1 

## Regulatory Impact Analysis For EPA’s Proposed RCRA Regulation

Of Coal Combustion Residues (CCR) Generated by the Electric Utility Industry

Prepared by:

US Environmental Protection Agency Office of Resource Conserva tion & Recovery (ORCR) (formerly Office of Solid Waste) 1200 Pennsylvania Avenue NW (Mailstop 5305P) Washington DC, 20460 USA

30 April 20102 

## Acknowledgements

EPA Contractor Support & EP A Staff Assistance for this RIA

In 2009 under EPA contract EP-W-07-0011, work assignment 2-33, Industrial Economics Inc. (C ambridge MA) and its subcontractor DPRA Inc (Minneapolis MN) provided data analysis support for iden tifying affected enti ties and estimating baseline CCR disposal practices and costs ( Chapter 3 ), and for estimating costs of regulatory engineering control requirements ( Chapter 4) in this RIA.

EPA ORCR staff contributing to this RIA: Rachel Alford, Ri chard Benware, Mark Eads, Christina Kager, and Scott Palmer.3 

## Table of Contents

Executive Summary 5 Chapter 1: Problem Statement: The Need for RC RA Regulation of CCR Disposal 13 Chapter 2: Potentially Affected Industries & RCRA Regulatory Options 18 2A. Identity of Potentially Affected I ndustries (Electric Utility Industry) 18 2B. Other Industries with CCR Disposal Units Not Covered by the Proposed Rule 20 2C. RCRA Regulatory Options Evaluated in this RIA 24 Chapter 3: Baseline CCR Disposal in the Electric Utility Industry 27 3A. Identity of Coal-Fired Electric Utility Plants 27 3B. Types of CCR Disposal Units 33 3C. Types of CCR Generated and Annual Quantities 36 3D. Size of CCR Disposal Units 41 3E. Cost of Baseline CCR Disposal 42 Chapter 4: Estimated Cost for RCRA Regulation of CCR Disposal 67 4A. EPA_s Prior Cost Estimates for RCRA Regulation of CCR Disposal at Electric Utility Plants 67 4B. Regulatory Cost Estimation Algorithms & Results 68 4B.1 Engineering Control Costs 69 4B.2 Ancillary Regulatory Requirement Costs 73 4B.3 Land Disposal Restriction ( CCR Dewatering Treatment) Cost 83 4C. State-by-State Distribution of Regulatory Cost 105 4D. Cost Estimation Uncertainty 107 Chapter 5: Potential Benefits of RC RA Regulation of CCR Disposal in the Electric Utility Industry 110 5A. Groundwater Protection Benefits (Avoided Future Cancer Risks & Groundwater Remediation Costs) 111 5B. Preventing Future CCR Impoundment Catastrophic Failures (Avoided Futu re Cleanup Costs) 133 5C. Induced Effect of RCRA Regulation of CC R Disposal on Future CCR Beneficial Use 149 Chapter 6: Comparison of Regulatory Benefits to Costs 191 6A. Comparison of Benefits to Costs Based on Alternative Discount Ra tes (7%, 3%, 0%) 191 6B. Factors Applied for Scaling Benefits and Costs to the Regulatory Options 198 Chapter 7: Supplemental Analyses Required by Congressi onal Statutes or White Ho use Executive Orders 204 7A. Electricity Price Impact (Executive Order 13211) 204 7B. Small Business Impact Analysis (RFA/SBREFA) 208 7C. Minority & Low-Income Populations Near Electr ic Utility Plants (Executive Order 12898) 216 7D. Child Population Statistics (Ex ecutive Order 13045) 229 7E. Unfunded Mandates (UMRA) & Federalism Imp lications Analysis (Executive Order 13132) 237 Appendix Provided as separate document (the contents of the Appendix are disp layed on the next page of this RIA)4 

## Table of Appendices

Note: Because of its large number of pages (>400 pages), the Appe ndix is provided as a separate companion document to this RIA.

Appendix A Chronology of EPA_s Regulatory Evaluation of CCR (1978 to March 2009)

Appendix B List of Other Industries with Coal-Fired Electricity Plants Not Cove red by the Proposed Rule or this RIA

Appendix C List of 495 Operating Electric Utility Pl ants Potentially Affected by the CCR Rulemaking (2007)

Appendix D Identity of 200 Entities Which Own the 495 Po tentially Affected Electr ic Utility Plants (2007)

Appendix E Baseline State Government Regulatory Requirement s for CCR Disposal Units in Top-34 Coal Utility States

Appendix F Baseline Engineering Contro ls Installed at CCR Disposal Units in the Electric Utility Industry

Appendix G Description of CCR Landfill & Surfa ce Impoundment Engineering Control Cost Model

Appendix H Baseline Cost Estimates for CCR Disposal by the Elect ric Utility Industry

Appendix I Geological Conditions at Electric Utility Industr y CCR Disposal Unit Locations

Appendix J Incremental Regulatory Cost Estimates for Co mpliance with the CCR Proposed Rule Regulatory Options

Appendix K Appendices Supporting the Regulatory Benefits Evaluation

Appendix L Electricity Price Impact Anal ysis Spreadsheet (Executive Order 13211)

Appendix M Small Entity Impact Data & Analysis Spreadsheet (RFA/SBREFA)

Appendix N Minority & Low-Income P opulation Data (Executive Order 12898)

Appendix O Child Population Data (Executive Order 13045)

Appendix P UMRA Written Statement

Appendix Q Documentation for EPA_s Social Cost Estimate Assigned to the TVA Ki ngston 2008 CCR Impoundment Failure Event5 

## Executive Summary

This RIA evaluates the expected regulato ry compliance costs, economic and environm ental benefits, and potential impact on CCR b eneficial use, of EPA_s proposed regulation of coal combustion residual (CCR) disposal by coal-f ired electric utility plants. The CCR di sposal regulatory options evaluated in this RIA are based on EPA_s stat utory authority contained in th e 1976 Resource Conservation and Recovery Act (RCRA). The main findings of this RIA are summarized below according to six sections:

ES-1: Regulatory Options Evaluated in this RIA ES-2: Benefits of Avoided Future Groundwater Contaminati on (Human Health Protection & Avoided Remediation Costs) ES-3: Benefits of Avoided Future CCR Impoundment Structural Failures (Avoided Cleanup Costs) ES-4: Economic and Environmental Benefits from Future Increase in CCR Beneficial Uses by Other Industries ES-5: Regulatory Compliance Costs ES-6: Comparison of Regulatory Benefits to Costs



### ES-1: Regulatory Options Evaluated in this RIA

This RIA evaluates three options for RCRA re gulation of CCR disposal at coal-fired el ectric utility plants. All options (a) ma intain the existing Bevill regulatory exclusion for CCR benefici al uses, and (b) propose the same set of 10 custom-tailored engineering controls (i .e., technical design and operating standard s) for CCR disposal units:

1. Subtitle C gSpecial Wasteh Option : Regulate CCR landfills and impoundments as a g special waste h under Subtitle C requirements, and would require phase out of im poundments within five years.

2. Subtitle D Option (version 2) : Composite liners required for all (i.e., existing a nd future new) CCR impound ments but only for new landfills. For any CCR landfills and impoundments that closed befo re the effective date, there would be no regulatory controls over those units, unless the states c hoose to adopt controls over such units. Also, all surface impoundments (e xisting and new) wou ld need to have composite liners within 5-years of the effective date.

3. Subtitle gD primeh Option : Composite liners required only for new impoundments and landfills; unlined units could continue to operate. This approach would be the same as the Subtitle D option above, except that existi ng impoundments would not be requir ed to retrofit and install a composite liner, or close.6 

### ES-2: Benefits of Avoided Future Groundwater Contamination (Human He alth & Avoided Remediation Costs)

By establishing management and permit standards for CCR dispos al units under RCRA, the proposed regulatory options will reduce uncontrolled releases and cancer risks, and improve detection a nd, if necessary, response to future groundwater contamination. This RIA quantifies two components of gr oundwater protection benefits: (a ) human cancer risks avoided fro m drinking contaminated groundw ater, and (b) groundwater contamination remediation costs avoided. Summary Exhibit 1 below presents the monetized results of this evaluation.

x Estimate of avoided human cancer risks from avoided future groundwater contamination by CCR disposal units:

o Individual skin cancer risks avoided (by eliminating the groundwater pathway for ar senic at CCR impoundments) are estimated up to 2 x 10 -2 (i.e., a probability equal to 2 individual human skin cancer incidence risks for every 100 persons exposed) using the current IRIS skin cancer slope factor for arsenic.

o 30,400 people use drinking water wells within on e mile of coal-fired elec tric utility plants; of which 8,150 (27%) are children

.
o Taking into account current CCR dis posal unit designs, an estimated 145 (using the IRIS cancer slope factor) to 2,509 (using the NRC lung and bladder cancer slope factor 1 ) future human cancer risks are expected to occur in absence of the proposed RCRA regulation, based on drinking wate r exposure to arsenic in CCR.

x Other human health risks from CCR dispos al units not quantified in this RIA:

o Human non-cancer risks, includi ng from selenium, cobalt, nitrate/nitrite, and molybdenum, which may be released to groundwater at levels above the MCL or 3 times the human hazard quotient (HQ).

o Cancer and non-cancer risks from arsenic and other metals rel eased in effluent from CCR impoundments to surface waters.

Summary Exhibit 1 Future Avoided Human Cancer Risks & Avoide d Groundwater Remediation Cost Benefits ($millions present value @7% discount rate over 50-years)

Groundwater Protection Benefit Category Subtitle C special waste Subtitle D (version 2) Subtitle gD primeh

Groundwater Remediation Costs Avoided $466 $168 $84 Monetized Value of Cancer Risks Avoided $504 $207 $104 Total = $970 $375 $188



### ES-3: Benefits of Avoided Future CCR Impoundm ent Structural Failures (Avoided Cleanup Costs)

This RIA estimated future avoided cleanup costs from catastrophic impoundment failures, like the one that occurred at TVA_s Kin gston TN coal-fired electricity plant in December 2008, which would be prevented under the proposed rule. Given the increasing age of C CR

1 EPA calculated a new cancer slope factor fo r arsenic from data in the National Research Council report gArsenic in Drinking Wa ter: 2001 Updateh at http://www.nap.edu/openbook.php?isbn=03090762937 impoundments, the relative number that present high or signifi cant hazard potential, and the hi story of CCR impoundment failure s to date, this RIA presents three alternative scenario s of future catastrophic failures, th e result for which are displayed in Summary Exhibit 2 below:

x Failure Scenario #1 : Extrapolation of future CCR impoundment failure probability based on the relative (a) recent historical occurrence frequency, (b) CCR quantity release magnit ude, and (c) cleanup costs, associated with three recent (2005, 2008, 2009) CCR impoundment failures which exceeded 1 m illion gallons in release quantity each.

x Failure Scenario #2 : Assumes 10% of CCR impoundments in the high failure risk group (i.e., above 40 feet tall and over 25 years old) fail over the next 20 years in absence of RCRA regulation. 2

x Failure Scenario #3 : Assumes 20% of CCR impoundments in the high failure risk group (i.e., above 40 feet tall and over 25 years old) fail over the next 20 years in absence of RCRA regulation.

Summary Exhibit 2 Avoided Future CCR Impoundment Ca tastrophic Failure Cleanup Costs ($millions present value @7% discount rate)

Impoundment Failure Scenarios Subtitle C special waste Subtitle D (version 2) Subtitle gD primeh

Failure Scenario #1: Extrapolation of three recent (2005, 2008, 2009) CCR impoundment failure events $5,285 $2,378 $1,216

Failure scenario #2: Assuming 10% of 96 high-risk impoundments fail $8,366 $3,795 $1,897

Failure Scenario #3: Assuming 20% of 96 high-risk impoundments fail $16,732 $7,590 $3,795

The proposed regulation has categories of ot her benefits from avoiding future CCR impound ment structural failures which this RI A did not quantify and monetize, including potential avoided costs associated with a few po ssible benefit categories:

1. Litigation costs : Avoided litigation and re lated costs associated with such damage events.
2. Riparian damages: Reduct ion of toxic chemical contaminated e ffluent discharges from CCR impoundment s to surface waters (i.e., rivers and lakes) through future phase-out of surface impoundments. 3

3. Non-cancer health risks : Reduction in human health risks from future reduc tion in human exposure to non-carcinogenic but otherwise toxic chemicals contained in CCR, such as selenium, cobalt, n itrate/nitrite, and molybdenum, which, as currently managed in CCR

2 Based on the responses to our CERCLA 104(e) information requests to utilities with impoundments, there are 96 impoundments tha t meet these criteria. However, this RIA estimates that 16 of these impoundments have closed or are expected to close before the CCR rule is finalized and goes into effect. Therefore, this analysis removed these 16 impoundments and based the estimated future impoundment failure cleanup costs on a subset of 80 CCR impoundments meeti ng the oat risk_ criterion.

3 EPA is developing a regulatory proposal under the Clean Water Act to revise the current effluent guidelines for steam electr ic utilities. Current guidelines only control pH, total chlorine, and total su spended solids (TSS). EPA_s proposed CCR rule would el iminate CCR surface impoundments, elimin ating much of the risk that would be addressed under revisions to the effluent guidelines, including risks posed by arsenic, selenium, mercury, cadmium, copper, chr omium, and nickel.8 disposal units, can exceed the human health hazard quotient (HQ) or Maximum Contaminant Limit (MCL). Chapter 5 of this RIA provides a list of contaminants of concer n in CCR surface impoundment effluent and poten tial human health and environmental eff ects. 4. Dry CCR disposal risks : Human health effects from impr operly managed dry disposal, which are based on ongoing research by EPA_s Office of Research & Development (ORD ), may pose greater risks than prev iously estimated by EPA in 2000 and 2007.



### ES-4: Economic & Environmental Benefits from Future In crease in CCR Beneficial Us es by Other Industries

This RIA evaluated the potential impact th at the CCR proposed rule may have on benefici al uses of CCR by ot her industries. Bas eline CCR beneficial use at the current 62 million tons per year rate (2009) is estimated in this RIA to provide $26 billion per year in nationwide social benefits consisting of: (a) materials cost savings, plus (b) lifecycle avoided pollu tion benefits, plus (c ) avoided CCR disposa l costs to the electric utility industry. On a present value basis over the 50-year future period- of-analysis (2012-2061) applied in this RIA , the present value of CCR beneficial use amounts to $778 billi on (@7% discount). Although the industrie s which use CCR for beneficial uses are no t subject to the requirements of the CCR proposed rule, this RIA presents th ree alternative scenarios of pot ential induced effect of the CCR rule on future CCR beneficial use, consisting of increased use (scenario #1), decreased use (scenario #2), and no cha nge (scenario #3). This RIA quanfities both scenario #1 and scenario #2 incrementa lly in relation to the gno changeh scenar io #3. EPA believes the increasing benefic ial use scenario #1 is most likely because (a) the proposed CCR regulation is targ eted at CCR disposal not at CCR beneficial us es, (b) all CCR regulatory options retain the existing RCRA Bevill exemption for CCR benefici al uses, and (c) the added cost of regulatory compliance will make beneficial use relatively more co st-effective and represent an g avoided disposal cost incentive h 4 to electric utility plants to increase their supply of CCR to industrial markets for CCR as a raw or intermediate input into industrial manufacturing and construction activities. Furthermore, EPA does not believe that market gstigmah of CCR regulation under RCRA Subtitle C --- as alleged in numerous stakeholder letter s to the EPA in 2009 --- will result in a reduc tion in future annual CCR beneficial use, becau se the proposed rule de signates the Subtitle C option as a

g special waste h rather than as a g hazardous waste .h Summary Exhibit 3 below presents the results for bot h the increase scenario #1 and the decrease scenario #2.

4 The concept of g avoided disposal cost incentive h is recognized and defined by the American Coal Ash Association (ACAA) on its website as follows:

g If a [coal-fired electric utility] plant markets its [CCR] into comm ercial applications, then disposal of this [CCR] is not req uired. Not only is a revenue stream created for the [coal-fired electricity plant] but also the need to dispose of the [CCR] is avoided. As discussed above, dispo sal is not just the transportation and placement of [CCR] in a disposal site. The need for future spa ce is a concern. If [CCR is] marketed, then the need to develop future [CCR disposal] sites (including land acquisition, permitting, design and construction costs) is avoided .... It is not uncommon for a company to help offset the costs of transportation or placement at construction sites by providing the contractor or trucking firm a payment of some sort. For example, if the cost of disposal at a plant is normally four dollars a ton, then the company may arrange a payment of four dollars or less to the contractors to cover transportation and pl acement costs. The difference between the amount of this payment and the cost of disposal is also referred to as “avoided disposal costs .h Source: ACAA Frequently Asked Question nr. 14 webpage at: http://acaa.affiniscape.com/di splaycommon.cfm?an=1&subarticlenbr=5#Q149 Summary Exhibit 3 Induced Effect of RCRA Regulation of CCR Disposal on Future Annual CCR Beneficial Use ($millions present value @7%)

Scenarios Subtitle C special waste Subtitle D (version 2) Subtitle gD primeh

Scenario #1: Induced Increase in CCR Beneficial Use Percentage increase relative to baseline CCR beneficial use +11% +4% +2% Economic market value +$5,560 +$2,224 +$890

Lifecycle social value +$84,489 +$33,796 +$13,518
Scenario #2: Induced Decrease in CCR Beneficial Use Percentage decrease relative to baseline CCR be neficial use -18% No impact No impact Economic market value -$18,7 44 No impact No impact

Lifecycle social value -$233, 549 No impact No impact



### ES-5: Regulatory Compliance Costs

Chapter 4 of the RIA presents the estimated costs for industry compliance (and for government implementation) of each regulatory option. Summary Exhibit 4 below presents the estimated costs on a present value basis. The RIA presents three catego ries of regulatory compliance cost. These regulatory costs are incremental to an estimated $5,556 million per year average an nual baseline (i.e., current) c ost to the electric utility industry for CCR disposal, which represents a baseline cost of $76,678 million in present value on a 7% and 50-year dis counting basis.

Summary Exhibit 4 Estimate of Regulatory Impl ementation & Compliance Cost ($millions present value @7% over 50-years)

Cost Category Subtitle C special waste Subtitle D (version 2) Subtitle gD primeh 1. Engineering controls $6,780 $3,254 $3,254 2. Ancillary costs $1,480 $5 $5 3. Dry conversion cost $12,089 4,836 $0 Total Cost (1+2+3) = $20,349 $8,095 $3,259 Increase over baseline CCR disposal cost = +27% +11% +4%

The dry conversion cost estimate incorpor ates projection of the recent (1995-2009) el ectric utility industry trend converting a way from wet CCR disposal to dry CCR disposal. In fact , there are several upcoming EPA regulations which could accelerate this trend but ar e not reflected in the cost estimate of this RIA. These are anticipated rule s under the Clean Air Act which w ill increase the installation of air pollution scrubbers and other air emission control tec hnology at coal-fired power plants, as well as new wastewater effluent guidelines u nder the Clean Water Act which will require installation of treatment technology for wastewater disc harges from CCR impoundments to surface wa ters.10 

### ES-6: Comparison of Regulatory Benefits to Industry Compliance Costs

The set of three Summary Exhibits 5, 6 and 7 below compare the estimated regulatory costs to estimated regulatory benefits, using gnet benefitsh and gbenefit-cost ratio h comparison indicators. The three Exhibits ar e based on the three alte rnative scenarios abou t the potential induced impact of the CCR rule on future annual CCR beneficial us e as presented in Section 5C of this RIA (i.e., increase, decr ease, and no change, respectively). All three Summary E xhibits below present costs, benefits, a nd net benefits on both a present value and average annualized equivalent basis, based on a 7% discount rate. A set of exhibits in Chapter 6 of this RIA present these values based on a 3% rate.

Summary Exhibit 5 Comparison of Regulatory Benefits to Costs Scenario #1 – Induced Increase in Future Annual CCR Beneficial Use ($Millions @2009$ Prices and @7% Discount Rate over 50-Year Future Period-of-Analysis 2012 to 2061)

Impact Element Subtitle C gSpecial Wasteh Subtitle D (version 2) Subtitle gD primeh
A. Present Values: 1. Regulatory Costs (1A+1B+1C): $20,349 $8,095 $3,259 1A. Engineering Controls $6,780 $3,254 $3,254 1B. Ancillary Regulatory Requirements $1,480 $5 $5 1C. Conversion to Dry CCR Disposal $12,089 $4,836 $0 2. Regulatory Benefits (2A+2B+2C+2D): $87,221 to $102,191 $34,964 to $41,761 $14,111 to $17,501 2A. Monetized Value of Human Cancer Risks Avoided $504 (726 cancer risks) $207 (296 cancer risks) $104 (148 cancer risks) 2B.Groundwater Remediation Costs Avoided $466 $168 $84 2C. CCR Impoundment Failure Costs Avoided $1, 762 to $16,732 $ 793 to $7,590 $405 to $3,795 2D. Induced Impact on Future CCR Beneficial Use $84,489 $33,796 $13,518 3. Net Benefits (2 - 1) $66,872 to $81,842 $26,869 to $33,666 $10,852 to $14,242 4. Benefit/Cost Ratio (2 / 1) 4.286 to 5.022 4.319 to 5.159 4.330 to 5.370 B. Average Annualized Equivalent Values:* 1. Regulatory Costs (1A+1B+1C) $1,474 $587 $236 1A. Engineering Controls $491 $236 $236 1B. Ancillary Regulatory Requirements $107 <$1 <$1 1C. Conversion to Dry CCR Disposal $876 $350 $0 2. Regulatory Benefits (2A+2B+2C+2D): $6,320 to $7,405 $2,533 to $3,026 $1,023 to $1,268 2A.Monetized Value of Human Cancer Risks Avoided $37 $15 $8 2B. Groundwater Remediation Costs Avoided $34 $12 $6 2C. CCR Impoundment Failure Cleanup Costs Avoi ded $128 to $1,212 $58 to $550 $29 to $275 2D. Induced Impact on Future CCR Beneficial Use $6,122 $2,450 $980 3. Net Benefits (2 - 1) $4,845 to $5,930 $1,947 to $2,439 $786 to $1,032 4. Benefit/Cost Ratio (2 / 1) 4.286 to 5.022 4.319 to 5.159 4.330 to 5.370 * Note: Average annualized equivalent values calculated by multiply ing 50-year present values by a 50-year 7% discount rate gca pital recovery factorh of 0.07246.11 Summary Exhibit 6 Comparison of Regulatory Benefits to Costs Scenario #2 – Induced Decrease in Future Annual CCR Beneficial Use ($Millions @2009$ Prices and @7% Discount Rate over 50-Year Future Period-of-Analysis 2012 to 2061)

Impact Element Subtitle C gSpecial Wasteh Subtitle D (version 2) Subtitle gD primeh
A. Present Values: 1. Regulatory Costs (1A+1B+1C) $20,349 $8,095 $3,259 1A. Engineering Controls $6,780 $3,254 $3,254 1B. Ancillary Costs $1,480 $5 $5 1C. Conversion to Dry CCR Disposal $12,089 4,836 $0 2. Regulatory Benefits (2A+2B+2C+2D): ($230,817) to ($215,847) $1168 to $7,965 $593 to $3,983 2A. Monetized Value of Human Cancer Risks Avoided $504 (726 cancer risks) $207 (296 cancer risks) $104 (148 cancer risks) 2B. Groundwater Remediation Costs Avoided $466 $168 $84 2C. CCR Impoundment Failure Costs Avoided $1, 762 to $16,732 $ 793 to $7,590 $405 to 3,795 2D. Induced Impact on CCR Beneficial Use ($233,549) $0 (no impact) $0 (no impact) 3. Net Benefits (2-1) ($251,166) to ($236,196) ($6,927) to ($130) ($2,666) to $724 4. Benefit/Cost Ration (2/1) (11.343) to (10.607) 0.144 to 0.984 0.182 to 1.222 B. Average Annualized Equivalent Values:* 1. Regulatory Costs (1A+1B+1C) $1,474 $587 $236 1A. Engineering Controls $491 $236 $236 1B. Ancillary Costs $107 $0.36 $0.36 1C. Dry Conversion $876 $350 $0 2. Regulatory Benefits (2A+2B+2C+2D): ($16,725) to ($15,640) $85 to $577 $43 to $289 2.A Monetized Value of Human Cancer Risks Avoided $37 $15 $8 2.B Groundwater Remediation Costs Avoided $34 $12 $6 2.C CCR Impoundment Failure Cleanup Costs Avoi ded $128 to $1,212 $57 to $550 $29 to $275 2.D Induced Impact on CCR Beneficial Use ($16,923) NA NA 3. Net Benefits (2-1) ($18,199) to ($17,115) ($502) to ($9) ($193) to $52 4. Benefit/Cost Ration (2/1) (11,347) to (10.610) 0.145 to 0.983 0.182 to 1.225 * Note: Average annualized equivalent values calculated by multiply ing 50-year present values by a 50-year 7% discount rate gca pital recovery factorh of 0.07246.12 Summary Exhibit 7 Comparison of Regulatory Benefits to Costs Scenario #3 – No Impact on Fu ture Annual CCR Beneficial Use ($Millions @2009$ Prices and @7% Discount Rate over 50-Year Future Period-of-Analysis 2012 to 2061)

Impact Element Subtitle C gSpecial Wasteh Subtitle D (version 2) Subtitle gD primeh
A. Present Values: 1. Regulatory Costs (1A+1B+1C) $20,349 $8,095 $3,259 1A. Engineering Controls $6,780 $3,254 $3,254 1B. Ancillary Costs $1,480 $5 $5 1C. Conversion to Dry CCR Disposal $12,089 4,836 $0 2. Regulatory Benefits (2A+2B+2C+2D): $2,732 to $17,702 $1168 to $7,965 $593 to $3,983 2A. Monetized Value of Human Cancer Risks Avoided $504 (726 cancer risks) $207 (296 cancer risks) $104 (148 cancer risks) 2B. Groundwater Remediation Costs Avoided $466 $168 $84 2C. CCR Impoundment Failure Costs Avoided $1, 762 to $16,732 $ 793 to $7,590 $405 to $3,795 2D. Induced Impact on CCR Beneficial Use $0 (no change) $0 (no change) $0 (no change) 3. Net Benefits (2-1) ($17,617) to ($2,647) ($6,927) to ($130) ($2,666) to $724 4. Benefit/Cost Ration (2/1) 0.134 to 0.870 0.144 to 0.984 0.182 to 1.222 B. Average Annualized Equivalent Values:* 1. Regulatory Costs (1A+1B+1C) $1,474 $587 $236 1A. Engineering Controls $491 $236 $236 1B. Ancillary Costs $107 $0.36 $0.36 1C. Dry Conversion $876 $350 $0 2. Regulatory Benefits (2A+2B+2C+2D): $198 to $1,283 $85 to $577 $43 to $289 2.A Monetized Value of Human Cancer Risks Avoided $37 $15 $8 2.B Groundwater Remediation Costs Avoided $34 $12 $6 2.C CCR Impoundment Failure Cleanup Costs Avoi ded $128 to $1,212 $57 to $550 $29 to $275 2D. Induced Impact on CCR Beneficial Use $0 $0 $0 3. Net Benefits (2-1) ($1,277) to ($192) ($502) to ($9) ($193) to $52 4. Benefit/Cost Ration (2/1) 0.134 to 0.870 0.145 to 0.983 0.182 to 1.225 * Note: Average annualized equivalent values calculated by multiply ing 50-year present values by a 50-year 7% discount rate gca pital recovery factorh of 0.07246.13 

## Chapter 1 Problem Statement: The Need for RCRA Regulation of CCR Disposal

1A. Institutional Context

For purpose of evaluating Federa l regulations, the 1993 Ex ecutive Order 12866 gRegulatory Plan ning and Reviewh (Section 1(b)(1) ) requires each Federal regulatory agency to identify the problem that it in tends to address, including wh ere applicable, the failures of private markets or public institutions that warrant new agency action, as well as to assess the significan ce of the problem. Inline with this re quirement, this Chapter provides a problem statement consisting of the institu tional context (i.e., prior EPA act ions), significance of the pro blem (i.e., evidence of environmental damages), and ch aracterization of market failure.

In September 2003, the White House Office of Management and Budge t (OMB) updated its guidance to federal agencies on the develo pment of regulatory analysis required under Secti on 6(a)(3)(c) of the 1993 Executive Order 12866 5 gRegulatory Planning a nd Review.h The updated guidance is OMB_s September 17, 2003 gCircular A-4 Regulatory Analysis.h 6 Section A (Introduction) of Circular A-4 defines three key elements of good regulatory analysis:

1. Statement of the need for the proposed regulation.
2. Examination of alternative approaches.
3. Evaluation of the benefits and costs (qua ntitative and qualitative) of the proposed regulation and the main alternatives.

Concerning the first basic elemen t listed above (i.e., statement of the need for regulation), Section B of Circular A-4 require s federal agencies to demonstrate that the proposed regulation is necessary. The Circular defines four categorie s of possible regulatory need:

1. Required by law : If the need results from statutory or judici al directive, agencies should describe the:

a. specific authority for the proposed regulation b. extent of discretion available to the agency

c. regulatory instruments available
2. Necessary to interpret law

. 3. Market failure : Three examples cited in Circular A-4 (pages 4 & 5) are:

a. externality, common property resources and public goods b. non-competitive market power

c. inadequate or asymmetric information
4. Other social purposes : Six examples cited in Circular A-4 (page 5) are:

a. make government operate more efficiently

5 1993 Executive Order 12866 (11 pages) is availabl e at: http://www.whitehouse. gov/OMB/inforeg/eo12866.pdf

6 2003 OMB Circular A-4 (48 pages) is available a t: http://www.whitehouse.gov/O MB/Circulars/a004/a-4.pdf14 b. redistribute resource s to select groups

c. prohibit discrimination d. protect privacy

e. permit more personal freedom f. promote other democratic aspirations

As explained below, EPA_s proposed RCRA 7 regulation of coal combustion residual (CCR) dispos al at coal-fired electricity plants is both required by law and will correct market failure

.



### 1B. EPA’s Proposed Regulation of CCR Disposal Is Required by Law

In 1976, Congress amended the 1965 Solid Waste Disposal Act (the first federal statute that specifically focused on improving s olid waste disposal methods) by adding industrial hazar dous waste management requirements as Sub title C, among other new requirements. Th is amendment is the 1976 Resource Conservation & Recovery Act (RCRA). The EPA_s regulator y evaluation of coal combustion residues (CCR) dates back to 1978, two years after enactment of RCRA. In December 1978, the EPA propos ed the first industrial hazardous waste regulations to implement Subtitle C (i.e., Sections 3001 to 3020 of RCRA). At that time, the EP A recognized that certain large-volume indu strial wastes, including wastes from the combustion of fossil fuels (aka gCCRh as named in this RIA), might warrant special treatment under RC RA regulation. On 18 December 1978, EPA proposed but deferred and neve r finalized a relatively limite d set of ten RCRA Subtitle C industrial hazardous waste regulations for the management of CCR. 8 Included in this deferral of hazardous waste requirements were six categories of industrial wastes --- which EPA termed gspecial wastesh 9 --- until further study and assessment could be completed by EPA to determine their risk to human health and the environment. Th e six categories of special wastes included:

1. Cement kiln dust
2. Mining waste
3. Oil and gas drilling muds a nd oil production brines
4. Phosphate rock mining, benefici ation, and processing waste
5. Uranium waste
6. Utility waste (i.e., fossil fuel combus tion waste by electric utility plants)

These wastes typically are generated in la rge volumes and, at the time, were believed to possess less risk to human health and the environment than the wastes being identified for regul ation as RCRA hazardous waste. On 12 Oc tober 1980, Congress enacted the Solid Waste Disposal Act Amendments of 1980 (Public Law 96-482) which amended RCRA in se veral ways. Pertinent to gsp ecial wastesh were the Bentsen and

7 RCRA = Resource Conservation & Recovery Act of 19 76: http://www.epa.gov/waste/laws-regs/rcrahistory.htm

8 Federal Register , Vol. 43, No. 243, 18 December 1978, page 59015, section 250 .46-2 gUtility Wasteh of gHazardous Waste Guidelines and Regulatio ns.h This action proposed the following ten regulatory conditions: (a) waste analysis standards, (b) waste site selection standards, (c) waste s ite security, (d) waste shipment manifesting, (e) recordkeeping, (f) reporting, (g) waste site visual inspections, (h) waste site closure, (i) wast e site post-closure care, and (j) groundwater monitoring.

9 To learn more about these six gspecial wastesh see EPA_s sp ecial waste website at http://www.epa.gov/osw/nonhaz/industrial/spe cial/index.htm15 Bevill Amendments 10 which exempted gspecial wastesh from regulation under S ubtitle C of RCRA until further study and assessment of risk could be performed:

x 1980 Bentsen Amendment (RCRA 3001(b)(2)(A)): Exempted drilling fluids, produc ed waters, and other wastes associated with the exploration, development, and production of cr ude oil or natural gas or geothermal energy.

x 1980 Bevill Amendment (RCRA 3001(b)(3)(A)( i-iii)): Exempted fossil fuel combustion waste ; waste from the extraction, beneficiation, and processing of ores and minerals (incl uding phosphate rock and overburden from ur anium ore mining); and cement kiln dust.

The Bevill and Bentsen Amendments required EPA to complete full a ssessments of each exempted waste and submit a formal report t o Congress on its findings. As itemized in Appendix A to this RIA, since 1978, EPA continued to ev aluate CCR (as well as the other five waste categories) for different possible RCRA hazardous and non-hazardous waste regulatory a pproaches. The proposed RCRA regulation this RIA supports is a continuation of those prior evaluations.



### 1C. EPA’s Proposed Regulation of CC R Disposal Will Correct Market Failure

OMB_s 2003 Circular A-4 gRegulatory Analysish guidance (pages 4 to 5) to Federal agenci es for implementation of Executive Order 12866 identifies three major types of market failure:

1. Externality, common property resource, and public good
2. Market power (i.e., lack of ma rket competition from monopolies)
3. Inadequate or asymmetric information

The CCR proposed rule which this RIA supports may be characterized as addressing the gn egative externalityh of environmental po llution and damages from CCR disposal landfills and impou ndments. As summarized in the gBenefitsh Chapter 5 of this RIA, there are a number of historical and recent environmental damage cases which represent ex ternalities, in that some or a ll of the (a) human health dam ages (i.e., human cancer cases from contaminated groundwater near CCR disposal sites) and (b) environmental damages (i.e., ecological damag es, natural resource damages, and socio-economic damage s from CCR spills/releases fr om structural failures in CCR disposal impoundments) ma y be external to the capital and operating costs of the electric utility plants. If imple mented, the CCR proposed rule may be expec ted to reduce this market failure externality, by internalizing into the capital an d operating costs of the electric utility plants, the added cos ts of installing engineering controls and ove rsight of the physical integrity of CCR disposal units.

Firms are sometimes held accountable for some of the external co sts through lawsuits brought by a ffected citizens. However, th e system of accountability can be imperfect. The primary human bearers of the external costs from CCR disposal are households residing dis posal units. When an unorganized group of households suffer external costs, they face a host of obs tacles to having their costs recuperated. They must

10 These 1980 RCRA gspecial wasteh amendments are named after US Senator Lloyd Bentsen (D-TX; Senate service years 1971-1993) and US House Congressman Tom Bevill (D-AL; House service years 1967-1997). Source: Biographi cal Directory of the US Congress at http://bioguide.congress.go v/biosearch/biosearch.asp16 form a coherent organization and they must have enough funding to launch and maintain a la wsuit. On the other side of such lit igation, households usually face a single fi rm often with greater legal funding resources. This imbalance suggests that external costs of leachate contamination from industrial waste di sposal sites (such as CCR landfills and impoundments) may not be recuperated.

The CCR proposed rule also addresses a second source of market failure v inadequate or asymmetric information. Citizens residi ng near CCR disposal sites may be unaware of exposure to chemical contaminants contained in CCR leaching from disposal units. Thus, while nearby citizens may have the right to legal lawsuits to recuperate health and property damage s, citizens may not be aware of the need to do so until health risks (and health costs) have already been incurred.

A very recent example of negative external ities associated with struct ural failures is the ecologi cal and socio-economic damage s and costs associated with a large environmental di saster involving the collapse of a CCR impoundment in 2008. On 22 December 2008, over a billion gallons (i.e., 5.4 million cubic yards) of CC R was unintentional environmental released over 300 acres from the collapse of a T ennessee Valley Authority (TVA) coal-fired elec tric utility surface impoundment in Kingston TN. This ev ent caused significant damage to 40 hom es, the Emory River, a nearby recreational lake, community roadwa ys, a gas pipeline, and a ra ilroad. As indicated in Exhibit 5B-2 of this RIA, the estimated cleanup costs to the TVA --- not including social cost s of ecological damages and community socio-economic damages -- - are estimated at $933 million to $1.2 billion. This event attracted majo r citizen, national press, and Congressional interest in t he subject of CCR management and the urgent need for prevention of such future envi ronmental and community damages. In the wake of this disaster , during her 14 January 2009 Senate confirmation hearing, EPA Admi nistrator-designate Lisa P. Jackson, testified 11 :

g

I think that you’ve put your finger on a very important thing that EPA must do righ t away, which is to assess the hundreds of other sites that are out there. Many of them ... are ... up hill from schools or from areas where just the physical hazard of having this mountain of wet coal ash, if there’s a break, can endanger lives immediately. So I woul d think that EPA needs to first and foremost assess the current st ate of what’s out here and where there mi ght be another horrible accident waiting to happen ... EPA currently has and has in the past, assessed its regu latory options with respect to coal ash, and I think it’s time to re-ask those questions and re-look at the state of regulation of th em from an EPA perspective .h

According to a 23 January 2009 news report, 12 there was growing Congressional interest for either the EPA w ith its existing RCRA regulatory authorities, or the Congress w ith potential new legi slation, to regulate CCR disposal units:

g Several lawmakers have introduced, or announced plans to intr oduce, competing legislation to regulate CCR. For example, Senate Environment & Public Works Comm ittee Chairwoman Barbara Boxer (D-CA) said she would introduce legislation compelling EPA to regulate CCR in the event the Obama EPA fails to act soon. "If we are not satisfied with action we may move legislatively," Boxer told EPA Admini strator-designate Lisa Jackson at a J anuary 14 [2009] confirmation hearing. "I don't want to get to that point beca use I think you have the authority to regulate this. It needs to be done ."h

11 Lisa Jackson_s 14 January 2009 Senate confirmation hearing tes timony and webcast is available from the US Senate Committee on Environment and Public Works_ website at: http://epw.senate.gov/public/index.cfm?FuseAction= Hearings.Hearing&Hearing_ID=ae2 c3342-802a-23ad-4788-d1962403eb76

12 Source: Waste Business Journal , gEPA Vows to Act on Coal Waste,h 23 January 2009 , http://www.wastebusin essjournal.com/news/wbj20090127B.htm17 Just three weeks after the TVA_s Kingston TN CCR impoundment disaster, House Natural Resources Committee Chairman Nick Rahall ( DWV) introduced legislation requiring federal standa rds to regulate the engin eering of CCR impoundments. 13 Introduced on 14 January 2009, the Coal Ash Reclamation and Environmental Safety Act of 2009 (H.R . 493) directs the Department of Interior to impose uniform f ederal design, engineering, and performance standard s on CCR impoundments to avoid a repeat of the damage done in Kingston TN. The le gislation, which requires minimum design and stability standards for all surface impoundments constr ucted to hold coal ash, draws on the r egulatory model for impoundments that is used for coal slurry manageme nt under the Surface Mining Control and Reclamation Act of 1977 (SM CRA).

In a letter dated 02 March 2009, the Environmental Integrity Project and Earthjusti ce, joined by the Nati onal Resources Defense Council, the Sierra Club, Environmental Defense, a nd 104 other environmental groups requested EPA Administrator Lisa Jackson g to act as soon as possible h to regulate CCR. A letter signed by the gr oups and delivered to EPA on 03 March 2009 id entified 12 principles to guide the development of EPA standards. These in clude the phase-out of CCR surface impoundment s, locating CCR disposal sites away from groundwater or surface water, requiring liner s, leachate collection systems and adequa te monitoring, and requiring industry to assume long term liability for cleanup:

g The recent disaster at TVA's Kingston Plant stands as a startling reminder that federal standards for CCR are long overdue. For too long, power companies have been able to dump CCR, laden with a host of to xic metals like arsenic, selenium, lead, mercury, and boron, in unlined mines, quarries, landfills, and surf ace impoundments. Without federal standards governing disposal pr actices, contaminants can leak or spil l from these dump sites, threatening human health, natural resources and wildlife .h 14

On 04 March 2009, US Senators Barbar a Boxer (D-CA) and Tom Carper (D-DE) submitted Senate Resolution 64 to the Senate Committee on Environment and Public Works. This re solution calls on the EPA to gimmediatelyh inspect all CCR impoundments and landfills ope rating at coal-fired electricity plants, and to propose and finalize gas quickly as possibleh ru les to regulate CCR under RCRA. 15

13 The text of the 14 January 2009 H.R. 493 bill is availa ble at: http://www.govtrack.us/congress/billtext.xpd?bill=h111-493

14 Source: http://www.environmentalintegrity.org/pub608.cfm

15 US Senate Resolution 64 is available at: http://www .govtrack.us/congress/bill.xpd? bill=sr111-64&tab=committees18 

## Chapter 2 Potentially Affected Industrie s & RCRA Regulatory Options

2A. Identity of Potentially Affected Industries

There are two categories of industries whic h may be directly affected by the CCR regul atory options. gDirectly affected entitie sh are entities potentially subject to any of the rule_s requirements. 16 In addition, there are 14 or more industries which beneficially use CCR.

1. Coal-Fired Electric Utility Industry

The scope of industrial plants directly affected by the regulato ry options is classifiable accord ing to at least two different glossary systems:

x Classification #1 of 2 : The scope of industrial pl ants is classifiable as g coal-fired electr ic utility plants h under the US Census Bureau_s North American Industrial Classification Syst emh NAICS code 22 gUtilitiesh economic sect or, and in that sector, as a subgroup o f the 1,245 establishments within the NAICS 221112 gFoss il Fuel Electric Power Generationh industry: 17

NAICS 221112: This industry comprises establishments primarily e ngaged in operating fossil fuel powered electric power generation facilities. These facilities use fossil fuels, such as coal, oil, or gas, in internal combustion or combustion turbine conventional steam process to produ ce electric energy. The electric energy produced in these establishments is provided to electric power tr ansmission systems or to el ectric power distribution systems

.

x Classification #2 of 2 : The scope of industrial pl ants is classifiable as g electric utilities plus i ndependent power producers h under the Energy Information Administration (EIA) ca tegorization system for its coal combustion electric power sector statistics: 18 Electric utility: Any entity that generates, tr ansmits, or distributes electric ity and recovers the cost of its generation, transmission or distribution assets and operations, either directly or indirectly, through cost-bas ed rates set by a separate regulatory authority (e.g., State Public Service Co mmission), or is owned by a governmen tal unit or the consumers that the entity serves. Examples of these entities include: inves tor-owned entities, public power districts, public utility districts, municipalities, rural electric cooperatives, and State and Federal agencies. Independent power A corporation, person, agency, authority, or other legal entity or instrumentality that owns or operates producer: facilities for the genera tion of electricity for use pr imarily by the public, and that is not an electric utility.

16 Source: gEPA_s Action Development Process: Final Guidance for EPA Rulewriters: Regulatory Flexibility Acth, OPEI Regulatory De velopment Series, Nov 2006, see footnote 14 at http://www.epa.gov/sbre fa/documents/rfafinalguidance06.pdf

17 Source: NAICS codes are define d at http://www.census. gov/cgi-bin/sssd/naics/n aicsrch?chart=2007

18 Source: EIA glossary of terms at h ttp://www.eia.doe.gov/glossary/index.html19 2. Waste & Environmental Management Services Industries

In addition, because some electr ic utility plants transport their CCR to either company-owned or to commercial offsite landfill s, and because some regulatory options may tri gger RCRA facility-wide co rrective action, the regulatory opti ons of the proposed rule may also affect: NAICS 562211: Hazardous waste treatment a nd disposal industry (may be affected under the RCRA Subtitle C regulatory options evaluated in this RIA). NAICS 562212: Solid waste landfill industry (may represent baseline offsite CCR landf ills to which the estimated 149 of the 495 electric utility plants may transp ort some or all of the 15 million tons per year CCR for offsite disposal). NAICS 562219: Other non-hazardous waste tr eatment and disposal industry (may re present baseline offsite CCR landfills to which some or all of 149 of the 495 electric utility plants may transport some or all of the 15 million tons per year CCR for offsite disposal). NAICS 562910: Environmental cleanup /remediation services industry.

3. Industries Which “Beneficially Use” CCR

According to the American Coal Ash Association (ACAA) 19 as of 2007 there are over 15 industr ies which gbeneficially useh CCR for industrial applications. These industrial applications are listed below with corresponding NAICS 20 codes estimated by EPA ORCR. Because the regulatory options evaluate d in this RIA establish CCR disposal requiremen ts, industries which bene ficially use CCR are cha racterized in this RIA as potentially gindirectlyh affect ed by the proposed rule rather than gdirect lyh affected (i.e., s ubject to the rule_s requirements).

1. Concrete/concrete products/grout NAICS 327 3 Cement & Concrete Product Manufacturing 2. Blended cement/raw feed for clinker NAICS 3273 Cement & Concrete Product Manufacturing 3. Flowable fill NAICS 23 Construction 4. Structural fills/embankments NAICS 23 Construction 5. Road base/sub-base NAICS 237310 Hi ghway, Street & Bridge Construction 6. Soil modification/stabilizat ion NAICS 23 Construction 7. Mineral filler in asph alt NAICS 324121 Asphalt Paving Mi xture & Block Manufacturing 8. Snow and ice control NAICS 488490 Other Support Activities for Road Transportation 9. Blasting grit/ Roofing granules NAICS 212319 Other Crushed & Br oken Stone Mining & Quarrying NAICS 324122 Asphalt Shingle & Co ating Materials Manufacturing 10. Mining applications NAICS 212 Mining

19 Source: American Coal Ash Asso ciation (ACAA) g2007 Coal Combustion Product (CCP ) Production & Use Survey Results (Revised)h athttp://www.acaausa.org/associations/8003/files/2007_ACAA_CCP_Survey_Report_Form%2809-15-08%29.pdf

20 NAICS = North American Industrial Classification System; NAICS codes defin itions are available at http://www.census.gov/cgi-bin/s ssd/naics/naicsrch?chart=2007

x 2-digit codes represent economic sectors

x 3-digit codes represent economic sub-sectors

x 4-digit codes represent industry groups

x 5-digit and 6-digit codes represent single industries20 11. Gypsum panel products (e.g., wallboard) NAICS 327420 Gypsum Product Manufacturing 12. Waste stabilization/solidification NAI CS 5622 Waste Treatment & Disposal 13. Agriculture NAICS 111 Crop Production 14. Aggregate NAICS 23 Construction 15. Miscellaneous/other ( unidentified industries) NAICS not identified



### 2B. Other Industries with CCR Disposal Un its Not Covered by the Proposed Rule

The scope of the proposed rule excludes two other categories of CCR disposal units fr om the regulatory options. These other tw o categories are identified here to provide a rough estimate of potential add itional cost for regulation if they were added to the scope of the rulemaking or addressed in a separate but similar rulemaking.

x Inactive/Abandoned CCR Disposal Units Excluded from Scope

The scope of the proposed rule only covers active (i.e., operating) CCR di sposal units used by electr ic utility plants. There are two other operating status categories consis ting of an estimated count of at least 197 additional CCR disposal units excluded from the sc ope of the rule: 21

x Inactive units: CCR impoundments and landfills not in operation or not receiving CCR. Inactive impoundments may receive CCR in the future, becoming active again, and therefore have not been closed permanently.

x Abandoned units: CCR impoundments and landfills not in operation and closed. These impoundments usually have been filled to capacity and have been permanently closed.

In absence of inventory data on inactive units, the nationw ide count of such inactive and aba ndoned units is in directly and rou ghly estimated in this RIA based on known data for large volume coal mining slurry waste impoundments. There ar e an estimated 1,600 coal waste impoundments in operation across the US in co al-related industries (i.e., coal mining industry plus industries which burn coal) . In addition, there are another 670 coal waste impoundments which are no longer in operation but still contain coal waste slurry (i.e., inact ive or abandoned). 22 These two counts represent a ratio of 0.42 inactive/abandoned:to:act ive (i.e., 670:to:1,600).

In absence of national survey data, multiplying the 0.42 inacti ve:to:active coal waste impoundme nts ratio by the 158 coal-fired electric utility plants estimated in this RIA using CCR impoundments, yields an estimate of at least 66 inactive/abandoned CCR impoundments may be located at electric utility plants (i .e., (158 impoundment using electric ut ility plants) x (0.42 ratio) = 66).

21 Source: Definitions of ginactiveh and gabandonedh coal waste impoundments from page 23 of the National Research Council book C oal Waste Impoundments: Risks, Responses and Alternatives , National Academy Press, 2002 at http://www.nap.edu/openbook.php?isbn=030908251X

22 Source: Counts of 1,600 active coal waste impoundments and 670 inactive or abandoned coal waste impoundments from the prior fo otnoted source.21 This RIA did not discover similar data for coal waste landfill s in active and inactive/abandoned status. For purpose of a roug h estimate in this RIA, multiplying the 0.42 inactive/abandoned:to:active ratio by th e 311 electric utility plants which use landfills, indicates there may be at least 131 inactive or abandoned CCR landfills at or near electric util ity plants (i.e., (311 landfill us ing electric utility plants) x (0.42 ratio) = 131).

As of 2004, the Mine Safety & Health Admi nistration (MSHA) oversees 646 active coal mi ning slurry impoundments in the US, which implies 954 remainder active coal slurry impoundments (i.e., 1,600 v 646 = 954). 23 Of these, this RIA estimates at least 158 active impoundments at 158 electric utility plants, which implie s that a fraction of 796 ot her active coal waste impound ments (i.e., 954 v 158 = 796) may be located at electric power plants in non-ut ility industries (see the next sub-section be low gOther Industries Excluded from Scopeh).

x Other Industries Excluded from Scope

The scope of the proposed rule only include s NAICS code 22 coal-fired electric utility plants (495 plants). However, there is a range of 139 to 759 non-utility facilities which curr ently, or have the capacity to, burn coal and thus generate CCR. Adding these facilities to the scope of the proposed rule could increase the cost estimates by 2% to 28%. This rang e is based on the following two data sources:

Source #1: As displayed below in Exhibit 2A based on 2005 data from the DOE-EIA, there ar e 139 non-utility coal-fired electricity plants owned and operated by 8 other industrial sub-sectors involving 27 industries. Appendix B of this RIA contains a list of these other industry plants according to NAICS industry codes. If these other non-utility industries were to be added to the scope o f the CCR proposed rule, a rough estimate of pot ential additional cost and benefit impact s would be between 2% and 28% relative to the impacts estimated in this RIA:

x >2%: Compared to the 369,183 megawatts (M W) nameplate capacity for the coal-fir ed electricity plants contained in the 2005 DOE-EIA database (which contains data on electri city plants at least 10 MW nameplate capacity in size), the 5,959 MW capacity of the 139 non- utility electricity plants represents about 2% of national coal-fired electricity generation capacity. For purpose of rough estimation v in so fa r that electricity plant capacity correlates to annual CCR generation and thus to annual CCR disposal costs and to regulatory costs --- this percentage indicates that the additional economic impact of including these additiona l 139 non-utility plants in the proposed rule might add at least 2% to the cost estimates under each regulatory option.

x <28%: On the other hand, some CCR disposal costs and regulatory costs be tter correlate to the c ount and size (footprint) of CCR landfills and impoundments, not to electricity generating capacit y. For such costs, adding the 139 nonutility plants to the scope of the pr oposed rule could increase the cost es timates for each regulatory option by up to 28% (i.e., (495 + 139) / (495)).

23 Source: MSHA gSupporting Stat ementh for Information Collection Request (ICR) 1219-0015 gRefuse Piles and Impoundment Structure s, Recordkeeping and Reporting Requirementsh, March 2008: http://www.msha.go v/regs/fedreg/paperwork/2004/04-24046.pdf22 Source #2: EPA_s 2002 analysis 24 of the results from a 2001 survey of non-utility CCR generation identified 759 non- utility facilities gwith the capacity to burn coal, and therefore, generate CCR.h The estimated annual CCR generation for these facilities is 7.8 milli on tons (as of year 2000), which is 5.5% to 6.3% of the 123.1 milli on to 141.2 million tons CCR generated by electric utility plan ts in 2005 as estimated in Exhibit 3D of this RIA. Allowing for annual growth of the 7.8 million tons since 2000 suggests that adding these 759 facilities to the sc ope of the proposed ru le could increase the cost estimates by 7%.

24 Source: gAnalysis of Non-Utility Coal Combustion Waste Generation and Management Based on the 2001 CIBO Voluntary Survey,h pre pared for EPA-OSWER by Science Applications International Corp (SAIC) Engineering & Environmental Management Group (Reston VA) under subcontract to Ea stern Research Group (Arlington VA), April 2002, EPA contract No. 68-W-02-036, WA 12:.23 Exhibit 2A Identity of Other Industries Operating Coal-Fired Electricity Plants Not Covered by the Proposed Rule or this RIA
2005 Count NAICS Sector NAICS Industry NAICS Industry Code Definition 2005 Boiler count 2005 Plant count 1 21 2122 Ore mining 4 1 2 31 311 Food Manufacturing 63 29 3 31 3122 Tobacco Manufacturing 3 2
4 31 314 Textile Product Mills 11 4 5 32 321 Wood Product Manufacturing 1 1 6 32 322 Paper Manufacturing 9 4 7 32 322122 Newsprint Mills 98 39 8 32 32213 Paperboard Mills 19 9 9 32 325 Chemical Manufacturing 31 6 10 32 325188 All Other Basic Inorganic Chemical Manufacturing 5 3 11 32 325211 Plastics Material and Resin Manufacturing 9 4 12 32 326 Plastics and Rubber Products Manufacturing 4 1 13 32 327 Nonmetallic Mineral Product Manufacturing 8 3 14 32 32731 Cement Manufacturing 2 1 15 33 331 Primary Metal Manufacturing 5 3 16 33 331111 Iron and Steel Mills 1 1 17 33 331312 Primary Aluminum Production 3 1 18 33 333 Machinery Manufacturing 7 2 19 33 3345 Navigational, Measuring, Electromedical, Control Instruments Mfg 10 1 20 33 336 Transportation Equipment Manufacturing 1 1 21 33 337 Furniture and Related Product Manufacturing 1 1 22 33 339 Miscellaneous Manufacturing 1 1 23 48 482 Rail Transportation 2 1 24 48 483 Water Transportation 3 1 25 61 611 Educational Services 37 14 26 62 624 Social Assistance 2 1
27 92 92 Public Administration 14 4

Count = 8 Count = 27 Column Totals = 354 139 2005 electricity generation namepl ate capacity (megawatts) = 5,959
Notes: (a) Source: US Dept of Energy, Energy Information Administration (EIA), 2005 Form EIA-860 "Annual Electric Generator Report" "Existing Electric Generating Units in the United States, 2005" at http://www.eia.doe.gov/cneaf/e lectricity/epa/epat2p2.html (b) NAICS codes: The first two digits designate the economic s ector, the third digit designates the subsector, the fourth digit designates the industry group, the fifth digit designates the NAICS industry, and the sixth digit designates the national industry. The five-digit NAIC S code is the level at which there is comparability in code and definitions for most of the NAICS sectors across the three countries participating in NAICS (the United States, Canada, and Mexico). The six-digit level allows for the United States, Canada, and Mexico each to have country-specific detail. A complete and valid NAICS code contains six digits. Source: http://www.census.gov/eos/www/naics/faqs/faqs.html#q524 

### 2C. RCRA Regulatory Options Evaluated in this RIA

This RIA evaluates three RCRA regulatory optio ns which are defined with reference to th e two alternative regulatory authorities --- Subtitle C and Subtitle D --- contained in EPA_s 1976 RCR A waste management statutory authority:

Option 1: RCRA Subtitle C g special waste h:

x Regulate CCR disposed in landfills and surface impoundments as gspecial wastesh under Subtitle C, and require phase out of surface impoundments within five years. This approach:

x Eliminates health risks from groundwater and surface water contamination for both landfills and surface impoundments, and avoids damages from uncontrolled ground gfillh operations (e.g., Gambrills MD and Chesapeake VA) and attendant environmental remediation costs.

x Eliminates the future threat of cat astrophic failures of surface impoundments.

x Provides for corrective action, including at closed units at facilities with surfac e impoundments or landfills regulated under the rule, and imposes groundwater monitoring requirements.

x Provides for Federal oversight, which EPA experience has shown is necessary for successful implementation of RCRA industrial waste regulations, esp ecially as it relates to ground-wate r monitoring and corrective action, when needed. Without Federal oversight, it is hi ghly questionable whether CCR will be properly managed, considering EPA_s experience with the RCRA program of th e last 10 years, which illu strate the limited results that could be expected of a Subtitle D rule.

Option 2: RCRA Subtitle D g non-hazardous h industrial waste (version 2):

x Liners required for all (i.e., existing and future ne w) CCR surface impoundments but only for new landfills. Subtitle D requirements would set national criteria for la ndfills and surface impoundments that manage CCR after the rule goes into effect. Fo r any CCR landfills and impoundments that closed before the effective date, there would be no regulatory controls ove r those units, unless the states choose to adopt controls over such units. Also, all surface impoundments (existing and new) would n eed to have composite liners within 5-years of the effective date. Consistent with the Subtitle C appr oach, existing landfills woul d not need to be lined.

x Requirements would not be enforceable by EPA or the stat es (unless states had sim ilar requirements under state law). Lack of enforcement and Federal oversight may significantly reduce compliance and effective implementation of regulatory requirements.

x Although this option does not require phase-out of existi ng surface impoundments, it c ould cause some phase-out because all surface impoundments would need to have compos ite liners by a certain date , or they would need to close down, assuming the rule is eff ectively implemented by the states.

x Eliminates some ground-water contamination over the cu rrent situation (e.g., because of surface impoundment retrofitting), thus avoiding some damage cas es, again assuming effective implementation.25 x Require review of surface impoundments for stability by independent experts, but because impoundments could remain in operation (because they are currently lined or ow ners choose to retrofit line them rather than phase them out), there would still be a risk of future structur al failures of impoundments.

Option 3: RCRA Subtitle gD primeh:

x Regulation of disposal under subtitle D, with liners required only for new surface impoundments and landfills. This approach would be the same as the subtitle D approach above, except that existing su rface impoundments would not be required to retrofit and install a composite liner, or close. Unlined existing impoundments could continue to operate, but new landfills and surface im poundments or expansions of existing la ndfills must have composite liners.

x Under this approach the potential for catastrophic failure of surface impoundments would remain significant, since phase-out of surface impoundments wouldn_t occur.

x Would be less effective than the subtitle C or subtitle D approaches in eliminating gr oundwater contamination (or in having it be discovered sooner), but would still provide some benefits ove r no national regulation. (The same caveats on state regulations and enforcement woul d apply as in the subtitle D option.)

x Would reduce regulatory costs significantly since conversion to dry disposal w ould not be required, but would also provide fewer benefits.

Evaluation of three regulatory options is consistent with OMB_s 2003 gC ircular A-4: Regulatory Anal ysish best practices guidanc e for Federal agencies, which requires analysis of at least three regulatory options. 25 All three regulatory options are identical in two ways:

1. Beneficial use : All options propose to replace the 1980 RCRA gBevill exclusionh under 40 CFR 261.4(b)(4) for CCR disposal with new RCRA waste regulation, but to retain the ex isting Bevill exclusion for CCR beneficial uses . Beneficial uses of CCR will retain the Bevill exclusion and will not be subject to any re gulation, either under Subtitle C or Subtitle D.

2. Engineering controls : All options propos e the same set of 10 custom-tailored engineering controls (i.e., technical design and operating standards) for CCR disposal units . For purpose of launching this RIA in April 2009, the waste disposal gmanagement standardsh described in EPA_s August 1999 cement kiln dust (CKD) proposed rule 26 were used in absence of uniquely defined controls specific to CCR disposal units. Th is was a reasonable starting poi nt because the CKD management standards are similar or ident ical to the technical standards defined in the CCR proposed rule.

25 OMB_s 2003 Circular A-4 (p.16) directs Fe deral agencies to analyze at least thr ee regulatory options: http://www.whitehouse.go v/omb/assets/omb/circulars/a004/a-4.pdf

26 EPA_s 20 August 1999 CKD proposed rule (Federal Register , 67 pages).26 During EPA_s April 2009 launch of this RIA, EPA defined three ot her RCRA options which are very similar to the above three opti ons. The initial set of options is included in EPA_ s October, 8 2009 initial draft (165 pages) of this RIA which EPA submitted to OMB fo r review in mid-October 2009. The regulatory cost estimation in Chapter 4 and the supplemental analyses in Chapter 7 of this RIA are based on the initial set of three options, defined as follows:

2009 Option 1: RCRA Subtitle C g hazardous h industrial waste:

x Subtitle C provides Fe deral enforceability.

x RCRA Section 3004(x) 27 custom-tailor engineering controls (i.e., t echnical standards) for CCR disposal units.

x Subject CCR to Subtitle C land disposal restricti on (LDR) treatment standa rds prior to disposal:

x Dry CCR (landfills): Moisture conditioning and co mpaction to attain 95% dry density value.

x Wet CCR (impoundments): Dewatering a nd dry disposal within 5 years after rule_s effective date.

2009 Option 2: RCRA Subtitle D g non-hazardous h industrial waste (version 1):

x This option is different from the 2010 Option 2: Subtitle D option because it does not require liners for existing impoundments as the 2010 Option 2 does, but it only requires liners fo r new impoundments (and only for new landfills).

x Regulate CCR disposal as RCRA Subtit le D non-hazardous waste based on the same custom-tailored engineering controls as the 2009 Option 1.

x Except under RCRA Section 7003 g imminent and substantial endangerment h authority, this option is not Federally enforceable because RCRA Subtitle D directs EPA only to assist state government waste management programs. 28

2009 Option 3: Hybrid RCRA Subtitle C & Subtitle D:

x Subtitle C regulation of CCR impoundments (same as the 2009 Option 1)

x Subtitle D regulation of CCR landfills (same as the 2009 Option 2)

27 The following excerpt from RCRA Section 3004(x) pertains specifi cally to CCR, by providing EPA with authority gto modifyh the RCRA Subtitle C technical standards for regulation of CCR disposal:

g Section 3004(x): If... (2) fly ash waste, bottom ash waste, slag waste, and flue gas emission control waste generated primarily from the combustion of coal or other fossil fuels... is subject to regulation under this subtitle , the [EPA] Administrator is authorized to modify the requirem ents of subsections (c), (d), (e), (f), (g), (o) and (u) and section 3005(j), in the case of landfills or surface impoundm ents receiving such solid waste, to take into acco unt the special characteristics of such wastes, the practical difficulties associated with implementation of such requirements, and site-specific characteristics, incl uding but not limited to the climate, geology, hydrology and soil chemistry at the site, so long as su ch modified requirements assure protection of human health and the environment .h

28 Section 4001 of Subtitle D of the 1976 RCRA statute prescribes the Federal role under Subtitle D as assistance to state govern ments: g The objectives of this subtitle are to assist in developing and encouraging methods for the disposal of solid waste... Such objectives are to be accomplished throug h Federal technical and financial assistance to States or regional authorities for comprehensive pl anning pursuant to Federal guidelines designed to foster coope ration among Federal, State and local governments and private industry .h27 

## Chapter 3 Baseline CCR Management in th e Electric Utility Industry

This Chapter characterizes baseline (i.e., current) CCR management practices within the electric utility industry. This baseli ne consists of two components described in this Chapter: CCR di sposal and CCR beneficial use. This Chap ter begins with a description of baseline CCR management quantities (i.e., annual tonnages of CCR) and CCR disposal me thods used by the electric utility industry. This Chap ter also presents an evaluation of baseline operat ing conditions (i.e., gengineer ing controlsh and gancillary costsh) of CCR disposal un its and an estimate of the associated costs to the el ectric utility industry. This Chapter c oncludes with a charact erization of baseline CCR gbeneficial useh (for CCR which is not disposed) and an estimate of associat ed net benefits to the environment and the national economy.



### 3A. Identity of Coal-Fi red Electric Utility Plants

This RIA initially identified the sub-group of potentially affected coal-f ired electric utility plan ts using the 2007 US Depart ment of Energy (DOE), Energy Information Agency (EIA) database for electricity power plants from the Form EIA-860 "Annual Electric Generator R eport.h This data was supplemented with the mast er list of utility plants from the 2007 EIA-860 database entitled gexistingunits2007h. 29 This RIA applied three database filte rs to identify the subset of electricity plants which may potentially be affected by the proposed r ule:

x Database filter #1 of 3 : EPA sorted the 2007 EIA-860 electric plant databa se by the North American Industry Classification System (NAICS) industrial codes, and deleted all plants no t assigned utility sector NAICS code 22 (only 2-digit NAICS codes are provided by the EIA database).

NAICS 22: The Utilities sector comprises establishments engaged in the provision of the following utility services: electric power, natural gas, steam supply, water supply, and sewage removal. Within this sector, the specific activities associated with th e utility services provided vary by ut ility: electric power includes generation, transmission, and distribution; natural gas includes distribution; steam supply includes provision and/or distribution; water supply includes treatment and distribution; and se wage removal includes collection, treatment, and disposal of waste through sewer systems and se wage treatment facilities. Excluded from this sector are establishments primarily engaged in waste management serv ices classified in Subsector 562 Waste Management and Remediation Services. These establishm ents also collect, treat, and dispose of waste

29 The EIA-860 database is itemized on an electricity generator unit basis, not on a per-plant basis. It includes specific infor mation about generators at electric power plants owned and operated by electric utilities and non-utility industries (i.e., including in dependent power producers, combined heat and power producers, and other industrials). The file contains generator-specific information such as initial date of commercial operation, prime movers, generating capacit y, energy sources, status of existing and proposed generators, proposed changes to existing generators, county and State location (including power plant address), owners hip, and FERC qualifying facility status. Also included are data related to the ability to use multiple fu els; specifically, data on co-firing and fuel switching are inc luded. The DOE spreadsheet gexistingunits2007h is available at http://www.eia.doe.gov/cneaf/electricity/page/capacity/capacity.html.28 materials; however, they do not use sewer systems or sewage treatment facilities” Source: US Bureau of Census at: http://www.census.gov/eos/www/naics/

x Database filter #2 of 3 : EPA deleted all of the units that did not use coal as either a primary or secondary energy source using the coal type codes displayed in Exhibit 3A below. In addition to these five categories of coal, examples of other primary or secondary energy sources reporte d by coal burning electric utility plants are agricultu re byproducts, distillate fue l oil, natural gas, petroleum coke, propane, and wood & waste solids.

Exhibit 3A Types of Coal Used by Electric Utility Plan ts as Coded in the 2007 DOE-EIA Database
Item Code Type of Coal

1 BIT Anthracite Coal, Bituminous Coal

2 LIG Lignite Coal

3 SUB Sub-bituminous Coal 4 WC Waste/Other Coal (Anthracite Culm, Bituminous Gob, Fine Coal, Lignite Waste, Waste Coal) 5 SC Coal Synfuel. Coal-based solid fuel that has been pro cessed by a coal synfuel plant, and coal-based fuels such as briquettes, pellets, or extrusions, which are formed from fresh or recycled co al and binding materials.

x Database filter #3 of 3 : The first two filter criteria result ed in a subset of 506 coal-fired el ectric utility plants. Based on the reported operating status of th e generators at these plants (i.e., OP, OS, SB, RE, OA) 30 , 11 plants reported that all generators are out-of-service, 2 plants reported that all generators are on standby and all remaini ng plants reported that at least one of the ir generators is operating. Removal of the 11 out-of-service plants from the master list resulted in a total affected plant popul ation of 495 coal-fired electric utility plants

. 31 Appendix C presents the list of 495 plants. 32

For purpose of identifying the t ypes and size classifications for owner entities, this RIA initially used the utility code repo rted in the 2007 EIA860 database to identify which plants are ow ned by the same company. Company owner cl assifications were al so checked for many plants using internet searches by plant and company name which some times revealed parent company owners. As summarized in Exhibit 3B and

30 OP = Operating - in service (commercial operation) and producing el ectricity. Includes peaking units that are run on an as nee ded (intermittent or seasonal) basis, OS = Out of service v was not used for some or all of the reporting period and is NOT expected to be returned to service in the next calendar year, SB = Standby/Backup - available for service but not normally used (has little or no ge neration during the year) for th is reporting period, RE = Retir ed - no longer in service and not expected to be returned to service, and OA = Out of service v was not used for some or all of the reporting period but was either returned to service on Dec 31 or will be returned to service in the next calendar year. Note: Units undergoing maintenance or repair of less than 12 months and are expected to be returned to service are assigned operating status.
31 This RIA filtered out 11 out-of-service electricity plant identifi cation codes: 508, 511, 996, 1732, 2341, 2468, 2529, 2531, 29 08, 3419, and 55612.

32 In comparison, a 2008 EPA Office of Water (OW) study estimate d a nationwide total of 497 coal -fired electric plants using the same 2005 EIA-767 database; the 495 plants estimated in this RIA are less than the 2008 EPA OW estimate becau se this RIA takes account of more recent plant operati ng status information (i.e., plants which have converted to other non-coal fuels or are not operating). Source: Table 3-1 (page 3-9) of EPA Office of Waster gSteam Elec tric Power Generating Point Source Category: 2007/2008 Detailed Study Report,h report nr. 821-R- 08-011, August 2008; http://www.epa.gov/guide/304m/2008/steam-deta iled-200809.pdf29 Exhibit 3C below, these 495 coal-fired electric utility plants are owned and operate d by 200 entities which are listed in Appendix D to this RIA. The 495 plants have a combined electricity generation nameplate capacity of 369,183 MW (meg awatts), ranging in individual plant size from 2.3 MW to 3,969 MW, with an average size of 746 MW and a median size of 497 MW. This combined capacity represents 34% of the 1.088 million MW total US electricity generation capacity as of 2007. 33

Exhibit 3B Summary Classification of 495 Coal-Fired Electric Ut ility Plants by Type/Size of Owner Entities (2007)

Item Type of Owner Entity* Entity Size Class** Coal-Fired Electric Utility Plant Count Owner Entity Count 1 Federal government Non-small 11 1 2 State government jurisdictions (aut horities, districts) Non-small 13 7 3 Medium & large population municipal government jurisdictions Non-small 27 19 4 Medium & large companies Non-small 372 110 5 Medium & large cooperatives (this RIA assumes all privately-owned) Non-small 20 12 6 Small county government jurisdictions (commission) Small 1 1 7 Small municipal government jurisdictions (agencies, commissions) Small 33 33 8 Small companies Small 12 11 9 Small cooperatives (this RIA assumes all privately-owned) Small 6 6 Summary: Column totals = 495 200 Private sector sub-total (items 4+5+8+9) = 410 (83%) 139 (70%) State/local government sub-total (items 2+3+6+7) = 74 (15%) 60 (30%) Small entity sub-total (items 6+7+8+9) = 52 (11%) 51 (26%)
Notes: * Type of owner entity estimated and assigned by EPA ORCR based on owner name or internet research on type of ownership. ** Size class determined according to the following numerical threshold criteria consis tent with EPA_s Nov 2006 guidance for Re gulatory Flexibility Act (RFA) Small Business Regulatory Enforcement Fairness Act (SBREFA) compliance:

x Small non-government = Based on the US Small Business Administration NAICS code 221112 small business size standard of <4 million megawatt hours per year total annual electricity generation by all plants owned by the entity).

x Non-small non-government = entity_s total annual electricity generation >4 million megawatt hours per year.

x Small government = Based on the RFA_s defi nition (5 US Code section 601(5)) of gsmall governme nt jurisdictionh as the government of a city, county, town, township, village, school district, or special district with a population of less than 50,0 00.

x Non-small government = entity_s jurisdiction population >50,000 people.

33 Source: US Dept of Energy (DOE), Energy Information Admini stration (EIA) website at http://www.eia.doe.gov/cneaf/electricity/e pa/epat2p2.html30 Exhibit 3C State-by-State Electric Utilit y Plant Counts by Type/Siz e of Owner Entity (2007) Count of Plants Owned by Non-Small Entities Count of Plants Owned by Small Entities

Item State Federal government State Government Non-small municipal Non-small

company Non-small cooperative County government Small municipal Small

company Small cooperative Row total plants
1 AK 2 2
2 AL 2 7 1 10
3 AR 3 3
4 AZ 2 3 1 6
5 CA 6 6
6 CO 1 2 11 14
7 CT 2 2
8 DC 0
9 DE 3 3
10 FL 5 9 1 15
11 GA 10 1 11
12 HI 2 2
13 IA 1 13 3 2 19
14 ID 0
15 IL 2 21 2 25
16 IN 21 5 26
17 KS 2 6 8
18 KY 2 1 14 3 1 21
19 LA 4 4
20 MA 4 4
21 MD 8 8
22 ME 1 1
23 MI 2 13 5 2 22
24 MN 1 10 5 16
25 MO 5 10 2 2 1 20
26 MS 3 1 1 5
27 MT 4 1 5
28 NC 19 3 22
29 ND 2 5 7
30 NE 4 3 7
31 NH 2 2
32 NJ 1 6 7
33 NM 3 3
34 NV 2 2
35 NY 11 1 1 13
36 OH 2 20 4 26
37 OK 1 4 1 6
38 OR 1 131 Exhibit 3C State-by-State Electric Utilit y Plant Counts by Type/Siz e of Owner Entity (2007) Count of Plants Owned by Non-Small Entities Count of Plants Owned by Small Entities

Item State Federal government State Government Non-small municipal Non-small

company Non-small cooperative County government Small municipal Small

company Small cooperative Row total plants
39 PA 32 2 34
40 RI 0
41 SC 4 10 14
42 SD 2 2
43 TN 7 7
44 TX 1 2 14 1 1 19
45 UT 1 4 1 6
46 VA 15 1 16
47 VT 0
48 WA 1 1
49 WI 12 3 2 17
50 WV 16 16
51 WY 8 1 9 Column totals= 11 13 27 372 20 1 33 12 6 495

The annual amount of coal burned by these 495 operating plants is 1.036 billion tons per year as reported in the 2007 EIA-923 d atabase, according to the following five types of coal fuel categories:

x Bituminous coal (DOE-EIA data code = BIT): 330 plants (67% of 495 plants)

x Lignite coal (LIG): 21 plants (4%)

x Coal-based synthetic fuel (SC): 19 plants (4%)

x Sub-bituminous coal (SUB): 201 plants (41%)

x Waste/other coal (WC): 33 plants (7%)

Many plants use more than one coal fuel type so the above percentages exceed 100%. Appendices B & C present the quantity of coal burned and the types of coal burned for the list of 495 plants. As displayed in the state-by-state Exhibit 3D below, 47 states have coal-fired electric utility plants (3 states --- ID, RI, VT --- and DC do not have el ectric utility plants). The top- 5 state coal-fired electric u tility plant counts are:



### 1. PA 34 plants 

### 2. IN & OH 26 plants each 

### 3. IL 25 plants 

### 4. MI & NC 22 plants each 

### 5. KY 21plants32 Exhibit 3D State-by-State Count of NAICS Code 22 Electric Utility Plants and Associated CCR Generation

Item State Count of Plants (2007) % of Plants CCR Generated (tons as of 2005) % of CCR Generation 1 AK 2 0.40% 46,179 0.03% 2 AL 10 2.02% 3,210,337 2.27% 3 AR 3 0.61% 744,267 0.53% 4 AZ 6 1.21% 3,334,030 2.36% 5 CA 6 1.21% 159,927 0.11% 6 CO 14 2.83% 1,704,432 1.21% 7 CT 2 0.40% 172,280 0.12%
8 DC 0 0% 0 0% 9 DE 3 0.61% 251,205 0.18% 10 FL 15 3.03% 6,132,345 4.34% 11 GA 11 2.22% 6,077,700 4.30% 12 HI 2 0.40% 58,968 0.04% 13 IA 19 3.84% 1,136,290 0.80%
14 ID 0 0% 0 0% 15 IL 25 5.05% 3,856,748 2.73% 16 IN 26 5.25% 8,798,844 6.23% 17 KS 8 1.62% 1,495,099 1.06% 18 KY 21 4.24% 9,197,567 6.51% 19 LA 4 0.81% 1,614,800 1.14% 20 MA 4 0.81% 363,150 0.26% 21 MD 8 1.62% 1,932,740 1.37% 22 ME 1 0.20% 48,000 0.03% 23 MI 22 4.44% 2,369,673 1.68% 24 MN 16 3.23% 1,525,979 1.08% 25 MO 20 4.04% 2,679,742 1.90% 26 MS 5 1.01% 1,229,400 0.87% 27 MT 5 1.01% 1,830,624 1.30% 28 NC 22 4.44% 5,504,531 3.90% 29 ND 7 1.41% 3,038,100 2.15% Exhibit 3D State-by-State Count of NAICS Code 22 Electric Utility Plants and Associated CCR Generation

Item State Count of Plants (2007) % of Plants CCR Generated (tons as of 2005) % of CCR Generation 30 NE 7 1.41% 614,473 0.44% 31 NH 2 0.40% 176,900 0.13% 32 NJ 7 1.41% 735,214 0.52% 33 NM 3 0.61% 3,983,300 2.82% 34 NV 2 0.40% 391,500 0.28% 35 NY 13 2.63% 1,479,792 1.05% 36 OH 26 5.25% 10,429,446 7.39% 37 OK 6 1.21% 1,490,800 1.06% 38 OR 1 0.20% 99,900 0.07% 39 PA 34 6.87% 15,359,680 10.88%
40 RI 0 0% 0 0% 41 SC 14 2.83% 2,178,359 1.54% 42 SD 2 0.40% 103,753 0.07% 43 TN 7 1.41% 3,240,120 2.29% 44 TX 19 3.84% 13,165,728 9.32% 45 UT 6 1.21% 2,582,144 1.83% 46 VA 16 3.23% 2,388,527 1.69%
47 VT 0 0% 0 0% 48 WA 1 0.20% 1,405,220 1.00% 49 WI 17 3.43% 1,412,534 1.00% 50 WV 16 3.23% 9,231,718 6.54% 51 WY 9 1.82% 2,224,848 1.58%

Total 495 100% 141.2 million* 100% * Note: In comparison to this estimate based on DOE-EIA databases cited in this RIA, the American Coal Ash Association (ACAA) estimated 123.1 million tons CCR generated in 2005 based on its annual voluntary participation survey : http://acaa.affiniscape.com/associati ons/8003/files/2005%20CCP%20Survey%20 %2809-19-06%29Corrected-11-09-07.pdf33 

### 3B. Types of CCR Disposal Units

x Estimated Plant Counts by Type of CCR Disposal Unit

The scope of CCR disposal units covered by this RIA is active units (i .e., operational units which we re receiving CCR as of yea r 2005). Inactive or abandoned units (i.e., non-operating units) are excluded from the scope of this RIA. The data source used to ident ify baseline CCR management practices and active units is th e 2005 U.S. Department of Energy (DOE) En ergy Information Administration (EIA) Form EIA-767 gSteam-Electric Plant Operati on and Design Reporth database. 34 The EIA-767 database is the primar y data source for reporting annual CCR disposition for plants generating greater th an 100 MW (megawatts) of electricity. Pl ants smaller than 100 MW are not required to report CCR tonnage and disposition (i.e., type of disposal and benefi cial use) data to the EIA-767 data base. Schedule 3 of the EIA-767 da tabase contains the annual disposition of CCR in one or more of the following fi ve forms of CCR management cate gories, according to annual tons disposed for each plant. EIA-767 does not contain c ounts of CCR disposal units for each plant:

1. Company-owned landfill
2. Company-owned disposal ponds (i.e., surface impoundments)
3. Onsite use and storage (this RIA assume s all of this quantity eventually goes to beneficial use, not disposal)
4. Sold (for beneficial use)
5. Disposed off site

The 2005 EIA-767 database contained annual CCR disposal data for 363 of the 495 plants identified in the 2007 EIA-860 database. The 363 plants are over 100 MW in size and thus are covered by the EIA-767 database. For the 132 plants which did not report CCR dispo sal practices in the 2005 EIA-767 database because they are less than 100 MW in size, disposal of CCR is assumed to take place in on-site or off-site landfills (whichever is the lowe st-cost method as assigned by the CCR disposal engineering control cost model used for this RIA ). For each of the 495 coal-fired utility plants identified in the prior secti on of this RIA using the 2007 EIA-860 database, baseline CCR dis posal practices were assigned using the methodology and data sour ces presented below. Based on this analysis, 467 of the 495 plants dispose CCR using the following methods. The 28 remainder of the 495 plants do not dis pose because they solely supply their CCR for beneficial uses. A total of 272 of the 495 plants supply CCR for beneficial uses. The total count of disposal met hods exceeds the 467 total count of disposing plants because some plants use more than one disposal method. The EIA-767 databa se does not contain counts of di sposal units for each plant s o only plant counts are summarized below according to disposal method, not CCR di sposal unit counts. Because some plants use more than one disposal unit, the total count of CCR disposal un its v although unknown for purpose of this RI A -- exceeds the 467 total count of dispos ing plants.

34 Source: The EIA-767 database includes annual data from organic-fueled or combustible renewable steam-electric plants with a ge nerator nameplate rating of 10 or more megawatts (MW) regardless of current owners hip and/or operation. However, it contains annual tonnage CCR generation, CCR disp osal, and CCR beneficial use data only for plants over 100MW in size. The EIA te rminated the EIA-767 database after year 2005. Beginning with calendar year 2007 dat a, two other surveys, the Form EIA-860 and the Form EIA-923, will collect most of the data formerly coll ected by Form EIA-767. No data will be collected for 2006. T he following weblink provides a crosswalk of the data elements previously collected on the Form EIA-767 for 2005 with the corresponding data elements to be collected beg inning with calendar year 2007 on the Form EIA-860 or the Form EIA-923: http://www.eia.do e.gov/cneaf/electricity/20 08forms/consolidate.html34 x Onsite landfills: 311 plants operate onsite CCR landfills (this RIA refers to these as gonsiteh landfills although some may be located off plant property). This estimate consists of two sources (i.e., 212 plants + 99 plants):

 212 plants: dentified through actual data reporting of 363 coal-fired electric plants in size >100 MW contained in the 2005 EIA-767 database, out of th e total 495 plants iden tified using the 2007 EIA860 database (as described in the previous section above).

 99 plants: This estimate is based on the remai nder 132 electric utility plants (i.e., 495 minus 363 plants = 132 plants) between 1 MW and 100 MW size for which there is no CCR disposal data in the EIA-767 database, and for which the CCR disposal engi neering control cost model used in this RIA assigned the lowest-cost of three landfill options: (1) onsite dug landfill, (2) onsite pile landfill, or (3) offsite landfill. The cost model assignment wa s dependent upon the level of baseline engineering controls assumed required by each plant_s state loca tion and annual CCR disposal tonnage. The cost model estimated that 99 of th e 132 plants without data di spose CCR in onsite landfills.

x Onsite impoundments: 158 plants operate onsite CCR surface impoundments (aka gponds,h gembankments,h gdams,h gdikes,h gwet dumps,h gconstructed wetlandsh). Th is RIA assumes that all impoundment s are gonsiteh although some may be located off plant property.

The non-duplicative count of pl ants using onsite landfills an d/or onsite impoundments is 383 plants

.

x Offsite disposal: 149 plants assigned as sending CCR offsite fo r disposal to commercial landfills (of which 84 plants solely ship CCR for offsite disposal). Off-site landfills receiving CCR are assumed to already be in compliance with EPA_s RCRA Subtitle D guidance. The 149 plants assigned as using offsite landfills consist of the following assignments according to data sources (i.e., 116 plants + 33 plants):

 116 plants : Electric utility plants >100 MW size (source : 2005 EIA-767 database): Final disposition of wastes is reported as either (a) company-ow ned landfill, (b) company-owned disposal pond, (c) on-site use & storage, (d) sold, or (e) off-site disposal. This RI A assumes that off-site disposal means offsite commercial landfill. Plants could have reported offsite minefill in this category if it was not "sold" (e.g., they paid to dispose it in a mi ne or it was used as minefill and no payment was made to the electric utility). However, it is unknown the sub-quantity of goffsite disposalh which includes plants reporting tonnages fo r non-sold uses as offsite minefill. 35

35 In July 2009, ORCR contacted the DOE-EIA Form 767 questionnaire contact person (Natalie Ko, El ectric Power Division) to clarif y this RIA_s assignment of all goffsite disposalh tonnages as commercial landfills. The DOE-EIA contact person responded with additional information from four 2005 Fo rm EIA-767 questionnaires regarding how electricity plant respondents optionally characterized the fly ash and bottom ash repo rted in the Form EIA-767 survey quest ionnaire as gOff Site Disposalh : · gThis quantity of fly ash was given away at no costh · gThe fly ash was sent off site for beneficial useh · gThe fly ash is injected into the nearby mines for recharging the minesh · gAsh is recycled as a beneficial re-use pr oduct for flowable fill in the construction industryh35 x 92 plants Offsite landfill fly ash

x 76 plants Offsite landfill bottom ash

x 4 plants Offsite landfill gypsum

x 16 plants Offsite landfill FGD

x 7 plants Offsite landfill other CCR (i.e., coal combustion by-products)

x Sub-total = 116 plants (non-duplicative count)

 33 plants : This estimate is based on the 132 electric utility plants betwee n 1 MW and 100 MW size for which there is no CCR disposal data in the EIA-767 database, and for which the CCR disposal engineering control cost model used in this RI A assigned the lowest-cost of three landfill options: (1) onsite dug landfill, (2) onsite pile landfill, or (3 ) offsite landfill. The cost model assignment was dependent upon the level of baseline engineering controls assumed required by each plant_s state location and annual CCR disposal tonnage.

x Estimated Counts of CCR Disposal Units

The methodology of this RIA does not estimate or use secondary information about the actual coun t of CCR disposal units (i.e., landfill units and impoundment units) used by these 467 onsite or offsite disposing plants. However, there are tw o sources of CCR disposal un it counts:

x Source #1 of 2: ASTSWMO: The February-Mar ch 2009 ASTSWMO voluntar y participation survey 36 of 42 states (which is incomplete coverage of the 47 states identified in this RIA for the 495 coal-fired electric pl ants) estimates a tota l of 484 electric util ity plant CCR disposal units:

x 227 electric utility plant CCR landfill units in 41 states

x 257 electric utility plant CCR im poundment units in 33 states

x Total electric utility plant CCR disposal uni ts = 484 (i.e., 227 landfills + 257 impoundments)

But it is not clear whether the ASTSWMO CCR di sposal unit counts (a) are restricted in the ASTSWMO survey to electric utility p lants in NAICS code 221112, (b) may also include counts of CCR disposal units associated with other indust ries which generate coal-fired electricity in the surveyed states, (c) may include inactive/abandoned as we ll as active CCR disposal units, or (d) may include landfills o r impoundments operated by electric utility plants which contain other types of waste streams (e.g. waste water treatment ponds without co-min gled CCR).

Source #2 of 2: EPA: In March 2009 EPA sent letters 37 to 210 coal-fired electric pl ant facilities and owner compan ies in order to identify the location of CCR impoundments and evaluate th eir structural integrity in the wake of the December 2008 CCR impoundment collapse and

36 Source: Association of State and Territorial Solid Waste Management Officials (ASTSWMO), 01 April 2009 letter to Matt Hale, D irector, EPA Office of Resource Conservation and Recovery: http://www.asts wmo.org/files/publications/Positionpap ers/ASTSWMO-CCB-letter-attachments.pdf36 flooding at the TVA Kingston TN electricity plant. Although not us ed in this RIA other than for reference here, the responses received to the March 2009 EPA letters resulted in identific ation of 584 CCR impoundments units at elect ric utility plants. The letters did no t collect information about CCR landfills 38



### 3C. Types of CCR and Annual Quantities

As of 2008, coal-fired utilities burn approximately 1.036 billion tons of coal per year using a variety of conventional combust ion technologies. NAICS 22 electric utility coal combustion results in the generation of five types of CCR:

1. Fly ash
2. Bottom ash
3. Flue gas desulfurization (FGD) sludge
4. Gypsum
5. Other residues (including boiler slag)

These wastes may be (a) disposed in onsite landfills and su rface impoundments (i.e., ponds, dams, embankments, lagoons), or (b) may be applied to beneficial uses, or (c) dispos ed offsite. At the time of preparing th is RIA in 2009, waste generation and dispositi on data from Schedule 8, Part A of the 2007 DOE EIA database for the Form EIA-932 gPower Plant Operations Reporth da tabase had yet to be fin alized. Instead, the most currently available wast e data was from the 2005 DOE EIA Form 767 gSteam-Electric Plant Operation and Design Reporth database. Therefore, the 2005 EIA-767 databa se is the primary source used in this RIA to quantify CCR generation and identify the ultimate disposition of CCR (i.e., type of disposal or beneficial us e). CCR generation and final dis position are repor ted under the abo ve five CCR type categories in the 2005 EIA 767 database. As estim ated in this RIA and displayed below in Exhibit 3E , the 495 electric utility plants generated 141.2 million tons per year of CCR (2005/2007 mixed data).

Interpretive Note: This RIA_s CCR generati on estimate of 141.2 million t ons is 15% and 8% higher, respectively, than the 123.1 million tons (2005) and the 131.1 million tons (2007) annual CCR generation estimates published by the American Coal Ash Association (ACAA). 39 The numerical discrepancy be tween this RIA_s estimate and the ACAA estimates may be explained by the fact thatboth estimates (i.e., this RIA and the ACAA) are based on incomplete CCR tonnage disposition data fo r less than the gunivers eh of all known operating

37 Source: Additional information about these March 2009 EPA le tters is available at http://www.epa.gov/osw/nonhaz/industrial/spe cial/fossil/coalashletter.htm

38 Source: EPA_s 584 CCR impoundment unit count is documented at http://www.epa.gov/osw/nonhaz/in dustrial/special/fossil/surveys/ faqs.htm#18

39 As of the date of this RIA, ACAA_s gCoal Combustion Products Production & Use Statisticsh website contains annual CCR generati on and annual CCR beneficial use tonnage estimates for the US electric utility industry for years 2001, 2002, 2003, 2004, 2005, 2006, 2007, and 2008. As report ed in footnotes on ACAA_s annual survey results data tables, ACAA_s CCR generation and CCR beneficial us e annual tonnage estimates are based on the following survey co verages: 2001 coverage not indicated on data table; 2002 2/3 rd coal burn; 2003 60% coal burn; 2004 60% coal burn; 2005 54% coal burn; 2006 57% coal burn reported by 58 electric utilities; 2 007 161 plants; and 2008 274 plants. ACAA_s annual CCR tonnage data webpage is at http://acaa.affiniscape.com/displa ycommon.cfm?an=1&subarticlenbr =337 electric utility plants in the data year, extrapolated to plants for whic h there is no CCR tonnage data in the EIA database (in the case of this RIA_s estimation methodology) and in the case of the ACAA estimates, extrapolated to plants not covere d by ACAA_s annual utility industr y survey by supplementing with EIA data.

The estimate of CCR generation developed in this RIA consists of the following breakout of generation estimates according to tw o electric utility plant size categories, wh ich correspond to the CCR tonnage di sposition data reporting cut- off requirement in the EIA-76 7 database:

x >100 MW plants: Exhibit 3E below presents CCR disposition data for a sub-total of 120.9 million tons CCR generated per year as reported by plants with annual electri city generation >100 MW from Schedul e 3A of the 2005 EIA-767 database for each plant.

x Ash generation data (fly ash and botto m ash) were available for 385 plants.

x FGD sludge generation data were available for 72 plants.

x Gypsum generation data were available for 31 plants.

x Other byproduct generation data were available for 40 plants. If plants > 100 MW reported either company landfill, compa ny disposal ponds, sold for bene ficial use, or off-site disposal of CCR in the EIA-767 database, th ese final disposition practic es are assumed in this RIA for the baseline. A total 179 plants with company-owned CCR landfills a nd 158 plants with company-owned CCR surface impoundments were reported in the 2005 EIA-767 database (i.e., 337 of the 495 electric plants). 40 112 of the 495 plants reported 8.2 million gon-site use and storageh which this RIA assigned as beneficial use not as disposal. This assumption is supported by (a) DOE_s August 2006 report 41 gCoal Combustion Waste Management at Landfills and Surface Impoundments 1994-2004h which interpre ted the entire "onsite use & storage" quantity as beneficial use, and (b) the American Coal Ash Association (ACAA) which indica tes that 49.6 million tons of coal ash were beneficially used in 2005 42 . However, the beneficial use estimate in Exhibit 3E below is much less at 38.8 million tons which is based on the EIA-767 gSoldh (i.e., benefici al use) CCR tonnage category. But adding the 8.2 million tons reported as "onsite use & storage" yields an estimate of 47.0 million tons ( Exhibit 3G ), which nearly matches the ACAA beneficial use estimate of 49.6 million tons. This suggests it is valid to assign the tonnage reported in the EIA-767 database as "onsite use & storage" to be neficial use rather than to disposal.

40 In the 2005 DPRA Report, an additional step was included after step 1 that identified additional disposal practices using landf ill and surface impoundment as reported in the 1995 EPRI Comanagement Survey. This data source was not used to identify CCR management units in this RIA given it dates b ack to 1995. The data source is only used to identify existing engineering controls for the units identified in the 2005 EIA 767 database. In the 2005 DPRA Report, 14 additional landfills and 10 surface impoundments were identified using this information source.

41 Source: Footnote c of Table 1 on page 6 of DOE_s August 20 06 report at http://www.ead.anl. gov/pub/dsp_detail.cfm?PubID=2008

42 Source: ACAA_s 2005 beneficial use data are available at http://acaa.affiniscape.co m/associations/8003/file s/2005%20CCP%20Surv ey%20%2809-19-06%29Corrected11-09-07.pdf38 x 1MW to 100 MW Exhibit 3F below presents an additional sub-total of 20.3 million tons per year of CCR generated by 132 electric utility plants between 1 MW and 100 MW in capacity wh ich had no CCR management information in the EIA767 database, because plants less than 10 0 MW are not required to report thei r CCR management annual tonnages in the EIA-767 database. Therefore, this RIA formulated an estimate for this size category of plants based on the following approach. Coal use and percent ash content da ta from Schedule 4A of the 2005 EIA-767 database were used to estimate ash generation quantit ies for 102 plants within this smalle r size category. For 5 plants for which EIA-767 coal use data were unavailab le for 2005, coal use data from Schedule 4A of the 2007 EIA-923 database were used to estimate CCR generation quantities for thos e 5 plants. FGD sludge gene ration data obtained from Schedule 8 43 of the 2005 EIA-767 database were used for 115 plants . Landfill (either on-site or off-site whichever is more economical) is the assumed C CR disposal practice. No gypsum or other byproduct generation quantities were estimated. For plants between 1 MW and 10 MW , ash generation quantities estimated using generator nameplate capacity rating data from the 2007 DOE Form 86 0 database. This 1 MW to 100 MW subtotal of 132 plants consists of two sub-categories:

x 10 MW to 100 MW : 5.4 million tons of CCR for 110 plants estimat ed by multiplying the quantity of coal they burned by the percent CCR content of the coal data fr om Schedule 4A of the 2005 EIA-767 database and 2007 DOE EIA 923 database, or using ge nerator nameplate rating data from the 2007 EIA-860 database and an average percent ash content.

x 1 MW to 10 MW : 14.9 million tons of FGD sludge reported fo r 22 plants in Schedule 8 of the 2005 EIA-767 database that did not report any FGD sludge in Schedule 3A of the 2005 EIA-767 database.

43 In general, data obtained from Schedule 8 of the 2005 EIA-767 da tabase reflects information reported by plants between 10 MW an d 100 MW. However, if a plant greater than 100 MW reported no final disposition quantities for FGD sludge in Schedule 3A of the 2005 EIA-767 database, the re ported FGD sludge quantity in Schedule 8 is assumed in this RIA to be pl aced in a landfill for that plant.39 Exhibit 3E Annual CCR Disposition for NAICS 22 Electric Utility Plants >100 MW Capacity (tons per year as of 2005) A B C D E F (A+{+E) Item CCR Category Company-Owned Landfill (Dry Disposal) Company-Owned Disposal Ponds (Wet Disposal) Onsite Use & Storage (assumed as beneficial use) Sold for Beneficial Use Offsite Disposal (assumed offsite landfills) Row Totals

1 Fly Ash 21,324,280 15,212,590 3,744,370 20,760,230 9,314,540 70,356,010 2 Bottom Ash 5,707,740 4,311,630 3,487,660 5,453,717 1,907,480 20,868,227 3 Flue Gas Desulfurization Sludge 9,526,400 1,886,200 465,600 408,910 2,506,540 14,793,650 4 Gypsum (salable) 54,620 872,100 372,100 8,437,400 782,800 10,519,020 5 Other CCR 226,510 82,900 108,830 3,729,400 247,680 4,395,320 6 Totals 36.8 million 22.4 million 8.2 million 38.8 million 14.8 million 120.9 million

Exhibit 3F Annual CCR Disposition for NAICS 22 El ectric Utility Plants 1 MW to 100 MW Ca pacity (tons per year as of 2005)
A B C D (A+B+C)

Item CCR Category Fly Ash Disposed in Off-site Landfill

(Plants 1 MW to 100 MW) Fly Ash Disposed in Company-owned Landfill (Plants 1 MW to 100 MW) FGD Disposed in Company-Owned Landfill (Plants >10 MW) Row Totals 1 Fly Ash 274,917 5,147,468 NA 5,422,385 2 Bottom Ash Included under Fly Ash Included under Fly Ash NA Included under fly ash 3 Flue Gas Desulfurization Sludge NA NA 14,852,300 14,852,300 4 Gypsum (salable) NA NA Included in row 3 Included in FGD 5 Other Byproducts Included under Fly Ash Included under Fly Ash NA Included under fly ash
6 Totals 0.3 million 5.1 million 14.9 million 20.3 million

Exhibit 3G Annual CCR Disposition for NAICS 22 Electric Utility Plants All Sizes (tons per year as of 2005) (Source: Exhibit 3E + Exhibit 3F )
A B C D E (A+B+C+D)

Item CCR Category Company-Owned Landfill (Dry disposal) Company-Owned Disposal Ponds (Wet disposal) Beneficial Use (onsite BU + offsite BU + storage for BU) Offsite Disposal (assumed offsite commercial landfills) Row Totals 1 Fly Ash 26,471,748 15,212,590 24,504,600 9,589,457 70,356,010 2 Bottom Ash 5,707,740 4,311,630 8,941,377 1,907,480 20,868,227 3 Flue Gas Desulfurization Sludge 24,378,700 1,886,200 874,510 2,506,540 14,793,650 4 Gypsum (salable) 54,620 872,100 8,809,500 782,800 10,519,020 5 Other CCR 226,510 82,900 3,838,230 247,680 4,395,320
6 Totals 56.8 million 22.4 million 47.0 million 15.0 million 141.2 million Percentages 40% 16% 33% 11% 100%40 Exhibit 3H below summarizes the respective plant c ounts, annual tonnage CCR disposal, and electr icity generation nameplate capacities of the 467 plants which dispose CCR, according to type of CCR dispos al method (i.e., CCR landfills and CCR impoundments). Because som e plants reported more than one management method, the sum of the plants across each disposal method exceeds the total count of 467 disp osing plants.

Exhibit 3H Summary of Plant Size and CCR Disposal Methods Estimated in this RIA
A B C D Plants Using CCR Landfills (dry disposal)

Characterizing Metrics Onsite Landfills Offsite** Plants Using CCR Impoundments***

(wet disposal) Row Totals (non-duplicative)
1. 2007 Count of Coal-Fired Electric Utility Plants which Dispose CCR 311 plants (63% of 495) 149 plants (30% of 495) (84 plants solely use

offsite landfills) 158 plants (32% of 495) 467 plants dispose CCR (94% of 495) (CCR from the remainder

28 plants is solely for beneficial uses) 2. Annual CCR Disposal (2005)

x Minimum per plant =

x Maximum per plant =

x Mean per plant =

x Median per plant = 56.8 million tons (60%)

x 400 tons

x 1.82 million tons

x 205,196 tons

x 90,700 tons 15.0 million tons (16%)

x 20 tons

x 1.28 million tons

x 100,899 tons

x 33,000 tons 22.4 million tons (24%)

x 500 tons

x 1.04 million tons

x 141,550 tons

x 67,300 tons 94.2 million tons (100%)

x 110 tons

x 2.11 million tons

x 201,796 tons

x 89,300 tons 3. Nameplate capacity* (2007)

x Minimum per plant =

x Maximum per plant =

x Mean per plant =

x Median per plant = 213,978 MW (58%)

x 11 MW

x 3,969 MW

x 772 MW

x 538 MW 90,547 MW (25%)

x 2 MW

x 2,911 MW

x 608 MW

x 350 MW 180,901 MW (49%)

x 75.3 MW

x 3,564 MW

x 1,145 MW

x 893 MW 369,183 MW (100%)

x 2 MW

x 3,969 MW

x 746 MW

x 497 MW
Notes: * Nameplate capacity = electricity generation output potential in megawatts (MW). ** This RIA assumes all reported gnon-company offsite disposal h in the EIA-767 database involves offsite landfill dry disposal, because it is expensive to transport large volumes of wet (i.e., watery) CCR long distances. *** Surface impoundments are repo rted in the EIA-767 database as gcompany-owned ponds.h This RIA assumes all are located onsit e.41 

### 3D. Size of CCR Disposal Units

The size of CCR disposal units ranges from modest to very large, with some impoundments covering 1,500 acres or more. Sizing o f the units is based on the annual tonnage of CCR placed in the unit. CCR disposal unit size assump tions for this RIA are adopted from Sec tion 4.4.1 of the 2005 DPRA Report:

x Landfills sizes: Designed as gcombination fill landfillsh

 3.8 million cubic yards capacity

 50% of the capacity excavated below grade

 40-year capacity (i.e., operating lifespan) 44

 Per-unit surface area size ranges from 12 acres for 10,000 tons per year to over 2,000 acres for 2,000,000 tons per year. Designed as gpile fill landfillsh

 3.4 million cubic yards capacity

 5% of the capacity excavated below grade

 40-year capacity (i.e., operating lifespan)

 Per-unit surface area ranges from 16 acres for 10,000 tons per year to over 3,000 acres for 2,000,000 tons per year.

x Surface impoundment sizes:

o 100% of capacity below grade

o 40-year capacity

o Per-unit surface area ranges from 30 acres for 10,000 tons pe r year, 140 acres for 50,000 tons per year, 500 acres for 200,000 tons per year, 1,400 acres for 500,000 tons per year , and 5,500 acres for 2,000,000 tons per year.

44 For the 30 Nov 2005 DPRA report (gEstimation of Costs for Regulating Fossil Fuel Combustion Ash Management at Large Electric U tilities Under Part 258h, docket document ID nr. EPA-HQ-RCRA- 2006-0796-0469), the EPA asked u tility industry representatives for the typical lifespan years of C CR landfills and impoundments. Industry representatives pr ovided a 40-year estimate for both. This estimate is supported by data provided by industry in the 1995 EPRI Comanagement Survey. In the EPRI Survey, data describing six CCR landfills noted the year the un it was opened and the estimated date of closure. The avera ge life expectancy is 34 years and the median life expectancy is 38 y ears. Similarly, data provided for 18 CCR impoun dments indicate an average life expectancy of 45 years and a median life expectancy of 46 years. Therefore, this RIA assumes a 40-y ear lifespan for both landfills and impoundments.42 

### 3E. Cost of Baseline CCR Disposal

This Chapter presents characteri zing data and estimates of the costs to the el ectric utility industry and to government, for ba seline (i.e., current) industry engineering controls an d other costs associated with CCR disposal. OMB_s 2003 Circular A-4 gRegulatory Analysish (pag e 15) requires RIAs to measure the benefits and costs of regulations against a baseline defined as:

Baseline = g [T]he best assessment of the way the wo rld would look absent the proposed rule. h

The baseline developed here uses the most recent data year availa ble and relies solely on publicly available data used in prior studies and reports, updated using empirically -justifiable factors. For purpose of this RI A, the possible types of baseline costs include:

A. Baseline gengineering control gcosts for CCR disposal units:
1. Ground water monitoring
2. Bottom liners
3. Leachate collection system
4. Dust controls v applicable to landfills only
5. Rain and surface water run-on/run-off cont rols v applicable to landfills only
6. Financial assurance for disposal unit closure and post-closure
7. Disposal unit location rest rictions (6 types: water tables , floodplains, wetlands, fault areas, seismic zones, karst terrain)
8. Closure capping to cover unit
9. Post-closure monitoring requirements
10. Storage design and operating standards (tanks, containers , containment buildings) v not evaluated in this RIA

B. Baseline gancillary costsh di rectly related to CCR disposal:
11. Offsite disposal
12. Structural integrity insp ections v impoundments only
13. RCRA facility-wide investigation (RFI)
14. Corrective action
15. Waste disposal permits
16. Inspection & enforcement
17. Remediation of environmental releases

x Characterization of Indust ry Baseline CCR Disposal

For each of the 467 operating electric utility plants which curr ently (2007) dispose CCR onsite or offsite (28 of the 495 total plants solely send their CCR for beneficial uses not disposal), this RIA estimated baseline engineering controls at dis posal units and associated baseline disposal43 costs for each type of disposal (note: the sum of plant coun ts for each disposal category below exceeds 467 because some plants use more than one type of CCR disposal method):

o 311 plants with active onsite CCR landfills

o 158 plants with active onsite CCR surface impoundments

o 149 plants which offsite dispose (assumed all involve offsite landfills)

For this RIA, the gbaselineh is defined as existing conditions pl us projection of future conditions over the 50-year future per iod-of-analysis 2012 to 2061 applied in this RIA (this RIA assu mes year 2012 represents the first year when the final rule could take effect, i f promulgated). Baseline engineering controls we re estimated using the following 2-step method which is based on two alternative and complement ary sources of information:

x Step 1: If the plant reported controls in the 1995 EPRI Comanagement Survey, 1 996 CIBO Survey, or the 1994-2004 DOE-EPA Study, the stricter of these controls or state-specified controls are assumed for the baseline. These studies contained control data for 89 plants with CCR landfills and 50 plants with CCR impoundments (i.e., 139 of the 495 electric utility plants). State regulations added addi tional controls at 69 of the 89 landfill plants and 43 of the 50 impoundme nt plants with plant specific information (e.g., the EPRI Su rvey data may have indicated that the unit ha d a liner only but state regulations required groundwater monito ring and capping so these additi onal controls were added).

x Step 2: Controls specified under state regu lations for 34 states are assu med for all other plants in those 34 states for the ba seline if no 1995 EPRI Comanagement Survey data, 1996 CIBO Survey data, or 199 4-2004 DOE-EPA Study data are availa ble for that plant. This step resulted in assigning state-required controls to 201 pl ants with CCR landfills and 55 plan ts with CCR impoundments (i.e., 256 of the 495 plants). Overall state regulations were added to 270 plants with CCR landfills and 98 plants with CCR impoundments. For the 100 plants (i.e., 47 plants with landf ills and 53 plants with impoundments) fo r which there are no data from the three studies, and no state-regulatory data on controls from Step 1, no controls are assumed under base line for on-site landfills and impoundments; this represents a wo rst case (i.e., high cost) assumption.

The associated data sources and findings for each ba seline characterization step are described below.

x Step 1: Baseline Installed CCR Disposal Engineering Controls Identified in Prior Industry Surveys (1995, 1996, 2004)

The controls identified through the Step 1 prior studies were more stringent than th e state government requirements discussed i n Step 2 for:

o Landfills : Voluntary controls for 25 plants with landfills (9% of 227 plants landfills) receiving 6.4 million tons per year (i.e., 9% of total landfill CCR quantity) in 12 states (some are identified as voluntary becaus e state regulations were not reviewed f or the state): AR, AZ, CA, IA, IN , KS, MD, MN, NE, SD, SI, WV.44 o Impoundments : Voluntary controls for 39 plants with impoundment s (25% of 158 plants with impoundments) receiving 5.5 million tons per year (i.e., 25% of total CCR impoundment quantity) in 14 states (som e are identified as voluntary because stat e regulations were not reviewed for the state): AL, FL, IA, IL, IN, LA, MN, MS, NM, OH, SC, TX, UT, WY.

x Step 2: Baseline State Government CCR Disposal Engineering Control Requireme nts for Landfills & Impoundments (2008)

Several states have already established cer tain CCR disposal unit design and operating requirements that are required to be imp lemented either upon the effective date of the regulation (e.g., groundwater monitoring), upon retireme nt of the disposal unit (e.g., post-clos ure monitoring), or for newly constructed units only. Appendix E of this RIA provides a summary of the stat e government requirements for both landfills and impoundments. Current CCR disposal regulation s have been reviewed for the top 34 stat es that utilize coal for producing electr icity for required engineering controls at landfills a nd impoundments. The plants located in thes e states account for 99% of the annual quantity of CCR managed in company-owned (i.e., onsite) landfills and impoundments. State regulations were review ed for the following 34 state s: AL, AZ, CO, FL, GA, IA, IL, IN, KS, KY, LA, MD, MI, MN, MS, MO, MT, NV, NM, NY, NC, ND, OH, OK, PA, SC, TN, TX, UT, VA, WA, WV, WI, WY. Below is a synopsis of the baseline state government re quirements according to the engineering controls listed above.

1. Groundwater monitoring requirements:

x Point-of Compliance: Two options for point-of-compliance groundwater monitoring include installing monitoring wells at the unit boundary or within 1 50 meters of the unit boundary. Recent changes to state regulations suggest that states typically require unit boundary monitorin g.

x Number of Wells: Certain states specify a minimum number of monitoring wells: FL (3 wells for impo undments), IA (1 well for landfill), IL (multiple wells for landfills), KY (3 wells for landfills), LA (3 wells for impoundments and landfills), MO (4 wells for impoundments and landfills), ND (3 wells for impoundments), OK (3 wells for impound ments and 4 wells for landfills), TN (3 wells for landfills), UT (3 wells for landfills), WV (3 wells for impoundments and 4 wells for landfills). Well spacing design criteria for landfill bound ary detection wells for FL, IA, and KS were re viewed. FL requires a minimum of one down -gradient detection we ll every 500 feet pla ced within 50 feet of the unit. Iowa requires a minimum of one dete ction well every 600 feet placed within 50 feet of the unit. K S recommends a minimum of one-down-gr adient detection well every 500 feet.

x Monitoring Parameters: Two options for sampling include testing fo r chemical indicators and testing for RCR A hazardous waste Appendix VIII constituent s (i.e., 40 CFR 261 Appendix VIII). Of the 34 state regulations reviewed, three states require chemical indicator monitoring for surface impoundments [CO, PA, WV] and 11 states re quire chemical indicator monitoring for la ndfills [IA, FL, KY, MI , OH, OK, PA, TN, UT

, WI, WV]. Three states require RCRA Appendix VIII constituent monitoring for im poundments [MO, PA, WV], and 10 states require RCRA Appendix VIII constituent monitoring for landfills [GA, FL, IA, IL, MI, MO, OH, TN, UT, WV].

x Monitoring Frequency: Three options for groundwater sampling freque ncy include quarterly, semi-annual and annua l. Of the 34 state regulations review ed, one state requires quarterly sampling for surface impoundments [CO (depending on the ground-water classification)] and three st ates require quarterly monitoring for landfills [IA (until baseline cond itions are established), IL (fir st 5 years), MI]. Five state s require semi-45 annual sampling for surface impoundments [LA, MO, ND, PA (chemi cal indicators), WV] and 12 states require semi-annual monitoring for landfills [FL, GA, KY, LA, MO , OH (chemical indicators), OK, PA (indicator parameters), TN (chemical indicators)

, UT, WV, WY]. Three states require a nnual sampling for surface impoundments [CO (dep ending on the ground-water classification), PA (metals and VOCs), WV] and five states require annual sampli ng for landfills [IA (after baseline established), IL (after 5 y ears), OH (metals, TOC, TDS, chloride, sodium and radionuclides), PA (metals and VOCs), TN (RCRA Appendix VIII constituents)].

x Timing of State Regulation Implementation : In the baseline, certain states require groundwater monitoring only for newly construc ted units. These baseline costs are trac ked as future baseline cost streams in the cost model. Of the 34 st ate regulations reviewed, nine st ates require immediate compliance with monitoring requirements for impoundments: LA , MN, MO, ND, NV, NY, OK, SC, UT. Eight states that only require groundwater monitoring only at newly constructed surf ace impoundments: CO, FL, KY, MI, NC, PA, WI, WV. 21 states require immediate compliance with monitoring requirements for landfills: AL, CO, GA, IA, IN, KS, KY, MI, MN, MT , NC, ND, NY, OH, PA, SC, TN, UT, VA, WA, WY. Ten states require groundwater monitoring only at newly cons tructed landfills: FL, IL, LA, MS, MO, NV, OK, TX, WV, WI.

2. Bottom liner requirements:

x Impoundments: Of the 34 state regulations reviewed, 10 st ates require immediate comp liance with liner requirements for surface impoundments: FL (composite), KS (composite), KY (composite), LA (composite), MO (composite), ND (clay or synthetic), NV (composite), NY (composite), OK (composite), and PA (composite). Six states re quire liners only at newly cons tructed surface impoundments: CO (clay or soil), MI (clay or composite), NC (c omposite), WI (composite, synt hetic or clay), WV (compo site), WY (composite).

x Landfills: Of the 34 state regulations reviewed, 19 states require immediat e compliance with liner requirements for landfills: AL (composi te), CO (clay or synthetic), GA (composite), IN (clay), KS (composite), LA (composite), MI (composite), MN (clay), MT (composite), NC (composite), ND (clay or synthetic), NY (composite), OH (composite), PA (composite), SC (composite or clay), TN (composite), UT (composite), VA (composite), and WA (composite). 10 states require liners only at newly constructed landfills: FL (composite o r double), IL (clay or composite), MS compos ite), MO (composite), NV (composite), OK (c omposite), TX (composite), WI (composite), WV (composite), WY (composite).

3. Leachate collection/detect ion system requirements:

x Impoundments: Of the 34 state regulations reviewed, nine states require immediate compliance with leachate collection/detection system requir ements for surface impoundments: FL, KS, KY, LA, MO, ND, NV, NY, PA. Fi ve states require leachate colle ction/detection systems only a t newly constructed surface impoundme nts: CO, MI, NC, WV, WI.

x Landfills: Of the 34 state regulations reviewed, 18 stat es require immediate compliance with leac hate collection system requirements for l andfills: AL, CO, GA, IN (karst areas on ly), KS, MI, MN, MT, NC, ND, NY, OH, PA, SC, TN, UT, VA, WA. 11 stat es require leachate collection systems at newly cons tructed landfills: FL, IL, LA, MS , MO, NV, OK, TX, WI, WV, WY.46 4. Dust control requirements: (landfills only) Of the 34 state regulations reviewed, 16 st ates require immediate comp liance with dust control requirements (wetting and truck covers and/or compaction) for landfills: CO, GA (compaction only), IA, IN, KS, MI, MN (includes compaction), ND (includes compaction), NY, OH, PA, SC, TN, UT, VA, WA. Nine states require dust controls only at newly constructed landfills: FL, IL (includes compaction ), LA, MO, NM, OK, WI, WV, WY (includes compaction).

5. Run-on/run-off control re quirements: (landfills only) Of the 34 state regulations reviewed, 18 st ates require immediate comp liance with run-on/run-off c ontrol requirements for landf ills: AL, CO, GA, IA, IN, KS, MD, MN, MT, NC, NY, OH, PA , SC, TN, UT, VA, WA. 11 states require run-on/run-off only at newly constructed landfills: FL, IL, LA, MS, MO , NV, OK, TX, WI, WV, WY.

6. Financial assurance for CCR dispos al unit closure & post-closure care

x Impoundments: Of the 34 state regulations reviewed, 11 st ates require immediate compliance with fi nancial assurance requirements for surface impoundments: AZ, KY, LA, MN, MO, ND, NM, NV, OK, TN, and UT. Four states require financial assurance requirements only at newly constructed surface im poundments: CO, MI, NC, WI.

x Landfills: Of the 34 state regulations reviewed, 22 st ates require immediate compliance with fi nancial assurance requirements for landfill s: CO, FL (new construction), GA, IA, IN, KS, KY, MI, MN, MO, MT, NC, ND, NY, OH, SC, TN, UT, TX , VA, WA, WY. Eight states require financial assurance requirements only at newl y constructed landfills: FL, IL, LA, MS, NV, OK, WI, WV.

7. Disposal Unit Location Re strictions (6 categories) State regulations for the top-25 coal usage states (for electricity) were reviewed b ack in year 2000 for any location restricti ons. These regulations were not updated as part of th is RIA. The following is a synopsis of state government locati on restrictions on loc ating CCR surface impoundments and landfills, according to six categories of location restri ctions (water table, floodplains, wetlands, f ault areas, seismic zones, unstable karst terrain).

x 7-1: Below the natural water table:

o Of the 25 state regulations reviewed, five states have location restrictions below the natural water table for surface impoundm ents: NC (4 feet above seasonal water table), ND (within aquifer), OK (if less than 15 feet above ground-water table), WV (5 feet abo ve ground-water table), WY.

o Of the 25 state regulations reviewed, eight states have locatio n restrictions below the natural water table for landfills: FL, IA (5 feet above ground water), MI (4 feet above ground water), MN (5 feet above gr ound water), NC (4 feet above seasonal water table), ND (within aquifer), OH (5 feet above water tabl e for wastes with higher leac hate concentrations), TN (i f less than 5 feet above w ater table).

x 7-2: Floodplains:47 o Of the 25 state regulations reviewed, eight states have location rest rictions in floodplains for surface impoundments: KS (unde r permit), KY, MO (if closed with waste in pl ace), NC, ND, OK (if dike not at least 1 foot above 100-y ear flood elevation), PA, W V.

o Of the 25 state regulations reviewed, 20 st ates have location restrictions in floodpl ains for landfills: AZ, CO, FL, IL, IN, IA , KS, KY, MI, MN, MO, NC, ND, OH, OK, PA, TN, WV, WI, WY.

x 7-3: Wetlands

o Of the 25 state regulations reviewed, five states have locati on restrictions in wetlands for surface impoundments: KY, MO (if c losed with waste in place), ND, PA, WV.

o Of the 25 state regulations reviewed, 17 states that have locati on restrictions in wetlands for landfills include AZ, CO, FL, I L, IN, IA, KY, MI, MN, MO, ND, OK, PA, TN, WV, WI, WY.

x 7-4: Fault areas:

o Of the 25 state regulations reviewed, two st ates have location restrictions in fault areas for surface impoundments: MO (if clo sed with waste in place), WV.

o Of the 25 state regulations reviewed, seven states have location restric tions in fault areas for landfills: AZ, CO, MO, OH, TN, WV and WI.

x 7-5: Seismic zones:

o Of the 25 state regulations reviewed, two st ates have location restrictions in seismi c impact areas for su rface impoundments: i nclude MO (if closed with waste in place), WV.

o Of the 25 state regulations reviewed, eight states have locatio n restrictions in seismic impact areas for landfills: AZ, CO, IL , MO, OK (if within 5 miles of epicenter of 4.0 earthquakes), TN, WV, WI.

x 7-6: Karst areas:

o Of the 25 state regulations reviewed, five states have location restrictions in uns table areas for surface impoundments: KY, MO (if closed with waste in place), ND, PA, WV (1,000 feet away).

o Of the 25 state regulations reviewed, 12 states have location re strictions in unstable areas for landfills: AZ, CO, IN, IA, KY, MN, MO, ND, PA, TN, WV ( 1,000 feet away), WI.

8. Closure cap controls

x Of the 34 state regulations reviewed, nine states require immediate compliance with closure control requirements for surface impoundments: AZ (synthetic cap), KY (syntheti c cap), LA (clay cap), MO (soil cap), ND (clay or synt hetic cap), NM (synthetic cap), OK (clay or synthetic cap), PA (clay or synthetic), TN (s ynthetic cap). Four states require closure controls only at newl y constructed surface impoundments: CO (clay or synthetic cap), MI (clay or synthetic cap), NC (soil cap), WI (synthetic cap).

x Of the 34 state regulations reviewed, 23 st ates require immediate comp liance with closure control requirements for landfills: A L (synthetic cap), CO (clay cap), GA (soil cap) , IA (clay cap), IN (clay cap), KS (soil cap), KY, MD (clay ca p), MI (clay or synt hetic cap), MN (clay cap), MO (soil cap), MT (clay cap), NC (soil cap), ND (clay or sy nthetic cap), NY (synthe tic cap), OH (synthetic cap), PA (synthetic cap), SC (synthetic cap), TN (clay cap), TX (synthetic cap), UT (soil cap), VA (synthetic cap), and WA (syn thetic cap). Nine states require closure controls only at newly constructed la ndfills: FL (synthetic cap), IL (clay or synthetic cap), LA (clay cap), MS (soil cap), NV (soil cap), OK (clay cap), WI (c lay cap), WV (soil or clay cap), WY (synthetic cap).48 9. Post-closure monitoring requirements

x Of the 34 state regulations reviewed, 11 st ates require immediate comp liance with post-closure gro undwater monitoring requireme nt for surface impoundments: AZ, LA, MO, ND, NM, NV, NY, OK, SC, TN, UT. Seven states require post-closure groundwater monitoring only at newly constructed surface impoundme nts: CO, KY, MI, NC, PA, WI, WV.

x Of the 34 states reviewed, 22 states requi re immediate compliance with post-closure groundwater m onitoring requirements for lan dfills: AL, CO, GA, IA, KS, KY, MD, MI, MN, MO, MT , ND, NY, OH, PA, SC, TN, TX , UT, VA, WA, WY. Eight st ates require post-closure groundwater monitoring at newly constructed la ndfills: FL, IL, LA, MS, NV, OK, WI, WV.

10. Baseline storage tank/container design and operating standards The baseline storage tank /container design a nd operating standards were no t evaluated in this RIA because of a lack of data ab out the baseline count and conditions of CCR storage or treat ment tanks, containers, and containment buildings at electric utility plants

x Industry Baseline CCR Disposal Characterization Findings

Appendix F of this RIA presents on a plant-by-plant basis the baseline engineeri ng controls assumed for each of the 383 of the 495 electr ic utility plants which onsite dispose CCR (84 plants solely dispose CCR offsite; this RI A assumes that all offsite CCR disposal u nits are landfills, and further assumes that all of those offsite landfills currently comply with the engineering controls described in this RIA fo r the regulatory options). Exhibits 3I (for landfills) and Exhibit 3J (for impoundments) below summ arize the assignment of base line conditions in this RIA for these 411 plants which dispose CCR onsite.49 Exhibit 3I Baseline Compliance with State Government Engineering Control Requirements: CCR Landfills
A B C D E F G H
Future new CCR landfills Existing CCR landfills

Current or State Regulated Engineering control No. of Plants Percent of 311 plants with LFs Volume of CCR diposed

in landfills (tons/year) % of 71.8 million tons onsite + offsite
LF No. of Plants Percent of 311 plants with LFs Volume of CCR disposed

in landfills (tons/year) % of 71.8 million tons onsite +

offsite LF 1. Groundwater Monitoring 302 97%* 69,706,646 97%* 272 81% 60,623,231 85% 2. Bottom Liner 302 97%* 69,706,646 97%* 238 71% 52,505,314 73% 3. Leachate Collection Syst em 273 81% 62,696,310 88 % 222 66% 49,213,424 69% 4. Dust Controls 215 64% 40,634,681 57% 205 61% 42,781,444 60% 5. Run on/Run off Controls 261 77% 60,342,426 84% 209 62% 46,232,440 65% 6. Financial Assurance 266 79% 56,861,231 79% 231 69% 49,487,222 69% 7. Site restrictins 1. Water table 98 29% 18,878,963 26% ND ND ND ND 2. Floodplains 232 69% 50,072,235 70% ND ND ND ND 3. Wetlands 199 59% 40,227,659 56% ND ND ND ND 4. Fault areas 72 21% 18,816,363 26% ND ND ND ND 5. Seismic zone 66 20% 13,056,165 18% ND ND ND ND 6. Karst areas 152 45% 33,970,045 47% ND ND ND ND 8. Cap Synthetic or Clay 245 73% 52,234,482 73% 213 63% 46,031,621 64% Soil 48 14% 10,990,166 15% 50 15% 12,094,140 17% Clay/Soil 13 4% 5,419,918 8% 5 1% 3,022,219 4% 9. Post Closure Monitoring 271 80% 61,444,140 86% 232 69% 53,249,880 74% 10. Storage design standards ND ND ND ND ND ND ND ND

Notes: ND = Not determined. Comparisons have no t been made comparing the date the state site restriction regul ation became effective and the date of existing landfill construction for each plant. * According to the August 2006 DOE/EPA report gCoal Combustion Waste Management at Landfills and Surface Impoundments, 1994-200 4h report nr. DOE/PI0004, 286 pp; http://www.ead.anl. gov/pub/dsp_detail.cfm?PubID=2008: ~ 97% of newly constructed CCR landfills have groundwater monitoring (Table 14, p.35) ~ 97% of newly constructed CCR landf ills have liners (Table 13, p.33) These percentages reflect a mix of state g overnment permit requirements for some surv eyed electricity plants, plus industry vol untary actions for other plants.50 Exhibit 3J Baseline Compliance with St ate Government Engineeri ng Control Requirements: CCR Surface Impoundments
A B C D E F G H Future new CCR impoundments Existing CCR impoundments

Current or State Regulated Engineering control No. of Plants Percent of 158 plants with SIs Volume of CCR disposed in impoundments

(tons/year) % of 22.4 million tons CCR disposed in impoundments No. of Plants Percent of 158 plants with SIs Volume of CCR disposed in impoundments

(tons/year) % of 22.4 million tons CCR disposed in impoundments 1. Groundwater Monitoring 123 78%* 17,472,000 78%* 78 49% 9,216,470 41% 2. Bottom Liner 158 100%* 22,400,000 100%* 62 39% 6,920,820 31% 3. Leachate Collection System 61 39% 7,676,710 34 % 48 30% 5,33 8,110 24%
4. Dust control NA NA NA NA NA NA NA NA
5. Runon/runoff control NA NA NA NA NA NA NA NA 6. Financial Assurance 63 40% 7,694,010 34% 58 37% 7,327,410 33% 7. Site restrictns 1. Water table 28 18% 3,039,860 14% ND ND ND ND 2. Floodplains 51 32% 6,902,610 31% ND ND ND ND 3. Wetlands 34 22% 5,347,550 24% ND ND ND ND 4. Fault areas 15 9% 1,675,350 7% ND ND ND ND 5. Seismic zone 15 9% 1,675,350 7% ND ND ND ND 6. Karst areas 34 22% 5,347,550 24% ND ND ND ND 8. Cap Synthetic 38 24% 5,911,760 26% 31 20% 4,298,660 19% Soil 27 17% 2,490,050 11% 23 15% 2,293,550 10% Clay 3 2% 254,800 1% 3 2% 254,800 1% 9. Post Closure Monitoring 78 49% 9,520,360 43% 65 41% 7,181,760 32% 10. Storage design standards ND ND ND ND ND ND ND ND

Notes: NA = Not applicable to surface impoundments. ND = Not determined. Comparisons have no t been made comparing the date the state site restriction regul ation became effective and the date of existing surface impoundment construction for each plant. * According to the August 2006 DOE/EPA report gCoal Combustion Waste Management at Landfills and Surface Impoundments, 1994-200 4h report nr. DOE/PI0004, 286 pages; http://www.ead.anl .gov/pub/dsp_detail.cfm?PubID=2008: ~ 78% of newly constructed CCR impoundments have groundwater monitoring (Table 14, p.35) ~ 100% of newly constructed CCR impoundments have liners (Table 13, p.33) These percentages reflect a mix of state g overnment permit requirements for some surv eyed electricity plants, plus industry vol untary actions for other plants.51 x Baseline CCR Disposal Cost Estimation

This section presents baseline cost estimates for both onsite and offsite CCR disposal units (i.e., landfills and impoundments) for 467 of the 495 electric utility plants which dispose CCR (CCR from the re mainder 28 of the 495 plants is solely beneficially used).

x Cost Estimation Framework

x Cost calculations: This RIA contains thr ee types of cost estimates (with decreasing relative degrees of expected accuracy):

o Data-based estimates : Based on a landfill and impoundment engineering c ontrols cost estimation model using relatively robust and recent data inputs (e.g., 2005 or newer) pertaining to CCR quantit ies and disposal methods for individual electric utility plants. The cost model was first de veloped by EPA in 1988 to suppor t EPA_s 1991 final criteria for municipal solid waste RCRA Subtitle D landfills, and EPA_s 1999 proposed rule cement kiln dust landfill requirements. 45 The cost model consists of two software components; Appendix G to this RIA provides a dditional details about the model:

 1 st of 2 cost model components: Unit Cost Component : The first component is a Fortran computer programmed cost model which dates back to 1988. This model spec ifies the various steps and physical units (e.g., square footage sizes and associated quantitie s of labor, equipment and materials fo r the specified sizes) involved in designing, constructing, operating, and closing a landfill or impoundment. Then it combines the physical component data inputs, with input data on the prices/ costs/ fees for the p hysical components to estimate as model outputs, the capital and annual O&M co sts of specified sizes of landfills and impoundments. The unit prices/ costs/fees used as input data include a wide range of items, such as the per- acre cost of land, clearing, excavation, equipment, labor, bottom liner materials, and cover materials. For this RIA, the model was run multiple times to generate individual cost estimates fo r a series of five alternatively-si zed CCR landfills and impoundments with varying types of engineering controls to represent the ra nge of sizes and en gineering controls in the population of 495 electric utility plants. The size categories are define d in tons per day of CCR di sposed. Each CCR landfill or

45 The 1988 cost model is documented in the gUser_s Manual for th e Subtitle D Municipal Landfill Cost Modelh draft report prepare d for EPA_s Office of Solid Waste by DPRA Inc, Sept 1988, 129 pages which is available from the Federal docket as document ID nr EPA-HQ-RCRA-2006-0796. EPA previously publicly referenced this cost model in the followi ng six publications: (a) gDraft Regulatory Impact Analysis fo r Proposed Revisions to Subtitle D Criteria for Municipal Solid Waste Landfills,h prepared for US EP A Office of Solid Waste by Temple, Barker & Sloane, Inc., ICF Incorporated, Pope-Reid Associates (now DPRA Inc.) and American Management Systems, Inc., 05 Aug 1988 (this document includes about a 4-page summary of the cost model) ; (b) gRegulatory Impact Analysis for the Final Criteria for Municipal Solid Waste Landfills,h prepar ed for US EPA Office of Solid Waste by Temple, Barker & Sloa ne/Clayton Environmental Consultants, ICF Inc, DPRA Inc, and American Management Systems, Inc., Dec 1990 (this document includes about a 4-page summary of the cost m odel); (c) gAddendum to the Regulatory Impact Analysis for the Final Criteria for Municipal Solid Waste Landfills,h prepared for US EPA, Office of Solid Wa ste by Temple, Barker & Sloane/Clayton Environmental Consultants and ICF Inc, August 1991; (d) g40 CFR Parts 257 and 258 Solid Waste Disposal Facility Criteria: Propo sed Rule,h Federal Register, Vol.53, No.168, pp.33314-33422, 30 Aug 1988; (e) gRevised Criteria for Mu nicipal Solid Waste Landfills,h Federal Register Volume 56, p p. 50978, 09 Oct 1991; (f) gTechnical Background Document: Compliance Cost Estimated for the Proposed Land Management Regulation of Cement Kiln Dust,h prepared for t he US EPA, Office of Solid Waste by DPRA Inc, 10 April 1998.; and (g) g40 CFR Parts 259, 261, 266, and 270 Standards for the Management of Cement Kiln Dus t; Proposed Rule,h Federal Register Vol.64, No.161, pp. 45632-45697, 20 Aug 1999.52 impoundment is assumed to operate 300 days per year (a verage number of operating days for coal-fired boilers based on 2005 DOE EIA 767 database). Th e size categories are 10,000, 50,000, 200,000, 500,000 and 2,000,000 tons of CCR per year. Size is the primary determin ant of overall cost; however, landfills and impoundments exhibit increasing returns to scale: the larger the la ndfill or impoundment, the lower the cost per ton of CCR managed. The cost equations generated by these unit cost model runs are used as inpu ts in the second component of the cost model to comput e landfill and impoundment cost curves (equations) based on size for each combination of engineering controls, so th at a unique cost estimate ma y be assigned to each of th e 495 electric utility plants according to each plant_s unique annual CCR disposal tonnage.

 2 nd of 2 cost model components: Plant- by-Plant & Aggregate Cost Component : The second component of the model is an Excel spreadsheet with Vi sual Basic programming used to estimat e unique baseline (i.e., current) and regulatory option costs for each electric utility plant. The spreadsheet is populated with plant-by-plant data including plant location, known disposal and beneficial reuse pr actices, known or estimated baseline engineering controls on CCR disposal units, annual CCR disposal tonnages, and known or estimated CCR landfill and impoundment future closure years. The spreadsheet is also populated with the cost equations generated by the first component of the model for the various engineering cont rols (e.g., groundwater monitori ng and safety inspections) and for off-site landfill disposal costs. The Visual Basic programming is used for this RIA to estimate engineering control costs for both the (a) baseline and (b) regulatoryoptions for each plant over a 50-year future period-ofanalysis (i.e., 2012 to 2061). The plant-by-plant estimated co sts are then aggregated in this second component of the model on an average annualized basis.

o Assumption-based estimates : These are based on relatively limited data, and/ or older data (e.g., older than 2005), or metaanalysis transfer of result s from other studies, or data from case studi es, or based mostly on professional judgment assumptions rather than data, for some of the major factors used in cost calculations.

o Scenario-based estimates : These are applied in absence of data, case stud ies, or assumptions for purpose of illustrating potential lower- and upper-bound co sts (i.e., bounding estimates). EPA defines gs cenariosh as qualitati ve projections of possible future conditions based on varia tions in key drivers of change, incl uding social, technolog ical, economic and institutional drivers. Scenario construction is a futures analysis method; as su ch, scenario-based estimat es do not strive to predict the future with absolute certainty, but to explore uncertainties, possible conseq uences, and possible outcomes. 46

x 2009 price level: Costs are normalized to beginning-of-year 2009 dollars using inflation factor s developed by Engineering News

Record (ENR) Construction Cost Index, and using regional cost adjustment f actors applied to each plant cost estimate involving on-site construction. These regional factor s account for the variability be tween states in site work and landscape construction costs. Cost adjustment factor s are derived from the Mean s Building Construction Costs Year 2003 city factors. All the citi es for each state were averaged toge ther to derive a state average.

46 gSource: EPA Office of Science Policy, gSha ping Our Environmental Future: Foresight in the Office of Research & Development,h report nr. EPA 600/R-06/150, 2006 at: http://www.epa.gov/osp/fut ures/FuturesHandbook.pdf53 x Before-tax costs: Baseline disposal costs estimated on a befo re-tax basis to approximate the overall economic cost (i.e., rea l resource allocation for the economy as a whole, rather than on an after-tax basis whic h would approximate a relatively narrower financial cost to the electric utility industry because af ter-tax costs subtract busine ss expense tax deductions and depreciation of capital expenditures for pollution control equipment.

x 50-year period: A 50-year future time hor izon (aka period-of-analysis) was applied because new construction for replacement o f all CCR disposal units and end of existing lifespan is estimat ed to have occurred at least once by that time.

x 7% discount rate: A 7% disco unt rate was applied for calculating both net pr esent value cost and average annualized cost for the engineering control unit costs applied in this RIA. Because both the annualized baseline cost and annualized incremental proposed rule costs estimate d in this RIA consist of primarily (i .e., >95%) industry cost rather than government cost, this RIA applies a 7% discount rate rather than a lower (e.g., 3%, 2%, 1% or 0%) discount rate to represent the opportunity cost of busine ss capital investment and business expens e financing (i.e., the average rate of return to corporate capital). This is consistent with OMB_s 2003 Circular A-4 47 (page 33) and 1992 Circular A-94 48 (page 8) which indicate that a 7% discount rate base-case should be used for regulatory analyses when regulation is expected to primarily and directly affect businesses and industries.

x 0.73% growth: Baseline cost estimates in creased 0.73% per year over the 50-year fu ture time horizon to reflect a 0.73% annual growth in coal consumption at electric utility plants (which is a proxy for future annual gr owth in the annual tonnage of CCR generation needing disposal from those plants). The 0.73% annual growth factor is based on DOE-EIA's January 2009 "Annual Energy Outlook 2009" forecast change in US coal consumption for electricity generation between year 2010 (22.91 quadrillion Btus) and 2030 (26.41 quadrillion Btus), available at: http://www.eia.doe.gov/oiaf/aeo/index.html

x Beneficial use: If reported in the base line by any particular plant, beneficial use was assumed to continue in the future by that plant under the baseline projection over the 50-year fu ture period-of-analysis. Section 5C in Chapter 5 of this RIA evaluates potential changes to this beneficial use baseline under altern ative regulatory impact scenarios.

x Offsite disposal: If reported in baseline by any particular plant, offsite disposal was assumed to continue in the future by that plant. Offsite disposal landfill cost estimated under both baseline and regulatory options using th e engineering control cost model. Truck operating cost estimated separately outside of the model.

x Existing unit closure: One set of years for the opening and clos ure of disposal units are assumed for each facility. If data for initial year of operation were provided in the 1995 EPRI Comanagement Survey, these data were used. If the plant had more than

47 2003 OMB Circular A-4: http://www.w hitehouse.gov/omb/circulars_a004_a-4/

48 1992 OMB Circular A-94: http://www.whitehouse.gov/omb/circulars_a094/54 one disposal unit and more than one reported date for initia l year of operation, the years we re averaged. For example, if a facility had three di sposal units (2 landfills a nd 1 impoundment) with insta llation dates of 1970, 1980, and 1990, this RIA assumed the installation date of all the units was 1980. This assumption simplifie d the cost calc ulations on a per facility basis instead of a per disposal unit basis. If no disposal unit in stallation data were available, the installatio n year is assumed to be equal to the ea rliest boiler installa tion year reported in either th e 2007 EIA 860 database for that plant or 1998 EIA 767 database, whichever was older. If no disposal unit or boiler installation year data were available, an installation y ear of 1980 was assumed. If the 1995 EPRI Comanagement Survey provided a forecasted closure year for a unit, new unit installati on is assumed to occur in that year. Ot herwise, if no closure forecast year is provided, closure is assumed to occur 40 years after the year of installation (assumed average lifespan for CCR landfills and impoundments).

x New unit construction: The timing of when baseline state regulatory requirements for ne wly constructed units begin to be incur red depends on the installation and closure date for the existing disposal units. Baseline state regu latory cost requirements are incurred at the closure date of the dis posal unit when new unit construction occurs . For example, if a plant_s disposal unit is assumed in this RIA to close in 2019; new unit cons truction costs required under st ate regulations are incurred over its assumed 40-year future lifespan beginning in 2020.

x New landfills : The most economic of three landfill options v (1) combination landfill with 50% of waste below ground and 50% above ground, (2) pile landfill with 5 % of waste below ground and 95% above ground, or (3) offsite landfill -- is determined within the cost model. The cost for the most economical approach is assigned to that plant unless available data sp ecify otherwise. The choice is dependent upon on estimated engineering control costs and annua l CCR disposal tonnage.

x New impoundments : If currently used as a disposal unit, this RIA assumes a landfill will be constructed as the future new disposal unit as impoundments reach end of lif espan, because the model calculates that new landfills are more economical to construct for two cost reasons: (a ) if no pre-existing land depressions for use as a new impoundment, the cost for a larger excavation for a new impoundment rather than a smaller excavation for a landfill is necessary, and (b) the primary determinant of many of the cost for engineering controls is the footprint of the disposal unit such that the same set of engineering controls for a new impoundment would be more expensive than for a new landfill. However, the cost m odel does not estimate the associated capital and annual O&M costs for future conversion of existing wet ash and wet scrubber boilers and conversion of wet CCR conveyance equipment used for moving CCR to disposal unit s. These conversion costs are estimated separately outside of the cost model in this RIA.55 x Baseline “Engineering Control” Cost Estimates

1. Baseline ground water monitoring Groundwater monitoring costs are based on the Remedial Action Cost Engineering and Requ irements (RACER) cost estimating softwar e (2002) with costs based on the R.S. Means, Environmental Cost Ha ndling Options and Solutions (ECH OS), Environmental Remediation Cost Data (2002).

 Assumes same groundwater monitoring requirem ents for both landfills and impoundments

 Point of compliance: Placement at the unit boundary is assumed in the cost estimates . Unit boundary point-of-compliance monitoring complies with th e gwithin 150 meter point-of-complianceh criterion. Plants monitoring at the unit boundary will incur no additional costs under the with in 150 meter placement criteria.

 Number of wells: EPA_s March 1985 gGround Water Technical Enfor cement Guidanceh Document (pages 2-8 to 2-16) recommends a maximum of 150 feet spacing between down-gradient wells. EPA_s December 1980 SW-611 gProcedures Manual for Groundwater Monitoring at Solid Waste Disposal Facilitiesh (pages 40 to 43) recomm ends a maximum of 250 feet spacing between down-gradient wells. Assuming the techn ical documents are the most stringent and the state regulation minimums are the least st ringent, a middle ground within the range is anticipated and used in the cost estimates. This RIA does not evaluate the cost differences between the upper and lower bounds of well spa cing. Groundwater monitoring well costs in this analysis assume a mini mum of 2 down-gradient wells for the first 800 feet of length a long two sides of the landfill or impoundment unit, which is assumed to be square, plus a dditional wells spaced every 400 feet. In addi tion, one upgradient well is assumed.

 Constituents: The cost estimates include monitoring for the following chemical indicators and metals, which re presents a reasonable glikely-c aseh scenario between indicators only and RCR A 40 CFR 261 Appendix VIII constituent monito ring which includes about 500 chemical substances:

o Chemical indicators: Based on EPA_s 1999 cemen t kiln dust proposed rule parameters (i.e., pH, conductivity, total dissolved sol ids, potassium, chloride, sodium, and sulfate) as a cost proxy.

o Metals: Metals with primary and secondary Maximum Contaminant Le vels (MCLs) (i.e., Al, Cu, Fe, Mn, Ag, Zn, Sb, As, Ba, Be, Cd, Cr, Pb, Hg, Se, Tl).

 Frequency: The cost estimates only include semi-annual sampling (most-likel y case) analogous to EPA_s 1999 ce ment kiln dust proposed rule and to many current state regulations, even if some states require a quarterly or annual basis.

 Unitized cost estimate: Dividing the averag e annual cost estimate result displayed in Exhibit 3L below (row item 1) for baseline ground water monitoring, by the count of elec tric utility plants estimated in Exhibit 3I (row 1, column A) and Exhibit 3J (row 1, column A) above to conduct that activity under state government requirements, yields an average annual per-plant (i.e., uniti zed) cost estimate of $64,000. In comparison, EPA_s most recent (2008) Information Collection Request (ICR) No. 0959.13 gGround-Wa ter Monitoring Requirementsh (renewal) for the RCRA Subtitle C 40 CFR 264.92 and 265.92 TSDF ggr ound-water protection standardh pr ovides an estimate of $28, 13056 per year. 49 The $64,000 unitized cost for groundwater monitoring generated by the above assumptions applied in the engineering control cost model used for this RIA is 2.3 times larger and more appropria te to this RIA because it refl ects a larger number of wells per-plant to monitor the groundwater under the la rger sized CCR disposal units compared to th e average sizes of other types of industrial wa ste disposal units.

2. Baseline bottom liners

 Same bottom liner requirements for both new landfills and new impoundments

 The cost estimates include a composite (2-foot compacted clay-s ynthetic) liner for the more stri ngent design and a 2-foot compa cted clay liner, single-synthetic liner, and a 2-foot compac ted ash liner for less stringent baseline designs.

3. Baseline leachate collection system

 No leachate collection is assumed from beneath the impoundment liner

 The cost estimate is comprised of perforated pipes spaced approxi mately 300 feet apart along the base of the unit. It includes a wet well for leachate collection. Leachate is ship ped by truck for off-site treatment.

 Assumes 3-inches of leachate per year coll ected in landfill leachate collection systems.

4. Baseline dust controls Cost estimate includes CCR compaction equipment, water trucks for spraying CCR during compaction and for spraying unpaved landf ill roads, and covers for landfill trucks:

 Compaction Equipment Ash is assumed to be compacted in the waste management area by self-propelled rollers for regula tory scenarios including dust c ontrols. A model cost assumption is that four passes are made by the roller in 6-inch lifts. W ith these assumptions, the roller can compac t approximately 1,300 cy of ash per day. The operating life of purchas ed compaction equipment is assumed to be five years. The n umber of sheepsfoot rollers required is estimated as follows: Rollers = (tons/yr)(2,000 lb/ton)(16.02 kg/m3 / lb/cf) (1,190 kg/m3)(27 cf/cy)(1,300 cy/day)(300 days/yr) The cost of a sheepsfoot roller is assumed to be $75,000 in 1995 dollars. Plants will incur annual costs for equi pment operation ($0.63/cy) and maintenance. Maintenance costs are assumed to be 5% of capital costs. Annual costs for compaction are estimated as follows: Annual Cost = (tons/yr)(2,000 lb /ton)(16.02 kg/m3 / lb/cf)($0.63/cy) + $75,000*0.05*Rollers (1,190 kg/m3)(27 cf/cy)

x Water Truck for Compaction: Ash is assumed to be wetted in the waste management area by wate r trucks to facilitate compacti on and to control dust. A model assumption is that FFC plants currently use water trucks 50% of the operational day to control dust on roads (see Water Spray on Roads). It i s reasonable to

49 $28,130 per year per-facility average cost derived for purpose of this RIA by dividing the reported $27.818 million annual cos t by the reported 989 TSDFs from the EPA ICR 0959.13, Federal Register , Vol.73, No.103 , page 30617; 28 May 2008 ; http://edocket. access.gpo.gov/2008/p df/E8-11888.pdf57 assume that the same water trucks will be used for the roads and the ash management un it. Therefore, it is assumed that an exis ting water truck is available for compaction 50% of the opera tional day. Additional water trucks are assume d to be necessary to facilitate compa ction for large facilities. The cost of tarps, tarp mechanisms, and installation of the mechanisms, as well as th e life of each tarp were estim ated by ICF in gCost Functions for Alternative CKD Control Technol ogiesh (Draft), 19 July 1996. A model a ssumption is that a water truck will be ne cessary for compaction 50% of the time required by the compaction equipment. The water truck time for compaction is estimated as follows: Water Truck Time for Compaction = (tons/yr) (2,000 lb/ton)(16.02 kg/m3 / lb/cf)(8 hr/day)(0.5) (1,190 kg/m3)(27 cf/cy)(1,300 cy/day) One existing water truck for compaction and water spray on roads is estim ated to be sufficient for plants managing less than 39 1,000 tons per year of ash. Facilities mana ging between 391,000 and 1,173,000 tons per year are assumed to purchase one additional water truck . Facilities managing between 1,173,000 and 1,955,000 tons per year are assumed to purchase two additional water trucks. Facilities managing more than 1,955,000 tons per year to the maximum facility size modeled of 2,000,000 tons per year are assumed to purchase three additiona l water trucks. The cost of a water truck is assumed to be $101,000 in 1995 dollars. The water truck opera ting life is assumed to be five years . The operating costs for water spray for compaction are estimated assuming that the truck travels approximately five miles per day, for each d ay used, with a fuel consumption of five miles per gallon at a fuel cost of $1.15 per gallon. The truc k is assumed to operate 50% of the hours required for compaction. The daily water volume used is assumed to be 10,000 gallons, at a cost of $2 per 1,000 gallons. The annual cost ass ociated with ash management is estimated as follows: Annual Cost = (tons/yr)(2,000 lb/MT)(16.02 kg/m3 / lb/cf)(0.5) * [(8hr/day)($31.50/hr) (1,190 kg/m3)(27 cf/cy)(1,300 cy/day) + (5 mi/day)($1.15/gal)/(5 mi/gal ) + (10,000 gal/day)($2/1,000 gal)]

x Covers on Trucks: Covers on hauling trucks as a fugitive dus t control technology is an option for the compliance scenarios. Capital costs for th is dust control technology include the cost of the roll-on ta rp mechanism and the installation of this mechanism. Capital costs for covers on trucks are estimated as follows: Capital Cost = [(tons/year) x (2,000 lb/ton) x (16.02 kg/m3 / lb/cf) x (0.65 hr/load)] x ($4,800) Water truck capacity, refill time, and spray width were estimate d by ICF in gCost Functions for Alternative CKD Control Technol ogiesh (Draft), dated July 19, 1996. (1,190 kg/m3)(0.80)(27 cf/cy)(9 cy/load)(2,400 hr/yr) Annual costs for this dust contro l technology include the co st of the tarps and the cost to replace the tarps. Tarps are estima ted to be replaced every 150 loads. Replacement of a tarp is estimated to require 15 minutes . Annual costs for covers on trucks are estimated as f ollows: Annual Cost = (tons/yr)(2,0 00 lb/ton)(16.02 kg/m3 / lb/cf )($155/tarp + 0.25hr/tarp*$19/hr) (1,190 kg/m3)(0.80)(27 cf/cy)(9 cy/load)(150 load/tarp)

x Water Spray on Roads: Water spray on roads is required as a fug itive dust control technology for the compliance scenarios. A model assumption is that FFC plants currently have water trucks and use water spray on roads as a baseline management pr actice. A model assu mption is that dust co ntrol is required for a road length of 1.5 miles (3 miles roundtrip), with a road width of 10 meters. The water truck capacity is assume d to be 5,000 gallons and requires approximately one hour to fill. The water truck can spray a width of five meters at an assumed speed of 10 miles per hour. For the baseline scenario, a model assumption is that the entire water volume (5,000 ga llons) will be sprayed on each pass of t he truck along one side of the road (i.e., 1.5 miles x 5 meters). The resu lting water volume per road area, averaged over the 1.25 hours requ ired to spray the58 road and refill the truck, is approximately 2.5 times that of th e average hourly daytime evapora tion rate. Therefore, water spr ay on roads will be required 3 times per day. The water volume spra yed per road area is estimated as follows: Water per Area = (1.5 mi)(5,280 ft/mi)(0.3048 m/ft )(10 m)(5,000 gal)(3.785 L/gal) = 0.784 L/m2 The time required for the water truck to be filled, spray along both sides of the road, and return for refill ing is estimated a s follows: Time = (1 hour) + (3 miles)/(10 miles/hour) = 1.3 hour Therefore, the total time for one pass is assumed to be 1 hour and 15 minutes. The average rate of water spray is estimated as follows: Spray Rate = (0.784 L/m2)(1,000 ml/L)(cm3/ml)(1,000 mm/m) = 0.6272 mm/hr (100 cm/m)3(1.25 hr) The average hourly daytime evaporation rate is approximately 0.25 mm/hr. Therefore, th e water spray rate is approximately 2.5 t imes the evaporation rate. Since the total time required for water sp ray (1.25 hour) times 2.5 is approximately 3, a model assumption is that water spray on roads is required approximately every 3 hour s. In order to coordinate the water tr uck use for road spray and ash compaction, it is assumed that the truck alternates between these two requirements during the day. Theref ore, over a nine-hour day (eight working hours p lus one hour for lunch), roads are sprayed 3 times, requiring a total of approxima tely 4 hours, or 50% of the operational day. Because it is ass umed that FFC facilities currently spray water on roads for dust control, the in cremental cost from the baseline to the compliance scenarios is zero.

5. Baseline rain and surface water run- on/run-off controls (landfills only) The cost estimates assume that stormwater run-on/run-off contro l is comprised of a ditch surroun ding active area of landfill an d an excavated bermed basin for water collection.

6. Baseline financial assura nce for CCR disposal unit clos ure and post-closure care Financial assurance helps assure that the owners and operators of CCR landfills and impoundments have adequately planned for th e future cost of closure, post-closure care, and correc tive action for known releases, and to assure that adequate funds will be available wh en needed to cover these costs if the owner or operator is unw illing or unable to do so. Financial assura nce helps protect future generations fro m paying for damages caused by or the prevention of damage s potentially created from current waste management activities. Requiring provisi on of financial assurance during operation of la ndfills and impoundments places the cost burden on the current owner and consumer, an d prevents costs from being passed from the curr ent generation to future generations. The cost estimate includes the costs for selecting a financia l mechanism, establishing a financial test, and establishing a le tter of credit. The differences between RCRA Subtitle C and Subtitle D financial assurance mechanisms are not assessed. This RIA assumes the s ame requirements for both landfills and impoundments:

x Capital cost includes selection of financia l assurance mechanism, establishment of financial test, and establishment of letter of credit. The letter of credit is assumed to be most available to utilitie s and will be utilized in most ci rcumstances. This is amortize d in the annual

cost.

x Annual cost includes maintenance of financia l test and maintenance of letter of credit . Establishment and annual maintenance o f the letter of credit is estimated to be 1% to 3% of the nominal value of the letter of credit (i.e., total co st of closure and post closure). This RIA applied the 2% midpoint of this range. Implementation costs ar e estimated on the assumption that an outside consulting firm an d legal assistance will assist in obtaining and ma intaining the letter of credit ($692 per ye ar in 1995 dollars or $1,051 per year infl ated to 2009 dollars). Estimate obtained from Mohammad Iqbal and John Collier, ICF, Inc., gLocal Government Financial Test Economic Analysi s,h59 memorandum to George Garland, EPA, 30 April 1995. Additional supp orting information obtained from EPA gEstimating Costs for th e Economic Benefits of RCRA N oncompliance,h September 1997.

7. Baseline disposal unit location restrictions Baseline cost not estimated in this RIA.

8. Baseline closure capping to cover unit The cost estimate for this engineering c ontrol does not include the closure plan cost or closure certifi cation costs. Capping costs are a large capital expense. So, if a unit is expected to close in one year the total capping cost is a ssigned to the last year in the lif e of the unit. However, businesses are likely to borrow money from a bank for these la rge capital costs and annualize them over a set period of time, f or example, 10 or 20 years. Incremental cost estimates in the cost model are ov erestimated for large capital expenditures applied to existing un its that have been added over short time periods. In addition, owners are likely to close these units prio r to the proposed rule coming into effe ct if promulgated as a final rule. This RIA assumes the same requirements for both landfills and impoundments:

 Synthetic cap with drainage layer is comp rised of a 60 mil HDPE synthetic liner, 1 fo ot sand, filter fabric , 1.5 foot slope and earth fill, 0.5 foot topsoil, and vegetation. It includes a perforated pipe for drainage collection.

 Synthetic cap without drainage layer is comprised of a 60 mil HDPE synthetic lin er, 1.5 foot slope and earth fill, 0.5 foot top soil, and vegetation.

 Clay cap is comprised of 2 feet of off-s ite clay, 0.5 foot topsoil, and vegetation. Cover costs would be lower if on-site clay is available.

 Soil/clay cover is comprised of 0.5 foot clay, 0.5 foot earthfill , and 0.5 foot topsoil, and vege tation. Cover costs would be lower if on-site clay is available.

 Soil cap is comprised of a 1.5 foot slope a nd earth fill, 0.5 foot topsoil, and vegeta tion. The slope of the cap is assumed to be 0.02:1 (rise:run) with a cover toe slope of 4:1 (run:rise).

9. Baseline post-closure ground water monitoring requirements

 Same requirements for both landfills and impoundments

 Baseline post-closure monitoring is assume d to comprise 30 years of groundwater m onitoring and surface water monitoring on a se mi-annual basis. The physical parameters (i.e., point of compliance, number of wells, sets of ch emical indicators and sets of chemical c onstituents monitored, and semi-annual frequency) and uni t cost are assumed identical as defined in the baseline groundwater monitoring cos t item 1 above in this section of the RIA.

 However, post-closure monitoring costs are es timated in this RIA assuming an annual su m is placed in a fund by affected entitie s (i.e., electric utility owners) during the assume d average 40-year operating life of the CCR disposal unit. At the time of closure sufficient monies will be available in the fund to cover post-closur e monitoring for the next 30 years beyond en d-of-lifespan, assumi ng an annual interes t rate of 7%.

10. Baseline storage tank/container design and operating standards Baseline cost not estimated in this RIA60 x Baseline “Ancillary Costs” Estimates

11. Baseline offsite disposal The baseline cost for engineering controls at offsite CCR disposal sites (assumed in th is RIA to be commercial Subtitle D landf ills) is estimated using the same cost model as the engineering controls for onsit e disposal units. In addition, th e offsite disposal baseline co st includes the cost for truck transport from the electric utility plan t to the offsite landfill, calculated as follows:

 Baseline Assumptions:

o 12% (15 million tons/year) CCR currently trucked offsite to non-haz LFs (2005)

o 6 miles average one-way trucking distance to offsite LFs 50

o $0.10/ton/mile non-haz wast e truck operating cost

o 12 tons CCR per full truckload (source: Gambrills MD case st udy); (15 million tons/year) / (12 tons/load) = 1.25 million truckl oads

per year

 Baseline Cost Calculations:

o Manifest cost: $0

o Trucking cost: (15 million tons/year) x (6 miles) x ($0.10/to n/mile truck operating cost for non hazmat) = $9.0 million/year

12. Baseline structural integrity inspections Assumptions: Baseline assumption is that 82% of CCR dispos al units at electric utility plants are inspected (source: page 36 of joint DOE/EP A report gCoal Combustion Waste Management at Landfills and Surface Impoundments, 1994-2004h, report nr. DOE/PI-0004, Aug 2006 at: http://www.ead.anl.gov/pub/dsp_detail.cfm?PubID=2008 ). Per-plant cost for inspections estimated in Exhibit 3K below. Cost Calculation: Industry cost: ($10,829/year per f acility) x (82% inspected) x ( 495 plants) = $4.40 million per year State government cost: ($599/year per facility) x (82% inspected) x (495 plants) = $0.24 million per year Total (industry + state) = $4.64 million per year

50 Source: based on actual distance reported for a MD plant at h ttp://www.rachel.org/en/ node/445). Note: a broader range of 2.4 miles to 25 miles in one-way offsite landfill distance was reported by an OH plant at http://www.columbus dispatch.com/live/content/local_news /stories/2008/04/14/Powerfills.A RT_ART_04-14- 08_B1_FF9TI0U.html?sid=101, and a WI plant, respectively at http://www.lacrossetribune.com/ articles/2007/09/21/news/03landfill0 921.txt61 Exhibit 3K Summary of Industry & State Government Labor Costs for MSHA Surface Impoundment Safety Plan & Annual Inspections & Estimate of Annual Costs for Similar Structural Integrity Activities for El ectric Utility Plant Su rface Impoundments
Item Paperwork Burden Element* Labor hours Cost (2006) Cost per facility Annualized Industry Costs 1 Impoundment Safety Plan prepared by mining company engineer >>> Purpose: To evaluate geotechni cal, hydrologic, hydraulic & other engineering factors to construct or im prove surface impoundment structures to avoid structural failures 1,300 $70.07/hr $91,091 $9,109

2 Revisions to Impoundment Safety Plan prepared by mining company engineer 2 40 $70.07/hr $2,803 $280 3 Fire Extinguishing Plan prepared by mining company engineer or supervisor 20 $70.07/hr $1,401 $140 4 Annual Status Report & Annual Certif ication prepared by company engineer >>> Purpose: To determine whether impou ndments are operated and maintained according to approved engi neering safety plan 2 $70.07/hr $140 $14

5 Recordkeeping and weekly inspections 3 >>> Purpose: To determine whether any signs of instability have developed 2.5 hrs per inspectn x 17 inspect = 42.5 $30.27/hr $1,286 $1,286

Subtotal (Industry costs): $10,829 per facility per year
State Government Costs

6 Review of Impoundment Safety Plans 160 hrs tech review + 2 hrs admin review $30.57/hr $4,952 $495

7 Review of revisions to Impoundment Safety Plans 30 hrs tech review + 2 hrs admin review $30.57/hr $978 $98

8 Review and prepare responses for impoundment abandonment plans 1 $30.57/hr $31 per plan $3 9 Review of annual inspection Status Reports and Certifications 1 $30.57/hr $31 per report $3 Subtotal (State government costs): $599 per facility per year
Total Cost Total industry + state government cost: $11,428 per inspection
Notes: * Elements, labor hours, and labor costs are based on the gSupporting Statementh for the March 2008 DOL/MSHA ICR 12-19-0015, gR efuse Piles and Impounding Structures, Recordkeeping, and Reporting Requirementsh at : http://www.msha.gov/regs/fedreg/paperwork/2004/04-24046.pdf 1. Assumes plans are valid for 10-years similar to the length of RCRA permits. 2. Assumes one revision to the plan will be made during 10-years. 3. Average labor hours per inspection between inspections at sites with monitoring instruments (3 hours) and at sites without m onitoring instruments (2 hours).62 13. Baseline RCRA facility-wide investigations (RFI) Baseline cost assumed to be $0 because this RIA assumes that a ll baseline CCR disposal units used by electric utility plants ar e not regulated under RCRA Subtitle C.

14. Baseline facility-wide corrective action Because CCR is not regulated as Subtitle C hazardous waste, there are no existing fa cility-wide (i.e., CCR disposal units plus other waste units also located at the same plant) correc tive action requirements, alt hough some state governments have the following unit-specifi c corrective action requirements affec ting CCR disposal units. State regulations for the top 25 coal usag e states (for electricity) were reviewed for correction action requirements in 2000. These regulations were not updated as part of this RIA. Corrective ac tion requirements were identifi ed in 21 of the 25 states.

x Surface impoundments: 71% of CCR impoundments representing 67% of CCR impoundment annual tonnage have state government baseline corrective action requirements:

o AZ, IN, and IA establish a corrective action alert level and response action in site-specific state permits

o CO requires corrective action for new units

o 9 states (FL, GA, KY, MI, NC, ND, PA, UT, WI) require corrective action

o IL, MN, TX, WV, WY do not allow groundwater degradation, but specific enforcement mechanisms are not specified in state regulations

o MO requires corrective action for units closed with waste in pl ace, otherwise, corrective action may be established under a per mit

o NM requires an abatement plan.

x Landfills: 66% of CCR landfills with 81% of CCR landfill annual tonnage have state gove rnment corrective action requirements:

o AZ establishes corrective action alert level and response action in site-specific state permits

o 15 states (CO, FL, GA, IL, KY, MI, NC, ND, OH, OK, PA, UT, WV, WI, WY) require corrective action

o MN, TX do not allow groundwater degradati on, but, specific enforcement mechanisms are not specified in state regulations

o MO, TN require assessment only

o NM requires an abatement plan

15. Baseline waste disposal permit cost

x Assumptions:

o 93% of CCR landfills have a state government non-hazardous wa ste disposal permit and 12% of CCR impoundments have such permits. Source: page 28, Table 9 of gCoal Combustion Wast e Management at Landfills a nd Surface Impoundments, 1994-2004h, August 2006 at http://www.ead.anl.gov/pub/dsp_detail.cfm?PubID=2008

x Industry waste disposal permit cost:

o ($5,000 RCRA Part A permit) + ($50,000 RCRA general facility permit requirements) + ($25,000 average RCRA Part B for impoundment or landfill) = $80,000 per Subtitle C permit

o Assume RCRA Subtitle D (40 CFR 257, 258) waste permitting activities are less bur densome than RCRA Subtitle C waste permits. Based on factor of 3.3 times more technical standard s listed in RCRA Subtitle C (40 CFR 264/265, 268, 270) compared to Subtitle D (40 CFR 257, 258), assume Subtitle D permitting costs are lower by the 3.3 factor:63 ($80,000 per year average Subtitle C wa ste disposal permit cost) / (3.3) = $24,300 per non-haz waste disposal permit [((93% landfills w/permit) x (337 landfills)) + ((12% impoundments w/permit) x (158 impoundments))] x ($24,300 per permit) = $8.1 million Amortized industry cost with a cap ital recovery factor of 0.07246 (@7% disc ount rate & 50-years) = $0.59 million/year

x State government waste disposal permit cost:

o Build estimate based on the following four RCRA Subtitle C pe rmit-related state government ac tivities associated with RCRA Subtitle C waste disposal permits: 51 (1,215 pre-application activities ) + ($27,063 application review) + ($26,846 permit issuance) + ($3,110 permit maintenance) = $58,200 average cost per Subtitle C waste disposal permit.

o Assume RCRA Subtitle D (40 CFR 257, 258) waste permitting activities are less bur densome than RCRA Subtitle C waste permits. Based on factor of 3.3 times more technical standard s listed in RCRA Subtitle C (40 CFR 264/265, 268, 270) compared to Subtitle D (40 CFR 257, 258), assume Subtitle D permitting costs are lower by the 3.3 factor: ($58,200 per year average Subtitle C wa ste disposal permit cost) / (3.3) = $17,600 per non-haz waste disposal permit

o State Cost Calculation: [((93% landfills w/permit) x (337 landfills)) + ((12% impoundments w/permit) x (158 impoundments))] x ($17,600 per permit) = $5.85 million Amortized state cost with a capital recovery factor of 0.07246 (@7% discount rate & 50-years) = $0.42 million/year Total baseline permit cost (industry + state government) = $1.01 million per year

16. Baseline enforcement inspection Not estimated in this RIA.

17. Baseline remediation of environmental releases Not estimated in this RIA.

51 Source: Based on cost data from page 84 of January 2007 ASTSWM O report gState RCRA Subtitle C Core Hazardous Waste Management Program Implementation Costs Final Reporth at: http://www.astswmo.org/files/publicati ons/hazardouswaste/Final%20Report%20-%20RCRA%20Subtitle%20C%20Cor e%20Project.pdf64 x Baseline CCR Disposal Cost Estimation Results

Exhibit 3L below displays the average annualized costs for each of the base line cost components, as well as on an average per-ton and per

plant basis. Appendix H provides plant-by-plant and owner entity -by-entity estimates of baseline costs.

Exhibit 3L Industry Baseline Cost Estimates for CCR Disposal by Electric Utility Plants (Onsite + Offsite) ($millions per year in 2009$ discounted @7% over 50-year period-of-analysis 2012 to 2061)
Baseline Cost Element CCR Landfills (311 plants) CCR Impoundments (158 plants) Row totals (467 of 495 plants) A. Engineering controls (onsite disposal): 1. Ground water monitoring $19.2 $8.0 $27.2 0.5% 2. Bottom liners $2,751 $1,219 $3,970 71.5% 3. Leachate collection system $105.5 $52.2 $157.7 2.8% 4. Dust controls $24.2 $2.8 $27.1 0.5% 5. Water run-on/run-off controls $4.8 $0.7 $5.6 0.10% 6..Financial assurance $61.2 $17.9 $79.2 1.4% 7. Disposal location restrictions Not estimated Not estimated Not estimated 8. Closure capping to cover unit $72.7 $15.7 $88.5 1.6% 9. Post-closure groundwater monitoring $1.3 $0.5 $1.8 0.03% 10. Storage design/operating requirements Not estimated Not estimated Not estimated Subtotal Engineering Control costs = $3,040 $1,317 $4,357 78% B. Ancillary costs for CCR disposal: 11. Offsite disposal (commercial landfills) $1,193 $0 $1,193 21.5% 12. Structural integrity inspections $2.46 $2.18 $4.64 0.08% 13. RCRA facility-wide investigation (RFI) $0 $0 $0 0%
14. Corrective action Not estimated Not estimated Not estimated NE 15. Waste disposal permits $0.69 $0.32 $1.01 0.02% 16. Enforcement inspection Not estimated Not estimated Not estimated NE
17. Remediation of environmental releases Not estimated Not estimated Not estimated NE Subtotal Ancillary costs = $1,196 $2.5 $1,199 22% Cost Summary (A+B) Column total annualized cost = $4,236 $1,320 $5,556 (includes $1,193 offsite disposal) PV = $76,678 (@7%, 50-years) Average annual cost per plant = $13.6 million per plant $8.4 million per plant $11.9 million per plant Average cost per CCR ton disposed = $59 per ton (71.8 million tons per year) $59 per ton (22.4 million tons per year) $59 per ton (94.2 million tons/year disposed)65 x Validity Check of Baseline Cost Estimate (2 Tests):

o Validity Test #1 of 2: Comparison to ACAA P ublished Estimate of Av erage CCR Disposal Cost

As displayed above in Exhibit 3L the estimated baseline (i.e., current) average annualized cost to the 495 coal-fired electric utility plants for disposal of CCR is $5.6 billion per year ( 2009$). This annualized cost includes amor tization of capital i nvestment in construc tion of disposal units and associated equipment (i.e., in-plant equipment for extracting CCR from boilers, CCR storage equipment, CCR conveyance equipment such as slurry pipelines for wet CCR or tr ucks and mechanical conveyor belts for dry CCR, and the disposal units themselves), p lus annual expenditures for operation, maintenance and replacement/expansion of this equipment and disposal units. On a unitized cost-per -ton basis -- calculated by dividing the annualized baseline cost by the estima ted 94.2 million tons per year (a s of 2005) CCR disposed in ( a) onsite landfills plus (b) offsite landfills plus (c) impoundment s annually v the estimated baseline cost represents an averag e unitized cost of $59 per-ton.

In comparison, the American Coal Ash Association (ACAA) estimates that the average un it cost (per-ton) for baseline disposal of CCR by coal-fired electric utility pl ants ranges as low as $3 pe r-ton to higher than $40 per-ton:

" As one can see, a variety of factors enter into determining disposal costs. The lowe st cost occurs when a disposal site is located near the power plant and the material being disposed can be easily handled. If the material can be piped, rather than trucked, costs are usually lower. In these types of situations, cost may be as low as $3 to $5 per ton. In other areas, when distance is far away and the [CCR] must be handled several times due to its moisture c ontent or volume, costs could range from $20 to $40 per ton. In some areas, the co sts are even higher. If new sites are required and extensive permitting processes ta ke place, the total cost of the facility may be incr eased, resulting in higher di sposal costs over time. " 52

The reasons the average annualized and unitized baseline CCR disposal cost of $59 per-ton estimated in this RIA, is higher than the baseline cost range of $3 to over $40 per-ton reported by the ACAA, are:

x Low-end unitized cost : The low-end of ACAA_s reported co st range is $3 to $5 per-ton. A ssuming the cheapest operating surface impoundment does not include a liner and leachate collection costs as estimated in this RIA for impoundments in states with suc h regulatory requirements, the baseline surface impoundment unitized cost may be as low as $2 per-ton based on the cost elements applied in this RIA. This low-end unitized cost may be derived from the impoundment cost column of Exhibit 3L as follows:

(Column total cost - Row 2 cost - Row 3 cost) / ( 22.4 million tons per year managed in impoundments) = ($1,317 million/year - $1,219 million/year - $52.2 m illion/year) / (22.4 million tons per year) = $2.04 per-ton



### x High-end unitized cost : The upper-end of ACAA_s reported cost range is $20 to $40 per ton, which applies to offsite disposal. The cost estimation of this RIA incorporates o ff-site commercial disposal costs on a state-by-state spec ific basis according to ele ctricity

52 Source: ACAA webpage containing Frequen tly Asked Question nr. 13 at http://acaa.affi niscape.com/displayco mmon.cfm?an=1&subarti clenbr=5#Q1366 power plant location, using commercial landf ill tipping fees ($2009) for contaminated so il, which range widely from $11 per-ton to $135 per-ton, with a national average of $50 per-ton. For example, commercial landfill tipping fees for contaminated soil for some of the high coal usage states are: TN = $11.19/ton, IN = $32.73/ton, OH = $35.48/ton, a nd PA = $57.96/ton. The baseline cost estimation method of this RIA then added a CCR offsite transportation and loading co st of approximately $33 per-ton based on th e RACER cost estimation tool. For the esti mated 15.0 million tons per-year of CCR dispos ed in offsite landfills, the estimated b aseline cost is $1,193 million per-year, which is equivalent to $79.53 per-ton over the 50-year time period of the RIA cost analysis which assumes increasing coal usage (0.73% per-year ) by electric utilities and subsequent offsite landfill disposal over the 50 year time period. It is unknown what cost elements are included in the high-end of the ACAA reported cost ra nge (e.g., transportation co st and/or landfill tipping fee cost). In addition, electric utility companies likely have annual or multi-year contracts with off site landfill operators that offer lower tipping fees than the state-average off-site contaminated soil tipping fees used in this RIA.

o Validity Test #2 of 2: Comparison to CCR Dispos al Costs Contained in the EIA Form 767 Database

The 2005 Energy Information Administration (E IA) Form 767 database (Schedule 3, Part B) indicates $5,890 million in annual capi tal and O&M cost reported by steam electric plants with nameplate capaci ty of 100 MW or greater, including (a) $0.314 million per year for water pollution controls, (b) $0.193 million per year for solid waste disposal, (c) $0.185 million per y ear for other pollution contr ols, (d) $3,627 million per year capital expense for air pollu tion abatement, and (e) $1,546 million per year for collection and disposal O&M c osts for fly ash, bottom ash, and FGD. This last cost element --- $1,546 million pe r year for CCR disposal --- is only 28% of the $5,556 million per year estimate displayed in Exhibit 3L above. However, the 2005 EIA Form 767 cost data are associated with only 179 coal-fired electric utility plants, which represent only 36% of the 495 co al-fired electric utility pl ants addressed by this RIA. Therefore, to facilitate a direct comparison, the $1,546 million per year cost from the data in EIA Form 767 ma y be extrapolated to all 495 plants by multiplying by the fact or 2.765 (i.e., 495 / 179), which produces an estimated extrapolated cost for all 495 plants of $4,275 million per year (i.e., 2.765 x $1,546 m illion per year). This extrapolated cost is 23% lower than the $5,556 million per year baseline cost estim ated in this RIA. This comparison sugg ests the baseline cost estimated in this RIA may be an over-estimate, but it is not clear whether the cost data in the EIA Form 767 data base include baseline costs to the electric utility pl ants for compliance with existing state gove rnment regulations concerning CCR disposal (e.g., the annualized cost for obtaining and maintaining state government di sposal permits and the annualized cost for impoundment structu ral integrity inspections), as does this RIA.67 

## Chapter 4 Estimated Cost for RCRA Regulation of CCR Disposal

Note : EPA formulated cost estimates in this Chapter based on the October 2009 draft RIA regul atory options. Because the high-end cost of those options (i.e., for th e Subtitle C ghazardous wasteh option) is larger than the high-end cost for the 201 0 regulatory options (i.e., for the Subtitle C gspecial wasteh opti on), the costs in this Chapter are proportionately over-estima ted. However, Section 6B of this RIA applies scaling factors to adjust the costs estima ted in this Chapter to the 2010 options.



### 4A. EPA’s Prior Cost Estimates for Possible RCRA Regulation of CCR Di sposal at Electric Utility Plants

In prior studies, EPA_s Office of Solid Waste (which EPA renamed as the ORCR eff ective 18 January 2009), formulated the followi ng industry compliance cost estimates for different RCRA-based regulatory approaches to CCR disposal by th e electric util ity industry:

1988: OSW's 1988 Report to Congress on CCR estimated $2.4 billion to $4.7 billion per year (1986$) in poten tial average annualized industry cost (514 plants in 1984) for compliance with technical standards cont ained in 40 CFR 264 RCRA Subtitle C hazardous waste regulations. The range reflects different lin er assumptions (i.e., single versus doubl e liners) and whether only unlined CCR un its close or all existing units close requiring constr uction of new units. This cost includes closure costs but not a cost for correctiv e action excavating and removing CCR to Subtitle C facilities for closure of existing units. This report separately estim ated that corr ective action gat a cost of about $2.0 billion per plant, industry-wide costs would exceed $1. 0 trillionh lump-sum cost, which is equi valent to $43 billion annualized cost (discounted @3% over 40-years) . Source: EPA-OSWER repor t nr. EPA/530-SW-88-002, Feb 1988. 1999: OSW_s 1999 Report to Congress focused on the gco-managementh (i.e., low-volume mixed with high-volume) subset of CCR unit s (i.e., 206 units at 353 plants in 1994), constituting 53 million tons (50%) of the 105 million to tal high-volume electric utili ty CCR generation in 1997. This report estimated a range of $800 million to $900 million per year (1998$) in pot ential average annualized compliance cost to the electric utility industry to comply with technical standards similar to 40 CFR 258 RCRA Subtitle D nonhazardous waste regulations. This cost estimate includes opening new CCR units to replace existing units that do not meet Subti tle D standards, including the following itemized costs: land purchase, site development, liner installation, leachate collection, gr oundwater wells & monitoring, closure costs, and post-closure costs. This estimate accounted for state CCR management requirements as of 1997. Source: EPA OSWER report nr. EPA 530-R-99-010, March 1999. 2005: In a November 2005 report, an OS W contractor (DPRA Inc) estimated $304 million to $521 million per year (2005$) in potential average annualized cost for the electric utility industry (i.e., 470 units at 452 pl ants in 2003) to comply with regulatory opt ions developed with reference to the gtailored standardsh of EPA_ s 1999 cement kiln dust proposed rule which based many elements on 40 CFR 258 RCRA Subtitle D non-hazardous waste regulations. Cost elements in this report included (a) location standards, (b) operating criteria such as cover material, dust cont rol, run-on/run-off control, (c) design cr iteria such as liner and leachate collectio n, (d) groundwater monitoring, (e) closur e and post-closure standards, and (f) financia l assurance for closure, post-closure and corre ctive68 action. This estimate accounted for state CCR management requirements as of 2004, but di d not include costs for corrective acti on. Source: EPA-OSWER document ID nr. EPA-HQ- RCRA-2006-0796-0469 at http://www.regulations.gov.

These three prior RCRA regulator y cost estimates range from $304 million to $4.7 billion per year. Even without updating these prior cost estimates to the current 2009 price level, all three prior cost estimates exceed the 1993 Executive Order 12866 Section 3(f)(1) geconomically significanth $100 million annual effect threshold for Federal rulemakings.



### 4B. Regulatory Cost Estimation Algorithms & Results

This section presents incremental cost estimates for each regulatory option, for both existing active (i.e., operating) and future new CCR landfills and impoundments, and by size/type of affected electric utility plant owner entity. Incremental comparison of the es timated cost of each regulatory option to the baseline (as estimated in Chapter 3 of this RIA) is consistent with OMB_s 2003 gCircula r A-4: Regulatory Analysish best practices guidance to Federal agencies:

g

Identify a baseline. Benefits and costs are defined in comparison with a clearly stated alterna tive. This normally will be a “no action” baseline: what the world will be like if the proposed rule is not adopted .h

As listed below, this RIA estimates 18 pot ential regulatory costs and the land disposal restricti on (LDR) dewatering treatment standard, based on many of the same unit cost data sources and the same framework (i.e., 2009 price leve l, 50-year period of analysis, etc.), i dentified in the prior chapter of this RIA for baseline co st estimation. According to three methodological groupings , this RIA estimates three categories of regulatory costs:

A. Engineering controls for CCR disposal units v estimated using the cost m odel described in the prio r chapter of this RIA:

1. Ground water monitoring
2. Bottom liners v for future new units only
3. Leachate collection system v for future new units only
4. Dust controls v applicable to landfills only
5. Rain and surface water run-on/run-off cont rols v applicable to landfills only
6. Financial assurance for disposal unit closure and post-closure
7. Disposal unit location rest rictions (6 types: water tables , floodplains, wetlands, fault areas, seismic zones, karst terrain)
8. Closure capping to cover unit
9. Post-closure monitoring requirements
10. Temporary storage requirements v not estimat ed in this RIA because do not have info rmation on the baseline counts or physical conditions of CCR storage tanks and storag e buildings at electr ic utility plants.69 B. Ancillary costs for CCR disposal v estimated outside of the engineering control cost model:
11. Offsite disposal (hazmat trucking, RCRA manifesting, offsite RCRA TSDF permits)
12. Structural integrity insp ections v impoundments only
13. RCRA facility-wide investigation (RFI)
14. RCRA facility-wide corrective action
15. RCRA TSDF hazardous waste disposal permits for onsite disposal
16. RCRA enforcement inspection
17. Cleanup remediation of future CCR impound ment failures as RCRA hazardous waste
18. EPA administrative repo rting & recordkeeping

C. LDR cost for land disposal restriction dewatering treatment v Sections 3004(d) and (m) of the RCRA statute require treatment prior to land disposal for Subtitle C hazardous waste listings, but not for Subtitle D non-hazardous waste regulation. The purpose of t he treatment is to gsubstantially diminish th e toxicity of the waste or s ubstantially reduce the likelihood of migration of hazardous consti tuents from the waste so that short-term and long-term threats to human health and the environm ent are minimizedh (source: section 3004(m)):

o Dry CCR disposal (landfills): Moisture conditioning and co mpaction included in engineering control cost item 4.

o Wet CCR disposal (impoundments): Estimated out side and separately of the engineeri ng controls cost model in this RIA.

This RIA does not include either qualitative or quantitative es timation of the potential effect s of the proposed rule on econom ic productivity, economic growth, employment, job creation, or international economic competitiveness. These potential effects are identified a s factors in both the 1993 Executive Order gRegulatory Pl anning and Reviewh (section 3( f)(1)) and in the 1995 Unf unded Mandates Reform Act ( section 202(a)(4)). These other potential economic e ffects are excluded from this RIA because the upper-end of the range in average an nualized regulatory cost across all regulatory options as estimated in this chapter below, does not exceed the 0.25% to 0.5% of Gross Do mestic Product (GDP) threshold identified in OMB_s 1995 guidance 53 for attempting to measure such other ec onomic effects for purpose of UMRA economic analysis compliance. Based on the 2008 US GDP of $14.42 trillion, 54 the 0.25% to 0.5% threshold is e qual to $36 billion to $72 billion.



### 4B.1 Regulatory Cost to Industr y for RCRA “Engineering Controls”

This RIA assumes that that same set of RCRA 3004(x) custom-tailored engineering controls is requi red under each of the regulato ry options, so the costs for engineering controls for all regulatory options are mostly, but not entir ely, based on the same cost estimation f ormulae described above in Chapter 3 for estimation of baseline engineering cont rol costs. Furthermore, this RIA assume s that the engineering control costs are

53 Source: Section 4.B(3) of OMB_s 31 March 1995 guidance for implementing the UMRA state that g We would note that such macro-economic effects tend to be measurable, in nation-wide econometric models, only if the economic impact of the regulation reaches 0.25 percent to 0.5 percen t of Gross Domestic Product. A regulation with a smaller aggregate effect is highly unlikely to have any measurable impact in macro- economic terms unless it is highly fo cuses on a particular geographic region or
economic sector. h

54 Source: 2008 3 rd quarter estimate of 2008 US GDP as reported in gTABLE Bv8.ÄGross domestic product by major type of product, 1959v2008h of the 2009 Economic Report of the President at http://www.gpoaccess.gov/eop/tables09.html70 similarly specified in EPA_s cement kiln dust 20 August 1999 proposed rule. 55 This assumption was required to launch this RIA in April 2009 prior to the initial draf t of the CCR proposed rule and its re gulatory options. This RIA assu mes that liners and leachate coll ection systems requirements apply only to future new CCR landfills and impoundments. Offsite dispos al costs are assumed unaffected under all regulatory options because offsite CCR disposal units are assumed to be commercially-owned units (i.e., owned by the waste management indu stry) and assumed currently in compliance with the custom-tailored engineer ing controls. For engineering controls added to existing unit s the costs are added to the remaining years of the li fespan of the landfill or impoundment.

1. Regulatory groundwater monitoring cost Same cost estimation formula applied above in Chapter 3 for baseline cost estimation.

2. Regulatory bottom liner cost Same cost estimation formula applied above in Chapter 3 for baseline cost estimation.

3. Regulatory leachate collection cost Same cost estimation formula applied above in Chapter 3 for baseline cost estimation.

4. Regulatory fugitive dust control cost Same cost estimation formula applied above in Chapter 3 for baseline cost estimation.

5. Regulatory financial assurance cost Same cost estimation formula applied above in Chapter 3 for baseline cost estimation.

6. Regulatory closure costs Same cost estimation formula applied above in Chapter 3 for baseline cost estimation.

7. Regulatory disposal unit location restriction costs This cost element is estimated outside of the engineering controls cost model, using the factors, data and calculations below.

x Count of Existing Electric Plants Which May be Affected by Lo cation Restrictions To estimate the potential cost of location re strictions, this RIA conducted a GIS analys is to determine whic h facilities may be affected by location restrictions. As summari zed below, the GIS analysis was conducted for th ree of the six possible site restrictions (i. e., using three GISbased datasets pertaining to fault areas, seismic zones, and karst zones readily available to EPA-ORCR at the 2009 launch of th is RIA). This limitation potentially results in unde r-estimation in this RIA of the number or elec tric utility plants which may be affected a nd thus underestimation of regulatory location restriction costs. On the other hand, the av erage per-plant cost of $4.1 million applied bel ow for estimating the potential cost of this regulatory element is over five-times higher than the $0.75 million 56 cost per-plant cost estim ated by another study for

55 Federal Register , Vol.64, No.161, 20 Aug 1999, pp.45632-45697.

56 Source: $0.75 million disposal unit location restriction mitigation cost for a single electric utility plant is from page 10 ( slide number TVA-00007496) of gKingston Fossil Plant Decision Matrix: Pond or Peninsula?,h 27 Jan 2005 Plant Managers Conference Room at http://www.tva.gov/kingston/tdec/pdf/ TVA-00007487.pdf71 location restriction mitigation involving karst mitigation and floodplain/wetland m itigation; this probably overly offsets the possible cost underestimation in this RIA fo r this regulatory element. The GIS was based on the DOE-EIA eGRID database to identify th e geographic coordinates for 491 of the 495 electric utility plan ts (disregarding four plants not present in the eGRID database)

. Appendix I of this RIA presents site location data for each electric utility plant used in the GIS analysis. In order to geographically capture bot h the facilities and their waste units, and to compensate for the fact that there exists uncertainty as to the exact facility location versus th e reported geographic coordinates (i.e., depending on whether loc ation was measured by plant centroid, street address, smokest ack, etc.), this GIS analysis used both a 1-mile and a 3-mile buffer around the repor ted facility coordinates. This RIA presumes these bu ffers are likely to ensure inclusion of th e facility's onsite CCR disposal units, and a ccount for uncertainty in the location data. The 1- mile buffer should capture all impoundments; the 3-mile buffer represents an upper-bou nd to capture all landfills that could reasonab ly be considered on-site. 1. Water table restrictions: GIS analysis not conducted for this site restriction 2. Floodplain restrictions: GIS analysis not conducted for this site restriction 3. Wetlands restrictions: GI S analysis not conducted for this site restriction 4. Fault area restrictions To identify fault zones, used the USGS database, gQuarternary Fa ult and Fold Database for the United States,h which contains na tional scale location data on faults and associated folds. 57 This analysis identified plants including their buffers which fall w ithin 200 feet of fault lines that have exhibited movement in the Holocene era. The USGS dataset includes fault lines th at are believed to have been a source of earthquakes greater than magnitude 6 during the Quarternary (the pa st 1,600,000 years) and it defines gHol oceneh as the past 15 thousand ye ars. 58, 59

x 1-mile buffer: 1 plant falls within 200 feet of a fault line.

x 3-mile buffer: 3 plants fall within 200 feet of a faul t line. (these three plants are located in NV and UT). It is important to note that this prelimin ary analysis has certain limitations and ma y not capture faciliti es in other areas of seismic risk. According to the USGS fault line database, no relevant faults are located in the central and eastern US. The USGS states in it s database description that this abse nce of identified faults with movement in the centr al and eastern US is partly a real phenomena, beca use the western US has more tectonic activity, but that it is partly a detecti on problem caused by geological ch aracteristics present in the ce ntral and eastern US, such as glacial sediments, that con ceal evidence of movement along faults. For this reason, the analysis of seismic zones below, which are defined based on the likelihood of future seismic activity, may represent a more reliable esti mate of the number of facilit ies potentially affected by fault area restrictions. 60

57 US Geological Survey, 2006, gQuarternary Fault and Fold Data base for the United Statesh at: http//earthquakes.usgs.gov/region al/qfaults. File used: fitarc.shp
58 RCRA defines gHoloceneh as gthe most recent epoch of the Quartern ary period, extending from the end of the Pleistocene to the p resenth (40 CFR 264.18(a)(2)(iii)).

59 Faults designated by the dataset as showing movement during the Holocene are not necessarily believed to have produced an earth quake of magnitude 6 or greater during the Holocene. Rather, they are believed to have produced an earthquake of magnitude 6 or greater during the Quarternary, but t heir most recent suspected movement of any degree was during the Holocene.

60 The USGS data layer used for this analysis indicates that fau lts with Holocene movement are locat ed only in states in the West and Southwest regions of the US. This appears generally consistent with a separate analysis in the RCRA Practice Manual (Garrett, Theodore L., 2004, published by American Bar Association), and the small number of plants affected is not unexpected given the relatively small number of plants in these regions. However, the RCRA Practice Manual also notes that virtually all plants in CA and NV, and in parts of AK, AZ, CO, HI, ID, MT, NM, UT, WA, WY would be located within 200 feet of relevant faults . This suggests an upper bound of 54 plants (out of the 491 plants analyzed), if all facilities in th e identified states may be affect ed by fault area restrictions.72 5. Seismic zone restrictions: To identify seismic zones, USGS National Se ismic Hazard Maps provide peak horizonta l acceleration at different probabilities of exceedance in 50 years. 61 Identified those facilities, including th eir buffers, which overlap with the seismic impact zones that have a 10% or greater probability of exceeding a maximum horiz ontal acceleration of 10% the force of gravity (i.e., 0.10 g) in 250 years. 62 The USGS data gives probabilities of exceedance over 50 years; thus used a data layer presenting 2% probabili ty of exceedance, and assumed that thi s equates to a 10% probability of exce edance in 250 years.

x 1-mile buffer: 151 plants fall within seismic zones

x 3-mile buffer: 152 plants fall within seismic zones 6. Karst zone restrictions: This analysis used two database s: (1) DOE-EIA_s eGRID database to identify the geographic coordinates of 491 of the 495 plants analyzed (disregarding four plants that were not pr esent in the eGRID database), and (2) the USGS's GIS database "Engineering Aspects of Karst," which provides national-scale data on karst coverage. 63 Four types of karst areas ar e identified in the da taset: (a) long karst features (fissures, tubes, and caves over 1000 feet long and 250 f eet deep); (b) short karst (fissures, tubes, and caves less than 1000 feet long a nd 50 feet deep), (c) areas where karst features are generall y absent but present in small isolated ar eas, and (d) pseudo-karst areas, which have features analogous to karst.

x 1-mile buffer: 138 plants fall within karst zones

x 3-mile buffer: 177 plants fall within karst zones These counts do not distinguish between the four different types of karst terrain identified in th e data set; this analysis rep resents an initial upper bound of potentially affected facilities.

x Potential Cost for Existing & New Electric Plants to Meet Disposal Unit Location Restrictions According to the above findings for the thr ee location criteria evaluated in this RIA (i.e., fault ar eas, seismic zones, karst zones), a maximum count of 177 plants could be a ffected (this is the upper-end of the affected plant counts acr oss the three lo cation evaluations ). The potential cost to these plants of the lo cation restrictions is estimated in this RIA using the cost to retro-fit existing CCR disposal un its and to protect new CCR disposal units with a berm (aka lev ee). A berm is a type of engineering meas ure which may serve to demonstrate that en gineering measures have been incorporated into disposal unit design to mitigate the potential adverse impacts disposal units may have on, or be caused by, these six location considerations. The cost to construct a berm is based on the cost to construct a 10-foot tall flood berm using US Army Corps of Engineers_ publ ication gFlood Proofing v How to Evaluate Your Options ,” (July 1993), which provides unit costs in 1993 dollars to cons truct clay core flood control levees that are two, four, and six-feet high. This RIA inflat ed these unit costs to 2009 dollars using the ENR Construction Co st Index, and conducted a regression analysis on the unit co sts (i.e., extrapolated the cost based on the implied cost curve of the smaller b erms) to estimate the cost to construct a 10-foot tall berm. The estimated cost per linear foot to construct a 10-foot tall berm is $375. It is assumed that this unit cost could apply to both existing and new un its, and that the berm would be constructe d physically separate from the disposal u nit, not integral as gfreeboardh to th e disposal unit_s structure.

61 U.S. Geological Survey, 2008, gNational Seismic Hazard Maps,h from USGS website: http://gldims. cr.usgs.gov/nshmp2008/viewer.ht m. Data file used: pga2pct_p.shp.

62 This threshold for seismic impact zones is consistent with RCRA _s municipal solid waste landfill location restrictions (40 CFR 258.14(a)(b)(1)).

63 U.S. Geological Survey, 1984, gEngineering aspects of karst,h from USGS website: h ttp://pubs.usgs.gov/of/2004 /1352. File used: karst.shp.73 o Impoundment berms: The average surface impoundment size for ex isting units in the cost m odel is 343 acres. Assuming a square impoundment and that the berm woul d be constructed on three sides of the im poundment the average berm length is 11,594 feet. Therefore, the cost to construct a be rm around an average-size impoundment is $4.3 million. 64

o Landfill berms: Similarly, the average landfill size for existing units in the cost model is 278 acres. Assuming a square lan dfill and that the berm would be constructed on three sides of the landfill (leaving one side open for truck access), the average ber m length is 10,447 feet, and the cost to construct a berm surrounding an average-size landfill is $3.9 million. Using the 3-mile buffer karst zone finding of 177 plants, the pote ntial cost for constructing berm s at those plants plus future plants is:

o Existing units: ($4.1 million average berm cost) x (177 disposal units) = $726 million total cost Amortized with a capital recovery fa ctor of 0.07246 (@7% discount rate & 50- years) = $53 million/year equivalent

o New units: Apply 0.73% average annual growth rate in future CCR generation (cited elsewh ere in this RIA) to estimate the count of future new or expanded disposal units over 50-year s, and assume 36% (i.e., 177/495) will need berms: (495 existing disposal units) x (1.0073% growth rate)^(50 years) = 712 exis ting plus new units over 50-years (712 units over 50-years) v (495 existing units) = 217 future new disposal units (217 future new units) x (36% needing berms) x ( $4.1 million average berm cost) = $318 million total cost Amortized with a capital recovery fa ctor of 0.07246 (@7% discount rate & 50- years) = $23 million/year equivalent Average annualized berm cost for existing + new units = $76 million/year equivalent

8. Regulatory closure cost Same cost estimation formula applied above in Chapter 3 for baseline cost estimation.

9. Regulatory post-closure monitoring cost Same cost estimation formula applied above in Chapter 3 for baseline cost estimation.

10. Storage design and operating standards for tanks, containers, and containment buildings Not estimated in this RIA due to lack of baseline information about the count and condition of th ese units at electric utility plants



### 4B.2 Ancillary Regulatory Requirement Costs

For estimating most of the gOther Ancillar y Costsh in this section, this RIA disti nguishes between RCRA Su btitle C and RCRA Sub title D requirements according to the respective basis of each regulatory option, as well as between costs to electric utility plants a nd costs to state government RCRA-authorized regulatory programs.

64 For purpose of comparison to the $4.3 million (per impoundme nt) and $3.9 million (per landfill) location restriction mitigatio n cost estimates above, in 2005 the TVA estimated an gassumedh cost of $500,000 for karst mitigation and $250,000 for floodplain mitigation for a potential new CCR di sposal site involving 1,300 linear feet for mitigation. Extrapolation of TVA_s $750,000 cost estimate to 11,594 feet (impoundment) yields $6.7 million (i.e., (11,594 feet / 1,300 feet) x ($750,000)), and to 10,447 feet (landfill) yields $6.0 million (i.e., 10,447 feet / 1,300 feet ) x ($750,000)). Source for TVA cost estimate: page 10 of g Kingston Fossil Plant Decision Matrix: Pond or Peninsula?h, 27 January 2005 Plant Managers Conferen ce, http://www.tva.gov/kingston/tdec/pdf/TVA-00007487.pdf74 11. Regulatory offsite disposal costs (hazmat trucki ng, RCRA manifests, RCRA TS DF permits for offsite) EPA assumed that Subtitle C options add ex tra cost to (a) truck hauling to offsite disposal, and (b) all offsite landfills must become RCRA Subtitle C permitted. This cost estimate doe s not include taxes/trans-state government fe es associated with off-site disposal.

11a & 11b. Added truck hauling cost (Subtitle C options) Assumptions:

x Affects the 12% (15 million tons per y ear) annual CCR generation currently trucked offsite to non-haz LFs (2005)

x 6 miles average one-way trucking distance to offsite LFs 65

x $0.19/ton/mile hazardous wast e truck operating cost

x 12 tons CCR per full truckload (source: Gambrills MD cas e study); (15 million tons/year) / (12 tons/load) = 1.25 million truckloads per year Cost Calculations:

x 11a. RCRA manifest cost: (1.25 million truckloads) x ($53 per manifest per load average cost from EPA 2007 ICR 801.15) = $66 million per year

x 11b. Trucking cost (distance + operating cost): (15 million tons/y ear) x (6 miles) x ($0.09/ton/mile added truck operating cost for hazardous waste loads) = $8.1 million per year

x Subtotal (11a manifest + 11b trucking): $74.1 million per year

11c. Added cost for RCRA Subtitle C permits for all offsite CCR landfills under Subtitle C Assumptions:

x Added operating cost to offsite CCR landfill s for meeting engineering co ntrol requirements under each of the regulatory options evaluated in this RIA are included in the gEngineering Control Costsh se ction above, so are not again calculated here to avoid double-counting. Only the paperwork burden cost for obtaining a RCRA permit is estimated here.

x Industry average cost per waste disposal permit: ($440 66 average RCRA Part A permit applic ation cost per-plant per-year) + ($68,960 67 average RCRA Part B application cost per-facility per-year) = $69,400 per Subtitle C permit per year ($69,400 per permit per year) x (3 years ICR annualization period) = $208,200 per permit (149 offsite CCR landfills) x ($208,200 per permit) = $31.02 million Amortized industry cost with a cap ital recovery factor of 0.07246 (@7% disc ount rate & 50-years) = $2.25 million/year

65 Source: based on actual distance reported for a MD plant at h ttp://www.rachel.org/en/ node/445). Note: a broader range of 2.4 miles to 25 miles in one-way offsite landfill distance was reported by an OH plant at http://www.columbus dispatch.com/live/content/local_news /stories/2008/04/14/Powerfills.A RT_ART_04-14- 08_B1_FF9TI0U.html?sid=101, and a WI plant, respectively at http://www.lacrossetribune.com/ articles/2007/09/21/news/03landfill0 921.txt

66 $440 unitized cost derived for this RIA from EPA Information Collection Request (ICR) No. 0262.12 gRCRA Hazardous Waste Permit Application and Modification Part Ah, Federal Register , Vol.74, No.17, 28 Jan 2009, page 4958; h ttp://edocket.access.gpo.gov/ 2009/pdf/E9- 1804.pdf

67 $68,960 unitized cost derived for this RIA from EPA Informati on Collection Request (ICR) No. 1573.12 gPart B Permit Applicati onh, Federal Register , Vol.74, No.100, page 25237, 27 May 2009; http://edocket. access.gpo.gov/2009/pdf/E9-12285.pdf75 x State government average cost per waste disposal permit: Average cost for state government review of RCRA Subtitle C permits consists of four activities: 68 (1,215 pre-application activities ) + ($27,063 application review) + ($26,846 permit issuance) + ($3,110 permit maintenance) = $58,200 per permit (149 offsite CCR landfills) x ($58,200 per Subtitle C permit) = $8.67 million Amortized state cost with a capit al recovery factor of 0.07246 (@7% disc ount rate & 50-years) = $0.63 million/year

x Total Subtitle C permit cost (industry + state government) = $2.9 million per year

Total cost for item 11 (11a + 11b + 11c):

x Industry share of cost = $76.35 million per year

x State government share of cost = $0.63 million per year

x Total (industry + states) = $76.98 million per year

12. Regulatory structural integrity inspection cost

x Assumptions: EPA assumed that the residual 18 % of the non-inspected plants re quire inspection over the 82% baseline inspection coverage. The per-plant cost for inspect ions is estimated in the Chapter 3 baseline above.

x Cost Calculation: Industry cost: ($10,829/year per faci lity) x (18% not inspected) x ( 495 plants) = $0.96 million per year State government cost: ($599/year per facility) x (18% not inspected) x (495 plants) = $0.054 million per year Total (industry + state) = $1.01 million per year

13. Regulatory RCRA facility-wide investigation (RFI) cost

x Industry RFI cost:

x As of 2008, state government corrective acti on covers 64% of electric utility indus try impoundments and 78% of landfills. Thus

, assume that 57 plants with impoundments (i.e., 36% x 158 plants with impoundments) plus 74 plants with landfills (i.e., 22% x 3 37 plants with landfills) may require RFIs, for a total of 131 RFIs.

x The purpose of an RFI is to obtain information to fully characteri ze the nature, extent and rate of migration of releases of ha zardous waste or constituents to determine whether interim corrective measures and/or a Corr ective Measures Study may be necessary for other waste units at the facility (source: EP A 530/SW-89-031, May 1989, Vol.I). RFIs may in clude: rapid field screening using portab le field instruments, drilling in soils, excavating test pits, ground-wate r monitoring, waste testing, biomonitoring, and site surveying , site photography, site mapping.

x RFI average cost: $0.75 million average cost for RFIs i nvolving captive industrial landfills

68 Source: Based on cost data from page 84 of January 2007 ASTSWM O report gState RCRA Subtitle C Core Hazardous Waste Management Program Implementation Costs Final Reporth at: http://www.astswmo.org/files/publicati ons/hazardouswaste/Final%20Report%20-%20RCRA%20Subtitle%20C%20Cor e%20Project.pdf76 $0.69 million average cost for RFIs invol ving captive industrial waste management (assume applies to impoundments) Source: EPA OSRE memorandum gTransmittal of Average Cost of Investigation Derived from Fund-Lead Superfund Costs, Interim Measures Cost Compendium, and Compendium of Related Guidance Documentsh, 01 Nov 2004. This memo indicates that Superfund remedial investigation costs can be used as a proxy for RCRA RFI costs. Industry RFI cost calculations:

x Landfills: (74 landfills) x ($0.75 million aver age cost per RFI) = $55.5 million total cost

x Impoundments: (57 impoundments) x ($0.69 million av erage cost per RFI) = $39.3 million total cost Total = $94.8 million total cost to industry Amortized industry RFI cost with a capita l recovery factor of 0.07246 (@7% discount rate & 50-years) = $6.9 million/year equiva lent

x State government RFI cost: State government RFI review, approval, oversight average cost per RFI = $76,000 69 (131 RFIs) x ($76,000 review, approval, oversight average cost per RFI to state governments) = $10 million total cost Amortized state government RFI cost with a capital recovery factor of 0.07246 (@7% discount rate & 50-years) = $0.7 million/yea r equivalent

x RFI total cost (industry + state governments) = $7.6 million per year

14. Regulatory RCRA facility-wide corrective action cost Average annualized future potential cost was not estimated in this RIA because of a high degree of uncer tainty. Through a proc ess called corrective action, RCRA Subtitle C requires RCRA -regulated facilities to investigate and clean-up releases of hazardous wastes or constituents to the environment identified in the RCRA facility-wide investigation (R FI). After the RFI, if the need for cleanup is discove red, the RCRAregulated facility must perform a gCorre ctive Measures Studyh (CMS ) which may range in cost from $100,000 to $800,000 for such a study. 70 State government cost for co rrective measures study & corr ective action review, approval, oversight is $117,300 per case. 71 The purpose of a CMS is to develop and evaluate the correc tive action alternative(s) and to recommend the corrective measure(s) be taken at the facility. 72

As of 2008 the RCRA corrective action uni verse is about 3,800 sites nationwide. 73 Relative to the RCR A-regulated universe of 217,500 facilities (consisting of about 16,000 haza rdous waste LQG glarge quantity genera torsh plus about 200,000 hazardous was te SQG gsmall quantity generatorsh plus about 1,500 h azardous waste TSDF gtreatment, storage, disposal facilities h as of 2008), the 3, 800 corrective action universe implies a 1.75% relative incidence of occu rrence (i.e., 3,800 / 217,500 = 1.75%). Corrective action costs vary from facility-tofacility depending on the number and types of waste management units and other indust rial equipment/processes and wastes involv ed. The

69 Source: Divided the $2,200,600 annual RFI cost to 10 state governments by the 29 annual RFIs from page 82 of the January 2007 ASTSWMO report gState RCRA Subtitle C Core Hazardous Waste Management Program Implementation Costs Final Reporth at: http://www.astswmo.org/f iles/publications/hazardouswaste/F inal%20Report%20-%20RCRA%20Sub title%20C%20Core%20Project.pdf

70 Source: RACER unit cost reported on p.38 of EPA_s 2000 gUnit Cost Compendiumh , document ID nr. EPA-HQ-RCRA-2002-0031-0429 at : http://www.regulations.gov

71 Source: derived from cost data contained on page 83 of the ASTSWMO gState RCRA Subtitle C Core Hazardous Waste Management Pro gram Implementation Costs Final Reporth, January 2007 at: http://www.astswmo.org/files/ publications/hazardous waste/Final%20Report%20-%20RCRA%20Subtitle%2 0C%20Core%20Project.pdf

72 Source: gCorrective Measures Study Sc ope of Workh, EPA Region 3 at: http://w ww.epa.gov/reg3wcmd/ca/pdf/CMSATTC.pdf

73 Source: 3,800 corrective action cases repr esents EPA_s g2020 Corrective Action Univer seh as identified on EPA Hazardous Waste Corrective Action Facility Information website at: http://www.epa.gov/waste/hazard /correctiveaction/f acility/index.htm#202077 corrective action remedies usually involve mitigating damages to surface water and groundwater. The General Accountability Off ice (GAO) reported 74 that RCRA corrective action could cost 3 ,698 non-Federal hazardous waste treatment, stor age, or disposal facilities a total of about $16 billion (1996$) to clean up their propert ies contaminated by hazardous substances, representing an average $4.327 million c orrective action cost per-facility. Updated 75 to 2009$ implies an average of $5.365 million RCRA corrective action cost per facility.

15. Regulatory RCRA TSDF waste disposal permit cost for onsite disposal RCRA Subtitle C hazardous waste regulations require hazardous wast e treatment, storage, disposal facilities (TSDFs) to obtain R CRA permits as described in 40 CFR 270 consisting of a tw o-part (i.e., Part A and Part B) applicat ion process. The paperwork burden cost o f this requirement is estimated below. Furthermore, but not included in the cost estimate below, are separate, additional RCRA regula tions containing gtechnical requirementsh used by permit issuing authorities (e.g., RCRA- authorized state government waste programs o r EPA Regional offices) to determine what technica l requirements must be placed in permits. The separate cost of technical requireme nts is estimated in the gEngineering Controlsh regulato ry cost section of this RIA above.

x Assumptions:

o Although 93% of CCR landfills have a state government non-hazar dous waste disposal permit and 12% of CCR impoundments have such state permits, assume CCR disposal units will need new RCRA disposal permits under Subtitle C options.

o 383 of the 495 total electric utility plants currently dispose onsite (i .e., 84 of the 495 plants solely dispose CCR offsite, p lus 28 plants solely supply CCR for beneficial uses).

x Industry average cost per waste disposal permit:

o ($440 76 average RCRA Part A permit applic ation cost per-plant per-year) + ($68,960 77 average RCRA Part B application cost per-facility per-year) = $69,400 per Subtitle C permit per year ($69,400 per permit per year) x (3 years ICR annualization period) = $208,200 per permit (383 plants) x ($208,200 per permit) = $79.74 million Amortized industry cost with a cap ital recovery factor of 0.07246 (@7% disc ount rate & 50-years) = $5.8 million/year

x State government average cost per waste disposal permit:

o Build estimate based on the following four RCRA Subtitle C pe rmit-related state government ac tivities associated with RCRA Subtitle C waste disposal permits: 78 (1,215 pre-application activities ) + ($27,063 application review) + ($26,846 permit issuance) + ($3,110 permit maintenance) = $58,200 average cost per Subtitle C waste disposal permit per year.

74 Source: page 1 of US General Accountability Office (GAO), gHazardous Waste: Progress Under the Corrective Action Program is Li mited, But New Initiatives May Accelerate Cleanups,h report nr. GAO /RCED-98-3, October 1997 ; http://www.g ao.gov/archive/1998/rc98003.pdf

75 Updated from 1996$ to 2009$ using the NASA gGross Domestic Pr oduct Deflator Inflation Calculatorh at http://cost.jsc.nasa.gov/ inflateGDP.html

76 $440 unitized cost derived for this RIA from EPA Information Collection Request (ICR) No. 0262.12 gRCRA Hazardous Waste Permit Application and Modification Part Ah, Federal Register , Vol.74, No.17, 28 Jan 2009, page 4958; h ttp://edocket.access.gpo.gov/ 2009/pdf/E9- 1804.pdf

77 $68,960 unitized cost derived for this RIA from EPA Informati on Collection Request (ICR) No. 1573.12 gPart B Permit Applicati onh, Federal Register , Vol.74, No.100, page 25237, 27 May 2009; http://edocket. access.gpo.gov/2009/pdf/E9-12285.pdf

78 Source: Based on cost data from page 84 of January 2007 ASTSWM O report gState RCRA Subtitle C Core Hazardous Waste Management Program Implementation Costs Final Reporth at: http://www.astswmo.org/files/publicati ons/hazardouswaste/Final%20Report%20-%20RCRA%20Subtitle%20C%20Cor e%20Project.pdf78 o State Cost Calculation: (383 electricity plants dispose CCR onsite) x ($58,200 per Subtitle C permit per year) = $22.3 million per year

x Total Subtitle C permit cost (industry + state government) = $28.1 million per year

16. Regulatory RCRA enforcement inspection cost

x Assumptions:

o State government average cost = $7,900 per Subtitle C inspec tion (source: hazardous waste LQG large quantity generator average calculated by dividing the $1,517,357 annual enforcement inspection cost to 10 surveyed state governments by 192 annual enforcement cases, from page 87 of the January 2007 AS TSWMO report gState RCRA Sub title C Core Hazardous Waste Management Program Implementation Costs Final Reporth

o 1.6% average annual enforcement inspection frequency based on dividing the 11,965 LQG glarge quantity generatorh universe reported by 10 survey states by the 192 hazardous waste LQG enforcement cases reported in the January 2007 ASTSWMO report gState RCRA Subtitle C Core Hazardous Waste Management Program Implementation Costs Final Reporth

x Cost calculation: ($7,900 per LQG enforcement) x (495 electric utility plants ) x (1.6% LQG enforcements annually) = $0.063 million per year

17. Regulatory future remediation added cost Potential $18.5 million to $376 million per case in added cleanup cost for future surface impoundment failures, if regulated un der RCRA Subtitle C rather than Subtitle D, is base d on the two example case studies summarized in Exhibit 4A below.79 Exhibit 4A Two Case Studies: Possible Added Cost Under RCRA Subtitle C Regulation of CCR Cleanup at Electricity Plants from CCR Impoundment Failures (Note: Assumptions or numerical factors unique to each case study are applied in the cost calculations below rather than the national average assumptions and numerical factors applied elsewhere in this RIA)

Case Study #1: TVA Kingston TN (2008) Case Study #2: Constellation Energy Gambrills MD (2008) If cleanup as non-hazardous waste: Baseline Assumptions:

x 3.32 million tons released

x $0.10/ton/mile truck operating cost (source: OSW-EMRAD)

x 45 miles to Subtitle D LF (source: OSW-EMRAD)

x $35/ton tipping fee (source: 2005 Chartwell)

x 154,000 truckloads (source: TVA assumes 21.6 tons ash per load) Baseline Cost Calculations:

x Trucking cost: (3.32 million tons) x (45 miles) x ($0.10/ton /mile) = $15 million

x LF tipping fee: ($35/ton) x (3.32 million tons) = $116 million

x Manifest: $0

x Case #1 total = $131 million for event If cleanup as non-hazardous waste: Baseline Assumptions:

x 0.25 million tons released

x $0.10/ton/mile truck operating cost (source: OSW-EMRAD)

x 193 miles to Subtitle D LF (Constellation Energy_s mileage estimate to existing VA fly ash LF)

x $35/ton tipping fee (source: 2005 Chartwell)

x 20,833 truckloads (source: Constellation Energy assumes 12 tons ash per load) Baseline Cost Calculations:

x Trucking cost: (0.25 million tons released) x (193 miles) x ($0.10/ton /mile) = $5 million

x LF tipping fee: ($35/ton) x (0.25 million.tons) = $9 million

x Manifest: $0 Case #2 total = $14 million for event If cleanup as RCRA Subtitle C hazardous waste Assumptions:

x 3.32 million tons released

x $0.19/ton/mile truck operating cost (source: TVA)

x 370 miles to Subtitle C LF (source: TVA)

x $80/ton Subtitle C tipping fee (source: TVA)

x 154,000 truckloads (source: TVA assumes 21.6 tons ash per load) Cost Calculations:

x Trucking cost: (3.32 million tons) x (370 miles) x ($0.19/ton/mile truck operating cost) = $233 million

x LF tipping fee: ($80/ton) x (3.32 million tons) = $266 million

x Manifest: (154,000 truckloads) x ($53 manifest cost per load) = $8 million

x Case #1 total = $507 million for event If cleanup as RCRA Subtitle C hazardous waste Assumptions:

x 0.25 million tons released

x $0.19/ton/mile truck operating cost (from TVA)

x 179 miles to Subtitle C LF (closest is Envirosafe OH with 0.9 million tons permitted capacity)

x $90/ton tipping fee (2004 ETC national median fee)

x 20,833 truckloads (source: Constellation Energy assumes 12 tons ash per load) Cost Calculations:

x Trucking cost: (0.25 million tons) x (179 miles) x ($0.19/ton/mile truck operating cost) = $8.5 million

x LF tipping fee: ($90/ton) x (0.25 million tons) = $23 million

x Manifest: (20,833 truckloads) x ($53 manifest cost per load) = $1 million

x Case #2 total = $32.5 million for event
Case #1 incremental cost over non-hazardous: $376 million for cleanup event Case #2 incremental cost over non-hazardous: $18.5 million for cleanup event80 18. EPA administrative repor ting and recordkeeping costs Three of the regulatory costs itemized above -- item 11 offsite disposal truck manife sting and offsite disposal hazardous waste permits, item 12 structural integrity inspections, and item 13 RCRA facility-wide investigation (RFI) v include the cost of paperwork burden for those items. In addition, certain features of the Subtitle C options of the proposed rule require four other paperwor k burden activities:

18a. Notice of Regulated Waste Activity & EPA ID Number RCRA Subtitle C regulations for hazardous waste ggeneratorsh require generators to notify their fa cilities as such and obtain E PA identification numbers (40 CFR 262.12). According to EPA_ s most recent (2009) estimate, the averag e per-facility response burden is $162 per facility. 79 Applied to the 495 electric util ity plants yields an estimated one-time notif ication cost of $80,190 (i.e., (495 electric utili ty plants) x ($162 per notification)). Amortized with a capital recovery factor of 0.07246 (@7% discoun t rate & 50-years) = $5,800 per year average a nnual equivalent.

o Industry share of cost: ( 86%) x ($5,800/year) = $5,000/year

o State government share of cost: (14%) x ($5,800/year) = $800/year

18b. General Facility Standards for Hazardous Waste TSDFs This cost item represents a set of paperwork burden activities grouped und er 40 CFR 264/265 Subpart B (i.e., 264.10 to 264.19 a nd 265.10 to 265.19) and includes (1) maintaining records fo r hazardous waste that is stored, treated, and/or disposed onsite, (2) descripti ons of location, design, construction, operating methods, techniqu es, and practices for onsite hazardous wa ste storage, treatment, and/or dispos al, (3) contingency plans for unanticipated damage s from hazardous waste onsite storage, treatment and/or disposal, (4) maintaining qua lifications of facility ownership, (5) maintaining contin uity and financial responsib ility of facility operation, a nd (6) employee hazardous w aste training. According to EPA_s most recent (2009) estimate the averag e per-facility paperwork burden is $27,350 per facility per year. 80 Applied to the 383 electric utility plants which currently dispose onsite (i.e., 84 of the 495 plants solely dispose CCR offsite with other co mpanies, plus 28 plants solely provide CCR for beneficial us es) yields an estimated cost of ($27,350 per facility pre year) x (383 plants which dispose CCR) = $10.48 million/year:

o Industry share of cost: (86%) x ($ 10.48 million/year) = $9.01 million/year

o State government share of cost: (14%) x ($10.48 million/year) = $1.47 million/year

18c. RCRA Hazardous Wast e Biennial Report RCRA Subtitle C requires hazardous waste LQG large quantity genera tors (40 CFR 262.41) and hazardous waste TSDF treatment, stor age, and disposal facilities (40 CFR 264.75 and 265.75) to submit gHazardous Waste Reporth informa tion on a 2-year repeating cycle (aka gRCRA

79 $162 per year notification cost derived from EPA Information Collection Request (ICR) No. 0261.16 gNotification of Regulated W aste Activity (Renewal)h, Federal Register , Vol.74, No.123, pages 310 28-31029, 29 June 2009; http://edock et.access.gpo.gov/2009 /pdf/E9-15310.pdf

80 $27,350 per facility per year average cost derived from EPA In formation Collection Request (ICR) No. 1571.09 gGeneral Hazardou s Waste Facility Standardsh, Federal Register , Vol.74, No.23, pages 6152-6154, 05 Feb 2009.81 Biennial Reporth). According to EPA_s mo st recent (2009) estimate, the average annu alized per-facility response burden is $3,4 10 per year. 81 Extrapolated to 495 electric utility plants pr oduces a cost estimate of $1.69 million per year.

o Industry share of cost: (86%) x ( $1.69 million/year) = $1.45 million/year

o State government share of cost: (14%) x ($1.69 million/year) = $0.24 million/year

18d. CERCLA Reportable Quantity (RQ) Spill/Leak Reporting Section 103(a) of CERCLA require s facilities and vessels to immediately notify th e National Response Center (NRC) of a hazardou s substance release (e.g., spill, leak) into the environm ent if the amount of the rel ease equals or exceeds the substance_s reportable quan tity (RQ) limit. In general there are five RQ categories (1, 10, 100, 1,000 or 5,000 pounds ). Subtitle C options may add CCR to the CERCLA list of hazardous substances and assign an RQ of one-pound, as well as allowing the us e of concentrations to determine RQ thus resulting in a ran ge of 1,294 pounds to 10,000,000 pounds for 12 chemicals. Using the total count of facilities (i.e., establishmen ts) in the US manufacturi ng sector (NAICS 31, 32, 33) plus the US waste management se ctor (NAICS 562) as rough indicators, th ere are 315,000 industrial facilities in the US which may handle RQ-listed hazardous substances. 82 According to EPA_s most recent (2007) estimate , the average per-facility response burden is $122 (i.e., 4.1 burden hours) per facility per response, based on an average annual 25,861 facilities at an annual paperwork burden cost of $3.161 million. 83 Relative to this 300,000 industrial facility universe, this annual count of RQ-reporti ng facilities represents an 8% fraction

. Extrapolated to the 495 electric utility plants yields a rough estimate of 40 possible RQ reports per year, at a cost of $4,900 per year (i.e., (495 electric utility plants) x (8% RQ repor ts per year) x ($122 per RQ report)).

o Industry share of cost: ( 86%) x ($4,900/year) = $4,200/year

o State government share of cost: (14%) x ($4,900/year) = $700/year

Sub-total cost item 17 (17a + 17b + 17c + 17d) = $12.94 million per year.

o Industry share of cost: (86%) x ($ 12.94 million/year) = $11.13 million/year

o State government share of cost: (14%) x ($12.94 million/year) = $1.81 million/year

Exhibit 4B below presents a summary of these gAncillary Costh elements numbered from 11 to 18.

81 $3,410 per facility per year average cost derived from EPA In formation Collection Request (ICR) No. 0976.14 g2009 Hazardous Wa ste Reporth, Federal Register

, Vol.74, No.93, pages 22922-22924, 15 May 2009; http://edocket.access.gpo.gov/2009/pdf/E9-11410.pdf

82 315,000 industrial facilities based on gNum ber of Establishmentsh published for NAICS codes 31-33 Manufacturing (293,919 estab lishments) plus NAICS code 562 Waste management and remediation services (21,254 establishments) from the US Census Bureau in its g2007 Economic Census.h No t all manufacturing or waste management facilities necessarily handle haza rdous substances so this is an over-estim ate, but there are also other economic se ctors (e.g., mining, construction, utilities, transporters, and wholesalers), which handle hazardous substances not included in this facility count which offsets this over-e stimate.

83 $122 per facility average cost derived from EPA Information Collection Request (ICR) No. 1049.11 gNotification of Episodic Rel eases of Oil and Hazardous Substances (Renewal); Federal Register , Vol.72, No.205, 24 Oc t 2007, pp.60357-60358; http://edocket.access.gpo.go v/2007/pdf/E7-20934.pdf82 Exhibit 4B Summary of “Ancillary Cost” Es timates Associated with RCRA Regulation of CCR Disposal ($millions average annualized; 2009$)

Ancillary Cost Element Applicability to CCR Regulatory Options Electric Utility Industry Cost State Government RCRA-Authorized Program Cost Row Total Cost 11. Ancillary offsite disposal costs Subtitle C $76.35 $0.63 $76.98 12. Impoundment structural integrity inspections Subtitle C and Subtitle D $0.96 $0.054 $1.01 13. RCRA facility-wide investigations (RFIs) Subtitle C $6.9 $0.7 $7.6 14. RCRA facility-wide corrective action Subtitle C Not estimated v historical average cost = $5.4 million per facility Not estimated Not est.

15. RCRA TSDF waste disposal permits Subtitle C $5.8 $22.3 $28.1 16. RCRA enforcement inspections Subtitle C $0 $0.063 $0.063 17. Future disposal unit failure cleanup remediation as RCRA hazardous waste Subtitle C Not est. v case study example Not est. v case study example Not est.

18. EPA administrative reporting & recordkeeping 18a. EPA regulated waste notification 18b. RCRA TSDF general facility standards 18c. RCRA haz waste biennial report 18d. CERCLA RQ reporting Subtitle C Subtotal= $11.13 $0.005

$9.01 $1.45 $0.0042 Subtotal= $1.81 $0.0008 $1.47 $0.24 $0.0007 $12.94 $0.0058

$10.48

$1.69 $0.0049 Column Totals for the three options of the October 2009 draft RIA : Subtitle C hazardous waste $100.4 $25.6 $126.7 Subtitle D (version 1) $0.96 $0.05 $1.0 Hybrid C&D* $7.9 $7.7 $15.6 * Hybrid C&D costs for ancillary cost items 13, 14, 15, 16, 17, 18 are proportioned only to the 158 plants with impoundments th at would be regulated under Subtitle C for this option, by the proportionate multiplie r: (158 plants w/impoundmen ts) / (495 total plants) = 0.31983 

### 4B.3 Land Disposal Restriction Cost (for dewatering treatment of CCR)

This element consists of two components:

x Dry CCR disposal (landfills) : Moisture conditioning and compaction to 95% maxi mum dry density value according to ASTM D 698 or ASTM D 1557 test methods prio r to disposal in landfills.

x Wet CCR disposal (impoundments) : Dewatering to remove solids prior to disposal in impoundments within 5- years of rule_s effective date. The potential cost for this treatment standard is estimated below.

However, only the potential cost for the wet CCR disposal dewateri ng treatment standard is estimate d in this section of the RIA because the potential cost for meeting the dry CCR mois ture conditioning and compaction requirement s are already estimated in item 4 of the gengineering controlsh in this chapter above:

x Examples of CCR Dewatering Methods

Based on the following recent (1997- 2009) example descriptions of dry CCR disposal practices at existing or planned coal-fired electric utility plants, dry CCR disposal may involve di fferent methods for any given plant:
1. Tanks & chain drag: As described in March 2009 by th e Basin Electric Power Cooperative. 84 Bottom ash will be dewatered in tanks and the water will be re-circulated to transport additional bottom ash. Bottom ash will be removed using a chain drag. The as h will then be hauled by truck to a lined landfill offsite. The fly ash will be conveyed in a dry state. Both ashes will be disposed in a landfill close to the plant site.
2. Pressure squeeze conveyor : Another tank-based example apparently similar to the Basin Cooperative method is reported for dry disposal conversion by the coal mining industry, involving the Phoe nix Process Equipment company supplier of alte rnative slurry processing equipment. This second exampl e involves a thickening tank, porous conveyor belt and pressure to squeeze water out o f the coal washings, producing a semi-solid, 75% dewatered cake which is scraped off the c onveyor belt and stacked like a pile of san d. The cost for this process is reported at $0.50 per ton of coal waste processed. 85

3. Horizontal belt filters : According to a May 2009 technical paper 86 , dewatering gypsum using horizontal belt filters is common in the electric utility industry, and a new modi fied horizontal belt filter method involving two feedboxes allows fly ash and FGD (gyp sum) to be dewatered simultaneously.
4. Storage silos & rail system : As described June 2009 87 for a $10 million conversion project located at Detroit Edison_s Monroe Michigan Power Plant -- a four boiler uni t, 3,200-megawatt power statio n originally constructed in 1974. Installation of equip ment to collect the coal ash in a dry state, plus dry ash storage facilities (storage silos) , and truck/rail loading equipment for dist ribution of the dry ash to concrete producers in the Mi dwest United States and Eastern Canada.

84 Source: March 2009 Basin Electric Power Co operative examples at http://www.basinel ectric.com/News_Center/Feature_Articles/Coal _ash_handling.html

85 Source: Dave Cooper, gBetter, Safer Ways to Handle Coal Slurry Do Existh, page 14 of the Nov 2001 gEh-Notes Newsletter of the Ohio Valley Environmental Coalition at http://www.ohvec.org/newsletters/e notes_97-01_pdf/enotes_2001_11.pdf

86 Source: May 2009 horizontal belt filter technical paper by Alex Hohne at http://www.flyash.info/2009/036-hohne2009.pdf

87 Source: June 2009 Detroit Edison Monroe Power Plant example at http://www.headwaters.com/data/upimages/press/6.30.09MonroeAshR elease.pdf84 5. Integrated silo system : Integrated with precipitators, vacuum pumps and bag filter/receivers, as described in an engineering report 88 about the 1997 dry fly ash system convers ion of Northern Indiana Public Serv ice Company_s Michigan City Plant.

For this RIA, EPA ORCR identified four alternative existing studies with cost estimates (dated 1981, 1985, 2005, and 2009) comp aring dry and wet CCR disposal at coal-fired electric utility plants. The fi rst three studies provided cost estimates on a per-plant basis, whereas the 2009 study provided an extrapolated nationwide cost estimate. However, only the 2005 study is used in this RIA as a basis for deriv ing a cost estimate for the wet CCR dewatering land disposal treatment, b ecause the first two studies ar e over 25-years old (1981 and 1985 ), and the 2009 study does not provide sufficient details for verification of data and calculations. These thre e other studies are summarized below in this chapter to illustrate the magnit ude of cost estimation uncertainty implied by th e other studies, compared to the estimate deriv ed below in this section of the RIA.

x Summary of 2005 TVA CCR Dry Disposal Cost Study

x In August 2009 TVA announced a proposed plan to convert its wet CCR disposal to dry dis posal. TVA_s CEO Tom Kilgore said befor e a 28 July 2009 US Congressional subcommittee hearing that TVA ha s developed a 5-year plan to shift CCR disposal from wet impoundments to dry landfills. TVA estimated it will cost between $1.5 billion to $2 billion over 8 to 10 years for its 11 coa l-fired electric utility plants. 89 Detailed or semi-detailed calculations of TVA_s 2009 cost estimate are not availabl e for this RIA to use for extrapolation nationwide.

x However, a 2005 TVA cost estimate titled gKingston Fossil Plant De cision Matrix: Pond or Peninsul a?h provides detailed cost est imates for dry conversion of the TVA Kingston TN plant. 90 The TVA cost study involves conversion of an existing impoundment currently used to dispose wet fly ash and wet bottom ash at the TVA Kingston TN el ectric utility plant, for future dry fly ash and dry bottom ash disposal. The FGD stream remains wet-sluiced before and after this hypothetical co nversion in the cost study. In addition to the cost of converting the electric plant boile rs and the impoundment for dry ash disposal, the cost study also incl udes the cost for construction of a new storm water runoff management pond (Source: ro w item 68 of TVA_s gAppendix C Detaile d Cost Sheetsh, slide nr. TVA-00007403).

x TVA cost study involves conversion of 475,600 cubi c yards of fly ash plus bottom ash per year; this RIA estimates this quantity is equivalent to 880,000 tons per year, assumi ng 1.85 tons per cubic yard multiplier. 91

88 Source: Dec 1997 NIPSC conversion report at http://www.babcockpower.com/pdf/rst-145.pdf

89 Source: TVA news release gTVA Coal Combustion Products Remedi ation Plan Proposedh, 20 Aug 2009 http://www.tva.gov/news/release s/julsep09/ccprp_other.htm

90 Source: TVA 27 January 2005 plant managers conference slide pres entation (25 pages).. Wet disposal is presented as gOption 1h and dry disposal is presented as gOption 2h in the TVA cost presentation. Additional details for the TVA cost estimates are available at http://www.tva.gov/kingston/td ec/pdf/TVA-00007402.pdf

91 "Source: 1.85 tons per cubic yard multiplier represents the midpoi nt from the following 1.2 to 2. 5 range: According to EPA_s 1988 Report to Congress (gWastes from the Combustion of Coal by Electric Utility Power Plants,h page 3-14), the dry density of fly ash is 80-90 lbs/cubic ft which trans lates to a specific density of 1.4. The Federal Highway Administration studied fly ash for use in highway construction and reported its specific gravity may be as low as 1.7 t o as high as 3.0. Conversion of this implied 1.4 to 3.0 range in fly ash specific gr avities to tons-per-cubic-yard as follows:

o Low-end: (1.4 g/cm3) / (0.000001 m3/cm3) x (0.764 m3/yd3) / (1000 g/kg) x (2.204 lbs/kg) / (2000 lbs/short ton) = 1.2 short ton s per cubic yard.

o High-end: (3.0 g/cm3) / (0.000001 m3/cm3) x (0.764 m3/yd3) / (1000 g/kg) x (2.204 lbs/kg) / (2000 lbs/short ton) = 2.5 short to ns per cubic yard.85 x The TVA cost study did not estimate the cost for dewatering FGD (gypsum) because FGD is already dewatered by most electric util ity plants for beneficial uses, thus only four of the 495 electric utility plants (i.e., TVA Widows Creek plant, TVA Paradise plant , Louisville Gas & Electric Co Trimble County plant, a nd Northern Indiana Public Service Company R.M. Schafer plant) wet dispose 1.9 million tons FGD per year in impoundments as of 2005 (source: column B of Exhibit 3G of this RIA).

x Unit cost (i.e., average cost per ton) of conversion from wet to dry disposal es timated from the 2005 TVA cost analysis which p rovides cost estimates for converting from wet as h disposal to dry ash disposal:

TVA wet disposal TVA dry disposal Added cost for dry Unitized dry cost

o Capital cost $13.12 million PV $38.45 million PV Cost not incremental $43.7/ton per year (@20 years)

o Annual O&M cost $10.63 million PV $17.51 milli on PV $6.88 million PV $0.60/ton (@13 years) (Note: PV = present value for TVA_s 25-year period of analysis 2005-2029; TVA costs are in 2005$ prices)

x Cost estimate calculation under c onversion to dry disposal scenar io, calculated based on TVA_s per-ton cost extrapolation to 22 .4 million tons per year baseline wet CCR (i.e., wet fly ash, wet bottom as h, wet FGD, wet gypsum, wet other CCR) disposal in impoundments at 158 of the 495 electric utility plants:

o Capital cost : (22.4 million tons per year wet CCR disposal for conversio n at 158 plants) x ($43.7/ton per year conversion capital cost) x (20 years capitalization pe riod) x (1.174 price update multiplier 92 to 2009$ price level) = $22,984 million undiscounted capital cost Annual equivalent capital: ($22,984 million) x (0.07246 capital recovery factor @7 % & 50-years) = $1,665 million per year

o O&M cost : ($0.60/ton conversion O&M cost) x (22.4 million tons/year wet CCR disposal for convers ion at 158 plants) x (45 years future operational period 2017-2061 wh ich assumed to begin 5 years after 2012 final rule promulgation) x (1.174 price update multiplier to 2009$ price level) = $710 million undiscounted total O&M PV present value discounted @7% over 50-years = $153 million PV present value O&M Annual equivalent O&M: ($153 million) x (0.07246 capital re covery factor @7% & 50-years) = $11 million per year

o Total annualized cost (capital + O&M) = ($1,665 millio n/year capital) + ($11 million/y ear O&M) = $1,676 million/year

x Uncertainty in Land Disposal Treatment Cost Estimate

In addition to the 2005 Tennessee Valley Authority (TVA) cost study referenced above, there are th ree other related cost studie s (1981, 1985, and 2009) which are summarized below. The first two studies pr ovide cost estimates on a per-plant basis for a few plant sizes, and the 2009 study provides a nationwide cost estimate. This RIA did not a pply these other studies because the first two are over 25-years old (i.e., 1981 and 1985) and the third study does not provide su fficient details for verification of data and calculations. Th ese studies are sum marized below and used as a basis for formulating alternative nationwide cost estimates for land disposal treatment, for the purpose of illustrat ing the potential magnitude of uncertainty in this RIA_s cost estimate in relation to these other studies.

92 1.174 price update multiplier represents 2009:to:2005 ratio in the Engineering-News Record Construction Cost Index: (8566 CCI for July 2009) / (7297 CCI for 2005).86 x Study #1 of 3: 1981 TVA/EPA

x In January 1981, TVA_s Energy Demonstra tions and Technology Office (Chattanooga TN) co-authore d with EPA_s Industrial Environmental Research Laboratory (Research Triangle Park NC) a study titled gEconomic Analysis of Wet Versus Dry Ash Disposal Systems,h Interagency Energy/Environment R&D Program Repor t, report no. TVA/OP/EDT-81/ 30 and EPA-600-7-81-013, 126 pages. 93

x The study compares the relative cost s of wet and dry methods of coal ash disposal for five electric pl ant power size categories (300 MW, 600 MW, 900 MW, 1,300 MW, 2,600 MW) with annual co al ash generation ranging from 0.2 milli on to 1.7 million per year per plant.

x Per-plant capital and O&M costs estimated based on 35-year assumed plant lifespan in 1980$. Capital costs for (a) in-plant coa l ash handling systems, (b) conveyance/transport, and dispos al units, were obtained from equipment suppliers.

x The study found (page 67) there is not a sign ificant difference in ash system economics based on the method of analysis. Prese nt worth analysis g indicates that wet disposal is typically the least cost alternat ive. However, various dry disposal options are within a 15 per cent range of those costs. The costs are, in fact, sensitive to spre ading the dry disposal area cap ital costs over the life of the power station and the in-plant handling system cost. Use of either the lower dilute phase transport system cost or the dense phase collection sy stem cost results in the dry disposal system alternativ e become the least cost alternative .h

x The study also noted that staged construction may provide 30% sa ving in system total cost: g [T]he above analyses assumed construction of all the required facilities upon star t-up. In the case of dry disposal, this is a reasonable assumption although site preparat ion costs would proceed during the development of the site. In the case of we t disposal, it may be economically sound to construct the embankm ent in stages, even if the amount of material to be placed or the engineerin g estimate is higher for staged cons truction. This is due to the high cost of the dam or levee and the cost of mon ey over the life of the project. As an example... wet disposal ar ea was analyzed for all constru ction occurring in 1980 and by a staged construction se quence (3 stages). In this case, staged construction provided a 30 percent sa vings in the total cost of the system. h

x The 1981 study used two cost methods. The gPresent Worthh (aka present value PV) cost method findings (page 62) indicated the following comparative ranges in wet dry versus wet disposal costs:

Disposal method 1980$ cost ($/ton) 2009$ update ($/ton) 94 Dry disposal $2.19 to $4.50 $4.81 to $9.87 Wet disposal $1.86 to $5.68 $4.08 to $12.46

93 Source: 1981 TVA/EPA report at http://nepis.epa.gov/Exe/ZyNET.exe/20006ORT.TXT?ZyActionD=ZyDocumen t&Client=EPA&Index=1981+Thru+1985&Docs=&Query=tva+wet+dry+di sposal&Time= &EndTime=&SearchMethod=3&TocRestrict=n&Toc=&TocEntry=&QField=pu bnumber%5E%22600781013%22&QFieldYear=&QFieldMonth=&QFieldDay=&Us eQFie ld=pubnumber&IntQFieldOp=1&ExtQFieldOp=1&XmlQuery=&File=D%3A%5Czyfiles%5CIndex%20Data%5C81thru85%5CTxt%5C00000000%5C20006ORT.tx t&Us er=ANONYMOUS&Password=anonymous&SortMethod=h%7C- &MaximumDocuments=10&FuzzyDegree=0&ImageQuality=r75g8/r75g8/x150 y150g16/i425&Display=p%7Cf&DefSe ekPage=x&SearchBack=ZyActionL&B ack=ZyAct ionS&BackDesc=Results%20page&MaximumPages=1&ZyEntry=1&SeekPage=x

94 1980$ costs from the 1981 TVA/EPA study updated by EPA ORCR to 2009$ using the GDP calculator at http://cost.jsc.nasa.gov/infl ateGDP.html87 x Using the EPA ORCR 2009$ updated unit cost mi dpoints displayed above yields the following rough cost estimate for the 158 elect ric utility plants with CCR impoundments:

o Capital cost : (22.4 million tons per year wet CCR disposal for convers ion at 158 plants) x ($4.81 to $9.87 per ton dry disposal unitized present value cost) x (40.6% capital cost fraction) x (50 years period-of-analysis for this RIA) = $2,187 million to $4,488 million present value capital cost Annualized capital cost: ($2,187 million to $4,488 million) x (0.07246 capital recovery factor @7% & 50-years) = $158.5 million to $325.2 million per year

o O&M cost 95 : (22.4 million tons per year wet CCR disposal for conversio n at 158 plants) x [(($4.81 to $9.87 per ton dry disposal unitized present value cost) x (59.4% dry O&M fraction)) v (($4.08 to $12.46 per ton wet disposal unitized present value cost) x (31.6% wet O&M fraction))] x (45 years dry disposal operational period 2017-2061 whic h assumed to begin 5 years after 2012 final rule promulgation) = $1,580.5 million to $1,941.4 million present value O&M Annualized O&M cost: ($1,580.5 million to $1,941.4 million) x (0.07246 capital recovery factor @7% & 50-years) = $114.5 million to $140.7 million per year

o Total annualized cost (capital + O&M) = ($158.5 milli on to $325.2 million per year capit al) + ($114.5 million to $140.7 million per year O&M) = $273 million to $466 million per year

x Study #2 of 3: 1985 EPA

x EPA_s Air and Energy Engineering Research Laboratory (Research Triangle Park NC) pub lished cost estimates for both wet and dry CCR disposal at coal-fired electric utility plants in the report gF ull-Scale Field Evaluation of Wast e Disposal from Coal-Fired Ele ctric Generating Plantsh, document nr. EPA/ 600/S7-85/028, August 1985, 12 pages. 96

x This is a 3-year study of waste characterization, environmental da ta, engineering, and cost evalua tions associated with disposa l of coal ash and FGD waste by six coal-fired electricity plants ranging in nameplate capacity between 310 to 1,786 megawatts and located in FL, IL, MN, NC, PA, and WY. EPA used this study to assist preparation of EPA_s 1988 gReport to Congress on Wa stes from the Combustion of C oal by Electric Utility Power Plantsh (report no. EPA530-SW-88-002, Feb 1988).

x This study developed ggenerich capital and annual O&M costs for both wet CCR pond disposal and dry CCR landfill disposal method s involving fly ash, bottom ash, and FGD, based on specific costs for the six sites combined with co st estimates from other studi es by TVA,

95 O&M cost extrapolation calculation in this RIA for the 1981 study applies two different O&M cost percentages based on the stud y_s 59.4% dry disposal O&M cost percentage derived from page B-10, and on the study_s 31.6% wet disposal O&M cost percentage derived from page C-11.

96 Source: 1985 EPA AEERL report at http://nepis.epa.gov/Exe/ZyNET.exe/2000TNFC.TXT?ZyActionD=ZyDocum ent&Client=EPA&Index=1981+Thru+1 985&Docs=&Query=&Time=&EndTime =&SearchM ethod=1&TocRestrict=n&Toc=&TocEntry=&QField=pubnumber%5E%22600S785028%22&QFieldYear=&QFieldMonth=&QFieldDay=&UseQField=pubnumbe r&IntQ FieldOp=1&ExtQFieldOp=1&XmlQuery=&File=D%3A%5Czyfiles%5CIndex% 20Data%5C81thru85%5CTxt%5C00000010%5C2000TNFC.txt&User=ANONYMOUS& Password=anonymous&SortMethod=h%7C- &MaximumDocuments=10&FuzzyDegree=0&ImageQuality=r75g8/r75g8/x150 y150g16/i425&Display=p%7Cf&DefSe ekPage=x&SearchBack=ZyActionL&B ack=ZyAct ionS&BackDesc=Results%20page&MaximumPages=1&ZyEntry=1&SeekPage=x88 EPRI, and other organizations. Exhibit 4C below displays the unitized capital costs and Exhibit 4D below displays the unitized O&M costs from the study updated for this RIA to 2009 price level.

x Using the 2009-updated mean unit capital a nd O&M cost estimates displayed in Exhibit 4C and Exhibit 4D , provides the following cost estimates for conversion to dry disposal, based on extrapolati on to 22.4 million tons per year baseline wet CCR (i.e., wet fly ash, wet bottom ash, wet FGD, wet gypsum, wet other CCR) disposal in impoundments at 158 of the 495 electric utility plants which have a subtot al of 180,901 MW nameplate total capacity:

o Capital cost: (180,901,000 kilowatt capacity for 158 electric utility plan ts with surface impoundment s) x ($37.60 dry conversion capital cost per kilowatt capacity from Exhibit 4C ) = $6,810 million capital cost Annual equivalent cost: ($6,810 million) x (0.07246 capital recovery factor @7% & 50-years) = $494 million/year

o O&M cost : (22.4 million tons per year wet CCR dis posed in impoundments) x (-$17.40 cost savings per ton to manage for dry disposal from Exhibit 4D ) = -$389 million per year O&M cost savings.

o Total average annualized cost (capital + O&M) = ($494 million/year capital co st) v ($389 million/year O&M cost savings) = $105 million per year dry conversion cost.

Exhibit 4C Comparison of Unitized Capital Costs for Wet and Dry CCR Disposal (Source: 1985 EPA Study; $/kW) Plant Size Categories (MW = megawatts)
250 500 1000 2000 Row Summary Across Four Size Categories
Item Disposal Operation Wet or Dry CCR Min Max Min Max Min Max Min Max Min Max Midpnt Mean 1A Fly ash handling/processing Wet $2.3 $6.8 $1.9 $5.5 $1.5 $6.4 $1.3 $3.6 $1.3 $6.8 $4.1 $3.7 1B Dry $2.2 $4.1 $1.8 $3.3 $1.4 $2.7 $1.2 $2.2 $1.2 $4.1 $2.7 $2.4 2 Fly ash storage Dry $4.7 $8.8 $4.2 $7.7 $3.7 $6.8 $3.2 $5.9 $3.2 $8.8 $6.0 $5.6 3A Fly ash transport Wet $3.5 $6.4 $2.7 $5.1 $2.2 $4.0 $1.7 $3.2 $1.7 $6.4 $4.1 $3.6 3B Dry $0.3 $0.5 $0.3 $0.6 $0.3 $0.5 $0.2 $0.5 $0.2 $0.6 $0.4 $0.4 4A Fly ash placement/disposal Wet $15. 1 $27.8 $12.9 $23.9 $11.0 $2 0.5 $9.4 $17. 5 $9.4 $27.8 $18.6 $17.3 4B Dry $4.3 $8.1 $3.3 $6.1 $2.5 $4.7 $1.9 $3.6 $1.9 $8.1 $5.0 $4.3
5 Bottom ash handling/processing Wet/Dry $2.2 $4.6 $1.7 $3.7 $1.3 $3.0 $1.0 $2.4 $1.0 $4.6 $2.8 $2.5

6A Bottom ash transport Wet $3.0 $5.6 $2.4 $4.5 $1.9 $3.6 $1.5 $2.8 $1.5 $5.6 $3.6 $3.2 6B Dry $0.2 $0.4 $0.2 $0.3 $0.1 $0.2 $0.1 $0.2 $0.1 $0.4 $0.3 $0.2
7A Bottom ash placement/disposal Wet $6.4 $11.8 $5.1 $9.6 $4.2 $7.7 $3.4 $6.2 $3.4 $11.8 $7.6 $6.8

7B Dry $1.3 $2.4 $1.1 $2.0 $0.9 $1.6 $0.7 $1.3 $0.7 $2.4 $1.6 $1.4 Summary: Wet Subtotal (1A+3A+4A+5+6A+7A) Wet (1982$) $32.5 $63.0 $26.7 $52.3 $22.1 $45.2 $18.3 $35.7 $18.3 $63.0 $40.7 $37.0 Dry Subtotal (1B+2+3B+4B+6B) Dry (1982$) $15.2 $28.9 $12.6 $23.7 $10.2 $19.5 $8.3 $16.1 $8.3 $29.0 $18.7 $16.8 2009 Updated Wet Subtotal* Wet (2009$) $72.8 $141.1 $59.8 $117.1 $49.5 $101.2 $41.0 $79.9 $41.0 $141.1 $91.0 $82.8 2009 Updated Dry Subtotal* Dry (2009$) $34.0 $64.7 $28.2 $53.1 $22.8 $43.7 $18.6 $36.0 $18.6 $64.9 $41.8 $37.6 * Note: 2009 price update multiplier (source: ENR Constructi on Cost Index ratio 2009:to:1982 = 8564/3825) = 2.23989 Exhibit 4D Comparison of Annual O&M Costs for Wet and Dry CCR Disposal (Source: 1985 EPA Study; $/dry metric ton) Plant Size Categories (MW = megawatts)
250 500 1000 2000 Row Summary Across Four Size Categories
Item Disposal Operation Wet or Dry CCR Min Max Min Max Min Max Min Max Min Max Midpnt Mean Fly Ash:

1A Fly ash handling/processing Wet $2.5 $6.8 $1.0 $5.4 $1.6 $4.3 $1.3 $3.6 $1.0 $6.8 $3.9 $3.3 1B Dry $2.5 $4.7 $2.1 $3.9 $1.7 $3.2 $1.5 $2.7 $1.5 $4.7 $3.1 $2.8 2 Fly ash storage Dry $3.3 $6.1 $3.0 $5.6 $2.8 $5.2 $2.5 $4.7 $2.5 $6.1 $4.3 $4.2 3A Fly ash transport Wet $4.2 $7.6 $3.2 $5.9 $2.5 $4.7 $2.0 $3.7 $2.0 $7.6 $4.8 $4.2 3B Dry $1.7 $3.1 $1.5 $2.8 $1.3 $2.5 $1.2 $2.2 $1.2 $3.1 $2.2 $2.0 4A Fly ash placement/disposal Wet $11. 5 $21.3 $9.1 $16. 8 $7.2 $13.5 $5.7 $10.5 $5.7 $2 1.3 $13. 5 $12.0 4B Dry $7.0 $13.0 $5.6 $10.5 $4.6 $8.5 $3.7 $6.9 $3.7 $13.0 $8.4 $7.5

Subtotal fly ash Wet (1982$) $18.2 $35.7 $13.3 $28.1 $11.3 $22.5 $9.0 $17.8 $8.7 $35.7 $22.2 $19.5 Dry (1982$) $11.2 $20.8 $9.2 $17.2 $7.6 $14.2 $6.4 $11.8 $6.4 $20.8 $13.6 $12.3
Bottom Ash: 5 Bottom ash handling/processing Wet/Dry $11.3 $22.8 $9.0 $19.1 $6.9 $15.7 $5.3 $12.8 $5.3 $22.8 $14.1 $12.9

6A Bottom ash transport Wet $9.2 $17.1 $7.3 $13.5 $5.6 $10.3 $4.3 $7.9 $4.3 $17.1 $10.7 $9.4 6B Dry $3.4 $6.3 $2.8 $5.2 $2.2 $4.1 $1.8 $3.3 $1.8 $6.3 $4.1 $3.6
7A Bottom ash placement/disposal Wet $9.2 $17.1 $7.9 $14.6 $6.5 $12.1 $5.4 $10.0 $5.4 $17.1 $11.3 $10.4

7B Dry $5.4 $10.0 $4.7 $8.8 $4.1 $7.6 $3.5 $6.5 $3.5 $10.0 $6.8 $6.3 Subtotal bottom ash Wet (1982$) $29.7 $57.0 $24.2 $47.2 $19.0 $38.1 $15.0 $30.7 $15.0 $57.0 $36.0 $32.6 Dry (1982$) $20.1 $39.1 $16.5 $33.1 $13.2 $27.4 $10.6 $22.6 $10.6 $39.1 $24.9 $22.8 Summary (Fly Ash & Bottom Ash): Weighted average* Wet (1982$) $20.7 $40.4 $15.7 $32.3 $13.0 $25.9 $10.3 $20.6 $10.1 $40.4 $25.2 $22.4 Dry (1982$) $13.2 $24.8 $10.8 $20.7 $8.8 $17.1 $7.3 $14.2 $7.3 $24.8 $16.1 $14.6 2009 updated weighted average** Wet (2009$) $46.4 $90.4 $35.2 $72.3 $29.1 $58.1 $23.1 $46.2 $22.6 $90.4 $56.5 $50.1 Dry (2009$) $29.5 $55.6 $24.2 $46.4 $19.8 $38.3 $16.4 $31.8 $16.4 $55.6 $36.0 $32.7
Incremental cost from conv ersion to dry disposal = -$17.4
Notes: * Fly:to:ash weighted average based on 2005 relative annual tonnages evaluated in the RIA: Fly ash tons/year = 15,200,000; Bott om ash tons/year = 4,300,000 ** 2009 price update multiplier (source: ENR Constructi on Cost Index ratio 2009:to:1982 = 8564/3825) = 2.23990 x Study #3 of 3: 2009 USWAG

x On 11 June 2009 the Utility Solid Waste Action Group (Jim Roewer , Executive Director) provided to EPA a 14-page cost study USWA G sponsored by the EOP Group Inc., containing an estimate of $39,000 m illion present value (PV) for conversion to dry disposal: g Cost Estimates for Closure of Ash Ponds at Fossil Fuel Power Generati on Facilitiesh, prepared in 2009 by EOP Group Inc. USWAG/EOP_s $39,000 million PV estimate uses a 3% disc ount rate over 20 years w ith a 10-year implementati on period, and consists of:

o $12,900 million PV (33%) for fly ash and bottom ash conversion to dry disposal

o $2,500 million PV (6%) for foregone sunk cost in ponds

o $23,700 million PV (61%) for construction of new wastewater plants for other non-ash ancillary wastewater s (e.g., stormwater) which are currently co-mingled with the wet ash.

x For purpose of comparing this estimate with the other two cost studies above, the following rough calculations extend the O&M c osts from the 20-year period from the USWAG/EOP study, to the 50-year period a pplied in this RIA:

o Dry management O&M cost = ($2.00 per ton higher cost than wet manageme nt) x (20.6 million tons per year in impoundments) x (40-years after 10-year impound ment phase-out) = $1,648 million (undiscounted). PV discounted @7% over 50-years = $279 million PV present value

o Waste water treatment plant (WWTP) O&M cost = ($525 million per year) x (40-years after 10-year impoundment phase-out) = $21,000 million (undiscounted). PV discounted @7% over 50-years = $3,558 million PV present value

x Substituting these 50-year based PV O&M cost estimates for th e 20-year based PV O&M cost estimates into the USWAG/EOP $39,000 million 20-year PV total cost estimate produces the following 50-year based average annualized cost:

o Capital cost :($39,000 million PV total cost) v ($400 million 20-year PV dry management O&M) v ($5,200 million 20-year PV WWTP O&M) = $33,400 million PV capital cost Annual equivalent capital cost: ($33,400 million PV) x (0.07246 capital recovery fact or @7% & 50-years) = $2,420 million per year annualized capital cost

o O&M cost : ($279 million 50-year PV dry management O&M) + ($3,558 million 50-year PV WWTP O&M) = $3,837 million PV present value O&M Annualized O&M cost: ($3,837 milli on PV) x (0.07246 capital recovery factor @7 % & 50-years) = $278 million per year O&M

o Total annualized cost (capital + O&M) = $2,698 million per year

Exhibit 4E below presents a summary of the extrapolated cost estimates based on the per-plant cost findings from these three alternative cost studies, compared to the cost estimate based on the 2005 TVA cost study applied in this RIA.91 Exhibit 4E Summary of Wet Conversion Cost Estimates Based on Four Alternative Studies 1981, 1985, 2005, 2009 ($millions updated to 2009$)
A B C D E (A to D)

Type of Dry Conversion Cost Element Cost Study #1 EPA 1981 Cost Study #2 EPA 1985 Selected for Basis of the Estimate Applied in this
RIA Cost Study #3

TVA 2005 Cost Study #4 USWAG/EOP 2009 Implied Range 1. Capital cost: 1a. Present value (PV) = $2,187 to $4,488 $6,810 $22,984 $33,400 $2,187 to $33,400 1b. Annualized equivalent* = $158 to $325 $494 $1,665 $2,420 $158 to $2,420 2. Average annual O&M cost $115 to $141 -$389 savings $11 $278 -$389 savings to $278 3. Total annualized cost (1b+2) $273 to $466 $105 $1,676 (PV** = $23,137) $2,698 $105 to $2,698

Row 3 implied uncertainty range compared to estimate based on 2005 TVA study = -94% to +61%
Notes: * Annualized over a 50-year period @7% discount rate. ** Present value computed by multiplying the annualized value by a 13.801 present value multiplier, which represents 7% discoun t over 50-years.

x Update of Cost Estimate for Conv erting from Wet to Dry CCR Disposal

o Purpose of Dry Conversion Cost Estimate Update

The purpose of this section is to update th e initial estimate above in this RIA, of the cost of converting CCR disposal impound ments to dry disposal (i.e., landfills). The initial $23.137 billion estimate (present value discounted at 7% over 50-years) presented in above in this section of the RIA is based on the 2005 universe of 158 coal-fired electric utility plants (classified in NAICS code 22) with active CC R impoundments addressed in EPA_s October 2009 dr aft RIA for the proposed rule. Exhibit 4F below provides a summary of this initial cost estimate. 97 As of February 2010, the 2005 universe is the latest available data from the U.S. Department of Energy_s Energy Information Administr ation (EIA) Form 767 database, because the EIA temporarily suspended its elec tric utility industry data colle ction survey questionnaire to revise it.

97 EPA_s 2009 draft RIA cost estimate was based on an extrapola tion of a cost estimate developed in 2005 by the Tennessee Valley Authority (TVA) for converting its Kingston TN coal-fired electric plant to dr y disposal of fly ash and bottom ash. In the RIA, EPA (a) unitized TVA_s cost estim ate on a cost-per-ton basis for both the capital cost and annual O&M cost components, and then (b) extrapolated the unit costs to the 2005 national universe of 22.4 mil lion tons wet disposed CCR associated with the 158 electric utility plants with active CCR impoundments as of 2005. Exhibit 4F below displays how the draft RIA timed th e capital and O&M cost s over the 50-year period of analysis applied in the RIA (2012 to 2061), and the result of discounting the 50-year cost stream at a 7% annual rate

.92 Exhibit 4F

PR O P O SE D R U L E OC T 200 9 R IA "O P T IO N 1" (R C R A S u b tile C 30 04x ) Al l Im p o u n d m e n ts M u s t C o n v e rt to D ry A s h S y s te m in 5 -Y e a rs

C a p it a l co st fo r c o n ve rs io n to d r y (n o n -d is c o u n t e d lu m p -s u m ) = $ 2 2 ,9 8 4 , 0 0 0 ,0 0 0 A d d e d a n n u a l O & M f o r d r y co m p a re d to w e t (n o n -d i sc o u n te d ) = $ 1 5 , 8 0 0 , 0 0 0
A B 5- Year pha se -out C o u n t o f e x is ti n g 0 8 O c t 2 0 0 9 d ra ft R I A

e le c t ric u tilit y s im p le e s t im a t e if p la n t s w it h lu m p -s u m c a p i ta l c o s t R o w Y e a r im p o u n d m e n t s i n 1 st ye a r o f f in a l ru le

1 201 2 1 5 8 $ 2 2 , 9 8 4 ,0 0 0 , 0 0 0 2 201 3 158 $0 3 201 4 158 $0 4 201 5 158 $0 5 201 6 158 $0 6 2 0 1 7 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 7 2 0 1 8 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 8 2 0 1 9 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 9 2 0 2 0 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 1 0 2 0 2 1 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 1 1 2 0 2 2 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 1 2 2 0 2 3 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 1 3 2 0 2 4 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 1 4 2 0 2 5 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 1 5 2 0 2 6 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 1 6 2 0 2 7 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 1 7 2 0 2 8 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 1 8 2 0 2 9 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 1 9 2 0 3 0 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 2 0 2 0 3 1 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 2 1 2 0 3 2 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 2 2 2 0 3 3 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 2 3 2 0 3 4 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 2 4 2 0 3 5 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 2 5 2 0 3 6 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 2 6 2 0 3 7 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 2 7 2 0 3 8 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 2 8 2 0 3 9 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 2 9 2 0 4 0 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 3 0 2 0 4 1 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 3 1 2 0 4 2 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 3 2 2 0 4 3 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 3 3 2 0 4 4 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 3 4 2 0 4 5 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 3 5 2 0 4 6 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 3 6 2 0 4 7 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 3 7 2 0 4 8 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 3 8 2 0 4 9 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 3 9 2 0 5 0 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 4 0 2 0 5 1 1 5 8 $ 2 2 , 9 8 4 ,0 0 0 , 0 0 0 4 1 2 0 5 2 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 4 2 2 0 5 3 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 4 3 2 0 5 4 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 4 4 2 0 5 5 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 4 5 2 0 5 6 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 4 6 2 0 5 7 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 4 7 2 0 5 8 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 4 8 2 0 5 9 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 4 9 2 0 6 0 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 5 0 2 0 6 1 1 5 8 $ 1 5 ,8 0 0 , 0 0 0 N o n -d is c o u n t e d t o ta l c o s t = $ 4 6 , 6 6 3 ,0 0 0 , 0 0 0 N o n -d is co u n t e d a v e ra g e c o s t = $ 9 3 3 ,0 0 0 , 0 0 0 P re s e n t va lu e c o s t (@ 7 % d is c .r a te ) = $ 2 3 , 1 6 7 ,0 0 0 , 0 0 0 A v e r a g e a n n u a liz e d c o s t (@ 7 % d is c .r a te ) = $ 1 ,6 7 9 , 0 0 0 , 0 0 0
Dis c o u n t ra t e = 7 %

A n n u a l e n g in e e ri n g + a n c illa r y co st s f o r R I A " O p t io n 1 " S u b t itle C = $ 5 9 5 ,0 0 0 , 0 0 0 T o t a l a n n u a lize d c o s t f o r R I A " O p t io n 1 " S u b t itle C = $ 2 ,2 7 4 ,0 0 0 ,0 0 0 P re se n t v a lu e c o s t (@ 7 % d is c . ra t e ) = $ 3 1 , 3 8 3 ,0 0 0 , 0 0 0 PR O P O SE D R U L E OC T 200 9 R IA "O P T IO N 1" (R C R A S u b tile C 30 04x ) Al l Im p o u n d m e n ts M u st C o n vert to D ry A sh S ys te m in 5 -Y e a rs

C a p it a l co st fo r c o n ve rs io n to d r y (n o n -d is c o u n t e d lu m p -s u m ) = $ 2 2 ,9 8 4 , 0 0 0 ,0 0 0 A d d e d a n n u a l O & M f o r d r y co m p a re d to w e t (n o n -d i sc o u n te d ) = $ 1 5 , 8 0 0 , 0 0 0
A B 5- Year pha se -out Co u n t o f e x is ti n g 0 8 O c t 2 0 0 9 d ra ft RI A

e le c tric u tilit y s im p le e s tim a t e if p la n t s w ith lu m p -s u m c a p i ta l c o s t R o w Y e a r im p o u n d m e n t s i n 1 st ye a r o f f in a l ru le

1 201 2 1 5 8 $ 2 2 , 9 8 4 ,0 0 0 ,0 0 0 2 201 3 158 $0 3 201 4 158 $0 4 201 5 158 $0 5 201 6 158 $0 6 2 0 1 7 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 7 2 0 1 8 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 8 2 0 1 9 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 9 2 0 2 0 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 1 0 2 0 2 1 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 1 1 2 0 2 2 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 1 2 2 0 2 3 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 1 3 2 0 2 4 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 1 4 2 0 2 5 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 1 5 2 0 2 6 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 1 6 2 0 2 7 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 1 7 2 0 2 8 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 1 8 2 0 2 9 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 1 9 2 0 3 0 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 2 0 2 0 3 1 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 2 1 2 0 3 2 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 2 2 2 0 3 3 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 2 3 2 0 3 4 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 2 4 2 0 3 5 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 2 5 2 0 3 6 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 2 6 2 0 3 7 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 2 7 2 0 3 8 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 2 8 2 0 3 9 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 2 9 2 0 4 0 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 3 0 2 0 4 1 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 3 1 2 0 4 2 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 3 2 2 0 4 3 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 3 3 2 0 4 4 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 3 4 2 0 4 5 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 3 5 2 0 4 6 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 3 6 2 0 4 7 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 3 7 2 0 4 8 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 3 8 2 0 4 9 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 3 9 2 0 5 0 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 4 0 2 0 5 1 1 5 8 $ 2 2 , 9 8 4 ,0 0 0 ,0 0 0 4 1 2 0 5 2 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 4 2 2 0 5 3 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 4 3 2 0 5 4 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 4 4 2 0 5 5 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 4 5 2 0 5 6 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 4 6 2 0 5 7 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 4 7 2 0 5 8 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 4 8 2 0 5 9 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 4 9 2 0 6 0 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 5 0 2 0 6 1 1 5 8 $ 1 5 ,8 0 0 ,0 0 0 N o n -d is c o u n t e d t o ta l c o s t = $ 4 6 , 6 6 3 ,0 0 0 ,0 0 0 N o n -d is co u n t e d a v e ra g e c o s t = $ 9 3 3 ,0 0 0 ,0 0 0 P re s e n t va lu e c o s t (@ 7 % d is c .r a te ) = $ 2 3 ,1 6 7 ,0 0 0 , 0 0 0 A v e r a g e a n n u a liz e d c o s t (@ 7 % d is c .r a te ) = $ 1 ,6 7 9 ,0 0 0 , 0 0 0
Dis c o u n t ra t e = 7 %

A n n u a l e n g in e e ri n g + a n c illa r y co sts fo r R I A " O p tio n 1 " S u b t itle C = $ 5 9 5 ,0 0 0 ,0 0 0 T o t a l a n n u a lize d c o s t fo r R I A " O p tio n 1 " S u b t itle C = $ 2 ,2 7 4 ,0 0 0 , 0 0 0 P re se n t v a lu e c o s t (@ 7 % d is c . ra t e ) = $ 3 1 ,3 8 3 ,0 0 0 , 0 0 093 o Recent Trend in CCR Impoundment Phase-Outs

Since formulating the initial cost estimat e above, EPA obtained new information which indicates that many el ectric utility plan ts have already closed or are planning to clos e CCR impoundments and convert to dry disposal (i .e., landfill disposal and/or sell and transport dry CCR offsite for beneficial use by other industries) for reasons independent of the CCR pr oposed rule. As displayed below in Exhibit 4G , EIA_s historical data 98 for the electric utility indus try indicate that between 1996 a nd 2005, the tonnage of CCR disposed in impoundments has decreas ed by 10% from 25.2 to 22.5 million tons despite to tal CCR generation at electric utility plan ts increasing 24% over that same period from 102.0 million tons (1996) to 126.3 million tons (2005). This represents an average annual CCR impoundment phase-out rate of 1.1% per year

.

1996 2005 10-year decrease Tonnage wet disposal 25.188 million 22.537 million 10% Percentage of generation 25% of CCR 18% of CCR 7%

Exhibit 4G Documentation of Recent Trend ( 1996-2005) In Switching From Wet to Dry CCR Disposal in the US Electric Utility Industry

Coal Ash, FGD Waste - EIA Data

Thousand Short Tons

Utility Landfill (Dry) Utility Disposal
Ponds (Wet) On Site
Use and Storage Sold Off Site Disposal Total % Utility Landfill (Dry) Utility Disposal
Ponds (Wet) On Site
Use and Storage Sold Off Site Disposal Total % Fly Ash 21,450 15,710 2,446 12,091 8,110 59,806 59% 22,557 15,322 4,645 21,211 10,626 74,360 59% Bottom Ash 5,340 4,973 1,968 4,322 2,537 19,140 19% 6,109 4,374 3,553 5,767 2,177 21,981 17% Sludge 12,938 3,484 1,011 236 987 18,655 18% 9,592 1,886 467 409 2,507 14,861 12% Gypsum 502 987 379 1,190 88 3,146 3% 55 872 372 8,513 783 10,595 8% Other 171 35 0 691 305 1,202 1% 227 83 116 3,749 315 4,490 4% Total 40,401 25,188 5,804 18,529 12,028 101,950 100% 38,539 22,537 9,153 39,650 16,407 126,286 100%

% Share of Total

Utility Landfill (Dry) Utility Disposal
Ponds (Wet) On Site
Use and Storage Sold Off Site Disposal Total Utility Landfill (Dry) Utility Disposal
Ponds (Wet) On Site
Use and Storage Sold Off Site Disposal Total Fly Ash 36% 26% 4% 20% 14% 100% 30% 21% 6% 29% 14% 100% Bottom Ash 28% 26% 10% 23% 13% 100% 28% 20% 16% 26% 10% 100% Sludge 69% 19% 5% 1% 5% 100% 65% 13% 3% 3% 17% 100% Gypsum 16% 31% 12% 38% 3% 100% 1% 8% 4% 80% 7% 100% Other 14% 3% 0% 57% 25% 100% 5% 2% 3% 84% 7% 100% Total 40% 25% 6% 18% 12% 100% 31% 18% 7% 31% 13% 100% 1996 2005

1996 2005

98 Source: US Department of Energy EIA F767_PLANT database at: http://www.eia.doe.gov/cneaf/electricity/page/eia767.html94 One important reason for this change is that dry systems allow plants more flexibility in the type of coal th ey use as fuel. F or example, as plants switched from bituminous to sub-b ituminous coal, they also converted to dry fly ash handling systems because the ash fro m some subbituminous coals has cementitious properties that can cause plugging and high maintenance costs for some wet ash disposal syste ms, thus necessitating dry ash systems. Also, some types of sub-bituminous coal fly ash are in economic demand by the cement industry b ecause of their low carbon content and need to be stored dry for transport. EIA_s historical da ta for coal-fired electric plant fly ash disposal confirms this same trend away from wet disposal to dry disposal (and to beneficial reuse). In 1996, 26% of fly ash was disposed of in ponds (aka gimpoundmentsh). This fly ash disp osal method dropped to 21% in 2005.

x Possible Factors Behind this CCR Dry Disposal Conversion Trend

In the next few years, there will be a number of factors that may affect the way coal-fired pl ants in the electric utility indu stry operate that may further encourage CCR dry disposal rather than wet dispos al. Five example factors are:

1. Federal regulations : EPA plans to issue a number of regulations that will affect electric utility pl ants under the Clean Air Act and the Clean Water Act. For example anticipated Clean Air Act regulations will likely le ad to increased use of SO2 controls on existing electric utility plants that will increase the tonnage of flue gas desulfurization (FGD) solids that must be processed (i.e., beneficially us ed or disposed) and is some cases add calciu m derivatives to the existing fly ash (through use of dry scrubbers). While the incremental costs of handling such additional materials are site specific, there are a number of factors that are likely to drive electric utility companies to give more considerat ion to dry CCR disposal. While wet disposal was common on earlier generations of wet scrubbers, in recent cases, some electric utility companies have focused much more strongly on options to reduce cost s by finding beneficial uses for CCR. Fu rthermore, given the magnitude of the upcoming projects and growing public intere st in how CCR are handled and dispos ed, expediting approval of the project may also drive towards consideration of dry disposal methods.
2. State regulations : A number of state governments are considering programs th at may affect their respective state-wide economic demand for electricity.
3. Technology : New technologies for generation, tran smission, and use of electricity are being introduced into the market.
4. Fuel cost : Spot markets for coal make it easy for plants to fuel switch or mix coal fuel types. This means, among other things that wet CCR disposal systems, because they limit the types of coal that these plants can use, are likely to be further reduced.
5. Plant property : As land availability constraints becomes more important to electric utility plants (e.g., some electric utility plants are located in riparian settings), on-site wet disposal areas become less impor tant in favor of smaller footprint on-sit e dry disposal landfills and se nding CCR off-site for dispos al or beneficial use.

As electric utility companies face this myriad of changes, they are likely to be rec onsidering at a very detailed level how the y are operating their plants. In fact, this is evident in the fact that some electric utility companies have already announced actua l or planned closures of a number of coal-fired electr ic generator units, while other companies have announced plans to switch some units or plants95 from coal to other fuels such as natural gas. This considera tion of the way electric utility plants will operate is likely to include a reconsideration of how the plants will handl e and disposal CCR. Furthermore, sin ce future air pollution regulations are likel y to cause more reassessment at electricity plants with older and less e fficient air emission particulate control devices and air pollutio n scrubbers, air regulations themselves are likely to pr ovide further inducement to reconsider CCR di sposal practices at plants that are cur rently using wet disposal. These actions in the near future also mean that the market and regulatory environment in which these plant s operate will continue to be in flux and the ability to operate in a way that will make them able to respond quickly to changes will be important.

Corroborating continuation of this histori cal phase-out trend are recen t (2009) announcements by five electric utility companie s (i.e., Tennessee Valley Authority (TVA), Duke Energy Company, Hoosier Energy REC Inc, Vectren Southern Indiana Gas & Electric Company, and Westa r Energy Company) 99 that they plan to convert all or a significant portion of their CCR impoundme nts to dry management within the next 10 years corroborates continuation of this recent impoundment phase- out trend. These 18 plants alon e comprise 17% of the annual 2 2.4 million tons CCR disposed annually in impoundments (as of 2005). In a ddition, three companies have announc ed planned coal-fired electr icity plant closures or planned switching from coal to other fuels. These three plants comprise 3% of the annual CCR impoundment disposal tonnage. See Exhibit 4H below for a list of these companies, their plant names, a nd associated CCR impoundment disposal annual tonnages. Future developments in the electric utility in dustry, including compliance with upcoming Cl ean Air Act and Clean Water Act regulations under development at EPA, will increase the dry disposal conversion tr end. It is inappropriate to a ssign the costs of these conversi ons to the CCR proposed rule, because they would happen anyway, in absence of the rule.

99 TVA_s 20 August 2009 news release gTVA Coal Combustion Products Remediation Plan Proposedh announced that TVA plans gto conver t all TVA wet ash and gypsum storage to dry{over eight to 10 years.h . Recent plans to convert from wet CCR impoun dment disposal to dry landfill disposal f or electric utility plants operated by the Duke Energy Company, the Hoosier Electric Cooperative, and Vectren Southe rn Indiana Gas & Electric Company were reported 24 Oct ober 2009 by Mark Wilson of the Courier Press gCoal Ash Disposal Varies From Company to Compan yh at http://btop.courierpress.com/news/2009/oct/24/coal-ash-disp osal-varies-from-company-tocompany/?print=1 Westar Energy apparently converted to dry fly ash management by December 2006 according to gCoal Plant O&M: Retrofit Flyash-Han dling System Pays Dividends,h Douglas J. Smith, Contributing Editor, Coal Power magazine, 01 Nov 2007: http://www.coalpowermag. com/transportation/Coal-Plant- O-and-M-Retrofit-Flyash-HandlingSystem-Pays-Dividends_79.html96 Exhibit 4H Lists of Coal-Fired Electric Utility Plants Wi th Active CCR Impoundments (as of 2005) Which are Either Voluntarily Planni ng to Convert to Dry Disposal or Voluntarily Planning to Close or Switch Away from Coal to Another Fuel Source (e.g., Natural Gas)

Plants With CCR Impoundments Soon Converting to Dry Disposal* Coal-Fired Electric Utility Plants Closing or Switching Away From Coal Fuel with CCR Impoundments**
A B C D E F G H Company Name Plant Name State 2005 CCR Pond Tons (1,000s)** * Company Name Plant Name State 2005 CCR Pond Tons (1,000s)***

1. PSI Energy Inc (Duke Energy) Cayuga IN 210.9 1. Progress Energy Cape Fear NC 101.3 2. PSI Energy Inc (Duke Energy) Edwardsport IN 11.5 2. Progress Energy Lee NC 106.1 3. PSI Energy Inc (Duke Energy) R Gallagher IN 125.6 3. Progress Energy L V Sutton NC 166.0 4. PSI Energy Inc (Duke Energy) Wabash River IN 192.1 4. Progress Energy W H Weatherspoon NC 47.0 5. PSI Energy Inc (Duke Energy) Gibson IN 897.8 5. Duke Energy Company Buck NC 121.9 6. Tennessee Valley Authority Colbert TN 29.2 6. Duke Energy Company Dan River NC 28.5 7. Tennessee Valley Authority Widows Creek TN 852.8 7. Northern States (Xcel Energy) High Bridge MN 0.01 8. Tennessee Valley Authority Paradise TN 517.9 8. Northern States (Xcel Energy) Riverside MN 6.7 9. Tennessee Valley Authority Shawnee TN 61.1 10. Tennessee Valley Authority Bull Run TN 22.4 11. Tennessee Valley Authority Gallatin TN 180.5 12. Tennessee Valley Authority John Sevier TN 10.0 13. Tennessee Valley Authority Johnsonville TN 53.7 14. Tennessee Valley Authority Kingston TN 325.9 15. Southern Indiana Gas & Electric Company (Vectren) F B Culley IN 35.6

16. Southern Indiana Gas & Electric Company (Vectren) A B Brown IN 165.8

17. Hoosier Energy R E C Inc Frank E Ratts IN 39.8 18. Westar Energy Jeffrey Energy Center KS 184.1

Subtotal impoundment tons for 18 plants listed above = 3,916.7 Subtotal for 8 plants listed above = 577.51 % of 22.4 million tons 2005 wet disposal tonnage by 158 plants = 17% % of 22.4 million tons 2005 wet disposal tonnage by 158 plants = 3%
Notes: * EPA-ORCR identified th e 18 plants with recent plans to convert from wet to dry CCR landf ill disposal for electric utility pla nts operated by the Duke Energy Company, the Vectren Company, and the Hoosier Electric Cooperative, from the 24 October 2009 news report by Mark Wilson of the Courier Press gCoal Ash Disposal Varies From Company to Company.h . The Westar Energy plant was identified by an EPA-ORCR staff person based on knowledge of tha t specific plant or company. ** EPA identified the 8 plants switching from coal from SourceWatch websites: http://www.sourcewatch.org/index.php?title=Coal_plant_conversion_projects and http://www.sourcewatch.org/index.php?title=Existing_U.S._Coal_Plants *** Source: Based on the 2005 DOE-EIA data.97 o Result of Dry Conversion Cost Update

The result of this dry conversion cost upda te is displayed below in comparison to th e initial conversion cost estimate. The ad justed cost incorporates the average annual 1.1% decrease in CCR impoundment disposal tonnage calcula ted based on the 1996-2005 EIA data trend as presented in Exhibit 4G above, relative to the 2005 base year impoundment disposal tonnage of 22.4 million tons over the same 50-year period (i.e., 2012 to 2061) applied in the RIA. This adjustment provide s a declining future CCR impoundment tonnage trend which would be impacted by the CCR proposed rule when it is implemented, rather th an simply assigning to the ru le a dry conversion cost for th e entire 2005 impoundment tonnage (i.e., 22.4 million tons) as was done in the initial cost estimate. The cost adjustment using this trend i nvolved two steps:

Step 1 : Assign a dry conversion cost to the ex trapolation phase-out trend (i.e., 2006 to 2061) representi ng what the electric utilit y industry could be expected to incur in the future in absence of the CCR rule. The results of this 1 st step are displayed in columns A1 to A4 of Exhibit 4I below.

Step 2 : Re-estimate the phase-out cost under this same industry trend but by adding th e requirement under the CCR rule that all remaining CCR impoundment tonnage that is not projected to be voluntarily phased-out w ithin 5-years of the final rule_s adoptio n must be phased-out. This step incorporates three assumptions: (a) EPA promulgates the final rule at the start of 2012, (b) state go vernments adopt the final rule 2-years later at en d of 2013, and (c) the final ru le allows a 5-year phase- out period which spans 2014 to 2018. The results of this 2 nd step are displayed in columns B1 to B4 of Exhibit 4I below.98 Exhibit 4I

Adjustment of Dry Conversion Cost Estimate to Account for Utility Industry's Voluntary Impoundment Phase-Out Trend

A 1 A 2 A 3 A 4 B1 B2 B3 B4 A. Cost of Dry Conversion Trend Without CCR Rule B. Dry Conversion Cost if Mandated by CCR Rule

Incremental added Incremental added cost year-by-year ---- Mandatory cost year-by-year ---- Projected Year-by-year regression trendline Regression trendline year-by-year mandatory Mandatory trendline RIA 50-year End Regression trendline incremental dry conversion dry conversion Mandatory wet incremental dry conversion dry con version

year period of of wet disposal phaseout conversion to dry cost projection cumulative cost phaseout within conversion to dry cost project ion cumulative cost count analysis year (million tons/year) (million tons/year) without CCR rule without CCR rule 5-years of rule (million tons/year) with C CR rule with CCR rule

1 2005 22.5 Base year Base year Base year 22.5 Base year Base year Base year 2 2006 22.2 0.3 $22,122,377 $22,122,377 22.2 0.3 $22,122,377 $22,122,377 3 2007 21.9 0.3 $22,122,377 $44,244,754 21.9 0.3 $22,122,377 $44,244,754 4 2008 21.7 0.3 $22,122,377 $66,367,131 21.7 0.3 $22,122,377 $66,367,131 5 2009 21.4 0.3 $22,122,377 $88,489,508 21.4 0.3 $22,122,377 $88,489,508 6 2010 21.1 0.3 $22,122,377 $110,611,885 21.1 0.3 $22,122,377 $110,611,885 7 2011 20.8 0.3 $22,122,377 $132,734,262 20.8 0.3 $22,122,377 $132,734,262
8 1 2012 20.5 0.3 $22,122,377 $154,856,640 20.5 0.3 $22,122,377 $154,856,640 9 2 2013 20.2 0.3 $22,122,377 $176,979,017 20.2 0.3 $22,122,377 $176,979,017 10 3 2014 19.9 0.3 $22,122,377 $199,101,394 19.9 4.0 $298,704,663 $475,683,680 11 4 2015 19.6 0.3 $22,122,377 $221,223,771 19.6 4.0 $298,704,663 $774,388,344 12 5 2016 19.3 0.3 $22,122,377 $243,346,148 19.3 4.0 $298,704,663 $1,073,093,007 13 6 2017 19.0 0.3 $22,122,377 $265,468,525 19.0 4.0 $298,704,663 $1,371,797,671 14 7 2018 18.7 0.3 $22,122,377 $287,590,902 18.7 4.0 $298,704,663 $1,670,502,334
15 8 2019 18.4 0.3 $22,122,377 $309,713,279 0 0 $0 $1,670,502,334 16 9 2020 18.1 0.3 $22,122,377 $331,835,656 0 0 $0 $1,670,502,334 17 10 2021 17.8 0.3 $22,122,377 $353,958,033 0 0 $0 $1,670,502,334 18 11 2022 17.5 0.3 $22,122,377 $376,080,410 0 0 $0 $1,670,502,334 19 12 2023 17.2 0.3 $22,122,377 $398,202,787 0 0 $0 $1,670,502,334 20 13 2024 16.9 0.3 $22,122,377 $420,325,164 0 0 $0 $1,670,502,334 21 14 2025 16.6 0.3 $22,122,377 $442,447,541 0 0 $0 $1,670,502,334 22 15 2026 16.4 0.3 $22,122,377 $464,569,919 0 0 $0 $1,670,502,334 23 16 2027 16.1 0.3 $22,122,377 $486,692,296 0 0 $0 $1,670,502,334 24 17 2028 15.8 0.3 $22,122,377 $508,814,673 0 0 $0 $1,670,502,334 25 18 2029 15.5 0.3 $22,122,377 $530,937,050 0 0 $0 $1,670,502,334 26 19 2030 15.2 0.3 $22,122,377 $553,059,427 0 0 $0 $1,670,502,334 27 20 2031 14.9 0.3 $22,122,377 $575,181,804 0 0 $0 $1,670,502,334 28 21 2032 14.6 0.3 $22,122,377 $597,304,181 0 0 $0 $1,670,502,334 29 22 2033 14.3 0.3 $22,122,377 $619,426,558 0 0 $0 $1,670,502,334 30 23 2034 14.0 0.3 $22,122,377 $641,548,935 0 0 $0 $1,670,502,334 31 24 2035 13.7 0.3 $22,122,377 $663,671,312 0 0 $0 $1,670,502,334 32 25 2036 13.4 0.3 $22,122,377 $685,793,689 0 0 $0 $1,670,502,334 33 26 2037 13.1 0.3 $22,122,377 $707,916,066 0 0 $0 $1,670,502,334 34 27 2038 12.8 0.3 $22,122,377 $730,038,443 0 0 $0 $1,670,502,334 35 28 2039 12.5 0.3 $22,122,377 $752,160,821 0 0 $0 $1,670,502,334 36 29 2040 12.2 0.3 $22,122,377 $774,283,198 0 0 $0 $1,670,502,334 37 30 2041 11.9 0.3 $22,122,377 $796,405,575 0 0 $0 $1,670,502,334 38 31 2042 11.6 0.3 $22,122,377 $818,527,952 0 0 $0 $1,670,502,334 39 32 2043 11.3 0.3 $22,122,377 $840,650,329 0 0 $0 $1,670,502,334 40 33 2044 11.0 0.3 $22,122,377 $862,772,706 0 0 $0 $1,670,502,334 41 34 2045 10.8 0.3 $22,122,377 $884,895,083 0 0 $0 $1,670,502,334 42 35 2046 10.5 0.3 $22,122,377 $907,017,460 0 0 $0 $1,670,502,334 43 36 2047 10.2 0.3 $22,122,377 $929,139,837 0 0 $0 $1,670,502,334 44 37 2048 9.9 0.3 $22,122,377 $951,262,214 0 0 $0 $1,670,502,334 45 38 2049 9.6 0.3 $22,122,377 $973,384,591 0 0 $0 $1,670,502,334 46 39 2050 9.3 0.3 $22,122,377 $995,506,968 0 0 $0 $1,670,502,334 47 40 2051 9.0 0.3 $22,122,377 $1,017,629,345 0 0 $0 $1,670,502,334 48 41 2052 8.7 0.3 $22,122,377 $1,039,751,722 0 0 $0 $1,670,502,334 49 42 2053 8.4 0.3 $22,122,377 $1,061,874,100 0 0 $0 $1,670,502,334 50 43 2054 8.1 0.3 $22,122,377 $1,083,996,477 0 0 $0 $1,670,502,334 51 44 2055 7.8 0.3 $22,122,377 $1,106,118,854 0 0 $0 $1,670,502,334 52 45 2056 7.5 0.3 $22,122,377 $1,128,241,231 0 0 $0 $1,670,502,334 53 46 2057 7.2 0.3 $22,122,377 $1,150,363,608 0 0 $0 $1,670,502,334 54 47 2058 6.9 0.3 $22,122,377 $1,172,485,985 0 0 $0 $1,670,502,334 55 48 2059 6.6 0.3 $22,122,377 $1,194,608,362 0 0 $0 $1,670,502,334 56 49 2060 6.3 0.3 $22,122,377 $1,216,730,739 0 0 $0 $1,670,502,334 57 50 2061 6.0 0.3 $22,122,377 $1,238,853,116 0 0 $0 $1,670,502,334

Summary Relative to 2005 Column total = 16.5 $1,238,853,116 $35,307,313,810 22.2 $1,670,502,334 $77,993,470,971 (56 years after base year) Average annual = $630,487,747 $1,392,740,553 Present value (PV) = $4,321,186,852 $12,375,281,254 Annualized PV value = $309,483,860 $886,318,954 Summary Relative to 2010 Column total = 15.3 $1,150,363,608 $35,086,090,039 21.1 $1,582,012,826 $77,772,247,201 (52 years after update) Average annual = $674,732,501 $1,495,620,138 Present value (PV) = $5,426,935,463 $15,984,210,270 Annualized PV value = $391,493,777 $1,153,085,179 Summary Relative to 2012 Column total = 14.7 $1,106,118,854 $34,842,743,891 20.5 $1,537,768,072 $77,528,901,053 (50 years same as RIA) Average annual = $696,854,878 $1,550,578,021 Present value (PV) = $5,962,000,000 $18,049,000,000 Annualized PV value = $432,005,623 $1,307,827,824
Discount rate = 7% A dded Cost for Conversion to Dry Disposal Under the CCR Proposed Rule Compared to Conversion Trend Without Rule: Present value (PV) = $12,087,000,000 Annualized PV value = $875,822,201 Percent reduction compared to October 2009 draft RIA dry conversion cost estimate: October 2009 draft RIA cost estimate = $23,200,000,000 Reduction in cost estimate compared to RIA = -48%99 As summarized below in comparison to the initial cost estimate, the upda ted conversion cost is the di fference in the step-1 cos t to the electric utility industry for continuation of the phase -out trend without the CCR rule, compared to the step-2 cost for mandatory phase- out with the rule.

Dry conversion cost : Initial cost estimate Updated cost estimate Average annualized cost $1.676 billion/year $0.876 billion/year (48% reduction) Present value (PV) cost $23.2 billion PV $12.1 billion PV (48% reduction)

The updated cost is also presented below af ter integrating the updated dry conversion co st back into the overall cost of the CC R proposed rule which contains two other cost categories as estimated for th e Subtitle C option (i.e., $491 m illion/year for engineering contro l costs + $107 million/year for ancillary regulatory costs).

Rule total cost : (i.e., updated dry conversi on cost + engineering contro l cost + ancillary cost) Initial cost estimate Updated estimate Average annualized cost $2.27 billion/year $1.47 billion/year (35% reduction) Present value (PV) cost $31.4 billion PV $20.3 billion PV (35% reduction)

As shown above, the composite effect of th e two cost update factors is they reduce th e initial dry conversion cost estimate by 48% , and reduce by 35% the overall compliance cost estimate (i.e., dry conversion co st plus engineering control costs plus ancillary costs).

o Factors Which May Accelerate the CCR Impoundment Phase-Out Trend

For the reasons described above, it is clear that there is a significant past and continui ng trend toward CCR impoundment phase -out at electric utility plants, regardless of the CCR rule , and that this trend will continue. Described below, EPA has identified seven factors which corroborate continuation of this impoundment phase-out trend, some of which have been quantified in the cost adjustment:

1. Industry conversions to dry CCR disposal : This factor corroborates th e phase-out trend applied in th e cost update. As discussed above, there is a documented over two-decade long trend 1996 to 2019 away from wet CCR disposal in the electric utility industry. This trend consists of two parts: (a) the 1996-2005 historical data period, plus (b) the more recent (2009) announcements of ac tual conversions which occurred between 2005 a nd 2009, and planned conversions to occur w ithin the next 10 years (i.e., by 2019). According to one company (United Conveyor Co rporation) who has been s upplying dry disposal equipmen t and conversion services to the electric utility industry, the main histor ical drivers for this voluntary shift have been (1) generating dry fly ash as a s aleable coproduct to other industries for beneficial uses, and (2) decreasing the volume of fl y ash going to impoundments to provide grea ter capacity for bottom ash. Since then, concer n over possible future environmental releas e liabilities associated with CCR impoun dments, and pressure from individual stat e governments, has led electric utility companies to consider dry conversion. TVA is the most prominent example of this trend which publicly announced 100 in 2009 it plans to convert its wet fly ash and wet bottom ash systems to

100 TVA_s 20 August 2009 news release is at http:// www.tva.gov/news/releases/ julsep09/ccprp_other.htm100 dry disposal within the next eight to 10 years (i.e. by 2019). Conversions of this so rt are a current trend, and they will def initely continue, even in the absence of th e CCR proposed rule. As summarized in Exhibit 4H above (columns A to D), EPA identified 18 such plants constituting 17% of the industry-wide wet CCR disposal tonnage as of 2005. It is inappropr iate to attribute the wet disposal phase-out cost of the CCR proposed rule to plants independently moving to dry CCR dispos al. At this point, EPA expects that mo st plants will choose to move to dry disposal given the additional factors presented below.

2. Plants switching to other fuels : EPA assumes this factor is refl ected in the phase-out trend applied to the co st update. Some coalfired electricity plants have since 2005 sw itched, or are planning to switch, some or all of their coal-fired boilers at certai n plants, from coal to other fuels (e.g. natural gas) for r easons unrelated to the CCR proposed rule. In such cases, the cost of closure of t heir CCR disposal impoundments should not be attributed to the cost of the proposed rule. This factor decreases the estimated cost of t he rule, and particularly EPA_s estimated future cost of phasing-out wet disposal attributable to the proposed rule. For example, based on EPA_s recent internet search, as also displayed in Exhibit 4H above (columns E to H), EPA identified 8 coal-fired electric utility plants using impoundments (as of 2005) representing 3% of wet CCR disposal by the 158 plants, which have or plan to switch fuels at one or more of their coal-fired electricity generation boilers within one or more plants, or to close one or more of their coal-fired boilers or entire coal-fired plants.

3. Lifespan expiration of existing CCR impoundments : This factor suggests a faster future phase-out trend than applied in the cost update, but is not applied in the cost upda te. Another factor which co rroborates the future continua tion of the electric utili ty industry_s voluntary phase-out of CCR impoundments, is the fact that exis ting (i.e., active, operational) CCR impoundments have distinct operational lifespans. When an impoundment reaches its end-of-lifespan, the electric u tility plant must in that future year ei ther add new impoundment capacity by installing another impoundment, or conve rt to dry disposal by instal ling a landfill (or providing t heir annual CCR for beneficial uses). For purpose of estimating the gengineeri ng costh component (in Chapter 4 of this RIA), EPA assigned impoundment lifespan start years (i .e., year in which impoundment constructi on was completed and began receiving CCR), and future expected impoundment operational lifespan closure years, to each of the 158 coal-fired plants with operational CCR impoundments (as of 2005) identifie d in this RIA. For the most part, the impound ment start years were based on actual industry

reported data from the references cited in this RIA. However, expected closure years were pr ovided by industry for 78 of the 1 58 plants; thus, EPA assigned expected closure years to the remainder 80 pl ants assuming a 40-year lifespan. Exhibit 4J below presents a summary of the expected future closure ye ars in relation to the remaining lifespan years and associated impoundment tonnages wh ich are expected to reach end of operational lifespan in absence of the CCR rule. This summary indicate s that all existing CCR impoundments could be expected to reach end-of-lifespan by year 2051, and that 20% of impoundments will have reached end-oflifespan by year 2018. According to the cost update assumptions discussed in the 2 nd update steps of prior section above, year 2018 represents the 5 th year of the CCR final rule_s assu med 5-year phase-out period spanning 2014 to 2018, which also assumes the CCR final rule is promulgated by EPA at the start of 2012 and that state governments will adopt the ru le 2-years late r by the end o f 2013. This lifespan expiration trend corrobo rates the assumed continuation of the phase-out trend depicted in Exhibit 4I (column A1) which indicates that 17% of CCR impoundment tonnage may be expected to have phased-out by year 2018 (i.e., 18.7 million tons remaining by 2018 compared to 22.5 million tons in the analysis base year 2005) in absence of the CCR rule. In fact, given that end-of-l ifespan provides companies with a low-cost opportunity to convert to dry disposal, the higher 20% end-of-lifespan percentage compared t o the101 17% phase-out trend suggest the future phase-out trend may be accelerated compared to the 1.1% annual phase-out assumed based o n the 1996-2005 trend. For example, this re sult suggests that by 2018 the annual phase -out rate in that year could be 1.3% (i.e., (20%/17%) x 1.1%)).

4. EPA’s Clean Air Act emissions standards: This factor is not quantif ied in the cost update. Where existing coal-fired electric utility plants put in new air emission sc rubbing systems, EPA believes they will overw helmingly rely on CCR management systems that do not require wet disposal impoundments. Two of EPA_s upcoming Clean Air Act (CAA) air pollution regulations may lead some co al plants to begin using large amounts of reag ent to capture SO2 from boiler flue gas:

x EPA_s Clean Air Mercury Rule (CAMR) which was vacated by th e DC Circuit Court in 2007 compels EPA under the CAA Section 112 to issue maximum achievable control technology (MACT) regulati ons for coal- and oil-fire d electric utility units: http://www.epa.gov/ttn/at w/utility/utilitypg.html

x EPA_s remanded Clean Air Interstate Rule (C AIR) was also vacated by the DC Circuit C ourt in 2007 but was la ter reinstated and remanded back to the Agency for further re view/clarification: h ttp://www.epa.gov/cair

Such plants would likely experien ce a significant increase in the amount of fly ash or wet FGD waste tonnage to be disposed, be cause the reactants are either captured with the fly ash or with the wet FGD waste. If th ese plants currently dispose of bottom ash, fly ash, or wet FGD waste in wet impoundments, the likel ihood of significantly increased future dis posal tonnages may prompt them to consid er a switch to dry disposal. Therefore, new CCR generated as a result of new Clean Air Ac t emissions requirements are very likely t o cause plants to switch away from wet disposal independent from the CCR proposed rule. EPA has not quantified this factor for purpose of updating the 2009 RIA regulatory cost estimate in this RIA.

5. EPA’s Clean Water Act effluent standards : This factor is not quantified in the co st update. EPA is currently developing new industrial wastewater effluent re gulations for coal-fired electricity plants. These new regul ations are likely to tighten sign ificantly existing effluent limits. These new regulations will be one more factor likely to influence plan ts to switch to dry disposal s ystems.

6. State government implementation of rule : This factor is quantified in the cost update. It recognizes that states re quire two years for their state legislatures or environmen tal regulatory programs to adopt new RCRA re gulations such as the CCR final rule, whi ch is necessary for the rule to become federally enforceable. In the initial cost estimat e, EPA assumed that the CCR final rule woul d become effective (i.e., adopted by stat es) in year 2012 and that dry co nversion capital costs would all be incurred in that single yea r. In contrast to that simple cost estimation framework, this cost update fact or pushes the dry conversion cost 2-years out into the future be ginning in 2014. The 5-year allowed dry conversion (i .e., impoundment phase-out) period is thus 2014 to 2018. In reality, there is a fur ther distinction to be made. For states wh ich operate EPA-authorized RCRA regulatory programs (as of 2005, EPA-authorized states comprise 97% of the 22.4 million tons annual CCR impoundment dispos al tonnage), they could have 2-years adoption period. Howev er, in non-authorized states (i.e., AK, IA), territories, and Indian count ry, the CCR rule becomes eff ective in 2012 by fact that E PA will implement it directly. Accordi ng to the 2005 EIA data, in this 2 nd group there are four plants with impoundments in IA plus one plant102 with impoundment(s) on tribal land totaling 3% of the 22.4 million tons impoundment disposal in 2005. 101 Because this 2 nd group only comprises a very small 3% fraction of the annual CCR impoundment di sposal tonnage, and to avoid adding another layer of complex ity to the cost update which would only result in a very small (i.e., <5%) difference in updated estimate, the cost update does not separately calculate costs for both groups addressing unde r this factor, but applies implementati on year to the entire 22.4 million tonnag e. This 2- year final rule adoption cost-timing ad justment factor is highlighted in Exhibit 4I above.

7. 5-year impoundment phase-out period : This factor is quantified in the cost update. It recognizes that electric utility plants are likely to incur dry conversion cap ital costs spread across each of the years in the CCR rule_s 5-year mandated phase-out period , rather than incurring all dry conversion capital cost in one year as was simply assumed in th e initial cost estimat e. This cost-timin g adjustment factor is highlighted in Exhibit 4I above.

101 As of 2005, the four IA plants are th e George Neal North plant (50,200 tons/year CCR impoundment disposal), the Lansing plant (24,000 tons/year), the Louisa plant (23,000 tons/year), and the Walter Scott Jr Energy Center plant (1 04,000 tons/year). The one plant located on tribal land is t he Four Corners plant in NM (501,400 tons/year).103 Exhibit 4J

RIA 50-

year period Actual company planned or EPA estimated pond

closure year CCR pond end of lifespan (tons/year) Cumulative pond lifespan end (tons/year) % pond tonnage phaseout
2009 Total 0 0 0%
2010 Total 0 0 0%
2011 Total 0 0 0%
1 2012 Total 481,300 481,300 2.1% 2 2013 Total 40,400 521,700 2.3% 3 2014 Total 634,700 1,156,400 5.2% 4 2015 Total 599,450 1,755,850 7.8% 5 2016 Total 2,021,700 3,777,550 16.9% 6 2017 Total 189,300 3,966,850 17.7%
7 2018 Total 513,400 4,480,250 20% 8 2019 Total 838,400 5,318,650 23.7% 9 2020 Total 1,969,160 7,287,810 32.5% 10 2021 Total 183,100 7,470,910 33.4% 11 2022 Total 661,700 8,132,610 36.3% 12 2023 Total 410,800 8,543,410 38.1% 13 2024 Total 39,000 8,582,410 38.3% 14 2025 Total 477,700 9,060,110 40.4% 15 2026 Total 280,900 9,341,010 41.7% 16 2027 Total 27,600 9,368,610 41.8% 17 2028 Total 134,000 9,502,610 42.4% 18 2029 Total 36,200 9,538,810 42.6% 19 2030 Total 527,100 10,065,910 44.9% 20 2031 Total 170,350 10,236,260 45.7% 21 2032 Total 327,400 10,563,660 47.2% 22 2033 Total 746,500 11,310,160 50.5% 23 2034 Total 594,100 11,904,260 53.1% 24 2035 Total 473,000 12,377,260 55.3% 25 2036 Total 322,000 12,699,260 56.7% 26 2037 Total 742,800 13,442,060 60.0% 27 2038 Total 476,100 13,918,160 62.1% 28 2039 Total 825,900 14,744,060 65.8% 29 2040 Total 642,050 15,386,110 68.7% 30 2041 Total 1,009,100 16,395,210 73.2% 31 2042 Total 141,600 16,536,810 73.8% 32 2043 Total 992,010 17,528,820 78.3% 33 2044 Total 505,700 18,034,520 80.5% 34 2045 Total 104,400 18,138,920 81.0% 35 2046 Total 338,000 18,476,920 82.5% 36 2047 Total 326,800 18,803,720 83.9% 37 2048 Total 575,800 19,379,520 86.5% 38 2049 Total 788,300 20,167,820 90.0% 39 2050 Total 2,075,700 22,243,520 99.3% 40 2051 Total 121,900 22,400,000 100.0% Column total (2005 base) = 22,400,000 Projection of Future CCR Pond Lifespan Closure Tonnage

- 5,000,000 10,000,000 15,000,000 20,000,000 25,000,000

20

1 2 To t al

20

1 4 To t al

20

1 6 Total

20

1 8 Total

2 02

0 Total

2 02

2 T

o t a l

2 02

4 T

o t a l

2 02

6 T

o t a l 2028 Total 2030 To t a l 2032 To t al 2034 Total 2036 Total 2038 Total

2 04

0 Total

2 04

2 T

o tal

2 04

4 T

o t a l 2046 Total 2048 Total 2050 Total

Projection of Future Percentage of 2005 CCR Pond Disposal Lifespan
Closure

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

2 01

2 Total

2 01

4

T

o t a l

2 0 1 6 T

otal 2018 Total

2 020 Total

2 022 To t a l

2 0 24

Tot

a l 2026 Total 2028 Total

2 0 30

T

o t a l 2032 T o t a l 203

4

T otal

2 03

6

T otal

2 0 38

T

o t a l

2 0 40

Total 2042 Total

2 04

4 Total

2 04

6

T

o t a l

2 0 48 Tot a l 2050 T otal104 Exhibit 4K below summarizes the above regulatory co st estimates on an incremental basis (i.e ., without including th e gBaseline Costsh estimated in Chapter 3 of this RIA). Appendix J presents regulatory costs estimates fo r each of the 495 electric utility plants.

Exhibit 4K Summary of Cost Estimates for the Octo ber 2009 Draft RIA Regulatory Options ($millions in 2009 price level; average annual amortized @7% discount rate over 50-year period 2012 to 2061)

RCRA Regulatory Cost Element Subtitle C Hazardous waste Subtitle D (version 1) Hybrid C&D

A. Engineering Controls (onsite): $491 $491 $491 1. Groundwater monitoring $13 $13 $13 2. Bottom liners $95 $95 $95 3. Leachate collection $8 $8 $8 4. Fugitive dust controls $5 $5 $5 5. Water runon/runoff controls $2 $2 $2 6. Financial assurance $30 $30 $30 7. Disposal unit location restrictions $76 $76 $76 8. Closure capping to cover unit $255 $255 $255 9. Post-closure groundwater monitoring $2 $2 $2 10. Storage design & operating standards Not estimated in this RIA Not estimated in this RIA Not estimated in this RIA B. Other Ancillary Costs: $107 $1 $9 11. For offsite disposal (11a+11b+11c) = 11a. RCRA manifest cost 11b. Added operation for hazmat truck 11c. Offsite LF RCRA Subtitle C permit $77 $66 $8 $3 $0 Not relevant Not relevant Not relevant $0 (offsite applies only to LFs so no incremental cost over baseline) 12. Structural integrity inspections $1 $1 $1 13. RCRA facility-wide investigation $7.6 Not relevant $2.4 14. RCRA facility-wide corrective acti on Not estimated in this RIA; historical average = $5.4 million per case Not relevant Not estimated in this RIA; historical average = $5.4 million per case 15. RCRA TSDF haz waste disposal permit $7 Not relevant $2 16. RCRA enforcement inspection $0.06 $0 $0.02 17. Future added cleanup cost as ghazar dous wasteh Not estimated in this RIA: case studies indicate possible $18 to $376 million per case Not relevant Not estimated in this RIA; case studies indicate possible $18 to $376 million per case 18. EPA paperwork reporting/recordkeeping $13 Not relevant $4 C. Land Disposal Restriction Dewatering Treatment $876 (updated) $876 (updated) $876 (updated)
TOTAL ANNUALIZED COSTS (A+B+C) = Average cost per-ton (94.2 million tons disposed) = Average cost per-plant (467 disposing plants) = $1,474 per year (updated) ($15.65 per ton) ($3.16 million per plant) $1,368 per year (updated) ($14.52 per ton) ($2.93 million per plant) $1,376 per year (updated) ($14.61 per ton) ($2.95 million per plant)

Note: Chapter 6 of this RIA scales these cost esti mates based on the October 2009 draft RIA options, to the 2010 regulatory options.105 

### 4C. State-by-State Distribution of Incremental CCR Regulatory Costs

Exhibit 4L below summarizes the distribution of es timated regulatory costs on a state-by-state basis and by option. This state-by-state summary is based on apportionment of nationwide average annualized cost estimated for each regulatory option, according to stat e-by-state annual CCR tonnage generated by the 495 co al-fired electric utility plants.

Exhibit 4L State-by-State Distribution of Estimated Incremental Cost s for the October 2009 Draf t RIA Regulatory Options ($million average annualized cost in 2009$ over 50-year period of analysis 2012 to 2061)
A B C D E F G H

Item State # of coalfired electricity

plants 2005 CCR generation by coal-fired electric

utility plants (tons/year) State % of nationwide CCR generation (based on Column D) Subtitle C Hazardous waste Subtitle D (version 1) Hybrid C&D: Subtitle C impoundments Subtitle D landfills

1 AK 2 46,179 0.03% $0.4 $0.4 $0.4 2 AL 16 3,210,337 2.27% $33.5 $31.1 $31.2 3 AR 4 744,267 0.53% $7.8 $7.3 $7.3 4 AZ 8 3,334,030 2.36% $34.8 $32.3 $32.5 5 CA 6 159,927 0.11% $1.6 $1.5 $1.5 6 CO 12 1,704,433 1.21% $17.8 $16.6 $16.6 7 CT 0 172,280 0.12% $1.8 $1.6 $1.7 8 DC 0 0 0.00% $0.0 $0.0 $0.0 9 DE 2 251,205 0.18% $2.7 $2.5 $2.5 10 FL 15 6,132,345 4.34% $64.0 $59.4 $59.7 11 GA 13 6,077,700 4.30% $63.4 $58.9 $59.2 12 HI 1 58,968 0.04% $0.6 $0.5 $0.6 13 IA 15 1,136,289 0.80% $11.8 $11.0 $11.0 14 ID 0 0 0.00% $0.0 $0.0 $0.0 15 IL 17 3,856,748 2.73% $40.2 $37.4 $37.6 16 IN 33 8,798,845 6.23% $91.8 $85.3 $85.7 17 KS 8 1,495,099 1.06% $15.6 $14.5 $14.6 18 KY 31 9,197,567 6.51% $96.0 $89.1 $89.6 19 LA 3 1,614,800 1.14% $16.8 $15.6 $15.7 20 MA 0 363,150 0.26% $3.8 $3.6 $3.6 21 MD 4 1,932,740 1.37% $20.2 $18.8 $18.9 22 ME 1 48,000 0.03% $0.4 $0.4 $0.4 23 MI 24 2,369,673 1.68% $24.8 $23.0 $23.1 24 MN 20 1,525,979 1.08% $15.9 $14.8 $14.9 25 MO 20 2,679,742 1.90% $28.0 $26.0 $26.1 26 MS 6 1,229,400 0.87% $12.8 $11.9 $12.0106 Exhibit 4L State-by-State Distribution of Estimated Incremental Cost s for the October 2009 Draf t RIA Regulatory Options ($million average annualized cost in 2009$ over 50-year period of analysis 2012 to 2061)
A B C D E F G H

Item State # of coalfired electricity

plants 2005 CCR generation by coal-fired electric

utility plants (tons/year) State % of nationwide CCR generation (based on Column D) Subtitle C Hazardous waste Subtitle D (version 1) Hybrid C&D: Subtitle C impoundments Subtitle D landfills

27 MT 5 1,830,624 1.30% $19.2 $17.8 $17.9 28 NC 27 5,504,531 3.90% $57.5 $53.4 $53.7 29 ND 9 3,038,100 2.15% $31.7 $29.4 $29.6 30 NE 6 614,473 0.44% $6.5 $6.0 $6.1 31 NH 1 176,900 0.13% $1.9 $1.8 $1.8 32 NJ 2 735,214 0.52% $7.7 $7.1 $7.2 33 NM 4 3,983,300 2.82% $41.6 $38.6 $38.8 34 NV 2 391,500 0.28% $4.1 $3.8 $3.9 35 NY 11 1,479,792 1.05% $15.5 $14.4 $14.4 36 OH 24 10,429,446 7.39% $108.9 $101.2 $101.7 37 OK 3 1,490,800 1.06% $15.6 $14.5 $14.6 38 OR 1 99,900 0.07% $1.0 $1.0 $1.0 39 PA 28 15,359,680 10.88% $160.4 $148.9 $149.7 40 RI 0 0 0.00% $0.0 $0.0 $0.0 41 SC 14 2,178,360 1.54% $22.7 $21.1 $21.2 42 SD 2 103,753 0.07% $1.0 $1.0 $1.0 43 TN 12 3,240,120 2.29% $33.8 $31.4 $31.5 44 TX 18 13,165,728 9.32% $137.4 $127.6 $128.2 45 UT 7 2,582,144 1.83% $27.0 $25.1 $25.2 46 VA 13 2,388,526 1.69% $24.9 $23.1 $23.3 47 VT 0 0 0.00% $0.0 $0.0 $0.0 48 WA 1 1,405,220 1.00% $14.7 $13.7 $13.8 49 WI 12 1,412,534 1.00% $14.7 $13.7 $13.8 50 WV 20 9,231,718 6.54% $96.4 $89.5 $90.0 51 WY 12 2,224,848 1.58% $23.3 $21.6 $21.7
Totals = 495 141.2 million 100% $1,474/year $1,368/year $1,376/year107 

### 4D. Cost Estimation Uncertainty

This section addresses OMB_s 2003 Circular A-4 gRegulatory Analysish guidance (page 40) requirement for RIAs involving rules wi th expected annual economic effects of $1 billion or more, to pres ent a formal quantitative analysis of the uncertainties about be nefit and cost estimates. This section only addresses uncertainties with resp ect to cost estimates for both baseline cost and incremental cos ts for the regulatory options. This section first presents three specific examples of data quality uncertainty factors in this RIA, followed by an overall uncertainty factor to represent all such specific data quality uncertainty factors combined (the three factors below are not additive across thei r low- and high-end percentage ra nge endpoints because such simple addition would represent unlikely comp ounding of these factors ):

x Specific Examples of Data Quality Uncertainty Factors in This RIA

1. CCR tonnage data:The baseline and regulatory cost estimates in th is RIA are based on the annual CCR disposal and beneficial use tonnages reported by electric utility plants to the 2005 DOE-EIA Form 767 database. However, the DOE-EIA 767 data reporting form 102 does not provide respondents with a definition for the gtonsh co llected in Schedule 3 of the data reporting form. Because there are three numerical defi nitions of gtonh commonly used in the US (i.e., short-ton = 2,000 pounds, long-ton = 2,200 pounds; and metric ton = 2 ,205 pounds), this factor potentially introduces -20% to +20% uncertainty range. For purpose of consistency with the use of short-tons in most EPA RCRA program reports, 103 this RIA interprets CCR gtonsh as short-tons.
2. Data sources: Also with respect to CCR tonna ge data, this RIA cites multiple possible sources of data based on different publis hed sources. For example, as displayed in Exhibit 4D of this RIA, one source (American Coal Ash Association) provides an industry survey-based estim ate of CCR generation by electric uti lity plants in 2005 of 123.1 million tons. Whereas this RIA estimates 141.2 million tons CCR gene ration in 2005 based on data from the 2005 DOE-EIA Form 767 database for plants >100 MW in size and based on supple mental estimates made in this RIA for <100 MW size plants. This data source inc onsistency factor represents -13% to +15% uncertainty range.
3. Data years: Information and data used to evaluate and estimate the cost of baseline CCR dispos al practices are from various published sources dated 1995, 1996, and 2006. Furthermore, un it costs for CCR disposal unit engineering controls applied in this RIA are from diffe rent published data years such as 2000, 2004, and 2007. This RIA updated historical data to 2009 price levels usi ng various indexes, some of which were specific to a partic ular type of unit cost, and other indexes were general (e.g., GDP Price Deflator). The uncertainty in accuracy of un it costs introduced by use of historical data is not quantified

.

x Overall Data Quality Uncertainty Range

102 Instructions to the 2005 DOE-EIA Form 767 data reporting questionnaire (24 pages) are available at http://www.eia.doe .gov/cneaf/electricity/f orms/eia767/eia767instr.pdf A copy of the 2005 DOE-EIA 767 data reporting questionnaire (1 6 pages) is available at http://w ww.eia.doe.gov/cneaf/electricity /forms/eia767/eia767.pdf

103 One example of the standardized use of gshort-tonsh in EPA RCRA program reports is the RCRA Biennial Hazardous Waste Reports w hich are archived at http://www.epa.gov/waste/inforesources/data/biennialreport/index.htm108 The method applied to characterize the overall level of quantitative uncertainty in the co st estimates of this RIA, is based on the 02 February 2005 gRecommended Practice No. 18R-97: Cost Estim ate Classification System as Applied in Engineering, Procurement, and Construc tion for the Process Industriesh 104 . This method is specifically applicable to cost estimat es developed for mechanical an d chemical process equipment used for engineering, procurement and construction across a wide variety of industries including the electric u tility industry sector (i.e., NAICS code 22). As summarized in Exhibit 4M below, this cost estimate classification system involves five estimation categ ories (i.e., Class 1, Class 2, Class 3, Class 4, Class 5) reflecting differe nt relative (a) levels of cost definition, (b) purposes and uses of cost estima tes, (c) cost estimation methodologies, (d) expected accuracy ranges, and (e) degrees of cost estima te preparation effort.

Exhibit 4M Summary of Cost Estimation Classifi cation System for Characterizing Data Quality Uncertainty in this RIA Estimate Category Level of Detail (Quantity of Input Information & Data) Level of Effort (Time Required to Complete the Cost Estimate) Expected Accuracy Range

Class 5 Very limited information (e.g., little more than proposed project type, location, and capacity). Very limited amount of time an d with little effort, sometimes requiring less than one hour F TE to prepare the cost estimate. -50% to +100%

Class 4 1% to 5% complete, limited information (e.g., preliminary engineered process and equipment lists) for purpose of alternatives analysis, screening analysis, or demonstration of economic feasibility. Sometimes requiring up to two months FTE for preparing the cost estimate. -30% to +50%

Data quality uncertainty range applied in this RIA (i.e., between Class 3 and Class 4) = -25% to +40%

Class 3 10% to 40% complete, semi-detailed information (e.g., process flow diagrams, equipment diagrams, layout drawings, engineered process and equipment lists). May require up to nine months FTE to prepare the cost estimate. -20% to +30%

Class 2 30% to 70% complete, detailed information May require up to 1.5 years FTE to prepare the cost estimate. -15% to +20%

Class 1 50% to 100% complete and full project definition (e.g., virtually all engineering and design documentation/plans) May require up to or over thr ee years FTE to prepare the cost estimate. -10% to +15%

Because the bulk of the data collection and analysis presented in this RIA was execute d in a relatively short time (i.e., five months) using semidetailed information for baseline CCR disposal conditions, dispos al unit costs, and engineering control and ancillary costs for the regulatory options, the level of numerical uncertainty for the baseline co st and incremental costs for each of the regulatory options esti mated in this RIA may be classified between a Class 3 and Class 4 type of estimate (i.e., -25% to +40%), as displayed below in Exhibit 4N. These uncertainty ranges represent a probability distribution a bout the cost estimates, and may be interp reted as the expected values (i.e., best estimates) and lowend and high-end ranges about each cost estimate. Such quantit ative indicators of un certainty are identified in OMB_s Circular A-4 (pages 40, 41) as acceptable for characterizing probability distributions fo r cost estimates involving major rules with possible annual ec onomic effects of $1 billion or more for one or more regulatory options.

104 Recommended Practice No. 18R-97 (10 pages) published by the Association for the Advancement of Cost Engineering at: http://www .aacei.org/technical/rps/18r-97.pdf109 Exhibit 4N Cost Estimation Uncertainty with Overall Data Quality Uncertainty Factor Applied to the October 2009 Draft RIA Options ($millions in 2009$)

Cost Estimate Uncertainty Indicator Subtitle C Hazardous waste Subtitle D (version 1) Hybrid C&D: Subtitle C for impoundments Subtitle D for landfills Best estimate (w/updated LDR cost): $1,474/year (updated) $20,343 PV $1,368/year (updated) $18,880 PV $1,376/year (updated) $18,990 PV -25% uncertainty low-end $1,106/year $15,264 PV $1,026/year $14,160 PV $1,032/year $14,243 PV +40% uncertainty high-end $2,064/year $28,485 PV $1,915/year $26,429 PV $1,926/year $26,581 PV
Note: PV = present value of average annualized cost over 50-years @7% discount rate, calculated by multiplying the average annualized cost by the present value factor = 13.801.

Note: Chapter 6 of this RIA scales these estimated costs based on th e October 2009 draft RIA, to the 2010 regulatory options.110 

## Chapter 5 Potential Benefits of RCRA Regulation of CCR Disposal in the Electric Utility Industry

Exhibit 5A below displays social benefits associat ed with EPA_s RCRA regulatory program, a few or many of which may be associated with any particular RCRA regulation. To a lesser or greater degree, a range of these benef it elements may be associated with future benefits from RCRA regulation of CCR disposal, acco rding to the unique physical and environmental attributes at any part icular CCR disposal s ite.

Exhibit 5A Human Health, Environmental, & Economic Bene fits of the EPA RCRA Regulatory Program* Benefit Category (n = 6) Benefit Sub-Element Examples (n = 36)
1. Human Health Protection Benefits 1A. Mortality Reduction-Examples 1) Reduced risk of cancer fatality 2) Reduced risk of acute fatality 1B. Morbidity reduction-Examples 1) Reduced risk of cancer 2) Reduced risk of morbidity (e.g., asthma, nausea) 2A. Market Ecological Values: 1) Commercial fisheries 2) Market recreational benefits (e.g., involving fees) 3) Food 4) Fuel 5) Fiber 6) Timber 7) Fur/leather 2. Ecological Protection Benefits

2B. Non-Market Ecological Values & Amenities (examples): 1) Non-market recreational benefits (e.g., w/out fees) 2) Non-use values: existence, bequest, and quasi-option values 3. Indirect Ecosystem & Resource Conservation Benefits 1) Climate moderation 2) Flood moderation 3) Groundwater recharge 4) Sediment trapping 5) Soil retention 6) Nutrient cycling 7) Pollination by wild species 8) Biodiversity 9) Water filtration 10) Soil fertilization 11) Pest control 12) Reduced pressure on endangered species 13) Avoided habitat destruction 4. Avoided Economic Costs 1) Avoided costs of providing government mandated alternate drinking water supplies 2) Avoided costs associated with government mandated cleanups of industrial waste accidents or spills 5. Avoided Materials Damages, Improved Aesthetics, & Historical Preservation 1) Aesthetic pleasure 2) Improved taste, order, visibility 3) Protection of resources with cultural and historic value 4) Protection of constructed resources (e.g., buildings, infrastructure) 6. Potential Long-Term Benefits (Sustainability) 1) Avoided increases in damages related to changes in affected populations 2) Benefits associated with resource conservation 3) Benefits associated with the precautionary principle, protection from unforeseen issues 4) Benefits from long-term increases in the value of environmental quality * Source: Exhibit 1-1 of EPA Office of Solid Waste, gApproaches to Assessing the Benefits, Costs, and Impacts of the RCRA Subti tle C Program,h prepared by Industrial Economics Inc., October 2000,111 In contrast to the Exhibit 5A list of RCRA regulatory program benefits, because of ti me, data, and methodological limitations, the regulatory benefits estimated in this RIA do not repr esent a complete list of expected benefits of the CCR proposed rule. For example, th e benefits analysis in this Chapter of the RIA does not estimate benefits of (a) reducing cancer risks associated with preventing direct e ffluent discharges of CCR to surface waters, (b) ecological and ecosystem benefits, (c) off-site CCR dispos al regulatory benefi ts, or (d) non-canc er human health protection benefits. In contrast to this large number of possible benefit elem ents, this RIA monetizes only three benefit cate gories consisting of five sub-elements.

1. Groundwater Protection Benef its at CCR Disposal Sites

a. Human health protection benefits (i.e., benefit of preventing cancer fr om arsenic exposure) b. Groundwater remediation costs avoided
2. CCR Impoundment Catastrophic Failure Benefits

a. Future cleanup costs avoided
3. Benefits from Increase in Future CCR Beneficial Uses

a. Direct market benefits (economic benefits) b. Lifecycle social benefits (ec onomic + environmental benefits)

These monetized benefits are based on EPA_s initial analysis using existing informati on and analytical techniques. EPA request s public comment on all data sources and analytical approaches used in estimating the benefits presented in this Chapter.



### 5A. Groundwater Protection Benefits (Avoided Future Cancer Risk s & Groundwater Remediation Costs)

This section estimates the potential future benefits of reduced human cancer risks and avoided groundwater contamination remedi ation costs associated with controlling arsenic from onsite CCR landfills a nd surface impoundments. The esti mates are based on EPA_s risk assessment, which predicts leaching behavior using SPLP and TCLP data. Recent research and damage cases indicate that these leaching tests underestimate risks from dry disposal. 105 Human cancer risks avoided are based on the indivi dual gexcessh lifetime cancer probabilities estimated below. This estimation follows an 8-step method which begins by characterizing the cancer risks a nd expected number of future cancer risks from arsenic releases to groundwater from CCR landfills and surface impoundments in the absence of EPA or state action. It the n proceeds to monetize these cancers using accepted economic practices. Next, a baselin e is established for the ope ration of state regulator y and remedial

105 Recent EPA research demonstrates that CC R can leach significantly more aggressively under different pH conditions potentially present in disposal units. In a 2009 EPA study of 34 electric utility plants, CCR from 19 facilities excee ded at least one of the 40 CFR Toxicity Characteristic reg ulatory values for at least one type of CCR (e.g., fly ash or FGD residue) at the self-g enerated pH of the material (source: EPA Office of Research & Development, gCharact erization of Coal Combustion Residues from Electric Utilities v Leaching and Characterization Data,h EPA- 600/R-09/151. Office of Research and Development, Air Pollut ion Control Division. Research Triangle Park, NC. December 2009). This behavior likely explains the rapid migration of chemical constituents from CCR disposal sites l ike Chesapeake, VA and Gambrills, MD. See also EPA gCharacterization of Mercury- Enriched Coal Combustion Residues from Electric Utilities Using Enhanced Sorbents forMercury Control,h EPA 600/R06/008. Office of Research and Development. Research Triangle Pa rk, NC. January 2006; and EPA gCha racterization of Coal Combust ion Residues from Electric Utilities Using Wet Scrubbers for Multi-Pollutant Control,h EPA/600/R-08/077 . Office of Research and Development, Air Pollution Control D ivision. Research Triangle Park, NC. July 2008.112 programs. Groundwater remediation costs and cancer costs under the baseline and each regulatory option are then estimated. Fin ally, the aggregate benefits from each regulatory opti on (incremental to the baseline) are estimated.

Step 1. Categorize CCR Disposal Units by Type

This step begins with the baseline data on CCR disposal (i.e., dispos al unit liner types, annual CCR disposal tonnages) contain ed in Appendix
F of this RIA for the 495 coal-fired electr ic utility plants. A subt otal 84 of the 495 plants di spose CCR offsite only, and thu s, no liner type is assigned to these facilities in this benefits analysis. 106 Some of the plants have multiple data en tries because they were known to have multiple CCR disposal units on-site. This estimation step assigned only th e riskiest disposal unit type a nd liner type combinations of those listed for each such plant, which resulted in the six combinations displayed below in Exhibit 5A-1

. 107 This hierarchy was based on the 90 th percentile, trivalent arsenic cancer ri sks in the EPA-ORCR 2009 CCR risk report as follows, with those units posing th e greatest risk appea ring first. Appendix K1 presents further information on CCR dispos al unit liner types a nd associated data.

These plants were then further divided by the type of waste di sposed in the units; CCR only or co -managed wastes. The ratio of facilities that only dispose CCR compared to facilities that co-manag e CCR with coal refuse is displayed below in Exhibit 5A-1 . These ratios allowed EPA to model a single number of potential cancer cases as a be st estimate. The data used in the 2009 risk assessment 108 were from a 1995 EPRI survey. Thus, there is some uncertainty regarding the current accuracy of these ratios. To account for this uncertainty, EPA also calculated a bounding range of cancers based on the assumpti on that all facilities would dispose of CCR only, and that all facilities would co-manage CCR with coal refuse only.

Exhibit 5A-1 Categorization of CCR Disposal Unit Types CCR Disposal Unit Type CCR Only Co-managed 1. Unlined Landfill 66% 34% 2. Clay-Lined Landfill 74% 26% 3. Composite-Lined Landfill 53% 47% 4. Unlined Surface Im poundment 32% 68% 5. Clay-Lined Surface Impoundment 48% 52% 6. Composite-Lined Surface Impoundment 71% 29%

106 Note: 83 facilities in Exhibits E2 and E4 of the 2009 risk asse ssment are not assigned WMUs or liner types, 5 fewer than indic ated in this RIA.

107 Multiple CCR disposal units at a single industrial facility will all affect the same surrounding population. To avoid duplica tion of population risks, the analysis used the simplifying assumption that the human health risks will be driven by the riskiest single WMU, when multiple waste management un its are present, but populations around all WMUs are accounted for in Appendix K2 of this RIA.

108 Source: EPA gHuman and Ecologi cal Risk Assessment of Coal Com bustion Wastes,h Office of Resource Conservation and Recovery, De cember 7, 2009.113 Step 2. Determine Potentially Affected Populations of Groundwater Drinkers

With information on the universe of facili ties, WMUs, and liners nearby groundwater-dri nking populations we re assigned. To acc omplish this, EPA first assigned latitude and longitude c oordinates to the 495 sites based on its 2007 eGRID database. Only a few sites wer e not in eGRID, and it is assumed that these sites were c onstructed since the 2007 eGRID data collection. Once latit ude and longitude data wer e assigned, EPA used GIS data to ascertain the location of private groundwater wells within a one-mile radius from the latitude and longitude c oordinates, and then the number of individuals drinking from those wells. 109, 110 The data divide populations into adu lts (18 and older) and children, the same two populations examined in the 2009 risk asse ssment. Once these data were attached to spec ific sites, they were aggregated ba sed on the liner/WMU categories above.

Aggregated data were then scaled to account for the missing population information a nd population growth. Fi rst, the data was scaled up to account for the missing population data in the sites not identified in eGRID. There we re 5 unlined landfills, 1 clay-lined lan dfill, and 7 composite-lined landfills that had onsite disposal but no eGRI D data from which to determin e the population. All surface impou ndments had the necessary eGRID data. To account for th ese individuals, EPA made the assumption th at these plants had populations similar to the plants EPA had data for, since EPA ha d no data to suggest otherwise. 111 Thus, the population was scaled up by a scaling factor eq ual to the total number of plants divided by the number of plan ts for which EPA had population data as follows:

1) Unlined Landfills = 76/71 (~1.07) 2) Clay-Lined Landfills = 28/27 (~1.04) 3) Composite-Lined Landfills = 150/143 (~1.05)

The populations were then scaled up to curre nt population levels based on Census da ta, resulting in a sc aling factor of 1.093.

Once these preliminary population estimates we re produced, it was also necessary to acc ount for the size of the waste managemen t unit. In the 2009 risk assessment, WMUs were assumed to be square as a require ment of the model. Using the same assumption here, the actual 1-mile radius around the square area of a WMU coul d be estimated by scaling the population dens ity of the original 1-mile radius up to the area 1-mile around a square WMU of average size. This led to scaling factors of 1.81 and 2.56 for landfills and surface impoundments, resp ectively. Further discussion of this area -based scaling can be found in Appendix K2

.
In addition to accounting for the increased ar ea in the 1-mile radius, EPA assumed that half of the receptors would be up-gradi ent and half would be down-gradient of the WMU. For th e purposes of this assessment, populations we re assumed to be equally distributed wit hin the

109 This data was developed through the use of the 2000 census block data in combination with the 1990 census drinking water sourc e data. For a further discussion of population development, see Appendix K3 of this RIA.

110 Municipal water systems using groundwater often rely on deeper aquifers, in which case they would be less susceptible to conta mination from CCR releases. Therefore, these systems were not included in the 2009 Risk Assessment or in this analysis. However, exposure through this pathway is pos sible, which means th at these population estimates could underestimate the population that is exposed to these wastes.

111 EPA does not account for CCR disposed off-site as in the Gambrills MD and Chesapeake VA damage cases.114 square whose center was the facility WMU. This is illustrated in Exhibit 5A-2 below. It was also assumed that only down-gradient populations would be affected (re d rectangle), and no up-gr adient populations would be affecte d. This was accounted for by div iding the onemile population by two. The issue of surf ace waterbodies is addressed below. Appendix K3 provides a detailed explanation of the derivation of the exposed population by plant. Over all, 715,855 individuals are potentially expo sed to CCR. Of this total, 34,533 use pr ivate drinking water wells.

W M U Groundwater Flow Potentially

Exposed Population Unexposed Population Exhibit 5A-2 Conceptual Model for Expose d Well-Drinking Population

1-mile

Surface Waterbody Contaminant Plume115 Step 3. Apply EPA-ORCR 2009 Arse nic Groundwater Risk Results

This step involved determining the most appropriate individual risk factors for use in estimatin g arsenic cancer population risk for the estimated populations residing near the CCR di sposal sites. There are two sources of info rmation on individual risks associated with ars enic exposure:

IRIS 1998: Based on skin cancer incidence, as data on skin cancer risks were availabl e prior to the availa bility of quantitativ e data for internal cancers. Skin cancer is a hea lth endpoint associated with lower fatality risk than th e internal cancers induced by arsenic. The skin cancer base d risk assessments no longer represent the curre nt state of the science for health risk assessment for arsenic. This RIA presents these estimates be low for informational purposes only. This source describes a distribution of risks to a hypothe tical individual who dr inks water from a well located at a randomly selected point one mile down-gradient from the waste management unit edge. The probabilistic risk estimate s were gsite-basedh (that is, not sitespecific, but based roughly on 181 actual coal-fired power plants that were ope rating in 1995). EPA has only the gpeakh risks (i.e., those corresponding ge nerally to the highest groundwat er concentrations that are m odeled to occur) available for analysis because computer modeling of peak risks contain gigabytes worth of information, and while EPA attempted to keep track of risks up to 10,000 years of the computer model r un, the data in these large files became corrupted and are now unusable. However, below in this RIA EPA does extrapolate population risks in other years. These other years are the years between the cessation of operation of the landfill, or the years after the beginning of operation of the surface impoundment, leading up to the years in which the gpeak h risks occur at half of the modeled facilities.

NRC 2001: The latest science on health risks associated with arsenic exposure is fr om the National Research Council (NRC) repor t gArsenic in Drinki ng Water: 2001 Updateh 112 which reviewed the available toxico logical, epidemiological, and risk assessment literature on the health effect s of inorganic arsenic, building upon the NRC_s prior report, gArsenic in Drinking Waterh (1999). The 2001 report, developed by an eminent committ ee of scientists with expertise in arsenic toxicology and risk assessment provides a scie ntifically sound and tran sparent assessment of cancer risk s from inorganic arsenic. EPA_s Science Advisory Board endorses these estimates and the IRIS estimates are currently being upda ted to reflect this latest science. Therefore, while IRIS estimate s exist, because the more recent NRC scient ific information is available, this RIA relies on the NRC information for analysis of the cancer risks a ssociated with CCR. Appendix K4 provides more detailed information on how this NRC research was used.

For the purposes of initially estimating the expected number of cancers (i.e., cancer risks) in St eps 3 and 4, this RIA applied risk results obtained with the latest (i.e., 1998) IRIS va lue. However, in Step 5 below, the 2001 NRC research was used to update these can cer estimates. It should be noted that the 1998 IRIS skin cancer value does not examine bladder and lung cancer in cidence, and therefore is no t a substitute for the 2001 NRC cancer risk research in this area. To the extent that the skin cancers estimated by the IRIS value are not accoun ted for, this RIA may underestimate total cancer incidence.

112 National Research Council, Arsenic in Drinking Water: 2001 Update , National Academy Press, 2001 at http://www.nap.edu/openbook.php?isbn=0309076293116 This RIA extracted only those results from the EPA 2009 risk assessment to either re present (a) conventional CCR (i.e., fly ash , bottom ash, boiler slag, and flue gas desulphurization waste managed in the landfil l or impoundment without mixi ng with other materials), o r (b) CCR comanaged with coal refuse. 113 Of these results, only those for trivalent arsenic were used. 114 For the primary analysis, it was assumed that all arsenic was speciated in this manner. As noted in the EPA s ource data, arsenic III and arsenic V cancer risk results for unlin ed surface impoundments that co-dispose CCR with coal refuse were not statistically different at the 90 th percentile, and these risks are likely to drive the population risk estimates. A sensitivity an alysis was conducted where all arsenic was a ssumed to be speciated in the arsenic V state. This analysis is presented in Appendix K5 . Finally, risks for both adult and child receptors we re included so that each group would be accurately represented. Once all of th ese data were collected they were so rted by CCR disposal unit and liner type.

This analysis reflects possible groundwater and surface water interactions that coul d affect the population risk estimates. In situations in which the modeled distance to a surface water body was less than the mode led distance to a drinking water well EPA assumed that the g roundwater plume is fully intercepted by a surface waterbody. 115 To this end, EPA extracted the model inputs for the distance to groundwater wells and the distance to surface waterbodies used in the EPA s ource, randomly selected from input distributions. 116 These two were then compared using a logical test in Microsoft Excel. This test returned a 0 if the surface waterb ody was closer than the drinking water well and 1 if it was not. Thus, a 1 was a positive indi cation that the contaminant plume in that model run reached the groundwater well.

Finally, EPA extracted the exposure durations used in each model run from the EPA-OR CR 2009 CCR risk report to capture the frac tion of the individual_s lifetime risk that was experienced in a one-yea r period. EPA accomplished this by matching the probabilistic expo sure duration inputs, to their corresponding age category. Then, each probabilistic run was sorted to return the exposure duration of the ad ult and child age category. These Monte Carlo data constituted a weighted approach for estimating individual human cancer risks. Population ris k is typically calculated by multiplying risk results by the affected population. Since there were thousands of equally valid model iteration s, this RIA assigned each of these risks an equal wei ght in its final population risks by using th e average of these individual risks.

Individual risk estimation took in to account the fact that the contaminant plumes might be intercepted by surface waterbodies b y multiplying by either 0 or 1 as identified above. Each of these risks was then divided by exposure du ration to estimate the yearly cancer risk

. 117 Once all of these risks were calculated for a given WMU/lin er type they were summed and divided by the number of iterations to give the ave rage one year increment of risk for that WMU/liner type at the peak risk. Thus, the final equati on that was used for calculating average ris ks can be stated as:

113 Fluidized Bed Combustion waste results were not deemed appropriate for use for the reasons discussed in EPA gHuman and Ecologi cal Risk Assessment of Coal Combustion Wastes,h Office of Resource Conservation & Recovery, August 2009.

114 A 1981 Oak Ridge National Laboratory study states gAs (III) is likely to be the predominant arsenic species in ash pore water and groundwater.h Source: Turner, Ralph R. gOxidation State of Arseni c in Coal Ash Leachate,h Environmental Science & Technology , Vol.15, Number 9, September 2001.

115 Full interception will not occur in instances where the waterbod y is shallow, the waterbody is man-made, or the facility is or iented perpendicular to the waterbody. This simplifying assumption serves to minimize the influence of the model runs in which interception may have occurred, but was not reflected in EPA gHuman and Ecological Risk Assessment of Coal Combustion Wastes,h Office of Resource Conservation & Recovery, August 2009.

116 For further discussion of how these distributions were developed, see Appendix C of EPA gHuman and Ecological Risk Assessment of Coal Combustion Wastesg Office of Resource Conservation and Recovery, Washington, DC, August 2009.

117 For further discussion of cancer risks and exposure durations, see Appendix K4 of this RIA.117 N EDn WELLREACH RISKn

iRISK 

## ¦ u

Where: iRISK = Average increment of lifetim e cancer risk from a 1-year exposure RISKn = Risk result for the nth model run WELLREACH = 0 if plume is inter cepted by a surface water body, 1 otherwise EDn = Exposure duration for the nth model run n = Iteration number N = Number of iterations

The results are presented in Exhibit 5A-3 below. For each, the results are presented for bot h adults and children under each of the WMU/liner scenarios. For full distributions of individual risks befo re averaging, see Appendix K6 v Distributions.

Exhibit 5A-3 Peak One Year Risks For CCR Cancer
Conventional CCR CCR Co-managed With Coal Refuse Liner - Receptor Landfills Impoundments Landfills Impoundments
Unlined - Adult 6E-06 4E-05 5E-06 2E-04
Unlined - Child 1E-05 1E-04 1E-05 4E-04 Clay-Lined - Adult 3E-06 3E-05 2E-06 1E-04 Clay-Lined - Child 7E-06 6E-05 4E-06 2E-04

Step 4. Extrapolate Annual Can cer Risks from Peak Cancer Risks

The peak risks that were calculated occur well after cancers can first materialize. Thus, constraining the benefits to only th e peak population risks significantly underestimates total cancers avoided. To compensate for this shortf all, this RIA formulated an approach il lustrated in Exhibit 5A-4 below. The blue parabolic curve for popula tion risk is based on the well concentratio ns over time in the results. While EPA cannot reconstruct the exact curve due to data availability issues, a parabolic curve represents groundw ater contamination. Fr om this shape it is clear that the peak population risks only capture a fraction of total population risks. Using an assumpti on of linear increase s to the peak and linear decreases from the peak, produced the si mplified risk profile seen as a red line in Exhibit 5A-4

.118 t = time to peak risk Exhibit 5A-4 – Population Risk Method

Time (years) t

t0 = WMU built t t0 Rt

Rt = peak population risk = Actual Risk Profile = Simplified Risk Profile Population Risks At Peak One Year Exposure Only119 The constant slope allowed estimation of the population risks fr om each year_s exposure by assembling the model iteration times to peak. 118 Dividing peak risks (y-value) by the time to peak (x-value), the slope of the time line was determined for each WMU/liner type as displayed in Exhibit 5A-5 below.

Exhibit 5A-5 Human Cancer Time Slope Factors For CCR Slopes For Conventional CCR Slopes For CCR Co-managed With Coal Refuse Liner - Receptor Landfills Impoundments Landfills Impoundments

Unlined - Adult 1E-08 6E-07 8E-09 3E-06
Unlined - Child 2E-08 1E-06 2E-08 6E-06 Clay-Lined - Adult 5E-09 4E-07 3E-09 1E-06 Clay-Lined - Child 1E-08 7E-07 6E-09 3E-06

Multiplying this slope by the number of years elapsed yields the yearly increment of individual risk for that year. Multiplyin g this average incremental individual risk by th e population exposed in each year 119 EPA estimated the number of cancer s in each year. While this underestimates cancer incidence by the difference between the blue and red profiles it is the best es timate based on currently avail able data.

As displayed in Exhibit 5A-6 below, this approach results in an estimate between 45 and 196 potential ca ncer cases over 75 years 120 as a result of arsenic consumed through contaminated groundwater using EPA_s 1995 cancer slope factor (1.5 mg/kg/d -1 ) for arsenic based on skin cancers. Using the ratios of conventional CCR co-managed w ith coal refuse a best estimate within this range is 145 cancers

.

118 Since these iterations were performed in later model runs they could not be tied to the specific model iterations used above. 67% of the model runs had the nearest groundwater well occurring beyond the neares t surface waterbody. Since the longer arriva l times occur with longer travel dista nces, and these iterations tended to be the iterations that were intercepted, assumed that the 33% of model r uns that were not intercepted are also the 33% of model runs w ith the shortest arrival times (i.e., shortest distances). Taking the midpoint of these arrival times yielded the 16.5 th percentile.

119 This RIA inflated the future population each year based on the future projections made by the US Census Bureau. From that poi nt on, this RIA assumed a constant annual growth rate equal to the growth rate in year 2050.

120 Seventy-five years were used for the analysis based on the 78 year time to peak period, less tw o years states are allowed to a dopt the rule_s provisions, and less an additional year for installing groundwater monitoring. Seventy- eight years are the time at which the risks for typical unlined and clay-lined surface impoundments that are not intercepted by surface water will peak. Cancers occurring after y ear 78, though potentially si gnificant, are unlikely to p lay a significant role when monetized because under a 3% discount rate, benefits fall to ten percent of their value at year 78, and at a 7% discount rate, benefits fall to 0 .5% of their value at year 78. These future cancers will be further reduced by state regulations, detection of c ontamination, and a general trend away from wet handling.120 Exhibit 5A-6 Potential Future Human Cancer Cases from the Disposal of CCR Based on Arseni c Cancer-Slope Factor from EPA/IRIS
Disposal of Conventional CCR Disposal of CCR Co-Managed with Coal Refuse

WMU Adult Child Totals Adult Child Totals

Unlined Landfills 0.1 0.1 0.2 0.1 0.1 0.2
Clay-Lined Landfills 0.1 0.1 0.2 0.0 0.0 0.0
Unlined Surface Impoundments 20.1 16.3 36.4 98.1 67.6 166.7
Clay-Lined Surface Impoundments 4.8 3.5 8. 3 17.6 12.6 309.2

Totals 25.1 20.0 45 115.8 80.3 196

Step 5. Estimate Arsenic Cancer Risks Using Recent NRC Science for Arsenic

Based on the NRC data source, lifetime exposure to 10 ug/L arseni c in drinking water would lead to 23 excess male bladder cance rs and 14 excess male lung cancers per 10,000 people. U nder the exposure factor assumptions used by the NRC the equivalent cancer slope factor (CSF) is 26 mg/kg/d -1 . For details of how this cancer slope factor was calculated, see Appendix K4 v Cancer Calculations. 121 Exhibit 5A-7 below displays the population risk estimates for CCR disposal base on the NRC source. 122 Using the NRC (2001) cance r slope factor one would expect between approximately 778 and 3,392 cancer cases over 75 ye ars as a result of arsenic consumed through contaminated grou ndwater. Using the ratios of conventional CCR co-man aged with coal refuse produces a best estimate within this range of 2,509 cancers

.

Exhibit 5A-7 Potential Future Human Cancer Cases from CCR Dispos al Based on Arsenic Cancer-Slope Factor from NRC
Disposal of Conventional CCR Disposal of CCR Co-Managed with Coal Refuse

WMU Adult Child Totals Adult Child Totals

Unlined Landfills 2 2 4 1 1 2
Clay-Lined Landfills 1 1 2 1 1 2
Unlined Surface Impoundments 348 281 629 1,696 1,169 2,865
Clay-Lined Surface Impoundmen ts 82 61 144 305 218 523

Totals 433 345 778 2,003 1,389 3,392

121 EPA is currently in the process of revisi ng the arsenic cancer slope factor in EPA_ s Integrated Risk Info rmation System (IRIS)

. 122 EPA also conducted a sensitivity analysis assuming the female cancer slope factor in Appendix K5 of this RIA.121 Step 6. Monetize Future Avoided Cancer Risk Benefits
Reflecting the best science available, EPA used a point es timate of cancer cases avoided to monetize cancer risks. Appendix K4 provides further explanation as to why the NRC scien ce is considered more appropriate than th e older skin cancer research that the curre nt IRIS value was derived from. Because EPA has greater confidence in the NRC estimates, it chose to use th e 2,509 cancers calculated above as the best estimate. EPA also used the NRC ratio of 23 male bladder can cers to 14 male lung cancers to estim ate how many of each type wer e likely to occur in each year. That is, 62%, or 1,556 cancers, are assumed to be bladder cancers and 38% or 953 are assumed to be lung ca ncers. Appendix K7 shows the best estimate number of lung and bl adder cancers in each year that was used in the remain ing portions of this analys is.

Since cancers are not all fatal, the next step was to estimate the numbe r of cancers that are fatal and non-fatal. This was do ne separately for each type of cancer using 5-year survival rates from the EPA-ORCR 2009 CCR risk report. The 5-year survival rate used for blad der cancer is 82% and the 5-year survival rate used for lung cancer is 14%. Thus, 1,276 (82%) of bladder cancers are non-fatal and 280 (18%) are fatal. For lung cancer, 133 (14%) are non-fatal and 820 (86 %) are fatal. Again, these cancers are spread over th e 75 years of the analysi s. In order to monetize avoided cancer risks, this RIA applie d the value of a statistical life (VSL) plus the cost of terminal cancer treatmen ts displayed in Exhibit 5A-8 below. To monetize avoided non-fatal cancer risks, this RIA used an estimate from Magat et al. (1996). 123 This study shows that a typical individual_s assessment of a non-fata l lymphoma risk reduction was the equivalent of 58.3% of a fatal lymphoma risk r eduction. 124 Therefore, this RIA assumed individuals value non-fatal bladder and lung cancer risk reduction in a similar manner.

Exhibit 5A-8 Unitized Monetary Valu es for Human Cancer Risks Applied in this RIA Monetized Value 2008$ Fatal cancers: value of statistical life (VSL)* $8,800,000
Non-fatal cancers: 58.3% of VSL* $5,130,400
Medical costs associated with fatal bladder can cer** $149,863
Medical costs associated with fatal lung cancer** $87,703
Notes: *Median VSL of $4.65 million (1997$) from Exhibit 7-3 (page 89) of EPA gGuidelines for Preparing Economic Analyses,h EPA 240- R-00-003, Sept 2000; converted for this RIA to 2008 dollars usin g the Consumer Price Index. In addition, projections of benefi ts in future years are subject to income elasticity adjustments. Thes e represent changes in valuation in relation to changes in real income. For example, if, for every 1% increase in real income, a partic ular consumer_s willingness-to-p ay for a particular item increas es by 1%, this would be represented by an income elasticity of 1.0. For most items, income elasticity values are actually less than 1, i ndicating that valuation of most items does not increase as fast as real in come levels. To do so, applied the change in Gross Domestic P roduct per-capita between the original dollar year of the estimates and 2008, and an income elasticity of 0.5 based on estimates from Viscusi, W. K. and Aldy, J. E. gThe Value of a Statistical Life: A Criti cal Review of Market Estimates throughout the World,h Journal of Risk and Uncertainty , Vol.27, 2003, pp. 15v76. ** These costs reflect the inpatient hospital stays, skilled nursin g facility stays, home health agency charges, physicians' se rvices, and outpatient and other medical services - in other words the treatment and maintenance costs. Costs are assumed to occur during initial

123 Magat, Wesley A., V. Kip Viscusi and Joel Huber "A Refere nce Lottery Metric for Valuing Health," Management Science , Vol.42, Issue 8, 1996, pp.1118 - 1130.

124 EPA acknowledges that alternative approaches to valuing non-fata l cancers are available. One such alternative is presented in Appendix K5 of this RIA.122 Exhibit 5A-8 Unitized Monetary Valu es for Human Cancer Risks Applied in this RIA treatment, maintenance care between initial and terminal treatment and terminal treatment during the final six months prior to death:

x Bladder cancer costs are based on surviv al and death rates each year for 20 y ears which captures most deaths from bladder cancer among those who ar e diagnosed with the disease.

x Lung cancer costs are based on a 10 year time horizon during which most deaths are assumed to occur. The original figures in the 2001 EPA report are in 1996 dollars (source: EPA gThe Cost of Illness Handbook,h Office of Pollutio n Prevention & Toxics, October 2001). These costs are updated for this RIA to 2008 dollars using the Medical Care Component of t he Consumer Price Index.

These values are further adjusted for ce ssation lag and income as described in Appendix K8 . EPA used the cessation data of bladder cancers from arsenic in Chen and Gibb (2003) 125 to construct a Weibull curve approximating the lag time between reduced arsenic exposure and reduced cancer outcomes. Because this lag will reduce willingness to pay compared to an immediate risk reduction, the value of reduced statistical cancers are 83% and 67% of what they would be using an unadjusted VSL (a t a 3% and 7% discoun t rate, respectively.) This is described in more detail in Appendix K8 . For income, EPA projected per capita GDP, and used this combined with an income elasticity of 0.5 income elasticity of 0.5 from Viscusi and Aldy (2003) to estimate the growth in VSL until the expo sure year. There has been ec onomic debate over whether VSL should be adjusted to the year of exposure or the year of the cancer. Howeve r, typically, it is not possible to know when the exposure occurred. Because of the model used here, this RIA applied the VSL adjustment at the time of exposure. The full tabl e of VSL adjustment factors, as well as their deri vation, is presented in more detail in Appendix K8

.
Applying these nominal dollar values to th e number of fatal and non-fatal bladder and lung cancers in each year, a current year value for avoiding cancer risk was calculated for each of th e 75 years. These values can be seen in Appendix K7 . The present value (PV) of these values is approximately $4,696 million at a 3% discount rate and $885 million at a 7% di scount rate. This would reflect the va lue of avoiding future cancer risks assuming that no steps we re taken to prevent contamination and the resulting cancers. However, as discusse d below, this is not realistic under baseline state regulatory controls.

Step 7. Account for Groundwater Remediatio n under the Baseline and Regulatory Options

The results above assume that arsenic is released from exis ting impoundments and landfills, without any controls (beyond the li ners taken into account in the model). The benefits of re gulatory options would be reflected by lower rates of cancer, resulting from the rule _s controls (including ground-water monitoring, permitting, corrective action, pha se-out of surface impoundments, financial assurance, etc. ). 126 The rule will also have the benefits of reducing or eliminating groundwater remediation cost, because groun dwater releases are eliminate d through

125 Source: Chen, C.W. & Gibb, H. gProcedures for Calculating Cessation Lag.h Regulatory Toxicology and Pharmacology,h Vol.38, Iss ue 2, 2003, pp.:157-65.

126 The two Subtitle D Options evaluated were: (1) Subtitle D Ä regulation of landfills and surface impoundments, with liners re quired for existing and new surface impoundments, and new landfills and (2) Subtitle gD Primeh Ä regul ation of landfills and surface impoundmen ts, with liners req uired only for new surface impoundments and landfills.123 controls like surface-impoundment phase-out, or reduced because releases are caught ear lier. These benefits, and how they relat e, are described in the section below.

First, even in the absence of federal re gulations, CCR disposal units wi ll not leach and cause cancers in all cases estimated t hrough the evaluation above. Even without federal re gulation, there will be facilities that discover contam ination and clean the contamin ation up before cancers occur, either due to state regulati ons or good practice. Where exposures are identified, this RIA assumed that the pat hway will be cut off (e.g., through provision of alternative wate r sources). Even facili ties that fail to prevent contamination may detect tha t contamination and clean it up at a later time, although after e xposure has occurred. This Step of the estimation attempted to account for these practices.

To estimate the different speed and cost of groundwater remedi ation likely under the baseline and under the three regulatory sc enarios (i.e., Subtitle C, Subtitle D and Subtitle D Prime), this RIA began by examining the differences across states in groundwater monitori ng requirements pertaining to CCR disposal units , and focused on groundwater monitoring re quirements because adequate monitoring i s needed to determine whether a release has occurred. Th is RIA assumes that, where releases of c oncern have been identified, and particula rly where people may be at risk, drinking water pathways will be cut off and alternative drinking water wi ll be provided. Then calculate d the percentage of CCR disposed by each state, and noted which of thr ee levels of groundwater m onitoring were required:

1. No monitoring requirements
2. Monitoring requirements for only future newly constructed CCR disposal units
3. Monitoring requirements for both future new and existing CCR disposal units

Then EPA tracked the percentage of total waste that was discarde d by facilities in states requiri ng each of these three monitor ing scenarios. Exhibit 5A-9 below presents these percentages for states requiring at least some monitoring (categories 2 a nd 3 above) and states requiring monitoring at exiting facil ities (category 3 above). The firs t value in the table, 91%, is th e percentage of CCR discarded in landfills that impose some form of monitoring requirements, whether for new landfills only, or for both new and existing landfills. 62% is the perce nt of CCR discarded in landfills that impose monitoring requirements on bot h new and existing CCR disposal units (a subset of the 91%). 127 Percentages are also provided for CCR that are managed in surface impoundments. Appendix K9 provides these data for each individual state.

127 Some states may require monitoring only for off-site units; ho wever, in the absence of a speci fic breakdown, EPA made the assu mption that on-site units would be monitored in all states that require monitoring.124 Exhibit 5A-9 State Government Groundwat er Monitoring Requirements Assumed in this RIA Landfills Surface Impoundments Any Monitoring

Requirements (categories 2&3) Required at New and Existing Units

(category 3) Any Monitoring Requirements (categories 2&3) Required at New and Existing Units

(category 3) Percent of Facilities 91% 62% 48% 12%

These percentages helped to determine when releases will be id entified, and the likely cost of cleanups or other remedies, when releases are identified, under the baseline and three regulatory scenarios. Since all but 4 of the 2,509 can cers projected above result fro m surface impoundments, only surface impoundment monitoring data were used in the calculations. 128 For the baseline scenario, it was assumed that states with the highest level of monito ring requirements (those requiring groundwater monitoring at both new and existing units ) would generally find groundwater contamination re latively early and would requ ire preventive measures that would avoid cancers (e.g., intercept the plume and/or put residents on municipal or bottled water). Thus , 12% of contamination that could occur would have already been detected, and the resulting cancers prevented. To the extent that cleanups and/or alternative water are re quired, that was considered p art of the baseline.

To model the Subtitle D option, EPA assumed that states with gr oundwater monitoring requirements at new units, or with some cov erage of the units in question, would upgrade th eir existing programs to provide fuller coverage v because they alrea dy have a regulatory in frastructure v but other states with no program would not. While states that do not currently regulate units would not change their practices simply because EPA issued national rules, EPA recognizes th at facilities in these latter states will to a certain extent comply, to avoid citi zens_ suits. However, EPA_s and states_ experience in implementing the RCRA program demo nstrates that self-implementi ng ground-water monitoring progr ams are of limited reliability. Given these factors, the percentage of waste disposed of in states with some le vel of groundwater moni toring programs is a reasonable estimate of benefits for the s ubtitle D approach. Under these assumptions , contamination in states with monitorin g requirements for only new units, as well as contamination in states with monitoring requirements fo r new and existing units would be detecte d promptly. This leads to 48% of surface impoundment groundwater contamination being detected before extensive damage has occurred, and the refore 48% of cancers being prevented.

Since the Subtitle gD Primeh option does not require the retrofitting of existing units, unlined surface impoundments would rem ain a continuing source of release. However, the presence of a new national rule accompanied by EPA support would lead at least some states to make such updates. Since the potential risks will fall somewhere betw een the Subtitle D option an d the baseline, the midpoint between baseline and the Subtitle D option (30%) was chosen as a best estimate. This leads to 30% of contamination being immediately d etected, and thus 30% of cancers being prevented.

128 Note, however, that considerable evidence indicates that releases from dry disposal can present significant risk as well, as d emonstrated by EPA research on CCR leach rates at different pHs and the damage cases.125 Finally, for Subtitle C, there would be fe deral oversight of the groundwater monitoring requirement, and therefore this RIA ass umes 100% of facilities would have contamination detected early. L ooking forward, this would eff ectively prevent all cancers. 129 In addition, the technical standards of the subtitle C rule would largely prevent future releases because surface impoundments would be phased-out, and be cause new landfills would require composite liners. Similarly, closure requirements would largel y prevent releases af ter closure of both types of units.

Where releases of arsenic from disposal units occur in the futu re, they will be detected prom ptly after they occur under the pr oposed option, as well as under the other options where good monitoring programs are in place. In these cases, ther e may be response costs, but no cancer risks. On the other hand, if facilities do not have adequate detection systems in place (and other adequate controls, e.g., liners, ad equate closure, etc.), then detection will be delayed. This RIA assumes that releases will eventually be discovered, but that detection may be on a d elayed basis. To quantify this assumed that contamination would be discovered c onsistently until it was all discovered. Since the rate of disco very is unpredictable, further assumed detection would be at a constant rate, reaching 100% detection by the final year of the analysis

. 130 These discoveries were assumed not to start for six years because th e first percentile of time duration until peak risks for unlined surface impoundments occurred. Restated, this prof ile assumes that facilities in states that require groundwater monitoring for existi ng units would generally find contamination in the future soon after it occurre d, reducing response costs, and pr eventing cancer risks. But w here monitoring and other controls were not ad equate, releases would potentia lly go undetected for lengthy period s, causing cancers until the c ontamination was eventually detected and those residents sw itched to municipal or bottled drinking wate r. In addition, response costs would be significantly increased. The present value of avoiding all of the risks in the baseline case is the upper-bound on benef its, and this upper bound is reduced by detection and groundwater remediation as desc ribed in this section. The risk reduction benefit for each regulatory option is t he difference between baseline risks and remaining risks under that option. These benefits, accounting for the detection and remediation, ar e presented in Exhibit 5A-10 below. Baseline expected cancer risks are accounting for detec tion and remediation, compared to without taking these factor into account. Further discussion of the cancer profile can be found in Appendix K7

.
This RIA projects a trend towards decreased management of CCR in surface impoundments. Facilities with surface impoundments ha ve been slowly moving from wet handling in impoundment s to dry handling in landfills or to bene ficial uses. While this trend could aff ect the profile discussed above, it is unlikely to have a significant effect on risks for two reasons . First, surface impoundments, to the ext ent they are closed, are typically closed with waste in place. Thus, they are likely to continue to le ach beyond the 75-year period modeled in the 2009 risk assessment; this is particularly true in situations where they are not lined (which are overwh elmingly the case) and where they are located in states without strong regulation. In the la tter case, closures are likely to be in adequate, leading to continued infiltration. Second, the releases that occurred before the surface impoundments are closed will continue to migrate un til they reach the groundwater wells or unt il they are intercepted by a surface waterbody (again partic ularly in states without strong programs) . Given the relatively very large siz e of the CCR impoundments, and the presence of a hydraulic head at least before closure, these histor ic releases have th e potential to be si gnificant. Given these considerations, the closure of surface impoundments in st ates without regulations (e.g., corrective action, groundwater m onitoring, etc.) would behave very similarly to active surface impoundments in terms of their risks to human health and the environment. For th is reason, the regulatory oversight in the opti ons above was not modified fo r closed CCR disposal units.

129 Cancers from historic releases would not be affected, but the releases would be promptly identified and future exposures avoid ed.

130 Some releases are likely to go entirely u ndetected in the absence of groundwater monitoring and other controls. However, to p ut a reasonable limit around the analysis, this RIA assumed 100% detection.126 Exhibit 5A-10 Present Value of Avoided Human Cancer Risks Associated with CCR Disposal ($millions present value over 50-years)
Discount rate Subtitle C Subtitle D Subtitle D_ @ 3% $1,825 $750 $375 @ 7% $504 $207 $104

The other major cost associated with groundwater contamination is that of remediation or other re sponse. To estimate that cost , EPA began by estimating the number of coal-fired electric utility plants that would require res ponses under various state environmental prog rams, based on the 2009 risk assessment. In any particular situation, a state could require remediation of a site involving potential drinkin g water to 10 -4 , 10 -5

, or 10 -6 levels. In addition, states may choose to require groundwater remedi ation for groundwater that is not a likely drinking water source, because of ecological concerns. Exhibit 5A-11 below shows the number of facilities potential ly requiring cleanup. Since each estimate is equally acceptable under current state program s, the average is believed to be a best estimate for how many electric utility pl ants will ultimately need groundwater remediation so as not to ove restimate the number of remediation events.

Exhibit 5A-11 Proportion of CCR Sites Requiring Reme diation Based on State Cleanup Levels Clean All Groundwater Clean Only Drinkable Groundwater State Cleanup Levels 10 -4 10 -5 10 -6 10 -4 10 -5 10 -6 Average

Total LF 22 50 72 7 16 24 32 Total SI 93 132 150 31 44 50 83

These plant counts are based on th e probabilistic model itera tions from the 2009 risk assessment which were used to estimate wh at fraction of sites would leach at above various cl ean up levels. Typically, solid waste cleanups can be conducted at either 10 -4 , 10 -5 , or 10 -6 individual cancer risk levels. Exhibit 5A-12 uses the PERCENTRANK function in Excel to estimate wh at percent of risk results fall at or below each clean up level. For exampl e, in the first cell of Exhibit 5A-12 , the 78% means that 10 -4 is higher than 78% of th e probabilistic results for unlined landfills with conventional ash.

UL = Unlined CL = Clay-Lined A = Conventionally Managed Ash C = Co-managed Ash LF = Landfill SI = Surface Impoundment127 Exhibit 5A-12 Percentile of Cleanup Levels in the EPA-ORCR 2009 CCR Risk Study

Clean Up Level UL A
LF CL A
LF UL C
LF CL C
LF UL A SI CL A SI UL C SI CL C SI
1.00E-04 78% 83% 74% 85% 46% 59% 30% 43%
1.00E-05 55% 59% 42% 57% 15% 24% 12% 21%
1.00E-06 36% 35% 18% 28% 5% 7% 3% 8%

Model results equal to or above these per centiles would require a state or federal cleanup. In ot her words, the percentage of sites above the cleanup level displayed in Exhibit 5A-13 can be derived by subtra cting the percents in Exhibit 5A-12 above from 100%. However, while states may require remediation of all groundwat er, whether or not it is potable, they may also choose not to on a site by site basis. As discussed in the EPA-ORCR 2009 CCR risk report, it is estimated that two-th irds of sites are located closer to a surface waterbody than t o the nearest groundwater well. Therefore, sites located on surface waterbodies ma y not be cleaned in some states. This 2/3 decrease is acc ounted for in the second set of values in Exhibit 5A-13

.

Exhibit 5A-13 Percent of Electric Utility Plants Requiring Future Groundwater Remediation

Clean Up Level UL A
LF CL A
LF UL C
LF CL C
LF UL A SI CL A SI UL C SI CL C SI Assuming All Groundwater is Remediated
1.00E-04 22% 17% 26% 15% 54% 41% 70% 58%
1.00E-05 45% 41% 58% 43% 85% 76% 89% 79%
1.00E-06 65% 65% 82% 72% 96% 93% 97% 93% Assuming Only Potable Groun dwater is Remediated
1.00E-04 7% 6% 8% 5% 18% 13% 23% 19%
1.00E-05 15% 14% 19% 14% 28% 25% 29% 26%
1.00E-06 21% 21% 27% 24% 32% 31% 32% 31%

The number of utility plants with each type of CCR disposal, lin er type, and management combin ation was calculated by taking th e Appendix
F plant data from this RIA and combining it w ith the conventional versus co-managed rates.128 Exhibit 5A-14 Estimated Number of Electric Utility Pl ants by CCR Disposal Unit Type
UL A

LF CL A
LF UL C
LF CL C
LF UL A SI CL A SI UL C SI CL C SI
50 21 26 7 31 28 68 31

Multiplying the number of facilities in each category from Exhibit 5A-14 above by the percent of facili ties requiring remediation in Exhibit 5A-13 above yields the estimated number of facilities that would lead to state or federal clean ups in Exhibit 5A-15 below. These estimates of the number of facilities requiring cleanup does not account for any cleanups resulting from other constituents exceeding a haza rd quotient of 1. Thus, this estimate may under-estimat e the total number of cleanups.

Exhibit 5A-15 Number of Electric Utility Plants Requi ring Future Groundwater Remediation

Clean Up Level UL A
LF CL A
LF UL C
LF CL C
LF UL A SI CL A SI UL C SI CL C SI Assuming All Groundwater Is Remediated

1.00E-04 11 4 7 1 17 11 47 18
1.00E-05 23 9 15 3 26 21 60 24
1.00E-06 32 14 21 5 30 26 66 29 Assuming Only Potable Groundwater Is Remediated

1.00E-04 4 1 2 0 6 4 16 6
1.00E-05 7 3 5 1 9 7 20 8
1.00E-06 11 5 7 2 10 9 22 9

With the number of units requiring remediation, EPA estimated the cost of groundwater remediation under the baseline and each r egulatory option presented above. Groundwater remediatio n costs were estimated in two steps. Fi rst, EPA assumed contamination that migh t occur at sites in states with more stringent monitoring requirements, w ould be discovered promptly. This suggests that there is likely to be less remediation required than at the typical s ite. Thus, EPA assigned these sites the 25 th percentile remediati on costs displayed in Exhibit 5A-16 below as the midpoint of the bottom half of costs. These future remediation events we re spread evenly acro ss all 75 years of t he analysis.129 Exhibit 5A-16 Per-Site Groundwater Contamination Remediation Costs* Cost element category 25 th percentile gearly costsh 75 th percentile glater costsh Capital Costs $6,075,900 $21,195,000 Annual O&M $98,910 $1,413,000 O&M at 3% discount rate** $1,978,242 $28,260,605 O&M at 7% discount rate** $1,239,522 $17,707,453 Total cost at 3% $8,054,142 $49,455,605 Total cost at 7% $7,315,422 $38,902,453
Notes: *Cost data from Exhibits 3 and 4 in EPA gCost Analyses for Selected Groundwater Cleanup Projects: Pump and Treat Systems and Permeable Reactive Barriers,h Office of Solid Waste & Emergency Response, EPA-542-R-00-013. February 2001 at: http://www.epa.gov/tio/download/remed/542r00013.pdf **O&M costs were capitalized over 30 years at both a 3% and 7% discount rate for use in the two estimates. This was done to simplify spreadsheet calculations.

For the remaining sites expected to requi re remediation, but lacking groundwater mo nitoring requirements, EPA assumed discovery of contamination would take longer. That is, CCR contamination would have migrated for so me number of years, resulting in a large r groundwater plume to remediate, or more extens ive remediation. EPA assigned these sites the 75 th percentile remediation costs as the midpoint of the top half of costs. Since the fi rst percentile time to peak results for un lined surface impoundments is six years, it is assumed that no discoveries and cleanups will be made in the first six years fo r these sites (three years once th e two years for state adoption and one year for groundwater monitoring are considered ). The costs are thus spread evenly over th e remaining 72 years. The present value of th ese remediations, accounting for the slow, but continued di scovery of contaminated sites, is presented in Exhibit 5A-17 below. Further discussion of the discounted remediation cost s for each year is presented in Appendix K10

.

Exhibit 5A-17 Present Value of Future Groundwater Re mediation Costs from CCR Contamination ($ millions present value over 50-years)
Discount Rate Subtitle C Subtitle D Subtitle D_ Baseline @ 3% $96 $1,016 $1,302 $1,587 @ 7% $39 $336 $420 $504130 Aggregate benefits from cancer risk reductions an d avoided remediation costs are summarized in Exhibit 5A-18 below. These benefits are calculated by subtracting the costs resulti ng under that option from the costs resulting under the base line (i.e., cost avoided ).

Exhibit 5A-18 Present Value of Future Avoided Human Cancer Risks

& Avoided Groundwater Remediation Cost Benefits ($millions present value over 50-years)
Subtitle C Subtitle D Subtitle D_ @ 3% discount Groundwater Remediation Costs Avoided* $1,491 $571 $286 Human Cancer Risks Avoided $1,825 $750 $375 Total $3,316 $1,321 $661 @ 7% discount Groundwater Remediation Costs Avoided* $466 $168 $84 Human Cancer Risks Avoided $504 $207 $104 Total $970 $375 $188
Note: * Calculated by subtracting the present value future groundwater remediation cost estimated in Exhibit 5A-17 for each regulatory option, from the estimated baseline present value in that same Exhibit.

Step 8. Characterize Cancer Risk Estimation Uncertainties

There are a number of uncertainties associ ated with the annualized cancer estimates calculated in this RIA which are likely to under-estimate groundwater protection benefits:

x Estimates do not account for historic releases at operating plants. These releases coul d lead to further migration and future cancer risks without proper regulatory actions like groundwater monitoring.

x A linear slope for individual cancer risk was used to approximate the increase in cancer risks instead of the parabolic curve.

x Approximately 18% of plants dispose of CCR off-site only. Since thes e facilities were not accoun ted for, additional population s would be exposed to arsenic cancer risks from dis posal as recently illustrated by the Gambr ills, MD and Chesapeake, VA damage cases.

x Three new research studies 131 (2006, 2008, 2009) from EPA_s Office of Research and Development, indicates that landfills may leach toxic metals much faster than originally believed. The damage cas es at Gambrills MD and Chesap eake VA resulted in groundwater contamination much more qui ckly than would be expect ed, and are therefore consis tent with this research.

131 The three new EPA studies are: 1. gCharacterization of Mercury-Enriched Coal Combustion Residu es from Electric Utilities Using En hanced Sorbents for Mercury C ontrol,h EPA 600/R-06/008. Office of Research and Development. Re search Triangle Park, NC. January 2006.131 x Multiple CCR disposal units at a single electric utility plant wi ll all affect the same population. The risk estimates do not account for any additive risks from multiple units. However, the populati ons around these units are accounted for as described in Appendix K2

.

x Multiple landfills could exist at some f acilities. While the area of multiple surface impoundments was considered, the area of multiple landfills was not considered because EPA did not have survey re sults for dry handling even though some facilities are known to have more than one CCR landfill onsite.

x Residents on municipal water syst ems were not included in the 2009 risk assessment or in this analysis. However, exposure thro ugh this pathway is possible, which means this RIA likely under-estim ated the human population that may be exposed to CCR.

x Populations that are farther than 1-mile that may be within the plume were not included.

x Some surface water bodies that this analysis assumes fully inte rcept the groundwater plume may in fact only partially intercept the plume, or not intercept it at all. This situat ion would be more likely to occur when surf ace water bodies are small or shallow with l ow flow rates, relative to the size of the aquifer underneath the CCR disposal un it, or are oriented such that they would not likely intercept the groundwater plume.

x Potential cancer cases resulting from cons umption of recreationally-caught fish (con taminated by direct surface impoundment dis charges and leaching from groundwater to surface water) are not included in the calculations.

x According to the EPA-ORCR 2009 CCR risk study, cancers can continue well after the analysis ends, but these cancers were not ca lculated in the population risk estimates.

x The use of a 5-year survival rate does not take into account those who may die from the cancer after year 5. Since some of the projected 5- year cancer survivors would have died in later years, they are undervalued in this assessment.

x The estimated number of cleanups is based only on modeled arseni c contamination. It does not ac count for cleanups based on haz ard quotients over 1 for toxic constitu ents with non-cancer endpoints.

The following are some uncertainties that are likely to cause over-estimation of gr oundwater protection benefits:

x Cancer risk estimates might include some individuals who are down-grad ient, but are outside the plume.

x All arsenic was assumed to be present in the arsenic III state. Appendix K5 contains an analysis in whic h all arsenic was assumed to be speciated in the arsenic V state, and EPA c oncluded that even if some portion of arsenic was speciate d in the arsenic V state, the final results would not significantly change.

x The male CSF estimate from NRC (2001) was used instead of the female CSF. Appendix K5 contains an analysis in which this female CSF was applied.

x It is possible that some states would c hoose not to remediate CCR contamination abov e cleanup levels once lo cal residents were placed on municipal or bottled water.

2. gCharacterization of Coal Combustion Residues from Electri c Utilities Using Wet Scrubbers for Multi-Pollutant Control,h EPA/ 600/R-08/077. Office of Research and Development, Air Pollution Control Division. Research Triangle Park, NC. July 2008. 3. gCharacterization of Coal Combustion Residues from Electric Utilities v Leaching an d Characterization Da ta,h EPA-600/R-09/15 1. Office of Research and Development, Air Pollution Cont rol Division. Research Triangle Park, NC. December 2009.132 x Willingness to pay estimates for non-fatal cancers has been assigned lower values in some researc h. An alternative valuation f or these cancers is presented in Appendix K5

.

x Medical treatment costs for those dying of cancer w ould not occur until the cance r was first discovered.

The following are some uncertainties that have an unknown effect on the benefits:

x This RIA assumed an evenly distributed population for establis hing up-gradient and down-gradien t populations, as well as for ad justing population for the WMU area.

x The latitude and longitude da ta of the WMU are uncertain.

x State programs serve as a proxy for units managed well and units ma naged poorly. However, there co uld be some WMUs managed wel l in states without any program. Conversely, there could be some WMUs managed poorly in states with an existing program.

x State regulatory programs aff ecting CCR disposal may be di fferent than summarized in Appendix E of this RIA.

x Remediation costs are very site-specific, and the 25 th and 75 th percentile costs used here may ove restimate or underestimate the true remediation costs of any particular cleanup. For example, the cost of responses to new releases caught early will sometimes be below the estimated costs. In other cases, even if contamination is id entified early, those costs can exceed the 75th percentile estimat es above. Responses at Gambrills MD and Chesapeake VA, two sites where CCR contamination was identified re latively early, are examples of sites where actual groundwater remediation responses will far exceed the cost estimates.

x This RIA assumed that discovery of CCR ground water contamination and the resulting remedi ation costs would be incurred evenly o ver the 75 year period for regulated faci lities and evenly over the 72 year s for unregulated facilities. However, experience under the municipal solid waste program indicates that the incorporation of lined units co uld reduce contamination over time.133 

### 5B. Benefit of Preventing Future CCR Impoundm ent Structural Failures (Avoided Cleanup Costs)

In December 2008, a failure of a CCR impoundment at the Tennessee Va lley Authority (TVA) Kingston Fossil Fuel Plant TN resulted in the environmental release of 5.4 million cubic yards of CCR. This impoundment failure event illustra ted the potential environmenta l damage severity of structural failures involvi ng CCR impoundments. This section of the RI A estimates future avoided impoundment failu re cleanup costs as a potential benefit of the CCR proposed rule, according to the following 5-step method.

Step 1. Characterize CCR Impoundment Release Data

EPA began by examining the CCR impoundment survey data collected in March and April 2009 by EPA under the authority of Section 104(e) of the Comprehensive Emergency Response, Co mpensation and Liability Act (CERCLA), from 162 individual electri c utility plants a nd from 61 electric utility corpor ate headquarters offices. EPA obt ained its list of fac ilities from a 2005 Department of Energy (DOE) Survey of coal burning electric utility facilities. EPA used DOE_s 2005 Energy Information Agency F767 database, which provides information o n the disposition of coal ash from coal burning electricity producers. The database included "steam-electric plants with a generator nameplate rating of 10 or more megawatts." The term ggener ator,h means the actual electr ic generator, not the whole plant. A plant typically w ill have one or more generators. EPA also sent the letters to corporate offices of the el ectric utilities to make su re that all of their facil ities were accounted for due to limitations in the DOE survey. Based on information recei ved in response to the initial letter to the utility corporate headquarters offices, on April 27, 2009, EPA sent informati on request letters to an additional 48 plan ts that had been identified by the cor porate offices.

Based EPA_s initial collation of the mail survey data, 42 CCR re leases from impoundments were reported, all of which occurred w ithin the last 15 years (1995-2009), in response to Question 8 of the survey questionnaire which asked for electric power plants to report all CCR impoundment releases which occurred within the last 10 years (i.e., 1999 to 2008). Exhibit 5B-1 below presents a summary of these 42 CCR impoundments release cases. Appendix K11 provides additional informati on about these 42 release cases.134 Exhibit 5B-1 2009 EPA Mail Survey Data for 42 Historical Release Events In volving CCR Impoundments at Coal -Fired Electric Utility Plants

Item Owner Company Name of Coal-Fired Electric Plant Name of CCR Impoundment Capacity (acre feet) Height (feet) Year Installed CCR Release (gallons) Release

year Age at release 1 Allete Inc Clay Boswell Power Sta tion Coal Pile Sump 1 20 1972 Unknown 2008 36 2 Ameren Energy Generating Co Meredosia Power Station Fly Ash Pond 650 24 1968 500 2006 38
3 American Electric Power Cardinal Power St ation Fly Ash Reservoi r 2 11350 237 1987 Unknown 2004 17 4 City of Springfield Lakeside Metal Cleaning Waste Basin 4 1982 Unknown 1998 16 5 City of Springfield Lakeside Metal Cleaning Waste Basin 4 1982 Unknown 2009 27
6 Dominion Chesterfield Power Station Lower (Old) Ash Pond 740 19 1964 Unknown 2005 41 7 Duke Energy Corp Walter C. Beckjord Power Station Ash P ond C 1400 50 1966 Unknown 1999 33 8 East Kentucky Power Coop Inc Dale Power Station Dale Ash P ond #4 112 26 1977 Unknown 2008 31 9 First Energy Generation Corp Bruce Mansfield Po wer Station Lakeside As h Pond 20 1957 Unknown 10 Georgia Power Co Harllee Branch Power Station C 1240 83 1971 Unknown 2000 29 11 Georgia Power Co Bowen Power Station Ash Pond 3719 45 1968 Unknown 2002 34 12 Georgia Power Co Bowen Power Station Ash Pond 3719 45 1968 Unknown 2008 40 13 Indianapolis Power & Light Co Eagle Valley Ge nerating Station A/B/C Pond 1949 30,000,000 2007 58 14 Indianapolis Power & Light Co Eagle Valley Ge nerating Station A/B/C Pond 1949 30,000,000 2008 59 15 Kansas City Power & Light Co LaCygne Genera ting Station Scrubber Sludge Ponds 6818 45 1971 Unknown 2007 36 16 Kansas City Power & Light Co LaCygne Genera ting Station Scrubber Sludge Ponds 6818 45 1971 Unknown 2007 36 17 Kansas City Power & Light Co LaCygne Genera ting Station Scrubber Sludge Ponds 6818 45 1971 Unknown 2009 38 18 MidAmerican Energy Co Riverside Generating Station South Surface Impoundment 109 10 1967 Unknown 2002 35
19 Northern Indiana Pub Serv Co R. M. Schahfer Power Station Little Blue Run Dam 84300 388 1975 Unknown
20 Northern States Power Co Sherburne C ounty Power Station Pond No. 2 57 1984 600 2007 23 21 PacifiCorp Naughton Power Sta tion FGD Pond #2 382 25 1999 Unknown 2006 7 22 PacifiCorp Naughton Power Station North Ash Pond 2100 61 1973 11,100,000 2007 34 23 PacifiCorp Dave Johnston Power St ation Blowdown Cana l 1 0 1972 14,400 2009 37 24 PacifiCorp Jim Bridger Power St ation FGD Pond #1 1340 32 1979 Unknown 25 PacifiCorp Jim Bridger Power St ation FGD Pond #2 11534 42 1990 Unknown 26 PPL Generation, LLC PPL Montour Power Station Detention Ba sin 53 8 1968 Unknown 2004 36 27 PPL Generation, LLC PPL Martins Creek Po wer Station Ash Basin 4 40 43 1989 100,000,000 2005 16 28 PPL Generation, LLC PPL Montour Power St ation Ash Basin No. 1 40 1968 Unknown 2007 39 29 PPL Montana LLC Colstrip Steam Electric Stati on Units 1 & 2 Stage Evaporation Ponds 4370 88 1992 100 1995 3 30 PPL Montana LLC Colstrip Steam Electric Station Units 3 & 4 Effluent Holding Pond 17000 138 1983 Unknown 1999 16 31 PPL Montana LLC Colstrip Steam Electric Stati on Units 1 & 2 Stage Evaporation Ponds 4370 88 1992 50 2000 8 32 PPL Montana LLC Colstrip Steam Electric Station Units 1 & 2 A Pond 245 25 1975 2,700 2003 28 33 PPL Montana LLC Colstrip Steam Electric Station Units 3 & 4 Effluent Holding Pond 17000 138 1983 Unknown 2004 21 34 PPL Montana LLC Colstrip Steam Electric Station Units 3 & 4 Effluent Holding Pond 17000 138 1983 Unknown 2005 22 35 PPL Montana LLC Colstrip Steam Electric Station Units 1 & 2 Stage Evaporation Ponds 4370 88 1992 2,000 2006 14 36 Progress Energy Carolinas Inc W. H. Weat herspoon Power Station 1979 Pond 28 1979 Unknown 2001 22 37 Progress Energy Carolinas Inc Roxboro Powe r Station FGD Flush P ond 33 2008 Unknown 2008 0 38 Santee Cooper Winyah Power Station Un it 3 & 4 Slurry Pond 1190 30 1980 Unknown 2008 28 39 Tennessee Valley Authority Kingston Power St ation Dredge Pond 1955 1,100,000,000 2008 53 40 Tennessee Valley Authority Widows Creek Power Station Gy psum Stack (Wet Stacking Area) 11157 75 1986 6,100,000 2009 23 41 Xcel Energy PSCo Comanche Stati on Polishing Pond (#4) 12 0 1972 3,000 2007 35 42 Xcel Energy PSCo Valmont Station West Ash Settling Pond 16 0 1964 5,050 2008 44
Minimum = 1 0 1949 50 1995 0 Maximum = 84,300 388 2008 1,100,000,000 2009 59 Mean (average) = 6,874 59 1976 85,148,560 2005 29 Median = 1,750 42 1974 5,050 2007 32 Column total (based on gallons released data for 15 of the 42 events) = 1.277 billion135 As displayed below in Exhibit 5B-2 , EPA was able to collect cost data on three of the most significant and recent release cases (i.e., cases resulting in the most gallons released):

Exhibit 5B-2 Cleanup Costs for Three Recen t Environmental Releases In volving CCR Impoundments

Item Owner company name Coal-fired electric utility Plant name & location Impoundment release year Release volume (gallons) EPA-assigned cost for this RIA* 1 PPL Generation LLC PPL Mart ins Creek Power Station PA (gAsh basin 4h) 2005 100 million $37 million

2 Tennessee Valley Authority (TVA) Kingston TN (gDredge cell dikeh) 2008 1.1 billion (5.4 million cubic yards) $3.0 billion

3 Tennessee Valley Authority (TVA) Widows Creek Power Station TN (gGypsum stackh) 2009 6.1 million $9.2 million

Column totals = 1.2061 billion $3.0462 billion
* Data sources:

x Item 1 : Page 29 of gPublic Health Issues Surrounding Coal as an Energy Source,h Brian Schwartz, MD, MS , Department of Environmental H ealth Sciences, February 2009 at http://www.jhsph.edu/bin/g/f/ Coal_and_public_health_Mar_2009.pdf

x Item 2 : $3.0 billion is EPA_s initial gsocial costh estimate assigned in this RIA to th e December 2008 TVA Kingston TN impoundment re lease event. Social cost represents the opportunity costs incurred by society, not just the monetary costs for cleanup. OMB's 2003 "Circular A-4: Regul atory Analysis" (page 18) instructs Federal agencies to estimate "opportunity co sts" for purpose of valuing benefits and cost s in RIAs. This $3.0 billion social c ost estimate is larger than TVA_s $933 million to $1.2 billion cleanup cost estimate (i.e., TVA_s estimate as of 03 Feb 2010), because EPA_s social cost estimate cons ists of three other social cost elements in addition to TVA_s cleanup cost estimate: (a) TVA cleanup cost , (b) response, oversight and ancillary costs associated with l ocal, state, and other Federal agencies, (c) ecological damages, and (d) local (community) socio-ec onomic damages. Appendix Q to this RIA provides EPA's documenta tion and calculation of these four cost elements, which total $3.0 billion in social cost. Appendix Q to this RIA also provides an alternative, lowe r estimate of social co sts, based on different modeling assumptions for capturing such costs. This alternative analysis suggests that TVA_s cleanup costs alone may be close t o the social costs associated with the Kingston impoundment failure. EPA specifically requests comment on this social cost estimate, and will c ontinue to develop thi s estimate for the final rule.

x Item 3 : 25 January 2010 e-mail entitled gTVA Widow_s Creek Clean Up Infoh from Anda Ray, Sr. Vice Presid ent of TVA Environment & Tech nology and TVA Sustainablity Officer, to Jim Kohler, EPA-ORCR Environmental Engineer.136 Given this limited data, this RIA attempte d to quantify the likelihood a nd costs of future releases using a historical methodol ogy. First, distinguished between three types of historical CCR impoundment struct ural failures (i.e., releases):

1. Catastrophic failures : Involving a billion gallons or more. These releases would have the potential to cause as much or more damage than occurred in December 2008 at TVA_s Kingston TN plant.
2. Significant failures : Involving between a million and a billion gallons. These w ould be less than a complete failure, but still costly. TVA Widow_s Creek (6,100,000 gallons) and PPL Martin_s Creek (100,000,000 gallons) are the lowest and highest known releases in this category, respectively. As an approximation, EPA assumes th eir costs should also bracket th e costs of other significant releases. 132 Thus, EPA estimates that the typical costs of a signifi cant failure will be $23.1 million (the average of TVA Widow_s Creek and PPL Martin_s Creek).
3. Seepage failures: Involving releases below one million gallons. While these releases can still be signifi cant and present risks to human health and the environment, this RIA does not include thes e in this analysis, which under-estimates total costs using thi s historical methodology. These smaller seeps are common to earthen dams and are not necessarily a problem unless the seepage volume is increasing or the seepage becomes cloudy - indicati ng the possible transport of CCR through the embankment.

Step 2. Fit a Distribution of Future Releases.

For the two categories consisting of catastr ophic and significant releas es, this RIA estimates not only the cleanup costs of th ese events, but also their frequency. Since relatively little data are available, this RI A applies a Poisson distribu tion. The Poisson distributio n is used when rare discrete events, and not continuous functions , are being modeled. To be a Poisson proc ess, the arrival of events must satisfy stationarity, nonmultiplicity, and independence. Here, the events (releases) sa tisfy non-multiplicity because the pr obability of two or more ev ents in a short period of time is very small. They also satisfy independence because releases occurring in one time period are independent of releases in any other time period. However, as these impoundme nts increase in age, it is quite likely that releases might increase over time, which would violate the stationarity requirement. This potential problem is dealt with in Step 4 below. Fo r the present, it will be assume d that releases occur at a constant rate in the future. In general, a Poisson distribution can be represented by the equation:



## ! ) ( ) (



## k

e t t k O 

## O



132 This is a valid assumption if cleanup costs are closely correla ted to tonnage released. Since cost modeling software typicall y requires an input of gallons released, the correlation is likely strong.137 Where: Ȝ

= Observed arrival rate (0.067 for catastrophic, 0.333 for significant); 133 t = Time period being projected (50 years) e = Constant (2.71828183) k = Number of impoundment release events projected

The probabilities of a specific number of future CCR impoundment catastrophic or si gnificant releases are illustrated in Exhibit 5B-2 and Exhibit 5B-3 (cumulative distribution) below.

Exhibit 5B-2

Poisson Distribution (Lamda=0.0 67, T=50) (Lamda=0.333, T=50)

0.0% 2.5% 5.0% 7.5% 10.0% 12.5% 15.0% 17.5% 20.0% 22.5%

0 5 10 15 20 25 30 35
Events (K)Probability

Catastrophic Significant

133 Ȝ was calculated by dividing the numb er of events observed between 1995 and 2009 by the 15-year time period.138 Exhibit 5B-3

Cumulative Distribution

0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0% 45.0% 50.0% 55.0% 60.0% 65.0% 70.0% 75.0% 80.0% 85.0% 90.0% 95.0% 100.0%

0 5 10 15 20 25 30 35

EventsProbability

Catastrophic Significant139 Step 3. Calculate Future Impoundment Fa ilure Avoided Cleanup Cost Benefits

After fitting a distribution of the number of releases likely to occur, EPA proceeded to combine these with the cost data prese nted in Step 1 above. This was done for the averag e case and three high-end cases (90 th , 95 th , and 99 th percentiles). For each case, the number of expected releases seen in Exhibit 5B-4 below was divided by 50 to get the expected number of re leases per year. These events were then multiplied by their respective costs, and the ca tastrophic and significant release va lues were summed in each year.

Exhibit 5B-4 Projected Future CCR Impoundment Releases Based on 15-Year (1995-2009) Period of Hist orical CCR Impoundment Structural Failure Cases Expected Number of Release Events Type of CCR Impoundment Release 99 th %-ile 95 th %-ile 90 th %-ile Average Assigned Cost Per Failure Event Catastrophic 8 7 6 3 $3.0 billion* Significant 27 24 22 17 $23.1 million * Note: $3.0 billion is EPA_s initial gsocial costh estimate assigned in this RIA to the December 2008 TVA Kingston TN impoundment release event. Social co st represents the opportunity costs incurred by society, not just the monetary costs for cleanup. OMB's 2003 "Circular A-4: Regulatory An alysis" (page 18) instructs Fe deral agencies to estimate "opportunity costs" for purpose of valuing benefits and costs in RIAs. This $3.0 billion social cost estimate is larger than TVA_s $933 million to $1.2 billion cleanup cost estimate (i.e., TVA_s es timate as of 03 Feb 2010), because EPA_s social cost estimate consists of three other social co st elements in addition to TVA_s cleanup cost estimate: (a) TVA cleanup cost, (b) response, oversight and ancillary costs associated with local, state, and other Federal agencies, (c) ecological damages, and (d) local (community) socio-economic damages. Appendix Q to this RIA provides EPA's documentation and calculation of these four cost elements, which total $3.0 billion in social cost. Appendix Q to this RIA also provides an alternative, lower estimate of social costs, based on different modeling assumptions for capturing such costs. This alte rnative analysis suggests that TVA_s cleanup costs alone may be close to the social costs associated with the Kingston impoundment failure. EPA specifically requests comment on this social cost estimate, and will continue to develop this estimate for the final rule.

However, EIA data indicate that there is a current trend among coal-fired power plan ts to switch from wet handling to dry handl ing. As seen below in Exhibit 5B-5 , this will lead to a decrease of approximately 300,000 tons being disposed of in surface impoundments per year, or approximately 1.3% of the initial 22.5 milli on tons in 2005. Since the tons disposed of (and similarly, the number of surface impoundments) likely relate to the number of releases, th ese decreases are accounted for by using 20 05 wet tonnage as a benchmark and assumin g the quantity of wet tonnage declines 300,000 tons per year. The cost for each year is multiplied by the remaining percent still handled wet

.140 Exhibit 5B-5 Decreasing CCR Wet Disposal Trend

Year % CCR Still Disposed Wet Year % CCR Still Disposed Wet Year % CCR Still Disposed Wet
2005 100.0% 2024 75.2% 2043 50.3%
2006 98.7% 2025 73.9% 2044 49.0%
2007 97.4% 2026 72.6% 2045 47.7%
2008 96.1% 2027 71.2% 2046 46.4%
2009 94.8% 2028 69.9% 2047 45.1%
2010 93.5% 2029 68.6% 2048 43.8%
2011 92.2% 2030 67.3% 2049 42.5%
2012 90.9% 2031 66.0% 2050 41.2%
2013 89.5% 2032 64.7% 2051 39.9%
2014 88.2% 2033 63.4% 2052 38.6%
2015 86.9% 2034 62.1% 2053 37.3%
2016 85.6% 2035 60.8% 2054 36.0%
2017 84.3% 2036 59.5% 2055 34.7%
2018 83.0% 2037 58.2% 2056 33.3%
2019 81.7% 2038 56.9% 2057 32.0%
2020 80.4% 2039 55.6% 2058 30.7%
2021 79.1% 2040 54.3% 2059 29.4%
2022 77.8% 2041 52.9% 2060 28.1%
2023 76.5% 2042 51.6% 2061 26.8%

The final step in the calculation was to take the adjusted cost s in each year and discount them by 3% and 7% to calculate the p resent value (PV) as displayed in Exhibit 5B-6 below. A full table of year-by-year costs can be found in Appendix K11 . Approximately 97% of these costs result from catastrophic releases, and the remaining 3% result from significant releases . It is important to note that no cost s are attributed to 2012-2014 as the rule will not be adopted and implemented until 2015. However, all costs beginning in 2015 are assumed to be a voided under subtitle C. Although facilities are given 5 years to phase out CCR impoundment s under one of the proposed regulatory options, the other options require regular inspections of CCR impoundments to prevent catastrophic or si gnificant releases.

For a subtitle D approach, expect delayed compliance with the requirement that surf ace impoundments be lined and that existing unlined surface impoundments be closed if they aren _t lined when compared to compliance w ith the surface impoundment phaseout under sub title C. Compliance will largely depend on the uncertainties of state regul ations, the implementation of those regulations, and citizen suits. Also, since some facilities will line their surface impound ments instead of converting to dry hand ling, these facilities will continue to p ose risks for catastrophic failure even though th ey may no longer require clea nup costs for groundwater contamin ation. The percent of states with at least141 some surface impoundment regulations, 48% as described in Appendix K9 , is used as a proxy for the phase -out of existing impoundments. However, the 5.5% of those 48% that would re trofit with composite liners could still pos e release risks. This results in 45% o f the subtitle C benefits being reali zed in subtitle D.

For the subtitle D prime approach, existing impoundments will not need to be lined, but can continue to operate until they clos e. Third-party inspections of surface impoundments would be required under this option, but it is difficult to predict the extent to which the se inspections would actually occur and would d ecrease catastrophic failures. In any case, the benefits of subt itle D prime would be less tha n those of subtitle D and greater than the baseline in terms of costs of catastrophic failures avoided. Th us, EPA used the midpoint as a best-esti mate of the effectiveness that these inspections would ha ve, which results in 23% of the subtitle C benefits being realized in a subtitle D prime approach.

Exhibit 5B-6 Estimate of Future CCR Impoundment St ructural Failure Cleanup Costs Avoided As Benefits Under Three RCRA Regulatory Options (present value in $millions) Discount Rate 99 th %-ile 95 th %-ile 90 th %-ile Average Subtitle C special waste 3% $7,407 $6,483 $5,567 $3,124 7% $4,177 $3,656 $3,140 $1,762 Subtitle D (version 2) 3% $3,333 $2,917 $2,505 $1,406 7% $1,880 $1,645 $1,413 $793
Subtitle gD Primeh 3% $1,704 $1,491 $1,280 $719 7% $961 $841 $722 $405

Step 4. Account for Increasing CCR Impoundment Release Trend

In Step 2 above, it was noted that the arri val rate of releases might violate the stationarity requirement for Poisson distribu tions. This is due to the trend of increasing release frequency ba sed on the aging structure of the earthen impoundments. EPA attempted to discern w hether a time trend was likely between releases and the av erage age of the surface impoundments. Firs t, EPA limited the universe to the 38 r eleases that had reported release dates within the past 15 years. Next, the num ber of releases in 2009 was scal ed up to account for the fact th at the EPA mail survey questionnaires were returned by June of 2009. Thus, the four releases in 2009 were scaled up by 12 months/6 months, or a factor of 2. Using commission age and only those releases for which a release year was known, EPA constructed th e profile of releases in the years ranging from 1995 to 2009 displayed in Exhibit 5B-7 below.142 Exhibit 5B-7 Summary of 15-Year (1995-2009) Period of Historical CCR Impoundment Structural Failures

Year CCR impoundment

average age Count of impoundment release events % of all CCR impoundments releasing
1995 21.1 1 0.20%
1996 21.5 0 0.00%
1997 22.5 0 0.00%
1998 23.5 1 0.19%
1999 24.5 2 0.38%
2000 25.3 2 0.38%
2001 26.1 1 0.19%
2002 27.0 2 0.37%
2003 27.9 1 0.19%
2004 28.7 3 0.55%
2005 29.7 3 0.55%
2006 30.5 3 0.55%
2007 31.3 7 1.27%
2008 32.3 8 1.45%
2009 33.0 8 1.44%

As can be seen in the table above, both th e absolute number of releases and the percen t of units with releas es have increased o ver the past 15 years. All five significant releases and the catastrophic release at TVA Kingston TN have happened since 2005. To account for this potential lack of stationarity, EPA conducted a sensi tivity analysis with alternate values of Ȝ . Instead of looking at the la st 15 years, EPA assumed that the previous 5-year period best reflects impoundment releases. Thus, in place of the earlier cal culated lambda values (0.067 a nd 0.333) derived by dividing the number of catastrophic and significant failures between 1995 and 2009 by 15, EPA calculated higher lambdas (0.2 and 1) by dividing the catastrophic and si gnificant failures between 2005 and 2009 by 5. Usi ng these new lambda values, but keeping the same 50-year forecast period, EPA derived the Poisson distri bution seen in the two figures below. The probability of a specific number of c atastrophic or significant releases is illustrated in Exhibit 5B-8 and Exhibit 5B-9 (cumulative distribution) below.143 Exhibit 5B-8

Poisson Distribution (Lamda=0.20, T=50) (Lamda=1.00, T=50)

0.0% 1.5% 3.0% 4.5% 6.0% 7.5% 9.0% 10.5% 12.0% 13.5%

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80
Events (K)Probability

Catastrophic Significant144 Exhibit 5B-9

Cumulative Distribution

0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0% 45.0% 50.0% 55.0% 60.0% 65.0% 70.0% 75.0% 80.0% 85.0% 90.0% 95.0% 100.0%

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80

EventsProbability

Catastrophic Significant145 With these new distributions, EPA performed the same calculations as described in Step 3. The expected number of releases in Exhibit 5B-10 below was divided by 50 to get releases per year; these releases were multiplied by the cost per re lease; an adjustment was mad e to account for voluntary switching to dry handling; and yearly values were disc ounted. A full exhibit of year-b y-year costs can be found in Appendix K11

.

Exhibit 5B-10 Projection of Future CCR Impoundment Releases Based on 5-Year (2005-2009) Historical CCR Impoundment Release Cases Expected Number of Release Events Type of CCR impoundment release

event 99 th %-ile 95 th %-ile 90 th %-ile Average Cost per CCR impoundment release

event Catastrophic 18 15 14 10 $3.0 billion* Significant 67 62 59 50 $23.1 million * Note: $3.0 billion is EPA_s initial gsocial costh estimate assigned in this RIA to the December 2008 TVA Kingston TN impoundment release event. Social cost represents the opportunity cost s incurred by society, not just the monetary costs for cleanup. OMB's 2003 "Circular A-4: Regulatory Analysis" (page 18) instructs Federal agencies to estimate "opportunity costs" for purpose of valuing be nefits and costs in RIAs. This $3.0 billion social cost estimate is larger than TVA_s $933 million to $1.2 billio n cleanup cost estimate (i.e., TVA_s estimate as of 03 Feb 2010), because EPA_s soci al cost estimate consists of three other social cost elements in addition to TVA_s cleanup cost estimate: (a) TVA cleanup cost, (b) response, oversight and ancillary costs associated with local, state, and other Federal agencies, (c) ecological damages, and (d) local (community) socio-economic damages. Appendix Q to this RIA provides EPA's documentation and calculation of these four cost elements, which total $3.0 billion in social

cost. Appendix Q to this RIA also provides an alternative, lower estimate of social costs, based on different modeling assumptions for capturing such costs. This altern ative analysis suggests that TVA_s cleanup costs alone may be close to the social costs associated with the Kingston impoundment failure. EPA specifically requests comment on this social cost estimate, and will con tinue to develop this estimate for the final rule.

EPA estimated subtitle C (special waste) costs avoided that were between two and three times the costs predicted in Step 3. Th is difference helps to explain how significan t the assumption of lambda, and the potential non-stationa rity of the data, can have on the fina l results. Sensitivity results were also calc ulated for subtitle D (version 2) and subtitle gD primeh approaches. As assumed above for th e subtitle D (version 2) option, EPA expects delayed compliance with the requi rement that surface impoundments be lined and that existing un lined surface impoundments be closed if they are not lined when compared to compliance with the surface impoundment phaseout under subtitle C

. Compliance will largely depend on the uncertainties of state regul ations, the implementation of those regulations, and citizen suits. Also, since some facilities will line their surface impound ments instead of converting to dry hand ling, these facilities will continue to p ose risks for catastrophic failure even though th ey may no longer require clea nup costs for groundwater contamin ation. The percent of states with at least some surface impoundment regulations, 48% as described in Appendix K9, is used as a proxy for the phase -out of existing impoundments. However, the 5.5% of those 48% that would re trofit with composite liners could still pos e release risks. This results in 45% o f the subtitle C (special waste) benefits being real ized in Subtitle D (version 2).146 For the subtitle gD primeh approach, exis ting impoundments will not need to be lined, but can continue to operate until they cl ose. Third-party inspections of surface impoundments would be required under this option, but it is difficult to predict the extent to which the se inspections would actually occur and would d ecrease catastrophic failures. In any case, the benefits of subt itle gD primeh would be less t han those of subtitle D (version 2) and greater than the baseline in terms of costs of catastr ophic failures avoided. Thus, this RIA used t he midpoint as a best-estimate of the effectiveness that thes e inspections would have. This results in 23% of the subtitle C (special waste) be nefits being realized in a subtitle gD primeh approach. Exhibit 5B-11 below presents the avoided cleanup cost estimates for the three regulatory options (i.e., Subtitle C special wa ste, Subtitle D version 2, and Subtitle gD primeh).

Exhibit 5B-11 Future CCR Impoundment Structural Failure Cleanup Costs Avoided ($millions present value over 50-years)
Discount Rate 99 th %-ile 95 th %-ile 90 th %-ile Average Subtitle C (special waste) 3% $16,708 $13,966 $13,043 $9,371 7% $9,423 $7,876 $7,356 $5,285 Subtitle D (version 2) 3% $7,519 $6,285 $5,869 $4,217 7% $4,240 $3,544 $3,310 $2,378
Subtitle gD Primeh 3% $3,843 $3,212 $3,000 $2,155 7% $2,167 $1,811 $1,692 $1,216

Step 5. Estimate Future Avoided Cleanup Costs for Two Al ternative Impoundment Failure Sc enarios (Scenario #2 & #3)

Not all of these releases are likely to pose the type of cat astrophic risks that were seen at TVA_s Kingston, TN plant. Catast rophic releases are more likely where there is a high potential for impoundment materials to disperse over la rge areas. This is most likely to occ ur at tall impoundments. Thus, this RIA presents an alternative assumption that th e Kinston-like catastrophic releases would only occur a t these tall impoundments. In addition, as age appears to be a driving factor in re leases, this analysis also assumed that Kingston-like ca tastrophic releases would occur at older impoundments. Particularly, 96 impoundments of the 584 covered in the 2009 EP A mail survey were at least 40 feet tall and at least 25 years old. The analysis below assumes that 10% - 20% of these impound ments could fail within the next 20 years . This is equivalent to the upper percentiles of failu res predicted in Steps 3 and 4 above; however it moves the costs forward in time, t o show the sensitivity of the benefits with respect to time.147 Exhibit 5B-12 Scenario #2: Cleanup Cost Estimates for CCR Impoundment Catastrophic Failures @ 10% Failures % of Tons Baseline Year Costs @3% (in millions) Costs @7% (in millions) % of Tons Subtitle C Costs @3% (in millions) Costs @7% (in millions)
88.2% 2014 - - 88.2% - - 86.9% 2015 $1,146 $1,022 70.6% $930 $830 85.6% 2016 $1,095 $941 52.9% $677 $582 84.3% 2017 $1,047 $866 35.3% $438 $362 83.0% 2018 $1,001 $797 17.6% $213 $169 81.7% 2019 $956 $733 0.0% $0 $0 80.4% 2020 $914 $674 79.1% 2021 $873 $619 77.8% 2022 $833 $569 76.5% 2023 $796 $523 75.2% 2024 $759 $481 73.9% 2025 $724 $441 72.6% 2026 $691 $405 71.2% 2027 $659 $372 69.9% 2028 $628 $341 68.6% 2029 $598 $313 67.3% 2030 $569 $287 66.0% 2031 $542 $263 64.7% 2032 $516 $241 63.4% 2033 $491 $221 62.1% 2034 $467 $202
Baseline Total $15,305 $10,309 C Total $2,259 $1,943

Given the costs above, the total benefits of a Subtitle C phase out over 5 year s would be the difference between the potential catastrophic failure costs under C and the cata strophic failure costs unde r the baseline. For the 20% gSce nario #3h, this figure is double, as displayed below in Exhibit 5B-13 . For Subtitle D, it is assumed that the 48% of states (by tonnage, as described in Appendix K9 ) that have at least some regulatory oversight currently, would enfor ce the retrofitting requirement. However, since 5.5% of impoundments already have c omposite liners, these units would not be expected to close. Thus 94.5% times 48% leads to an approximately 45% of the Subtitle C benef its. For Subtitle D prime, the requirement of dam sa fety inspections would be likely to result in some amount cat astrophic failure reduc tion between the baseline and the Subtitle D appr oach. This RIA uses the midpoint, a 23% reducti on, as a best estimate. While these estimates are likely much higher than the actual benefits from preven ting catastrophic failures, they do help to define the upper bound of what is possib le under current practices of mismanagement.148 Exhibit 5B-13 Avoided Future CCR Impoundment Ca tastrophic Failure Cleanup Costs ($millions present value)

Scenarios Subtitle C Special waste Subtitle D (version 2) Subtitle gD Primeh

Scenario #2: Assuming 10% of the 96 Impoundments Fail at 3% $13,046 $5,918 $2,959 at 7% $8,366 $3,795 $1,897 Scenario #3: Assuming 20% of the 96 Impoundments Fail at 3% $26,092 $11,836 $5,918 at 7% $16,732 $7,590 $3,795

Note: These future CCR impoundment failure cleanup costs avoided do not account for avoided costs from releases th at are less than gcatastrophic.h149 

### 5C. Induced Effect of RCRA Regu lation on CCR Beneficial Use

This section assesses the potential effects of the different regulatory options for di sposal of CCR on the future annual quanti ties of CCR beneficially used. It also estimates the values of social and economic impacts associ ated with baseline and different levels o f beneficial use. It estimates the expected increase in beneficial use from increased cost of disposal of CCR and eval uates future changes in the be neficial use of coal combustion residuals (CCR) as a result of a potential g stigma h effect.



### 5C1. Baseline Environmental & Economic Benefits of CCR Benef icial Use by Other Industries

According to CCR beneficial use market data compiled for year 2005 as displayed below in Exhibit 5C-1 , and extrapolated in this RIA to 2009 as displayed in Exhibit 5C-2 below, 62 million tons of annual CCR generated by 272 of the 495 electric utility plan ts is not disposed, but is beneficially used as materi al substitutes in at least 14 industrial applications . The purpose of this section is to provide estimates of two categories of baseline benefits associated with baseline CCR beneficial use, consisting of five sub-elements (i.e., 1a, 1b, 2a, 2b, 2c):

1. Economic benefits: Economic benefits estimated in this s ection are based on recent ma rket prices and include:

a. Annual cost savings to over 14 CCR be neficial use industries in the fo rm of reduced industrial raw and intermediate materials purchase prices relative to purchasing higher-priced substi tute materials, compared to paying electric utility plants lower prices for buying and usi ng CCR as an industrial material. b. Cost savings to electric utility plants for avoiding the cost of disposing CCR which is beneficially used.

2. Lifecycle benefits: Lifecycle benefits as qua ntified in this RIA are based on market or social values assigned to the relative physical consequences of using CCR compared to substitu te industrial materials, thro ugh the entire gmaterials flowh chain of the national economy which consists of five basic stages (1. raw materials extraction, 2. materials processing, 3. industrial manufacturing, 4. product use, 5. product end-of-lifespan disposal/recycling). Three lifecycle physical consequences are quantified in this RIA but not all monetized:

a. Lifecycle resource consumption savi ngs (water & energy consumption) b. Lifecycle air pollution emissions (GHG, CO, NOx, SOx, PM, Hg, Pb)

c. Lifecycle wastes (wastewaters and solid wastes) Lifecycle benefits in this RIA ar e only based on three categories of CCR beneficial uses (i.e., concrete, cement, and wallboard representing a s ub-total of 58% of all CCR benefici al uses) which were addressed in the prior 2008 study 134 used as a reference for this section of the RIA.

134 Source: EPA Office of Solid Waste gWaste an d Materials-Flow Benchmark Sector Report: Beneficial Use of Secondary Materials v C oal Combustion Products,h Final Report, EPA report nr. 530-R-08-003, prepared by Industrial Eco nomics Inc., 95 pages, 12 Feb 2008 at: http://www.epa.gov/osw/pa rtnerships/c2p2/pubs/benuse07.pdf. The beneficial use market data cited in this source is summarized from the American Coal Ash A ssociation (ACAA) 2005 national s urvey of the electric utility industry.150 Lifecycle benefits encompass economic benefi ts so these two categories are not additive but duplicative. Li fecycle benefits in this RIA are based on glifecycle analysish (LCA), a met hod which involves estimating both internali zed (e.g., market priced) and externalize d (e.g., costs not captured in market prices) material flow consequences:

g

Life cycle analysis depicts the production of materials in a system of complex physica l outcomes, and can predict the incremental physical consequences of a change in material input s, technology, waste management practices, or price incentives. In LCA, as in reality, one change in the physical system, such as the substitution of fly ash for virgin Portland cement, leads to a corresponding cascade of economy-wide impacts and shifts. As inputs are substitute d, technologies, physical outputs, and exposure pathways change. Using a range of modeling platform s and life cycle inventories to ca lculate the outputs associated with each incremental change, LCA calculates the net result of a ll of these interactions, captur ing the total incremental effec t of a change in operations on physical environmental impac ts such as air emissions, and energy and water use. h

x Economic Benefits of CCR Beneficial Use

As estimated in Exhibit 5C-1 below (Column F), CCR used for beneficial use applic ations has an estimated an nual US market value of $177 million per-year based on annual CCR sales revenue data supplied by 233 electric utility plants to the 2005 EIA-767 database, updated in this RIA to 2009. Based on comparison with the average higher prices for substitute industrial mate rials, using lower-priced CCR pr ovides the US national economy with $2,300 million in annual net cost savings compared to the higher $2,477 million annual cost of substitute materials in these 14 industrial applications (see Column I of Exhibit 5C-1 ).151 Exhibit 5C-1 Estimate of Annual Materials Co st Savings Benefit of CCR Generated by the Elect ric Utility Industry for Beneficial Use in Indus trial Applications A B C D E F (C x E) G H (C x G) I (H v F) Item Industry Application 2005 CCR beneficial use (million tons) % of CCR beneficial use market 2005 average market price paid

electric plants* ($/ton) Implied annual CCR sales revenues to electric utility plants 2005 avg price for substitute

material ($/ton) 2005 implied annual alternative materials cost Implied annual US national cost savings w/CCR beneficial uses 1 Construction concrete ingredient NAICS code 3273 See 1A + 1B See 1A + 1B See 1A + 1B See 1A + 1B See 1A + 1B See 1A + 1B See 1A + 1B

1A Direct ingredient: substitute for portion of Portland cement ingredient in concrete mfg NAICS code 3273 16.35 33.0% $0 to $45 $0 to $735.8 million $80 $1,308 million $572.2 to $1,308 million

1B Indirect ingredient: raw feed blended with limestone or shale to make cement clinker to be ground into cement for concrete mfg NAICS code 3273 4.22 8.5% $0 to $45 $0 to $189.9 million $80 $337.6 million $147.7 to $337.6 million

2 Construction structural fill for building foundations and embankments NAICS code 238910 8.35 16.8% $1 $8.35 million $3 $25.05 million $16.7 million

3 Construction wall board NAICS code 327420 8.18 16.5% $0 to $8 $0 to $65.4 million $4.5 to $12 $36.8 to $98.2 million $32.8 to $36.8 million 4 Waste stabilization (substitute for lime) NAICS code 5622 2.84 5.7% $15 to $25 $42.6 to $71.0 m illion $66 $187.4 million $116.4 to $144.8 million 5 Blasting grit NAICS code 212322 1.63 3.3% Not reported Not reported Not reported Not estimated Not estimated

6 Roofing granules NAICS code 324122 Included with grit (row 5) Included with grit (row 5) Not reported Not estimated Not reported Not estimated Not estimated

7 Minor uses (n=7)** 8.04 16.2% $3 to $20 $24.1 to $160.8 million $5 to $83 $40.2 to $667.3 million $16.1 to $506.5 million

Column totals (2005) = 49.61 100% Implied average (F/C) = $3 $75 to $1,231 million (best estimate  = $149 million) Implied average (H/C) = $40 $1,935 to $2,624 million (best est.** ** = $1,979 million) $1,830

2008 updated estimates = 62*** $177 million $2,477 million $2,300 million ($37 per ton) Explanatory notes: Source: Data in columns C, E, and G are from gWaste and Materi als-Flow Benchmark Sector Report: Beneficial Use of Secondary Mat erials v Coal Combustion Products,h EPA report nr. 530-R-08-003, prepared by Industrial Economics Inc., 95 pages, 12 Feb 2008 at http://www.epa.gov/osw/partnership s/c2p2/pubs/benuse07.pdf * Average price includes gfree on boardh (FOB) shipping and insurance costs paid by the supplier from the point of manufacture to a specified destination. ** Minor uses include: (1) agricultural soil amendment for flue gas desulfurization gypsum, (2) road base foundation layer unde rlying pavements for bottom ash, (3) mine reclamation material as substitute for soil, (4) mineral filler in asphalt, (5) soil stabilizer, (6) snow and ice control subst itute for sand, and (7) mining. *** 2009 update estimated tonnage (Column C above) derived in Exhibit 5C-2 of this RIA; 2009:to2005 multiplier = 62.09/49.61 = 1.25. **** gBest estimateh in Column F based on sum of coal-fired el ectric plant CCR gbyproduct sales revenuesh from the DOE-EIA F767 _PLANT database for 233 plants. gBest estimateh in Columns H and I derived by numerical interpolation of the ranges displayed based on the proportiona te best estimate and range of Column F.152 Exhibit 5C-2 2001-2008 Historical Trend in CCR Benefici al Use Quantity (Short Tons*) A. Actual Data: Year CCR Beneficial Use** (tons per year) % change % Use Linear Regression Output

Actual = 2001 37,119,321 R-Squared 0.943 Actual = 2002 45,523,256 +22.6% 35% Standard Error 1,859,123 Actual = 2003 46,384,405 +1.9% 38% Observations 8 Actual = 2004 49,089,818 +5.8% 40% Coefficients Actual = 2005 49,612,541 +1.1% 40% Intercept 39,784,058 Actual = 2006 54,203,170 +9.3% 43% X Variable 2,867,597 Actual = 2007 56,039,005 +3.4% 43% Actual = 2008 60,593,660 +8.1% 46%
Notes: * Tons source: Amer. Coal Ash Assoc http://acaa.affiniscape.com/displaycommon.cfm?an=1&subarticlenbr=3 ** gBeneficial useh data in this Exhibit correspond to the 15 categories defined in the ACAA dataset which do not match the definition (examples) of CCR beneficial uses in EPA-ORCR_s CCR proposed rule.
B. Trendline: Year Regression best fit % change Trendline = 2001 39,784,100 Trendline = 2002 42,651,700 7.2% Trendline = 2003 45,519,300 6.7% Trendline = 2004 48,386,800 6.3% Trendline = 2005 51,254,400 5.9% Trendline = 2006 54,122,000 5.6% Trendline = 2007 56,989,600 5.3% Trendline = 2008 59,857,200 5.0% Projection = 2009 62,724,800 4.8% Annual average growth rate = 5.2%

A nnual CCR Beneficial Use Tons

30,000,000 35,000,000 40,000,000 45,000,000 50,000,000 55,000,000 60,000,000 65,000,000

2001 2002 2003 2004 2005 2006 2007 2008 2009

Year ACAA actual data Trendline153 Exhibit 5C-3 below presents a 2004 state-by-state summary of annual quantity of CCR beneficially used.

Exhibit 5C-3 State-by-State Summary of CCR Beneficial Use (2004*)

A B C D E

Item State 2004 CCR generation (short tons) 2004 CCR beneficial use

(short tons) % CCR used beneficially 1 AK 43,000 Not reported NR 2 AL 3,408,000 663,000 19% 3 AR 688,000 324,000 47% 4 AZ 2,764,000 1,161,000 42% 5 CA 50,000 0 0% 6 CO 1,548,000 252,000 16% 7 CT 181,000 0 0%
8 DC 0 0 NA 9 DE 121,000 24,000 20% 10 FL 5,092,000 3,171,000 62% 11 GA 3,141,000 1,022,000 33% 12 HI 48,000 0 0% 13 IA 1,260,000 750,000 60%
14 1D 0 0 0% 15 IL 4,419,000 1,968,000 45% 16 IN 9,549,000 3,023,000 32% 17 KS 1,399,000 575,000 41% 18 KY 14,537,000 2,521,000 17% 19 LA 1,588,000 716,000 45% 20 MA 310,000 130,000 42% 21 MD 1,983,000 646,000 33% 22 ME 36,000 0 0% 23 MI 2,145,000 614,000 29% 24 MN 1,561,000 387,000 25% 25 MO 2,348,000 1,070,000 46% 26 MS 1,758,000 681,000 39% 27 MT 952,000 51,000 5% 28 NC 3,545,000 1,641,000 46% 29 ND 2,757,000 731,000 27% 30 NE 469,000 299,000 64% A B C D E

Item State 2004 CCR generation (short tons) 2004 CCR beneficial use

(short tons) % CCR used beneficially 31 NH 141,000 57,000 40% 32 NJ 600,000 112,000 19% 33 NM 3,668,000 864,000 24% 34 NV 825,000 314,000 38% 35 NY 1,379,000 368,000 27% 36 OH 6,980,000 2,290,000 33% 37 OK 1,277,000 625,000 49% 38 OR 95,000 81,000 85% 39 PA 9,545,000 2,941,000 31%
40 RI 0 0 NA 41 SC 2,172,000 1,169,000 54% 42 SD 105,000 28,000 27% 43 TN 3,803,000 2,163,000 57% 44 TX 12,943,000 4,395,000 34% 45 UT 2,341,000 812,000 35% 46 VA 2,442,000 203,000 8%
47 VT 0 0 NA 48 WA 2,301,000 1,683,000 73% 49 WI 1,437,000 1,219,000 85% 50 WV 7,220,000 2,401,000 33% 51 WY 2,106,000 508,000 24%

Totals = 129,001,000 44,653,000 35%
Notes: * Source: DOE & EPA, gCoal Combustion Waste Management at Landfills and Surface Impoundment s 1994-2004,h DO E/PI-0004, Aug 2006, page 5 (Table 1) at: http://www.ead.anl.gov/pub/doc/coal_waste_report.pdf In comparison, the ACAA reports that a 5% smaller amount of 122,465,119 tons CCR was generated in 2004154 x Lifecycle Benefits Associat ed with CCR Beneficial Use

The baseline (2005) material cost savings estimate displayed in Exhibit 5C-1 above is adjusted below to excl ude the mining applications use, because mine-filling is not covered in the proposed rule. 135 As displayed in Exhibit 5C-4 below, subtracting 2.3% of the mining applications beneficial use category decreased the base line CCR beneficial use from 49.6 million tons to 48.5 mill ion tons (relative to 2005 ).

Exhibit 5C-4 Subtraction of Mining Application Mino r Use from the Minor Use Category of the Material Cost Savi ngs for CCR Beneficial Use
CCR Beneficial Use Category (Minor Uses) CCR beneficial use tons (2005) % of all CCR uses Materials price cost savings (million 2009$) 1. Flowable fill 259,907 0.5% $10.7 2. Road base/sub-base 1,461,992 2.9% $60.0 3. Soil modification/stabilization 1,139,640 2.3% $46.8 4. Mineral filler in asphalt 140,838 0.3% $5.8 5. Snow & ice control 547,541 1.1% $22.5 6. Mining applications 1,132,945 2.3% $46.5 7. Agriculture 415,741 0.8% $17.1 8. Aggregate 872,776 1.8% $35.8 9. Miscellaneous minor uses 2,071,157 4.2% $85.1 Sub-total Minor Uses = 8,042,537 16.2% $330.3 Total All Uses (Major + Minor) = 49,612,541 100.0% $1,830

Total Excluding Mining = 48,479,596 97.7% $1,783.5 ($37 per ton)

From a materials lifecycle anal ysis perspective, CCR beneficial use generate s net environmental benefits. Based on a 2008 life cycle study 136
of two of the 14 CCR beneficial use industr ial applications (i.e., conc rete and wallboard) there are 12 environmental benefit c ategories with the annual magnitudes estimated below in Exhibit 5C-5 . This estimate of environmental benefits is based on only 47% (i.e., 23.2 million tons) of the 49.62 million tons for the 2005 CCR beneficial use market as re ported in that 2008 study. Thus, these estimates may unders tate annual environmental benefits of CCR beneficial us es. These net benefits are not additive to the economic benefits, but encompass the m.

135 As noted in the Federal Register notice of EPA_s proposed CCR rule, minefilling w ill be addressed in an alternate rulemaking.

136 Source: Exhibit 5-3 of gWaste and Materials-Flow Benchmark Sector Report: Beneficial Use of Secondary Materials v Coal Combust ion Products,h prepared by Industrial Economics Inc for the EPA Office of Solid Waste, 12 Feb 2008, 95 pages at http://www.epa.gov/osw/partnerships/c2p2/p ubs/benuse07.pdf155 To avoid double-counting of economic and so cial benefits, EPA evaluated the monetiza tion of the energy, water, and air pollutio n-related impacts for any such double counting. Based on this evaluation, this RIA concludes that each of the individual monetized estim ates for these impacts are fully additive and do not double co unt benefits, with one exception regardi ng partial overlap between energy cost s avings and the value of avoided SOx air emissions. For SOx, where there exists a cap and trade permit program, firms must pay to emit SOx. A portion of the SOx emissions avoided from beneficially us ing CCR is from the energy sector. Under th e presumption that th e marginal costs of abatement equal the value of marginal damages, the va lue of the portion of SOx emissions from th e energy sector will be reflected in the energy cost savings. The portion of avoided SOx emissions that comes from s ectors other than energy is not reflected in energy cost saving s and thus should be retained. However, separately adding a value for reduced SOx emissions likely represents some amount of double coun ting.

Unlike the SOx permit program, most regulati on of NOx and particulate ma tter (PM) does not require firms to purchase permits to pollute. Thus there is little to no overlap between the external costs of these air pollutants and energy costs. In addition, aside fro m limited state programs, GHG damages are not currently regu lated and would not be reflected in the ma rket price for energy. Thus, the benefit s from NOx, particulates and GHG reductions ar e fully additive to private en ergy cost savings. Furthermore, for water use, the only benefi ts included are the direct cost savings, and because the water savings in th ese cases are not associated w ith energy production, these savings are not being captured elsewhere. Reduced water use in th e production process is a real cost savings that should be a component of total ben efits.

Therefore, this RIA concludes that there is only a partial double count ing between energy cost savi ngs and the savings associat ed with reduced SOx emissions. No other beneficial use benefits categories are affected by this double counting issue. Thus, Exhibit 5C-5 below has subtracted the $1,491 million benefits attribut able to SOx reductions from the environm ental benefits estimate, resulting in an environmental estimate of $22,980 million per year , or $474 per ton average lifecycle benefit, assigning zero valu es to tonnage other than concrete and wallboard. In addition to baseline lifecycle benefits, there are an estimated $2,927 million per year in baseline avoided disposal cost benefits to the electric utility industry (i.e., (49.61 million tons CCR be neficial use in 2005) x ($59 pe r ton average baseline disposa l cost estimated in Exhibit 3L of this RIA)), which constitutes a total of $25,907 million per year (relative to 2005 CCR beneficial use tonnage), which is an average of $533 per ton nationwide baseline social bene fits from CCR beneficial use.

Exhibit 5C-5 Estimate of Annual Baseline Lifecycl e Benefits from CCR Beneficial Use (Based on 2005 CCR beneficial use tonnage)

Benefit category Physical quantity of environmental benefits for 48.5 million tons annual CCR beneficial use w/out mining application* Unit monetization values (2009$)** Estimated benefits ($millions per year) A. Resource Consumption Savings 1. Energy consumption 158 trillion BTU energy savings $0.00003093 per BTU $4,888 2. Water consumption 32.1 billion gallons water savings $0.0025259 per gallon $81 Subtotal (1+2) = $4,969 B. Air Pollution Savings 3. GHG - greenhouse gases 11.5 million metric tons CO2 equivalent emissions avoided $20.76 per metric ton $239 4. CO v carbon monoxide 9,200 metric tons em issions avoided Not estimated Not estimated 5. NOx v nitrous oxides 30,400 metric tons emissions avoided $10,255 per metric ton $312156 Exhibit 5C-5 Estimate of Annual Baseline Lifecycl e Benefits from CCR Beneficial Use (Based on 2005 CCR beneficial use tonnage)

Benefit category Physical quantity of environmental benefits for 48.5 million tons annual CCR beneficial use w/out mining application* Unit monetization values (2009$)** Estimated benefits ($millions per year) 6. SOx – sulfur oxides 23,900 metric tons emissions avoided $62,375 per metric ton $1,491 7. PM v particulate matter 9,704 metric tons emissions avoided $486,312 per metric ton $4,719 8. Particles non-specified 26,200 metric tons emissions avoided $486,312 per metric ton $12,741 9. Hg - mercury 0.584 metric tons emissions avoided Not estimated Not estimated
10. Pb - lead 0.656 metric tons emissions avoided Not estimated Not estimated Subtotal (3 to 10) = $19,502 Subtotal air pollution savings excluding SOx & excluding mine-filling use = $18,011 C. Other Environmental Savings

11. Waterborne wastes 2,446 short tons waste generation avoided (SM + BOD + COD + Cu + Hg + Pb + Se) Not estimated Not estimated

12. Solid waste 27,991 short tons waste generation avoided Not estimated Not estimated Total (1 to 12) = $24,471

Total annual lifecycle benefits (excluding SOx & excluding mine-filling use) = $22,980 ($474/ton)
Notes: * Physical quantity of environmental benefits are based on only two of the 14 beneficial use in dustrial applications (i.e., 15. 0 million tons per year fly ash CCR used in concrete, plus 8.2 million tons per year FGD CCR used in wallboa rd). These estimates are from E xhibit 5-3 (page 5-6) of gWaste and Materials-Flow Benchmark Sector Report: Beneficial Use of Secondary Materials v Coal Combustion Products,h prepared by Industrial Economics Inc for the EPA Office of Solid Waste, 12 Feb 2008; available at http://www.epa.gov/osw/partnerships/c2p2/pubs/benuse07.pdf . This 2008 reference report does not provide environmental impact estimates for the other 12 beneficial use industrial applications. ** Unit monetary values applied for monetization are from the following sources:

x Row 1 & Row 2: 2007 values from Exhibit 5-3 (page 5-6) of the Industrial Economics Inc reference report. Unit values updated f or this RIA from 2007 to 2009 using NASA_s Gross Domestic Product Deflator Inflation Calculator at http://cost.jsc.nasa.gov/inflateGDP.html

x Row 3: Based on the September 2009 interim social cost of carbon (i.e., interim SCC) from Table III.H.6-3, page 29617 of the jo int EPA and DOT-NHTSA gProposed Rulemaking to Establish Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Stand ards,h Federal Register, Volume 74, No. 186, 28 Sept 2009. The value applied in this RIA is the $19.50 per ton median value from the $5 to $56 per ton range displayed in the 2007 column in that source. Furthermore, this RIA updated the 2007$ median value from 2007 to 2009 dollars using the NASA Gross Dom estic Product Deflator Inflation Calculator at http://cost.jsc.nasa. gov/inflateGDP.html. EPA is aware that fi nal SCC values were published on March 9 , 2010 in conjunction with a Department of Energy final rule. EPA intends to use the final SCC values for the CCR final rule RIA. The final SCC values are published in the Department of Energy, Energy Efficiency & Renewable Ener gy Building Technologies Program, "Small Elect ric Motors Final Rule Technical Support Document: Chapter 16 - Regulatory Impact Analysis", March 9, 2010 at http://www1.eere .energy.gov/buildings/appliance_standards/commercial/sem_finalrul e_tsd.html).

x Rows 4-10: Unit values from the report gThe Influence of Location, Source, and Emission Type in Estimates of the Human Health B enefits of Reducing a Ton of Air Pollutionh by Neal Fann, Charles Fulcher and Br yan Hubbell, in Air Quality, Atmosphere & Health, Volume 2, No.3, Sept 2009, pages 169-176. The dollar values from this report were updated from 2006 to 2009 using NASA_s Gross Domestic Product Deflator Inflation Calculator at http://cost.jsc.nasa. gov/inflateGDP.html

x Rows 12-13: Waterborne waste and solid waste generation avoided benefits were not monetized in the 2008 Industrial Economics In c. reference study cited above.157 

### 5C2. Potential Effect of RCRA Regulation of CCR Disposal on CCR Beneficial Use

Under the proposed regulation, the Bevill exem ption still applies to quanti ties of CCR directed to cert ain beneficial uses so t hat these quantities do not face increased disposal costs associat ed with Subtitle C or D regulation of di sposed CCR. The increased costs of dispos al of CCR as a result of their regulation under RCRA sub title C will create a strong economic and regul atory incentive for increased beneficia l uses of CCR. In fact, EPA concludes that the increased costs of disposal of CCR under subtitle C of RCRA, but not the beneficial use of CCR, will actually increase their usage in non-regul ated beneficial uses, simply as a result of the economics of supply and demand. The economic driver - availability of a low-cost, func tionally equivalent or often supe rior substitute for other raw ma terials - will continue to mak e CCR an increasingly desirable product. Furtherm ore, it has been EPA_s experience in the RCRA hazardous waste regulations and elsewher e that material inevitably flows to less regulated applications.

On the other hand, industry and state government stakeholders have asserted in letters to EPA, that regulation of CCR as a RCRA ghazardous wasteh will impose a gstigmah on CCR beneficial use which will signi ficantly curtail these uses. In their view, even an action that regulates only the disposal of CCR in landfills or surface impoundments as hazardous waste, but retains th e Bevill exemption for benefici al uses, would have this effect. Also, the st ates particularly have argued th at, by operation of state law, th e beneficial use of CCR would b e prohibited under many states_ beneficial use programs, if EPA were to designate CCR as a hazardous waste when disposed.

The purpose of this section of the RIA is to quantify both possibilities v i.e., an induced increase (Scenario #1) and an induc ed decrease (Scenario #2) -- in future CCR beneficial us e, and to explain the basis for this RIA selecting the former (Scenario #1) as the gbase case.h

x Examples of Hazardous Waste Recycling Success Not “ Stigma ”

EPA_s past experiences with the impacts of RCRA regulation, and with how RCRA indus trial hazardous wastes and other hazardous m aterials are used and recycled, suggests that a gh azardous wasteh designation of industrial s econdary materials and wastes, does not imp ose a significant barrier to its benefi cial use (e.g., recycling), and that non-regulated uses generally increase as the costs of reg ulated disposal increase. As summarized below, EPA_s experience has shown that the economic incentive of a high disposal cost has outweighed a ny hypothetical stigma effect in case after case of hazardous waste recycling. Six examples liste d below illustrate the point tha t a RCRA ghazardous wasteh designation does not stand in the way of a material_s (or waste_s) s ubsequent industrial recycling or reuse a s a raw or intermediate material:

1. Electric arc furnace dust: RCRA hazardous waste (waste code = K061), and yet it is a highly recycled materi al. Specifically, between 2001 and 2007, approximately 42% to 51% of K061 was recycled as evidenced by Biennial Reporti ng System (BRS) data. Both currently and historically, K061 has been used as an ingredient in fert ilizer, an input in making st eel, and in the production of zinc products, including pharmaceutical materials. Slag from the smelting of K061 is in high demand for use in road construction. The use of slag is regulated under Pennsylvania_s be neficial use program, despite the fact that it is derived from a listed hazardous w aste. In fact, there is little doubt that, without its regulation as a hazardous waste, a significantly greater amount of K061 would be diverted from recycling to disposal in non-hazardous landfills.158 2. Electroplating wastewater sludge: Listed hazardous waste (F006) that is recycled fo r its copper, zinc, and nick el content for use in the commercial market. In 2007, approximately 35% of F006 material wa s recycled according to BRS da ta. These materials are clearl y in no way stigmatized in the marketplace.
3. Chat: Superfund cleanup waste with lead contam ination is used in road c onstruction in Oklahoma and the surrounding areas. In this case, the very waste that has triggered an expensive Superfund cleanup is successfully offered in the marketplace as a raw mate rial in road building. The alternative cost s of disposal in this case ar e a significant driver in the beneficial use of this material, and the Superfund origin of the material has not prevented its use.
4. Used oil: Frequently a hazardous waste if disposed of, and is regulated under the RCRA subtitle C standards. While used oil that is recycled is subject to a separate set of standards under subtitle C (and is not identified as a h azardous waste), gstigmah does not prevent home do-it-yourselfers from collecting used oil, or automotive shops from accepting it and sending it on for recovery. Collect ed used oil may be re-refined, reused, or used as a fuel in boilers, of ten at the site where it is collected. One large commercial us ed oil handler reports managing 500 million ga llons of used oil a year.
5. Spent etchants: Directly used as ingredients in the pr oduction of a copper micronutrient for livestock.
6. Spent solvents: Generated from metals parts washing are dire ctly used in the producti on of roofing shingles.

And in all such cases, these materials are generally RCRA hazardous wastes before reclamation. Many materials widely used in h omes today can be classified as ghazardoush materials, and many come with warning labels. For ex ample, motor oil comes with warning label s. Gasoline would be a characteristic hazardous waste if disposed of, as would many common drai n cleaners and household cleaners. Cathode ray tube monitors for TVs and computers, as well as many fluorescent lamps are all hazardous wastes if dis posed of. Fluorescent lamps ( and CFLs) are potentially hazardous when disposed of because of mercury. Merc ury is an indispensable resource, and virtually all of the merc ury used for lamps and other uses in the U.S. is derived from discarded merc ury or mercury products v that is , from hazardous waste. Even p roducts as unlikely as nicotine gum or dental amalgam would be a hazardous waste when disposed of. Consumers are generally comfortable wi th these products, and their regulatory stat us does not discourage their use.

x Differing Views About Prospect of Future “ Stigma ”

Stakeholders have also expresse d the concern that standards-se tting organizations might prohib it the use of CCR in specific pro ducts or materials in their voluntary standards. Recently, the American Standards and Testi ng Materials (ASTM) International Committee C09, and its subcommittee, C09.24, in a December 23, 2009 letter to EPA indicated th at ASTM would remove fly ash from the project specificat ions in its concrete standard if EPA determined that CCR were a hazardous waste. However, ASTM standards are developed through an open con sensus process, and current standards cover the us e of numerous hazardous materials in cons truction and other activities. For example , ASTM provides specifications for the reuse of so lvents and thus, by implication, does not appear to take issue with the use of these recycled wastes, despite their classification as hazardous wastes. 137

137 For example, see ASTM Volume 15.05, Engine Coolants, Halogenated Organic Solvents and Fire Extinguishing Agents; Industrial an d Specialty Chemicals, at or ASTM D5396 - 04 Standard Specificatio n for Reclaimed Perchloroethylene.159 Others take a different view on how standard-setting organizations will react. Most notably, a US Green Building Council repre sentative has been quoted in the New York Times as saying that LEED incentives for using fly ash in concrete would remain in place, even under an EPA hazardous determination. If the Green Build ing Council (along with EPA) c ontinues to recognize fly ash as an environmentally b eneficial substitute for Portland cement, EPA believes th at the use of this material is unlikely to decrease solely because of gstigmah c oncerns.

In addition, Congress directed government ag encies to increase their purchase of r ecycled-content products. Specifically, sect ion 6002 of RCRA requires EPA to designate products that can be made with recovered materials and to recommend practices for buying these p roducts. Once a product is designated, gprocuring agenciesh 138 are required to purchase it with the highest recovered material content level practicable if they spend more than $10,000 a year on that item. EPA_s federal Comprehensive Proc urement Guidelines (CPG), requiring the u se of fly ash in cement for federally funded projects, would remain in place. Thus, any federal, state, or lo cal agency carrying out federal ly funded construction projects would continue to be required to give a pref erence to fly ash as a Portland cement replacement.

Finally, many state governments have argued th at their statutes or regulations prohibi t the use of hazardous wastes in their st ate beneficial use programs, and therefore that, if EPA lists CCR as a hazardous waste (even if only for di sposal), their use w ould be precluded i n those states. EPA has reviewed the regulations of 10 states with the highest consumption of fl y ash and/or cement and concluded that while th ese states do not allow the use of hazardous waste in thei r beneficial use programs, C CR that are beneficially reus ed will remain Bevill-exem pt solid wastes, or in some cases, would not be considered wastes at all and thus, the continued use of CCR under these programs should not be a ffected by the proposed CCR rule. For EPA_s summary of 10 state government CCR beneficial use regulations, see Appendix K12 . For the above reasons, this RIA presents the increased future CCR beneficial use (Scenario #1) as the gbase case.h However, this RIA monetizes both s cenarios (i.e., induced increase and induced gstigmah decr ease) using the following 10-step method.

Step 1. Project Future A nnual Tonnage CCR Generation

To estimate the levels of CCR beneficial use, the first task wa s to project the future annual t onnage of CCR generated by the e lectric utility industry. The amount of CCR is likely to increase proportionally, as utilities comply with new Clean Air Act requirements. No t reflecting this proportional increase, this RIA relied on the EIA future fo recast for coal burned by th e electric utility industry. 139 As displayed in Exhibit 5C6 below, the EIA data extends out to the ye ar 2035. However, to remain consistent with the other cost and benefit estimates, th is RIA extended this trend out to the year 2061 based on re gression-fit extrapolation using the followi ng first-order regres sion of coal burned as dependent variable against year as independent variable:

138 Procuring agencies include all federal agen cies, and any state or local agency or gove rnment contractor th at uses appropriated federal funds.

139 Source: Based on 2007 to 2035 annual short tons coal consump tion by electric power sector for ecast data from the Energy Inform ation Administration (EIA), gYear-byYear Reference Case Tables (2008-2035): Table 15 Coal Supply, Disposition, and Pricesh from the report gAnnual Energy Outlook 2 010 Early Release,h December 14,
2009 at http://www.eia.doe.gov/oiaf/aeo . The EIA report presents a midterm projection and analysis of US energy supply, demand, and prices through 2035, based on the EIA_s National Energy Modeling System. Further information on the EIA_s projections is available at160 x y 1 0 E E 
Where: y = Tons coal burned at time = x ȕ 0 = Tons coal burned at time = 0 ȕ 1 = Additional tons coal burned each year, on average x = Time elapsed (years)

Running the regression, calculated a ȕ 0 (or intercept) of 1,001,902,312; a ȕ 1 (or slope) of 6,082,277; and an R-s quared (or fit) of 87%. This regression was used to extrapolate the EIA proj ection out to the year 2061 as displayed in Exhibit 5C-7 and as graphed in Exhibit 5C-8 below.

Table 5C-6 Coal Burned Forecast Data From EIA

Year X = Time Elapsed Y = EIA Projection (Tons Coal Burned) 2007 0 1,045,140,137 2008 1 1,041,599,976 2009 2 951,846,252 2010 3 970,887,207 2011 4 1,025,782,227 2012 5 1,049,056,519 2013 6 1,057,912,842 2014 7 1,069,233,154 2015 8 1,044,051,880 2016 9 1,053,579,224 2017 10 1,052,420,654 2018 11 1,062,561,646 2019 12 1,071,914,062 2020 13 1,073,440,308 2021 14 1,090,903,931 2022 15 1,098,539,673 2023 16 1,102,742,065 2024 17 1,096,057,129 2025 18 1,115,724,243 2026 19 1,111,202,026 2027 20 1,121,313,477 2028 21 1,131,518,677 2029 22 1,128,823,120 2030 23 1,146,826,782 2031 24 1,149,894,043 2032 25 1,160,750,977 2033 26 1,156,721,802 2034 27 1,161,479,736 2035 28 1,182,647,705161 Exhibit 5C-7 EPA Extrapolation of EIA Projection to 2061
Year Tons Burned Year Tons Burned 2007 1,001,902,312 2035 1,172,206,065 2008 1,007,984,589 2036 1,178,288,342 2009 1,014,066,866 2037 1,184,370,619 2010 1,020,149,143 2038 1,190,452,896 2011 1,026,231,420 2039 1,196,535,173 2012 1,032,313,697 2040 1,202,617,450 2013 1,038,395,974 2041 1,208,699,727 2014 1,044,478,251 2042 1,214,782,003 2015 1,050,560,527 2043 1,220,864,280 2016 1,056,642,804 2044 1,226,946,557 2017 1,062,725,081 2045 1,233,028,834 2018 1,068,807,358 2046 1,239,111,111 2019 1,074,889,635 2047 1,245,193,388 2020 1,080,971,912 2048 1,251,275,665 Exhibit 5C-7 EPA Extrapolation of EIA Projection to 2061
Year Tons Burned Year Tons Burned 2021 1,087,054,189 2049 1,257,357,942 2022 1,093,136,466 2050 1,263,440,219 2023 1,099,218,743 2051 1,269,522,495 2024 1,105,301,019 2052 1,275,604,772 2025 1,111,383,296 2053 1,281,687,049 2026 1,117,465,573 2054 1,287,769,326 2027 1,123,547,850 2055 1,293,851,603 2028 1,129,630,127 2056 1,299,933,880 2029 1,135,712,404 2057 1,306,016,157 2030 1,141,794,681 2058 1,312,098,434 2031 1,147,876,958 2059 1,318,180,710 2032 1,153,959,235 2060 1,324,262,987 2033 1,160,041,511 2061 1,330,345,264 2034 1,166,123,788 Total 64,136,808,356162 Exhibit 5C-8

Extending EIA Projections

900,000,000 950,000,000 1,000,000,000 1,050,000,000 1,100,000,000 1,150,000,000 1,200,000,000 1,250,000,000 1,300,000,000 1,350,000,000 1,400,000,000

2007 2012 2017 2022 2027 2032 2037 2042 2047 2052 2057

YearCoal Burned (Tons)

EIA Projection EPA Regression163 Based on the most recent CCR beneficial use da ta from ACAA, EPA estimated the average t ons of CCR generated for every ton of co al burned by electric utility plants. For this calc ulation, this RIA only used the most recent data year (2008) to estimate a conversion rate because over time, the quantities of CCR generated per ton of coal combusted ha s steadily increased. Thus an average of recent years would not reflect this trend. The steady increase over time is due to tightening of industrial air polluti on regulations. This trend would likely co ntinue in the future as further facilities undergo new source re view, or implement new Clean Air Act requ irements under upcoming EPA rules like the Clean Air Interstate Rule (CAIR) and the Clean Air Mercury Rule (CAMR). Thus, the future a nnual tonnages of CCR estimated in this RIA ar e likely under-estimates. Dividing the 2008 tons of CCR generated (136 m illion tons) by the 2008 tons of coal burned by the electric po wer sector (1,042 million tons), EPA produced a CCR-to-coal relationship factor of 0.131. Applying this factor to the extrapolated coal c onsumption projection produced the future CCR gene ration scenario displayed below in Exhibit 5C-9

.

Exhibit 5C-9 Projected Future Annual CCR Generati on by the Electric Utility Industry: Scenario Based on Extrapolation of EIA’s Projectio n of Electric Power Sector Coal Burned 2007-2035 (Short Tons)
Year CCR Year CCR Year CCR Year CCR 2012 134,764,862 2025 145,087,115 2038 155,409,369 2051 165,731,622 2013 135,558,881 2026 145,881,135 2039 156,203,388 2052 166,525,642 2014 136,352,901 2027 146,675,154 2040 156,997,408 2053 167,319,661 2015 137,146,920 2028 147,469,174 2041 157,791,427 2054 168,113,681 2016 137,940,940 2029 148,263,193 2042 158,585,447 2055 168,907,700 2017 138,734,959 2030 149,057,213 2043 159,379,466 2056 169,701,720 2018 139,528,979 2031 149,851,232 2044 160,173,486 2057 170,495,739 2019 140,322,998 2032 150,645,252 2045 160,967,505 2058 171,289,759 2020 141,117,018 2033 151,439,271 2046 161,761,525 2059 172,083,778 2021 141,911,037 2034 152,233,291 2047 162,555,544 2060 172,877,798 2022 142,705,057 2035 153,027,310 2048 163,349,564 2061 173,671,817 2023 143,499,076 2036 153,821,330 2049 164,143,583 2024 144,293,096 2037 154,615,349 2050 164,937,603

Appendix K5 to this RIA presents alternative estimat es of future CCR generation. These estimate s take into account the recent increasing trend in the ratio of tons CCR generated to the tons coal combustion. For example, in year 2035 the constant ratio projection above yields a value of 153 million tons CCR generated wher eas the increasing ratio projection in Appendix K5 yields a value of 191 million tons of CCR generated. While the exact magnitude of such an increase is uncertain, there would be at least some increase as a result of in creased air pollution controls. These include future changes due to EPA_s New Source Review (N SR), EPA_s Clean Air Interstate Rule (CAIR), and EPA_s Clean Air Mercury Rule (CAMR).164 Step 2. Project Future Baseline Annual Tonnage CCR Beneficial Use (Wit hout RCRA Regulation)

This step involves projecting the extent to which CCR would be beneficia lly used in the absence of the proposed RCRA regulation of CCR disposal (i.e., future ba seline CCR beneficial use). Exhibit 5C-10 below displays the recent (i.e., 2001 to 2008) trend in annual tonnage of CCR beneficial use, and as a percen tage relative to annual CCR genera tion by the electric utility industry.

Exhibit 5C-10 Recent CCR Beneficial Use Trend (2001-2008)

Year CCR Generation (short tons) CCR Beneficial Use (short tons) Fraction

2001 117,930,542 37,119,321 31.5% 2002 128,703,572 45,523,256 35.4% 2003 121,744,571 46,384,405 38.1% 2004 122,465,119 49,089,818 40.1% 2005 123,126,093 49,612,541 40.3% 2006 124,795,124 54,203,170 43.4% 2007 131,127,693 56,039,005 42.7% 2008 136,073,107 60,593,660 44.5% Source: American Coal As h Association (ACAA) at http://acaa.affiniscape.com/displayc ommon.cfm?an=1&subarticlenbr=3

If the recent trends in CCR gene ration and CCR beneficial use continued in a linear fashion, mo re than 100% of CCR would be ben eficially used before year 2061. Furthermore, a linea r extrapolation for beneficial use would not be appropriate because as more and mor e CCR is used, it would likely become increasingly difficu lt to use the remaining CCR due to saturati on of local markets, competition between CCR generators, and other factors, depending on overall macro-economic factors. Thus, fo r purpose of extrapolation to the 50-year period-ofanalysis (2012 to 2061), this RIA instead modeled the recent trend data as an asym ptotic, exponential function of the form:

) *(

1 1 D X C B Y

 
Where: Y = Percent of CCR beneficially used X = Time elapsed relative to 2001
B = 1.021 C = 1.369 D = 13.99165 Beneficial uses of CCR have been consistently growing in the r ecent past. Since the percent of CCR beneficially used has been growing, EPA sought to characterize that trend so that the future percent benefici ally used could be applied to the future tons of CCR. The ACAA data from 2001 to 2008 indicate that this trend was in creasing. After running several regressions, EPA disposed of the typical trend fit s for various reasons. A first-order (linear) trend line was abandoned because it would have le d to beneficial use a bove 100% well within th e time-frame of the analysis. Higher order regressions led to oddities where beneficial use would tren d away from 100% at some point in time. Once typical fits were ruled out, EPA assumed that CCR benefi cial use would not exceed 100% of CCR generated. 140 Instead, it would potentially become more and more difficult to use CCR as a highe r percent went to beneficial uses, because of market limitations. Thus, it made s ense to use an exponential curve that approached, but never cr ossed an asymptote of 100% beneficial use.

To fit an exponential curve to the 2001 to 2008 CCR beneficial use data, a spreadsh eet calculation solver was programmed to min imize the residual sum of squares between the actual and projected percent of CCR beneficial us e by changing the regression equation vari ables B, C, and D. From solver result, B was set to 1.021, C was set to 1.369, and D was set to 13.99. Usi ng these values, the future CCR beneficial use projection as measured on a percentage basis relative to CCR generation were estimated, as displayed in Exhibit 5C-11 and Exhibit 5C-12 below. The percentage of CCR beneficia lly used under the baseline (i.e ., without RCRA regulation) is expected to gradually app roach, but never reach 100% of CCR generation. By 2061 at the end of the 50-year period-of-analysi s, 88% of CCR would be beneficially use d under this projection. While this is a rela tively high number, current experiences in at le ast one US state and in at least 16 other coun tries (i.e., 15 European countries + Japan), al ready demonstrate that very hi gh CCR beneficial use rates of 90% and above are achievable:

1. Wisconsin : Several companies are developing technol ogies to convert CCR into bricks used in construction, and one such technology was recently commercialized in Wisconsin. 141 Some of these technologies have the potential for using 100% CCR (fly ash) in brick production, as opposed to the conventional 30%-50% limit for replacing Portland cement in concrete.
2. Europe : As of 2007, 15 European countries re ported a CCR beneficial use rate of 89% (i.e., 55.449 million metric tons beneficially used in 2007 in 24 industrial applications, out of the 62.094 million metric tons generated in 2007). 142

3. Japan : As of 2006, Japan reported a CCR beneficial use rate of 97% (i.e., 10.657 million tons used in Japan in 2006 for 3 cement applications, 6 civil engineering applicat ions, 3 construction applications, 2 agricu lture/forestry/fisheries applications, and at least three other miscellaneous applications, out of the 10.969 million tons CCR generated in Japan in 2006). 143

140 The fact that some electric utility plants currently excavate previously disposed CCR for supplying to beneficial use markets suggests this may be a limiting assumption which could underestimate future potential growth of CCR benefici al use. For example, one electric utility company reported a 106% CCR beneficial use rate in 2006 for its four electricity plants because it reco vered CCR that it had previously disposed.

141 Source: gCalStar Gives Sneak Peek of Low-Carbon Brick Factor y,h Cleantech Group, 27 Oct 2009 at http://cleantech.com/news/5217 /calstar-flyash-l ow-carbon-brick

142 Source: Europe_s 2007 CCR beneficial use rate is reported by EC OBA (European Coal Combustion Products Association) which was f ounded in 1990 by European energy producers to deal with matters related to the usage of co nstruction raw materials from coal. As of 2009, membership in ECOBA consists of 24 companies and associations from 15 countries in Europe, all generators of elect ricity and heat. ECOBA members represent over 86 % of total C CR generation by the 27 total European countries. ECOBA_s 15 member countries are Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Netherlands, Po land, Portugal, Romania, Russia, Spain, and United Kingdom. ECOBA_s 2007 CCR beneficial use rate is reported in gProduction and Utilisation of CCPs in 2007 in Europe (EU 15)h at: http://www.ecoba.com/evjm,media/sta tistics/ECOBA_Stat_2007_EU15.pdf

143 Source: Japan_s 2006 CCR beneficial use rate is reported by the Ja pan Coal Energy Center (JCOAL) in Table 3-1 of gStatus of Co al Ash Productionh at: http://www.jcoal.or.jp/coaltech_en/coalash/ash01e.html166 Exhibit 5C-11 Projected Future Baseline CCR Beneficial Use Measured as Percentage of CCR Generation
Year % Beneficial Use Year % Beneficial Use Year % Beneficial Use Year % Beneficial Use
2001 33.22% 2016 56.67% 2031 71.89% 2046 81.76%
2002 35.11% 2017 57.91% 2032 72.69% 2047 82.28%
2003 36.96% 2018 59.10% 2033 73.47% 2048 82.79%
2004 38.75% 2019 60.27% 2034 74.22% 2049 83.28%
2005 40.49% 2020 61.39% 2035 74.95% 2050 83.75%
2006 42.19% 2021 62.49% 2036 75.67% 2051 84.21%
2007 43.83% 2022 63.56% 2037 76.36% 2052 84.66%
2008 45.43% 2023 64.60% 2038 77.03% 2053 85.10%
2009 46.98% 2024 65.60% 2039 77.68% 2054 85.52%
2010 48.49% 2025 66.58% 2040 78.32% 2055 85.93%
2011 49.95% 2026 67.53% 2041 78.94% 2056 86.33%
2012 51.37% 2027 68.45% 2042 79.53% 2057 86.72%
2013 52.76% 2028 69.35% 2043 80.12% 2058 87.10%
2014 54.10% 2029 70.22% 2044 80.68% 2059 87.47%
2015 55.41% 2030 71.07% 2045 81.23% 2060 87.82%

2061 88.17%

Japan_s 17 types of CCR beneficial use applications are listed for year 2003 in Table 1 gBreakdown of Fields for the Effective Use of Coal Ashh from gPart 2 CCT Overview Environmental Protection Technologies (Technologies to Effectively Use Coal Ash): 5C1. Coal Ash Generation Process and Application Fieldsh at http://www.brain-c-jcoal.info/cctin japan-files/english/2_5C1.pdf167 Exhibit 5C-12

Beneficial Use Trend

0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00%

2001 2006 2011 2016 2021 2026 2031 2036 2041 2046 2051 2056 2061

YearBeneficial Use (%)

Actual Projected168 Applying the percent of CCR beneficially used in each year to the quantities of CCR shown above, the following future annual to ns of beneficially used CCR may be e xpected as displayed below in Exhibit 5C-13 . The monetized value of this future baseline projection is:

PV @3% discount PV @7% discount Economic value: $102,290 million PV $51,170 million PV Lifecycle social value: $1,554,323 million PV $777,541 million PV

Exhibit 5C-13 Baseline Projected Future CCR Beneficial Use (Short Tons)
Year CCR Beneficial Use Year CCR Beneficial Use Year CCR Beneficial Use Year CCR Beneficial Use 2012 69,234,181 2025 96,599,301 2038 119,713,602 2051 139,569,037 2013 71,516,427 2026 98,514,244 2039 121,345,430 2052 140,985,202 2014 73,767,022 2027 100,404,645 2040 122,958,473 2053 142,387,139 2015 75,986,563 2028 102,270,993 2041 124,553,122 2054 143,775,155 2016 78,175,638 2029 104,113,770 2042 126,129,762 2055 145,149,549 2017 80,334,827 2030 105,933,448 2043 127,688,769 2056 146,510,616 2018 82,464,703 2031 107,730,494 2044 129,230,513 2057 147,858,644 2019 84,565,827 2032 109,505,366 2045 130,755,358 2058 149,193,918 2020 86,638,755 2033 111,258,513 2046 132,263,659 2059 150,516,713 2021 88,684,034 2034 112,990,378 2047 133,755,767 2060 151,827,302 2022 90,702,202 2035 114,701,396 2048 135,232,025 2061 153,125,952 2023 92,693,789 2036 116,391,994 2049 136,692,770 2024 94,659,318 2037 118,062,592 2050 138,138,332

Step 3. Estimate Potential Induced Effect of RCRA Regulation on CCR Beneficial Use

After establishing a future baseline of CCR beneficial use annual tonnage, this step involved formulating three alternative sce narios whereby future CCR beneficial use under RCRA regul ation of CCR disposal could either:

o Scenario #1: Increase in beneficial use

o Scenario #2: Decrease

o Scenario #3: Remain unchanged from baseline169 Increases due to increased disposal costs we re estimated first and constitute the gbas e caseh of this RIA. By increasing dispo sal costs, electric utility plants face an g avoided disposal cost incentive h to ship their CCR farther for be neficial uses by other industries ; that is, utilities would be willing to pay more transportation costs to avoid the higher dis posal costs. Thus, RCRA regulat ion of CCR disposal would likel y open new markets at farther transport distances, or increase purchases by ex isting markets. The effect of this stimulus would be to inc rease CCR beneficial use. The concept of g avoided disposal cost incentive h is recognized and defined by the Amer ican Coal Ash Association (ACAA) on its website as follows:

g

If a [coal-fired electric util ity] plant markets its [CCR] into commercial applic ations, then disposal of this [CCR] is not required. Not only is a revenue stream crea ted for the [coal-fired electricity plant] but also the need to dispose of the [CCR ] is avoided. As discussed above, disposal is not just the transportation an d placement of [CCR] in a di sposal site. The need for future space is a concern. If [CCR is] marketed, then the need to develop future [CCR disposal] sites (including land acquisition, permitting, design and cons truction costs) is avoided .... It is not unc ommon for a company to help offset the cost s of transportation or placement at constructi on sites by providing the contractor or tr ucking firm a payment of some sort. For example, if the cost of disposal at a pl ant is normally four dollars a ton, then the company may arrange a payment of four dollars or less to the contractors to cover transportation and placement costs. The difference between the amount of this payment and the cost of dispos al is also referred to as “avoided disposal costs. h Source: ACAA Frequently Asked Question nr. 14 webpage at: http://acaa.affiniscape.com/ displaycommon.cfm?an= 1&subarticlenbr=5#Q14

On the other hand, some stakeholders have claimed that a Subt itle C ghazardous wasteh approach w ould have a gstigmah effect on CCR, reducing their use. That is, due to the label of ghazardous waste,h some purchas ers of CCR might opt to turn down the CCR for more expensive substitutes in fear that the CCR mi ght either harm their sales or create li ability, and generators might be reluctant to provide the material to users because of liability con cerns. The final alternative, that benefi cial use quantities remain the same, result s in no net costs or benefits for the Subtitle C approach becau se it is assumed that the baseline trend plays out the same as it would absent a rule . Thus, no further analysis of this option was necessary.

The two alternative Scenario an alyses (i.e., Scenario #1, Scenario #2) in this section build upon the ACAA_s historical CCR ben eficial use data. 144 ACAA data on the beneficial use was modified to remove the use of CCR in minefilling applica tions because the proposed rule d oes not address minefilling operations. Excluding 100% of the ACAA reported quantity of CCR used in minefilling results in a reduc tion of 1.13 million tons per year in the amount beneficially used. As a re sult, the 2005 quantity of beneficial use relied upon for our an alyses is 48.5 million tons per year of CCR, rather than the or iginal 49.6 million tons per year reported by ACAA.

144 Source: Historical CCR beneficial use data from the American Coal Ash Association (ACAA) gCoal Combustion Products -- Producti on & Use Statisticsh webpage at: http://acaa.affiniscape.com/displayc ommon.cfm?an=1&subarticlenbr=3170 Step 4: Estimate Potential Induced Increase in Future CCR Beneficial Use (Scenario #1)

Under the assumptions and numerical framework described below, th is RIA estimates that the Subtitle C option would initially in duce an increase of 28% in CCR beneficial uses. This growth estimat e is a generalized, aggregate es timate across all 15 existing CCR b eneficial use markets. Due to a lack of av ailable data (i.e., market locatio n, elasticity, cross-elasticity, et c.), this estimate does not t ake into account unique economic supply or economic demand conditions in any single market or for any particular benefici al use, relative to the genera lized aggregate estimate. However, key uses, such as use of fly ash as a Po rtland cement replacement, have gr eat opportunity for increased use , far above 28% in the initial year. For example, if fly ash use in concrete increased to a 30% repl acement rate for Portland cement (a very r easonable replacement rate, consistent with current specifications), fly ash usage could increa se by more than 100% from the 14 million t ons used annually at current replacement rates of 10% to 12%. One of the main barriers to th is increase usage is transportation costs. Because EPA did not have specific data on this market, this RIA does not spec ifically quantify it; however, it is exactly the type of use that increased disposal costs could foster.

The method presented below ma y be characterized as a " Raw Material Cost Method " which represents the 1 st stage of the generalized 4-stage materials flow lifecycle (MFL) through the economy. This 4-stage MFL conceptual framework has b een integrated into existing co st modeling software systems 145 used by government agencies and the priv ate sector, and consists of the following four material flow cradle-to-grave or cradle-to-cradle stages:

1 st

MFL stage: Raw materials acquisition
2 nd MFL stage: Product manufacturing
3 rd MFL stage: Product use, re-use, maintenance
4 th MFL stage: Recycling, waste management

This method evaluates the difference in ra w material acquisition cost under two altern ative conditions. The first condition (B aseline) represents current conditions without RCRA regulation of CCR disposal. The s econd condition (Subtitle C) repr esents future conditions wit h RCRA regulation for CCR disposed by electric utilities.

The economic mechanism in this estimation method, which affects different raw material acquisiti on costs under the two alternat ive conditions, is the g avoided disposal cost incentive h described above. In other words, it is the avoi ded disposal cost under RCRA regulation compared to the industry_s baseline disposal cost. This difference in cost is an incremental cost relative to baseline. From an economic standpoint, this represents an incremental economic incentive to electric utility plants to reduce or eliminate CCR dispos al, thereby reducing o r avoiding new regulatory compliance costs by increasing their future annu al supply of CCR to beneficial use markets. This g avoided disposal cost incentive h induced by RCRA regulation has already been anticipated in 2009 by at least one CCR beneficial use industry ( bold face added for emphasis):

145 Example cost modeling/estimation software systems using this 4-stage framework are 1. FAST, 2. EE Energy/ Environment Life-Cyc le Assessments, 3. EPA Enviro Accounting Method, and 4. TEAM (Tools for Environmental Analysis and Mangement); source: gTable 3-1. Overview of Life-Cycle Sta ges and Costs Considered by Software Systems and Toolsh at http://www.p2pays.org/ref/01/00047/00047e.htm171 g Using [coal] fly ash in building materials is nothing new, as it’s already incorporat ed in products including Portland cement and asphalt concrete. However, it’s estimated that 65 percent of fly ash from coal -fired power plants worldwide goes to landfills, with the U.S. reporting a slightly lower 57 percent, according to the American Coal Ash Association. Kane said the key to CalStar’s products is that they offer the same performan ce as aesthetics as traditional bricks, but without the energy u se. Currently, the cost to buy a ton of fly as h in the U.S. ranges from about $5 to $30, but that could change as fly ash disposal faces tighter government restrictions, he said. “The cost to send fly ash to landfills will go up, and utilities will be faced with finding the most beneficial use, ” Kane said. h 146

The baseline average g raw material acquisition cost h is $94.50/ton, consisting of CCR price, CCR di sposal cost, and CCR transportation cost:

1. CCR price: Price paid to electric ut ility plants by beneficial use industries for the purchase of CCR . ACAA identifies 15 industrial beneficial use markets involving the beneficial use of CCR, many of wh ich involve the construction industry. 147 The average price paid by these industries to electric ut ility plants is $3.00 per ton, across a reported range of $0 to $45 per ton. 148

2. CCR disposal cost: Cost to the electric utility industry for disposing CCR. This factor also represents the g avoided disposal cost
incentive h in the sense that this is an g avoided cost h to the electric utility industry for CCR tonnages beneficially used by other industries. A unitized gtotal costh ($ pe r ton) for CCR disposal consisting of both a 50-year amortized capital cost for CCR d isposal units plus a 50-year amortized O&M costs for CCR di sposal is used to monetize this cost factor. 149 The average baseline CCR disposal cost is $59/ton (source: Exhibit 3L ). This is additive to the gCCR priceh element becau se it represents a subs idy by electricity plants.
3. CCR transport cost: Average one-way CCR transport distan ce between electric utility plants a nd their CCR beneficial use customer industries. This method does not explicitly distinguish whether the transport cost is paid by the electric utility plants or b y the beneficial use industries. 150 Average CCR transport cost from electric utility plants to beneficial us e sites is estimated at ($0.26/mile/ton) 151 x (125 miles) 152 = $32.50/ton.

146 Source: Cleantech Group, gCalStar Gives Sneak Peek of Low-Carb on Brick Factory,h 29 Oct 2009 at http://cleantech.com/news/5217 /calstar-flyash-l ow-carbon-brick

147 ACAA lists 15 beneficial use markets: concrete, cement, flow able fill, structural fill/embankm ents, road base/sub-base, soil m odification, mineral filler in asphalt, snow/ice control, blasting grit/roo fing granules, mining applications, gypsum panel products, waste stabilization/solidificatio n, agriculture, construction aggregate, and miscellaneous uses.

148 $3 per-ton CCR price is from Column E of Exhibit 5C-1 ; this price represents the tonnage-w eighted average across a reported pri ce range of $0 to $45 per ton CCR.

149 Although in the short-run (< 3 years), marginal business decisi ons may be made relative to short-term O&M costs, long-term (> 3 years) business decisions usually consider both amortized cap ital costs and O&M costs.

150 The CCR price data used to monetize the CCR price factor above ar e reportedly based on gFOBh prices which may include some por tion of transport cost (e.g., transport vehicle loading to a tr ans-shipment location).

151 $0.26 per-ton-per-mile is the midpoint of the $0.15 to $0.37 per-ton-per-mile range reported in gEstimation of the Marginal Gr eenhouse Gas Abatement Curve for the Beneficial Use of Fly Ash as a Substitute for Portland Cement in Ready-Mix Concrete Production,h EPA Office of Resource Conserv ation and Recovery (ORCR), 19 June 2009, page 11.

152 125 miles is the midpoint of the 100 to 150 mile range reported in footnote 74 on page 4-8 of EPA_s 03 June 2008 gReport to Co ngress: Study on Increasing the Usage of Recovered Mineral Components in Federal Funded Projects Involving Procurement of Cement or Concrete to Address the Safe, Acc ountable, Flexible, Efficient Transportation, Equity Act: A Legacy for Uses by the EPA, the Department of Transportation (DOT) and the Department of Energy ( DOE),h report nr. EPA530-R-08-007, available at http://www.epa.gov/waste/conserve/tools/cpg/products/cement2.htm.172 In comparison to these baseline g raw materials acquisition cost h elements, CCR disposal costs are estimated to be $83/ton for the Subtitle C option (source: Exhibit 4K ). While this represents a 44% incr ease ($26/ton) over the baseline disposal cost of $59/ton, this ignores the CCR price and the transportation cost elements. Factoring these co mponents in, the $26/ton increase represents a 28% increase abov e the total baseline raw material cost of $94.50/t on. This RIA applies this 28% growth factor to repres ent demand elasticity 153 assumptions of:

+0.64 with respect to the CCR g avoided disposal cost incentive h factor (i.e., +28%/+44%). +1.00 with respect to total g raw material acquisition cost h consisting of all three cost fa ctors included (i.e., +28%/+28%).

This RIA applies the elasticity estim ate of 1.0 in reference to the g raw material acquisition cost h to represent the poten tial increase in CCR beneficial use by 28% over the baseline under the Subtitle C op tion. The other regulatory opti ons are proportionately adjusted below. In comparison to historical annual percentage changes in CCR beneficial use tonnages, this 28% increase is a reasonable assumption as it falls between the -22.6% decrease and +55.2% increa se min-max range (annual mean = +8.2% increase) over the 43 year period 1966 to 20 08, 154 as displayed in Exhibit 5C-14 below.

Exhibit 5C-14 Historical Annual Percenta ge Change in CCR Bene ficial Use (1966-2008)
A B C D E F (E/C) G

Item Year CCR generation (tons) CCR disposal (tons) CCR beneficial use (tons) Percent CCR beneficial use Annual % change in CCR beneficial use tons 1 1966 26,000,000 22,000,000 4,000,000 15% 2 1967 28,000,000 23,000,000 5,000,000 18% 25.0% 3 1968 30,000,000 24,000,000 6,000,000 20% 20.0% 4 1969 31,500,000 26,000,000 5,500,000 17% -8.3% 5 1970 39,000,000 33,200,000 5,800,000 15% 5.5% 6 1971 41,500,000 32,500,000 9,000,000 22% 55.2% 7 1972 46,000,000 38,000,000 8,000,000 17% -11.1% 8 1973 50,000,000 41,500,000 8,500,000 17% 6.3% 9 1974 59,000,000 50,000,000 9,000,000 15% 5.9% 10 1975 60,000,000 50,000,000 10,000,000 17% 11.1% 11 1976 62,000,000 50,000,000 12,000,000 19% 20.0% 12 1977 67,000,000 53,000,000 14,000,000 21% 16.7% 13 1978 68,000,000 52,000,000 16,000,000 24% 14.3% 14 1979 75,500,000 60,000,000 15,500,000 21% -3.1% 15 1980 66,000,000 54,000,000 12,000,000 18% -22.6% 16 1981 68,000,000 51,500,000 16,500,000 24% 37.5%

153 In economics, the elasticity of supply indicates the responsive ness of the quantity of a product or service supplied to the ma rket relative to a change in its price (i.e., (% change in quantity supplied) / (% change in its price)). Simi larly, the elasticity of demand i ndicates the responsiveness of t he quantity of market demand for a product or service relative to a change in its price (i.e., (% chan ge in quantity demanded) / (% change in its price)).

154 Historical CCR beneficial us e data for 1966-2008 from ACAA at http://www.acaa-usa .org/associations/8003 /files/Revised_1966_200 7_CCP_Prod_v_Use_Chart.pdf173 Exhibit 5C-14 Historical Annual Percenta ge Change in CCR Bene ficial Use (1966-2008)
A B C D E F (E/C) G

Item Year CCR generation (tons) CCR disposal (tons) CCR beneficial use (tons) Percent CCR beneficial use Annual % change in CCR beneficial use tons 17 1982 65,000,000 51,000,000 14,000,000 22% -15.2% 18 1983 64,000,000 51,000,000 13,000,000 20% -7.1% 19 1984 69,000,000 53,000,000 16,000,000 23% 23.1% 20 1985 66,000,000 48,000,000 18,000,000 27% 12.5% 21 1986 67,500,000 53,000,000 14,500,000 21% -19.4% 22 1987 82,000,000 63,000,000 19,000,000 23% 31.0% 23 1988 83,000,000 62,500,000 20,500,000 25% 7.9% 24 1989 87,000,000 69,500,000 17,500,000 20% -14.6% 25 1990 86,000,000 64,000,000 22,000,000 26% 25.7% 26 1991 88,000,000 65,500,000 22,500,000 26% 2.3% 27 1992 82,000,000 62,000,000 20,000,000 24% -11.1% 28 1993 88,000,000 69,000,000 19,000,000 22% -5.0% 29 1994 89,000,000 66,000,000 23,000,000 26% 21.1% 30 1995 92,000,000 68,000,000 24,000,000 26% 4.3% 31 1996 102,000,000 76,000,000 26,000,000 25% 8.3% 32 1997 104,000,000 74,500,000 29,500,000 28% 13.5% 33 1998 108,000,000 77,000,000 31,000,000 29% 5.1% 34 1999 107,000,000 74,000,000 33,000,000 31% 6.5% 35 2000 108,500,000 76,500,000 32,000,000 29% -3.0% 36 2001 117,930,542 80,811,221 37,119,321 31% 16.0% 37 2002 128,703,572 83,180,316 45,523,256 35% 22.6% 38 2003 121,744,571 75,360,166 46,384,405 38% 1.9% 39 2004 122,465,119 73,375,301 49,089,818 40% 5.8% 40 2005 123,126,093 73,513,552 49,612,541 40% 1.1% 41 2006 124,795,124 70,591,954 54,203,170 43% 9.3% 42 2007 131,127,693 75,088,688 56,039,005 43% 3.4% 43 2008 136,073,107 75,479,447 60,593,660 45% 8.1% Minimum annual %= -22.6% Maximum annual % = 55.2% Median annual % = 6.4% Mean annual % = 8.2% Overall percent growth = 1414.8% Average annual compound growth = 6.5%174 This is a limiting analysis because it does not include other developments that may be expected increasingly to push CCR to ben eficial use:

1. Aspects of the proposed CCR rule: This anal ysis does not take into account that so me RCRA regulatory optio ns for CCR disposal require electricity plants to move to dry management of CCR, either through changes to air pollution control strategies or thro ugh drying of CCR after they have been gene rated. This will make the material more amenable to beneficial uses.
2. The analysis is based on current market conditions: It does no t take into account new technolog ies and products now being devel oped, for example, involving the use of CCR in brick construction. 155 An increased g avoided disposal cost incentive h could be a great boon to such new beneficial use techno logies, applications, and products.

x Comparison of “ Raw Materials Acquisition Cost Method ” to “ Travel Cost Method ”

The method applied above involved three cost components of the g raw material acquisition cost ,h not just in relation to the transportation cost component, which is relatively narrower approach that can be called a g Transportation Cost Method .h Compared to this other method, the raw material acquisition cost method pr ovides a smaller estimate of effect because the incremental cost is evaluated relative to a broader set of costs thereby translating numerically into a sma ller percentage change, rather than relativ e to only one cost fa ctor which would tran slate into a relatively larger percentage change. Th is methodological difference may be illustra ted by using the calculation numbers applie d above, to only the transportation cost factor. Using a si mplistic transportation distance model whic h uses the CCR disposal unit cost ($ per ton) to determine the average circular radius of a CCR tran sportation market between elect ricity utility plant suppli ers of CCR and their benefic ial users customers, the increase in transport distance would be calcu lated as follows (relative to the 2005 49.6 million tons CCR benefi cially used as reported by the ACAA):

x Baseline transportation cost (without CCR rule) ($0.26/mile/ton) x (125 miles one-way aver age CCR transport distance) x (49.6 million tons/year beneficial use in 2005) = $1,61 2 million/year transport cost

x Hypothetical new transpor tation cost (with rule) Transport subsidy equivalency = ($85/ton avoided disposal cost under rule) v ($59/ton avoided disposal cost without rule) = $26 /ton subsidy equivalency (49.6 million tons/year beneficial use) x ($26/ton subsidy equivalency) = $1,290 million per year subsidy equivalency

x Hypothetical new transport distance: [($1,612 million/year) + ($1,290 million/year)] / (49.6 million tons per year benefici al use) / ($0.26/mile/ton) = 225 miles Percentage increase in transport distance: [(225 miles) v (125 miles)] / (125 miles) = 80 % increase in radial transport distance

155 Several companies are developing technologies to convert CCR into bricks used in construction, and one such technology was rec ently commercialized at a power plant in Wisconsin. Some of these technologies have the potential for using 100% CCR (fly ash) in brick production, as opposed to th e conventional 30%-50% limit for replacing Portland cement in concrete.175 x Hypothetical expansion of CC R customer delivery area: Baseline customer area @125 miles radial transport distance = (3.1415 x (125 mile s)^2) = 49,100 square miles Expanded customer area @225 miles radial transport distance = (3.1415 x (225 miles)^2) = 159,000 square miles Incremental increase in customer area = (159,000 v 49,100 sq. miles) / (49,100 sq.mile s) = 124% increase in delivery area

Step 5: Estimate Hypothetical “ Stigma ” Decrease in Future CCR Beneficial Use (Scenario #2)

A number of industry and state government st akeholders have asserted to the EPA, that designating CCR as a hazardous waste (eve n if the designation is only applicable to those CCR that are disposed of) would create a gstigmah that would reduc e or curtail or elimi nate the beneficial use of CCR. This RIA presents an alternative stigma effect scenario in an effort to evaluate what countervailing i mpact that gstigmah may have on the increased beneficial use of CCR estimated in this RIA above . This potential reduction scenario assume s different potential impacts in three categ ories of beneficial CCR usage (u ses covered in the CPGs, conso lidated uses, and unconsolidated uses). For documentation of the calculations discussed in this section, see Appendix K13

.

x “ Stigma ” on CCR in Consolidated Uses Specified in Comprehensive Procurement Guidelines

First, some uses for CCR involve the producti on of specific products that are expressly covered by the federal Comprehensive Pr ocurement Guidelines (CPGs), which require procuri ng agencies that spend more than $10,000 a y ear on an item to buy products containing r ecovered materials. Procuring agencies are federal, state, and local agencies, and their cont ractors, that use appropriated federal fun ds. For example, if a county agency spends more than $10,000 a year on an EPA-designated item and part of that money is from appropriated federal fun ds, then the agency must purchase that item made from recovered materials. 156 As such, if there were any impact s due to stigma, EP A believes that the markets for these uses are less likely to be affected by a h azardous waste label for CCR. CCR categories currently covered und er the CPGs include concrete/concrete products/grout, flowab le fill, and blasting grit/roofing granules.

According to U.S. Census data, the pub lic portion of total cons truction spending equaled 20.7% in 2005, 21.4% in 2006, 24.6% in 2007, and had swelled to 35.4% by Nov. 2009 (likely in di rect relationship to the current state of the economy and current federal stimul us spending). Similarly, U.S. EPA (2008d) estimates that fo r concrete projects, the cement demand attr ibutable to federal concrete projects r eflects approximately 20% of the annual total demand. EPA then apportio ned the amounts of CCR usage into a public construction vs. a p rivate construction split. Based on the Census Bureau and EPA data, 157 EPA established a 25% / 75% split of th e totals for these products, such that 25% of the total usage is recognized as accruing to public constructi on and 75 % to private construction.

156 Agencies may elect not to purchase designated items when the cost is unreasonable; inadequate competition exists; items are no t available within a reasonable period of time; or items do not meet the agency's reasonable performance specifications.

157 Source: EPA gReport to Congress: Study on Increasing the Usage of Recovered Mineral Components in Federal Funded Projects Invo lving Procurement of Cement or Concrete to Address the Safe, Accountable, Flexible, Efficient Tr ansportation, Equity Act: A Legacy for Uses by the EPA, the De partment of Transportation (DOT) and the Department of Energy (DOE),h EPA530-R-08- 007, June 3, 2008 at: http://www.epa.gov/ waste/conserve/tools/cpg/products/cement2.htm176 Given that the public procurement of these products should continue because of their CPG designation, this RIA assumed that the re will be no negative impact on the public portion of CCR usage. That is, the demand for CPG products made from CCR will be the same as it currently is for the public portion of the construction market. However, this RIA assumes a 50% reduction of total private uses. 158 This results in an estimated 6.8 million tons per year reduction in CCR use for this category of beneficial uses.

x “ Stigma ” for CCR in Other Consolidated Uses

Not all consolidated uses of CCR are cove red under federal CPGs. Thus, this scenar io also estimated the potential impacts on t he use of CCR in non-CPG, consolidated uses. These CCR cat egories include blended cement/raw feed fo r clinker, mineral filler in asphalt, gy psum panel products, waste stabilization/solidification, and miscellaneous/other. In the case of CCR used in blended cement, mineral fill er v asphalt, gypsum for wallboard, and miscellaneous/other applications, this RIA assumed that 50% of these uses will be reduced. Thus, the potential reductions in this category will total 6.8 million tons per year.

For the use of CCR in waste stabilization/solidification applica tions, this RIA assumed that stigma will not have a negative im pact. For this use, the CCR are already being used in a waste management context. The CCR are used in secure landfills to immobilize wastes t ypically more hazardous than the CCR themselves. Therefore, this RIA projects no reduction in the future annu al tonnage of CCR used for this purpose.

x “ Stigma ” for Unconsolidated Uses

In addition to the consolidated uses of CCR discussed above, CCR can be employed in unc onsolidated uses. For some of these use s, the CCR products may be more similar to the disposed material proposed to be regulated. In addition, they have typically not been chem ically fixed within a product. As a result, stigma concerns may be more pl ausible. Markets that involve unconsolidated uses of CCR include structural fill/embankments, road base/sub-base, soil modification/stabiliz ation, snow/ice control, aggregate, agriculture, and miscellane ous/other. For purpose of the sensitivity analysis, this RIA assumed a poten tial reduction of 80%. 159 This results in an additional 11.1 million tons per year reduction of beneficially used CCR. By adding the 6.8 million tons from CPG consolid ated uses, to the 6.8 million tons from no n-CPG consolidated uses, plus the 11.1 million tons from unconsolidated us es, this RIA estimates that a severe stigma effect would le ad to a 51% reduction of beneficial use.

158 The 50% reduction is considered a worst- case assumption because these materials prov ide significant value at competitive costs v for example, concrete that includes fly ash typically performs better than non-CCR concrete, and is likely to retain favorable treatment under Leadership in Energy and Environmental Design (LEED). In addition, academic studies of gstigmah associated with pr oducts rarely leads to decreased usage to this extent.

159 EPA has assumed this high gstigmah effect because a number of the uses may appear close to the di sposal scenario, e.g., struct ural fills. Also, it is widely recognized that CCR in unconsolidated uses may present risks, if used in the wrong conditions. (Indeed, EPA takes comment on unconsolidate d uses in the preamble to the CCR proposed rule due to the increased potential for risks.) Some of these uses are likely to be particularly sensitive to public concerns and liability concerns. These include agricultural uses and dispersive uses, like use of bottom ash or boiler slag for ice and snow control. Therefore, if stigma do es have a role to play, EPA believes it is reasonable to assume it will be significant for unconsolidated us es. Even for the purposes of a worst-case sensitivity analysi s, however, EPA believes that, given the success of many of these uses in states w ith rigorous benefici al use programs, gstigmah will not completely eliminate such uses ; therefore, it has estimated a decrease of 80%.177 Step 6: Apply Estimated Induced Effect Scenarios to Baseline CCR Beneficial Use

Applying the first effect (increas e in the sale of CCR due to a d ecrease in price), EPA noted that a 28% increase with an elast icity of 1.0 would makes sense when there is ample room for growth. But as the market becomes more and more sa turated, it is less and less likely that unit elasticity would apply. Instead, the elasticity is likely to decrease with in creasing saturation. To account for this, the be neficial use increase was set to 28% of either the existing benefi cial use tonnage, or to 28% of the remain ing CCR tonnage, whichever was less. In o ther words, once beneficial use was greater than 50% of total CCR, the increase would be constraine d to 28% of what was left over after ben eficial use was accounted for. EPA also accounted for the fact that the price ch ange would not fully affect the market until the rule (and the refore the costs) had been phased in. Full implementation was assumed to occu r by 2019. However, industry would undoubtedly likely attempt to p repare for these increased costs as soon as a final ru le was passed, and therefore th e beneficial use increases we re assumed to linearly a pproach 28% by 2019. The projected tons of beneficial use unde r Subtitle C are shown in Exhibit 28 below.

As seen below, subtitle C in EPA_s analysis would drive more CCR toward beneficial use due to th e increased costs of disposal. However, as discussed in Step 4 above, there is also the possibility that there would be a stigma associated with the ghazardous wasteh des ignation. Here the beneficial use of CCR would be 49% of the ba seline due to stigma. Since the maximum CC R beneficially used is less than 50% of all CCR, the constraint imposed on the straight 28% increase would not be necessary. Thus, once the full 51% decrease and 28% increase are accounted for, the future CCR beneficial use annual t onnages are calculated as displayed below in Exhibit 5C-15

.178 Exhibit 5C-15 Two Alternative Scenarios of Projected Future CCR Beneficial Use 2012-2061 (Short Tons)

Year Scenario #1: w/out Stigma Scenario #2: w/Stigma Year Scenario #1: w/out Stigma Scenario #2: w/Stigma 2012 71,527,755 33,924,749 2037 128,297,364 82,753,160 2013 75,999,399 36,206,995 2038 129,708,417 84,404,170 2014 80,338,539 38,457,590 2039 131,105,658 86,035,997 2015 84,549,013 40,677,131 2040 132,489,375 87,649,041 2016 88,634,566 42,866,206 2041 133,859,848 89,243,690 2017 92,598,855 45,025,395 2042 135,217,354 90,820,330 2018 96,445,450 47,155,270 2043 136,562,164 92,379,337 2019 100,177,835 49,256,395 2044 137,894,545 93,921,081 2020 101,892,669 51,329,323 2045 139,214,759 95,445,925 2021 103,587,595 53,374,602 2046 140,523,061 96,954,227 2022 105,263,001 55,392,770 2047 141,819,704 98,446,334 2023 106,919,270 57,384,357 2048 143,104,936 99,922,592 2024 108,556,775 59,349,885 2049 144,378,997 101,383,338 2025 110,175,889 61,289,868 2050 145,642,128 102,828,900 2026 111,776,973 63,204,812 2051 146,894,561 104,259,605 2027 113,360,387 65,095,213 2052 148,136,525 105,675,770 2028 114,926,484 66,961,561 2053 149,368,245 107,077,707 2029 116,475,608 68,804,337 2054 150,589,942 108,465,723 2030 118,008,102 70,624,016 2055 151,801,831 109,840,117 2031 119,524,301 72,421,062 2056 153,004,125 111,201,184 2032 121,024,534 74,195,934 2057 154,197,031 112,549,212 2033 122,509,126 75,949,081 2058 155,380,753 113,884,485 2034 123,978,394 77,680,946 2059 156,555,491 115,207,281 2035 125,432,652 79,391,964 2060 157,721,441 116,517,870 2036 126,872,208 81,082,562 2061 158,878,794 117,816,520

Step 7: Estimate Potential Induced Effect s on Future Annual Tonnage s of CCR Beneficial Use

Exhibit 5C-16 below shows beneficial use projected under Subtitle C. Benefi cial use under the increasing dispos al cost scenario would lead to an increase of 28% above the baseline estimate. However, as th e market becomes more and more saturated, it will likely become harder to increase beneficial use. Thus, the incr ease is constrained to 28% of the remaini ng unused CCR. The elasticity column represen ts the effective percent change in quantity for each percent change in price once this constraint has been accounted for. While the elasticity is assumed to initially be 1.0, the effect of market saturation drives that elasticity towards zero over time as seen below.179 Exhibit 5C-16 Scenario #1: Increase in Future CCR Benefi cial Use Under the Subtitle C Option

Year CCR generation (tons) % beneficial use Beneficial use (tons) % increase Increased beneficial use (tons) Increase w/o mine filling (tons) Implied elasticity 2012 134,764,862 53.08% 71,527,755 3.31% 2,293,574 2,241,198 0.95 2013 135,558,881 56.06% 75,999,399 6.27% 4,482,972 4,380,599 0.90 2014 136,352,901 58.92% 80,338,539 8.91% 6,571,517 6,421,451 0.85 2015 137,146,920 61.65% 84,549,013 11.27% 8,562,450 8,366,919 0.80 2016 137,940,940 64.26% 88,634,566 13.38% 10,458,928 10,220,089 0.76 2017 138,734,959 66.75% 92,598,855 15.27% 12,264,028 11,983,968 0.73 2018 139,528,979 69.12% 96,445,450 16.95% 13,980,748 13,661,485 0.69 2019 140,322,998 71.39% 100,177,835 18.46% 15,612,008 15,255,494 0.66 2020 141,117,018 72.20% 101,892,669 17.61% 15,253,914 14,905,577 0.63 2021 141,911,037 72.99% 103,587,595 16.81% 14,903,561 14,563,225 0.60 2022 142,705,057 73.76% 105,263,001 16.05% 14,560,799 14,228,291 0.57 2023 143,499,076 74.51% 106,919,270 15.35% 14,225,480 13,900,629 0.55 2024 144,293,096 75.23% 108,556,775 14.68% 13,897,458 13,580,097 0.52 2025 145,087,115 75.94% 110,175,889 14.05% 13,576,588 13,266,555 0.50 2026 145,881,135 76.62% 111,776,973 13.46% 13,262,729 12,959,864 0.48 2027 146,675,154 77.29% 113,360,387 12.90% 12,955,743 12,659,887 0.46 2028 147,469,174 77.93% 114,926,484 12.37% 12,655,491 12,366,492 0.44 2029 148,263,193 78.56% 116,475,608 11.87% 12,361,839 12,079,545 0.42 2030 149,057,213 79.17% 118,008,102 11.40% 12,074,654 11,798,919 0.41 2031 149,851,232 79.76% 119,524,301 10.95% 11,793,807 11,524,485 0.39 2032 150,645,252 80.34% 121,024,534 10.52% 11,519,168 11,256,118 0.38 2033 151,439,271 80.90% 122,509,126 10.11% 11,250,612 10,993,695 0.36 2034 152,233,291 81.44% 123,978,394 9.72% 10,988,015 10,737,095 0.35 2035 153,027,310 81.97% 125,432,652 9.36% 10,731,256 10,486,198 0.33 2036 153,821,330 82.48% 126,872,208 9.00% 10,480,214 10,240,889 0.32 2037 154,615,349 82.98% 128,297,364 8.67% 10,234,772 10,001,052 0.31 2038 155,409,369 83.46% 129,708,417 8.35% 9,994,815 9,766,574 0.30 2039 156,203,388 83.93% 131,105,658 8.04% 9,760,228 9,537,345 0.29 2040 156,997,408 84.39% 132,489,375 7.75% 9,530,902 9,313,255 0.28 2041 157,791,427 84.83% 133,859,848 7.47% 9,306,725 9,094,198 0.27 2042 158,585,447 85.26% 135,217,354 7.20% 9,087,592 8,880,069 0.26 2043 159,379,466 85.68% 136,562,164 6.95% 8,873,395 8,670,764 0.25 2044 160,173,486 86.09% 137,894,545 6.70% 8,664,032 8,466,182 0.24 2045 160,967,505 86.49% 139,214,759 6.47% 8,459,401 8,266,224 0.23 2046 161,761,525 86.87% 140,523,061 6.24% 8,259,402 8,070,792 0.22 2047 162,555,544 87.24% 141,819,704 6.03% 8,063,938 7,879,791 0.22 2048 163,349,564 87.61% 143,104,936 5.82% 7,872,911 7,693,126 0.21 2049 164,143,583 87.96% 144,378,997 5.62% 7,686,228 7,510,706 0.20180 Exhibit 5C-16 Scenario #1: Increase in Future CCR Benefi cial Use Under the Subtitle C Option

Year CCR generation (tons) % beneficial use Beneficial use (tons) % increase Increased beneficial use (tons) Increase w/o mine filling (tons) Implied elasticity 2050 164,937,603 88.30% 145,642,128 5.43% 7,503,796 7,332,440 0.19 2051 165,731,622 88.63% 146,894,561 5.25% 7,325,524 7,158,239 0.19 2052 166,525,642 88.96% 148,136,525 5.07% 7,151,323 6,988,016 0.18 2053 167,319,661 89.27% 149,368,245 4.90% 6,981,106 6,821,687 0.18 2054 168,113,681 89.58% 150,589,942 4.74% 6,814,787 6,659,166 0.17 2055 168,907,700 89.87% 151,801,831 4.58% 6,652,282 6,500,372 0.16 2056 169,701,720 90.16% 153,004,125 4.43% 6,493,509 6,345,224 0.16 2057 170,495,739 90.44% 154,197,031 4.29% 6,338,387 6,193,644 0.15 2058 171,289,759 90.71% 155,380,753 4.15% 6,186,835 6,045,554 0.15 2059 172,083,778 90.98% 156,555,491 4.01% 6,038,778 5,900,878 0.14 2060 172,877,798 91.23% 157,721,441 3.88% 5,894,139 5,759,541 0.14 2061 173,671,817 91.48% 158,878,794 3.76% 5,752,842 5,621,471 0.13

Exhibit 5C-17 below shows beneficial use projected under Su btitle C with a worst-case stigma assump tion. Increased beneficial use under the increasing disposal costs of a Subtitle C ru le are not accounted for. However, as s oon as the rule becomes effective in 2012, the Scenario #2 of this RIA simulates a stigma effect which decreases the tons bene ficially used by 51%. Once the disposal cost effect is fully c aptured by 2019, and the market has adjusted to stigma, beneficial use is assumed to grow at the same rate it would have otherwise.

Exhibit 5C-17 Scenario #2: Decrease in Future CCR Beneficial Use Because of Stigma U nder Subtitle C Option

Year CCR generation

tons % beneficial use Beneficial use

tons %
Decrease Decrease tons Decrease w/out mine filling tons 2012 134,764,862 25.17% 33,924,749 -51.00% -35,309,432 -33,342,859 2013 135,558,881 26.71% 36,206,995 -49.37% -35,309,432 -33,342,859 2014 136,352,901 28.20% 38,457,590 -47.87% -35,309,432 -33,342,859 2015 137,146,920 29.66% 40,677,131 -46.47% -35,309,432 -33,342,859 2016 137,940,940 31.08% 42,866,206 -45.17% -35,309,432 -33,342,859 2017 138,734,959 32.45% 45,025,395 -43.95% -35,309,432 -33,342,859 2018 139,528,979 33.80% 47,155,270 -42.82% -35,309,432 -33,342,859 2019 140,322,998 35.10% 49,256,395 -41.75% -35,309,432 -33,342,859 2020 141,117,018 36.37% 51,329,323 -40.75% -35,309,432 -33,342,859 2021 141,911,037 37.61% 53,374,602 -39.81% -35,309,432 -33,342,859 2022 142,705,057 38.82% 55,392,770 -38.93% -35,309,432 -33,342,859 2023 143,499,076 39.99% 57,384,357 -38.09% -35,309,432 -33,342,859 2024 144,293,096 41.13% 59,349,885 -37.30% -35,309,432 -33,342,859 2025 145,087,115 42.24% 61,289,868 -36.55% -35,309,432 -33,342,859181 Exhibit 5C-17 Scenario #2: Decrease in Future CCR Beneficial Use Because of Stigma U nder Subtitle C Option

Year CCR generation

tons % beneficial use Beneficial use

tons %
Decrease Decrease tons Decrease w/out mine filling tons 2026 145,881,135 43.33% 63,204,812 -35.84% -35,309,432 -33,342,859 2027 146,675,154 44.38% 65,095,213 -35.17% -35,309,432 -33,342,859 2028 147,469,174 45.41% 66,961,561 -34.53% -35,309,432 -33,342,859 2029 148,263,193 46.41% 68,804,337 -33.91% -35,309,432 -33,342,859 2030 149,057,213 47.38% 70,624,016 -33.33% -35,309,432 -33,342,859 2031 149,851,232 48.33% 72,421,062 -32.78% -35,309,432 -33,342,859 2032 150,645,252 49.25% 74,195,934 -32.24% -35,309,432 -33,342,859 2033 151,439,271 50.15% 75,949,081 -31.74% -35,309,432 -33,342,859 2034 152,233,291 51.03% 77,680,946 -31.25% -35,309,432 -33,342,859 2035 153,027,310 51.88% 79,391,964 -30.78% -35,309,432 -33,342,859 2036 153,821,330 52.71% 81,082,562 -30.34% -35,309,432 -33,342,859 2037 154,615,349 53.52% 82,753,160 -29.91% -35,309,432 -33,342,859 2038 155,409,369 54.31% 84,404,170 -29.49% -35,309,432 -33,342,859 2039 156,203,388 55.08% 86,035,997 -29.10% -35,309,432 -33,342,859 2040 156,997,408 55.83% 87,649,041 -28.72% -35,309,432 -33,342,859 2041 157,791,427 56.56% 89,243,690 -28.35% -35,309,432 -33,342,859 2042 158,585,447 57.27% 90,820,330 -27.99% -35,309,432 -33,342,859 2043 159,379,466 57.96% 92,379,337 -27.65% -35,309,432 -33,342,859 2044 160,173,486 58.64% 93,921,081 -27.32% -35,309,432 -33,342,859 2045 160,967,505 59.30% 95,445,925 -27.00% -35,309,432 -33,342,859 2046 161,761,525 59.94% 96,954,227 -26.70% -35,309,432 -33,342,859 2047 162,555,544 60.56% 98,446,334 -26.40% -35,309,432 -33,342,859 2048 163,349,564 61.17% 99,922,592 -26.11% -35,309,432 -33,342,859 2049 164,143,583 61.77% 101,383,338 -25.83% -35,309,432 -33,342,859 2050 164,937,603 62.34% 102,828,900 -25.56% -35,309,432 -33,342,859 2051 165,731,622 62.91% 104,259,605 -25.30% -35,309,432 -33,342,859 2052 166,525,642 63.46% 105,675,770 -25.04% -35,309,432 -33,342,859 2053 167,319,661 64.00% 107,077,707 -24.80% -35,309,432 -33,342,859 2054 168,113,681 64.52% 108,465,723 -24.56% -35,309,432 -33,342,859 2055 168,907,700 65.03% 109,840,117 -24.33% -35,309,432 -33,342,859 2056 169,701,720 65.53% 111,201,184 -24.10% -35,309,432 -33,342,859 2057 170,495,739 66.01% 112,549,212 -23.88% -35,309,432 -33,342,859 2058 171,289,759 66.49% 113,884,485 -23.67% -35,309,432 -33,342,859 2059 172,083,778 66.95% 115,207,281 -23.46% -35,309,432 -33,342,859 2060 172,877,798 67.40% 116,517,870 -23.26% -35,309,432 -33,342,859 2061 173,671,817 67.84% 117,816,520 -23.06% -35,309,432 -33,342,859182 Exhibit 5C-18 below shows the projected future annual CCR generation and three trends in beneficial use (i.e., scen ario #1 increase without stigma, scenario #2 decrease with stigma, and scenario #3 no cha nge in relation to the increasing baseline trend). Scenario #1 assumes that the increased cost of disposal from regulati on will induce the electric ut ility industry to seek out additional CCR beneficial use markets thereby increasing future annual beneficial use of CCR above the increasing baseline trend. Expe riences with the EPA RCRA Subtitle C h azardous waste program indicate that indus try often increases annual recycling and materi als recovery rates af ter RCRA regulation (e.g., after EPA has listed certain types and sources of secondary industrial materials as RCRA ghazardous wastesh). Thus, EPA regards the increase d beneficial use Scenario #1 as the most likel y outcome. A second curve in the Exhibit belo w displays the Scenario #2 decreased CCR benefic ial use stigma effect under the Subtitle C regulatory option (this RIA does not apply scenario #2 under the Subtitle D options). The E xhibit also presents Scenario #3 in which future annua l CCR beneficial use is projected to contin ue on its recent upwardly increasing trend line without any induced future change as a result of the CCR rule. The future annual beneficial use tonnages for both scenario #1 and scenario #2 are estimated in this RIA incrementally relative to the scenario #3 baseline trend.183 Exhibit 5C-18

Beneficial Use Trends

0 15,000,000 30,000,000 45,000,000 60,000,000 75,000,000 90,000,000 105,000,000 120,000,000 135,000,000 150,000,000 165,000,000 180,000,000

2012 2017 2022 2027 2032 2037 2042 2047 2052 2057

YearCCRs (Short Tons)

CCRs Generated Baseline BU Subtitle C BU Subtitle C w/Stigma184 Step 8: Monetize Potential Induced Effects on Future CCR Beneficial Use

Based on multiplying a unitized average monetized social benefit value of $559 per ton consisting of (a) the $474 per ton unitized lifecycle benefit value, plus the (b) $85 per ton aver age avoided disposal cost es timated for the subtitle C option, to the 50-year (i.e. , 2012 to 2061) projected future baselin e tonnage displayed in Exhibit 5C-18 above, produces an estimated future ba seline social benefit value from CCR beneficial use of:

PV @3% discount PV @7% discount Future baseline economic value: $102,290 million PV $51,170 million PV Future baseline lifecycle social value*: $1,554,323 million PV $777,541 million PV (* Includes avoided CCR disposal cost to electric utility industry)

x Monetization of Scenario #1 (Induced Increase in CCR Beneficial Use)

Exhibit 5C-19 below provides an estimate of the potential increase in future annual t onnage and economic and social benefits associated with CCR beneficial uses (not including minefilling) that could occur as a result of the C CR proposed rule. This quantity is increme ntally calculated each year as the quantity projected under the Subtitle C option (without stigma), less the quantity projected under the baselin e.

Exhibit 5C-19 Scenario #1: Benefit from Future Increase in CCR Beneficial User Under Subtitle C “Special Waste” Nominal Benefits (Millions) Discounted Benefits @ 3% (Millions) Discounted Benefits @ 7% (Millions) Year CCR Beneficial
Use Increase (tons) Econ Social Econ Social Econ Social 2012 2,241,198 $82 $1,253 $82 $1,253 $82 $1,253 2013 4,380,599 $161 $2,449 $156 $2,377 $151 $2,289 2014 6,421,451 $236 $3,590 $223 $3,384 $206 $3,135 2015 8,366,919 $308 $4,677 $282 $4,280 $251 $3,818 2016 10,220,089 $376 $5,713 $334 $5,076 $287 $4,359 2017 11,983,968 $441 $6,699 $380 $5,779 $314 $4,776 2018 13,661,485 $503 $7,637 $421 $6,396 $335 $5,089 2019 15,255,494 $561 $8,528 $456 $6,934 $350 $5,311 2020 14,905,577 $548 $8,332 $433 $6,578 $319 $4,850 2021 14,563,225 $536 $8,141 $411 $6,239 $291 $4,428 2022 14,228,291 $523 $7,954 $389 $5,918 $266 $4,043 2023 13,900,629 $511 $7,771 $369 $5,614 $243 $3,692 2024 13,580,097 $500 $7,591 $350 $5,324 $222 $3,371 2025 13,266,555 $488 $7,416 $332 $5,050 $203 $3,077185 Exhibit 5C-19 Scenario #1: Benefit from Future Increase in CCR Beneficial User Under Subtitle C “Special Waste” Nominal Benefits (Millions) Discounted Benefits @ 3% (Millions) Discounted Benefits @ 7% (Millions) Year CCR Beneficial
Use Increase (tons) Econ Social Econ Social Econ Social 2026 12,959,864 $477 $7,245 $315 $4,790 $185 $2,810 2027 12,659,887 $466 $7,077 $299 $4,542 $169 $2,565 2028 12,366,492 $455 $6,913 $284 $4,308 $154 $2,342 2029 12,079,545 $444 $6,753 $269 $4,085 $141 $2,138 2030 11,798,919 $434 $6,596 $255 $3,874 $128 $1,951 2031 11,524,485 $424 $6,442 $242 $3,674 $117 $1,781 2032 11,256,118 $414 $6,292 $229 $3,484 $107 $1,626 2033 10,993,695 $404 $6,146 $217 $3,304 $98 $1,484 2034 10,737,095 $395 $6,002 $206 $3,132 $89 $1,355 2035 10,486,198 $386 $5,862 $195 $2,970 $81 $1,237 2036 10,240,889 $377 $5,725 $185 $2,816 $74 $1,129 2037 10,001,052 $368 $5,591 $176 $2,670 $68 $1,030 2038 9,766,574 $359 $5,460 $167 $2,532 $62 $940 2039 9,537,345 $351 $5,331 $158 $2,400 $56 $858 2040 9,313,255 $343 $5,206 $150 $2,276 $52 $783 2041 9,094,198 $335 $5,084 $142 $2,157 $47 $715 2042 8,880,069 $327 $4,964 $135 $2,045 $43 $652 2043 8,670,764 $319 $4,847 $128 $1,939 $39 $595 2044 8,466,182 $311 $4,733 $121 $1,838 $36 $543 2045 8,266,224 $304 $4,621 $115 $1,742 $33 $496 2046 8,070,792 $297 $4,512 $109 $1,651 $30 $452 2047 7,879,791 $290 $4,405 $103 $1,565 $27 $413 2048 7,693,126 $283 $4,301 $98 $1,484 $25 $376 2049 7,510,706 $276 $4,199 $93 $1,406 $23 $343 2050 7,332,440 $270 $4,099 $88 $1,333 $21 $313 2051 7,158,239 $263 $4,002 $83 $1,263 $19 $286 2052 6,988,016 $257 $3,906 $79 $1,198 $17 $261 2053 6,821,687 $251 $3,813 $75 $1,135 $16 $238 2054 6,659,166 $245 $3,723 $71 $1,076 $14 $217 2055 6,500,372 $239 $3,634 $67 $1,019 $13 $198 2056 6,345,224 $233 $3,547 $64 $966 $12 $181 2057 6,193,644 $228 $3,462 $60 $916 $11 $165 2058 6,045,554 $222 $3,380 $57 $868 $10 $150 2059 5,900,878 $217 $3,299 $54 $822 $9 $137 2060 5,759,541 $212 $3,220 $51 $779 $8 $125 2061 5,621,471 $207 $3,142 $49 $738 $8 $114 Present Value $9,806 $149,001 $5,560 $84,489186 x Monetization of Potential “ Stigma ” Decrease in CCR Beneficial Use (Scenario #2)

The $559 per ton social benefit value estimated above is the proper estimate for increased beneficial use because this RIA assumes that all beneficial uses will increase in equal propor tions. However, it would not be appropria te to apply this same dollar estimate to decreased beneficial use from stigma because different uses decrease by different amounts, and th erefore the decrease in benefits would n ot necessarily equal the 51% decrease in tons. Based on the breakdown of benefi cial uses displayed below in Exhibit 5C-20 , these individual use category losses were summed to create a weighted aver age benefit reduction of 42%. However, on a tonnage basis 51% of beneficial use to ns are reduced. Dividing the weighted value by the unweighted value fo r each ton lost, the benefits de creased by only 82% of the aver age $559/ton, or $458/ton. This average unitized social be nefits value is used to monetize the estimated tons lost from the stigma Scenario #2.

Exhibit 5C-20 Calculation of the “ Stigma ” Adjustment Factor for the CCR Beneficial Use Reduction Scenario #2 Beneficial Use Industrial Category CCR Beneficial Use (2005 tons) Disposal Cost Savings (millions) Life Cycle Benefits (millions) Total Benefits (millions) Percent Lost From Stigma Benefits Lost (millions)

1. Concrete/concrete products/grout 16,353,331 $1,390 $17,593 $18,983 37.5% $7,118.6 2. Blended cement/raw feed for clinker 4,215,234 $358 Not estimated $358 50% $179.0 3. Flowable fill 259,907 $22 Not estimated $22 37.5% $8.3 4. Structural fill/embankments 8,349,999 $710 Not estimated $710 80% $568.0 5. Road base/sub-base 1,461,992 $124 Not estimated $124 80% $99.2 6. Soil modification/stabilization 1,139,640 $97 Not estimated $97 80% $77.6 7. Mineral filler in asphalt 140,838 $12 Not estimated $12 50% $6.0 8. Snow & ice control 547,541 $47 Not estimated $47 80% $37.6 9. Blasting grit/roofing granules 1,633,407 $139 Not estimated $139 37.5% $52.1 10. Gypsum panel products (wallboard) 8,178,079 $695 $5,387 $6,082 50% $3,041.0 11. Waste stabilization/solidification 2,839,954 $241 Not estimated $241 0% $0.0 12. Agriculture 415,741 $35 Not estimated $35 80% $28.0 13. Aggregate 872,776 $74 Not estimated $74 80% $59.2 14. Miscellaneous other 2,071,157 $176 Not estimated $176 65% $114.4 Weighted Total = 48,479,596 $4,120 $22,980 $27,100 42% $11,382 Unweighted Total = 48,479,596 $4,120 $22,980 $27,100 51% $13,821 Adjustment Factor = 0.82

Exhibit 5C-21 below provides an estimate of the beneficial use decrease scen ario. This quantity is calcul ated each year as the quantity projected under subtitle C (w ith stigma) less the quantity projected under the baseline.187 Exhibit 5C-21 Scenario #2: Cost of Potential Future Reduction in CCR Beneficial Use Under Subtitle C with “ Stigma ” Nominal Costs (Millions) Discounted Costs @ 3% (Millions) Discounted Costs @ 7% (Millions) Year CCR Beneficial
Use Decrease (Short Tons) Economic Social Economic Social Economic Social 2012 -33,342,859 -$1,269 -$15,816 -$1,269 -$15,816 -$1,269 -$15,816 2013 -33,342,859 -$1,269 -$15,816 -$1,232 -$15,355 -$1,186 -$14,781 2014 -33,342,859 -$1,269 -$15,816 -$1,196 -$14,908 -$1,109 -$13,814 2015 -33,342,859 -$1,269 -$15,816 -$1,162 -$14,474 -$1,036 -$12,910 2016 -33,342,859 -$1,269 -$15,816 -$1,128 -$14,052 -$968 -$12,066 2017 -33,342,859 -$1,269 -$15,816 -$1,095 -$13,643 -$905 -$11,276 2018 -33,342,859 -$1,269 -$15,816 -$1,063 -$13,245 -$846 -$10,539 2019 -33,342,859 -$1,269 -$15,816 -$1,032 -$12,860 -$790 -$9,849 2020 -33,342,859 -$1,269 -$15,816 -$1,002 -$12,485 -$739 -$9,205 2021 -33,342,859 -$1,269 -$15,816 -$973 -$12,122 -$690 -$8,603 2022 -33,342,859 -$1,269 -$15,816 -$944 -$11,768 -$645 -$8,040 2023 -33,342,859 -$1,269 -$15,816 -$917 -$11,426 -$603 -$7,514 2024 -33,342,859 -$1,269 -$15,816 -$890 -$11,093 -$564 -$7,022 2025 -33,342,859 -$1,269 -$15,816 -$864 -$10,770 -$527 -$6,563 2026 -33,342,859 -$1,269 -$15,816 -$839 -$10,456 -$492 -$6,134 2027 -33,342,859 -$1,269 -$15,816 -$815 -$10,152 -$460 -$5,732 2028 -33,342,859 -$1,269 -$15,816 -$791 -$9,856 -$430 -$5,357 2029 -33,342,859 -$1,269 -$15,816 -$768 -$9,569 -$402 -$5,007 2030 -33,342,859 -$1,269 -$15,816 -$746 -$9,290 -$376 -$4,679 2031 -33,342,859 -$1,269 -$15,816 -$724 -$9,020 -$351 -$4,373 2032 -33,342,859 -$1,269 -$15,816 -$703 -$8,757 -$328 -$4,087 2033 -33,342,859 -$1,269 -$15,816 -$682 -$8,502 -$307 -$3,820 2034 -33,342,859 -$1,269 -$15,816 -$662 -$8,254 -$287 -$3,570 2035 -33,342,859 -$1,269 -$15,816 -$643 -$8,014 -$268 -$3,336 2036 -33,342,859 -$1,269 -$15,816 -$624 -$7,780 -$250 -$3,118 2037 -33,342,859 -$1,269 -$15,816 -$606 -$7,554 -$234 -$2,914 2038 -33,342,859 -$1,269 -$15,816 -$589 -$7,334 -$219 -$2,723 2039 -33,342,859 -$1,269 -$15,816 -$571 -$7,120 -$204 -$2,545 2040 -33,342,859 -$1,269 -$15,816 -$555 -$6,913 -$191 -$2,379 2041 -33,342,859 -$1,269 -$15,816 -$539 -$6,711 -$178 -$2,223 2042 -33,342,859 -$1,269 -$15,816 -$523 -$6,516 -$167 -$2,078 2043 -33,342,859 -$1,269 -$15,816 -$508 -$6,326 -$156 -$1,942 2044 -33,342,859 -$1,269 -$15,816 -$493 -$6,142 -$146 -$1,815 2045 -33,342,859 -$1,269 -$15,816 -$479 -$5,963 -$136 -$1,696 2046 -33,342,859 -$1,269 -$15,816 -$465 -$5,789 -$127 -$1,585 2047 -33,342,859 -$1,269 -$15,816 -$451 -$5,621 -$119 -$1,481 2048 -33,342,859 -$1,269 -$15,816 -$438 -$5,457 -$111 -$1,384 2049 -33,342,859 -$1,269 -$15,816 -$425 -$5,298 -$104 -$1,294188 Exhibit 5C-21 Scenario #2: Cost of Potential Future Reduction in CCR Beneficial Use Under Subtitle C with “ Stigma ” Nominal Costs (Millions) Discounted Costs @ 3% (Millions) Discounted Costs @ 7% (Millions) Year CCR Beneficial
Use Decrease (Short Tons) Economic Social Economic Social Economic Social 2050 -33,342,859 -$1,269 -$15,816 -$413 -$5,144 -$97 -$1,209 2051 -33,342,859 -$1,269 -$15,816 -$401 -$4,994 -$91 -$1,130 2052 -33,342,859 -$1,269 -$15,816 -$389 -$4,848 -$85 -$1,056 2053 -33,342,859 -$1,269 -$15,816 -$378 -$4,707 -$79 -$987 2054 -33,342,859 -$1,269 -$15,816 -$367 -$4,570 -$74 -$923 2055 -33,342,859 -$1,269 -$15,816 -$356 -$4,437 -$69 -$862 2056 -33,342,859 -$1,269 -$15,816 -$346 -$4,308 -$65 -$806 2057 -33,342,859 -$1,269 -$15,816 -$336 -$4,182 -$60 -$753 2058 -33,342,859 -$1,269 -$15,816 -$326 -$4,060 -$56 -$704 2059 -33,342,859 -$1,269 -$15,816 -$316 -$3,942 -$53 -$658 2060 -33,342,859 -$1,269 -$15,816 -$307 -$3,827 -$49 -$615 2061 -33,342,859 -$1,269 -$15,816 -$298 -$3,716 -$46 -$574 Present Value -$33,639 -$419,145 -$18,744 -$233,549

Step 9: Estimate Potential Induc ed Effect on CCR Benefi cial Use of the Other RCRA Regulatory Options

The analysis above demonstrates the valuat ion of beneficial use effects using only th e subtitle C option. However, the results may be extrapolated to the other regulatory options. Exhibit 5C-22 below displays the beneficial use effect scenarios linearly extrapolated in relation to the result of subtitle C based on the poten tial increase in CCR disposal cost. In other words, the ratio of the disposal co st estimated under those other scenarios to the subtitle C dis posal cost can be applied to the benefici al use benefits under those alternative opt ions.

Exhibit 5C-22 Potential Induced Effect of R CRA Regulation on Future CCR Beneficial Use: 2 Scenarios ($millions present value @7%) Component Subtitle C Special waste Subtitle D (version 2) Subtitle gD primeh Assumed scaling ratios relative to C value = 100% 40% 16%
Scenario # 1: Increase in Beneficial Use (Base Case) Percentage increase relative to baseline = +11% +4% +2% Economic market value +$5,560 +$2,224 +$890 Lifecycle social value +$84,489 +$33,796 +$13,518
Scenario #2 : Decrease in Beneficial Use Percentage increase relative to baseline = -18% N/A N/A Economic market value -$18,744 N/A N/A Lifecycle social value -$233,549 N/A N/A189 Step 10: Quantify Potential Capacity Impacts on Commercial Subtitle C Waste Landfills (Under Scenario #2)

For Scenario #2 estimated above involving a potential future re duction in annual CCR bene ficial use, such loss would require ad ditional disposal of 33.3 million tons CCR annually (source: Exhibit 5C-16 ) which will likely create four future industrial waste disposal problems:

1. Annual disposal rate exceedance : Relative to the 33.3 million lost beneficial use a nnnual tonnages, there is a much smaller quantity of 2 million tons per year of RCRA-regulated h azardous waste which is currently disposed in RCRA Subtitle C permitted onsite (capt ive) and offsite (commercial) landfills in the US. 160 This implies a potential 1,665% annual incr ease (i.e., 16.65 times larger) in demand for hazardous waste landfill capacity.
2. Limited geographic availability : There are currently 19 to 24 commercial hazardous waste landfills operati ng in 15 to 17 states. 161 However, the CCR which is currently beneficially used is gene rated by 272 electric utility pl ants located in 41 states. 162 Thus disposal at commercial hazardous waste landfills w ould require out-of-state shipment involving at least 24 to 26 stat es which do not hav e commercial hazardous waste landfills.
3. Remaining disposal capacity exceedance : The 19 to 24 commercial hazardous waste landfill s have an available total remaining capacity of 21.7 million to 25.4 milli on tons hazardous waste. 163 The additional 33.3 million tons per year of CCR beneficial use needing disposal under the Scenario #2 will consume this entire remaining total capacity within less than one year.
4. Increase landfill prices : In addition, such a large increase in nationwide economic demand for co mmercial hazardous waste landfills could drive-up landfill tippi ng fees which recently (2004) ranged between $61 and $139 per ton nationwide ($90 per ton national average). 164 As verification of this potential effect on landfill prices, a recent (August 2009) market study 165 of the US commercial

160 Source: 2 million tons per year is based on the annual aver age of landfill tonnages reported for years 2001 (2.09 million tons ), 2003 (1.68 million tons), 2005 (2.04 million tons), and 2007 (1.94 million tons) in EPA_s gRCR A National Analysis Biennial Hazardous Waste Reporth at http://www.epa.gov/waste/inforesources/data/biennialreport/index.htm

161 Source: These two ranges (i.e., 19 to 24 commercial haz waste la ndfill counts and 15 to 17 stat es) are from two alternative da ta sources:

x Source #1 of 2: 24 commercial RCRA-permitted hazardous waste landfill count and 17 state identities as listed in the Hazardous Waste Consultant g2007 Directory of US Commercial Hazardous Waste Management F acilities,h Vol.25, Issue 1, 2007, pp.4.1 to 4.44. The 17 states are AL, AR, CA, CO, ID, IL, IN, LA, MI, NV, NJ, NY, OH, OK, OR, TX, UT.

x Source #2 of 2: As compiled 02 Oct 2009 by EPA OSWER-ORCR staff (Cpan Lee, Environm ental Scientist), this available remaining capacity estimate is based on three sources: (a) actual capacity estimates provided to OSWE R-ORCR by facilities in April-Sept 2009, (b) information provided to OSWER-ORCR by EPA Regions and States in April/May 2009, and (c) capacity estimates developed by OSWER-ORCR using 1995-2007 RCRA Biennial Report data. Th e 15 States are AL, CA, CO, ID, IL, IN, LA, MI, NV, NY, OH, OK, OR, TX, and UT.

162 The 41 states are AL, AR, AZ, CO, DE, FL, GA, IA, IL, IN, KS, KY, LA, MA, MD, MI, MN, MO, MS, MT, NC, ND, NE, NH, NJ, NM, NV, NY, ,OH, OK, OR, SC, SD, TN, TX, UT, VA, WA, WI, WV, WY.

163 Source: 02 Oct 2009 estimates by EPA OSWER-ORCR staff (Cpan Lee, Environmental Scientist) cited in a prior footnote in this se ction of the RIA.

164 Source: US commercial hazardous waste landf ill prices for bulk hazardous waste without treatment reported by the Environmental Technology Council (ETC) gMay 2004 Incinerator and Landfill Cost Datah we bsite at http://www.etc.org/costsurvey8.cfm

165 Source: Page 10 of gHazardous Waste Industry Review 20 08-2009,h Joan Berkowitz and Robert Cr isp, Farkas Berkowitz & Company, A ugust 2009; http://www.farkasberkowitz .com/marketresearch.htm190 hazardous waste industry, provides the follo wing empirical evidence of price increases by commercial hazardous waste landfills in response to annual increases in landfill disposal tonnage:

g On average, the number of surveyed landfill firms that increased prices exceeds the num ber that received higher volumes in 2008. Volumes increased for 50 percent of resp ondents and decreased for 42 percent, but 67 percent raised prices and 33 percent left prices unchanged. The survey did not ask how much, if any, of the reported price increase was due to fuel surcharges. The survey did determine that 92 percent of respondents applied fuel surcharges, but fuel surcharges cannot account for all of the price increases because the surcharges cover increased costs, and 77 percent of respondents reported increased [profit] margins. h191 

## Chapter 6 Comparison of Regulatory Benefits to Costs

Section 6A of this Chapter pres ents a series of exhib its which summarize and compare the resu lts of the cost and benefit estima tes presented in Chapter 4 and Chapter 5 , respectively, scaled to the three 2010 regulatory options. Section 6B of this Chapter provides explanation of the scaling method and factors applied.



### 6A. Comparison of Regulatory Benefits to Costs Based on Alternative Discount Rates

The series of six Exhibits 6A to 6F below summarize cost and benefits according to the th ree alternative beneficial use scenarios (i.e., induced increase, induced decrease, and no change), and according to the tw o OMB-prescribed alternative di scount rates of 7% and 3% for use in RIAs: 7% discount rate: The 7% discount rate as a gbase caseh to represent the financial opportunity cost (i.e., borrowing cost) to a ffected businesses, which is consistent w ith OMB_s 2003 Circular A-4 guidance 166 (page 33), and with OMB_s 1992 Circular A-94 guidance 167 (page 8) which indicate th at a 7% discount rate gbase caseh should be used for regulatory analyses when regulation is expected to primarily and directly affect businesses and industries. 3% discount rate: This is a second manda tory discount rate specified in OMB_ s 2003 Circular A-4 guidance (page 34).

In these six summary exhibits below, the comparison of regul atory benefits to costs invol ves two numerical comparisons:
1. Net benefits (i.e., benefits minus costs)
2. Benefit/cost ratios (i.e., benefits divided by costs)

Two alternative discount rates:

Three alternative CCR beneficial use impact scenarios: 7% discount rate (base case in this RIA) 3% discount rate

Scenario #1: Induced increase (base case) Exhibit 6A Exhibit 6B Scenario #2: Induced decrease Exhibit 6C Exhibit 6D Scenario #3: No change Exhibit 6E Exhibit 6F

166 OMB_s 17 Sept 2003 Circular A-4 gRegulatory Analysish guidance is available at: http://www.whitehouse.gov/omb/circulars_a004_a -4/

167 OMB_s 29 Oct 1992 Circular A-94 gGuidelines and Discount Rates for Benefit-Cost Analysis of Federal Programs,h is available at http://www.whitehouse.gov/omb/rew rite/circulars/a094/a094.html192 Exhibit 6A Comparison of Regulatory Benefits to Costs Under Scenario #1 – Induced Beneficial Use Increase @7% Discount Rate – Detailed Sum mary ($Millions in 50-Year Present Values @2009$ Prices)
Costs Subtitle C “Special Waste” Subtitle D (version 2) Subtitle “D prime” 1. Engineering Controls $6,780 $3,254 $3,254 2. Ancillary Costs $1,480 $5 $5 3. Dry Conversion $12,089 4,836 $0 Total Costs (1+2+3) = $20,349 $8,095 $3,259
Benefits 4. Groundwater Protection Benefits* $970 $375 $188
Count of Human Cancer Risks Avoided** 726 296 148 Monetized Value of Human Cancer Risks Avoided $504 $207 $104 Groundwater Remediation Costs Avoided $466 $168 $84 5. Induced Impact on CCR Beneficial Use Econ. benefits Social bene fits Econ. benefits Social bene fits Econ. Benefits Social ben efits Scenario #1 @7% discount rate = $5,560 $84,489 $2,224 $33,796 $890 $13,518 6. CCR Impoundment Failure Costs Avoided If Based on Extrapolated R ecent Failure Cases $1, 762 $793 $405 If Based on 10% Future Failures $8,366 $3,795 $1,897 If Based on 20% Future Failures $16,732 $7,590 $3,795 7. Non-quantified Benefits*** Q R S Total Benefits (4+5+6): Total Benefits w/Extrapolated Recent Failure Cases = $8,292 $87,221 $3,392 $34,964 $1,483 $14,111 Total Benefits @10% Future Failures = $14,896 $93,825 $6,394 $37,966 $2,975 $15,603 Total Benefits @20% Future Failures = $23,262 $102,191 $10,189 $41,761 $4,873 $17,501 Net Benefits (Total Benefits minus Total Costs)

Net Benefits w/Extrapolated Recent Failure Cases = ($12,057) $66,872 ($4,703) $26,869 ($1,776) $10,852 Net Benefits @10% Future Failures = ($5,453) $73,476 ($1,701) $29,871 ($284) $12,344 Net Benefits @20% Future Failures = $2,913 $81,842 $2,094 $33,666 $1,614 $14,242 Benefit/Cost Ratio (BCR) BCR w/Extrapolated Recent Failure Cases = 0.407 4.286 0.419 4.319 0.455 4.330 BCR @10% Future Failures = 0.732 4.611 0.790 4.690 0.913 4.788 BCR @20% Future Failures = 1.143 5.022 1.259 5.159 1.495 5.370
Notes: * Cancer risk reflects the arsenic groundwater pathway only and does not include other human health mortality or morbidity risk s from non-carcinogens, nor do they reflect ecological and socio-ec onomic damages that could occur. Thus, the benefits are underestimated in this RIA. ** Cancer risks avoided are based on National Academy of Scien ce (2001) data, which represents recent scientific information. *** Q>R>S; For example, non-quantified ecological benefits could add 159%, and socio-economic benefits could add 24%, compared to avoided cleanup cost benefit.193 Exhibit 6B Comparison of Regulatory Benefits to Costs Under Scenario #1 – Induced Beneficial Use Increase @3% Discount Rate ($Millions in 50-Year Present Values @2009$ Prices)
Costs Subtitle C “Special Waste” Subtitle D (version 2) Subtitle “D prime” 1. Engineering Controls $12,640 $6,067 $6,067 2. Ancillary Costs $2,759 $9 $9 3. Dry Conversion $22,538 $9,016 $0 Total Costs (1+2+3) = $37,938 $15,092 $6,076
Benefits 4. Groundwater Protection Benefits* $3,316 $1,321 $661
Count of Human Cancer Risks Avoided** 726 296 148 Monetized Value of Human Cancer Risks Avoided $1,825 $750 $375 Groundwater Remediation Costs Avoided $1,491 $571 $286 5. Induced Impact on CCR Beneficial Use Econ. benefits Social bene fits Econ. benefits Social bene fits Econ. Benefits Social ben efits Scenario #1 @3% discount rate = $9,806 $149,001 $3,922 $59,600 $1,569 $23,840 6. CCR Impoundment Failure Costs Avoided If Based on Extrapolated R ecent Failure Cases $3,124 $1,406 $719 If Based on @ 10% Future Failures $13,046 $5,918 $2,959 If Based on @ 20% Future Failures $26,092 $11,836 $5,918 7. Non-quantified Benefits*** Q R S Total Benefits (4+5+6): Total Benefits w/Extrapolated Recent Failure Cases = $16,246 $155,441 $6,649 $62,327 $2,949 25,220 Total Benefits @10% Future Failures = $26,168 $165,363 $11,161 $66,839 $5,189 $27,460 Total Benefits @20% Future Failures = $39,214 $178,409 $17,079 $72,757 $8,148 $30,419 Net Benefits (Total Benefits minus Total Costs)

Net Benefits w/Extrapolated Recent Failure Cases = ($21,692) $117,503 ($8,443) $47,235 ($3,127) $19,144 Net Benefits @10% Future Failures = ($11,770) $127,425 ($3,931) $51,747 ($887) $21,384 Net Benefits @20% Future Failures = $1,276 $140,471 $1,987 $57,665 $2,072 $24,343 Benefit/Cost Ratio (BCR) BCR w/Extrapolated Recent Failure Cases = 0.428 4.097 0.441 4.130 0.485 4.151 BCR @10% Future Failures = 0.690 4.359 0.740 4.429 0.854 4.519 BCR @20% Future Failures = 1.034 4.703 1.132 4.821 1.341 5.006
Notes: * Cancer risk reflects the arsenic groundwater pathway only and does not include other human health mortality or morbidity risk s from non-carcinogens, nor do they reflect ecological and socio-economic damages that could occur. Thus, the benefits are underestimated in this RIA. ** Cancer risks avoided are based on National Academy of Scien ce (2001) data, which represents recent scientific information. *** Q>R>S.194 Exhibit 6C Comparison of Regulatory Benefits to Costs Under Scenario #2 – Induced Beneficial Use Decrease @7% Discount Rate ($Millions in 50-Year Present Values @2009$ Prices)
Costs Subtitle C “Special Waste” Subtitle D (version 2) Subtitle “D prime” 1. Engineering Controls $6,780 $3,254 $3,254 2. Ancillary Costs $1,480 $5 $5 3. Dry Conversion $12,089 4,836 $0 Total Costs (1+2+3) = $20,349 $8,095 $3,259
Benefits 4. Groundwater Protection Benefits* $970 $375 $188
Count of Human Cancer Risks Avoided** 726 296 148 Monetized Value of Human Cancer Risks Avoided $504 $207 $104 Groundwater Remediation Costs Avoided $466 $168 $84 5. Induced Impact on CCR Beneficial Use Econ. benefits Social bene fits Econ. benefits Social bene fits Econ. Benefits Social ben efits Scenario #2 @7% discount rate = ($18,744) ($233,549) $0 (no impact) $0 (no impact) $0 (no impact) $0 (no impact) 6. CCR Impoundment Failure Costs Avoided If Based on Extrapolated Recen t Failure Cases $1,762 $793 $405 If Based on 10% Future Failures $8,366 $3,795 $1,897 If Based on 20% Future Failures $16,732 $7,590 $3,795 7. Non-quantified Benefits*** Q R S Total Benefits (4+5+6): Total Benefits w/Extrapolated Recent Failure Cases = ($16,012) ($230,817) $1,168 $1,168 $593 $593 Total Benefits @10% Future Failures = ($9,408) ($224,213) $4,170 $4,170 $2,085 $2,085 Total Benefits @20% Future Failures = ($1,042) ($215,847) $7,965 $7,965 $3,983 $3,983 Net Benefits (Total Benefits minus Total Costs)

Net Benefits w/Extrapolated Recent Failure Cases = ($36,361) ($251,166) ($6,927) ($6,927) ($2,666) ($2,666) Net Benefits @10% Future Failures = ($29,757) ($244,562) ($3,925) ($3,925) ($1,174) ($1,174) Net Benefits @20% Future Failures = ($21,391) ($236,196) ($130) ($130) $724 $724 Benefit/Cost Ratio (BCR) BCR w/Extrapolated Recent Failure Cases = (0.787) (11.343) 0.144 0.144 0.182 0.182 BCR @10% Future Failures = (0.462) (11.018) 0.515 0.515 0.640 0.640 BCR @20% Future Failures = (0.051) (10.607) 0.984 0.984 1.222 1.222
Notes: * Cancer risk reflects the arsenic groundwater pathway only and does not include other human health mortality or morbidity risk s from non-carcinogens, nor do they reflect ecological and socio-ec onomic damages that could occur. Thus, the benefits are underestimated in this RIA. ** Cancer risks avoided are based on National Academy of Scien ce (2001) data, which represents recent scientific information. *** Q>R>S.195 Exhibit 6D Comparison of Regulatory Benefits to Costs Under Scenario #2 – Induced Beneficial Use Decrease @3% Discount Rate ($Millions in 50-Year Present Values @2009$ Prices)
Costs Subtitle C “Special Waste” Subtitle D (version 2) Subtitle “D prime” 1. Engineering Controls $12,640 $6,067 $6,067 2. Ancillary Costs $2,759 $9 $9 3. Dry Conversion $22,538 $9,016 $0 Total Costs (1+2+3) = $37,938 $15,092 $6,076
Benefits 4. Groundwater Protection Benefits* $3,316 $1,321 $661
Count of Human Cancer Risks Avoided** 726 296 148 Monetized Value of Human Cancer Risks Avoided $1,825 $750 $375 Groundwater Remediation Costs Avoided $1,491 $571 $286 5. Induced Impact on CCR Beneficial Use Econ. benefits Social bene fits Econ. benefits Social bene fits Econ. Benefits Social ben efits Scenario #2 @3% discount rate = ($34,946) ($435,419) $0 (no impact) $0 (no impact) $0 (no impact) $0 (no impact) 6. CCR Impoundment Failure Costs Avoided If Based on Extrapolated Recen t Failure Cases $3,124 $1,406 $719 If Based on 10% Future Failures $13,046 $5,918 $2,959 If Based on 20% Future Failures $26,092 $11,836 $5,918 7. Non-quantified Benefits*** Q R S Total Benefits (4+5+6): Total Benefits w/Extrapolated Recent Failure Cases = ($28,506) ($428,979) $2,727 $2,727 $1,380 $1,380 Total Benefits @10% Future Failures = ($18,584) ($419,057) $7,239 $7,239 $3,620 $3,620 Total Benefits @20% Future Failures = ($5,538) ($406,011) $13,157 $13,157 $6,579 $6,579 Net Benefits (Total Benefits minus Total Costs)

Net Benefits w/Extrapolated Recent Failure Cases = ($66,443) ($466,917) ($12,365) ($12,365) ($4,696) ($4,696) Net Benefits @10% Future Failures = ($56,521) ($456,995) ($7,853) ($7,853) ($2,456) ($2,456) Net Benefits @20% Future Failures = ($43,475) ($443,949) ($1,935) ($1,935) $503 $503 Benefit/Cost Ratio (BCR) BCR w/Extrapolated Recent Failure Cases = (0.751) (11.307) 0.181 0.181 0.227 0.227 BCR @10% Future Failures = (0.490) (11.046) 0.480 0.480 0.596 0.596 BCR @20% Future Failures = (0.146) (10.702) 0.872 0.872 1.083 1.083
Notes: * Cancer risk reflects the arsenic groundwater pathway only and does not include other human health mortality or morbidity risk s from non-carcinogens, nor do they reflect ecological and socio-ec onomic damages that could occur. Thus, the benefits are underestimated in this RIA. ** Cancer risks avoided are based on National Academy of Scien ce (2001) data, which represents recent scientific information. *** Q>R>S.196 Exhibit 6E Comparison of Regulatory Benefits to Costs Under Scenario #3 – No Change to Beneficial Use @ 7% Discount Rate ($Millions in 50-Year Present Values @2009$ Prices)
Costs Subtitle C “Special Waste” Subtitle D (version 2) Subtitle “D prime” 1. Engineering Controls $6,780 $3,254 $3,254 2. Ancillary Costs $1,480 $5 $5 3. Dry Conversion $12,089 4,836 $0 Total Costs (1+2+3) = $20,349 $8,095 $3,259
Benefits 4. Groundwater Protection Benefits* $970 $375 $188
Count of Human Cancer Risks Avoided** 726 296 148 Monetized Value of Human Cancer Risks Avoided $504 $207 $104 Groundwater Remediation Costs Avoided $466 $168 $84 5. Induced Impact on CCR Beneficial Use Econ. benefits Social bene fits Econ. benefits Social bene fits Econ. Benefits Social ben efits Scenario #3 @7% discount rate = $0 (no change) $0 (no change) $0 (no change) $0 (no change) $0 (no change) $0 (no change) 6. CCR Impoundment Failure Costs Avoided If Based on Extrapolated R ecent Failure Cases $1, 762 $793 $405 If Based on 10% Future Failures $8,366 $3,795 $1,897 If Based on 20% Future Failures $16,732 $7,590 $3,795 7. Non-quantified Benefits*** Q R S Total Benefits (4+5+6): Total Benefits w/Extrapolated Recent Failure Case s = $2,732 $2,732 $1, 168 $1,168 $593 $593 Total Benefits @10% Future Failures = $9,336 $9,336 $4,170 $4,170 $2,085 $2,085 Total Benefits @20% Future Failures = $17,702 $17,702 $7,965 $7,965 $3,983 $3,983 Net Benefits (Total Benefits minus Total Costs)

Net Benefits w/Extrapolated Recent Failure Cases = ($17,617) ($17,617) ($6,927) ($6,927) ($2,666) ($2,666) Net Benefits @10% Future Failures = ($11,013) ($11,013) ($3,925) ($3,925) ($1,174) ($1,174) Net Benefits @20% Future Failures = ($2,647) ($2,647) ($130) ($130) $724 $724 Benefit/Cost Ratio (BCR) BCR w/Extrapolated Recent Failure Cases = 0.134 0.134 0.144 0.144 0.182 0.182 BCR @10% Future Failures = 0.459 0.459 0.515 0.515 0.640 0.640 BCR @20% Future Failures = 0.870 0.870 0.984 0.984 1.222 1.222
Notes: * Cancer risk reflects the arsenic groundwater pathway only and does not include other human health mortality or morbidity risk s from non-carcinogens, nor do they reflect ecological and socio-ec onomic damages that could occur. Thus, the benefits are underestimated in this RIA. ** Cancer risks avoided are based on National Academy of Scien ce (2001) data, which represents recent scientific information. *** Q>R>S.197 Exhibit 6F Comparison of Regulatory Benefits to Costs Under Scenario #3 – No Change to Beneficial Use @ 3% Discount Rate ($Millions in 50-Year Present Values @2009$ Prices)
Costs Subtitle C “Special Waste” Subtitle D (version 2) Subtitle “D prime” 1. Engineering Controls $12,640 $6,067 $6,067 2. Ancillary Costs $2,759 $9 $9 3. Dry Conversion $22,538 $9,016 $0 Total Costs (1+2+3) = $37,938 $15,092 $6,076
Benefits 4. Groundwater Protection Benefits* $3,316 $1,321 $661
Count of Human Cancer Risks Avoided** 726 296 148 Monetized Value of Human Cancer Risks Avoided $1,825 $750 $375 Groundwater Remediation Costs Avoided $1,491 $571 $286 5. Induced Impact on CCR Beneficial Use Econ. benefits Social bene fits Econ. benefits Social bene fits Econ. Benefits Social ben efits Scenario #3 @3% discount rate = $0 (no change) $0 (no change) $0 (no change) $0 (no change) $0 (no change) $0 (no change) 6. CCR Impoundment Failure Costs Avoided If Based on Extrapolated R ecent Failure Cases $3,124 $1,406 $719 If Based on 10% Future Failures $13,046 $5,918 $2,959 If Based on 20% Future Failures $26,092 $11,836 $5,918 7. Non-quantified Benefits*** Q R S Total Benefits (4+5+6): Total Benefits w/Extrapolated Recent Failure Cases = $6,440 $6,440 $2,727 $2,727 $1,380 $1,380 Total Benefits @10% Future Failures = $16,362 $16,362 $7,239 $7,239 $3,620 $3,620 Total Benefits @20% Future Failures = $29,408 $29,408 $13,157 $13,157 $6,579 $6,579 Net Benefits (Total Benefits minus Total Costs)

Net Benefits w/Extrapolated Recent Failure Cases = ($31,498) ($31,498) ($12,365) ($12,365) ($4,696) ($4,696) Net Benefits @10% Future Failures = ($21,576) ($21,576) ($7,853) ($7,853) ($2,456) ($2,456) Net Benefits @20% Future Failures = ($8,530) ($8,530) ($1,935) ($1,935) $503 $503 Benefit/Cost Ratio (BCR) BCR w/Extrapolated Recent Failure Cases = 0.170 0.170 0.181 0.181 0.227 0.227 BCR @10% Future Failures = 0.431 0.431 0.480 0.480 0.596 0.596 BCR @20% Future Failures = 0.775 0.775 0.872 0.872 1.083 1.083
Notes: * Cancer risk reflects the arsenic groundwater pathway only and does not include other human health mortality or morbidity risk s from non-carcinogens, nor do they reflect ecological and socio-ec onomic damages that could occur. Thus, the benefits are underestimated in this RIA. ** Cancer risks avoided are based on National Academy of Scien ce (2001) data, which represents recent scientific information. *** Q>R>S.198 

### 6B. Factors Applied for Scaling Benefits and Costs to the Three 2010 Regulatory Options

The regulatory compliance cost estimation presented in Chapter 4 of this RIA was initially formulat ed with reference to the October 2009 draft RIA regulatory options. Furthermore, the regulatory benefits evaluation in Chapter 5 of this RIA was based only on the 2010 regulatory options. To resolve this inconsistency in scope between the two different sets of re gulatory options eval uated for costs and f or benefits, respectively, this RIA applies the scaling factors (i.e., percentage extrapolation multipliers) displayed below in Exhibit 6F

.
The cost analysis presented in Chapter 4 of this RIA is built upon a detail ed (i.e., plant-by-plant for all 495 co al-fired electric utility plants) engineering cost model which estimated "engi neering control" costs associated with th e RCRA 3004(x) custom-tailored technical s tandards of the 2009 regulatory options (i.e., Subtitle C "hazardous waste" option, Subtitle D no n-hazardous waste option requiring composi te liners for new CCR disposal units, and a "hybrid" C/D option). Although the e ngineering control costs were th e same for each of the three October 2009 options, "ancillary costs" differed according to whether an option was form ulated in reference to Sub title C or to Subtitle D a uthority. For example, only the Subtitle C "hazardous wast e" option and the Subtitle C component of the "Hybrid C/D" option required the cost associated with manifesting offsite shipments of CCR between coal-fired el ectric utility plants and offsite CCR disposal locations. The O ctober 2009 draft RIA presented the "dry conve rsion cost" element as a separable "sub-option" for both the Subtitle C and Subtitle D option s.

However, in 2010 EPA identified a different set of three regulatory options to describe in the pr oposed rule and evaluate in RI A (i.e., Subtitle C "special waste" option with wet disposal phase-out, Subtitle D option wh ich in effect would phase- out wet CCR disposal by requi ring retrofitting existing impoundments with composite liners, and a Subtitle "D prim e" option requiring liner s only for new disposa l units). In order to meet EPA_s end-of-March 2010 internal deadline for completing the 2 nd draft of this RIA, EPA did not revised the Chapter 4 cost analysis or the Chapter 7 supplemental analyses, but applied scal ing factors for bridging the cost estim ates to the 2010 options. Numerically, the scaling factors represent al ternative compliance rate assumptions in relati on to the 2009 draft RIA_s Subtitle C "hazardous waste" option as a reference case for both cost and benefit estimate scaling to the three 2010 regulatory options. The scaling factors assume l ess compliance under the non-Federally enforceable Subtitle D based options compared to the Federa lly-enforceable Subtitle C option. Section 6B of this RIA provides the numerical values assigned to the scaling factors on an itemized basis acco rding to the separate cost element and b enefit element categories, for each of the three 2010 regulatory options.

Exhibit 6F Scaling Factors (Extrapolation Mu ltipliers) Applied in this RIA to Estimate the Costs & Benefits of the 2010 Regulatory Options for CCR Disposal Economic Impact Category Subtitle C Special Waste Subtitle D (version 2) Subtitle gD primeh Regulatory Compliance Costs: 1. Engineering control costs 100% 48% 48% 2. Ancillary costs 100% 48% 48% 3. Dry conversion costs 100% 40% 0% Regulatory Benefits:199 Exhibit 6F Scaling Factors (Extrapolation Mu ltipliers) Applied in this RIA to Estimate the Costs & Benefits of the 2010 Regulatory Options for CCR Disposal Economic Impact Category Subtitle C Special Waste Subtitle D (version 2) Subtitle gD primeh 1. Groundwater contamination prevention benefits: Groundwater remediation costs avoided 100% 48% 30% Monetized value of human cancer risks avoided 100% 48% 30% 2. Impoundment structural failure cleanup costs avoided 100% 45% 23% 3. Induced impact on CCR beneficial use: Scenario #1: Induced increase Scenario #2: Induced decrease Scenario #3: No change 100% 100% Not relevant 40% None (0%) Not relevant 16% None (0%) Not relevant

The following two sub-sections (6B.1 and 6B.2) provide explan ation and documentation of the scaling factors displayed in Exhibit 6F above.



### 6B.1 Regulatory Cost Scaling Factors

o Engineering control costs: For both RCRA subtitle C and subtitle D, the engi neering control costs would be identical under both options. However, state governments are not required to develop comparable programs under RCRA Subtitle D rules, and states cannot enforce Federal subtitle D rules. In addition, because of the na ture of subtitle D authorit y, individual requirements ( e.g., groundwater monitoring, impoundment closure) will be more gene ric, allowing industry great latitude in complying. Thus, actual costs under Subtitle D options will be lower than under Subtitle C, because facilities would not be expected to comply t o the same extent. In estimating future annual tons of CCR that might be managed under new standa rds, and the extent to which they would be similar under the Subtitle C option, this RIA applies the percentage of tons of CCR disposed in states with groundwater monitoring requirements as a way to estimate the likel y costs incurred by industry fo r the other options. Although the engineering control cost cate gory consists of 10 cost elements as defined in this RIA, the percentage of states with groundwater monitoring programs is a reas onable surrogate indicator because states imposing groundwater monitoring requirements indicates which states will ge nerally address specific units, and which are likely to upgrade their programs under subtitle D, if EPA were to issue a national subtitle D rule. In those states, management st andards may significantly improve, although not to the level of subtitle C for the reasons discussed above. On the other hand, certai nly some facilities in state s without programs will choose to comply with the national regulat ion (taking full advantage of th e more generic nature of the federal D standards). Taking these two f actors together, using the percentage of CCR disposed in states with groundwater monitoring programs provides a reasonable estimate of the extent to which facilities will take steps to comply with the nationa l standards, and therefore of th e costs of compliance. For the federally-enforceable subtitle C option, the cost recognizes that all states (100%) will be required by the CCR ru le to install groundwater m onitoring (and all other engine ering controls). For bot h the non-federally enforceable subtitle D and the gD primeh options, the cost estimates a ssume that the 48% of waste disposed of in states that currently requi re surface impoundments to have groundwater monitoring (either for new units only or for new and200 existing units) will generally upgrade their programs, improving co mpliance, and that a modest number of facilities in other states would independently make efforts to comply v giving an overall estimate of 48%. This 48% is applied as a scaling factor multiplier to estimate engineering control costs for both the Subtit le D and gD primeh in relation to the Subtitle C engineerin g cost estimate.

o Ancillary costs : The RIA separately estimated gancillaryh costs under both Subtitle C and Subtitle D assuming 100% nationwide adoption. For the Subtitle D or gD primeh options, the cost estimat e only includes inspections of surface impoundments by qualified engineers. The sa me logic applies to this requirement as it does to the engine ering controls, and therefore this RIA applied the same 48% scaling factor multip lier relative to the Subtitle D ancillary cost estimates.

o Dry conversion costs : For the dry conversion cost, 40% is only applied as a scaling multip lier under the Subtitle D option because the gD primeh option does not require dr y conversion. The 40% value is calculated in Exhibit 6G below, which is based in part on assuming that the cost for retrofitting or building new impoundments is 63% of the cost of dry conversion unde r Subtitle C as calculated in Exhibit 6H below.

Exhibit 6G Estimate of Subtitle D (version 2) Impoundment Li ner Retrofit or Build New Lined Impoundment Cost
A B C D E F G (D x F x 63%**)

Row Year Count of existing electric utility

plants with impoundments Subtitle C special waste : Dry Conversion Cost Percent existing CCR impoundments with composite liners* Percent of CCR impoundments without composite liners Subtitle D (v.2) : Must Retrofit or Build New Lined

Impoundments 1 2012 158 $22,984,000,000 5.5% 94.5% $13,709,900,000 2 2013 158 $0 5.5% 94.5% $0 3 2014 158 $0 5.5% 94.5% $0 4 2015 158 $0 5.5% 94.5% $0 5 2016 158 $0 5.5% 94.5% $0 6 2017 158 $15,800,000 5.5% 94.5% $9,400,000 7 2018 158 $15,800,000 5.5% 94.5% $9,400,000 8 2019 158 $15,800,000 5.5% 94.5% $9,400,000 9 2020 158 $15,800,000 5.5% 94.5% $9,400,000 10 2021 158 $15,800,000 5.5% 94.5% $9,400,000 11 2022 158 $15,800,000 5.5% 94.5% $9,400,000 12 2023 158 $15,800,000 5.5% 94.5% $9,400,000 13 2024 158 $15,800,000 5.5% 94.5% $9,400,000 14 2025 158 $15,800,000 5.5% 94.5% $9,400,000 15 2026 158 $15,800,000 5.5% 94.5% $9,400,000 16 2027 158 $15,800,000 5.5% 94.5% $9,400,000 17 2028 158 $15,800,000 5.5% 94.5% $9,400,000 18 2029 158 $15,800,000 5.5% 94.5% $9,400,000 19 2030 158 $15,800,000 5.5% 94.5% $9,400,000 20 2031 158 $15,800,000 5.5% 94.5% $9,400,000201 Exhibit 6G Estimate of Subtitle D (version 2) Impoundment Li ner Retrofit or Build New Lined Impoundment Cost
A B C D E F G (D x F x 63%**)

Row Year Count of existing electric utility

plants with impoundments Subtitle C special waste : Dry Conversion Cost Percent existing CCR impoundments with composite liners* Percent of CCR impoundments without composite liners Subtitle D (v.2) : Must Retrofit or Build New Lined

Impoundments 21 2032 158 $15,800,000 5.5% 94.5% $9,400,000 22 2033 158 $15,800,000 5.5% 94.5% $9,400,000 23 2034 158 $15,800,000 5.5% 94.5% $9,400,000 24 2035 158 $15,800,000 5.5% 94.5% $9,400,000 25 2036 158 $15,800,000 5.5% 94.5% $9,400,000 26 2037 158 $15,800,000 5.5% 94.5% $9,400,000 27 2038 158 $15,800,000 5.5% 94.5% $9,400,000 28 2039 158 $15,800,000 5.5% 94.5% $9,400,000 29 2040 158 $15,800,000 5.5% 94.5% $9,400,000 30 2041 158 $15,800,000 5.5% 94.5% $9,400,000 31 2042 158 $15,800,000 5.5% 94.5% $9,400,000 32 2043 158 $15,800,000 5.5% 94.5% $9,400,000 33 2044 158 $15,800,000 5.5% 94.5% $9,400,000 34 2045 158 $15,800,000 5.5% 94.5% $9,400,000 35 2046 158 $15,800,000 5.5% 94.5% $9,400,000 36 2047 158 $15,800,000 5.5% 94.5% $9,400,000 37 2048 158 $15,800,000 5.5% 94.5% $9,400,000 38 2049 158 $15,800,000 5.5% 94.5% $9,400,000 39 2050 158 $15,800,000 5.5% 94.5% $9,400,000 40 2051 158 $22,984,000,000 5.5% 94.5% $13,709,900,000 41 2052 158 $15,800,000 5.5% 94.5% $9,400,000 42 2053 158 $15,800,000 5.5% 94.5% $9,400,000 43 2054 158 $15,800,000 5.5% 94.5% $9,400,000 44 2055 158 $15,800,000 5.5% 94.5% $9,400,000 45 2056 158 $15,800,000 5.5% 94.5% $9,400,000 46 2057 158 $15,800,000 5.5% 94.5% $9,400,000 47 2058 158 $15,800,000 5.5% 94.5% $9,400,000 48 2059 158 $15,800,000 5.5% 94.5% $9,400,000 49 2060 158 $15,800,000 5.5% 94.5% $9,400,000 50 2061 158 $15,800,000 5.5% 94.5% $9,400,000 Non-discounted total cost = $46,663,000,000 $27,833,000,000 Non-discounted average cost = $933,000,000 $557,000,000 Present value cost (@7% disc.) = $23,167,000,000 $13,819,000,000 Average annualized cost (@7%) = $1,679,000,000 $1,001,000,000 Percent reduction in annualized cost compared to Subtitle C Option conversion cost = 40%
Notes:202 Exhibit 6G Estimate of Subtitle D (version 2) Impoundment Li ner Retrofit or Build New Lined Impoundment Cost
A B C D E F G (D x F x 63%**)

Row Year Count of existing electric utility

plants with impoundments Subtitle C special waste : Dry Conversion Cost Percent existing CCR impoundments with composite liners* Percent of CCR impoundments without composite liners Subtitle D (v.2) : Must Retrofit or Build New Lined

Impoundments * 5.5% existing impoundments with composite liners based on EP A_s 2000 CCR regulatory determination and on the August 2006 joint EPA-DOE survey report. ** EPA estimated the capital and annual O&M costs for the Subtitle D requirement for either retrofitting or building new CCR impoundments with composite liners, by assuming that the cost for those requirements are 63% of the $23.167 billion present val ue cost for dry conversion under the Subtitle C option. This 63% cost scaling factor is calculated in Exhibit 6H of this RIA.

Exhibit 6H Reference Data for Calculation of "63% Cost Scaling Factor" Applied in Exhibit 6G Capital cost O&M cost Row total Percent Capital cost Percent Dry Coal Ash Management (35-year lifespan cost in 1980$)

1 In-plant handling syst em $19,500,000 $693,100,000 $712,600,000 76% $19,500,000 23% 2 Conveyance (transport) $10,364,000 $116,996,000 $127,360,000 14% $10,364,000 12% 3 Disposal (lined landf ill) $53,952,000 $39,926,000 $93,878,000 10% $53,952,000 64% Total = $83,816,000 $850,022,000 $933,838,000 100% $83,816,000 100% Wet Coal Ash Management (35-year lifespan cost in 1980$)

1 In-plant handling syst em $8,500,000 $302,121,000 $310,621,000 69% $8,500,000 9% 2 Conveyance (transport) $31,954,000 $42,140,000 $74,094,000 16% $31,954,000 34% 3 Disposal (lined impoundm ent) $52,906,000 $14,448,000 $67,354,000 15% $52,906,000 57% 63%*

Total = $93,360,000 $358,709,000 $452,069,000 100% $93,360,000 100% Source: Based on cost data for an exam ple 2600 megawatt (MW) na meplate capacity elec tric utility plant from pages B-8 (dry) an d C-9 (wet) of the EPA/TVA joint study gEconomic Analysis of Wet Versus Dry Ash Disposal Systems: Inte ragency Energy/Environment R&D Program Repor t,h report nr. EPA-600/7-81-013, January 1981: http://nepis.epa.gov/Exe/ZyPURL.cgi?Dockey=20006ORT.txt * EPA estimated the capital and annual O&M costs for the Subtitle D re quirement for either retrofitting or building new CCR imp oundments with composite liners, by assuming that the cost for those requirements are 63% of the $23.167 billion present value cost for dry co nversion under the Subtitle C option. This 63% cost scaling factor is calculated in this exhibit.



### 6B.2 Regulatory Benefits Scaling Factors

o Groundwater contamination benefits : Percentages are based on an examinati on of state programs re lated to groundwater monitoring requirements as described in Chapter 5 of this RIA. The percentages given in Exhibit 6F above refer only to the input values to the estimation of groundw ater protection benefits presented in Chapter 5 of this RIA. For the Subtitle C option, all states will be required by the rule to have groundwater monitoring in place so that 100% of facilities over the baseline wo uld203 detect contamination early and thus human cancers would be prev ented. For the Subtitle D option, 48% of CCR are placed in surface impoundments in states with groundwater monitoring in plac e for new units only (or for new and existing units). It is likely that these states with some level of attention to groundw ater monitoring would increase their attention (e.g., because t hey already have a RCRA program infrastructu re) to groundwater monitoring, providing for much more effective systems, while other states would tend not to (although so me individual facilities with in those states would upgr ade groundwater monitoring to some extent). Thus, this RIA estimates that overall, the new regulation would result in 48% of facilities detecting contaminat ion early and 48% of cancers would be prevente d. For the Subtitle D prime option, retrof itting existing units would not be require d, and therefore existing and future releases would continue to occur from unlined surfaced impoundments. Currently 12% of CCR are placed in surface impoundments in stat es with groundwater monitoring. Some of these states would certainly upgrade their regulations, but given that surface im poundments would remain a potential source of release in all states, the Subtitle D prime option is less protective of groundwater than the Subtitle D opti on. Since this fraction is li kely to fall between 48% an d 12%, the mid-point of 30% was chosen as a best estimate for the D prime option.

o Impoundment structural failu re cleanup costs avoided : This factor is not based on estimate s of percentages of states likely to implement the new requirements (which for subtitle D would re quire liners for existing surfac e impoundments); it is unlikely that many states will choose to implement this requirement. In stead, compliance will not be enforc eable, and will be left up t o self-imposed schedules of industry or ci tizens suits. While most impoundments may eventually close, it will be a lengthy process. As a general estimate, through delaying closures and lengtheni ng the process, industry may be able to reduce costs b y 50%. In addition, since 5.5% of surface impoundments have composite liners already, they would re main in place, and therefore would not incur costs. Taking these figures together, th is RIA applies a 45% scaling factor for this benefit.

o Induced impact on CCR beneficial uses :

 Under Scenario #1 induced increase in benefi cial use, beneficial uses are assumed to be linear with respect to total costs because increases in usage are directly pr oportional to the cost of the regulatory options. Therefore, under the Subtitle D option, the net reduction in total costs compared to the Subt itle C option is 40%. Under the Subtitle gD primeh option, since the dry conversion costs are 0%, a net result of 16% was applied. This pe rcentage was derived by dividing the Subtitle gD primeh option cost by the total cost of Subtitle C.

 Under Scenario #2 induced decrease in bene ficial use, for the reasons described in Section 5C of this RIA, this RIA assumes that potential induced future decr ease on beneficial use only applies to the Subtitle C regulatory option, not to the Subtitle D-based options.

 Under Scenario #3 no change in beneficial use (relative to baseline), there is no impact s under any of th e regulatory options, so no scaling assumptions are applied.204 

## Chapter 7 Supplemental Analyses Required by Congressional Statutes or White House Executive Orders

Note : The computations presented in this Chapter are based on the cost estimates for the October 2009 draft RIA regulatory options using the larger dr y conversion cost estimate prior to its update in Chapter 4 . Because the high-end cost of the October 2009 draft RIA regulatory options (i.e., for the Subtitle C ghazardous wasteh option) is larger than the high-end cost for the 2010 options (i.e., for the Subtitle C gspecial wasteh option), the effects estimated in this Chapter are proportionately over-estim ated.



### 7A. Electricity Price Impact (Executive Order 13211)

The 2001 Executive Order 13211 168 gActions Concerning Regulations that Significantly Affect Energy Supply, Distri bution, or Useh requires Federal agencies to evaluate and prepare a statement on any pot ential adverse effects of economically-significant rulemakings o n energy supply, distribution or use, including:

x Shortfall in energy supply

x Energy price increases

x Increased use of foreign energy supplies

The OMB_s 13 July 2001 Memorandum M-01-27 169 guidance for implementing this Executive Or der identifies nine numerical indicators (thresholds) of potential adverse ener gy effects, three of which are rele vant for evaluation in this RIA:

x Increases in the cost of en ergy production in excess of 1%

x Increases in the cost of ener gy distribution in excess of 1%

x Other similarly adverse outcomes.

Because this RIA did not collect and anal yze data on energy production cost or energy distribution cost, this RIA evaluated the potential impact of the CCR regulatory options on elec tricity prices relative to the 1% threshold of both indicators as an indicator of gother s imilarly adverse outcomeh. This RIA calculated the potential increase in statewide elec tricity prices that the i ndustry compliance costs might induce under each CCR regulatory option. This calculation involv ed plant-by-plant annual revenue estima tes and annualized compliance cost estima tes, and respective statewide av erage electricity prices for the 495 electric utility plants, accordi ng to the following four steps.

168 The 18 May 2001 EO-132 11 is available at: http://frwebgate .access.gpo.gov/cgi-bin/getdoc.cgi? dbname=2001_register&docid=fr22my 01-133.pdf

169 OMB_s 13 July 2001 Memorandum M-01-27 is available at: http://www.whitehouse.gov/omb/memoranda_m01-27/205 x Step 1: Downloaded the annual million mega watt capacity data for each of the 495 pl ants from the DOE-EIA website (2007), and estimated annual electricity output for each plant, by multiplying the capacity data by three factors:

o 365 operating days per year

o 24 operating hours per day

o 86.8% capacity utilization per year 170

x Step 2: Estimated the annual electricity sales revenue for each plant by multiplying the estimated annual electricity output so ld by each plant (from Step 1), by the respective stat ewide average retail price (M ay 2009) of electricity for all sectors (i.e., resident ial, commercial, industrial, transportatio n) from DOE-EIA at http://www.eia.doe.gov/cneaf/el ectricity/epm/table5_6_a.html

x Step 3: Added the estimated incremental regulatory costs on a pl ant-by-plant basis, to the esti mated annual electricity sales r evenue for each plant, to obtain a hypothetical future annual revenue target , which represents a 100% cost pa ss-thru scenario. This simpl e scenario represents an upper-bound case of potential el ectricity price increase. Furthermore, if this 100% cost pass-thru is averaged o ver the entire electricity supply in each state, not just averaged over the 495 coal-fir ed electricity plants as done in this RIA, the potenti al percentage increase in electricity price would be less than this upper-bou nd case presented in this RIA.

x Step 4: Divided the hypothetical future annu al revenue target by the estimated annual electricity output for each plant, to obt ain a hypothetical future (higher) target price for each plant, which in corporates the added regulatory cost. Compared the higher ta rget price to the current price to calculate the potential price increase on a percentage basis for each of the 495 plants.

Exhibit 7A below presents the findings of this ener gy price evaluation on a state-by-state basi s. As displayed in the bottom row of Exhibit 7A , none of the options have an expected na tionwide average energy price increase >1%. Appendix L presents the plant- by-plant calculation spreadsheet used for this electricity price impact analysis.

Exhibit 7A State by State Breakout of Average Electricity Price Increases Per Option

Item Number of Plants State May 2009 statewide average electricity price ($ per kilowatt hour) Subtitle C
hazardous waste

Average Price
Increase Subtitle D (version 1) Average Price
Increase C - impoundments D - landfills Average Price
Increase Average annualized cost (from Exhibit 4F ) = $2,274 $492 $2,176 1 2 AK $0.1518 1.30% 1.23% 1.25% 2 10 AL $0.0856 1.43% 0.189% 1.419%

170 Source: 86.8% capacity utilization is the 1972-2008 annual average published in the 15 May 2009 Federal Reserve Statistical Re lease G.17 gIndustrial Production & Capacity Utilizationh data for Utilities at http://www. federalreserve.gov/releases/g17/Current/default.htm206 Exhibit 7A State by State Breakout of Average Electricity Price Increases Per Option

Item Number of Plants State May 2009 statewide average electricity price ($ per kilowatt hour) Subtitle C
hazardous waste

Average Price
Increase Subtitle D (version 1) Average Price
Increase C - impoundments D - landfills Average Price
Increase 3 3 AR $0.0762 0.293% 0.225% 0.283% 4 6 AZ $0.1002 1.141% 0.622% 1.113% 5 6 CA $0.1337 0.717% 0.676% 0.687% 6 14 CO $0.0797 0.121% 0.006% 0.017% 7 2 CT $0.1712 0.074% 0.000% 0.000% 8 0 DC $0.1337 9 3 DE $0.1236 0.156% 0.127% 0.129% 10 15 FL $0.1136 0.131% 0.077% 0.113% 11 11 GA $0.0859 1.160% 0.163% 1.152% 12 2 HI $0.1892 0.245% 0.171% 0.174% 13 19 IA $0.0710 0.548% 0.198% 0.537% 14 0 ID $0.0602 15 25 IL $0.0924 0.531% 0.099% 0.488% 16 26 IN $0.0766 1.387% 0.207% 1.348% 17 8 KS $0.0822 0.545% 0.190% 0.532% 18 21 KY $0.0640 2.307% 0.593% 2.237% 19 4 LA $0.0748 0.464% 0.040% 0.462% 20 4 MA $0.1534 0.027% 0.000% 0.000% 21 8 MD $0.1316 0.080% 0.017% 0.037% 22 1 ME $0.1222 0.520% 0.346% 0.352% 23 22 MI $0.0986 0.459% 0.052% 0.455% 24 16 MN $0.0804 2.013% 0.471% 1.993% 25 20 MO $0.0757 0.817% 0.116% 0.798% 26 5 MS $0.0893 0.197% 0.106% 0.193% 27 5 MT $0.0720 5.582% 1.193% 5.531% 28 22 NC $0.0839 1.122% 0.148% 1.102% 29 7 ND $0.0698 0.994% 0.012% 0.982% 30 7 NE $0.0705 0.223% 0.206% 0.210% 31 2 NH $0.1544 0.055% 0.004% 0.004% 32 7 NJ $0.1421 0.118% 0.045% 0.045% 33 3 NM $0.0769 2.103% 0.407% 1.729% 34 2 NV $0.0960 0.548% 0.518% 0.526% 35 13 NY $0.1543 0.024% 0.000% 0.000% 36 26 OH $0.0930 1.193% 0.132% 1.157% 37 6 OK $0.0698 0.151% 0.050% 0.081% 38 1 OR $0.0751 0.212% 0.200% 0.204% 39 34 PA $0.0960 0.702% 0.229% 0.665%207 Exhibit 7A State by State Breakout of Average Electricity Price Increases Per Option

Item Number of Plants State May 2009 statewide average electricity price ($ per kilowatt hour) Subtitle C
hazardous waste

Average Price
Increase Subtitle D (version 1) Average Price
Increase C - impoundments D - landfills Average Price
Increase 40 0 RI $0.1343 41 14 SC $0.0826 0.394% 0.028% 0.384% 42 2 SD $0.0742 0.098% 0.084% 0.086% 43 7 TN $0.0860 0.517% 0.001% 0.504% 44 19 TX $0.1019 0.292% 0.038% 0.256% 45 6 UT $0.0690 0.602% 0.336% 0.588% 46 16 VA $0.0916 0.688% 0.078% 0.629% 47 0 VT $0.1282 48 1 WA $0.0684 0.000% 0.000% 0.000% 49 17 WI $0.0918 0.082% 0.063% 0.078% 50 16 WV $0.0668 1.441% 0.615% 1.379% 51 9 WY $0.0602 1.396% 0.315% 1.351% Summary: Minimum = $0.0602 0.0000% 0.0000% 0.0000% Maximum = $0.1892 5.5822% 1.2259% 5.5313%

Average = $0.0985 0.7489% 0.2259% 0.7076% Median = $0.0860 0.5205% 0.1316% 0.4876%
Nationwide = $0.0884 0.795% 0.172% 0.761%

Because this price analysis is based only on the 495 potentially affected co al-fired electric utili ty plants (with 333,500 mega watts nameplate capacity) rather than on all electr ic utility and independent electricity producer plants in each state using other fuels such as natural gas, nuclear, hydroelectric, etc. (with 678,200 megawatts nameplate capacity ), these price effects are hi gher than would be if the r egulatory costs were averaged over the entire electric utility and independe nt electricity producer supply (totaling 1,011,700 megawatts, not c ounting the 76,100 megawatts of combined heat and electricity producers). 171

x Electricity Impact Findings

On a nationwide basis for all 495 plants, compared to the estim ated average electricity pri ce of $0.0884 per kilowatt-hour acro ss the 495 plants, the 100% regulatory cost pass-thru scenario ma y increase prices for the 495 plants by 0.172% to 0.795% across the regulatory options. None of the regulatory options exceed the 1% thre shold of EO 13211, thus this RIA does not include a gSta tement of Energy Effecth as would be required by Section 1 of EO 13211 if the price impact indicator as estimated in this RIA exceeded 1%.

171 Source: 2007 megawatt nameplate capacity data from the Energy Information Administration gTable 2.3. Existing Capacity by Prod ucer Type, 2007h at http://www.eia.doe.gov/cneaf/electricity/epa/epaxlfile2_3.pdf208 

### 7B. Small Business Impact Analysis (RFA/SBREFA)

According to the requirements of the 1980 Regulatory Flexibility Act (RFA) as amende d by the 1996 Small Business Regulatory Enf orcement Fairness Act (SBREFA), Federal regulatory ag encies are required to make initial dete rminations if proposed regulatory actions m ay have a gsignificant economic impact on a substantia l number of small entitiesh (SISNOSE). Small entities include small businesses, sm all organizations, and small governmental jurisdictions. Agencies are required to conduct a Regulator y Flexibility Screening Analy sis (RFSA) to make this determination. This section of the RIA presents the methodology and findings for the RFSA conducted for the proposed rule.

Unless Agencies are able to certify that a particular regulatory action is not expected to have a SISNOSE, the RFA/SBREFA requi res a formal analysis of the potential adverse economi c impacts on small entities, completion of a Small Business Advocacy Review Panel (pro posed rule stage), preparation of a Small Entity Complian ce Guide (final rule stage), and Agency re view of the rule within 10 years of pro mulgation.

The small business impact analysis of this RIA follows the four analytic steps described in EPA_ s RFA/SBREFA analysis guidance 172 :

Step 1: Determine which small entities are subject to the rule_s requirements Step 2: Select appropriate measures for determining econom ic impacts on these small entities and estimate those impacts Step 3: Determine whether the rule may be certified as not having a significant impact on small entities (SISNOSE) Step 4: Document the screening analysis and include the appropriate RFA statements in the preamble

x Step 1: Identification of Small Entities

The scope of entities addressed by this analysis includes the aff ected coal-fired electric util ity plants in NAICS code 221112. Not included in the scope of this RFA/SBREFA analysis are offsite commercial landfills which currently receive and dispose CCR generated by ele ctric utility plants. EPA_s RCRA statute does not provide EPA with authority to collect information from so lid waste facilities; it only pro vides EPA with authority to collect information from RCRA -regulated hazardous waste management facilit ies (via the RCRA biennial report). EPA does not know the identity, company size, or other in formation about the offsite landfills curren tly used by the electric utility indust ry. Therefore, this RFA/SBREFA analysis is limited to only electr ic utility plants. Consistent with EPA_ s RFA/SBREFA guidance (page 15), this RIA applies the following small size definitions for owner entities of electric utility plants:

Small company: Based on the US Small Business size standard fo r NAICS code 221112 (fossil fuel electric utility plants): a company which generates less than 4 million megawatt-hours electricity output per year.

172 EPA_s RFA/SBREFA guidance: gEPA_s Action Development Process: Final Guidance for EPA Rulewriters: Regulatory Flexibility Act a s amended by the Small Business Regulatory Enforcement Fairness Acth, EPA Office of Policy, Economics & Innovation, Nov 2006, 105 pages: http://www.epa.gov/sbrefa/docum ents/rfaguidance11-00-06.pdf209 Small government: Based on the RFA/SBREFA_s definition (5 US C ode section 601(5)) of small government jurisdiction as the government of a city, county, town, township, village, sc hool district, or special di strict with population <50,000.

Based on the nameplate megawatt (MW) capacity for all electricit y generating units (including those powered by non-coal fuel ty pes) at each electricity plant from the 2007 DOE-EIA 860 database, this RIA es timated annual megawatt-hours el ectricity generation capacity by multiplying the nameplate capacity by (a) 365 days per year, and (b ) 24 hours per day to calculate each owner entity_s annual e lectricity capacity. Appendix D of this RIA indicates the assigned size of the owner company or city government for each el ectric utility plant according to two size categories: gSmallh or gNon-smallh. 173 Exhibit 7B below presents the result ant count and summary of th e characteristics of the small electric utility entities as estimated in this RIA.

Exhibit 7B Summary of Characteristics of Small Electric Utility Entities
A B C D E (D / B)

Small Entity Sub-Categories Count of coalfired electric utility plants (2005/2007) Estimated count of owner entities (2005/2007) Estimated 2007 annual megawatt hours (mwh) capacity for all electricity plants owned by all entities Estimated 2009 annual electricity sales for all entities

($millions/year) 2009 average annual electricity sales revenue per entity

($millions/year) 1. Small City Government 33 33 34.0 $2,592 $78.5 2. Small Company 12 11 10.6 $948 $86.2 3. Small Cooperative 6 6 12.0 $947 $157.8 4. Small County Government 1 1 0.3 $23 $23 Summary: All small entities = 52 plants (11%) 51 entities (26%) 56.8 (1%) $4,509 (1%) $88.4

All non-small entities = 443 plants (89%) 149 entities (74%) 5,380.5 (99%) $419,056 (99%) $2,812.5

All entities (non-small + small) = 495 plants 200 entities 5,437 million mwh* $423,565** $2,118
Notes: * Annual electricity generation capacity based on all electric plants and type s of electric generation units (e.g. coal-fired, oil-fired, hydropower, nuclear, wind, biomass, etc.) owned by these companies, no t just coal-fired electricity generation capacity. ** $423.6 billion per year annual electricity sales estimated in this RIA is 73% of the $581.6 billion per year total revenues reported for NAICS code 22 (Utilities sector) in the 2007 Economic Census at: http://factfinde r.census.gov/servlet/IBQTable?_bm=y&-geo_id=D&-ds_name=EC070 0A1&-_lang=en

173 It should be noted that some of the companies identified as small using the SBA size standard for NAICS 22 and the utility cod e specification in the 2007 EIA 860 database to identify each corporate entity may be subsidiaries of a larger holding company (classified under a different NAICS) rather than a larger power company. In addition some of these power companies may have merged. For example, State Line is owned by Dominion Resources of Virginia, No rtheastern Power is owned by Suez Energy North America, Inc. (SEG NA), Rio Bravo Poso and Rio Bravo Jasmin are owned by the North American Power Group, Ltd (NAPG) , TES Filer City Station LP is owned by TONDU, Public Service Enterprise Group (PSEG) and Excel on are merged. This approach lik ely overstates the number of sm all entities.210 x Step 2: Measures for Determining Ec onomic Impacts on Small Entities

According to Exhibit 1 of EPA_s 2006 RFA/SB REFA small business impact analytic guida nce, there are the following suggested test s that may be used to determine if small entities may be significantly impact ed by a proposed rule:

x Small business impact tests:

o Sales test: Annualized compliance co sts as a percentage of sales

o Cash flow test:Debt-financed capital comp liance costs relative to current cash flow

o Profit test: Annualized compliance co sts as a percentage of profits

x Small government impact tests:

o Revenue test: Annualized compliance costs as a percentage of annual government revenues

o Income test: Annualized compliance costs to household (per capita) as a percentage of median hous ehold (per capita) income

Based on annual electricity generation da ta for the small owner entities in th e electric utility i ndustry identified in Appendix D of this RIA, the annual sales/annual revenue test was used fo r this analysis. As itemized and estimate d for each owner entity in the spreadshee ts presented as Appendix M to this RIA, for each small entity EPA computed the respective sales revenue te st percentages by the equation below:

(AEGC x 1,000) x (ASP) x (CU) = annual $sales or $revenues per small entity Where:

AEGC = Annual electricity genera tion capacity per-entity in annual million megawatts (per-entity megawatt data is displayed in Appendix D ). This estimate involved downloading the annual million megawatt capacity data for each of the 495 electricity plants from the DOE-EIA website (2007), a nd then multiplying the capacity data by two factors:

o 365 operating days per year

o 24 operating hours per day ASP = February 2009 average statewide reta il price to ultimate consumers for electric ity (i.e., cents per kilowatt-hour) for th e relevant state or states applicable to the location of electric plants owned by each company; electricity price reflects the composite price charged to residential, co mmercial, industry and transportation sectors 174 CU = 86.8% electric utility industry cap acity utilization from 1972-2008 average re ported by the 15 May 2009 Federal Reserve Statistical Release G.17 gIndustrial Production & Ca pacity Utilizationh data for Utilities at: http://www.federalreserve.gov/rele ases/g17/Current/default.htm

174 DOE_s Energy Information Administration (EIA) publishes state-by-state average retail el ectricity prices for four end-user sect ors (i.e., residential, commercial, industrial, transportation) and on a composite basis at: h ttp://www.eia.doe.gov/cneaf/electricity/epm/table5_6_a.html211 x Step 3 & Step 4: Determine and document whether the pr oposed rule may be certified as having “No SISNOSE”

EPA determined whether each regulatory option may have a gsignificant impact on a subs tantial number of sm all entitiesh (i.e., SISNOSE) which may become subject to the requirements of the proposed rule . This determination involved comparing the estimated regulat ory compliance costs for each entity as displayed in Appendix J of this RIA and as summarized in Exhibit 7C below (small entity row items 6, 7, 8, 9), to the respective annual sa les and revenues for each entity estimated in St ep 2 above. Numerically, this comparison inv olved calculating the percentage of regulatory compliance cost s relative to annual sales and revenues fo r each company for each of the regulatory options. Then compared the percentage results for each small entity to the following three impact thresholds defined in Table 2 of EPA_s RFA/ SBREFA analytic guidance. Exhibit 7D below displays the numerical results of this analysis and the suggested RFA/SBRE FA impact interpretation according to the three thresholds.

<1% threshold: Annualized regulatory costs may be less th en 1% of annual sales or re venues for small entities 1% or more threshold: Annualized regulator y costs may be 1% or more of annual sales or revenues for affected small entities 3% or more threshold: Annualized regulator y costs may be 3% or more of annual sales or revenues for affected small entities

Exhibit 7C Summary of Regulatory Cost Estima tes According to Electric Utility Plan t Owner Entity Size/Type Category

($millions in 2009 price level; average annual amortized @7% discount rate over 50-year period 2012 to 2061)

Size/Type of Entity* Count of plants in category*** Subtitle C Hazardous waste Subtitle D (version 1) Subtitle C for impoundments Subtitle D for landfills 1. Non-Small City 27 plants $46.9 $27.1 $43.9 2. Non-Small Company 372 plants $1,897.2 $378.5 $1,821.2 3. Non-Small Coop 20 plants $87.7 $34.6 $85.3 4. Non-Small Federal 11 plants $183.2 $20.8 $181.0 5. Non-Small State** 13 plants $41.6 $27.1 $39.8 6. Small City 33 plants $2.8 $1.6 $2.5 7. Small Company 12 plants $4.1 $1.9 $2.0 8. Small Coop 6 plants $10.4 $0.3 $0.3 9. Small County 1 plant $0.004 $0.004 $0.004 Total all 9 categories = 495 plants*** $2,274 $492 $2,176
Notes: * Size/Type classification meth odology defined according to Exhibit 3B of this RIA. ** State government costs include costs to (a) state government el ectric utility plants regulatory costs, plus (b) state govern ment RCRA-authorized programs for option implementation. *** The total count of coal-fired electric utility plants is show n in the Exhibit; however, only a sub-total of 467 of the 495 may incur these regulatory costs because 28 plants solely supply their CCR for beneficial uses.212 Exhibit 7D Estimated Impact of Regulatory Options on Small Entities (RFA/SBREFA Analysis Results)

($millions average annualized direct costs @7 % discount rate over 50-year period 2012-2061) Cost as Percentage of Annual Electricity Revenues Subtitle C Hazardous waste Subtitle D (version 1) Subtitle C for impoundments Subtitle D for landfills
A. Count of Small Entities: Annualized cost on small entities:* $17.3 $3.8 $4.8
Less than 1% 46 50 50 1% or greater 5 1 1 3% or greater 0 0 0
B. % of Small Entities: Less than 1% 90% 98% 98% 1% or greater 10% 2% 2% 3% or greater 0% 0% 0% C. SISNOSE Findings: Less than 1% Presumed No SISNOSE Pres umed No SISNOSE Presumed No SISNOSE 1% or greater Presumed No SISNOSE Pres umed No SISNOSE Presumed No SISNOSE 3% or greater Presumed No SISNOSE Pres umed No SISNOSE Presumed No SISNOSE * Source: Costs for each option based on total cost for the four smal l entity categories displayed as rows 6 + 7 + 8 + 9 from Exhibit 7C

.

x Limitations of RFA/SB REFA Determination

Not included in the RFA/SBREFA analysis of this RIA are two factors unique to the electric utility i ndustry, which may reduce the small entity impacts relative to the estimates above in this RIA:

x Factor #1 of 2 : According to the 2007 DOE-EIA database on electric utility plants, two-thirds of the coal-fired electricity generation units at electric utility plants ow ned by small entities can switch to at least one of six other fuels:
1. Agricultural byproducts (database code = AB)
2. Distillate fuel oil (DFO)
3. Natural gas (NG)
4. Petroleum coke (PC)
5. Propane (PG)
6. Wood & wood waste solids (WDS)213 x Factor #2 of 2 : The small business impact analysis in th is RIA applies the full indus try compliance cost to the revenue and sales tests. However, because consumer demand for electricity is (a) high ly price-inelastic and (b) proj ected go grow by 30% by year 2025 175

, electric utility plants may be expected to pass-thru much, if not all, of their regulatory costs (p ending state government util ity rate hike approval). The next section of this RIA evaluate s the possibility of regulator y compliance cost pass-thru.

x Compliance Cost Pass-Thru Analysis

o Ability to Raise Electricity Prices

Traditionally, the electric utility industry has functioned as a regulated monopol y, providing essential electrical services un der an exclusive franchise in exchange for having rates cl osely regulated by State public utility comm issions (PUCs; sometimes called PSC public service commissions) and the Federal Energy Regulat ory Commission (FERC). Th e FERC regulates rates charge d for sales of bulk power be tween utilities, even if they are in the same state. It also regulates th e pricing and use of transmi ssion for wheeling, and asset tr ansfers, including mergers. In most states (California de -regulated electricity in 1998), the PUCs/PSC s set allowable rates upon application by t he utility, with other affected parties allowed to present testimony. By law the ut ility must recover its cost of service, which includes "prude ntly" incurred expenses and a "fair" return on equity. 176

Based on the electricity ratemaking pro cess described by the Pennsylvania PUC 177 as a case example, when an el ectric utility company seeks a price increase (aka rate hike), it must f ile a request with the PUC s howing the proposed new rates and effective date, and must prove that the increase is needed. The utility also must notify customers at least 60 days in adva nce. The notice must include the amount of the proposed rate increase, the proposed effective date, and how much more the rate payer can expect to pay. Under the law, the utility is entitl ed to recovery of its reasonably incurred expenses and a fair return on its investment. The PUC evalua tes each utility_s reque st for a rate incr ease based on those criteria. During the investigati on, hearings are held before an Administrative Law Judge (ALJ) at which the evidence in suppor t of the rate increase is examined and expert witnesses testify. In addition, consumers are offered an opportun ity to voice their opinions an d give testimony. Briefs may be submitted by the formal parties. A recommendati on to the PUC is made by the ALJ. Finally, the matter is brought before the Commissioners for a vote and final decision. Together with the 60-day notice period, the rate in crease process takes about nin e months. Recent (2008) examples of requested or PUC-a pproved electricity rate hikes are summarized in Exhibit 7E below: 178

175 30% additional electricity demand forecst for year 2025 relative to year 2005, from slide 17 of gEnergy & Water: Emerging Issu es and Trandsh by Richard Kottenstette and Mike Hightower, Sandia National Laboratories, a t: http://www.ct-si.org/Summit 2007/spk/RKottenstette.pdf

176 Source: gElectric Utility Regulationh by Robert J. Michaels in the Concise Encyclopedia of Economics at: http://www.econlib.org/library/Enc1/ElectricUtilityRegulation.html

177 Source: Pennsylvania Public Utility Commission, gThe PUC Ratema king Process and the Role of Consumersh, January 2008 at: http://www.puc.state.pa.us/g eneral/consumer_ed/pdf/Ratemaking_Complaints.pdf

178 Source: gRecent Examples of Rate Increases in Vertically Inte grated Statesh, The Compete Coalition, Washington DC, 05 November 2008 at: http://www.competecoalitio n.com/resources/recent-examples-rate-inc reases-vertically-integrated-states214 Exhibit 7E Summary of 2008 US Electricity Price Hikes
Item State Effective date Requested or approved price hike

1 AL Oct 2008 14.6% 2 CO Feb 2008 28% 3 FL July to Oct 2008 10 to 37% (8 companies)
4 KS 2008 15%
5 MO Jan 2008 28% 6 NC Sept 2008 to Jan 2009 10% to 17.7% (3 companies) 7 SC July to Oct 2008 6% to 10% (4 companies) 8 TVA (7 states) Oct 2008 20% Overall range = Jan to Oct 2008 6% to 37% Average (20 electricity plant owner entities) = 19%

Some state governments have deregulated th e electric utility industry, thereby allowing multiple electric suppliers, not just a monopoly electricity supplier, to compete and set th eir own retail prices in those state market s. As of 2003, 18 states have deregulate d and six states may soon deregulate: 179

x Deregulated states (18): AZ, CT , DE, DC, IL, ME, MD, MA, MI, NH, NJ, NY, OH, OR, PA, RI, TX, VA (11 of these states no longer have a price cap)

x May soon deregulate (6): AR, MT, NM, NV, OK, WV ( note: CA deregulated in 1998 but has suspended)

While average prices rose 21% in regulated states from 2002 to 2006, prices increased 36% during that period in 11 of the 18 de regulated states where rate caps expired, suggesting greater pricing flexibility in deregulated states. 180

o Inelastic Demand for Electricity

At the wholesale level, as a re sult of technological and regulat ory barriers, the majority of electricity pricing plans do not allow end users to see and react to the actual market value of their electricity consumption/ conserva tion. Since end-users do not face the real-time market price in making their consumption decisions, there is little demand reaction to changes in real time wholesale electricity prices. 181 At the retail level, consumer demand for electricity has been largely inelastic. The lack of real time metering at the retail level means that cons umers don't know

179 Source: gStatus of State Electric Industry Restructuring Activity as of February 2003h, US Dept of Energy, Energy Information Administration at: http://www.eia.doe.gov/cneaf/elect ricity/chg_str/restructure.pdf

180 Source: gShocking Elect ricity Prices Follow Deregulationh, USA Today , 10 Aug 2007 at: http://www.usatoday.com/money/industries/energy/2007-08-09-powerprices_n.htm

181 Source: page 1 of gDemand Responsiveness in Electricity Market sh, Ronald Lafferty et al., O ffice of Markets, Tariffs and Rate s, 15 Jan 2001 at: http://www.naseo.org/committees/energyproduction/documents /demand_responsiveness_in_electricity_markets.pdf215 how much they use or indeed how much el ectricity costs until after the fact. Thus consumers cannot react to high prices easily by cutting consumption. 182

o Cost Pass-Thru Conclusion

Based on the above three cost pass-thru fact ors consisting of (a) 20 examples of recen t (2008) PUC-regulated rate hikes which a verage almost 19% per company which far exceeds the 1% and 3% SISNOSE screeni ng analysis thresholds defined by EPA_s guidance, (b) 11 of the 18 deregulated states which have de -regulated the price of electric ity, and (c) the fact that cons umer demand for electricity has been relatively inelastic, this RIA concludes that it is likely that electric ut ility suppliers could pass-thru al l, or nearly all, of the futu re average annual regulatory compliance costs for the CCR proposed rule such that a significant impact on small entities and non-small entities w ould not occur.

182 Source: gPower Price Volatility and Risk Management: An Introduc tionh, Anne Ku, Sept 2000 (this is the original, unedited arti cle, later submitted to Global Energy Business magazine Sept/Oct 2000) at: http://www .analyticalq.com/energy/volatility/default.htm216 

### 7C. Minority & Low-Inco me Population Statistics (Executive Order 12898)

Under the 1994 Executive Order (EO) 12898 183 it is the responsibility of Federal agencies to the greatest extent practicable and permitted by law, and consistent with the principles set forth in the report on the National Performance Review, each Federal agency shall m ake achieving environmental justice (EJ) part of its mission by identifying and addressing, as appr opriate, disproportiona tely high and adver se human health or environmental effects of its progr ams, policies, and activities on (a) minority populations and (b) low-income populations. Although not defined in EO 12898, for purpose of this RI A the following definitions are applied:

x Minority population: Numerically measured according to Census Bureau gnon-wh iteh statistics (does not include Hispanics).

x Low-income population: Numerically measured according to Census Bureau gindividuals below poverty 184 level.h

Furthermore, section 3-302(b) of EO 12898 pr ovides a trigger which indicates that Federa l agencies shall collect and evaluate E J data for any facilities or sites expected to have gsubstantial environmental, human health, or economic effecth when such facilities or site s become subject to gsubstantialh Federal environmental action:

g

In connection with the development and implementation of agency strategies in section 1-103 of this order, each Federal agency, whenever practicable and appropriate, shall collect, main tain and analyze information on the race, national origin, income level, and other readily accessible and appropriate inform ation for areas surrounding facili ties or sites expected to ha ve substantial environmental, human health, or economic effect on the surrounding populations, when such facilities or sites become the subject of a substantial Fede ral environmental administrative or judici al action. Such information shall be made available to the public unless prohibited by law .h

The EO 12898 does not establish quantitati ve thresholds for gsubstantial effecth on the surrounding populations, nor does this RIA formulate a quantitative threshold. This RIA uses the (1) CCR disposal baseline environmental an d human health hazards (e.g., damage cases ), and (2) the environmental and human health protection objectives described in the CCR proposed rule, as indica tors of gsubstantial effecth. For that reason, this section of the RIA presents an EJ data collection and anal ysis involving a 5-step proc ess to compare minority and low-income population data for each electric utility plant location, to respective statewide popul ation data, to identify whether these tw o population subgroups disproportionately reside in geogra phic areas where electric util ity plants are located. In addition, this RIA identifi es two other possible affects of the CCR proposed rule on (a) environmental justi ce populations surrounding offsite landfills which may receive CCR, and (b) environmental justice populations within el ectric utility plant customer service areas.

183 Source: 1994 Executive Order 12898 is availa ble at: http://www.epa.gov/ fedrgstr/eo/eo12898.htm

184 The US Census Bureau defines gpovertyh following the Office of Management and Budget's (OMB) Statistical Policy Directive 14. The Census Bureau uses a set of money income thresholds that vary by family size and composition to determine who is in poverty. If a family_s total income is less than the family_s threshold, then that family and every individual in it is considered in poverty. Poverty income thresholds are available at http://www.census.gov/h hes/www/poverty/threshld/thresh08.html217 x Collection of Minority & Low-Income Demographic Data

Step 1: Plant address 5-digit gZip Code Tabulation Areash (ZCTAs) formed the geographi c basis for this EJ population data colle ction. Because ZCTAs represent irregularly shaped geographic areas, this ZCTA based data co llection may be consid ered a gscreening lev elh analysis. The US Bureau of Census uses over 33,000 ZCTA for its Census counts of popul ation and other demographic statistics b ased on the US Postal Service_s over 42,000 nationwide ZCTAs. 185 Currently, there are no size restri ctions limiting how large or small a ZCTA can be in terms of either a minimum/maximum number of hous ing units or geographic area. A ny particular ZCTA may be as small as a few city blocks or may cover many square miles. Ma ny ZCTAs are for villages, census-d esignated places, portions of cities, or other entities that are not municipali ties. The nationwide average ZCTA populat ion is about 7,200 persons (i.e., (306.6 mil lion mid2009 US population) / (42,500 ZCTAs)). The nationwide average ZCTA area is about 83 square miles (i.e., (3,536,278 square mile s total US land and water area) / (42,500 ZCTAs)), which is a land area equivalent to a five-mile radial distance (i.e., ((83 squ are miles) / (3.1416))^0.5). In comparison, the radial area monitored for c ontamination in response to the December 2009 TVA Kingston TN electric plant CCR spill is reportedly four miles, 186 and this average four-mile ZCTA radial di stance falls between the 1-mile to 15-mile radial distances used by EPA_s Superfund gHa zard Ranking Systemh (HRS) to define affect ed populations of sites having either (a ) soil contamination only (1-mile), (b) groundwater and/or airborne contamination (4-miles), or (c) surface water contamination (15-mi les downstream). More information about EPA_s HRS is availabl e at http://www.epa.gov/superf und/programs/npl_hrs/hrsint.htm.

Using the Census search engine Factfinde r (http:factfinder.census.gov/home/saff/mai n.html?_lang=en), EPA retrieved population statistics for 464 (94%) of the 495 electric utility plants. For 42 plants (8%) there was no ZCTA Census da ta because the plan ts did not have complete address data from DOE, or because the Ce nsus search engine did not have data for the ZCTA.

Step 2: EPA collected statewide percentage data for minority and low-income subgroups for purpose of benchmark comparison to th e plant-by-plant sub-group population statistics.

o EPA collected low-income population st atewide percentages (3-year averages for 1998 to 2000) from the following Census Bureau website: http://www.census.gov/hhes/www/ poverty/poverty00/tabled.pdf

o EPA collected statewide percentages for white population sub- group (data year 2000) from the Census Bureau website: . EPA then subtracted the percentage of white population in each state from 100% to produce the respective minority percentage for each state. For data year 2000, the Census Bureau expanded the whit e population classification by collecting both data for people who claime d to be gwhite-onlyh and for people who claimed to be gmixed whiteh. Since the purpose of the EJ analysis is to evaluate all minorities, this step involved collecting the gwhite-onlyh data in order to calculate the minority percentage which include s people who reported to be of mixed race. Exhibit 7F below displays the statewide Census data for low- income and minority sub-populations.

185 Source: US Census Bureau ZIP Code Tabulation Area (ZCTA) Freq uently Asked Questions at: Nationwide total ZCTA count is from the US Postal Service_s FAQ website at: http://zip4.usps.com/zip4/welcome.jsp

186 Source: 4 mile radial monitoring area reported by Waste & Recycling News , 13 Feb 2009; http://www.wasterecyc lingnews.com/email.html?id=1234543579218 Exhibit 7F Statewide Benchmark Data on Low-Inco me and Minority Populations (2000)

Item State Low Income % Minority %

1 AK 8.4% 30.7%
2 AL 14.7% 28.9%
3 AR 15.8% 20.0%
4 AZ 13.5% 24.5%
5 CA 14.0% 40.5%
6 CO 8.5% 17.2%
7 CT 7.7% 18.4%
8 DC 17.4% 69.2%
9 DE 9.9% 25.4%
10 FL 12.1% 22.0%
11 GA 12.5% 34.9%
12 HI 10.6% 75.7%
13 IA 7.9% 6.1%
14 ID 13.3% 9.0%
15 IL 10.5% 26.5%
16 IN 8.3% 12.5%
17 KS 10.5% 13.9%
18 KY 12.5% 9.9%
19 LA 18.5% 36.1%
20 MA 10.1% 15.5%
21 MD 7.3% 36.0%
22 ME 9.8% 3.1%
23 MI 10.2% 19.8%
24 MN 7.8% 10.6%
25 MO 9.8% 15.1%
26 MS 15.5% 38.6%
27 MT 16.% 9.4%
28 NC 13.2% 27.9% Item State Low Income % Minority %
29 ND 12.7% 7.6%
30 NE 10.7% 10.4%
31 NH 7.6% 4.0%
32 NJ 8.1% 27.4%
33 NM 19.3% 33.2%
34 NV 10.1% 24.8%
35 NY 14.7% 32.1%
36 OH 11.1% 15.0%
37 OK 14.1% 23.8%
38 OR 12.9% 13.4%
39 PA 9.8% 14.6%
40 RI 10.2% 15.0%
41 SC 12.0% 32.8%
42 SD 9.4% 11.3%
43 TN 13.4% 19.8%
44 TX 14.9% 29.0%
45 UT 8.1% 10.8%
46 VA 8.1% 27.7%
47 VT 10.3% 3.2%
48 WA 9.5% 18.2%
49 WI 9.0% 11.1%
50 WV 15.8% 5.0%
51 WY 11.1% 7.9% Min = 7.3% (MD) 3.1% (ME) Max = 19.3% (NM) 75.7% (HI) National = 11.9% 24.9%219 x Comparison of Minority & Low-Income Populations Surro unding Electric Utility Plants to Statewide Benchmarks

Step 3, Step 4 and Step 5 of this evalua tion described below involved three complement ary levels of data comparisons. All thre e comparisons also involved two complementary numerical comparisons, one base d on calculating numerical percen tages and the other on numerica l ratios:

1. Plant level: Plant-by-plant disaggregated data comparison to st atewide benchmarks
2. State level: State-by-state a ggregated plant data comparis on to statewide benchmarks
3. Nationwide level: Nationwide aggregated plant data comparison to nationwide benchmarks

x Calculation of Three Alternative Demogr aphic Statistics Comparison Methods

Step 3: On a plant-by-plant basis, EPA co mpared the plant ZCTA percentage minority and percentage low-income population data, t o the respective statewide av erage percentages for each sub- group. This constituted the 1 st level of data comparison.

Step 4: For purpose of summary, EPA aggregated the plant level population compar ison data for each state as displayed in Exhibit 7G below. This constituted the 2 nd level of data comparison. There ar e no data displayed for DC, ID, RI or VT because there are no coal-fired electric utility plants in those states. Appendix N of this RIA presents the plant-by-plant Ce nsus data on which this Exhibit is based. This step also involved aggregating the data across all 495 plants for comparison wi th the nationwide aggregate minority and lo wincome percentage benchmarks. This constituted the 3 rd level of data comparison.

Exhibit 7G Minority and Low-Income Population Data Aggregated on State-by-State Basis

A B C D E F (E/D) G ( Exh 7F ) H (DxG) I J K (DxJ) L ( Exh 7F ) M (DxL) N

General Population Data Low Income Population Data (Below Poverty) Minority Population Data

Item State ZCTA

count 2000 population residing in electric utility plant ZCTA

areas Count of plant
ZCTA residents

below poverty

level % of plant ZCTA residents below poverty level State % below poverty

level Expected count of residents

below poverty based on

state% Count of plants with ZCTA% >

state% poverty

level % of plant
ZCTA residents that are minority Count of plant ZCTA

residents that are minority Statewide % minority Expected count of minority based on

state% Count of plants with ZCTA% >

state% minority

level 1 AK 2 18,552 2,284 12.31% 8.40% 1, 558 1 31.95% 5,928 30.70% 5,695 1 2 AL 9 82,854 20,331 24.54% 14.70% 12,180 6 42.17% 34,942 28.90% 23,945 4 3 AR 3 11,786 1,214 10.30% 15.80% 1,862 0 7.74% 912 20.00% 2,357 0 4 AZ 6 34,941 7,433 21.27% 13.50% 4,717 5 43.70% 15,270 24.50% 8,561 3 5 CA 4 112,895 24,749 21.92% 14.00% 15,805 5 45.22% 51,049 40.50% 45,722 2 6 CO 15 214,095 29,395 13.73% 8.50% 18,198 10 17.88% 38,275 17.20% 36,824 8 7 CT 2 42,716 6,427 15.05% 7.70% 3,289 1 45.14% 19,284 18.40% 7,860 1
8 DC ND220 Exhibit 7G Minority and Low-Income Population Data Aggregated on State-by-State Basis

A B C D E F (E/D) G ( Exh 7F ) H (DxG) I J K (DxJ) L ( Exh 7F ) M (DxL) N

General Population Data Low Income Population Data (Below Poverty) Minority Population Data

Item State ZCTA

count 2000 population residing in electric utility plant ZCTA

areas Count of plant ZCTA residents

below poverty

level % of plant
ZCTA residents below poverty level State % below poverty

level Expected count of residents

below poverty based on

state% Count of plants with ZCTA% >

state% poverty

level % of plant ZCTA residents that are minority Count of plant ZCTA

residents that are minority Statewide % minority Expected count of minority based on

state% Count of plants with ZCTA% >

state% minority

level 9 DE 3 46,925 3,979 8.48% 9.90% 4,646 1 28.86% 13,543 25.40% 11,919 1 10 FL 13 224,502 23,866 10.63% 12.10% 27,165 5 20.76% 46,617 22.00% 49,390 3 11 GA 9 202,973 29,461 14.51% 12.50% 25, 372 4 42.66% 86,581 34.90% 70,838 4 12 HI 1 25,054 1,150 4.59% 10.60% 2,656 0 78.17% 19,584 75.70% 18,966 1 13 IA 14 324,050 31,434 9.70% 7.90% 25,600 13 7.02% 22,744 6.10% 19,767 9
14 ID ND 15 IL 23 455,834 83,407 18.30% 10.50% 47,863 14 41.46% 188,970 26.50% 120,796 8 16 IN 17 323,323 25,460 7.87% 8.30% 26,836 10 6.96% 22,488 12.50% 40,415 2 17 KS 6 59,517 7,718 12.97% 10.50% 6,249 4 36.76% 21,881 13.90% 8,273 3 18 KY 17 255,033 32,497 12.74% 12.50% 31, 879 7 8.48% 21,615 9.90% 25,248 2 19 LA 4 30,381 7,546 24.84% 18.50% 5,620 3 45.16% 13,721 36.10% 10,968 2 20 MA 3 95,798 14,420 15.05% 10.10% 9,676 1 20.69% 19,819 15.50% 14,849 1 21 MD 7 101,141 10,622 10.50% 7.30% 7,383 4 12.39% 12,527 36.00% 36,411 1 22 ME 1 6,748 1,037 15.37% 9.80% 661 1 1.30% 88 3.10% 209 0 23 MI 20 383,284 30,735 8.02% 10.20% 39,095 8 10.56% 40,477 19.80% 75,890 2 24 MN 15 187,012 20,910 11.18% 7.80% 14,587 10 10.78% 20,157 10.60% 19,823 3 25 MO 19 251,484 24,714 9.83% 9.80% 24,645 10 7.47% 18,794 15.10% 37,974 2 26 MS 4 69,209 17,675 25.54% 15.50% 10,727 3 51.63% 35,735 38.60% 26,715 2 27 MT 5 53,209 8,441 15.86% 16.00% 8,513 2 13.25% 7,050 9.40% 5,002 4 28 NC 16 238,874 37,388 15.65% 13.20% 31,531 9 34.49% 82,397 27.90% 66,646 12 29 ND 5 27,087 2,440 9.01% 12.70% 3, 440 1 4.40% 1,193 7.60% 2,059 0 30 NE 6 79,313 8,992 11.34% 10.70% 8,486 2 11.38% 9,027 10.40% 8,249 2 31 NH 2 53,302 4,355 8.17% 7.60% 4, 051 2 5.40% 2,877 4.00% 2,132 2 32 NJ 6 119,286 17,958 15.05% 8.10% 9,662 3 43.96% 52,438 27.40% 32,684 3 33 NM 4 17,491 4,638 26.52% 19.30% 3,376 3 55.72% 9,746 33.20% 5,807 3 34 NV 3 8,471 823 9.72% 10.10% 856 1 15.75% 1,334 24.80% 2,101 1 35 NY 13 226,416 29,187 12.89% 14.70% 33, 283 3 17.42% 39,451 32.10% 72,680 3 36 OH 23 391,705 42,242 10.78% 11.10% 43, 479 7 12.24% 47,953 15.00% 58,756 2 37 OK 6 30,357 6,117 20.15% 14.10% 4, 280 4 38.84% 11,791 23.80% 7,225 1 38 OR 1 3,884 596 15.35% 12.90% 501 1 39.19% 1,522 13.40% 520 1 39 PA 28 167,254 15,499 9.27% 9.80% 16,391 15 6.61% 11,048 14.60% 24,419 3
40 RI ND 41 SC 12 222,414 28,746 12.92% 12.00% 26,690 8 31.40% 69,831 32.80% 72,952 6 42 SD 2 30,508 1,763 5.78% 9.40% 2,868 1 5.55% 1,694 11.30% 3,447 0221 Exhibit 7G Minority and Low-Income Population Data Aggregated on State-by-State Basis

A B C D E F (E/D) G ( Exh 7F ) H (DxG) I J K (DxJ) L ( Exh 7F ) M (DxL) N

General Population Data Low Income Population Data (Below Poverty) Minority Population Data

Item State ZCTA

count 2000 population residing in electric utility plant ZCTA

areas Count of plant ZCTA residents

below poverty

level % of plant
ZCTA residents below poverty level State % below poverty

level Expected count of residents

below poverty based on

state% Count of plants with ZCTA% >

state% poverty

level % of plant ZCTA residents that are minority Count of plant ZCTA

residents that are minority Statewide % minority Expected count of minority based on

state% Count of plants with ZCTA% >

state% minority

level 43 TN 8 158,267 26,572 16.79% 13.40% 21,208 4 37.38% 59,159 19.80% 31,337 1 44 TX 17 98,402 14,147 14.38% 14.90% 14,662 10 22.41% 22,052 29.00% 28,537 3 45 UT 6 34,209 3,885 11.36% 8.10% 2,771 6 5.22% 1,784 10.80% 3,695 0 46 VA 15 220,800 21,822 9.88% 8.10% 17, 885 11 37.78% 83,411 27.70% 61,162 11
47 VT ND 48 WA 1 21,842 3,394 15.54% 9.50% 2,075 1 9.54% 2,083 18.20% 3,975 0 49 WI 13 178,705 23,577 13.19% 9.00% 16,083 8 12.00% 21,446 11.10% 19,836 4 50 WV 13 64,771 15,577 24.05% 15.80% 10,234 11 6.45% 4,179 5.00% 3,239 2 51 WY 8 69,736 6,439 9.23% 11.10% 7,741 1 4.92% 3,428 7.90% 5,509 0 Summary:

Column totals 430 6,076,410 783,062 12.9% 11.9% 658,336 240 21.7% 1,317,895 24.9% 1,241,382 129
18.9% -5.8% Min = 4.6% 7.3% 1.3% 3.1%
Max = 26.5% 19.3% 78.2% 75.7% Extrapolated to 495 plants = 256 138222 Step 5: Ratios: EPA compared the percen tages of minority and low-income populations surrounding the plants to their respective statewide benchmark percentages and to the nationwid e percentages of these populations as calcu lated in Step 4, by calculating numerical ratios between the plant ZCTA group populations co mpared to statewide and nationwide percentages of minority and low-income populations. The purpose of these ratios is to indicate the relative degree by which th e percentages are below or above the st atewide percentages. Exhibit 7H below displays the results.

Exhibit 7H Comparison of Minority and Low-Income Populations Near Coal-Fired Electric Utility Plan ts to Statewide Percentages
A B C D E F (DvE) G (D/E) H I J (HvI) K (I/J) Low-Income Data Comparison Minority Data Comparison

Item State Count of plants Percent
Low-Income

Population Surrounding Plants Statewide
Low-Income Percentage ( Exhibit 7F ) Difference Ratio Percent Minority Population Surrounding Plants Statewide Minority Percentage ( Exhibit 7F ) Differenc

e Ratio
1 AK 2 12.3% 8.4% 3.9% 1.47 32.0% 30.7% 1.3% 1.04
2 AL 9 24.5% 14.7% 9.8% 1.67 42.2% 28.9% 13.3% 1.46
3 AR 3 10.3% 15.8% -5.5% 0.65 7.7% 20.0% -12.3% 0.39
4 AZ 6 21.3% 13.5% 7.8% 1.58 43.7% 24.5% 19.2% 1.78
5 CA 5 21.9% 14.0% 7.9% 1.57 45.2% 40.5% 4.7% 1.12
6 CO 15 13.7% 8.5% 5.2% 1.62 17.9% 17.2% 0.7% 1.04
7 CT 2 15.0% 7.7% 7.3% 1.95 45.1% 18.4% 26.7% 2.45
8 DC NR NA NA NA NA NA NA NA NA
9 DE 3 8.5% 9.9% -1.4% 0.86 28.9% 25.4% 3.5% 1.14
10 FL 14 10.6% 12.1% -1.5% 0.88 20.8% 22.0% -1.2% 0.94
11 GA 9 14.5% 12.5% 2.0% 1.16 42.7% 34.9% 7.8% 1.22
12 HI 1 4.6% 10.6% -6.0% 0.43 78.2% 75.7% 2.5% 1.03
13 IA 17 9.7% 7.9% 1.8% 1.23 7.0% 6.1% 0.9% 1.15
14 ID NR NA NA NA NA NA NA NA NA
15 IL 25 18.3% 10.5% 7.8% 1.74 41.5% 26.5% 15.0% 1.56
16 IN 19 7.9% 8.3% -0.4% 0.95 7.0% 12.5% -5.5% 0.56
17 KS 7 13.0% 10.5% 2.5% 1.24 36.8% 13.9% 22.9% 2.64
18 KY 19 12.7% 12.5% 0.2% 1.02 8.5% 9.9% -1.4% 0.86
19 LA 4 24.8% 18.5% 6.3% 1.34 45.2% 36.1% 9.1% 1.25
20 MA 4 15.1% 10.1% 5.0% 1.49 20.7% 15.5% 5.2% 1.33
21 MD 8 10.5% 7.3% 3.2% 1.44 12.4% 36.0% -23.6% 0.34
22 ME 1 15.4% 9.8% 5.6% 1.57 1.3% 3.1% -1.8% 0.42
23 MI 23 8.0% 10.2% -2.2% 0.79 10.6% 19.8% -9.2% 0.53
24 MN 15 11.2% 7.8% 3.4% 1.43 10.8% 10.6% 0.2% 1.02
25 MO 19 9.8% 9.8% 0.0% 1.00 7.5% 15.1% -7.6% 0.49
26 MS 4 25.5% 15.5% 10.0% 1.65 51.6% 38.6% 13.0% 1.34223 Exhibit 7H Comparison of Minority and Low-Income Populations Near Coal-Fired Electric Utility Plan ts to Statewide Percentages
A B C D E F (DvE) G (D/E) H I J (HvI) K (I/J) Low-Income Data Comparison Minority Data Comparison

Item State Count of plants Percent
Low-Income

Population Surrounding Plants Statewide
Low-Income Percentage ( Exhibit 7F ) Difference Ratio Percent Minority Population Surrounding Plants Statewide Minority Percentage ( Exhibit 7F ) Differenc

e Ratio
27 MT 6 15.9% 16.0% -0.1% 0.99 13.2% 9.4% 3.8% 1.41
28 NC 19 15.7% 13.2% 2.5% 1.19 34.5% 27.9% 6.6% 1.24
29 ND 7 9.0% 12.7% -3.7% 0.71 4.4% 7.6% -3.2% 0.58
30 NE 6 11.3% 10.7% 0.6% 1.06 11.4% 10.4% 1.0% 1.09
31 NH 2 8.2% 7.6% 0.6% 1.08 5.4% 4.0% 1.4% 1.35
32 NJ 6 15.1% 8.1% 7.0% 1.86 44.0% 27.4% 16.6% 1.60
33 NM 4 26.5% 19.3% 7.2% 1.37 55.7% 33.2% 22.5% 1.68
34 NV 3 9.7% 10.1% -0.4% 0.96 15.7% 24.8% -9.1% 0.63
35 NY 13 12.9% 14.7% -1.8% 0.88 17.4% 32.1% -14.7% 0.54
36 OH 24 10.8% 11.1% -0.3% 0.97 12.2% 15.0% -2.8% 0.82
37 OK 6 20.2% 14.1% 6.1% 1.43 38.8% 23.8% 15.0% 1.63
38 OR 1 15.3% 12.9% 2.4% 1.19 39.2% 13.4% 25.8% 2.92
39 PA 31 9.3% 9.8% -0.5% 0.95 6.6% 14.6% -8.0% 0.45
40 RI NR NA NA NA NA NA NA NA NA
41 SC 12 12.9% 12.0% 0.9% 1.08 31.4% 32.8% -1.4% 0.96
42 SD 2 5.8% 9.4% -3.6% 0.61 5.6% 11.3% -5.7% 0.49
43 TN 8 16.8% 13.4% 3.4% 1.25 37.4% 19.8% 17.6% 1.89
44 TX 18 14.4% 14.9% -0.5% 0.96 22.4% 29.0% -6.6% 0.77
45 UT 6 11.4% 8.1% 3.3% 1.40 5.2% 10.8% -5.6% 0.48
46 VA 16 9.9% 8.1% 1.8% 1.22 37.8% 27.7% 10.1% 1.36
47 VT NR NA NA NA NA NA NA NA NA
48 WA 1 15.5% 9.5% 6.0% 1.64 9.5% 18.2% -8.7% 0.52
49 WI 15 13.2% 9.0% 4.2% 1.47 12.0% 11.1% 0.9% 1.08
50 WV 16 24.0% 15.8% 8.2% 1.52 6.5% 5.0% 1.5% 1.29
51 WY 9 9.2% 11.1% -1.9% 0.83 4.9% 7.9% -3.0% 0.62 Summary: Min = 4.6% 7.3% -6.0% 0.43 4.4% 3.1% -23.6% 0.34
Max = 26.5% 19.3% 10.0% 1.95 78.2% 75.7% 26.7% 2.92 Nationwide = 464 12.9% 11.9% 1.0% 1.08 21.7% 24.9% -3.2% 0.87224 x Minority & Low-Income Demographic Findings

Below is a summary of the three alternative but complementary co mparison approaches based on the same minority and low-income p opulation data: (a) itemized plant-by-plant basis, (b) nationwide aggrega tion basis, and (c) state-by-stat e aggregation basis. For purpo se of determining the relative degree by which either group living near the 495 plants may exceed their resp ective statewide population percentages, the percentages are compared as a numerical ratio where by a ratio of 1.00 indicates th at the group populati on percentage living near a plant is equal to the statewide average, a ratio great er than 1.00 indicates the group population percentage near the pl ant is higher than the statew ide population, and a ratio less than 1.00 indicates the group population is less than the respect ive statewide average.

x General population findings:

o 464 plants (i.e., 94% of the 495 universe) fo r which year 2000 Census plant address ZC TA data are availabl e are located in 47

states.

o The plant address ZCTA population surroundi ng the 464 plants with ZCTA data is 6.08 million , which is an average of 13,091 surrounding population per plant.

x Low-income population findings:

o 0.78 million low-income population surroundi ng the 464 plants represents 12.9% of the 6.08 million total surrounding populations; this is higher than the 11.9% national percentage.

o State-by-state low-income population per centages surrounding these plants range from 4.6% in HI to 26.5% in NM.

o Extrapolated and aggregated ac ross all 495 plants, 256 plants ( 52% ) have surrounding populations wh ich exceed their statewide benchmark percentage of low-income population.

o The ratios of low-income population per centages surrounding these plants range from 0.43 to 1.95, and the average of the ratios compared to the national average ratio of the low-income population is 1.08.

o Approximately 29 of the 47 states (62%) have higher percentage s of low-income populations compared to their respective statewide benchmarks.

o States with the largest difference in low- income populations surrounding the plants comp ared to their statewide benchmarks are:

1. Mississippi (26% vs. 16%) 2. Alabama (25% vs. 15%)
3. Illinois (18% vs. 11%)
4. New Jersey (15% vs. 8%)
5. Connecticut (15% vs. 8%)

x Minority population findings:

o 1.32 million minority population surrounding the 464 plants represents 21.7% of the 6.08 million total surrounding populations; this is lower than the 24.9% national minority population.225 o The state-by-state range of minority population percentages su rrounding these plants ranges from 1.3% in ME to 78.2% in HI.

o Extrapolated and aggregated ac ross all 495 plants, 138 plants ( 28% ) have surrounding populations wh ich exceed their statewide benchmark minority percentage of population.

o The ratio of minority population percentages surrounding these plan ts range from 0.34 to 2.92, and the average of the ratios compared to the national average ratio of the minority population is 0.87.

o Approximately 24 of the 47 states (51.1%) have disproportionately high percentages of minority populations within the plant address ZCTA area compared to the rest of the state.

o States with the largest difference in minor ity populations between the ZCTA where the pl ants are located comp ared to the rest o f the state are as follows:

1. Connecticut (45% vs. 18%)
2. Arizona (44% vs. 25%)
3. Oregon (39% vs. 13%)
4. Tennessee (37% vs. 20%)
5. Kansas (37% vs. 14%)

x Plant level results:

Using the plant-by-plant (i.e., itemized ZC TA) basis, 138 plants (28%) have surround ing minority populations which exceed their statewide minority benchmark percentages, whereas 357 plants (72%) have minority populations belo w their statewide benchmarks, which repr esents a plant ZCTA ratio of 0.39 (i.e., 138/357). Because this rati o is 61% less than 1.00 (i.e., 1.00 minus 0.39), this finding indic ates that only a relatively small count of plants have su rrounding minority population pe rcentages which disproportio nately exceed their statewi de benchmarks. Also on a plant-by-plant ZCTA basis, 256 pl ants (52%) have surrounding low-income popul ations which exceed their respective sta tewide benchmarks, whereas 239 plants (48%) have surrounding low-income populations below thei r statewide benchmarks, which represents a plant ZCTA ratio of 1.07 (i.e., 256/239). Because th is ratio is only slightly (7%) above 1.00, it indicates that a slightly dispropo rtionate count of plants have surrounding low-income population percenta ges which exceed their statewide benchmarks.

x State level results:

Using the state-by-state aggregation basis, the percentages of minority and low-inco me populations surroundin g the plants were compared to their respective statew ide population benchmarks. From th is, state ratios revealed that 24 of the 47 states (51%) have higher minority percentages, and 29 of the 47 states (62 %) have higher low-income percentages surro unding the 495 plants, suggesting a slightly disproportionate higher minority surrounding population and a re latively large disproportionate, higher low-income surrounding population. Howe ver, in comparison to the other two numerical comp arisons, this state-by-state count approach does not include num erically-weighting of state plant counts or state surrounding populations, which ex plains why this comparison method yields a different numerical result. This m ethod illustrates how population comparison results may be sensitive to the comparison method.226 x Nationwide results:

Using the nationwide aggregation basis ac ross all 495 plants in all 47 states wher e the plants are located, 6.08 million people live in ZCTA surrounding the plants, which include a sub-total of 1.32 milli on (21.7%) minority and a sub-total of 0.8 million (12.9%) low-i ncome population groups. A comparison of these percentages to the national benchmark averages across all states of 24.9% minority and 11.9% low -income, represents a minority ratio of 0.87 (i.e., 21.7%/24.9%) and a low-income ratio of 1.08 (i.e., 12.9%/11.9%). These nationwide a ggregate ratios indicate a slightly lower di sproportionate minority population surrounding the 495 plants, and a slightly higher disproportiona te low-income population surrounding the plants. Comparison of nationwide populati on sub-totals for all plants for each demographic group co mpared to the expected value based on statew ide averages, reveals that:

o +18.9% additional low-income residents near the plants compared to the expected low-income population based on statewide averages (i.e., 783,062 low-income population for all 464 plants compared to 658,336 expected count if based on statewide averages.)

o -5.8% less minority residents near the plants compared to the expected minority popul ation based on statewide averages (i.e., 1,317,896 minority population for all 464 plants compared to 1,241,382 expected count if based on statewide averages).

These three alternative comparisons indicate that the current (bas eline) environmental and human health hazards and risks from electric utility CCR disposal units, and the expected future benefits of the regulatory options, may ha ve a disproportionately lower effect on m inority populations and may have a disproportionately higher effect on low-income populations.

x Other Potentially Affected Mino rity & Low-Income Populations

There are two other potential differential effects of the re gulatory options on two other popul ation groups: (a) populations su rrounding offsite CCR landfills, and (b) populations within the customer service areas of the 495 electric utility plants.

o Offsite CCR Landfills

The potential effect on offsite landfills involves the RCRA Subtitle C based regulatory options wher eby four different fraction s of CCR generation may be required to be disposed in RCRA Subtitle C permitted landfills rath er than in non-RCRA permitted waste landfi lls:

x CCR fraction #1: Electric utilit y plants may switch the management of CCR, in whole or in part, from current onsite disposal to offsite commercial RCRA-permitted hazardous wast e landfills (56.8 million is disposed in onsite landfills, and 22.4 million is disposed in onsite impoundments, tota ling 79.2 million tons disposed onsite).

x CCR fraction #2: Some or all of the CCR which is currently disposed in offsite landfills that do not have RCRA Subtitle C permi ts may also switch to RCRA-permitted commercial hazardous waste landfills if the current recei ving landfills do not obtain RCRA Subtitle C permits (15.0 million tons is disposed offsite).227 x CCR fraction #3: Annual CCR generati on which is currently supplied for industrial beneficial use applica tions could also switch to offsite commercial RCRA Subtitle C permitted landfills if such use becomes curtailed in part or in whole from either state government regulations or from market st igma (47.0 million tons is beneficially used).

x CCR fraction #4: Future cleanup of CCR dispos al unit failures (e.g., impoundment collapse ) would require dis posal in RCRA Subti tlepermitted waste landfills (the two CCR impoundment release case studies in Exhibit 4A of this RIA represent a range of 0.25 million to 3.3 million tons per failure event).

One or more of these four poten tial shifts of CCR disposal from current non- hazardous landfills to ha zardous waste landfills, c ould have a disproportionate effect on populations surr ounding these locations, and in particular, minority and low-income populations surr ounding commercial hazardous waste facilitie s, if current landfills operated by electric util ity plants do not obtain future Subtitle C permits (Option 1). A recent (2007) study determined that minority and low-income popul ations disproportionately live near commercial hazardous was te facilities, although the study include d other types of commercial hazardous waste treatment and disposal facilities in addition to commercial hazardous waste landfills. 187 An example of such potential EJ concerns is a 2009 US national news item involvi ng the decision made by the Tennessee Valley Authority (TVA) to train transport 3 million tons of the TVA_s (Kingston TN electricity plant) December 2008 C CR impoundment collapse site cleanup waste, 350 miles away to a landfill in a rural Alab ama county which reportedly has about 70% minority (African American) and 33% low-income residents. 188 However, this example serves to illust rate that EJ concerns are not necessarily conclusive or shared by all affected EJ populations, as evidenced by the following rema rks made to news re porters by the Alabam a county government officials and county residents: 189

g To county leaders, the train’s loads, which will total three million cubic yards of coal ash from a massive spill at a power pl ant in east Tennessee last December [2008], are a tremendous financial windfall. A per- ton “host fee” that the landfill operators pay the county will add more than $3 milli on to the county’s budget of about $4.5 mill ion. The ash has created more than 30 jobs for local residents in a county wher e the unemployment rate is 17 percent and a third of all households are below the poverty line. A sign on the door of the landfill’s scale hous e says job applications are no longer being accepted — 1,000 were more than enough. But some residents worry that their leaders ar e taking a short-term view, and that their community has been too easily persuaded to take on a wealthier, whiter community’s problem.... County leaders, who are mostly black, bristle at accusations of environmental injustice, sa ying that the ash is perfectly safe and that criticism has been fostered by outsiders , or even competitors who wanted the ash disposal contract for themselves..... Bob Deacy, vice president of clean strategies and

187 Source: United Church of Christ, gToxic Wastes and Race at Twenty 1987-2007h, March 2007. . This study evaluated and made find ings on minority and low-income population data within a 1.8-m ile radius ghost neighborhoodh of 413 commercia l hazardous waste facilities, compared to gnon-hos th areas. The study (page x) found that gHost neighborhoods of commercial hazardous waste facilities are 56% people of colo r whereas non-host area s are 30% of color{ Poverty rates in the host neighborhoods are 1.5 times greater than non-host areas (18% vs. 12%).h

188 Source: Shaila Dewan, gClash in Alabama Ov er Tennessee Coal Ash,h The New York Times , 30 Aug 2009 at h ttp://www.nytimes.com/2009/08/30/us/30ash.html

189 Source: At least two news organizations identically reported these remarks on 30 Aug 2009: #1 of 2: New York Times , gClash in Alabama Over Tennessee Coal Ashh at http://www.nytimes.com/2009/08/30/us/30ash.html #2 of 2: Waste Business Journal , gWaste From TVA Spill Begins to Arrive at Alabama Landfill Amid Controversyh at http://www.wastebusinessjournal. com/news/wbj20090901D.htm228 project development for the Tennessee Valley Authority, whose Ki ngston Fossil Plant was the site of the ash spill that covered almost 300 acres of land and waterways, said Arrowhead [Al abama landfill] was chosen beca use it was reachable by train instead of truck, because it underbid other sites and because, unlike cl oser landfills, it had the capacity to handle all the a sh. h

o Electricity Service Area Customers

A third potential effect of the regulatory op tions described in today_s notice is the price of electricity supplied by some or all of the affected 495 electric utility plants could in crease to cover the cost of regulatory compliance. Thus customers in electric utility service areas could experience price increases, although the RIA esti mates that future potential price increases could be expected to be below 1% i ncrease relative to the $0.0900 per kilowatt hour national averag e price (February 2009) for all four cust omer sectors (i.e., residential, comme rcial, industrial, and transportation). The RIA for today_ s action did not evaluate the customer service area populations for the 495 plants.229 

### 7D. Child Population Stati stics (Executive Order 13045)

x Purpose of Child Population Data Analysis

Under Executive Order (EO) 13045 of 21 April 1997, Federal Agencies shall make it a high priority (a) to identify and assess en vironmental health and safety risks that may dispropor tionately affect children, and (b) shall en sure that its policies, programs, activiti es, and standards address disproportionate risks to children th at result from environmental health or sa fety risks. Although the EO does not def ine children, the US Census Bureau defines gchildrenh as follows 190 :

Children: The term "children"... are a ll persons under 18 years, excluding people who maintain households, families, or subfamilies as a reference person or spouse.

The purpose of this section is not to evaluate children risks, but to evaluate whether disproportionate percentages of children live near electric utility plants. This analysis involves a 5-step process for comparing children populat ion data for each electric utility plant location, to statewide children population data to iden tify whether children disp roportionately reside in geographi c areas where electric utility plan ts are located.

x Collection of Child Demographic Data

Step 1:Plant address 5-digit gZip Code Ta bulation Areash (ZCTAs) formed the geographic basis for this child population data col lection. Because ZCTAs represent irregularly shaped geographic areas, this ZCTA based data co llection may be consid ered a gscreening lev elh analysis. The US Bureau of Census uses over 33,000 ZCTAs for its Census counts of population and other demographic statistics based on the US Postal Service_s over 42,000 nationwide ZCTAs. 191 Currently, there are no size restri ctions limiting how large or small a ZCTA can be in terms of either a minimum/maximum number of hous ing units or geographic area. A ny particular ZCTA may be as small as a few city blocks or may cover many square miles. Ma ny ZCTAs are for villages, census-d esignated places, portions of cities, or other entities that are not municipali ties. The nationwide average ZCTA populat ion is about 7,200 persons (i.e., (306.6 mil lion mid2009 US population) / (42,500 ZCTAs)). The nationwide average ZCTA area is about 83 square miles (i.e., (3,536,278 square mile s total US land and water area) / (42,500 ZCTAs)), which is a land area equivalent to a 5-mile radial di stance (i.e., ((83 square miles) / (3.1416))^0.5). In comparison, the radial area monitored for c ontamination in response to the December 2009 TVA Kingston TN electric plant CCR spill is reportedly four miles, 192 and this average 5-mile ZCTA radial dist ance falls between the 1-mile to 15-mile radial distances used by EPA_s S uperfund gHazard Ranking Systemh (HRS) 193 to define affected populations of sites having either (a) soil contamination only (1-mile), (b) groundwater and/or airborne contamination (4-miles), or (c) surface water contamination ( 15-miles

190 The US Census Bureau definition of gchildrenh is from its gCur rent Population Survey (CPS) - De finitions and Explanationsh web site at: http://www.census.gov/population/www/cps/cpsdef.html

191 Source: US Census Bureau ZIP Code Tabulation Area (ZCTA) Freque ntly Asked Questions.: Nationwide total ZCTA count is from t he US Postal Service_s FAQ website at: http://zip4.usps.com/zip4/welcome.jsp

192 Source: 4 mile radial monitoring area reported by Waste & Recycling News , 13 Feb 2009; http://www.wasterecyc lingnews.com/email.html?id=1234543579

193 More background information about EPA_s HRS is available at http://www.epa.gov/superfund /programs/npl_hrs/hrsint.htm.230 downstream). Using the Census search engine Factfinder (htt p:factfinder.census.gov/home/saff/ma in.html?_lang=en), EPA retrieve d total population and people 18 and over for 464 (94%) of the 495 el ectric utility plants. For 42 plants (8%) there was no ZCTA Census data because the plants did not have comple te address data from DOE or b ecause the Census search engine did not have data for t he ZCTA.

Step 2: EPA collected 3-year (2005 to 2007) average statewide percen tages for people 18 and older data as displayed in Exhibit 7I below.

Exhibit 7I State-by-State Data on Child Populations (2005-2007 Average)

Row State % children in state

1 AK 27.0%
2 AL 24.4%
3 AR 24.8%
4 AZ 26.4%
5 CA 25.9%
6 CO 24.7%
7 CT 23.7%
8 DC 19.5%
9 DE 23.9%
10 FL 22.3%
11 GA 26.5%
12 HI 22.3%
13 IA 23.9%
14 ID 27.3%
15 IL 25.1%
16 IN 25.1%
17 KS 25.2%
18 KY 23.9%
19 LA 25.4%
20 MA 22.5%
21 MD 24.4%
22 ME 21.5%
23 MI 24.6%
24 MN 24.5%
25 MO 24.4%
26 MS 26.3%
27 MT 23.2%
28 NC 24.4%
29 ND 22.5%
30 NE 25.3% Row State % children in state
31 NH 23.1%
32 NJ 24.0%
33 NM 25.6%
34 NV 25.8%
35 NY 23.2%
36 OH 24.2%
37 OK 24.9%
38 OR 23.2%
39 PA 22.6%
40 RI 22.3%
41 SC 24.2%
42 SD 24.8%
43 TN 24.1%
44 TX 27.7%
45 UT 30.9%
46 VA 23.9%
47 VT 21.6%
48 WA 23.9%
49 WI 23.8%
50 WV 21.5%
51 WY 24.0% Max (UT) 30.9% Min (DC) 19.5%
Nationwide 24.7%231 x Comparison of Child Populations Living Near El ectric Utility Plants to Statewide Benchmarks

Step 3, Step 4 and Step 5 of this evalua tion described below involved three complement ary levels of data comparisons. All thre e comparisons also involved two complementary numerical comparisons, one base d on calculating numerical percentages and the other based on ca lculating numerical ratios:

1. Plant level: Plant-by-plant disaggregated data comparison to st atewide benchmarks
2. State level: State-by-state a ggregated plant data comparis on to statewide benchmarks
3. National level: National aggregated plant data comparison to statewide benchmarks

Step 3: On a plant-by-plant basis, EPA co mpared the plant ZCTA percentage children, to the respective statewide average percent age children.

Step 4: For purpose of summary, EPA aggregated the plant level children population comparison data for each state as displayed in Exhibit 7J below. There are no data displayed for DC, ID, RI or VT because there are no coal-fired electric utility plants in those state s. Appendix O of this RIA presents the plant-by-plant Ce nsus data on which this Exhibit is based.

Exhibit 7J State-by-State Child Population Data for Coal-Fired Electric Utility Plants General Population Data Child Population Data

Item Count of plant unique ZCTAds State Count of plant ZCTAs which have Census population data 2000 plant ZCTA resident population Child population count (<18 years) in plant ZCTAs Child population percentage

in plant ZCTAs Statewide percentage child population Expected children count in plant ZCTAs if based on state % If plant ZCTA child% >

state children% 1 2 AK 2 18,552 5,188 27.96% 27.00% 5,009 2 2 9 AL 9 82,854 21,978 26.53% 24.40% 20,216 4 3 3 AR 3 11,786 3,359 28.50% 24.80% 2,923 3 4 6 AZ 6 34,941 11,526 32.99% 26.40% 9,224 5 5 5 CA 4 112,895 36,285 32.14% 25.90% 29,240 5 6 15 CO 15 214,095 49,190 22.98% 24.70% 52,881 11 7 2 CT 2 42,716 10,743 25.15% 23.70% 10,124 1
8 NA DC 9 3 DE 3 46,925 11,169 23.80% 23.90% 11,215 1 10 14 FL 13 224,502 55,025 24.51% 22.30% 50,064 11 11 9 GA 9 202,973 50,964 25.11% 26.50% 53,788 5 12 1 HI 1 25,054 8,158 32.56% 22.30% 5,587 1 13 17 IA 14 324,050 77,708 23.98% 23.90% 77,448 15
14 NA ID232 Exhibit 7J State-by-State Child Population Data for Coal-Fired Electric Utility Plants General Population Data Child Population Data

Item Count of plant unique ZCTAds State Count of plant ZCTAs which have Census population data 2000 plant ZCTA resident population Child population count (<18 years) in plant ZCTAs Child population percentage

in plant ZCTAs Statewide percentage child population Expected children count in plant ZCTAs if based on state % If plant ZCTA child% >

state children% 15 25 IL 23 455,834 129,772 28.47% 25.10% 114,414 14 16 19 IN 17 323,323 83,594 25.85% 25.10% 81,154 14 17 7 KS 6 59,517 16,532 27.78% 25.20% 14,998 6 18 19 KY 17 255,033 63,012 24.71% 23.90% 60,953 15 19 4 LA 4 30,381 8,617 28.36% 25.40% 7,717 4 20 4 MA 3 95,798 23,078 24.09% 22.50% 21,555 1 21 8 MD 7 101,141 23,529 23.26% 24.40% 24,678 5 22 1 ME 1 6,748 1,561 23.13% 21.50% 1,451 1 23 23 MI 20 383,284 94,994 24.78% 24.60% 94,288 13 24 15 MN 15 187,012 46,208 24.71% 24.50% 45,818 5 25 19 MO 19 251,484 60,084 23.89% 24.40% 61,362 12 26 4 MS 4 69,209 19,867 28.71% 26.30% 18,202 4 27 6 MT 5 53,209 14,115 26.53% 23.20% 12,344 5 28 19 NC 16 238,874 57,728 24.17% 24.40% 58,285 6 29 7 ND 5 27,087 7,411 27.36% 22.50% 6,095 4 30 6 NE 6 79,313 20,853 26.29% 25.30% 20,066 4 31 2 NH 2 53,302 10,713 20.10% 23.10% 12,313 0 32 6 NJ 6 119,286 29,806 24.99% 24.00% 28,629 4 33 4 NM 4 17,491 5,656 32.34% 25.60% 4,478 3 34 2 NV 2 8,471 1,827 21.57% 25.80% 2,186 1 35 13 NY 13 226,416 57,612 25.45% 23.20% 52,529 9 36 24 OH 23 391,705 101,253 25.85% 24.20% 94,793 14 37 6 OK 6 30,357 8,513 28.04% 24.90% 7,559 6 38 1 OR 1 3,884 1,378 35.48% 23.20% 901 1 39 31 PA 28 167,254 36,581 21.87% 22.60% 37,799 13
40 NA RI 41 12 SC 12 222,414 60,391 27.15% 24.20% 53,824 10 42 2 SD 2 30,508 7,510 24.62% 24.80% 7,566 1 43 8 TN 8 158,267 40,682 25.70% 24.10% 38,142 4 44 18 TX 17 98,402 27,471 27.92% 27.70% 27,257 7 45 6 UT 6 34,209 11,769 34.40% 30.90% 10,571 4 46 16 VA 15 220,800 55,824 25.28% 23.90% 52,771 10
47 NA VT 48 1 WA 1 21,842 5,514 25.24% 23.90% 5,220 1 49 15 WI 13 178,705 36,428 20.38% 23.80% 42,532 10233 Exhibit 7J State-by-State Child Population Data for Coal-Fired Electric Utility Plants General Population Data Child Population Data

Item Count of plant unique ZCTAds State Count of plant ZCTAs which have Census population data 2000 plant ZCTA resident population Child population count (<18 years) in plant ZCTAs Child population percentage

in plant ZCTAs Statewide percentage child population Expected children count in plant ZCTAs if based on state % If plant ZCTA child% >

state children% 50 16 WV 13 64,771 10,946 16.90% 21.50% 13,926 10 51 9 WY 8 69,736 19,732 28.30% 24.00% 16,737 6 Summary: Total 464 429 6,076,410 1,541,854 25.37% 24.70% 1,480,831 291
4.1% Min= 16.90% 21.50%
Max= 35.48% 30.90% Extrapolated to 495 plants = 310

Step 5: The percentage of children population surrounding the pl ant ZCTAs were compared to overall state percentages and the nationwide percentage of this sub-gr oup population, by calculating ratios between the plant ZCTA ch ildren populations compared to statewide and nationwide percentages of children population. Exhibit 7K below displays the results.

Exhibit 7K Comparison of Child Population Data on a State-by-State Basis

Item State Plants Percentage of ZCTA Population Under 18 Years Old Statewide Percentage of Children ( Exhibit 7I ) Difference Ratio
1 AK 2 28.0% 27.0% 1.0% 1.04
2 AL 9 26.5% 24.4% 2.1% 1.09
3 AR 3 28.5% 24.8% 3.7% 1.15
4 AZ 6 33.0% 26.4% 6.6% 1.25
5 CA 5 32.1% 25.9% 6.2% 1.24
6 CO 15 23.0% 24.7% -1.7% 0.93
7 CT 2 25.1% 23.7% 1.4% 1.06
8 DC NR NA NA NA NA
9 DE 3 23.8% 23.9% -0.1% 1.00
10 FL 14 24.5% 22.3% 2.2% 1.10
11 GA 9 25.1% 26.5% -1.4% 0.95
12 HI 1 32.6% 22.3% 10.3% 1.46234 Exhibit 7K Comparison of Child Population Data on a State-by-State Basis

Item State Plants Percentage of ZCTA Population Under 18 Years Old Statewide Percentage of Children ( Exhibit 7I ) Difference Ratio
13 IA 17 24.0% 23.9% 0.1% 1.00
14 ID NR NA NA NA NA
15 IL 25 28.5% 25.1% 3.4% 1.13
16 IN 19 25.9% 25.1% 0.8% 1.03
17 KS 7 27.8% 25.2% 2.6% 1.10
18 KY 19 24.7% 23.9% 0.8% 1.03
19 LA 4 28.4% 25.4% 3.0% 1.12
20 MA 4 24.1% 22.5% 1.6% 1.07
21 MD 8 23.3% 24.4% -1.1% 0.95
22 ME 1 23.1% 21.5% 1.6% 1.08
23 MI 23 24.8% 24.6% 0.2% 1.01
24 MN 15 24.7% 24.5% 0.2% 1.01
25 MO 19 23.9% 24.4% -0.5% 0.98
26 MS 4 28.7% 26.3% 2.4% 1.09
27 MT 6 26.5% 23.2% 3.3% 1.14
28 NC 19 24.2% 24.4% -0.2% 0.99
29 ND 7 27.4% 22.5% 4.9% 1.22
30 NE 6 26.3% 25.3% 1.0% 1.04
31 NH 2 20.1% 23.1% -3.0% 0.87
32 NJ 6 25.0% 24.0% 1.0% 1.04
33 NM 4 32.3% 25.6% 6.7% 1.26
34 NV 2 21.6% 25.8% -4.2% 0.84
35 NY 13 25.4% 23.2% 2.2% 1.10
36 OH 24 25.8% 24.2% 1.6% 1.07
37 OK 6 28.0% 24.9% 3.1% 1.13
38 OR 1 35.5% 23.2% 12.3% 1.53
39 PA 31 21.9% 22.6% -0.7% 0.97
40 RI NR NA NA NA NA
41 SC 12 27.2% 24.2% 3.0% 1.12
42 SD 2 24.6% 24.8% -0.2% 0.99
43 TN 8 25.7% 24.1% 1.6% 1.07
44 TX 18 27.9% 27.7% 0.2% 1.01
45 UT 6 34.4% 30.9% 3.5% 1.11
46 VA 16 25.3% 23.9% 1.4% 1.06
47 VT NR NA NA NA NA
48 WA 1 25.2% 23.9% 1.3% 1.06235 Exhibit 7K Comparison of Child Population Data on a State-by-State Basis

Item State Plants Percentage of ZCTA Population Under 18 Years Old Statewide Percentage of Children ( Exhibit 7I ) Difference Ratio
49 WI 15 20.4% 23.8% -3.4% 0.86
50 WV 16 16.9% 21.5% -4.6% 0.79
51 WY 9 28.3% 24.0% 4.3% 1.18

Min = 16.9% 19.5% -4.6% 0.79
Max = 35.5% 30.9% 12.3% 1.53 Nationwide = 464 25.4% 24.7% 0.7% 1.03

x Child Population Data Findings

Below is a summary of the three alternative but complementary comparison approaches based on th e same children population data: (a) plantby-plant (i.e., itemized ZCTA) basis, (b) nationwide aggregat ion basis, and (c) state-by-s tate aggregation basis. For purpose of determining the relative degree by which children may exceed th ese statewide percentages, the percentage s are compared as a numerical ratio whe reby a ratio of 1.00 indicates that the child population percentage livi ng near a plant is equal to the st atewide average, a ratio greater t han 1.00 indicates the child population percentage near the plant is higher than the statewide population, and a ratio less than 1.00 indicates the ch ild population is less than the respective statewide average.

x General population findings

o 464 plants (i.e., 94% of the 495 universe) for which Census plant address ZCTA data are located in 47 states.

o The plant address ZCTA population surrounding these plants is 6.08 million, which is an average of 13,091 surrounding population per plant.

x Child population findings

o The sub-total number of children surrounding these 464 plants is 1.54 million (i.e., 25.4% of 6.08 million). In comparison, the national average of the child population in the US is 24.7%.

o The ratios of the children population pe rcentages surrounding these plants range from 0.79 to 1.53, and the average of the ratios compared to the national average ratio of the low-income population is 1.03.

o 27 of the 47 states (57%) have disproportio nately high percentages of children within the plant a ddress ZCTAs compared to the statewide percentages.

o States with the largest difference in th e children population between th e ZCTAs where the plants are located compared to the statewide percentages are as follows:
1. Oregon (36% vs. 23%)236 2. Hawaii (33% vs. 22%)
3. New Mexico (32% vs. 26%)
4. Arizona (33% vs. 26%)
5. California (32% vs. 26%)

o A sub-total of 291 plants (63%) have su rrounding children popul ations which exceed their resp ective statewide percentage.

x Plant level results:

Using the plant-by-plant (i.e. itemized ZCTA) basis, 310 plants (63%) have surrounding child populations which exceed their sta tewide children benchmark percentages, whereas 185 plants (37%) have ch ildren populations below their st atewide benchmarks, which repr esents a plant ZCTA ratio of 1.68 (i.e., 310/185). Since this ratio is much greater than 1.00, this findi ng indicates that a highly dis proportionate count of plants have surrounding child population percenta ges which exceed their statewide benchmark.

x State level results:

Using the state-by-state aggregation basis, the percentage of child popu lations surrounding the plants were compared to their r espective statewide population benchmarks. The state- by-state ratios revealed th at approximately 27 of the 47 states (57%) have dispropo rtionate percentages of children within th e plant address ZCTA compared to the rest of the state sugge sting a dispropo rtionate surroundi ng child population. However, in comparison to the other two numerical comparisons above, this state-by-state count approach does not i nclude numerically-weighting of state pl ant counts or state surr ounding populations, which explains w hy this comparison method yields a different numerical result. This method illustra tes how population comparison results may be sensitive to the comparison method.

x Nationwide results:

Using the nationwide aggregation basis ac ross all 495 plants in all 47 states wher e the plants are located, 6.08 million people live in ZCTAs surrounding the plants, which include a sub-to tal of 1.54 million children (25.4%). Compar ison of this percentage to the natio nal aggregate benchmark across all states of 24.7% childre n yields a ratio of 1.03 (i.e., 25.4%/24.7%). This ratio indica tes a slightly high er disproportionate child population surrounding the 495 plants. Comparison of the nationwide child populat ion sub-total for all plants reveals th at +4.1% additional children reside near the plants, compared to the expected child population if base d on state averages (i.e., 1,541,8 54 children living near the 464 plants compared to 1,480,831 expected children count).

These three alternative comparisons indicate that the current (bas eline) environmental and human health hazards and risks from electric utility CCR disposal units, and the expected future benefits of the regulatory options, may ha ve a disproportionately higher effect on child populations.237 

### 7E. Unfunded Mandates (UMRA) & Federalism Imp lications Analysis (Executive Order 13132)

x UMRA

Among its other purposes and Federal agency rulemaking requirements, Title II of the 1995 Unfunded Mandates Reform Act (UMRA; 2 U.S.C. 1531-1538), requires Federal agencies , unless otherwise prohibited by law, to assess the effect s of their regulatory act ions on State, local, and tribal governments and on the private sect or, to determine whether any proposed rulemaking:

g ...is likely to result in promulgation of any rule that includes any Federal mandate that may result in the expenditure by State, local, and tribal governments, in the aggr egate, or by the private sector, of $100 million or more in any one year. h

Section 202 of UMRA requires Federal agenci es which propose rules that are likely to exceed this $100 million expenditure thres hold on either the private sector or on state/lo cal/tribal governments, to prepare a gWritten Statementh containing the following five compone nts, and supply the Written Statement to OMB as well as summarize it in the Federal Register notice (aka gpreambleh ) for the proposed rule:

1. Identification of the applicable authorizing Federal law
2. Qualitative and quantitative assessment of the anticipated costs and benefits of the rule including the costs and benefits to S tate, local, and tribal governments or the private sector , and an analysis of whether Federal reso urces may be available to pay these costs
3. Estimates of future compliance costs a nd any disproportionate budgetary effects
4. Estimates of effects on the national economy such as productiv ity, economic growth, employment , job creation, international competitiveness
5. Description and summary of agency_s prior consultation with elected representatives of the affected State, local and tribal gov ernments.

Section 202 of UMRA allows Federal agencies to prepare the gWritten Statement gin conj unction with or as a part of any other st atement or analysis. Accordingly, the purpose of this section of the RIA is to determine whether the regul atory options evaluated in this RIA exceed this UMRA direct cost threshold.

Findings: The private sector and the state/local government shares of direct compliance costs un der each option are displayed b elow in Exhibit 7L , which indicates that:

 Private sector cost test : All of the regulatory options are expected to result in expenditure s of $100 million or more in the aggregate for the private sector, in an y one year (i.e., 139 companies and coopera tives of the total 200 owner entities).

 State/local/tribal government cost test : None of the regulatory options are exp ected to result in expenditures of $100 million or more for State, local, and tribal governments in the aggregate in any one year (there are 60 state/local government owner entities identified in Exhibit 7M below, no known tribal owner entit ies, plus one Federal owner).

According to the private sector test findi ng, EPA has prepared an gUMRA Written Statemen th which is attached to this RIA as Appendix P

.238 x Federalism (Executi ve Order 13132)

The 1999 Federalism Executive Order 13132 (Federal Register , Vol.64, No. 153, 10 Aug 1999) furthers the policies of the 1995 Unfunded Mandates Reform Act (UMRA) by establishing fe deralism principles, federalism policymak ing criteria, and a state/local governmen t consultation process for the development of Fe deral regulations that have federalism im plications. Federalism implications ref ers to regulations and other Federal polic ies and actions that have substantial direct effects on states, on th e relationship between the Federal government and the states, or on the dist ribution of power and res ponsibilities among the various levels of government.

For purpose of complying with the Section 6 consultation process of EO 13132, this section of the RI A evaluates whether the CCR regulatory options may gimpose substantial direct compliance cost sh on state/local governments. As summarized in Exhibit 7L , the proposed rule might impose four types of direct costs on the 60 stat e/local government owner entities identified in Exhibit 7M below:

x State/local government owned electric utility plants: 1. Engineering control costs for CCR disposal units located at electr ic utility plants owned by state/local governments.
2. Ancillary costs for CCR disposal units located at elec tric utility plants owned by state/local governments.
3. Conversion to dry disposal costs for CCR di sposal units located at electricity util ity plants owned by st ate/local governments.

x State government environmental agencies:
4. Regulatory implementation, administration, and enforcement costs to RCRA-authoriz ed state government programs/agencies.

Consistent with the gdirect costh scope of EO 13132, not included in Exhibit 7L are potential indirect costs in the form of potential lost annual revenues to electricity plants associated with potential reducti ons in CCR sold by plants for be neficial use under the three Su btitle C options for which such an possible indirect effect is estimated in this RIA.

EPA_s 2008 guidance 194 for compliance with EO 13132 describes two numerical methods (i.e., numerical tests) fo r evaluating whether an EPA rule may have federalism implications with re spect to gsubstantial direct compliance costsh:

1. $25 million test : Annualized direct compliance cost expenditures to st ate/local governments in aggregate of $25 million or more 195

2. 1% test : Annualized direct compliance costs faced by state/local government s is likely to equal or exceed 1% of their annual revenues* [* Note: Page 29 of gAttachment A: Guidance for Implementing th e Federalism 1% Testh to EPA_s Nov 2008 gGuidance on Executive Order 13132: Federalismh defines small governme nt ggeneral revenueh as gmade up of inte rgovernmental revenue plus revenue from their own sources and excludes u tility, liquor store and employee retirement revenue .h However, given that the CCR proposed ru le affects electric utility industry, this RIA applies the g1% Testh in relation to only State/lo cal government electric utility a nnual revenue.]

194 The two methods are from page 6 of gEPA_s Action Development Process -- Guidance on Executive Order 13132: Federalism,h OPEI R egulatory Development Series, Nov 2008, 62 pages at http://intranet.epa.gov/adplibrary/documents/federalismguide11-00-08.pdf

195 Although one of the stated purposes of EO 13132 in its first paragraph is gto further the policies of the 1995 Unfunded Mandat es Reform Act (UMRA), EPA_s $25 million annual direct cost trigger is 75% lower than the $100 mi llion annual direct cost trigger prescribed in Section 202 of U MRA.239 x Findings for UMRA Impact and Federalism Implication Tests

Based on estimated regulatory costs on state/local governments displayed in Exhibit 4B of this RIA for each regulatory option, Exhibit 7L below displays whether the costs po tentially exceed the UMRA and Fe deralism thresholds defined above.

o UMRA finding: All options >$100 million private sector test; all options <$1 00 million state/local government test

o Federalism finding: All options >$25 million state/local govern ment test; all options <1% state/local government test

However, for consistency with the RFA/SBREFA small business impact analysis presented in a separa te section above in this RIA, this RIA estimates it is highly likely that the direct compliance costs under each option may be passed-thru to electricity plant custom ers in the form of higher electricity prices. The f easibility of such a compliance cost pass-thru scenario is evaluated and confirmed by the info rmation presented in the RFA/SBREFA small business impact section of this RIA.

Exhibit 7L UMRA and Federalism Tests for CCR Disposal Regulatory Options ($millions average annualized costs @7% discount rate over 50-years 2012 to 2061, 2009$)

Type of Direct Compliance Cost Subtitle C Hazardous waste Subtitle D (version 1) Subtitle C for impoundments Subtitle D for landfills Average annualized cost (source: Exhibit 5F ): $2,274 $492 $2,176
UMRA Test: 1. Private sector $100 million direct cost threshold test $1,999.4 $415.3 $1,908.8 2. State/local government $100 million direct cost threshold test* $96.7 $55.9 $91.6
Federalism Test: 1. $25 million threshold test: sub-total State/Local govt cost $96.7 $55.9 $91.6 2. 1% Test: State/local govt cost as percentage of State/Local government electric utility annual revenues 0.227% 0.131% 0.215%

* Note: Remainder Federal government costs represent costs associated w ith Federally-owned electric utility plants (i.e., Tennessee Val ley Authority) which are not subject to either the UMRA or Federalism te sts. Therefore, the sub-total private sect or direct cost plus the state/local gover nment direct cost does not add-up to the total annual cost estimate under each option; th e remainder cost is for the Federally-owned plants.240 Exhibit 7M List of 74 Coal-Fired Electric Utility Ge neration Plants Which EPA Estimates A re Owned by 60 State/Local Governments Source: Compiled by EPA-OSWER-ORCR based on 2007 data from the US Energy Information Administration*

Item Owner Entity Name Electric Utility Plant Name State Owner Entity Size/Type** 1 Grand River Dam Authority GRDA OK Non-Small State 2 Lower Colorado River Authority Faye tte Power Project TX Non-Small State 3 Nebraska Public Power District Ge rald Gentleman NE Non-Small State
4 Nebraska Public Power Distri ct Sheldon NE Non-Small State 5 Omaha Public Power District Ne braska City NE Non-Small State 6 Omaha Public Power District North Omaha NE Non-Small State 7 Platte River Power Authority Rawhide CO Non-Small State 8 Salt River Project Coronado AZ Non-Small State 9 Salt River Project Navajo AZ Non-Small State 10 South Carolina Pub Service Auth Cross SC Non-Small State 11 South Carolina Pub Service Auth Dolphus M Grainger SC Non-Small State 12 South Carolina Pub Service Auth Jefferies SC Non-Small State 13 South Carolina Pub Service Auth Winyah SC Non-Small State 14 American Municipal Power-Ohio, Inc Richard Gorsuch OH Non-Small City 15 Ames City of Ames Electric Servi ces Power Plant IA Non-Small City 16 City of Columbia Columbia MO Non-Small City 17 City of Hamilton Hamilton OH Non-Small City 18 City of Lakeland C D McIntosh Jr FL Non-Small City 19 City of Owensboro Elmer Smith KY Non-Small City 20 City of Springfield Dallman IL Non-Small City 21 City of Springfield Lakeside IL Non-Small City 22 City Utilities of Springfield James River Power Station MO Non-Small City 23 City Utilities of Springfield Southwest Power Station MO Non-Small City 24 Colorado Springs City of Martin Drake CO Non-Small City 25 Colorado Springs City of Ray D Nixon CO Non-Small City 26 Gainesville Regional Utilities Deerhaven Generating Station FL Non-Small City 27 Independence City of Blue Valley MO Non-Small City 28 Independence City of Missouri City MO Non-Small City 29 JEA Northside Generating Station FL Non-Small City 30 JEA St Johns River Power Park FL Non-Small City 31 Kansas City City of Nearman Creek KS Non-Small City 32 Kansas City City of Quindaro KS Non-Small City 33 Lansing Board of Water and Light Eckert Station MI Non-Small City 34 Lansing Board of Water and Light Erickson Station MI Non-Small City 35 Los Angeles City of Intermountain Power Project UT Non-Small City 36 Orlando Utilities Comm Stanton Energy Center FL Non-Small City 37 Rochester Public Utilities Silver Lake MN Non-Small City241 Exhibit 7M List of 74 Coal-Fired Electric Utility Ge neration Plants Which EPA Estimates A re Owned by 60 State/Local Governments Source: Compiled by EPA-OSWER-ORCR based on 2007 data from the US Energy Information Administration*

Item Owner Entity Name Electric Utility Plant Name State Owner Entity Size/Type** 38 San Antonio City of J K Spruce TX Non-Small City 39 San Antonio City of J T Deely TX Non-Small City 40 Vineland City of Howard Down NJ Non-Small City 41 Crisp County Power Comm Crisp Plant GA Small - County 42 Austin City of Austin Northeast MN Small City 43 Board of Water Electric & Communications Muscatine Plant #1 IA Small City 44 Cedar Falls Utilities Streeter Station IA Small City 45 City of Dover Dover OH Small City 46 City of Grand Haven J B Sims MI Small City 47 City of Holland James De Young MI Small City 48 City of Jasper Jasper 2 IN Small City 49 City of Logansport Logansport IN Small City 50 City of Marquette Shiras MI Small City 51 City of Marshall Marshall MO Small City 52 City of Menasha Menasha WI Small City 53 City of Orrville Orrville OH Small City 54 City of Painesville Painesville OH Small City 55 City of Richmond Whitewater Valley IN Small City 56 City of Shelby Shelby Municipal Light Plant OH Small City 57 City of Sikeston Sikeston Power Station MO Small City 58 City of Virginia Virginia MN Small City 59 Crawfordsville Electric Light & Power Crawfordsville IN Small City 60 Fremont City of Lon Wright NE Small City 61 Grand Island City of Platte NE Small City 62 Greenwood Utilities Commissi on Henderson MS Small City 63 Hastings City of Whelan Energy Center NE Small City 64 Henderson City Utility Commission Henderson I KY Small City 65 Hibbing Public Utilities Commission Hibbing MN Small City 66 Jamestown Board of Public Utilities S A Carlson NY Small City 67 Manitowoc Public Utilities Manitowoc WI Small City 68 Michigan South Central Power Agency Endicott Station MI Small City 69 New Ulm Public Utilities Commission New Ulm MN Small City 70 Pella City of Pella IA Small City 71 Peru City of Peru IN Small City 72 Texas Municipal Power Agency Gibbons Creek TX Small City 73 Willmar Municipal Utils Commission Willmar MN Small City 74 Wyandotte Municipal Service Commission Wyandotte MI Small City242 Exhibit 7M (Continued) List of 74 Coal-Fired Electric Utility Ge neration Plants Which EPA Estimates A re Owned by 60 State/Local Governments Source: Compiled by EPA-OSWER-ORCR based on 2007 data from the US Energy Information Administration*
Footnotes: * NAICS code 22 electric gutilityh generator plants listed in EIA_s 2007 data source at: http://www.eia.doe.gov/cneaf/electricity/page/eia860.html **Type of owner entity assigned by EPA ORCR based on business type disclosed in owner name or plant-by-plant internet research on type of ownership. Size class determined according to the following numerical criteria consistent with EPA_s Nov 2006 guidance for Regulatory Flexibility Act (RFA) Small Business Regulat ory Enforcement Fairness Act (SBREFA) compliance: ~ Small non-government = Based on the US Small Business Administration NAICS code 221112 small business size standard of <4 million megawatt hours per year total annual electricity generation by all plants owned by the entity. ~ Non-small non-government = Entity_s total annual elect ricity generation >4 million megawatt hours per year. ~ Small government = Based on the RFA_s de finition (5 US Code sectio n 601(5)) of gsmall government jurisdictionh as the government of a city, county, town, township, village, school district, or special district with a population less than 50,000. ~ Non-small government = Entity_s jurisdiction population with more than 50,000 people.