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Exhibit 5A-6 Potential Future Human Cancer Cases from the Disposal of CCR Based on Arsenic Cancer-Slope Factor from EPA/IRIS Disposal of CCR Disposal of Conventional 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 arsenic in drinking water would lead to 23 excess male bladder cancers and 14 excess male lung cancers per 10,000 people. Under 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 – 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) cancer slope factor one would expect between approximately 778 and 3,392 cancer cases over 75 years as a result of arsenic consumed through contaminated groundwater. Using the ratios of conventional CCR co-managed with coal refuse produces a best estimate within this range of 2,509 cancers. Exhibit 5A-7 Potential Future Human Cancer Cases from CCR Disposal Based on Arsenic Cancer-Slope Factor from NRC Disposal of CCR Disposal of Conventional 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 Impoundments 82 61 144 305 218 523 Totals 433 345 778 2,003 1,389 3,392 121 EPA is currently in the process of revising the arsenic cancer slope factor in EPA’s Integrated Risk Information System (IRIS). 122 EPA also conducted a sensitivity analysis assuming the female cancer slope factor in Appendix K5 of this RIA. 120
Step 6. Monetize Future Avoided Cancer Risk Benefits Reflecting the best science available, EPA used a point estimate of cancer cases avoided to monetize cancer risks. Appendix K4 provides further explanation as to why the NRC science is considered more appropriate than the older skin cancer research that the current IRIS value was derived from. Because EPA has greater confidence in the NRC estimates, it chose to use the 2,509 cancers calculated above as the best estimate. EPA also used the NRC ratio of 23 male bladder cancers to 14 male lung cancers to estimate how many of each type were 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 cancers. Appendix K7 shows the best estimate number of lung and bladder cancers in each year that was used in the remaining portions of this analysis. Since cancers are not all fatal, the next step was to estimate the number of cancers that are fatal and non-fatal. This was done 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 bladder 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 the 75 years of the analysis. In order to monetize avoided cancer risks, this RIA applied the value of a statistical life (VSL) plus the cost of terminal cancer treatments 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-fatal lymphoma risk reduction was the equivalent of 58.3% of a fatal lymphoma risk reduction. 124 Therefore, this RIA assumed individuals value non-fatal bladder and lung cancer risk reduction in a similar manner. Exhibit 5A-8 Unitized Monetary Values 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 cancer** $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 “Guidelines for Preparing Economic Analyses,” EPA 240- R-00-003, Sept 2000; converted for this RIA to 2008 dollars using the Consumer Price Index. In addition, projections of benefits in future years are subject to income elasticity adjustments. These represent changes in valuation in relation to changes in real income. For example, if, for every 1% increase in real income, a particular consumer’s willingness-to-pay for a particular item increases by 1%, this would be represented by an income elasticity of 1.0. For most items, income elasticity values are actually less than 1, indicating that valuation of most items does not increase as fast as real income levels. To do so, applied the change in Gross Domestic Product 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. “The Value of a Statistical Life: A Critical Review of Market Estimates throughout the World,” Journal of Risk and Uncertainty, Vol.27, 2003, pp. 15–76. ** These costs reflect the inpatient hospital stays, skilled nursing facility stays, home health agency charges, physicians' services, 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 Reference Lottery Metric for Valuing Health," Management Science, Vol.42, Issue 8, 1996, pp.1118 - 1130. 124 EPA acknowledges that alternative approaches to valuing non-fatal cancers are available. One such alternative is presented in Appendix K5 of this RIA. 121
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Regulatory Impact Analysis For EPA
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Table of Contents Executive Summary
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Executive Summary This RIA evaluate
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impoundments, the relative number t
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Summary Exhibit 3 Induced Effect of
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Summary Exhibit 6 Comparison of Reg
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Chapter 1 Problem Statement: The Ne
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Bevill Amendments 10 which exempted
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Just three weeks after the TVA’s
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2. Waste & Environmental Management
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This RIA did not discover similar d
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Exhibit 2A Identity of Other Indust
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Require review of surface impoundme
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Chapter 3 Baseline CCR Management i
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Exhibit 3C below, these 495 coal-fi
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Exhibit 3C State-by-State Electric
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3B. Types of CCR Disposal Units Es
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92 plants Offsite landfill fly ash
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electric utility plants in the data
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Exhibit 3E Annual CCR Disposition f
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3D. Size of CCR Disposal Units The
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costs for each type of disposal (no
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annual sampling for surface impound
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o Of the 25 state regulations revie
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Exhibit 3I Baseline Compliance with
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Baseline CCR Disposal Cost Estimati
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Before-tax costs: 50-year period:
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Baseline “Engineering Control”
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assume that the same water trucks w
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memorandum to George Garland, EPA,
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Exhibit 3K Summary of Industry & St
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($80,000 per year average Subtitle
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Validity Check of Baseline Cost Est
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Chapter 4 Estimated Cost for RCRA R
Page 69 and 70: B. Ancillary costs for CCR disposal
Page 71 and 72: location restriction mitigation inv
Page 73 and 74: o Impoundment berms: The average su
Page 75 and 76: State government average cost per w
Page 77 and 78: corrective action remedies usually
Page 79 and 80: Exhibit 4A Two Case Studies: Possib
Page 81 and 82: Biennial Report”). According to E
Page 83 and 84: 4B.3 Land Disposal Restriction Cost
Page 85 and 86: The TVA cost study did not estimate
Page 87 and 88: Using the EPA ORCR 2009$ updated un
Page 89 and 90: Exhibit 4D Comparison of Annual O&M
Page 91 and 92: Exhibit 4E Summary of Wet Conversio
Page 93 and 94: o Recent Trend in CCR Impoundment P
Page 95 and 96: from coal to other fuels such as na
Page 97 and 98: o Result of Dry Conversion Cost Upd
Page 99 and 100: As summarized below in comparison t
Page 101 and 102: 17% phase-out trend suggest the fut
Page 103 and 104: RIA 50- ye ar period Actual company
Page 105 and 106: 4C. State-by-State Distribution of
Page 107 and 108: 4D. Cost Estimation Uncertainty Thi
Page 109 and 110: Exhibit 4N Cost Estimation Uncertai
Page 111 and 112: In contrast to the Exhibit 5A list
Page 113 and 114: Step 2. Determine Potentially Affec
Page 115 and 116: Step 3. Apply EPA-ORCR 2009 Arsenic
Page 117 and 118: RISKn WELLREACH iRISK EDn N Where
Page 119: The constant slope allowed estimati
Page 123 and 124: controls like surface-impoundment p
Page 125 and 126: Finally, for Subtitle C, there woul
Page 127 and 128: Exhibit 5A-12 Percentile of Cleanup
Page 129 and 130: Exhibit 5A-16 Per-Site Groundwater
Page 131 and 132: Multiple CCR disposal units at a si
Page 133 and 134: 5B. Benefit of Preventing Future CC
Page 135 and 136: As displayed below in Exhibit 5B-2,
Page 137 and 138: Where: = Observed arrival rate (0.
Page 139 and 140: Step 3. Calculate Future Impoundmen
Page 141 and 142: some surface impoundment regulation
Page 143 and 144: Exhibit 5B-8 Poisson Distribution (
Page 145 and 146: With these new distributions, EPA p
Page 147 and 148: Exhibit 5B-12 Scenario #2: Cleanup
Page 149 and 150: 5C. Induced Effect of RCRA Regulati
Page 151 and 152: Exhibit 5C-1 Estimate of Annual Mat
Page 153 and 154: Exhibit 5C-3 below presents a 2004
Page 155 and 156: To avoid double-counting of economi
Page 157 and 158: 5C2. Potential Effect of RCRA Regul
Page 159 and 160: Others take a different view on how
Page 161 and 162: Exhibit 5C-7 EPA Extrapolation of E
Page 163 and 164: Based on the most recent CCR benefi
Page 165 and 166: Beneficial uses of CCR have been co
Page 167 and 168: Exhibit 5C-12 Beneficial Use Trend
Page 169 and 170: Increases due to increased disposal
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“Using [coal] fly ash in building
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Exhibit 5C-14 Historical Annual Per
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Hypothetical expansion of CCR custo
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Step 6: Apply Estimated Induced Eff
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Exhibit 5C-16 Scenario #1: Increase
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Exhibit 5C-17 Scenario #2: Decrease
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Exhibit 5C-18 Beneficial Use Trends
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Exhibit 5C-19 Scenario #1: Benefit
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Exhibit 5C-21 Scenario #2: Cost of
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Step 10: Quantify Potential Capacit
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Chapter 6 Comparison of Regulatory
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Exhibit 6B Comparison of Regulatory
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Exhibit 6D Comparison of Regulatory
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Exhibit 6F Comparison of Regulatory
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Exhibit 6F Scaling Factors (Extrapo
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Exhibit 6G Estimate of Subtitle D (
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detect contamination early and thus
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Step 1: Downloaded the annual milli
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Exhibit 7A State by State Breakout
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Small government: Based on the RFA/
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Step 3 & Step 4: Determine and docu
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Factor #2 of 2: The small business
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how much they use or indeed how muc
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Collection of Minority & Low-Income
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Comparison of Minority & Low-Income
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Exhibit 7G Minority and Low-Income
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Exhibit 7H Comparison of Minority a
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o The state-by-state range of minor
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CCR fraction #3: CCR fraction #4:
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7D. Child Population Statistics (Ex
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Comparison of Child Populations Liv
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Count of plant unique ZCTAds Exhibi
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Exhibit 7K Comparison of Child Popu
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7E. Unfunded Mandates (UMRA) & Fede
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Findings for UMRA Impact and Federa
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Exhibit 7M List of 74 Coal-Fired El
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Analysis - The Institute for Southern Studies

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