23%) 34 (19%) 40 (19%)

75 th 

# : 8 (31%) 38 (21%) 46 (22%)

90 th 

# : 9 (35%) 47 (26%) 56 (27%)

95 th 

# : 13 (50%) 52 (28%) 65 (31%)

10 Percent of Mallard Population Experiencing Hatching Failure

10 th 

# : 0 (0%) 14 (7.7%) 14 (6.7%)

25 th 

# : 3 (12%) 17 (9.3%) 20 (9.6%)

Median: 5 (19%) 26 (14%) 31 (15%)

75 th 

# : 6 (23%) 32 (17%) 38 (18%)

90 th 

# : 8 (31%) 36 (20%) 44 (21%)

95 th 

# : 8 (31%) 42 (23%) 50 (24%)

50 Percent of Mallard Population Experiencing Hatching Failure

10 th 

# : 0 (0%) 10 (5.5%) 10 (4.8%)

25 th 

# : 0 (0%) 13 (7.1%) 13 (6.2%)

Median: 2 (7.7%) 17 (9.3%) 19 (9.1%)

75 th 

# : 4 (15%) 22 (12%) 26 (12%)

90 th 

# : 6 (23%) 28 (15%) 34 (16%)

95 th 

# : 6 (23%) 34 (19%) 40 (19%)

75 Percent of Mallard Population Experiencing Hatching Failure

10 th 

# : 0 (0%) 7 (3.8%) 7 (3.3%)

25 th 

# : 0 (0%) 10 (5.5%) 10 (4.8%)

Median: 0 (0%) 14 (7.7%) 14 (6.7%)

75 th 

# : 3 (12%) 17 (9.3%) 20 (9.6%)

90 th 

# : 5 (19%) 22 (12%) 27 (13%)

95 th 

# : 6 (23%) 27 (15%) 33 (16%)

90 Percent of Mallard Population Experiencing Hatching Failure

10 th 

# : 0 (0%) 3 (1.6%) 3 (1.4%)

25 th 

# : 0 (0%) 8 (4.4%) 8 (3.8%)

Median: 0 (0%) 12 (6.6%) 12 (5.7%)

75 th 

# : 1 (3.8%) 14 (7.7%) 15 (7.2%)

90 th 

# : 4 (15%) 18 (9.8%) 22 (11%)

95 th 

# : 5 (19%) 22 (12%) 27 (13%)

Notes:

a – Percentile refers to the risk percentile. For example, values in the 90 th 

# percentile row indicate the numbers of

receiving waters whose selenium concentr ations are high enough to result in a 10 percent probability of the indicated

reproductive effect.

b – The national-scale ecological risk model encompasses a to tal 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 Eff ects in Mallards – Final Rule (Option D)

Percentile a 

# Lake b 

# River b 

# Total b



# 1 Percent of Mallard Population Experiencing Hatching Failure

10 th 

# : 0 (0%) 7 (3.8%) 7 (3.3%)

25 th 

# : 0 (0%) 12 (6.6%) 12 (5.7%)

Median: 0 (0%) 19 (10%) 19 (9.1%)

75 th 

# : 0 (0%) 23 (13%) 23 (11%)

90 th 

# : 0 (0%) 26 (14%) 26 (12%)

95 th 

# : 2 (7.7%) 26 (14%) 28 (13%)

10 Percent of Mallard Population Experiencing Hatching Failure

10 th 

# : 0 (0%) 3 (1.6%) 3 (1.4%)

25 th 

# : 0 (0%) 6 (3.3%) 6 (2.9%)

Median: 0 (0%) 12 (6.6%) 12 (5.7%)

75 th 

# : 0 (0%) 17 (9.3%) 17 (8.1%)

90 th 

# : 0 (0%) 21 (11%) 21 (10%)

95 th 

# : 0 (0%) 25 (14%) 25 (12%)

50 Percent of Mallard Population Experiencing Hatching Failure

10 th 

# : 0 (0%) 3 (1.6%) 3 (1.4%)

25 th 

# : 0 (0%) 3 (1.6%) 3 (1.4%)

Median: 0 (0%) 5 (2.7%) 5 (2.4%)

75 th 

# : 0 (0%) 9 (4.9%) 9 (4.3%)

90 th 

# : 0 (0%) 14 (7.7%) 14 (6.7%)

95 th 

# : 0 (0%) 18 (9.8%) 18 (8.6%)

75 Percent of Mallard Population Experiencing Hatching Failure

10 th 

# : 0 (0%) 2 (1.1%) 2 (0.96%)

25 th 

# : 0 (0%) 3 (1.6%) 3 (1.4%)

Median: 0 (0%) 3 (1.6%) 3 (1.4%)

75 th 

# : 0 (0%) 6 (3.3%) 6 (2.9%)

90 th 

# : 0 (0%) 9 (4.9%) 9 (4.3%)

95 th 

# : 0 (0%) 13 (7.1%) 13 (6.2%)

90 Percent of Mallard Population Experiencing Hatching Failure

10 th 

# : 0 (0%) 1 (0.55%) 1 (0.48%)

25 th 

# : 0 (0%) 2 (1.1%) 2 (0.96%)

Median: 0 (0%) 3 (1.6%) 3 (1.4%)

75 th 

# : 0 (0%) 3 (1.6%) 3 (1.4%)

90 th 

# : 0 (0%) 6 (3.3%) 6 (2.9%)

95 th 

# : 0 (0%) 9 (4.9%) 9 (4.3%)

Notes:

a – Percentile refers to the risk percentile. For example, values in the 90 th 

# percentile row indicate the numbers of

receiving waters whose selenium concentr ations are high enough to result in a 10 percent probability of the indicated

reproductive effect.

b – The national-scale ecological risk model encompasses a to tal of 209 immediate receiving waters (183 rivers and

streams; 26 lakes, ponds, and reservoirs) and loadings from 188 steam electric power plants.



# F-11Appendix F— Overview of Ecological Risk Modeling Setup and OutputsTable F-5. Risk of Selenium-Driven Reproductive Effects in Fish Downstream from Morrow Generating Site ImmediateReceiving Water (Black Creek Case Study) – BaselinePercentileaBlack Creek WASP Model Segment IDb,c3938373635343332313029282710th:<0.1%<0.1%<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%<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%<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%1.62%1.46%90th:>99.9%98.7%98.3%94.6%93.4%87.7%95.2%94.4%40.8%36.3%20.5%82.6%79.6%95th:>99.9%>99.9%>99.9%>99.9%>99.9%99.8%>99.9%>99.9%94.2%92.8%80.6%99.7%99.6%2625242322212019181716151410th:<0.1%<0.1%<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%<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%<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%0.331%0.323%90th:80.9%57.1%86.5%87.8%83.9%80.1%81.0%84.1%73.4%66.5%64.6%60.3%58.4%95th:99.7%97.8%99.8%99.7%99.7%99.5%99.6%99.7%99.1%98.9%98.7%97.9%97.7%1312111098765432110th:<0.1%<0.1%<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%<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%<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%0.292%0.421%90th:57.9%60.3%59.2%72.3%66.7%59.1%59.7%56.3%58.4%63.1%63.1%59.5%59.5%95th:97.6%98.5%97.9%98.9%97.8%97.5%97.8%97.8%97.4%98.4%98.4%97.9%98.3%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, thereis a 25 percent probability that seleniumconcentrations in fish eggs/ovaries are high enough to cause negative reproductive effects in 83 percent of the exposed fish population inhabiting that segment ofBlack Creek.b – Segment 39 is the immediate receiving water for Morrow Generating Site. Segment 1 is farthest downstream from the immediatereceiving water. The 39segments 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-12Appendix F— Overview of Ecological Risk Modeling Setup and OutputsTable F-6. Risk of Selenium-Driven Reproductive Effects in Mallards Downstream from Morrow Generating Site ImmediateReceiving Water (Black Creek Case Study) – BaselinePercentileaBlack Creek WASP Model Segment IDb,c3938373635343332313029282710th:<0.1%<0.1%<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%<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%1.17%1.10%75th:37.3%19.4%18.6%15.0%14.8%12.6%13.7%14.6%5.33%4.81%3.57%9.98%9.13%90th:71.1%49.5%47.4%41.4%40.5%38.3%40.5%41.6%22.1%21.2%17.6%33.6%32.0%95th:86.1%68.0%66.7%60.5%58.6%57.2%59.7%60.6%38.4%37.2%33.2%52.5%51.7%2625242322212019181716151410th:<0.1%<0.1%<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%<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%0.698%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%7.06%7.32%90th:33.2%35.3%35.6%36.0%34.5%32.9%33.5%33.9%31.1%27.2%27.4%26.6%26.5%95th:53.1%53.7%54.7%55.3%53.5%52.5%51.2%52.4%50.2%44.9%44.9%44.9%44.4%1312111098765432110th:<0.1%<0.1%<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%<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%<0.1%0.900%75th:7.20%7.12%6.63%8.59%7.89%7.35%7.42%7.17%7.21%7.03%7.65%6.75%7.20%90th:25.5%26.1%25.4%31.0%26.8%26.5%26.0%25.9%26.9%26.1%27.0%27.2%27.3%95th:44.3%44.4%44.2%48.6%45.7%44.3%43.4%43.6%44.9%43.6%44.8%45.6%45.5%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, thereis a 25 percent probability that seleniumconcentrations in mallard eggs are high enough to cause negative reproductive effects in 37.3 percent of the exposed mallard population inhabiting that segment ofBlack Creek.b – Segment 39 is the immediate receiving water for Morrow Generating Site. Segment 1 is farthest downstream from the immediatereceiving water. The 39segments 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 Methodolo gy Limitations and Assumptions

The limitations and assumptions of the ecol ogical 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 thatsupport the nationalscale ecological risk model. The assumpti ons listed for the case study water quality

model in Appendix G apply to the Black Cree k case study ecological risk model. As

discussed in Section 8 of the EA report, th e case study models do incorporate available

data regarding background pollu tant concentrations and pollu tant loading contributions

from non-steam-electric point sources. For the Black Creek case study, however, EPA

did not identify sufficient STORET monitori ng data to represent upstream pollutant

contributions, and did not identify any upstr eam non-steam-electric point sources with

loadings for the modeled pollutants. EPA therefore assumed pollutant concentrations

of zero within the water co lumn 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 (represe ntative 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 ma y not reflect potential impacts to other

species that consume primarily fish rather than invertebrates, and that may show

differential sensitivity. The literature suggests that ma llards are among the most

sensitive bird species to selenium [Chapman et al ., 2009]. Therefore, use of these

exposure-response functions re sults in an environmenta lly protective estimate of

reproductive risk among the fish and avia n 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 simu ltaneously. 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 im pacts the receptors. For example, EPA did

not consider the impact of mercury on the uptake or toxicity of selenium. There is

evidence in the literatu re that these two compounds inte ract 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 syne rgistic 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 cons ideration of only selenium-driven impacts

in this analysis likely results in an underestimation of th e 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 potential ly overestimates the dietary

intake of selenium (because invertebrates te nd to bioaccumulate selenium to a higher

degree than submerged aquatic vegetation, a nother component of mallard diets). EPA

also assumed that the diets of fish and malla rds consisted entirely of aquatic organisms

that inhabit the modeled waterbodies. These assumptions result in an environmentally

protective estimation of diet ary 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 methodol ogy limitations/assumptions applicable to case

study modeling performed using EPA’s Water Qu ality Analysis Simulation Program (WASP).

This appendix also presents additional informati on regarding the site-speci fic design, site-specific

input parameters ( e.g. , background pollutant concentrations, U.S. Geological Survey (USGS) time

series flow data, steam electr ic 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 Modeli ng of Aquatic Systems in Support of the Final

Steam Electric Power Generating Industry En vironmental Assessment” (DCN SE05570) ( Case

Study Water Quality Modeling Memorandum ).

C ASE 

# S TUDY 

# M ODEL 

# S ETUP



# – A LL 

# M ODELS



# This section of the appendix focuses on the development of the case study models,

including the limitations/assum ptions , input parameters, and methodologi es 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 WA SP model calculates the

water column and benthic pollutant concentratio ns of the eight modeled pollutants using userdefined parameters and default assumption va lues. Table G-1 presents the WASP default

parameters and values that EPA us ed 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 se diment layer, except for the Lake Sinclair

model where benthic layers are not simulated. Fo r 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 a nd suspended solids. EPA selected the suspended

sediment-water (Kd

sw 

# ) partition coefficient for each of the ei ght 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 Powe r 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 Paramete rs – All Models

Input Parameter Description Value Used Units

Silts and Fines Density WASP default density for silts/fines 2.650 g/cm 3



# Sand Density WASP default density for sand 2.650 g/cm 3



# Organic Solids Density WASP default density for organic solids 1.350 g/cm 3



# fcritcoh Critical cohesive sediment fraction; above which

sediment bed acts cohesively 0.200 (fraction)

vRCohMult Shear stress multiplier for cohesive resuspension 2.500 g/m 2 

# /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/m 2



# TAU_cD1_si b 

# Lower critical shear stress for silt; below which

deposition is maximum 3.500 or 5.000 N/m 2



# TAU_cD2_si b 

# Upper critical shear stress for sand; above which

deposition is zero 7.000 or 10.000 N/m 2



# TAU_cD1_sa Lower critical shear stress for sand; below which

deposition is maximum 4.000 N/m 2



# TAU_cD2_sa Upper critical shear stress for sand; above which

deposition is zero 5.000 N/m 2



# TAU_cD1_PO b 

# Lower critical shear stress for organic solids; below

which deposition is maximum 3.500 or 5.000 N/m 2



# TAU_cD2_PO b 

# Upper critical shear stress for organic solids; above

which deposition is zero 7.000 or 10.000 N/m 2



# Acronyms: g/cm 3 

# (grams per cubic centimeter); g/m 2 

# /sec (grams per square meter per second); mm (millimeter);

N/m 2 

# (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/m 2 

# , 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/m 2 

# 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/m 2 

# 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/cm 3 

# )

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 STOR ET 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



# E QUATION 

# G-1

C

os 

# = TOC × f

os



# E QUATION 

# G-2

C sand 

# = ሺTSS	‐	C

os 

# ሻ × f sand



# E QUATION 

# G-3

C sf 

# = ሺTSS	‐	C

os 

# ሻ × f sf



# Where:

C

os 

# = Initial concentra tion of organic solids

(mg/L) Output from Equation G-1

C sand 

# = Initial concentration of sands (mg/L) Output from Equation G-2

C sf 

# = Initial concentration of silts/f ines (mg/L) Output from Equation G-3

TOC = Total organic carbon (mg/L) S ite-specific value derived from

STORET monitoring data

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

STORET monitoring data

f

os 

# = Fraction of total organic carbon that is

organic solids (unitless) Model assumption value of 0.5

f

sand 

# = Fraction of total suspended solids

composed of sands Model assumption value of 0.05

f

sf 

# = 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 ca librated the model outputs by manipulating one

sediment transport parameter, ‘Critical Shear St ress for Erosion of Cohe sive Bed’ (defined as

‘TAUcritcoh’ in WASP), until the modeled TSS c oncentrations 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 St ress 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 sometim es observed during high

1 

# If EPA observed a significant diff erence 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 pe riod. These large spikes we re an indication that

too much sediment was present in the modeled be nthic 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 along side the actual observed

results from STORET monitoring data as anothe r check in the calibration process. The initial

concentrations of the or ganic solids, sands, and s ilts/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 pr esented in the case study modelspecific sections of this appendix. The Case Study Water Quality Modeling Memorandum further

describes the methodology for calcu lating and incorporating steam electric power plant loadings

data into the WASP models.

Non-Steam Electric Loadings. EPA incorporated pollutant load ings and/or concentrations

data from Discharge Monitoring Reports (DMR), the Toxics Rel ease 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 th e modeling area. STORET monitoring data were

incorporated to account for c ontributions upstream of the m odeling boundaries and for use in

calibration. For the modeled pollutants (not incl uding TOC and TSS), EPA converted the average

concentration or annual load to a daily mass loading. 2 

# Each case study mode l-specific section of

this appendix presents the non-steam electric polluta nt loadings incorporated into the model. The

Case Study Water Quality Modeling Memorandum further describes the methodology for

collecting, assessing, and incorpor ating DMR and TRI pollutant lo adings data into the WASP

models.

WASP Output Analysis Methodology

The WASP models generate output data for po llutant concentration (total, dissolved, and

sorbed) in each water column and benthic segm ent on a daily output time step. For the purposes

of assessing the baseline impacts and the improveme nts under the final rule, EPA used the baseline

and regulatory option WASP model outputs from the period after th e 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 bo th based on the same underlying flow data, meaning that the

differences in modeled pollutant concentrations ar e solely attributable to the pollutant loading

reductions under the final rule.

2 

# EPA converted the average concentration calculated fro m the STORET monitoring data to a mass loading using

the average annual flow rate for the stream r each 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 th e 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 downst ream of the steam electric power plant(s)

that showed any exceedances of these benchmar ks at any point during the modeling period.

Wildlife Assessment. The WASP models generate daily po llutant concentrations in the

upper and lower benthic sediment segments with in the models. EPA quantified the impact to

benthic organisms as the percent of days wher e the total sediment c oncentration 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 downst ream of the steam electric power plant(s)

that showed any exceedances of these CSCL s 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 co lumn concentrations to “threshold” water

concentrations that would result in exceedances of no effect hazard conc entrations (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 averag e 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 methodol ogy 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 aver age concentrations to “threshol d” 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 qua lity 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 con centrations 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 pollu tant loadings and normalized flow rates

from the steam electric power plants. Un like the water quality module, however, the

case study models do account for temporal va riability 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 mode ls are not representative of the total

pollutant loadings from steam electric pow er 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 wa ter 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 m odeling methodology incorporates the following

limitations and assumptions:

 

# The models assume that pollutant contri butions from background sources and other

point and nonpoint sources are constant over the entire modeling period. This

assumption reduces the variability in modele d 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 loadi ngs data to represent other point source

dischargers. In DMR, facili ties are required to report lo adings 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 pa rt of their NPDES permit. TRI collects

facility-reported estimates of wastewater lo adings data for both direct and indirect

dischargers. The TRI releases database does not include lo adings from facilities with

total annual chemical releas es of less than 500 lbs a nd incorporates assumptions

regarding plants with annual releases of less than 1,000 lbs. This limitation results in

a potential underestimation of pollutant lo adings from smaller point sources. Other

limitations of the data collected in TRI include the following: small establishments

are not required to report, nor are facilitie s 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 ar e identified by NAICS

code, not point source category; and TRI re quires 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 purpos es 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 con centrations at the time and location of

monitoring were higher or lower th an 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 output s 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 assu med 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 magnit ude of these impacts and improvements.

 

# By incorporating wildlife, human health, and ecological risk analyses, the models

incorporate all of the limitations and assu mptions described for those analyses (see

Appendices D, E, and F).

G-8

# Appendix G—Overview of Case Study Modeling Setup and Outputs



# C ASE 

# S TUDY 

# M ODEL 

# S ETUPS AND 

# O UTPUTS 

# – B LACK 

# C REEK



# , MS

This section presents information regarding the site-specific desi gn, site-specific input

parameters ( e.g. , background pollutant concentrations, US GS 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 receiv ing water (COMID 18104316), as defined by the

IRW model, and extends approximately 95 miles dow nstream 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 revisi on to the steam electric ELGs)

and extends through 2036, covering a period of 55 years. Base d 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 Cr eek stream gage data from Ga ge 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 US GS stream gage to represent inflow from

Cypress Creek, a significant tributary to the Bl ack 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 contri buting 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 stre am gages into the model to complete a full record

of flow data for the entire modeling period. For a ll 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 m odeled from Morrow

Generating Plant at the evaluated wastestream leve l, 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 Bl ack Creek WASP model

boundaries calculated using availa ble 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 assu med 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 manipulat ing the sediment transport parameters until

the modeled concentrations in the benthic segm ents closely matched the available sediment

concentration monitoring data derived from STOR ET. 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 il lustrate 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 Cr eek revealed that average wate r column concentrations of

three pollutants (cadmium, selenium, and thalliu m) 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 Generati ng Site (including the immediate receiving

water) for baseline and following compliance with the final rule, resp ectively. Table G-11 and

Table G-12 present the total miles with averag e 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 modeli ng 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 Gene rating Station. All analyses of the WASP model outputs

were performed on the baseline output after the assumed compliance date.



# G-11Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-3. USGS Stream Gages with FlowData Used in Black Creek WASP ModelGage IDUSGS GageLocationStream Flow Record PeriodCumulative DrainageArea Represented byGage(sq km)Model BoundaryCumulative DrainageArea at ModelBoundary(sq km)Scale Factor2479130Black Creek nearBrooklyn, MSFull Record from 10/01/1970- 04/14/2014929Black Creek3790.4082479155Cypress Creek nearJanice, MSFull Record from 10/01/1966- 04/15/2014138Cypress Creek1581.143Acronyms: USGS (U.S. Geological Survey).Table G-4. Stream Flow Data Periods – Black Creek WASP ModelModeling PeriodCorresponding StreamFlow Data PeriodBlack Creek (Gage ID 2479130)01/01/1982 - 09/30/201301/01/1982 - 09/30/201310/01/2013 – 12/31/202010/01/2005 – 12/31/201201/01/1998 - 09/30/202901/01/1982 - 09/30/201310/01/2029 – 12/31/203610/01/2005 – 12/31/2012Cypress Creek (Gage ID 2479155)01/01/1982 - 09/30/201301/01/1982 - 09/30/201310/01/2013 – 12/31/202010/01/2005 – 12/31/201201/01/1998 - 09/30/202901/01/1982 - 09/30/201310/01/2029 – 12/31/203610/01/2005 – 12/31/2012G-12Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-5. Pollutant Loadings - Morrow Generating SiteWastestreamPollutant Loadings (g/day)AsCdCuNiPbSeTlZnBaselineaFGD Wastewater6.87101.8819.68794.504.221,057.2212.431,259.97Fly AshTransportWater---­-­---­-­---­Bottom Ash Transport Water3.681.024.5016.933.391.8717.2613.83Combustion Residual Leachate6.291.661.247.61--18.190.1934.52Total16.84104.5625.42819.037.611,077.2729.881,308.32Final RulebFGD Wastewater5.283.813.425.703.075.188.8718.07Fly AshTransportWater---­-­---­-­----Bottom AshTransportWater---­-­---­-­---­Combustion Residual Leachate6.291.661.247.61--18.190.1934.52Total11.575.474.6613.323.0723.379.0652.59Acronyms: 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-13Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-6. Pollutant Contributions from STORETMonitoring Data – Black Creek WASP ModelModel BoundaryModel BoundaryCOMIDStation ID(s) (lat, long)ParameterAverage Concentration(μg/L)aMass Loading(g/day)bClear Creek18104458NLA06608-2010 (31.20,-89.30)TOC4,420.00-­Little Black Creek18104706PA361 (31.09,-89.49)TOC7,400.00-­TSS4,642.86-­Big Creekc18104940PA043 (31.07,-89.27)TOC10,000.00-­TSS7,000.00-­Big Creekc18104992PA240 (31.07,-89.17)PA360 (31.14,-89.24)TOC10,333.33-­TSS4,666.67-­Cypress Creek18108034OWW04440-HBN8 (31.02,-89.01)PA056 (31.03,-89.02)TSS10,000.00-­TOC18,000.00-­Hickory Creek18106316112D33 (30.97,-88.97)TOC3,000.00-­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 calculated and incorporatedthe weighted average concentration across the monitoring stations (weighted bynumber 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 theaverage annual flow rate for thestream reach represented bythe monitoring station(s).c – There are two distinct tributary systems that are identified as “Big Creek” inthe National Hydrography Dataset Plus (NHDPlus Version 1) database.G-14Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-7. Organic Solids, Sands, and Silts/Fines Inputs – Black Creek WASP ModelModel BoundaryModel BoundaryCOMIDOrganic Solids Concentration(mg/L)aSands Concentration(mg/L)bSilts/Fines Concentration(mg/L)cBlack Creekd181043163.430.7814.74ClearCreek181044582.21**Little Black Creek181047063.700.234.41Big Creeke181049405.000.356.65BigCreeke181049925.170.234.43Cypress Creek181080345.000.9017.10Hickory Creek181063161.50**All Other InflowsfN/A3.760.438.14Acronyms: N/A (Not Applicable).*–No TSSresultsavailable. The ‘All OtherInflows’concentrationwas usedinthis scenario.a –Theorganic solidsconcentrationwas calculatedusingEquationG-1andtheSTORETmonitoringdatapresented inTableG-6.b– The sandsconcentrationwas calculatedusing EquationG-2and the STORET monitoringdatapresented inTableG-6.c –The silts/fines concentration was calculatedusing EquationG-3andthe STORET monitoringdatapresentedin Table G-6.d–Theorganic solids, sands, andsilts/finesconcentrationspresented for this segment wereused as theinitial surfacewaterconditions.e –There are two distinct tributary systems that are identifiedas “BigCreek”inthe National HydrographyDatasetPlus(NHDPlusVersion1)database.f– For tributaries whereboundaryconcentrationsfromSTORET monitoringdatawerenotavailable, EPA assumed the averageboundary concentrationfromalltributaries enteringthe modeling area.G-15Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-8. Sediment Transport Parameters – Black Creek WASP ModelInput ParameterValue UsedUnitsTAUcritcoh3.5N/m2TAU_cD1_sia3.5N/m2TAU_cD2_sia7.0N/m2TAU_cD1_POa3.5N/m2TAU_cD2_POa7.0N/m2Note: Table G-1 presents additional solids constants and sediment transport parameters that are used ineach of the case study models.a – This parameter is a WASP model default based on the value of the ‘TAUcritcoh’ parameter.G-16Appendix G—Overview of Case Study Modeling Setup and OutputsFigure G-2. Modeled Concentrations in Black Creek Water Column at Morrow Generating Site Immediate Receiving Water(Total Cadmium, Dissolved Cadmium)G-17Appendix G—Overview of Case Study Modeling Setup and OutputsFigure G-3. Modeled Concentrations in Black Creek Water Column at Morrow Generating Site Immediate Receiving Water(Total Arsenic, Total Thallium)G-18Appendix G—Overview of Case Study Modeling Setup and OutputsFigure G-4. Modeled Concentrations in Black Creek Water Column at Morrow Generating Site Immediate Receiving Water(Total Selenium)G-19Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-9. Average Water Column Concentrations Downstream of Morrow Generating Site at BaselineSegment DataAverage Total Water Column Concentration over Modeling Period (μg/L)aSegment IDSegment NameSegment Length(mi)DistanceDownstream(mi)AsCdCuPbNiSeTlZn39Black Creek/ IRW1.641.640.08330.60450.14070.04984.23305.64970.15107.721738Black Creek1.443.080.05430.40950.09420.03462.78903.73620.09895.241037Black Creek2.235.310.05210.31720.07740.02262.52983.31950.09263.942636Black Creek2.687.990.04450.28830.06930.02182.20092.90670.07983.635935Black Creek0.938.920.04500.31140.07350.02492.26283.00740.08123.968934Black Creek2.1011.010.04200.29600.06960.02402.12552.82910.07603.786333Black Creek1.8912.900.04830.62510.12200.06253.02844.27970.09886.365132Black Creek1.6814.580.04760.67120.13070.06943.12244.45100.10007.405731Black Creek1.8416.430.03130.58510.10740.06192.34123.43410.06956.225130Black Creek1.4817.900.02820.39990.07830.04001.88572.68700.05974.522529Black Creek1.4419.350.02410.32750.06500.03241.59022.25460.05093.742628Black Creek2.6421.990.03960.94090.18160.10953.47355.21320.096912.611927Black Creek2.0924.080.03640.76420.14890.08663.00674.45460.08689.934426Black Creek2.6626.740.03480.68550.13440.07642.79464.11240.08218.765025Black Creek1.3128.050.03981.10030.21310.13833.89275.97340.095114.404524Black Creek1.0729.120.04131.20140.23110.15324.13716.38330.099915.767823Black Creek2.8631.980.04251.30700.24980.16884.38206.79890.104517.221222Black Creek3.0235.000.04251.30560.24990.16904.38616.80230.104817.225221Black Creek1.5936.590.03821.11680.21470.14313.84835.92760.093114.672620Black Creek2.5039.090.03961.21330.23190.15694.07716.32000.097715.971219Black Creek1.9841.070.03991.23270.23520.15964.12226.39560.098616.226718Black Creek4.2145.290.03491.11060.21140.14513.66605.70480.087314.581117Black Creek2.6247.910.03150.98200.18720.12763.27305.08230.078312.861016Black Creek2.7550.660.02990.93540.17800.12183.10874.83130.074312.259115Black Creek2.0952.750.03091.03010.19450.13573.31265.18420.078213.5792G-20Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-9. Average Water Column Concentrations Downstream of Morrow Generating Site at BaselineSegment DataAverage Total Water Column Concentration over Modeling Period (μg/L)aSegment IDSegment NameSegment Length(mi)DistanceDownstream(mi)AsCdCuPbNiSeTlZn14Black Creek4.5557.300.03051.00670.19030.13253.24985.08220.076913.257113Black Creek2.3559.650.03000.98220.18600.12903.19034.98200.075612.932612Black Creek2.1461.790.01940.25140.05690.02081.45242.06050.04093.050711Black Creek2.0163.800.01920.24670.05580.02111.42832.02540.04022.999110Black Creek4.0067.800.02690.50340.10330.05652.21243.24810.06046.45489Black Creek1.8069.610.02820.62480.12420.07472.47623.69020.06558.14678Black Creek3.5073.100.02650.56200.11250.06622.27823.38750.06107.31747Black Creek3.0276.120.02610.54800.10990.06422.23463.32010.06007.13656Black Creek3.3379.450.02610.55510.11090.06502.24723.34810.06037.21155Black Creek3.1682.610.02600.54750.10960.06392.23013.31990.05997.11444Black Creek3.3685.970.02630.56580.11290.06662.27683.39700.06097.37153Black Creek1.9087.870.02480.46460.09470.05172.03542.98170.05575.96872Black Creek3.6691.540.02410.42790.08770.04621.94062.82220.05365.44961Black Creek/ End3.8595.380.02470.47990.09430.04922.03622.97580.05565.7478Acronyms: IRW (Immediate receiving water).a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modeling period after the assumedcompliance date.G-21Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-10. Average Water Column Concentrations Downstream of Morrow Generating Site Under Final RuleSegment DataAverage Total Water Column Concentration over Modeling Period (μg/L)aSegment IDSegment NameSegment Length(mi)DistanceDownstream(mi)AsCdCuPbNiSeTlZn39Black Creek/ IRW1.641.640.05750.03220.02610.02040.07020.12500.04600.316738Black Creek1.443.080.03750.02180.01750.01410.04640.08280.03010.215337Black Creek2.235.310.03600.01690.01440.00920.04190.07340.02820.161536Black Creek2.687.990.03080.01530.01290.00890.03660.06440.02430.148535Black Creek0.938.920.03110.01660.01360.01020.03780.06690.02470.162934Black Creek2.1011.010.02900.01580.01290.00980.03550.06290.02320.155533Black Creek1.8912.900.03350.05320.02730.02740.10160.17660.03090.642032Black Creek1.6814.580.03300.05450.02860.03010.09720.17170.03120.646031Black Creek1.8416.430.02170.04690.02330.02690.07780.13920.02170.568930Black Creek1.4817.900.01960.03350.01710.01740.06350.11070.01870.388329Black Creek1.4419.350.01670.02740.01420.01400.05340.09270.01590.314328Black Creek2.6421.990.02720.06390.03580.04600.09160.17180.03010.723827Black Creek2.0924.080.02490.05360.03000.03660.08230.15180.02700.607026Black Creek2.6626.740.02390.04910.02740.03230.07840.14340.02550.556625Black Creek1.3128.050.02790.10610.04420.06070.19960.34540.03131.355224Black Creek1.0729.120.02890.12050.04860.06750.22330.38800.03301.549123Black Creek2.8631.980.02980.13390.05300.07460.24370.42530.03471.727822Black Creek3.0235.000.02980.13490.05340.07480.24670.43050.03481.742721Black Creek1.5936.590.02680.12140.04690.06390.22910.39760.03111.570120Black Creek2.5039.090.02780.12760.05000.06970.23510.40990.03251.650319Black Creek1.9841.070.02800.12910.05070.07090.23700.41370.03291.671018Black Creek4.2145.290.02450.11760.04580.06430.21430.37470.02911.524617Black Creek2.6247.910.02210.10290.04040.05650.18810.32850.02611.3331G-22Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-10. Average Water Column Concentrations Downstream of Morrow Generating Site Under Final RuleSegment DataAverage Total Water Column Concentration over Modeling Period (μg/L)aSegment IDSegment NameSegment Length(mi)DistanceDownstream(mi)AsCdCuPbNiSeTlZn16Black Creek2.7550.660.02090.09880.03860.05400.18210.31540.02481.278415Black Creek2.0952.750.02170.10920.04220.06020.19510.34230.02611.417514Black Creek4.5557.300.02140.10850.04160.05900.19370.34210.02571.407013Black Creek2.3559.650.02100.10680.04080.05740.19210.33850.02531.386412Black Creek2.1461.790.01360.02360.01180.00900.07290.11760.01340.275211Black Creek2.0163.800.01340.02320.01160.00950.07160.11570.01320.273710Black Creek4.0067.800.01870.05140.02230.02490.12310.20370.02000.63759Black Creek1.8069.610.01970.06520.02710.03300.14850.24200.02180.81578Black Creek3.5073.100.01850.05850.02450.02910.13520.22220.02030.72967Black Creek3.0276.120.01820.05710.02400.02820.13220.21810.02000.71136Black Creek3.3379.450.01830.05800.02420.02860.13330.22010.02010.72225Black Creek3.1682.610.01820.05680.02390.02810.13140.21740.02000.70664Black Creek3.3685.970.01840.05820.02450.02920.13290.22040.02030.72333Black Creek1.9087.870.01730.05100.02110.02280.12500.20410.01860.62332Black Creek3.6691.540.01690.04690.01950.02040.11960.19360.01860.57201Black Creek/ End3.8595.380.01730.04970.02080.02170.12330.19980.01860.5997Acronyms: IRW (Immediate receiving water).a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modeling period after the assumedcompliance date.G-23Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-11. Total Miles of Black Creek with Wildlife And Human Health Impacts at BaselineWildlife & Human Health Impact ThresholdsTotal Miles with Average Water Column Concentration Translating to Wildlife or Human HealthBenchmark Exceedances (mi)AsCdCuPbNiSeTlZnWL - NEHC, T3 (mink)0.000.000.000.000.0089.79No NEHC0.00WL - NEHC, T4 (eagle)0.000.000.000.000.0089.79No NEHC0.00HH - Non-Cancer Adult Subsistence0.000.000.00No RfD0.0095.3889.790.00HH - Non-Cancer Adult Recreational0.000.000.00No RfD0.0012.750.000.00HH - Non-Cancer Child Subsistence (1 to <2 y.o.)a0.0037.640.00No RfD0.0095.3895.380.00HH - Non-Cancer Child Subsistence (16 to <21 y.o)b0.000.000.00No RfD0.0089.7958.530.00HH - Non-Cancer Child Recreational (1 to <2 y.o.)a0.000.000.00No RfD0.0089.7958.530.00HH - Non-Cancer Child Recreational (16 to <21 y.o.)b0.000.000.00No RfD0.0011.430.000.00HH - Cancer Adult Subsistence0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Adult Recreational0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (6 to <11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (6 to 11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRAcronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration);Rfd (Reference dose); LECR (Lifetime excesscancer risk); y.o. (year old).a – This row represents the most sensitive child fisher cohort.b – This row represents the least sensitive child fisher cohort.G-24Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-12. Total Miles of Black Creek with Wildlife And Human Health Impacts Under Final RuleWildlife and Human Health Impact ThresholdsTotal Miles with Average Water Column Concentration Translating to Wildlife or Human HealthBenchmark Exceedances (mi)AsCdCuPbNiSeTlZnWL - NEHC, T3 (mink)0.000.000.000.000.000.00No NEHC0.00WL - NEHC, T4 (eagle)0.000.000.000.000.000.00No NEHC0.00HH - Non-Cancer Adult Subsistence0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Adult Recreational0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Subsistence (1 to <2 y.o.)a0.000.000.00No RfD0.000.0058.530.00HH - Non-Cancer Child Subsistence (16 to <21 y.o.)b0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Recreational (1 to <2 y.o.)a0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Recreational (16 to <21 y.o.)b0.000.000.00No RfD0.000.000.000.00HH - Cancer Adult Subsistence0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Adult Recreational0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (6 to <11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (6 to 11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRAcronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration);Rfd (Reference dose); LECR (Lifetime excesscancer risk); y.o. (year old).a – 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



# C ASE 

# S TUDY 

# M ODEL 

# S ETUPS AND 

# O UTPUTS 

# – E TOWAH 

# R IVER



# , GA

This section presents information regarding the site-specific desi gn, site-specific input

parameters ( e.g. , background pollutant concentrations, US GS time series flow data), model

settings ( e.g. , sediment transport parameters), and cas e study modeling results for the Etowah

River case study model.

Model Development & Input Variables

WASP Model Design. The Etowah River WASP model star ts at Plant Bowen’s immediate

receiving water (COMID 6499098), as defined by th e 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 upstrea m 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 laye rs (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 revisi on 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 lim itations 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 US GS stream gage to represent inflow from

Two Run Creek, a significant tributary to the Etow ah 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 contri buting 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 pres ents 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 stre am gages into the model to complete a full record

of flow data for the entire modeling period. For a ll other local inflows, EPA used the mean annual

flow defined in NHDPlus Version 1.

G-26

# Figure G-5. Geographic Extent and Segm entation – Etowah River WASP Model Appendix G—Overview of Case Study Modeling Setup and Outputs



# Model Input Variables. Table G-15 presents the pollutant loadings m odeled 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 poin t 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 pollu tant contributions flowing in to the Etowah River WASP

model boundaries calculated using av ailable 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 assu med 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 manipulat ing the sediment transport parameters until

the modeled concentrations in the benthic segm ents closely matched the available sediment

concentration monitoring data derived from STOR ET. 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 rev ealed 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 Rive r revealed that average water column

concentrations of three pollutants (arsenic, sele nium, 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 th e immediate receiving water) for baseline and

following compliance with the final rule, respecti vely. Table G-21 and Tabl e G-22 present the total

miles with average water column concentrations translating to exceedances of these benchmarks

for baseline and under the fina l 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-28Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-13. USGS Stream Gages with FlowData Used in Etowah River WASP ModelGage IDUSGS GageLocationStream Flow Record PeriodCumulative DrainageArea Represented byGage(sq km)Model BoundaryCumulative DrainageArea at ModelBoundary(sq km)Scale Factor02395000Etowah River nearKingston, GAPartial Record from07/18/2928 – 09/30/2013(Missing Data between10/24/1995 – 10/01/2008)4,239Etowah River3,6830.86902395120Two Run Creek nearKingston, GAFull Record from 05/02/1980– 09/30/201385Two Run Creek1301.52Acronyms: USGS (U.S. Geological Survey).Table G-14. Stream Flow Data Periods – Etowah River WASP ModelModeling PeriodCorresponding StreamFlow Data PeriodEtowah River (Gage ID 02395000)01/01/1982 - 10/23/199501/01/1982 - 10/23/199510/24/1995 - 09/30/200810/24/1967 - 09/30/198010/01/2008 - 9/30/201310/01/2008 - 9/30/201310/01/2013 – 12/31/202010/01/2005 – 12/31/201201/01/1994 - 10/23/200701/01/1982 - 10/23/199510/24/2007 - 09/30/202010/24/1967 - 09/30/198010/01/2020 - 9/30/202510/01/2008 - 9/30/201310/01/2025 – 12/31/203210/01/2005 – 12/31/2012Two Run Creek (Gage ID 02395120)01/01/1982 - 09/30/201301/01/1982 - 09/30/201310/01/2013 – 12/31/202010/01/2005 – 12/31/201201/01/1994 - 09/30/202501/01/1982 - 09/30/201310/01/2025 – 12/31/203210/01/2005 – 12/31/2012G-29Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-15. Pollutant Loadings – Plant BowenWastestreamPollutant Loadings (g/day)AsCdCuNiPbSeTlZnBaselineaFGD Wastewaterc27.56408.7478.963187.4216.934241.4349.875054.84Fly AshTransportWater---­-­---­-­---­Bottom Ash Transport Water13.793.8116.8663.4612.696.9964.6951.86Combustion Residual Leachate---------------­Total41.35412.5595.823,250.8829.624,248.42114.565,106.71Final RulebFGD Wastewater21.1815.2813.7122.8912.3120.7735.6072.51Fly AshTransportWater---­-­---­-­----Bottom AshTransportWater---­-­---­-­---­Combustion Residual Leachate----------------Total21.1815.2813.7122.8912.3120.7735.6072.51Acronyms: 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 loadings from FGD wastewateras the systems were installed, between 2008 and 2011. EPA did not model any FGD wastewater pollutant loadings before the installation of Plant Bowen’s first FGDsystem.G-30Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-16. Pollutant Contributions from STORET Monitoring Data – Etowah River WASP ModelModel BoundaryModel BoundaryCOMIDStation ID(s) (lat, long)ParameterAverage Concentration(μg/L)aMass Loading (g/day)bEtowah River649909814310011 (34.15,-84.77)1404130102 (34.15,-84.77)1404130103 (34.15,-84.77)1404130105 (34.12,-84.82)As--9,993.11Cd--1,279.89Cu--5,103.32Ni--2,909.40Pb--2,631.57Tl--5,004.55Zn--7,666.84TOC3,531.41--TSS8,775.41--Euharlee Creek64977521404140704 (34.13,-84.94)1404140701 (34.12,-84.95)Pb--1,480.69TOC6,734.53--TSS16,323.08--Two Run Creek649737414340201 (34.22,-84.97)As--693.96Cd--86.75Cu--346.98Ni--173.49Pb--138.79Tl--346.98Zn--693.96TOC7,996.03--TSS12,847.83--Connesena Creek64973061404150501 (34.24,-84.97)TOC4,191.06--TSS4,640.00--Toms Creek64997781404160201 (34.26,-84.99)TOC9,465.83--G-31Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-16. Pollutant Contributions from STORET Monitoring Data – Etowah River WASP ModelModel BoundaryModel BoundaryCOMIDStation ID(s) (lat, long)ParameterAverage Concentration(μg/L)aMass Loading (g/day)bSpring Creek64998201404160301 (34.21,-85.07)14340991 (34.21,-85.07)As--541.04Cd--67.63Cu--270.52Ni--202.89Pb--54.10Tl--270.52Zn--270.52TOC8,526.71--TSS14,434.78--Dykes Creek64997821404160401 (34.25,-85.08)1404160402 (34.26,-85.09)TOC2,350.53--TSS3,661.11--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 calculated and incorporatedthe weighted average concentration across the monitoring stations (weighted bynumber 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 theaverage annual flow rate for thestream reach represented bythe monitoring station(s).G-32Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-17. Organic Solids, Sands, and Silts/Fines Inputs – Etowah River WASP ModelModel BoundaryModel BoundaryCOMIDOrganic Solids Concentration(mg/L)aSands Concentration(mg/L)bSilts/Fines Concentration(mg/L)cEtowah River64990981.770.448.33Euharlee Creek64977523.370.8215.50Two Run Creek64973744.000.6412.20Connesena Creek64973062.100.234.41Toms Creek64997784.73**Spring Creek64998204.260.7213.71Dykes Creek64997821.180.183.48All Other InflowsdN/A3.060.519.61Acronyms: 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 EquationG-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 concentration from alltributaries entering the modeling area.Table G-18. Sediment Transport Parameters – Etowah River WASP ModelInput ParameterValue UsedUnitsTAUcritcoh3.5N/m2TAU_cD1_sia3.5N/m2TAU_cD2_sia7.0N/m2TAU_cD1_POa3.5N/m2TAU_cD2_POa7.0N/m2Note: Table G-1 presents additional solids constants andsediment transport parameters that are used in eachof the case study models.a – This parameter is a WASP model default based on the value of the ‘TAUcritcoh’ parameter.G-33Appendix G—Overview of Case Study Modeling Setup and OutputsFigure G-6. Modeled Concentrations in Etowah River Water Column at Plant Bowen Immediate Receiving Water(Total Arsenic, Total Thallium)G-34Appendix G—Overview of Case Study Modeling Setup and OutputsFigure G-7. Modeled Concentrations in Etowah River Water Column at Plant Bowen Immediate Receiving Water(Dissolved Cadmium, Total Selenium)G-35Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-19. Average Water Column Concentrations Downstream of Plant Bowen at BaselineSegment DataAverage Total Water Column Concentration over Modeling Period (μg/L)aSegmentIDSegment NameSegmentLength(mi)DistanceDownstream (mi)AsCdCuPbNiSeTlZn18Etowah River / IRW3.613.613.55210.50951.64210.66672.09281.42251.77893.745617Etowah River1.485.092.53730.35321.14840.59901.48361.00561.26642.585516Etowah River1.426.512.46250.30771.03950.43001.40910.94701.21782.200015Etowah River0.587.102.43510.29881.01630.40171.38870.93201.20252.127214Etowah River1.208.292.39590.28710.98500.36601.36010.91111.18092.031613Etowah River3.6911.992.40260.31901.05500.49241.39180.93991.19442.309312Etowah River1.0913.082.37710.31151.03540.46811.37390.92691.18052.250211Etowah River1.2914.362.35820.29761.00340.41551.35380.91081.16782.130410Etowah River0.3714.742.47420.30761.05500.42261.36320.88871.22462.21149Etowah River2.9517.692.41810.30331.03630.42461.33390.87011.19722.18618Etowah River2.7020.392.73080.55301.66591.30161.71911.16941.43874.26007Etowah River0.9021.292.68900.52561.59991.19821.67851.13801.41164.02646Etowah River1.2622.552.64580.49431.52391.08271.63341.10321.38213.75975Etowah River2.8225.382.61890.48471.49721.05591.61131.08731.36583.68304Etowah River2.1927.572.73240.64941.88521.70941.78071.20691.46855.05783Etowah River2.4830.052.68860.65361.88731.74311.76391.19811.44955.10462Etowah River1.8931.942.68920.66291.90091.77461.76961.20321.45265.15471Etowah River / End2.8134.752.65540.62821.82031.63511.72791.17041.42704.8579Acronyms: IRW (Immediate receiving water).a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modeling period after the assumedcompliance date.G-36Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-20. Average Water Column ConcentrationsDownstream of Plant Bowen Under Final RuleSegment DataAverage Total Water Column Concentration over Modeling Period (μg/L)aSegmentIDSegment NameSegmentLength(mi)DistanceDownstream(mi)AsCdCuPbNiSeTlZn18Etowah River/IRW3.613.613.54500.39001.61620.66240.99630.00721.75152.270017Etowah River1.485.092.53220.27041.13020.59600.70630.00511.24691.566816Etowah River1.426.512.45760.23551.02310.42780.67090.00481.19901.333315Etowah River0.587.102.43020.22871.00030.39980.66110.00471.18401.289114Etowah River1.208.292.39110.21970.96950.36420.64750.00461.16261.231213Etowah River3.6911.992.39780.24421.03840.49000.66270.00491.17601.400612Etowah River1.0913.082.37230.23851.01910.46570.65420.00491.16241.363611Etowah River1.2914.362.35340.22780.98760.41340.64460.00481.14991.291010Etowah River0.3714.742.30360.24011.03960.42060.67060.00461.20711.40179Etowah River2.9517.692.25170.23681.02120.42270.65600.00451.18011.38558Etowah River2.7020.392.53770.43281.64181.29650.84790.00621.41822.71587Etowah River0.9021.292.49790.41131.57681.19350.82800.00601.39152.56546Etowah River1.2622.552.45790.38661.50191.07850.80560.00591.36242.39265Etowah River2.8225.382.43310.37911.47531.05250.79470.00591.34622.34414Etowah River2.1927.572.43240.51001.85801.70330.89920.00721.44813.23273Etowah River2.4830.052.39300.51341.86021.73680.89080.00721.42953.26362Etowah River1.8931.942.39260.51971.87541.75780.89390.00731.43253.29651Etowah River/End2.8134.752.36240.49231.79551.62120.87280.00721.40723.1060Acronyms: IRW (Immediate receiving water).a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modeling period after the assumedcompliance date.G-37Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-21. Total Miles of Etowah River withWildlife And Human Health Impacts at BaselineWildlife and Human Health Impact ThresholdsTotal Miles with Average Water Column Concentration Translating to Wildlife or Human HealthBenchmark Exceedances (mi)AsCdCuPbNiSeTlZnWL - NEHC, T3 (mink)0.000.000.000.000.000.00No NEHC0.00WL - NEHC, T4 (eagle)0.000.000.000.000.000.00No NEHC0.00HH - Non-Cancer Adult Subsistence0.000.000.00No RfD0.000.0034.750.00HH - Non-Cancer Adult Recreational0.000.000.00No RfD0.000.0034.750.00HH - Non-Cancer Child Subsistence (1 to <2 y.o.)a0.000.000.00No RfD0.0034.7534.750.00HH - Non-Cancer Child Subsistence (16 to <21 y.o.)b0.000.000.00No RfD0.000.0034.750.00HH - Non-Cancer Child Recreational (1 to <2 y.o.)a0.000.000.00No RfD0.000.0034.750.00HH - Non-Cancer Child Recreational (16 to <21 y.o.)b0.000.000.00No RfD0.000.0034.750.00HH - Cancer Adult Subsistence3.61No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Adult Recreational0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (6 to <11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (6 to 11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRAcronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration);Rfd (Reference dose); LECR (Lifetime excesscancer risk); y.o. (year old).a – This row represents the most sensitive child fisher cohort.b – This row represents the least sensitive child fisher cohort.G-38Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-22. Total Miles of Etowah River with Wildlife And Human Health Impacts Under Final RuleWildlife and Human Health Impact ThresholdsTotal Miles with Average Water Column Concentration Translating to Wildlife or Human HealthBenchmark Exceedances (mi)AsCdCuPbNiSeTlZnWL - NEHC, T3 (mink)0.000.000.000.000.000.00No NEHC0.00WL - NEHC, T4 (eagle)0.000.000.000.000.000.00No NEHC0.00HH - Non-Cancer Adult Subsistence0.000.000.00No RfD0.000.0034.750.00HH - Non-Cancer Adult Recreational0.000.000.00No RfD0.000.0034.750.00HH - Non-Cancer Child Subsistence (1 to <2 y.o.)a0.000.000.00No RfD0.000.0034.750.00HH - Non-Cancer Child Subsistence (16 to <21 y.o.)b0.000.000.00No RfD0.000.0034.750.00HH - Non-Cancer Child Recreational (1 to <2 y.o.)a0.000.000.00No RfD0.000.0034.750.00HH - Non-Cancer Child Recreational (16 to <21 y.o.)b0.000.000.00No RfD0.000.0034.750.00HH - Cancer Adult Subsistence3.61No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Adult Recreational0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (6 to <11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (6 to 11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRAcronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration);Rfd (Reference dose); LECR (Lifetime excesscancer risk); y.o. (year old).a – 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



# C ASE 

# S TUDY 

# M ODEL 

# S ETUPS AND 

# O UTPUTS 

# – L ICK 

# C REEK 

# & W HITE 

# R IVER



# , IN

This section presents information regarding the site-specific desi gn, site-specific input

parameters ( e.g. , background pollutant concentrations, US GS time series flow data), model

settings ( e.g. , sediment transport parameters), and cas e 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 Rive r WASP model starts at the

convergence of the West Fork White River (C OMID 18471042) and the East Fork White River

(COMID 18446060). The model extends approximatel y 52 miles downstream to just upstream of

where the White River converges with th e Wabash River (COMID 18471318). Petersburg

Generating Station’s immediate receiving water, Lick Creek (C OMID 18471122) is approximately

3 miles downstream of the confluen ce of the East Fork and West Fo rk 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 immediat e receiving water, is represented as Segment 76

and intersects the White River between Segm ent 16 and Segment 17. The remaining model

segments represent tributary surface waters (Segment IDs 20-25), th e 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 operati ng) and extends through 2034, covering a period of 49 years.

Based on Petersburg Generating Station’s NPDES permitting cycle, EPA assumes that the plant

will achieve the limitations under the final rule by 2019.

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 Rive r stream gage data from Gage ID 033740000 to

account for the difference in drainage area between the actual gage loca tion 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 Kessi nger Ditch as a surrogate stream to represent

inflow from Lick Creek. EPA s caled the Kessinger Ditch stream gage data from Gage ID 03360895

to produce a dataset with an averag e annual flow rate that closely a pproximates 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 pres ents 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 stre am gages into the model to complete a full record

of flow data for the entire modeling period. For a ll other local inflows, EPA used the mean annual

flow defined in NHDPlus Version 1.

G-40

# Figure G-8. Geographic Extent and Segmenta tion – Lick Creek & White River WASP

Model Appendix G—Overview of Case Study Modeling Setup and Outputs



# Model Input Variables. Table G-2 5 presents the pollu tant loadings modeled from

Petersburg Generating Station at the evaluated wastestream level, both at baseline and after the

plant achieves the limitati ons under the final rule.

Table G-26 presents the pollutant loadings modeled from non-s team electric point sources

with 2011 DMR or TRI loadings which would imp act the Lick Creek and White River case study

model.

Table G-27 presents the pollutant contributi ons flowing into the Lick Creek and White

River WASP model boundaries calculated us ing 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 assu med 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 manipulat ing the sediment transport parameters until

the modeled concentrations in the benthic segm ents closely matched the available sediment

concentration monitoring data derived from STOR ET. 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 a nd/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 fo r 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 se gments 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 translati ng 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-42Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-23. USGS Stream Gages with Flow Data Used in Lick Creek and White River WASP ModelGage IDUSGS GageLocationStream Flow Record PeriodCumulative DrainageArea Represented byGage(sq km)Model BoundaryCumulative DrainageArea at ModelBoundary(sq km)Scale Factor3374000White River nearPetersburg, INFull Record from 04/01/1928- 12/11/201328,825West Fork WhiteRiver13,9230.4833374000White River nearPetersburg, INFull Record from 04/01/1928- 12/11/201328,825East Fork WhiteRiver14,8800.5163360895Kessinger Ditchnear Monroe City,INFull Record from 10/01/1992- 9/30/199864.27aLickCreek4.46b0.069cAcronyms: 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 receivingwater.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 immediate receiving water.G-43Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-24. Stream Flow Data Periods– Lick Creek and White River WASPModelModeling PeriodCorresponding StreamFlow Data PeriodWhite River (Gage ID 3374000)01/01/1986 - 12/11/201301/01/1986 - 12/11/201312/12/2013 – 12/31/201812/12/2005 – 12/31/201001/01/2002 - 12/11/202901/01/1986 - 12/11/201312/12/2029 – 12/31/203412/12/2005 – 12/31/2010Kessinger Ditch (Gage ID 3360895)01/01/1986 - 9/30/198601/01/1998 - 09/30/199810/01/1986 - 9/30/199210/01/1992 - 09/30/199810/01/1992 - 9/30/199810/01/1992 - 09/30/199810/01/1998 - 9/30/200410/01/1992 - 09/30/199810/01/2004 - 9/30/201010/01/1992 - 09/30/199810/01/2010 - 9/30/201610/01/1992 - 09/30/199810/01/2016 - 12/31/201810/01/1992 - 12/31/199401/01/2002 - 9/30/200201/01/1998 - 09/30/199810/01/2002 - 9/30/200810/01/1992 - 09/30/199810/01/2008 - 9/30/201410/01/1992 - 09/30/199810/01/2014 - 9/30/202010/01/1992 - 09/30/199810/01/2020 - 9/30/202610/01/1992 - 09/30/199810/01/2026 - 9/30/203210/01/1992 - 09/30/199810/01/2032 - 12/31/203410/01/1992 - 12/31/1994G-44Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-25. Pollutant Loadings– Petersburg Generating StationWastestreamPollutant Loadings (g/day)AsCdCuNiPbSeTlZnBaselineaFGD Wastewaterc2.862.071.854.471.66455.144.819.80Fly AshTransportWater---­-­---­-­---­Bottom Ash Transport Water49.7825.34174.33150.9679.015.4067.21152.59Combustion Residual Leachate----------------Total52.6427.40176.18155.4380.67460.5496.27162.39Final RulebFGD Wastewater2.862.071.853.091.662.814.819.80Fly AshTransportWater---­-­---­-­----Bottom AshTransportWater---­-­---­-­---­Combustion Residual Leachate----------------Total2.862.071.853.091.662.814.819.80Acronyms: 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 pollutant loadings fromFGD wastewater as the systems were installed, between 1977 and 1996. The pollutant loadings associated with FGD systems installed before the start of themodeling period (01/01/1986) are incorporated at the beginning or the model.G-45Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-26. Pollutant Contributions fromNon-Steam Electric Point Sources – Lick Creek and White River WASP ModelFacility NameModel COMIDCityLocation (lat, long)ParameterAverage Daily Pollutant Loadings(g/day)Cu9.23Pride Mine S-321a18471050(White River)Monroe City(38.54,-87.27)Ni9.23Zn9.23a – EPA identified that this industrial facility isa direct discharger with 2011 DMR loadings.Table G-27. Pollutant Contributionsfrom STORET Monitoring Data – LickCreek and White River WASP ModelModel BoundaryModel BoundaryCOMIDStation ID(s) (lat, long)ParameterAverage Concentration(μg/L)aMass Loading(g/day)bWest Fork WhiteRiver1847104210947 (38.56,-87.24)2719 (38.56,-87.24)WWL090-0028 (35.55,-87.24)As--19,498.53Cu--74,468.84Ni--130,549.28Pb--37,390.75Zn--228,842.01TOC5,104.00--TSS104,000.00--East Fork WhiteRiver184460602619 (38.54,-87.22)As--17,881.15Cd--506.03Cu--35,794.47Ni--43,219.91Pb--20,429.79Zn--134,155.14TOC3,475.43--TSS62,087.96--G-46Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-27. Pollutant Contributionsfrom STORET Monitoring Data – LickCreek and White River WASP ModelModel BoundaryModel BoundaryCOMIDStation ID(s) (lat, long)ParameterAverage Concentration(μg/L)aMass Loading(g/day)bConger Creek184710782511 (38.52,-87.45)2513 (38.51,-87.45)WWL100-0002 (38.51,-87.44)Cu--1,045.39Pb--269.15Zn--2,736.70TOC5,700.00--TSS95,200.00--Upper RiverDeshee184710822512 (38.52,-87.53)Pb--362.50Zn--1,100.85TOC3,120.00--TSS18,600.00--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 calculated and incorporatedthe weighted average concentration across the monitoring stations (weighted bynumber 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 theaverage annual flow rate for thestream reach represented bythe monitoring station(s).G-47Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-28. Organic Solids, Sands, and Silts/FinesInputs – Lick Creek and White River WASP ModelModel BoundaryModel BoundaryCOMIDOrganic Solids Concentration(mg/L)aSands Concentration(mg/L)bSilts/Fines Concentration(mg/L)cWest Fork White River184710422.555.2098.80East Fork White River184460601.743.1058.98Conger Creek184710782.854.7690.44Upper River Deshee184710821.560.9317.67All Other InflowsdN/A2.173.5066.47Acronyms: 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 EquationG-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 concentration from alltributaries entering the modeling area.Table G-29. Sediment Transport Parameters– Lick Creek and White River WASP ModelInput ParameterValue UsedUnitsTAUcritcoh3.5N/m2TAU_cD1_sia3.5N/m2TAU_cD2_sia7.0N/m2TAU_cD1_POa3.5N/m2TAU_cD2_POa7.0N/m2Note: Table G-1 presents additional solids constants and sediment transport parameters that are used in each of thecase study models.a – This parameter is a WASP model default based on the value of the ‘TAUcritcoh’ parameter.G-48Appendix G—Overview of Case Study Modeling Setup and OutputsFigure G-9. Modeled Concentrations inLick Creek Water Column at PetersburgGenerating Station Immediate ReceivingWater (Total Cadmium, Dissolved Cadmium)G-49Appendix G—Overview of Case Study Modeling Setup and OutputsFigure G-10. Modeled Concentrations inLick Creek Water Column at PetersburgGenerating Station Immediate ReceivingWater (Total Selenium, Dissolved Copper)G-50Appendix G—Overview of Case Study Modeling Setup and OutputsFigure G-11. Modeled Concentrations inLick Creek Water Column at PetersburgGenerating Station Immediate ReceivingWater (Total Arsenic, Total Thallium)G-51Appendix G—Overview of Case Study Modeling Setup and OutputsFigure G-12. Modeled Concentrations inLick Creek Water Column at PetersburgGenerating Station Immediate ReceivingWater (Total Lead)G-52Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-30. Average Water Column Concentrations Downstream of Petersburg Generating Station at BaselineSegment DataAverage Total Water Column Concentration over Modeling Period (μg/L)aSegment IDSegment NameSegment Length(mi)DistanceDownstream(mi)AsCdCuPbNiSeTlZn76Lick Creek / IRW1.821.827.80991.426012.16232.225617.096243.031812.02677.990216White River2.534.352.17410.01693.92021.48787.97450.02170.005311.084315White River3.647.991.98420.01303.14281.03606.89400.01760.00468.391914White River3.3911.381.89880.01082.71870.77646.34290.01560.00426.880513White River3.3914.771.84980.00962.48780.63996.03500.01470.00416.069212White River3.3918.171.82940.00902.36420.56435.88190.01430.00405.625711White River4.4322.591.90380.01653.49441.45716.91690.02900.005610.218110White River1.7824.371.89900.01974.02541.87437.29950.03330.006012.37419White River3.8828.261.91060.01873.86921.74047.20150.03250.005911.74218White River3.2231.482.81650.065711.72047.884115.33970.08720.011944.42057White River2.9734.452.93780.057210.44776.591314.72310.08130.011938.20406White River2.9737.422.64710.05219.49876.068113.28680.07240.010534.90365White River2.9740.392.55500.04949.03075.732912.70970.06870.010133.10434White River2.9743.362.49860.04748.67865.478712.30550.06610.009831.72933White River2.9746.332.45690.04578.39005.264511.98470.06400.009530.55712White River2.9749.302.42650.04438.15205.074611.72640.06230.009329.57841White River / End1.1750.472.40610.04558.30715.234111.79540.06460.009530.2942Acronyms: IRW (Immediate receiving water).a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modeling period after the assumedcompliance date.G-53Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-31. Average Water Column Concentrations Downstream of Petersburg GeneratingStation Under Final RuleSegment DataAverage Total Water Column Concentration over Modeling Period (μg/L)aSegment IDSegment NameSegmentLength(mi)DistanceDownstream(mi)AsCdCuPbNiSeTlZn76Lick Creek / IRW1.821.820.43060.10930.73010.04691.28030.26170.59950.885916White River2.534.352.17110.01593.91321.48557.96690.00010.000311.079015White River3.647.991.98150.01233.13771.03466.88770.00010.00028.388214White River3.3911.381.89620.01032.71440.77546.33720.00010.00026.877113White River3.3914.771.84730.00922.48380.63926.02950.00010.00026.066312White River3.3918.171.82690.00862.36040.56365.87670.00010.00025.622911White River4.4322.591.90100.01563.48671.45566.90880.00540.000610.212310White River1.7824.371.89610.01854.01571.87227.29050.00640.000712.36659White River3.8828.261.90770.01763.85991.73867.19280.00630.000711.73528White River3.2231.482.81200.060811.68557.873515.31770.01370.001344.39057White River2.9734.452.93310.053010.41626.582814.70210.01290.001338.17916White River2.9737.422.64300.04849.47166.060413.26830.01170.001134.88125White River2.9740.392.55100.04599.00555.726112.69220.01100.001133.08314White River2.9743.362.49480.04408.65455.472412.28860.01060.001131.70903White River2.9746.332.45310.04258.36795.258511.96820.01020.001030.53242White River2.9749.302.42280.04118.12435.068911.71040.00990.001029.55391White River / End1.1750.472.40240.04218.28185.227811.77880.01000.001030.2683Acronyms: IRW (Immediate receiving water).a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modeling period after the assumedcompliance date.G-54Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-32. Total Miles of Lick Creekand White River with Wildlife And Human Health Impacts at BaselineWildlife and Human Health Impact ThresholdsTotal Miles with Average Water Column Concentration Translating to Wildlife or Human HealthBenchmark Exceedances (mi)AsCdCuPbNiSeTlZnWL - NEHC, T3 (mink)0.000.000.000.000.001.82No NEHC0.00WL - NEHC, T4 (eagle)0.000.000.000.000.001.82No NEHC0.00HH - Non-Cancer Adult Subsistence0.000.000.00No RfD0.001.821.820.00HH - Non-Cancer Adult Recreational0.000.000.00No RfD0.001.821.820.00HH - Non-Cancer Child Subsistence (1 to <2 y.o.)a0.001.820.00No RfD0.001.821.820.00HH - Non-Cancer Child Subsistence (16 to <21 y.o.)b0.000.000.00No RfD0.001.821.820.00HH - Non-Cancer Child Recreational (1 to <2 y.o.)a0.000.000.00No RfD0.001.821.820.00HH - Non-Cancer Child Recreational (16 to <21 y.o.)b0.000.000.00No RfD0.001.821.820.00HH - Cancer Adult Subsistence1.82No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Adult Recreational0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (6 to <11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (6 to 11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRAcronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration);Rfd (Reference dose); LECR (Lifetime excesscancer risk); y.o. (year old).a – This row represents the most sensitive child fisher cohort.b – This row represents the least sensitive child fisher cohort.G-55Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-33. Total Miles of Lick Creekand White River with Wildlife And Human Health Impacts Under Final RuleWildlife and Human Health Impact ThresholdsTotal Miles with Average Water Column Concentration Translating to Wildlife or Human HealthBenchmark Exceedances (mi)AsCdCuPbNiSeTlZnWL - NEHC, T3 (mink)0.000.000.000.000.000.00No NEHC0.00WL - NEHC, T4 (eagle)0.000.000.000.000.000.00No NEHC0.00HH - Non-Cancer Adult Subsistence0.000.000.00No RfD0.000.001.820.00HH - Non-Cancer Adult Recreational0.000.000.00No RfD0.000.001.820.00HH - Non-Cancer Child Subsistence (1 to <2 y.o.)a0.000.000.00No RfD0.000.001.820.00HH - Non-Cancer Child Subsistence (16 to <21 y.o.)b0.000.000.00No RfD0.000.001.820.00HH - Non-Cancer Child Recreational (1 to <2 y.o.)a0.000.000.00No RfD0.000.001.820.00HH - Non-Cancer Child Recreational (16 to <21 y.o.)b0.000.000.00No RfD0.000.001.820.00HH - Cancer Adult Subsistence0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Adult Recreational0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (6 to <11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (6 to 11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRAcronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration);Rfd (Reference dose); LECR (Lifetime excesscancer risk); y.o. (year old).a – 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



# C ASE 

# S TUDY 

# M ODEL 

# S ETUPS AND 

# O UTPUTS 

# – O HIO 

# R IVER



# , PA/WV/OH

This section presents information regarding the site-specific desi gn, site-specific input

parameters ( e.g. , background pollutant concentrations, US GS time series flow data), model

settings ( e.g. , sediment transport parameters), and cas e study modeling results for the Ohio River

case study model.

Model Development & Input Variables

WASP Model Design. The Ohio River WASP model st arts 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 Oh io River (COMID 3821113) from a large surface

impoundment named Little Blue Run. Approximate ly 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 Pl ant 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 upstr eam segment. The immediate receiving waters

of the Bruce Mansfield plant and the W.H. Sa mmis plant are located at Segment ID 13 and 9,

respectively. The remaining model segments repr esent tributary surface waters (Segment IDs 18­

28), the upper benthic layers (Seg ment 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 y ears. Based on their NPDES permitting cycles,

EPA assumes that Bruce Mansfiel d and W.H. Sammis plants will achieve the limitations under the

final rule by 2020 and 2021, resp ectively. EPA focused the assessment of the improvements under

the final rule on the period after the 2021 assu med 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 th e 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 actua l gage location and the point wh ere the contribu ting 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 WA SP modeling area, as described below:

 

# EPA scaled the Little Beaver Creek st ream 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 fl ows enter the modeling area.

 

# EPA scaled the Yellow Creek stream ga ge data from Gage ID 03110000 to account

for the difference in drainage area betw een the actual gage location and the point

where the contributing flows enter the modeling area.

G-57

# Figure G-13. Geographic Extent and Segm entation – 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 betw een 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 pres ents 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 pe riod. 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 m odeled from Bruce

Mansfield plant at the evaluated wastestream level, both at baseli ne and after the plant achieves

the limitations under the final rule. Table G-37 presen ts the pollutant loadi ngs 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-s team electric point sources

with 2011 DMR or TRI loadings which would impact the Ohio River case study model.

Table G-39 presents the pollutant contributi ons flowing into the Ohio River WASP model

boundaries calculated using availa ble 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 assu med 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 manipulat ing the sediment transport parameters until

the modeled concentrations in the benthic segm ents closely matched the available sediment

concentration monitoring data derived from STOR ET. 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 reveal ed water quality benchmark exceedances in

the W.H. Sammis plant immediate receiving water a nd/or in downstream se gments for arsenic and

lead. Figure G-14 illustrates the water concentrati on 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 immedi ate receiving water and/or downstream segments

would trigger exceedances of human health be nchmarks. 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 fina l rule. Table G-42 and Table G-43 illustrate the

average modeled pollutant concentration in eac h water column segment downstream of Bruce

Mansfield plant (including the Bruce Mansfield plan t immediate receiving water) for baseline and

following compliance with the final rule, respecti vely. Table G-44 and Tabl e G-45 present the total

miles with average water column concentrations translating to exceedances of these benchmarks

for baseline and under the fina l rule, respectively.

10 

# To improve clarity, Figure G-14 and Figure G-15 presen t the baseline water column concentrations leading up to

the assumed compliance date of Bruce Mansfield plant an d W.H. Sammis plant. All analyses of the WASP model

outputs were performed on the baseline output after the assumed compliance date.



# G-59Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-34. USGS Stream Gages with FlowData Used in Ohio River WASP ModelGage IDUSGS GageLocationStream Flow Record PeriodCumulative DrainageArea Represented byGage(sq km)Model BoundaryCumulative DrainageArea at ModelBoundary(sq km)Scale Factor3086000Ohio River nearSewickley, PAFull Record from 01/01/1982- 09/30/201350,475Ohio River58,9471.1703109500Little Beaver CreekFull Record from 01/01/1982- 09/30/20131,286Little Beaver Creek1,3451.0463110000Yellow CreekFull Record from 01/01/1982- 09/30/2013382Yellow Creek6121.6003108000Raccoon CreekFull Record from 01/01/1982- 09/30/2013464Raccoon Creek4771.028Acronyms: USGS (U.S. Geological Survey).G-60Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-35. Stream Flow Data Periods – Ohio River WASP ModelModeling PeriodCorresponding StreamFlow Data PeriodOhio River (Gage ID 3086000)01/01/1982 - 09/30/201301/01/1982 - 09/30/201310/01/2013 – 12/31/202010/01/2005 – 12/31/201201/01/1998 - 09/30/202901/01/1982 - 09/30/201310/01/2029 – 12/31/203610/01/2005 – 12/31/2012Little Beaver Creek(Gage ID3109500)01/01/1982 - 09/30/201301/01/1982 - 09/30/201310/01/2013 – 12/31/202010/01/2005 – 12/31/201201/01/1998 - 09/30/202901/01/1982 - 09/30/201310/01/2029 – 12/31/203610/01/2005 – 12/31/2012Yellow Creek (Gage ID 3110000)01/01/1982 - 09/30/201301/01/1982 - 09/30/201310/01/2013 – 12/31/202010/01/2005 – 12/31/201201/01/1998 - 09/30/202901/01/1982 - 09/30/201310/01/2029 – 12/31/203610/01/2005 – 12/31/2012Raccoon Creek (Gage ID 3108000)01/01/1982 - 09/30/201301/01/1982 - 09/30/201310/01/2013 – 12/31/202010/01/2005 – 12/31/201201/01/1998 - 09/30/202901/01/1982 - 09/30/201310/01/2029 – 12/31/203610/01/2005 – 12/31/2012G-61Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-36. Pollutant Loadings – Bruce Mansfield PlantWastestreamPollutant Loadings (g/day)AsCdCuNiPbSeTlZnBaselineaFGD Wastewater29.09431.4283.343,364.2717.874,476.7552.635,335.30Fly AshTransportWater---­-­---­-­---­Bottom Ash Transport Water50.2113.8661.38231.0146.2125.46235.52188.79Combustion Residual Leachate---------------­Total79.30445.28144.723,595.2864.084,502.21288.155,524.09Final RulebFGD Wastewater22.3516.1314.4824.1612.9921.9337.5876.53Fly AshTransportWater---­-­---­-­----Bottom AshTransportWater---­-­---­-­---­Combustion Residual Leachate---------------­Total22.3516.1314.4824.1612.9921.9337.5876.53Acronyms: 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-62Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-37. Pollutant Loadings – W.H. Sammis PlantWastestreamPollutant Loadings (g/day)AsCdCuNiPbSeTlZnBaselineaFGD Wastewaterc5.824.203.779.093.38925.469.7819.92Fly AshTransportWater---­-­---­-­---­Bottom Ash Transport Water353.6197.59432.311,626.99325.44179.301,658.761,329.69Combustion Residual Leachate2.340.620.462.83-6.750.0712.82Total361.77102.41436.541,638.91328.821,111.511,668.611,362.43Final RulebFGD Wastewater5.824.203.776.293.385.719.7819.92Fly AshTransportWater---­-­---­-­----Bottom AshTransportWater---­-­---­-­---­Combustion Residual Leachate2.340.620.462.83-6.750.0712.82Total8.164.824.239.123.3812.469.8532.74Acronyms: 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 loadings from FGDwastewater as the systems were installed, between March and May2010. EPA did not model any FGD wastewater pollutant loadings before the installation of W.H.Sammis plant’s first FGD system.G-63Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-38. Pollutant Contributions from Non-Steam Electric Point Sources–Ohio River WASP ModelFacility NameModel COMIDCity, StateLocation (lat, long)ParameterAverage Daily PollutantLoadings (g/day)City of Chestera3821165(Ohio River)Chester, WV(40.61,-80.57)Cu32.63Pb24.40Zn87.47East Liverpool WWTPa3821167(Ohio River)East Liverpool, OH(40.62,-80.58)Cu13.96Zn375.00Town of Newella3821149(Ohio River)Newell, WV(40.62,-80.61)Cu3.92Pb1.49Zn6.80Wellsville STPa3821273(Ohio River)Wellsville, OH(40.60,-80.66)Cu48.94Pb2.64Zn134.64Hancock County PSDa3821301(Ohio River)New Cumberland, WV(40.58,-80.66)Cu4.69Pb1.57Hancock County PSD WWTPa3821355(Ohio River)New Cumberland, WV(40.51,-80.62)Cu6.05Pb0.87Zn45.16City of New Cumberlanda3824147(Ohio River)New Cumberland, WV(40.49,-80.60)Cu6.85Pb0.48Zn18.25Toronto WWTPa3824175(Ohio River)Toronto, OH(40.50,-80.61)Zn150.75G-64Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-38. Pollutant Contributions from Non-Steam Electric Point Sources–Ohio River WASP ModelFacility NameModel COMIDCity, StateLocation (lat, long)ParameterAverage Daily PollutantLoadings (g/day)City of Weirtona3824185(Ohio River)Weirton, WV(40.38,-80.61)As12.03Cd15.49Cu149.90Ni101.78Pb60.88Zn1,040.57City of Steubenville, WastewaterTreatment Planta3824195(Ohio River)Steubenville, OH(40.36,-80.61)Cu116.49Zn560.18City of Follansbeea3824211(Ohio River)Follansbee, WV(40.32,-80.60)As1.47Cd14.91Cu183.20Ni24.38Pb14.08Zn392.83Mingo Junction WTPa19453097(Cross Creek)Mingo Junction, OH(40.31,-80.61)Cu35.80City of Wellsburga19453103(Ohio River)Wellsburg, WV(40.27,80.62)As436.14Cd31.90Cu1,159.12Ni2.26Pb0.24Zn20.64CBS Beaver GroundwaterRemediationb3821033(Two Mile Run)Beaver, PA(40.69,-80.31)Zn1,772.26G-65Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-38. Pollutant Contributions from Non-Steam Electric Point Sources–Ohio River WASP ModelFacility NameModel COMIDCity, StateLocation (lat, long)ParameterAverage Daily PollutantLoadings (g/day)Horsehead Corp Monaca Smelterb3821033(Ohio River)Monaca, PA(40.67,-80.34)As16.34Cd66.43Cu190.61Pb63.10Se12.39Zn1,259.91BASF Monaca Plantb3821039(Ohio River)Monaca, PA(40.66,-80.35)Zn257.26Lyondell Chem Beaver Valleyb3821057(Ohio River)Monaca, PA(40.66,-80.36)Cu72.06Ni64.22Pb36.23Zn83.68Allegheny Technologies MidlandPlantb3821109(Ohio River)Midland, PA(40.64,-80.47)Ni441.29Heritage-WTI Inc.b3821157(Ohio River)East Liverpool, OH(40.63,-80.55)As0.84Cd0.57Cu5.42Ni2.69Pb5.00Zn48.85Homer Laughlin China Cob3821149(Ohio River)Newell, WV(40.62,-80.61)Cd1.13Ni7.71Pb0.99Se1.45Zn1,101.25G-66Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-38. Pollutant Contributions from Non-Steam Electric Point Sources–Ohio River WASP ModelFacility NameModel COMIDCity, StateLocation (lat, long)ParameterAverage Daily PollutantLoadings (g/day)Ergon West Virginia Incb3821189(Ohio River)Newell, WV(40.61,-80.63)As304.33Cu7.99Zn13.55Marsh Bellofram Corporationb3821301(Ohio River)Newell, WV(40.58,-80.65)Cu2.24Ni0.30Pb0.15Zn1.03Mountaineer ParkIncorporatedb3821301(Ohio River)Chester, WV(40.57,-80.65)Cu2,669.15Pb2,358.45Zn36,768.62Titanium Metals Corpb3824175(Ohio River)Toronto, OH(40.45,-80.61)Cu0.09Zn1.63Mittal Steel USA Weirton Incb3824175(Ohio River)Weirton, WV(40.43,-80.60)Cu385.18Ni63.48Pb182.75Se252.54Zn1,935.80Severstal Wheeling Inc -Steubenville Plantb3824211(Ohio River)Steubenville, OH(40.35,-80.61)Zn1,042.47Severstal Wheeling Inc -Follansbeeb3824211(Ohio River)Follansbee, WV(40.35,-80.61)As250.85Cd0.01Cu201.14Ni0.06Pb0.33Se3,364.80Zn460.56G-67Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-38. Pollutant Contributions from Non-Steam Electric Point Sources–Ohio River WASP ModelFacility NameModel COMIDCity, StateLocation (lat, long)ParameterAverage Daily PollutantLoadings (g/day)RG Steel Wheeling LLC BeechBottom Plantb3824211(Ohio River)Beech Bottom, WV(40.35,-80.61)As2.22Cu3.57Ni68.46Pb2.86Se5.92Zn229.79Koppers Follansbee Tar Plantb3824211(Ohio River)Follansbee, WV(40.34,-80.61)As11.94Se2.33Zn15.42Wheeling-Nisshinb3824211(Ohio River)Follansbee, WV(40.33,-80.60)Pb5.06Zn55.43Wheeling Pittsburgh SteelSteubenville South Mingob3824211(Ohio River)Mingo Junction, OH(40.32,-80.60)Cu0.73Zn9.33NGC Industries LLC A Subsidiaryc3821097(Ohio River)Shippingport, PA(40.63,-80.42)Pb0.62Whemco-Steel Castings Incc3821109(Ohio River)Midland, PA(40.63,-80.45)Ni0.76Mittal Steel USA Weirton Incc3824175(Ohio River)Weirton, WV(40.42,-80.60)Cu518.22Ni134.22Pb334.29Zn1,923.75a – 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 isa direct discharger with 2011 DMR loadings.c - EPA identified that this facility is a direct discharger with 2011 TRI loadings.G-68Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-39. Pollutant Contributions from STORET Monitoring Data – Ohio River WASP ModelModel BoundaryModel BoundaryCOMIDStation ID(s) (lat, long)ParameterAverage Concentration(μg/L)aMass Loading(g/day)bOhio River3821033WQN0902 (40.53,-80.19)Cu--175,758.13Ni--126,664.12Pb--79,371.40Zn--1,247,520.00TOC2,426.67--TSS21,434.78--Raccoon Creek3821043WQN0903 (40.63,-80.34)Cu--376.43Ni--1,663.34Pb--525.00Zn--13,504.33TOC2,232.63--TSS16,893.62--Buffalo Creek19453099O-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)TSS10,333.33--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 calculated and incorporatedthe weighted average concentration across the monitoring stations (weighted bynumber 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 theaverage annual flow rate for thestream reach represented bythe monitoring station(s).G-69Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-40. Organic Solids, Sands, and Silts/Fines Inputs – Ohio River WASP ModelModel BoundaryModel BoundaryCOMIDOrganic Solids Concentration(mg/L)aSands Concentration(mg/L)bSilts/Fines Concentration(mg/L)cOhio River38210331.211.0720.36Raccoon Creek38210431.120.8416.05Buffalo Creek3821043*0.52e9.82eAll Other InflowsdN/A1.160.8115.41Acronyms: N/A (Not Applicable).* – No TOC results available. The ‘All Other Inflows’ concentration was usedin 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 EquationG-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 concentration from alltributaries entering the modeling area.e – These concentrations were calculated using the ‘All Other Inflows’ concentration.Table G-41. Sediment Transport Parameters – Ohio River WASP ModelInput ParameterValue UsedUnitsTAUcritcoh3.5N/m2TAU_cD1_sia3.5N/m2TAU_cD2_sia7.0N/m2TAU_cD1_POa3.5N/m2TAU_cD2_POa7.0N/m2Note: Table G-1 presents additional solids constants andsediment transport parameters that are used in eachof the case study models.a – This parameter is a WASP model default based on the value of the ‘TAUcritcoh’ parameter.G-70Appendix G—Overview of Case Study Modeling Setup and OutputsFigure G-14. Modeled Concentrations in Ohio River WaterColumn at W.H. Sammis Plant Immediate Receiving Water(Total Arsenic, Total Lead)G-71Appendix G—Overview of Case Study Modeling Setup and OutputsFigure G-15. Modeled Concentrations in OhioRiver Water Column at W.H. Sammis Plant Immediate Receiving Water(Total Thallium)G-72Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-42. Average Water Column ConcentrationsDownstream of Bruce Mansfield Plant at BaselineSegment DataAverage Total Water Column Concentration over Modeling Period (μg/L)aSegmentIDSegment NameSegmentLength(mi)DistanceDownstream(mi)AsCdCuPbNiSeTlZn13Ohio River / MansfieldIRW3.313.310.00200.00822.64160.69652.45640.08670.005815.517412Ohio River3.717.020.00830.00942.81860.85862.45770.08830.005717.638411Ohio River3.2610.290.00830.01113.12270.99132.57190.09390.005920.013010Ohio River2.4012.690.00930.01453.92761.40323.01750.11180.006726.63039Ohio River / Sammis IRW3.4316.120.01580.01653.86151.46522.89460.12850.039426.88088Ohio River3.8820.000.01650.01473.60631.12812.94810.12750.040123.27387Ohio River3.4523.450.01570.01273.21230.90502.74350.12250.038019.86696Ohio River1.7625.210.01550.01213.08560.81192.69840.12000.037518.63835Ohio River1.3326.540.01570.01203.00460.75272.66890.11830.037217.85634Ohio River2.0228.560.01560.01172.95130.72282.64190.11710.036917.39053Ohio River3.0831.640.02090.01823.13090.87252.74270.18770.037119.01882Ohio River3.0634.700.02020.01833.09560.90172.66550.18360.036019.11721Ohio River / End1.8536.550.02850.01953.19280.95292.69980.18590.036219.7848Acronyms: IRW (Immediate receiving water).a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modeling period after the assumedcompliance date.G-73Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-43. Average Water Column Concentrations Downstream of Bruce Mansfield Plant Under Final RuleSegment DataAverage Total Water Column Concentration over Modeling Period (μg/L)aSegmentIDSegment NameSegmentLength(mi)DistanceDownstream(mi)AsCdCuPbNiSeTlZn13Ohio River / MansfieldIRW3.313.310.00080.00112.63930.69592.38630.00060.000815.430712Ohio River3.717.020.00720.00132.81610.85772.38750.00070.000717.535511Ohio River3.2610.290.00710.00163.11990.99002.49860.00120.000819.890610Ohio River2.4012.690.00800.00203.92411.40132.93130.00140.000926.48249Ohio River / Sammis IRW3.4316.120.00760.00213.84931.45612.78090.00160.001026.70548Ohio River3.8820.000.00800.00193.59491.12132.83370.00160.001123.12087Ohio River3.4523.450.00760.00163.20190.89952.63700.00630.001019.73426Ohio River1.7625.210.00750.00163.07560.80692.59360.00620.001018.51275Ohio River1.3326.540.00770.00182.99480.74812.56530.00610.001017.73514Ohio River2.0228.560.00770.00182.94170.71832.53930.00610.001017.27333Ohio River3.0831.640.01300.00753.12090.86742.63880.07460.001018.88682Ohio River3.0634.700.01250.00763.08550.89612.56420.07310.001018.98221Ohio River / End1.8536.550.02080.00843.18260.94682.59740.07380.001019.6433Acronyms: IRW (Immediate receiving water).a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modeling period after the assumedcompliance date.G-74Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-44. Total Miles of Ohio River withWildlife And Human Health Impacts at BaselineWildlife and Human Health Impact ThresholdsTotal Miles with Average Water Column Concentration Translating to Wildlife or Human HealthBenchmark Exceedances (mi)AsCdCuPbNiSeTlZnWL - NEHC, T3 (mink)0.000.000.000.000.000.00No NEHC0.00WL - NEHC, T4 (eagle)0.000.000.000.000.000.00No NEHC0.00HH - Non-Cancer Adult Subsistence0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Adult Recreational0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Subsistence (1 to <2 y.o.)a0.000.000.00No RfD0.000.0023.860.00HH - Non-Cancer Child Subsistence (16 to <21 y.o.)b0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Recreational (1 to <2 y.o.)a0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Recreational (16 to <21 y.o.)b0.000.000.00No RfD0.000.000.000.00HH - Cancer Adult Subsistence0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Adult Recreational0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (6 to <11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (6 to 11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRAcronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration);Rfd (Reference dose); LECR (Lifetime excesscancer risk); y.o. (year old).a – This row represents the most sensitive child fisher cohort.b – This row represents the least sensitive child fisher cohort.G-75Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-45. Total Miles of Ohio River with Wildlife And Human Health Impacts Under Final RuleWildlife and Human Health Impact ThresholdsTotal Miles with Average Water Column Concentration Translating to Wildlife or Human HealthBenchmark Exceedances (mi)AsCdCuPbNiSeTlZnWL - NEHC, T3 (mink)0.000.000.000.000.000.00No NEHC0.00WL - NEHC, T4 (eagle)0.000.000.000.000.000.00No NEHC0.00HH - Non-Cancer Adult Subsistence0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Adult Recreational0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Subsistence (1 to <2 y.o.)a0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Subsistence (16 to <21 y.o.)b0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Recreational (1 to <2 y.o.)a0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Recreational (16 to <21 y.o.)b0.000.000.00No RfD0.000.000.000.00HH - Cancer Adult Subsistence0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Adult Recreational0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (6 to <11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (6 to 11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRAcronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration);Rfd (Reference dose); LECR (Lifetime excesscancer risk); y.o. (year old).a – 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



# C ASE 

# S TUDY 

# M ODEL 

# S ETUPS AND 

# O UTPUTS 

# – M ISSISSIPPI 

# R IVER



# , MO/IL

This section presents information regarding the site-specific desi gn, site-specific input

parameters ( e.g. , background pollutant concentrations, US GS time series flow data), model

settings ( e.g. , sediment transport parameters), and cas e 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 mode l 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 upstr eam segment. The Meramec River start boundary,

which is also the Meramec plant’s immediat e 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 tributar y surface waters (Segment IDs 18-30), the upper

benthic layers (Segment IDs 31- 60), and the lower benthic laye rs (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 y ears. Based on their NPDES permitting cycles,

EPA assumes that the Meramec and Rush Island plan ts 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 assume d 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 th e upstream end of the modeling ar ea of the Mississippi River WASP

model. EPA scaled the Mississi ppi River stream gage data fr om Gage ID 07010000 to account for

the difference in drainage area between the ac tual gage location and the point where the

contributing flows enter the modeling area.

EPA used USGS stream flow data from one ot her USGS stream gages to represent inflow

from the Meramec River, a tributary to the Mi ssissippi River WASP mode ling 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 pres ents 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 stre am gages into the model to complete a full record

G-77

# Figure G-16. Geographic Extent and Segmen tation – Mississippi River WASP Model Appendix G—Overview of Case Study Modeling Setup and Outputs



# of flow data for the entire modeling period. For a ll other local inflows, EPA used the mean annual

flow defined in NHDPlus Version 1.

Model Input Variables. Table G-48 presents the pollutant loadings m odeled 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 presen ts 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-s team electric point sources

with 2011 DMR or TRI loadings which would impact the Mississippi Rive r case study model.

Table G-51 presents the pollu tant contributions flowing into the Mi ssissippi River WASP

model boundaries calculated using av ailable 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 assu med 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 manipulat ing the sediment transport parameters until

the modeled concentrations in the benthic segm ents closely matched the available sediment

G-78

# Appendix G—Overview of Case Study Modeling Setup and Outputs



# concentration monitoring data derived from STOR ET. 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 pl ant’s immediate receiving water and/or downstream

segments would trigger exceedances of human h ealth benchmarks. Table G-54 and Table G-55

illustrate the average modeled pollutant concentr ation 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 tran slating to exceedances of these benchmarks for

baseline and under the fina l 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-79Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-46. USGS Stream Gages with Flow Data Used in Mississippi River WASP ModelGage IDUSGS GageLocationStream Flow Record PeriodCumulative DrainageArea Represented byGage(sq km)Model BoundaryCumulative DrainageArea at ModelBoundary(sq km)Scale Factor7010000Mississippi Rivernear St. Louis, MOFull Record from 01/01/1880- 11/19/20141,668,452Mississippi River1,667,8671.0007019000Meramec River nearEureka, MOFull Record from 10/01/1903- 02/04/20159,811Meramec River10,2641.046Acronyms: USGS (U.S. Geological Survey).Table G-47. Stream Flow Data Periods – Mississippi River WASP ModelModeling PeriodCorresponding StreamFlow Data PeriodMississippi River (Gage ID 7010000)01/01/1982 - 09/30/201401/01/1982 - 09/30/201410/01/2014 – 12/31/202010/01/2002 – 12/31/200801/01/1998 - 09/30/203001/01/1982 - 09/30/201410/01/2030 – 12/31/203610/01/2002 – 12/31/2008Meramec River (Gage ID 7019000)01/01/1982 - 09/30/201401/01/1982 - 09/30/201410/01/2014 – 12/31/202010/01/2002 – 12/31/200801/01/1998 - 09/30/203001/01/1982 - 09/30/201410/01/2030 – 12/31/203610/01/2002 – 12/31/2008G-80Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-48. Pollutant Loadings – Meramec PlantWastestreamPollutant Loadings (g/day)AsCdCuNiPbSeTlZnBaselineaFGDWastewater---­-­---­-­----Fly AshTransportWater---­-­---­-­---­Bottom Ash Transport Water425.25117.36519.891,956.61391.37215.631,994.811,599.08Combustion Residual Leachate---------------­Total425.25117.36519.891,956.61391.37215.631,994.811,599.08Final RulebFGDWastewater---­-­---­-­----Fly AshTransportWater---­-­---­-­----Bottom AshTransportWater---­-­---­-­---­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-81Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-49. Pollutant Loadings – Rush Island PlantWastestreamPollutant Loadings (g/day)AsCdCuNiPbSeTlZnBaselineaFGDWastewater---­-­---­-­---­Fly Ash Transport Water2,617.69338.241,490.401,152.471,054.611,171.401,220.863,112.40Bottom Ash Transport Water109.0755.52381.96330.76173.1111.83200.40334.33Combustion Residual Leachate---------------­Total2,726.76393.761,872.361,483.221,227.721,183.231,421.263,446.73Final RulebFGDWastewater---­-­---­-­----Fly AshTransportWater---­-­---­-­----Bottom AshTransportWater---­-­---­-­---­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-82Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-50. Pollutant Contributions from Non-SteamElectric Point Sources – Mississippi River WASP ModelFacility NameModel COMIDCity, StateLocation (lat, long)ParameterAverage Daily Pollutant Loadings(g/day)MSD Meramec TreatmentPlanta3629071(Mississippi River)St. Louis, MO(38.39,-90.34)As139.02Cd3.50Cu52.2Ni52.5Pb156.5Zn999.6Doe Run Co HerculaneumSmelterb3629127(Mississippi River)Herculaneum, MO(38.26,-90.38)Cd156.87Cu11.56Pb49.42Zn66.51Doe Run Co HerculaneumSmelterc3634867d(Joachim Creek)Herculaneum, MO(38.26,-90.38)As6.09Cd6.09Cu8.35Ni0.61Pb280.97Zn36.80a – 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 isa 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 POTW.G-83Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-51. Pollutant Contributions from STORET Monitoring Data – Mississippi River WASP ModelModel BoundaryModel BoundaryCOMIDStation ID(s) (lat, long)ParameterAverage Concentration(μg/L)aMass Loading(g/day)bMississippi River36290711707.02/3.7 (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--1,533,384.42Cd--63,000.95Cu--1,772,153.59Ni--4,216,002.40Pb--1,764,990.67Zn--6,485,964.73TSS220,098.26--TOC5,298.95--Maeystown Creek3629179JD-02 (38.21,-90.26)As--49.83Cd--1.21Cu--38.90Ni--11.55Pb--29.09Zn--152.55TOC3,928.00--TSS43,000.00--South GabouriCreek36304531707.02/121/0.9/1.5 (37.97,-90.06)TSS5,000.00--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 calculated and incorporatedthe weighted average concentration across the monitoring stations (weighted bynumber 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 theaverage annual flow rate for thestream reach represented bythe monitoring station(s).G-84Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-52. Organic Solids, Sands, and Silts/Fines Inputs – Mississippi River WASP ModelModel BoundaryModel BoundaryCOMIDOrganic Solids Concentration(mg/L)aSands Concentration(mg/L)bSilts/Fines Concentration(mg/L)cMississippi River36290712.6511.00209.09Maeystown Creek36291791.962.1540.85South Gabouri Creek3630453*0.25e4.75eAll Other InflowsdN/A2.314.4784.90Acronyms: N/A (Not Applicable).* – No TOC results available. The ‘All Other Inflows’ concentration was usedin 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 EquationG-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 concentration from alltributaries entering the modeling area.e – These concentrations were calculated using the ‘All Other Inflows’ concentration.Table G-53. Sediment Transport Parameters – Mississippi River WASP ModelInput ParameterValue UsedUnitsTAUcritcoh5.0N/m2TAU_cD1_sia5.0N/m2TAU_cD2_sia10.0N/m2TAU_cD1_POa5.0N/m2TAU_cD2_POa10.0N/m2Note: Table G-1 presents additional solids constants and sediment transport parameters that are used ineach of the case study models.a – This parameter is a WASP model default based on the value of the ‘TAUcritcoh’ parameter.G-85Appendix G—Overview of Case Study Modeling Setup and OutputsFigure G-17. Modeled Concentrations inMississippi River Water Column at RushIsland Plant Immediate Receiving Water(Total Arsenic)G-86Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-54. Average Water Column ConcentrationsDownstream of Rush Island Plant at BaselineSegment DataAverage Total Water Column Concentration over Modeling Period (μg/L)aSegmentIDSegment NameSegmentLength(mi)DistanceDownstream(mi)AsCdCuPbNiSeTlZn9Mississippi River /Rush Island IRW1.481.483.29120.12873.58783.51498.71160.00440.008613.01088Mississippi River2.694.174.09440.12373.55463.21029.50520.00460.009912.35547Mississippi River4.338.493.09720.11713.27543.17898.04770.00400.008011.81956Mississippi River2.2110.703.10500.11743.28333.18598.06840.00400.008011.84685Mississippi River1.2511.953.10570.11743.28343.18588.06930.00400.008011.84674Mississippi River2.9314.883.10550.11733.28163.18358.06670.00400.008011.83923Mississippi River1.4016.273.10650.11733.28193.18348.06820.00400.008011.83952Mississippi River1.9218.193.10780.11733.28203.18318.06990.00400.008011.83931Mississippi River / End5.0623.253.11230.11733.28323.18308.07660.00400.008011.8412Acronyms: IRW (Immediate receiving water).a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modeling period after the assumedcompliance date.G-87Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-55. Average Water Column Concentrations Downstream of Rush Island Plant Under Final RuleSegment DataAverage Total Water Column Concentration over Modeling Period (μg/L)aSegmentIDSegment NameSegmentLength(mi)DistanceDownstream(mi)AsCdCuPbNiSeTlZn9Mississippi River /Rush Island IRW1.481.483.28330.12753.58193.51098.70340.00080.000612.99848Mississippi River2.694.174.08470.12253.54883.20669.49640.00090.000612.34387Mississippi River4.338.493.08980.11593.27003.17538.04020.00080.000511.80836Mississippi River2.2110.703.09760.11623.27793.18238.06090.00080.000511.83575Mississippi River1.2511.953.09840.11623.27803.18228.06180.00080.000511.83564Mississippi River2.9314.883.09820.11613.27633.17998.05920.00080.000511.82813Mississippi River1.4016.273.09920.11623.27653.17988.06070.00080.000511.82842Mississippi River1.9218.193.10040.11623.27673.17958.06240.00080.000511.82821Mississippi River / End5.0623.253.10490.11623.27793.17958.06910.00080.000511.8300Acronyms: IRW (Immediate receiving water).a - Concentrations represent the average daily total pollutant concentration in the water column. The averaging period is the entire modeling period after the assumedcompliance date.G-88Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-56. Total Miles of Mississippi River withWildlife And Human Health Impacts at BaselineWildlife and Human Health Impact ThresholdsTotal Miles with Average Water Column Concentration Translating to Wildlife or Human HealthBenchmark Exceedances (mi)AsCdCuPbNiSeTlZnWL - NEHC, T3 (mink)0.000.000.000.000.000.00No NEHC0.00WL - NEHC, T4 (eagle)0.000.000.000.000.000.00No NEHC0.00HH - Non-Cancer Adult Subsistence0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Adult Recreational0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Subsistence (1 to <2 y.o.)a0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Subsistence (16 to <21 y.o.)b0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Recreational (1 to <2 y.o.)a0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Recreational (16 to <21 y.o.)b0.000.000.00No RfD0.000.000.000.00HH - Cancer Adult Subsistence23.25No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Adult Recreational0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (6 to <11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (6 to 11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRAcronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration);Rfd (Reference dose); LECR (Lifetime excesscancer risk); y.o. (year old).a – This row represents the most sensitive child fisher cohort.b – This row represents the least sensitive child fisher cohort.G-89Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-57. Total Miles of Mississippi River withWildlife And Human Health Impacts Under Final RuleWildlife and Human Health Impact ThresholdsTotal Miles with Average Water Column Concentration Translating to Wildlife or Human HealthBenchmark Exceedances (mi)AsCdCuPbNiSeTlZnWL - NEHC, T3 (mink)0.000.000.000.000.000.00No NEHC0.00WL - NEHC, T4 (eagle)0.000.000.000.000.000.00No NEHC0.00HH - Non-Cancer Adult Subsistence0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Adult Recreational0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Subsistence (1 to <2 y.o.)a0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Subsistence (16 to <21 y.o.)b0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Recreational (1 to <2 y.o.)a0.000.000.00No RfD0.000.000.000.00HH - Non-Cancer Child Recreational (16 to <21 y.o.)b0.000.000.00No RfD0.000.000.000.00HH - Cancer Adult Subsistence23.25No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Adult Recreational0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (6 to <11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Subsistence (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (6 to 11 y.o.)a0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRHH - Cancer Child Recreational (1 to <2 y.o.)b0.00No LECRNo LECRNo LECRNo LECRNo LECRNo LECRNo LECRAcronyms: WL (Wildlife); HH (Human health); NEHC (No effect hazard concentration);Rfd (Reference dose); LECR (Lifetime excesscancer risk); y.o. (year old).a – 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



# C ASE 

# S TUDY 

# M ODEL 

# S ETUPS AND 

# O UTPUTS 

# – L AKE 

# S INCLAIR



# , GA

This section presents information regarding the site-specific desi gn, site-specific input

parameters ( e.g. , background pollutant concentrations, EFDC model flow data), model settings

( e.g. , sediment transport parameters), and case st udy 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 wate r 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, whic h 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 coordina tes to represent the physical characteristics of Lake Sinclair.

Plant Harllee Branch’s immediate receiving water is identified by the coor dinate code I=30 J=32

K=5, where each coordinate represents the positi on on x, y, and z axes, respectively. The Lake

Sinclair model does not have any segments repr esenting 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 mode l. Based on Plant Harllee Branch’s NPDES

permitting cycle, EPA assumed that the plant woul d have achieved the limitations under the final

rule by 2019, if it continued to operate. The modeling peri od begins in February 2012

(approximately seven years before the assumed compliance date) and extends through November

2025 (approximately seven years afte r the assumed compliance date).

Incorporation of Flow Data . EPA did not incorporate any US GS 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 reco rd of flow data for th e 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. Despit e the retirement of this plant,

EPA proceeded with case study modeling of Lake Si nclair to represent the potential impacts of

steam electric discharges on lent ic waterbodies. Table G-59 pres ents 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 identif y any point sources

with 2011 DMR or TRI loadings which would im pact the Lake Sinclair case study model.

Table G-60 presents the pollutant contributions flowing into the Lake Sinclair WASP

model boundaries calculated using av ailable 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 assu med 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 Si nclair revealed water qual ity benchmark exceedances in

the immediate receiving water and neighboring se gments 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 qu ality 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 le vel 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 Bran ch. All analyses of the WASP model outputs were performed on the baseline

output after the assumed compliance date.



# G-92Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-58. Stream Flow Data Periods – Lake Sinclair WASP ModelModeling PeriodCorresponding StreamFlow Data PeriodLake Sinclair (EFDC Hydrodynamic Model)02/01/2012 – 12/31/20182/1/2001 – 12/31/200701/01/2019 – 11/30/20252/1/2001 – 12/31/2007G-93Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-59. Pollutant Loadings – Plant Harllee BranchWastestreamPollutant Loadings (g/day)AsCdCuNiPbSeTlZnBaselineaFGD Wastewaterc35.18521.69100.784,068.2021.615,413.4663.656,451.65Fly Ash Transport Water44.2812.0197.9155.2839.7714.8013.57360.25Bottom Ash Transport Water22.296.1527.25102.5620.5211.30104.5683.82Combustion Residual Leachate---------------­Total101.75539.85225.944,226.0481.905,439.56181.786,895.72Final RulebFGD Wastewater27.0319.5017.5029.2115.7126.5145.4492.54Fly AshTransportWater---­-­---­-­----Bottom AshTransportWater---­-­---­-­---­Combustion Residual Leachate---------------­Total27.0319.5017.5029.2115.7126.5145.4492.54Acronyms: FGD (flue gas desulfurization).Note: Plant Harllee Branch has retired all coal-fired generatingunits. EPA calculated pollutant loadings at the wastestream level for Plant Harllee Branch using thesame loadings methodology that EPA used for other plants in the loadings analyses. EPA did not include Plant Harllee Branch inthe other quantitative andqualitative 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 loadings from FGDwastewater when the system was installed in2013. EPA did not model any FGD wastewaterpollutant loadings before the installation of Plant Harllee Branch’s FGDsystem.G-94Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-60. Pollutant Contributions from STORET Monitoring Data – Lake Sinclair WASP ModelModel BoundaryModel BoundaryCOMIDStation ID(s) (lat, long)ParameterAverage Concentration(μg/L)aMass Loading(g/day)bOconee River10575030301100602 (33.35,-83.16)3038901 (33.35,-83.16)0301100603 (33.33,-83.14)TOC3,818.44--TSS6,941.46--Crooked Creek10564070301180202 (33.32,-83.28)TOC7,124.62--TSS18,992.31--Rooty Creek10576290301180301 (33.32,-83.27)3040101 (33.32,-83.37)0301180302 (33.29,-83.35)3040501 (33.29,-83.25)As--58.89Cd--14.99Cu--45.10Ni--33.07Pb--29.59Tl--58.95Zn--452.25TOC5,347.26--TSS11,635.71--Little River10576813042001 (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--960.78Cd--243.11Cu--1,037.67Ni--644.08Pb--482.01Tl--961.37Zn--6,098.66TOC4,960.21--TSS15,576.92--G-95Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-60. Pollutant Contributions from STORET Monitoring Data – Lake Sinclair WASP ModelModel BoundaryModel BoundaryCOMIDStation ID(s) (lat, long)ParameterAverage Concentration(μg/L)aMass Loading(g/day)bMurder Creek10576790301160703 (33.27,-83.48)3043401 (33.25,-83.48)0301160701 (33.25,-83.48)As--642.79Cd--162.65Cu--328.26Ni--347.78Pb--322.48Tl--643.18Zn--1,654.57TOC2,773.47--TSS21,383.33--Big Cedar Creek10568933043801 (33.19,-83.44)0301170401 (33.19,-83.44)As--450.16Cd--113.90Cu--229.89Ni--243.56Pb--225.84Tl--450.44Zn--345.37TOC3,407.30--TSS20,223.08--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 calculated and incorporatedthe weighted average concentration across the monitoring stations (weighted bynumber 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 theaverage annual flow rate for thestream reach represented bythe monitoring station(s).G-96Appendix G—Overview of Case Study Modeling Setup and OutputsTable G-61. Organic Solids, Sands, and Silts/Fines Inputs – Lake Sinclair WASP ModelModel BoundaryModel BoundaryCOMIDOrganic Solids Concentration(mg/L)aSands Concentration(mg/L)bSilts/Fines Concentration(mg/L)cOconee River10575031.910.356.59Crooked Creek10564073.560.9518.04Rooty Creek10576292.670.5811.05Little River10576812.480.7814.80Murder Creek10576791.391.0720.31Big Cedar Creek10568931.701.0119.21All Other InflowsdN/A2.290.7915.00Acronyms: 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 EquationG-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 concentration from alltributaries entering the modeling area.Table G-62. Sediment Transport Parameters – Lake Sinclair WASP ModelInput ParameterValue UsedUnitsTAUcritcoh3.5N/m2TAU_cD1_sia3.5N/m2TAU_cD2_sia7.0N/m2TAU_cD1_POa3.5N/m2TAU_cD2_POa7.0N/m2Note: Table G-1 presents additional solids constants andsediment transport parameters that are used in eachof the case study models.a – This parameter is a WASP model default based on the value of the ‘TAUcritcoh’ parameter.G-97Appendix G—Overview of Case Study Modeling Setup and OutputsFigure G-18. Average Modeled Concentrations in All Segments inLake Sinclair WASP Model (Total Arsenic, Total Thallium)G-98

# Appendix H—Additional Model Results



# APPENDIX H

ADDITIONAL MODEL RESULTS

Table H-1. Number and Percentage of Immedi ate Receiving Waters that Exceeded a

Criterion by Pollutant and Criteria Ty pe 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); NRWQ C (National Recommended Water Quality Criteria).

a – A total of 209 immediate receiving waters (183 rive rs 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 60Number of Immediate Receiving Waters



# Total Arsenic Concentration in Receiving Water (mg/L) 

# Figure H-1. Baseline Total Ar senic 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 60Number of Immediate Receiving Waters



# Total Cadmium Concentration in Receiving Water (mg/L) 

# Figure H-2. Baseline Total Ca dmium 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 160Number 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 60Number 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 50Number 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 80Number of Immediate Receiving Waters



# Total Mercury Concentration in Receiving Water (mg/L) 

# Figure H-6. Baseline Total Me rcury 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 50Number 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 50Number of Immediate Receiving Waters



# Total Selenium Concentration in Receiving Water (mg/L) 

# Figure H-8. Baseline Total Se lenium 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 60Number 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 60Number 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 Immediat e 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 60Number 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 Append ix D). Therefore, the estimated concen trations presented here are identical

for both trophic levels.



# Table H-12. Total Arsenic Concentration (m g/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 60Number 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 D 

# Error!

Reference source not found. ). Therefore, the estimated concentratio ns presented here are identical for both

trophic levels.



# Table H-13. Total Cadmium Concentration (m g/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 es timated 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 250Number 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 (s ee 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 es timated 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 50Number 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 Tissu e 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 (m g/kg) in Fish Tissu e (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 es timated 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 50Number 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 Tissu e 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/k g) 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 60Number of Immediate Receiving Waters



# Methylmercury Concentration in Fish Tissue (mg/kg) 

# Figure H-16. Methylmercury Co ncentration in Trophic Level

3 Fish Tissue in the Immediate Receiving Water

Table H-17. Methylmercury Concentration (mg/k g) 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 bioaccum ulation factors which do not fully

account for the complexity of biogeochemical reactions that can occur w ithin 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 w ith high selenium concentr ations. In addition, bio accumulation factors do not

account for a maximum limit a fish coul d 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 re present 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 60Number of Immediate Receiving Waters



# Methylmercury Concentration in Fish Tissue (mg/kg) 

# Figure H-17. Methylmercury Co ncentration in Trophic Level

4 Fish Tissue in the Immediate Receiving Water

Table H-18. Methylmercury Concentration (mg/k g) 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 bioaccum ulation factors which do not fully

account for the complexity of biogeochemical reactions that can occur w ithin 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 w ith high selenium concentr ations. In addition, bio accumulation factors do not

account for a maximum limit a fish coul d 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 re present 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 50Number of Immediate Receiving Waters



# Total Nickel Concentration in Fish Tissue (mg/kg) 

# Figure H-18. Total Nickel Con centration in Trophic Level 3

and Trophic Level 4 Fish Tissu e 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 he re 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 50Number 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 45Number 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/k g) 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 50Number of Immediate Receiving Waters



# Total Thallium Concentratio n 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 50Number of Immediate Receiving Waters



# Total Thallium Concentratio n 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 60Number 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 Tissu e 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/k g) 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 st andards (ELGs). The anal yses presented in the

report incorporate some adjustments to current conditions in the industr y. The analyses in the

report, however, do not reflect ch anges in the industry that may occur as a result of the Clean

Power Plan [Clean Air Act Sect ion 111(d)] (CPP). This appendix pr esents 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 surf ace 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 Lim itations 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-1Figure I-1. Locations and Counts of Immediate Receiving Waters in EA Scope and Modeling AnalysesAppendix I—Analysis for Alternate Scenario with Clean Power PlanI-2

# Appendix I—Analysis for Alternate Scenario with Clean Power Plan



# Table I-2. Receiving Water Types fo r 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 wate rs and loadings from 148

steam electric power plants (some of which discharge to multiple recei ving waters). The immediate receiving

water (IRW) model, which excludes the Great Lakes an d 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 change s in the industry that may occur as a result of

the CPP. Table I-3 presents th e annual pollutant loadings in pounds and toxic-weighted pound

equivalents (TWPE). 1,2 

# Table I-4 compares pollutant di scharges, as TWPE, from the steam

electric power generating industr y to discharges from the other top ten dischargi ng point source

categories, as estimated by EPA for the 2010 Effl uent 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 (lb

equivalent/yr), or TWPE. TWFs account for differences in toxicity across pollutants and allow mass loadings of

different pollutants to be compared on the basis of their toxic potential. EPA has developed TWFs for more than

1,000 pollutants based on aquatic life and human health toxi city data, as well as physical/chemical property data

[U.S. EPA, 2012b].

2 

# Prior to finalizing the rulemaking, EPA revised the datase ts used to calculate pollutant loadings for bottom ash

transport water and fly ash transport water. The final indust ry loadings calculated using these revised datasets are

presented in the TDD. The total industry loadings presen ted 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 Discharg es from Steam Electric Power Plants

(Evaluated Wastestreams)

Pollutant a 

# TWF b 

# Annual Discharge,

pounds (lbs) c 

# Annual TWPE,

pound-equivalent

(lb-eq) c



# Metals and Toxic Bioaccumulative Pollutants

Manganese 0.103 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 zi nc. EPA updated TWFs for arsenic, cadmium, copper,

manganese, mercury, thallium, and vanadium for the steam electric ELGs pollutant loadings analysis.

c – These loadings reflect adjustments to current conditions in the industry to account for publicly announced plans

from the steam electric power generatin g 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 an d 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 discha rges of the evaluated wastestreams – specifically, flue gas

desulfurization (FGD) wastewater, fly ash transport wast ewater, bottom ash transport wastewater, and combustion

residual leachate (see Section 10 of the TDD). Loadings pres ented 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 20 10 Effluent Guidelines Planning Process:

Top 10 Point Source Categories

40 CFR Part Point Source Category Total TWPE a



# (lb-eq/yr)

423 Steam Electric Power Generating 2,140,000 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 gene rating industry include updates to TWFs for arsenic,

cadmium, copper, manganese, mercury, thallium, and vanadium. The TWPE for all other point source categories is

estimated from 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 powe r generating industry (40 CFR 423) discharges for the alternate scenario

analysis as total of 2,140,000 TWPE a nnually (see Section 10 of the TDD).



# EPA estimated that the total alternate scenar io 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 industr y; and nonferrous metals manufacturing (second,

third, and fourth highest ranking), and it is over fi ve 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 magn itude of the pollutant loadings from steam

electric power plants in the alte rnate 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 wastestream 4 

# 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

plants 5 

# 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 wast estream 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 wastes treams directly to surface wa ters. 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-6Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-5. Comparison of Average Pollutant Loadingsin the Evaluated Wastestreams to an Average POTWPollutantAverage Plant FGDWastewater Dischargea,bAverage Plant Fly AshTransport WaterDischargea,cAverage Plant BottomAsh Transport WaterDischargea,dAverage PlantCombustion ResidualLeachate Dischargea,eAverage POTWDischargea,fLoadings(lbs/yr)TWPE(lb-eq/yr)Loadings(lbs/yr)TWPE(lb-eq/yr)Loadings(lbs/yr)TWPE(lb-eq/yr)Loadings(lbs/yr)TWPE(lb-eq/yr)Loadings(lbs/yr)TWPE(lb-eq/yr)Aluminum1,7201119,0105833,88025198863.93,590215Arsenic9.6833.63101,08061.121212.744.245.9159Boron333,0002,78019,8001662,06017.27,70064.21,54012.8Cadmium91.72,09049.21,12017.74033.3977.23.5480.6Chromium VI(g)(g)2.481.280.1450.0750(g)(g)17.79.02Copper19.612.228217683.051.72.551.5915495.3Iron1,2707.105,74032.16,96039.012,20068.52,53014.2Lead5.8213.015735158.6131(g)(g)48.5109Manganese81,8008,40052253.64,34044693395.835436.1Mercury6.246877.768543.043340.35138.73,180350,000Nickel70176.418820.527530.015.41.6830.63.06Selenium1,4701,64013214829.533.136.741.218.520.7Thallium17.048.61343842767890.3991.149.9428.2Vanadium21.05.8720958.512.23.42631177No dataNo dataZinc1,11052.381438.222710.669.83.2745318.1Total Nitrogen132,000--25,000--22,500--(g)--123,000--TotalPhosphorus453--849--657--(g)--17,800--Chlorides10,100,00024684,6002.0688,5002.16142,0003.451,610,00039.3TDS40,800,000--1,870,000--2,340,000--1,200,000--No data--Note: Numbers are rounded to three significant figures.a – TWPE presented in the table include updates to TWFs for arsenic, cadmium, copper, manganese,mercury, thallium, and vanadium.b – Average loadings based on 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 andwastestream. See the Costs andLoads Report (DCN SE05831).I-7

# Appendix I—Analysis for Alternate Scenario with Clean Power Plan



# Table I-6. Estimated Number of POTW Equivalen ts 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 load ings 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 th at 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 wa ters in the alternate s cenario 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 consump tion 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 proxim ity analysis, EPA evaluated 172 immedi ate receiving waters that receive

discharges of the evaluated wastestreams [ERG, 2015c; ERG, 2015d].

b – Table B-1 in Appendix B contains a complete list of the impairment categories identified in EPA’s 303(d)

- listed waters and designates the subset of pollutants evaluated.

c – Table B-2 in Appendix B contains a complete list of the types of advisories identified under the sensitive

environment proximity analysis, including pollutants that are not associated with the evaluated wastestreams.

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, accounti ng for changes in the industry baseline as a

result of the CPP. Table I-10 presents the numbe r 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 im mediate 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 c onsumption advisory for lead.

The results of the threatened and endangere d species analysis pr esented in Section 3.4.5

already account for changes in th e industry as a result of the CPP. Table I-11 presents the

number of steam electric power plants located w ithin five miles of a drinking water resource and

the number of drinking water resources located with in 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 ar e 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 G reat 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 pl ants 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 Ches apeake 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 immedi ate receiving waters in

the Chesapeake Bay watershed.



# Table I-10. Number and Percentage of Imme diate Receiving Waters Classified as

Impaired for a Pollutant Associated with the Evaluated Wastestreams

Pollutant Causing Impairment Number (Percentage) of Immediate

Receiving Waters Identified a



# Mercury 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 immedi ate receiving waters that receive

discharges of the evaluated wastestreams [ERG, 2015c; ERG, 2015d].

b – The EPA impaired water database listed 24 immediate r eceiving 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 Perce ntage of Steam Electric Power Plants

Located within 5 Miles of a Drinking Water Resource

Type of Drinking Water

Resource Number of Drinking Water

Resources within 5 Miles of a Steam

Electric Power Plant Number (Percentage) of Steam

Electric Power Plants

Located within 5 Miles of a

Drinking Water Resource a



# Intakes and reservoirs 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, EP A 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 pow er 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 subsistenc e fishers (Table I-16 through Table I-19); and

human health impacts to cohorts representing recreational and subsiste nce fishers by race or

Hispanic origin (Table I-20 and Table I-21, respectively).

The ecological risk modeling resu lts under the alternat e scenario analysis indicate that 16

percent of the lakes, ponds, and re servoirs (3 out of 19) and 13 pe rcent of the rivers and streams

(18 out of 144) that receive disc harges of the evaluated wastestrea ms 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 per cent of the rivers and streams (22 out of 144)

presenting these risks.

Selecting the 90 th 

# percentile modeled egg/ovary concentration, meaning there is a 10

percent probability that the egg/ovary concentrati ons are greater than the selected concentration,

reveals that 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 re sults for mallard s (20 percent)

are very similar. These counts ar e considerably higher than the results obtained using the median

modeled egg/ovary concentrati on, indicating the potential for more widespread ecological

impacts among those waterbodies and food webs that tend to experience higher bioaccumulation

of selenium.

I-12

# Table I-12. Number and Percentage of Imme diate 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.

Acron yms: NRWQC (National Recommended Water Quality Criteria); MCL (maximum contaminant level).

a – The alternate scenario analysis encompasses a total of 172 immediate receiving wate rs and loadings from 148

steam electric power plants (some of which discharge to multiple r eceiving waters). The IRW model, which

excludes the Great Lakes and estuaries, encompasses a total of 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 th at exceeded at least one criterion.



# Table I-13. Number and Percentage of Immediat e 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 wate rs and loadings from 148

steam electric power plants (some of which discharge to multiple r eceiving waters). The IRW model, which

excludes the Great Lakes and estuaries, encompasses a total of 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 Im mediate Receiving Waters That Exceed

Wildlife Fish Consumption NEHCs fo r 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 iden tified in the wildlife analysis for thallium); NC (Not

calculated); NEHC (No Effect Hazard Con centration); ug/g (m icrograms/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 wate rs and loadings from 148

steam electric power plants (some of which discharge to multiple r eceiving waters). The IRW model, which

excludes the Great Lakes and estuaries, encompasses a total of 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 Imme diate 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 wate rs and loadings from 148

steam electric power plants (some of which discharge to multiple r eceiving waters). The IRW model, which

excludes the Great Lakes and estuaries, encompasses a total of 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 Immedi ate Receiving Waters That Exceed Human

Health Evaluation Criteria (Lifetime Ex cess Cancer Risk) for Inorganic Arsenic

Receptor Cohort Exposure

Duration

(Years) Number of Immediate Receiving Waters Where

Lifetime Excess Cancer Ri sk Exceeds 1-in-a-Million a,b



# Number of

Rivers and

Streams Number of

Lakes, Ponds,

and Reservoirs Total Receiving Waters c



# Number

Exceeding Percentage

Exceeding

Child

recreational

fisher 1 to <2 years 1 4 0 4 2%

2 to <3 years 1 4 0 4 2%

3 to <6 years 3 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 wate rs and loadings from 148

steam electric power plants (some of which discharge to multiple r eceiving waters). The IRW model, which

excludes the Great Lakes and estuaries, encompasses a total of 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 wate rs and loadings from 148

steam electric power plants (some of which discharge to multiple r eceiving waters). The IRW model, which

excludes the Great Lakes and estuaries, encompasses a total of 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 Imme diate Receiving Waters That Exceed NonCancer Oral Reference Dose Values at Baseline by Pollutant

Pollutant Oral

Reference Dose

(mg/kg/day) Number of Immediate Receiving Waters where Estimated

Exposure Doses Exceed Non- Cancer Reference Doses a



# Number Exceeding Percentage Exceeding

Inorganic arsenic 0.0003 b 

# 3 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 wate rs and loadings from 148

steam electric power plants (some of which discharge to multiple r eceiving waters). The IRW model, which

excludes the Great Lakes and estuaries, encompasses a total of 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 Co ncentrations 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 sc reening values indicates that more

intensive site-specific monitoring and/or evaluation of human health risk should be conducted [U.S. EPA, 2000a,

Table 5-3].

b – The alternate scenario analysis encompasses a total of 172 immediate receiving wate rs and loadings from 148

steam electric power plants (some of which discharge to multiple r eceiving waters). The IRW model, which

excludes the Great Lakes and estuaries, encompasses a total of 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 Immedi ate Receiving Waters That Exceed Human

Health Evaluation Criteria (L ifetime 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 Ri sk Exceeds 1-in-a-Million a,b



# 1 to <2

years 2 to <3

years 3 to <6

years 6 to <11

years 11 to <16

years 16 to <21

years Adult

Recreational Non-Hispanic White 3 3 4 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 wate rs and loadings from 148

steam electric power plants (some of which discharge to multiple r eceiving waters). The IRW model, which

excludes the Great Lakes and estuaries, encompasses a total of 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-20Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-21. Number and Percentage of Immediate Receiving Waters That Exceed Non-Cancer Oral Reference Dose Values, byRace or Hispanic OriginReceptorRace or Hispanic OriginNumber of Immediate Receiving Waters Where Pollutant Exceeds a Non-Cancer Reference DoseaInorganicArsenicCadmiumCopperMercurybSeleniumThalliumcZincRecreational,Child FisherNon-Hispanic White0 (0%)8 (5%)3 (2%)63 (39%)26 (16%)44 (27%)4 (2%)Non-Hispanic Black0 (0%)9 (6%)4 (2%)64 (39%)27 (17%)45 (28%)4 (2%)Mexican-American0 (0%)11 (7%)4 (2%)66 (40%)27 (17%)48 (29%)4 (2%)Other Hispanic0 (0%)10 (6%)4 (2%)64 (39%)27 (17%)47 (29%)4 (2%)Other, including Multiple Races0 (0%)11 (7%)4 (2%)68 (42%)28 (17%)48 (29%)4 (2%)Subsistence,Child FisherNon-Hispanic White0 (0%)8 (5%)3 (2%)63 (39%)26 (16%)44 (27%)4 (2%)Non-Hispanic Black0 (0%)9 (6%)4 (2%)64 (39%)27 (17%)45 (28%)4 (2%)Mexican-American0 (0%)11 (7%)4 (2%)66 (40%)27 (17%)48 (29%)4 (2%)Other Hispanic0 (0%)10 (6%)4 (2%)64 (39%)27 (17%)47 (29%)4 (2%)Other, including Multiple Races0 (0%)11 (7%)4 (2%)68 (42%)28 (17%)48 (29%)4 (2%)Recreational,Adult FisherNon-Hispanic White3 (2%)17(10%)4 (2%)74 (45%)33 (20%)58 (36%)4 (2%)Non-Hispanic Black3 (2%)18 (11%)4 (2%)74 (45%)34 (21%)58 (36%)4 (2%)Mexican-American3 (2%)20 (12%)4 (2%)76 (47%)36 (22%)60 (37%)5 (3%)Other Hispanic3 (2%)20 (12%)4 (2%)76 (47%)36 (22%)60 (37%)5 (3%)Other, including Multiple Races3 (2%)24 (15%)4 (2%)79 (48%)38 (23%)67 (41%)5 (3%)Subsistence,Adult FisherNon-Hispanic White3 (2%)17(10%)4 (2%)74 (45%)33 (20%)58 (36%)4 (2%)Non-Hispanic Black3 (2%)18 (11%)4 (2%)74 (45%)34 (21%)58 (36%)4 (2%)Mexican-American3 (2%)20 (12%)4 (2%)76 (47%)36 (22%)60 (37%)5 (3%)Other Hispanic3 (2%)20 (12%)4 (2%)76 (47%)36 (22%)60 (37%)5 (3%)Other, including Multiple Races3 (2%)24 (15%)4 (2%)79 (48%)38 (23%)67 (41%)5 (3%)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 electricpower plants (some of whichdischarge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving watersand 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 industr y as a result of the CPP. Ta ble 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, Chlo rides, and TDS Under Regulatory Options

Pollutant Pollutant Removals, lbs/yr (Percent Reduction) a



# Option A Option B Option C Option D Option E

Arsenic 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 Kj eldahl 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 Generati ng Industry TWPE Removals for Metals,

Bioaccumulative Pollutants, Nutrients, Chlo rides, and TDS Under Regulatory Options

Pollutant Pollutant Removals, TWPE/year (Percent Reduction) a



# Option A Option B Option C Option D Option E

Arsenic 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 nitr ogen, total phosphorus, and TDS because EPA has not

established a toxic weighting factor (TWF) for these pollutants.

a – >0 to 15 percent reduction; 16 to 30 percent reduction; 31 to 45 percent reduction; 46 to 60 percent reduction ;

>60 percent reduction

.



# Table I-24 presents key environmental improve ments 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 e nvironmental improvements based on reduced

discharges of arsenic, mercury, selenium, cad mium, and thallium are included in Table I-26

through Table I-30.

I-23Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-24. Key Environmental Improvements Under the Regulatory OptionsEvaluation BenchmarkModeled Immediate ReceivingWaters Exceeding BenchmarkUnder Baseline ConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the RegulatoryOptionsbNumberPercentageOption AOption BOption COption DOption EWater Quality ResultsFreshwater Acute NRWQC74%5(29%)5(29%)5(29%)3(57%)2(71%)Freshwater Chronic NRWQC2817%27(4%)22(21%)18(36%)16(43%)16(43%)Human Health Water and Organism NRWQC7345%70(4%)70(4%)55(25%)42(42%)35(52%)Human Health Organism Only NRWQC5131%48(6%)48(6%)3629%)28(45%)22(57%)Drinking Water MCL2918%27(7%)26(10%)12(59%)6(79%)6(79%)Wildlife ResultsFish Ingestion NEHC for Minks4628%46(0%)41(11%)25(46%)19(59%)18(61%)Fish Ingestion NEHC for Eagles5634%52(7%)48(14%)34(39%)23(59%)20(64%)Human Health Results—Non-CancerNon-Cancer Reference Dose for Child(recreational)7546%69(8%)67(11%)51(32%)38(49%)30(60%)Non-Cancer Reference Dose for Adult(recreational)6741%60(10%)58(13%)44(34%)32(52%)23(66%)Non-Cancer Reference Dose for Child(subsistence)9055%81(10%)79(12%)59(34%)43(52%)39(57%)Non-Cancer Reference Dose for Adult(subsistence)7848%72(8%)71(9%)54(31%)40(49%)32(59%)I-24Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-24. Key Environmental Improvements Under the Regulatory OptionsEvaluation BenchmarkModeled Immediate ReceivingWaters Exceeding BenchmarkUnder Baseline ConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the RegulatoryOptionsbNumberPercentageOption AOption BOption COption DOption EHuman Health Results—CancerArsenic Cancer Risk for Child (recreational)42%3(25%)3(25%)3(25%)2(50%)2(50%)Arsenic Cancer Risk for Adult (recreational)96%7(22%)7(22%)5(44%)3(67%)2(78%)Arsenic Cancer Risk for Child (subsistence)64%6(0%)6(0%)5(17%)3(50%)2(67%)Arsenic Cancer Risk for Adult (subsistence)2113%19(10%)19(10%)13(38%)11(48%)4(81%)Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (maximum contaminant level); NEHC (No Effect Hazard Concentration); NRWQC (National Recommended Water Quality Criteria).a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 steam electricpower plants (some of whichdischarge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving watersand 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-25Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-25. Number of ImmediateReceiving Waters with Sediment Pollutant Concentrations Exceeding TELs for SedimentBiota Under the Regulatory OptionsPollutantModeled ImmediateReceiving WatersExceeding CSCLs UnderBaseline ConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the Regulatory OptionsbOption AOption BOption COption DOption EArsenic5(3%)4(20%)4(20%)4(20%)3(40%)2(60%)Cadmium22(13%)17(23%)17(23%)12(45%)10(55%)8(64%)Chromium VIc0(0%)0(N/A)0(N/A)0(N/A)0(N/A)0(N/A)Copper5(3%)4(20%)4(20%)4(20%)2(60%)2(60%)Lead4(2%)3(25%)3(25%)3(25%)1(75%)1(75%)Mercury40(25%)36(10%)35(13%)20(50%)16(60%)7(83%)Nickel27(17%)22(19%)22(19%)12(56%)10(63%)4(85%)SeleniumNCNCNCNCNCNCThalliumNCNCNCNCNCNCZinc13(8%)7(46%)7(46%)7(46%)6(54%)2(85%)Total40(25%)36(10%)35(13%)21(48%)17(58%)8(80%)Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: CSCL (Chemical stressor concentration limit); N/A (Not Applicable, no exceedances at baseline conditions to compare option results); NC (Notcalculated; no benchmark for comparison).a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 steam electricpower plants (some of whichdischarge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving watersand 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-26Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-26. Key Environmental Improvements for Arsenic Under the Regulatory OptionsEvaluation BenchmarkModeled ImmediateReceiving Waters ExceedingBenchmark Under BaselineConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the RegulatoryOptionsbNumberPercentageOption AOption BOption COption DOption EWater Quality ResultsFreshwater Acute NRWQC32%2(33%)2(33%)2(33%)2(33%)1(67%)Freshwater Chronic NRWQC42%3(25%)3(25%)3(25%)2(50%)1(75%)Human Health Water and OrganismNRWQC7345%70(4%)70(4%)55(25%)42(42%)35(52%)Human Health Organism Only NRWQC5131%48(6%)48(6%)36(29%)28(45%)22(57%)Drinking Water MCL96%7(22%)7(22%)5(44%)3(67%)2(78%)Wildlife ResultsFish Ingestion NEHC for Minks00%0(N/A)0(N/A)0(N/A)0(N/A)0(N/A)Fish Ingestion NEHC for Eagles00%0(N/A)0(N/A)0(N/A)0(N/A)0(N/A)Human Health Results—Non-CancerNon-Cancer Reference Dose for Child(recreational)21%1(50%)1(50%)1(50%)1(50%)0(100%)Non-Cancer Reference Dose for Adult(recreational)00%0(N/A)0(N/A)0(N/A)0(N/A)0(N/A)Non-Cancer Reference Dose for Child(subsistence)32%2(33%)2(33%)2(33%)2(33%)1(67%)Non-Cancer Reference Dose for Adult(subsistence)32%2(33%)2(33%)2(33%)2(33%)1(67%)I-27Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-26. Key Environmental Improvements for Arsenic Under the Regulatory OptionsEvaluation BenchmarkModeled ImmediateReceiving Waters ExceedingBenchmark Under BaselineConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the RegulatoryOptionsbNumberPercentageOption AOption BOption COption DOption EHuman Health Results—CancerArsenic Cancer Risk for Child(recreational)42%3(25%)3(25%)3(25%)2(50%)2(50%)Arsenic Cancer Risk for Adult(recreational)96%7(22%)7(22%)5(44%)3(67%)2(78%)Arsenic Cancer Risk for Child(subsistence)64%6(0%)6(0%)5(17%)3(50%)2(67%)Arsenic Cancer Risk for Adult(subsistence)2113%19(10%)19(10%)13(38%)11(48%)4(81%)Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (Maximum contaminant level); N/A (Not Applicable, no exceedances atbaseline conditions tocompare option results); NEHC (No EffectHazard Concentration); NRWQC (NationalRecommended Water Quality Criteria).a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 steam electricpower plants (some of whichdischarge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving watersand 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-28Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-27. Key Environmental Improvements for Mercury Under the Regulatory OptionsEvaluation BenchmarkModeled Immediate Receiving WatersExceeding Benchmark Under BaselineConditionsaNumber of Immediate Receiving Waters ExceedingBenchmark(Percent Reduction from Baseline Conditions) Under theRegulatory OptionsbNumberPercentageOption AOption BOption COption DOption EWater Quality ResultsFreshwater Acute NRWQC00%0(N/A)0(N/A)0(N/A)0(N/A)0(N/A)Freshwater Chronic NRWQC11%0(100%)0(100%)0(100%)0(100%)0(100%)Human Health Water and Organism NRWQCNobenchmark for comparisonN/AN/AN/AN/AN/AHuman Health Organism Only NRWQCNo benchmark for comparisonN/AN/AN/AN/AN/ADrinking Water MCL42%4(0%)4(0%)4(0%)2(50%)1(75%)Wildlife ResultsFish Ingestion NEHC for Minks4326%40(7%)39(9%)23(47%)17(60%)8(81%)Fish Ingestion NEHC for Eagles5534%48(13%)48(13%)34(38%)23(58%)17(69%)Human Health Results—Non-CancerNon-Cancer Reference Dose for Child(recreational)7244%65(10%)62(14%)46(36%)35(51%)27(63%)Non-Cancer Reference Dose for Adult(recreational)6439%55(14%)54(16%)41(36%)30(53%)20(69%)Non-Cancer Reference Dose for Child(subsistence)8452%74(12%)73(13%)55(35%)41(51%)37(56%)Non-Cancer Reference Dose for Adult(subsistence)7546%68(9%)66(12%)49(35%)37(51%)29(61%)Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (Maximum contaminant level); N/A (Not Applicable, no exceedances atbaseline conditions tocompare option results); NEHC (No EffectHazard Concentration); NRWQC (NationalRecommended Water Quality Criteria).a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 steam electricpower plants (some of whichdischarge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving watersand 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-29Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-28. Key Environmental Improvements for Selenium Under the Regulatory OptionsEvaluation BenchmarkModeled ImmediateReceiving Waters ExceedingBenchmark Under BaselineConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the RegulatoryOptionsbNumberPercentageOption AOption BOption COption DOption EWater Quality ResultsFreshwater Acute NRWQCNo benchmark for comparisonN/AN/AN/AN/AN/AFreshwater Chronic NRWQC2717%25(7%)17(37%)16(41%)14(48%)14(48%)Human Health Water and OrganismNRWQC85%7(13%)3(63%)3(63%)2(75%)2(75%)Human Health Organism Only NRWQC11%1(0%)1(0%)1(0%)1(0%)1(0%)Drinking Water MCL106%9(10%)4(60%)4(60%)3(70%)3(70%)Wildlife ResultsFish Ingestion NEHC for Minks3320%32(3%)23(30%)19(42%)17(48%)17(48%)Fish Ingestion NEHC for Eagles3320%32(3%)23(30%)19(42%)17(48%)17(48%)Negative Reproductive Effects in Fishc2113%17(19%)9(57%)9(57%)8(62%)8(62%)Negative Reproductive Effects inMallardsc2515%21(16%)13(48%)12(52%)11(56%)11(56%)I-30Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-28. Key Environmental Improvements for Selenium Under the Regulatory OptionsEvaluation BenchmarkModeled ImmediateReceiving Waters ExceedingBenchmark Under BaselineConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the RegulatoryOptionsbNumberPercentageOption AOption BOption COption DOption EHuman Health Results—Non-CancerNon-Cancer Reference Dose for Child(recreational)3320%32(3%)23(30%)19(42%)17(48%)17(48%)Non-Cancer Reference Dose for Adult(recreational)2616%23(12%)14(46%)14(46%)13(50%)13(50%)Non-Cancer Reference Dose for Child(subsistence)4125%39(5%)31(24%)28(32%)24(41%)24(41%)Non-Cancer Reference Dose for Adult(subsistence)3421%32(6%)23(32%)19(44%)17(50%)17(50%)Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (Maximum contaminant level); N/A (Not Applicable, no exceedances atbaseline conditions tocompare option results); NEHC (No EffectHazard Concentration); NRWQC (NationalRecommended Water Quality Criteria).a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 steam electricpower plants (some of whichdischarge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving watersand 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 numberof immediate receiving waters whose median modeled egg/ovary concentration is predicted to result in reproductive impactsamong at least 10 percent of the exposed fish or mallard population, as determined using the ecological risk model.I-31Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-29. Key Environmental Improvements for Cadmium Under the Regulatory OptionsEvaluation BenchmarkModeled Immediate ReceivingWaters Exceeding BenchmarkUnder Baseline ConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the RegulatoryOptionsbNumberPercentageOption AOption BOption COption DOption EWater Quality ResultsFreshwater Acute NRWQC74%4(43%)4(43%)4(43%)3(57%)2(71%)Freshwater Chronic NRWQC2314%18(22%)18(22%)13(43%)11(52%)9(61%)Human Health Water and Organism NRWQCNobenchmark for comparisonN/AN/AN/AN/AN/AHuman Health Organism Only NRWQCNo benchmark for comparisonN/AN/AN/AN/AN/ADrinking Water MCL85%6(25%)6(25%)5(38%)3(63%)2(75%)Wildlife ResultsFish Ingestion NEHC for Minks53%4(20%)4(20%)4(20%)2(60%)2(60%)Fish Ingestion NEHC for Eagles42%3(25%)3(25%)3(25%)2(50%)2(50%)Human Health Results—Non-CancerNon-Cancer Reference Dose for Child(recreational)138%9(31%)9(31%)7(46%)5(62%)3(77%)Non-Cancer Reference Dose for Adult(recreational)85%6(25%)6(25%)5(38%)3(63%)2(75%)Non-Cancer Reference Dose for Child(subsistence)2717%22(19%)22(19%)17(37%)15(44%)10(63%)Non-Cancer Reference Dose for Adult(subsistence)1811%13(28%)13(28%)9(50%)7(61%)4(78%)Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (Maximum contaminant level); N/A (Not Applicable, no exceedances atbaseline conditions tocompare option results); NEHC (No EffectHazard Concentration); NRWQC (NationalRecommended Water Quality Criteria).a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 steam electricpower plants (some of whichdischarge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving watersand 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-32Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-30. Key Environmental Improvements for Thallium Under the Regulatory OptionsEvaluation BenchmarkModeled ImmediateReceiving Waters ExceedingBenchmark Under BaselineConditionsaNumber of Immediate Receiving Waters Exceeding Benchmark(Percent Reduction from Baseline Conditions) Under the Regulatory OptionsbNumberPercentageOption AOption BOption COption DOption EWater Quality ResultsFreshwater Acute NRWQCNo benchmark for comparisonN/AN/AN/AN/AN/AFreshwater Chronic NRWQCNo benchmark for comparisonN/AN/AN/AN/AN/AHuman Health Water and OrganismNRWQC3924%36(8%)36(8%)22(44%)12(69%)12(69%)Human Health Organism Only NRWQC3521%32(9%)32(9%)18(49%)8(77%)8(77%)Drinking Water MCL2717%25(7%)25(7%)11(59%)5(81%)5(81%)Wildlife ResultsFish Ingestion NEHC for MinksNo benchmark for comparisonN/AN/AN/AN/AN/AFish Ingestion NEHC for EaglesNo benchmark for comparisonN/AN/AN/AN/AN/AHuman Health Results—Non-CancerNon-Cancer Reference Dose for Child(recreational)5534%54(2%)54(2%)36(35%)23(58%)23(58%)Non-Cancer Reference Dose for Adult(recreational)4326%41(5%)41(5%)26(40%)16(63%)16(63%)Non-Cancer Reference Dose for Child(subsistence)7244%69(4%)69(4%)47(35%)30(58%)30(58%)Non-Cancer Reference Dose for Adult(subsistence)5836%58(0%)58(0%)39(33%)25(57%)25(57%)Source: ERG, 2015d; ERG, 2015h; ERG, 2015i.Acronyms: MCL (Maximum contaminant level); N/A (Not Applicable, no exceedances atbaseline conditions tocompare option results); NEHC (No EffectHazard Concentration); NRWQC (NationalRecommended Water Quality Criteria).a – The alternate scenario analysis encompasses a total of 172 immediate receiving waters and loadings from 148 steam electricpower plants (some of whichdischarge to multiple receiving waters). The IRW model, which excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving watersand 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, EP A 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 re movals to impaired waters under the

regulatory options.

EPA determined that 79 of the 172 immediat e 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 di scharges only) will decrease by 59 percent,

thereby reducing the pote ntial threat to human health fr om consuming contaminated fish.

Under the alternate scenario analysis, EPA id entified 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 annu ally (>99 percent reduction).

 

# 6,450 pounds of total phosphorus annua lly (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 s cenario analysis. The ta ble also presents the

percent reduction in number of impacted river miles.

7 

# The count of impaired waters excludes th e general impairment category “metals (not mercury)” and includes receiving waters

impaired for arsenic, boron, cadmium, chromium, copper, le ad, manganese, mercury, seleni um, zinc, phosphorous, nutrients,

TDS, or chlorides.



# I-34Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-31. Pollutant Removals to Impaired Waters by Impairment TypeImpairmentType/Number ofReceiving WatersbPollutantBaselineLoadings(lbs/yr)Pollutant Removals (lbs/yr) toImpaired Waters Under the Regulatory Options (PercentReduction)aOption AOption BOption COption DOption EMercury-Impaired Receiving Waters21Mercury12352.352.6100123123(42%)(43%)(81%)(99%)(>99%)Metals (Not Mercury)-Impaired Receiving Waters24Arsenic4,0202,6602,6603,5403,8303,880(66%)(66%)(88%)(95%)(96%)Boron4,420,000312,000312,000344,000353,000353,000(7%)(7%)(8%)(8%)(8%)Cadmium1,8101,3601,3601,6301,7101,720(75%)(75%)(90%)(94%)(95%)ChromiumVI25.622.022.025.525.625.6(86%)(86%)(>99%)(>99%)(>99%)Copper4,1502,4102,4103,6904,0604,060(58%)(58%)(89%)(98%)(98%)Lead2,5001,3001,3002,1702,4402,440(52%)(52%)(87%)(98%)(98%)Manganese1,030,000718,000718,000778,000800,000800,000(70%)(70%)(76%)(78%)(78%)Nickel14,7009,2109,25013,20014,50014,600(62%)(63%)(89%)(99%)(99%)Selenium20,0003,25019,10019,50019,70019,700(16%)(95%)(98%)(98%)(98%)Thallium6,6201,1901,1905,0706,4506,450(18%)(18%)(77%)(97%)(97%)Zinc23,60018,40018,40021,70022,80023,100(78%)(78%)(92%)(96%)(98%)I-35Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-31. Pollutant Removals to Impaired Waters by Impairment TypeImpairmentType/Number ofReceiving WatersbPollutantBaselineLoadings(lbs/yr)Pollutant Removals (lbs/yr) toImpaired Waters Under the Regulatory Options (PercentReduction)aOption AOption BOption COption DOption ENutrient-Impaired Receiving Waters15TotalNitrogen242,0000(0%)158,000212,000241,000241,000(65%)(87%)(99%)(99%)TotalPhosphorous2,8700(0%)0(0%)1,5202,3302,330(53%)(81%)(81%)TDS and Chlorides-Impaired Receiving Waters2ChloridesCBICBICBICBICBICBITDSCBICBICBICBICBICBISource: 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 wastestreams.c – The EPA impaired water database listed 24immediate receiving waters as impaired based on the “metal, other than mercury” impairment category. Of those24 immediate receiving waters, 13 receivingwaters are also listed as impaired for one or more specific metals (arsenic, cadmium, manganese, selenium, andzinc). One additional immediate receiving water is impaired for boron (but not includedin the “metals, other than mercury” impairment category).d – Total phosphorous and total nitrogen loadings are presented with this impairmentcategory. Total nitrogen loadings are thesum of total Kjeldahl nitrogen andnitrate/nitrite as N loadings.I-36

# Appendix I—Analysis for Alternate Scenario with Clean Power Plan



# Table I-32. Pollutant Removals to the Grea t 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 Kj eldahl nitrogen and nitrate/nitrite as N loadings.



# I-37Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-33. Key Environmental Improvements for Downstream Waters Under the Regulatory OptionsEvaluation CriteriaNumber of RiverMiles ExceedingCriteria UnderBaseline ConditionsNumber of River-Miles Exceeding Criteria(Percent Reduction from Baseline Conditions) Under the Regulatory OptionsaOption AOption BOption COption DOption EWater Quality ResultsFreshwater Acute NRWQC412395(4%)395(4%)393(5%)388(6%)388(6%)Freshwater ChronicNRWQC605592(2%)560(8%)542(10%)514(15%)514(15%)Human Health Water andOrganism NRWQC4,0503,390(16%)3,390(16%)2,480(39%)1,930(52%)1,710(58%)Human Health Organism-onlyNRWQC1,5001,230(18%)1,230(18%)1,030(31%)781(48%)713(52%)Drinking WaterMCL751725(3%)720(4%)629(16%)487(35%)487(35%)Wildlife ResultsFish Ingestion NEHC for Minks1,070893(17%)862(19%)720(33%)524(51%)503(53%)Fish Ingestion NEHC for Eagles1,8701,580(15%)1,560(16%)1,260(32%)957(49%)899(52%)Human Health Results—Non-CancerNon-cancer reference dose forchild (recreational)5,8004,380(24%)4,380(25%)2,890(50%)2,250(61%)2,080(64%)Non-cancer reference dose foradult (recreational)3,4202,830(17%)2,820(17%)1,960(43%)1,430(58%)1,350(61%)Non-cancer reference dose forchild (subsistence)9,2407,790(16%)7,760(16%)5,520(40%)4,490(51%)4,080(56%)Non-cancer reference dose foradult (subsistence)6,5405,050(23%)5,050(23%)3,330(49%)2,620(60%)2,410(63%)I-38Appendix I—Analysis for Alternate Scenario with Clean Power PlanTable I-33. Key Environmental Improvements for Downstream Waters Under the Regulatory OptionsEvaluation CriteriaNumber of RiverMiles ExceedingCriteria UnderBaseline ConditionsNumber of River-Miles Exceeding Criteria(Percent Reduction from Baseline Conditions) Under the Regulatory OptionsaOption AOption BOption COption DOption EHuman Health Results—CancerCancer risk for child(recreational)227216(5%)216(5%)211(7%)210(8%)207(9%)Cancer risk for adult(recreational)286263(8%)263(8%)251(12%)246(14%)245(14%)Cancer risk for child(subsistence)262241(8%)241(8%)239(9%)235(10%)231(12%)Cancer risk for adult(subsistence)414375(9%)375(9%)355(14%)328(21%)304(26%)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. Downstream receiving waterconcentrations are calculated until one of three conditions occurs: 1) the discharge travels 300 kilometers (km) downstream; 2)the discharge travels downstreamfor a week; or 3) the concentration reaches 1 x 10-9milligrams per liter (mg/L).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 pres ented in the environmental assessment (EA)

report are based on loadings datasets that differ from those that are summarized in the Technical

Development Document for Effluen t 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 ev aluates the difference between the two pollutant

loadings datasets (the “EA load ings” 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 indu stry 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 lo adings would have on the overall counts of

exceedances identified in the EA Report, EPA took the following steps:

1. EPA determined how many immediate receiv ing 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 w hole, to zinc (whose loadings are 14 percent

lower in the TDD loadings). By assuming th at the difference in loadings would result

in an equal change in the count of exceed ances, EPA assumed that use of the TDD

loadings would have resulted in 14 per cent fewer exceedances among this group of

immediate receiving waters.

4. EPA repeated this process for the remaini ng 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 analys is, which demonstrates that use of the TDD

loadings in place of the EA lo adings 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 recei ving 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 sedi ment 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 inst ead 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 presen ts the industry-wide pollutant -specific removals under the

regulatory options (reflecting chan ges in the industry as a result of the CPP). Table I-25 through

Table I-30 present the pollutant-specific e nvironmental improvements under the regulatory

options. A comparison of the values in these tabl es indicates that an industry-wide pollutant

loading reduction of x under the regulatory options usuall y 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 pe rcent; exceedances reduced by approximately 7 to

14 percent.

 

# Arsenic : Loadings reduced by 56 percent; exce edances 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 exceedan ces in the EA for each pollutant. Based on this

observation, EPA estimates that use of the T DD loadings would resu lt 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-2Appendix J —EA Loadings and TDD Loadings: Sensitivity AnalysisTable J-1. Comparison of Annual Baseline Pollutant Discharges from Steam Electric Power Plants (EvaluatedWastestreams), EA Loadingsversus TDD LoadingsPollutantBaseline LoadingsOption D RemovalsOption D RemovalsEA Version(lbs/yr)TDDVersion(lbs/yr)PercentChangeEA Version(lbs/yr)TDDVersion(lbs/yr)PercentChangeEA Version(%)TDDVersion(%)PercentChangeArsenic22,20020,100-9.4%20,70018,700-10%93%93%-0.73%Cadmium10,9008,290-24%10,3007,660-26%94%92%-1.9%Chromium (VI)1191190%1191190%100%100%0%Copper24,00016,400-32%23,40015,800-33%98%97%-1.1%Lead14,6007,670-47%14,2007,340-48%98%96%-2.0%Mercury1,180992-16%1,150961-16%97%97%-0.47%Nickel94,20061,900-34%92,40060,200-35%98%97%-0.87%Selenium113,000115,0001.4%110,000111,0001.4%97%97%0.032%Thallium43,90043,9000%42,80042,8000.0%98%98%-0.020%Zinc145,000124,000-14%138,000117,000-15%95%95%-0.79%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 Baselin e Exceedances (Using EA Loadings) and

Approximated Baseline Exceedan ces (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 wate rs and loadings from 148

steam electric power plants (some of which discharge to multiple r eceiving waters). The IRW model, which

excludes the Great Lakes and estuaries, encompasses a total of 163 immediate receiving waters and loadings from

143 steam electric power plants.

b – These rows indicate the number of immediate receiving waters whose me dian 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