United States Office of Water

Environmental Protection Washington, DC 20460 September 2015

Agency

Effluent Limitations Guidelines 

and Standards for the Steam 

Electric Power Generating 

Point Source Category:

EPA’s Response to Public 

Comments

Part 9 of 10
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28.a. Econ – Plants/owners profile 

Commenter Name: Winslow Sargeant

Commenter Affiliation: U.S. Small Business Administration, Office of Advocacy

Document Control Number: EPA-HQ-OW-2009-0819-4477-A1

Comment Excerpt Number: 5

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The agency certifies that this proposal will not have a significant economic impact on a 

substantial number of small entities.8 EPA produced a certification analysis that showed 

surprisingly few plants with costs owned by small entities. The same analysis showed some 

significant costs for a large fraction of plants owned by municipalities and rural electric 

cooperatives of unknown size.9 Given the hundreds of small entity owners that could be 

affected, small entity trade associations also concluded that the number of plants with costs 

owned by small entities was too low.10

8

78 Fed. Reg. 34432, 34530 (June 7, 2013).

9 As discussed below, EPA failed to identify the affected plants, and in turn, which affected 

plants with costs had small entity owners, preventing us from commenting effectively on the 

validity of EPA’s determinations.

10 Personal communication with Dorothy Kellogg, NRECA and Theresa Pugh, APPA, July 19, 

2013.

Comment Response: 

As explained in preamble Section XVII.C, the final rule will not have a significant economic 

impact on a substantial number of small entities. EPA cannot respond to the commenter’s 

statement that the analysis for the proposed rule “showed surprisingly few plants with costs 

owned by small entities” because the statement is too generalized, and the commenter offers no 

explanation of what constitutes “surprisingly few plants.”

In Chapter 8 of the RIA document, EPA described how it identified parent entities, determined 

which entities are small, and estimated impacts to small entities under the final rule, following 

EPA and SBA guidance. EPA’s analysis of the final rule uses the same methodology and data as 

were used in the proposed rulemaking, but with revised SBA size standards effective July 14, 

2014.

EPA cannot publicly provide information for, or identification of, individual steam electric 

power plants and owning entities projected to incur compliance costs under the final rule, as this 

information was obtained directly or derived from the steam electric industry survey and a 
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significant number of respondents identified the data as confidential business information, which 

EPA has a regulatory responsibility to protect (see 40 CFR Part 2, Subpart B). See response to 

DCN EPA-HQ-OW-2009-0819-4477-A1, Excerpt Number 23 (in comment code 28.e) regarding 

disclosure of plant-level data.

EPA did, however, present detailed information in the RIA that makes it possible to review and 

understand EPA’s methodology, as well as aggregated data for the industry by entity type and 

ownership category, to support its finding that the rule will not have a significant economic 

impact on a substantial number of small entities.

As described in Chapter 8 of the RIA, most of the 110 to 191 small entities owning steam 

electric power plants are projected to incur no costs under the final rule. EPA estimated that six 

small entities incur costs at or above the 1 percent cost-to-revenue threshold, and for one of these 

small entities the costs are at or above 3 percent (see Table 8-4 in the RIA).

Commenter Name: Theresa Pugh

Commenter Affiliation: American Public Power Association (APPA)

Document Control Number: EPA-HQ-OW-2009-0819-5140-A2

Comment Excerpt Number: 108

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

APPA notes that EPA also asserts that the rulemaking only affects eight electric utilities that 

generate less than 100 MW. APPA does not know how EPA came to this conclusion

Comment Response: 

EPA disagrees with the commenter that the Agency asserted that the rule “only affects eight 

electric utilities that generate less than 100 MW” because, for either the proposed or final rule, 

EPA did not estimate impacts using a size threshold at a parent level or a plant 

level. Rather, EPA estimated impacts using certain size thresholds at a generating unit level. It 

is not clear what data the commenter is referencing, and thus EPA cannot offer any further 

explanation.
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28.b. Econ – Total costs and economic impact analyses assumptions 

Commenter Name: R. W. Greene

Commenter Affiliation: Mercatus Center at George Mason University

Document Control Number: EPA-HQ-OW-2009-0819-3411-A1

Comment Excerpt Number: 8

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

 By the EPA's own admission in section 4.2.3 of the Regulatory Impact Analysis, the 

analysis of plant-level impacts is subject to uncertainties and limitations, including plantrevenue values differing from those estimated using earlier databases and deviations from 

a zero-cost pass-through assumption. Plant-level impacts could exceed or be less than 

those projected in the analysis; there is no way of telling.

Comment Response: 

EPA acknowledges the commenter’s statements about uncertainties and limitations in the 

analysis of plant-level impacts, but maintains that the analyses EPA conducted are appropriate to 

produce informed regulatory results. While cost and economic impact analyses conducted in 

support of the Steam Electric ELGs embed some uncertainty and limitations (which EPA has 

tried to identify to promote transparency), the Agency used the best information available to 

support the analyses, reduced the uncertainty where possible with additional data collection, and 

where uncertainty remains, provided conservative estimates or ranges of values to inform policy 

decisions. For example, EPA’s assumption of zero-cost pass-through represents a conservative 

estimate of the impact of compliance costs from the perspective of the regulated facilities; when 

looking at the impacts from the perspective of the electricity consumers, EPA reversed the 

assumption to assume, again conservatively, a 100 percent cost pass-through.

Commenter Name: R. W. Greene

Commenter Affiliation: Mercatus Center at George Mason University

Document Control Number: EPA-HQ-OW-2009-0819-3411-A1

Comment Excerpt Number: 10

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

 The EPA claims high benefits and low costs, but it has not carried out a complete benefitcost analysis. Since benefits and costs may easily be higher or lower than the estimates, 

the EPA has not really calculated anything and cannot really claim anything other than an 

unquantified statement that the proposals are a good thing.
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Comment Response: 

Pursuant to Executive Order, EPA conducted a benefit-cost analysis, in which EPA compared 

total and incremental costs to total and incremental benefits; the results of this analysis are 

presented in Chapter 13 of the BCA. While both benefits and costs values are subject to 

uncertainties (as EPA has tried to be transparent about by providing information on uncertainties 

and limitations where possible), they are based on the best information available to EPA, and 

EPA considered any specific suggestions for reducing uncertainty provided by commenters. As 

such, EPA’s analysis is appropriate to produce an informed regulatory result.

Commenter Name: R. W. Greene

Commenter Affiliation: Mercatus Center at George Mason University

Document Control Number: EPA-HQ-OW-2009-0819-3411-A1

Comment Excerpt Number: 11

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

This is an important area of environmental concern. The regulations were last updated in 1982 

and the EPA claims that they no longer provide adequate control of wastewater discharges, 

although it does not really support that claim beyond general references to health concerns and 

observations of water deterioration in bodies, such as the Chesapeake Bay. The rulemaking 

needs to have a firmer basis in economic analysis and be less reliant on a whole series of 

assumptions that are built one upon another. Better analysis is needed to show whether there is a 

systemic problem to be addressed in the first place. This rulemaking is at a proposal stage, and 

we can only hope that public discussion between now and 2014 will encourage the EPA to under

take a more detailed analysis of the benefits of its proposals and consider a wider variety of 

alternatives.

Comment Response: 

The commenter states that the steam electric ELGs need to have a “firmer basis in economic 

analysis” and “better analysis,” but the commenter does not offer any specific comments with 

respect to how EPA’s analyses for the rule could be improved.

With respect to the commenter’s statements that the rule is based on “a whole series of 

assumptions,” see the response to DCN EPA-HQ-OW-2009-0819-3411-A1, Excerpt Number 8.

EPA’s disagrees with the commenter’s statement that EPA has not demonstrated the

environmental need for the rule. The Agency described in the preamble and further detailed in 

supporting documents (e.g., TDD and EA Report), the rationale for the regulation, changes in the 

characteristics of discharges from the steam electric industry, and demonstrated environmental 

impacts of these discharges. The Environmental Assessment describes the impacts associated 
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with pollutant loadings reductions under the final rule, and the benefits analysis (contained in the 

Benefit-Cost Analysis (BCA) document) further describes, in quantified and monetized terms 

where possible, the benefits associated with the final rule.

Regarding the commenter’s statement that EPA should “undertake a more detailed analysis of 

benefits,” the commenter offers no specific suggestions of how EPA’s benefits analysis could be 

improved. EPA disagrees that the benefits analysis is not detailed enough. EPA conducted a 

benefits analysis of the proposed rule pursuant to Executive Order. Chapter 2 of the BCA 

provides an overview of the benefits of the final rule, and each benefits category is described in 

more detail in subsequent chapters of the BCA. Moreover, EPA considered public comments it 

received on the benefits analysis for proposed rule, and subsequently made several 

improvements in its benefits analysis for the final rule. For more details on updates to the 

benefits analyses, see Appendix A of the BCA for the final rule. As a result, the final rule does 

contain a more detailed analysis of the benefits of the ELGs, consistent with the commenter’s 

request. EPA also notes that, as required by the Clean Water At, the final rule reflects 

technologies that are available, economically achievable and have acceptable non-water quality 

impacts. See Section VIII of the preamble to the final rule for the rationale underlying EPA’s 

decisions on the final rule.

Regarding the commenter’s statement that EPA should “consider a wider variety of alternatives,” 

EPA notes that its proposal for the final rule described at least eight different regulatory options 

under consideration, providing extensive details on each of the wastestreams to be addressed 

under the options, as well as the treatment technologies for controlling the discharge of 

pollutants under the options.

Commenter Name: R. W. Greene

Commenter Affiliation: Mercatus Center at George Mason University

Document Control Number: EPA-HQ-OW-2009-0819-3411-A1

Comment Excerpt Number: 14

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

 More generally, costs are estimated by extrapolation from known data, which is 

questionable because it implies linear relationships when these may not be appropriate,

Comment Response: 

It is not clear what specific cost data the commenter is referring to in their statement. EPA uses 

several different analyses to inform the regulatory development process, relying on available 

information as the basis for key values. EPA determined compliance costs based on facilityspecific information. See the TDD for details. The commenter is correct that some of the 

economic analyses rely on known data (such as data about electricity sales) to infer future values 
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based on historical trends, but EPA disagrees that using extrapolation from known data means 

that the analysis is not appropriate. In the absence of evidence suggesting otherwise, known data 

is the most appropriate and least speculative basis for decisions.

Commenter Name: R. W. Greene

Commenter Affiliation: Mercatus Center at George Mason University

Document Control Number: EPA-HQ-OW-2009-0819-3411-A1

Comment Excerpt Number: 17

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

 The EPA has made many spurious, rule-of-thumb type assumptions in analyzing this 

proposal and gives the impression that it would have found a basis for proceeding with 

tighter regulation regardless of the underlying economics. The approach seems to reflect 

a common administra tive view that quantification, however spurious, is a valuable 

exercise.

Comment Response: 

EPA disagrees that the Agency “made many spurious, rule-of-thumb type assumptions” in its 

analyses of the steam electric ELGs and that EPA’s “quantification” was also “spurious.” The 

commenter offer no specific examples here of an assumption or quantification that it views as 

“spurious.” Nonetheless, EPA notes that, while cost and economic impact analyses conducted in 

support of the ELGs embed some uncertainty, in EPA’s view, the undertaken analyses are 

appropriate to produce informed regulatory results. The Agency necessarily made assumptions to 

conduct the analyses when data were not available or for projecting future conditions (e.g., future 

electricity market). EPA detailed these assumptions and discussed their implications on the 

insight drawn from the results in the RIA and BCA. The Agency used the best information 

available to support the analyses, including data provided by steam electric power plants in 

response to the industry survey. Where uncertainty remained, EPA used conservative estimates 

or ranges of values that provide insight on the magnitude or direction of the effects of the 

regulation. For example, EPA’s assumption of zero-cost pass-through represents a conservative, 

worst-case estimate of the impact of compliance costs from the perspective of the regulated 

facilities; whereas when looking at the impacts from the perspective of the electricity consumers, 

EPA reversed the assumption to assume, again conservatively, a worst-case scenario of 100 

percent cost pass-through. Results of these analyses, which represent worst-case conditions from 

either perspective, provide bounding cases to understand the impacts of the ELGs and inform 

decisions.
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Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 7

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

By contrast, EPA found that the vast majority of power plants will be able to meet even the 

strongest of the rule's requirements by spending less than 1 percent of their annual revenue and 

with minimal impact on electricity rates or grid reliability. No matter how you slice the 

numbers, there is no doubt that the rule will greatly benefit the country with costs that can be 

reasonably born by the industry.

Comment Response: 

The preamble describes in detail the requirements of the final rule and EPA’s rationale for 

selecting the options that it did for the final rule. As discussed in the RIA and BCA, EPA agrees 

with the commenter that the final rule will have a minimal impact on electricity rates or grid 

reliability, and that the final rule is affordable for the industry as a whole.

Commenter Name: John McManus

Commenter Affiliation: American Electric Power System (AEP)

Document Control Number: EPA-HQ-OW-2009-0819-4448-A1

Comment Excerpt Number: 67

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

1. In some cases, annualization and cost recovery periods shorter than 15 years need to be 

accounted for in the proposed rule.

As has been mentioned earlier, the time period assumed for cost recovery is a primary 

consideration when the cost effectiveness of any new technology installation is evaluated. EPA 

assumes that costs are annualized over a 20-year period, but has previously used a 15-year period 

to develop ELGs for other industry categories. But in some cases, even a 15-year service life 

assumption is not appropriate. This is the case with Public Service Company of Oklahoma’s 

(PSO’s) Northeastern Plant where a coal-fired unit is planned to be retired by 2026, providing a 

significantly shorter time period for cost annualization. Based on EPA’s preferred option and an 

expected ELG compliance date of 12/12/2021 for this unit (first permit renewal after July 1, 

2017), the bottom ash transport system would need to be converted to a “dry” system and be 

operational by the compliance date. After the completion of the retrofit, the plant will only 
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operate for an additional 5 years before being retired. Using the cost effectiveness information 

estimated for two AEP dry bottom ash conversions as examples (Table 10), the effects of the

shortened cost recovery period can be illustrated.

The direct costs in 2010 dollars to retrofit dry bottom ash systems at these two facilities were 

provided earlier (Table 5). These costs were converted to 1981 dollars and annualized over a 20-

year period at 7% in order to calculate $/TWPE values for both plants (Table 6). Use of a shorter 

cost recovery period has a significant effect on the cost effectiveness of dry bottom 

ash conversions. Using a 15-year annualization period for Plant 1 increases the $/TWPE by over 

16%, from $16,007 to $18,639 per TWPE removed (Table 10). Using a 5-year cost recovery 

period, the $/TWPE values increases by almost 160%, further devaluing an already not-costeffective technology retrofit (Table 10).

This analysis illustrates that not only is the dry bottom ash conversion not cost effective for any 

plant at any cost recovery period, but that some provision needs to be included in the proposed 

ELG rule that accounts for plants that will be retired prior to a 20-year cost annualization 

period.] If the new ELGs are adopted as proposed, the PSO Northeastern Plant must install a dry 

bottom ash conversion by December 12, 2021, but due to an agreement among

stakeholders regarding its air pollution control requirements, the plant must be retired by 2026, 

providing only five years to recover the cost of the dry bottom ash conversion from the 

customers that receive service during the period of ELG compliance.

Some minimal cost-recovery period must be used to estimate the cost effectiveness of the 

proposed technology revisions and in cases where that cost annualization period is not available, 

the cost effectiveness needs to be reassessed.

Comment Response: 

The commenter states that “EPA assumes that costs are annualized over a 20-year period, but has 

previously used a 15-year period to develop ELGs for other industry categories” and that EPA’s 

choice of annualization period is “inappropriate.” EPA disagrees with these comments. For 

analysis of technology capital costs on an annualized basis, or when performing other cost and 

impact analyses that account for the service life of the installed equipment (e.g., electricity rate 

impact analysis), the number of years reflect the reasonably expected service life of the 

equipment. Using a number of years that is longer than the service life would understate costs on 
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an annual equivalent basis, while using a number of years that is less than the service life would 

overstate costs on annual equivalent basis. As described in the RIA and TDD, EPA based its 

estimate of service life of equipment that may be installed to meet the ELGs on a review of 

reported performance characteristics of compliance technology components. From this review, 

EPA concluded that the equipment could reasonably be expected to operate for 20 years or more, 

and thus further concluded that 20 years is an appropriate basis for cost and economic impact 

analyses that account for the estimated operating life of compliance technology. EPA notes that 

the 20-year service life is longer than the service life used in some CWA regulatory analyses, 

while shorter than the life used in other analyses (for example, the service life was 10 years for 

compliance equipment analyzed for the Concentrated Animal Feeding Operations ELGs, 15 

years for analyses of the Metal Products and Machinery and Pharmaceutical Manufacturing 

ELGs, and 30 years for certain compliance equipment for the CWIS final rule). The differences 

are based on the type of equipment and expected service lives. Note that for each system for 

which the Agency estimated costs, EPA evaluated whether equipment would have a shorter life 

than 20 years and would need to be purchased more frequently; the Agency accounted for this 

shorter life by including recurring costs for equipment replaced within the 20-year period. In 

summary, in its CWA regulatory analyses, EPA used realistic estimates of service life for the 

equipment expected to be used in complying with regulatory requirements.

The commenter further states that, based on its calculations for a particular plant whose planned 

retirement is 2026, “use of a shorter cost recovery period has a significant effect on the cost 

effectiveness of dry bottom ash conversions.” EPA understands that some plants may retire 

earlier than 20 years after the limitations are incorporated into their permits, and that if EPA 

calculated cost-effectiveness using a shorter technology service life, the cost-effectiveness values 

would be higher ($/TWPE) than using a uniform 20-year period. However, EPA’s decisions on 

the final rule are based on the factors discussed in Section VIII of the preamble. The Agency did 

not base its decisions on the final rule on its cost-effectiveness findings. Thus, even if EPA 

recalculated cost-effectiveness with shorter technology-use periods and found higher (i.e., less 

favorable) cost-effectiveness values, these different results would not affect EPA’s decisions for 

the final rule since, as mentioned above, cost-effectiveness is not a determining factor in EPA’s 

ELG decision making. For the role of cost-effectiveness in EPA’s decisions for the final rule, see 

response to DCN EPA-HQ-OW-2009-0819-4655, Excerpt Number 27 in Comment Code 6.h. 

For the same reason, EPA disagrees with the commenter that the final rule should contain “some 

provision ... that accounts for plants that will be retired prior to a 20-year cost annualization 

period.” For the reasons explained in the preamble, EPA determined that the final rule is 

economically achievable for the industry as a whole. Nonetheless, EPA notes that the analyses 

for the final rule take into account generating units and plants that are expected to retire prior to 

the implementation dates in the final rule (which extend to December 31, 2023), and that the 

final rule provides some flexibility to permitting authorities in determining when plants must 

meet the final limitations (see preamble Sections VIII.C.7 and XVI.A.1).

Finally, the commenter states that its analysis “illustrates that ... dry bottom ash conversion [is] 

not cost effective for any plant at any cost recovery period.” EPA disagrees that the technology 

basis for the control of pollutants in discharges of bottom ash transport water in the final rule is 

not cost-effective. The commenter presents no substantive basis for this sweeping conclusion. As 

discussed in Section XV of the preamble and in Appendix F of the RIA document, EPA 
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calculated the cost effectiveness for the final ELGs and found the cost-effectiveness ratio of the 

BAT requirements ($134/lb-eq (in 1981 dollars)) to be within the range of cost-effectiveness 

ratios for BAT requirements in other industries.

Commenter Name: John McManus

Commenter Affiliation: American Electric Power System (AEP)

Document Control Number: EPA-HQ-OW-2009-0819-4448-A1

Comment Excerpt Number: 70

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

3. Economic Impact and Social Cost Analysis

EPA’s annualization of the compliance costs is misleading in that: 1) it characterizes costs as 

affordable; and 2) neglects to consider the impacts to companies for financing in a capital 

intensive industry. EPA assumes that the cost of these retrofits will be annualized over a 20-year 

period, but this position inherently assumes that all of the affected facilities from this rule will 

operate over that entire timeframe. Given the current environmental regulatory climate, older 

and less efficient facilities that dispatch less frequently, but provide some economic benefit, will 

be adversely affected through these guidelines and future rule promulgations, such as with 

proposed CCR and 316(b) rules, as well as the anticipated Greenhouse Gas Standards for 

existing sources. Though the proposed ELG rule may not make these units uneconomic to 

generate electricity over a short term by itself, the cumulative effect of the ELG in combination 

of other regulations may push these units into an accelerated retirement. Many of the affected 

facilities will not have 20-year lifespans or service lives, but will still have to shoulder the 

financial burden to comply with these rules in the short term. The EPA’s analysis is not 

sufficiently refined to properly account for these shortened facility service life periods.

For example, such a scenario where a shortened service life is evident when considering the EPA 

Settlement Agreement that remedies the dispute with the Regional Haze Rule state 

implementation plan entered in Oklahoma. In the Settlement Agreement AEP and EPA agreed

that one of the coal-fired units of the Northeastern Station will retire in 2016, while the other 

unit will operate through 2026. The remaining operating unit will have to meet compliance with 

the ELG, as well as CCR, and these costs cannot be annualized over twenty years because the 

remaining plant life ends in 2026. Any costs that aren’t fully amortized will need depreciation 

adjustment to align with plant retirement dates, elevating the annualized cost impact of the rule. 

Aligning cost recovery with customers who receive the benefits of service is vitally important for 

regulatory commissions in order to not unfairly burden future customers with costs for which 

they do not receive any service benefit.

Further, the EPA assessment of estimated costs for compliance neglects to consider the capital 

requirements of utility’s to install control technologies over a short compliance period of a few 
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years. As stated above, the AEP estimated costs could potentially approach $4 billion. To 

contrast, AEP’s near-term capital forecast is $3+ billion per year, but these expenditures 

encompass all business segments including transmission and distribution, in addition to 

generation. Expenditures to comply with the ELG will directly follow the current large 

expenditures within AEP’s capital budget to comply with the Mercury and Air Toxics Standard 

by the 2015-2016 timeframe.

[...]

4. Cost-to-Revenue Screening Analysis

The assessment of the economic impacts of the rule per EPA methodology does not provide a 

reasonable presentation of the full impact on existing individual facilities and their parent entities 

incurring compliance costs in the cost-to-revenue basis screening-level economic 

assessment. Given AEP’s estimated capital compliance cost for its facilities are roughly 40% of 

EPA’s estimated capital compliance costs for the entire industry, it can be reasonably ascertained 

that there would be a significant increase in the number of individual steam electric plants 

flagged by the cost-to-revenue screening analysis and parent entities that would incur costs of 

greater than 3% of revenues. According to EPA, exceeding this threshold is an indicator of 

potential financial distress to the facilities and entities; therefore, EPA’s analysis paints a rosy 

picture of little financial impact to utilities when the costs of this rule could cause financial 

distress and burden utility customers for the foreseeable future.

Further, a substantial number of public utilities and parent entities are vertically integrated 

businesses, comprised of various business segments including transmission, distribution, and 

retail services in addition to generation services and electric generating facilities to which this 

rule targets. Other parent entities operate in other industries where electric generation may or 

may not be their business focus. Neglecting to consider the vertically integrated construct 

artificially minimizes the impact of the ELG compliance costs to the specific business segments 

of parent entities, and unduly penalizes other facets of the business. It also artificially minimizes 

the impact of this rule on a specific business segment, when the generation portion could be a 

small, but vital piece of the overall business construct.

Additionally, EPA wrongly claims that the screening analysis makes a “counterfactual, 

conservative assumption of zero cost pass-through to customers.”48 While this position is less 

than conservative considering that recovery for environmental investment for utilities in 

regulatory proceedings is highly probable, it fundamentally neglects the consideration 

of downstream effects to customers that will inevitably result in higher electricity prices in a 

downtrodden economy and demonstrates that EPA further underestimates the real societal 

impact associated with this rule. Regulated entities are entitled to a fair return on their 

investment, and such a return will be borne by, and burden, customers in a much higher degree 

than EPA’s analysis describes. Such costs that are not considered in EPA’s cost-effective 

analysis underestimate the expected actual mitigation cost that will be charged to utility 

customers in any modeling considerations. Absent regulatory treatment, merchant customers will 

still bear the burden of this rule manifesting in higher electricity prices to cover the exorbitant 

costs associated with implementing these proposed guidelines.
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[...]

6. Summary of Economic Impacts for Existing Sources

The economic impact of the ELG rulemaking should not be compared on a cost-to- revenue basis 

as this metric is meaningless and misleading in that it compares the cost for compliance for a 

single business unit to the total revenue for the entire company. Thus it is not surprising that the 

results of EPA’s economic impacts are negligible versus comparing the cost of compliance to the 

revenue of the generation business unit of a utility. While more appropriate than EPA’s 

approach, even this comparison could be improved as it does not reflect the true impact on a 

company’s owners – i.e. its shareholders. To do so requires calculating the impact on a 

company’s earnings on a $/share basis.

48 Table XI-3, 78 Fed. Reg. at 34494.

Comment Response: 

Response to comments regarding "Economic Impact and Social Cost Analysis"

The commenter makes several arguments: (1) EPA’s annualization assumptions understate the 

annual equivalent cost burden of capital and other one-time outlays for some facilities, and thus 

may lead to an incorrect assessment of the affordability of compliance costs for those facilities; 

(2) EPA has not considered the financing burden of compliance capital outlays, particularly in 

the context of the electric power industry’s broader set of near-term capital requirements; (3) 

EPA has not properly accounted for the impact of several environmental regulations imposing 

costs in a short period on the economic/financial viability of generating units; impacts may be 

consequential when viewed in this context. EPA addresses each argument below.

EPA’s annualization assumptions understate the annual equivalent cost burden of capital and 

other one-time outlays for some facilities, and may lead to an incorrect assessment of the 

affordability of compliance costs for those facilities

EPA understands the commenter’s statement that using a longer annualization period than the 

expected remaining useful life of the generating unit will understate the annual equivalent cost 

burden of capital and other one-time outlays for the compliance technology. The commenter is 

specifically concerned about instances in which the remaining operating life of a plant or specific 

generating units is less than the estimated service life of the compliance technology. In such 

instances, the calculated annual equivalent cost will be lower when using the estimated 20-year 

service life than would be estimated if a shorter remaining operating life were used as the basis 

for annualization. However, this effect, which is a simple artifact of annualization math, does not 

mean that a given technology is not generally economically achievable or affordable within the 

CWA’s economic achievability criteria for effluent guidelines regulations. EPA based its 

determination of best available technology economically achievable on broader criteria than the 

impact of technology installation at individual selected facilities. Overall, EPA concludes that the 
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technology basis for the final rule constitutes best available technology economically achievable

for the industry as a whole. As described in the preamble to the final rule, EPA reached this 

determination in part based on an analysis of the impacts of the final rule using the Integrated 

Planning Model (IPM), a comprehensive electricity market optimization model that assesses 

economic/financial impacts within the context of regional and national electricity markets. This 

analysis, which is documented in the RIA report, found minimal impact on the steam electric 

power industry from the final rule, both nationally and regionally, in terms of accelerated 

retirement of electric generating capacity. The analysis also shows minimal impact on electricity 

production costs and prices, and other measures of economic impact (see Chapter 5 in RIA for 

details).

EPA further understands that some generating facilities operating under rate regulation may need 

to recover capital outlays in fewer years than the estimated technology service life, which would 

lead to higher electricity rate increases than calculated using the 20-year technology life. This 

impact, if it occurs, would unfold in the broader electricity generation market, with many 

generating units incurring little or no cost as a result of the final rule, and for those generating 

units more affected by the rule, most are expected to be able to operate the compliance 

technology for the full estimated service life (very few retirements expected as a direct result of 

the final rule). Again, a key overall finding from the IPM analysis, which bears specifically on 

this point, is that electricity production costs and prices are expected to increase by no more than 

0.8 percent in any electricity market region as a result of the final rule (see Table 5-1 in RIA 

document). EPA finds this extent of production cost and price increase minimal within the 

electricity customer community.

EPA has not considered the financing burden of compliance capital outlays, particularly in 

the context of the electric power industry’s broader set of near-term capital requirements

EPA understands the commenter’s arguments concerning the near-term financing burden for 

installing technology to comply with the Steam Electric ELGs. However, EPA’s analysis, as 

documented in the RIA for the final rule, indicates the financing burden associated with the final 

rule’s requirements to be comparatively modest for virtually all organizations – both private 

companies and other entities – expected to incur costs under the final rule (See Chapter 4 in RIA 

document).

In terms of considering the impact of the final rule on capital requirements in the context of the 

electric power industry’s broader near-term capital needs, EPA first notes that this consideration 

is not necessary for a finding of economic achievability under the CWA. Under the CWA, ELGs 

based on BAT must be economic achievability for the industry as a whole, which EPA has 

demonstrated as described in the preamble and RIA. Nevertheless, given the overall small 

financing burden from the Steam Electric rule’s compliance outlays, EPA does not view the 

Steam Electric ELGs as imposing an undue burden on the overall electric power industry even in 

the context of the industry’s near-term capital needs.

EPA has not properly accounted for the impact of the Steam Electric and other environmental 

regulations imposing costs in a short period, on the economic/financial viability of generating 

units. Impacts may be consequential when viewed in this context.
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The commenter expresses concern that “older and less efficient facilities that dispatch less 

frequently, but provide some economic benefit” will be adversely affected by the final rule and 

other environmental regulations requiring compliance expenditures at approximately the same 

time as the Steam Electric ELGs. The commenter acknowledges that the ELGs, themselves, are 

not likely to render these generating units unviable, but goes on to argue that the “the cumulative 

effect of the ELG in combination of other regulations may push these units into an accelerated 

retirement.”

EPA agrees that the Steam Electric regulation, by itself, is unlikely to make electricity generation 

from steam electric generating units uneconomical, but recognizes that other regulations or a 

combination of factors may affect a plant owner’s decision of whether to continue operating a 

given generating unit.

The commenter noted the importance of evaluating the impact of the final Steam Electric ELGs 

in the context of multiple environmental regulations affecting the electric power industry, and of 

recognizing the potential for adverse impact due to compressed and overlapping compliance 

periods from multiple regulations. EPA generally agrees, and it did account for the potential 

cumulative impact that multiple environmental regulations may have on the electric power 

industry in analyzing the impacts of the ELGs. As described above and as documented in 

Chapter 5 of the RIA report, EPA used IPM to assess the effect of the final rule in the context of 

regional and national electricity markets, accounting for the costs and market-level effects of 

additional environmental regulations (e.g., MATS, CWIS, CCR) requiring compliance outlays at 

about the same time as the Steam Electric rule. EPA also included the impacts of the Clean 

Power Plan regulation, which limits GHG emissions from existing electric generating units.

As described in Chapter 5 of the final Environmental Assessment for the Effluent Limitations 

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

Report) (DCN SE04527), EPA found that the ELGs are expected to have a minimal impact on 

steam electric generating unit capacity retirements, in the order of 0.1 percent of national electric 

generating capacity and no more than 0.3 percent of generating capacity in any electricity market 

region. Specifically, the final rule will lead to incremental capacity retirement of 8 electricity 

generating units representing for 1,416 MW of capacity. These retirements are offset by 574 MW 

of avoided retirement of capacity otherwise projected to retire by 2030, for a net change in 2 

generating units and 843 MW (see Table 5-3 in RIA document). The retirements involve older, 

less efficient generating units with very low capacity utilization rates. EPA assesses that these 

very small accelerated retirements are not consequential relative to total national and regional 

generating capacity.

Response to comments regarding "Cost-to-Revenue Screening Analysis"

The commenter raises three main concerns, addressed in turn below.

First, regarding the commenter’s assertion that EPA does not provide a reasonable presentation 

of the full impact on existing individual facilities and their parent entities in the cost-to-revenue 

basis screening-level economic assessment, EPA used data available about each plant (including 

detailed responses by plant operators to the industry survey) to determine the technology changes 
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that are expected to meet the ELGs and to estimate the costs of those changes. EPA made several 

changes to the analysis in response to comments regarding individual plants or technologies and 

has updated the technology costs accordingly (see the TDD). The commenter does not raise 

specific concerns about the methodology used to aggregate these costs to the level of the plants 

and their owners, and EPA used the same methodology to estimate cost-to-revenue ratios for the 

final rule.

Second, regarding the concern that EPA neglected to consider the vertically integrated structure 

of affected businesses, for parent-entity cost-to-revenue and Regulatory Flexibility Act (RFA) 

analyses, EPA determined the highest level domestic parent entity for each surveyed steam 

electric power plant and conducted these analyses at the level of that entity. This approach is 

consistent with EPA economic analysis guidance. As discussed in Chapter 4 of the RIA report, 

the primary focus of operations of some of these entities is not electric power generation. EPA 

conducted the same cost-to-revenue and RFA analyses for each identified parent entity 

regardless of primary focus of its operations. To the extent that this entity is at the top of 

domestic-ownership pyramid, its revenue includes revenue from all operations it owns. EPA 

does not have enough information to assess how these regulatory effects are passed through the 

ownership pyramid and to what extent each business segment is affected. The cost-to-revenue 

and RFA analyses both assume that the entities do not pass through the compliance costs to 

customers and therefore the analyses represent a worst case from the perspective of the entities 

that own the plants.

Third, regarding the commenter’s assertion that the Agency understated impacts to electricity 

consumers, EPA disagrees. The assertion seems to reflect a misunderstanding of EPA’s 

assumptions regarding cost pass-through in different analyses. As mentioned above, and 

discussed in Chapters 4 and 8 of the RIA report, for these analyses, EPA assumed that steam 

electric generating units owned by these entities will not be able to pass any of their compliance 

costs to their electricity consumers (zero cost-pass-through). This assumption is used for analytic 

convenience and provides a worst-case scenario of regulatory impacts to steam electric power 

plants, from the perspective of the plants. Even though the majority of steam electric power 

plants may be able to pass increases in production costs to consumers through increased 

electricity prices, it is difficult to determine exactly which plants would be able to do so. 

Consequently, EPA judges that assuming zero cost pass-through is appropriate as a screeninglevel, upper bound estimate of the potential cost impact of the ELGs to steam electric power 

plants and their parent entities. To the extent that some steam electric power plants are able to 

recover some of the increased production costs in increased prices, this analysis overstates plantlevel impacts.

As discussed in Chapter 7 of the RIA report, to assess the impact of the ELGs on electricity 

consumers, EPA reversed the assumption used in estimating impacts on entities that own steam 

electric power plants and instead assumed that steam electric power plants will be able to pass 

100 percent of compliance costs onto their consumers. The 100-percent cost-pass-through 

assumption is a conservative assumption from the perspective of electricity consumers because 

some electric power plants may not be able to pass all of their compliance costs onto consumers 

in the form of price increases. As discussed in Chapter 7, plants located in states where 

electricity prices remain regulated under the traditional cost-of-service rate regulation framework 
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may be able to recover compliance cost-based increases in their production costs through 

increased electricity rates, depending on the business operation model of the plant owner(s), the 

ownership and operating structure of the plant itself, and the role of market mechanisms used to 

sell electricity. In contrast, in states in which electric power generation has been deregulated, 

cost recovery is not guaranteed. While plants operating within deregulated electricity markets 

may be able to recover some of their additional production costs in increased revenue, it is not 

possible to determine the extent of cost recovery ability for each plant. Moreover, even though 

individual complying plants may not be able to recover all of their compliance costs through 

increased revenues, the market-level effect may still be that consumers would see higher overall 

electricity prices because of changes in the cost structure of electricity supply and resulting 

changes in market-clearing prices in deregulated generation markets. Although the convenient 

analytical simplification of the 100-percent cost-pass-through assumption does not reflect actual 

market conditions, EPA judges that this assumption is appropriate for two reasons: (1) the 

majority of steam electric power plants operate in the cost-of-service framework (see Chapter 2 

of the RIA report) and may be able to recover increases in their production costs through 

increased electricity prices and (2) for plants operating in states where electric power generation 

has been deregulated, it would not be possible to estimate this consumer price effect at the state 

level. Thus, this 100 percent cost pass-through assumption represents a “worst-case” impact 

scenario from the perspective of the electricity consumers. To the extent that all compliancerelated costs are not passed forward to consumers but are absorbed, at least in part, by electric 

power generators, this analysis overstates consumer impacts.

Response to comments regarding "Summary of Economic Impacts for Existing Sources"

The commenter makes three arguments, each addressed below.

First, the commenter states that cost-to-revenue analysis, as presented for the proposed rule (and 

also presented for the final rule), should not be used in evaluating the rule because it is 

“meaningless and misleading” in comparing compliance cost for a single business unit to total 

company revenue. EPA disagrees that the cost-to-revenue analysis is meaningless and 

misleading. This analysis provides screening-level insight into the significance of impact of 

compliance requirements on the overall business. The cost-to-revenue analysis is not meant to be 

a precise indicator of economic impact, but nonetheless provides useful insight. For example, if 

this analysis found, for a particular regulatory option, that a substantial number of businesses 

could incur costs exceeding levels of concern, as described in the RIA, this would signal that the 

regulatory option should be more closely scrutinized to confirm that the option is affordable for 

the industry as a whole. EPA further notes that the IPM analysis, which was also conducted for 

both the proposed and final rule, provides a considerably more detailed assessment of impact at 

the level of the plant and generating unit.

Second, the commenter argues that compliance cost should be compared to revenue from the 

generating business unit instead of total company revenue. Recognizing the limited objective of 

the cost-to-revenue analysis, as described above, EPA concludes that performing this analysis at 

the level of the total company is appropriate and reasonable for a screening-level assessment. 

EPA also notes that performing the cost-to-revenue analysis at the level of the generation 

business unit, when the overall business is vertically integrated, including transmission and 
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9-17

distribution services, would provide an artificially constrained assessment of impact. In a 

vertically integrated electric power company, generation is the primary business driver, 

providing the basis for revenue in the transmission and distribution segments. As a result, EPA 

again concludes it is appropriate and reasonable to use total revenue in the cost-to-revenue 

analysis. Further, EPA also conducted a complementary analysis where it compared compliance 

costs to revenue from electricity generated at the level of the individual generating plant (see 

Chapter 4 in RIA report). This level of analysis is, in most instances, lower organizationally than 

the level of the generating business unit suggested by the commenter and offers additional 

insight on potential impact of compliance requirements on the generation business. The plantlevel screening analysis for the final rule shows only 17 plants with cost-to-revenue ratios 

exceeding 3 percent under the final rule (Option D, for scenario without CPP), out of a total of 

1,080 plants in the universe (see Appendix B, Table B.2.1 of RIA).

Third, the commenter argues that impact should be assessed in terms of the firm’s owners – i.e., 

shareholders – by assessing impact on earnings per share. EPA understands that looking at 

potential impact on business value and, hence, the firm’s owners provides meaningful insight 

into the impact of a regulation on the business. In its regulatory analyses for effluent guidelines 

and other Clean Water Act regulations, EPA regularly looks at the potential impact of 

compliance costs and market-level impacts on business value, and accounts for this analysis in 

assessing the ‘economic achievability’ of regulations. From a financial analysis standpoint, EPA 

does not agree that earnings per share would be the best metric of impact. This measure does not 

account directly for impact on business value and financial viability, and is actually inconsistent 

with the commenter’s preceding arguments about needing to look below the level of the total 

firm in assessing impact: earnings per share is necessarily a total firm concept since earnings per 

share is customarily reported at the level of the total firm and the impact would therefore also be 

assessed at the level of the total firm. Instead, in its analyses of cost and economic impact for 

effluent guidelines, EPA estimates change in business value, frequently at the level of the 

regulated facility, and looks, in particular, for instances in which business value would become 

negative as a result of compliance requirements, thus signaling the possibility of a facility 

closure. EPA regards such analysis as very important in establishing the economic achievability 

of a regulation. In the context of the Steam Electric ELGs regulatory analysis, this level of 

analysis is performed via the IPM market model analysis (presented in Chapter 5 of the RIA 

report), which assesses impact at the level of the individual steam electric generating unit and 

plant in the context of electricity markets. EPA views this analysis as more insightful in its 

regulatory decisions than the commenter’s proposal to use change in earnings per share as impact 

metric.

Commenter Name: Tom DeLawrence

Commenter Affiliation: PowerSouth Energy Cooperative

Document Control Number: EPA-HQ-OW-2009-0819-4460-A1

Comment Excerpt Number: 88

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

Unfortunately, as detailed in our comments below, EPA’s callous approach to determining costeffectiveness and ignorance of technological shortcomings with the proposed technology-based 

limits, will have an extraordinary impact on an already economically disadvantaged population. 

As compared to EPA’s unreasonably low cost estimates, PowerSouth’s engineering estimates of 

the capital costs required to comply with EPA’s preferred options at the Lowman Plant are in 

excess of $140 million. EPA should reassess their cost estimates and reconsider their preferred 

options as selected in the Draft Rule.

Comment Response: 

EPA disagrees with the commenter that there are “technological shortcomings” with the final 

rule. The commenter offers no basis for this general claim. EPA addressed specific comments on 

the demonstration and performance of each technology evaluated (by wastestream). These 

responses can be found in the comment codes 9.a (FGD Chemical Precipitation), 10.a (FGD 

Bio), 11.a (FGD VCE), 14.a (Dry Fly Ash Handling), 16.a (Zero Discharge Bottom Ash).

EPA also disagrees with the commenter that EPA’s compliance cost estimates for the Lowman 

Plant are “unreasonably low,” as well as the claim that compliance costs for the Lowman Plant 

“are in excess of $140 million.” The commenter offers no specific basis for these claims. 

However, EPA evaluated any specific cost estimates provided by the PowerSouth for the 

Lowman Plant. See the responses to the following excerpts for EPA’s response to the estimates 

provided:

 DCN EPA-HQ-OW-2009-0819-4460-A1, Excerpt Number 34 (in comment code 9.b) 

(EPA’s response to FGD chemical precipitation cost estimates);

 DCN EPA-HQ-OW-2009-0819-4460-A1, Excerpt Number 40 (in comment code 10.b) 

(EPA’s response to FGD biological treatment cost estimates);

 DCN EPA-HQ-OW-2009-0819-4460-A1, Excerpt Number 44 (EPA’s response to FGD 

evaporation cost estimates) (in comment code 11.b);

 DCN EPA-HQ-OW-2009-0819-4460-A1, Excerpt Number 56 (EPA’s response to 

bottom ash cost estimates and space constraints) (in comment code 7); and

 DCN EPA-HQ-OW-2009-0819-4460-A1, Excerpt Number 63 (EPA’s response to fly ash 

cost estimates) (in comment code 14.b).

For the final rule, based on public comments, EPA reassessed cost estimates applicable to the 

commenter and made several modifications, as detailed in EPA’s Incremental Costs and 

Pollutant Removals for the Final Effluent Limitations Guidelines and Standards for the Steam 

Electric Power Generating Point Source Category (Cost & Loads Report) (DCN 

SE05831/SE05832).

Second, regarding the commenter’s general assertions about the impacts of the rule, EPA 

disagrees that the rule will have an “extraordinary impact on an already economically 

disadvantaged population.” EPA conducted analyses to quantify impacts of the rule at levels of 

the individual plants, entities that own/operate the plants, electricity consumers, and national and 
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9-19

regional electricity markets. The proposed rule analysis did not indicate impacts in the magnitude 

suggested by the commenter, nor does the final rule analysis. For the final rule, EPA 

incorporated additional information on the costs expected to be incurred by plants to which the 

ELGs apply and resulting pollutant loading reductions. EPA also expanded its analysis to 

evaluate the impacts of electricity rate increases on households within various income groups, 

including households the commenter refers to as “economically disadvantaged.” As summarized 

in the preamble and detailed in the RIA document for the final rule, the analyses show that the 

final rule is economically achievable by the industry and will result in small changes in total 

electricity production costs (approximately 0.4 percent nationally and 0.5 percent in the SERC 

NERC region where the two plants identified by the commenter operate; see Table 5-1 in RIA 

document).

EPA also notes that the final rule will provide significant benefits (see the BCA for the final 

rule). In fact, EPA analyses show that the “economically disadvantaged” population of concern 

to the commenter is expected to receive a proportionally greater share of the health benefits from 

reducing toxic pollutant discharges to surface waters.

For the role of cost-effectiveness in EPA’s decisions for the final rule, see response to DCN 

EPA-HQ-OW-2009-0819-4655, Excerpt Number 27 in Comment Code 6.h.

Commenter Name: Thomas H. Adams

Commenter Affiliation: American Coal Ash Association (ACAA)

Document Control Number: EPA-HQ-OW-2009-0819-4511-A2

Comment Excerpt Number: 11

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The ELG Proposed Rule, like the CCR Proposed Rule, fails to consider the economic impact to 

ACAA members and its niche recycling industry, and continues to neglect the interests of 

utilities, ash marketing companies, technology developers, suppliers, various industry jobs, and 

end users focused on recycling CCR’s through beneficial use. The ACAA has repeatedly pleaded 

for consideration of these interests and how they are affected by the proposed regulations, and 

repeatedly they have been overlooked. Despite a twelve page section of the ELG Proposed Rule 

dedicated to economic and social impacts, it fails to display any concern for the beneficial use 

industry.15 Any final rule that is reached without adequate consideration of these issues would be 

disconnected from a complete understanding of the surrounding facts and circumstances, and 

would fail to consider relevant material presented by interested parties, as is required by the 

APA.16 The final rule should reflect full consideration of all affected industries and stakeholders, 

in order to achieve a fair and equitable result.
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15

See Steam Electric Power Generating Point Source Category: Effluent Guidelines Limitations 

and Standards, 78 Fed. Reg. 34432, 34491 to 34503 (proposed July 7, 2013) (to be codified at 40 

C.F.R. pt. 423)

16 5 U.S.C. § 553(c).

Comment Response: 

As noted in the response to DCN EPA-HQ-OW-2009-0819-4511-A2, Excerpt Number 8, the 

final steam electric ELGs do not directly affect the potential for beneficial use of CCR, and in 

fact may increase the amount of CCR that is available for beneficiation by promoting changes to 

plant processes, such as conversions to dry handling, that will enhance CCR marketability. For 

the final ELGs, EPA specifically included consideration of how changes in plant operations as a 

result of the final rule may affect the availability of CCR for beneficial use, including concrete 

and fill applications.

Comments specifically pertaining to EPA’s analysis of the CCR rule are outside the scope of this 

rulemaking. EPA addressed comments on the CCR rule in the context of that rulemaking (see 

Docket EPA-HQ-RCRA-2009-0640-11970).

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 100

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

B. THE ELECTRIC POWER INDUSTRY CAN AFFORD THE TECHNOLOGIES THAT 

WOULD ELIMINATE THE DISCHARGE OF FLY ASH TRANSPORT WATER.

As explained above in Section II, the relevant test for economic achievability is whether the costs 

can be reasonably borne by the industry as a whole.394 The technologies for dry fly ash handling 

meet this test.

The economic impact of requiring dry handling of fly ash is relatively small given that the 

overwhelming majority of plants that generate fly ash already use dry handling technology. EPA 

projects that basing the BAT limits on dry handling would cause 66 plants395 to incur compliance 

costs.396 This amounts to only 12-13 percent of all coal, coke, and oil plants.397 Put 

differently, 87-88 percent of all coal and oil plants would have zero compliance costs to comply 

with a BAT standard based on dry handling of fly ash.
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Even if EPA focuses on the 481 coal, coke, and oil plants that generate fly ash,398 only 14 

percent of plants would face compliance costs. And even if the agency zeroes in on coal and 

coke plants, which generate the greatest amount of fly ash, only 19% of coal and coke plants 

would face compliance costs.399 81% of coal and coke plants would face zero compliance costs 

because they already have dry handling systems in place. A rule that would lead 81% of the 

most affected plants to incur no compliance costs is economically achievable.

The total, industry-wide cost of a zero discharge standard can be reasonably borne by the 

industry. EPA calculates that the 66 plants that would have to convert to dry handling would 

spend $398 million on capital costs, $177 million on operating and maintenance costs per year, 

and an additional $20.7 million per year on 10-year recurring costs.400 We are unable to 

comment on the compliance costs for specific plants, since the plant-level data has been redacted 

by EPA.401 As a rough guide to the plant-level costs, we divided these costs by 66, the 

number of affected plants. Based on this calculation, the average plant would incur $6 million in 

capital costs and approximately $3 million in O&M costs per year.402

Whatever cost metric one uses, these costs are achievable for the electric sector as a whole. Since 

EPA has analyzed the cost of regulatory options rather than the component costs of treating 

different waste streams, we can examine the economic impact of the various options that include 

dry handling of fly ash as BAT. EPA conducted the full suite of cost analyses for only two 

options, Options 3 and 4. Option 4 includes dry handling for fly ash, and the record 

demonstrates that Option 4 is economically achievable, which means that each of the component 

parts of Option 4—including dry fly ash handling—is economically achievable.403

For Options 3 and 4, EPA presented a cost-to-revenue screening analysis. Option 4 would 

cause 798 plants to devote 0% of their revenues to compliance costs; 117 plants would spend 1-

3% of the revenues on costs, and only 48 plants would have a cost-to-revenue ratio greater than 

3%.404 EPA asserts that “entities incurring cost below 1% of revenue are unlikely to face 

economic impacts,”405 and 84% of plants will have costs at or below 1% of revenues. This 

suggests that the industry as a whole can easily bear the cost of dry fly ash handling that is part 

of the cost of Option 4.

Option 4 would increase variable production cost by only 1% on a per megawatt hour 

basis.406 EPA modeling indicates that Option 4 would result in only a .1% increase in retirements

(relative to the baseline capacity of the industry).407 Even if all of the costs of Option 4 were 

attributable to dry fly ash handling – which they obviously are not – the costs are so small that 

only .1% of total industry capacity would retire early.

Finally, the cost effectiveness of requiring dry handling of fly ash is $27 per TWPE,408 which is 

well within the range of cost effectiveness values EPA has found reasonable in other ELGs.409

In short, whether one determines economic achievability based on the total cost to industry, cost 

to revenue ratios, plant closures, or cost-effectiveness, dry handling of fly ash is economically 

achievable. As explained infra Section IX, it is unlawful for EPA to base its BAT determination 

on cost metrics other than the standard for economic achievability articulated by the courts, 

namely, whether the costs can be reasonably borne by the industry as a whole. But even 
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assuming, for the sake of argument, that all of the cost metrics EPA has evaluated in this 

rulemaking are appropriate potential bases for a BAT determination, dry fly ash handling is 

economically achievable under any of them. Therefore, there can be no dispute that the cost of 

dry fly ash handling can be reasonably borne by the industry as a whole and therefore is 

economically achievable.

394 Waterkeeper Alliance v. EPA, 399 F.3d 486, 516 (2d Cir. 2005); Rybachek v. EPA, 904 F.2d 

1276, 1290-91 (9th Cir. 1990); Am. Iron & Steel Inst. v. EPA, 526 F.2d 1027 (3d. Cir. 1975).

395 This excludes certain small (<50MW) and oil-fired units. If those plants are included, 76 

plants would incur costs to convert from wet-sluicing to dry vacuum handling of fly 

ash. Incremental Costs and Pollutant Removals at 7-4.

396 Id. at 7-4 n.43.

397 See TDD at 4-16 (calculating that there are 527 to 552 coal, coal, and oil plants).

398 Id. at 7-22.

399 Id. at 7-23.

400 Id. at 9-40.

401 See Appendices to Incremental Costs and Pollutant Removals.

402 TDD at 9-40.

403 Like Option 4, Option 3 is economically achievable. However, in the technologies proposed 

as BAT for waste streams other than fly ash transport water fall, Option 3 falls far short of what 

the Clean Water Act requires.

404 78 Fed. Reg. at 34,494.

405 78 Fed. Reg. at 34,495.

406 78 Fed. Reg. at 34,498.

407 Id.

408 TDD at 8-34.

409 RIA at D-8 (11 final effluent limitations guidelines have cost-effectiveness values greater 

than or equal to $27 for direct dischargers).
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Comment Response: 

The commenter supports a zero-discharge requirement for the discharge of pollutants in fly ash 

transport water because, as the commenter states, “the total, industry-wide cost of a zero 

discharge standard can be reasonably borne by the industry.” For the final rule, EPA evaluated 

the economic achievability of several regulatory options that involve control of multiple 

wastestreams, rather than the economic achievability of controls for particular wastestreams. 

These options are described in Section VIII of the preamble. The final rule is based on regulatory 

Option D for existing sources and regulatory Option F for new sources. Option D includes a zero 

discharge requirement for fly ash transport water (based on dry handling) for existing sources 

that are not oil-fired generating units nor are less than or equal to 50 MW in nameplate capacity, 

and Option F includes a zero discharge requirement for fly ash transport water (based on dry 

handling) for new sources. As explained in the preamble, EPA concluded that Option D for 

existing sources is economically achievable for the industry as a whole, and that Option F for 

new sources does not present a barrier to entry.

For the role of cost-effectiveness in EPA’s decisions for the final rule, see response to DCN 

EPA-HQ-OW-2009-0819-4655, Excerpt Number 27 in Comment Code 6.h.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 105

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA's analyses of Option 4, which would require zero discharge of bottom ash transport water 

for all units greater than 50 MW, show that the economic impact of requiring zero discharge of 

bottom ash can be reasonably borne by the industry as a whole. Option 4 would increase annual 

costs by approximately 1.4% and increase variable production costs by 1%.437 Option 4 would 

cause a 0.1% increase in unit retirements.438 Even if all of the costs of Option 4 were attributed 

to zero discharge of bottom ash transport water – which they are not, making it 

a highly conservative assumption – the costs could still be reasonably borne by industry, since 

they would increase annual costs by roughly 1% and cause a less than 1% increase in unit 

retirements.

The impacts of Option 4 are also reasonable when viewed through the lens of cost-to-revenue 

ratios. Under a zero discharge standard for plants greater than 50 MW, 85 percent of plants 

would incur costs that are less than 1 percent of revenues,439 which EPA claims means that they 

“are unlikely to face economic impacts.”440 Under Option 4, only 48 plants – 4 percent of the 

industry – would incur compliance costs greater than 3 percent of revenues. And those costs 

include the cost to treat all waste streams (FGD wastewater, fly ash transport water, etc.). Given 
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that the costs of Option 4 as a whole are achievable, the component cost to convert all units 

greater than 50 MW to zero discharge systems is also achievable.

Zero discharge of bottom ash is economically achievable if cost-effectiveness is considered as 

well. Requiring all units greater than 50 MW to meet a zero discharge standard for bottom ash 

transport water would cost $107 per TWPE.441 This is well within the cost-effectiveness values 

that EPA has approved in other effluent limitations guidelines; $107 per TWPE is lower than the 

cost-effectiveness of the final ELGs for seven separate industries.442 EPA has issued final 

effluent limitations guidelines with cost-effectiveness values nearly four times as high as 

the cost-effectiveness of bottom ash retrofits.443

437 78 Fed. Reg. at 34,498.

438 Id.

439 78 Fed. Reg. at 34,494.

440 Id. at 34,495.

441 TDD at 8-34.

442 RIA at D-8 ($404 per TWPE for direct dischargers in the electrical and electronic components 

industry; $155, $175, $111, $116, $127, and $380 per TWPE for indirect dischargers in the 

aluminum forming, centralized waste treatment, leather tanning, metal molding and castings, 

metal products and machinery, and transportation equipment cleaning industries, respectively).

443

See id.

Comment Response: 

The commenter supports a zero-discharge requirement for the discharge of pollutants in bottom 

ash transport water because, as the commenter states, “the economic impact of requiring zero 

discharge of bottom ash can be reasonably borne by the industry as a whole.” For the final rule, 

EPA evaluated the economic achievability of several regulatory options that involve control of 

multiple wastestreams, rather than evaluating the economic achievability of individual controls 

for particular wastestreams. These options are described in Section VIII of the preamble. The 

final rule is based on regulatory Option D for existing sources and regulatory Option F for new 

sources. Option D includes a zero discharge requirement for bottom ash transport water (based 

on dry handling or closed-loop systems) for existing sources that are not oil-fired generating 

units nor are less than or equal to 50 MW in nameplate capacity, and Option F includes a zero 

discharge requirement (based on dry handling or closed-loop systems) for bottom ash transport 

water for new sources. As explained in the preamble, EPA concluded that Option D for existing 

sources is economically achievable for the industry as a whole, and that Option F for new 

sources does not present a barrier to entry.
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For the role of cost-effectiveness in EPA’s decisions for the final rule, see response to DCN 

EPA-HQ-OW-2009-0819-4655, Excerpt Number 27 in Comment Code 6.h.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 108

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA's annualization method overestimates annual costs by a factor of nearly two. EPA used a 

7% discount rate and 20-year equipment lifetime to annualize costs.460 EPA selected a 7% 

discount rate based on the claim that it “is the real (i.e., inflation rate factored out) cost of capital 

as estimated by the U.S. Office of Management and Budget [OMB, 2003]” and has been used by 

EPA in the rulemakings.461 But the referenced OMB document recommends that agencies use 

additional discount rates, including 3%, as sensitivity analyses to the use of a 7% discount 

rate.462 Moreover, the OMB circular cautions that the appropriate discount rate changes over 

time as interest rates and rates of return change. Accordingly, with interest rates having 

plummeted since the circular was drafted in 2003, EPA's choice of only a 7% discount rate 

conflicts with the circular’s recommendations.

460 78 Fed. Reg. at 34,492; Incremental Costs and Pollutant Removals at 8-32.

461 Incremental Costs and Pollutant Removals at 8-32.

462 OMB, Circular A-4 (Sept. 17, 2003), available at 

http://www.whitehouse.gov/omb/circulars_a004_a-4/#d. This error in calculating the 

annualization factor affects all of EPA's cost calculations, not just the calculations for bottom ash 

conversions.

Comment Response: 

EPA disagrees with the commenter that its use of a 7 percent discount rate conflicts with the 

Office of Management and Budget (OMB)’s Circular A-4 guidance. The commenter 

misunderstands or describes incorrectly EPA’s use of discount rates in the analyses for the Steam 

Electric ELGs. Specifically, as explained below, EPA used discount rates in two parts of the 

regulatory analysis, and it used more than one discount rate value in these analyses. EPA’s use of 

discount rates in these analyses is appropriate and reasonable given the purpose of the analyses, 

and, further, is consistent with OMB guidance. EPA used discount rates as follows:
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1. Analyzing the regulation’s cost burden and economic impact on the regulated 

community (i.e., the steam electric generating units and plants that will need to comply 

with the final Steam Electric ELGs). For this analysis, EPA used 7 percent to discount 

and annualize the capital outlays and other costs of regulatory compliance. In its Circular 

A-4, OMB recommends using 7 percent for evaluating a regulation that will mainly 

displace or alter the use of capital in the private sector (OMB, 2003; updated 2009). 

Given that the Steam Electric ELGs analysis assesses burden on the steam electric power 

industry of capital outlays that would alter and potentially displace the industry’s capital 

outlay profile, using 7 percent is consistent with the OMB Circular A-4 guidance.

2. Analyzing the social cost and benefits of the Steam Electric ELGs. For this analysis, EPA 

performed calculations using two different discount rates – 7 percent and 3 percent – both 

drawing from OMB Circular A-4 guidance (OMB, 2003; updated 2009). As described 

above, the 7 percent discount rate reflects the opportunity cost of capital to society. Per 

OMB guidance, the 3-percent discount rate is intended to reflect society’s valuation of 

differences in the timing of consumption. EPA views use of both discount rates as 

reasonable and appropriate for the social cost and benefit analysis; each provides a 

different perspective for understanding the rule’s economic consequences considering the 

fact that its costs and benefits occur over a lengthy timeframe. The analysis using the 7 

percent discount rate captures the rule’s effects from the standpoint of competing uses of 

capital in the economy. The analysis using the 3 percent discount rate takes a different 

perspective in valuing the rule’s costs over time, in effect considering how the rule 

affects households’ consumption profile – e.g., via price increases – both in the 

composition and timing of consumption. The 3 percent discount rate analysis is also 

relevant for valuing the temporal flow of human health and other environmental benefits 

achieved by the rule.

In summary, EPA performed more than one analysis involving present value discounting and 

annualization, and thus requiring a discount rate, for assessing the economic impact, and cost and 

benefits of the rule. EPA used more than discount rate value in these analyses and views its use 

of the different discount rates in these analyses as appropriate and reasonable considering their 

conceptual objectives: assessment of economic impact on the regulated community, and 

calculation and reporting of the rule’s social cost and benefits. EPA chose the specific discount 

rate values for these analyses based on OMB guidance.

The commenter also states that interest rates have “plummeted since the circular was drafted in 

2003,” arguing that EPA should use lower rates than those published by OMB for discounting 

and annualization in the steam electric rule analysis. EPA acknowledges that interest rates, 

particularly short-term rates, have fallen substantially in recent years, and remain at historically 

low values in large part because of the U.S. Federal Reserve’s interventions to maintain low 

borrowing costs as a lever for stimulating U.S. economic recovery following the severe recession 

of 2008-2010. However, the current occurrence of lower interest rates does not mean that EPA 

that should use lower rates than those proposed by OMB for the steam electric ELG analysis. 

Two points are relevant:

 First, OMB’s recommended societal cost of capital – i.e., 7 percent real discount rate – is 

based on the observed average real rate of return on capital over a substantial number of 
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years. The period includes years in which rates of return were higher than this average, 

and years in which rates were lower than the average. In 2013 revisions to Circular A-4, 

OMB notes that a recent analysis “found that the average rate of return to capital remains 

near the 7 percent rate estimated in 1992.”

 Second, facilities are expected to comply with the steam electric rule over a substantial 

number of years into the future; for the final rule, EPA analyzed incremental costs over 

the period of 2015 through 2042, with capital outlays assumed to largely occur between 

2019 and 2023. It is widely acknowledged, in particular by the Federal Reserve, itself, 

that the efforts to maintain exceptionally low interest rates will end as the economy 

continues to recover. As the U.S. unemployment rate continues to decline, both shortand long-term interest rates are expected to increase, both in nominal and real terms, and 

to return to rate levels that have more customarily occurred in the U.S. economy over the 

past several decades. Given the likelihood of increasing rates, potentially as soon as 2015, 

using the very low rates of recent years as the basis for discounting in the steam electric 

rule analysis would artificially reduce the present and annualized values of costs, whether 

from the industry or societal perspective, and of the rule’s benefits. Relying on these 

artificially reduced values could lead to incorrect assessments of economic impact and 

cost-benefit findings.

In view of these considerations, EPA concludes that use of the 7 percent discount rate for 

analyzing cost and economic impact on the regulated community, and as the alternative, higher 

value for social cost and benefit analysis, is reasonable and appropriate.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 109

External Review Flag: Engineering

External Review Incorporated into Response: Yes

Comment Excerpt: 

The other primary component of the annualization method is the equipment lifetime. “EPA 

selected a timeframe of 20 years based on the expected operational life of the dry/closed-loop 

recycle bottom ash handling technology.”463 However, zero discharge systems have been used 

for longer than 20 years; a more appropriate equipment lifetime would be 30 years.464 If 

EPA were to use a 3% interest rate – which is much closer to the interest rate on a 30-year 

treasury note – and equipment lifetime of 30 years, the annualization factor would be roughly 

half of what EPA used.465 Bringing these inputs more in line with contemporary data would cut 

the costs of a zero discharge standard in half.

463 Incremental Costs and Pollutant Removals at 8-32.
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464 Fox Report, Appendix E, at 45. Additionally, the useful life of dry handling systems is often 

assumed to be longer than 20 years; for example, a 1981 TVA study seems to have assumed that 

dry handling systems could operate for the 35-year expected life of the new plant. See Economic 

Analysis of Wet Versus Dry Ash Disposal Systems (1981).

465 Fox Report, Appendix E, at 45-46.

Comment Response: 

As discussed in Chapter 3 of the RIA, EPA calculated private costs at the level of the individual 

regulated facility and annualized the cost of compliance technology expenditures and other nonannually recurring outlays over various time periods based on (1) the estimated useful life of 

individual capital cost components or (2) the frequency of recurrence for other non-annual 

outlays (e.g., permit renewal).

The Commenter is correct that the useful life and discount rate both affect calculation of 

annualized compliance costs, but EPA maintains that the 20-year life and 7 percent discount 

rates the Agency used in its analyses are reasonable and appropriate to produce informed 

regulatory results.

EPA does not agree with the commenter that the Agency should have used a 3 percent discount 

rate in calculating private costs. See discussion of the use of the 7 percent discount rate for the 

private compliance outlays analysis in the response to DCN EPA-HQ-OW-2009-0819-4684-A1, 

Excerpt Number 108. As described in that comment response, EPA used the 7 percent discount 

rate for the private cost analysis because this rate is intended to reflect the opportunity cost of 

capital to society. Consistent with OMB guidance, EPA concludes that this rate is applicable for 

analyzing for cost and economic impact from the standpoint of regulated facilities, and their 

owners in the steam electric power industry.

EPA also does not agree with the commenter that the Agency’s analyses should have used 30 

years as the operational life of the dry/closed-loop recycle bottom ash handling technology. EPA 

used a 20-year service life as a typical planning period for wastewater treatment operations. As 

described in the RIA and TDD, EPA based its estimate of service life of equipment that may be 

installed to meet the ELGs on a review of reported performance characteristics of compliance 

technology components. From this review, EPA concluded that the equipment could reasonably 

be expected to operate for 20 years or more and thus further concludes that 20 years is an 

appropriate basis for cost and economic impact analyses that account for the estimated operating 

life of compliance technology.

EPA discounted and annualized cost values using a 7-percent discount rate, which is an estimate 

of the opportunity cost of capital to society. In Circular A-4, the Office of Management and 

Budget (OMB) recommends that 7 percent be used in evaluating a regulation that will mainly 

displace or alter the use of capital in the private sector (OMB, 2003; updated 2013). Given that 

this analysis assesses burden on individual companies and power plants using 7 percent is 

appropriate. EPA also uses the 7 discount rate in the social cost analysis. In addition, for the 

social cost and benefit analysis, EPA uses the 3 percent discount rate, which is intended to 
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capture the effect of changes in consumption flows (see the BCA); however, this rate would not 

be appropriate for the private cost analysis, which is intended to estimate the economic/financial 

impact of compliance requirements on facilities and companies.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 216

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

b. EPA’s conclusion that the total industry cost of Option 5 is too high is not supported by the 

record and is an improper basis for rejecting this option.

EPA never evaluates whether the costs of mechanical evaporation are economically achievable 

by the industry, and there is nothing in the record to demonstrate that it is not. Instead 

of applying this well-establish standard for economic achievability, EPA rejected Option 5 based 

on the total cost to industry, which it calculated at $2.3 billion in annualized social costs, 

and “because of preliminary indications that it may not be economically achievable.”233 EPA 

notes that while affordability to the industry is the relevant cost factor for BAT, at isolated times 

it has considered total industry cost.

The previous rulemakings to which EPA cites as precedent for this approach do not demonstrate 

that total industry cost is a valid basis for concluding whether a technology is economically 

achievable. For instance, a 2009 rulemaking on the construction and development point source 

category, EPA rejected options for sediment control that would have cost $4.9 billion and $9 

billion because they would provide only marginally greater removals than the preferred option 

costing just under $1 billion.234 In that rulemaking, as well as in this one, total industry cost is 

merely a guise for incremental cost-benefit decision making. EPA may not base its BAT 

determination on the cost effectiveness of the technology in question, see supra Section II. 

However, a comparison to the 2009 rulemaking in fact demonstrates the relative costeffectiveness of Option 5 and mechanical evaporation. While Option 5 costs three times more 

than Option 4, 235 it removes over 10 times as much pollution from our waterways.236

The statutory mandate to consider cost in setting BAT has been interpreted definitively by the 

courts. With respect to cost, the relevant inquiry for EPA is whether “costs can be reasonably 

borne by the industry.”237 The inquiry is not whether the costs of a given control are warranted in 

EPA’s estimation, or whether the costs are “high” in an abstract and subjective sense. Total 

industry cost, taken out of the context of the industry’s size and revenues,238 is an 

arbitrary metric and an inappropriate basis to reject a technologically feasible option as 

BAT.239 Here, EPA’s assessment that the total industry cost is too high is totally unmoored from 
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any standards governing what total costs are acceptable; thus, total industry cost is not only the 

wrong cost test for determining BAT, it is wholly arbitrary in application.

EPA’s other economic basis for rejecting Option 5 is the vague assertion that based on “certain 

screening-level economic impact analyses,” “compliance costs may result in financial stress to 

some entities owning steam-electric plants.240 In fact, as discussed below in Section IX, EPA’s 

own screening-level analysis demonstrates that the costs of Option 5 can be borne by the 

industry. That some entities may experience some degree of financial stress is not a reason to 

reject mechanical evaporation as BAT.241

233 78 Fed. Reg. at 34,473.

234 Effluent Limitations Guidelines and Standards for the Construction and Development Point 

Source Category, 74 Fed. Reg. 62,996, 63,026.

235 TDD at Table 9-3 (comparing total capital costs).

236 TDD at Table 10-9.

237 Waterkeeper Alliance v. U.S. EPA, 399 F.3d 486, 516 (2nd Cir. 2005) (emphasis added); see 

also Rybachek v. U.S. EPA, 904 F.2d 1276, 1290-91 (9th Cir. 1990) (discussing this standard).

238 See Synapse Report, Appendix A, at 48.

239 In addition, the affordability of an option combining BAT proposals for various waste streams 

is an inappropriate basis to conclude that a particular technology is not economically achievable 

for the waste stream it is designed to address. Economic achievability should be determined on 

the waste stream level, not the option level.

240 74 Fed. Reg. at 34,473.

241 See infra bottom ash section, discussing some plant closures not a barrier to BAT.

Comment Response: 

EPA disagrees with the commenter that “EPA’s conclusion that the total industry cost of Option 

5 is too high is not supported by the record and is an improper basis for rejecting this option.” 

Proposed Option 5 was renamed as Option F for the final rule. EPA did not select Option F as 

the basis for requirements for existing sources for the final rule. Option F would have established 

limitations and standards applicable to FGD wastewater based evaporation technology.

As detailed in the preamble, EPA decided that it would not be appropriate to identify evaporation 

as the BAT basis for control of pollutants in discharges of FGD wastewater at all steam electric 

power plants because of the high costs associated with these potential regulatory requirements. 
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The cost of an option based on evaporation would be about $800 million more expensive, on an 

annual basis, for the industry as a whole than the cost of limitations based on chemical 

precipitation plus biological treatment (the technology basis for the final BAT limitations 

applicable to FGD wastewater). Furthermore, these costs would be incurred while the industry is 

also facing costs associated with several other rules in addition to the ELGs. Nonetheless, the 

final rule does establish a voluntary incentives program in which participating plants may opt to 

meet BAT limitations applicable to FGD wastewater based on evaporation, and receive a definite 

date of December 31, 2023, for implementation of those limits (see preamble Section VIII for 

more details).

EPA disagrees with the commenter’s statement that “In [the C&D] rulemaking, as well as in this 

one, total industry cost is merely a guise for incremental cost-benefit decision making.” For the 

final rule, EPA calculated the cost-benefit ratio and cost-effectiveness of the options separately 

(see Section XV of the preamble, Appendix F in the RIA, and the Benefit Cost Analysis) and did 

not use these as the bases for rejecting Option F or, for that matter, for selecting Option D as 

BAT. For the role of cost-benefit in EPA’s decisions on the final rule, see response to DCN 

EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 in Comment Code 6.e, and for the role of 

cost-effectiveness in EPA’s decisions for the final rule, see response to DCN EPA-HQ-OW2009-0819-4655, Excerpt Number 27 in Comment Code 6.h. Moreover, EPA did not use the 

results of its screening-level economic impact analyses, such as the cost-to-revenue ratios noted 

by the commenter as indicators of financial stress, to reject Option F for existing plants.

EPA also disagrees with the commenter’s statements that: “Total industry cost . . . is an 

arbitrary metric and an inappropriate basis to reject a technologically feasible option as 

BAT. Here, EPA’s assessment that the total industry cost is too high is totally unmoored from 

any standards governing what total costs are acceptable; thus, total industry cost is not only the 

wrong cost test for determining BAT, it is wholly arbitrary in application.” The “cost” of 

achieving the effluent reduction is a factor explicitly mentioned in section 304(b)(2)(B) of the 

Act to be “take[n] into account” for BAT. EPA must therefore consider cost in developing ELGs 

based on BAT. And, while the legislative history makes clear that EPA’s decision must be 

“reasonable,” the Act provides EPA with a great deal of discretion in how exactly cost should be 

considered and what weight to give that factor. See Weyerhaeuser Co. v. Costle, 590 F.2d 1011, 

1045 (D.C. Cir. 1978) (“Congress did not mandate any particular structure or weight for the 

many consideration factors. Rather, it left EPA with discretion to decide how to account for the 

consideration factors, and how much weight to give each factor.”); BP Exploration & Oil, Inc. v. 

EPA, 66 F.3d 784, 799-800, 802 (6th Cir. 1995); see also Ass’n of Pacific Fisheries v. EPA, 615 

F.2d 794, 817 (9th Cir. 1980) (citing legislative history). In this case, EPA offered a reasonable 

basis for rejecting BAT requirements for FGD wastewater based on evaporation by 

demonstrating that the annual cost to the industry of limitations based on evaporation would be 

more than 2 and 1⁄2 times the cost to industry estimated for the final rule (after tax) 

(approximately $570 million more expensive than the final rule, on an annual basis, after tax). 

and explaining that the industry is simultaneously facing requirements associated with several 

other rules, which make the potential additional cost to the industry not insignificant (see DCN 

SE05978 for memo presenting technology-specific compliance costs).
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As the commenter notes, EPA has considered total cost to the industry in several other ELG 

rules, including for the Electroplating and Metal Finishing Point Source Categories, 48 FR 

32462, 32468 (July 15, 1983), and for the Construction and Development Point Source Category, 

74 FR 62996, 63026 (Dec. 1, 2009), and its decision to reject a BAT option in the Oil and Gas 

Extraction ELGs based in part on total industry court has been upheld in court. BP Exploration 

& Oil, Inc. v. EPA, 66 F.3d 784, 796-97 (6th Cir. 1995).

EPA notes that, for the final rule, it did select Option F as the basis for new source requirements, 

NSPS/PSNS (which includes standards for discharges of pollutants in FGD wastewater based on 

evaporation). This is based on the demonstrated performance of evaporation technology and the 

lower cost of installing technologies at new sources as compared to retrofitting existing sources. 

See Section VIII.D of the preamble for further discussion of the basis for EPA’s determination.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 217

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

2. Chemical precipitation plus biological treatment is economically achievable.

EPA has estimated that the total capital cost for the 116 plants that would need to retrofit with 

biological treatment is $2.5 billion, and that total O&M costs across these same plants would 

be $257 million. The data show that, considering the size and revenues of this industry, it can 

reasonably bear these costs.

Option 3 would increase annual costs by approximately 0.6% and increase variable production 

costs by 0.5%, and would result in no change in generating capacity.301 Option 4 would increase 

annual costs by 1.4%, variable production costs by 1%, would cause a 0.1% increase in unit 

retirements.302 Even if all of the costs of either Option 3 or Option 4 were attributed 

to biological treatment of FGD wastewater – which they are not, making it a highly conservative 

assumption – the costs could still be reasonably borne by industry.

Although EPA did not directly evaluate the cost-to-revenue ratios for biological treatment 

standing alone, it did so for the options including a biological treatment component—Options 

2, 3, and 4—and the results confirm that this technology is affordable. Even the most expensive 

of these options, Option 4, would impose annualized compliance costs of more than 3 percent of 

revenue for only 48 out of 1,079 plants.303 Nearly 800 plants would experience no costs, 111 

plants would experience costs of less than 1 percent of annual revenues, and 117 plants would 

experiences costs of between 1 and 3 percent of annual revenues.304
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The baseline cost-to-revenue analysis assumes—unrealistically—that utilities would pass on 

none of the costs to their customers. EPA did conduct a sensitivity analysis to account for the 

likelihood that 50% of these costs could be passed through to consumers; that sensitivity analysis 

illustrates the affordability even more starkly. For Option 3, assuming that plants could pass 

through 50 percent of their costs to consumers, only three plants would see a cost-to-revenue 

impact that is greater than 3 percent. For Option 4, that number increases to only ten 

plants.305 As biological treatment is a part of each of these options, it follows that it too, is 

economically achievable for the industry as a whole.

301 78 Fed. Reg. at 34,498.

302 Id.

303RIA at Table 4-1.

304 Id.

305 RIA, Appendix B, at Table B-2.

Comment Response: 

The commenter states that “chemical precipitation plus biological treatment is economically 

achievable” for the steam electric power generating industry. For the final rule, EPA evaluated 

the economic achievability of several regulatory options that involve control of multiple 

wastestreams, rather than evaluating the economic achievability of individual controls for 

particular wastestreams. These options are described in Section VIII of the preamble. The final 

rule is based on regulatory Option D for existing sources and regulatory Option F for new 

sources. Option D includes limitations and standards applicable to the discharge of FGD 

wastewater (based on chemical precipitation plus biological treatment) for existing sources that 

are not oil-fired generating units nor are less than or equal to 50 MW in nameplate capacity. For 

the final rule, EPA used a very similar approach to estimate impacts on the steam electric 

industry as it did at proposal, updating certain assumptions to reflect new information the 

Agency compiled upon reviewing the public comments. The results of EPA’s analyses are 

available in the preamble and the RIA. As explained in the preamble, EPA concluded that Option 

D for existing sources is economically achievable for the industry as a whole.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 218

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

2. Reliance on BPJ determinations will disproportionately affect environmental justice 

communities.

As noted above, it is challenging and rare for environmental organizations such as the 

undersigned commenters to marshal the resources to comprehensively evaluate a BAT 

determination for a particular plant. Clearly, most impacted local communities lack these kinds 

of resources. Thus, a critical flaw with relying on case-by-case BPJ determinations is that BAT 

determinations will vary by jurisdiction and, even within a single jurisdiction, may vary 

depending on whether a local community or environmental organization is able to participate in 

the administrative process and has the resources to advocate for protective permit limits. 

Communities without resources to engage in the permitting process in this way are much less 

likely to be able to compel the permitting authority to issue a permit containing strong BATbased limits. EPA should have evaluated the environmental justice implications of two of its 

preferred options—3a and 3b—which would fail to provide the same protection to underresourced communities as a uniform national standard. EPA’s environmental justice analysis 

fails to acknowledge the implications of reliance on BPJ for these groups.358

358 See 78 Fed. Reg. at 34,532; RIA at 10-2 to 10-5.

Comment Response: 

EPA agrees with the commenter that, where EPA has the information to establish nationally 

applicable, technology-based effluent limitations and standards, such limitations and standards 

are generally preferable to those developed on a “best professional judgment” (BPJ) basis. This 

is due, in part, to the fact that national limits provide predictability and clarity to the regulated 

entities, as well as affected communities, and they reduce the burdens associated with developing 

limits on a site-specific basis.

The commenter states that EPA should have evaluated the environmental justice implications of 

two of its proposed regulatory options, which would have required limitations and standards for 

discharges of FGD wastewater from steam electric generating units to be determined on a BPJ 

basis. For the final steam electric ELGs, where possible, EPA established uniform, nationally 

applicable limitations. In particular, and of interest to the commenter, the final rule establishes 

nationally applicable limitations and standard for discharges of FGD wastewater from the steam 

electric industry because EPA had sufficient information with which to set such limitations and 

standards and thus requiring BPJ permitting would have placed an unnecessary burden on both 

the regulated industry and the permitting authorities. See Section VIII of the preamble for details.

For the reasons explained in Section VIII.I of the preamble, the final rules continues to reserve 

BAT/PSES and NSPS/PSNS for non-chemical metal cleaning wastes. Thus, permitting 

authorities must continue to establish limitations and standards based on BPJ for generating units 

discharging that wastestream. See preamble Section XVI.A.5 for more information on permitting 
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of non-chemical metal clean wastes. See comment code 6.j. of this comment-response document 

for more detailed responses to comments related to BPJ.

EPA is sensitive to concerns regarding the disadvantage to certain communities of relying on 

BPJ to set permit requirements. The Agency did not find data to assess whether reliance on BPJ 

place certain communities at a greater disadvantage. As noted above, however, EPA recognizes 

that relying on BPJ increases the burden associated with developing limits and has, where 

possible, established nationally applicable limitations. 

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 25

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

With regards to the question of whether or not these technologies represent an unreasonable 

burden to the category as a whole (all steam electric generators other than oil‐fired generating 

units and generating units with capacities 50 MW or smaller), EPA notes that it “retains 

considerable discretion in assigning the weight to be accorded these factors.”151 In the Federal 

Register, EPA explains that Option 4 and 5 have not been selected as preferred options on 

economic grounds:

EPA did not select Option 4 as its preferred regulatory option because of concerns expressed 

above associated with the projected compliance costs associated with zero discharge 

requirements for bottom ash for units equal to or below 400 MW.152

EPA did not select Option 5 as its preferred option for BAT because of the high total industry 

cost for the option ($2.3 billion/year annualized social cost) and because of preliminary 

indications that Option 5 may not be economically achievable.153

As evidence of this judgment, EPA provides the results of several economic screening tests, 

notably: total annualized compliance and social costs, plant and firm cost‐to‐revenue ratios, cost‐

effectiveness, plant closures, costs to households, and job effects (see Table 11).

The results of EPA’s screening tests, however, do not support a determination that Options 4 

and 5 are not economically achievable. On the contrary, Options 4 and 5 appear to be 

economically achievable both in the context of the steam electric industry and in comparison to 

other industries.

Table 11. Summary of steam electric ELG screening test results
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 Cost‐to‐revenue ratios: This screening test compares EPA’s measure of compliance costs 

to revenues on a plant and firm basis. In Options 4 and 5, 74.0 percent of plants have no 

compliance costs whatsoever. Just 4.4 and 6.7 percent of plants, respectively, have costs 

greater than 3 percent of revenues; while most of the EPA rulemakings that presented a 

cost‐to‐revenue measure showed smaller shares of entities with cost‐to‐revenue ratios 

greater than 3 percent, at least one ELG category was approved at the same approximate 

level.155

EPA’s assumption of zero cost pass‐through is a key determining factor in estimating the share 

of plants with costs greater than 3 percent of revenues. An assumption of 50‐ percent pass‐

through of compliance costs would lower the Option 4 and 5 shares substantially: EPA 

performed this sensitivity for Option 4 and found that the share of plants with costs greater than 

3 percent fell from 4.4 percent to 0.9 percent.156 An assumption of 100‐percent pass‐through (as 

is used in EPA’s household cost and jobs analyses) would bring these shares down to zero. 

EPA’s explanation that the zero cost pass‐through assumption was chosen to provide a worst 

case outcome is accurate, but unhelpful:
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This assumption is used for analytic convenience and provides a worst‐case scenario of 

regulatory impacts to steam electric plants. Even though the majority of steam electric plants 

may be able to pass increases in production costs to consumers through increased electricity 

prices, it is difficult to determine exactly which plants would be able to do so. Consequently, 

EPA judges that assuming zero cost pass‐through is appropriate as a screening‐level, upper 

bound estimate of the potential cost impact from the proposed ELGs to steam electric plants and 

their parent entities. To the extent that some steam electric plants are able to recover some of the 

increased production costs in increased prices, this analysis overstates plant‐level impacts.49 The 

analysis, while helpful to understand potential cost impact, does not generally indicate whether 

profitability is jeopardized, cash flow is affected, or risk of financial distress is increased.157

151 Technical Development Document, pp.1‐4 and 1‐5; EPA cites Weyerhaeuser Co. v. Costle, 

590 F.2d 1011, 1045 (D.C. Cir.1978) in support of this statement.

152 78 Fed. Reg. at 34,473.

153 78 Fed. Reg. at 34,473.

155 Concentrated Aquatic Animal Production at 5.7 percent; see 69 Fed. Reg. at 51,892 (August 

23, 2004).

156 Regulatory Impact Analysis, p.B‐2.

157 Regulatory Impact Analysis, p.4‐2.

Comment Response: 

The commenter states that the results of EPA’s analyses “do not support a determination that 

Options 4 and 5 are not economically achievable. On the contrary, Options 4 and 5 appear to be 

economically achievable both in the context of the steam electric industry and in comparison to 

other industries.” The final rule establishes limitations and standards for existing sources based 

on Option D, which is similar to proposed Option 4, but unlike proposed Option 4, it does not 

contain limitations and standards applicable to the discharge of combustion residual leachate 

based on chemical precipitation. Section VIII of the preamble explains the basis for EPA’s 

decision to select Option D for existing sources, including why EPA did not identify chemical 

precipitation as the technology basis for control of pollutants in discharges of combustion 

residual leachate. As explained in the preamble, EPA determined that Option D is economically 

achievable for the steam electric industry as a whole, based on its expected impacts on steam 

electric generating capacity as reflected in EPA’s IPM analysis.

Regarding EPA’s rejection of Option F (the same as proposed Option 5) as the basis for BAT, 

see Section VIII of the preamble and EPA’s response to related comment DCN EPA-HQ-OW2009-0819-4684-A1, Excerpt Number 216.
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28.c. Econ – IPM

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A2

Comment Excerpt Number: 42

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Uncertainty in the Modeled Air-related Benefits

US EPA used the IPM to estimate the change in emissions of NOx, SO2 and CO2 for two of the 

eight proposed ELG options. The model is an economic optimization model that is used to 

evaluate the impact of environmental policies on the electric power sector in US. According to 

the US EPA, specifically, "IPM is a multi-regional, dynamic, deterministic linear programming 

model of the U.S. electric power sector. It provides forecasts of least-cost capacity expansion, 

electricity dispatch, and emission control strategies for meeting energy demand and 

environmental, transmission, dispatch, and reliability constraints" (US EPA, 2011b, pg. 1-1). 

While we have not critically analyzed the technical merit of each of the IPM model assumptions, 

it is clear that the model involves a series of simplifying assumptions that contribute to the 

significant uncertainties in modeled emissions estimates. US EPA discusses some of these 

sources of uncertainty, but not others. While it is not always discernible in what direction 

(increased or reduced benefit) simplifying assumptions will affect that analysis, importantly, US 

EPA provides no sensitivity analyses to bound benefit estimates. Some of the key uncertainties 

associated with the IPM model in general, as well as specific assumptions made for the ELG 

analysis, are listed below.

 Assumption that electricity demand will not change between the baseline level and the 

years analyzed, and therefore does not capture electricity price increases that might result 

from the proposed ELGs;

 Simplified estimates of projected changes in fuel prices and the assumption that imports 

from Canada and Mexico would not change;

 The use of baseline air emissions under existing air regulations to benchmark the 

additional reductions expected from the regulatory options of the ELG rule, even though 

at least one of considered rules, the final Cross-State Air Pollution Rule (CSAPR), has 

not been finalized;

 The aggregation of all EGUs into "model plants" based on similar costs and operational 

characteristics, which because of significant variability among plants by location, plant 

characteristics, and by meteorology, likely skews the results and provides an unrealistic 

estimate of air-related benefits;

 Running the IPM model for only two years (2020 and 2030) to represent the time periods 

2017- 2024 and 2025-2040, respectively, without specifying extrapolation methods for 

the individual intervening years (US EPA, 2013d, Chapter 8); and
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 Selection by US EPA of a compliance response for each plant based on complete 

compliance with proposed regulatory options, instead of the IPM option in which 

modeled plants select their own compliance response based on the most economic 

outcome for that plant (US EPA, 2013h, Appendix C).

Comment Response: 

For the role of benefits-costs in ELG determinations, see response to DCN EPA-HQ-OW-2009-

0819-4464-A1, Excerpt Number 3 (in comment code 6a).

EPA acknowledges the uncertainties embedded in IPM. However, EPA determined that IPM is 

an appropriate tool for estimating the electricity market and emissions impacts of the ELGs. IPM 

is a dynamic linear programming model that can be used to project power sector behavior under 

future business-as-usual conditions. It provides forecasts of least cost capacity expansion, 

electricity dispatch, and emission control strategies while meeting energy demand and 

environmental, transmission, dispatch, and reliability constraints. EPA uses the best available 

information from utilities, industry experts, gas and coal market experts, financial institutions, 

and government statistics as the basis for the detailed power sector modeling in IPM. This 

information includes projected demand, fuel prices and imports assumptions highlighted by the 

commenter. See response to related comment DCN EPA-HQ-OW-2009-0819-4655, Excerpt 204 

(in Section 29.h) for further discussion of IPM uncertainty, review process, and prior 

applications.

EPA notes that the aggregation of generating units into model plants does not have nearly the 

significance on the results as what is implied by the commenter. The aggregation of steam 

electric electricity generation units, in particular, retains much of the spatial specificity present in 

the EGU-level information by grouping similar units within a given plant. See Section 4.2.6 in 

the IPM v5.13 documentation for details. EGUs are only aggregated if they have all of the 

following 11 characteristics: Model Region; unit technology type; fuel demand region; 

applicable environmental regulations; state; facility for fossil units; unit configuration; emission 

rates; heat rates; fuel; and size. As a result of the aggregation, the number of modeled coal steam 

units goes from 1,003 units to 759 model plants.

As discussed in Chapter 5 of the RIA and Chapter 7 of the BCA, EPA used data for each of the 

four run years (2016, 2020, 2025, and 2030) as representing all years within each run year 

period.

Regarding the general concern that EPA did not conduct sensitivity analyses using IPM to 

evaluate how projected generation (and therefore emissions) may change, the Agency notes that 

the analyses EPA conducted using IPM (total of three model runs, including sensitivity around 

the effects of the Coal Combustion Residuals (CCR) rule) all show very small incremental 

impacts associated with the ELGs. The model runs all point to positive improvements in air 

quality. Given the small magnitude of impacts, conducting additional IPM runs is unlikely to 

provide any more useful or consequential insight on the impacts of the final ELGs, while 

requiring considerable resources and time.
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While it is true that the model does not model changes in demand that may result from increased 

electricity rates (i.e., demand is assumed to be inelastic), EPA notes that, as far as the ELG 

impacts are concerned, the impacts are very small (wholesale electricity price effects are 0.5 

percent or less, depending on the region; see Chapter 5 in RIA) and therefore unlikely to 

significantly affect electricity consumption and, by extension, projected emissions associated 

with the amount of electricity generated to meet the demand.

The concern regarding the emissions baseline reflecting the effects of CSAPR does not apply to 

the final ELG analysis which IPM v5.13 as the model base case for the final rule instead includes 

the Clean Air Interstate Rule (CAIR), which remains in effect by a standing court order while 

EPA reconsiders CSAPR.

Regarding the commenter’s concern that the aggregation of units into model plants in IPM 

results in different geographical distribution of the impacts, EPA notes that model plants 

represent the aggregation of units with similar operating characteristics, which include the 

geographical location of the unit (i.e., only units located in the same state can be aggregated 

together), size, technology, heat rate, fuel choices, unit configuration, SO2 emission rates and 

environmental regulations, among other. See Chapter 4 of the IPM documentation for details 

(documentation is available at http://www.epa.gov/airmarkets/programs/ipm/psmodel.html). The 

combination of eleven categories considered in the aggregation scheme and the fact that only 

units located within the same state and which have all other 10 aggregation categories in 

common can be aggregated into a model plant, significantly reduces the uncertainty associated 

with using model plants as compared to modeling units individually in IPM. This is particularly 

true for coal steam units where the number of model plants (759) is over 75 percent of the 

number of individual units (1,003). The fact that IPM groups two similar units at the same plant 

into a model plant for computational efficiency does not significantly skew the geographical 

distribution of the effects.

Regarding the commenter’s concern that EPA simulated only two run years and did not 

interpolate to the intervening years, EPA provided a response specific to the interpolation of airrelated benefits in EPA-HQ-OW-2009-0819-4655, Excerpt 204 (in Section 29.h).

Finally, regarding the commenter’s concern that EPA pre-selected the compliance response for 

each plant, EPA notes that the final rule establishes limitations on discharges of pollutants, and 

plants are free to meet those limitations as they see fit. Plants may be able to meet those limits 

using a range of approaches. EPA used the BAT bases to develop plant-specific cost estimates. 

Any incremental costs associated with the BAT technologies are included in IPM when 

determining the lowest costs of meeting total electricity demand. The lowest-cost optimization 

conducted in IPM simulates the decisions of plant owners to retire units prematurely, refuel, or 

otherwise select an appropriate “compliance response.” EPA recognizes that other, potentially 

less expensive, compliance approaches may be possible for individual plants.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.
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Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 222

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

With respect to the first metric, EPA states that it didn’t even run the IPM for Option 5 “[d]ue to 

scheduling constraints” and because screening-level analysis for existing plants showed that 

Option 5 costs might result in “financial stress” to some utilities.632 As discussed in greater 

detail elsewhere, EPA’s screening-level analysis does not support EPA’s dismissal of Options 4 

and 5 for existing plants.633 EPA states that this “analysis, while helpful to understand potential 

cost impact, does not generally indicate whether profitability is jeopardized, cash flow is 

affected, or risk of financial distress is increased.”634 Furthermore, even incorrectly assuming 

that all compliance costs will be borne by utilities without at least some part passed on 

to consumers in the form of higher utility rates,635 the results of the “screening-level analysis 

shows that the entity-level compliance costs are low in comparison to the entity-level revenues; 

very few entities are likely to face economic impacts at any level.”636 The results of the plantlevel cost-to-revenue analysis also show that “for the majority of steam electric plants, including 

those expected to incur zero compliance costs, costs would not exceed the 1 percent of revenue 

threshold under any of the eight regulatory options.”637 In addition, the compliance costs used in 

the screening-level analysis don’t account for “anticipated unit retirements and conversions 

announced between August 2012 and April 2013, and announced retirements, repowerings, and 

conversions that are scheduled to occur by 2022”, all of which would reduce total annualized 

compliance costs. 638 Thus, there is no basis at all for EPA declining to run the IPM for Option 

5, especially where it would preclude a more thorough examination of the economic impacts to 

new sources associated with Option 5.

632 Id. at 5-6 to 5-7.

633 See infra Section IX; see also attached Synapse Report, Appendix A.

634 RIA at 4-2.

635 RIA at 4-2.

636 RIA at 4-13.

637 RIA at 4-3.

638 RIA at 4-5, 4-12.

Comment Response: 
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For the final rule, EPA analyzed Options B and D using IPM (see the final preamble for a 

description of these options and how they compare to proposed Option 5). As described in the 

preamble, EPA selected Option D as the BAT/PSES technology basis for the final rule.

EPA did not analyze Option F, which includes evaporation as the BAT/PSES technology basis 

for controlling pollutants in FGD wastewater discharges (as proposed Option 5 did), using IPM 

because EPA determined that evaporation for FGD wastewater is not BAT for all existing steam 

electric power plants. In particular, EPA did not identify evaporation as the BAT basis for FGD 

wastewater discharges from all existing steam electric power plants due to the high cost of 

possible regulatory requirements based on evaporation for discharges of FGD wastewater at 

existing facilities. The annual cost to the industry of limitations based on evaporation would be 

more than 2 and 1⁄2 times the cost to industry estimated for the final rule (after tax) 

(approximately $570 million more expensive than the final rule, on an annual basis, after tax) 

(see DCN SE05978). Given the high costs associated with the technology, and the fact that the 

steam electric industry is facing costs associated with several other rule sin addition to this rule, 

EPA decided not to establish BAT limitations for FGD wastewater based on evaporation for all 

steam electric power plants (however, plants that opt into the voluntary incentives program 

would be subject to BAT limitations for FGD wastewater based on evaporation, see preamble 

section VIII.C.13). Conducting an IPM analysis of proposed Option 5 or Option F would thus 

not have changed EPA’s BAT determination in this regard. See section VIII of the preamble for 

the final rule and the response to related comment DCN EPA-HQ-OW-2009-0819-4684-A1, 

Excerpt Number 216 (Section 28.b), for further discussion of EPA’s rationale for not 

establishing BAT limitations for FGD wastewater based on evaporation for all steam electric 

power plants in the final rule.

Regarding the commenter’s assertion that EPA’s decision to not run IPM on the most stringent 

option (Option 5) discussed at proposal precluded a more thorough examination of the economic 

impacts to new sources associated with that option, EPA notes that the IPM analysis would not 

have provided insight on the economic impacts to new sources associated with the ELGs because 

the model projects no new coal-fueled capacity to which the incremental costs would apply. 

Therefore, increases in the costs of constructing and operating new coal-fueled capacity due to 

the ELGs do not affect modeled decisions to add such capacity. For the final rule analysis, EPA 

specified incremental costs for new sources in IPM based on technologies defined under Option 

F, but IPM again projects no new coal-fueled capacity in either the base case or the ELG policy 

cases and the incremental costs are of no consequences to the modeled decisions to add 

generating capacity.
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28.d. Econ – Impacts on new plants

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 150

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA states that it assessed the economic impacts of NSPS requirements on new units in two 

different ways: (1) using the Integrated Planning Model (IPM) to determine “whether the costs of 

complying with the proposed ELGs would affect future capacity additions” and (2) “by 

comparing the incremental costs for new units to the overall cost of building and operating new 

units, on a per MW basis”631 Yet the rule and Regulatory Impact Analysis only provide the 

analysis for these two metrics for Option 4.

With respect to the first metric, EPA states that it didn’t even run the IPM for Option 5 “[d]ue to 

scheduling constraints” and because screening-level analysis for existing plants showed that 

Option 5 costs might result in “financial stress” to some utilities.632 As discussed in greater 

detail elsewhere, EPA’s screening-level analysis does not support EPA’s dismissal of Options 4 

and 5 for existing plants.633 EPA states that this “analysis, while helpful to understand potential 

cost impact, does not generally indicate whether profitability is jeopardized, cash flow is 

affected, or risk of financial distress is increased.”634 Furthermore, even incorrectly assuming 

that all compliance costs will be borne by utilities without at least some part passed on 

to consumers in the form of higher utility rates,635 the results of the “screening-level analysis 

shows that the entity-level compliance costs are low in comparison to the entity-level revenues; 

very few entities are likely to face economic impacts at any level.”636 The results of the plantlevel cost-to-revenue analysis also show that “for the majority of steam electric plants, including 

those expected to incur zero compliance costs, costs would not exceed the 1 percent of revenue 

threshold under any of the eight regulatory options.”637 In addition, the compliance costs used in 

the screening-level analysis don’t account for “anticipated unit retirements and conversions 

announced between August 2012 and April 2013, and announced retirements, repowerings, and 

conversions that are scheduled to occur by 2022”, all of which would reduce total annualized 

compliance costs. 638 Thus, there is no basis at all for EPA declining to run the IPM for Option 

5, especially where it would preclude a more thorough examination of the economic impacts to 

new sources associated with Option 5.

With respect to the second metric, EPA evaluates only the relative magnitude of compliance 

costs for new units for Option 4. Furthermore, much of the detailed costing information for 

NSPS is unavailable to the public as three out of four NSPS costing memoranda in the docket are 

not available due to CBI claims.639 The attachment to the one non-CBI memorandum is also 

identified as CBI.640 For Option 4, EPA concludes that compliance costs for a new unit at a new 

plant are 1.5% of expected annualized costs; compliance costs for a new unit at an existing 
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plant are 1.2% of expected annualized costs.641 Using information in the TDD, Commenters 

were able to calculate incremental costs as a percent of new generation.

Table 6 – Comparison of Option 4 and Option 5 Incremental Costs and as Percent of New 

Generation642

With respect to total annualized costs, Option 5 will only result in a 4% increase in the total 

annualized costs of a new 1,300 MW coal-fired generation unit at a new plant, and a 3.2% 

increase in total costs for an existing plant. EPA states that a 1.5% increase under Option 4 is 

not too high, but EPA does not identify the threshold above which the increase in 

annualized costs as a share of baseline costs cannot be reasonably borne by the industry. There 

is no basis in the record for EPA’s rejection of Option 5 as BADCT based on the increase in total 

annualized costs in relation to total costs for the new unit.643 Thus, EPA’s record does not 

demonstrate that the costs of Option 5 cannot be reasonably borne by industry, and Option 5 is 

BADCT for new sources.

631 RIA at 3-11.

632 Id. at 5-6 to 5-7.

633 See infra Section IX; see also attached Synapse Report, Appendix A.

634 RIA at 4-2.

635 RIA at 4-2.

636 RIA at 4-13.

637 RIA at 4-3.
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638 RIA at 4-5, 4-12.

639 See EPA, CBI Memorandum to the Steam Electric Rulemaking Record: New Source 

Performance Standards (NSPS) Costing Memorandum, Docket No. EPA-HQ-OW-2009-0819-

2210; EPA, CBI Characteristics of New Generating Units and NSPS Analyses, Docket No. EPAHQ-OW-2009-0819-1966; EPA, CBI NSPS Capital and O&M Compliance Costs, Docket 

No. EPA-HQ-OW-2009-0819-197581.

640 See Memorandum from TJ Finseth, ERG, to Steam Electric Rulemaking Record Re Steam 

Electric NSPS Costs Methodology (DCN SE02130) (Apr. 19, 2013).

641 RIA at 3-12.

642 See RIA at 3-12 tbl. 3-5 and TDD at 9-46 tbl. 9-12. Calculations are from Synapse 

Economics.

643 EPA may have overestimated the capital costs for a new 1,300 MW coal plant. For example, 

EPA estimates costs of approximately $2,982/kW, but a Black & Veatch calculator last updated 

in 2011 estimates costs for this type of unit between $3,000/kW to $4,000/kW. Ryan Pletka PE, 

Black & Veatch’s (RETI’S) Cost of Generation Calculator (May 16, 2011), available at 

http://www.energy.ca.gov/2011_energypolicy/documents/2011-05-

16_workshop/presentations/Ryan_Pletka_B&V.pdf.

Comment Response: 

For the final rule, EPA based effluent standards for new sources of discharges of FGD 

wastewater from steam electric power plants on Option F, which is equivalent to proposed 

Option 5 EPA, which the commenter supports.

Chapter 3 of the RIA describes the projected economic impacts of the final ELGs on new sources 

(see Section 3.2). The analysis shows that the costs of the suite of technologies that forms the 

basis for Option F represent a small fraction of the overall costs of building and operating a new 

steam electric generating unit, in the range of 0.3 percent to 3.3 percent. While there is no set 

threshold for determining the fraction of costs that would constitute a barrier to additional 

generation (such threshold would depend on the cost of generation alternatives), this fraction of 

overall cost is low and unlikely to be material in the investment decision. EPA therefore 

concluded that the ELGs do not, by themselves, present a barrier to entry.

The commenter’s concerns that EPA may have overestimated the capital cost for a new 1,300 

MW coal plants (in footnote 643) seem unfounded given the differences in costs provided by the 

commenter ($2,982/kW is similar to, or even less, than the range of $3,000/kW to $4,000/kW 

provided by the commenter). From the context, EPA infers that the commenter meant that the 

Agency overestimated the relative impacts of the compliance costs on this type of plant. On this 

point, the Agency notes that it used estimates published by the Energy Information 

Administration for new coal-fired capacity that underlay the widely used Annual Energy Outlook 

(AEO) projections. As described in Chapter 4 of the RIA for the final rule, EPA revised the 
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values to incorporate the most recent plant cost information from the AEO and concluded that 

the costs associated with NSPS do not present a barrier to new coal capacity.

EPA notes that no coal-fired steam electric power plants (i.e., those with wastestreams addressed 

in this rulemaking) have been announced, nor are projected in the U.S. Department of Energy’s 

Annual Energy Outlook (AEO) 2014,1 making the assessment of the relative costs and of any 

barrier the final ELGs may pose to additional steam electric generation hypothetical. Similarly, 

results of the electricity market model using the Integrated Planning Model (see Chapter 5 in 

RIA document) show no additional coal steam capacity being built through 2050 in the Base 

Case (in the absence of the ELGs) or in the policy cases (with the final ELGs). As discussed in 

Chapter 5 of the RIA, the IPM results help demonstrate that the ELGs do not pose a barrier to 

new electricity generation overall (i.e., not just steam electric generation capacity); the model 

shows essentially negligible differences in new capacity projected in IPM under the final rule 

option.

See related answers for other issues raised in the comment excerpt:

 Regarding EPA’s analysis of Options 4 for existing plants, see DCN EPA-HQ-OW-2009-

0819-4684-A1, Excerpt Number 105 (in comment code 28.b)

 Regarding EPA’s analysis of Option 5 for existing plants, see DCN EPA-HQ-OW-2009-

0819-4684-A1, Excerpt Number 216 (in comment code 28.b).

1 U.S. Department of Energy (U.S. DOE). 2014a. Annual Energy Outlook 2014 (AEO2014). 

Release Date: April 2014. Available at: http://www.eia.gov/forecasts/aeo/pdf/0383(2014).pdf. 

Accessed on September 11, 2014.
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28.e. Econ – Impacts on specific types of entities (small entities, government) / RFA and 

UMRA

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 100

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Kevin Bromberg with the U.S. Small Business Administration, Office of Advocacy, and our role 

is to protect small entities before the federal government.

In the context of this rule, it's small independently owned utilities, small rural electric co ops, and 

small municipalities.

There was a Reg Flex Analysis done by EPA, and here, we have hundreds of small entities who 

own power plants, but EPA surprisingly has certified the rule as not having a significant 

economic effect on these small entities, and the first problem that we want to address is 

transparency.

We are unable to look behind that finding. EPA thinks there is no problem here, but we cannot 

look behind that finding for the following reasons.

Comment Response: 

EPA disagrees with the commenter’s statement that the Agency “surprisingly has certified the 

rule as not have a significant economic effect on . . . small entities” and the commenter’s 

statement that there is a “problem” with “transparency” in EPA’s analysis. EPA’s analysis to 

assess whether the final rule would have “a significant impact on a substantial number of small 

entities” (SISNOSE) is consistent with Regulatory Flexibility Act (“RFA”) guidance and follows 

the approach utilized by EPA in the development of a number of other industry effluent 

limitations guidelines and standards. EPA provided as much information to the public as possible 

underlying its RFA analysis, consistent with the requirements of EPA’s regulations regarding the 

protection of Confidential Business Information (see 40 CFR Part 2, Subpart B). While the 

Agency is unable to provide results of its RFA analysis for each individual entity that owns 

steam electric power plants due to the need to protect data claimed as CBI by the steam electric 

industry survey respondents, the Agency made public review and participation possible by 

describing its approach and data sources in detail and providing analytical results for the overall 

electricity market and for the steam electric power generating industry. As described in Chapter 

8 of the RIA, EPA identified parent entities of steam electric power plants by determining the 

highest level of domestic ownership of entities that own majority shares in steam electric power 

plants, based on data provided by the plant owners in response to the detailed industry survey. 

EPA then determined which of these entities are considered small by comparing data about the 
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characteristics of the parent entities to the most recent Small Business Administration size 

threshold guidelines available at the time of analysis (last updated in July 2014). EPA conducted 

a cost-to-revenue analysis to assess the regulatory impact on all small entities and reported the 

results in the RIA by entity type and ownership category. Based on the reported results for the 

steam electric power generating industry, EPA certified the rule as not having a significant 

impact on small entities.

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 149

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

We are a bit disappointed that there was not a SBREFA review. We would have liked 

one. There was a very fine effort initiated by EPA to extend an invitation for mayors to come in 

and meet on unfunded mandates. Unfortunately, the meeting was never completed. We would 

have liked to have seen that meeting with mayors completed. Mayors, too, want good drinking 

water, but the mayors were concerned about the impacts on both the electric and the water side 

of the house. And it would have been far preferable that both the SBREFA panel and the UMRA 

panels and the UMRA panel is new to me, but it would have been preferable that that would 

have been completed before the actual proposal of the rule.

Comment Response: 

EPA appreciates the interest the Steam Electric ELGs generated by mayors and representatives 

of government entities. Consistent with the intergovernmental consultation provisions of Section 

204 of the UMRA, EPA held consultations with governmental entities potentially affected by 

this rule to ensure their meaningful and timely input into development of the ELGs. The 

consultations included a briefing with elected officials or their designated employees in October 

2011 and outreach with several intergovernmental associations representing elected officials. 

The preamble for the final rule describes these consultations. In attendance at the briefing were 

representatives from the National League of Cities, the National Conference of State 

Legislatures, the National Association of Counties, the National Association of Towns and 

Townships, the U.S. Conference of Mayors, the Council of State Governments, the County 

Executives of America, and the Environmental Council of the States. Policy and professional 

groups such as the National Rural Electric Cooperative Association, America’s Clean Water 

Agencies, and the American Public Power Association also participated in the briefing, as did 

environmental and natural resource policy staff representing nine state agencies and 

approximately 25 local governments and/or utilities. The participants asked questions and raised 

comments during the meeting and – in response to the agency’s specific request for pre-proposal 

comments within eight weeks of the briefing -- separate written submittals regarding technology 
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options, pollutant removal effectiveness, costs of specific technologies and overall costs, impacts 

on small generating units and on small governments were received and carefully considered by 

EPA while developing the proposed rule. EPA received comments from state and local 

government representatives on the proposed rule from 31 state and local officials or their 

representatives. Some state and local officials expressed concerns that the ELGs would impose 

significant costs on small entities, and would result in electricity rate increases that are 

unaffordable for households. They also noted that small municipal systems typically operate 

smaller generating units with disproportionally greater compliance costs as compared to larger 

generating units. Other state and local officials supported revisions of the ELGs and generally 

opposed reliance on BPJ as basis for establishing limits for FGD wastestreams.

EPA considered comments from state and local government representatives in developing the 

final rule. Many of the concerns expressed by state and local government representatives are 

addressed in the final rule. For example, as explained in the preamble, the final rule establishes 

differentiated BAT/PSES requirements for existing oil-fired generating units and existing 

generating units with a nameplate capacity of 50 MW or less, which will alleviate some of the 

concerns raised by state and local government representatives by reducing the number of 

government entities incurring costs to meet the ELG requirements (see Section VIII.C.12 and 

VIII.E of the final rule preamble).

Regarding the establishment of a SBREFA or UMRA panel, EPA notes that this rule is not 

subject to the requirements of Section 203 of UMRA because it contains no regulatory 

requirements that might significantly or uniquely affect small governments. As detailed in 

Chapter 9 of the RIA, EPA evaluated costs to government entities and in all of these analyses, 

both when comparing the total costs and the average and maximum cost per plant, the costs for 

small government-owned facilities were less than those for large government-owned facilities or 

for small nongovernment-owned facilities. On this basis, EPA concluded that the compliance 

cost requirements of the final rule would not significantly or uniquely affect small governments.

Similarly, EPA certified that the rule would not have a significant economic impact on a 

substantial number of small entities (SISNOSE) and therefore EPA was not required to convene 

a Small Business Advocacy Review (SBAR) Panel under SBREFA. See preamble Section 

XVII.C and Chapter 8 of the RIA for more details.

Commenter Name: Lisa C. Messinger

Commenter Affiliation: Vectren Corporation

Document Control Number: EPA-HQ-OW-2009-0819-4317-A1

Comment Excerpt Number: 30

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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We feel the added restrictions on the discharge of fly ash transport water, and potentially bottom 

ash transport water, as well as the inability to co-manage waste streams into single treatments 

systems will add a disproportionate cost to our otherwise very controlled , small generating units.

Comment Response: 

The commenter does not provide a definition of what it views as constituting a “disproportionate 

cost” for small generating units, does not raise specific concerns with the use of the size 

threshold EPA proposed for establishing differentiated BAT/PSES requirements (50 MW), nor 

offers an alternate size threshold that would satisfy those concerns.

Nevertheless, EPA recognizes the potentially higher relative costs faced by owners and operators 

of small generating units and, for the final rule considered establishing differentiated BAT/PSES 

requirements based on generation capacity. As described in Section VIII.C.12 and VIII.E of the 

preamble, the final rule establishes differentiated BAT/PSES requirements for existing oil-fired 

generating units and existing units with a nameplate capacity of 50 MW or less.

The commenter also does not explain what it means when it refers to the “inability to co-manage 

waste streams into single treatment systems.” EPA’s final rule does not prohibit any particular 

practices at steam electric power plants. Rather, it establishes limitations and standards for 

discharges of pollutants based on available and demonstrated technologies. Nonetheless, EPA 

notes that the final rule does not contain one of the anti-circumvention provisions proposed, 

which would have required internal monitoring to demonstrate compliance with certain numeric 

limitations and standards (see preamble Section VIII.G).

Commenter Name: Winslow Sargeant

Commenter Affiliation: U.S. Small Business Administration, Office of Advocacy

Document Control Number: EPA-HQ-OW-2009-0819-4477-A1

Comment Excerpt Number: 1

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA has certified that the proposal will not have a significant economic impact on small entities 

under the Regulatory Flexibility Act (RFA). Advocacy disagrees and believes that EPA should 

have convened a Small Business Regulatory Enforcement Fairness Act (SBREFA) panel, as 

required by the RFA.6 Small entities potentially affected by this rule include several hundred 

small independently-owned private utilities, small government-owned utilities, and small rural 

electric cooperative-owned utilities. The proposal would have substantially benefited from this 

pre-proposal input. 
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6 Section 609(c) of the RFA requires the formation of a SBREFA panel of three federal agency 

representatives that receives small entity input for all EPA rules, except those that are certified 

by the Administrator as having no significant economic impact on a substantial number of small 

entities.

Comment Response: 

EPA disagrees with the commenter’s assertion that EPA should have convened a SBREFA panel 

for the steam electric rule. In preamble Section XVII.C and Chapter 8 of the RIA, EPA discussed 

how it identified parent entities, determined which entities are small, and estimated impacts to 

small entities under the final rule, following largely the same approach used for the proposal (but 

using revised SBA size standards available as of July 2014).

As described in Chapter 8 of the RIA, EPA identified parent entities of steam electric power 

plants by determining the highest level of domestic ownership of entities that own majority 

shares in steam electric power plants, based on data provided by the plant owners in response to 

the detailed industry survey. EPA then determined which of these entities are considered small 

by comparing data about the characteristics of the parent entities to the most recent Small 

Business Administration size threshold guidelines available at the time of analysis (last updated 

in July 2014). EPA conducted a cost-to-revenue analysis to assess the regulatory impact on all 

small entities and reported the results in the RIA by entity type and ownership category. Based 

on the reported results for the steam electric power generating industry, EPA concluded that the 

rule would not have “a significant impact on a substantial number of small entities” (SISNOSE). 

The analysis and findings are consistent with RFA guidance, as well as approaches used by EPA 

in the development of a number of other industry effluent limitations guidelines and standards. 

See Chapter 8 of the RIA for more information.

EPA also analyzed regulatory alternatives that would specifically minimize impacts on small 

entities. As described in Section 8 of the TDD and Appendix C of the RIA, EPA estimated that 

by establishing differentiated requirements for existing oil-fired generating units and existing 

generating units with a nameplate capacity of 50 MW or less (“small” generating units), the final 

rule reduces the number of small entities incurring costs, as well as the costs incurred by small 

entities.

Regarding a Small Business Advocacy Review (SBAR) Panel, since EPA certified that the rule 

would not have a significant economic impact on a substantial number of small entities 

(SISNOSE), a SBAR Panel was not required under SBREFA.

Commenter Name: Winslow Sargeant

Commenter Affiliation: U.S. Small Business Administration, Office of Advocacy

Document Control Number: EPA-HQ-OW-2009-0819-4477-A1

Comment Excerpt Number: 18

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

Advocacy believes that the rule as proposed is improperly certified under the RFA.

Comment Response: 

EPA disagrees with the commenter’s assertion that the final rule “is improperly certified under 

the RFA”. EPA followed SBA and EPA guidance in determining that the final rule would not 

have “a significant impact on a substantial number of small entities” (NO SISNOSE). See 

preamble Section XVII.C and Chapter 8 of the RIA for more details.

See also response to DCN EPA-HQ-OW-2009-0819-4477-A1, Excerpt Number 1.

Commenter Name: Winslow Sargeant

Commenter Affiliation: U.S. Small Business Administration, Office of Advocacy

Document Control Number: EPA-HQ-OW-2009-0819-4477-A1

Comment Excerpt Number: 23

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

I. EPA’s Certification of No Significant Economic Impact on Small Entities Lacks a 

Factual Foundation and Transparency

A. The Certification Lacks a Factual Basis and Transparency

The agency certifies that this proposal will not have a significant economic impact on a 

substantial number of small entities.8 EPA produced a certification analysis that showed 

surprisingly few plants with costs owned by small entities. The same analysis showed some 

significant costs for a large fraction of plants owned by municipalities and rural electric 

cooperatives of unknown size.9 Given the hundreds of small entity owners that could be 

affected, small entity trade associations also concluded that the number of plants with costs 

owned by small entities was too low.10

EPA’s analysis in Chapter 8 of the May 2013 Regulatory Impact Analysis (RIA), does not in our 

view, comply with the RFA requirement to provide a “statement providing the factual basis for 

such certification”11 because the agency has withheld the underlying data supporting this 

determination. EPA has not revealed which plants will have compliance costs, which plants with 

costs have small entity owners, what those costs are, or the revenues that such plants have to 

address those costs. This makes it impossible to verify EPA’s underlying data, estimated values 

and calculations. We do not have the knowledge to identify these plants or estimate these costs 

without record information. EPA informs us that this additional transparency would reveal 

confidential business information (CBI) about these or other plants, without explaining why it is 
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unable to provide this information in some redacted form. However, model plant costs would 

adequately serve commenters’ needs. EPA could simply identify the plants with costs, by plant 

ID, and provide the approximate costs. Revenues, or at least electric generation rates, are 

available for virtually all plants, which would allow for the cost/revenue comparison to be 

calculated and compared with the EPA evaluation.

[

8

78 Fed. Reg. 34432, 34530 (June 7, 2013).

9 As discussed below, EPA failed to identify the affected plants, and in turn, which affected 

plants with costs had small entity owners, preventing us from commenting effectively on the 

validity of EPA’s determinations.

10 Personal communication with Dorothy Kellogg, NRECA and Theresa Pugh, APPA, July 19, 

2013.]

11 5 U.S.C § 605(b).

Comment Response: 

See DCN EPA-HQ-OW-2009-0819-4477-A1, Excerpt Number 5 (in comment code 28.a) for a 

response to the commenter’s concern regarding the number of plants incurring costs owned by 

small entities.

EPA disagrees with the commenter that it has not provided a statement providing the factual 

basis for its certification that the final rule will not have a significant economic impact on a 

substantial number of small entities because the Agency “withheld the underlying data 

supporting this determination.” EPA’s analysis to assess whether the final rule would have “a 

significant impact on a substantial number of small entities” (SISNOSE) is consistent with 

Regulatory Flexibility Act (“RFA”) guidance and follows the approach utilized by EPA in the 

development of a number of other industry effluent limitations guidelines and standards. EPA 

provided as much information to the public as possible underlying its RFA analysis, consistent 

with the requirements of EPA’s regulations regarding the protection of Confidential Business 

Information (see 40 CFR Part 2, Subpart B). While the Agency is unable to provide results of its 

RFA analysis for each individual entity that owns steam electric power plants due to the need to 

protect data claimed as CBI by the steam electric industry survey respondents, the Agency made 

public review and participation possible by describing its approach and data sources in detail and 

providing analytical results for the overall electricity market and for the steam electric power 

generating industry. As described in Chapter 8 of the RIA, EPA identified parent entities of 

steam electric power plants by determining the highest level of domestic ownership of entities 

that own majority shares in steam electric power plants, based on data provided by the plant 

owners in response to the detailed industry survey. EPA then determined which of these entities 

are considered small by comparing data about the characteristics of the parent entities to the most 

recent Small Business Administration size threshold guidelines available at the time of analysis 

(last updated in July 2014). EPA conducted a cost-to-revenue analysis to assess the regulatory 

impact on all small entities and reported the results in the RIA by entity type and ownership 
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category. Based on the reported results for the steam electric power generating industry, EPA 

certified the rule as not having a significant impact on small entities.

Regarding the commenter’s request that EPA provide data for a model plant, EPA performed its 

BAT analysis on a plant-specific basis using the plant-specific information collected in the 

survey. Additional plant-specific information was also received during the public comment 

period. EPA determined that the model plant approach bears little resemblance to actual plants 

and therefore does not provide meaningful information. In other words, there is no model plant 

approach that reasonably predicts the costs and/or pollutant removals for a given size of 

generating unit across the industry. For example, some plants have a single generating unit while 

others have multiple generating units. One or more generating units at a plant may have one or 

more of the discharges regulated by this rulemaking, but not other discharges (consider, for 

example, unit 1 at a plant with dry fly ash, wet bottom ash and no FGD; unit 2 at the plant with 

wet fly and bottom ash and FGD; unit 3 with FGD but dry fly & bottom ash). Many of the 

compliance costs take into account shared systems (e.g., shared ash silos, shared FGD treatment 

system) and thus realize some savings not necessarily reflected at a single unit plant. 

Additionally, certain compliance cost elements are related to wastewater flow rate (which is not 

correlated to size of the generating unit), while other elements are related to size; and then there 

are other elements that are related to plant-specific ash generation rates and ash disposal 

practices. These cost elements, at any specific plant, are affected by variables including coal type 

and characteristics, capacity utilization rate, system metallurgy, and existing ash solids and 

wastewater management practices. A model plant approach would not adequately take these 

considerations into account.

Commenter Name: Winslow Sargeant

Commenter Affiliation: U.S. Small Business Administration, Office of Advocacy

Document Control Number: EPA-HQ-OW-2009-0819-4477-A1

Comment Excerpt Number: 25

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

B. Small Entity Costs Appear High, But the Record is Insufficient to Permit Analysis

Advocacy is concerned about the EPA finding in Table 4-1 of the RIA that approximately half of 

all the municipally-owned and rural electric cooperative plants have cost-to-revenue ratios in 

excess of 3%. Under EPA’s own RFA guidance, if these reflect small entity costs, such large 

impacts preclude the presumption of a certification.12 Also, such a finding suggests that many 

of these plants would not be financially viable, particularly since the 3% figure is a lower bound 

for these plants. It is reasonable to expect that several plants would experience cost/revenue 

ratios exceeding 10% or 20%. Evidence of the degree of serious impact on individual plants is, 

therefore, lacking in the record. This analysis suggests that the certification may not be correct, 

but without the underlying data, we can only speculate as to its validity.
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Second, this high rate of economic impact on plants generally is not consistent with EPA’s 

historic interpretation over three decades of “best available technology economically 

achieveable” (BAT) determinations, where average cost/revenue impact ratios are generally in 

the range of 1 percent or less. We anticipate that a large proportion, if not almost all such plants 

under severe economic pressure, are owned by small entities. Unfortunately, EPA has not 

identified these impacted plants, the plant owners, or their estimated revenues or compliance 

costs. Therefore, we cannot comment effectively on the underlying data or the basis for these 

determinations. Since cost estimates for model size plants, cost curves, plant revenues and plantbased costs are not provided, it is difficult for Advocacy to provide informed comment on this 

issue.

Third, EPA reports that, of 1,079 steam electric plants, only 277 face costs under Option 4, 

regulating FGD, fly ash and bottom ash wastewaters. Similarly, of 122 municipally-owned 

plants, only 23 plants report costs under Option 4. We find this surprisingly small, but cannot 

evaluate the basis of this claim since EPA has not identified the plants with estimated costs. 

Underreporting of plant costs would also lead to an underestimate of the economic impact in the 

certification analysis.

12 Table 1 shows 8 of 19 co-op plants, and 10 of 23 municipally owned plants face cost/revenue 

ratios in excess of 3%. Under EPA’s RFA guidance, if these had been individual plants owned 

by small entities, there would be no presumption of a certification, as the 

percentage of plants in each category exceeds 20% (see Table 2, November 2006 EPA RFA Gui

dance at 24; http://www.epa.gov/sbrefa/). Further, for the certification analysis, EPA incorrectly 

identifies the percentage of affected small entities in Table 8-4, instead of the percentage of 

affected small entities with costs imposed by the rule, which prevents us from examining this 

proposal using the guidance in Table 2. Use of this metric underestimates the percentage of 

plants with costs for the parameter used in Table 2 and is insufficient to reach a conclusion 

regarding certification.

Comment Response: 

The commenter’s interpretation of data presented in the RIA for the proposed rule is incorrect. 

Because EPA provided a similar presentation of data for the final rule, this response explains the 

data presented in the RIA for the proposed rule, as well as identifies corresponding data for the 

final rule RIA.

Advocacy asserts that Table 4-1 of the proposed rule RIA indicates that approximately half of 

municipality-owned (10 of 23) and rural electrical cooperative plants (8 of 19) have cost-torevenue values exceeding 3 percent. However, this is not correct. Instead, Table 4-1 indicates 

that, under Option 4 for the proposed rule, 8 of 67 cooperative-owned plants (12 percent) and 10 

of 122 municipality-owned plants (8 percent) would have a cost-to-revenue value exceeding 3 

percent. Advocacy’s assertion appears to be based on a misunderstanding of the appropriate 

value for the denominator in calculating the percentage of plants with cost-to-revenue values 

exceeding 3 percent. Advocacy is using the number of plants incurring non-zero costs as the 
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denominator in its calculation, whereas the appropriate denominator is the number of plants 

subject to regulation under the steam electric ELGs . For the final rule, EPA estimated that one 

out of 63 cooperative-owned plants (2 percent) and 4 of 122 municipality-owned plants (3 

percent) have a cost-to-revenue value exceeding 3 percent (see Table 4-1 in the RIA for the final 

rule).

The commenter then speculates as to the potential impacts precluding a certification of the 

proposed rulemaking under the Regulatory Flexibility Act (RFA) if the cooperatives and 

municipalities mentioned were small. However, Table 4-1 presents the cost-to-revenue value for 

plants, not parent entities, and the RFA analysis is conducted at the level of the entity. Moreover, 

elsewhere in the TDD (Section 8) EPA provided information on which entities owning steam 

electric power plants were identified as small, along with an analysis of the potential for 

significant economic impact for those entities. The Agency provided similar information in the 

RIA for the final rule. For the reasons explained in Section 8 of the final TDD, EPA certified the 

final rule as not having a significant economic impact on a substantial number of small entities.

EPA also disagrees with Advocacy’s assertion that Table 8-4 in the proposed rule RIA only 

indicates the percentage of small entities owning steam electric power plants, as opposed to the 

percentage of small entities owing steam electric power plants that are estimated to incur 

compliance costs under the final rule. Instead, it is Table 8-2 that presents the number of small 

entities owning steam electric power plants, along with the percentage of entities owning steam 

electric power plants that are small. Table 8-4, on the other hand, presents the cost-to-revenue 

analysis for small entities, providing the number and percentage of small entities with costs 

greater than or equal to 1 percent and 3 percent, and therefore it provides the percentage of small 

entities incurring compliance costs that are greater than or equal to 1 percent of the entity’s 

revenue. This analysis is consistent with RFA guidance for assessing whether the final rule 

would have “a significant economic impact on a substantial number of small entities” 

(SISNOSE), as well as the approach that EPA has used in the development of a number of other 

industry effluent limitations guidelines and standards.

The commenter also claims that “evidence of the degree of serious impact on individual plants is, 

therefore, lacking in the record.” However, in Table 4-1 of the proposed rule RIA (and Table 4-1 

of the final rule RIA), EPA did in fact identify the cost-to-revenue values, in ranges, for all plants 

to which the ELGs apply. EPA disagrees with Advocacy’s contention that it is reasonable to 

expect cost-to-revenue values exceeding 10 percent or 20 percent and notes that Advocacy 

provided no factual support for its assertion. For the final rule, EPA found very few plants with 

costs exceeding 3 percent of revenue (eight plants under Option D, of which four plants are 

owned by municipalities (out of a total of 122 municipal-owned plants), and one plant is owned 

by a cooperative (out of 63 cooperative-owned plants)). Of these eight plants, two are owned by 

small entities (see Section 4.2.2 of the RIA).

With respect to the commenter’s statement about “best available technology economically 

achievable,” EPA notes that it determined that the final rule is economically achievable – as 

required by the Clean Water Act – based on a comprehensive assessment using the Integrated 

Planning Model, which projected a very small impact on the steam electric industry as a whole 

as a result of the final rule. In particular, the final rule is projected to result in a net reduction of 
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843 MW in generating capacity as of model year 2030, reflecting full compliance by all plants, 

which corresponds to a net effect of two generating unit (partial) closures and one plant (full) 

closure.

With respect to Advocacy’s statement that “EPA has not identified these impacted plants, the 

plant owners, or their estimated revenues or compliance costs,” EPA notes that it provided, in 

Chapter 8 of the final rule RIA, a detailed discussion of how it identified parent entities, 

determined which entities are small, and conducted an analysis to estimate potential significant 

impacts to small entities under the final rule. EPA cannot provide information for, or 

identification of, individual plants subject to this rulemaking because of its regulatory obligation 

to protect information claimed as “confidential business information” by steam electric power 

plants (see 40 CFR Part 2, Subpart B). See response to DCN EPA-HQ-OW-2009-0819-4477-A1, 

Excerpt Number 25.

Without providing any specific information, Advocacy further suggests that EPA may have 

underreported plant costs, which would in turn lead to an underestimate of economic impacts in 

the certification analysis. The TDD describes the methodology used to develop plant-level costs. 

These plant-level costs were used in the cost-to-revenue analysis for small parent entities, which 

underlies the certification under RFA. EPA does not agree that costs are underreported, as 

addressed in responses to other comments. EPA revised the estimated compliance costs for the 

final rule based in part on public comments.

In summary, EPA disagrees with the commenter’s assertion that the final rule is improperly 

certified under the RFA. In the RIA, EPA discussed how it identified parent entities, determined 

which entities are small, and estimated impacts to small entities under the final rule. Chapter 8 of 

the RIA presents the cost-to-revenue analysis for small entities, providing the number and 

percentage of small entities with costs greater than or equal to 1 percent and 3 percent. The 

methodology used for the final rule is the same as that used and described for the proposed rule. 

The analysis used data provided directly by the plant owners in response to the detailed industry 

survey. For the final rule, EPA found that the absolute numbers of small entities, and the

fractions of small entities estimated to incur costs exceeding either 1 or 3 percent of revenue are 

low (see details in Chapter 8 of the RIA). The analysis and findings are consistent with RFA 

guidance to assess whether the final rule would have “a significant economic impact on a 

substantial number of small entities” (SISNOSE), as well as the approach used by EPA in the 

development of a number of other industry effluent limitations guidelines and standards.

Commenter Name: Dorothy Kellogg and Michael Leitman

Commenter Affiliation: National Rural Electric Cooperative Association (NRECA)

Document Control Number: EPA-HQ-OW-2009-0819-4565-A1

Comment Excerpt Number: 1

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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NRECA urges EPA to reconsider the potential impact of this rule on small entities, 

including the small distribution cooperatives that own the affected G&T cooperatives.

NRECA is disappointed that EPA did not convene a Small Business Regulatory Enforcement 

Fairness Act (SBREFA) panel. Cooperative G&Ts generate and transmit power to 

their distribution cooperative owners, most of which qualify as small entities by the Small 

Business Administration (SBA) criteria (sale of less than 4 million megawatt hours/year). In fact, 

only five of our distribution cooperatives and 17 G&Ts do not meet the SBA definition of 

“small”. We question the analysis underlying EPA’s certification that this proposal will not 

have a significant economic impact on small entities under the Regulatory Flexibility Act (RFA). 

While most of the potentially affected G&T cooperatives do not themselves qualify as “small” 

under the SBA definition, 265 of the 266 distribution cooperatives that own the G&Ts do.

We agree with SBA’s concern over the potential costs to small entities: (1) the number that may 

experience cost-to-revenue ratios greater that 1%, the upper-bound EPA has historically used to 

define “best available technology economically achievable” (BAT); and (2) the number that may 

experience cost-to-revenue rations greater than 3%, a threshold that under EPA’s Regulatory 

Flexibility Assessment (RFA) that would preclude a finding of no significant impact.

NRECA surveyed our members and identified nine cooperatives operating 13 plants with one or 

more wastestreams affected by one or more of EPA’s preferred options. The costs of complying 

with any of these options would be substantial and would significantly exceed both the 1% and 

3% cost-to-revenue ratios above. Depending on the number of wastestreams affected at a plant 

and using the cost estimates developed by the Utility Water Act Group (UWAG):

 Cost for three plants potentially subject to Options 3a or 3b would be 4.8% to 13.1% of 

annual revenue.

 Costs for the 10 plants potentially subject to Option 3 would be 2.5% to 17.8% of annual 

revenue.

 Costs for 13 plants potentially subject to Option 4 would be 1.7% to 17.8% of annual 

revenue.

NRECA agrees with SBA that EPA’s certification of “no significant economic impact on small 

entities” lacks a factual basis, especially since EPA has withheld the underlying data supporting 

this determination. (See SBA comments section 1.B. Small Entity Costs Appear High, But the 

Record is Insufficient to Permit Analysis.)

Comment Response: 

EPA notes that SBA has revised the size standards applicable to entities within NAICS code 

2211 that generate, transmit or distribute electricity. The applicable size standards are no longer 

based on electricity sales, but are instead based on the number of employees. EPA conducted its 

RFA analysis for the final rule using these revised size standards. Chapter 8 of the RIA provides 

the details of how EPA identified the parent entity and categorized entities as small for the 

purpose of the RFA analysis. EPA identified a total of 29 to 49 cooperatives that own steam 

electric power plants to which the final ELGs apply. Of these only one cooperative was 
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estimated to incur compliance costs of at least 1 percent of revenue. No cooperative was 

estimated to incur costs of at least 3 percent of revenue.

Refer to comment EPA-HQ-OW-2009-0819-4477-A, Excerpt Number 1 (in comment code 28.e) 

and Excerpt Number 5 (in comment code 28.a) for EPA’s response to the concerns raised by 

SBA which were referenced by the commenter, including the convening of a SBREFA panel, 

lack of factual basis for the NO SISNOSE finding, and discussion of compliance costs and 

results for individual steam electric power plants.

Commenter Name: Dorothy Kellogg and Michael Leitman

Commenter Affiliation: National Rural Electric Cooperative Association (NRECA)

Document Control Number: EPA-HQ-OW-2009-0819-4565-A1

Comment Excerpt Number: 19

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The cost-effectiveness of environmental regulations is particularly important to cooperatives 

since, unlike investor owned utilities that can spread costs to their investors as well as their rate 

payers, the cooperative economic model means that the G&T costs are borne by their memberowners. Demographically, the member-owners of the distribution cooperatives that own the nine 

G&Ts potentially affected by this proposal are older (17% are over 65 compared to 13% 

nationally), many living on fixed incomes, and live in:

 Non-metropolitan counties (53% compared with 17% nationally);

 Households with incomes 17% lower than the national average;

 Mobile homes (16% compared to 6.5% nationally) which are generally less energyefficient.

Energy costs can be a significant expense for such households, and any increase needs to be well 

justified by improvements in environmental quality which EPA’s proposal does not provide.

Comment Response: 

The commenter asserts that “the cost-effectiveness of environmental regulations is particularly 

important to cooperatives” because “costs are borne by their member-owners.” For the role of 

cost-effectiveness in EPA’s decisions for the final rule, see response to DCN EPA-HQ-OW2009-0819-4655, Excerpt Number 27 in Comment Code 6.h.

Regarding the commenter’s statements about how the demographics of member-owners of their 

distribution cooperatives compare against national demographics, and that energy costs can be a 

“significant expense for such households,” EPA’s analysis of the proposed rule found that the 

estimated rate effects were uniformly low across the electric power market regions. For the final 
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rule, after considering public comments, EPA conducted a more detailed analysis to evaluate 

whether the small rate increases projected to result from the ELG will have significant impacts 

on households (see Section 7.4 in RIA document). This analysis shows that the incremental 

economic burden of the final rule on households is small both relative to income and relative to 

the baseline energy burden of households in different income ranges. Furthermore, while the 

incremental burden relative to income is relatively greater for low-income households, this 

impact is still relatively small (maximum of 0.44 percent) and may be further moderated by 

existing pricing structures. For more about impacts on cooperatives, see response to DCN EPAHQ-OW-2009-0819-4460-A1, Excerpt Number 1 (located in comment code 28.f)

Finally, EPA disagrees with the commenter’s assertion that the Agency failed to provide 

information regarding “improvements in environmental quality” expected under the final rule. 

The Environmental Assessment and Benefit Cost Analysis describe in detail the environmental 

improvements projected to result from implementation of the final ELGs, and the societal 

benefits that these improvements will generate, including to the very member-owners discussed 

by the commenter.

Commenter Name: Floyd Gilzow

Commenter Affiliation: Missouri Joint Municipal Electric Utility Commission (MJMEUC)

Document Control Number: EPA-HQ-OW-2009-0819-4576-A1

Comment Excerpt Number: 2

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Further we believe that EPA has not taken into full account that a significant percentage of 

municipal electric utilities with coal‐fired power plants are qualified under the Small Business 

Regulatory Enforcement and Fairness Act (SBREFA). We ask that EPA consider all of the 

SBREFA implications as this rulemaking process moves forward.

Comment Response: 

EPA disagrees with the commenter’s statement that EPA did not take “into full account that a 

significant percentage of municipal electric utilities with coal‐fired power plants are qualified 

under the Small Business Regulatory Enforcement and Fairness Act (SBREFA).” First, the 

commenter did not provide a basis for its claim regarding a “significant percentage of municipal 

electric utilities.” Chapter 8 of the RIA describes how EPA identified parent entities, determined 

which entities are small, and estimated impacts to small entities under the final rule. EPA 

presented the cost-to-revenue analysis for small entities, providing the number and percentage of 

small entities projected to incur compliance costs greater than or equal to 1 percent and 3 

percent. This analysis and interpretation of the results are consistent with RFA guidance to assess 

whether the final rule would have “a significant economic impact on a substantial number of 
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small entities” (SISNOSE), as well as the approach used by EPA in developing a number of 

other industry effluent limitations guidelines and standards.

Commenter Name: Jim Weeks

Commenter Affiliation: Michigan Municipal Electric Association (MMEA)

Document Control Number: EPA-HQ-OW-2009-0819-4767-A2

Comment Excerpt Number: 5

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA SHOULD SET A “SMALL GENERATING UNIT” THRESHOLD FOR

APPLICABILITY OF BAT/PSES REQUIREMENTS AT 100MW

The Michigan municipal entities commenting here are potentially subject to the EPA Steam 

Power ELG Rule as follows:

o The Grand Haven Board of Light & Power owns and operates a coal-fired electric 

generating unit with a nameplate capacity of 73 megawatts (MW) that uses a wet flue gas 

desulfurization system to control sulfur dioxide emissions.

o The Lansing Board of Water & Light owns and operates the coal-fired Eckert Station, 

which has three potentially affected units including Unit 4 (66MW), Unit 5 (68MW), and 

Unit 6 (66 MW), as well as another coal-fired plant known as Ericson Unit 1 (159MW).

o The Michigan South Central Power Agency (MSCPA) owns and operates a 55 MW coalfired electric unit. This MSCPA units uses an electro-static precipitator to manage 

particulates in the boiler exhaust.

All three of these Michigan municipal entities are “small entities” under the Small Business 

Regulatory Enforcement Fairness Act (“SBREFA”), 5 U.S. C. 801 et seq. as all they each sell 

less than 4 million megawatt hours of electricity annually, and all three are also defined as 

“small” under the Michigan Administrative Procedures Act 306, Section 24.240 (a section 

dealing with “reducing disproportionate economic impact of rules on small business”).

Moreover, these non-profit municipal entities and their small units are critical to their 

communities. Despite the small size of these systems and units, these municipal utilities are 

essential to electric reliability and energy supply diversity, and critical to the communities they 

serve. These public power systems provide energy to important community facilities such as law 

enforcement, hospital, and educational buildings. These facilities increase electric reliability and 

help avoid wholesale electric market price spikes. They provide reactive power to the 

transmission grid, and serve “load pocket” areas in which there are limited available options for 

securing power. For the systems commenting here, the plants subject to EPA’s proposed rule are 

the core of the electricity system in the region, with no readily available alternatives within the 

service territory – and if a plant shuts down or is made too expensive, it could cause a 
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community and business crisis. Localities like Grand Haven and MSCPA typically own and 

operate only one baseload plant, which means that municipal utilities do not have any flexibility 

to shift load among other units, as they would if they had a multi-unit system.

In addition to these public power systems being small entities, the units they own and operate 

that could become subject to the EPA ELG rules are relatively small compared to steam electric 

generating units in the power sector. According to the Energy Information Administration’s 2011 

assessment of “Operable Generating Units in the United States by State and Energy Source”, 

only 11% of coal-fired units are between 50MW and 100MW. Of those approximately 158 units 

between 50MW-100MW in size, around 50 are owned and operated by municipal “small 

entities” under federal SBREFA standards, or less than one-half of one percent (0.04 percent) of 

all operating coal-fired units.

It is clear, and EPA has recognized, that smaller entities and smaller units could bear 

disproportionate impacts from one-sized-fits-all, technology-forcing requirements. These small 

municipal systems have smaller plants, and control technology costs impose disproportionate 

impacts because of diseconomies of scale, because these systems have smaller customer bases 

upon which to pass the costs of controls, and because these municipalities have more limited 

capital financing options as compared to large, investor-owned utilities.

EPA has recognized such disproportionate impacts on small entities. For example, under the 

Clean Water Act effluent limitations and guidelines program established under 33 U.S.C. Section 

1311 et seq., EPA has recognized the importance of mitigating impacts on small entities and 

sources that have a relatively minor impact on public health and the environment. In its 1987 

regulation establishing effluent standards for organic chemicals and plastics and synthetic fibers, 

52 Federal Register 42, 521 (November 5, 1987), EPA reduced the impact on small businesses 

from effluent guidelines by creating a cut-off threshold for regulation specifically developed 

during the Regulatory Impact Analysis to reduce the impacts and threats of plant closure to small 

businesses. In this instance, EPA applied Best Practicable Control Technology Currently 

Available (“BPT”) rather than Best Achievable Technology (“BAT”). EPA undertook a threestep approach in that ELG rulemaking to identify impacts from the rulemaking, assess how those 

impacts could particularly affect small entities, and then develop regulatory alternatives for small 

entities. See 

http://water.epa.gov/scitech/wastetech/guide/ocpsf/upload/2007_10_22_guide_ocpsf_tddvol1.pdf.

EPA has also chosen to impose less stringent ELGs on small businesses in other rules, such as 

the effluent standards for meat and poultry products (69 Fed. Reg. 54,475, September 8, 2004),

EPA conveyed well how regulations could have disproportionate impacts on small businesses in 

the clean air context, a context that has impacted these Michigan public power units 

substantially. In its “Guidance on Mitigation of Impact to Small Business While Implementing 

Air Quality Standards and Regulations,” EPA Policy Guidance at www.epa.gov/ttn/oar/oarpg

(April 18, 1998), and in a Regulatory Impact Analysis for the 8-hour ozone standard, EPA 

recognized that:
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Small entities, all other factors being equal, generally have less capital available for purchase of 

add-on pollution control technology than large entities. In addition, the control cost per unit of 

production for small entities will likely be higher than for large entities due to economies of 

scale. Thus, control measures requiring the use of add-on control technology may cause small 

entities affected by State rules to experience disproportionate economic impacts compared to 

large entities if no strategies to mitigate potential small entity impacts are available for 

implementation by States. . . . Consequently, EPA is encouraging States to exercise regulatory 

flexibility for small entities when developing strategies to meet the standards adopted today. 

While some States may need to turn to small businesses for emission reductions, small 

businesses will likely be among the last sources the States will choose to control. States may 

consider controls on small businesses only if such businesses are a significant part of an area’s 

nonattainment problem and attainment cannot be reached through application of all available 

cost-effective measures to major sources. To the extent States consider controlling small 

businesses, EPA believes there are many ways States can mitigate the potential adverse impacts 

those businesses might experience. For example, States could choose to exempt or apply less 

stringent requirements to small businesses . . .. States could also extend the effective date for 

control requirements for small businesses . . . States could also choose to apply control 

requirements to other businesses first, before requiring them for small businesses.1

MMEA and Michigan public power are very pleased that EPA, in this proposed Steam Power 

ELG rule, has recognized the potentially significant impacts on small units that would be 

associated with meeting ELG requirements:

Small units are more likely to incur compliance costs that are disproportionately higher per 

amount of energy produced than those incurred by large units because they are not as able to take 

advantage of economies of scale. . . . Moreover, the record demonstrates that the amount of 

pollutants collectively discharged by small generating units is a very small portion of the 

pollutants discharged collectively for all steam electric power plants (e.g., less than 1 percent 

under Option 3). As a result, setting BAT limits equal to BPT for existing steam electric 

generating units with a capacity of 50 MW or less will have little impact on the pollutant 

removals for the overall rule. . . . EPA currently proposes a threshold of 50 MW rather than 25 

MW because the proposed 50 MW threshold would do more to alleviate potential impacts. EPA 

recognizes that any attempt to establish a size threshold for generating units will be imperfect 

due to individual differences across units and firms. However, EPA believes that a threshold of 

50 MW or less reasonably and effectively targets those generating units that should receive 

different treatment based on the considerations described above. EPA requests comment on the 

proposed 50 MW threshold applicable to discharges of the wastestreams described under each of 

the preferred options, and as well as other possible thresholds for small units.

In a real example, consider what the potential impact of the steam electric ELG on small units 

could be by considering the Grand Haven Board of Light and Power. Grand Haven has an annual 

revenue stream/budget of approximately $34.4 million. With EPA’s estimated cost of annual 

compliance of up to $6,440,000 for units in the 50-100MW range, the 68MW Sims unit in Grand 

Haven would have annual compliance costs under the Steam Electric ELG of nearly 20 percent 

of the entire budget of this public power system. Taken alone, and certainly in combination 

with the other EPA regulatory challenges facing Grand Haven’s plant, it is likely that the plant 
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would close. This would leave Grand Haven without a baseload option to serve its customers and 

businesses.

1 Ozone Regulatory Impact Analysis at pp. 11-27, 11-28, 11-29.

Comment Response: 

Regarding the size classification of the three entities identified by the commenter, EPA notes that 

the size determination for municipalities is based on population, not electricity generation. For 

the final rule analysis, EPA used U.S. Census data for 2013 to determine whether government 

entities are classified as small (population of 50,000 or less) or not (population greater than 

50,000). Based on Census figures, the city of Lansing, MI is not a small entity. Both Grand 

Haven Board of Light & Power and Michigan South Central Power Agency (MSCPA) are 

considered small entities, based on 2013 Census populations for Grand Haven and for the towns 

served by MSCPA, respectively.

As the commenter recognized, EPA considered whether it would be appropriate to establish 

differentiated requirements in the final rule based on, among other things, generating unit 

size. Like the proposed rule, the final rule establishes certain differentiated requirements for 

existing oil-fired generating units and existing generating units with a nameplate capacity of 50 

MW or less. The requirements for these generating units, as well as the basis for establishing a 

size threshold of 50 MW, are explained in preamble Section VIII.C.12 and VIII.E. These 

differentiated requirements for existing “small” generating units are expected to reduce the 

potential impacts of the rule on small entities and municipalities.

In accordance with the Clean Water Act, EPA determined that the final rule is economically 

achievable for the steam electric power generating industry as a whole. The final rule is projected 

to have a minimal impact on the industry. In particular, the final rule is projected to result in a 

net reduction of 843 MW in generating capacity as of model year 2030, reflecting full 

compliance by all plants, which corresponds to a net effect of two generating unit (partial) 

closures and one plant (full) closure.

Finally, EPA appreciates the data offered by the commenter on potential impacts to the plant 

owned by Grand Haven Board of Light and Power. EPA’s considered this information in 

conducting the analyses for the final rule.

Commenter Name: Theresa Pugh

Commenter Affiliation: American Public Power Association (APPA)

Document Control Number: EPA-HQ-OW-2009-0819-5140-A2

Comment Excerpt Number: 2

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

APPA also notes that a significant percentage of electric utilities with coal-fired power plants are 

qualified under the Small Business Regulatory Enforcement and Fairness Act (SBREFA). APPA 

asks EPA to consider the SBREFA implications of this rulemaking. While no SBREFA Small 

Entity Representative (SER) panel was convened on this important rulemaking, APPA believes 

that there are ways that the EPA could address small entity concerns about costs, operational 

conditions, and setting reasonable regulatory deadlines that do not harm the integrity of the 

CWA and the Effluent Limitations Guidelines (ELG) program. APPA disagrees with EPA’s 

certification in the proposed rule that the proposal will not have a significant economic impact on 

small entities under the Regulatory Flexibility Act (RFA) EPA should have convened a Small 

Business Regulatory Fairness Act (SBREFA) panel.

Comment Response: 

Refer to comment EPA-HQ-OW-2009-0819-4477-A, Excerpt Number 1 (in comment code 28.e) 

and Excerpt Number 5 (in comment code 28.a) for EPA’s response to the concerns raised by 

SBA which were referenced by the commenter, including the number of plant owners quantified 

under SBREFA, convening of a SBREFA panel, lack of factual basis for the NO SISNOSE 

finding, and discussion of compliance costs and results for individual steam electric power 

plants.

Regarding ways that the EPA could address small entity concerns, as explained in the preamble 

to the final rule, the differentiated BAT/PSES requirements for oil-fired generating units and 

units of 50 MW or less will alleviate some of the concerns raised by small entities by reducing 

the number of small entities incurring costs to meet the ELG requirements. Regarding regulatory 

deadlines, as described in the preamble for the final rule, as part of the consideration of the 

technological availability and economic achievability of the BAT limitations in the rule, EPA 

considered the magnitude and complexity of process changes and new equipment installations 

that would be required at facilities to meet the rule’s requirements. Where BAT limitations in 

this rule are more stringent than previously established BPT limitations, those limitations do not 

apply until a date determined by the permitting authority that is as soon as possible beginning 

November 1, 2018 (approximately three years following promulgation of this rule), but that is 

also no later than December 31, 2023 (approximately eight years following promulgation). See 

Sections VIII and XVI of the preamble to the final rule for details on the timing of 

implementation of the final rule.

Commenter Name: Theresa Pugh

Commenter Affiliation: American Public Power Association (APPA)

Document Control Number: EPA-HQ-OW-2009-0819-5140-A2

Comment Excerpt Number: 41

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

EPA Certification of No Significant Economic Impact on Small Entities Lacks a Factual 

Foundation and Transparency, and Appears to be Incorrect

The agency certifies that this proposal will not have significant economic impact on a substantial 

number of small entities.5 The same analysis showed some significant costs for a large fraction 

of plants owned by municipalities, of unknown size. Given the hundreds of small entity owners 

that could be affected this number is too low. Therefore, EPA should have convened a SBREFA 

panel.

This analysis, found in Chapter 8 of the May 2013 Regulatory Impact Analysis (RIA) does not, 

in our view, comply with the RFA requirements to provide a “statement providing the factual 

basis for such certification”6because the agency has withheld the underlying data supporting this 

determination. To our knowledge EPA has not revealed which plants will have compliance costs,

which plants with costs have small entity owners, and what those costs are, or the revenues that 

such plants have to address those costs. This makes it impossible to verify EPA’s underlying 

data, estimated values and calculations. APPA does not have the knowledge to identify these 

plants or estimate these costs without record information. EPA would likely not be revealing 

confidential business information (CBI) about these or other plants as long as it provided 

information in some redacted form. Model plant costs would adequately serve commenters’ 

needs. EPA should identify the plants with costs, by plant ID, and provide the approximate costs, 

revenues, or at least electric generation rates. This data should be fairly readily available for 

virtually all plants, which should allow for the cost/revenue comparison to be calculated and 

compared with EPA evaluation.

5

78 Fed. Reg. 34432, 34530 (June 7, 2013)

6 U.S.C § 605(b).

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4477-A1, Excerpt Number 23
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28.f. Econ – Electricity rate and household impacts

Commenter Name: R. W. Greene

Commenter Affiliation: Mercatus Center at George Mason University

Document Control Number: EPA-HQ-OW-2009-0819-3411-A1

Comment Excerpt Number: 9

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Many calculations in the analysis supporting the regulatory proposal are so poorly carried out 

that they are misleading.

 One example of poor calculation, concerning the estimation of electricity demand by 

households:

To calculate average annual electricity sales per household, EPA divided the total quantity of res

idential sales...for 2009 in each... region by the number of households in that region...For this 

analysis, EPA assumed that the average quantity of electricity sales per household by NERC 

region would remain the same in 2014 as in 2009.9

Why make this assumption? It is most unlikely that electricity consumption would show that 

pattern. This is just a simple, although important, element in the body of analysis, which is 

fatally flawed by poor quantification.

9 EPA, Regulatory Impact Analysis, Section 7.3.1.

Comment Response: 

EPA cannot respond to the commenter’s general claim that “many calculations” in the Agency’s 

analysis “are so poorly carried out that they are misleading” because the statement lacks any 

specificity that could serve as the basis for a response.

EPA disagrees with the commenter’s statement that assuming that electricity sales per 

household, by NERC region, would remain the same in 2014 as in 2009 makes the resulting 

electricity rate impact analysis “fatally flawed by poor quantitation.” While EPA acknowledges 

that there is some uncertainty in the electricity rate impact analysis due to the use of historical 

residential consumption data to infer future residential consumption, EPA used the best data 

available for its analyses of the final rule. For the electricity rate impact analysis, EPA used 

residential consumption data from the U.S. Department of Energy’s Energy Information 

Administration (EIA) Form EIA-861. At the time EPA conducted the analysis of the proposed 

rule, the most recent data available was for 2009. For the final rule, EPA updated the information 

to use the most recent values, which are for 2012. EIA publishes separate projections of total 

residential consumption by household at the national-level, but not at the regional-level or statelevel. EPA did not identify alternate projections of future residential consumption by NERC 
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regions and determined that making such projections would introduce additional and 

unnecessary uncertainty in the analysis. EPA notes that the commenter also did not provide a 

recommended alternative source of future residential consumption.

Furthermore, the data show that assuming level residential consumption data is reasonable. For 

example, EIA data for the 2014 Annual Energy Outlook (AEO) projects a declining trend in 

residential electricity consumption per household at the national level, with a total decline of less 

than 4 percent between 2012 and 2040 (See Annual Energy Outlook 2014: Reference case; DOE 

2014, available at http://www.eia.gov/forecasts/aeo/MT_residentialdemand.cfm). The projected 

annual electricity demand for the average household will be 11.6 MWh in 2040, which is very 

close to the 11.3 MWh reported in the 2009 Residential Energy Consumption Survey. While 

regional patterns may differ from the national trend, EPA concluded that the using 2009 

residential consumption data in estimating 2014 electricity rate impacts is a reasonable 

assumption and that the resulting analysis provides an informed assessment of the impacts of the 

final ELGs on rate payers. Likewise, EPA concluded that using the updated 2012 data to 

estimate electricity rate impacts in 2015 for the final rule is also reasonable.

EPA notes that the electricity market analyses conducted using the Integrated Planning Model 

(see Chapter 5 in the RIA document) incorporate demand projections from the 2013 Annual 

Energy Outlook, as well as other projected changes affecting the electricity market (generation 

capacity, environmental regulations, etc.). These analyses also show small impacts from the final 

rule across the range of metrics analyzed, including production costs and wholesale electricity 

prices.

Commenter Name: R. W. Greene

Commenter Affiliation: Mercatus Center at George Mason University

Document Control Number: EPA-HQ-OW-2009-0819-3411-A1

Comment Excerpt Number: 13

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

 It is difficult to unearth some of the important conclusions in this regulatory proposal. For 

example, it will cost the average household between nothing and $7.22 on an annual 

electricity bill, depending on location and exactly what is done. Why can't this sort of 

information be more prominently recorded?

Comment Response: 

EPA disagrees with the commenter that “important conclusions” are “difficult to unearth” in the 

rulemaking record, including information about impacts on an average household electricity bill. 

The results of EPA’s analyses are prominently featured in the preamble for both the proposed 
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and final rules, and EPA’s analysis of impacts on residential electricity prices is further discussed 

in detail in Chapter 7 of the RIA report.

For the final rule, as detailed in the RIA, EPA estimated that the annual electricity bill of an 

average household will increase between $0 and $2.67, depending on the region, with the 

average U.S. ratepayer seeing an increase of $1.42 per year (Table 7-3; Option D). This estimate 

is based on a conservative assumption of 100 percent pass-through of compliance costs to 

electricity prices and, to the extent that some plants are not able to pass compliance costs onto 

consumers, is an overstatement of the potential impact of the final rule.

Commenter Name: Leonard F. Hopkins

Commenter Affiliation: Southern Illinois Power Cooperative (SIPC)

Document Control Number: EPA-HQ-OW-2009-0819-4309-A1

Comment Excerpt Number: 16

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Southern Illinois Power Cooperative believes that curtailing economic costs is perhaps the most 

significant issue to consider in addressing the nation’s energy and emission control 

objectives. The nation is still suffering through one of the worst economic downturns since the 

Great Depression. Most sectors of the economy are facing rising costs and lower economic 

output. It is simply not appropriate to institute a regulatory program at this time that would 

impose even higher energy costs on American businesses and consumers.

As a consumer-owned electricity supplier, Southern Illinois Power Cooperative understands that 

reliable, affordable electricity has been one of the key drivers of economic growth and prosperity 

in this country. That fact must not be forgotten as the agency makes decisions on this and future 

potential rulemakings.

Comment Response: 

EPA disagrees with the commenter’s suggestion that the final rule will adversely affect the 

national economy. As reported in the RIA, the estimated total annual social cost of the final rule 

($479.5 million at a 3 percent discount rate) is very small in relation to the total economy – less 

than 0.01 percent of GDP in 2014. EPA determined that the final rule is economically achievable 

for the steam electric industry as a whole. In particular, the final rule is projected to result in a 

net reduction of 843 MW in steam electric generating capacity (0.2 percent of the baseline 

capacity) as of model year 2030, reflecting full compliance by all plants, which corresponds to a 

net effect of two generating unit (partial) closures and one plant (full) closure. EPA assesses that 

these retirements are inconsequential relative to total national and regional generating capacity. 

Furthermore, these retirements are offset by increased capacity for other plants. As a result, the 

final rule will not significantly affect electric supply reliability – either nationally or by NERC 
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region. Furthermore, EPA estimated the potential increase in cost per unit of electricity sales for 

the U.S. under the final rule to be 0.013 cents, with costs by NERC region ranging from 0.000 

cents per kWh to 0.027 cents per kWh. This estimate is based on a conservative assumption of 

100 percent pass-through of compliance costs to electricity prices and, to the extent that some 

plants are not able to pass compliance costs onto consumers, is an overstatement of the potential 

impact of the final rule. Accordingly, EPA disagrees that the rule will effect economic recovery.

Commenter Name: Lisa C. Messinger

Commenter Affiliation: Vectren Corporation

Document Control Number: EPA-HQ-OW-2009-0819-4317-A1

Comment Excerpt Number: 1

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Vectren, through its utility subsidiary Southern Indiana Gas and Electric Company (SIGECO) 

is the owner operator of a vertically integrated electric utility with 1200 MWs of generating 

capacity headquartered in Evansville, Indiana. More specifically, Vectren owns and operates 

two coal-fired power plants1 and co-owns another electric generating unit2in southwest Indiana. 

Moreover, as an Indiana utility, Vectren's generating portfolio is predominantly coal-fired, and 

as such , Vectren's customers could be disproportionately impacted by a final rule that forces 

significant changes in the operation or the fly ash, bottom ash, and FGD wastewater systems. 

Thus Vectren's generating facilities, and more importantly- its ratepayers, may be significantly 

impacted by the proposed rules.

1 A.B. Brown Generating Station in Posey County and F.B. Culley Generating Station in Warrick

County

2 One-half of Unit 4 at Warrick Generating Station, Warrick County

Comment Response: 

EPA disagrees with the commenter that its “generating facilities, and more importantly – its 

ratepayers, may be significantly impacted” by the final steam electric ELGs. First, EPA 

determined that the final rule is economically achievable for the industry as a whole. The final 

rule will have little impact on the steam electric industry. In particular, the final rule is projected 

to result in a net reduction of 843 MW in steam electric generating capacity (0.2 percent of the 

baseline capacity) as of model year 2030, reflecting full compliance by all plants, which 

corresponds to a net effect of two generating unit (partial) closures and one plant (full) closure.
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Second, as part of both the proposed and final rule analyses, EPA evaluated the potential impacts 

of the rule on customers. As documented in the RIA, EPA’s analysis found minimal impact on 

electricity rates from the final rule. As reported in Chapter 7 of the RIA, EPA estimated the 

potential increase in cost per unit of electricity sales for the U.S. under the final rule to be 0.013 

cents, with costs by NERC region ranging from 0.000 cents per kWh to 0.027 cents per kWh. 

Costs in the ReliabilityFirst Corporation NERC region, where SIGECO operates, were estimated 

at 0.027 cents per kWh. This estimate is based on a conservative assumption of 100 percent passthrough of compliance costs to electricity prices and, to the extent that some plants are not able 

to pass compliance costs onto consumers, is an overstatement of the potential impact of the final 

rule.

In response to comments EPA received on the proposed ELG, the Agency also looked at the 

distribution of the impacts of the final ELG across households. This analysis shows that the 

incremental economic burden of the final rule on households is small both relative to income and 

relative to the baseline energy burden of households in different income ranges. Furthermore, 

while the incremental burden relative to income is relatively greater for low-income households, 

this impact is still relatively small (maximum of 0.44 percent) and may be further moderated by 

existing pricing structures (see Section 7.4 of the RIA for details).

Commenter Name: Lisa C. Messinger

Commenter Affiliation: Vectren Corporation

Document Control Number: EPA-HQ-OW-2009-0819-4317-A1

Comment Excerpt Number: 3

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Vectren is committed to sustainable and responsible operation of our coal fired units. This 

corporate decision, however, comes at a financial cost which our customers must bear. 

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4317-A1, Excerpt Number 1.

Commenter Name: Mark Thoma

Commenter Affiliation: Otter Trail Power Company

Document Control Number: EPA-HQ-OW-2009-0819-4446-A1

Comment Excerpt Number: 1

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

Otter Tail is concerned that the proposed ELG revisions could result in more costs for our 

ratepayers.

Comment Response: 

In response to the commenter’s concern that the final rule will result in “more costs for our 

ratepayers,” EPA conducted analyses that demonstrate that the final rule will have minimal 

impact on electricity rates. As part of both the proposed and final rule analyses, EPA evaluated 

the potential impacts of the rule on customers. As reported in Chapter 7 of the RIA, EPA 

estimated the potential increase in cost per unit of electricity sales for the U.S. under the final 

rule to be 0.013 cents, with costs by NERC region ranging from 0.000 cents per kWh to 0.027 

cents per kWh (for the scenario without CPP; the impacts are even smaller when considering the 

scenario with CPP). Costs in the MRO NERC region, where Otter Trail operates, were estimated 

at 0.014 cents per kWh. This estimate is based on a conservative assumption of 100 percent passthrough of compliance costs to electricity prices and, to the extent that some plants are not able 

to pass compliance costs onto consumers, is an overstatement of the potential impact of the final 

rule.

In response to comments EPA received on the proposed ELG, the Agency also looked at the 

distribution of the impacts of the final ELG across households. This analysis shows that the 

incremental economic burden of the final rule on households is small both relative to income and 

relative to the baseline energy burden of households in different income ranges. Furthermore, 

while the incremental burden relative to income is relatively greater for low-income households, 

this impact is still relatively small (estimated at 0.1 percent in North Dakota, which is within the 

service area of Otter Trail Power Company) and may be further moderated by existing pricing 

structures (see Section 7.4 of the RIA for details).

In response to comments EPA received on the proposed ELG, the Agency also looked at the 

distribution of the impacts of the final ELG across households. This analysis shows that the 

incremental economic burden of the final rule on households is small both relative to income and 

relative to the baseline energy burden of households in different income ranges. Further, while 

the incremental burden relative to income is relatively greater for low income households, this 

impact is still relatively small (estimated at 0.1 percent in North Dakota, which is within the 

service area of Otter Trail Power Company) and may be further moderated by existing pricing 

structures (see Section 7.4 of the RIA for details).

Commenter Name: John McManus

Commenter Affiliation: American Electric Power System (AEP)

Document Control Number: EPA-HQ-OW-2009-0819-4448-A1

Comment Excerpt Number: 84

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

Any costs that aren’t fully amortized will need depreciation adjustment to align with plant 

retirement dates, elevating the annualized cost impact of the rule. Aligning cost recovery with 

customers who receive the benefits of service is vitally important for regulatory commissions in 

order to not unfairly burden future customers with costs for which they do not receive any 

service benefit.

[...]

Additionally, EPA wrongly claims that the screening analysis makes a “counterfactual, 

conservative assumption of zero cost pass-through to customers.”48 While this position is less 

than conservative considering that recovery for environmental investment for utilities in 

regulatory proceedings is highly probable, it fundamentally neglects the consideration 

of downstream effects to customers that will inevitably result in higher electricity prices in a 

downtrodden economy and demonstrates that EPA further underestimates the real societal 

impact associated with this rule. Regulated entities are entitled to a fair return on their 

investment, and such a return will be borne by, and burden, customers in a much higher degree 

than EPA’s analysis describes. Such costs that are not considered in EPA’s cost-effective 

analysis underestimate the expected actual mitigation cost that will be charged to utility 

customers in any modeling considerations. Absent regulatory treatment, merchant customers will 

still bear the burden of this rule manifesting in higher electricity prices to cover the exorbitant 

costs associated with implementing these proposed guidelines.

5. Assessment of the Impacts in the Context of Electricity Markets

Based on AEP’s cost estimate, EPA has significantly underestimated the compliance costs of this 

rule. If EPA’s modeling underestimates the real costs borne by a utility’s customers in 

complying with this rule in its IPM modeling, there will be a greater number of incremental 

closures with associated reduction in overall generating capacity, likely supplanting lower-cost 

power with higher-cost power. EPA notes,49 that its key inputs for the model include the capital, 

annual fixed O&M, and annual variable O&M costs.

49 EPA Regulatory Impact Analysis, April 2013, at 6-8.

Comment Response: 

With respect to the commenter’s statement related to (1) the length of the depreciation period for 

some plants that may have a relatively short remaining useful life, and (2) analysis of impacts on 

consumers from the pass through of compliance costs from regulated entities to consumers to 

ensure fair returns, please see the response to DCN EPA-HQ-OW-2009-0819-4448-A1, Excerpt 

Number 70 (in comment code 28.b).
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In addition, with respect to the commenter’s statement regarding the need for “depreciation 

adjustment to align with plant retirement dates” in the cost analysis for the final rule, EPA 

recognizes that some plants may be set to retire within the next few years. The final rule accounts 

for announced plant retirements expected to occur before plants would have to meet the final 

limitations and standards. For BAT limitations that are more stringent than previously 

established BPT limitations, the final rule allows permit writers to establish a date on which the 

final limitations apply, which must be as soon as possible beginning November 1, 2018, but no 

later than December 31, 2023. EPA does not expect that plants that have announced closures 

within this period will incur any costs to meet the final ELGs.

Regarding the cost-effectiveness analysis, EPA notes that the calculation is based on total 

compliance costs. For the role of cost-effectiveness in EPA’s decision for the final rule, see DCN 

EPA-HQ-OW-2009-0819-4655, Excerpt Number 27 in Comment Code 6.h.

Regarding the analysis of impacts in the context of electricity markets, the commenter is correct 

in noting that the Integrated Planning Model (IPM) policy scenario results are based on the same 

ELG compliance costs used in other analyses (with necessary adjustments to make the 

compliance costs compatible with IPM, such as adjusting the dollar year). EPA revised 

compliance cost estimates for the final rule based on public comments and used these revised 

costs to analyze the impacts of the final ELGs on the electricity market overall, and on the steam 

electric generating units in particular. The results show small impacts across all metrics analyzed 

(see Chapter 5 of the RIA for details) and support EPA’s determination that the final rule is 

economically achievable (see preamble Section VIII.C.9 for discussion).

Commenter Name: Tom DeLawrence

Commenter Affiliation: PowerSouth Energy Cooperative

Document Control Number: EPA-HQ-OW-2009-0819-4460-A1

Comment Excerpt Number: 1

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

As a not-for-profit rural electric generation and transmission cooperative, PowerSouth was 

chartered to provide reliable electric service to our distribution cooperative member-owners at 

the lowest reasonable cost. In addition to being overwhelmingly smaller than most electric 

utilities, PowerSouth and other electric cooperatives operate under a different economic model 

from investor-owned and municipal utilities. PowerSouth is owned by the member distribution 

cooperatives we serve, which means our operating costs – including costs to comply with 

environmental regulations – are directly borne by cooperative members, mostly rural residential 

consumers, directly through increased utility rates. On a national scale, mean household income 

for rural electric cooperatives is 17% less than the U.S. average household income, with the 

average poverty rate for cooperatives being 10% higher than the national poverty rate. 

Additionally, cooperatives serve only 5.4 consumer-members per mile of electric line, compared 
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to the national average of investor-owned utilities of 34 consumers per mile of line. Largely 

because of this lower density, most cooperatives, including PowerSouth’s members, already have 

electricity rates higher than those of our nearest investor-owned utilities.

Comment Response: 

The commenter states that its operating costs, “including costs to comply with the environmental 

regulations” are directly borne by cooperative members, who are demographically different in 

terms of household income and location from the national average. EPA notes that the 

commenter provided no direct information or data showing that electric cooperatives, as an 

ownership category, would incur impacts under the final steam electric ELGs that are 

disproportionately greater than that of other ownership categories. EPA does not agree that the 

business profile of electric cooperatives in terms of a requirement to pass through compliance 

costs in electricity rates is somehow different from other categories of ownership in terms of 

potential for impacts as a result of the final rule. Much of the generating capacity to which the 

final rule applies (65 percent) continues to operate under a rate regulation framework, in which 

costs are passed forward in rate increases to electricity customers (see Section 2.5 in RIA 

document). Customers of electric cooperatives will experience similar rate effects to those 

experienced by the customers of regulated utilities and municipally owned generators that incur 

costs as a result of the final rule: both of these categories of generators will pass forward 

essentially all compliance costs to their customers. EPA also notes that estimated rate effects are 

uniformly quite low by electric power market region (see Chapter 7 in RIA document).

EPA also does not agree that electric cooperatives who may have “fewer” customers would be 

disproportionately impacted as a result of the final rule. EPA notes that the scale of compliance 

costs under the rule generally increases in an approximately proportional manner to the size of 

steam electric generating units and presumably the customer base that they serve. As a result, 

just because electric cooperatives have a smaller generation and customer base does not mean 

that their customers will incur disproportionately higher rate effects. In addition, the commenter 

points out that electric cooperatives have very low customer density on an areal basis. EPA does 

not agree that this operating profile would somehow lead to disproportionately higher rate 

effects. The final rule applies to steam electric generating units, not electric power distribution 

systems; customer density on an areal basis will have no effect on the costs incurred by those 

customers.

For the final rule, EPA found that electric cooperatives, like other categories of ownership for 

regulated facilities, will generally incur low costs relative to their baseline revenue. In particular, 

only one cooperative is estimated to incur costs of 1 percent or greater of revenue, and no 

cooperative incurs costs of 3 percent or greater (see Table 4-2 in RIA document); the remaining 

28 to 48 cooperatives that own steam electric power plants (92 to 97 percent) incur costs below 1 

percent of revenue. This finding is almost identical to the finding for all ownership categories, 

where EPA estimates that 96 to 98 percent of owners of regulated facilities will incur costs of 

less than 1 percent of revenue under the final rule. Based on this analysis, EPA does not agree 

that electric cooperatives, as an ownership category, will incur costs that are systematically 

higher than those of other ownership categories.
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Finally, EPA’s analysis found minimal effect on electricity rates from the final rule. As reported 

in Chapter 7 of the RIA, EPA estimated the potential increase in cost per unit of electricity sales 

for the U.S. under the final rule to be 0.013 cents per kWh, with costs of 0.019 cents per KWh in 

the SERC NERC region where the commenter operates (see Table 7-1). This estimate is based 

on a conservative assumption of 100 percent pass-through of compliance costs to electricity 

prices and, to the extent that some plants are not able to pass compliance costs onto consumers, 

is an overstatement of the potential impact of the final rule. In response to other comments EPA 

received on the proposed ELG, the Agency also looked at the distribution of the impacts of the 

final rule across households in different income ranges. This analysis shows that the incremental 

economic burden of the final rule on households is small both relative to income and relative to 

the baseline energy burden of households in different income ranges. Furthermore, while the 

incremental burden relative to income is relatively greater for low-income households, this 

impact is still relatively small (maximum of 0.44 percent) and may be further moderated by 

existing pricing structures (see Section 7.4 of the RIA for details).

Commenter Name: Tom DeLawrence

Commenter Affiliation: PowerSouth Energy Cooperative

Document Control Number: EPA-HQ-OW-2009-0819-4460-A1

Comment Excerpt Number: 89

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In addition to being overwhelmingly smaller than most electric utilities, PowerSouth and other 

electric cooperatives operate under a different economic model from investor-owned and 

municipal utilities.

Comment Response: 

See response to comments EPA-HQ-OW-2009-0819-4565-A1, Excerpt Number 19 (in comment 

code 29.e) and EPA-HQ-OW-2009-0819-4460-A1, Excerpt Number 1.

Commenter Name: Jay Hudson

Commenter Affiliation: Santee Cooper

Document Control Number: EPA-HQ-OW-2009-0819-4476-A1

Comment Excerpt Number: 4

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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In the proposal, EPA evaluated costs and determined that utilities should not have to increase 

electricity rates; however it appears that most utilities would have to increase rates in order to 

recover the incurred costs.Since we are a cost of service utility, all costs for compliance will be 

shared directly by our customers.

Comment Response: 

EPA disagrees with the commenter’s claim that, for either the proposed or final rule, EPA 

“determined that utilities should not have to increase electricity rates.” As reported in Chapter 7, 

EPA evaluated the impact of compliance costs on electricity rates assuming a worst case in 

which 100 percent of compliance costs would be passed through to consumers. Based on this 

analysis, EPA estimated an increase of 0% to 0.2% in electricity rates to residential consumers, 

depending on the region, and a national average increase of 0.11% (see Table 7-2 of the RIA; 

Option D). Therefore, while EPA acknowledges the commenter’s claim that the costs of 

compliance may be directly shared with customers, EPA’s analyses show that any resulting 

increase would be low.

Commenter Name: Vicki Card

Commenter Affiliation: Colorado Springs Utilities

Document Control Number: EPA-HQ-OW-2009-0819-4483-A1

Comment Excerpt Number: 16

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Since Colorado Springs Utilities is a non-profit entity, these combined costs will be passed along 

to our ratepayers.

Comment Response: 

EPA understands that some of the costs of compliance are passed on to consumers, depending on 

rate regulations, and that, in the case of Colorado Springs Utilities, the impact to consumers may 

be the full cost of compliance. As part of both the proposed and final rule analyses, EPA 

evaluated the potential impacts of the rule on customers. As documented in Chapter 7 of the RIA 

document, EPA’s analysis found that costs associated with the final rule will have a small effect 

on electricity rates. EPA estimated that the compliance costs correspond to increases in the 

average monthly household bill of $0.12 for the average U.S. household, and $0.01 for the 

average household in the WECC NERC region where Colorado Springs Utilities operate. This is 

based on an assumption that 100 percent of the compliance costs are passed on to consumers.
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Commenter Name: Michael G. Cashin

Commenter Affiliation: Minnesota Power (MP)

Document Control Number: EPA-HQ-OW-2009-0819-4484-A1

Comment Excerpt Number: 1

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

MP’s northern location and high percentage of industrial customers who operate around-theclock make MP a winter-peaking utility. Thirteen large power customers (requiring at least 10 

megawatts of generating capacity) purchase about half the electricity MP sells. Considering MPs 

high percentage of industrial customers who are high energy users and struggling to compete in a 

competitive global market economy, we are concerned that any further restrictions applicable to 

our facilities be implemented with reasonable timeframes and cost to minimize adverse impacts 

on our customers.

Comment Response: 

EPA acknowledges the commenter’s concern that the regulation may affect industrial energy 

consumers. EPA cannot share particular data on how MP’s operation and customers may be 

affected by the final rule since data supporting the analysis were classified as confidential 

business information but notes that, as part of the impact analysis reported in Chapter 7 of the 

RIA report, EPA estimated potential rate impacts by customer class for each NERC region. This 

analysis assumed that regulated facilities would pass through all of their compliance costs under 

electricity rate regulation procedures, which is not accurate for all States, and thus very likely 

overstates the potential rate impact of compliance outlays. For industrial customers, EPA 

estimated an average national increase of 0.21 percent, with the highest impact in the SERC 

region (0.34 percent). EPA assesses that these very small rate increases will have a minimal 

impact on industrial facilities, regardless of the amount of electricity they purchase.

With regard to the commenter’s statement that it is “concerned that any further restrictions 

applicable to our facilities be implemented with reasonable timeframes and cost,” EPA notes that 

the ELG rulemaking process provided significant advance notice to potentially affected entities 

to evaluate the potential impacts of any new ELG requirements on their operations. As described 

in the preamble for the final rule, EPA also provided considerable flexibility and time for facility 

owners to implement any changes to such operations to meet the final limitations and standards. 

The Agency specifically considered the timing of requirements for other environmental 

regulations in the ELG to provide affected plants ample time to consider their strategy to 

implement any needed changes. See Sections VIII and XVI of the preamble to the final rule for 

details on the timing of implementation of new requirements. Moreover, EPA notes that the final 

rule is affordable for the industry as a whole. See Section VIII.C.9 of the preamble.
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Commenter Name: Joseph G. Eutizi

Commenter Affiliation: San Miguel Electric Cooperative, Inc.

Document Control Number: EPA-HQ-OW-2009-0819-4485-A1

Comment Excerpt Number: 2

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

San Miguel has a significant interest in the outcome of this rulemaking. San Miguel’s lignite 

fired electric generating facility is a major source of electrical generation to our member 

cooperatives, under long term wholesale power contracts for 100% of the output of the San 

Miguel Generating Station. Being not-for-profit, San Miguel will be forced to pass along, to its 

consumer-owners, all costs of meeting any new requirements that may result from the 

implementation of this proposed rule.

As a member-owned electricity supplier, San Miguel understands that reliable, affordable 

electricity has been one of the key drivers of economic growth and prosperity in this country. 

This fact must not be forgotten as the EPA makes decisions on whether and how to regulate 

electric generating units under this and future potential rulemakings.

Comment Response: 

EPA understands that some regulated entities might pass compliance costs through to customers 

as electricity rate increases and accounted for this potential in analyzing the impacts of the final 

Steam Electric ELGs. EPA assessed the potential impact of increased ratepayer charges under 

the assumption that all costs will be passed through regardless of the regulated status or other 

considerations that could mitigate ratepayer impacts. Under this assumption, EPA found that the 

final rule would increase electricity costs to households by approximately 0.013 cents per kWh, 

representing an increase of $1.42 per year for the average U.S. household. For industrial and 

commercial consumers, EPA found that costs would increase by approximately 0.21 percent and 

0.14 percent, respectively, relative to baseline rates. Estimated increases are even smaller in the 

TRE region where San Miguel operates. EPA judges these projected increases to be minimal 

impacts to electricity customers.

See response to DCN EPA-HQ-OW-2009-0819-4460-A1, Excerpt Number 1 for a discussion of 

considerations specific to cooperatives.

In addition, EPA determined that the final rule is economically achievable for the steam electric 

industry as a whole and will have minimal effect on generating capacity. In particular, the final 

rule is projected to result in a net reduction of 843 MW in steam electric generating capacity (0.2 

percent of the baseline capacity) as of model year 2030, reflecting full compliance by all plants, 

which corresponds to a net effect of two generating unit (partial) closures and one plant (full) 

closure. EPA assesses that these retirements are inconsequential relative to total national and 

regional generating capacity. Furthermore, these retirements are offset by increased capacity for 
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other plants. As a result, the final rule will not significantly affect electric supply reliability –

either nationally or by NERC region.

Finally, EPA estimated that total annual costs of the final rule would be less than 0.01 percent of 

Gross Domestic Product (based on comparison of the estimated total annual cost in 2014 dollars 

to GDP for 2013). Given the very small cost of the final rule in relation to the total value of 

goods and services produced in the U.S. economy, EPA judges that the Steam Electric final rule 

will not materially impair performance of the nation’s economy.

Commenter Name: Quinlan J. Shea III

Commenter Affiliation: Edison Electric Institute (EEI)

Document Control Number: EPA-HQ-OW-2009-0819-4487-A1

Comment Excerpt Number: 126

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

To avoid and minimize such adverse consequences, any final steam electric ELG rule needs to 

meet three objectives: (1) it should be based on accurate, representative data and sound analyses; 

(2) it should include only cost-effective requirements; and (3) it should provide for flexible 

implementation and reasonable compliance deadlines. Such objectives will help to ensure net 

benefits, minimize unnecessary costs, and allow plant owners to make rational decisions taking 

into account all the new air, water, and solid waste regulations. Meeting these objectives will 

help to ensure that electricity rates remain reasonable and electricity supply and delivery remains 

reliable as the electric power industry transitions to a more modern, lower emissions 

fleet. Unfortunately, the proposed rule does not meet these objectivesy proposed a rule to 

control greenhouse gas emissions from electric utilities.

Comment Response: 

EPA generally agrees with, and views the final steam electric ELGs as meeting, the first and 

third “objectives” stated by the commenter – that the rule “be based on accurate, representative 

data and sound analyses” and that “it should provide for flexible implementation and reasonable 

compliance deadlines.” Regarding the second “objective,” cost-effectiveness, please see response 

to DCN EPA-HQ-OW-2009-0819-4655, Excerpt Number 27 in Comment Code 6.h. for the role 

of cost-effectiveness in EPA’s decisions for the final rule.

With respect to the commenter’s statement about basing the rule on “accurate, representative 

data and sound analyses,” the commenter did not provide any specific examples of where it 

thinks that the rule is not based on such data and analyses. EPA’s data sources and analytical 

methodologies are discussed in great detail elsewhere in the rulemaking record.
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With respect to the commenter’s statement that the final rule “should provide for flexible 

implementation and reasonable compliance deadlines,” EPA notes that the ELG rulemaking 

process provided significant advance notice to potentially affected entities to evaluate the 

potential impacts of any new ELG requirements on their operations. As described in the 

preamble for the final rule, EPA also provided considerable flexibility and time for facility 

owners to implement any changes to such operations to meet the final limitations and standards. 

The Agency specifically considered the timing of requirements for other environmental 

regulations in the ELG to provide affected plants ample time to consider their strategy to 

implement any needed changes. See Section VIII of the preamble to the final rule for details on 

the timing of implementation of new requirements.

Regarding the commenter’s statement about ensuring that “electricity rates remain reasonable 

and electricity supply and delivery remains reliable,” as noted in the proposed rule support 

documents, and now in the final rule support documents, the analyses for the rule clearly show 

that electricity rates will remain reasonable and that the ELG is not projected to cause supply and 

delivery reliability issues (see RIA for more details). The preamble to the final rule provides 

EPA’s justification for establishing the final limitations and standards, including its 

determination that the final rule is economically achievable.

Commenter Name: Steve Jackson

Commenter Affiliation: Alliant Energy Corporate Services, Inc.

Document Control Number: EPA-HQ-OW-2009-0819-4516-A2

Comment Excerpt Number: 21

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Alliant Energy has performed a high level impact evaluation of the proposed rule. The cost to 

comply with the proposed bottom ash requirements, and associated pond closure, are not 

insignificant and will have a considerable impact on our ratepayers.

Comment Response: 

The commenter does not provide data to quantify its claim that the costs of the final rule would 

be “not insignificant,” nor does the commenter provide an information supporting its claim that 

there would be a “considerable impact” associated with bottom ash requirements under the final 

rule. The final rule, which is based on Option D and (except for certain existing “small” and oilfired generating units) establishes a zero discharge requirement for bottom ash transport water, 

will have estimated annualized social costs of $479.5 million (at 3 percent discount). EPA 

determined that while these costs are not insignificant, they are economically achievable for the 

steam electric industry as a whole. The rule is projected to have minimal impacts on the industry. 

In particular, the final rule is projected to result in a net reduction of 843 MW in steam electric 

generating capacity (0.2 percent of the baseline capacity) as of model year 2030, reflecting full 
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compliance by all plants, which corresponds to a net effect of two generating unit (partial) 

closures and one plant (full) closure (see preamble Section VIII.C.9).

See responses to related comments regarding EPA’s assessment of the impacts of the final ELGs 

on ratepayers (e.g., DCN EPA-HQ-OW-2009-0819-3920-A1, Excerpt Number 156; EPA-HQOW-2009-0819-4460-A1, Excerpt Number 1). As detailed in these responses and in Chapter 7 of 

the RIA, the impact of the final ELGs on ratepayers is expected to be minimal.

Finally, EPA notes that the final rule establishes effluent limitations and standards for discharges 

of pollutants. It does not require “pond closure,” as the commenter states.

Commenter Name: Floyd Gilzow

Commenter Affiliation: Missouri Joint Municipal Electric Utility Commission (MJMEUC)

Document Control Number: EPA-HQ-OW-2009-0819-4576-A1

Comment Excerpt Number: 11

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

5. Finally the proposed rule does not appear to consider the cost to electric consumers for 

purchase of more expensive power during the time that units are not available because of retrofit. 

This is especially concerning due to the fact that this rule is planned to be implemented shortly 

after mandatory retrofits under the Mercury and Air Toxics Standards retrofit which may also 

boost the cost of interim electric power.

Comment Response: 

The final rule is not projected to result in any incremental generation downtime. The timing for 

implementation of the rule provides considerable flexibility for any changes that plants decide 

they need to make to meet the final limitations and standards. Section 7 of the TDD provides 

more details about the timing that may be required for the installation or conversion of certain 

equipment to meet the final limitations and standards.

Commenter Name: Kevin D. Frizzell

Commenter Affiliation: Owensboro Municipal Utilities (OMU) Elmer Smith Station (ESS)

Document Control Number: EPA-HQ-OW-2009-0819-4683-A2

Comment Excerpt Number: 13

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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All new costs due to the environmental regulations forthcoming will result in increased 

electricity rates for our customers.

Comment Response: 

For a response to the expected impact on electricity rates, see DCN EPA-HQ-OW-2009-0819-

5140-A2, Excerpt Number 16.

In response to the commenter’s concern about “all new costs due to the environmental 

regulations forthcoming,” EPA notes that it made every effort to appropriately account for other 

relevant rules in its many analyses for this rule. The preamble and supporting documents 

describe how EPA accounted for the effects of other rules, such as the Cooling Water Intake 

Structures rule for existing facilities, the Coal Combustion Residuals (CCR) rule, the Clean 

Power Plan (CPP) rule, and the Carbon Pollution Standard for New Power Plants (CPS) rule.

Commenter Name: Theresa Pugh

Commenter Affiliation: American Public Power Association (APPA)

Document Control Number: EPA-HQ-OW-2009-0819-5140-A2

Comment Excerpt Number: 16

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

All new costs due to the proposed rule (whether for effluent discharge controls or for waste 

management) might result in increased electricity rates. Public power or community-owned 

utilities pass through all costs to the consumer.

Comment Response: 

EPA understands that some of the costs of compliance are passed on to consumers, depending on 

rate regulations, and that in many cases the impact to consumers may be the full cost of 

compliance. As part of both the proposed and final rule analyses, EPA evaluated the potential 

impacts associated with the rule on customers. As documented in Chapter 7 of the RIA, EPA 

assessed the potential impact of increased ratepayer charges under the assumption that all costs 

will be passed through regardless of the regulated status or other considerations that could 

mitigate ratepayer impacts. Under this assumption, EPA found that the final rule would increase 

electricity costs to households by approximately 0.013 cents per kWh, representing an increase 

of $1.42 per year for the average U.S. household. For industrial and commercial consumers, EPA 

found that costs would increase by approximately 0.21 percent and 0.14 percent, respectively, 

relative to baseline rates. EPA judges these small cost increases as not likely to pose an undue 

burden on electricity customers.
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Commenter Name: Theresa Pugh

Commenter Affiliation: American Public Power Association (APPA)

Document Control Number: EPA-HQ-OW-2009-0819-5140-A2

Comment Excerpt Number: 53

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In the proposal, EPA evaluated costs and determined that utilities should not have to increase 

electricity rates. However, through our assessment of member utilities, we believe that most 

utilities will in fact have to resort to increasing electricity prices in order to recover the cost 

suffered. It would be difficult for a public power utility to avoid increasing rates to comply with 

additional regulations because there is no profit margin from which the additional compliance 

expenditures could come from. It would have to come from increased customer rates. APPA 

notes that EPA also asserts that the rulemaking only affects eight electric utilities that generate 

less than 100 MW. APPA does not know how EPA came to this conclusion. Perhaps EPA’s 

assumption distorts the overall costs and impacts, as well as minimizes the risk that electricity 

prices could be affected.

Comment Response: 

EPA disagrees with the commenter’s claim that EPA determined that utilities should not have to 

increase electricity rates. In fact, as discussed in the preamble and detailed in Chapter 7 of the 

RIA, EPA evaluated the impact of compliance costs on electricity rates assuming that 100 

percent of compliance costs would be passed through to consumers. Based on this analysis, EPA 

estimated an increase of 0.000 cents/kWh to 0.027 cents per kWh in electricity rates, depending 

on the region, with an average national increase of 0.013 cents/kWh. Therefore, while EPA did 

not determine that there would be no effect on electricity rates due to compliance with the final 

rule, EPA found that any impact would be low.

See response to DCN EPA-HQ-OW-2009-0819-5140-A2, Excerpt Number 108 (in comment 

code 28.a) regarding the commenter’s statement about utilities generating less than 100 MW.

Commenter Name: Theresa Pugh

Commenter Affiliation: American Public Power Association (APPA)

Document Control Number: EPA-HQ-OW-2009-0819-5140-A2

Comment Excerpt Number: 106

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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All new costs due to the proposed rule (whether for effluent discharge controls or for waste 

management) might result in increased electricity rates. Public power or community-owned 

utilities pass through all costs to the consumer.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-5140-A2, Excerpt Number 53.

Commenter Name: Thomas W. Easterly

Commenter Affiliation: Indiana Department of Environmental Management (IDEM)

Document Control Number: EPA-HQ-OW-2009-0819-5553-A2

Comment Excerpt Number: 9

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

While we believe the time for updating the steam electric ELG is long overdue, we also believe it 

is important for EPA to carefully consider the impact that these proposals will have on not only 

the environment and industry, but also on the rate payers. The buying power of rate payers is 

slowly eroding as their incomes remain steady while inflation slowly rises. It is, therefore, 

important at this delicate time of economic uncertainty to ensure that whatever approaches are 

adopted not only significantly improve the environment, but also do not harm the economy and 

jobs.

Therefore, we strongly urge EPA to develop a final rule that allows state environmental 

regulators to protect the environment while balancing the impact on consumers.

Comment Response: 

EPA conducted a number of analyses to support its determination that the final ELGs are 

economically achievable and to evaluate the potential impacts of the rule. The Regulatory Impact 

Analysis for the Effluent Limitations Guidelines and Standards for the Steam Electric Power 

Generating Point Source Category (RIA) (DCN SE05976) describes EPA's analysis of the 

impacts of the final ELGs on the steam electric generating industry, rate payers, and 

employment. Analysis of the impacts of the final ELGs on the environment are described in the 

Environmental Assessment for the Effluent Limitations Guidelines and Standards for the Steam 

Electric Power Generating Point Source Category (EA Report) (DCN SE04527).

As summarized in related responses, the estimated impacts of the final rule are low whether the 

Agency considered impacts on rate payers (e.g., see DCN EPA-HQ-OW-2009-0819-3920-A1, 

Excerpt Number 156 in comment code 28.f), or on the economy overall (see DCN EPA-HQOW-2009-0819-4309-A1, Excerpt Number 16).
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28.g. Econ – Employment impacts

Commenter Name: Paul Carpmone

Commenter Affiliation: Tampa Electric Company (TEC)

Document Control Number: EPA-HQ-OW-2009-0819-4520-A2

Comment Excerpt Number: 14

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

We note that this is only one of a number of very significant rulemaking initiatives that EPA has 

chosen to engage in nearly simultaneously which if adopted will result in an unprecedented 

burden on the utility industry significantly increasing the cost of producing electricity and, 

therefore, the costs to our customers. Florida and the rest of the country are continuing to 

struggle due to the slow pace of economy recovery and continued unemployment, and these 

initiatives will only serve to worsen the situation. EPA should consider staggering these 

proposals to delay the potential adverse economic impact that they will produce. This would 

provide the utility industry with an opportunity to commit its resources to cost effectively 

providing necessary energy at a time of economic distress, rather than expending significant 

resources responding to regulatory initiatives.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4183-A2, Excerpt Number 22 (Comment Code 

28.j) regarding considerations of the cumulative impacts of regulations affecting the steam 

electric power generating industry and timing of the final ELGs.

Regarding the impacts of final ELG on electricity rates and, by extension, on the total economy, 

EPA found the final rule will result in only small effects on electricity rates nationally, and at the 

level of the NERC region. For the final rule, under an assumption that all compliance costs 

would be passed through to consumers in electricity rate increases, EPA estimated that rates 

would increase by approximately 0.013¢ per kWh across the United States. On a percentage 

basis, the estimated rate increases are comparably small, both nationally and by region: the 

estimated percentage increase in electricity rates averages 0.14 percent nationally, with the 

largest increase by region being 0.27 percent. EPA found that these increases are also low.

In terms of broader economic effects, EPA expects minimal impact from the final rule. Given the 

low cost of the rule in relation to the total economy (less than 0.01 percent of GDP in 2013), 

EPA concludes that the final rule will not adversely affect overall economic activity.

Regarding adverse impact due to compressed and overlapping compliance periods from multiple 

regulations, EPA addressed this concern specifically in determining the appropriate 

implementation dates for the final rule. See the preamble to the final rule. In addition, as 

discussed in the final RIA, the resource requirements of the final rule – in terms of estimated 

capital outlay, near-term capacity effects, and ongoing operating costs and effects – are relatively 
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small in themselves. As a result, facilities should not face unreasonable challenges in obtaining 

financial capital to comply with the Steam Electric ELG even as they may also be meeting 

requirements from other environmental regulations at approximately the same time.
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28.h. Econ – Environmental justice

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 52

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

And, you know, these are never found near wealthy communities. They tend to be those 

communities that are least able to fight back, who don't have the political power. So by 

promulgating zero waste effluent requirements for coal plants, you and we can create justice for 

many communities across this land that have been denied it for far too long, communities that 

have every right to expect relief from the awful legacy of dirty coal and dirty water. The time is 

now, and if not now, when?

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-5084-A1, Excerpt Number 3.

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 92

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

These power plants contribute over half of all toxic pollutants to surface waters by industrial 

categories regulated by the Clean Air Act. We are most concerned about the coal waste going to 

public water treatment, but also to the lead, mercury, arsenic, selenium, and other minerals which 

become toxic pollutants, causing cancers and neurological damage among Hispanics and others 

who reside in industrial communities near these plants.

Of growing concern to our organization is the disparate impact on the health and quality of life 

that pollutants from coal fired power plants have on Hispanics. We have advocated persistently 

to eliminate health disparities among this population, and four of the five leading causes of 

death cancer, heart disease, and diabetes have all been linked to these toxic pollutants.
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Without strong and effective Effluent Limitation Guidelines from EPA, harmful substances will 

continue to pollute the waterways of communities hampered by low socioeconomic health 

outcomes, decreased productivity of our students and workers, and the health of all Americans.

Comment Response: 

The final rule establishes the first nationally applicable limits on the allowable levels of toxic 

metals and other pollutants for much of the wastewater discharged by steam electric power 

generating plants. EPA’s environmental assessment and benefit-cost analysis documents (see 

DCNs SE04527 and SE05977 in the docket) demonstrate human health benefits associated with 

the final rule including reduced incidence of cancer, neurological effects, and cardiovascular 

disease, and other human health impacts from pollutant discharges.

While pollutants in steam electric power plant discharges have broad ecological and human 

health impacts, EPA recognizes the specific concerns expressed by the commenter about the 

existing health impacts on communities around steam electric power plants, particularly with 

respect to communities with environmental justice concerns (including those of Hispanic origin). 

As part of the final rule analysis, EPA revised its analysis of environmental justice concerns 

associated with steam electric power plant discharges to provide a more detailed understanding 

of the baseline impacts on potentially disadvantaged communities and of how benefits of the 

ELG are distributed among communities (see Chapter 14 of the BCA for the final rule).

The final rule analysis shows that minorities, including people of Hispanic origin, account for 

34.4 percent of the population that may be exposed to steam electric pollutants via self-caught 

fish consumption. 13.9 percent of affected individuals are below the poverty threshold, and 6.5 

percent are both minority and below the poverty threshold. Overall, 41.9 percent of potentially 

exposed individuals are minority, below the poverty threshold, or both.

As described in the BCA, EPA also assessed the share of IQ-point-based health benefits 

attributable to these communities, and found that while individuals who are both poor and 

minority account for 6.5 percent of the population, they account for 7.8 and 7.5 percent of the 

estimated lead and mercury IQ benefits of the final regulation, respectively. The individuals who 

are poor or minority account for 35.3 percent of the population but 36.1 percent of the mercury 

IQ benefits.

These results show that poor and minority communities (including poor and minority populations 

encompassing Hispanic individuals) are expected to receive benefits from the final ELGs that is 

proportional with, or exceed, their representation in the affected populations.

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 110
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External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The water in many low income communities primarily of color contain arsenic, nitrates, and 

other chemicals because the fertilizers, animal waste, and pesticides on agribusiness farms would 

run off into the groundwater that became tap water. And in communities where the average 

annual income was less than 15,000 a year, families were paying double for water, for the tap 

water they used to wash clothes and shower and for the bottles that they bought for drinking, 

cooking, and brushing their teeth. And why this is relevant to this is that these communities in 

Central Valley face a double threat to their drinking water. One is from agribusiness, and 

another one is from coal.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-5084-A1, Excerpt Number 3 and EPA-HQ-OW2009-0819-3920-A1, Excerpt Number 92.

EPA notes that the final ELGs apply to steam electric power generating plants. Discharges from 

agribusinesses are outside the scope of this rulemaking.

For a response to comments related to groundwater, see response to DCN EPA-HQ-OW-2009-

0819-4657-A6, Excerpt Number 1 (Section 25.b.ii).

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 120

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Water is at the heart of our environmental problems and priorities. Its management and 

consumption play a crucial role in health, agriculture, and ecology. For decades, the self evident 

worth has been ignored, and water pollution mismanagement afflict enumerable communities, 

particularly Environmental Justice communities. Chronic pathologies related to dehydration and 

water pollution are widespread. Despite the worth of water, it is often treated with that little care 

of caution.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-5084-A1, Excerpt Number 3
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Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 127

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Our coalition partners are deeply concerned about the continued adverse impacts that harmful 

pollutants, particularly from coal fired power plants, are causing on Hispanic and other 

communities of color.

According to the 2000 Census, nearly 40 percent of Latinos live within 30 miles of a power 

plant, and that is expected to increase. As a consequence, Latino communities are 

disproportionately impacted by the toxic pollutants that are discharged from these dirty power 

plants both in the air and into our water.

1.3 million Hispanics nationwide actively participate in fishing as a recreational, social, or family 

activity. However, much of the Latino community is unaware that invisible toxic chemicals such 

as mercury, PCBs, and other toxic substances could be present in the water and the fish that they 

eat.

In a number of studies, it's been shown that Latino sport and commercial anglers catch a variety 

of sport fish and consume fish that they catch more frequently than non Latino consumers. At 

the same time, Hispanic and other minorities are less likely than non Hispanics to be aware of 

fish consumption advisories. This is yet another compelling reason why the EPA should enact 

the most stringent Effluent Limitation Guidelines possible to protect families from exposure to 

harmful pollutants through their water and aquatic activities.

It is because Latino and other traditionally underrepresented communities are so 

disproportionally impacted by these harmful pollutants that NLCCC must urge the EPA to adopt 

the strictest possible wastewater guidelines that will adequately protect our communities, both 

for pretreatment standards for coal waste going to public water treatment facilities and for all 

discharges generally.

Comment Response: 

EPA recognizes the concerns expressed by the commenter about existing health impacts on 

communities around steam electric power plants, and agrees that ethnicity plays a role in fishing 

habits, fish consumption rates, and behavioral changes in response to fish consumption 

advisories (FCAs). Differences in these factors between Latino and other anglers may result in 

an elevated health risk to anglers from the Latino community from exposure to the toxic 

chemicals in fish tissue under the baseline conditions and these anglers will thus derive 
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comparatively greater benefits from the final rule. As described in Chapter 3 of the BCA for the 

final rule, EPA distinguishes and accounts for differences in fishing behaviors across ethnic 

groups, where possible given available data.

For more on results of the EJ analysis relevant to latino communities, see response to DCN EPAHQ-OW-2009-0819-3920-A1, Excerpt Numbers 92 and 198 (in comment code 29.c).

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 130

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Today, nearly 80 percent of the outflow from coal fired power plants is responsible for virtually 

unlimited discharges of these toxic metals and other chemicals.

Further, as air pollution control technologies improve, these discharges will only 

increase. Without effective rules on power plant water pollution, the generation of this toxic 

waste will continue with ongoing harmful, disproportionate, and environmental justice effects on 

nearby communities, many of whom are Latino.

Comment Response: 

EPA agrees with the concern expressed by the commenter regarding discharges from steam 

electric power plants and expected increases due to changes in air pollution control technologies. 

According to EPA analysis, steam electric power plants discharges account for over one-third of 

all toxic pollutants discharged into surface waters by industrial categories currently regulated 

under CWA. This is lower than the 80 percent suggested by the commenter, but these pollutant 

discharges nonetheless present a serious public-health concern and cause severe ecological 

damage, as demonstrated by numerous documented impacts, scientific modeling, and other 

studies. See the Environmental Assessment for the Effluent Limitations Guidelines and Standards 

for the Steam Electric Power Generating Point Source Category (EA Report) (DCN SE04527)

for the final rule for discussion of the environmental effects of steam electric power plant 

discharges.

For more on results of the EJ analysis relevant to Latino communities, see response to DCN 

EPA-HQ-OW-2009-0819-3920-A1, Excerpt Number 92.
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Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 134

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

I'm concerned with the Proposed Rule under review at this afternoon's hearing, including the 

pretreatment standard for coal waste. There is an increasing body of research that continues to 

highlight health disparities of economically disadvantaged communities that reside near coal 

fired power plants. The NAACP also has an excellent Coal Blooded report, C-o-a-l, that you 

may want to refer to.

The chemicals that are discharged from coal plants drastically impact the health and quality of 

life of nearby residents who are already disproportionately affected by asthma, heart disease, 

cancer, diabetes, and other chronic diseases, which are all preventable.

Comment Response: 

EPA recognizes the concerns expressed by the commenter about existing health impacts on 

communities around steam electric power plants, particularly with respect to low income and 

minority populations. The Agency has reviewed the NAACP report cited by the commenter, as 

well as other studies. As part of the final rule analysis, EPA revised its analysis of environmental 

justice concerns associated with steam electric power plant discharges to provide a more detailed 

understanding of the baseline impacts on potentially disadvantaged communities and of how 

benefits of the ELG are distributed among communities. Also see answer to related comments 

(e.g., DCN EPA-HQ-OW-2009-0819-5084-A1, Excerpt Number 3) and Chapter 14 of the BCA 

for the final rule for details.

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 138

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In Los Angeles, our mayor recently announced that the city would no longer rely on coal for 

energy needs, and while this is a step in the right direction, coal plants continue to operate 

around the country, and often their air and water pollution disproportionately affect underserved 

and poor communities.
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Comment Response: 

See answer to comment EPA-HQ-OW-2009-0819-5084-A1, Excerpt Number 3.

Commenter Name: Disha Banik

Commenter Affiliation: Private Citizen

Document Control Number: EPA-HQ-OW-2009-0819-3920-A10

Comment Excerpt Number: 2

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The water in many low income communities. primarily of color, contained arsenic, nitrates, and 

other chemicals because the fertilizers, animal wastes, and pesticides on agribusiness farms

would run off into the groundwater that became tapwater. In communities where the average 

annual income was less than $15,000, families were paying double for water: for the tap water 

they use to wash clothes and shower, and for the bottles they bought for drinking, cooking, and 

brushing their teeth.

These communities in Central Valley face a double threat to their drinking water. One from 

agribusiness and another from coal.

Comment Response: 

See answer to comments EPA-HQ-OW-2009-0819-3920-A1, Excerpt Number 110 and EPAHQ-OW-2009-0819-5084-A1, Excerpt Number 3.

Commenter Name: Dorothy Kellogg and Michael Leitman

Commenter Affiliation: National Rural Electric Cooperative Association (NRECA)

Document Control Number: EPA-HQ-OW-2009-0819-4565-A1

Comment Excerpt Number: 4

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The cost-effectiveness of environmental regulations is particularly important to cooperatives 

since, unlike investor owned utilities that can spread costs to their investors as well as their rate 

payers, the cooperative economic model means that the G&T costs are borne by their memberowners. Demographically, the member-owners of the distribution cooperatives that own the nine 
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G&Ts potentially affected by this proposal are older (17% are over 65 compared to 13% 

nationally), many living on fixed incomes, and live in:

 Non-metropolitan counties (53% compared with 17% nationally);

 Households with incomes 17% lower than the national average;

 Mobile homes (16% compared to 6.5% nationally) which are generally less energyefficient.

Energy costs can be a significant expense for such households, and any increase needs to be well 

justified by improvements in environmental quality which EPA’s proposal does not provide.

Comment Response: 

See response to comments EPA-HQ-OW-2009-0819-4565-A1, Excerpt Number 19 (comment 

code 28.e) and EPA-HQ-OW-2009-0819-4460-A1, Excerpt Number 1 (comment code 28.f)

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 22

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA Must Revise its Environmental Justice Analysis to Evaluate Impacts to Communities 

Surrounding Power Plants and to Consider the Impacts of its Weakest Options. EPA failed 

to conduct the required inquiry into whether its regulatory options have a disproportionately high 

and adverse health or environmental impact on communities of color and low-income 

populations. The Agency’s cursory inquiry focused on only one adverse impact of pollution 

discharges (consumption of contaminated fish) and failed entirely to evaluate the health and 

environmental harms suffered by communities proximate to the source of pollution. The 

abbreviated inquiry does not satisfy Executive Order 12989 nor is it consistent with the 

environmental justice assessment conducted by the Agency for its 2010 proposed CCR rule on 

identical pollution sources. EPA’s indefensibly narrow environmental justice analysis represents 

substantial noncompliance with the Executive Order that must be rectified.

Comment Response: 

EPA agrees that the EJ analysis conducted to inform the proposed rulemaking did not provide 

detailed information on the relative effects of the regulatory options on EJ communities. While 

the approach used for the proposed rule analysis was similar to that EPA has taken on other 

rules, EPA recognizes that more could be done to explore how different communities are 

affected by steam electric power plant discharges and how the rule options serve to redress 
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environmental justice issues. Accordingly, as part of the final rule analysis, EPA significantly 

revised its analysis of environmental justice concerns associated with steam electric power plant 

discharges to provide a more detailed understanding of the baseline impacts on disadvantaged 

communities, and of how benefits of the ELG are distributed among population subgroups.

To meet the objectives of Executive Order 12898, EPA examined whether the rule creates 

potential environmental justice concerns in the areas affected by steam electric power plant 

discharges. EPA conducted the analysis in two ways. First, EPA compared demographic data for 

populations living in proximity to steam electric power plants to demographic characteristics at 

the state and national levels. This analysis focuses on the spatial distribution of minority and 

low-income groups to determine whether these groups are more or less represented in the 

populations that are expected to benefit from the final rule, based on their proximity to steam 

electric power plants. Second, EPA conducted analyses of populations exposed to steam electric 

power plant discharges through consumption of recreationally caught fish by estimating 

exposure and health effects by demographic cohort. Where possible, EPA used analytic 

assumptions specific to the demographic cohorts – e.g., fish-consumption rates specific to 

different racial groups.

See Chapter 14 in the BCA for the final rule for details of the analysis and results.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 41

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The nationwide poisoning of fish is particularly unjust for communities that depend heavily on 

fish for food. According to the National Environmental Justice Advisory Council, families in 

many communities of color, including African-Americans and Native peoples, rely on fishing to 

supply basic nutritional needs.89 As the Council wrote, “[p]ut simply, communities of 

color, low-income communities, tribes, and other indigenous peoples depend on healthy aquatic 

ecosystems and the fish, aquatic plants, and wildlife that these ecosystems support.”90 Fishing 

provides an inexpensive, reliable, and healthful food source, but when fish are contaminated, 

reliance on fishing for food makes these communities far more vulnerable to water pollution and 

contaminated fish than the general population.91

89 National Environmental Justice Advisory Council, Fish Consumption and Environmental 

Justice iii-iv (2002), available at 
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http://www.epa.gov/environmentaljustice/resources/publications/nejac/fish-consumpreport_1102.pdf.

90 Id. at 2.

91 Id.

Comment Response: 

EPA recognizes and shares the concerns expressed by the commenter about the impact of fish 

tissue contamination from steam electric power plant discharges to communities that rely on selfcaught fish for basic dietary and nutritional needs. As part of the final rule analysis, EPA has 

significantly revised its analysis of environmental justice concerns associated with steam electric 

power plant discharges to provide a more detailed understanding of the baseline impacts on 

potentially disadvantaged communities and of how benefits of the ELG are distributed among 

different population subgroups (see Chapter 14 of the BCA for the final rule).

Among several improvements, the final ELG analysis considers differences in consumptions 

rates across different socioeconomic groups that may contribute to differences in exposure, and 

benefits from the final ELG improvements. These differences enhance past analyses that looked 

at differences for anglers that practice subsistence fishing. As in the proposed rule analysis, EPA 

also differentiated between recreational anglers and subsistence fishers, who consume more selfcaught fish and can be expected to experience higher health risks associated with contaminated 

fish tissue, as noted by the commenter.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 93

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

2. Reliance on BPJ determinations will disproportionately affect environmental justice 

communities.

As noted above, it is challenging and rare for environmental organizations such as the 

undersigned commenters to marshal the resources to comprehensively evaluate a BAT 

determination for a particular plant. Clearly, most impacted local communities lack these kinds 

of resources. Thus, a critical flaw with relying on case-by-case BPJ determinations is that BAT 

determinations will vary by jurisdiction and, even within a single jurisdiction, may vary 

depending on whether a local community or environmental organization is able to participate in 

the administrative process and has the resources to advocate for protective permit limits. 
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Communities without resources to engage in the permitting process in this way are much less 

likely to be able to compel the permitting authority to issue a permit containing strong BATbased limits. EPA should have evaluated the environmental justice implications of two of its 

preferred options—3a and 3b—which would fail to provide the same protection to underresourced communities as a uniform national standard. EPA’s environmental justice analysis 

fails to acknowledge the implications of reliance on BPJ for these groups.358

358 See 78 Fed. Reg. at 34,532; RIA at 10-2 to 10-5.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4684-A1, Excerpt Number 218 (in comment 

code 28.b).

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 204

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA failed to conduct the required inquiry into whether its regulatory options have a 

disproportionately high and adverse health or environmental impact on communities of color and 

low-income populations. The Agency’s cursory inquiry focused on only one adverse impact of 

pollution discharges (consumption of contaminated fish) and failed entirely to evaluate the health 

and environmental harms suffered by communities proximate to the source of pollution. The 

abbreviated inquiry does not satisfy the Executive Order nor is it consistent with the 

environmental justice assessment conducted by the Agency for its 2010 proposed CCR rule on 

identical pollution sources.915 EPA’s indefensibly narrow environmental justice analysis 

represents substantial noncompliance with the Executive Order that must be rectified.

Under Executive Order 12898, each Federal agency must make achieving environmental justice 

part of its mission by identifying and addressing, as appropriate, disproportionately high and 

adverse human health or environmental effects of its programs, policies, and activities on 

minorities and low-income populations.916 EPA, however, summarily sidestepped the directive 

of Executive Order 12898 by concluding that its environmental justice analysis “indicates 

that minority and low-income communities are expected to benefit as much as anyone from the 

proposed ELGs.” This statement entirely misconstrues the mandate of Executive Order 12898. 

EPA performed only a perfunctory analysis to determine whether a very broad population 

benefitting in one specific way from pollution reductions would exclude minority and low-
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income populations. The Agency did not even begin to examine the widely divergent regulatory 

options in the ELG rule and consider whether the outcomes of those options would have a 

disproportionate impact considering the many harms presented by coal-burning power plants to 

directly impacted communities.

The decision currently before EPA is not whether to promulgate an ELG rule, but to determine 

the precise coverage and breadth of a final ELG rule. According to analyses of the populations 

proximate to power plants recently completed by EPA, this decision assuredly affects lowincome populations disproportionately. EPA must therefore identify any disproportionate impact 

on minority and low-income populations that results from the Agency’s choice of one option over 

another. According to the Executive Order, if disparate impacts are identified, EPA must address 

those impacts. Most importantly, the Agency must make achieving environmental justice 

a factor in its decision to choose one option over another. Unfortunately EPA has barely begun 

the analysis required by the Executive Order.

915 See CCR RIA at 216-226.

916 Executive Order 12898, Federal Actions to Address Environmental Justice in Minority 

Populations and Low- Income Populations (59 Fed. Reg. 7629, Feb. 16, 1994). See also Interim 

Guidance on Considering Environmental Justice During the Development of an Action (July 

2010), available at http://www.epa.gov/environmentaljustice/resources/policy/considering-ej-inrulemaking-guide-07-2010.pdf.

Comment Response: 

EPA agrees with the imperative to examine potential environmental justice impacts of the 

revised ELGs. The focus of the ELGs revisions is to strengthen existing controls on discharges 

from steam electric power plants, reducing pollutant loadings to receiving waters and in turn 

enhancing surface water quality, reducing health risks, and increasing productivity in economic 

activities adversely affected by steam electric discharges. These changes will improve 

environmental conditions broadly across the country, and most particularly in communities that 

neighbor steam electric power plants.

EPA also agrees with the commenter’s implication that the rule options vary with respect to 

coverage and breadth, and thus may also vary in the scale and scope of benefits provided. This is 

consistent with the analyses EPA presented in the BCA. However, we disagree that EPA has 

“summarily sidestepped” the directive of Executive Order 12898. As presented in the final BCA, 

the EPA’s analyses provide a basis for characterizing environmental justice concerns within the 

constraints of the available data, and support a reasoned determination that the preferred option 

is unlikely to systematically preclude minority and low-income communities from receiving 

environmental and health benefits of the rule.

However, EPA also recognizes that the proposed environmental justice analysis could be 

improved to better inform decisions on the options, though environmental justice is not, strictly 
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speaking, one of the statutory factors that the Agency must consider in setting Best Available 

Technology. Accordingly, EPA revised its proposed environmental justice analysis for the final 

rule analysis to more fully consider each of the options from an EJ perspective, based on 

available data. The updated analysis considers the distribution of impacts and benefits of each 

option on different populations, taking into account exposure, relevant to each category of 

impact. EPA intends these changes to address the commenter’s request that the Agency 

“examine the widely divergent regulatory options in the ELG rule and consider whether the 

outcomes of those options would have a disproportionate impact considering the many harms 

presented by coal-burning power plants to directly impacted communities.” EPA also compared 

how the five regulatory options analyzed for the final rule compare on with respect to the 

distribution of the benefits. Section 14.5 of the BCA describes the findings of this comparison.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 205

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

C. EPA FAILED TO COLLECT AND EVALUATE ENVIRONMENTAL JUSTICE 

DATA AS REQUIRED BY EXECUTIVE ORDER 12898.

The information collection and analysis mandates of Executive Order 12898 are crystal clear. 

Section 3-302(b) of Executive Order 12898 requires Federal agencies to collect and evaluate 

environmental justice data for areas surrounding facilities or sites expected to have “substantial 

environmental, human health, or economic effect” on local populations when such facilities or 

sites become subject to “substantial” Federal environmental action:

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, maintain and 

analyze information on the race, national origin, income level, and other readily accessible and 

appropriate information for areas surrounding facilities or sites expected to have substantial 

environmental, human health, or economic effect on the surrounding populations, when such 

facilities or sites become the subject of a substantial Federal environmental administrative or 

judicial action. Such information shall be made available to the public unless prohibited by 

law.917

Certainly the ELG rule is a substantial federal environmental action likely to have a substantial 

environmental, health or economic effect on populations proximate to the power plant. However, 

EPA did not conduct any environmental justice analyses of populations surrounding the 

hundreds of coal-burning plants subject to the ELG rule. Instead, EPA performed a birds-eye 
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evaluation of the make-up of the population located within a 100-mile downstream reach of the 

plants, focusing on only one aspect of harm.918

EPA described their sole, specific inquiry for their environmental justice analysis:

To address the EJ implications of the proposed ELGs, EPA analyzed the demographic 

characteristics of the populations currently exposed to these discharges through consuming selfcaught fish from receiving reaches (i.e., populations located within 100 miles of the affected 

reaches also referred to as the “benefit regions” in the rest of this discussion) to determine 

whether minority and/or low-income populations incur disproportionally high 

environmental impacts or are disproportionally excluded from realizing the benefits of this 

proposed regulation.919

EPA’s exceedingly narrow scope of inquiry does not meet the requirements of the Executive 

Order. The Agency’s analysis does not in any way evaluate effects on the health, environment or 

economy of populations “surrounding” the power plants, nor does EPA evaluate whether these 

impacts will be felt disproportionately by communities of color or low-income communities.

917 Id. at Section 3-302(b).

918 RIA at 10-2.

919 Id. at 10-2.

Comment Response: 

See response to related comments, including comment EPA-HQ-OW-2009-0819-4684-A1, 

Excerpt Numbers 204 and 206

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 206

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

D. EPA MUST EVALUATE COMMUNITIES IMMEDIATELY SURROUNDING COALBURNING POWER PLANTS FOR DISPARATE IMPACT.
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In addition to its general assessment of populations 100 miles from coal-burning power plants, 

EPA must evaluate populations within 15 miles of all facilities affected by the ELG rule. A 15-

mile evaluation is consistent with Superfund’s Hazard Ranking System (HRS), which is used to 

define affected populations at sites having either (a) soil contamination only (1 mile), (b) 

groundwater and/or airborne contamination (4 miles), or (c) surface water contamination (15 

miles downstream).920 Because the ELG rule will impact waste disposal practices at coalburning power plants that adversely affect soil, air and groundwater, it is appropriate to examine 

populations within a four-mile radius, as well as 15 miles downstream.

This approach is consistent with EPA’s 2010 environmental justice analysis for the proposed 

CCR Rule completed pursuant to Executive Order 12898. EPA’s 2010 analysis was based on 

“Zip Code Tabulation Areas (ZCTAs).921 EPA used ZCTAs as the geographic basis for the 

analysis because it offered a land area equivalent to a five-mile radial distance. EPA 

collected 2000 census data in the ZCTAs for 464 coal burning plants. After assessing the extent 

of minority and low-income populations found in these ZCTAs, EPA concluded that low-income 

citizens were disproportionately represented in the populations within the four-mile radius of 

the plants, and therefore the hazards and risk from coal ash landfills and surface 

impoundments “may have a disproportionately higher effect on low income populations.”922

Furthermore, EPA’s current analysis of fish consumers within 100 miles of power plants cannot 

capture disproportionate impacts that may be occurring locally. It is essential to perform an 

accurate and precise assessment because poisoning of fish is particularly unjust for communities 

that depend heavily on fish for food. According to the National Environmental Justice Advisory 

Council, families in many communities of color, including African-Americans and Native 

peoples, rely on fishing to supply basic nutritional needs.923 Fishing provides an inexpensive and 

healthful food source, but when fish are contaminated, reliance on fishing for food makes these 

communities far more vulnerable to water pollution and contaminated fish than the general 

population.924 EPA failed to identify environmental justice communities proximate to 

power plants that rely on such food sources and who would be disproportionately impacted by 

options in the ELG rule that fail to control pollution sources.

EPA therefore must examine the surrounding communities, as required by the Executive Order, 

and investigate with much greater diligence whether harm to health, the environment and the 

economies of these communities are disproportionately impacted.

920 HRS is available at http://www.epa.gov/superfund/programs/npl_hrs/hrsint.htm.

921 EPA, CCR RIA at 217.

922 75 Fed. Reg. at 35230.

923 National Environmental Justice Advisory Council, Fish Consumption and Environmental 

Justice iii-iv (2002), available at 
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http://www.epa.gov/environmentaljustice/resources/publications/nejac/fish-consumpreport_1102.pdf.

924 Id.

Comment Response: 

EPA shares the commenter’s concerns that, when evaluating distributional impacts across 

population subsets, the Agency should use an appropriate zone of influence around steam electric 

facilities and affected waterbodies. Analysis of the proposed rule options used a distance of 100 

miles as the appropriate distance for exposure to recreationally-caught fish. The Agency 

recognizes that such a distance may mask the distribution of effects to populations living in close 

proximity to steam electric power plants.

In response to this and other comments EPA received on the proposed rule analysis, EPA revised 

its EJ assessment approach for the final rule. Chapter 14 of the BCA for the final rule provides 

more details on these updates and presents the results of these analyses. For example, EPA 

described the socioeconomic profile of communities within 1, 3, 15, 30, and 50 miles of reaches 

receiving discharges from steam electric power plants, based on suggestions from this and other 

commenters.

EPA also enhanced its EJ analysis by considering the distribution of health effects and benefits 

across socioeconomic groups exposed to the contaminants through consumption of self-caught 

fish. The analysis considers differences in socioeconomic factors leading to lower or greater 

exposure, based on available data. EPA also differentiated between recreational anglers and 

subsistence fishers, who consume more self-caught fish and can be expected to experience higher 

health risks associated with contaminated fish tissue, as noted by the commenter.

Chapter 14 of the BCA describes the analysis. The results show that a greater fraction of the 

communities living in close proximity to waters directly affected by steam electric power plant 

discharges is poor, when compared to the national average. The results also show that the final 

rule will increases the level of environmental protection (reduces adverse human health and 

environmental effects) for all affected populations, including minority or low-income 

populations.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 207

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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E. EPA MUST EVALUATE ALL REGULATORY OPTIONS IN THE PROPOSED ELG 

RULE TO DETERMINE WHETHER THE OPTIONS RESULT IN DISPROPORTIONATE 

EFFECTS ON COMMUNITIES OF COLOR AND LOW-INCOME COMMUNITIES.

The range of options proposed by EPA creates dramatically different outcomes in protection of 

health and the environment for environmental justice communities. Consequently, EPA must 

evaluate its range of eight options and identify such disparate impacts. Below, 

we highlight three examples of disproportionate impact that must be analyzed and addressed, 

according to the requirements of the Executive Order.

Comment Response: 

As described in Chapter 14 of the BCA for the final rule, EPA revised its benefits and 

environmental justice analyses to evaluate impacts of steam electric discharges on different 

communities. The revisions include, notably, analyses of individual options to understand the 

distribution of benefits across population subgroups according to socioeconomic indicators. EPA 

made these adjustments in part to address requests, such as the one from this commenter, for this 

information. See response to DCN EPA-HQ-OW-2009-0819-4684-A1, Excerpt Number 206.

While all options EPA analyzed for the final rule benefit minority and poor populations by 

reducing potential exposure to pollutants discharged by steam electric power plants, Options C, 

D, and E are expected to provide significantly greater human health benefits than Options A and 

B as indicated by higher reductions in adverse health effects from lead and mercury exposure. 

Improvements under Option C accrue to poor and minority population to a larger relative extent 

than do improvements under Options D and E, but Option D (on which the final limitations and 

standards are based) provides greater benefits overall than Option C, including to poor and 

minority populations exposed to steam electric pollutants through consumption of self-caught 

fish. Thus, EPA concluded that Option D furthers environmental justice objectives.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 208

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

1. Reliance on BPJ in Options 3a and 3b will have a disparate impact on communities of 

color and low-income populations.

EPA must evaluate the environmental justice implications of two of its preferred options, 3a 

and 3b. As discussed previously, Options 3a and 3b (for plants with less than 2,000 MW wetscrubbed capacity) would leave effluent limits to be set on a case-by-case basis.925 The practical 
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implications of EPA’s failure to set ELGs for FGD wastewater are enormous. The record shows 

that local permitting authorities do not rigorously apply best professional judgment for 

determination of the best available technology for FGD wastewater and coal combustion 

residuals.926 EPA, in fact, is well aware that states have failed to establish technology-based 

effluent limits for these waste streams, as evidenced by the dozens of objection letters issued by 

EPA regional offices.

Case-by-case BAT determinations are extremely problematic for local communities affected by 

these discharges who might seek stronger permits. To fully participate in the administrative 

review process, local groups must pay for legal and technical assistance, including hiring experts 

to investigate existing technologies and present alternative BAT analyses. Clearly, most 

impacted local communities lack these kinds of resources. Thus, a critical flaw with relying on 

case-by-case BPJ determinations is that BAT determinations will vary by jurisdiction and, even 

within a single jurisdiction, may vary depending on whether a local community is able to 

participate in the administrative process and has the resources to advocate for protective permit 

limits.

Communities without resources to engage in the resource-intensive permitting process are much 

less likely to be able to compel the permitting authority to issue a permit containing strong BATbased limits. Consequently it is likely that Options 3a and 3b would provide less protection to 

under-resourced communities, such as low-income communities and communities of color, 

then a uniform national standard. The Executive Order therefore requires EPA to fully evaluate 

the impact on these communities of the reliance on BPJ in its environmental justice analysis.

925 78 Fed. Reg. at 34,458, Table VIII-1.

926 See Closing the Floodgates, (finding that out of 274 power plants discharging wastewater, 

only 86 had at least one limit on arsenic, boron, lead, mercury, cadmium, or selenium; 255 plants 

lacked any limits on arsenic; 235 plants lacked any limits on mercury; 232 lacked limits on 

selenium; and nearly 40 percent did not even require monitoring for any of these pollutants).

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4684-A1, Excerpt Number 218 (in comment 

code 28.b)

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 209

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

1. Proposed regulatory options that permit the continued use of coal ash surface impoundments 

will have disparate impact on communities of color and low-income populations.

As EPA demonstrated in its environmental justice analysis for the 2010 proposed CCR rule, coal 

ash landfills and surface impoundments are more often located in low-income communities and 

therefore may have a disproportionately higher impact on this population. Further, Earthjustice’s 

own environmental justice analysis in 2010 of the proposed CCR rule also found coal-burning 

power plants disproportionately located in impoverished areas. Earthjustice found that almost 70 

percent of coal ash impoundments in the United States are in areas where household income is 

lower than the national median.927 Earthjustice also found that, of the 181 ZIP codes nationally 

that contain coal ash ponds, 118 (65.19 percent) have above-average percentages of low-income 

families.

928 Given the serious health threats posed by coal ash, it is particularly troublesome that 

coal ash impoundments are disproportionately located in low-income communities, where 

residents are more likely to rely on fish consumption, groundwater supplies and less likely 

to have access to medical insurance and care. Consequently, ELG options that rely on the 

continued use of impoundments are likely to disproportionately impact environmental justice 

populations near the power plants.

Earthjustice also found in its 2010 analysis that the lack of standards for safe operation of surface 

impoundments was most acute in states where the disproportionate impact for both income and 

race was greatest for communities living near the impoundments.929 In addition, Earthjustice 

found that the largest number of coal ash impoundments were located in states that 

generally have the weakest regulations.930 Because EPA has proposed options that would permit 

the continued use of surface impoundments, EPA must examine the potential disparate impact on 

environmental justice communities in light of current state law as well as the options EPA is 

considering in its proposed CCR rule.

927 U.S. Census Bureau, Census 2000 Summary File 3 (SF 3) - Sample Data, All 5-Digit ZIP 

Code Tabulation Areas (860), Table P53 "Median Household Income in 1999 (Dollars)", 

available at http://factfinder.census.gov/servlet/DCSubjectKeywordServlet?_ts=307978361769.

928 U.S. Census Bureau, Census 2000 Summary File 3 (SF 3) - Sample Data, All 5-Digit ZIP 

Code Tabulation Areas (860), Table P76 "Family Income in 1999" (downloaded June 23, 2009), 

available at

http://factfinder.census.gov/servlet/DownloadDatasetServlet?_lang=en&_ts=263843114140. “L

ow-income” defined as earning less than $20,000 annually. ZIP codes containing coal ash ponds 

compared to a national mean percent “low-income” of 12.61%, calculated based on the “Family 

Income in 1999” dataset; United States Environmental Protection Agency (U.S. EPA). Database 

of coal combustion waste surface impoundments (2009). Information collected by EPA from 

industry responses to Information Collection Request letters issued to the companies on March 9, 

2009. Sufficient data to determine ZIP code Census Data was available for 511 of the nation’s 

584 known coal ash impoundments. Many impoundments are adjacent to one another 
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surrounding generating facilities, and are listed with identical geographic coordinates in the EPA 

data—hence why only 181 ZIP codes contain 511 ash impoundments.

929 See Comments of Earthjustice et al. to U.S. Environmental Protection Agency (“U.S. EPA”), 

Office of Resource Conservation and Recovery, Hazardous and Solid Waste Management 

System; Identification and Listing of Special Wastes; Disposal of Coal Combustion Residuals 

From Electric Utilities, 75 Fed. Reg. 35,128 (proposed June 21, 2010) (comments filed Nov. 19, 

2010) (Document ID No. EPA-HQ-RCRA-2009-0640-6315), 195-205.

930 Id.

Comment Response: 

EPA appreciates the commenter’s concern about the safe operation of impoundments which 

plants may continue to use following the final CCR and ELG rules. Under RCRA, the recent 

promulgated Coal Combustion Residuals Rule (the CCR rule) is the major controlling action for 

safe operation of surface impoundments.

For the final ELG rule, the Agency adjusted its avoided impoundment failure benefits analysis to 

account for anticipated changes in coal combustion residue (CCR) management practices 

(Chapter 6 in the BCA for the final rule). These benefits are incremental to those of the CCR 

rule, which is accounted for in the baseline for the ELG analysis.

EPA also revised its analysis of environmental justice concerns to highlight potential changes in 

communities affected by future expected impoundment releases based on the profile of 

communities living in proximity to the reaches that receive direct discharges from steam electric 

power plants (Chapter 14 in the BCA). Specifically, EPA describes the demographic 

characteristics of populations living within 1, 3, 15, 30, and 50 miles of steam electric power 

plants. The profile supports the commenter’s claim that communities living in close proximity to 

steam electric power plants are more likely to be low income than the national average.

Note that the final ELG rule doesn’t require plants to close impoundments, but EPA expects that 

many plants will implement operational changes – including reduced reliance on impoundments 

– to comply with the limitations of the final regulation. These changes will reduce the amount of 

CCR that is released in the event of an impoundment failure, thereby reducing impacts to nearby 

communities, including low-income and minority populations.

EPA’s impoundment analysis values avoided releases based on available data regarding cleanup 

costs, natural resource damages, and litigation costs; data on the human health impacts of 

impoundment releases are not available and are therefore not reflected in the impoundment 

benefits described in Chapter 6 of the BCA.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.
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Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 210

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

2. The failure to establish specific and enforceable BMPs for structural stability and closure 

will have disparate impact on communities of color and low-income populations.

The failure to require structural stability and closure requirements in BMPs will also have a 

disproportionate impact on low-income communities. Low-income populations immediately 

surrounding a coal ash impoundment will be most heavily impacted if impoundments are not 

required to ensure structural stability or have not been properly closed. Adverse impacts from 

coal ash surface impoundments on local communities can include seeps of highly polluted, 

water, groundwater contamination, poisoning of fish, birds, wildlife and livestock that frequent 

the impoundment, destruction of recreational opportunities in nearby surface waters, 

depressed property values, fugitive airborne ash, as well as cataclysmic dam failures. Such 

adverse impacts from inadequately maintained or improperly closed impoundments are 

potentially severe, and such localized impacts must be examined for their disparate impacts 

under all ELG options that do not include BMPs addressing such risks.

Comment Response: 

The final CCR rule addressed requirements for plant owners to implement structural stability and 

closure best management practices (BMPs) for coal ash impoundments. The final CCR rule also 

addressed many of the other impacts on local communities raised by the commenter. To the 

extent that ELG rule affects residual impacts of impoundments, EPA discusses the benefits 

qualitatively in Section 2 of the BCA for the final rule. Also see BMP discussion in Section VIII 

of the preamble to the final ELG rule.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 211

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

F. EPA’S ENVIRONMENTAL JUSTICE ANALYSIS IS ARBITRARY AND 

CAPRICIOUS AND MUST BE REVISED TO EVALUATE ADEQUATELY THE IMPACTS 

OF THE PROPOSED ELG RULE, AS REQUIRED BY EXECUTIVE ORDER 12898.
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Courts have held that an agency’s environmental justice analysis is subject to review under the 

Administrative Procedure Act and can be found arbitrary and capricious.931 EPA’s failure to 

follow the explicit requirements of Executive Order 12898 to evaluate surrounding communities 

impacted by the proposed rule or to evaluate the options being considered by the Agency and 

their impacts on environmental justice communities renders its analysis arbitrary and 

capricious. EPA must therefore revise the analysis and consider the results of its new 

environmental justice analysis in its decision making for the final ELG rule.

931 See Communities Against Runway Expansion, Inc. v. FAA, 355 F.3d 678, 688-689 (D.C. Cir. 

2004) (in the context of a challenge to an agency’s choice of reference group in the 

disproportionality analysis, the court ruled that where an agency exercises its discretion to 

include an environmental justice analysis, it is subject to review under the arbitrary and 

capricious standard pursuant to the APA); Coliseum Square Ass’n, Inc. v. Jackson, 465 F.3d 215 

(5th Cir. 2006) (review of agency’s consideration of environmental justice appropriate under 

APA arbitrary and capricious standard).

Comment Response: 

EPA disagrees that the environmental justice analysis conducted to inform development of the 

proposed rule is “arbitrary and capricious.” The approach used for the proposed rule analysis was 

similar to that EPA has used on other rules, which have been subject to review and public 

comments. However, EPA recognizes that more could be done to explore how different 

communities are affected by steam electric power plant discharges and how the rule options 

serve to redress environmental justice issues. Accordingly, as part of the final rule analysis, EPA 

has significantly revised its analysis of environmental justice concerns associated with steam 

electric power plant discharges to provide a more detailed understanding of the baseline impacts 

on communities and of how benefits of the ELG are distributed among communities (see Chapter

14 in the BCA for the final rule).

The results show that a greater fraction of the communities living in close proximity to waters 

directly affected by steam electric power plant discharges is poor, when compared to the national 

average. The results also show that the final rule will increases the level of environmental 

protection (reduces adverse human health and environmental effects) for all affected populations, 

including minority or low-income populations.

As also shown in Chapter 14 of the BCA, while all options EPA analyzed for the final rule 

benefit minority and poor populations by reducing potential exposure to pollutants discharged by 

steam electric power plants, EPA determined that the option selected for the final rule provides 

significant benefits to poor and minority populations exposed to steam electric pollutants through 

consumption of self-caught fish and furthers environmental justice objectives
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Commenter Name: C. and C. Timko

Commenter Affiliation: Private Citizen

Document Control Number: EPA-HQ-OW-2009-0819-5084-A1

Comment Excerpt Number: 3

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Once environmental impacts have been neglected, social inequities grow.

It should not be the case that Americans' health is influenced by where they live, as it currently 

is. Let us not allow environmental injustice as a social issue to grow more than it already has.

Comment Response: 

EPA shares the concerns expressed by the commenter about the distribution of environmental 

impacts across populations. EPA conducted an environmental justice analysis to support the final 

rule, in accordance with requirements in Executive Order 12898: Federal Actions to Address 

Environmental Justice in Minority Populations and Low-Income Populations and Chapter 10 in 

EPA's Guidelines for Conducting Economic Analyses. Chapter 14 of the BCA for the final rule 

describes this analysis. The results show that a greater fraction of the communities living in close 

proximity to waters directly affected by steam electric power plant discharges is poor, when 

compared to the national average. The results also show that the final rule will increases the level 

of environmental protection (reduces adverse human health and environmental effects) for all 

affected populations, including minority or low-income populations.
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28.j. Econ – EOs 12866 and 13563 

Commenter Name: R. W. Greene

Commenter Affiliation: Mercatus Center at George Mason University

Document Control Number: EPA-HQ-OW-2009-0819-3411-A1

Comment Excerpt Number: 6

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

As required by Executive Order 128667the EPA assessed the regulatory proposal (ELGs) as an 

economi cally significant regulatory action because it is likely to have an annual effect on the 

economy of $100 million or more. The EPA accordingly prepared an analysis of the potential 

benefits and costs associated with the ELGs.8

 The EPA has carried out a partial analysis of costs and benefits, at best amounting to a 

cost effectiveness appraisal of alternatives, which are rather narrow. There is an effort to 

model the impact of the regulatory proposal on generating costs for each alternative and 

to examine impacts such as those on markets and employment (likely to fall by around 

1.6 percent in the sector). Benefits are not fully quantified.

7 Exec. Order No. 12866, 58 Fed. Reg. 51735 (October 4, 1993).

8 EPA, Regulatory Impact Analysis, 10-1.

Comment Response: 

EPA disagrees with the commenter’s assertion that the agency “carried out a partial analysis of 

costs and benefits, at best amounting to a cost effectiveness appraisal of alternatives, which are 

rather narrow.” EPA conducted a thorough and detailed analysis of estimated compliance costs 

for the final rule, in accordance with section 304(b) of the Clean Water Act. EPA also conducted 

a detailed Environmental Assessment regarding impacts of the final rule. The estimated 

compliance costs were then used to calculate social costs and information from the 

Environmental Assessment was used to calculate social benefits of the final rule, pursuant to 

Executive Order. These analyses are described in detail in the RIA, EA Report, and BCA 

documents included in the record. In some cases, lack of data prevented EPA from fully 

quantifying and/or monetizing the benefits, and to that extent, EPA agrees with the commenter 

that “benefits are not fully quantified.” See the BCA for a listing of benefits that could not be 

fully quantified and/or monetized. Also see responses to related comments (e.g., DCN EPA-HQOW-2009-0819-3411-A1, Excerpt Numbers 8 and 16 in Sections 28.b and 29.a, respectively).
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Commenter Name: L. Niemala

Commenter Affiliation: Private Citizen

Document Control Number: EPA-HQ-OW-2009-0819-3549-A1

Comment Excerpt Number: 1

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Power plant water pollution will cost the citizens real money in health suffering and costs as well 

as the cost of cleaning the water.

When will the government finally include the long range costs to the society in their decisions?

Comment Response: 

EPA recognizes the concerns expressed by the commenter about the costs to society associated 

with steam electric power plant discharges, and it conducted a detailed Environmental 

Assessment and analysis of benefits, in terms of human health, water quality, and other aspects, 

of strengthening pollution controls on these discharges under the final rule. These analyses are 

summarized in the preamble and detailed in the EA Report and BCA for the final rule.

Commenter Name: Patrick O’Loughlin

Commenter Affiliation: Buckeye Power, Inc.

Document Control Number: EPA-HQ-OW-2009-0819-4183-A2

Comment Excerpt Number: 22

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Buckeye Power is concerned that EPA has not adequately considered the cumulative impacts of 

the ELG rules, CCR rules and the avalanche of other rulemakings affecting the coal-fired power 

industry. EPA's recent and pending rules dealing with mercury, particulates, interstate transport, 

greenhouse gases, and cooling water intake structures already are imposing or likely to impose 

major new requirements, and restrictions that will be extremely costly, many of which are now 

being implemented or will soon be implemented. This barrage of regulation makes it 

increasingly difficult for facilities to design, plan, and implement efficient improvements. Steam 

electric power generating facilities are capital intensive and complex, and they are integral 

components of our nation's electric energy supply. To impose substantial new requirements on 

facilities already undergoing significant transitions -without fully evaluating the costs, 

environmental necessity, and timing of further changes - is ill-advised and not in keeping with 

Executive Order 13610 on reducing regulatory burdens, including cumulative effects of multiple 

regulations.
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Comment Response: 

EPA acknowledges the concern expressed by the commenter regarding the effects of multiple 

rules affecting the electric power industry. EPA is sensitive to the need to provide sufficient time 

for affected entities to understand, plan for, and implement any changes to their operation to 

meet their environmental responsibilities. The ELG rulemaking process provided significant 

advance notice to potentially affected entities to evaluate the potential impacts of any new ELG

requirements on their operations. As described in the preamble for the final rule, EPA also 

provided time for facility owners to implement any changes to such operations to meet the final 

limitations and standards, as well as flexibility to permitting authorities in implementing the final 

rule. The Agency specifically considered the timing of requirements of other environmental 

regulations in the ELGs to provide steam electric power plants time to consider their strategy to 

implement any needed changes. See Sections VIII and XVI of the preamble to the final rule for 

details on the timing of implementation of the final rule.

EPA’s analysis of the proposal and final rule accounted for the potential cumulative impact that 

multiple environmental regulations might have on the steam electric power generating 

industry and is consistent with EPA’s requirements under the CWA authority and applicable 

Executive Orders, including EOs 13653 and 13610, to evaluate the cumulative effects of 

regulations.

For the proposed rule analysis, EPA analyzed the impact of the ELGs using the Integrated 

Planning Model (IPM), a comprehensive electricity market optimization model that assesses 

impacts of environmental regulations within the context of regional and national electricity 

markets. The proposal analysis used IPM version v4.10_MATS, which includes the effects of the 

Mercury and Air Toxics Standards (MATS) rule, the Cross-State Air Pollution Rule (CSAPR), 

and various other federal and state programs (see IPM documentation for more details; available 

at http://www.epa.gov/powersectormodeling/). EPA added the ELG impacts on top of the 

impacts modeled in the base case.

For the final rule analysis, EPA again used IPM to understand the impacts of the ELGs on the 

electricity market (and on the steam electric power generating industry in particular), accounting 

for the effects of other regulations. EPA used IPM model version 5.13 for the final rule analysis. 

The analysis base case includes the regulations included at proposal, as well as the cooling water 

intake structure rule and the Coal Combustion Residuals (CCR) rule. Based on their breadth of 

effect and potential cost, EPA views these regulations as the most significant other regulations 

affecting the electric power industry, and steam electric generators in particular. Given the 

potential magnitude of effects, EPA also conducted an analysis that accounts for the effects of 

the Clean Power Plan (CPP) regulation (as proposed in July 2014). See Section V.B of the 

preamble for the final rule for additional information. Also see DCN SE05978 for a discussion of 

the anticipated effects of the final CPP regulation. The model outputs therefore reflect the 

combined effects of all these regulations on generation capacity, electricity production costs, 

prices, etc. accounting for the costs to electricity generators of complying with the environmental 

requirements. The model allows consideration of the incremental impacts of the ELGs in the 

context of the various rules and programs affecting the power sector during the period of 

analysis. Furthermore, EPA accounted for the effects of other regulations in the ELG rulemaking 
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in several other ways. For the final rule, EPA coordinated the ELG analysis with the Air Office 

and Office of Resource Conservation and Recovery to identify changes potentially affecting the 

universe of plants to which the ELGs apply (e.g., EPA accounted for changes in plant handling 

of CCR waste due to the CCR rule in determining the waste streams applicable to each 

plant). See Section 9.4.1 in the Technical Development Document for the Effluent Limitations 

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

(TDD) (DCN SE05904).

Finally, EPA analyzed the ELG regulatory options under scenarios that look at various impacts 

of other rules in the baseline (e.g., with and without the CCR rule, without and without the CPP 

rule). For example, see Appendix B and C in the RIA for impacts of alternate baseline 

assumptions on total compliance costs, cost-to-revenue ratios, electricity rates, etc.

Regarding the commenter’s statement about “environmental necessity,” EPA notes that it 

prepared a comprehensive Environmental Assessment and Benefits analysis for the final rule. 

The benefits analysis quantifies those that can be estimated, and monetizes the benefits where 

possible. The analyses, which are summarized in the preamble for the final rule and further 

detailed in the BCA, show clear and significant benefits in terms of human and ecological health, 

avoided costs, and other societal values. EPA estimates that the final ELGs will generate 

monetized benefits valued at $450.6 million to $565.6 million per year, using a 3 percent 

discount rate ($387.3 million to $478.4 million using a 7 percent discount rate), not including 

important other benefits that the Agency was not able to assign a dollar value to. These are 

benefits that are incremental to and separate from the benefits as a result of other regulations that 

the Agency has promulgated.

As discussed in the preamble and detailed in the RIA document for the final rule, the results of 

EPA’s analyses demonstrate that the final ELGs are economically achievable for the industry as 

a whole, and they will have minimal economic impacts in a broader sense. The final rule will 

have small incremental impacts across the range of metrics EPA analyzed. These finding hold 

across the various scenarios the Agency analyzed with respect to the effects of other 

environmental regulations included in the baseline. For example, results of the electricity market 

model analysis show a decline in total capacity of 843 MW for steam electric power plants as a 

group, or approximately 0.2 percent of the 359,982 MW baseline capacity for these plants, 

corresponding to a net closure of two units and one plant (see Chapter 5 in RIA document for 

details). This is a minimal impact on the steam electric industry. EPA assesses that these 

retirements are inconsequential relative to total national and regional generating capacity. 

Furthermore, these retirements are offset by increased capacity for other plants. As a result, the 

final rule will not significantly affect electric supply reliability – either nationally or by NERC 

region.

Commenter Name: Leonard F. Hopkins

Commenter Affiliation: Southern Illinois Power Cooperative (SIPC)

Document Control Number: EPA-HQ-OW-2009-0819-4309-A1

Comment Excerpt Number: 1
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External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Over the years, SIPC has implemented pollution prevention measures to control water-borne 

pollutants in its discharge, but this new proposal from EPA may render these efforts useless, and 

the cost of compliance with this rule will significantly affect Southern Illinois Power 

Cooperative and its consumer-owners.

Being not-for-profit, Southern Illinois Power Cooperative will be forced to pass along all costs of 

meeting any new requirements that may result from complying with such a rule to its consumerowners. Southern Illinois Power Cooperative believes that increased cost of electric power, 

particularly in rural areas served by SIPC has negative impacts on economic development and 

jobs. Because Southern Illinois Power Cooperative has a disproportionate amount of fossil-fuel 

fired generation when compared to the electric utility industry as a whole, these negative impacts 

could be disproportionately higher for SIPC and its consumer-owners.

Comment Response: 

EPA addressed concerns on the specific impacts of the rule on cooperatives in its response to 

DCN EPA-HQ-OW-2009-0819-4460-A1, Excerpt Number 1 (Section 28.f).

EPA disagrees with the commenter that the final rule will render previous efforts to control the 

discharge of pollutants “useless.” EPA’s final rule establishes nationally applicable technologybased effluent limitations. The commenter does not specify why it has implemented certain 

pollution prevention measures to control its discharge of pollutants, but EPA notes that the final 

rule’s requirements are in addition to any requirements necessary to meet water quality 

standards, pursuant to section 301(b)(1)(C) of the Act.

The commenter raises a concern about potential disproportionate impacts in regions that generate 

a larger share of their electricity from coal. First, EPA notes that its final rule is affordable for the 

industry as a whole, which, along with technological availability, is key factor for Best Available 

Technology Economically Achievable under section 301 the Clean Water Act.

Second, EPA disagrees with the commenter that the final rule will negatively impact those that 

generate a substantial amount of electricity using fossil-fuels. EPA recognizes that the SERC 

region, in which the commenter (SIPC) operates, does get a significant share of its current 

electricity supply from steam electric generators, accounting for the largest national share of 

steam electric generating capacity. However, EPA’s electricity market modeling for that region, 

presented in Chapter 5 of the RIA, shows small impacts of the rule on electricity wholesale 

prices (0.2 percent increase), and cost of generation (0.5 percent increase) (see RIA Table 5-1). 

Additionally, the model shows that these results are obtained with small reduction in capacity 

(0.2 percent) and very modest (0.5 percent) reduction in the amount of electricity generated by 

steam electric units (see RIA Table 5-2).
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Given these and other small impacts, EPA disagrees that the final rule will adversely affect 

economic development or jobs. The commenter is not specific on the nature of its 

concerns. Nonetheless, EPA does not anticipate that there will be an adverse effect on regional 

economic development or jobs due to changes in generation at individual steam electric power 

plants, or higher electricity rates.

First, regarding impacts on individual steam electric power plants, as detailed above, the final 

rule is expected to reduce the amount of electricity generated by steam electric power plants by 

only a small amount (0.4 percent) in the region where SIPC operates (0.2 percent nationwide); 

the final rule is not expected to reduce steam electric generating capacity in the SERC region, 

and has minimal impacts nationwide with 1 net plant retirement.

Second, regarding impacts on electricity rates, as reported in the RIA, the final rule is expected 

to have very small impacts on the cost of electricity. EPA estimated the potential increase in cost 

per unit of electricity sales for the U.S. under the final rule to be 0.013 cents per kWh, with costs 

in the SERC region where SIPC operates representing an estimated 0.019 cents per kWh (see 

RIA Table 7-1). This increase represents approximately 0.2 percent of the baseline price of 

electricity for residential users, and 0.2 and 0.3 percent of the baseline price of electricity for 

commercial and industrial users, respectively (see RIA Table 7-2). These estimates are based on 

a conservative assumption of 100 percent pass-through of compliance costs to electricity prices; 

to the extent that some plants are not able to pass compliance costs onto consumers, it overstates 

the potential impact of the final rule on consumers. Thus, even with these conservative 

assumptions, the incremental impacts of the final Steam Electric ELGs on electricity rates are 

expected to be minimal and are unlikely to negatively affect regional economic development or 

employment.

Commenter Name: Nancy A. Evans

Commenter Affiliation: PPL Services Corporation

Document Control Number: EPA-HQ-OW-2009-0819-4348-A2

Comment Excerpt Number: 1

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

We urge EPA to take all appropriate steps to ensure that new rules applicable to the power 

generation industry – including the ELGs and the coal combustion residuals (CCRs) - are 

grounded in sound science and reflect an understanding of the challenges currently confronting 

the industry. Over the past several years, merchant and regulated utility power generators have 

been subject to an unprecedented number of new environmental rules under the air, water, and 

waste programs with major cost and operational implications for hundreds of power plants. If 

implemented in a piece-meal manner or if fashioned to include requirements which are 

unsupported by sound science, these new rules – including the ELGs – have the potential to 
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impose significant, unnecessary costs and operational restrictions with little or no corresponding 

environmental benefit.

Comment Response: 

With respect to the commenter’s statement about the final steam electric ELGs in conjunction 

with the CCR rule, see response to DCN EPA-HQ-OW-2009-0819-4183-A2, Excerpt Number 

22, regarding EPA’s consideration of other environmental regulations affecting the electric 

power sector in developing the final steam electric ELGs.

EPA cannot respond to the commenter’s statement that if the ELGs are “unsupported by sound 

science” they have the potential to impose “significant, unnecessary costs and operational 

restrictions.” The commenter offers no concrete example of how it views the ELGs as 

unsupported. Nonetheless, as explained elsewhere in the rulemaking record, EPA’s analyses for 

the final rule use sound data and methods.

EPA disagrees that the rules will have “little or no corresponding environmental benefit.” EPA 

conducted a benefit analysis, pursuant to Executive Order, which carefully lay out the benefits, 

quantifies those that can be estimated, and monetizes the benefits where possible. The analysis, 

which is summarized in the preamble for the final rule and further detailed in the BCA, shows 

clear and significant benefits in terms of human and ecological health, avoided costs, and other 

societal values as a result of the final steam electric rule. EPA estimates that the final ELG will 

generate benefits valued at $450.6 million to $565.6 million per year using a 3 percent discount 

rate ($387.3 million to $478.4 million using a 7 percent discount rate), not including important 

other benefits the agency was not able to assign a dollar value to. These are benefits that are 

incremental to and separate from the benefits from other regulations the agency promulgated.

Commenter Name: John McManus

Commenter Affiliation: American Electric Power System (AEP)

Document Control Number: EPA-HQ-OW-2009-0819-4448-A1

Comment Excerpt Number: 83

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Given the current environmental regulatory climate, older and less efficient facilities that 

dispatch less frequently, but provide some economic benefit, will be adversely affected through 

these guidelines and future rule promulgations, such as with proposed CCR and 316(b) rules, as 

well as the anticipated Greenhouse Gas Standards for existing sources. Though the proposed 

ELG rule may not make these units uneconomic to generate electricity over a short term by 

itself, the cumulative effect of the ELG in combination of other regulations may push these units 

into an accelerated retirement. Many of the affected facilities will not have 20-year lifespans or 
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service lives, but will still have to shoulder the financial burden to comply with these rules in the 

short term.

[...]

In its social cost analysis, EPA assumes that the estimated cost to society resulting from 

compliance with the proposed ELG rulemaking is simply the total compliance costs without 

accounting for tax effects. That is a valid assumption with respect to who will ultimately be 

paying for the compliance. However, EPA is confusing the concept of mitigation – i.e. the cost 

required to reduce pollutant loadings to meet a new standard – with the concept of social cost, 

which is the expense to an entire society resulting from continuing “business as usual.” In this 

case, the basis for assessing social costs is the impact to society from facilities continuing to 

operate under the limitations of the current effluent guidelines compared to the projected 

benefits to society resulting from implementing the new rulemaking. Theoretically, if the social 

cost exceeds the mitigation cost, society will benefit.

In terms of social costs, if effluent discharges from electric generating units under the current 

ELG are having an adverse effect on the environment and public health, the challenge is to 

quantify this impact in economic terms and assign a value to it. The process is fairly subjective 

as there are likely many different models forecasting the impacts of power generation facilities 

continuing under the current effluent guidelines – perhaps as long as 100 years. But whatever 

the length of the period, the difference between operating on a business-as-usual basis versus 

implementing the proposed ELGs must be valued and discounted to current dollars. This 

“value” is the externality that represents the impact to society of not implementing the proposed 

ELG or of industry not complying with the proposed rules post-implementation. It’s a process 

that merits review and scrutiny in terms of how the value is developed, whether or not the value 

make sense, and how the ranges around that value account for the uncertainty and variability of 

inputs to the model; expressing it as a single number automatically requires questioning its 

validity. In summary, developing an estimate of social cost is merely an attempt to put a dollar 

value on potential public health or environmental impacts going forward from continued use of 

the current ELG rule limitations. That is very different from calculating the cost to mitigate 

current discharges to meet the requirements of the proposed ELG rulemaking. The two costs are 

not comparable although EPA has suggested they are with the only difference being the 

exclusion of the tax discount afforded to the mitigation costs.

[...]

7. EPA fails to account for all employment impacts in its analysis of job creation.

EPA has misrepresented reasonably expected employment impacts associated with 

implementation of the proposed ELG rule by projecting a net increase in employment based on 

its myopic position of only estimating national level employment changes in the directly 

regulated electric power industry sector. Ignored in the Agency’s analysis is the largest potential 

employment impact – i.e. any associated with other sectors of the economy, whereby the 

increased electric rates due to ELG compliance would make domestic manufacturers less 

competitive, leading to job losses from business shutdowns or moving of operations outside of 
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the United States. The EPA attempts to sidestep this issue by generalizing that the net effect of 

an environmental regulation on regulated sectors and the overall economy as 

indeterminate. 50 Less discretionary income for all working Americans from higher electric rates 

due to ELG implementation would only compound employment losses due to lower demand for 

products and services. Put differently, EPA’s narrow consideration of only including potential 

job creation by implementation of the ELG rule neglects the deleterious effects of job destruction 

that would likely result in a net loss of domestic employment. Before finalizing this rule, EPA 

must examine and identify the full impacts of the rule to domestic employment by including the 

impacts to all sectors of the economy in its modeling.

50 Id. at 6-1.

Comment Response: 

The commenter raises three main issues addressed in turn below:

First, the commenter raises concern about early retirements of steam electric generating capacity. 

Specifically, the commenter states that ELG rule “in combination of other regulations may push 

these units into an accelerated retirement. Many of the affected facilities will not have 20-year 

lifespans or service lives, but will still have to shoulder the financial burden to comply with these 

rules in the short term.” EPA disagrees that it did not consider the “cumulative effect” of the 

final ELGs in light of other relevant rules because the Agency did consider the combined effects 

of environmental regulations in its analyses of the ELGs. See response to related comment DCN 

EPA-HQ-OW-2009-0819-4183-A2, Excerpt Number 22, for a discussion of how EPA accounted 

for the impacts of the ELGs in the context of various other rules affecting the electric power 

sector. As discussed in the preamble, EPA also took into account announced plant retirements 

and fuel conversions, as well as changes in plants’ ash-handling and wastewater-treatment 

practices, expected to occur by the implementation dates in the final rule. EPA recognizes that 

these plants will have much less than the assumed 20 years of service life, but notes that they are 

not expected to incur costs to meet the final limitations and standards. See response to DCN 

EPA-HQ-OW-2009-0819-4448-A1, Excerpt Number 67 (in section 28.b) for response to related 

concerns regarding the cost recovery period.

Second, the commenter states that the Agency’s social costs analysis failed to distinguish 

between the concepts of mitigation costs and social costs. EPA disagrees with the commenter’s 

suggestion that its social cost analysis was flawed. EPA followed well-accepted economic 

concepts for establishing the relevant costs from society’s perspective, as described in EPA 

Guidelines for Preparing Economic Analyses (U.S. EPA, 2010).

Third, the commenter raises concerns regarding the Agency’s employment analysis, stating that 

the Agency failed “to account for all employment impacts.” In particular, the commenter states 

that higher electricity rates may have negative impacts on employment in other sectors such as 

manufacturing, which EPA failed to account for. EPA’s analysis of the potential electricity rate 

effects, discussed in Chapter 7 of the RIA, shows that the final rule is expected to have very 
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small impacts on electricity rates; in the range of 0.11 to 0.21 percent, on average across the 

country, depending on the sector (Tables 7-2 and 7-3). Regarding estimates of how the electricity 

rates may potentially affect employment, EPA points out that there are myriad uncertainties in 

estimating employment effects and that estimated effects could range from positive to negative 

impacts overall, and with varying effects over time. Chapter 6 of the RIA document for the final 

rule discusses the ways a regulation can affect employment in the directly affected and other 

industries and resulting uncertainties in employment effects assessment. RIA Chapter 6 also 

provides context for understanding potential employment effects by looking at employment, 

production costs, and incremental costs in selected sectors directly or indirectly affected by the 

final rule. In EPA’s view, the development of a comprehensive and sufficient approach for 

quantitatively estimating employment effects remains an ongoing challenge, which EPA is 

addressing via a carefully structured review of methods for analyzing the economy-wide effects 

of environmental regulations, including employment effects. Until completion of this effort, and 

associated development of improved methods for analyzing employment effects, EPA will not 

provide estimates that, in EPA’s view, are based on an inadequate or insufficiently validated 

methodology.

In summary, given the multiplicity of factors affecting employment, the conflicting character of 

their effects, and the likelihood that effects will vary substantially by industry, EPA concluded 

that the steam electric ELG regulation could have a range of employment effects – overall 

increases or decreases in employment, and with varying effects over time. Ultimately, however, 

the EPA concluded that, in no event, would these employment effects be so substantial that they 

would change EPA’s decision about what limitations and standards it should adopt for the final 

rule. As stated above, in EPA’s view, in the absence of a robust quantitative employment effects 

methodology and adequate data, and in light of the very small increases in electricity rates 

expected to result from the rule, the qualitative employment effects analysis undertaken for the 

final rule is appropriate to produce an informed regulatory result.

Commenter Name: Basil G. Constantelos

Commenter Affiliation: Midwest Generation, LLC.

Document Control Number: EPA-HQ-OW-2009-0819-4464-A1

Comment Excerpt Number: 2

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Midwest Gen encourages EPA to apply Executive Order 13563 calling for greater flexibility in 

regulatory implementation.

Comment Response: 

The commenter asks for flexibility in regulatory implementation. See response to DCN EPAHQ-OW-2009-0819-4183-A2, Excerpt Number 22, for a discussion of how the final steam 
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electric ELGs establish a flexible implementation period that provides steam electric power 

plants with sufficient time to consider their strategy to comply with the final requirements.

Commenter Name: Daniel Simmons

Commenter Affiliation: Institute for Energy Research

Document Control Number: EPA-HQ-OW-2009-0819-4473-A1

Comment Excerpt Number: 2

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Failing to quantify these important climate change indicators deprives the public of an 

opportunity to fully participate in the regulatory process because by excluding the information, 

EPA is not including relevant scientific and technical findings. This is specifically forbidden by 

President Obama’s Executive Order 13563.

Executive Order 13563 requires:

Sec. 2. Public Participation. (a) Regulations shall be adopted through a process that involves 

public participation. To that end, regulations shall be based, to the extent feasible and consistent 

with law, on the open exchange of information and perspectives among State, local, and tribal 

officials, experts in relevant disciplines, affected stakeholders in the private sector, and the public 

as a whole.

(b) To promote that open exchange, each agency, consistent with Executive Order 12866 and 

other applicable legal requirements, shall endeavor to provide the public with an opportunity 

to participate in the regulatory process. To the extent feasible and permitted by law, each 

agency shall afford the public a meaningful opportunity to comment through the Internet on any 

proposed regulation, with a comment period that should generally be at least 60 days. To the 

extent feasible and permitted by law, each agency shall also provide, for both proposed and final 

rules, timely online access to the rulemaking docket on regulations.gov, including relevant 

scientific and technical findings, in an open format that can be easily searched and downloaded. 

For proposed rules, such access shall include, to the extent feasible and permitted by law, an 

opportunity for public comment on all pertinent parts of the rulemaking docket, including 

relevant scientific and technical findings. [emphasis added]

By failing to provide the public with this important information regarding projected impacts on 

climate change indicators such as temperature and sea level, EPA has not appropriately assessed 

the reductions in carbon dioxide emission from this regulation.

Comment Response: 
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See response to DCN EPA-HQ-OW-2009-0819-4473-A1, Excerpt Number 1 (in Section 29.h) 

regarding the commenter’s statement that EPA “fail[ed] to quantify . . . important climate change 

indicators.”

Regarding the more general comment regarding public participation (which the commenter 

raises in the context of the impacts of changes in CO2emissions), EPA disagrees. For the CO2-

related benefits, as for other analyses supporting the final ELG, EPA used appropriate and wellaccepted approaches and data to develop as comprehensive an analysis of the benefits as possible 

given the available data, methods, and scope of the rule. EPA described its approach in detail in 

supporting documents (TDD, EA Report, RIA, BCA, and others) provided in the docket for the 

proposal and received numerous comments that indicated not only significant public interest in 

the process, but significant participation in addressing substantive analytic and policy issues. 

EPA extended the period for the public to comment on the proposed rule to give over 100 days 

for stakeholders to review the material and provide input for the rulemaking. As described in the 

preamble and elsewhere in the rulemaking record, EPA also engaged with the regulated 

community and the public in other ways, such as meetings and conference calls with 

stakeholders, throughout the development of this rule.

Commenter Name: Winslow Sargeant

Commenter Affiliation: U.S. Small Business Administration, Office of Advocacy

Document Control Number: EPA-HQ-OW-2009-0819-4477-A1

Comment Excerpt Number: 22

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Given that the record lacks the specific underlying data and analyses to facilitate informed 

comment on the RFA certification and the costs and benefits of this proposal, Advocacy believes 

that the agency has not complied fully with the transparency requirements of Executive Order 

13563.7

7

January 18, 2011, Executive Order 13563.

Comment Response: 

EPA disagrees with the commenter that the Agency has not adequately complied with the Office 

of Management and Budget’s Executive Order 13563 implementation guidance regarding 

transparency. EPA conducted the rulemaking process in accordance with the standard of 

transparency prescribed by Executive Order 13563. As such, EPA has established an official 

public docket for this action under Docket ID EPA-HQ-OW-2009-0819. The official public 

docket consists of the documents specifically referenced in today’s rulemaking action, any public 
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comments received, and other information related to this action. Confidential business 

information and other information, the disclosure of which is restricted by law, are a part of the 

official record for the rule, though this information is not available in the public docket. The 

Agency made every effort possible to accommodate requests for confidential and copyrighted 

information used in this rulemaking consistent with law. EPA responded to information requests 

and has made every effort possible to provide assistance to the public to access and understand 

data used, to the extent allowed by the confidential business information requirements at 40 CFR 

Part 2. With respect to specifically to the information underlying EPA’s RFA analysis, see 

response to DCN EPA-HQ-OW-2009-0819-4477-A1, Excerpt Number No. 23 (in comment code 

28.e).

Given the longstanding discussions of issues related to steam electric industry discharges over 

many years, EPA provided sufficient time for the regulated community and others to review and 

comment on these materials and their potential effects on EPA’s selection of regulatory options. 

EPA made substantial efforts to help explain the issues involved with the Steam Electric ELGs, 

and it has met with many stakeholders beginning very early in the rulemaking process and 

throughout. This outreach is documented elsewhere in the rulemaking record.

Commenter Name: Vicki Card

Commenter Affiliation: Colorado Springs Utilities

Document Control Number: EPA-HQ-OW-2009-0819-4483-A1

Comment Excerpt Number: 12

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

COST BENEFIT ANALYSIS

EPA has proposed multiple rules in the last several years targeted at the electric power 

generating industry. The cumulative costs associated with complying with these rules, including 

the proposed ELG rule, are substantial. [...]

Colorado Springs Utilities therefore respectfully requests that EPA consider the benefit to human 

health, public safety, the economy and national security that come with having reliable, 

affordable, redundant sources of electricity when conducting cost benefit 

analysis of rules affecting the electric power generating industry. These benefits are not 

typically included in EPA's regulatory analysis. The cumulative impact of multiple regulations 

on the affordability and reliability of the nation's electric power supply should also be considered 

each time a new rule is proposed or an existing rule is amended.
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7 Colorado Springs Gazette, 2013. The Road to a Longer Life by Laura Helmuth. Section D 

Page 1. Tuesday, September 17, 2013.

Comment Response: 

With respect to the commenter’s statement about the “substantial” costs to industry of complying 

with multiple rules affecting the electric power generating industry, see response to DCN EPAHQ-OW-2009-0819-4183-A2, Excerpt Number 22, regarding EPA’s consideration of other rules 

affecting the electric power industry in developing the final steam electric ELGs.

With respect to the commenter’s statement about having “affordable” and “reliable” sources of 

electricity, EPA determined that the final rule is economically achievable for the steam electric 

industry as a whole. In particular, the final rule is projected to result in a net reduction of 843 

MW in steam electric generating capacity (0.2 percent of the baseline capacity) as of model year 

2030, reflecting full compliance by all plants, which corresponds to a net effect of two 

generating unit (partial) closures and one plant (full) closure. EPA assesses that these retirements 

are inconsequential relative to total national and regional generating capacity. Furthermore, these 

retirements are offset by increased capacity for other plants. As a result, the final rule will not 

significantly affect electric supply reliability – either nationally or by NERC region. 

Furthermore, EPA estimated the potential increase in cost per unit of electricity sales for the U.S. 

under the final rule to be 0.013 cents, with costs by NERC region ranging from 0.000 cents per 

kWh to 0.027 cents per kWh. This estimate is based on a conservative assumption of 100 percent 

pass-through of compliance costs to electricity prices and, to the extent that some plants are not 

able to pass compliance costs onto consumers, is an overstatement of the potential impact of the 

final rule.

Commenter Name: Quinlan J. Shea III

Commenter Affiliation: Edison Electric Institute (EEI)

Document Control Number: EPA-HQ-OW-2009-0819-4487-A1

Comment Excerpt Number: 12

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The cumulative impact of the multiple regulations facing the electric utility industry, if not the 

individual regulations themselves, already is forcing some plant closures and threatening to 

strand newly upgraded assets.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4183-A2, Excerpt Number 22, regarding EPA’s 

consideration of other environmental rules, in addition to the final steam electric ELGs, affecting 

the electric power sector.
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Commenter Name: Quinlan J. Shea III

Commenter Affiliation: Edison Electric Institute (EEI)

Document Control Number: EPA-HQ-OW-2009-0819-4487-A1

Comment Excerpt Number: 117

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

To ensure that electricity rates can remain reasonable and electricity supply and delivery can 

remain reliable, EPA needs to ensure that the steam electric ELGs are accurate, representative, 

sound, reasonable, and flexible, and comply with the APA, CWA section 304(b), Executive 

Order 13563, and other applicable requirements.

Comment Response: 

The commenter expresses a concern that the final rule ensure that electricity rates “remain 

reasonable” and electricity supply and delivery “remain reliable.” EPA analyzed the impacts on 

electricity rates, and supply and delivery associated with the final steam electric ELGs, as 

detailed in the RIA, and found that the final rule would have minimal impacts. For example, see 

Chapter 7 which discusses electricity rate impacts and Section 10.6 which addresses Executive 

Order 13211: Actions Concerning Regulations That Significantly Affect Energy Supply, 

Distribution, or Use.

The commenter does not identify specific issues that would suggest that the ELGs are not 

“accurate, representative, sound, reasonable and flexible.” Nonetheless, regarding these topics, 

see response to DCN EPA-HQ-OW-2009-0819-4487-A1, Excerpt Number No. 126.

The also commenter does not identify specific issues that would suggest that EPA did not 

comply with “APA, CWA section 304(b), Executive Order 13563, and other applicable 

requirements” in developing the ELGs. However, EPA notes that it has complied with all

requirements specified in the CWA, other statutes, and Executive Order, as discussed in the 

preamble and detailed in the RIA for the final rule.

Commenter Name: Thomas H. Adams

Commenter Affiliation: American Coal Ash Association (ACAA)

Document Control Number: EPA-HQ-OW-2009-0819-4511-A2

Comment Excerpt Number: 13

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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Disregarding the impact of this rulemaking on beneficial use would be a significant 

violation of administrative policy.

Successive administrations have issued executive orders (12866 and 13563) that compel EPA to 

consider the impact of its proposed regulations on all sectors of society and the economy. 

Specifically, Executive Order 13563, entitled “Improving Regulation and Regulatory Review” 

(Jan. 18, 2011), instructs federal agencies, including EPA, to assess benefits and costs of 

regulations in an effort to “impose the least burden on society, consistent with obtaining 

regulatory objectives, taking into account, among other things, and to the extent practicable, the 

costs of cumulative regulations.” The order also directs consideration of alternative regulatory 

approaches and allowance for public participation in the rulemaking process.

As stated earlier, any decision by EPA to disregard information on CCR beneficial use would 

exclude from the cost‐ benefit analysis consideration of the fate of more than 40 percent of the 

CCRs generated annually in the U.S. It would further disenfranchise the participation of tens of 

thousands of individuals and entities who submitted testimony on beneficial use in public 

hearings and the public comment process surrounding the agency’s proposed rule. Both 

consequences would be direct and substantial violations of the executive orders.

Comment Response: 

EPA does not agree with the commenter that the final rule “disenfranchise[s] the participation of 

tens of thousands of individuals and entities who submitted testimony on beneficial use in public 

hearings and the public comment process.” EPA did consider the comments and testimony of the 

public, submitted during the public comment period for this rule, on its analysis of the benefits 

associated with increased CCR marketability, as evidenced by EPA’s responses to public 

comments submitted. As noted in the Agency’s response to a related comment (DCN EPA-HQOW-2009-0819-4511-A2, Excerpt Number 7 (in comment code 29.a)), as part of the final rule 

analysis, EPA quantified the potential benefits associated with increased CCR marketability. 

This analysis addresses the commenter’s concerns regarding the exclusion of these potential 

benefits, although EPA notes that EPA had analyzed the benefits qualitatively at proposal and 

did not disregard them, as claimed by the commenter.

Commenter Name: Floyd Gilzow

Commenter Affiliation: Missouri Joint Municipal Electric Utility Commission (MJMEUC)

Document Control Number: EPA-HQ-OW-2009-0819-4576-A1

Comment Excerpt Number: 1

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In particular, Executive Order 13563 directs agencies to take into account “to the extent 

practicable, the costs of cumulative regulations.” A memorandum for the heads of executive 
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departments and agencies, issued March 20, 2012, by the Administrator of the Office of 

Regulation and Regulatory Affairs, directs that, so far as the law allows, “agencies should take 

active steps to take account of the cumulative effects of new and existing rules and to identify 

opportunities to harmonize and streamline multiple rules.” Where appropriate and feasible, 

agencies should consider cumulative effects and opportunities for regulatory harmonization as 

part of their analysis of particular rules, and should carefully assess the appropriate content and 

timing of rules in light of those effects and opportunities. Also, the memorandum reminds 

agencies that they should choose regulatory approaches that “maximize net benefits.”

The electric generation industry, including public power or community‐owned utilities, face a 

host of rigorous new requirements including several Clean Air Act (CAA) regulations, the Coal 

Combustion Residuals rule (CCR), and the Clean Water Act (CWA) § 316(b) intake aquatic 

protection fine structure rule (expected by November 2013) and the CO2 regulations for new and 

existing power plants. The Environmental Protection Agency (EPA) needs to evaluate the 

cumulative impact of these regulations as part of its assessment of the proposed effluent 

guidelines rule. The Office of Management and Budget (OMB) guidance and Executive 

Order 13563 require EPA to consider the cumulative effects of regulations and seek to reduce 

overlapping and inconsistent requirements.

Comment Response: 

EPA disagrees with the commenter’s suggestion that the Agency did not consider the potential 

cumulative effects of certain other environmental regulations in its analyses or in developing the 

final ELG requirements. EPA’s response to a related comment (DCN EPA-HQ-OW-2009-0819-

4183-A2, Excerpt Number 22) describes the multiple ways in which EPA accounted for the 

potential cumulative effects of environmental regulations on the electric power industry, as well 

as how the Agency coordinated among rulemakings affecting the electric power sector. EPA also 

carefully considered the substantive requirements of the final rule to ensure that they would not 

create inconsistent or duplicative requirements with other rules. For example, the final rule does 

not establish Best Management Practice for surface impoundments, since the final CCR rule 

already establishes such BMPs.

Commenter Name: Kevin D. Frizzell

Commenter Affiliation: Owensboro Municipal Utilities (OMU) Elmer Smith Station (ESS)

Document Control Number: EPA-HQ-OW-2009-0819-4683-A2

Comment Excerpt Number: 1

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

OMU ESS supports responsible environmental regulation aimed at protecting public health and 

the environment in a cost-effective manner that will also provide appropriate protection for the 

economic well-being of the community we serve and the markets in which we operate. 
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Nonetheless, OMU ESS has increasing cost burdens with the Mercury and Air Toxic Standards 

Rule, 316(b) Cooling Water Intake Structure Rule, Coal Combustion Residuals Rule, and these 

ELG rules.

Comment Response: 

As noted in responses to other comments (e.g., DCN EPA-HQ-OW-2009-0819-4183-A2, 

Excerpt Number 22) and in the preamble for the final rule, EPA specifically considered the 

potential cumulative effects of multiple environmental regulations in its analyses for the final 

steam electric ELGs, and the Agency determined that the final rule is economically achievable 

for the industry as a whole, as required by the CWA.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 31

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

As discussed in the next sub‐section, benefit‐cost analysis compares complete (and sometimes 

overestimated) costs of compliance with incomplete (and very often underestimated) social 

benefits. EPA’s qualitative analysis and—where data exist—empirical treatment of human health 

and environmental impacts is detailed and helpful to understanding the many important positive 

benefits of strengthening the steam electric ELGs. In contrast, EPA’s monetization of benefits 

that are never traded in a market and are, quite literally, priceless is incomplete, inaccurate, 

and—to the extent that it distracts from the legitimate decision‐making process associated with 

the Clean Water Act—unhelpful.

[...]

Uncertainty affects many aspects of EPA’s massive evaluation of costs and benefits of the 

proposed steam electric ELGs. As in many benefit‐cost analyses, the uncertainties are not 

symmetrical: costs of meeting a standard, commonly based on ex ante engineering estimates, are 

often overestimates of actual, ex post compliance costs, while health and environmental benefits 

of the same standard are surrounded by different types of uncertainty. Standard practices in 

calculation of monetized benefits, particularly the high threshold requirements for including any 

nonzero value, tend to underestimate the true magnitude of benefits.

The result is a systematic imbalance in EPA’s benefit‐cost analyses: Complete and sometimes 

overestimated costs of regulation are weighted against incomplete and often underestimated 

benefits of regulation. It can be no surprise that, using this highly biased methodology, costs 

exceed the measured benefits of the proposed steam electric ELGs.
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Comment Response: 

EPA agrees with the commenter that there is almost an unavoidable asymmetry in the evaluation 

of the costs and benefits of effluent guidelines regulations, where there is a tendency for costs to 

be overstated and benefits understated. The Agency specifically recognizes this asymmetry in its 

discussion of the analyses for the final rule, noting limitations of the benefits analysis where 

several potentially significant benefits are not fully quantified or monetized. It is welldocumented that there are difficulties associated with measuring and monetizing all categories of 

benefits, which EPA cannot solve in their entirety through one rulemaking. Nevertheless, as 

detailed in the BCA, EPA used sound data and methodologies to quantify and monetize benefits 

associated with the ELGs where possible. EPA, therefore, disagrees that the monetization of 

benefits as presented in the BCA is “inaccurate” and “unhelpful.” Finally, while the Agency 

considers benefit-cost analysis as informative in the ELG rulemaking process, and it is 

something that is done pursuant to Executive Order, EPA based the final rule on factors that the 

Clean Water Act (sections 301 and 304) expressly directs EPA to consider when establishing 

Best Available Technology Economically Achievable (see Section VIII.C. of the preamble). 

Regarding the role of cost-benefit analysis in EPA’s decisions on the final steam electric ELGs, 

see response to DCN EPA-HQ-2009-0819-4464-A1, Excerpt Number 3 (in comment code 6.e).

Commenter Name: Kelly Jean Heffner

Commenter Affiliation: Pennsylvania Department of Environmental Protection

Document Control Number: EPA-HQ-OW-2009-0819-4811-A1

Comment Excerpt Number: 6

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In recent years, industry has been the subject of significant rulemakings by EPA. While EPA 

considers this Proposal singularly, such a view is not useful. The cumulative effects of EPA's 

rules should be weighed during the promulgation of rules. More importantly, as much flexibility 

as is reasonably possible must be provided to ensure compliance is timely, cost effective and fair 

on the National front.

Comment Response: 

EPA disagrees that EPA considered the ELG “singularly.” See response to DCN EPA-HQ-OW2009-0819-4183-A2, Excerpt Number 22, regarding EPA’s consideration of the other rules 

affecting the electric power sector in developing the final steam electric ELGs.

Commenter Name: Theresa Pugh

Commenter Affiliation: American Public Power Association (APPA)
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Document Control Number: EPA-HQ-OW-2009-0819-5140-A2

Comment Excerpt Number: 1

External Review Flag: Engineering

External Review Incorporated into Response: No

Comment Excerpt: 

The steam electric industry, including public power or community-owned utilities, face a host of 

rigorous new requirements including several Clean Air Act (CAA) regulations, the Coal 

Combustion Residuals rule (CCR), the Clean Water Act (CWA) § 316(b) intake aquatic 

protection structure rule (expected by November 2013), and the greenhouse gas emissions 

regulations for new and existing power plants. The Environmental Protection Agency (EPA) 

needs to evaluate the cumulative impact of these regulations as part of its assessment of the 

proposed effluent guidelines rule. The Office of Management and Budget (OMB) guidance and 

Executive Order 13563 require EPA to consider the cumulative effects of regulations and seek to 

reduce overlapping and inconsistent requirements.

In particular, Executive Order 135631directs agencies to take into account “to the extent 

practicable, the costs of cumulative regulations.” A memorandum for the heads of executive 

departments and agencies, issued March 20, 2012, by the Administrator of the Office of 

Regulation and Regulatory Affairs, directs that, so far as the law allows, “agencies should take 

active steps to take account of the cumulative effects of new and existing rules and to identify 

opportunities to harmonize and streamline multiple rules.”2 Where appropriate and feasible, 

agencies should consider cumulative effects and opportunities for regulatory harmonization as 

part of their analysis of particular rules, and should carefully assess the appropriate content and 

timing of rules in light of those effects and opportunities. Also, the memorandum reminds 

agencies that they should choose regulatory approaches that “maximize net benefits.”

It is with these executive branch policy directives, in tandem with the CWA’s historical record 

on setting Best Available Technology (BAT)3considering remaining life of plant and feasibility, 

that APPA asks EPA to consider APPA’s recommendations.

1

http://www.whitehouse.gov/sites/default/files/omb/inforeg/eo12866/eo13563_01182011.pdf.

2

http://www.whitehouse.gov/sites/default/files/omb/assets/inforeg/cumulative-effectsguidance.pdf.

3BAT is defined at Section 304(b)(2) of the CWA. In general, BAT represents the best available 

economically achievable performance of plants in the industrial subcategory or category. The 

factors considered in assessing BAT include the cost of achieving BAT effluent reductions, the 

age of equipment and facilities involved, the process employed, potential process changes, and 

non-water quality environmental impacts, including energy requirements and other such factors 

as the EPA Administrator deems appropriate. EPA retains considerable discretion in assigning 

the weight according to these factors. BAT limitations may be based on effluent reductions 

attainable through changes in a facility's processes and operations. Where existing performance 

is uniformly inadequate, BAT may reflect a higher level of performance than is currently being 
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achieved within a particular subcategory based on technology transferred from a different 

subcategory or category. BAT may be based upon process changes or internal controls, even 

when these technologies are not common industry practice. 

http://water.epa.gov/scitech/wastetech/guide/questions_index.cfm#bat

Comment Response: 

With respect to the commenter’s statement about evaluation of the potential cumulative impact 

of regulations in developing the final steam electric ELGs, see response to DCN EPA-HQ-OW2009-0819-4183-A2, Excerpt Number 22. EPA also carefully considered the substantive 

requirements of the final ELGs to ensure that they would not create inconsistent or duplicative 

requirements with other rules. For example, the final rule does not establish Best Management 

Practice for surface impoundments, since the final CCR rule already establishes such BMPs.

With respect to the commenter’s statement about “remaining life of plant and feasibility,” see 

response to DCN EPA-HQ-OW-2009-0819-3920-A1, Excerpt Number 151 (in comment code 

5.b).
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28.l. Econ – Other comments 

Commenter Name: R. W. Greene

Commenter Affiliation: Mercatus Center at George Mason University

Document Control Number: EPA-HQ-OW-2009-0819-3411-A1

Comment Excerpt Number: 19

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

 There will be a general tightening across the board on these emissions, but they affect a 

small part of the generating industry (just over 1000 plants in 2010).

 The EPA claims high benefits and low costs, but it has not carried out a complete benefitcost analysis. Since benefits and costs may easily be higher or lower than the estimates, 

the EPA has not really calculated anything and cannot really claim anything other than an 

unquantified statement that the proposals are a good thing.

 The EPA has made many spurious, rule-of-thumb type assumptions in analyzing this 

proposal and gives the impression that it would have found a basis for proceeding with 

tighter regulation regardless of the underlying economics. The approach seems to reflect 

a common administra tive view that quantification, however spurious, is a valuable 

exercise.

 Poor analysis may be worse than useless, but that is not the impression given by this 

regulatory proposal and associated regulatory impact assessment.

 Is there a systemic problem to be addressed in the steam electric industry? It seems as 

though the regulator is gaining information about possible improvements because they 

are happening in parts of the baseline existing development of the sector. It requires a 

major research project to explain why these practices appear to be growing without 

regulatory change. Likely expla nations are the need to avoid workplace hazards and the 

risk of being liable for damages in tort vis-à-vis the local community. The EPA does not 

consider baseline momentum apart from making a claim that current effluent levels are 

simply too high.

 With admittedly poor quantification of benefits, the most that the EPA can claim is that it

has assessed the costs of 

achieving certain technical changes in regulation that are motivated by command and con

trol concerns. Better understanding of why best practices are improving and diffusing 

would help the EPA determine whether a new regulation is needed at all or which 

alternative approaches might better help reduce emissions at lower cost.

Comment Response: 

The commenter raises several, sometimes interrelated points for consideration. These points are 

addressed below:

In the first bullet, the commenter notes that the general tightening of the “emissions” (which the 

Agency took to be the same as discharges in the context of this rule) affects a small part of the 
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generating industry. Whether this is raised as a concern is unclear. This statement, however, is 

consistent with EPA’s determination that the technology bases for the final rule (or other 

technologies or processes capable of meeting the final effluent limitations and standards) are 

currently employed by a significant number of plants (i.e., they are available and welldemonstrated technologies). See preamble Section VIII.

In bullets 2 through 4, the commenter raises concerns about the quality and usefulness of the 

costs and benefits analyses. EPA addressed the general concerns in responses to related 

comments. For example, see DCN EPA-HQ-OW-2009-0819-3411-A1, Excerpt Numbers 8 and 

11 (comment code 28.b). Regarding the basis for the decision to proceed with regulation, EPA 

described the extensive process it followed prior to initiating the rulemaking in the preamble for 

the proposed rule and summarized the process in the preamble for the final rule. This process 

included a review of national effluent guidelines, in accordance with Section 304(m) of the 

CWA, a detailed study of the industry, as well as input from industry, environmental groups, and 

other stakeholders. In deciding to proceed with a rulemaking, EPA considered the significant 

pollutant loadings attributable to this industry alone, as well as the fact that there had been 

significant changes in the industry since the last time the ELGs were revised, and that there were 

available technologies for controlling pollutant discharges from the industry other than surface 

impoundments, upon which the previously established regulations were mostly based. EPA’s 

decision to initiate a rulemaking and its decisions as to the content of the fine rule were based on 

a consideration of “cost,” consistent with the statute, but not on a cost-benefit analysis. EPA 

determined that the final rule is economically achievable (i.e., affordable) for the industry as a 

whole. See preamble section VIII and the RIA. For the role of benefit-cost in EPA’s decisions 

for the final rule, see response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 in 

comment code 6.e.

Finally, the commenter appears to be concerned about EPA using current industry trends as the 

basis for the regulation and asking whether there is a systematic problem in the industry that 

requires a regulatory approach (bullets 5 and 6). EPA notes that section 304(m) of the CWA 

directs EPA to develop a plan for issuance of new regulations and revision of existing 

regulations for categories of industrial wastewater discharges. Part of this review involves 

evaluating advances in treatment technologies and changes in industry processes that may 

warrant ELG revisions. As mentioned above, EPA described in the detailed study and preambles 

for the proposed and file rule the “problem” that EPA is aiming to redress by revising the ELGs: 

The previously established regulations, which were last updated in 1982, do not adequately 

address the toxic pollutants discharged from the electric power industry, nor have they kept pace 

with process changes that have occurred over the last three decades. The development of new 

technologies for generating electric power (e.g., coal gasification) and the widespread 

implementation of air pollution controls (e.g., flue gas desulfurization (FGD), selective catalytic 

reduction (SCR), and flue gas mercury controls (FGMC)) have altered existing wastestreams or 

created new wastewater streams at many power plants. As a result, each year the pollutant 

discharges from this industry are increasing in volume and total mass, and currently account for 

approximately 30 percent of all toxic pollutants discharged into surface waters by all industrial 

categories currently regulated under the CWA. There are affordable technologies that are widely 

available, and already in place at some plants, which are capable of reducing or eliminating 
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steam electric power plant discharges. In the several decades since the steam electric ELGs were 

last revised, such technologies shave increasingly been used at plants.

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 103

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The cost of zero discharge of bottom ash and fly ash can be very prohibitive for small units, and 

those units would be better off closing, which isn't as good an option for certain people, than 

having those costs, but that is something that needs to be considered under the Clean Water Act.

Comment Response: 

The final rule includes a zero discharge requirement for fly ash and bottom ash transport water 

and FGMC wastewater (based on dry handling and/or closed-loop systems) for existing sources 

that are not oil-fired generating units nor are less than or equal to 50 MW in nameplate 

capacity. For generating units that are 50 MW or less or that are oil-fired, the final rules 

establishes BAT limitations and PSES for these wastestreams (and others) that are equal to 

previously established BPT limitations, based on use of a surface impoundment. As explained in 

the preamble to the final rule, the differentiated BAT/PSES requirements for oil-fired generating 

units and units of 50 MW or less will alleviate some of the concerns raised by various 

commenters about possible comparatively higher costs faced by small units, as defined in this 

rule. As explained in the preamble, EPA concluded that the final limitations and standards are 

economically achievable (i.e., affordable) for the industry as a whole. EPA projects net capacity 

retirement of 843 MW (0.2 percent), corresponding to a net closure of 2 units or one plant, as a 

result of the final rule. See Chapter 5 of the RIA for details.

For more about applicability thresholds for small units, see comment EPA-HQ-OW-2009-0819-

4317-A1, Excerpt Number 30 (in comment code 28.e) and responses to comments in comment 

code 5c.

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 160

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

We also think the agency may have underestimated some pollutant removal cost per pound, and 

our preliminary calculations suggest that EPA's estimates of removing a toxic weighted pound 

equivalent are significantly underestimated for a number of waste streams, including bottom ash 

and fly ash. As a result, your cost effectiveness analysis will probably need to be revisited, we 

believe.

Comment Response: 

EPA has revised the pollutant removals, costs, and cost-effectiveness calculations and data as 

part for its analyses of the final ELG. The revised values are provided in the preamble, with 

details provided in the TDD and the RIA for the final rule. For the role of cost-effectiveness in 

EPA’s decisions for the final rule, see response to DCN EPA-HQ-OW-2009-0819-4655, Excerpt 

Number 27 in Comment Code 6.h.

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 200

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The rule should also -- and this is very important -- minimize cost to customers and be consistent 

with the industry's ongoing investments to transition to a cleaner generating fleet with an 

enhanced electric grid.

Comment Response: 

The final rule establishes limitations and standards applicable to the discharge of pollutants from 

the steam electric power generating industry based on the “best available technology 

economically achievable” and the “best available demonstrated control technology,” as those 

terms are used in sections 301, 304, and 306 of the Clean Water Act.

EPA determined that the technologies that form the basis for regulatory Option D and Option F 

represent Best Available Technology Economically Achievable (except for discharges from 

“small” or oil-fired generating units) and Best Available Demonstrate Control Technology, 

respectively, because these technologies are available, demonstrated, and economically 

achievable (i.e., affordable) for the industry as a whole, and they have acceptable non-water 

quality environmental impacts, as required by the Clean Water Act (see preamble Section VIII).
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EPA's analyses show that the final rule achieves results consistent with the objectives sought by 

the commenter. As documented in the RIA, EPA’s analysis projected minimal impacts on 

electricity rates as a result of the final rule. As reported in Chapter 7 of the RIA, EPA estimated 

the potential increase in cost per unit of electricity sales for the U.S. under the final rule to be 

0.013 cents per KWh, with costs by NERC region ranging from 0.000 cents per KWh to 0.027 

cents per KWh (see Section 7.2.2 in RIA). This estimate is based on a conservative assumption 

of 100 percent pass-through of compliance costs to electricity prices and to the extent that some 

plants are not able to pass compliance costs onto consumers, is an overstatement of the potential 

impact of the final rule.

In response to other comments EPA received on the proposed ELG, the Agency also looked at 

the distribution of the impacts of the final ELG across households and found that the incremental 

economic burden of the final rule on households is small both relative to income and relative to 

the baseline energy burden of households in different income ranges (see Section 7.4.3 in RIA).

Regarding consistency with the objective of a cleaner generating fleet, EPA's analyses show 

lower projected air pollutant emissions under the final ELGs than in the baseline, due to shift of 

electricity generation toward lower emitting electricity generating units. See Chapter 7 of the 

BCA for air-related benefits of the final ELGs.

Commenter Name: Jamie Rhodes

Commenter Affiliation: Environment Council of Rhode Island

Document Control Number: EPA-HQ-OW-2009-0819-4034-A2

Comment Excerpt Number: 10

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

When considering costs, the Clean Water Act allows EPA to evaluate whether costs can 

be reasonably borne by the industry as a whole.13 EPA acknowledges in its proposal that Option 

5 would by far remove the largest amount of pollutants from power plant discharges, resulting 

in the greatest benefit to public health and the environment.14 And EPA has estimated that 

most utilities would only incur costs of less than 1% of annual revenue.15 Yet the Agency claims 

it did not select Option 5 as a “preferred” option because of concern that it is too expensive 

when compared with the other options. Clearly this industry can bear the comparatively small 

cost to comply with requirements mandated by the Clean Water Act to clean up their toxic 

discharges. Society has been unfairly forced to bear the cost of these discharges for decades.

13See Waterkeeper Alliance v. U.S. EPA, 399 F.3d 486, 516 (2d Cir. 2005) and Rybachek v. U.S. 

EPA, 904 F. 2d 1276, 1290-91 (9th Cir. 1990)
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14Id. at 34,473

15Id. at 34,494 (Table XI-4); 34,493

Comment Response: 

The commenter supports proposed Option 5, which is substantially similar to the Option F 

described in the final rule preamble (see preamble section VIII). Proposed Option 5 and Option F 

include evaporation as the technology basis for control of FGD wastewater discharges. As 

discussed in the preamble, EPA did not select evaporation as the BAT basis for control of 

discharges of FGD wastewater from all existing steam electric generating units because of the 

high cost of possible regulatory requirements based on evaporation for discharges of FGD 

wastewater from existing facilities. The annual cost to the industry of limitations based on 

evaporation would be more than 2 and 1⁄2 times the cost to industry estimated for the final rule 

(after tax) (approximately $570 million more expensive than the final rule, on an annual basis, 

after tax). Given the high costs associated with the technology, and the fact that the steam 

electric industry is facing costs associated with several other rules in addition to this rule, EPA 

decided not to establish BAT limitations for FGD wastewater based on evaporation for all steam 

electric power plants. Nevertheless, as described preamble section VIII.C.13, the final rule does 

establish a voluntary incentives program under which steam electric power plants can choose to 

be subject to more stringent BAT limitations for FGD wastewater based on evaporation. Also see 

responses to comments in comment code 28.b and comment code 6.iii.

Commenter Name: Cari Boyce

Commenter Affiliation: Duke Energy

Document Control Number: EPA-HQ-OW-2009-0819-4305-A3

Comment Excerpt Number: 21

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The revised analysis should, at a minimum, include: Conducting the cost-benefit analysis on the 

incremental treatment of a technology for FGD wastewater.

Comment Response: 

EPA does not conduct cost-benefit analysis for individual treatment technologies; instead EPA 

compares options that incorporate technology control options across all the waste streams being 

regulated. For the role of benefit-cost in EPA’s decisions for the final rule, see response to 

DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 in comment code 6.e.
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Commenter Name: John McManus

Commenter Affiliation: American Electric Power System (AEP)

Document Control Number: EPA-HQ-OW-2009-0819-4448-A1

Comment Excerpt Number: 85

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

8. Cost-Effectiveness Analysis

EPA’s use of the time-value of money in 1981 dollars is inappropriate and a deliberate attempt to 

unfairly characterize the costs of compliance with the proposed rule as reasonable. The reported 

cost effectiveness of other guidelines should be escalated to current (2010) dollars in the timevalue of money construct to demonstrate the magnitude of the real incremental cost that will be 

incurred and borne by a utility’s customers, not masking these real costs in three decades old 

dollars.

Comment Response: 

EPA disagrees with the commenter’s assertion that the reporting of cost-effectiveness in 1981 

dollars is “inappropriate and a deliberate attempt to unfairly characterize the cost of compliance 

with the final rule.” First, EPA evaluates cost-effectiveness values for the regulatory options in 

1981 dollars so that they are readily comparable with cost-effectiveness values from previous 

ELGs. Second, EPA clearly presents the compliance costs in 2014 dollars throughout the 

supporting documents, notably in the preamble and RIA document, and even in the detailed 

description of the cost-effectiveness analysis prior to restating the costs to the conventional 1981 

dollars (see Appendix F in final rule RIA).

For the role of cost-effectiveness in EPA’s decisions for the final rule, see response to DCN 

EPA-HQ-OW-2009-0819-4655, Excerpt Number 27 in Comment Code 6.h.

Commenter Name: Winslow Sargeant

Commenter Affiliation: U.S. Small Business Administration, Office of Advocacy

Document Control Number: EPA-HQ-OW-2009-0819-4477-A1

Comment Excerpt Number: 6

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

B. Small Entity Costs Appear High, But the Record is Insufficient to Permit Analysis
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Advocacy is concerned about the EPA finding in Table 4-1 of the RIA that approximately half of 

all the municipally-owned and rural electric cooperative plants have cost-to-revenue ratios in 

excess of 3%. Under EPA’s own RFA guidance, if these reflect small entity costs, such large 

impacts preclude the presumption of a certification.12 Also, such a finding suggests that many 

of these plants would not be financially viable, particularly since the 3% figure is a lower bound 

for these plants. It is reasonable to expect that several plants would experience cost/revenue 

ratios exceeding 10% or 20%. Evidence of the degree of serious impact on individual plants is, 

therefore, lacking in the record. This analysis suggests that the certification may not be correct, 

but without the underlying data, we can only speculate as to its validity.

Second, this high rate of economic impact on plants generally is not consistent with EPA’s 

historic interpretation over three decades of “best available technology economically 

achieveable” (BAT) determinations, where average cost/revenue impact ratios are generally in 

the range of 1 percent or less.

Comment Response: 

Regarding the first part of the Excerpt Number (first paragraph), see response to DCN EPA-HQOW-2009-0819-4477-A1, Excerpt Number 23 (section 28.e). Also, EPA disagrees that it has not 

followed its own RFA guidance or that its certification of no SISNOSE is incorrect. As explained 

in response to DCN EPA-HQ-OW-2009-0819-4477-A1, Excerpt Number 5 in comment code 

28.a, and as described in Chapter 8 of the RIA, most of the 110 to 191 small entities owning 

plants to which the ELGs apply incur no costs under the final rule. EPA estimated that six small 

entities incur costs at or above the 1 percent cost-to-revenue threshold (i.e., 3 to 5 percent of 

small entities to which the ELGs apply), and for one of these small entities (less than 1 percent of 

small entities) the costs are at or above 3 percent (see Table 8-4 in the RIA). These findings 

support EPA’s determination of no SISNOSE based on both the small absolute number of small 

entities estimated to incur a potentially significant impact, and the small fraction of small entities 

the significantly impacted facilities represent.

The commenter does not provide data to support the assertion that the economic impact is not 

consistent with EPA’s historic interpretation of BAT determinations. EPA typically estimates the 

costs of compliance with ELGs and determines whether they are affordable to the industry as a 

whole, or whether the costs can be “reasonably borne” by the industry. Chem. Mfrs. Ass’n v. 

EPA, 870 F.2d 177, 262 (5th 1989); BP Exploration & Oil, Inc. v. EPA, 66 F.3d 66 F.3d 784, 

799-800 (6th Cir. 1996). See also Nat’l Wildlife Fed’n v. EPA, 286 F.3d 554, 570 (D.C. Cir. 

2002); CPC Int’l Inc. v. Train, 540 F.2d 1329, 1341-42 (8th Cir. 1976), cert. denied, 430 U.S. 

966 (1977). EPA has generally looked at the affordability of the costs on the industry as a whole 

(or for a subcategory of the industry, as appropriate) by analyzing the effect of the regulation on 

plant closures and, to a more limited degree, firm failures. See Nat’l Wildlife Fed’n, 286 F.3d at 

562-65; Nat’l Ass’n of Metal Finishers v. EPA, 719 F.2d 660, 666 (3d Cir. 1983); Am. Iron & 

Steel Inst., 526 F.2d at 1054; Ass’n of Pac. Fisheries, 615 F.2d at 808. The preamble to the final 

rule lays out the criteria for BAT generally (e.g., see Section IV), and EPA’s rationale for the 

BAT determinations for this final rule specifically (e.g., see Section VIII). As noted in preamble 

section VIII, EPA determined that the final rule’s costs are economically achievable for the 

industry as a whole, as their projected impact on steam electric generating capacity in terms of 
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retirements is expected to be minimal. While not a factor in EPA’s BAT determination, EPA 

notes that the average plant-level cost-to-revenue ratios for the final ELGs is well below the 1 

percent level noted by the commenter.

Commenter Name: Quinlan J. Shea III

Commenter Affiliation: Edison Electric Institute (EEI)

Document Control Number: EPA-HQ-OW-2009-0819-4487-A1

Comment Excerpt Number: 127

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The industry is investing billions of dollars to effect the current transition. But there is a tipping 

point at which additional investment becomes unaffordable. It would be bad environmental and 

economic policy to squander resources on unnecessary or excessive regulation in one area, 

limiting the ability of the industry to complete investments to meet other more beneficial 

environmental, economic, and energy regulations and goals.

The proposed steam electric ELG rule is a case in point. As discussed below, EPA has adopted 

very conservative assumptions and extrapolated from limited data to propose a rule that will have 

limited environmental benefits and significant costs. This action is not compelled by the CWA, 

which requires that controls on existing sources be available and economically achievable. If 

EPA nonetheless issues a final rule that consumes limited capital to install controls that are not 

cost-effective to pursue negligible environmental benefits, the funds expended will not be 

available to meet future EPA regulations or for other more beneficial uses.1 The cumulative 

impact of the multiple regulations facing the electric utility industry, if not the individual 

regulations themselves, already is forcing some plant closures and threatening to strand newly 

upgraded assets.

To avoid and minimize such adverse consequences, any final steam electric ELG rule needs to 

meet three objectives: (1) it should be based on accurate, representative data and sound analyses; 

(2) it should include only cost-effective requirements; and (3) it should provide for flexible 

implementation and reasonable compliance deadlines. Such objectives will help to ensure net 

benefits, minimize unnecessary costs, and allow plant owners to make rational decisions taking 

into account all the new air, water, and solid waste regulations. Meeting these objectives will 

help to ensure that electricity rates remain reasonable and electricity supply and delivery remains 

reliable as the electric power industry transitions to a more modern, lower emissions 

fleet. Unfortunately, the proposed rule does not meet these objectives

1 Utilities are still assessing how they will comply with various final and proposed EPA rules, 

such as the Mercury and Air Toxics Standards Rule, Cross State Air Pollution Rule, Cooling 
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Water Intake Structures Proposal, and Coal Combustion Residuals (CCR) Proposal. In addition, 

EPA has just today proposed a rule to control greenhouse gas emissions from electric utilities.

Comment Response: 

EPA disagrees that the final rule provides “negligible environmental benefits” as claimed by the 

commenter. The preamble, EA Report, and BCA describe the environmental improvements and 

benefits of the rule. For example, EPA estimated monetized benefits ranging between $450.6 

million to $565.6 million per year (using a 3 percent discount rate). In accordance with the Clean 

Water Act, EPA determined that the final rule is technologically available, economically 

achievable, and has acceptable non-water quality environmental impacts (see preamble section 

VIII). For the role of cost-benefit analysis in EPA’s decisions on the final rule, see response to 

DCN EPA-HQ-2009-0819-4464-A1, Excerpt Number Number 3 (in comment code 6.e).

See response to DCN EPA-HQ-OW-2009-0819-4183-A2, Excerpt Number 22, regarding EPA’s 

consideration of the cumulative impacts of multiple regulations facing the electric utility 

industry.

See response to related comment DCN EPA-HQ-OW-2009-0819-4487-A1, Excerpt Number 126 

(comment code 28.f) for a discussion of the three objectives listed by the commenter.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 75

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

2. Chemical precipitation plus biological treatment is economically achievable.

EPA has estimated that the total capital cost for the 116 plants that would need to retrofit with 

biological treatment is $2.5 billion, and that total O&M costs across these same plants would 

be $257 million. The data show that, considering the size and revenues of this industry, it can 

reasonably bear these costs.

Option 3 would increase annual costs by approximately 0.6% and increase variable production 

costs by 0.5%, and would result in no change in generating capacity.301 Option 4 would increase 

annual costs by 1.4%, variable production costs by 1%, would cause a 0.1% increase in unit 

retirements.302 Even if all of the costs of either Option 3 or Option 4 were attributed 

to biological treatment of FGD wastewater – which they are not, making it a highly conservative 

assumption – the costs could still be reasonably borne by industry.
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Although EPA did not directly evaluate the cost-to-revenue ratios for biological treatment 

standing alone, it did so for the options including a biological treatment component—Options 

2, 3, and 4—and the results confirm that this technology is affordable. Even the most expensive 

of these options, Option 4, would impose annualized compliance costs of more than 3 percent of 

revenue for only 48 out of 1,079 plants.303 Nearly 800 plants would experience no costs, 111 

plants would experience costs of less than 1 percent of annual revenues, and 117 plants would 

experiences costs of between 1 and 3 percent of annual revenues.304

The baseline cost-to-revenue analysis assumes—unrealistically—that utilities would pass on 

none of the costs to their customers. EPA did conduct a sensitivity analysis to account for the 

likelihood that 50% of these costs could be passed through to consumers; that sensitivity analysis 

illustrates the affordability even more starkly. For Option 3, assuming that plants could pass 

through 50 percent of their costs to consumers, only three plants would see a cost-to-revenue 

impact that is greater than 3 percent. For Option 4, that number increases to only ten 

plants.305 As biological treatment is a part of each of these options, it follows that it too, is 

economically achievable for the industry as a whole.

301 78 Fed. Reg. at 34,498.

302 Id.

303 RIA at Table 4-1.

304 Id.

305 RIA, Appendix B, at Table B-2.

Comment Response: 

See response to related comment DCN EPA-HQ-OW-2009-0819-4684-A1, Excerpt Number 217 

in comment code 28b.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 154

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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Using a 3% discount rate, the total social costs of Options 4 and 5 are $1.38 billion and $2.32 

billion per year, respectively.654 Using a 7% discount rate, the total social costs are $1.32 billion 

and $2.2 billion annually for Options 4 and 5.655 EPA never discloses the annual revenues of the 

plants subject to this rule, and we were unable to make the calculation ourselves because of 

revenue information redacted as CBI from the responses to the survey questionnaire. 

Nonetheless, as context for the total annual compliance costs, it is worth noting that 2011 

revenues for retail sales of electricity were $371 billion.656

The costs of both options can be reasonably borne by the industry as a whole based on the costto-revenue ratios EPA estimated. Under Option 5, nearly three quarters of the entire industry 

will have no compliance costs, and an additional 8% of plants will have costs that are less 

than 1% of revenues.657 Under Option 5, 82% of plants have costs less than 1% of revenues, and 

EPA claims that “[e]ntities incurring costs save below 1% of revenues are unlikely to face 

economic impacts.”658 According to EPA's own data and benchmarks, 82% of the industry is 

“unlikely to face economic impacts” from Option 5, which directly contradicts EPA's assertion 

that Option 5 has a “high total industry cost” and “may not be economically 

achievable.”659 Indeed, EPA states in the RIA that its entity-level cost-to-revenue analysis 

indicates that for all options, “the entity-level compliance costs are low in comparison to the 

entity-level revenues; very few entities are likely to face economic impacts at any level.”660

Moreover, by EPA’s own admission, the “screening level” cost-to-revenue analysis overstates 

the economic impacts of Options 4 and 5. EPA’s cost-to-revenue ratios are biased toward 

overestimating costs, because EPA made the “counterfactual, conservative assumption of zero 

cost pass-through” of compliance costs from utilities to ratepayers.661 In other words, EPA 

assumed that utility companies themselves would bear 100% of the compliance costs of the rule, 

despite the fact that utilities in a majority of states are regulated by public utility commissions 

pursuant to state laws that authorize utilities to incorporate environmental compliance costs into 

their rates.662 EPA conducted only one sensitivity analysis to correct this obvious bias by 

assuming that 50% of costs would be passed on to customers 

through higher rates. Unfortunately, EPA conducted the sensitivity for Option 4 but not for 

Option 5, because 

EPA eliminated Option 5 from further consideration after screening level analyses -

- that is, the cost to revenue ratio analysis erroneously assuming that the company bears 100% of 

the compliance costs. Nonetheless, EPA’s sensitivity analysis for Option 4 shows that an 

assumption of zero pass-through costs significantly biases the results of EPA’s cost-to-revenue 

analysis by showing a greater economic impact than is likely to occur, as the following table 

demonstrates.

Table 7
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Under a 50-50% split between the company and customers, Option 4 would cause 92% of plants 

to incur compliance costs less than 1% of revenues, which EPA claims is a level at which a plant 

“is unlikely to face economic impacts.” As a result, the evidence in the record does not support 

EPA's rejection of Option 4 because of compliance costs.665

Just as the 50-50 sensitivity analysis showed that the economic impacts from Option 4 would be 

far lower than EPA initially estimated, the sensitivity analysis would likely show that the 

economic impacts from Option 5 would be dramatically lower than EPA 

calculated. In particular, the number of plants and parent companies incurring compliance costs 

less than 1% of revenues would be far greater in a scenario where companies can pass on some 

of the compliance costs to customers. This undermines EPA's rationale for rejecting Option 5, 

since the sensitivity analysis shows that changing EPA's counterfactual, conservative assumption 

that companies will bear 100% of the compliance costs changes the results significantly.

Moreover, EPA has presented no basis for the cost-to-revenue thresholds it has 

selected. EPA has presented no analysis of the electric power industry to indicate that 1% or 3% 

of revenues is a meaningful number for the industry. Nor has EPA substantiated its assertions 

that costs greater than 1%, or greater than 3%, the revenues indicates economic stress. EPA has 

set the bar for economic stress much higher in other rulemakings, claiming that costs equal to 5% 

of revenue are a “moderate” impact.666 Nonetheless, even under these unsubstantiated 

thresholds, the cost- to-revenue ratios for Options 4 and 5 are comparable to the cost-to-revenue 

ratios of other final effluent guidelines.667

EPA modeling of early plant retirements caused by the rule demonstrates that the costs of 

Options 4 and 5 can be reasonably borne by the industry as a whole. EPA unjustifiably 

eliminated Option 5 at an early stage and thus did not model the impact of Option 5 on plant 

retirements. According to EPA's modeling of Option 4, however, that option would cause a net 

decrease of only .1% of total industry capacity, equivalent to 317 MW.668 This represents nine 

units expected to close early as a result of Option 4, id. at 34,472, out of over 2000 units in the 

industry.669 The percentage of plants expected to close early as a result of Option 4 are far lower 

than the projected closures for many other final effluent limitations guidelines.670 Courts have 

consistently upheld final effluent limitations guidelines that EPA projected would cause some 

plants to shut down.671 Having approved final rules determining that the Clean Water Act’s 

stringent BAT mandate required effluent limitations to be set at a level that would cause a far 

greater percentage of the affected industry to retire early, EPA has no basis for rejecting Option 4 

or 5 on the grounds that they would lead to excessive plant closures.
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Even judged by cost-effectiveness,672 which is not the appropriate test,673 both Options 4 and 5 

can be reasonably borne by the industry. Options 4 and 5 would cost $70 and $111 per 

TWPE.674 The cost-effectiveness of Option 4 is below the cost of four other final effluent 

limitations guidelines, and close to the cost of two additional final guidelines.675 The costeffectiveness of Option 5 is lower than the cost of two final effluent limitations guidelines, and is 

roughly 4 times less expensive than the most expensive guidelines EPA has promulgated.676

Even under this test – which is not the appropriate standard for EPA to use 

when determining BAT – both Options 4 and 5 pass, and are reasonable.

Every form of cost analysis that EPA has conducted indicates that the costs of both Options 4 

and 5 can be reasonably borne by the industry as a whole. Whether the agency considers total 

costs relative to total industry revenues, the cost-to-revenue ratio at the plant or parent-company 

level, plant closures, or even the unlawful cost-effectiveness metric, the costs of Options 4 and 5 

can be reasonably borne by the electric power industry. Accordingly, both Options 4 and 5 are 

economically achievable and there is no support in the record for rejecting them on economic 

grounds.

654 78 Fed. Reg. at 34,493.

655 Id.

656 EIA, Table 2.3, Revenue from Retail Sales of Electricity to Ultimate Customers, available 

at http://www.eia.gov/electricity/annual/html/epa_02_03.html.

657 78 Fed. Reg. at 34,494.

658 Id. at 34,495.

659 Id. at 34,473.

660 RIA at 4-9. EPA's parent-company level analysis showed that of 507 parent companies, only 

20 would have costs between 1% and 3% of revenues and only 15 would have costs greater than 

3% of revenues. Id. 442 parent companies would have compliance costs less than 1% of 

revenues. Id.

661 Id. at 34,494.

662 RIA at 2-18 to 2-19; see also M.J. Bradley & Associates LLC, Public Utility Commission 

Study (Mar. 31, 2011) (prepared for EPA's mercury and air toxics rule), available 

at http://www.epa.gov/airtoxics/utility/puc_study_march2011.pdf. Moreover, in many 

traditionally regulated states, the costs of environmental compliance are added to rate base and 

companies are not only reimbursed for their compliance costs but earn a rate of return on capital 

investments.
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663 All figures in this role come from 78 Fed. Reg. at 34,494.

664 All figures in this row come from RIA at B-2.

665 See 78 Fed. Reg. at 34,473.

666 See 69 Fed. Reg. 51,892, 51,916 (Aug. 23, 2004) (“facilities show additional moderate 

impacts if they are not projected to close but incur compliance costs in excess of 5 percent of 

facility revenue”).

667 50 Fed. Reg. 45,212, 45,233 (Oct. 30, 1985) (compliance costs less than 1% of revenues for 

most firms in the metal molding and casting industry); 69 Fed. Reg. 51,892, 51,917-18 (Aug. 23, 

2004) (5.8% of commercial facilities in the concentrated aquatic animal production industry 

would have costs greater than 3% of revenues under the final rule).

668 78 Fed. Reg. at 34,498.

669 Id. at 34,447.

670 65 Fed. Reg. 81,242 (Dec. 22, 2000) (11.7% of centralized waste treatment plants expected to 

close); 52 Fed. Reg. 42,522 (Nov. 5, 1987) (4% of chemicals manufacturing facilities expected 

to close); 48 Fed. Reg. 49,126 (Oct. 24, 1983) (3.8% of aluminum forming plants expected to 

close); 69 Fed. Reg. 51,892 (Aug. 23, 2004) (2.9% of concentrated aquatic animal production 

plants expected to close); 47 Fed. Reg. 52,848 (Nov. 23, 1982) (2.5% of leather tanning plants 

expected to close); 63 Fed. Reg. 18,504 (Apr. 15, 1998) (2.3% of pulp and paper mills expected 

to close).

671 See, e.g., Am. Paper Inst. v. Train, 543 F.2d 328 (D.C. Cir. 1976) (upholding BPT guidelines 

that EPA projected would cause 7-10 out of 188 paper mills to shut down); Ass’n of Pac. 

Fisheries, 615 F.2d at 808-09 (upholding BPT limits that EPA estimated would cause 33% of 

non-remote Alaskan salmon canning facilities to close and would cause 57% of non-remote 

Alaskan fresh and frozen salmon facilities to close); Weyerhaeuser, 590 F.2d at 1047 (rejecting 

challenges to effluent guidelines that EPA estimated would cause 8 plants to close); Chem. Mfrs. 

Ass'n, 870 F.2d at 250-51 (upholding as reasonable effluent guidelines that EPA stated might 

cause 14% of indirect dischargers to close).

672 In the attached report, Appendix E, Dr. Phyllis Fox notes that the cost-effectiveness for 

bottom ash conversions is inflated because EPA has overestimated the cost of converting to zero

discharge systems. See Fox Report, Appendix E, at 17. For example, EPA has calculated costeffectiveness at the unit level and ignored the cost savings from retrofitting multiple units at the 

same plant or multiple plants in the same fleet, thereby driving up the cost-effectiveness 

numbers. Id.

673 Cost-effectiveness measures cost as a function of pollutant removals at the plant level, 

whereas the proper legal test is whether the industry as a whole can reasonably bear the costs of a 

control technology. At least one circuit has held that EPA is not required to conduct a cost-
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effectiveness analysis for BAT guidelines. Responding to the argument that “EPA is under a 

duty to make a reasonable determination with regard to cost effectiveness,” the Fifth Circuit held 

that “EPA is not required to show a direct cost/benefit correlation, but only that a beneficial 

substitution is ‘technologically and economically achievable.’” API v. EPA, 858 F.2d 261, 264 

n.4 (5th Cir. 1988).

674 See 78 Fed. Reg. at 34,504.

675 RIA at D-7 to D-8 ($84, $96, $121, and $404 per TWPE for the metal molding and casting, 

pharmaceutical manufacturing B/D, aluminum forming, and electrical and electrical components 

industries, respectively, and $65 and $69 per TWPE for waste combustors and nonferrous metals 

forming and metal powders industries).

676 Id. ($121 and $404 per TWPE for the aluminum forming and electrical and electronic 

components industries).

Comment Response: 

The commenter points to results of the screening-level cost-to-revenue analyses to make the case 

that proposed options 4 and 5 are economically achievable. First, regarding the thresholds used 

by the Agency as screening-level indicators of relative impacts (i.e., 1 percent and 3 percent), 

EPA selected these thresholds more as a convention based on values also used in the 

RFA/SBREFA analyses, than based on an industry-specific analysis of the levels above which 

plant closures may be expected. The ratios indicate the potential for economic stress only to the 

extent that higher ratios are more likely to indicate such stress than the lower ratio. The use of 

general threshold is appropriate for a screening-level analysis where a key purpose is to compare 

regulatory options or to provide context for the magnitude of compliance costs relative to 

revenue. In determining that the final rule is economically achievable, EPA did not rely on its 

cost-to-revenue analyses, but considered the more detailed analysis conducted using the IPM 

model, which takes into account the electricity market where the plants operate to project 

electricity generation and plant closures.

The final rule establishes limitations and standards for existing sources based on Option D, 

which is similar to proposed Option 4, but unlike proposed Option 4, it does not contain 

limitations and standards applicable to the discharge of combustion residual leachate based on 

chemical precipitation, nor does it contain BAT limitations and PSES applicable to the discharge 

of non-chemical metal cleaning wastes. Section VIII of the preamble explains the basis for 

EPA’s decision to select Option D for existing sources, including why EPA did not identify 

chemical precipitation as the technology basis for control of pollutants in discharges of 

combustion residual leachate and its decision regarding non-chemical metal cleaning wastes. As 

explained in the preamble, EPA determined that Option D is economically achievable for the 

steam electric industry as a whole, based on its expected impacts on steam electric generating 

capacity as reflected in EPA’s IPM analysis detailed in Chapter 5 of the RIA document.
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Regarding EPA’s rejection of Option F (substantially similar to proposed Option 5) as the basis 

for BAT, see Section VIII of the preamble and EPA’s response to related comment DCN EPAHQ-OW-2009-0819-4684-A1, Excerpt Number 216 in comment code 28.b.

For the role of cost-effectiveness in EPA's decisions for the final rule, see response to DCN 

EPA-HQ-OW-2009-0819-4655, Excerpt Number 27 in Comment Code 6.h.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 219

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

2. Reliance on BPJ determinations will disproportionately affect environmental justice 

communities.

As noted above, it is challenging and rare for environmental organizations such as the 

undersigned commenters to marshal the resources to comprehensively evaluate a BAT 

determination for a particular plant. Clearly, most impacted local communities lack these kinds 

of resources. Thus, a critical flaw with relying on case-by-case BPJ determinations is that BAT 

determinations will vary by jurisdiction and, even within a single jurisdiction, may vary 

depending on whether a local community or environmental organization is able to participate in 

the administrative process and has the resources to advocate for protective permit limits. 

Communities without resources to engage in the permitting process in this way are much less 

likely to be able to compel the permitting authority to issue a permit containing strong BATbased limits. EPA should have evaluated the environmental justice implications of two of its 

preferred options—3a and 3b—which would fail to provide the same protection to underresourced communities as a uniform national standard. EPA’s environmental justice analysis 

fails to acknowledge the implications of reliance on BPJ for these groups.358

358 See 78 Fed. Reg. at 34,532; RIA at 10-2 to 10-5.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4684-A1, Excerpt Number 218 in comment 

code 28.b.
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Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 220

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

B. THE ELECTRIC POWER INDUSTRY CAN AFFORD THE TECHNOLOGIES THAT 

WOULD ELIMINATE THE DISCHARGE OF FLY ASH TRANSPORT WATER.

As explained above in Section II, the relevant test for economic achievability is whether the costs 

can be reasonably borne by the industry as a whole.394 The technologies for dry fly ash handling 

meet this test.

The economic impact of requiring dry handling of fly ash is relatively small given that the 

overwhelming majority of plants that generate fly ash already use dry handling technology. EPA 

projects that basing the BAT limits on dry handling would cause 66 plants395 to incur compliance 

costs.396 This amounts to only 12-13 percent of all coal, coke, and oil plants.397 Put 

differently, 87-88 percent of all coal and oil plants would have zero compliance costs to comply 

with a BAT standard based on dry handling of fly ash.

Even if EPA focuses on the 481 coal, coke, and oil plants that generate fly ash,398 only 14 

percent of plants would face compliance costs. And even if the agency zeroes in on coal and 

coke plants, which generate the greatest amount of fly ash, only 19% of coal and coke plants 

would face compliance costs.399 81% of coal and coke plants would face zero compliance costs 

because they already have dry handling systems in place. A rule that would lead 81% of the 

most affected plants to incur no compliance costs is economically achievable.

The total, industry-wide cost of a zero discharge standard can be reasonably borne by the 

industry. EPA calculates that the 66 plants that would have to convert to dry handling would 

spend $398 million on capital costs, $177 million on operating and maintenance costs per year, 

and an additional $20.7 million per year on 10-year recurring costs.400 We are unable to 

comment on the compliance costs for specific plants, since the plant-level data has been redacted 

by EPA.401 As a rough guide to the plant-level costs, we divided these costs by 66, the 

number of affected plants. Based on this calculation, the average plant would incur $6 million in 

capital costs and approximately $3 million in O&M costs per year.402

Whatever cost metric one uses, these costs are achievable for the electric sector as a whole. Since 

EPA has analyzed the cost of regulatory options rather than the component costs of treating 

different waste streams, we can examine the economic impact of the various options that include 

dry handling of fly ash as BAT. EPA conducted the full suite of cost analyses for only two 

options, Options 3 and 4. Option 4 includes dry handling for fly ash, and the record 
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demonstrates that Option 4 is economically achievable, which means that each of the component 

parts of Option 4—including dry fly ash handling—is economically achievable.403

For Options 3 and 4, EPA presented a cost-to-revenue screening analysis. Option 4 would 

cause 798 plants to devote 0% of their revenues to compliance costs; 117 plants would spend 1-

3% of the revenues on costs, and only 48 plants would have a cost-to-revenue ratio greater than 

3%.404 EPA asserts that “entities incurring cost below 1% of revenue are unlikely to face 

economic impacts,”405 and 84% of plants will have costs at or below 1% of revenues. This 

suggests that the industry as a whole can easily bear the cost of dry fly ash handling that is part 

of the cost of Option 4.

Option 4 would increase variable production cost by only 1% on a per megawatt hour 

basis.406 EPA modeling indicates that Option 4 would result in only a .1% increase in retirements 

(relative to the baseline capacity of the industry).407 Even if all of the costs of Option 4 were 

attributable to dry fly ash handling – which they obviously are not – the costs are so small that 

only .1% of total industry capacity would retire early.

Finally, the cost effectiveness of requiring dry handling of fly ash is $27 per TWPE,408 which is 

well within the range of cost effectiveness values EPA has found reasonable in other ELGs.409

In short, whether one determines economic achievability based on the total cost to industry, cost 

to revenue ratios, plant closures, or cost-effectiveness, dry handling of fly ash is economically 

achievable. As explained infra Section IX, it is unlawful for EPA to base its BAT determination 

on cost metrics other than the standard for economic achievability articulated by the courts, 

namely, whether the costs can be reasonably borne by the industry as a whole. But even 

assuming, for the sake of argument, that all of the cost metrics EPA has evaluated in this 

rulemaking are appropriate potential bases for a BAT determination, dry fly ash handling is 

economically achievable under any of them. Therefore, there can be no dispute that the cost of 

dry fly ash handling can be reasonably borne by the industry as a whole and therefore is 

economically achievable.

394 Waterkeeper Alliance v. EPA, 399 F.3d 486, 516 (2d Cir. 2005); Rybachek v. EPA, 904 F.2d 

1276, 1290-91 (9th Cir. 1990); Am. Iron & Steel Inst. v. EPA, 526 F.2d 1027 (3d. Cir. 1975).

395 This excludes certain small (<50MW) and oil-fired units. If those plants are included, 76 

plants would incur costs to convert from wet-sluicing to dry vacuum handling of fly 

ash. Incremental Costs and Pollutant Removals at 7-4.

396 Id. at 7-4 n.43.

397 See TDD at 4-16 (calculating that there are 527 to 552 coal, coal, and oil plants).

398 Id. at 7-22.
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399 Id. at 7-23.

400 Id. at 9-40.

401 See Appendices to Incremental Costs and Pollutant Removals.

402 TDD at 9-40.

403 Like Option 4, Option 3 is economically achievable. However, in the technologies proposed 

as BAT for waste streams other than fly ash transport water fall, Option 3 falls far short of what 

the Clean Water Act requires.

404 78 Fed. Reg. at 34,494.

405 78 Fed. Reg. at 34,495.

406 78 Fed. Reg. at 34,498.

407 Id.

408 TDD at 8-34.

409 RIA at D-8 (11 final effluent limitations guidelines have cost-effectiveness values greater 

than or equal to $27 for direct dischargers).

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4684-A1, Excerpt Number 100 in comment 

code 28.b.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 221

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA's analyses of Option 4, which would require zero discharge of bottom ash transport water 

for all units greater than 50 MW, show that the economic impact of requiring zero discharge of 

bottom ash can be reasonably borne by the industry as a whole. Option 4 would increase annual 

costs by approximately 1.4% and increase variable production costs by 1%.437 Option 4 would 

cause a 0.1% increase in unit retirements.438 Even if all of the costs of Option 4 were attributed 
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to zero discharge of bottom ash transport water – which they are not, making it 

a highly conservative assumption – the costs could still be reasonably borne by industry, since 

they would increase annual costs by roughly 1% and cause a less than 1% increase in unit 

retirements.

The impacts of Option 4 are also reasonable when viewed through the lens of cost-to-revenue 

ratios. Under a zero discharge standard for plants greater than 50 MW, 85 percent of plants 

would incur costs that are less than 1 percent of revenues,439 which EPA claims means that they 

“are unlikely to face economic impacts.”440 Under Option 4, only 48 plants – 4 percent of the 

industry – would incur compliance costs greater than 3 percent of revenues. And those costs 

include the cost to treat all waste streams (FGD wastewater, fly ash transport water, etc.). Given 

that the costs of Option 4 as a whole are achievable, the component cost to convert all units 

greater than 50 MW to zero discharge systems is also achievable.

Zero discharge of bottom ash is economically achievable if cost-effectiveness is considered as 

well. Requiring all units greater than 50 MW to meet a zero discharge standard for bottom ash 

transport water would cost $107 per TWPE.441 This is well within the cost-effectiveness values 

that EPA has approved in other effluent limitations guidelines; $107 per TWPE is lower than the 

cost-effectiveness of the final ELGs for seven separate industries.442 EPA has issued final 

effluent limitations guidelines with cost-effectiveness values nearly four times as high as 

the cost-effectiveness of bottom ash retrofits.443

437 78 Fed. Reg. at 34,498.

438 Id.

439 78 Fed. Reg. at 34,494.

440

Id. at 34,495.

441 TDD at 8-34.

442RIA at D-8 ($404 per TWPE for direct dischargers in the electrical and electronic components 

industry; $155, $175, $111, $116, $127, and $380 per TWPE for indirect dischargers in the 

aluminum forming, centralized waste treatment, leather tanning, metal molding and castings, 

metal products and machinery, and transportation equipment cleaning industries, respectively).

443 See id.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4684-A1, Excerpt Number 105 in comment 

code 28.b.
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Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 223

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

As discussed in greater detail elsewhere, EPA’s screening-level analysis does not support EPA’s 

dismissal of Options 4 and 5 for existing plants.633 EPA states that this “analysis, while helpful 

to understand potential cost impact, does not generally indicate whether profitability is 

jeopardized, cash flow is affected, or risk of financial distress is increased.”634 Furthermore, 

even incorrectly assuming that all compliance costs will be borne by utilities without at least 

some part passed on to consumers in the form of higher utility rates,635 the results of the 

“screening-level analysis shows that the entity-level compliance costs are low in comparison to 

the entity-level revenues; very few entities are likely to face economic impacts at any level.”636 

[...]

There is no basis in the record for EPA’s rejection of Option 5 as BADCT based on the increase 

in total annualized costs in relation to total costs for the new unit.643 Thus, EPA’s record does 

not demonstrate that the costs of Option 5 cannot be reasonably borne by industry, and Option 5 

is BADCT for new sources.

633 See infra Section IX; see also attached Synapse Report, Appendix A.

634 RIA at 4-2.

635 RIA at 4-2.

636 RIA at 4-13.

643 EPA may have overestimated the capital costs for a new 1,300 MW coal plant. For example, 

EPA estimates costs of approximately $2,982/kW, but a Black & Veatch calculator last updated 

in 2011 estimates costs for this type of unit between $3,000/kW to $4,000/kW. Ryan Pletka PE, 

Black & Veatch’s (RETI’S) Cost of Generation Calculator (May 16, 2011), available 

at http://www.energy.ca.gov/2011_energypolicy/documents/2011-05-

16_workshop/presentations/Ryan_Pletka_B&V.pdf.

Comment Response: 
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Regarding existing sources, see response to DCN EPA-HQ-OW-2009-0819-4686-A1, Excerpt 

Number 25, in comment code 28.b.

Regarding cost estimates for new sources, see DCN EPA-HQ-OW-2009-0819-4686-A1, Excerpt 

Number 150, in comment code 26.d

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 9

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Table 5 presents the benefit‐to‐cost ratios calculated by EPA for the proposed steam electric 

ELGs in relation to ratios for other categories. With one exception, ELGs have been approved 

either with no benefit‐cost analysis or with costs that exceed measured benefits. The benefit‐cost 

ratios of all eight proposed steam electric regulatory options are well within the range of those of 

approved ELGs.

Table 5. Clean Water Act ELGs and proposed steam electric ELGs: Benefit‐cost ratios
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a EPA infers benefits for Options 3a, 3b, and 4a from analysis for Options 3 and 4. See 78 Fed. 

Reg. at 34,519, Table XIV‐9. 

b EPA omitted air‐related benefits for Options 1 and 2. See 78 Fed. Reg .at 34,519, Table XIV‐9.

c EPA omitted air‐related benefits for Option 5. Here, we have added Option 4's air‐related 

benefits to Option 5's non‐air‐related benefits to provide a lower bound for Option 5 benefits. 

See 78 Fed. Reg. at 34,519‐34,518, Tables XIV‐8 and XIV‐9.

Comment Response: 

EPA agrees with the commenter that ELGs have been promulgated in the past that have benefitcost ratios that are lower than those of the various ELGs options EPA considered in this 

rulemaking. The criteria for BAT and EPA’s rationale for its BAT determination in this final rule 

are described in the preamble (see preamble sections IV and VIII). See response to DCN EPAHQ-2009-0819-4464-A1, Excerpt Number 3 (in comment code 6.e) regarding the role of costbenefit analysis in EPA’s decisions on the final steam electric ELGs.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 11

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

In a more recent study, Frank Ackerman examines the debate surrounding regulatory cost 

impacts, and reviews reports by the Office of Management and Budget and by consultants to the 

Small Business Administration, which claim to find substantial regulatory compliance 

costs.46 He finds a series of errors and misrepresentations, which tend to exaggerate the widely 

reported bottom‐line estimates of regulatory costs. The Small Business Administration, in 

particular, has sponsored an annual series of studies estimating ever‐more‐alarming total costs of 

regulation; careful examination shows that these costs are based on fanciful extrapolation at best, 

combined with misuse of statistical evidence. The 2010 study, for example, reports an alarming 

$1.75 trillion annual cost of regulations. Two‐thirds of that putative cost, however, is based on a 

single regression estimate linking per capita income to a World Bank index of regulatory quality. 

That regression analysis suffers from multiple fundamental flaws, including misunderstanding 

and misrepresenting the World Bank index, boosting significance levels by padding the database 

with 7 years of near‐identical data, and failing to distinguish between correlation and causation. 

(Additional serious problems affect the remaining one‐third of the estimated cost 

ofregulations.)47

Another recent study examines predicted and actual price impacts of Department of Energy 

(DOE) appliance and equipment energy efficiency standards. Across nine rulemakings, DOE 

estimated an average increase in the manufacturers’ selling prices of $148; the actual average 

change was a decrease of $12.48

46 Ackerman, F. "The unbearable lightness of regulatory costs." Fordham Urban Law Journal 33 

(2005): 1071‐1095.

47 Heinzerling, L., and F. Ackerman, “The $1.75 trillion lie,” Michigan Journal of Environmental 

and Administrative Law 1 (2012): 127‐158.

48 Steven Nadel and Andrew deLaski, “Appliance Standards: Comparing Predicted and Observed 

Prices,” American Council for an Energy‐Efficient Economy, 2013, 

http://www.aceee.org/research‐report/e13d.

Comment Response: 

The commenter does not identify any specific errors that it believes are present in EPA’s analysis 

of the costs of the ELGs. In analyzing the costs of the ELGs, EPA used the best available and 

representative data, including with respect to relevant technologies and the plants to which the 

final rule applies. Although EPA’s estimates are subject to uncertainty, as detailed and discussed 

in the supporting documents for the final rule, they are reasonable in light of available and 

relevant data, and they meet the requirements of the Clean Water Act to take into account 

“costs.” See, e.g., CMA v. EPA, 870 F.2d 177, 237-38 (5th Cir. 1989) (“The Act requires the 

EPA to ‘take into account’ the costs of BAT; it does not require a precise calculation. The EPA 

‘need make only a reasonable cost estimate in setting BAT’; it is sufficient if the EPA develops 
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‘a rough idea of the costs the industry would incur’” (citation omitted).); Kennecott Copper v. 

EPA, 612 F.2d 1232, 1238 (10th Cir. 1979) (EPA has “wide leeway in its analysis of costs”); 

BASF Wyandotte Corp. v. Costle, 598 F.2d 637, 662 (1st Cir. 1979) (upholds using averages in 

estimating costs); BP Exploration & Oil Inc. v. EPA, 66 F.3d 784, 799-800 (6th Cir. 1995) (“The 

CWA does not require a precise calculation of BAT and NSPS costs” (citation omitted).); NRDC 

v. EPA, 863 F.2d 1420, 1426 (9th Cir. 1988) (“[T]he Act does not require a precise calculation of 

BAT costs.”); Weyerhaeuser v. Costle, 590 F.2d 1011, 1045 (D.C. Cir. 1978) (“[Congress] left 

EPA with discretion to decide how to account for the consideration factors, and how much 

weight to give each factor.”).

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 33

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Surely, a screening measure that “does not generally indicate whether profitability is jeopardized, 

cash flow is affected, or risk of financial distress is increased” cannot be a reliable measure of the 

economic achievability of ELGs.

 Plant closures: EPA used IPM analysis to estimate plant closures from Options 3 and 4 

only. Modeling of Option 4 resulted in a net increase in capacity of 317 MW (less than 

0.1 percent of baseline U.S. capacity), which included small net decreases in the NPCC 

and SPP regions:159 “As a result, for Option 4, the IPM analysis projects total net closure 

of nine generating units...The results support EPA’s conclusion that Option 4 is 

economically achievable.”160 EPA uses the analysis of plant closures as evidence of the 

economic achievability of Option 4 and fails to complete plant closure analysis for 

Option 5.

 Costs to U.S. households: Using the worst‐case assumption (from rate‐payers 

perspective) of 100‐percent cost pass‐through to customers, average annual costs to U.S. 

households are far from onerous: $3.89 for Option 4 and $6.46 for Option 5. The highest 

regional costs were found for the ECAR region: $10.08 and $16.86 per year respectively. 

The average U.S. household spends about $2,000 each year on electricity, heating and 

cooking fuels combined.161

 Job effects: EPA estimates average annual employment increases from all eight 

regulatory options. Employment increases from Options 4 and 5 are 1,253 and 2,112 job‐

years, respectively.

EPA fails to make a case that Options 4 and 5 are not economically achievable. Indeed, EPA 

states outright that Option 4 is economically achievable. Similarly, EPA notes that its analysis of 

Option 5 “shows that the entity‐level compliance costs are low in comparison to the entity‐level 
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revenues; very few entities are likely to face economic impacts at any level.”162 Given 

reasonable assumptions regarding cost pass‐through in the steam‐electric industry, it seems likely 

that economic screening measures for Options 4 and 5 would fall within the bounds of those 

presented in approved ELGs. Plant closures—EPA’s ostensible reason for not selecting Option 

4—and costs to households are negligible. Jobs are expected to increase as a result of all of the 

proposed steam electric regulatory options, including Options 4 and 5.

159 78 Fed. Reg. at 34,498, Table XI‐6.

160 78 Fed. Reg. at 34,472.

161 EIA, 2009 Residential Energy Consumption Survey, Table 

CE1.1, http://www.eia.gov/consumption/residential/data/2009/index.cfm?view=consumptio

n.

162 RIA at 4‐9

Comment Response: 

The commenter states that EPA “fails to make the case that Options 4 and 5 are not economically 

achievable.” EPA agrees that Option 4 is economically achievable, as the Agency stated in the 

proposed rule documentation. For the final rule analysis, EPA updated its economic impact 

analyses to incorporate additional, more recent information and looked again at the results of 

these analyses to inform its assessment that the final ELGs are economically achievable. The 

final rule establishes limitations and standards for existing sources based on Option D, which is 

similar to proposed Option 4, but unlike proposed Option 4, it does not contain limitations and 

standards applicable to the discharge of combustion residual leachate based on chemical 

precipitation, nor does it contain BAT limitations and PSES applicable to the discharge of nonchemical metal cleaning wastes. Section VIII of the preamble explains the basis for EPA’s 

decision to select Option D for existing sources, including EPA’s decision regarding the control 

of pollutants in discharges of combustion residual leachate and with respect to non-chemical 

metal cleaning wastes. As explained in the preamble, EPA determined that Option D is 

economically achievable for the steam electric industry as a whole, based on its expected impacts 

on steam electric generating capacity as reflected in EPA’s IPM analysis detailed in Chapter 5 of 

the RIA document.
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29.a. Benefits – Analysis scope and benefit categories 

Commenter Name: R. W. Greene

Commenter Affiliation: Mercatus Center at George Mason University

Document Control Number: EPA-HQ-OW-2009-0819-3411-A1

Comment Excerpt Number: 18

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

 With admittedly poor quantification of benefits, the most that the EPA can claim is that it

has assessed the costs of 

achieving certain technical changes in regulation that are motivated by command and con

trol concerns.

Comment Response: 

EPA disagrees. The Agency used methodologies recommended in EPA’s guidelines for 

conducting economic analysis (U.S. EPA, 2014) and OMB’s circular A-4 to estimate the benefits 

anticipated to result from implementation of the ELGs, within the constraints of the available 

data.

For more on consideration of benefits in the development of the final ELGs, see response to 

DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 6.e).

References:

U.S. EPA, 2014. Guidelines for Preparing Economic Analyses (updated May 2014).

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 23

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Florida generates the third most energy in the U.S. Our economy is largely tourism based with a 

record breaking 89.3 million visits last year and relies on an abundance of fresh clean water that 

is currently threatened by toxic power plant pollution.

Comment Response: 
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EPA appreciates that nationally-applicable ELGs have impacts at the local level. As noted in the 

TDD for the final rule, the final technology-based effluent standards are estimated to reduce 

loadings of toxic pollutants to waters by nearly 1.5 million toxic-weighted pounds, nation-wide, 

including Florida receiving waters specifically. The Agency estimated that the rule will provide a 

wide range of benefits to population living in proximity to affected receiving waters and to 

others who use or enjoy these waters. See the BCA for the final rule for details on the benefits.

Commenter Name: Jamie Rhodes

Commenter Affiliation: Environment Council of Rhode Island

Document Control Number: EPA-HQ-OW-2009-0819-4034-A2

Comment Excerpt Number: 11

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Our organizations urge EPA to monetize the benefit of reduced costs for drinking water 

treatment, reduced non-cancer health impacts and other benefits mentioned in its analysis 

but not monetized in order to provide a more accurate assessment of the benefits of the 

proposed rule. Though not required by the Clean Water Act and not allowed to be used to 

determine best available technology to achieve effluent reductions,16. EPA conducted a costbenefit analysis to accompany this proposal.17 Our organizations are concerned that the 

Agency chose not to monetize certain benefits, particularly the reduced cost of drinking water 

treatment for pollutants with drinking water criteria. By EPA’s own estimate, nearly 400 water 

bodies that are sources of drinking water have been degraded by power plant water pollution. 

The agency also did not monetize non-cancer health benefits (other than IQ benefits from 

reduced childhood exposure to lead and in-utero exposure to mercury), or benefits to tourism.

16 http://www.cleanwateraction.org/files/publications/OMB%20Letter_4_15_filed2-1.pdf

17Id. at 34,503

Comment Response: 

For the final rule, EPA quantified and monetized additional non-cancer health benefits; 

specifically, the Agency estimated the benefits to adults of reduced cardiovascular mortality 

from exposure to lead and arsenic via fish consumption. These analyses are described in greater 

detail in Sections 3.4 and 3.7, respectively, of the BCA for the final rule.

EPA evaluated potential drinking water treatment benefits, such as those resulting from reducing 

bromide discharges and pollutants for which EPA has established drinking water criteria, and 

determined that a quantitative analysis of these benefits was not warranted as they would likely 
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be small. EPA reached this conclusion after reviewing baseline and post-compliance pollutant 

concentrations in streams where public drinking water intakes are located to determine whether 

the ELGs may contribute to reducing treatment costs. EPA instead provides a qualitative 

discussion of the benefits, including the results of the Agency’s evaluation of potentially affected 

drinking water intakes and ambient pollutant concentrations in source waters. Chapter 2 of the 

BCA for the final rule provides detail of this analysis. The discussion also includes a qualitative 

review of the magnitude and extent of bromide discharges and their potential impacts on 

drinking water systems and public health.

Commenter Name: Lynn Thorp

Commenter Affiliation: Clean Water Action (CWA)

Document Control Number: EPA-HQ-OW-2009-0819-4451-A1

Comment Excerpt Number: 4

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA’s Proposed Rule and supporting documents confirm that power plant pollution is directly 

responsible for toxic discharges which cause contamination in drinking water supplies. In the 

Benefits and Costs Analysis document for the Proposed Rule, EPA did not monetize benefits of 

improved surface water quality in terms of drinking water consumption because Public Water 

Systems are required to meet federal standards and thus are eliminating most of the health risks 

posed by any SDWA-regulated contaminant present in power plant discharges.22 This is a 

powerful fact. It indicates that in terms of regulated contaminants, PWS and their consumers are 

essentially footing the bill to reduce the public health risks from power plant water discharges. 

While this benefits public health and is a testament to modern drinking water treatment, it is not 

an efficient way to control industrial pollution. Eliminating contaminants at their source is vastly 

more appropriate than relying on our nation’s Public Water Systems to clean up the toxic waste 

stream from a polluting sector of the economy.

22 EPA, Benefit and Cost Analysis for the Proposed Effluent Limitations Guidelines and 

Standards for the Steam Electric Power Generating Point Source Category, 2-4, (April 2013)

Comment Response: 

EPA agrees with the commenter that reduction at the source is preferable to relying on later 

treatment to remove toxic pollutants from drinking water, and the final rule will accomplish this 

by having plants reduce their discharges of toxic, bioaccumulative, and other pollutants. As 

discussed in Chapter 2 of the final BCA, EPA acknowledges that source water quality 

improvement may affect drinking water treatment, but EPA is not able to attribute reductions of 

drinking water treatment costs to these improvements given the presence of other contaminants, 
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nature of the treatment process, and other factors that contribute to treatment costs beyond 

concentrations of individual pollutants discharged by steam electric power plants. As a result, the 

Agency discusses this benefit category qualitatively.

Commenter Name: S. Fischer

Commenter Affiliation: Appalachian Voices

Document Control Number: EPA-HQ-OW-2009-0819-4479

Comment Excerpt Number: 3

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Clean water is an economic boost for us in Northwest North Carolina in particular. The French 

Broad River brings in a lot of income to our area, with lots of boaters and kayakers who love the 

river. We have worked hard to clean the river up. Are we going to waste taxpayer dollars that 

have already been spent on the river, and are we going to made to spend more money to clean up 

after Duke Energy? They should be required to use the best technology to keep their waste out of 

water.

Comment Response: 

EPA appreciates that nationally-applicable ELGs have impacts at the local level. As noted in the 

TDD for the final rule, the final technology-based effluent standards are estimated to reduce 

loadings of toxic pollutants to waters by nearly 1.4 million toxic-weighted pounds nationwide. 

The Agency estimated that the rule will provide a wide range of benefits to population living in 

proximity to affected receiving waters and to others who use or enjoy these waters. See the BCA 

for the final rule for details on the benefits.

Commenter Name: Vicki Card

Commenter Affiliation: Colorado Springs Utilities

Document Control Number: EPA-HQ-OW-2009-0819-4483-A1

Comment Excerpt Number: 14

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Having affordable power and money available to invest in reliable, redundant electric 

transmission is critical to the protection of human health, the economy and safety. This was 

vividly illustrated by 2012’s Hurricane Sandy. Without electrical power, businesses could not 

operate, thus impacting the local economy; nursing homes and hospitals had to be evacuated; 
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heating systems could not operate, impacting human health; communications were hampered; 

and streets went dark putting public safety in jeopardy. A recent study showing that air 

conditioning has reduced the death rate on hot days by 80% since 19607further illustrates the 

importance of having affordable electricity to the protection of human health.

Colorado Springs Utilities therefore respectfully requests that EPA consider the benefit to human 

health, public safety, the economy and national security that come with having reliable, 

affordable, redundant sources of electricity when conducting cost benefit 

analysis of rules affecting the electric power generating industry. These benefits are not 

typically included in EPA's regulatory analysis. 

7 Colorado Springs Gazette, 2013. The Road to a Longer Life by Laura Helmuth. Section D 

Page 1. Tuesday, September 17, 2013.

Comment Response: 

EPA agrees that reliable, affordable, redundant electricity supply is important to human health, 

public safety, the economy and national security. Accordingly, the Agency analyzed the impacts 

of the ELG on the electricity market, on rates paid by households, businesses and other 

electricity consumers, and on electricity supply reliability. As described in details in the RIA 

document, these analyses show that the final rule will have a minimal impact across all metrics 

EPA evaluated. Impacts on electricity generation are very small, with only 0.2 percent change in 

the quantity generated by plants to which the final rule applies, which will be offset by increased 

generations from other plants. Impacts on generating capacity and production costs are similarly 

very small (less than 1 percent), as are impacts on electricity rates. Further, EPA also analyzed 

the effects of the regulation with respect to human health, ecological, and economic productivity 

benefits that will result from reducing toxic pollutant discharges to surface waters. These 

analyses are detailed in the BCA for the final rule.

Commenter Name: Becky Hayat

Commenter Affiliation: Natural Resources Defense Council (NRDC)

Document Control Number: EPA-HQ-OW-2009-0819-4490-A1

Comment Excerpt Number: 29

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

By using dry ash handling, the quality of the fly ash and bottom ash is improved. High-quality 

ash, when mixed with cement and water, increases the strength of concrete26, thereby making it a 

sought-after product by the construction materials industry. As the market for usable ash product 

increases, the economic incentive for plants to convert to dry ash handling methods is also 
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heightened.27 Thus, converting to a dry handling method will not only reduce a power plant’s 

water demand, but it may also provide additional revenues from the sale of fly ash and bottom 

ash.28

26 Headwater Resources, Fly Ash for Structural Concrete, available at 

http://www.flyash.com/data/upimages/press/TB.10%20Fly%20Ash%20for%20Structural%20Co

ncrete.pdf.

27 Power Engineering, Ash Handling Options for Coal-fired Power Plants (Feb. 1, 2011).

28 POWER, The Better Environmental Option: Dry Ash Conversion Technology (July 2011).

Comment Response: 

EPA notes that the final steam electric ELGs do not require the use of “dry handling.” Rather, 

the final rule establishes limitations and standards applicable to the discharge of pollutants from 

steam electric generating units. Nonetheless, EPA agrees with the general comment about 

potential increase in beneficial use of coal combustion ash resulting from plants’ decision to 

convert to dry ash handling and has considered these potential impacts as part of the analyses of 

the final steam electric ELGs. The analyses are described in Chapter 10 of the BCA and provide 

information about the potential magnitude of benefits to steam electric power plants and to 

society more generally from enhancing beneficial reuse of the CCR.

Commenter Name: Becky Hayat

Commenter Affiliation: Natural Resources Defense Council (NRDC)

Document Control Number: EPA-HQ-OW-2009-0819-4490-A1

Comment Excerpt Number: 30

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA must take into account other benefits associated with reduced surface water withdrawals, 

including but not limited to, healthier aquatic ecosystems, higher recreational value, agricultural 

benefits, and increase in property values. EPA’s failure to quantify/monetize the one type of 

benefit it identified in relation to reduced surface water withdrawals, along with its 

undercounting of other associated benefits, results in an unfair balancing act where the agency 

weighs complete costs against incomplete benefits. This biased cost-benefit analysis is especially 

troublesome for the most stringent regulatory options (e.g. Options 4 and 5) where EPA 

overestimated compliance costs and blatantly underestimated the benefits.

Comment Response: 
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For discussion of the benefits from surface water withdrawals specifically, see Section 29.i (e.g., 

DCN EPA-HQ-OW-2009-0819-4490-A1, Excerpt Number 28).

EPA disagrees that it has not included monetized benefits estimates for healthier aquatic 

ecosystems and higher recreational value; both are included in the “Ecological Conditions and 

Recreational Use Benefits from Surface Water Quality Improvements” category. On the more 

general implications of excluding certain categories of benefits from the monetized estimates, 

EPA agrees that the monetized values do not reflect all benefits of the regulation. The Agency 

used the best methods and available data to identify, quantify, and wherever possible monetize, 

the benefits of the rule. For the final rule, EPA expanded its benefit analyses in response to 

comments received on the proposal, including accounting for additional benefit categories (e.g., 

non-cancer health benefits and reduced maintenance dredging of reservoirs and navigational 

waterways). As described in Chapter 2 of the final BCA, the Agency was unable to quantify the 

benefits from improved quality of source water used for public water supply, reduced surface 

water withdrawals, property values, and other categories due to data limitations. The Agency 

describes these benefits in qualitative terms in the document and, if feasible, presents screening 

level assessment of potential benefits. In addition, if the Agency had been able to fully monetize 

these categories, it would also be important to make sure that benefits weren’t double counted. 

Overall, EPA considers that its benefit analysis provides a reasonable understanding of the 

magnitude of the major benefits expected to result from the final rule. The Agency acknowledges 

that exclusion of some benefit categories is likely to understate the total benefits of the final rule, 

particularly when compared to costs which are more readily quantifiable.

For more on consideration of benefits in the development of the final ELGs, see response to 

DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number Number 3 (in Comment Code 6.e).

Commenter Name: David Pringle

Commenter Affiliation: New Jersey Environmental Federation/Clean Water Action et al.

Document Control Number: EPA-HQ-OW-2009-0819-4509-A2

Comment Excerpt Number: 1

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In addition to monetizing benefits to drinking water, our organizations urge EPA to 

monetize (1) the benefits of improved water and sediment quality, healthy natural 

resources, and reduced costs from pollution impacts and (2) the benefits in improved 

sediment quality in reducing dredge material management costs. Both nationally and in New 

Jersey, on top of human health impacts, a high price is paid due to pollution in impacts to aquatic 

life and efforts to clean up contaminated waters. Moreover, the costs on managing contaminated 

dredged material is multiple times the cost of managing clean sediments which have more 

beneficial uses.
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Comment Response: 

EPA agrees that the monetized values do not reflect all benefits of the regulation and has 

recognized this in providing an overview of benefits in Chapter 2 of the BCA. The Agency 

estimated, and monetized, several benefit categories associated with improved quality of surface 

water and ancillary benefits stemming from reduced air emissions. The monetized benefit 

categories include: reduced incidence of cancer and non-cancer human health outcomes, 

improved total value of water resources (including use and nonuse), and improved habitats for 

endangered and threatened species, among others. In response to comments, the Agency revised 

its analysis to quantify and monetize additional categories of benefits, including reduced 

incidence of cardiovascular diseases from exposure to lead and arsenic and avoided cost of 

maintenance dredging resulting from reduction in sediment discharges. These revisions provide a 

more comprehensive understanding of the benefits of the final rule, but EPA recognizes that 

even these improvements don’t capture all benefits of the final rule. The monetized benefit 

estimates need to be understood within the broader discussion of the benefits, which also 

highlights several benefit categories that EPA could analyze qualitatively only, or could quantify 

but not monetize, such as reductions in the cost of disposing of contaminated dredged material. 

EPA discusses these other benefits qualitatively in the BCA (see Chapter 2).

Commenter Name: Thomas H. Adams

Commenter Affiliation: American Coal Ash Association (ACAA)

Document Control Number: EPA-HQ-OW-2009-0819-4511-A2

Comment Excerpt Number: 7

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Disregarding the impact of this rulemaking on beneficial use would be a significant 

violation of administrative policy.

Successive administrations have issued executive orders (12866 and 13563) that compel EPA to 

consider the impact of its proposed regulations on all sectors of society and the economy. 

Specifically, Executive Order 13563, entitled “Improving Regulation and Regulatory Review” 

(Jan. 18, 2011), instructs federal agencies, including EPA, to assess benefits and costs of 

regulations in an effort to “impose the least burden on society, consistent with obtaining 

regulatory objectives, taking into account, among other things, and to the extent practicable, the 

costs of cumulative regulations.” The order also directs consideration of alternative regulatory 

approaches and allowance for public participation in the rulemaking process.

As stated earlier, any decision by EPA to disregard information on CCR beneficial use would 

exclude from the cost‐ benefit analysis consideration of the fate of more than 40 percent of the 

CCRs generated annually in the U.S. It would further disenfranchise the participation of tens of 

thousands of individuals and entities who submitted testimony on beneficial use in public 
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hearings and the public comment process surrounding the agency’s proposed rule. Both 

consequences would be direct and substantial violations of the executive orders.

In addition to executive orders, EPA is compelled to consider information it has received about 

beneficial use under the Administrative Procedure Act (“APA”). The APA allows reviewing 

courts to set aside agency action that is “arbitrary, capricious, an abuse of discretion, or 

otherwise not in accordance with law.” EPA has received voluminous public comments on its 

proposed CCR rule that are both relevant and significant pertaining to beneficial use. EPA is not 

entitled to simply set this information aside without providing analysis and response.

Comment Response: 

EPA disagrees with the commenter that it has not followed the Administrative Procedure Act 

because, as stated by the commenter, “EPA received voluminous public comments on its 

proposed CCR rule that are both relevant and significant pertaining to beneficial reuse.” Comments specific to the proposed CCR rule are outside the scope of the ELG rulemaking. 

EPA addressed public comments on the CCR rule in the context of that rulemaking (See Docket 

EPA-HQ-RCRA-2009-0640-11970).

EPA agrees with the commenter that changes in coal combustion residuals (CCR) management 

prompted by the final rule will allow plants to more readily market CCR for beneficial uses. For 

the final rule, the Agency estimated the benefits associated with the increased CCR 

marketability. In its analysis of the CCR market value, EPA relied on the methodologies used in 

the analysis of beneficial uses of CCRs in the final CCR rule. As documented in Chapter 10 of 

the final BCA, EPA estimated that CCR beneficial uses under the final rule will yield a net social 

value of approximately $31 million annually.

See response EPA-HQ-OW-2009-0819-4511-A2, Excerpt Number 9, for a discussion of 

analyses EPA conducted for the final rule to account for enhanced marketability of CCR for 

beneficial uses.

Commenter Name: Thomas H. Adams

Commenter Affiliation: American Coal Ash Association (ACAA)

Document Control Number: EPA-HQ-OW-2009-0819-4511-A2

Comment Excerpt Number: 9

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In both rulemakings the impacts of regulations on the beneficial use of CCR has either been 

minimized or disregarded. The ACAA again calls attention to the significance of beneficial use 

to the desired outcome of these and all rulemakings – protection of human health and the 

environment.
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Comment Response: 

The commenter is concerned about the impact of the final rule on the “beneficial use of CCR.” 

First, EPA notes that the final steam electric ELGs do not regulate the beneficial use of CCR. 

Rather the final rule establishes limitations and standards applicable to the discharge of 

pollutants from steam electric power plants. Nonetheless, EPA recognizes that the rule has the 

potential to increase the beneficial use of coal combustion ash as a result of plants’ decisions to 

convert to dry ash handling. The Agency accounted for these potential impacts as part of its 

analyses of the final steam electric ELGs. The analyses are described in Chapter 10 of the BCA 

and provide information about the potential magnitude of benefits to steam electric power plants 

and to society more generally from enhancing beneficial reuse of the CCR.

Comments specifically pertaining to EPA’s analysis of the CCR rule are outside the scope of this 

rulemaking. EPA addressed comments on the CCR rule in the context of that rulemaking (see 

Docket EPA-HQ-RCRA-2009-0640-11970).

Commenter Name: Thomas H. Adams

Commenter Affiliation: American Coal Ash Association (ACAA)

Document Control Number: EPA-HQ-OW-2009-0819-4511-A2

Comment Excerpt Number: 16

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

However in an effort to create regulations for the disposal of CCR and process water 

management, the EPA has created major obstacles to maintaining and increasing beneficial use. 

Therefore the ACAA must again speak up on behalf of those dedicated to recycling CCP and call 

attention to the beneficial use impacts of EPA’s regulatory decisions in these and other matters. 

We strongly advise the agency to take great care to avoid further damage to the beneficial use of 

CCP by overly burdensome and unnecessary regulations.

Comment Response: 

EPA disagrees with the commenter that the EPA has created “major obstacles to maintaining and 

increasing beneficial use.” First, EPA notes that the final steam electric ELGs do not regulate the 

beneficial use of CCR. Rather the final rule establishes limitations and standards applicable to 

the discharge of pollutants from steam electric generating units. Moreover, the ELGs do not 

directly affect the potential for beneficial use of CCR, and in fact may increase the amount of 

CCR that is available for beneficiation by promoting changes to plant processes (e.g., 

conversions to dry handling) that should enhance CCR marketability. EPA estimated the 

potential magnitude of benefits to steam electric power plants and to society more generally from 

enhancing beneficial reuse of the CCR in the BCA for the final rule (see Chapter 10).
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Comments specifically pertaining to EPA’s analysis of the CCR rule are outside the scope of this 

rulemaking. EPA addressed comments on the CCR rule in the context of that rulemaking (see 

Docket EPA-HQ-RCRA-2009-0640-11970).

Commenter Name: Becky Smith

Commenter Affiliation: Clean Water Action et al.

Document Control Number: EPA-HQ-OW-2009-0819-4548-A1

Comment Excerpt Number: 9

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Our organizations urge EPA to monetize the benefit of reduced costs for drinking water 

treatment, reduced non-cancer health impacts and other benefits mentioned in its analysis but not 

monetized in order to provide a more accurate assessment of the benefits of the proposed rule. 

Though not required by the Clean Water Act and not allowed to be used to determine best 

available technology to achieve effluent reductions,16 EPA conducted a cost-benefit analysis to 

accompany this proposal.17 Our organizations are concerned that the Agency chose not to 

monetize certain benefits, particularly the reduced cost of drinking water treatment for pollutants 

with drinking water criteria. By EPA’s own estimate, nearly 400 water bodies that are sources of 

drinking water have been degraded by power plant water pollution. The agency also did not 

monetize non-cancer health benefits (other than IQ benefits from reduced childhood exposure to 

lead and in-utero exposure to mercury), or benefits to tourism.

16 http://www.cleanwateraction.org/files/publications/OMB%20Letter_4_15_filed2-1.pdf

17 Id. at 34,503

Comment Response: 

See response to related EPA-HQ-OW-2009-0819-4034-A2, Excerpt Number 11 (comment code 

29.a)

Commenter Name: Pamela Ritger

Commenter Affiliation: Clean Wisconsin

Document Control Number: EPA-HQ-OW-2009-0819-4632-A1

Comment Excerpt Number: 13

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

As noted in the rulemaking materials, there are a number of benefits that have not been 

quantified in the net social benefits calculation for these guidelines. Instead, their impacts have 

been discussed qualitatively. These benefits include the benefits of improved tourism, increased 

commercial fishery yields, reduced need for water treatment and enhanced property values.39

The EPA did not quantify the benefits of improved tourism because their overall societal benefits 

are likely to be small.40 However, the impact of higher revenues from tourism can have a 

significant impact at a local level, especially for states like Wisconsin, with its strong tourism 

sector. Therefore, the social benefits that result from increased tourism are likely underestimated 

in the EPA benefit-cost analysis, especially for states like Wisconsin. Similarly, the EPA did not 

quantify the social benefits of increased property values due to lower levels of contamination 

from combustion wastewater, due to data limitations.41 Although these benefits would accrue to 

the property owner, the net impact represents an overall increase in societal 

wealth.42 Accordingly, total social benefits that will result from increased property values have 

similarly been undercounted in the EPA’s benefit-cost analysis.

39 United States Environmental Protection Agency (U.S. EPA). 2013a. Benefit and Cost Analysis 

for the Proposed Effluent Limitations Guidelines and Standards for the Steam Electric Power 

Generating Point Source Category (40 CFR 423). EPA-821-R-13-004, p. 2-2.

40 Id. at 2-10.

41 United States Environmental Protection Agency (U.S. EPA). 2013a. Benefit and Cost Analysis 

for the Proposed Effluent Limitations Guidelines and Standards for the Steam Electric Power 

Generating Point Source Category (40 CFR 423). EPA-821-R-13-004, p. 2-10.

42 Id.

Comment Response: 

EPA agrees with the commenter that the increase in revenues from tourism can have a significant 

local impact, as discussed in the BCA for the final rule (see Chapter 2). As described in the 

BCA, tourism may increase in the vicinity of steam electric power plants, while possibly 

decreasing in other locations, transferring tourism revenues from one area to another. The 

Agency recognizes that excluding benefits from tourism is likely to understate benefits to some 

communities (including areas of Wisconsin), as discussed in Chapter 2 of the BCA for the final 

rule. However, the Agency also notes that because of transfers, the benefits derived from tourism 

are likely to be small at the national level. It is therefore not unreasonable to exclude such 

benefits from the national level estimates presented in the BCA and discuss them qualitatively as 

the Agency has done.

EPA also agrees with the commenter that reduced surface water contamination resulting from 

implementation of the ELGs will likely result in increased property values in the vicinity of 

affected waters, and that this will yield an overall net benefit to society (see Section 2.4 of the 

final BCA for detail). EPA notes that the increase in use values associated with water quality 
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improvements on property values is reflected in the total willingness-to-pay for surface water 

quality improvements, which the Agency did quantify and monetize (see Chapter 4 of the final 

BCA). Therefore, estimates of changes in property values and willingness to pay for water 

quality improvements are not additive.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 211

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In addition, EPA has not performed a thorough benefit and cost analysis for three of its preferred 

options: Options 3a, 3b, and 4a. As EPA explains:

...EPA used its understanding of the wastestreams and treatment technologies for these options, 

along with projections of pollutant reductions for all eight options, to infer total monetized 

benefits for Options 3a, 3b, and 4a. This is because the five options EPA analyzed can serve as 

upper and lower bounds for the benefits of Options 3a, 3b, and 4a. . . . However, EPA is less 

confident that the approach used to infer benefits for Options 3a, 3b, and 4a based on the results 

of the other five options would yield reasonable estimates if applied to the individual categories 

of benefits (e.g., water quality, air emissions, avoided impoundment failure cleanup costs) and 

therefore the Agency did not infer values for individual benefit categories but presents categoryspecific estimates only for Options 1, 2, 3, 4, and 5.

BCA, p. 1-2.

It seems the analysis for three of the four preferred options was rushed and did not adequately 

analyze all facets of the analysis that EPA thought proper to apply to the other options. While 

UWAG appreciates EPA’s willingness to consider other options, the Agency still must perform 

an appropriate level of analysis for those options. To do otherwise deprives the public of an 

adequate opportunity to review and comment on the analysis.

Comment Response: 

For information about benefits in the development of the final ELGs, see response to DCN EPAHQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 6.e).

EPA disagrees that its analysis for the three options referenced by the commenter was rushed. 

The Agency used a reasonable approach to estimate the potential magnitude of the benefits of 

three of the eight proposed options, based on information from detailed analysis of the other five 
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options. This approach provided an appropriate level of analysis by allowing comparison across 

the options.

For the final rule, EPA analyzed the five options for existing sources (A through E) described in 

the supporting documents using the same rigorous approaches for all but one category of 

benefits; EPA estimated the air-related benefits resulting from changes in the electricity 

generation profile for two of the five options based on outputs from the Integrated Planning 

Model for these two options. The BCA for the final rule details these analyses.

Commenter Name: James D. Taft

Commenter Affiliation: Association of State Drinking Water Administration (ASDWA)

Document Control Number: EPA-HQ-OW-2009-0819-4668-A2

Comment Excerpt Number: 4

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

We also believe that the final rule will be on firmer ground and more defensible if it accounts for 

benefits (both qualitative and quantitative) of avoided drinking water treatment costs and 

improved health outcomes as a result of this effluent guideline being promulgated. The Agency’s 

current analysis may be under-representing the potential benefits of the risk management options 

presented.

Comment Response: 

EPA agrees with the commenter that exclusion of avoided drinking water treatment costs may 

result in an underestimate of the benefits of ELG revisions, but notes that these benefits are 

expected to be small in relation to other benefits of the final rule.

EPA agrees that the final rule could result in reduced treatment costs for utilities by reducing 

pollutant concentrations in source waters. As described in Chapter 2 of the BCA, EPA conducted 

a screening-level assessment to identify the number of public drinking water sources that may be 

affected by steam electric power plant discharges in the baseline and may benefit from higher 

quality source water. This assessment suggested that changes in drinking water treatment costs 

would be small.

Additionally, EPA does not expect the final regulation to yield significant health benefits from 

reduced drinking water pollutant concentrations, since public drinking water systems are already 

required to meet strict treatment levels for pollutants that pose human health risks. There may be 

some benefits associated with pollutants for which the allowable contaminant concentration is 

higher than the lowest threshold for potential health impacts; however, EPA’s analysis indicated 

that these benefits would be minimal given the number of affected public water intakes and the 

population served. Chapter 2 of the BCA for the final rule provides detail of this assessment.
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Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 66

External Review Flag: Envr Assess

External Review Incorporated into Response: No

Comment Excerpt: 

4. The public health and economic benefits of mechanical evaporation are much larger than 

EPA has estimated

Disinfection by-products are extremely difficult and costly to remove from the public water 

supply.252 A study of the water supply for 23 million Californians estimated costs of up to $90 

million to treat disinfection by-products based on current water quality and drinking water 

standards.253 As those drinking water standards are updated to reflect mounting evidence about 

the harms of brominated disinfection byproducts, and as source water quality continues to 

decline, it is estimated that those costs could rise to $1 billion.254

As discussed in the attached report by Synapse Energy Economics, Inc., Appendix A, because 

EPA did not attempt to quantify how reduced bromide discharges would reduce water treatment 

costs for often cash-strapped water supply systems, this key societal and public health benefit 

was essentially ignored in EPA’s decision-making process about BAT for FGD wastewater.255

Thus, EPA has underestimated both the public health and public financial implications of failing 

to control bromide levels in FGD wastewater. EPA’s benefit-cost analysis for Option 5 is 

therefore skewed. Moreover, because EPA does not account for brominated disinfection 

byproducts as part of the toxic-weighted pound equivalent value that is critical to the costeffectiveness analysis, the true cost-effectiveness of mechanical evaporation is seriously 

understated.

Drinking water utilities are concerned about escalating levels of bromide in the water supply, as 

those elevated levels has made it increasingly difficult for them to meet Safe Drinking Water Act 

requirements for trihalomethanes.256 Indeed, even at Belews Creek, which operates a biological 

treatment system, the permitting authority is concerned about bromides in the FGD wastewater. 

The plant’s 2012 NPDES permit requires, for the first time, monthly monitoring for bromides at 

the outfall from an ash settling pond that receives the effluent from the FGD 

treatment system.257 The permit contains a separate requirement to evaluate bromide reduction 

technologies for these discharges and to coordinate with downstream water systems.258 If EPA

does not select mechanical evaporation as BAT, it will simply be shifting the cost of addressing 

the bromides problem from the well-funded electric generating sector onto resource- limited 

public water systems.
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252 Id. at 20-22.

253 Id. at 21.

254 Id.

255 Instead, EPA “recommends that permitting authorities consider the potential for bromide 

discharges to adversely impact drinking water intakes when determining whether additional 

water quality-based effluent limits may be warranted.” 78 Fed. Reg. at 34,473, 34,477. But EPA 

may not defer to the WQBEL process its responsibility to regulate, under Section 1311(b)(2)(A), 

pollutants found in these waste streams.

256 EA at 3-11.

257 2012 NPDES Permit for Belews Creek Steam Station, NC0024406, at p.4.

258 Id. at Condition A.(14), p.9.

Comment Response: 

EPA shares the concern expressed by the commenter about disinfection byproducts and the 

potential for steam electric power plant discharges to increase the incidence of these products in 

treated drinking water. Thus, in the final rule analysis, the Agency evaluated information about 

the connection between bromide levels and drinking water treatment. The data suggest that 

concerns may exist on a site-specific basis. Section 2 of the BCA characterizes the potential 

impacts to drinking water treatment and human health in the baseline, and describes in 

qualitative terms the benefits that could accrue from reducing bromide discharges from stream 

electric plants.

EPA notes that the final rule does not set effluent limits for bromide for the steam electric 

industry, based on the performance of the best available technology (BAT) for FGD wastewater 

treatment (chemical precipitation and biological treatment).As discussed further in Section 2.4 of 

the BCA, EPA encourages permit writers to consider potential impacts on drinking water 

intakes, where applicable, when developing permits for steam electric power plants. As noted by 

the commenter, some permit writers are already including these considerations and requiring that 

the plant monitor for bromide. In addition, EPA did establish controls on TDS (as an indicator) 

of bromide for new sources and also included a voluntary incentives program that would address 

bromide discharges from units at existing steam electric power plants. See Section VIII of the 

preamble to the final rule.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 158
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External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

3. EPA underestimated benefits.

On one side EPA has placed well-defined, but overestimated, costs, while on the other side of the 

ledger has placed benefits that the agency itself acknowledges are 

incomplete and underestimated. Yet EPA presents tables of costs and benefits as if the two sets 

of data are equally well-defined and can be meaningfully compared.694 Nothing could be farther 

from the truth, as EPA's own costs and benefits document explains, and as additional materials 

suggest.

EPA did not monetize whole categories of benefits. Some of these benefits were not discussed at 

all; some were discussed qualitatively but not quantified or monetized; others were quantified 

but not monetized. But for all of the following categories, EPA did not assign a monetary value 

to include in the benefits calculations.

Table 8 – Benefits not Monetized by EPA695
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The benefits not monetized by EPA are discussed in the attached Synapse Report. 

[...]

For each category of benefits mentioned above, EPA set the value equal to zero.705 In other 

words, EPA notes that there is a category of benefits from the rule, but in the face of uncertainty 

surrounding the monetary value of those benefits, treats the value as zero. This systematically 

biases the cost-benefit analysis toward prioritizing costs. There are other ways to deal with 

uncertainty besides setting the value of the uncertain variable to zero. For example, EPA could 

develop ranges for each of the categories of benefits. Alternatively, EPA could apply different 

multipliers to the total monetized benefits to arrive at a series of low, mid, and high cases to 

account for uncertainty surrounding the un-monetized benefits. Regardless of how exactly EPA 

deals with the un-monetized benefits, one thing is clear: their value is not zero. Treating these 

categories of benefits as if they have no monetary value is inconsistent with EPA's own claim 

that these are actual benefits from the rule.706
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694 E.g., 78 Fed. Reg. at 34,526.

695 Synapse Report, Appendix A, at 22. Benefits containing a * indicate that EPA did not discuss 

the category in the Benefits and Costs document but did discuss the benefits qualitatively in 

other documents in the record.

705 Id. at 19-35.

706 Id. at 19-20.

Comment Response: 

EPA recognizes the limitations of the total benefits estimates, but the Agency has been as 

comprehensive as possible in its analysis given the available data and tools for estimating 

benefits. To address commenters’ concerns about excluding a number of benefit categories, EPA 

revised its benefits analysis for the final rule to include additional categories not monetized in the 

proposed rule, including reduced incidence of cardiovascular disease from exposure to lead and 

arsenic, avoided cost of maintenance dredging of reservoirs and navigational waterways, and 

increased marketing of coal combustion residuals for beneficial reuse (see Chapters 3, 9 and 10 

in the BCA). In addition, EPA expanded the qualitative discussion of non-monetized benefit 

categories in Chapter 2 of the final BCA. If feasible, the Agency has included information 

indicating the relative magnitude of the excluded benefits.

Regarding the commenter's suggestion that EPA develop ranges, the Agency notes that it uses 

ranges to indicate uncertainty in benefit estimates, when such ranges can be reasonably 

estimated. For example, for the final rule analysis, EPA presents ranges for several categories of 

benefits, including human health benefits, benefits from avoided impoundment failures, and 

benefits from water quality improvements.

EPA disagrees that the Agency is treating non-monetized benefits as equivalent to zero when 

conducting benefit cost analysis. EPA provided quantitative estimates of benefits where possible, 

and presented the results together with the Agency’s estimate of costs consistent with 

requirements of Executive Order 12866 (Regulatory Planning and Review) and Executive Order 

13563 (Improving Regulation and Regulatory Review). As described in the preamble to the final 

rule, EPA considered both monetized and nonmonetized benefits in support of the regulation.

For more on consideration of benefits in the development of the final ELGs, see response to 

DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 6.e).
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Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 2

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA omits numerous critical benefits in its valuation of the proposed ELGs including: reduced 

adverse health effects due to less exposure to pollutants from recreational water uses; reduced 

deposition of arsenic, selenium, and other pollutants in sediment on stream and lake beds; 

improved fisheries yield and harvest quality due to aquatic habitat improvement for commercial 

fisheries; benefits to the tourism industry from increased participation in water‐based 

recreation; increased property values from water quality improvements; fewer fish trapped and 

killed by water intake systems (i.e., reduced impingement and entrainment mortality); reduced 

costs to processing drinking water; reduced health effects from limiting exposure to pollutants in 

drinking water; eliminated attractive nuisances; reduction of bromide pollution; additional 

recycling of coal combustion residuals; value of land for impoundments for redevelopment; 

reduced air emissions from impoundments’ parasitic load; reduced air emissions from true dry 

handling of ash; avoided costs of BPJ determinations; avoided costs of TMDLs; reduced surface 

water withdrawals and consumptive use; and avoided costs of litigation.

Comment Response: 

The commenter noted a variety of expected benefits that may result from revising the steam 

electric ELGs. EPA agrees with the commenter that the listed benefits are real and of critical 

ecological, social, and economic importance. In the final rule, EPA describes these categories of 

benefits, although data limitations preclude the Agency from quantifying and monetizing many 

of them (see Chapter 2 in BCA). Where possible, EPA also provided information about the 

potential magnitude of these benefits, relative to other benefits the Agency was able to monetize. 

EPA disagrees that a qualitative discussions of benefits that cannot be quantified or monetized 

constitute omissions of these benefits, as suggested by the commenter.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 13

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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The environmental controls discussed in the proposed steam electric ELGs will prevent the 

discharge of billions of pounds of pollutants each year and result in important benefits to 

society.55 EPA correctly identifies most of the benefits of the proposed rule (see Table 6 and 

Table 7 below), but many of these benefits, either in whole or in part, were not included in 

EPA’s calculations of the total monetary benefit of the regulatory options, and, therefore, were 

not included in the benefit‐cost ratio. The monetary value of benefits is either omitted or 

undervalued for improvements to human health, the environment and ecosystems, and economic 

productivity. When EPA is unable to quantify or monetize an ELG impact with sufficient 

certainty, it effectively values the benefit at zero dollars.

This sub‐section first reviews three types of benefits for which monetary values are omitted 

from the proposed steam electric ELGs:

 Benefits discussed in EPA’s Benefit‐Cost Analysis but not given a monetary value: In 

EPA’s Benefit‐Cost Analysis, some benefits that are discussed qualitatively but never 

given a monetary value. These benefits are effectively valued at zero dollars.

 Benefits discussed in EPA other documentation but not included in the Benefit‐Cost 

Analysis: EPA discusses several benefits in other supporting documents to the steam 

electric ELGs but does not include any discussion or monetization of these values in the 

Benefit‐Cost Analysis. These benefits are effectively valued at zero dollars.

 Benefits not discussed by EPA: Several additional benefits are not discussed in any of 

the steam electric ELG supporting documents. These benefits are effectively valued at 

zero dollars.

and then provides an overview of the benefits the EPA did monetize:

 Benefits assigned monetary values by EPA. Fifteen benefits of the ELGs are monetized 

by EPA; 13 of these are, as acknowledged by EPA, underestimated.

The omitted benefits are summarized in Table 6; monetized benefits are summarized in Table 7 

below.

Table 6. Benefits omitted from EPA analysis of proposed steam electric ELGs

Benefit Inclusion Quantification Monetization

Reduced other adverse health 

effects (cancer and non‐cancer) 

from reduce d exposure to other 

pollutants (arsenic, lead, etc.) via 

fish consumption

Discussed in BCA 

but not given 

monetary value

Quantified 

(Low) Not Monetized
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Improved fisheries yield and 

harvest quality due to aquatic 

habitat improvement of 

commercial fisheries

Discussed in BCA 

but not given 

monetary value

Not Quantified Not Monetized

Benefits to tourism industries from 

increased participation in water 

based recreation

Discussed in BCA 

but not given 

monetary value

Not Quantified Not Monetized

Increased property values from 

water quality improvements

Discussed in BCA 

but not given 

monetary value

Not Quantified Not Monetized

Reduced impingement and 

entrainment mortality from 

reduced surface water withdrawals

Discussed in BCA 

but not given 

monetary value

Not Quantified Not Monetized

Reduced deposition of toxic 

pollutants to sediment

Discussed in BCA 

but not given 

monetary value

Not Quantified Not Monetized

Reduced adverse health effects 

from reduced exposure to 

pollutants from drinking water 

uses

Discussed in BCA 

but not given 

monetary value

Not Quantified Not Monetized

Reduced water treatment costs for 

drinking water and irrigation water 

from improved quality source 

water used for drinking and 

irrigation

Discussed in BCA 

but not given 

monetary value

Not Quantified Not Monetized

Reduced adverse health effects 

from reduced exposure to 

pollutants from recreational water 

uses

Discussed in BCA 

but not given 

monetary value

Not Quantified Not Monetized

Reduced bromide pollution in 

drinking water

Discussed in EPA 

documentation but 

not included in BCA

Not Quantified Not Monetized

Attractive nuisance: Reduced 

direct exposure to wildlife from 

surface impoundments

Discussed in EPA 

documentation but 

not included in BCA

Not Quantified Not Monetized

Recycling coal combustion 

residuals

Discussed in EPA 

documentation but 

not included in BCA

Not Quantified Not Monetized

Reduced air emissions from 

impoundments’ parasitic load

Completely omitted 

benefits Not Quantified Not Monetized

Reduced air emissions from true 

dry handling of ash

Completely omitted 

benefits Not Quantified Not Monetized

Value of land used for 

impoundments for redevelopment

Completely omitted 

benefits Not Quantified Not Monetized
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Avoided costs of BPJ 

determinations

Completely omitted 

benefits Not Quantified Not Monetized

Avoided costs of TMDLs Completely omitted 

benefits Not Quantified Not Monetized

Reduced withdrawals and 

consumptive use of surface water

Completely omitted 

benefits Not Quantified Not Monetized

Avoided costs of litigation Completely omitted 

benefits Not Quantified Not Monetized

55 78 Fed. Reg. at 34,504‐34,522; and Benefit‐Cost Analysis.

Comment Response: 

The commenter noted a variety of expected benefits that may result from revising the steam 

electric ELGs. EPA agrees with the commenter that the listed benefits are real and of critical 

ecological, social, and economic importance. To address commenters’ concerns, EPA revised its 

benefits analysis for the final rule to include additional categories not monetized in the proposed 

rule, including reduced incidence of cardiovascular disease from exposure to lead and arsenic, 

avoided cost of maintenance dredging of reservoirs and navigational waterways, and increased

marketing of coal combustion residuals for beneficial reuse (see Chapters 3, 9 and 10 in the 

BCA). In addition, EPA provides detailed description of all applicable categories of benefits, 

although data limitations preclude the Agency from quantifying and monetizing many of them 

(see Chapter 2 in BCA). Where possible, EPA also provided information about the potential 

magnitude of these benefits, relative to other benefits the Agency was able to monetize. EPA 

disagrees that a qualitative discussions of benefits that cannot be quantified or monetized 

constitute omissions of these benefits, or treating these benefit categories as generating $0 

benefits, as suggested by the commenter. As described in the preamble to the final rule, EPA 

considered both monetized and nonmonetized benefits in support of the regulation.

For a more detailed discussion on some of the specific benefit categories listed, see response to 

DCN EPA-HQ-OW-2009-0819-4686-A1, Excerpt Number 14.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 14

External Review Flag: Envr Assess

External Review Incorporated into Response: No

Comment Excerpt: 

Discussed in EPA’s Benefit‐Cost Analysis but not given a monetary value
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EPA discusses many benefits to which it fails to assign a monetary value, stating that it could not 

find adequate information to appropriately quantify a dollar impact to society. The benefits 

discussed qualitatively in EPA’s Benefit‐Cost Analysis but omitted from the total monetary value 

of the steam electric ELGs include:

 Reduced adverse health effects due to less exposure to pollutants from recreational water 

uses

 Reduced deposition of arsenic, selenium, and other pollutants in sediment on stream and 

lake beds

 Improved fisheries yield and harvest quality due to aquatic habitat improvement for 

commercial fisheries

 Benefits to the tourism industry from increased participation in water‐based recreation

 Increased property values from water quality improvements

 Fewer fish trapped and killed by water intake systems (i.e., reduced impingement and 

entrainment mortality)

There are also two benefits of the proposed ELGs that are mentioned in the Benefit‐Cost

Analysis, but for which EPA does not provide any qualitative assessment:

Reduced costs to processing drinking water: EPA includes reduced costs to treat drinking water 

as a benefit and mentions in a footnote that, “There may also be market benefits associated with 

the decreased need for drinking water treatment, but EPA did not estimate these benefits as part 

of its analysis of the proposed ELG.”56 Consequently, this benefit is not quantified or 

monetized.57

Reduced health effects from limiting exposure to pollutants in drinking water: EPA’s Benefit‐

Cost Analysis omits the reduction in negative health effects caused by improved drinking water 

quality: “The analysis of human health benefits focuses on the fish consumption pathway only, 

since EPA assumed that drinking water is treated to reduce pollutant concentrations below 

[maximum contaminant levels].”58 EPA acknowledges, however, that there are “documented 

exceedances of drinking water maximum contaminant levels (MCLs) downstream of steam 

electric power plants.”59 The benefits of reduced cancer exposure from pollutants other than 

arsenic are omitted because, according to EPA, “[a]mong steam electric pollutants analyzed in 

the [Environmental Assessment], arsenic is the only confirmed carcinogen with a published dose 

response function.”60 As such, any potential reduction in cancer rates from exposure to other 

carcinogens is omitted.

By default, EPA assigns these benefits a zero dollar value in the total monetized benefit of the 

regulatory options. These values of these omitted benefits are not reflected in the final number 

EPA uses to estimate the social value of the proposed ELG rules.

Discussed in EPA’s other documentation but not included in the Benefit‐Cost Analysis

Several other benefits are discussed in background documentation to the steam electric ELGs, 

but not in the Benefit‐Cost Analysis itself. These benefits, too, are effectively valued at zero 

dollars in the total monetary benefits of the regulatory options.
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Eliminated attractive nuisances: According to EPA’s Environmental Assessment the proposed 

steam electric ELGs will reduce the exposure of wildlife to pollutants at surface impoundments 

and constructed wetlands:

Documented case studies demonstrate that wildlife living near steam electric surface 

impoundments exhibit elevated levels of arsenic, cadmium, chromium, lead, mercury, selenium, 

strontium, and vanadium... Multiple studies have linked attractive nuisance areas at steam 

electric power plants to diminished reproductive success... EPA estimates that the pollutant 

loadings associated with the preferred options will decrease the exposure of wildlife populations 

to toxic pollutants and reduce the threat combustion residuals surface impoundments pose to 

surrounding wildlife.61

While EPA makes note of this important benefit of the proposed ELGs and cites several 

published reports to support their claims, this benefit does not appear in the Benefit‐Cost

Analysis.

Reduction of bromide pollution: Regulatory Option 5 (discussed in detail in Section 5 below) 

includes the only control technology in the proposed steam electric ELGs that would address 

pollutants from FGD wastewater that are particularly dangerous in drinking water: boron, 

bromides, and total dissolved solids. EPA explains that:

[B]romide in wastewater discharges from steam electric power plants located upstream from a 

drinking water intake has been associated with the formation of trihalomethanes, also known as 

THMs, when it is exposed to disinfectant processes in water treatment plants. Bromate, a 

disinfection byproduct (DBP) associated with drinking water treatment plants that employ 

ozonation may also increase under the influence of increased bromide in the source water. 

Human exposure to THMs and DBPs in chlorinated drinking water is associated with bladder 

cancer.62

EPA’s Benefit‐Cost Analysis does not discuss or monetize benefits of reduced bromide pollution 

in drinking water.

Additional recycling of coal combustion residuals: EPA does not discuss or monetize the 

benefits of the additional recycling of coal combustion residuals that would occur if FGD and 

other wet handling systems were converted to dry handling systems. Approximately 15 to 18 

percent of coal combustion residuals stored in wet surface impoundment are recycled, as 

compared to 22 to 27 percent of these residuals when subjected to dry handling. If the wet‐stored 

residuals from 2009 through 2011 had instead been recycling at the same rate as dry residuals, 

annual recycled materials would have increased by 1.6 million tons.63 Using a dollars per ton 

value of $99—which includes social benefits and the cost of avoided disposal—the annual 

benefit of this additional recycling would be $154 million.64

56 Benefit‐Cost Analysis, p.2‐5.
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57 Benefit‐Cost Analysis, p.2‐13.

58 Benefit‐Cost Analysis, p.3‐1.

59 Environmental Assessment, p. 3‐1.

60 Benefit‐Cost Analysis, p.3‐2.

61 Environmental Assessment, p. 6‐48.

62 78 Fed. Reg. at 34,477.

63 Troy Sanders, Environmental Integrity Project, “Coal Combustion Waste Recycling Analysis,” 

September 17, 2013.

64 See Frank Ackerman and Elizabeth A. Stanton comments on Docket ID EPA‐HQ‐RCRA‐

2009‐6040 on behalf of Earthjustice.

Comment Response: 

EPA agrees with the commenter that the proposed rule analysis did not sufficiently address some 

benefit categories. To address issues raised by public commenters (including issues raised in this 

comment), EPA expanded the benefit-cost analysis of the final rule to include the following 

benefit categories:

Reduced costs to processing drinking water: EPA conducted a screening-level analysis to 

evaluate the potential reduction in drinking water treatment needs and determined that these 

benefits are unlikely to be significant (see Section 2.4 of the BCA document). Based on this 

evaluation, EPA did not estimate changes in drinking water treatment costs but instead discussed 

potential benefits to drinking water utilities qualitatively. 

Eliminated attractive nuisances: EPA acknowledges that changes in CCR handling may 

contribute to reducing wildlife exposure to pollutants at surface impoundments. EPA revised the 

BCA for the final rule to discuss this benefit category qualitatively (see Chapter 2), but was 

unable to quantify or monetize those benefits due to data limitations.

Reduced health effects from limiting exposure to pollutants in drinking water: EPA conducted a 

screening-level analysis of the potential for reduced health impacts from exposure to pollutants 

in drinking water. As detailed in the BCA for the final rule(see Section 2.1), since few drinking 

water intakes are affected by steam electric power plant discharges at levels that exceed safe 

drinking water levels, and since drinking water supplies must already be treated for pollutants 

that pose human health risks, EPA determined that this benefit category is unlikely to be 

significant.

Reduction of bromide pollution: EPA agrees that bromide is a potential issue for drinking water 

treatment plants. For the final rule, EPA expanded discussion of the benefits of reducing bromide 
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pollution from the steam electric industry in drinking water sources (see BCA Section 2.4). See 

response to DCN EPA-HQ-OW-2009-0819-4684-A1, Excerpt Number 66.

Additional recycling of coal combustion residuals: EPA revised its analysis of this benefit 

category to estimate avoided disposal costs to steam electric power plants and avoided life cycle 

costs of virgin materials, following the same approach the Agency had used to estimate the 

benefits of the final CCR rule. See Chapter 10 of the final BCA document for details.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 15

External Review Flag: Engineering, Envr Assess

External Review Incorporated into Response: No

Comment Excerpt: 

Finally, there is no discussion whatsoever of several benefits of the steam electric ELGs.

Value of land for impoundments for redevelopment: The reduction in wastewater storage should 

result in less land used to build new impoundments, and more land available for redevelopment. 

This land has a value, either to the power plant itself for multiple potential purposes, or for sale 

to another prospective user. EPA neither discusses nor monetizes this benefit.

Reduced air emissions from impoundments’ parasitic load: EPA’s calculation of reduced air 

emissions appears to omit several sources of reductions. Surface impoundments require 

electricity to operate (a type of so‐called “parasitic load”). Fewer impoundments would result in 

air emission benefits from reduced parasitic load. These reduced air emissions are neither 

discussed nor monetized by EPA.

Reduced air emissions from true dry handling of ash: Similarly, the costs the EPA associates 

with bottom‐ ash handling are not based on true dry handling (as called for by the proposed 

ELGs), but rather on wet handling with zero discharge.65 True dry handling would greatly 

improve total unit efficiency and thereby producing more energy with less air emissions. These 

benefits are neither discussed nor monetized by EPA.

Avoided costs of BPJ determinations: Options 3a and 3b (for plants with less than 2,000 MW 

wet‐scrubbed capacity) would leave effluent limitations for FGD wastewater to be set on a case‐

by‐case basis by permitting authorities.66 This is not only inconsistent with EPA’s mandate under 

the Clean Water Act to set effluent limitations, but it also creates additional costs for permitting 

authorities, permitees, and interested third parties to develop, implement, and sometimes litigate 

BAT limitations for individual plants instead of having those limitations established by a 

national rule. The other options proposed by EPA avoid those costs, but EPA did not describe, 

let alone attempt to quantify or monetize, these benefits.
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Avoided costs of TMDLs: EPA estimates that 78 power plants discharge a pollutant into a water 

body that is listed under the Clean Water Act as “impaired” for that pollutant under Section 

303(d) of the Clean Water Act.67 Pursuant to that section of the Act, states are required to 

established total maximum daily loads (“TMDLs”) in those waters for pollutants that are 

contributing to water quality impairments.68 EPA last published a comprehensive study of the 

costs of developing and implementing TMDLs in 2001.69 According to that study, the average 

TMDL costs $52,000 in administrative costs to develop,70 and the study estimates that, 

nationwide, a total of 36,000 TMDLs are needed that will cost between $900 million and $3.2 

billion per year to implement.

71 With respect to the 78 power plants governed by the ELG rule 

that are contributing to water quality impairments, EPA found that both Options 4 and 5 would 

eliminate close to 100% of the pollution that those plants are contributing to those impairments,

whereas other options proposed in the rule would reduce that pollution by lesser 

amounts.72 Thus, the ELG rule would produce benefits by avoiding some or all of the costs of 

the TMDLs needed for the impaired water bodies into which those 78 power plants discharge. 

These benefits were neither discussed nor monetized by EPA.

[...]

Avoided costs of litigation: EPA also failed to quantify and monetize benefits from avoided 

litigation and related costs associated with illegal discharges, and ground and surface water 

pollution. Litigation costs can be substantial. There has been a wave of recent lawsuits filed 

against utilities for ground and surface water pollution in recent years, many of which have or 

will impose damages, penalties, monitoring and reporting requirements, corrective action to 

clean up ground and/or surface waters, installation of liner and leachate collection systems, 

replacement of drinking water, and/or closure.

65 Incremental Costs and Pollutant Removals at 8‐1.

66 78 Fed. Reg. at 34,458, Table VIII‐1.

67 Environmental Assessment at 6‐36 to 6‐37.

68 33 U.S.C. § 1313(d)(1)(C).

69 EPA, Office of Water, “The National Costs of the Total Maximum Daily Load Program (Draft 

Report)” (2001), available at http://nepis.epa.gov/Exe/ZyNET.exe/901K0800.TXT.

70 Id. at 18.

71 Id. at i‐ii.

72 Environmental Assessment at 6‐37.

Comment Response: 
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EPA agrees that the list of avoided costs and environmental effects presented by the commenter 

are potentially applicable benefit categories. The Agency used the best methods and available 

data to identify, quantify, and wherever possible monetize, the benefits of the rule. The BCA for 

the final rule describes the wide range of benefits EPA expects to result from the ELGs, 

including the benefits highlighted by the commenters. Many of these benefits are unquantifiable; 

they are discussed qualitatively in Chapter 2 of the BCA. EPA notes that the analysis of benefits 

fulfills the Agency’s requirements under Executive Order 12866 and supports informed policy 

decision, but is not a statutory factor for determining effluent limitations and standards.

Regarding the role of cost-benefit analysis in EPA’s decisions on the final steam electric ELGs, 

see response to DCN EPA-HQ-2009-0819-4464-A1, Excerpt Number 3 (in comment code 6.e).

Regarding the avoided burden of BPJ determinations, see response to DCN EPA-HQ-OW-2009-

0819-4684-A1, Excerpt Number 218 (in comment code 28.b).

Regarding the avoided cost of developing and implementing TMDLs, EPA recognizes that, to 

the extent that steam electric power generating plants discharges contribute to waterbody 

impairments, reducing the steam electric power plant discharges of pollutants of concern could 

reduce the need to develop TMDLs to address these impairments. EPA expects such benefits to 

be marginal. There is considerable uncertainty involved in estimating the benefits attributable to 

the ELGs from avoiding TMDLs, however, because steam electric power plants are often not the 

only cause of impairment within a watershed, and reducing their discharges may not obviate the 

need for a TMDL.

Regarding the avoided cost of litigation, generally, EPA agrees with the commenter that 

litigation costs associated with groundwater and surface water contamination, and the benefits of 

avoiding these costs, may be substantial. EPA included avoided cleanup costs and transactional 

costs of litigation in its avoided impoundment failure benefits analysis (see Chapter 6 in BCA) 

for cases that may result in surface water contamination. Regarding litigation costs associated 

with groundwater contamination specifically, in December 2014, EPA promulgated the CCR 

rule, which specifically addresses risks to groundwater quality from leaking impoundments. The 

CCR rule is included in the baseline for the ELG analysis, and as such, benefits derived from the 

CCR rule implementation have been accounted for and are not attributable to the final ELG.

Regarding reduced air emissions from impoundments’ parasitic load, EPA notes that the reduced 

air emissions from impoundments’ parasitic load are accounted for in EPA’s benefit analysis. 

Specifically, EPA netted out electricity savings associated with changes in impoundment 

operations when calculating changes in auxiliary power for the air-related benefits. This analysis 

is discussed in Section 12 of the TDD.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 17
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External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Methodological and ethical issues with monetizing benefits

In the monetization of the benefits from the proposed ELGs EPA employs several controversial 

valuation techniques, discussed below: restricting willingness‐to‐pay to local impacts; the use of 

diverging state income in valuing a statistical life; and including lower educational expenses as a 

value to society. Variations on these tools are commonly used in EPA benefit‐cost analyses, but 

are subject to well‐known critiques for undervaluing ecosystems, and human health and well‐

being.91

91 Ackerman, F and L Heinzerling, Priceless: On Knowing the Price of Everything and the Value 

of Nothing (New York: New Press, 2004).

Comment Response: 

EPA disagrees that it has employed monetization approaches that raise methodological and 

ethical issues, but acknowledges shortcomings in the description that lead to the commenter’s 

concerns about methodologies employed in the analysis of benefits of the steam electric 

ELGs. For complete responses to more specific concerns, see responses to comments EPA-HQOW-2009-0819-4686-A1 excerpt 43 (regarding the use of local willingness-to-pay for water 

quality improvements) and EPA-HQ-OW-2009-0819-4686-A1 excerpt 44 (regarding the use of 

income in adjusting the value of a statistical life and the cost of education as a component of IQ 

valuation).

EPA agrees with the commenter that some of the methodologies may result in underestimates of 

benefits to ecosystems and human health and well-being, but notes that the final rule analysis, as 

detailed in the BCA, reflects the up-to-date methods available for benefits analysis and valuation 

and appropriately notes the associated uncertainties.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4724-A2

Comment Excerpt Number: 2

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

I.EPA failed to monetize health benefits arising from cleaner drinking water as a result of 

the ELGs.
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EPA did not monetize health benefits arising from the removal of power plant pollution from 

source waters for drinking water.9 EPA’s rationale for not including these important benefits in 

its analysis is that “public drinking water supplies are already treated for pollutants that pose 

human health risks.”10 EPA’s rationale is flawed for several reasons. First, not all MCLs are set 

at a level that eliminates the risk of adverse health effects.11 Second, power plants discharge 

some pollutants that pose health risks, but are not currently regulated in drinking water.12 Third, 

some water systems do exceed MCLs.13 Finally, monitoring for dangerous pollution in drinking 

water can be infrequent (i.e. every 9 years).14 Thus, EPA should account for benefits arising 

from the removal of power plant pollution from source waters in this rulemaking.

9 U.S. Envtl. Prot. Agency, Benefit and Cost Analysis for the Proposed Effluent Limitations 

Guidelines and Standards for the Steam Electric Power Generating Point Source Category (EPA821-R-13-004) 2-4 to 2-5 (Apr. 2013) [hereinafter BCA].

10 Id. at 2-4. At the same time, EPA acknowledges that “treatment may not remove all 

contaminants from the drinking water supplies and there may be some incremental health-related 

benefits associated with reduced concentrations arising from the proposed ELGs.” Id. at 2-4 to 2-

5.

11 U.S. Envtl. Prot. Agency, Drinking Water Standards & Health Effects (EPA-816-F-04-037) 

(June 2004) [hereinafter Drinking Water Standards], available at 

http://water.epa.gov/lawsregs/guidance/sdwa/upload/2009_08_28_sdwa_fs_30ann_standards_we

b.pdf.

12 Power plants discharge 158,000 pounds of vanadium annually. EA at 3-13 tbl. 3-2. Although 

there is no MCL for vanadium at this time, this pollutant is on the Contaminant Candidate List. 

U.S. Envtl. Prot. Agency, Contaminant Candidate List 3 – CCL, 

http://water.epa.gov/scitech/drinkingwater/dws/ccl/ccl3.cfm#chemical (last visited Sept. 15,

2013).

13 See, e.g., U.S. Envtl. Prot. Agency, Office of Water, Fiscal Year 2011 Drinking Water and 

Ground Water Statistics (EPA-816-R-13-003) (Mar. 2013), available at 

http://water.epa.gov/scitech/datait/databases/drink/sdwisfed/upload/epa816r13003.pdf.

14 40 C.F.R. § 141.23(c)(4).

Comment Response: 

EPA agrees with the commenter that revised ELGs for the steam electric industry are likely to 

provide benefits arising from cleaner drinking water supplies and understands the commenter’s 

concerns that the analysis of the proposed rule did not quantitatively analyze such benefits.

For the final rule, EPA conducted a screening-level analysis to determine the potential magnitude 

of these benefits. This analysis, which is described in Section 2.1 of the BCA, suggests that the 
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benefits are unlikely to be substantial based on the number of drinking water intakes located on 

reaches where estimated concentrations exceed maximum contaminant levels (MCLs) in the 

baseline. Based on this assessment, EPA did not monetize the benefits in this category, but 

instead provided a more detailed qualitative discussion of health benefits arising from cleaner 

drinking water sources.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4724-A2

Comment Excerpt Number: 7

External Review Flag: Envr Assess

External Review Incorporated into Response: No

Comment Excerpt: 

EPA should have accounted for benefits arising from reduced exposure to these pollutants in 

drinking water as a result of the ELGs.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4724-A2 excerpt 2.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4724-A2

Comment Excerpt Number: 8

External Review Flag: Envr Assess

External Review Incorporated into Response: No

Comment Excerpt: 

C.EPA acknowledges violations of MCLs at some water treatment systems.

EPA’s rationale for not quantifying benefits arising from cleaner drinking water as a result of the 

ELGs is also flawed because it assumes that all water treatment systems are in compliance with 

all MCLs at all times. Yet this is not the case.46 In its most recent drinking water report, EPA 

notes that the overall national average for compliance with health-based drinking water standards 

is approximately 93%, with some regions as low as 84%.47 In 2011, there were 8,522 violations 

of MCLs at 4,010 community water systems alone.48 The population potentially impacted by 

these violations was nearly 15 million people.49 That same year, EPA reports over 76,000 

monitoring and reporting violations at 17,519 systems, affecting over 60 million people.50
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EPA’s report also identifies MCL violations of DBP standards.51 For all water treatment 

systems subject to the rule, there were 2,599 MCL violations of the Stage 1 DBP rule at 1,026 

systems serving over 3 million people.52 In fact, in the supporting documents for this 

rulemaking, EPA states that drinking water utilities have “not[ed] that . . . bromide 

concentrations have made it increasingly difficult for them to meet Safe Drinking Water Act 

requirements for TTHMs.”53 A recent report by several drinking water utilities in Pittsburgh, 

PA notes that “[a] number of US drinking water utilities have struggled to comply” with EPA’s 

Stage 1 DBP rule and “even more utilities anticipate difficulty meeting the more stringent 

requirements” of the Stage 2 DBP rule that recently took effect.54 Thus, for the purposes of the 

analysis for the ELGs, EPA should not assume that all systems are in compliance with all MCLs 

at all times.

D.In some cases, water treatment system monitoring for pollutants discharged from power 

plants is infrequent.

EPA’s assumption also ignores the potential for violations of drinking water standards to remain 

undetected under infrequent Federal and State monitoring requirements. For example, federal 

regulations require public drinking water systems to monitor for inorganic chemicals (including 

antimony, arsenic, barium, beryllium, cadmium, chromium, cyanide, mercury, nickel, selenium, 

and thallium) once during an initial period of one year for surface water systems or three years 

for groundwater systems.55 However, States can reduce the monitoring requirement to only 

once every nine years if three consecutive samples from initial monitoring produce results below 

the applicable MCL.56 Infrequent monitoring over several years is not sufficient to identify 

whether a drinking water system is consistently complying with MCLs. Because many systems 

may monitor infrequently for pollutants in power plant discharges, EPA should not assume that 

all systems are in compliance at all times for the purposes of determining whether the ELGs will 

result in health benefits from cleaner source waters.

46 U.S. Envtl. Prot. Agency, Office of Water, Fiscal Year 2011 Drinking Water and Ground 

Water Statistics (EPA- 816-R-13-003) (Mar. 2013), available at 

http://water.epa.gov/scitech/datait/databases/drink/sdwisfed/upload/epa816r13003.pdf.

47 Id. at 17.

48 Id. at 18-19. A “community water system” is “a public water system that supplies water to 

the same population year-round.” Id. at 5.

49 Id. at 19.

50 Id. at 18-19.

51 Id. at 25, 28.

52 Id. at 25.
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53 EA at 3-11.

54 Stanley States et al., Marcellus Shale Drilling and Brominated THMs in Pittsburgh, PA, 

Drinking Water, 105 Journal American Water Works Association E432, E432, E448 (Aug. 2013) 

(noting that Marcellus Shale drilling activities and coal plants account for increases in bromide 

concentrations in Allegheny River Systems).

55 40 C.F.R. § 141.23(c)(1).

56 40 C.F.R. § 141.23(c)(4). In addition, reduced monitoring for cyanide requires the State to 

determine that the system is not vulnerable due to lack of any industrial source of cyanide. 40 

C.F.R. § 141.23(c)(2).

Comment Response: 

EPA acknowledges the commenter’s concerns that drinking water sources may not be in 

compliance with MCLs at all times, and thanks the commenter for providing data on occurrences 

of exceedances.

EPA notes, however, that its Guidelines for Preparing Economic Analyses (U.S. EPA, 2014) 

describe how to treat compliance with existing regulations in the baseline for analyzing a 

rule. “As a general rule, when preparing analyses of regulations analysts should develop 

baseline and policy scenarios that assume full compliance with existing and newly enacted (but 

not yet implemented) regulations. Assuming full compliance with existing regulations enables 

the analysis to focus on the incremental economic effects of the new rule or policy without 

double counting benefits and costs captured by analyses performed for other rules.” (U.S. EPA, 

2014, p. 5-9).

For the final rule, EPA conducted a screening-level analysis to determine the potential magnitude 

of benefits to public drinking water systems. This analysis, which is described in Section 2.1 of 

the BCA, looked at the number of drinking water intakes located on reaches where estimated 

concentrations exceed maximum contaminant levels (MCLs) in the baseline and suggested that 

expected benefits to public drinking water systems would be small. Based on this assessment, 

EPA did not monetize the benefits in this category, but instead provided a more detailed 

qualitative discussion of health benefits arising from cleaner drinking water sources, including 

recognizing that monitoring of drinking water systems is imperfect. Also, based on this analysis, 

EPA determined that an alternative baseline assuming less than full compliance with SDWA 

regulations would not result in an important sensitivity analysis.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4724-A2

Comment Excerpt Number: 9
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External Review Flag: Envr Assess

External Review Incorporated into Response: No

Comment Excerpt: 

II.EPA did not quantify or monetize benefits from reduced drinking water treatment costs.

EPA also failed to monetize benefits from reduced drinking water treatment costs arising from 

cleaner source waters as a result of the ELGs. EPA states that

[t]he proposed ELGs are expected to reduce costs of drinking water treatment (e.g., filtration 

and chemical treatment) by reducing metal concentrations and eutrophication in source waters. 

Eutrophication is one of the main causes of taste and odor impairment in drinking water, which 

has a major negative impact on public perceptions of drinking water safety. Additional treatment 

to address foul tastes and odors can significantly increase the cost of public water supply. 

Further, public drinking water sources do not always effectively remove bromides (a steam 

electric pollutant) from raw surface waters. Elevated bromide concentrations in source waters 

result in increased trihalomethanes (THMs) in drinking water. Drinking water utilities 

downstream of bromide sources are increasingly finding it difficult to meet drinking water 

standards for THMs. If water treatment is not sufficient, an alternate water source needs to be 

substituted (if available). Longterm solutions might require the development of new raw water 

supplies, which would involve costs for the acquisition of land (if available), regulatory review 

and permitting, development of infrastructure (dams, pumps, pipes), and watershed protection.57

EPA did not quantify or monetize these important benefits because of “data limitations.”58 Yet 

the EPA Office of Ground Water and Drinking Water routinely estimates incremental costs 

associated with drinking water treatment during the SDWA regulatory process.59 In addition, 

the Office of Water has quantified and monetized the benefits from reduced drinking water 

treatment costs as a result of improved surface water quality from an ELG in the past.60 EPA 

should do the same here.

In 2008, EPA estimated avoided costs of drinking water treatment from reduced sediment 

loadings from construction sites as a result of the proposed ELG.61 EPA estimated “[s]ediment 

concentrations and drinking water influent volumes . . . for each surface drinking water intake in 

the United States.”62 “EPA [then] calculated the costs of treatment chemicals and sludge 

disposal by surface drinking water intake . . .” and compared the baseline and post-compliance 

costs to estimate the cost savings arising from the requirements of the ELG.63 EPA also 

conducted a sensitivity analysis to address uncertainty.64 EPA has provided no reason why they 

cannot do the same analysis here.

Furthermore, during the regulatory processes to set MCLs, the Office of Ground Water and 

Drinking Water estimates the incremental capital, operating and maintenance, and waste disposal 

costs associated with drinking water treatment for the purposes of compliance with a potential 

MCL.65 For example, in the rulemaking to revise the arsenic MCL, EPA evaluated the 

following costs for various treatment systems to meet the MCL of 0.010 mg/l where source 

waters were 0.011 mg/l and 0.050 mg/l: capital, operating and maintenance, waste disposal, 
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waste disposal operating and maintenance, and annual.66 In other words, EPA is able to 

estimate incremental operating and maintenance costs to clean up water contaminated at various 

levels. Thus, monetizing benefits arising from reductions in source waters pollution as a result of 

the proposed Steam Electric ELGs is possible.

As EPA notes in the Benefit and Cost Analysis for the Proposed Effluent Limitations Guidelines 

and Standards for the Steam Electric Power Generating Point Source Category, these costs can 

be significant.67 Increased pollution in source waters means increased costs associated with 

additional chemicals, more frequent replacement of filters and adsorptive media, waste disposal, 

and additional training,68 all of which EPA must quantify and monetize in order to better 

represent the benefits associated with the ELGs. “Bromide is particularly difficult and expensive 

to remove and its associated brominated DBPs are among the most harmful.”69 In some cases, 

systems must switch disinfectants, “which carries increased costs as well as a need for additional 

training of operators. For example, the switch to chloramine requires addition of phosphate to 

control lead releases that can be caused by the transition . . . ."70 Water treatment systems may 

also be forced to find an alternative drinking water supply, which can carry substantial costs.71

One system in California estimated these additional costs at approximately $20 to $60 per square 

acre-foot, resulting in increased costs of $30 to $90 million dollars each year.72

In conclusion, Steam Electric ELGs that eliminate or significantly reduce discharges of toxic 

pollution from power plants will have a significant and positive impact on the quality of drinking 

water and the cost of treatment. Finalizing Option 5 provides EPA with a unique opportunity to 

advance the goals of both the Clean Water Act and SDWA and ensure the public has access to 

safe drinking water. Thus, EPA should quantify and monetize these important benefits.

57 BCA at 2-9.

58 Id. at 2-10.

59 U.S. Envtl. Prot. Agency, Arsenic in Drinking Water Rule Economic Analysis (EPA-815-R00-0026) (Dec. 2000).

60 U.S. Envtl. Prot. Agency, Environmental Impact and Benefits Assessment for Proposed 

Effluent Guidelines and Standards for the Construction and Development Category (EPA-821-R08-009) (Nov. 2008).

61 Id. at 9-1 to 9-14.

62 Id. at 9-2.

63 Id.

64 Id.
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65 U.S. Envtl. Prot. Agency, Arsenic in Drinking Water Rule Economic Analysis (EPA-815-R00-0026) (Dec. 2000).

66 Id. at Exhibit 6-2a and 6-2b.

67 BCA at 2-9.

68 See, e.g., EA at 3-32; Memo from Lydia Lambert & Kristi Bubb, ERG, to Bill Swietlik, 

EPA, Re Drinking Water Treatment Technologies that Can Reduce Metal and Selenium 

Concentrations Associated with Discharges from Steam Electric Power Plants (DCN SE02154) 

(Sept. 2, 2010).

69 Wei-Hsiang Chen et al., Delta Drinking Water Quality and Treatment Costs Technical 

Appendix H iv (Sept. 2008), available at 

http://www.ppic.org/content/pubs/other/708EHR_appendixH.pdf.

70 Jeanne M. VanBriesen, Potential Drinking Water Effects of Bromide Discharges from CoalFired Electric Power Plants (2013).

71 Wei-Hsiang Chen et al., Delta Drinking Water Quality and Treatment Costs Technical 

Appendix H iii (Sept. 2008), available at 

http://www.ppic.org/content/pubs/other/708EHR_appendixH.pdf.

72 Id. at iv.

Comment Response: 

EPA agrees with the commenter that the final rule will improve water quality in receiving 

reaches, including reaches used as drinking water sources. EPA did not quantify drinking water 

benefits of the ELGs revisions because public drinking water supplies are already treated for 

most steam electric pollutants that pose human health risks. Additionally, while EPA recognizes 

that it is possible to estimate changes in treatment costs due to improved water quality, and that 

the Agency has calculated these costs for several rules, the discussion in Chapter 2 addresses 

why the Agency did not quantify the changes in treatment costs for the final ELGs.

Specifically, EPA’s screening-level analysis (see Section 2.1 in BCA) identified few reaches 

with drinking water intakes where the estimated pollutant concentrations exceed MCLs in the 

baseline, which suggests that benefits associated with improvements in source water quality 

would be relatively small. During the first step in the assessment, EPA determined that water 

utilities may see reduced costs for the removal of arsenic, cadmium, copper, lead, mercury, 

selenium, thallium, nitrogen, and total suspended solids. During the second step in the 

assessment, EPA determined that few drinking water systems are currently drawing water at 

levels that exceed one or more MCLs and would improve under the policy options. And 

similarly, few reaches with elevated total nitrogen levels will see those levels decline 

significantly under the regulatory options to result in substantive cost savings. When EPA looked 

at the potential for reduced drinking water treatment costs arising from reduced suspended solids 
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concentrations using the same methodology it previously used for the Construction and 

Development ELG rule analysis, the Agency found de minimis changes in treatment costs due to 

the very few intakes located downstream from steam electric power plant discharges.

For the final rule, EPA revised its analysis to include additional drinking water treatment 

literature (including studies provided by the commenter), and to provide a more detailed 

discussion of other steam electric pollutants, such as bromide. The Environmental Assessment for 

the Effluent Limitations Guidelines and Standards for the Steam Electric Power Generating 

Point Source Category (EA Report) (DCN SE04527) summarizes the relationships between 

bromide levels and drinking water treatment practices, and health effects of disinfection 

byproducts. The BCA describes why EPA did not quantify or monetize the particular benefits of 

bromide reductions. Specifically, EPA’s final rule does not set effluent limits for bromide for the 

steam electric industry, based on the performance of the best available technology (BAT) for 

FGD wastewater treatment (chemical precipitation and biological treatment). Because the final 

ELG does not set technology-based limits on bromide discharge, EPA did not estimate the 

bromide reduction benefits of the rule. EPA notes, however, that the rule allows permit writers to 

set bromide discharge limits on a plant-by-plant basis based on site-specific considerations that 

include the potential to affect public drinking water sources. Benefits of any plant-specific limits 

in terms of avoided treatment costs or human health risk would need to be determined based on 

more detailed information about the receiving waters and drinking water system.

Commenter Name: J. Duggan

Commenter Affiliation: Environmental Integrity Project (EIP) et al.

Document Control Number: EPA-HQ-OW-2009-0819-5488-A2

Comment Excerpt Number: 1

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The comments we submitted on September 20, 2013 identified EPA’s failure to quantify and 

monetize benefits from avoided litigation and related costs associated with illegal discharges and 

ground and surface water pollution.1 Litigation costs can be substantial. For example, 

Constellation Energy Group paid $54 million to settle a lawsuit brought by Maryland residents 

for groundwater contamination at a coal ash disposal site.2 Landowners in Montana settled a 

coal ash contamination lawsuit for $25 million.3 There has been a wave of recent lawsuits filed 

against utilities for ground and surface water pollution in recent years, many of which have, or 

will, impose damages, penalties, monitoring and reporting requirements, corrective action to 

clean up ground and/or surface waters, installation of liner and leachate collection systems, 

replacement of drinking water, and/or closure. Exhibit No. 32 of our comments4is a survey of 

just a few of recent proposed and final consent orders and other agreements. All of the 

requirements imposed by these agreements carry significant costs. Yet EPA has failed to 

account for them in its analysis.
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1 See Comments submitted by Earthjustice et al. to Water Docket, U.S. Envtl. Prot. Agency, on 

proposed rule to revise Effluent Limitations Guidelines and Standards for the Steam Electric 

Power Generating Point Source Category (Sept. 20, 2013) (Document ID EPA-HQ-OW-2009-

0819-4684).

2 S. Schultz, Constellation Reaches $54 Million Settlement of Fly Ash Lawsuit,” Baltimore 

Business Journal (Dec. 31, 2008).

3 N. Goldman, Federal Regulation Needed for Coal Fly Ash, The Missoulian (2010).

4 See Document IDs EPA-HQ-OW-2009-0819-4724, -4725, -4726.

Comment Response: 

EPA agrees with the commenter that litigation costs associated with groundwater and surface 

water contamination may be substantial (but notes that settlement amounts do not constitute 

costs to society but rather transfers). To the extent that such costs result from accidental releases 

that would be prevented or reduced by actions the plants may take to meet their permitted limits 

(e.g., convert to dry handling of ash), avoiding the costs are a relevant benefit of the rule. In 

December 2014, EPA promulgated the CCR rule, which specifically addresses risks to 

groundwater quality from leaking impoundments. The CCR rule establishes technical 

requirements for CCR surface impoundments, including composite liners, groundwater 

monitoring, corrective action, and closure/post closure care, among others. The CCR rule is 

included in the baseline for the ELG analysis, and as such, benefits derived from the CCR rule 

implementation have already been accounted for (i.e., they are not attributable to the final ELG). 

Including them in the final ELG analysis would be double-counting.

EPA included avoided cleanup costs and transactional costs of litigation in its avoided 

impoundment failure benefits analysis (see Chapter 6 in the BCA). EPA agrees that these costs, 

and the benefits of avoiding these costs, may be substantial as reflected by the benefit estimates 

presented in the BCA.
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29.b. Benefits – Benefit analyses assumptions 

Commenter Name: Daniel Simmons

Commenter Affiliation: Institute for Energy Research

Document Control Number: EPA-HQ-OW-2009-0819-4473-A1

Comment Excerpt Number: 5

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA FAILS TO FOLLOW OMB’S CIRCULAR A-4 ON THE PRESENTATION OF 

COST/BENEFIT ANALYSES

OMB Circular A-47 (relying in turn on Circular A-94) states that “a real discount rate of 7 

percent should be used as a base-case for regulatory analysis,” as this is the average before-tax 

rate of return to private capital investment. However, Circular A-4 acknowledges that in some 

cases, the displacement of consumption is more relevant, in which case a real discount rate of 3 

percent should be used. Thus it states: “For regulatory analysis, you should provide estimates of 

net benefits using both 3 percent and 7 percent.” Note that Circular A-4 does not say that a 

discount rate should be chosen based on the impacts; instead it says quite clearly that estimates 

should be made using both rates.

In the economics of climate change academic literature, there are disputes over the proper 

discount rate, with some economists arguing that very low rates should be used in order to place 

future generations on a nearly equal footing with the present generation in policy analysis. 

Circular A-4 and the White House’s primer on Circular A-4,8explicitly cited the work of 

Martin Weitzman, one of the leading scholars in the field on this issue, who argues for a low 

discount rate in climate change analysis.9 Nonetheless, after this discussion the 2011 primer still 

concluded:

If the regulatory action will have important intergenerational benefits or costs, the agency might 

consider a sensitivity analysis using a lower but positive discount rate, ranging from 1 to 3 

percent, in addition to calculating net benefits using discount rates of 3 percent and 7 

percent. [“Regulatory Impact Analysis: A Primer,” p. 12, bold added.]

But instead of following OMB’s guidance and calculating the social cost of carbon at a 7 percent 

discount rate, EPA refuses and only uses a 5 percent discount rate. EPA states:

Because SCC values are not available for the 7 percent discount rate, EPA used the SCC based 

on a 5 percent discount rate to estimate values presented for the 7 percent discount rate. EPA 

uses 5 percent to discount CO2-related benefits and 7 percent to discount benefits from changes 

in NOX and SO2 emissions.10
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This is an arbitrary and capricious deviation from OMB’s guidance on the use of discount rates. 

EPA could have run the social cost of carbon models at a 7 percent discount rate, but it failed to 

do so.

It certainly is possible to run social costs of carbon models at a 7 percent discount rate. Recently, 

the Heritage Foundation ran the DICE model,11 one of the three models that the administration 

used to estimate the social cost of carbon. Here are the results from the DICE mode at a 2.5 

percent, 3 percent, 5 percent, and 7 percent discount rate, according to the Heritage Foundation 

analysis.

It is easy to see why EPA would be reticent to include the 7 percent discount rate as required by 

OMB—the SCC at the 7 percent discount rate is substantially lower, at roughly only 50 percent 

of the 5 percent discount rate. This demonstrates why EPA’s exclusion of the SCC at the 7 

percent discount rate is arbitrary and capricious. Furthermore, although the Heritage Foundation 

only tested the effect of including a 7 percent discount rate using the DICE model, the results 

would presumably be even more striking had they done the same procedure with the FUND 

model. This is because the DICE projects immediate (and rising) net damages from global 

warming. In contrast, the FUND model projects decades of global benefits from global warming, 

which only switches over to net damages after the year 2050.12 Therefore, applying a 7 percent 

discount rate (rather than the highest rate of 5 percent as the Working Group chose to do) to the 

stream of benefits and damages in the FUND model, would yield a present-value SCC very close 

to $0/ton, if not negative.

7OMB Circular A-4 available at: http://www.whitehouse.gov/omb/circulars_a004_a-4.
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8

“Regulatory Impact Analysis: A Primer,” available 

at: http://www.whitehouse.gov/sites/default/files/omb/inforeg/regpol/circular-a4_regulatory- impact-analysis-a-primer.pdf.

9See: http://www.whitehouse.gov/sites/default/files/omb/inforeg/regpol/circular-a- 4_regulatoryimpact-analysis-a-primer.pdf.

10Environmental Protection Agency, Effluent Limitations Guidelines and Standards for the 

Steam Electric Power Generating Point Source Category, 78 Fed. Reg. 34432, 34517, June 7, 

2013.

11Kevin Dayaratna & David Kreutzer, Re: Social Cost of 

Carbon, http://www.scribd.com/doc/168715712/Comment-to-EPA-on-the-Social-Cost-ofCarbon-Sept-16-2013.

12See Figure 1B (page 10) from the 2010 report of the Working Group on Social Cost of Carbon.

Comment Response: 

EPA disagrees with the commenter’s assertion that the Agency’s CO2 valuation approach 

arbitrarily and capriciously deviates from OMB regulatory impact analysis guidance in Circular 

A-4. EPA valued CO2 emissions reductions using the United States Government Interagency 

Working Group on Social Cost of Carbon’s (“Working Group”) social cost of carbon (SCC) 

estimates (IWGSCC, 2013) and recommended discount rates. This is consistent with the 

approach EPA used in other analyses that value reductions in CO2 emissions. GAO addressed the 

apparent inconsistencies between OMB Circular A-4 and the Working Group’s 2013 guidance 

directly in its review of regulatory impact analyses and concluded that the “discount rates [2.5, 3, 

and 5 percent] are consistent with the latitude provided in Circular A-4 and span a plausible 

range to account for disagreement in the literature on the appropriate rate to use in this context 

and various uncertainties.” (GAO, 2014; p. 25). Using a SCC estimate based on 7 percent 

discount rate, as the commenter suggests would be feasible, but is inconsistent with explicit 

recommendations of the Working Group’s panel of economic experts and federal agencies.

For the final rule, EPA used the full suite of SCC estimates developed by IWGSCC to estimate 

the value of CO2 emission reductions (2.5, 3, and 5 percent). EPA acknowledges that using SCC 

estimates based on these discount rates differs from estimates of other benefits in the BCA 

(which EPA valued at 3 percent and 7 percent discount rates). As recognized by OMB (cited in 

GAO, 2014; p.25), however, the difference in discount rates is “unavoidable due to the 

intergenerational nature of the benefits associated with reducing carbon dioxide emissions.”

EPA maintains that its approach to valuing CO2 emissions reductions for the final rule, as 

presented in Chapter 7 of the BCA for the final rule, is not arbitrary and capricious but rather 

reflects best practices and follows recommendation of IWGSCC and GAO.

For the role of cost-benefit in EPA’s decisions on the final rule, see response to DCN EPA-HQOW-2009-0819-4464-A1, Excerpt Number 3 (in comment code 6.e).
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References

Government Accounting Office. 2014. “Environmental Regulation: EPA Should Improve 

Adherence to Guidance for Selected Elements of Regulatory Impact Analyses” 

http://www.gao.gov/assets/670/664872.pdf

Commenter Name: Quinlan J. Shea III

Commenter Affiliation: Edison Electric Institute (EEI)

Document Control Number: EPA-HQ-OW-2009-0819-4487-A1

Comment Excerpt Number: 97

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In the background documents for the proposed rule, EPA calculates the monetized benefits and 

assesses associated regulatory impacts for the various proposed regulatory options discussed 

above. EPA’s benefits calculation is mainly based on "avoided" adverse effects on human health 

and the environment related to water and air quality, and on market and productivity benefits, 

including avoided costs related to impoundment guidelines. In the Environmental Assessment 

prepared in support of the proposed rule, EPA also presented water quality evaluations that were 

not quantified as part of the benefits evaluation, but were apparently used to justify the need for 

the proposed rule. As further detailed below and in UWAG Comments, EPA’s Benefit and Cost 

Analysis (EPA-HQ-OW-2009-0819-2238) and Regulatory Impact Analysis (EPA-HQ-OW2009-0819-2239), which build on other faulty EPA analyses such as the Environmental 

Assessment and Technical Development Document, are flawed.

Comment Response: 

The comment characterizes the cost-benefit and regulatory impact analyses as “flawed” and 

based on “faulty” analyses. EPA disagrees with this characterization.

As noted in responses to other comments (e.g., see DCN EPA-HQ-OW-2009-0819-4487-A1, 

Excerpt Number 107), EPA acknowledges that it was not able to bring the same depth of 

analysis to all categories of benefits because of imperfect understanding of the link between 

discharge reductions or other environmental effects of the ELGs and benefit categories, and how 

society values some of the benefits. Nonetheless, EPA determined that its methods provide the 

best possible estimates of benefits from the final rule, given challenges posed by limitations in 

data, modeling tools, and the available scientific literature. EPA’s benefit analysis for the final 

rule clearly highlights ecological and other benefits of improved ambient water quality in 

receiving reaches, benefits from avoided adverse health effects and from avoided costs of 

impoundment failures (see the BCA for details).
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EPA addressed the commenter’s concerns about the analyses described in the EA Report and 

TDD in separate answers (for example, see answers to comment EPA-HQ-OW-2009-0819-4487-

A1, Excerpt Number Numbers 14, 22, 37, etc.). EPA incorporated changes made in response to 

comments, where applicable, when analyzing the benefits of the final rule. For example, the final 

rule benefits analysis is based on EPA’s revised loading estimates, which were updated as a 

result of public comments. These changes, which are detailed in the rulemaking record for the 

final rule, result in loading estimates that are lower than those EPA calculated for the proposed 

rule.

For the role of cost-benefit in EPA’s decisions on the final rule, see response to DCN EPA-HQOW-2009-0819-4464-A1, Excerpt Number 3 (in comment code 6.e).

Commenter Name: Quinlan J. Shea III

Commenter Affiliation: Edison Electric Institute (EEI)

Document Control Number: EPA-HQ-OW-2009-0819-4487-A1

Comment Excerpt Number: 107

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA Assumptions Overestimate Benefits

Building upon the exaggerated power plant environmental impacts described by EPA, the 

Agency then employs assumptions resulting in flawed and systematic overestimation of benefits 

associated with the proposed rule. It is not clear from the fundamentally flawed benefits analysis 

that any of the proposed ELG regulatory options will provide a measurable benefit to human 

health or the environment.

As discussed above, EPA failed to sufficiently justify many of the assumptions used to estimate

surface water quality and in turn the potential effects on human health and the 

environment. Also, in many cases, the assumptions underlying EPA’s benefits analysis fail to 

acknowledge previously identified uncertainties (as documented in other EPA reports). The use 

of uncertain assumptions with known limitations makes the benefit-cost analysis an unreliable 

tool for rulemaking.

[...]

Finally, as discussed above, many of the analyses associated with the proposed rule are 

interconnected, which means flaws in one analysis are compounded by use in subsequent 

analyses. For example, the flawed cost-effectiveness analyses discussed above feed into the 

various background support analyses, including the regulatory impacts assessment. This effect 

extends to EPA’s benefits calculations where overly conservative assumptions in primary 

analyses (i.e., surface water contaminant modeling) are propagated through the assessment and 
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compounded in the final output (i.e., the benefit calculation). [In another example, EPA’s 

estimate of benefits attributable to reduced impoundment failure, which make up 37-58% of the 

total benefits attributed to the proposed ELG (for options 3 and 4 where air benefits estimates are 

provided), is likely overestimated as a result of compounded flaws on EPA’s unit cost and failure 

probabilities. Gradient Report at 35.] These compounded flaws throughout the interconnected 

analysis feeding into EPA’s benefits analysis manifest as benefits estimates that are over-inflated 

and overstate the effectiveness of the proposed control options such that it is not clear that any of 

the proposed ELG regulatory options will provide a measurable benefit to human health or the 

environment.

Comment Response: 

This comment relays four general assessments of EPA’s cost benefit analyses, all of which EPA 

disagrees with: (1) that benefit environmental assessment and benefit estimation models are 

“fundamentally flawed,” (2) that benefit-cost analyses do not sufficiently justify assumptions 

used in estimating surface water quality improvements and associated benefits, (3) that 

documentation does not acknowledge previously-identified uncertainties, and (4), a concern that 

uncertainties in analyses “compound” when used in subsequent analyses.

EPA details reasons for disagreement with assertions about individual benefit analyses in its 

responses to other comments (e.g., for response to air-related benefits analyses, see response to 

DCN EPA-HQ-OW-2009-0819-4487-A1, Excerpt Number 129; for comments about the 

impoundment analysis, see responses EPA-HQ-OW-2009-0819-4655, Excerpt Number 190). 

Regarding outputs from the environmental assessment or engineering analysis that are used as 

inputs for the benefits analyses, EPA addressed the commenter’s concerns in separate answers 

(for example, see answers to comment EPA-HQ-OW-2009-0819-4487-A1, Excerpt Number 

Numbers 14, 22, 37, etc.). EPA incorporated changes made in response to comments, where 

applicable, when analyzing the benefits of the final rule. For example, the final rule benefits 

analysis is based on EPA’s revised loading estimates, which incorporate revisions made to the 

engineering analysis and environmental assessment in response to comments, and additional data 

received or published since the proposed rule analysis. EPA also updated its estimates to account 

for the impacts of other federal rules on pollutant loads and plant characteristics. These changes,

which are detailed in the rulemaking record for the final rule resulted in loading estimates that 

are lower than those EPA calculated for the proposed rule.

In documents supporting the final rule, EPA articulates methods, documents data sources, and 

discusses underlying assumptions crucial to the scope of the analysis, including discussions and 

quantifications of the implications of uncertainty for benefit estimates. The BCA outlines the 

analytic framework uniting all analyses, demonstrates analytic steps used to link expected 

pollutant load reductions with changes in environmental endpoints and economic values (e.g., 

dose-response functions, value of statistical life, etc.), and describes methods and results of its 

uncertainty and sensitivity analyses.

Note that EPA determines ELGs based on factors specified in the Clean Water Act (including 

economic achievability), rather than strict comparison of benefits and costs. Nonetheless, as 

Executive Order 12866 acknowledges, the existence of limitations, assumptions, and/or 
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uncertainties does not make any given benefit-cost analysis “an unreliable tool” as claimed by 

the commenter. That uncertainties in one stage of the analysis may propagate to secondary stages 

is unavoidable, but EPA maintains that its analyses of the final rule provide well-supported 

information on the expected benefits of the ELGs.

Commenter Name: Cathy S. Woollums

Commenter Affiliation: MidAmerican Energy Holdings Company

Document Control Number: EPA-HQ-OW-2009-0819-4495-A1

Comment Excerpt Number: 6

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA's more detailed report on the benefits of the ELG proposal relied on census data and other 

studies that were conducted 10 or more years ago, and had some questionable assumptions that 

are questionable, at best, and potentially inaccurate. For example:

 EPA assumed that a plant would generate approximately the same quantity of electricity 

in 2014 as it did from 2007 through 2009. However, recent data and announced plant 

shutdowns associated with compliance with the Mercury and Air Toxics Standards, 

depressed market conditions, and low natural gas prices point to flaws in this assumption. 

Electricity generation between 2007-2009 was, likewise, depressed with reduced load 

corresponding with the national economic recession, during which utilities nationwide 

experienced reduced demand.

Comment Response: 

In conducting benefit and other analyses for the ELGs, EPA used studies and datasets which the 

Agency determined most accurately estimated, described, or could be used to model 

environmental and economic conditions. EPA updated some of these data for the final rule 

analysis to reflect more recent information not available at the time of the proposed rule; see the 

BCA (Appendix A) for a description of updates and other changes since the proposed rule 

analysis.

Regarding the specific example the commenter provides of EPA’s use of EIA data, EPA 

acknowledges that historical trends reflected in EIA data may over- or under-estimate impacts of 

the ELGs if actual conditions differ materially from the trends. EPA updated the data to include 

more recent information from EIA for 2012, as well as used the most recent version of the 

Integrated Planning Model (IPM v5.13) which includes updated electricity demand projections, 

generating capacity, environmental regulations, etc. For details, see the RIA document for the 

final rule. EPA maintains that the data and methods used for both benefit and cost analyses are 

appropriate for their intended use.
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Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 197

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

UWAG asked Gradient to review the methodologies and assumptions that EPA used to calculate 

baseline pollutant loadings, as well as the underlying models, toxicity, benchmarks and 

assumptions used to quantify the reduced risks (i.e., the benefits) under the different regulatory 

options. Gradient’s focus was to understand and evaluate the scientific validity of EPA’s 

methodology and uncertainty associated with specific assumptions. Gradient found that 

substantial portions of both the monetized and non-monetized benefits asserted by EPA are 

overstated or not adequately detailed, calling into question whether the proposed rule is 

adequately supported.

Comment Response: 

EPA disagrees with the commenter’s characterization of the results that “substantial portions” of 

the benefits are overstated or insufficiently documented to support the rule.

EPA acknowledges that some benefits may be over- or under-stated due to limitations and 

uncertainties of available data and environmental or economic models, and discusses these 

limitations as well as the direction of the uncertainty where known in the BCA. EPA determined 

that its approach to estimating benefits in the face of limitations has been rational and provided 

reasoned support for policy decisions. For more on the role of cost-benefit in EPA’s decisions on 

the final rule, see response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in 

comment code 6.e).

For more detailed responses to specific aspects of the benefit analysis, see response to related 

comments (e.g., DCN EPA-HQ-OW-2009-0819-4655, Excerpt Number 207 in comment code 

29.c for discussion of the human health benefit analyses related to mercury exposure). For more 

detailed response on EPA’s estimate of baseline pollutant loadings, see DCN EPA-HQ-OW2009-0819-4487-A1, Excerpt Number 97.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 205
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External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Based on the assumptions and methodology EPA has used to calculate pollutant loads and 

benefits under the regulatory options, Gradient developed the following overall conclusions:

EPA has not sufficiently justified many of the assumptions used to estimate surface water quality 

and the potential effects on human health and the environment. In many cases, the assumptions 

fail to acknowledge uncertainties that EPA has identified in previous reports. The use of 

uncertain assumptions with known limitations makes the benefit/cost analysis an unreliable tool 

for rule-making.

Comment Response: 

EPA disagrees with the commenter that it has not provided sufficient justification for 

assumptions used to estimate the benefits of the ELGs. See response to other comments 

addressing specific assumptions of the benefit analysis for details (e.g., DCN EPA-HQ-OW2009-0819-4487-A1, Excerpt Number 97).

Additionally, the existence of limitations, assumptions, and/or uncertainties does not make any 

given benefit-cost analysis “an unreliable tool for rule-making.” EPA maintains that its analyses 

of the final rule provide well-supported information on the expected benefits of the ELGs. For 

the role of cost-benefit in EPA’s decisions on the final rule, see response to DCN EPA-HQ-OW2009-0819-4464-A1, Excerpt Number Number 3 (in comment code 6.e).

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 206

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Because many of the analyses used to calculate benefits are interconnected, overly conservative 

assumptions in primary analyses (i.e., surface water contaminant modeling) will be propagated 

through the assessment. As a result, the uncertainty is compounded in the final output (i.e., the 

benefit calculation). This manifests as benefits estimates that are over-inflated and overstate the 

effectiveness of the proposed control options.

Uncertainties associated with selected assumptions and the impact of alternative assumptions are 

not quantified. Given the large impact of some of the selected assumptions and its approach to 
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the analysis, EPA should have explored a range of possible results in a sensitivity analysis. For 

example, considering reasonable parameter adjustments for the impoundment failure analysis 

would reduce the estimated benefits by nearly a factor of 2. Because Gradient’s analysis 

indicates that EPA made several assumptions that overestimate risk, it is likely that plausible 

benefits of the various options, or even the basic support for the need for additional regulation, 

could be significantly lower and would be insufficient to support particular regulatory options.

Overall, because of the profound uncertainty in the assessment, the failure to quantify that 

uncertainty, and the substantial potential overestimation of benefits, it is not clear that any of the 

proposed ELG regulatory options will provide a measurable benefit to human health or the 

environment.

Comment Response: 

For the role of cost-benefit in EPA’s decisions on the final rule, see response to DCN EPA-HQOW-2009-0819-4464-A1, Excerpt Number 3 (in comment code 6.e).

EPA estimated benefits using data and methods that provide a reasoned basis for demonstrating 

the benefits of the ELGs, and for comparing the relative benefits achieved under different 

regulatory options. While EPA acknowledges that even the best-available empirical estimation 

methods inherently include some scientific uncertainty, the Agency disagrees with the 

commenter that resulting estimates are “insufficient to support particular regulatory options.”

EPA also disagrees that the Agency has neither documented uncertainty in assessments nor 

quantified that uncertainty where possible, and with the commenter's implication that the Agency 

systematically overestimated risk to the degree that plausible benefits would be significantly 

lower. The record shows the opposite. For example, in estimating willingness to pay for water 

quality improvements (Chapter 4 in BCA) EPA used – and documented—assumptions and 

specifications to minimize the risk of over-stating the benefits. For each benefit associated with 

the final rule, EPA qualitatively discusses the impact of assumptions on all benefit calculations 

and conducts quantitative sensitivity analyses on parameters used in several analyses (see 

Appendices in the BCA).

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A2

Comment Excerpt Number: 9

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

 Because many of the analyses used to calculate benefits are-interconnected, overly 

conservative assumptions in primary analyses (i.e., surface water contaminant modeling) 
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will be propagated through the assessment. As a result, the uncertainty is compounded in 

the final output (i.e., the benefit calculation). This manifests as benefits estimates that are 

over-inflated and overstate the effectiveness of the proposed control options.

 Uncertainties associated with selected assumptions and the impact of alternative 

assumptions are not quantified. Given the large impact of the some of the selected 

assumptions and approach to the analysis, US EPA should have explored a range of 

possible results in a sensitivity analysis. For example, considering reasonable parameter 

adjustments for the impoundment failure analysis would reduce the estimated benefits by 

nearly a factor of 2. Because our analysis indicates that US EPA made several 

assumptions that overestimate risk, it is likely that plausible benefits of the various 

options, or even the basic support for the need for additional regulation, could be 

significantly lower and would be insufficient to support particular regulatory options.

 Overall, because of the profound uncertainty in the assessment, the failure to quantify 

that uncertainty, and the substantial potential overestimation of benefits, it is not clear 

that any of the proposed ELG regulatory options will provide a measurable benefit to 

human health or the environment.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4655, Excerpt Number 206 for the response to 

the general statements about uncertainty.

Regarding the impoundment analysis, EPA does not agree that its analysis has overestimated 

risk, but the commenter does not provide sufficient detail for EPA to respond directly to the 

assertion that “reasonable parameter adjustments” would reduce the benefits by nearly a factor of 

2. The information provided in other parts of their submittal describes the commenter’s concerns 

with specific parameters used in the calculations, noting that uncertainty in individual 

components of the analysis result in EPA overstating benefits by factors ranging from 4 to 10. 

See response to DCN EPA-HQ-OW-2009-0819-4655, Excerpt Number Numbers 38, 41, 190, 

and 230 (Section 29.g) for EPA's more detailed response to concerns about individual 

parameters.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A2

Comment Excerpt Number: 13

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Our analysis indicates that US EPA substantially overstated the magnitude of the expected cost 

reductions associated with the proposed ELG. Additionally, the US EPA does not explain the 
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basis for some aspects of their analysis well enough to be able to trace the development of the 

parameters used in the analysis.

Comment Response: 

The commenter generally claim – without supported this claim with evidence— that EPA has 

substantially overstated expected cost reductions associated with ELG revisions (referring 

specifically to the reduction in cleanup and other costs resulting from impoundment failures).The 

information provided in other parts of their submittal describes the commenter’s concern with 

specific parameters used in the calculations, noting that uncertainty in individual components of 

the analysis result in EPA overstating benefits by factors ranging from 4 to 10. See response to 

DCN EPA-HQ-OW-2009-0819-4655, Excerpt Numbers 38, 41, 190, and 230 (Section 29.g) for 

a more detailed response regarding individual parameters.

EPA responded to the concern that EPA did not explain the analysis well enough in comments 

that address specific assumptions of the cost and benefit analyses (e.g., DCN EPA-HQ-OW2009-0819-4655, Excerpt 205). The BCA for the final rule describes the data, methods, and 

limitations of EPA’s benefit analysis.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 224

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In addition to benefits that were not monetized at all, there are many categories of benefits for 

which EPA likely underestimated the monetary value. The following table, from the Synapse 

report, lists the benefits that, with one exception, were underestimated.707
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EPA has compounded the problem by using conservative, counterfactual assumptions that drive 

up the costs and economic impacts, such as by assuming that 100% of compliance costs will be 

borne by utilities and 0% will be passed on to consumers. Ultimately, EPA's cost-benefit 

analysis compares well-defined but nonetheless overestimated compliance costs with incomplete 

and underestimated benefits. For reasons of coherent and logical policy, this cost-benefit 

analysis should not drive the rule. And for legal reasons, the cost-benefit analysis cannot be a 

factor in deciding the BAT limitations.

707 Id. at 26.

Comment Response: 

EPA acknowledges that some benefits are underestimated due to limitations in available 

methodology, data, or both. In its final rule analyses, the Agency specifically recognizes the 

potential for over-estimated costs and under-estimated benefits, given several potentially 

significant benefits that the Agency cannot quantify and/or monetize. EPA discusses such 

benefits qualitatively in Chapter 2 of the BCA. See response to DCN EPA-HQ-OW-2009-0819-

4686-A1, Excerpt Number 12 (Section 29(j)) for further details. Regarding the role of cost-
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benefit analysis in EPA’s decisions on the final steam electric rule, see response to DCN EPAHQ-OW-2009-0819-4464-A1, Excerpt Number Number 3.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 32

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In addition, EPA underestimated numerous benefits including: reduced risk of impoundment 

failures due to changes in the use of impoundments; reduced mortality from exposure to NOx, 

SO2 and particulate matter and reduced CO2 emissions resulting in avoided climate change 

impacts; improved aquatic and wildlife habitat from improved ambient water quality in receiving 

reaches; enhanced swimming, fishing, boating, and near‐water activities from improved water 

quality; increased aesthetics from improved water clarity, color, odor, including nearby site 

amenities (residing, working, traveling); enhanced existence, option, and bequest values from 

improved ecosystem health; reduced risks to aquatic life from exposure to steam electric 

pollutants; improved threatened and endangered habitat and thus potential increase in threatened 

and endangered population; reduced incidence of cancer due to less exposure to arsenic from fish 

consumption; reduced IQ losses to infants due to less in‐utero mercury exposure from maternal 

fish consumption; reduced IQ losses to children ages 0 to 7 due to less childhood exposure to 

lead from fish consumption; reduced need for specialized education due to less childhood 

exposure to lead from fish consumption; and reduced other adverse health effects (cancer and 

non‐cancer) due to less exposure to other pollutants (arsenic, lead, etc.) from fish consumption.

Comment Response: 

EPA acknowledges that a complete accounting of all the benefits of the ELG is not possible 

given data and methodology limitations. EPA conducted a detailed analysis that uses the best 

information available to provide a reasoned assessment of the benefits of the final rule to support 

policy decisions. The BCA describes EPA’s efforts to accurately estimate and monetize benefits 

and discusses the degree to which uncertainties and limitations (e.g., data limitations, 

methodological limitations, and others) may under- (or over-) state the benefits. For more 

discussion on particular categories of benefits mentioned by the commenter, see responses to 

related comments (e.g., DCN EPA-HQ-OW-2009-0819-4686-A1, Excerpt Number 12 (in 

section 29(j)).
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29.c. Benefits – Human health benefits 

Commenter Name: R. W. Greene

Commenter Affiliation: Mercatus Center at George Mason University

Document Control Number: EPA-HQ-OW-2009-0819-3411-A1

Comment Excerpt Number: 15

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

 More generally, costs are estimated by extrapolation from known data, which is 

questionable because it implies linear relationships when these may not be appropriate, 

but many benefits are simply left not quantified, as in the case of some health benefits.

Comment Response: 

As detailed in the BCA, EPA’s analysis was as comprehensive as possible given the limitations 

of data and methods to quantify and monetize the benefits of the rule. Some benefits are difficult 

or impossible to quantify or monetize given current data and methods, even where these benefits 

are known to be present. EPA analyzed these benefits qualitatively, in accordance with OMB’s 

guidance on regulatory impact analysis for significant rules (see the BCA for details). For 

information on the role of benefits analysis in establishing effluent limitations based on Best 

Available Technology Economically Achievable (“BAT”), see response to DCN EPA-HQ-OW2009-0819-4464-A1, Excerpt Number 3.

Commenter Name: R. W. Greene

Commenter Affiliation: Mercatus Center at George Mason University

Document Control Number: EPA-HQ-OW-2009-0819-3411-A1

Comment Excerpt Number: 22

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Compliance costs are also calculated, but many environmental benefits are either not quantified 

or result, as in the case of estimated health benefits, from inference and assumptions worked 

through complex modeling. Not only would it be difficult for the independent researcher to 

replicate the results, but such an exercise does not give well-grounded estimates; actual benefits 

could easily be higher or lower.

Comment Response: 
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EPA disagrees that the benefit estimates are not well-grounded and difficult to replicate. In 

estimating human health benefits, the Agency relied on thoroughly reviewed scientific and 

epidemiological evidence and the resulting concentration-response functions to estimate avoided 

case of adverse human health impacts. EPA notes that fate and transport and exposure models 

are well-accepted tools for evaluating policy actions and resource management alternatives. To 

estimate the impact of the final rule and estimate changes in stream pollutant concentrations, the 

Agency used water quality and ecological models with well-accepted methods and assumptions 

(e.g., bioaccumulation factors). For more discussion of these models, see the Environmental 

Assessment for the Effluent Limitations Guidelines and Standards for the Steam Electric Power 

Generating Point Source Category (EA Report) (DCN SE04527). Similarly, to estimate 

pollutant exposure, EPA used publicly available data and various methods clearly described in 

the BCA.

EPA also disagrees with the commenter’s assertion that it has not provided sufficient 

documentation. The commenter did not provide specific examples of lacking data or 

methodological descriptions that that would prevent an independent researcher from replicating 

EPA’s analyses. The methodology and data used in the health benefits analyses are documented 

in detail in the Environmental Analysis report (Section 6) and the BCA (Chapter 3). The public 

record includes underlying data and models used to support analyses of human health benefits, to 

the extent possible given the constraints of Confidential Business Information.

For information on the role of benefits analysis in establishing effluent limitations based on Best 

Available Technology Economically Achievable (“BAT”), see response to DCN EPA-HQ-OW2009-0819-4464-A1, Excerpt Number 3.

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 136

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

As a practicing pediatrician, I'm deeply concerned that children are exposed to a greater dose of 

these toxins due to their smaller body weight, their earlier exposure when their organs are still in 

development, and even trace exposures can be devastating to the fetus.

There is a disturbing relationship between these heavy metals and the rising incidence of autism, 

which is now seen in 1 in 50 children. We should all be alarmed. The cost of treating autism is 

estimated at $7.9 billion annually, and this is according to a 2011 report published in Health 

Affairs. I'm also concerned about the correlations between these radionuclides and the rapidly 

rising rate of pediatric cancer, which has an estimated cost of $95 million, according to the same 

study.
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Comment Response: 

EPA shares the commenter’s concerns that infants and children are especially at risk for the 

adverse health effects associated with pollutant exposures, particularly lead and mercury from 

steam electric power plant discharges. The Agency quantified and monetized the neurological 

benefits of reduced mercury and lead exposure to these populations, using IQ as a quantification 

endpoint. This approach captures some neurological impacts to children exposed to lead from 

fish consumption and infants exposed to mercury in-utero, but it does not capture all populations 

exposed to these pollutants (e.g., infants exposed to lead in-utero), nor all impacts from these 

pollutants. For example, many children suffer from cognitive impacts from these pollutants that 

are not measured as IQ, such as acquisition and retention of information presented verbally and 

many motor skills. As such, while IQ is the best available quantification endpoint for the impacts 

of lead and mercury to children and infants, respectively, it may underestimate the benefits of 

reducing exposures to these pollutants.

Although the commenter notes that some research has suggested that children with autism have 

elevated blood lead levels, there is no established concentration-response relationship between 

elevated lead exposure and autism, and EPA therefore did not quantify and monetize reduced 

cases of autism that may result from the regulation.

For similar reasons, EPA did not estimate benefits associated with decreased pediatric cancers 

resulting from decreased radionuclides from this regulation; however, EPA did include children 

in the populations assessed for reduced skin cancer cases from arsenic exposure via fish 

consumption.

For information on the role of benefits analysis in establishing effluent limitations based on Best 

Available Technology Economically Achievable (“BAT”), see response to DCN EPA-HQ-OW2009-0819-4464-A1, Excerpt Number 3.

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 146

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The benefit and cost analysis estimates that the rule will produce hundreds of millions of dollars' 

worth of public health benefits based only on the quantifiable subset of potential health 

benefits. These benefits are large, even without consideration of significant effects from arsenic, 

mercury, lead, and other toxics subject to the ELGs. The rule will also have a number of 

secondary health benefits as well.
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Comment Response: 

EPA agrees that the ELGs will result in significant public health benefits, both from direct 

reduction in pollutant discharges to waters, and from secondary effects on air emissions and 

other pollution sources. The Agency quantified and monetized benefits associated with reduced 

cancer cases from arsenic exposure via fish tissue, reduced neurological effects in infants and 

children from mercury and lead exposure, respectively, and reduced cardiovascular impacts in 

adults from lead and arsenic exposure via fish tissue. The BCA for the final rule provides EPA's 

estimates of the annualized value of human health benefits from the final ELG. As discussed in 

Chapter 7 of the BCA, secondary health benefits arise from reduced air pollutant exposures.

These quantified and monetized benefits represent a fraction of the total public health benefits 

expected from the rule. Section 2.1 in the BCA describes unquantified benefit human health 

benefit categories and discusses potential bias from omitting these categories from the monetized 

value of the final rule benefits.

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 198

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

1.3 million Hispanics nationwide actively participate in fishing as a recreational, social, or family 

activity. However, much of the Latino community is unaware that invisible toxic chemicals such 

as mercury, PCBs, and other toxic substances could be present in the water and the fish that they 

eat.

In a number of studies, it's been shown that Latino sport and commercial anglers catch a variety 

of sport fish and consume fish that they catch more frequently than non Latino consumers.

Comment Response: 

EPA agrees that ethnicity plays a role in fishing habits, fish consumption rates, and behavioral 

changes in response to fish consumption advisories (FCAs). Differences in these factors 

between Latino and other anglers may result in an elevated health risk to recreational anglers 

from the Latino community from exposure to the toxic chemicals in fish tissue under the baseline 

conditions and thus these anglers would derive comparatively greater benefits from the final 

ELG regulation. The final rule analysis describes the regulation’s effects on various demographic 

groups, including information on the minority and low-income populations currently exposed to 
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Steam Electric pollutant discharges. The analysis accounts for demographic differences in 

fishing behaviors where possible given the available data. For more information on this revised 

analysis, see Chapters 3 (human health benefits) and 14 (environmental justice) of the final rule 

BCA.

For more on results of the environmental justice analysis relevant to latino communities, see 

response to DCN EPA-HQ-OW-2009-0819-3920-A1, Excerpt Number 92, and comment EPAHQ-OW-2009-0819-3920-A1, Excerpt Number 127.

Commenter Name: Cathy S. Woollums

Commenter Affiliation: MidAmerican Energy Holdings Company

Document Control Number: EPA-HQ-OW-2009-0819-4495-A1

Comment Excerpt Number: 44

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

 EPA relied on medical studies from the 1990s that estimate a one-point IQ reduction 

from lead exposure reduces expected education years and lifetime earnings.3,4 EPA also 

relied on a study5that estimates an annual education cost of $9,724 for the average 

student. EPA used these studies to estimate the value of the IQ point reduction associated 

with lead exposure while adjusting for the avoided cost of education. However, it is 

apparent that studies used by EPA underestimate the rising cost of education. Data from 

the National Center for Education Statistics reveals that expenditures per student in 

public elementary and secondary schools have increased by 11% from 2003-04 estimates 

to 2008-09, and tuition, room and board for college undergraduates at public institutions 

rose 24% from 2003-04 to 2010-11 after inflation adjustments.6In the past decade, 

college graduates also face a decline in earnings by 19% for men and 16% for women 

after inflation adjustments.7 Studies used by the EPA fail to account for the increasing 

cost of education and declining college graduate earnings resulting in an overestimation 

of the reduced earnings associated with IQ loss after adjustment for the cost of education.

3 Schwartz, 1994.

4 Salkever, 1995.

5 Chambers, 2004.

6 NCES Fast Facts, http://nces.ed.gov/FastFacts/display.asp?id=76. Last accessed July 23, 2013.
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7 Heller, 2013. Higher Education Not What It Used To Be. The Economist. Web version. Last 

accessed July 23, 2013.

Comment Response: 

EPA agrees with the commenter that costs associated with education have generally risen over 

time and that it is appropriate to use more recent data (instead of the U.S. Department of 

Education data from 2004 (updated to 2010$ using the Consumer Price Index for Education), 

EPA used in the proposed rule analysis).

For the final rule analysis, the Agency used data from the National Center for Education 

Statistics, which show that 2010/2011 expenditures for students are approximately $12,600 per 

year in 2012/2013 dollars. EPA did not adjust further for declining income for college graduates, 

since the lifetime average income is based on overall averages for the population, and not 

contingent on college graduation. See Section 3.3 of the final BCA for details.

Commenter Name: Pamela Ritger

Commenter Affiliation: Clean Wisconsin

Document Control Number: EPA-HQ-OW-2009-0819-4632-A1

Comment Excerpt Number: 16

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

the EPA expects that additional health benefits would result from reduced exposure to pollutants 

in steam electric power plant discharges. However, a monetary valuation of these other health 

benefits is not possible due to lack of data on a dose-response relationship between pollutant 

ingestion rate and potential adverse health effects. The EPA did conduct a non-monetized 

analysis, finding that exceedances of pollutants would be reduced through implementation of the 

preferred options. For example, there is currently a baseline of 146 receiving reaches nationwide 

where in-stream concentrations of steam electric pollutants exceed human health criteria or 

MCLs for at least one pollutant. Under Option 3, 3a and 3b, 119 receiving reaches would still 

exceed human health criteria for at least one pollutant, with 27 having all exceedances 

eliminated. Under Option 4a, the number of receiving reaches with pollutant concentrations 

exceeding human health criteria for at least one pollutant would be reduced by 98, with just 48 

receiving reaches that remain with pollutant concentrations that exceed human health criteria for 

at least one pollutant.46 While this analysis demonstrates the impact of implementing Option 4a 

versus the remaining three options, it does not include all possible human health benefits 

associated with post-compliance reductions in pollutant discharges due to lack of data on a doseresponse relationship between ingestion rates and potential adverse health effects. Accordingly, 

as noted in the EPA benefit-cost analysis, “the total quantified human health benefits included in 

this analysis represent only a subset of the potential health benefits expected to result from the 

proposed ELGs.”47 As a final example that the social benefits accruing from health outcomes are 
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likely undercounted in the EPA analysis, EPA did not quantify the benefits associated with 

reduced adult exposure to lead and mercury. The scientific literature suggests that exposure to 

lead and mercury may have significant adverse health effects for adults, but these impacts were 

not quantified. Accordingly, excluding the benefits of reduced adult exposure to these pollutants 

results in an underestimate of benefits.48

46 United States Environmental Protection Agency (U.S. EPA). 2013a. Benefit and Cost Analysis 

for the Proposed Effluent Limitations Guidelines and Standards for the Steam Electric Power 

Generating Point Source Category (40 CFR 423). EPA-821-R-13-004, p. 3-16 to 3-17.

47 Id.

48 United States Environmental Protection Agency (U.S. EPA). 2013a. Benefit and Cost Analysis 

for the Proposed Effluent Limitations Guidelines and Standards for the Steam Electric Power 

Generating Point Source Category (40 CFR 423). EPA-821-R-13-004, p. 3-18.

Comment Response: 

EPA agrees that additional non-monetized benefits may be significant. However, EPA’s ability 

to quantify and monetize categories of human health benefits is constrained by the availability of 

data and methods, such as peer reviewed and accepted concentration-response functions for 

steam electric pollutants. Given these challenges, EPA used methods that provide the best 

possible estimates of the health benefits expected to arise from implementation of the final rule, 

and clearly described uncertainties, limitations, and exclusions in the BCA.

For the final rule, as suggested by this and other commenters, EPA was able to quantify and 

monetize additional health benefit categories such as reduction in cardiovascular disease 

mortality from adult exposure to lead, as described in Section 3.4 of the BCA, and arsenic, as 

described in Section 3.7. Although these additions expand upon EPA’s analysis of human health 

benefits and helps address some of the concern raised by the commenter, total monetized health 

benefits exclude some likely health benefits due to lack of published concentration-response 

relationships for other pollutants (e.g., cadmium) and/or health effects.

For information on the role of benefits analysis in establishing effluent limitations based on Best 

Available Technology Economically Achievable (“BAT”), see response to DCN EPA-HQ-OW2009-0819-4464-A1, Excerpt Number 3.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 203

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

D. Water Quality Impacts to Human Health

EPA’s estimated human health benefits based on improvements to water range from $0.3 million 

for regulatory Option 1 to $1.6 million for Option 5. The benefits to human health from 

improved water quality are likely overestimated for several reasons. First, as described above, 

the human health evaluation relies on many of the same modeling assumptions as the wildlife 

analysis. That is, human health risks are based on assumptions about contaminant fate and 

transport and uptake into fish, which as noted in earlier comments are likely to yield overprediction of exposure. Additionally, because EPA has assumed linearity in the dose response 

function (such that any decrease in exposure will decrease risk), it has overestimated the public 

health benefit of small decreases in contaminant exposures calculated under the different 

regulatory options. In the case of arsenic, EPA has based benefits on arsenic exposures 

reductions that are below natural background levels.

Comment Response: 

First, regarding assumptions used for to estimate contaminant fate and transport and uptake into 

fish, see responses to comments EPA-HQ-OW-2009-0819-4655-A2, Excerpt Number 29 (in 

section 25.g) and EPA-HQ-OW-2009-0819-4655-A2, Excerpt Number 23 (in section 25.f).

For information on the role of benefits analysis in establishing effluent limitations based on Best 

Available Technology Economically Achievable (“BAT”), see response to DCN EPA-HQ-OW2009-0819-4464-A1, Excerpt Number 3.

Second, EPA disagrees that the use of linear concentration-response functions results in an 

overestimate of benefits. The Agency relies on published concentration-response functions that 

were extensively peer reviewed, including reviews by the National Academy of Science and/or 

EPA’s Science Advisory Board. The Agency found no scientific evidence of threshold effects 

associated with the pollutants analyzed (arsenic, lead, mercury) and human health endpoints used 

to estimate the benefits of the final rule.

The Agency recognizes that the impacts of exposure at low doses may not be the same as at high 

doses (i.e., the concentration response may not be linear even if a threshold effect is absent); 

however, this does not necessarily indicate that the impacts at low doses are overestimated in the 

benefits. As noted in the BCA for the final rule (Section 3.3), research has shown that lead 

effects on cognitive abilities are steeper at low doses, meaning that using a simple linear dose 

response function would underestimate the impacts, contrary to the commenter’s concern.

EPA applied a concentration-response function more specific to low doses of pollutant, rather 

than a simple linear concentration-response function for all dose levels to avoid bias. For 

example, in the analysis of lead exposure impacts to children (see Section 3.3 of the BCA), the 

Agency used a concentration-response function that is specific to children with blood lead 

concentrations below 7.5 μg/dL, since the estimated mean blood lead concentration for children 

exposed to lead from fish consumption in the baseline is approximately 2.7 μg/dL. EPA also 
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conducted a sensitivity analysis using a log-linear concentration-response function, as described 

in Appendix F of the BCA.

Regarding benefits from reductions in arsenic concentrations, EPA notes that the benefit 

estimates presented in the BCA (Section 3.6) are in line with low arsenic levels. While EPA 

recognizes that the benefits are small and not significant relative to the total health benefits for 

the final ELGs, the Agency presents these results to be transparent about the magnitude of 

potential health benefits.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 207

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

H. EPA’s Assessment of Benefits from Mercury Reduction Is Flawed

EPA’s assessment of benefits from mercury reduction is flawed as reflected in record support 

documents for the proposed ELG rule. The Agency continues to rely on analysis, assumptions, 

and support materials thoroughly critiqued and never effectively rebutted by EPA in prior 

rulemakings.

Rather than fully restate the extensive critiques and their support here, we identify significant 

examples of (1) flaws in EPA’s mercury health benefits assessment for the proposed ELG rule; 

(2) where EPA made the same questionable assertions in past rulemakings; and (3) where legal 

and technical critiques of the analysis have been set forth without effective resolution.

1. IQ Is a Questionable Basis for Measuring Mercury Reduction Benefits

In support of the proposed ELG rule, EPA assesses benefits from reduced exposure to mercury 

by estimating reduction in IQ losses among children exposed to mercury in-utero as a result of 

maternal consumption of contaminated fish. BCA at 3-11. EPA similarly relied on estimates of 

IQ loss reductions in prior rulemakings, including the CAMR and MATS rules. As further 

detailed in comments on those rulemakings, EPA’s use then and now of IQ loss estimates to 

estimate benefits in reduction of mercury is wholly inappropriate. EPA’s IQ loss-based 

assessment is inappropriate, both in the current and prior rulemakings, for the following reasons:

a. Changes in IQ are not a well-defined health consequence of mercury exposure. See

UARG Comments on the National Emissions Standards for Hazardous Air Pollutants from Coaland Oil-Fired Electric Utility Steam Generating Units, EPA-HQ-OAR-2009-0234 (August 4, 

2011) (UARG 2011 MACT Comments) at 69; EPRI Comments on the National Emissions 
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Standards for Hazardous Air Pollutants from Coal and Oil-Fired Electric Utility Steam 

Generating Units and Standards of Performance for Fossil-Fuel-Fired Electric Utility, IndustrialCommercial-Institutional, and Small Industrial-Commercial-Institutional Steam Generating 

Units (August 4, 2011) (EPRI 2011 MACT Comments) at § 3.12.

b. EPA assumes a dose-response relationship between methylmercury exposure and IQ 

based on a study by Axelrad, et al. (2007) (BCA at 3-12) that was developed for marine fish and 

mammalian species whereas EPA’s risk assessment for the proposed ELG rule (as in the CAMR 

and MACT rulemakings) involves risk exposure from freshwater fish consumption. The effects 

of these exposure differences are unaddressed in the record. Furthermore, the Axelrad, et al. 

study pulled from three primary studies - none of which originally measured full IQ - and 

resulted in a relatively small incremental change not measurable on an individual level that must 

be estimated for a population to derive national levels. EPRI 2011 MACT Comments at § 3.12.

c. EPA relies on valuation models (e.g., Schwarz (1994) and Salkever (1995)) to translate 

IQ loss estimates into reductions in lifetime earnings (BCA at 3-13); however, the national data 

set used to estimate the relationship between IQ and lifetime earnings does not contain a direct 

measure of IQ, but instead relies on scaled adjustments from an armed forces qualification test, 

which results in loss of precision. EPRI 2011 MACT Comments at § 3.13.

d. EPA relies on a highly controversial and overly conservative Agency-developed 

methylmercury RfD value to estimate exposure risks and draw conclusions about IQ-based risk, 

which is inappropriate for the many reasons described below. EPRI 2011 MACT Comments at 

§ 3.11.

In recognition of the significant uncertainties associated with use of IQ loss to assess mercury 

reduction health benefits, a Scientific Advisory Board review panel reviewing the MACT 

rulemaking recommended de-emphasis of such analysis. SAB Letter to EPA regarding Review 

of EPA’s Draft National-Scale Mercury Risk Assessment (Sept. 29, 2011) at 2. Despite the 

associated uncertainties and the SAB’s recommendation of its de-emphasis, EPA continues to 

rely on IQ loss to assess mercury reduction health benefits. This is wholly inappropriate.

Comment Response: 

Any comments related to rules other than the steam electric ELG are outside the scope of this 

rulemaking and comment response document. For information on the role of benefits analysis in 

establishing effluent limitations based on Best Available Technology Economically Achievable 

(“BAT”), see response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3.

EPA disagrees that reliance on IQ loss to assess mercury reduction health benefits is 

inappropriate. The commenter makes several points, which the Agency addresses below:

First, the commenter asserts that changes in IQ are not a well-defined health consequence of 

mercury exposure. EPA disagrees. Several epidemiological studies have demonstrated the 

relationship between exposure to mercury in-utero and IQ, including the examples provided in 
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the next paragraph which provide the functional form of the relationship between mercury 

exposure and IQ effects.

Second, the commenter takes issue with the particular function used to relate exposure and IQ. 

As documented in the BCA, to estimate impacts of mercury exposures to IQ, EPA applied a 

concentration-response function from Axelrad and others (2007), which drew on data from three 

large-scale epidemiological studies (in New Zealand, the Faroe Islands, and the Seychelle 

Islands). The National Research Center (NRC) has described the studies as being “well designed 

and carefully conducted, and each examined prenatal MeHg exposures within the range of the 

general U.S. population exposures” (from the 2000 report Toxicological Effects of 

Methylmercury). EPA has no evidence of differences in health outcomes resulting from 

methylmercury exposure via consumption of marine fish and freshwater fish.

Additionally, while the SAB Letter to EPA regarding review of EPA’s Draft National-Scale 

Mercury Risk Assessment (September 29, 2011) expresses concern over the use of IQ as the 

indicator of neurobehavioral effects as noted by the commenter, this concern is based on the fact 

that SAB considers IQ to be an insensitive indicator of the effects and as such may result in an 

underestimate of benefits. SAB recommended that EPA explore additional endpoints, but did not 

recommend eliminating the use of IQ endpoints altogether. Further, as noted by the SAB, there is 

no substitute for IQ that can be quantitatively estimated with a “reasonable degree of confidence” 

(see page 7 of the report accompanying the SAB letter, Review of EPA’s Draft National-Scale 

Mercury Risk Assessment).

Third, the commenter raises concerns about the approach used to estimate the monetized value of 

avoided IQ decrement. As noted by the commenter, EPA used estimates from Schwartz (1994) 

and Salkever (1995) of the change in lifetime earnings resulting from a one-point change in IQ. 

EPA disagrees with the commenter that the use of these studies results in a loss of precision. In 

fact, Salkever (1995) addresses the translation issue directly in the study. As noted in Salkever 

(1995), the Armed Forces Qualifying Test (AFQT) is the underlying test of cognitive abilities in 

the studies, which has been used in a wide variety of studies in sociological, psychological, and 

neurological fields. In the studies used by Schwartz (1994) and Salkever (1995), the AFQT score 

is converted to IQ units by assigning a score to each percentile AFQT based on a normal 

distribution with a mean of 100 and a standard deviation of 15. Since this translation of AFQT 

scores onto an IQ scale is a linear transformation, it does not influence the results (see Salkever 

(1995), page 3).

Finally, the commenter states that EPA “relies on a highly controversial and overly conservative 

Agency-developed methylmercury RfD value to estimate exposure risks and draw conclusions 

about IQ-based risk.” EPA does not use a methylmercury RfD value to estimate exposure risks, 

nor to draw conclusions about IQ-based risks. Instead, EPA quantified IQ-based risks to the 

exposed population based on an established concentration-response function, as described above 

and in the BCA.
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Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 209

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

3. Lack of Record Transparency

As highlighted by SAB Peer Review of prior EPA assessment of health benefits from mercury 

reduction, documentation of such analysis is “deficient” where lacking “transparency in 

describing key analytical methods and findings” (SAB Letter at 2) and the “integrity” of a “risk 

assessment” is “dependent in part on a transparent description of the analysis ...” (Id. at 

1). Lack of transparency remains a substantial issue in assessing the proposed ELG rule mercury 

reduction health benefits analysis approach, specifically, and throughout the proposed ELG rule 

record support documents, more generally.

Having quantified expected benefits from mercury reduction generally, EPA then estimates 

benefits expected in conjunction with the proposed ELG rule specifically. EPA’s analysis of 

mercury reductions expected from the proposed ELG rule, is lacking in transparency. This is in 

great part due to minimal, missing, and disjointed details on the record regarding pollutant 

impacts modeling and associated assumptions and data inputs.

This lack of transparency undermines the integrity of the mercury reduction estimate and, in turn, 

associated benefits analysis and EPA’s record support for the proposed ELG rule as a whole.

Comment Response: 

EPA disagrees that the final rulemaking record for the steam electric ELGs lacks transparency.

The methodology and data used in the environmental assessment and health benefits analyses are 

detailed in Section 6 of the Environmental Assessment for the Effluent Limitations Guidelines 

and Standards for the Steam Electric Power Generating Point Source Category (EA Report) 

(DCN SE04527) and Chapter 3 of the BCA, respectively. Given that the commenter did not 

identify specific items missing from the public record, EPA is unable to provide a more focused 

response to direct the commenter to the particular documents where to find certain items.

EPA notes that the SAB Peer Review letter cited by the commenter refers to a different benefit 

cost analysis, not the analysis EPA conducted for this particular rulemaking.

For information on the role of benefits analysis in establishing effluent limitations based on Best 

Available Technology Economically Achievable (“BAT”), see response to DCN EPA-HQ-OW2009-0819-4464-A1, Excerpt Number 3
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Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 231

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In addition to Gradient’s analysis, UWAG has looked independently at aspects of EPA’s 

Environmental Assessment that EPA offered in rulemakings under the Clean Air Act, 

particularly the Clean Air Mercury Rule (CAMR) (now vacated) and then the MATS Rule. In 

assessing the environmental and human health effects of mercury for those rulemakings, EPA 

used assumptions and methods that were challenged in comments by the Utility Air Act Group 

and others. EPA should have reconsidered those assumptions and methods for this ELG 

rulemaking but apparently has not. Accordingly, we summarize here, again, the flaws in EPA’s 

approach to calculating the effects of mercury in the environment.

Comment Response: 

For responses to similar comments about the Agency’s methods for the final steam electric 

ELGd, see responses to comment EPA-HQ-OW-2009-0819-4655, Excerpt Numbers 207 and 

209.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A2

Comment Excerpt Number: 35

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In addition to overestimated exposure, US EPA has made the assumption that the dose response 

function for the three contaminants evaluated in the benefits analysis—arsenic, lead, and 

mercury—is linear. This means that any reduction in exposure, however small, will confer a 

health benefit, even in cases where the baseline exposure was not associated with a contaminant 

level of public health significance. The overestimates of benefits associated with lead and 

arsenic, as examples, are discussed in more detail below. The specific modeling approaches used 

were described by US EPA (2013c, Appendix E).

4.1 Lead
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US EPA estimated benefits to pre-school children (age 0 to 7) from reduced lead exposure via 

consumption of contaminated fish. To perform the benefit analysis, US EPA modeled blood lead 

(PbB) concentrations under the baseline and post-compliance scenarios, and then used a dose 

response relationship between PbB and IQ loss to estimate avoided IQ losses in the affected 

population of children, and reduced incidences of IQ scores less than 70. US EPA then 

calculated the monetary value of benefits to children based on the impact of an additional IQ 

point on an individual's future earnings, and the cost of compensatory education for children with 

learning disabilities (including children with PbB above 20 g/dL and IQ less than 70).

US EPA estimated the annual benefits from avoided IQ losses for children ages 0 to 7 (Table 3-

4). For a 3% discount rate, the benefits ranged from $0.06 to $7.94 million, depending on the 

control option. For a 7% discount rate, the benefits ranged from $0.01 to $0.08 million, 

depending on the control option. These results demonstrate that the benefits from avoided IQ 

losses are very small, particularly when compared with the estimated annualized benefits from 

reduced air emissions, which were $127.6 and $170.5 million for Options 3 and 4, respectively, 

at a 3% discount rate (Table 8-8).

US EPA assumed that 20 percent of children with PbB above 20 μg/dL would have IQs less than 

70 and require compensatory education. We note that it is highly improbable that any child 

would have a PbB above 20 μg/dL due to fish consumption under any of the modeled scenarios, 

and even less probable that they would also have an IQ less than 70. For example, using US 

EPA's estimated mean PbB of 2.7 μg/dL3under the baseline scenario, and the default IEUBK 

model GSD of 1.6, the probability of a child having a PbB above 20 μg/dL is only 0.001%, and 

20% of this value is 0.0002%. US EPA's estimated annual benefits for avoided compensatory 

education range from $0 to $0.07 million, depending on the scenario and discount rate (Table 3-

5). These results demonstrate that the benefits from reduced compensatory education are very 

small, particularly when compared with the estimated benefits from reduced air emissions, as 

noted above.

3 This value was assumed to be a geometric mean.

Comment Response: 

EPA disagrees that the use of linear dose response functions results in an overestimate of 

benefits. First, the Agency relies on published concentration-response functions that were 

extensively peer reviewed, including reviews by the National Academy of Science and /or EPA’s 

Science Advisory Board. The Agency found no scientific evidence of threshold effects 

associated with the pollutants analyzed (arsenic, lead, mercury) and human health endpoints used 

to estimate the benefits of the ELGs.

The Agency agrees that the impacts of exposure at low doses may differ from those at high doses 

(i.e., the dose response may not be linear even if a threshold effect is absent), but this does not 

necessarily indicate that the impacts at low doses are overestimated in the benefits. In fact, as 

noted in the BCA (Section 3.3), research has shown that lead effects on cognitive abilities are 
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steeper at low doses, meaning that the use of a simple linear dose response function would result 

in an underestimate of impacts, contrary to the commenter’s concern. When warranted, EPA 

applied a concentration response function appropriate for low level exposure (e.g., lead), rather 

than a simple linear dose response function for all dose levels to avoid bias.

EPA agrees with the commenter that the estimated annual benefits associated with reduced 

childhood exposure to lead via fish consumption are small compared with the estimated benefits 

of reduced air pollutant emissions. This finding is not surprising given differences in the 

geographic scope of the exposed populations for the two regulations the commenter compares. 

This was also particularly true of the proposed rule analysis which considered exposure only for 

immediate reaches receiving steam electric power plant discharges. The final rule analysis 

considers exposure in both immediate and downstream reaches, but this is still a subset of all 

reaches that may be affected by air deposition. EPA further notes that health benefits to children 

ages 0 to 7 from reduced lead exposure, although they may seem low at the national level and are 

small relative to other benefits of the ELG, are significant for the communities residing in the 

vicinity of the affected reaches. EPA estimated that the final rule will improve water quality by 

reducing lead concentrations in approximately 28,000 stream miles and will result in annualized 

benefits to children of approximately $0.8 million to $1.1 million, using a 3 percent discount rate 

($0.1 to $0.2 million using a 7 percent discount rate). See Section 3.3 of the BCA for detail.

For information on the role of benefits analysis in establishing effluent limitations based on Best 

Available Technology Economically Achievable (“BAT”), see response to DCN EPA-HQ-OW2009-0819-4464-A1, Excerpt Number 3.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A2

Comment Excerpt Number: 36

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

US EPA's benefit analysis used a linear dose-response relationship between PbB and IQ of -2.94 

IQ points per μg/dL for children with PbB concentrations below 7.5 g/dL, based on a study by 

Lanphear et al. (2005). US EPA should consider a range of values for the dose response 

relationship (as was done for the Lead NAAQS), rather than relying on one value from one 

study. In the Lead NAAQS Final Rule (US EPA, 2008b, pg. 66978), US EPA discussed the 

slope of -2.94 from Lanphear et al. (2005), but also included the slope of -1.71 for the subset of 

24-month old children in a Mexico City cohort with PbB levels < 5 μg/dL (n = 193), for which 

the mean concurrent PbB was 2.9 μg/dL (Tellez-Rojo et al. 2006, 2008, as cited in US EPA, 

2008b). US EPA also included two slopes derived from a loglinear function with low-exposure 

linearization (LLL) in the Lanphear et al. (2005) study: -2.29 at 2 μg/dL, and -1.89 at

3 μg/dL. US EPA noted that for PbB up to approximately 3.7 μg/dL, they placed the "greatest 
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confidence" in the slopes derived from the LLL function, and that these slopes lie intermediate 

between the other two values [-1.71 and -2.94] (US EPA, 2008b). Thus, US EPA's own risk 

assessment done in support of the revised Lead NAAQS used an IQ/PbB slope less than -2.94, 

and if a lower slope had been used here, the derived benefits would be even lower than those 

estimated in Table 3-4 of the benefits analysis.

Finally, another key issue related to the effects of lead on IQ is that, while a modest association 

with low- level lead exposure may be measurable in population-based studies, these effects 

would not be measurable and would be unlikely to be of any clinical significance in an individual 

(i.e., the reduced lead exposure would not provide any meaningful health benefit in an 

individual). The decrease in predicted PbB was not explicitly presented in the cost benefit 

analysis, but under most scenarios the decrease was presumably very small given the modest 

associated benefit. Thus, the small associated increase in IQ is unlikely to manifest in any 

meaningful way on an individual child's intellectual ability. The available studies of low-level 

lead exposures rarely address this issue. This limitation, however, has been acknowledged by 

CDC, the agency charged with developing childhood lead intervention programs. In particular, 

the report issued by the CDC advisory committee expressed its concerns with low-level lead 

exposures in the context of "the public health impact," rather than in the context of impacts on 

individuals (CDC, 2012).

4.2 Arsenic

Similar to lead, US EPA estimated the annual benefits from avoided cancer cases from arsenic 

exposure via fish ingestion. The number of avoided cancer cases (and the monetized) benefit was 

smaller than for lead. For a 3% discount rate, the benefits ranged from 0 to $0.2 million, 

depending on the option, while the benefits using a 7% discount rate ranged from 0 to $0.01 to 

$0.08.

Although these benefits are relatively small, they are likely overestimated because the reduction 

in cancer cases is predicated on a low-dose linear dose-response relationship for arsenic. The 

assumption of linearity in the human health benefits analysis, i.e., that any decrease in exposure 

will confer a health benefit is particularly problematic for arsenic because the proposed ELG rule 

has quantified human health benefits from arsenic reductions that are below background. For 

example in the EA, US EPA estimated baseline levels in the "immediate receiving water" that 

are significantly lower than background levels across the (US EPA, 2013c). Specifically, in the 

EA, US EPA has calculated the 50th percentile baseline arsenic concentration of 1.72E-05 mg/L 

(0.017 μg/L) (Table F-2); while a US survey (conducted by the US EPA) demonstrates that US 

surface water bodies have a geometric mean of 0.19 μg/L (US EPA, 2001b). Thus, under the 

regulatory options the estimated benefits are contingent on removing arsenic below background 

levels.

Moreover, the EA document states that "EPA used the benchmark value for evaluating cancer 

risk of one in 1,000,000 people. Therefore, a calculated LECR [lifetime excess cancer risk] 

greater than 1 × 10-6 indicates carcinogenic human health impacts from the consumption of fish 

exposed to discharges of evaluated waste streams" (US EPA, 2013c). Using a benchmark of 1 x 

10-6 for arsenic is not supportable. Background risk to arsenic from food, water, and soil are 
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estimated to be 1.1 × 10-4 at 50th percentile exposures and 3.4 × 10-4 at the 95th percentile 

(Petito Boyce et al., 2008). While US EPA does not present the actual risk values for baseline 

and each regulatory option, presumably the risks are small, since the most significant benefit 

(under Option 5), resulted in a reduction of total cancer cases of 0.7 over a 25 year period (for a 

population of 137,467). This small decrease in cancer cases would be associated with a very 

small cancer risk, below the level that is typically observed for individuals across the US.

Finally, the assumption that arsenic dose-response in linear at low doses is not well supported 

(and is being actively debated) (Petito Boyce et al., 2008; Cohen et al., In press). 

Epidemiological studies, overall, are consistent that measurable effects are observed only at 

drinking water concentrations above 100 μg/L (i.e., doses above 0.003 mg/kg-d

4

) (Cohen et al., 

In press). A nonlinear dose-response for arsenic is also supported by animal and in vitro studies. 

Based on the available evidence, there simply is no credible scientific support that small 

decreases in arsenic exposures (as those calculated from reduced fish consumption under the 

various ELG options5) would reduce cancer risk.

4 Assumes a 55-kg individual drinks 2 L water/day.

5 The arsenic doses associated with fish ingestion are not presented in the ELG, but based on the 

calculated cancer risks, the doses (mg/kg-d) can be assumed to be on the 10-6 order of 

magnitude.

Comment Response: 

For information on the role of benefits analysis in establishing effluent limitations based on Best 

Available Technology Economically Achievable (“BAT”), see response to DCN EPA-HQ-OW2009-0819-4464-A1, Excerpt Number 3 (in comment code 6.e).

The commenter requests that EPA “consider a range of values for dose response relationship... 

rather than relying on one value from one study.” EPA notes that the Lanphear et al. (2005) 

study the Agency used is a pooled analysis that included seven prospective studies initiated prior 

to 1995 and included 1,333 children where complete data on confounding factors were available. 

The pooled analysis by Lanphear et al. (2005) is the best study available for estimating the IQ 

loss associated with elevated blood lead levels because it evaluated the relationship between 

elevated blood lead levels and IQ loss across a much larger population, several countries, various 

patterns of lead exposure, and a wider range of socioeconomic conditions compared to any other 

study.

The commenter cites another study, Tellez-Rojo et al. (2006, 2008); however that study looked 

at a single age cohort in a small geographic area. Lanphear et al. (2005) study is a superior study 

because of its broader scope in populations and lead exposure.

The commenter notes that in the lead National Ambient Air Quality Standards (NAAQS) 

analysis, EPA “also included two slopes derived from a loglinear function with low-exposure 

linearization (LLL) in the Lanphear et al. (2005) study: -2.29 at 2 μg/dL, and -1.89 at 3 μg/dL. 
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US EPA noted that for PbB up to approximately 3.7 μg/dL, they placed the "greatest confidence" 

in the slopes derived from the LLL function.” For the final steam electric ELG rule, EPA has 

conducted an additional sensitivity analysis applying a log-linear concentration response function 

that was also used in the NAAQS analysis. This sensitivity analysis is discussed in Appendix F 

of the BCA.

EPA agrees with the commenter that lead-related IQ impacts may generally be clinically 

insignificant at the individual level; however, population-level impacts are the appropriate unit of 

analysis for such benefits. As such, any lack of clinically significant impacts to a single 

individual from the ELGs does not undermine benefits calculated.

Regarding the commenter’s concern regarding modeled arsenic concentrations, EPA agrees that 

in some instances, the IRW model (which does not account for arsenic contributions from nonsteam-electric point sources or background concentrations) calculated arsenic concentrations in 

the water column that are less than background levels. However, some steam electric power plant 

discharges result in arsenic concentrations up to 10,000 times greater than the geometric mean 

provided by the commenter. EPA disagrees that “the estimated benefits are contingent on 

removing arsenic below background levels.” For the final rule, EPA based the arsenic human 

health benefits on reduced arsenic concentrations in receiving waters as calculated by the RSEI 

model (which does account for non-steam-electric point sources) which are then used to 

calculate reduced arsenic intake via fish consumption. Under baseline conditions, the RSEI 

modeling results indicate an average total arsenic concentration of 17.7 μg/L [DCN SE04588] in 

the modeled stream reaches downstream from steam electric power plant discharges, which is 

nearly ten times greater than the geometric mean background concentration provided by the 

commenter. The benefits are derived from steam electric power plants meeting the final ELGs 

and reducing arsenic concentrations in receiving waters to below these modeled baseline 

concentrations. This does not require “removing arsenic levels to below background levels.”

EPA disagrees that “(u)sing a benchmark of 1 x 10-6for arsenic is not supportable.” The 

commenter notes that background cancer risk from arsenic exposure could be higher than this 

threshold. EPA used this cancer risk threshold in the IRW model to indicate whether arsenic 

loadings from steam electric power plants alone are significant enough to cause elevated cancer 

risk due to fish consumption. Because the IRW model does not account for background pollutant 

concentrations, a modeled exceedance of this cancer risk threshold (and avoided exceedances 

under the final rule) would be solely attributable to arsenic loadings from the steam electric 

power plant and is calculated independently from any background sources of arsenic. Additional 

sources of arsenic in the receiving water could result in a greater cancer risk than calculated by 

the IRW model.

The selected threshold is within the range of cancer risk thresholds employed by EPA for various 

analyses (from 1 x 10-6to 1 x 10-4), and EPA selected this threshold to be most protective of 

carcinogenicity and to assess the potential effects on human health. EPA notes that the use of this 

cancer risk threshold in the EA does not influence the calculation of human health benefits, 

which are based on an estimate of the number of cancer cases under baseline and the avoided 

cancer cases under the final rule.
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The commenter noted that the assumption that the arsenic concentration-response function is 

linear at low doses is being debated. EPA acknowledges that the effects of low-dose exposure to 

arsenic is an active area of research (see overview in Schmidt, 2014). Some researchers present 

evidence for a threshold at levels below 100 μg/L in drinking water (Cohen et al. 2013) and 

recent studies have linked low-doses of arsenic in humans with diabetes (Navas-Acien et al., 

2008), cardiovascular disease (Moon et al., 2013), immunotoxicity (Dangleben et al., 2013), and 

cancer (Gilbert-Diamond et al, 2013; Garcia-Esquinez et al., 2013; Mostafa et al., 2013).

EPA is currently revising its inorganic arsenic assessment (both cancer and non-cancer) with 

guidance from National Research Council and expects to complete this effort in 2016. The 

Agency has regularly treated carcinogens assuming low-dose linearity and used this assumption 

in the final rule analysis. Further, while NRC (2013) recommended that EPA consider lung 

cancer, bladder cancer, ischemic heart disease, and skin lesions in the assessment, EPA only had 

sufficient evidence to include benefits from reductions in skin cancer in the quantified benefits of 

the ELG and relied on the existing cancer slope factor for skin cancer only. The omission of 

other cancer and non-cancer effects results in an underestimate of the health benefit associated 

with reduced arsenic exposure via fish consumption.

EPA disagrees that the record “does not present the actual risk values for baseline and each 

regulatory option.” The databases with calculated risk values for each modeled immediate 

receiving water are listed in DCN SE04452, which is included in the confidential record.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 41

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Reduced incidence of cancer due to less exposure to arsenic from fish consumption; reduced IQ 

losses to infants due to less in‐utero mercury exposure from maternal fish consumption; reduced 

IQ losses to children ages 0 to 7 due to less childhood exposure to lead from fish consumption; 

reduced need for specialized education due to less childhood exposure to lead from fish 

consumption; and reduced other adverse health effects (cancer and non‐cancer) due to less 

exposure to other pollutants (arsenic, lead, etc.) from fish consumption: The proposed ELGs are 

expected to reduce the number incidences of cancer from consumption of fish containing arsenic. 

EPA first determines how many fewer people will be exposed to arsenic, and from this values 

the benefits of reduced cancers. EPA fails, however, to value risks to recreational anglers and 

subsistence fishers downstream of receiving reaches: “By omitting downstream effects, this 

analysis potentially understates baseline risks that could be reduced by the proposed ELGs, and 

therefore underestimates the benefits.”88 A cancer slope factor—taken from toxicology studies—
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is then applied this underestimated exposure rate. A cancer slope factor is the number of cases of 

cancer expected based on a population’s exposure to a given carcinogen.

EPA uses an arsenic cancer slope factor that is significantly smaller than the value that it has 

proposed as an updated arsenic cancer slope factor. As the benefit‐cost analysis for the proposed 

steam electric ELGs explains, “EPA is currently revising its cancer assessment of arsenic to 

reflect new data on internal cancers. It is possible that the revised combined (lung and bladder 

cancer) [cancer slope factor] would be higher (draft value is 25.7 per mg/kgBW/day), 

suggesting that the use of the current [1.5 cases per mg/kgBW/day] value may result in an 

underestimate of benefits.”89 Inclusion of downstream reaches and more up‐to‐date cancer 

parameters would dramatically increase the expected reduction in cancer cases from lower 

exposure to arsenic from fish consumption, and would increase the total monetized benefit of the 

regulatory options. The new, draft, value for the cancer slop factor is over 17 times higher 

than the slope factor currently used by EPA. Had EPA used the updated value (albeit a draft 

value) they would have calculated 17 avoided cancer cases for every one cancer case currently 

reported as avoided. That multiplier would carry over through the rest of EPA’s calculation and 

would result in value of reduced cancer cases 17 times higher than the currently reported value.

For mercury‐ and lead‐related benefits, EPA used IQ losses as the measured effect, or 

“endpoint,” for quantifying adverse resulting from childhood or in‐utero exposure to these 

toxins. EPA points out that:

IQ may not be the most sensitive endpoint. Additionally, there are deficits in cognitive abilities 

that are not reflected in IQ scores, including acquisition and retention of information presented 

verbally and many motor skills. To the extent that these impacts create disadvantages for 

children exposed to mercury at current exposure levels or result in the absence of (or 

independent from) measurable IQ losses, this analysis may underestimate the benefits of the 

proposed ELG of reduced lead and mercury exposure.90

EPA’s assumptions result in an undervaluation of the benefits associated with (1) reduced IQ 

losses to infants from reduced in‐utero mercury exposure from maternal fish consumption, (2) 

reduced IQ losses to children ages 0 to 7 from reduced childhood exposure to lead from fish 

consumption, and (3) reduced need for specialized education from reduced childhood exposure 

to lead from fish consumption. Using a more holistic method, beyond IQ point loss, would result 

in an increase in benefits associated with childhood development. (Below we discuss additional 

concerns with EPA’s methodology for monetizing IQ losses avoided by the proposed ELGs.)

88 Benefit-Cost Analysis, p.3-17, Table 3-9.

89 Benefit‐Cost Analysis, p.3‐17, Table 3‐9. Mg/kg /day is milligrams of toxin per kilogram of 

body weight per day exposed.

This means that 1.5 cases of cancer are observed for every milligram of arsenic per kilogram of 

body weight per day exposed.
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90 Benefit‐Cost Analysis, p.3‐17, Table 3‐9.

88 Benefit‐Cost Analysis, p.3‐17, Table 3‐9.

Comment Response: 

EPA agrees that excluding downstream populations and using a cancer slope factor that may not 

reflect the total cancer risks associated with arsenic exposure via contaminated fish consumption 

likely results in an underestimate of the health benefits. In response, EPA revised its analysis to 

include downstream reaches in the analysis of human health benefits for the final rule. See 

Chapter 3 of the BCA for detail.

Regarding the CSF, EPA used the CSF that has been published in the Integrated Risk 

Information System (IRIS) and reflects incidences of skin cancer cases resulting from arsenic 

exposure via ingestion (1.5 cases per mg/kg BW/day). As mentioned by the commenter, EPA is 

currently revising its cancer assessment of arsenic to reflect new data on internal cancers (lung 

and bladder) that have also been associated with arsenic exposure. Because EPA has not 

finalized the revisions to the CSF for use in risk analyses, the Agency decided to continue using 

the existing CSF for ingestion in its benefit analysis of the final ELG.

EPA also agrees that using only IQ to quantify and monetize the benefits associated with reduced 

children’s and infants’ exposure lead and mercury likely results in an underestimate benefits 

from improved neurological functions in children, as described in Section 3.10 of the BCA for 

the final rule. As noted in the comment, IQ may not be the most sensitive health endpoint, and it 

does not capture impacts to other cognitive abilities such as acquisition and retention of 

information presented verbally and many motor skills. However, available concentration 

response functions limit the range of impacts that may be quantified and monetized. EPA used 

the best data and methods available to estimate the benefits of the final rule.

For information on the role of benefits analysis in establishing effluent limitations based on Best 

Available Technology Economically Achievable (“BAT”), see response to DCN EPA-HQ-OW2009-0819-4464-A1, Excerpt Number 3.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 44

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Use of (diverging state) income in valuing human life
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In one section of the proposed steam electric ELGs benefits analysis, EPA suggests, with 

little explanation, the ethically troubling and politically controversial notion that the lives of 

richer people are worth more than the lives of their fellow citizens with lower incomes. This 

judgment is never stated explicitly, but is implied by the following technical paragraph from the 

benefit‐cost analysis (sentences in the quoted paragraph are separated here to facilitate 

discussion):

The value of cancer risk reduction is a “normal good,” and thus is expected to grow over time as 

real income grows.

EPA used historic state‐specific median household income data ... for the years 1984 to 2009, 

and applied a stepwise autoregressive forecasting method to estimate future annual state level 

median household income through 2040.

For each year in the analysis, EPA adjusted the VSL to account for income growth projections 

and the mid‐range income elasticity assumptions...94

VSL is an abbreviation for “value of a statistical life,” a standard monetization of the benefits of 

avoided premature deaths; it is the basis for the valuation of cancer risk reduction in the proposed 

steam electric ELGs. A “normal good,” in economics, is one for which the demand grows as 

income rises. Thus the first quoted sentence asserts that the value of lives saved by cancer risk 

reduction is expected to grow as the income of the general population grows.

Earlier on the same page, EPA notes that the current default VSL is $8.0 million (in 2010 

dollars) per life saved; that value is typically applied to people throughout the country, 

independent of income.95 In order to apply it to future cancer risk reduction, however, EPA felt it 

necessary to calculate state median incomes; the second sentence quoted above describes a 

statistical procedure EPA used to forecast state median incomes through 2040.

It is unclear, from the limited explanation provided by EPA in the documentation to the 

proposed steam electric ELGs, which of two procedures was then followed. On the one hand, 

EPA could merely be engaging in an unusually complex method of projecting the national 

average growth of incomes, and hence the growth of the national VSL; indeed, through personal 

correspondence with EPA and its consultants, we were assured that this first explanation 

accurately describes the use of median income in the proposed steam electric ELGs.96 On the 

other hand, EPA’s methodology as described in the Benefit‐Cost Analysis could easily be 

interpreted as projecting state‐specific values of the VSL, based on future interstate differences 

in income. Under the former interpretation, there are no new problems raised here, other than the 

use of a nonstandard and needlessly circuitous method of forecasting the growth of national 

average incomes. Under the latter interpretation, however, EPA would be breaking new ground 

in a disturbing direction.

The third sentence quoted above could be read—and introduced as precedent into future 

rulemakings—as saying that EPA adjusted the VSL for future years based on state income 

growth. While presumably starting at a single national value for the recent past, the value of life 

would then diverge along with state income growth rates in the future. The “mid‐range income 
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elasticity assumptions,” referred to at the end of the quote, determine the pace at which the value 

of life changes with income. EPA’s assumption of an elasticity of 0.4 (in footnote 27, on the 

same page of the benefits analysis) means that every 1 percent increase in income is associated 

with a 0.4 percent increase in the value of human life.

In the absence of EPA’s (unpublished) state median income projections, it would not be possible 

to determine exactly how unequal the projected values of lives would become by 2040. From 

1984 to 2009, the average annual growth in real median household income ranged from 1.1 

percent in the District of Columbia to ‐0.3 percent in Kansas.97 If these growth rates continued 

for another 30 years, from 2010 through 2040, and EPA’s elasticity assumption applied to 

income growth by state, then by 2040, a human life would be worth 18 percent more in DC than 

in Kansas.98 In short, this unconventional method would assign higher values to some future 

human lives than to others. It appears that this usage is not intended by EPA, but the ambiguous 

language in the Benefit‐Cost Analysis nonetheless opens the door to future uses of differentiated 

incomes in VSL calculations.

The application of income elasticity to VSL estimation is unorthodox and, if its use took place in 

a less obscure EPA publication, would almost certainly be controversial. In addition, this 

departure from the EPA’s more traditional monetization procedures raises a question regarding 

the use of income‐ dependent VSLs in other analyses: If the “income elasticity assumption” is 

applicable to the future growth of income, does it apply to base‐year differences in income as 

well? There is no obvious logical difference between past and future income inequality, when it 

comes to valuing human lives. In 2011 the richest state, Maryland, had median household 

income 1.9 times as large as the poorest state, Mississippi.99 Under EPA’s assumption that 

avoiding death from carcinogenic pollutants is a “normal good” whose value is higher at higher 

income levels, one could argue that life is worth 30 percent more today in Maryland than in 

Mississippi.100

This approach to benefit‐cost analysis, extended more broadly, could lend support to numerous 

morally repugnant conclusions: It would, for example, reliably demonstrate the greater 

monetized benefit of protecting human health in richer communities, seemingly providing 

“objective” economic grounds for concentrating hazardous facilities in poor neighborhoods. 

Valuing human lives based on their income is at variance with a legal system premised on equal 

protection for all and clashes with widely held ethical, philosophical, and religious beliefs that 

assign an equal worth to every human being.

As noted above, it seems that EPA did not intend to introduce state‐specific VSL calculations.

For the reasons explained here, we hope that the ambiguity in EPA methodological description is 

resolved and EPA’s position on using different VSLs for different populations made clear.

Valuing children’s IQ loss: Is lower educational expenditure a benefit of pollution?

To monetize reductions in childhood ingestion of lead, EPA estimates the economic losses that 

result from lower IQs, a well‐documented consequence of lead exposure.101 The principal 

economic effect of a lower IQ is a reduction in the present value of lifetime earnings (since, on 
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average, people with higher IQs have higher incomes). Depending primarily on the chosen 

discount rate, EPA estimates that incomes are $2,429 to $14,631 lower for each lost IQ point.

EPA then reduces this income loss to take account of an offsetting factor: Students with lower 

IQs spend fewer years in school, reducing society’s educational costs. This calculation is 

troubling in at least three respects: It raises philosophical questions about the treatment of 

reduced education as a benefit; it miscalculates the true marginal cost of reduced education; and 

it entirely omits discounting of these changes in costs, which often occur more than a decade 

after exposure.

If lead poisoning results in children leaving school at a younger age, is the reduced cost of 

education a benefit to society, or a measure of what has been lost through environmental harm to 

the next generation? EPA’s numerical tally of reduced school costs opts for the former answer: 

the less schooling, the more society saves. This is numerically accurate in a short‐run, tunnel 

vision of the bottom line, but substantively absurd in a broader, long‐run view of social value, 

responsibility to the nation’s children, and the human and economic benefits of education. 

Viewing these lost years of education instead as a loss to society would increase the monetized 

benefits of the lead poisoning avoided by implementing more stringent ELGs.

Setting aside such broad framing questions, EPA uncritically adopts a simple estimate of cost 

savings due to slightly reduced years of schooling. The cost used by EPA, $9,724 (in 2010 

dollars) per pupil‐year of school, comes from a document that calculates the average cost of K‐

12 education.102 Elementary and secondary education systems, however, have substantial fixed 

costs in facilities and tenured faculty and staff; thus the marginal cost of a small change in the 

number of pupils is likely to be much smaller than the average cost. It is, of course, only the 

marginal cost that is avoidable by a small change in the number of pupils, and the lead‐induced 

change in numbers at any one school system will be quite small. Again, using the small marginal 

cost of reduced education costs instead of the inflated average cost would increase the monetized 

benefits of ELGs.

Moreover, a significant fraction of children will go on to post‐secondary education, which is 

frequently financed as an investment by the student or the student’s family. A lead‐related 

reduction in the years of post‐secondary education—assuming the same calculation remains 

applicable at this level—has different consequences and cost implications than a reduction in 

public K‐12 education. Reduced investment in a student’s future, by the student or family, is 

again a sad indicator of what has been lost; it is not in any sense a social benefit.

Finally, EPA neglects to discount the estimated “savings” from reduced education expenditure, 

but simply subtracts the current estimate of savings from the present value of lost earnings. If 

children are impaired by lead exposure in early childhood, while the slight resulting reduction in 

years of schooling occurs in high school, then the “savings” occurs many years after the 

exposure. Suppose, for example, that the reduced school attendance occurs 12 years after lead 

exposure; standard practice in EPA cost calculations would then call for discounting the 

“savings” over 12 years, to calculate its present value. At a 3 percent discount rate, the present 

value is 70 percent of the reported value; at a 7 percent discount rate, the present value is 44 

percent of the reported value. Using this approach to discounting—a well‐ established practice in 
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EPA analyses, used in other aspects of the ELG analysis—would lower the value of these lost 

years of education and raise the monetized benefits of the proposed steam electric ELGs.

EPA reports that the (undiscounted) savings for avoided cost of education is $979 in one study, 

and $1,274 in another, and then subtracts these from the present value of earnings, ignoring the 

discount rate.103 In fact, assuming that those savings were correctly calculated but occur 12 years 

after exposure, EPA should have used present values of $685 at 3 percent or $431 at 7 percent 

for the first study, and $892 at 3 percent or $561 at 7 percent for the second study. In quantitative 

terms, this would cause a large percentage increase in the overall valuation of lead exposure at a 

7 percent discount rate and a smaller increase at the 3 percent rate.

94 Benefit‐Cost Analysis, p.3‐5

95 See http://yosemite.epa.gov/ee/epa/eed.nsf/pages/MortalityRiskValuation.html#whatisvsl for a 

discussion of the history and original of the “value of a statistical life” measure.

96 Abt Associates, Memorandum to the Steam Electric ELG Record, “Responses to Questions 

regarding EPA’s Analysis of Benefits of the Proposed Steam Electric ELGs, received from Liz 

Stanton on August 13, 2013,” August 26, 2013. Apt explains that state income was used only to 

predict an average national income. In this memo, Abt compares the elasticity‐adjusted income 

growth factor based on state average income, as used in the proposed steam electric ELGs, and 

the same factor based on national income. The gap between these two factors grows over time. 

The former is 1.04 in 2024, while the latter is 1.12. Abt does not present a national‐income‐based 

factor for 2025 through 2040, but does indicate that an linear extrapolation would be used for 

years after 2024. Using this methodology, the state‐based factor would be 1.09 in 2040, while the 

national‐based factor would be 1.26.

97 From U.S. Census Bureau, Current Population Survey, Annual Social and Economic 

Supplements, “Table H‐8 Median Household Income by State: 1984 to 

2011”, http://www.census.gov/hhes/www/income/data/statemedian/

98 Under these assumptions, median income would grow by a ratio of (1.011)30 in DC, and 

(0.997)30 in Kansas; the VSL would grow by [(1.011)30]0.4 and [(0.997)30]0.4, respectively. 

The ratio of these VSL values is 1.18.

99 Calculated from U.S. Census Bureau, 2011 American Community Survey, Table S1903, 

“Median Income in the Past 12 Months,” http://factfinder2.census.gov/

100 Because (1.90)0.4 = 1.293.

101 Benefit‐Cost Analysis, p.3‐6 to 3‐11

102 Chambers, J.G., T.B. Parrish, and J.J. Harr, “What Are We Spending on Special Education 

Services in the United States, 1999‐ 2000?” (Special Education Expenditure Project, report to 
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U.S. Department of Education, 

2004, http://www.csef‐ air.org/publications/seep/national/advrpt1.pdf).

103 Benefit‐Cost Analysis, p.3‐9

Comment Response: 

The commenter discusses two main issues, addressed below.

The first issue pertains to the Agency’s adjustments to the VSL value, EPA agrees with the 

commenter that it would be inappropriate to value lives differentially based on income. If the 

documentation of the methodology for the proposed rule suggested this interpretation, it was not 

intentional and reflects an editing error rather than factual description of the methodology. The 

August 13, 2013 memorandum referenced by the commenter clarified the approach. EPA also 

clarified the approach in the BCA that describes the final rule analysis.

As described in Chapter 3 of the BCA, the Agency applied a single VSL estimate throughout the 

country in a given year. For future years, the current default VSL ($8.0 million in 2010 dollars) 

is adjusted based on the projected national income growth. In the final rule analysis, EPA used 

VSL to value benefits from avoiding cardiovascular diseases.

The second issue pertains to the Agency’s approach to value IQ points. The commenter states 

that EPA underestimates lead benefits by overestimating cost savings from education and seems 

to imply that avoided education is a benefit of pollution. This is an incorrect interpretation of the 

methodology. EPA’s methodology uses lifetime income as a proxy for the value of an IQ point, 

which is in no way meant to suggest that society benefits from reduced expenditures on 

education. Rather than placing an actual value on an IQ point, which is not possible due to data 

and methodology limitations, this analysis represents a simplified accounting framework, in 

which education costs and lifetime earnings serve as a proxy for the gains and losses associated 

with changes in IQ. EPA does not intend for these calculations to represent actual costs and cost 

savings for individual, but rather to represent an approximate range of values associated with IQ 

points in society.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4724-A2

Comment Excerpt Number: 3

External Review Flag: Envr Assess

External Review Incorporated into Response: No

Comment Excerpt: 

A.Some MCLs are set at a level that does not eliminate the risk of adverse health effects.
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Under the SDWA, EPA is required to conduct cost-benefit analysis and an additional feasibility 

analysis when setting MCLs and other standards.15 When setting health-based drinking water 

standards, EPA first “[d]etermine[s] whether a contaminant should be regulated based on peerreviewed science, including data on: how often the contaminant occurs in the environment; how 

humans are exposed to it; the health effects of exposure (particularly to vulnerable 

subpopulations).”16 Based on this information, EPA sets a Maximum Contaminant Level Goal 

(MCLG), which is the level at which EPA expects no health risks.17 MCLGs “take into account 

the risks of exposure for certain sensitive populations, such as infants, the elderly, and persons 

with compromised immune systems.”18 Next, EPA sets an enforceable MCL "as close to 

MCLGs as feasible, considering available technology and costs.”19 Before finalizing any 

proposed MCL, EPA must "complete an economic analysis to determine whether the benefits of 

that standard justify the costs. If not, [the Agency] may adjust the MCL for a particular class or 

group of systems to a level that ‘maximizes health risk reduction benefits at a cost that is 

justified by the benefits."20 Thus, an MCL may be set at a level that does not eliminate adverse 

health impacts, especially to vulnerable populations like children and the elderly. In the case of a 

known carcinogen, for example, the MCLG is always zero, but MCL’s higher than zero have 

been set for carcinogens in drinking water.21

Arsenic illustrates this point. Power plants dump nearly 80,000 pounds of arsenic into surface 

waters each year. Arsenic is a potent carcinogen, and has been linked to miscarriages, stillbirths, 

and infants with low birth weights when ingested in drinking water.22 Arsenic can also cause

cancer, including skin tumors and internal organ tumors,23 and is also connected to heart 

problems, nervous system disorders, and intense stomach pain.24 The MCLG for arsenic is zero, 

meaning that any amount of arsenic can cause adverse health effects.25 EPA initially proposed 

that the MCL be set at 0.005 mg/l,26 and the MCL for arsenic was finalized at 0.010 mg/l.27 Yet 

any amount of arsenic presents increased health risk in water, even if that water meets federal 

drinking water standards.

Power plant discharges also contain bromide, which is difficult to remove short of evaporating 

wastewater to crystallize out these pollutants. “While bromide itself is not thought to be toxic at 

levels present in the environment,” this pollutant reacts with chemicals commonly used in 

wastewater treatment systems to form disinfection byproducts (DBPs), including bromate, 

trihalomethanes (TTHMs), and halogenated acetic acids (HAAs).28 “Studies indicate that 

exposure to TTHMs and other DBPs from chlorinated water are associated with human bladder 

cancer” and can increase risk of liver, kidney, and central nervous system problems.29 In 

addition, some studies report associations with DBPs and adverse reproductive and 

developmental effects.30 See “Potential Drinking Water Effects of Bromide Discharges from 

Coal-Fired Electric Power Plants” for a more detailed discussion of the human health risks 

associated with DBPs.31

EPA has set MCLs for bromate, TTHMs, and HAAs.32 The MCL for bromate is 0.010 mg/l, but 

the MCLG is zero.33 The MCL for TTHMs is 0.080 mg/l, but the MCLG for specific TTHMs 

are zero for bromodichloromethane, zero for bromoform, 0.060 mg/l for dibromochloromethane, 

and 0.070 mg/l for chloroform—all of which are below the MCL.34 Similarly, the MCL for 

HAAs is 0.060 mg/l, and the specific MCLG for specific HAAs are zero for dichloroacetic acid, 

0.020 mg/l for trichloracetic acid, and 0.070 mg/l for monochloroacetic acid.35 With the 
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exception of the MCLG for monochloroacetic acid, all of the specific MCLGs for HAAs are 

below the MCL.36 In describing how EPA set the current MCLs for DBPs, EPA states that

[d]isinfection byproducts are a special case because decreasing disinfection byproduct risk could 

increase risks from disease- causing microorganisms. Eliminating or significantly decreasing 

disinfection to stop disinfection byproduct formation would seriously compromise overall public 

health protection. The Agency’s priority is maintaining protection from disease-causing 

microorganisms. However, there are a number of things that water systems can do to reduce the 

levels of disinfection byproducts in drinking water (such as decreasing the amount of disinfectant 

and removing as much organic material as possible prior to disinfection).37

While this comment does not address EPA’s judgment as to the relative risks associated with 

DBPs in relation to the importance of protecting public health from disease causing 

microorganisms, the fact is that the MCLs for DBPs do not eliminate all adverse health effects. 

Any additional contamination beyond the MCLG presents some health risk. In conclusion, 

removal of any additional discharges which leads to lower concentrations of a contaminant for 

which the MCLG is zero or lower than the MCL has public health benefit. EPA improperly 

failed to account for benefits arising from reduced health risks from drinking water that is 

cleaner as a result of the ELGs.

15 Drinking Water Standards.

16 Id.

17 Id.

18 Id.

19 Id.

20 Id

21 Id.

22 Agency for Toxic Substances and Disease Registry, Toxicological Profile for Arsenic 18 

(2007), available at http://www.atsdr.cdc.gov/toxprofiles/tp2.pdf.

23 Id.

24 Id. at 20-22.

25 66 Fed. Reg. 6,976, 6,981 (Jan. 22, 2001).

26 65 Fed. Reg. 38,888 (Jun. 22, 2000).
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27 66 Fed. Reg. at 6,981.

28 See, e.g., EA at 3-10; 78 Fed. Reg. 34,432, 34,505 (June 7, 2013).

29 EA at 3-10-3-11.

30 John S. Reif et al., Reproductive and Developmental Effects of Disinfection By-Products in 

Drinking Water, 104 Envtl. Health Perspectives 1056 (Oct. 1996), available at 

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1469476/pdf/envhper00341-0056.pdf;

31 Jeanne M. VanBriesen, Potential Drinking Water Effects of Bromide Discharges from CoalFired Electric Power Plants (2013).

32 U.S. Envtl. Prot. Agency, National Primary Drinking Water Regulations (EPA-F-09-004) 

(May 2009), available at http://water.epa.gov/drink/contaminants/upload/mcl-2.pdf.

33 Id.

34 Id.

35 Id.

36 Id.

37 U.S. Envtl. Prot. Agency, Water: Stage 2 DBP Rule: Basic Information, 

http://water.epa.gov/lawsregs/rulesregs/sdwa/stage2/basicinformation.cfm#twelve (last visited 

Sept. 15, 2013) (emphasis added).

Comment Response: 

EPA agrees that the ELGs will reduce concentrations of contaminants in discharges and ambient 

water, and thus have potential to provide public health benefits particularly in cases where 

current MCLs exceed MCLGs. The commenter uses arsenic as an example of such pollutants. 

EPA disagrees that it has estimated benefits “improperly” by not accounting for health benefits 

of consuming drinking water that is cleaner as a result of the ELG. In developing the analysis for 

the ELGs, EPA looked at those categories of benefits for which data and methods could support 

quantification. Data on the concentrations of steam electric pollutants in treated drinking water 

are not readily available to support the analysis to respond directly to the comment, nor are 

methods to estimate changes in pollutant concentrations post-treatment that may result from ELG 

implementation. For categories of benefits where quantification was not possible, such as the 

benefits of improving drinking water source quality, EPA analyzed the potential benefits 

qualitatively, including by describing the potential magnitude of the benefits where possible. 

Regarding benefits to drinking water systems, EPA conducted a screening-level assessment as 

part of its analysis of the final rule to determine the potential baseline impacts of steam electric 

power plant discharges on public drinking water sources. This assessment identified few reaches 

with drinking water intakes where estimated pollutant concentrations exceeded health thresholds 
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in the baseline and that would improve by removing contributions from steam electric power 

plant discharges. This screening-level assessment suggests that benefits to drinking water 

systems may not be as significant as implied by the commenter, relative to other benefits EPA 

analyzed.

EPA used accepted methods to estimate and monetize health benefits of ELG-related pollutant 

reductions in cases where the expected change in exposure due to ELGs is quantifiable, where 

relevant epidemiological exposure pathways exist and are well-supported by the literature, and 

where peer-reviewed concentration-response functions and necessary data exist to quantify and 

monetize health benefits (e.g., arsenic, lead, mercury). Chapter 3 in the BCA details EPA’s 

analyses.

Following OMB guidance, EPA conducted qualitative health benefits analyses where 

quantitative analysis was not possible given the available data or methods. This inability to 

quantify some categories of benefits potentially leads to underestimates of the benefits of a 

regulation. The commenter specifically mentions benefits of reducing bromide (a DBP 

precursor) discharges as example of important benefits omitted from the ELG analysis 

accounting. The Agency acknowledges evidence suggesting links between DBP exposure and 

adverse health effects (U.S. EPA, 2012), and the general potential for ELGs to reduce 

concentrations of DBP precursors in drinking water supplies. Human health and epidemiological 

literature remain, at this time, too incomplete and too inconclusive (e.g., Rief et al., 1996; 

Arbuckle et al., 2002) to support quantitative benefit assessment of potential DBP reductions 

(e.g., exposure pathways and dose-response functions). In the BCA EPA discusses the potential 

extent and significance of potential reductions of bromide discharges from steam electric power 

plants on public drinking water treatment facilities qualitatively.

As mentioned in responses to other comments (e.g., DCN EPA-HQ-OW-2009-0819-4632-A1, 

Excerpt Number 16), EPA acknowledges that some health benefits are not quantified due to data 

limitations.

For information on the role of benefits analysis in establishing effluent limitations based on Best 

Available Technology Economically Achievable (“BAT”), see response to DCN EPA-HQ-OW2009-0819-4464-A1, Excerpt Number 3.
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29.d. Benefits – Water quality improvement nonuse benefits 

Commenter Name: Quinlan J. Shea III

Commenter Affiliation: Edison Electric Institute (EEI)

Document Control Number: EPA-HQ-OW-2009-0819-4487-A1

Comment Excerpt Number: 101

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Index models such as the WQI are a well-established method for integrating several measures of 

waterbody health or integrity into a single number, and are a useful means of tracking changes in 

waterbody health over time or assessing relative health of different waterbodies at one time. It is 

less clear, however, that the WQI provides an appropriate basis for developing an absolute dollar 

value of benefits. Some of the specific problematic aspects of the WQI include:

• Insufficient acknowledgement of the uncertainties of the WQI model, which is a model that 

generates a single numerical value (i.e., from 0 to 100) for a waterbody based on routine 

analytical data – the WQI model is best used to relay water quality information, while unreliable 

for quantifying environmental damages and benefits or for establishing regulatory criteria; and

• Lack of validation analyses in order to assess the predictive ability (and constraints) of the 

water quality model as compared to field-verified observations of the influence of steam electric 

power generation wastewaters on water quality.

Comment Response: 

EPA agrees with the commenter that the index models such as the WQI are a well-established 

method for integrating several measures of waterbody health or integrity into a single number. 

The Agency recognizes that there are uncertainties inherent in its application of the WQI, as 

discussed in Chapter 4 of the BCA for the final rule, but EPA still considers the WQI to be the 

best available metric for quantifying water quality improvements resulting from the ELGs. 

EPA’s assessment is based on the particular application of the WQI to relate changes in water 

quality across a range of different parameters, to the public’s willingness-to-pay (WTP) for 

improvements expressed on a readily understood scale unambiguously linked to specific water 

uses (e.g., recreational).

EPA also agrees with the commenter that the WQI model is useful for “relaying water quality 

information.” This statement is supported by evidence from the environmental benefits valuation 

literature, where similar numeric measures are often used to relay information about baseline 

water quality and water quality changes to survey respondents. As described in the BCA, the 

meta-analysis of household WTP for water quality improvements includes 140 WTP 

observations from 51 primary valuation studies. The primary study observations are measures of 

household benefits (or damages) for water quality changes presented to survey respondents. 

About 31 percent of the observations used the numeric, 10-point water quality ladder (WQL) 
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(Vaughan 1986) to communicate water quality conditions to survey respondents and to estimate 

willingness-to-pay for water quality improvements. Many other studies use descriptive metrics 

that define water quality categories based on ecological and/or recreational services provided. 

EPA translated all water quality changes (i.e., WQL-based and described qualitatively) to the 

100-point WQI prior to estimating the meta-regression. EPA tested a dummy variable (WQI) that 

captures the effect of a study using (WQI=1) or not using (WQI=0) the WQI. The variable 

coefficient was not statistically different from zero, indicating no systematic bias in the mapping 

of studies that did not use the WQI. This supports the use of the WQI as an appropriate metric 

for linking water quality changes resulting from the final ELG to public values of water quality 

improvements reported in the published literature.

In its analysis of the final rule, EPA translated parameter concentrations estimated using existing 

water quality models (SPARROW, RSEI) to into WQI values for baseline conditions and under 

each of the regulatory options. EPA then used a meta-regression that relates the baseline WQI 

value and WQI change resulting from each regulatory option to household WTP for the degree 

of improvement, accounting for the characteristics of the water body, household, etc. Chapter 4 

in the BCA discusses the uncertainty of the methodology.

Regarding validation of the water quality models, see DCN EPA-HQ-OW-2009-0819-4655-A2, 

Excerpt Number 24 and the case study modeling discussion in Section 8 of the Environmental 

Assessment for the Effluent Limitations Guidelines and Standards for the Steam Electric Power 

Generating Point Source Category (EA Report) (DCN SE04527).

Cited References:

Vaughan, W.J. 1986. ―The RFF Water Quality Ladder.‖ In: Mitchell, R.C. and R.T. Carson. 

The Use of Contingent Valuation Data for Benefit/Cost Analysis in Water Pollution Control, 

Final Report. Washington: Resources for the Future. Appendix B.

Commenter Name: Quinlan J. Shea III

Commenter Affiliation: Edison Electric Institute (EEI)

Document Control Number: EPA-HQ-OW-2009-0819-4487-A1

Comment Excerpt Number: 102

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In addition, the WQI, which was used to link the individual modeled pollutant loading and the 

“health” of a water body for ecological receptors and recreational use, and was the basis of 

monetized benefits, is a model that introduces additional uncertainty into the assessment.
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Specific problematic aspects of the surface water quality analysis include:

• Insufficient acknowledgement of the uncertainties of the WQI model, which is a model that 

generates a single numerical value (i.e., from 0 to 100) for a waterbody based on routine 

analytical data. (The WQI model is best used to relay water quality information, while 

unreliable for quantifying environmental damages and benefits or for establishing regulatory 

criteria);

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4487-A1, Excerpt Number 101.

Commenter Name: Roger E. Claff

Commenter Affiliation: American Petroleum Institute (API)

Document Control Number: EPA-HQ-OW-2009-0819-4641-A1

Comment Excerpt Number: 4

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA Should Not Rely on Willingness-to-Pay Survey Results in Determining Benefits of the 

Proposed Rule

EPA relied upon consumer and household willingness-to-pay surveys to estimate the benefits of 

the proposed effluent guidelines. Yet willingness-to-pay surveys provide only a 

highly subjective and therefore arbitrary monetized measure of the value people place on 

environmental goods. The typical survey respondent is not well versed in environmental 

economics and is not skilled in objectively measuring environmental benefits, particularly taking 

a single proposed environmental benefit and placing it in the context of the myriad other 

economic costs and benefits with which he/she is confronted. Also, the typical survey 

respondent will not place this single proposed environmental benefit in the context of all other 

conceivably proposed environmental benefits to assess which has more value than 

another. Without such context, the survey respondent is likely to over-value the single proposed 

environmental benefit, simply because that benefit has been placed in front of 

him/her. Additionally, using stated preference survey to measure "nonuse" benefits is 

inappropriate when EPA has not shown the affected resources to be unique or limited and the 

impacts to be substantial or irreversible.

API refers EPA to API, the Utility Water Act Group, and the Cooling Water Intake Structure 

Coalition comments submitted in response to EPA's proposed cooling water intake structure rule 

(EPA Docket No. EPA-HQ-OW-2008-0667). These comments provide detailed assessments of 

the technical inadequacies of willingness-to-pay surveys in objectively measuring the benefits of 

a proposed rule.
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Comment Response: 

EPA disagrees and notes that the comment is inconsistent with accepted findings and approaches 

in benefit-cost analysis. EPA recognizes that there has been controversy over the use of stated 

preference valuation methods. However, a recent evaluation of this controversy by Kling et al. 

(2012, p. 23), concludes that “that the last 20 years of research have shown that some carefully 

constructed number based on stated preference analysis is now likely to be more useful than no 

number [for] cost–benefit analysis.” Stated preference methods have “... been tested and 

validated through years of research and are widely accepted by federal, state, and local 

government agencies and the U.S. courts as reliable techniques for estimating nonmarket values” 

(Bergstrom and Ready 2009, p. 26;)

There are no theoretical necessary conditions for the existence of nonuse values. For example, 

resources do not have to be unique to be the source of nonuse WTP. This is demonstrated by the 

primary studies that make up the meta-data EPA used to relate water quality improvements to 

WTP. Many of the primary studies estimate total WTP values (use plus nonuse) for resources 

similar to those affected under the final ELGs. While EPA recognizes the possibility of low nonuse values, significant non-use values are also possible. EPA notes that when a substantial 

fraction of the population holds even small per capita nonuse values, these nonuse values can be 

very large in the aggregate. As stated by Freeman (2003, p. 138), "If nonuse values are large, 

ignoring them in natural resource policymaking could lead to serious errors and resource 

misallocations." Office of Management and Budget (OMB) Circular A-4, governing regulatory 

analysis, support the need to assess nonuse values (U.S. OMB 2003). Also, see DCN EPA-HQOW-2009-0819-4655, Excerpt Number 233.

EPA agrees with the commenter’s statement that “the typical survey respondent is not well 

versed in environmental economics,” but notes that if a stated preference survey is well designed, 

proficiency in environmental economics is not needed to provide informed and valid results. The 

Agency took care to identify studies that use accepted stated preference methods. Each primary 

study is based on a population sample within which respondent proximity and familiarity within 

the resource varies. The information provided in each primary study’s survey varies across the 

meta-data due to factors including, but not limited to, survey methodology, the characteristics of 

the affected resource and sampled area, and the magnitude, nature, and source of the water 

quality changes.

The expansive stated preference literature clearly supports the use of meta-analysis benefit 

transfer to estimate WTP for water quality improvements. The Agency recognizes the 

commenter’s perspectives on the validity of stated preference methods, but notes that this is just 

one perspective. Stated preference approaches and benefit transfer based on stated preference 

studies have now been applied in numerous cases to value nonmarket environmental resources 

and related policy changes in various contexts (including damage assessments). Official 

guidance documents (e.g., OMB’s Circular A-4; U.S. EPA 2010) and the Blue Ribbon Panel 

(Arrow et al. 1993)—while explicitly recognizing the controversies and challenges—both 

consider stated preference methods to be a valid source of information. Moreover, OMB’s 

Circular A-4 also notes that “stated-preference study may be the only way to obtain quantitative 

information about non-use values”.
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Cited References:

Arrow, K. , R. Solow, E. Leamer, P. Portney, R. Rander, and H. Schuman. 1993. Report of the 

NOAA Panel on Contingent Valuation, Federal Register 58 (Jan.): 4602-4614.

Bergstrom, J.C. , and R.C. Ready. 2009. What Have We Learned from Over 20 Years of 

Farmland Amenity Valuation Research in North America? Review of Agricultural Economics, 

31(1): 21-49.

Kling, C.L., D.J. Phaneuf and J. Zhao. 2012. From Exxon to BP: Has Some Number Become 

Better than No Number? Journal of Economic Perspectives 26(4): 3-26.

U.S. EPA. 2010. Guidelines for Preparing Economic Analyses. EPA 240-R-10-001. U.S. EPA, 

Office of the Administrator, Washington D.C. December 2010 (updated May 2014).

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 201

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Index models such as the WQI are a well-established method for integrating several measures of 

waterbody health or integrity into a single number, and are a useful means of tracking changes in 

waterbody health over time or assessing relative health of different waterbodies at one time. It is 

less clear, however, that the WQI provides an appropriate basis for developing an absolute dollar 

value of benefits. Some of the specific problematic aspects of the WQI include:

 insufficient acknowledgement of the uncertainties of the WQI model, which is a model 

that generates a single numerical value (i.e., from 0 to 100) for a waterbody based on 

routine analytical data – the WQI model is best used to relay water quality information, 

while unreliable for quantifying environmental damages and benefits or for establishing 

regulatory criteria; and

 lack of validation analyses in order to assess the predictive ability (and constraints) of the 

water quality model as compared to field-verified observations of the influence of steam 

electric power generation wastewaters on water quality.

Comment Response: 

Refer to response to DCN EPA-HQ-OW-2009-0819-4487-A1, Excerpt Number 101.
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Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 233

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

I. EPA Should Not Rely on Willingness-to-Pay Surveys

In its BCA (p. 1-2) EPA says “[s]everal categories of benefits presented in this report are 

estimated based on consumer or household willingness-to-pay (WTP) surveys, such as WTP for 

surface water quality improvements applied in this BCA for monetizing ecological benefits of 

the proposed ELGs.” As EPA knows, willingness-to-pay surveys to measure subjective values 

that people assign to environmental goods have been controversial, especially in the rulemakings 

for cooling water intake structures under § 316(b) of the Clean Water Act.

UWAG comments now, as it has in past rulemakings, that using a stated preference survey to 

measure “nonuse” benefits is inappropriate where, as here, the Agency has not shown indicator 

resources (e.g., water clarity and blue crab) to be unique or limited and the impacts to be 

substantial or irreversible. See Attachment 24, Comments on EPA’s Notice of Data Availability 

for § 316(b) Stated Preference Survey, prepared by NERA Economic Consulting for UWAG 

(NERA Report), July 2012, pp. E-10, 7 (citing Freeman, A. Myrick III. 2003. The Measurement

of Environmental and Resource Values: Theory and Methods. 2nd ed. Washington, DC: 

Resources for the Future).

Comment Response: 

Refer to response to DCN EPA-HQ-OW-2009-0819-4641-A1, Excerpt Number 4 regarding 

controversy related to stated preference approaches.

The commenter’s reference to a “uniqueness” criterion is misguided. Evidence from the 

environmental economics literature indicates that households may have material nonuse 

willingness-to-pay for relatively common ecological services and resource improvements, which 

would not be considered unique by the commenter. UWAG cites Freeman (2003)[1] in its 

assessment of the likely significance of nonuse values, interpreting Freeman (2003) as 

suggesting that nonuse values are unlikely unless: (1) the resource is unique and (2) the loss 

would be irreversible or subject to a long recovery period.

The commenter’s assertion reflects an ad hoc interpretation of Freeman (2003)’s discussion of 

nonuse values. Freeman (2003) goes on to state that “at the present time there is no general 

method for determining whether a resource is sufficiently unique or a resource change is of 

sufficient duration to generate important nonuse values” (p. 157). Bateman et al. (2002)[2] 
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advises against the use of ad hoc, expert assumptions regarding the magnitude of nonuse values –

particularly assuming that nonuse values are trivial – stating that “it would be wrong for experts 

to assume that one resource is a perfectly good substitute for another” (p. 75), and consequently 

to assume that nonuse values are trivial, because values concerning the quality of substitutes are 

inherently subjective. Freeman also states that in economic terms “uniqueness would be reflected 

in the absence of substitutes and low price elasticity of demand...but there is no threshold on 

price elasticity that distinguishes between the presence or absence of close substitutes” (p. 157).

[1] Freeman, A.M., III. 2003. The Measurement of Environmental and Resource Values: Theory 

and Methods. Washington, DC: Resources for the Future.

[2] Bateman, I.J., R.T. Carson, B. Day, M. Hanemann, N. Hanley, T. Hett, M. Jones-Leee, G. 

Loomes, S. Mourato, E. Ozdemiroglu, D.W. Pierce, R. Sugden, and J. Swanson. 2002. Economic 

Valuation with Stated Preference Surveys: A Manual. Northampton, MA: Edward Elgar.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A2

Comment Excerpt Number: 24

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

There are several uncertainties in the WQI which have not been identified by US EPA nor has 

their effect on the model results been evaluated.

 Despite being the only water quality analysis to be monetized in support of the proposed 

ELG, US EPA provides substantially less documentation regarding how the analysis was 

performed than for the other water quality evaluations. For example, US EPA (2013d, pg. 

4-5) cites to an evaluation performed for the construction and development point source 

category for information on how the SPARROW model was applied. This may be an 

efficient way to describe the general procedures, but does not provide specifics of the 

application of SPARROW model to the steam electric power plant point source category. 

For the RSEI model, US EPA (2013d) does not cite to any supporting documentation 

beyond the RSEI model description. The level of documentation provided for these 

significant modeling efforts is not adequate to support a reasonable understanding of how 

the modeling was performed, nor is it adequate to support reasonable opportunity to offer 

comment. For example, there is a lack of documentation on the assumptions regarding 

water hardness. US EPA's AWQC for several metals (cadmium, chromium, lead, nickel, 

zinc) are dependent on water hardness, which is a highly site-specific water quality 

parameter. The process to adjust the WQI for receiving-water specific hardness is 
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presently unspecified, and therefore unknown whether the WQI is providing accurate 

predictions for the metals sub-index.

 US EPA adapted the WQI from multiple sources (Cude, 2001; CCME, 2001 Carruthers 

and Wazniak, 2005, each of which report limitations that have not been addressed in the 

ELG rule. CCME (2001) note that the WQI, "is not intended to replace a detailed analysis 

of environmental monitoring data, nor should it be used as the only tool for management 

of water bodies." Further disadvantages include, "the loss of information on single 

variables, the sensitivity of the results to the formulation of the index, the loss of 

information on interactions between variables, and the lack of portability of the index to 

different ecosystem types." Cude (2001) also reported that the WQI, "was designed for 

Oregon's streams, and its application to other geographic regions or waterbody types 

should be approached with caution." In the current ELG rule, none of these uncertainties 

have been addressed quantitatively nor has a validation study been conducted to evaluate 

the predictability of the WQI for use at a national scale. For instance, US EPA could have 

evaluated environmental monitoring data from case studies mentioned in the EA to 

evaluate the accuracy of the predicted WQI results. This could provide a more detailed 

analysis (as suggested by CCME) to calibrate the WQI model. US EPA should provide a 

demonstration that results of the WQI are predictive (with uncertainty bounds) of realworld effects on water quality. Without this type of analysis we cannot ascertain whether 

the environmental or monetary benefits are reliable.

 US EPA's contractor acknowledged that portions of the WQM (SPARROW and RSEI) 

have limitations (e.g., simple algorithm to model fate and transport) and that the models 

provide "screening-level" insight into the potential downstream effects of the ELGs (Abt 

Associates, 2013). A screening level-approach (as used in the WQI and in other areas of 

the EA) is generally useful for removing parameters that are unlikely to present a risk and 

identifying those that require further study. The WQI is inherently a screening-level 

model and the other agencies have explicitly (see CCME above) suggested that detailed 

environmental modeling (i.e., including assessments of both exposure and health effects) 

should be conducted in addition to the use of this model. US EPA should acknowledge 

throughout the ELG rule that the approaches undertaken are "screening-level" and that 

they may not accurately predict environmental damage or benefit.

In addition to the issues noted above, all the issues described for the pollutant loadings analysis 

(WQM) would affect the WQI model analysis.

Comment Response:

The commenter raises several issues related to the use of the Water Quality Index (WQI) in 

valuing water quality improvements. EPA addresses these issues below, expanding on the 

response to related comments (e.g., see DCN EPA-HQ-OW-2009-0819-4487-A1, Excerpt 

Number Number 101).

First, the commenter notes the sparse description of the modeling approaches that provide inputs 

to the WQI calculations. For the final rule analysis, EPA expanded the discussion of these 

models to describe how they were used to estimate changes in ambient water pollutant 

concentrations. See Appendix D in the BCA for the final rule. Regarding water hardness, EPA 
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compared the dissolved concentrations (based on the average dissolved/total fraction of modeled 

total concentration) to the ambient aquatic life water quality criteria provided for nominal 

hardness levels of 100 mg/L.

Second, the commenter notes the limited discussion of the uncertainty of the WQI approach, as 

adapted from original sources. As discussed in Chapter 4 of the BCA, EPA modified the WQI 

originally developed by McClelland to incorporate two main improvements: 1) regionally 

specific subindex curves that reflect differences in natural conditions present in these 

waterbodies, and 2) addition of a subindex for metals that accounts for exceedances of 

established water quality criteria. EPA carefully considered the changes in light of the limitations 

and uncertainty noted by the original sources.

For the regionally specific subindex curves, EPA notes that it did not adopt the values developed 

by Cude directly, but instead used the approach developed by Cude to determine the values 

specific to different ecoregions across the country. This approach improves on the index 

developed by McClelland by recognizing that different, and possibly relatively high, levels of 

nutrient and sediment can occur naturally even under undisturbed conditions. In the unmodified 

McClelland index, such locations may be assigned very low WQI values due to naturally high 

sediment concentrations, even though they support expected uses of the waters. Conversely, the 

unmodified McClelland index may yield high WQI values in regions with naturally low nutrient 

levels, even for locations comparatively impacted by excess nutrients. EPA thus used the 

approach developed by Cude to develop region-specific scales that tie to the distribution of 

values in the underlying data, assuming that the cleanest waters within the underlying data 

represent reference, unaffected waters (based on the 25th percentile of the distribution). This 

approach is consistent with the use of inference methods for deriving numeric criteria (e.g., U.S. 

EPA, 2000a; U.S. EPA, 2000b).

Regarding the CCME-inspired subindex, EPA similarly notes that it used the methodology 

developed by CCME and not the actual scoring scale. The original index developed by 

McClelland includes a parameter for toxics as an overall modifier to the score calculated based 

on the other parameters. Thus, under the original McClelland index, any exceedance of a water 

quality criterion for toxic pollutants restates the WQI value to zero. This makes the original 

index somewhat insensitive to improvements in concentrations of non-toxic parameters and 

overly sensitive to very small changes when they affect values close to the threshold. EPA 

deemed the CCME-based approach superior as it provides a finer gradation of effects as 

waterbody exceedances are addressed for the same set of modeled parameters. EPA conducted 

sensitivity analyses using alternate definitions of the WQI and determined that the WQI 

formulation used in the main analysis provided the optimal balance between being sensitive to 

change in toxic parameters while minimizing eclipsing of other water quality indicators.

Third, the commenter requested more details on the validity of the WQI at the national scale. As 

part of the final rule analysis, EPA confirmed that the WQI provides valid indication of overall 

water quality by comparing the baseline WQI scores (without the ELG loading reductions) 

against historical water quality assessment data for the same waterbodies. The comparison shows 

statistically significant differences in the WQI score obtained for those waterbodies assessed as 

impaired (i.e., poor water quality) and those assessed as meeting designated uses (i.e., good 
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water quality). This comparison lends support to the index as a reasonable indicator of existing 

water quality. EPA recognizes that this comparison only addresses the validity of the index for 

existing conditions and does not provide separate confirmation that the changes calculated based 

on the index formula predict the “real-world” overall changes in water quality. The estimated 

changes in the WQI resulting from the ELGs are, however, consistent with modeled changes in 

concentrations.

Finally, the commenter notes that the WQI model is by definition a screening-level approach and 

suggests that modeling be undertaken to better characterize water quality changes that may result 

from the ELGs. The values EPA uses to calculate the WQI came from modeling the fate and 

transport of pollutants discharged by steam electric power plants. While EPA acknowledges that 

these models necessarily use simplifying assumptions given the national scope of the analysis, 

EPA used appropriate modeling approaches given data limitations. For the final rule analysis, 

EPA also conducted analyses using the same national models used at proposal (which use a more 

detailed partitioning algorithm to estimate water column concentrations of toxic pollutants), as 

well as expanded the analysis to also look at specific case study locations using models that 

incorporate a more comprehensive representation of environmental fate of the modeled 

pollutants. In general, the detailed case study models support the overall conclusions of the 

national-level model in corresponding water bodies, and where there are differences between the 

case study and national models, the case study model shows more severe impacts in small 

receiving waters with highly variable flow rates. The case study model also shows that the 

impacts from the steam electric power plant discharge may propagate farther downstream than 

the directly receiving waterbody in the scope of the national model. See Chapter 8 of the 

Environmental Assessment for the Effluent Limitations Guidelines and Standards for the Steam 

Electric Power Generating Point Source Category (EA Report) (DCN SE04527) for details.

EPA refers to its response to DCN EPA-HQ-OW-2009-0819-4487-A1, Excerpt Number 101, on 

the specific application of the WQI to support monetization of the water quality improvements.

U.S. EPA. 2000a. Nutrient Criteria Technical Guidance Manual: Lakes and Reservoirs. EPA822-B-00-001. April 2000.

U.S. EPA. 2000b. Nutrient Criteria Technical Guidance Manual: Rivers and Streams. EPA-822-

B-00-002. July 2000.

Commenter Name: Jerry Schwartz

Commenter Affiliation: American Forest & Paper Association (AF&PA)

Document Control Number: EPA-HQ-OW-2009-0819-4656-A2

Comment Excerpt Number: 7

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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Of equal concern is the use of Willingness-to-Pay surveys to increase the benefits of the 

Proposal. AF&PA previously joined UWAG and other parties in filing a detailed critique of such 

surveys in another EPA rulemaking.

Comment Response: 

Refer to response to DCN EPA-HQ-OW-2009-0819-4641-A1, Excerpt Number 4.

Commenter Name: Amy Trojecki

Commenter Affiliation: Exelon Corporation

Document Control Number: EPA-HQ-OW-2009-0819-4662-A2

Comment Excerpt Number: 4

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

 EPA should abandon use of stated preference surveys, willingness-to-pay estimates and 

similarly unreliable techniques to assess value of non-use benefits.

Comment Response: 

Refer to response to DCN EPA-HQ-OW-2009-0819-4641-A1, Excerpt Number 4.

Commenter Name: Amy Trojecki

Commenter Affiliation: Exelon Corporation

Document Control Number: EPA-HQ-OW-2009-0819-4662-A2

Comment Excerpt Number: 10

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

IV. EPA Should Not Rely on Stated Preference Surveys and Similar Unreliable Studies to 

Estimate Benefits

Exelon objects to EPA’s use of stated preference surveys, willingness-to-pay estimates and 

similarly unreliable tools for assessing the value of non-use benefits. This concern is amplified 

here, where EPA’s assessment of non-use values is based on “meta-analysis” of many such 

unreliable inputs, as described in the benefit cost analysis performed in connection with the 

proposed Rule. See EPA, Benefit and Cost Analysis for the Proposed Effluent Limitations 

Guidelines and Standards for the Steam Electric Power Generating Point Source Category, EPA 
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821-R-13-004 (April 2013), EPA-HQ-OW-2009-0819-2238 (“ELG BCA”) at

Appx. E. While robust stated preference surveys can provide useful directional value signals 

concerning specific types of resources (e.g., endangered or threatened species or unique natural 

resources) in specific areas, such studies are of little value in assessing the benefits of a rule of 

national scope, like the ELGs, which will necessarily apply in cases where those specific highvalue resources are absent. Under the ELG program, EPA cannot justify imposing obligations on 

all sources in this category by pointing to benefits that will occur, if at all, at only a small subset 

of sources in the category.

In the proposed Rule, EPA compounds its error by aggregating the results of 45 studies over 

three decades in a “meta-analysis.” Id. at E.1.2. These studies used different methodologies and 

assessed different types of environmental impacts in different areas of the country. Most of these 

studies assessed only the perceived value of improvements to “general water quality” – at best a 

vague environmental benefit unmoored from specific objective such as the protection of 

endangered species. Indeed, only a handful of the studies included in EPA’s meta-analysis relate 

to “wildlife habitat.” While the goal of EPA’s meta-analysis is to derive useful observations 

from a group of unrelated, differently configured studies, the very nature of this synthesis further 

compromises the utility of the result. Even if each of the 45 studies was individually sound, and 

reached reliable conclusions with respect to the value of the resources evaluated, the strength of 

these individual findings is so diluted through the meta-analysis as to be useless, particularly as 

applied to a national standard. Therefore, Exelon comments that EPA should abandon use of 

stated preference surveys, willingness-to-pay estimates and similar techniques, with or without 

meta-analysis, to monetize non-use values, and should not base its benefit cost analysis for any 

national rulemaking on such unreliable data.

Comment Response: 

EPA disagrees with the commenter that the Agency should abandon its use of stated preference 

studies and meta-analyses for estimating benefits of water quality improvements resulting from 

the final ELG. Refer to response to comment DCN EPA-HQ-OW-2009-0819-4641-A1, Excerpt 

Number 4 regarding the reliability of stated preference approaches in general and refer to 

response to comment DCN EPA-HQ-OW-2009-0819-4655, Excerpt Number 233, regarding 

values for “non-unique” resources, that is, values for resources that the commenter would not 

consider to be “high value” a priori.

For the final rule, EPA used a revised meta-regression to estimate water quality benefits for the 

final ELGs. This meta-regression is based on 140 willingness-to-pay observations from 51 

primary valuation studies. EPA disagrees with the commenter’s assessment of the primary study 

values as “vague environmental benefit unmoored from specific objective.” On the contrary, the 

primary studies often provide detailed information regarding the environmental improvement 

and any recreational improvements that occur under the valuation scenario. Furthermore, while 

the primary studies were conducted independently, EPA does not consider them to be 

“unrelated.” As discussed in Chapter 4 of the BCA for the final rule, EPA followed specific 

criteria in determining whether studies should be included in the metadata, including commodity 

consistency (i.e., studies must value water quality changes) and welfare consistency (i.e., studies 

must use general accepted stated preference approaches and report theoretically comparable 
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Hicksian welfare measures). EPA recognizes that primary studies are “differently configured” 

(i.e., use different stated preferences methodologies or payment vehicles). The systematic effects 

of differences in studies’ methodology, sampled populations, affected resources, and water 

quality on willingness-to-pay are captured by explanatory variables in the meta-regression. See 

Chapter 4 of the BCA for detail on the revised meta-regression model used in EPA’s analysis of 

water quality benefits for the final ELGs. EPA also disagrees with the assertion that using a 

meta-analysis compounds the error of relying on stated preference results. The meta-analysis 

allows EPA to project, based on a comparison to the existing literature, the results that could be 

obtained had EPA conducted a stated preference survey tailored to the ELGs.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 39

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Improved aquatic and wildlife habitat from improved ambient water quality in receiving 

reaches; enhanced swimming, fishing, boating, and near‐water activities from improved water 

quality; increased aesthetics from improved water clarity, color, odor, including nearby site 

amenities (residing, working, traveling); enhanced existence, option, and bequest values from 

improved ecosystem health; reduced risks to aquatic life from exposure to steam electric 

pollutants; and improved threatened and endangered habitat and thus potential increase in 

threatened and endangered population: Several assumptions made by EPA regarding the value 

of water quality result in an underestimation of the value of improved ambient water quality in 

receiving reaches. The value of these benefits depends on how much water quality is expected to 

improve under each regulatory option. EPA notes that their measure of water quality accounts 

for metal and nutrient concentrations but does “not include improvements in water quality 

indicators associated with other pollutant loadings (e.g., BOD, dissolved oxygen), nor does it 

consider improvements in other water quality variables such as TSS. Omitting some water 

quality parameters from the analysis is likely to result in underestimation of the expected water 

quality changes.”83

83 Benefit‐Cost Analysis, p.4‐20, Table 4‐14

Comment Response: 

For the final ELGs, EPA has revised its analysis to include changes in TSS based on 

SPARROW. See Chapter 4 of the BCA for the final rule for additional discussion of EPA’s 

analysis of metals, nutrients, and TSS. EPA did not estimate changes in BOD and dissolved 

oxygen under the final ELGs. EPA agrees within the commenter that to the extent that these 

parameters would also improve under the Steam Electric ELG, omitting BOD and dissolved 
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oxygen from the analysis results in underestimation of the expected water quality changes and, 

as a result, the monetary value of benefits of water quality improvements resulting from the final 

ELGs.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 43

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Willingness to pay for improved water quality

EPA uses a willingness‐to‐pay methodology to monetize the value that society places on water 

quality, other than for its direct use: for example, the value of the existence of good water quality 

(even if the water is not used by society); the value of having the option to use that clean water in 

the future; and the value of being able to pass clean water down to future generations. EPA’s 

non‐use value for improved water quality is derived from “willingness‐to‐pay” surveys that ask 

respondents to assign a value to a social or environmental good.

EPA concludes that their attempt to determine society’s willingness‐to‐pay for improved water 

quality in the proposed steam electric ELGs is likely an underestimation and that “[t]he 

estimation of [willingness‐ to‐pay] may be sensitive to differences in the environmental water 

quality measures across studies in the meta data.”92

Once determined from survey results, individual willingness to pay is extrapolated to the affected 

population. EPA assumes that households will only value improvements of nearby water bodies, 

further underestimating the value of increased water quality. “Residents of other states may hold 

values for water resources outside of their home state, in particular if such resources have 

personal, regional, or national significance. Even if per household [willingness‐to‐pay] for out‐

of‐state residents are small they can be very large in the aggregate if these values are held by a 

substantial fraction of the population.”93Correcting these assumptions would increase the water 

quality benefits from the proposed ELGs.

92 Benefit‐Cost Analysis, p.4‐19, Table 4‐14.

93 Benefit‐Cost Analysis, p.4‐19, Table 4‐14.

Comment Response: 

EPA agrees with the commenter that some assumptions used in the analysis of total willingness 

to pay (WTP) for water quality improvements may lead to underestimation of total benefits of 
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the ELG. The Agency notes that it revised its analysis of water quality improvement benefits to 

address a variety of limitations, including those noted by the commenter. First, the Agency 

revised the water quality meta-regression function that was used to estimate household 

willingness-to-pay for water quality improvements for the proposed ELGs to better reflect 

geospatial characteristics of the waterbodies affected by the final ELG, presence of substitute 

sites, and the extent of the market for water quality improvements. The revised meta-regression 

is discussed in Chapter 4 and Appendix H of the BCA for the final ELGs.

EPA also revised its benefit transfer approach for applying the meta-regression to water quality 

improvements under the ELGs. As discussed in Chapter 4 of the BCA for the final ELGs, the 

benefit transfer approach for the final ELGs uses Census block groups as the geographic unit of 

analysis, assuming that households in each Census block group value changes in the affected 

waterbodies not just within the Census block group area, but within a 100-mile distance from the 

center of the block group. EPA notes that the area corresponding to the 100-mile radius is 

consistent with the typical study area (i.e., extent of the market) used in the original studies 

included in the meta-analysis. Although households may hold values for water quality 

improvements outside of the 100-mile radius these values are likely to be very small for noniconic waterbodies given the estimated small changes in water quality resulting from the final 

ELG, a large number of substitute sites, and distance decay factors associated with willingness to 

pay for water quality changes (e.g., Bateman et al. 2006,; Schaafsma et. al. 2013).

Cited Literature:

Bateman Ian J., Day Brett H., Georgiou Stavros, Lake Iain R. 2006. “The Aggregation of 

Environmental Benefit Values: Welfare Measures, Distance Decay and Total WTP.” Ecological 

Economics 60 (2): 450–60.

Schaafsma, M., R. Brouwer, A. Gilbert, J. van den Bergh, and A. Wagtendonk. 2014 

“Estimation of Distance-Decay Functions to Account for Substitution and Spatial Heterogeneity 

in Stated Preference Research”. Land Economics, 2013 vol. 89 no. 3 514-537
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29.e. Benefits – E&T species benefits 

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 96

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In my class, Environment, Technology, and Economy, my students become well versed in the 

effects of heavy metals emitted by coal plants on our local industries that depend on the 

Bay. For crabbers, oystermen, and the Vitamin E industry dependent on the Menhaden fish, 

these industries are incredibly vulnerable to pollution and have all been suffering, especially the 

Vitamin E industry affected by heavy metals that bioaccumulate in the fish.

I am personally concerned about business because after I leave the university, I intend on starting 

my own as a farmer and chef. With a degree in conservation biology, I intend to be extremely 

choosy as a find a place that is right for me and where I can offer products where I can account 

for every ingredient in them.

Current effluent water standards will drive young entrepreneurs such as me away from locations 

where business could be affected. I am concerned about coal fired power plant effluent because 

of the effects of the metals emitted.

Comment Response: 

As described in the BCA, the final rule will reduce discharges of pollutants by coal fired power 

plants about which the commenter is concerned, thereby improving surface water quality and 

reducing metal pollutant concentrations in fish tissue. These reductions have a range of human 

health and ecological benefits described in the BCA.

Commenter Name: Ernest Lehmann

Commenter Affiliation: Private Citizen

Document Control Number: EPA-HQ-OW-2009-0819-3920-A16

Comment Excerpt Number: 5

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Today, the greatest threats to the survival of the shortnose sturgeon include, among other 

things, power plant construction and operation, and pollutant and thermal discharges. ld. at 116.
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Indeed, NMFS has concluded that electric power generating plants are a significant threat to the 

species and contribute to the species' decline. /d. at 117. Of particular concern is the impact 

that electric power generating plants' cooling water intake structures have on sturgeon through 

impingement and entrainment of larval and young juvenile sturgeon, when the fish are small and 

poor swimmers. !d. As NMFS explained in the Recovery Plan for the shortnose sturgeon,

Shortnose sturgeon are susceptible to impingement on cooling water intake screens. Electric 

power and nuclear power generating plants can affect sturgeon by impinging larger fish on 

cooling water intake screens and entraining larval fish.

Recovery Plan at 53. Numerous observations in laboratories have demonstrated that larvae and 

young juveniles cannot escape flow rates as low as 0.25 feet per second. See Kynard Dec!. at 1 

17. Moreover, because sturgeon are relatively slow growing and exist in a vulnerable larval and 

young juvenile stage for 10-12 months, sturgeon and sturgeon populations are particularly 

susceptible to adverse impacts from impingement and entrainment. The take of young sturgeon 

can have magnified impacts on sturgeon populations. This is because sturgeon are slow 

maturating, they do not spawn every year, and the species is already critically imperiled. See id.

Comment Response: 

EPA appreciates concerns regarding the impacts of cooling water intake structures (CWIS) on 

shortnose sturgeon and other protected species, but the Agency notes that the ELG regulation is 

intended to strengthen the existing controls on pollutant discharges from steam electric power 

plants by revising technology-based effluent limitations guidelines and standards.

Section 316(b) of the Clean Water Act requires EPA to issue regulations on the design and 

operation of intake structures, in order to minimize adverse environmental impacts. EPA 

promulgated regulations in 2001, 2003, 2006 and 2014. Thus, this comment is outside the scope 

of the steam electric ELG. However, changes in wastewater processes at the plants will reduce 

surface water withdrawals from steam electric power plants, which will in turn reduce the 

impingement and entrainment mortality threats which the commenter discusses. EPA discusses 

these benefits qualitatively in Chapter 8 of the BCA for the final rule. EPA also analyzed 

potential benefits to endangered and threatened species, including sturgeons, from improvements 

in water quality resulting from the final rule. This analysis is detailed in Chapter 5 of the BCA.

Commenter Name: Ernest Lehmann

Commenter Affiliation: Private Citizen

Document Control Number: EPA-HQ-OW-2009-0819-3920-A16

Comment Excerpt Number: 7

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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The Shortnose Sturgeon In The Potomac

NMFS has recognized 19 distinct population segments of shortnose sturgeon. Shortnose 

sturgeon populations consist of two clusters: a northern cluster of population segments (spanning 

from New Brunswick to the Hudson River) and a southern cluster of population 

segments (spanning from Cape Fear in South Carolina down through Georgia). Accordingly, 

there is a gap in the middle of the species range that is only filled by the Delaware River 

population (in Pennsylvania) and the Chesapeake population. /d. at 'l[ 9; see also Recovery Plan 

at 2, 12. As NMFS has concluded, the "loss of a single shortnose sturgeon population segment 

may risk the permanent loss of unique genetic information that is critical to the survival and 

recovery of the species." Recovery Plan at 7 (emphasis added).

The Chesapeake population, however, is of particularly critical importance to the long term 

survival of the species. This is because, as NMFS itself has concluded, it is highly important to 

"re-establish minimal gene flow" between the northern and southern populations. and doing so

requires "restoring the historically continuous range of the species." /d. at 5 (emphasis 

added). The Chesapeake population-situated as it is in the center of the gap between the 

northern and southern sturgeon populations-is the population that must provide that cmcial 

genetiC"!ink between the otherwise isolated northern and southern populations. See Kynard 

Decl. at 19. Accordingly, the health of the Chesapeake population is critical to the health and 

viability of the species as a whole.

The Potomac sturgeon, in turn. is the key to fulfilling the role of the Chesapeake population in 

linking northern and southern populations. This is because the Potomac River is the only river in 

the Chesapeake population range where a permanent presence of adults year round has been 

documented. See Kynard Dec!. at !d. at !d. Indeed, aJI other instances of sturgeon in the 

Chesapeake population have been limited to sturgeon that were found in the Chesapeake itself 

and at the mouths of rivers. See Recovery Plan at 19. As such, "adverse impacts to the Potomac 

shortnose sturgeon are of grave concern to, and may well have adverse impacts on. the long term 

survival of the species.'' Kynard Decl. at 31 (emphasis added).

In the recent past, at least eight shortnose sturgeon have been caught in fishing gear in the 

Potomac. See USGS ·'Status of Shortnose Sturgeon in the Potomac River" Part I- Field Studies, 

attached hereto as Exhibit No. 22 (hereinafter "Kynard/FWS Field Study") at 3-4. From March 

2004 to July 2007, the National Park Service and the Fish and Wildlife Service commissioned a 

Field Study of the shortnose sturgeon in the Potomac, performed by Professor Boyd Kynard. !d. 

at 4. The Kynard/FWS Field Study, as well a<; other catch reports of the shortnose sturgeon in 

the Potomac, indicates that the shortnose sturgeon is a permanent resident of the Potomac River. 

Kynard Decl. at 1[27. Adults are returning year after year to an area within approximately nine 

miles of the Plant with spawning habitat in an attempt to spawn. !d. at 1[26.

As noted above, NMFS itself has previously concluded that the nine miles or so immediately 

below spawning grounds are where larval and young juvenile shortnose sturgeon reside for the 

most vulnerable first 10-12 months of life, while they grow large enough to move further 

downstream into more saline waters. See Ex. 21, September 21,2006 Correspondence between 

Julie Crocker and Karen M. Greene. It is therefore inevitable that the Potomac Plant will likely 
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injure and kill young shortnose sturgeon through entrainment and impingement, particularly at 

the larval and young juvenile life stages. Kynard Decl. at 1[28. For the reasons discussed above, 

the impact of such take is of great concern to the Potomac sturgeon generally given the slow 

maturation of the shortnose sturgeon, the fact that they do not spawn every year, and the 

imperiled status of the fish, and moreover the take of Potomac River sturgeon raises "grave 

concern[]" for the viability of the species as a whole. !d. at TJ[l7, 31.

Comment Response: 

Refer to response to DCN EPA-HQ-OW-2009-0819-3920-A16, Excerpt Number 5.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 40

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA’s quantification of improved ecosystem health; reduced risks to aquatic life from exposure 

to steam electric pollutants; and improved threatened and endangered species habitat and thus 

potential increase in threatened and endangered population is based on a series of assumptions 

that ultimately result in an underestimation. First, EPA notes, “[t]he databases used to estimate 

benefits to [threatened and endangered] species exclude all species considered threatened or 

endangered by scientific organizations but not protected by the [Endangered Species Act]. The 

magnitude of the underestimate is likely to be significant.”84 Moreover, “EPA excluded all 

species with low and moderate vulnerability potentials based upon life history traits. For all 

species with high potential vulnerability, EPA conducted further analyses to identify those 

species likely to be affected by the proposed ELGs, rather than all species whose life histories 

make them vulnerable.”85 EPA further reduces the pool of threatened and endangered species 

included in its benefits calculations. EPA’s meta‐regression analysis includes only benefits of 

threatened and endangered freshwater fish; other types of animals are either valued at zero 

dollars or excluded from any mention.86 EPA illustrates the scale of the impact of its incomplete 

analysis using the example of one species of insect, the Hine’s Emerald Dragonfly:

It is likely that population increases in [the Hine’s Emerald Dragonfly] have value to the public. 

In addition to bequest, altruistic, and existence values, dragonflies may have aesthetic or cultural 

values. Dragonflies also provide beneficial ecological services. They are voracious insectivores 

that prey on mosquitoes, flies, and other small insects. The estimated annual benefits of pest 

control attributable to insects are $4.5 billion in the United States...87

While the EPA is able to estimate a monetary value for the benefits of endangered species, they 

do so by limiting their analysis to a sub‐set of the affected species. Some of these species have an 
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obvious value to the public, including the Hine’s Emerald Dragonfly, which contributes to the 

$4.5 billion of annual benefits associated with pest control in the United States. EPA’s 

methodology omits this value.

84 Benefit‐Cost Analysis, p.5‐11 Table 5‐7.

85 Benefit‐Cost Analysis, p.5‐11, Table 5‐7.

86 Benefit‐Cost Analysis, p.5‐6, Table 5‐4.

87 Benefit‐Cost Analysis, p.5‐11, Table 5‐7.

Comment Response: 

EPA agrees with the commenter that benefits to threatened and endangered species (T&E) are 

likely underestimated given limitations in data, information and tools for estimating T&E 

benefits, but EPA disagrees that the scope of the analysis for the final rule was too narrow. EPA 

structured the scope of its T&E species benefit analysis for consistency with existing legal 

frameworks. Thus, EPA focused on ESA-listed species because steam electric power plant 

NPDES permits incorporate consideration of impacts to ESA-listed species. For this reason, EPA 

did not examine benefits to species which scientific organizations consider threatened or 

endangered, but which the ESA does not protect. Regarding the exclusion of species with

moderate or low vulnerability to changes in water quality, EPA recognizes that water quality 

issues may be important to species recovery even if not listed explicitly in species recovery 

plans, but given the uncertainty and data limitations, determined that it was reasonable to focus 

the benefit analysis on those species more likely to be affected by steam electric power plant 

discharges.

The Agency used the best monetization approach available to estimate benefits to T&E species 

from water quality improvements. This approach relies on a meta-regression valuation function 

that allows valuation of increased protection of freshwater fish, marine mammal, and bird T&E 

species. For the final rule, EPA estimated benefits to two fish species (Vermilion darter and 

Etowah darter). Lack of valuation studies prevented EPA from monetizing expected benefits of 

the final rule to amphibians (e.g., Hellbender salamander) in four states. EPA discussed these 

benefits qualitatively in the final rule analyses (see Chapter 5 in BCA).

Regarding the value the public places on the Hine’s Emerald Dragonfly, the final rule analysis 

did not identify Hine’s Emerald Dragonfly as a species whose recovery would benefit from the 

final ELGs, based on updates to the set of receiving waters affected by steam electric power 

plant discharges in the baseline (and which are expected to improve as a result of the final rule).
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29.g. Benefits – Benefits from avoided impoundment failures 

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 15

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Virginia has many reasons to support stringent limitations on effluence from power 

plants. Virginia ranks 18th in the U.S. for production of coal ash and has 25 coal ash ponds and 

11 power plants. Eight of the ponds are classified as significant hazards, meaning failure would 

cause economic and environmental damage.

Comment Response: 

EPA thanks the commenter for providing state-specific context about coal ash impoundments, 

and agrees that mitigating the risk of future impoundment failures, which can cause significant 

economic and environmental damage, is beneficial in Virginia and elsewhere.

For more on consideration of benefits in the development of the final ELGs, see response to 

DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 6.e).

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 124

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

West Virginia has more slurry impoundments than any other state in the nation. A 2011 report 

by the Office of Surface Mining Reclamation found that the walls of coal slurry impoundments 

be dangerously weak. Tests of the densities of impoundment walls show flaws in all seven sites 

surveyed in West Virginia.

Comment Response: 

The 2011 report cited by the commenter focuses on coal waste impoundments affiliated with 

coal mines in the Appalachian region, which are outside the scope of the Steam Electric 

Generating Industry ELGs. EPA agrees that impoundments failures can cause significant 
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damages, whether the impoundments are used to manage coal slurry at mines (as in the examples 

highlighted by the commenter), or to manage coal combustion residuals at 14 power plants in 

West Virginia. As discussed in Chapter 6 of the BCA, the final rule will reduce the risk posed by 

impoundments at power plants.

For more on consideration of benefits in the development of the final ELGs, see response to 

DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 6.e).

Commenter Name: Patrick O’Loughlin

Commenter Affiliation: Buckeye Power, Inc.

Document Control Number: EPA-HQ-OW-2009-0819-4183-A2

Comment Excerpt Number: 13

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

It also bears noting that surface impoundments containing ash sluice water pose a very low risk 

of structural failure. EPA's multi-year effort to inspect every ash impoundment in the country 

found no "unsatisfactory" impoundments (i.e., in imminent danger of structural failure). Those 

ranked as "poor" did so primarily due to missing records rather than structural concerns.

Comment Response: 

EPA agrees that structural failures of surface impoundments are episodic events; as detailed in 

Chapter 6 of the BCA, the historical probability of a failure is approximately 0.09 percent per 

impoundment per year for wall breaches, and 0.59 percent for other releases. However, as 

demonstrated by recent high-profile, catastrophic structural failures, including the release at 

TVA’s Kingston plant, a single failure can have very serious consequences, including very high 

cleanup costs, natural resource damages, and transaction costs. Other types of releases, which 

have historically been more frequent, can also cause environmental damages and have high 

associated cleanup, damage, and transaction costs, as evidenced in Duke Energy’s Dan River 

coal ash release in 2014, which occurred after that impoundment had been assessed.

EPA’s final CCR rule is expected to significantly reduce the future probability of impoundment 

releases. By reducing the amount of CCR handled wet in impoundments, the final ELG rule will 

help further reduce damages from potential future releases from the impoundments.

For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 

6.e).
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Commenter Name: Cari Boyce

Commenter Affiliation: Duke Energy

Document Control Number: EPA-HQ-OW-2009-0819-4305-A3

Comment Excerpt Number: 129

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA’s Assumptions and Methodology for Determining Benefits from Avoided

Impoundment Failures are Flawed

From a review of EPA’s “Benefit and Cost Analysis for the Proposed Effluent Limitations 

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

(BCA), the highest annualized benefits associated with the ELG Proposal are the avoided costs 

that result from EPA’s predicted reduction in the number of impoundment failures. The avoided 

costs in the analysis are assumed reductions in the costs that utilities would be expected to incur 

due to the fewer number of predicted structural failures of their CCR impoundments as attributed 

to operational changes at facilities resulting from the ELG Proposal. However, there are a 

number of flaws in how EPA determines these avoided costs and, subsequently, the benefits 

included in the ELG Proposal.

 Mischaracterized Changes to Utility Impoundment Management Practices

The ELG proposal does not require an existing impoundment to close, and EPA contemplates 

that impoundments will continue be used to manage “legacy” wastewater. Duke Energy will 

likely continue to use impoundments that are meeting all the ground water protection and dam 

integrity protection standards. For this scenario to occur, EPA must select the Subtitle D Prime 

option under the CCR rule, as Duke Energy recommended above. Duke Energy may need to 

continue to operate surface impoundments for the function as a wastewater treatment system, for 

operational processes and/or for management of low volume wastestreams such as stormwater, 

leachate and coal pile runoff, even if no new CCRs are sent to them. Therefore, the continued use 

of these ponds is necessary since they are an integral part of the wastewater treatment systems 

used to manage the facility’s ancillary wastewaters.

EPA maintains that the benefits from “operational changes prompted by compliance with the 

ELG Proposal that may cause some utilities to reduce their reliance on impoundments to handle 

their waste.”111EPA assumes that there will be a reduction in reliance on impoundments which 

will reduce the total number and total storage capacity of impoundments in service. EPA 

concludes that this reduction will in turn diminish the “number of structural failure events” that 

would then require industry to expend significant dollars on cleanup and damage costs. EPA 

calculated the avoided cost benefits to range from $52.2 million to $295.1 million on an 

annualized basis depending on the regulatory options included in the ELG Proposal. In 

estimating this range of expected benefits, the Agency makes a number of assumptions and 

extrapolations that overestimates the avoided costs of reduced impoundment failures and creates 

an unrealistic economic benefit from compliance with the ELG Proposal.
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Duke Energy agrees with the analysis conducted by USWAG112 that points out that EPA inflated 

the benefits in the ELG Proposal for avoided impoundment failures. The USWAG analysis is 

significantly more detailed, but the major points will be summarized below. The EPA Benefit 

and Cost Analysis assumes that these impoundments will close and excludes the capacity of all 

these “closed” units. This assumption is at odds with the structure of the ELG Proposal, which in 

fact contemplates the continued operation of these impoundments for certain wastewaters and 

therefore overstates the avoided costs and benefits associated with fewer potential impoundment 

failures.

For impoundments slated to be “partially closed,” EPA identifies a key supposition that while the 

reduction in flow entering the impoundment will not necessarily decrease the size of the 

impoundment, the impoundment will receive less combustion residuals and therefore, will be 

less likely to have a breach of the impoundment. There are no analyses or background data to 

justify this assumption, and Duke Energy believes it is invalid. Surface impoundments no longer 

receiving CCR transport water will continue to receive other low volume wastewaters and will 

control the water level in the impoundment to the same design elevation prior to discharging 

through its outfall, no different from when the impoundment was receiving CCR transport water. 

An impoundment failure is not related to the volume, flow, or density of the receiving 

wastewaters. It is generally the result of an equipment failure or the structural failure of a berm, 

dike, or dam due to the lack of proper construction or maintenance. EPA’s rationale that assumes 

a reduction in the flow rate, associated with the operation of the impoundment or the amount of 

solids (CCR) in the wastewaters that are discharged into an impoundment, will result in fewer 

structural failures of impoundments is flawed. Duke Energy is not in a position to provide our 

own analysis of the actual cost impact adjustment needed due to the flawed assumptions EPA 

used in determining the projected number of impoundment closures, since the report that 

includes the necessary details for recalculation was not included in the docket.

 EPA Overstates the Rate at which Impoundments Fail

The chapter in EPA’s Benefit and Cost Analysis113 that estimates the avoided costs of 

impoundment failures begins with a calculation of the probability of impoundment failures based 

on historic trends. It bases this calculation on an EPA Office of Resource Conservation and 

Recovery (“ORCR”) survey of impoundments whereby plant owners and operators were asked if 

they had any releases from their 

impoundments during the period of 2000 through 2009 from a total of 726 

impoundments. This survey was specific to the utility industry and facilities that manage CCR 

in impoundments. The surveyed utilities reported 38 releases over 10 years during the requested 

time period and 4 other releases that actually occurred in the five years prior to the requested 

period. EPA divided the number of total releases across all the years reported by the industry and 

determined a failure rate of 0.58%.

In the analysis, the Agency confuses a spill or release from an impoundment with the concept of 

a structural failure. In fact, several releases included in these survey results are summarized on 

ORCR’s spreadsheet included in the docket. This summary indicates that some of these releases 

were captured by pumps, did not leave the permitted area of the impoundment and were very 

limited in volume released. EPA should only consider failures requiring the significant 
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expenditure of resources for response and cleanup activities that triggered cleanup obligations in 

determining a failure rate. EPA describes impoundment “failures” as those for which a 

significant portion of a dam fails, causing a significant release impacting many entities. 

However, EPA’s calculation of the impoundment failure rate includes these very small 

“releases” that clearly do not constitute impoundment “failures”. The Agency provides no 

explanation why the extrapolation of the cost benefit from preventing a catastrophic berm failure 

is appropriate to assume the same cost benefit for the total of modeled failures that were 

calculated based on the number of spills, some of which were very small releases, as reported in 

the ELG ICR survey. Most of the spills reported in the survey did not have details of the actual 

duration and volume of the release and they cannot be assumed to be similar to the failures of the 

CCR-containing impoundments identified by ORCR.

In 2009, after TVA’s Kingston event, ORCR sent out an Information Collection Request that 

was sent to all utilities to identify all surface impoundments that were used to manage or store 

CCR. Based on the information collected, EPA hired an engineering consultant with dam 

integrity experience to inspect all of Duke Energy’s surface impoundments that were managing 

CCR. Duke Energy did not receive any unsatisfactory inspection reports. In fact, EPA did not 

find a single impoundment in the country that could be rated as unsatisfactory out of the 374 

units inspected. An unsatisfactory rating meant there was evidence that would indicate the 

potential for a berm or dam failure. The majority of EPA’s inspections conducted on Duke 

Energy’s surface impoundments resulted in the issuance of a satisfactory rating (the highest 

rating issued for an inspection). The few “poor” inspection ratings that Duke Energy received 

were from the lack of documentation of the stability analysis conducted during design of the 

impoundments decades prior. Subsequently, the missing analyses were all reproduced and any of 

the minor inspection requirements noted by the inspectors were completed in a timely manner.

Duke Energy has a comprehensive maintenance program for all surface impoundments to 

maintain structural integrity, which was in place even before the EPA inspections were 

conducted. These maintenance programs include routine inspections along with inspections 

performed by PE-licensed consulting engineers (i.e. certified Professional Engineers). When the 

TVA collapse occurred, the entire industry reviewed their inspection and maintenance programs 

and improved them as required to reduce the risk of another failure. The probability of an 

impoundment failure today, even without the additional regulation to be implemented, is greatly 

reduced. These benefits, however, do not come from the ELG prohibition of discharging 

transport water, but from properly operating, inspecting, and maintaining berms, dikes, and dams 

of the surface impoundments used to manage CCR and other wastewaters. Duke Energy, 

therefore, recommends that EPA reevaluate this flawed approach which overstates the 

probability of future impoundment failures.

 EPA Overestimates the Capacity for Typical Discharges by Relying on the Details 

Reported from only a Few Impoundment Release Events

The Agency assumes that each spill included in the survey required cleanup costs, transaction 

costs, and natural resource damage costs and that these costs would be avoided if the 

impoundment were closed, pursuant to the implementation of the ELG Proposal. It is highly 

unlikely that the magnitude of costs assumed by EPA would be incurred by the utilities for the 
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modeled number of spills in the analysis. EPA developed their value of the cost benefit for spills 

that will not occur if the ELG Proposal is implemented, from the 42 total spills reported in the 

ICR. Of the 42 spills reported, only 15 included detailed information about the spills. Since 

companies were not required to disclose spill volume, many companies did not include this 

information.

It is likely that utility companies did not report the volume for minor leaks and seepage due to 

the difficulty in determining the volume released as compared to the size of the impoundment or 

the flow emitting from the NPDES permitted outfall. A review of ORCR’s spreadsheet confirms 

this assertion since the other 27 spills, for which volume was not reported, described minor 

seepage, limited quantities of materials leaking, or minor NPDES permit limitation exceedances. 

These 27 minor spills are unlike the large capacity spills for which more detailed information 

was reported, such as the Martin’s Creek and Kingston events. For EPA to take the 15 spills with 

more detailed information and extrapolate them directly to the remaining 27 minor spills, for 

which data on capacity was not known, is a flawed methodology. This position assumes that two 

additional spills similar to the Kingston event and another two other spills similar to the Martin’s 

Creek release would have occurred in the U.S. over the last 10 years.

Duke Energy contends that EPA should not use this flawed methodology for calculating the cost 

benefit since it leads to a significant overestimation of the likelihood of a significant spill 

occurring. It also ignores the extensive efforts that Duke Energy and other electric utilities have 

taken to ensure that spills of this sort will not occur in the future.

 EPA’s Cost Sources and Estimates Are Inapplicable to CCR Impoundments

EPA calculates the costs associated with each of these impoundment failures in terms of cleanup, 

natural resources damages, and transaction costs.114 The problem with this analysis is that the 

studies on costs from which EPA draws its model do not fairly represent the types of damages or 

costs typically associated with spills from surface impoundments with CCR. This factor alone 

significantly overestimates the avoided costs of the ELG proposal.

The first cost component is the “cleanup costs.” EPA identified three historical cleanup costs for 

impoundment failures, including the two largest spill cleanups in recent history, Martin’s Creek 

and Kingston. Using these two spills as sources of cost data will certainly overestimate the costs 

associated with cleanup because of the complexity of the remediation and significant off-site 

disposal costs associated with these events. Since this estimation is such a significant component 

of the BCA, Duke Energy strongly encourages EPA to revisit this calculation by at least 

examining more representative spills and cleanup costs. Rather than address the avoided costs of 

impoundment failures on a per-gallon spilled basis, we strongly encourage EPA to assess 

representative spill costs for typical CCR impoundment spills rather than exclusively relying on 

large capacity spills, which will result in a more representative avoided cost.

The second component of the cost estimate is the “Natural Resource Damages” (NRD) 

component in which EPA relies on a study that looked at prominent NRD cases from oil and 

chemical spills, among other incidents. EPA should identify specific NRD costs associated with 

CCR impoundment spills for use in these calculations instead of using costs from spills derived 
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from other unrelated industrial events that pose very different risks. EPA also makes no attempt 

to identify cost data associated with less prominent spills, which are more typical of CCR 

impoundment releases.

The third component of the cost estimates involve “Transaction Costs”, where EPA relies on 

studies that summarize these costs as a share of Superfund spending. The source of this data is 

very troubling and has very little relevance to releases from CCR impoundments. CCR 

impoundment releases are typically identified as coming from only one possible source, which is 

not the case in the examples EPA uses. Also, CCR impoundment spills generally are identified 

immediately and remediated before contamination spreads widely. Superfund cleanups are 

seldom, if ever, triggered by CCR releases. Using Superfund cases in this way wildly inflates the 

estimated costs to address releases from CCR impoundments.

In summary, the portion of the BCA that calculates the avoided costs of impoundment failures 

relies very heavily on the two most significant CCR impoundment release events in U.S. history. 

The BCA also relies on flawed assumptions related to the probability of impoundment closures 

and it overinflates the costs associated with predicted failures. Duke Energy urges EPA to 

reevaluate these costs and benefits using a broader range of spill costs and realistic failure 

scenarios that do not rely on only the worst case scenarios and costs. Duke Energy also suggests 

that EPA include in its closure projections a more accurate representation of the number of 

wastestreams managed in impoundments, as well as, the likelihood that these impoundments 

would remain open regardless of whether CCR wastestreams can continue to be managed in 

them. These revised projections will provide a more representative and realistic estimate of the 

avoided costs of impoundment failures likely to be realized through this rulemaking.

111 78 Fed. Reg. at 34516

112 See Utility Solid Waste Activities Group comments submitted on September 20, 

2013. Section 6 -EPA inflates the Benefits from the ELG Proposal on Avoided impoundment 

failures.

113 Benefit and Cost Analysis (BCA) for the Proposed Effluent Limitations Guidelines and 

Standards for Steam Electric Power Generating Point Source Category, April 2013, Section 7.1 -

Benefits from Avoided Impoundment Failures [EPA-821-R-13-004]

114 See BCA 7-2 [EPA-821-R-13-004]

Comment Response: 

EPA disagrees with the commenter’s assertion that assumptions and methodologies to estimate 

the benefits from avoided impoundment failures are flawed. While EPA recognizes limitations in 

the data available to support analysis of the final rule, the assumptions and methodology are 

reasonable to inform understanding of the potential impacts of impoundment failures, and 
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benefits from avoiding or reducing future releases. We provide specific response to the issues 

raised by the commenter below.

First, the commenter expresses concerns that EPA “mischaracterized changes to utility 

impoundment management practices” by assuming that plant owners would close their 

impoundments. EPA notes that this statement reveals a misunderstanding of EPA’s assumptions 

and methodology. In the impoundment analysis, EPA does not assume that all impoundments 

would close as a result of the ELGs, but instead assumes that plants would reduce the amount of 

coal combustion residues handled wet and therefore stored in impoundments. This will in turn 

reduce the amount of CCR that may be involved in the event of an impoundment release.

The commenter states that EPA assumes that “the impoundment will receive less combustion 

residuals and therefore, will be less likely to have a breach of the impoundment.” This is not an 

accurate depiction of EPA’s analysis; EPA does not assume that decreasing the size of 

impoundments will reduce the probability of an impoundment breach. Instead, EPA assumed a 

constant rate of failure across impoundments under the baseline and post-compliance scenarios. 

However, EPA did assume that reducing the amount of ash stored in a given impoundment will 

reduce the volume that accumulates in the impoundment over time, and that may be released in 

the event of a release. EPA accordingly estimated lower expected costs for the same number of 

future releases due to reduced CCR volumes involved. Additionally, for the final rule, EPA 

further improved this analysis by calculating release rates separately for large impoundments and 

small impoundments for two types of failures, and calculating probabilities and capacity factors 

within those groups.

Next, the commenter notes that EPA “overstates the rate at which impoundments fail” and 

“overestimates the capacity for typical discharges by relying on the details reported from only a 

few impoundment release events.” EPA agrees that the size of, and damages associated with, 

impoundment releases tend to be very different for catastrophic structural failures, such as wall 

breaches, versus other releases. For the analysis of the final rule, EPA revised the analysis of 

failure probabilities and capacity factors (i.e., the amount of CCR released as a percent of 

impoundment capacity) by distinguishing between wall breaches and other types of events (see 

Chapter 6 in BCA).

The commenter describes the proposed rule analysis to imply that EPA assumed that the costs 

would be equivalent for all release types and sizes. This mischaracterizes EPA’s methodology. 

EPA applies per-gallon cleanup costs and smaller releases therefore have proportionally smaller 

costs associated with them. For the final rule analysis, EPA continued to use a per-gallon cleanup 

cost to estimate the costs associated with different size releases, but revised the costs to 

incorporate more recent publicly available data. See Section 6 of the BCA for more details.

EPA does not agree with the commenter’s assertion that the Agency “should only consider 

failures requiring the significant expenditure of resources for response and cleanup activities that 

triggered cleanup obligations in determining a failure rate.” Smaller expenditures may also be 

avoided through implementation of the ELGs. Aggregated across many releases, the avoided 

costs of small releases may be significant.
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EPA appreciates that Duke Energy and other companies have inspected and performed 

maintenance on CCR impoundments in the aftermath of the TVA Kingston release. However, as 

clearly apparent by Duke Energy’s Dan River release (see Section 6 of the final BCA for more 

discussion of this incident), these inspections do not prevent all releases. TVA had also 

conducted inspections of their impoundment at the Kingston Fossil plant before the dike's 

catastrophic failure. EPA’s analysis of the final CCR rule recognizes that inspections cannot 

entirely eliminate the risk of future releases, relative to historical rates, as while the probability 

of such future releases is lower post-compliance, it is not zero. EPA used the remaining, postcompliance probability of failures from the CCR rule analysis as baseline for the final ELG rule 

analysis.

With regard to NRD, the commenter notes that “cost sources and estimates are inapplicable to 

CCR impoundments.” There is little publicly available data on NRD arising from CCR releases, 

and EPA therefore used historical NRD assessed for a variety of spills to estimate the NRD 

arising from CCR releases to the environment. EPA notes that the magnitude of NRD is likely to 

be a function of the resources impacted by a release, even if materials differ. To address the 

commenters concerns that CCR impoundment damages are substantively different from damages 

in certain NRD cases, EPA revised the data used to develop NRD assumptions to exclude 

damages from legacy releases or releases to resources (e.g., marine waters) unlikely to be 

affected by an impoundment release.

Lastly, with regard to transaction costs, EPA disagrees that the Agency’s assumptions are based 

on data that are not relevant to this application. Searches to identify data specific to transaction 

costs incurred as a result of coal ash impoundment releases yielded no such data in public 

records. EPA determined that data from Superfund cases were the best available indicators of the 

transaction costs associated with impoundment failures since they provide insight into the typical 

types of costs that may arise from releases and other environmental damages. These costs may 

include negotiating natural resource damage payments, determining responsibility among parties 

(i.e., the utility owner or the insurer), and litigating details regarding settlements and 

remediation. These activities are relevant to the resolution of impoundment releases, as 

exemplified by the significant costs TVA incurred following the Kingston spill to address claims 

by neighboring property owners.

Regarding the commenter’s request that EPA reevaluate the number of wastestreams managed in 

impoundments as well as the likelihood that these impoundments would remain open, see the 

Agency’s response to DCN EPA-HQ-OW-2009-0819-4652-A1, Excerpt Number 20 (in 

comment code 6.f).

Commenter Name: Quinlan J. Shea III

Commenter Affiliation: Edison Electric Institute (EEI)

Document Control Number: EPA-HQ-OW-2009-0819-4487-A1

Comment Excerpt Number: 130

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

In another example, EPA’s estimate of benefits attributable to reduced impoundment failure, 

which make up 37-58% of the total benefits attributed to the proposed ELG (for options 3 and 4 

where air benefits estimates are provided), is likely overestimated as a result of compounded 

flaws on EPA’s unit cost and failure probabilities. Gradient Report at 35

Comment Response: 

EPA disagrees that the analysis of benefits of reduced impoundment failures is flawed, resulting 

in an overestimate of the rule benefits. For responses to the more specific comments about the 

Agency’s methods, see responses to related comments (e.g., DCN EPA-HQ-OW-2009-0819-

4655, Excerpt Number 190; EPA-HQ-OW-2009-0819-4305-A3, Excerpt Number 129).

For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number Number 3 (in Comment 

Code 6.e).

Commenter Name: Cathy S. Woollums

Commenter Affiliation: MidAmerican Energy Holdings Company

Document Control Number: EPA-HQ-OW-2009-0819-4495-A1

Comment Excerpt Number: 46

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

 When estimating benefits by avoiding impoundment failures EPA did not account for 

current best management practices and actions undertaken to assess and improve 

structural integrity in light of the 2007 Kingston incident, resulting in an inflated 

probability of impoundment failures.

Comment Response: 

EPA acknowledges that the industry has inspected and performed maintenance on CCR 

impoundments in the aftermath of the TVA Kingston release, and that these actions may reduce 

the future failure probability. However, as clearly apparent by Duke Energy’s Dan River release 

(see Section 6 of the BCA for more discussion of this incident), these inspections do not prevent 

all releases. Inspections and other best practices required by the CCR rule are expected to reduce 

the future probability of impoundment failures. The baseline for the final ELG rule analysis 

assumes compliance with the CCR rule, and the probability of impoundment failures therefore 

accounts for the required inspections and best practices. Chapter 6 of the BCA describes the 

analysis.
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For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 

6.e).

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 20

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA’s calculated societal benefit for avoided pond failures is based on a subset of available data 

that represents different types of releases and imparts a significant bias to large releases, and 

costs are also based on large releases while most releases are relatively small.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Numbers 100 and 101 for 

specific issues raised by the commenter.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 100

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

13 CALCULATED BENEFITS FROM AVOIDED POND FAILURES

EPA based its benefits analysis on avoided costs associated with reduced potential for coal 

combustion residual (CCR) pond failures. The benefits calculation estimated the probability and 

size of future pond failures, and avoided costs associated with clean-up, natural resource damage, 

and transactions.

13.1 EPA estimates spill size and spill probability based on a subset of available 

data that represent different types of release and impart a significant bias to 

large releases
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EPA identified 42 releases over a 15-year period, and then estimated a capacity factor by 

calculating the ratio of release size to impoundment capacity. The capacity factor was calculated 

for 15 of the 42 sites for which EPA had both release volume and pond capacity data. The 

average capacity factor (6.45% of impoundment capacity) was then assumed to be representative 

of all 42 releases. The 2010 Regulatory Impact Assessment (RIA) for the proposed CCR disposal 

rule [EPA, 2010] was cited as the source of the release volume and impoundment capacity data.

Release volumes for the 15 reported releases span a range of more than 8 orders of magnitude, 

from 50 gallons to 1.1 billion gallons. More than half of the releases (9 of 15) were less than 

15,000 gallons, 5 were between 6 million and 100 million gallons, and 1 was greater than 1 

billion gallons (Figure 13-1). EPA recognized this wide range and uneven distribution in the 

2010 RIA, breaking the data into three groups: releases of 1 billion gallons or more (termed 

catastrophic failures), releases between 1 million and 100 million gallons (termed significant 

failures), and releases of less than 1 million gallons (termed seepage failures). For the seepage 

failures, EPA stated,

“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...” [EPA, 2010, page 136]

The 9 small releases in this grouping are all well below the 1-million-gallon threshold and 

represent small releases that are fundamentally different from large facility failures. Combining 

these small releases with the large failures to generate an average release behavior is 

inappropriate. The skew in the dataset is made apparent by comparing the mean (85 million 

gallons) and median (5,000 gallons) releases. Moreover, it is likely that most of the 27 releases 

with no reported volumes were small releases that did not constitute significant containment 

failures, and therefore had limited data available.

EPA assumes a uniform failure rate across all impoundments. Given the different types of 

release described above—ranging from small seepages to the catastrophic containment failure at 

TVA’s Kingston facility—along with the known variations in site setting, design, and operation, 

a uniform failure rate across all impoundments is unlikely. EPA has site-specific inspection data 

on facility engineering that could be used to better determine the distribution of relative risk of 

failure for the facilities, rather than simply assuming all facilities have the same probability of 

failure.

EPA also assumes that the pond failure rate after 2018 will return to its pre-2010 rate. This 

assumption, as EPA acknowledges, is questionable because it ignores improvements in 

engineering, impacts of the impending CCR rule, increased regulatory and public scrutiny, and 

planned plant closures that preferentially affect older plants (and presumably higher-risk ponds). 

All of these will mitigate future failure risk, even in the absence of the ELG rule.

EPA’s on-site structural stability assessment reports should be used—along with knowledge of 

changes within the industry on engineering practices, the CCR rule, and plant closures—to 

develop a better estimate of the probability of future spills, rather than assuming it will be the 

same for all sites as the historical probability.
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Comment Response: 

EPA used available historical data to calculate average release rates and capacity factors (i.e., the 

amount released as a percent of impoundment capacity) for use in the analysis, and adjusted 

future release probabilities to reflect the effects of the final CCR rule in estimating the 

incremental benefits of the final ELG rule. EPA acknowledges the possibility that releases for 

which volume data was not provided may have smaller volume than those for which the release 

volume was provided in the OCRC survey responses, but notes that there is no evidence that the 

volume data is skewed toward smaller or larger releases. Further, EPA found no evidence that 

the historical release data derived from the ORCR survey is fundamentally different than the 

types of releases that would be associated with impoundments at power plants to which the rule 

applies, and no evidence that missing data skews the estimates toward smaller or larger releases.

To address concerns associated with applying assumptions uniformly across all releases, EPA 

revised the impoundment analysis for the final rule based on the approach used for the final CCR 

rule, notably by estimating release rates and capacity factors separately for structural failures 

(e.g., wall breaches) and other types of releases, and for big vs. small impoundments. 

The revisions incorporate several of elements suggested by the commenter, including the effects 

of the CCR rule and plant closures. See Chapter 6 of the BCA for more details on the 

impoundment failure analysis.
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For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 

6.e). For additional information on the future probability of impoundment failures, see response 

to DCN EPA-HQ-OW-2009-0819-4495-A1, Excerpt Number 46.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 101

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

13.2 EPA estimates of cleanup costs are based on the largest releases, while most 

releases are relatively small

EPA based their cleanup costs on the average of only two large CCR releases (Kingston CCR 

site and Martin’s Creek CCR site) and one large coal slurry pond (Massey site). In the 2010 RIA, 

EPA characterized the Kingston and Martin’s Creek costs as,

“...[three] of the most significant and recent release cases (i.e., cases resulting in the most 

gallons released).”1[EPA, 2010]

There is no reason to believe that costs for these three spills are representative of the other 40 

CCR spills. As previously noted, most of the other releases were as much as 8 orders of 

magnitude smaller than the Kingston and Martin’s Creek releases; these other releases likely 

incurred minimal cleanup costs. EPA presents no data to support the assumption that smaller 

spills will have a cost structure similar to that of these very large spills. For the three large spills 

alone, the cost range varies by a factor of 5 ($0.22/gal to $1.15/gal); we would expect that the 

cost factors for much smaller spills would significantly extend the lower end of that range. In 

addition, there is an implicit assumption in the avoided cost calculation that there are no risks 

associated with prematurely closing an active pond, and the construction and operation of a 

replacement facility.

1 The third site from the 2010 RIA, Widows Creek, was not included in the ELG cleanup cost 

calculation. It is not clear why Widows Creek was excluded from this analysis while Massey 

Coal Slurry Pond was added.

Comment Response: 
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The commenter does not provide a basis for his/her assertion that “cost factors for much smaller 

spills would significantly extend the lower end of [the range of cleanup costs],” or explain how 

the cost structure would differ between large and small spills. EPA found no evidence that the 

unit costs associated with smaller releases would be meaningfully smaller than those associated 

with releases for which costs are available.

EPA derived reasonable estimates of the unit cost of cleaning releases using the available data. 

For the final rule analysis, EPA updated cost assumptions to incorporate more recent data from 

public records. The final analysis includes data for five historical impoundment failures: the 

three used in the proposed rule analysis, plus the Widows Creek release and the 2011 Oak Creek 

release in Wisconsin. These data show that, contrary to the commenter’s assertion, comparably 

smaller releases such as the Oak Creek release in Wisconsin (see Chapter 6 of the BCA for

discussion of this incident) can result in higher per gallon costs than larger releases such as the 

Kingston release. Chapter 6 of the BCA describes this analysis.

Regarding the commenter’s concern that the avoided cost calculation does not account for risks 

from prematurely closing an active ponds or the cost of a replacement facility, EPA notes:

1) The ELGs do not require closure of the impoundments. EPA’s analysis of avoided costs 

accordingly focuses on the changes in the amount of CCR managed in the impoundments rather 

than assumes that the impoundment will close.

2) EPA does not have data on any increase in risks from prematurely closing active ponds, or 

perhaps more relevant for the ELG analysis, any increase in risk from reducing the amount of 

CCR managed in the ponds. The commenter did not provide such information.

3) It is unclear what “replacement facility” the commenter is referring to. EPA notes that the 

costs of the final ELGs include the capital and O&M costs for systems and equipment that would 

be implemented by facilities currently using impoundments to manage their CCR and would be 

expected to convert to dry ash handling. It would not be appropriate to also include these costs 

into the benefit column.

For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 

6.e).

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 102

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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13.3 No justification is presented for applying Superfund transaction costs to 

CCR pond cleanup costs

Transaction costs were estimated based on cleanup costs at Superfund sites; these costs represent 

over 25% of the estimated benefits in the ELG rule. Transaction costs at Superfund sites are 

typically associated with litigation to determine the liabilities of multiple potentially responsible 

parties (PRPs). Because CCR ponds are located on or near power plant property and typically do 

not have multiple PRPs, the transaction actions would be expected to be significantly lower or 

negligible. EPA should either eliminate the transaction costs from the avoided cost calculation, 

or provide justification for including typical Superfund transaction fees in the benefits 

assessment for CCR ponds.

Comment Response: 

EPA disagrees that it should eliminate transaction costs from the avoided cost calculation, as 

suggested by the commenter. Data from Superfund cases provide insight in the types of costs that 

arise from releases and other environmental damages. These costs may include negotiating 

natural resource damage payments, determining responsibility among parties (i.e., the utility 

owner or the insurer), and litigating details regarding settlements and remediation. These 

activities are relevant to the resolution of impoundment releases. Searches to identify data 

specific to transaction costs incurred as a result of coal ash impoundment releases yielded no 

such data in public records. As such, EPA determined that data from Superfund cases represent 

the best available indicators of transaction costs associated with impoundment failures. Based on 

data from these cases together with historical data on cleanup costs and natural resource 

damages, EPA estimated that, on average, transaction costs represent 26 percent of the costs 

associated with a spill. For more details, see Section 6.1 of the BCA.

For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 

6.e).

Commenter Name: James R. Roewer

Commenter Affiliation: Utility Solid Waste Activities Group (USWAG)

Document Control Number: EPA-HQ-OW-2009-0819-4652-A1

Comment Excerpt Number: 7

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Finally, Section VI reviews EPA’s Benefit and Cost Analysis” (“BCA”) for a portion of the ELG 

Proposal and identifies multiple and compounding erroneous assumptions in the BCA that lead it 

to drastically inflate the benefits of the ELG Proposal with respect to avoided CCR impoundment 

failures.
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Comment Response: 

EPA disagrees that the benefits associated with avoided CCR impoundment releases are 

drastically inflated. See responses to the related comments about the Agency’s methods in EPAHQ-OW-2009-0819-4652-A1 (excerpts 21, 22, and 23).

Commenter Name: James R. Roewer

Commenter Affiliation: Utility Solid Waste Activities Group (USWAG)

Document Control Number: EPA-HQ-OW-2009-0819-4652-A1

Comment Excerpt Number: 19

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

VI. EPA DRASTICALLY INFLATES THE BENEFITS FROM THE ELG 

PROPOSAL ON AVOIDED IMPOUNDMENT FAILURES

According to EPA’s “Benefit and Cost Analysis for the Proposed Effluent Limitations 

Guidelines and Standards for the Steam Electric Power Generating Point Source 

Category” (“BCA”), the highest annualized benefits associated with the proposed ELGs are the 

avoided costs that result from the reduced number of impoundment failures. Id. at 10-2. These 

purportedly avoided costs are reductions in the costs that utilities would incur due to the fewer 

number of structural failures of their CCR impoundments attributable to facility operational 

changes driven by the proposed ELGs.

EPA maintains that these benefits originate from “operational changes prompted by compliance 

with the proposed ELGs [that] may cause some plant owners to reduce their reliance on 

impoundments to handle their waste.” 78 Fed. Reg. at 34516. This reduction in reliance on 

impoundments is expected to reduce the number and capacities of impoundments in service, 

which will, in turn, reduce the “number of structural failure events” which require industry to 

expend significant sums on cleanup and damage costs. Id. EPA calculated that these avoided 

cost benefits will range from $52.2 million to $295.1 million on an annualized basis depending 

on the regulatory option that the Agency decides to adopt through this rulemaking and the 

relative applicable discount rate. Id. In estimating this range of expected benefits, the Agency 

makes a number of assumptions and extrapolations that vastly overestimate the avoided costs of 

reduced impoundment failures and create an unrealistic picture of the likely actual economic 

impacts of the ELGs. As discussed below, these errors include:

 Overestimating the likelihood that CCR surface impoundments will close,

 Mischaracterizing changes to utility management practices,

 Overstating the rate at which impoundments “fail,”

 Overestimating the capacity for typical discharges by over relying on very few 

impoundment failures, and
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 Calculating likely costs by relying on extreme cost scenarios and evidence unrelated to 

typical CCR impoundment spills.

Comment Response: 

EPA disagrees that the avoided impoundment failure analysis vastly overestimates the avoided 

costs and creates an unrealistic picture of the likely actual economic impacts of the ELG. For 

responses to specific comments about the Agency’s methods, see responses to comment EPAHQ-OW-2009-0819-4652-A1 (excerpts 21, 22, and 23).

For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 

6.e).

Commenter Name: James R. Roewer

Commenter Affiliation: Utility Solid Waste Activities Group (USWAG)

Document Control Number: EPA-HQ-OW-2009-0819-4652-A1

Comment Excerpt Number: 21

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

B. EPA Mischaracterizes the Recent Changes to Utility Management Practices

Following the Kingston release, owners and operators of CCR impoundments took determined 

steps to ensure that no similar spill would take place elsewhere. The spill itself increased 

awareness of the issue among industry and the public. Following these steps conducted by 

utilities, EPA also conducted a series of extensive assessments of the structural integrity of CCR 

surface impoundments throughout the country. These assessments did not identify a single 

unsatisfactory CCR impoundment. See EPA Website at

http://www.epa.gov/osw/nonhaz/industrial/special/fossil/surveys2/index.htm (last viewed on 

Sept. 12 2013). In fact, the vast majority of the deficiencies noted by the Agency and its 

representatives related to a lack of original paperwork for these facilities and very few significant 

structural issues. Utilities were required to develop and implement action plans to address all of 

the Agency’s findings, which, again, mainly involved a lack of original paperwork.

In its analysis of the significant avoided costs associated with impoundment failures that will be 

realized through the promulgation of the ELGs, EPA assumes that these structural assessments 

will reduce the failure rate from impoundments to zero until 2019 at which time the failure rate 

will return to its 2000 to 2009 baseline. BCA at 7-2. Underlying this assumption is the 

Agency’s implicit assertion that utilities will take measures to rectify significant concerns with 

impoundments, but only in the short term. By 2019, according the BCA, utilities will have 
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completely forgotten the lessons from the Kingston spill and will revert to a less careful 

approach to impoundment safety.

This assumption also completely ignores the actual findings of the assessments that primarily 

found a lack of original paperwork. The resolution of this concern will normally require a 

detailed structural evaluation by the utility and the development of engineering drawings and 

studies of the impoundments. These actions will typically address EPA’s finding in both the 

short and the long term and it is very unlikely that these companies will need to conduct a similar 

effort in the future. EPA’s assumption in the BCA undervalues the utilities’ attention to the 

structural integrity of their impoundments and mischaracterizes the findings of EPA’s own 

structural integrity assessments.

Comment Response: 

EPA appreciates that the industry has inspected and performed maintenance on CCR 

impoundments in the aftermath of the TVA Kingston release, and that these actions may reduce 

the future failure probability. These inspections do not prevent all releases and in the absence of 

more regulation governing the impoundments, future releases would be expected to occur. This 

is evidenced by the coal ash release into the Dan River in February 2014, despite regular 

inspections and after completion of an inspection that found the site to be well maintained and in 

good working order (see Final Report: CCW Impoundment Inspection Report, Dan River Steam 

Station Rockingham County, North Carolina; submitted to EPA in September 2009).

EPA’s analysis for the final CCR rule (U.S. EPA, 2014) recognizes that inspections cannot 

entirely eliminate the risk of future releases, relative to historical rates, as while the probability 

of such future releases is lower post-compliance, it is not zero. EPA accounted for the effects of 

the inspections and best practices required in the CCR rule in the baseline for the final ELG in 

assuming a residual, post-compliance probability of failures. For more details, see Chapter 6 of 

the BCA for the final rule.

For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 

6.e).

References:

United States Environmental Protection Agency (U.S. EPA). 2014. Regulatory Impact Analysis 

for EPA’s 2015 RCRA Final Rule Regulating Coal Combustion Residue (CCR) Landfills and 

Surface Impoundments at Coal-Fired Electric Utility Power Plants.

Commenter Name: James R. Roewer

Commenter Affiliation: Utility Solid Waste Activities Group (USWAG)

Document Control Number: EPA-HQ-OW-2009-0819-4652-A1

Comment Excerpt Number: 22
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External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

C. EPA’s Assessed Benefits from Avoided Impoundment Failures Overstates the 

Likelihood and Size of these Failures

EPA’s chapter in the BCA that estimates the avoided costs of impoundment failures begins with 

a calculation of the probability of impoundment failures based on historic trends. BCA at 7-1. It 

bases this calculation on an EPA Office of Resource Conservation and Recovery (“ORCR”) 

survey of impoundments whereby plant owners and operators were asked if they had any 

releases from their impoundments during the period of 2000 through 2009 from a total of 726 

impoundments. This survey was aimed at utility facilities that managed CCRs in impoundments, 

and were accordingly subject to ORCR jurisdiction. These surveyed facilities reported 38 

“releases” for the 10 years surveyed and 4 facilities reported “releases” that actually occurred in 

the five years prior to the surveyed period. EPA divided the number of total releases across all 

the years reported by the impoundments to determine a failure rate of .58%. Id.

While this method seems unobjectionable on its face, this analysis confuses several issues. The 

Agency conflates “release” with the concept of impoundment failure. In fact several releases 

captured by these survey results and summarized on ORCR’s spreadsheet 

at http://www.epa.gov/osw/nonhaz/industrial/special/fossil/surveys/survey_database_041212.xls

x (last viewed on June 24, 2013) indicate that some of these releases were captured by pumps, 

did not leave the permitted area of the impoundment, or were otherwise very limited in 

scope. EPA needs to ensure that what it considers failures requiring significant expenditure of 

resources for response and cleanup activities actually would have triggered cleanup 

obligations. While the Agency appears to be indicating that impoundment “failures” are those 

for which a significant portion of a dam fails causing a significant release impacting many 

entities, its calculation of the impoundment failure rate includes small “releases” that clearly do 

not constitute impoundment “failures.”

EPA next extrapolates this failure rate to calculate the expected number of releases for the 

universe of 1070 impoundments that the Office of Water has identified. The Agency does not 

provide any analysis for why this extrapolation is at all appropriate or identify how these 

impoundments might be similar to the CCR-containing impoundments identified by ORCR. It 

can be assumed that the 344 impoundments identified by the Office of Water but not included in 

the ORCR survey pose a lesser degree of risk or contain substantially less quantities of CCR 

because they were neither identified by ORCR nor included in that office’s comprehensive 

survey. EPA makes a direct extrapolation from the surveyed units to the non-surveyed units 

without regard to whether the capacity or risks associated with these units are similar.

Our understanding is that the 344 additional impoundments include wastewater ash storage 

ponds, low volume waste ponds with limited CCR disposal, and stormwater ponds. These ponds 

are very different from the impoundments included in the ORCR survey and pose significantly 

lower risks than the bulk of the ponds in the survey. These ponds are often very small 
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(approximately one or two acres) and have typically very low elevation or are incised within the 

general topography. Thus, the extrapolation from the ORCR surveyed units to the entire 

universe of 1070 identified by the Office of Water has a high potential of overestimating the total 

risks and avoided costs associated with these additional units not included in the ORCR survey.

One of the most serious errors in this chapter of the BCA is EPA’s assessment of its so called 

“capacity factor,” which is the expected average volume of material spilled for the expected 

release from each of the 1070 impoundments. Id. at 7-2. The Agency briefly explains this 

concept as reflecting a calculation of a ratio between the spill volume and impoundment capacity 

for 15 of the 42 releases where the surveyed companies happened to report the spill volume on 

their survey responses. While impoundment capacity was requested on the survey, spill volumes 

were not. Nonetheless 15 spill volumes were reported by certain facilities and several other 

facilities provided other types of details concerning their spills. EPA calculated an average spill 

volume of 6.45% of impoundment capacity based on the 15 spills and assumed this average was 

the same for the other 27 spills.

There are several glaring problems with this analysis. USWAG was able to obtain access to 

EPA’s calculation worksheet for determining this capacity factor, which was not located in the 

docket for this rulemaking or cited in this chapter of the BCA. While 6.45% is the average 

capacity spilled, a quick perusal of the underlying data indicates that very few spills were either 

of a significant percentage of the impoundment’s volume or a significant volume of CCR 

wastewater. For example, while 6.45% is the mean of the 15 spills, the median (eighth largest 

capacity spill) is .1% and only 4 spills were of a capacity larger than 2%. This means, 

in essence, that only a very few number of spills are significantly impacting EPA’s 

findings. In fact, the two largest recent spills, Kingston and Martin’s Creek, are clearly the most 

significant spills by capacity and contribute over 97% of the total volume of CCR wastewaters 

included in this analysis of reported spills. This finding seems reasonably intuitive because these 

spills are widely known as the most significant CCR spills, but it also drastically skews EPA’s 

calculations in this report.

The Agency assumes that each spill included in the survey required cleanup costs, transaction 

costs, and natural resource damage (“NRD”) costs which are avoided if the impoundment would 

be closed, pursuant to the implementation of the ELGs. It is highly unlikely that these costs will 

even be incurred for all of the 15 spills for which details are known (e.g., 50 gallon spill of 

wastewater). What is much more troubling, however, is that EPA is assuming the spills for 

which it has data (15) are identical to the spills (27) for which is does not have data. Because 

companies were not required to disclose spill volume, many companies did not include this 

information. We would posit, however, that companies would more likely disclose this 

information if the spill was so significant that the company knew the volume of the 

spill. Companies probably would not report the volume of minor leaks and seepage because it 

would be less likely that they could determine the volume spilled. A review of ORCR’s 

spreadsheet confirms this position. Many of the other 27 spills for which volume was not 

reported described minor seepage, limited quantities of materials leaking, or minor NPDES 

permit limitation exceedances.
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Furthermore, the other 27 spills that are reported to have taken place are unlike the large capacity 

spills for which data were reported—e.g., Martin’s Creek and Kingston. Similar spills could not 

realistically have taken place without EPA being aware of them. As mentioned above, EPA 

takes the 15 spills and extrapolates them directly to the remaining 27 spills for which data on 

capacity is not known. This implicitly but directly assumes that two other spills like Kingston 

and two other spills like Martin’s Creek have occurred in the U.S. over the last 10 years, when in 

fact such spills simply did not occur. The addition of such non-events leads to a drastic 

overestimating of the likelihood of a serious spill occurring. It also ignores the efforts that the 

regulated industry has taken to ensure that spills of this sort will not occur going forward.

Comment Response: 

EPA recognizes that there is a difference between the release rates and capacity factors (i.e., the 

amount of CCR released as a percent of impoundment capacity) associated with large structural 

failures (i.e., wall breaches) and other types of generally more minor releases. For the benefit 

analysis of the final rule, EPA revised the analysis of release rates and capacity factors by 

distinguishing between wall breaches and other types of events that are likely to release a smaller 

share of impoundment capacity, following the approach used for the final CCR rule analysis. 

These changes address the commenter’s concern regarding the application of uniform 

assumptions to potentially very different types of impoundments and releases. For further 

description of this revised approach, see Chapter 6 of the BCA.

For the final rule, EPA also distinguished “big” impoundments that may have either wall 

breaches or other types of releases from “small” impoundments that are unlikely to have wall 

breaches, where classification of the impoundments in one or the other category is based on the 

impoundment capacity and berm height. EPA then applied the release probability and capacity 

factor to each category of impoundment and type of release. This change further addresses the 

commenter’s concern regarding the application of uniform assumptions to potentially very 

different types of impoundments and releases.

EPA also appreciates the industry’s efforts to ensure that catastrophic releases do not occur in the 

future. However, these efforts cannot prevent all unanticipated release events, as evidenced by 

the Dan River release in February 2014, which occurred despite regular inspections and after 

completion of an inspection that found the site to be well maintained and in good working order 

(see Final Report: CCW Impoundment Inspection Report, Dan River Steam Station Rockingham 

County, North Carolina; submitted to EPA in September 2009; see Chapter 6 of the BCA for 

more information on this event). For the final rule analysis, EPA used baseline failure 

probabilities that reflect compliance with the recently promulgated final CCR rule. While the 

CCR rule is expected to significantly reduce the probability of future impoundment failures, 

relative to historical failure rates, the residual risk is not zero.

For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 

6.e).
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Commenter Name: James R. Roewer

Commenter Affiliation: Utility Solid Waste Activities Group (USWAG)

Document Control Number: EPA-HQ-OW-2009-0819-4652-A1

Comment Excerpt Number: 23

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

D. EPA’s Cost Sources and Estimates Are Inapplicable to CCR Impoundments

In the BCA, EPA next calculates the costs associated with each of these impoundment failures in 

terms of cleanup, natural resources damages, and transaction costs. BCA at 7-2. The most 

significant problem with this analysis is that the studies on costs from which EPA draws its 

model do not fairly represent the types of damages or costs typically associated with spills of 

CCR from surface impoundments. This factor alone significantly overestimates the avoided 

costs of the ELG proposal.

The first cost component is “cleanup costs.” EPA identified three historical cleanup costs for 

impoundment failures and calculated an average cleanup cost based on a per-gallon spilled 

basis. One of these cleanup costs was from a site that contained coal slurry which 

only nominally is similar to the wastewaters contained in CCR impoundments. The other two 

sources are from the TVA Kingston and Martin’s Creek spills, the two largest spill cleanups in 

recent history. We assume that these two spills would be the most expensive cleanups for 

obvious reasons and would pose the most significant and complex costs associated with off-site 

cleanup and remediation. Using these two spills as sources of cost data will almost 

certainly overestimate the costs associated with cleanup. Since this estimation is such a 

significant component of the BCA, we strongly encourage EPA to revisit this calculation by at 

least examining more representative spills and cleanup costs. Rather than address the avoided 

costs of impoundment failures on a per-gallon spilled basis, we strongly encourage EPA to 

assess representative spill costs for typical CCR impoundment spills rather than exclusively 

relying on large capacity spills. This will result in a more representative avoided cost.

The second portion of the cost estimate is the “Natural Resource Damages” component in which 

EPA relies on a study that looked at prominent NRD cases that arise, as EPA states, from oil and 

chemical spills among other incidents. It unknown why EPA did not attempt to at least identify 

some NRD costs from CCR impoundment spills in forming this calculation, which we assume 

would pose very different risks from oil or chemical spills. EPA also makes no attempt to find 

cost data associated with less prominent spills, which are more typical of impoundment 

releases—e.g., the median capacity spill from the group of 15 releases for which details were 

known involved a 5,000 gallon discharge of wastewater.

The third component of the cost estimates involved “Transaction Costs” where EPA relies on 

studies summarizing these costs as a share of Superfund spending. These costs include 

“negotiating NRD, determining responsibility among potentially responsible parties, and 

litigating details regarding settlements and remediation.” Id. at 7-4. The source of these data is 
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very troubling because typical Superfund cases address long-standing soil and groundwater 

contamination usually occurring over many years and include litigation between any number of 

potentially responsible parties that have very little relevance to releases from CCR 

impoundments, which are typically obvious and presumably could have come from only one 

possible source. Furthermore, CCR impoundment spills generally would be identified 

immediately and remediated before contamination could spread widely. In contrast, Superfund 

sites typically involve contamination plumes that have spread both horizontally and vertically 

over years or decades. Using Superfund cases in this way wildly inflates these costs for CCR 

impoundments.

The portion of the BCA that calculates the avoided costs of impoundment failures relies very 

heavily on the two most major CCR impoundment spills. This reliance as well as its mistaken 

assumptions on the probability of impoundment closures, necessarily overinflates the costs 

associated with these types of failures as well as the likelihood that the promulgation of the 

ELGs will cause impoundment closures to avoid these costs. We strongly urge EPA to evaluate 

a broader range of spill costs and failure scenarios that do not overly rely on worst case scenario 

possibilities and costs. We also suggest that EPA include in its closure scenarios a 

more complete picture of the number of wastestreams managed in impoundments as well as 

the likelihood that these impoundments will remain open regardless of whether CCR 

wastestreams can continue to be managed in them. This will provide a more representative and 

realistic estimate of the avoided costs of impoundment failures likely to be realized through this 

rulemaking. As currently drafted, the BCA does not provide a reliable avoided cost estimate 

related to reduced impoundment failures and we respectively submit cannot reasonably serve as 

the basis for this rulemaking.

Comment Response: 

The commenter does not provide data to support the assertion that larger-scale spills “would be 

the most expensive cleanups for obvious reasons” and while the commenter may be making this 

statement based on aggregate costs, EPA did not find evidence that smaller spills have smaller 

unit (i.e., per-gallon) costs. In fact, publicly available cost data EPA compiled to support the final 

rule analysis show that comparably smaller releases such as the Oak Creek release in Wisconsin 

(see Chapter 6 of the BCA for more information on this incident) may have higher per-gallon 

costs than larger releases such as the Kingston release.

While EPA agrees with the commenter that CCR may cause different natural resource damages 

than oil or chemical spills, the magnitude of NRD is likely to be a function of the resources 

impacted by a release, even if materials differ. The commenter asserts that EPA did not attempt 

to identify costs associated with NRD from CCR impoundment releases. EPA’s searches for 

additional data on the NRD associated with these releases showed that there is little publicly 

available data on NRD arising from CCR releases due to infrequent incidents, or incidents that 

happened too recently for the assessment to be complete.

As EPA noted in the Regulatory Impact Analysis (RIA) for the CCR final rule (U.S. EPA, 2015, 

page 5-17), many factors influence the scale of NRD associated with a particular event, such that 

two release events of exactly the same substance (e.g., coal ash) and size, but at two different 
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locations and points in time, could easily produce very different claims. Thus, even if a large 

sample of NRD cases associated with coal ash releases were available, it could only serve to 

bound the likely order of magnitude of damages for any particular event. For example, NRD 

costs are primarily based on the value of the affected resource rather than the magnitude of the 

damage event and the analysis would ideally use GIS data to build a location-specific habitat 

description for each of the impoundments in the universe. However, habitat factors that drive 

NRD values vary widely with location, reflecting altitude, geology, local climatic conditions, and 

combinations of terrestrial and aquatic species with differing values. The value of habitat is also 

linked to the location-specific recreational opportunities it provides. While detailed, highresolution spatial data are available to characterize site-specific features, the scope of the 

impoundment universe is too broad to allow a detailed assessment of site-specific habitat. In the 

absence of a directly analogous sample and site-specific data on resources that may be affected 

in the event of a release, a large sample of settled or otherwise resolved damage claims 

representing a wide variety of release event types provides the soundest basis for establishing the 

order of magnitude of damages for releases of different sizes. As such, for the final rule analysis, 

EPA used historical NRD assessed for a variety of spills involving oil and chemical substances 

to estimate the NRD arising from CCR releases to the environment. EPA revised the data used to 

develop NRD assumptions to address commenters concerns that CCR impoundment damages are 

substantively different from damages in certain NRD cases, notably damages from legacy 

releases or releases to resources (e.g., marine waters) unlikely to be affected by an impoundment 

release.

With regard to transaction costs, EPA disagrees that the use of Superfund data “wildly inflates 

these costs.” Data from Superfund cases provide insight in the types of costs that arise from 

releases and other environmental damages. As noted by the commenter, these costs may include 

negotiating natural resource damage payments, determining responsibility among parties (i.e., 

the utility owner or the insurer), and litigating details regarding settlements and remediation. 

These activities are relevant to the resolution of impoundment releases. Searches to identify data 

specific to transaction costs incurred as a result of coal ash impoundment releases yielded no 

such data in public records. As such, EPA determined that data from Superfund cases were the 

best available indicators of the transaction costs associated with impoundment failures.

For more information on the methodology used to evaluate wastestreams managed in 

impoundments and the likelihood that these impoundments would remain open, see the Agency’s 

response to DCN EPA-HQ-OW-2009-0819-4652-A1, Excerpt Number 20 and the memorandum 

titled “Avoided Impoundment Failures Capacity Reduction Analysis” (DCN SE05825).

For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 

6.e).

Commenter Name: James R. Roewer

Commenter Affiliation: Utility Solid Waste Activities Group (USWAG)

Document Control Number: EPA-HQ-OW-2009-0819-4652-A1
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Comment Excerpt Number: 28

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Finally, for the reasons detailed in the above comments, USWAG believes that EPA has 

dramatically inflated the alleged benefits from the ELG rule with respect to avoided CCR 

impoundment failures.

Comment Response: 

EPA disagrees that it has dramatically inflated the benefits of avoided CCR impoundment 

failures. For responses to specific comments about the Agency’s methods, see responses to 

comment EPA-HQ-OW-2009-0819-4652-A1 (excerpts 21, 22, and 23).

For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 

6.e).

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 190

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

E. EPA’s Analysis of Impoundment Failures Is Inadequate

In its Benefit and Cost Analysis, EPA has calculated the probability and costs of catastrophic 

impoundment failures. At least in part this analysis is intended to justify the proposed BMPs.

1. Failure Probability

However, the impoundment failure analysis suffers from several shortcomings, as documented in 

the attached report by Gradient. Attachment 2.

First, EPA calculated an aggregate annual release probability without regard to the size or 

seriousness of the releases. EPA lumped together 42 releases, only one of which was 

catastrophic.
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Of the five “significant” failures, two were in the same embankment and another was not a 

sudden failure but a release over several years. Thus only four of the six significant failures were 

independent and sudden. Considering only the four changes the annual failure rate from 0.58% 

to 0.055%, a tenfold reduction.

Also, EPA divided the total reduction of releases by the number of impoundment years. A more 

appropriate approach would be to use a Poisson distribution.

2. Capacity Factor

To calculate the “capacity factor” of impoundments, EPA mixed impoundment capacities with 

storage capacities. The only storage value relevant to EPA’s method is the stored volume when 

the release occurred. It appears EPA expects the capacities of impoundments to change due to 

the ELG rule, but EPA does not explain how.

Also, EPA applies the capacity factor to all the 36 releases, even the ones that are not spills and 

were not likely related to capacity or stored volume.

Moreover, EPA does not explain its analysis of capacity factors, as explained in the Gradient 

report.

3. Failure Costs

EPA’s estimation of the costs of impoundment failures is also inadequate. “Direct costs” were 

based on sudden releases (generally an embankment failure), but 36 of the 42 releases were 

seepage releases, which generally do not involve the kinds of cleanup associated with larger 

embankment failures.

“Natural resource damages” and “transaction costs” were based on CERCLA cleanups, which 

usually last for years and involve multiple parties who must work out responsibility.

4. Benefits of Reducing Volume of CCRs in Impoundments

Finally EPA calculated the “benefit” of having the ELG rule reduce the amount of CCRs treated 

in impoundments. EPA does not explain how it estimated the reduction in volume to be caused 

by the ELG rule. Moreover, the flawed parameters mentioned above make the estimation of 

reduced volume unreliable.

Comment Response: 

EPA recognizes that there is a difference between the release rates and capacity factors (i.e., the 

amount of CCR released as a percent of impoundment capacity) associated with large structural 

failures (i.e., wall breaches) and other types of generally more minor releases. For the benefit 

analysis of the final rule (see Chapter 6 of the BCA), EPA revised the analysis of release rates 

and capacity factors by distinguishing between wall breaches and other types of events that are 

likely to release a smaller share of impoundment capacity, following the approach used for the 
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final CCR rule analysis (see U.S. EPA, 2014). Additionally, EPA removed 13 releases 

categorized as “seepage” (not 36 as stated by the commenter) from the calculation of release 

rates and capacity factors, since these events are unlikely to result in cleanup. These changes 

address the commenter’s concern regarding the application of uniform assumptions to potentially 

very different types of impoundments and releases.

For the final rule, EPA also distinguished “big” impoundments that may have either wall 

breaches or other types of releases from “small” impoundments that are unlikely to have wall 

breaches, where classification of the impoundments in one or the other category is based on the 

impoundment capacity and berm height. EPA then applied the release probability and capacity 

factor to each category of impoundment and type of release. This change further addresses the 

commenter’s concern regarding the application of uniform assumptions to potentially very 

different types of impoundments and releases.

EPA acknowledges that dividing the number of releases by the total number of releases and the 

total number of impoundment years represented in the survey universe is a simplified approach 

to calculating the release rate. However, this approach is reasonable given the available data. The 

calculation of the release rate in the BCA represents an appropriate analysis to identify the 

overall average probability of wall breaches and other releases based on publicly available 

historical data. Further, for the final rule analysis, EPA used baseline failure rates that reflect 

compliance with the recently promulgated final CCR rule (see U.S. EPA, 2014).

As noted by the commenter, EPA based the capacity factor on the storage capacity rather than 

the actual volume of waste stored in the impoundment at the time of the release. EPA does not 

agree that this is inappropriate. First, EPA does not have information on the amount stored in the 

impoundments at the time that the historical releases occurred, nor information about the amount 

that will be stored in impoundments at the time of any future release. Calculating the average 

storage amount as a share of impoundment capacity and applying the amount released to that 

share is effectively equivalent to deriving the capacity factor based on the released volume as a 

share of the impoundment capacity. As such, it is appropriate to estimate the amount released as 

a share of the impoundment capacity based on historical releases and known information about 

impoundment capacity. See Section 6.1 of the BCA for a discussion of the methods used to 

derive capacity factors for wall breaches and other releases from big impoundments, and other 

releases only from small impoundments.

EPA disagrees with the commenter that EPA’s estimation of the costs associated with a release is 

inadequate. For the final rule analysis, EPA updated cost assumptions to incorporate more recent 

data from public records. The final analysis includes data for five historical impoundment 

failures: the three used in the proposed rule analysis, plus the Widows Creek release and the 

2011 Oak Creek release in Wisconsin. These data show that comparably smaller releases such as 

the Oak Creek release in Wisconsin (see Chapter 6 of the BCA for discussion of this incident) 

can result in higher per gallon costs than larger releases such as the Kingston release. EPA found 

no evidence that the unit costs associated with smaller releases would be meaningfully smaller 

than those associated with releases for which costs are available.
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Regarding natural resource damagers, EPA addressed the commenter’s concerns about 

applicability of CERCLA sites by removing cases resulting from legacy pollution associated 

with Superfund sites from the data, instead basing NRD estimates on 65 cases that are applicable 

based on the resources affected and the general circumstances of the release. With regard to 

transaction costs, data from Superfund cases provide insight in the types of costs that arise from 

releases and other environmental damages. These costs may include negotiating natural resource 

damage payments, determining responsibility among parties (i.e., the utility owner or the 

insurer), and litigating details regarding settlements and remediation. These activities are 

relevant to the resolution of impoundment releases. In the absence of data specific to transaction 

costs incurred as a result of coal ash impoundment releases in public records, EPA determined 

that data from Superfund cases were the best available indicators of the transaction costs 

associated with impoundment failures. See Section 6.1.3 of the BCA for more details on this 

analysis.

For more information on how EPA estimated the changes in the quantity of CCR managed in 

impoundments see memorandum titled “Avoided Impoundment Failures Capacity Reduction 

Analysis” (DCN SE05825) in the record for the final steam electric ELG.

For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 

6.e).

References

United States Environmental Protection Agency (U.S. EPA). 2014. Regulatory Impact Analysis 

for EPA’s 2015 RCRA Final Rule Regulating Coal Combustion Residue (CCR) Landfills and 

Surface Impoundments at Coal-Fired Electric Utility Power Plants.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 230

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

F. Avoided Costs Related to Impoundment Failures

Benefits from the proposed ELGs attributed to avoided costs related to reduced impoundment 

failures comprise 37-58% of the total benefits under the evaluated regulatory options. The EPA 

analysis, however, substantially overstates the potential benefit from the proposed ELGs because 

of the following key reasons:
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 The estimated failure probability and direct cost analysis are inconsistent. The cost 

analysis is based on remedial efforts related to catastrophic failures only, but the failure 

probability estimates include, and are in fact dominated by, occurrence of smaller failures 

for which the level of remedial costs are much lower.

 The indirect unit costs (natural resources damages and transaction costs) are most likely 

substantially overstated.

Since the unit costs are multiplied by the failure probabilities, the flaws in these values are 

magnified. For example, if the failure probability is too large by a factor of 2 and the unit costs 

are too large by a factor of 2, the estimated total benefits would be too large by a factor of 

4. This is particularly significant because, as already described, the failure probability is most 

likely a factor of 10 too large.

Additionally, EPA’s “Benefit and Cost Analysis for the Proposed Effluent Limitations 

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

EPA-821-R-13-004 (April 2013), EPA-HQ-OW-2009-0819-2238 (BCA) does not describe 

certain aspects of the analysis well enough to follow its process, and hence be able to critique the 

process. These areas include:

 Estimation of the capacity factor, the ratio between the volume stored in an

impoundment, and the size of the release in the event of failure. This factor is partially 

explained, so we are able to provide some comments.

 Estimation of the reduction in CCR volume in impoundments, which underlies the whole 

evaluation performed by EPA. EPA neither explains these estimates nor cites to another 

source, so we are unable to provide any further comment.

Comment Response: 

EPA disagrees that the potential impoundment benefits are substantially overstated. The Agency 

found no evidence in the publicly available data that smaller releases have smaller unit costs. In 

fact, EPA found some empirical evidence that comparably smaller releases such as the Oak 

Creek release in Wisconsin (see Section 6.1 of the final BCA for more information on this 

incident) may have higher unit costs than larger releases such as the Kingston release.

For the final rule analysis, EPA expanded the data points for estimating cleanup costs, including 

5 historical impoundment failures: the three used in the proposed rule analysis, plus the Widows 

Creek release and the 2011 Oak Creek release in Wisconsin. The two new data points used in 

estimating cleanup costs had smaller volumes released with higher unit costs of cleanup. See 

Section 6.1 of the BCA for more details on this analysis.

EPA also disagrees with the commenter’s characterization of natural resource damages and 

transaction costs as “indirect costs,” and that these are significantly overstated. Again, the 

commenter does not provide data to support the assertion. For a response to the commenter’s 

assertion that the failure probability is overstated by a factor of 10, see response to DCN EPAHQ-OW-2009-0819-4655-A2 (excerpt 38).
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EPA agrees with the commenter that there is a difference between the release rates associated 

with catastrophic failures (i.e., wall breaches) and other types of generally more minor releases 

that are more prevalent in the historical release data. For the analysis of the proposed rule, EPA 

had calculated one overall release rate based on all release events, large or small. For the benefit 

analysis of the final rule, EPA revised the analysis of release rates by distinguishing between 

wall breaches and other types of events that are likely to release a smaller share of impoundment 

capacity. The analysis differentiates between the types of releases both on the basis of the 

probability of a release, and the capacity factor (i.e., quantity of CCR released in the event of a 

release as a share of the impoundment capacity). For further description of this revised approach, 

see Section 6 of the BCA.

EPA disagrees that information the Agency provided about the analysis in the documentation 

that accompanied the proposed rule was insufficient. The methodology and data were 

extensively described in BCA. The capacity factor was derived based on historical releases, as 

was the release rate, with details provided in the BCA. EPA provided similarly detailed 

discussion of the basis for these parameters in the BCA for the final rule.

For more information on how EPA estimated the changes in the quantity of CCR managed in 

impoundments see memorandum titled “Avoided Impoundment Failures Capacity Reduction 

Analysis” (DCN SE05825) in the record for the final steam electric ELG.

For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 

6.e).

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A2

Comment Excerpt Number: 38

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

6 Avoided Costs Related to Impoundment Failures

The benefits attributed to reduced impoundment failures range from 37-58% of the total benefits 

attributed to the proposed ELG, based on Options 3 and 4 for which air quality related benefit 

estimates are provided (US EPA, 2013d, Table 10-1). These avoided costs derive from US EPA's 

expectation that the amount of CCRs managed in impoundments will decline under the proposed 

ELG. US EPA (2013d, Section 7) then used the impoundment release survey data summarized in 

US EPA (2010b) to estimate an aggregate annual occurrence rate for CCR impoundment releases 

(0.58%) and an average release as a percentage of the impoundment capacity (6.45%). These 

factors were used, along with estimated costs that would be incurred by steam electric power 
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plants to address impoundment failures, to estimate the reduced costs to the utilities for 

addressing impoundment failures that would be attributed to the proposed ELG. This estimated 

reduction was then viewed as a benefit attributable to the proposed ELG. This analysis 

substantially overstates the potential benefit from the proposed ELG because of the following 

key reasons:

 The estimated failure probability and direct cost analysis are inconsistent. The cost 

analysis is based on remedial efforts related to catastrophic failures only, but the failure 

probability estimates includes, and is in fact dominated by, occurrence of smaller failures 

for which the level of remedial costs are much lower.

 The indirect unit costs (natural resources damages and transaction costs) are most likely 

substantially overstated.

Since the unit costs are multiplied by the failure probabilities, the flaws in these values are 

magnified. For example, if the failure probability is too large by a factor of 2 and the unit costs 

are too large by a factor of 2, the estimated total benefits would be too large by a factor of 4. This 

is particularly significant because, as described below, the failure probability is most likely a 

factor of 10 too large.

Additionally, US EPA (2013d) does not describe certain aspects of the analysis well enough to 

follow their process, and hence be able to critique the process. These areas include:

 Estimation of the capacity factor, the ratio between the volume stored in an impoundment 

and the size of the release in the event of failure. This factor is partially explained, so we 

are able to provide some comments below.

 Estimation of the reduction in CCR volume in impoundments, which underlies the whole 

evaluation performed by the US EPA. US EPA neither explains these estimate nor cites 

to another source, so we are unable to provide any further comment.

6.1 Failure Probability

US EPA (2013d) combines all releases reported in US EPA (2010b) together to generate an 

aggregate annual release probability, ignoring the character of the releases. This contrasts starkly 

with the approach used by US EPA (2010b), in which the releases were divided into three 

categories: seepage failures, significant failures, and catastrophic failures. Of the 42 releases 

listed in Exhibit 5B-1 in US EPA (2010b), 36 were seepage failures, 5 were significant failures, 

and only 1 was a catastrophic failure. Lumping all of the releases together into one release failure 

probability most likely overstates the failure costs, because the cost estimates (discussed below) 

reasonably apply only to the larger failures ‒ those classified as significant or catastrophic by US 

EPA (2010b).

Additionally, of the five events identified by US EPA (2010b) as significant failures, two of 

them were failure of the same embankment, the second failure occurring a year after the first and 

attributed to a faulty repair of the damage from the prior year. While these are indeed two 

failures, they are not two independent failures, and the statistical approach used by US EPA 

(2013d) is not valid if the failure events are not independent. Further, one of the significant 
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events was not a sudden failure. PacifiCorp Energy (Skinner, 2009) reported Item 22 in US EPA 

(2010b) Exhibit 5B-1 at the Naughton plant as a release that happened over the course of several 

years. Thus, out of six release events identified by US EPA (2010b) as significant or 

catastrophic, only four are actually independent release events and associated with costs 

applicable to the US EPA (2013d) evaluation. Considering only these four events in US EPA 

(2013d), Eq. 7-1 changes the annual failure rate from 0.58% to 0.055%, a 10-fold reduction. 

Applying just this correction, before considering the overestimation of costs discussed below, 

would reduce the benefits attributable to reduced impoundment failures, and hence benefits 

attributable to the proposed ELG, substantially.

US EPA (2013d) chose to use a very simplistic approach to model failure risk, simply dividing 

the total number of releases by the number of impoundment years represented in the survey 

universe. In contrast, US EPA (2010b) used the same data to estimate the parameters of a 

Poisson distribution, which is a more appropriate approach to modeling failures over a universe 

of independent entities, though it leads to a more complex benefits analysis. US EPA should 

justify their selection of this simplistic failure analysis approach.

6.2 Capacity Factor

US EPA (2013d) describes this factor as the ratio of the spill volume to the impoundment 

capacity, stated as a percentage. This ratio could be a reasonable attempt to characterize release 

volume variability as a function of impoundment size, but there are problems with the 

implementation of this calculation.

First, some of the entries in US EPA (2010b) are the impoundment capacity and others are the 

storage capacity as of the survey date; none are the stored volume as of the release incident, 

which is the only storage value that is relevant to the method employed by US EPA (2013d). If 

the capacity factor is really computed as a percentage of capacity, as stated by US EPA (2013d), 

then US EPA should explain why they expect that the impoundment capacities will change as a 

result of the proposed ELG. Perhaps US EPA expects that total installed impoundment capacity 

will decline, but we were not able to find documentation of US EPA's evaluation.

Second, the fundamental concept of applying this factor to all the releases identified in US EPA 

(2010b) Exhibit 5B-1 is flawed. It does not apply at all to the 36 seepage releases, as those 

releases are not spills that might be expected to be related to either capacity or stored volume at 

the time of a release.

Finally, the calculation of the capacity factor is difficult to follow, as illustrated by the following:

 US EPA (2013d) claims that both capacity and release volume are provided in US EPA 

(2010b) for 15 of the 42 documented releases, data from which US EPA (2013d) 

calculated that the average release was 6.45% of the capacity. Exhibit 5B-1 in US EPA 

(2010b) provides release volume for 15 of the documented releases, but both capacity and 

release volume for only 10 of the documented releases. If US EPA (2013d) supplemented 

the data provided in US EPA (2010b), the source should be documented.
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 US EPA (2013d) stated that the range of capacity factors is from less than 0.01% to 

37.9%, with an average of 6.45%. Using the values in US EPA (2010b) Exhibit 5B-1, the 

range of capacity factors is from well less than 0.01% to 767%. The largest value comes 

from Item 27 in US EPA (2010b) Exhibit 5B-1, where there was a release of 100 million 

gallons over a period of several days from an impoundment with a capacity of 12.75 

million gallons above grade (Murphy, 2009). Considering this large capacity factor alone 

would produce an average capacity factor of about 50% over 15 events or about 70% 

over 11 events. This large release relative to the impoundment capacity is probably not 

representative of typical release scenarios and should probably not be incorporated into 

the calculation without some adjustment. If US EPA (2013d) applied some adjustment to 

the individual release capacity factors, such adjustment should be described and 

documented.

US EPA should reconsider their use of the capacity factor and either develop the correct 

parameters or develop an alternate approach.

6.3 Failure Costs

US EPA (2013d) estimated cleanup costs for CCR releases in terms of three components ‒ direct 

cleanup, natural resource damages, and transaction costs ‒ as follows:

 Direct cleanup costs (Section 7.1.3.1) were based on three cases ‒ two for power plant 

CCR releases and one for a mine impoundment. The three costs ranged from $0.26/gal 

(released gallons) to $1.16/gal, and averaged $0.62/gal.

 Natural resource damage (NRD) costs (Section 7.3.1.2) were estimated by diving the 

median of the NRD costs reported by Israel (2006), approximately $4 million, by the 

median total cost for the three case studies used to develop the direct cleanup cost 

estimate, $65 million. This produced a value of 6% for NRD costs as a percentage of 

cleanup costs. This percentage was then applied to the cleanup cost of $0.62/gal to 

produce an NRD estimate of $0.04/gal.

 Transaction costs were based on information presented in four studies, all from the mid1990s, of transaction costs for sites regulated under the Comprehensive Environmental 

Response, Compensation and Liability Act (CERCLA, commonly known as Superfund). 

Based on these four studies, US EPA (2013d) estimated that transaction costs were about 

37% of cleanup costs, which, when applied to the cleanup cost estimate, comes to 

$0.23/gal. These three cost elements sum to $0.89/gal.

There are numerous issues with this methodology and with specific estimates that call this 

calculation into serious question and indicate that the benefits are substantially overstated. US 

EPA should consider the comments presented below and reevaluate this benefit computation.

6.3.1 Direct Cost Analysis

The direct cleanup cost analysis presented by US EPA (2013d) applies to events that involve the 

sudden release of impoundment contents, generally due to an embankment failure. For these 

types of events, the US EPA (2013d) cost analysis is generally reasonable, though it does not 
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recognize that such costs are not always incurred, even for what US EPA (2010b) termed 

significant releases. For example, IPL (Marsan, 2009) reported that no released materials were 

recovered for release items 13 and 14 in US EPA (2010b) Exhibit 5B-1.

A more significant issue with the direct cost analysis, however, is that it potentially applies to 

only 6 of the 42 release events identified in the 2009 survey, an issues discussed above under the 

failure probability heading. The remaining 36 events are seepage releases, which generally do 

not involve the kinds of cleanup activities associated with the larger embankment failure 

releases. Additionally, the NRD and transaction cost categories would generally not apply to 

these seepage releases.

Therefore, US EPA should either adjust their failure probability estimates to be consistent with 

the cost estimates or adjust the cost estimates to be consistent with their approach to estimating 

the failure probability. Either adjustment will lead to a substantial reduction in the total benefits 

attributed to reduced impoundment failures.

6.3.2 NRD Cost Analysis

The NRD cost analysis is flawed in that the universe of events from which the median NRD cost 

was taken (the study by Israel, 2006) is not the same as, and not even closely related to, the 

universe of events being evaluated as potential CCR impoundment releases. We would expect 

NRD costs to be relatively low compared to NRD costs related to sites regulated under 

CERCLA, because the environmental damages for sites regulated under CERCLA have often 

been in place for many years, whereas the damages related to CCR impoundment failures will 

generally be of shorter duration. US EPA should either provide further justification for the NRD 

cost value or modify the value.

6.3.3 Transaction Cost Analysis

The transaction cost analysis is flawed in that the CERCLA program transaction costs that were 

evaluated in the studies cited bear no resemblance to the expected transaction costs for CCR 

impoundment releases. The reason there were so many studies of CERCLA transaction costs in 

the mid-1990s is that there was substantial concern that transaction costs were excessively high. 

There were major elements of CERCLA transaction costs at that time that simply do not exist for 

CCR impoundment releases. For example:

 CERCLA sites often have multiple responsible parties. Determining how the costs are 

allocated among the parties can be a substantial transaction cost. CCR releases more 

commonly have a single clearly identified responsible party.

 CERCLA liabilities are commonly related to past events for which the records are less 

than clear. Substantial CERCLA transaction costs were related to evaluating whether 

potentially responsible parties actually bore any liability. The events addressed by the 

ELG analysis are future events for which the responsible party will be easily identifiable.

 CERCLA established liability for past events that may have been legal at the time they 

occurred. Some of the transaction costs were related to disputing the validity of the 
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statute itself. Such costs are unlikely to occur in relationship to CCR impoundment 

releases.

We would expect transaction costs for CCR releases from impoundments to be very low. US 

EPA should either provide further justification for the transaction cost value or modify the value.

Additionally, we were not able to find the reference "U.S. EPA Analysis, 2013" cited in the 

footnotes for Tables 7-2 and 7-3 in US EPA (2013d). Please clarify the citation.

6.4 Benefit Calculation

The annual expected cost for each impoundment, in the absence of the proposed ELGs, is 

calculated as the product of the annual release probability × impoundment capacity × capacity 

factor (proportion of contents released) × the cost per gallon released. These individual facility 

costs were then totaled for the universe of regulated facilities using CCR impoundments to get 

the total baseline cost. Estimated benefits attributed to the proposed ELG then apparently derive 

from the expected reduction in CCR waste volume in impoundments expected to be caused by 

the proposed ELG. That is, the same calculation is performed under the proposed ELG 

conditions, but with the lower volume of CCR contained in impoundments. This basic 

calculation approach is reasonable, though the flawed parameter estimates, as described above, 

lead to a substantial overestimation of benefits.

6.5 Summary

In summary, US EPA (2013d) used a failure probability that substantially overstates the 

probability of impoundment failures that are potentially relevant to the ELG benefits and 

overestimated the costs associated with cleanup, leading to a substantial overestimation of the 

benefits related to potential CCR impoundment failures that might be attributable to the proposed 

ELG.

Comment Response: 

The commenter asserts that the potential impoundment benefits are substantially overstated, and 

challenges several key aspects of the impoundment analysis, including the release rate, capacity 

factor, release costs, and benefit calculation. EPA disagrees with the commenter’s general 

conclusion that impoundment benefits are substantially overstated, and with several of the 

commenter’s key assertions, but agrees with the commenter on some aspects of the analysis, as 

described in more detail below.

First, the Agency found no evidence in the publicly available data that smaller releases have 

smaller unit costs. In fact, EPA found some empirical evidence that comparably smaller releases 

such as the Oak Creek release in Wisconsin (see Section 6.1 of the final BCA for more 

information on this incident) may have higher unit costs than larger releases such as the Kingston 

release. For the final rule analysis, EPA expanded the data points for estimating cleanup costs, 

including 5 historical impoundment failures: the three used in the proposed rule analysis, plus the 

Widows Creek release and the 2011 Oak Creek release in Wisconsin. The two new data points 
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used in estimating cleanup costs had smaller volumes released with higher unit costs of cleanup. 

See Section 6 of the BCA for more details on this analysis.

EPA also does not agree with the commenter’s characterization of natural resource damages and 

transaction costs as “indirect costs,” nor that these are significantly overstated. Additionally, 

EPA disagrees with the commenter that it has not provided enough information about the 

analysis in the documentation. The methodology and data are well-documented in the BCA and 

EPA expanded on the extensive documentation for the final rule. The capacity factor is based on 

historical releases, as is the release rate. Section 6 of the BCA for the final rule details the basis 

for these parameters.

EPA agrees with the commenter that there is a difference between the release rates associated 

with catastrophic failures (i.e., wall breaches) and other types of generally more minor releases 

that are more prevalent in the historical release data. As described in more detail below, EPA has 

revised the analysis of the final rule to account for these differences.

The specific assumptions, methodologies, and data sources challenged by the commenter are 

described in more detail below.

Failure Probability

The commenter asserts that it is inappropriate for EPA to combine all 42 historical releases to 

calculate an aggregate annual release probability. EPA agrees with the commenter that there is a 

difference between the release rates associated with catastrophic failures (i.e., wall breaches) and 

other types of generally more minor releases that are more prevalent in the historical release data. 

For the benefit analysis of the final rule, EPA revised the analysis of release rates by 

distinguishing between wall breaches and other types of events that are likely to release a smaller 

share of impoundment capacity. The analysis differentiates between the types of releases both on 

the basis of the probability of a release, and the capacity factor (i.e., quantity of CCR released in 

the event of a release). Additionally, EPA removed 13 releases categorized as “seepage” (not 36 

as stated by the commenter) from the calculation of release rates, since these events are unlikely 

to result in cleanup. For further description of this revised approach, see Section 6.1 of the BCA.

The commenter also states that “the cost estimates (discussed below) reasonably apply only to 

the larger failures ‒ those classified as significant or catastrophic” and that only four of the 

historical release events “are actually independent release events and associated with costs 

applicable to the USEPA evaluation.” The commenter asserts that restricting the release 

probability to four events reduces the probability from 0.58% to 0.055%, a 10-fold reduction. 

However, EPA does not agree that it should consider only the four catastrophic and independent 

events. First, expenditures associated with smaller releases may also be avoided through 

implementation of the ELGs. Aggregated across many releases, the avoided costs of small 

releases may be significant. Secondly, releases that are not independent (for example, the release 

that was the result of a faulty repair of a previous failure) still result in cleanup costs, damages, 

and litigation costs. If the regulation reduces the probability of these types of releases, then this 

represents a benefit to society.
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EPA agrees with the commenter that dividing the number of releases by the total number of 

releases and the total number of impoundment years represented in the survey universe is a 

simplified approach to calculating the release rate. However, data and resource methodology 

constrain EPA’s ability to conduct a more complex modeling approach. The calculation of the 

release probability in the BCA represents an appropriate analysis to identify the overall average 

probability of wall breaches and other releases based on publicly available historical data.

Capacity Factor

For more information on how EPA estimated the changes in the quantity of CCR managed in 

impoundments see memorandum titled “Avoided Impoundment Failures Capacity Reduction 

Analysis” (DCN SE05825) in the record for the final steam electric ELG.

As noted by the commenter, EPA based the capacity factor on the storage capacity rather than 

the actual volume of waste stored in the impoundment at the time of the release. EPA maintains 

that this is reasonable and appropriate. First, EPA does not have information on the amount 

stored in the impoundments at the time that the historical releases occurred, nor information 

about the amount that will be stored in impoundments during future predicted releases. While it 

may be possible to determine the average storage amount as a share of impoundment capacity 

and apply the amount released to that share, this would effectively be equivalent to deriving the 

capacity factor based on the released volume as a share of the impoundment capacity. EPA’s 

approach of estimating the amount released as a share of the impoundment capacity based on 

historical releases and known information about impoundment capacity is therefore appropriate. 

See Section 6.1 of the BCA for a complete discussion of the methods used to derive capacity 

factors for wall breaches and other releases from big impoundments, and other releases only 

from small impoundments.

As noted above, EPA agrees that seepage events are not relevant to this analysis, and has 

removed 13 such events (not 36 as stated by the commenter) from the calculation of capacity 

factor. For the final rule analysis, EPA has modified the approach to calculating the capacity 

factor by distinguishing between wall breaches and other types of smaller releases (excluding 

seepage events). See Section 6.1 of the BCA for a description of these calculations and the 

underlying data.

As noted by the commenter, the survey responses indicate that the 2005 release from Martin’s 

Creek released a volume of 100 million gallons, but that the impoundment capacity was 40 acrefeet or about 13 million gallons, yielding a capacity factor of 767%. As such, EPA modified the 

impoundment capacity in the dataset to 1,085 acre-feet or about 354 million gallons based on 

information in the 2009 Dam Assessment Report for the facility. EPA has clarified this 

modification in the final BCA.

Failure Costs

EPA disagrees that the cleanup costs, NRD, and litigation cost estimates result in benefits that 

are “substantially overstated.” First, EPA disagrees that the cleanup costs apply to only sudden 

large embankment failure releases. While EPA recognizes that cleanup costs will generally not 
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be applicable to seepage events (and has removed seepage events from the final rule analysis), 

EPA notes that there are 13 seepage events in the historical release data rather than 36 as stated 

by the commenter. Some non-wall breach releases will entail cleanup costs and as such it is 

appropriate to include these releases in the analysis and apply cleanup costs to them.

The commenter states that CERCLA cases are not representative of the NRD resulting from 

CCR impoundment releases. To address this comment, EPA removed CERCLA cases from the 

data used to calculate NRD. See Section 6.1.3 of the BCA for more information on this revised 

approach.

EPA disagrees with the commenter that transaction costs for CCR releases would be very low, 

and the commenter does not provide evidence to support this assertion. EPA has conducted 

additional searches to identify data on transaction costs incurred as a result of coal ash 

impoundment releases, but none is publicly available. Data from Superfund cases provide the 

most comprehensive insight in the types of costs that arise from releases and other environmental 

damages. These costs may include negotiating natural resource damage payments, determining 

responsibility among parties (i.e., the utility owner or the insurer), and litigating details regarding 

settlements and remediation. As such, EPA determined that these were the best available data to 

indicate the potential magnitude of transaction costs associated with impoundment failures.

Note that EPA (2013) refers to the proposed rule analysis.

Benefit Calculation

As noted by the commenter, benefits from the rule “derive from the expected reduction in CCR 

waste volume in impoundments expected to be caused by the proposed ELG. That is, the same 

calculation is performed under the proposed ELG conditions, but with the lower volume of CCR 

contained in impoundments.” EPA disagrees that its analysis of the proposed rule substantially 

overestimated the benefits. EPA provided responses above to concerns regarding individual 

components of the calculations, describing changes the Agency made for the final rule analysis, 

where appropriate. To the extent that parameter estimates determine the final benefit values, 

these changes also address the commenter’s comment regarding any substantial overestimate of 

the benefits.

For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 

6.e).

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A2

Comment Excerpt Number: 41

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

Avoided Costs Related to Impoundment Failures

Benefits from the proposed ELGs attributed to avoided costs related to reduced impoundment 

failures comprise 37-58% of the total benefits under the evaluated regulatory options. The US 

EPA analysis, however, substantially overstates the potential benefit from the proposed ELGs 

because of the following key reasons:

 The estimated failure probability and direct cost analysis are inconsistent. The cost 

analysis is based on remedial efforts related to catastrophic failures only, but the failure 

probability estimates includes, and is in fact dominated by, occurrence of smaller failures 

for which the level of remedial costs are much lower.

 The indirect unit costs (natural resources damages and transaction costs) are most likely 

substantially overstated.

Since the unit costs are multiplied by the failure probabilities, the flaws in these values are 

magnified. For example, if the failure probability is too large by a factor of 2 and the unit costs 

are too large by a factor of 2, the estimated total benefits would be too large by a factor of 4. This 

is particularly significant because, as described in Section 6, the failure probability is most likely 

a factor of 10 too large.

Additionally, US EPA (2013c) does not describe certain aspects of the analysis well enough to 

follow their process, and hence be able to critique the process. These areas include:

 Estimation of the capacity factor, the ratio between the volume stored in an impoundment 

and the size of the release in the event of failure. This factor is partially explained, so we 

are able to provide some comments.

 Estimation of the reduction in coal combustion residue (CCR) volume in impoundments, 

which underlies the whole evaluation performed by the US EPA. US EPA neither 

explains these estimates nor cites to another source, so we are unable to provide any 

further comment.

Comment Response: 

EPA disagrees that the potential impoundment benefits are substantially overstated. The Agency 

found no evidence in the publicly available data that smaller releases have smaller unit costs. In 

fact, EPA found empirical evidence that comparably smaller releases such as the Oak Creek 

release in Wisconsin (see Section 6.1 of the BCA for more information on this incident) may 

have higher unit costs than larger releases such as the Kingston release.

For the final rule analysis, EPA expanded the data points for estimating cleanup costs, including 

5 historical impoundment failures: the three used in the proposed rule analysis, plus the Widows 

Creek release and the 2011 Oak Creek release in Wisconsin. The two new data points used in 

estimating cleanup costs had smaller volumes released with higher unit costs of cleanup. See 

Section 6.1 of the BCA for more details on this analysis.
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EPA also disagrees with the commenter’s characterization of natural resource damages and 

transaction costs as “indirect costs,” or that values used by EPA are significantly overstated. 

Again, the commenter does not provide data to support the assertion. For a response to the 

commenter’s assertion that the failure probability is overstated by a factor of 10, see response to 

DCN EPA-HQ-OW-2009-0819-4655-A2 (excerpt 38).

EPA recognizes that there is a difference between the release rates associated with catastrophic 

failures (i.e., wall breaches) and other types of generally more minor releases that are more 

prevalent in the historical release data. For the analysis of the proposed rule, EPA had calculated 

one overall release rate based on all release events, large or small. For the benefit analysis of the 

final rule, EPA revised the analysis of release rates by distinguishing between wall breaches and 

other types of events that are likely to release a smaller share of impoundment capacity. The 

analysis differentiates between the types of releases both on the basis of the probability of a 

release, and the capacity factor (i.e., quantity of CCR released in the event of a release as a share 

of impoundment capacity). For further description of this revised approach, see Section 6.1 of 

the BCA for the final rule.

Finally, EPA disagrees with the commenter that the documentation that accompanied the 

proposed rule provided insufficient details about the analysis to allow external review and 

comments on the analysis. The BCA described the methodology and data extensively, including 

by providing a listing of individual observations used to derive the capacity factor and the release 

rate. The BCA also described the basis for these parameters. EPA expanded on this already 

extensive documentation for the final rule. See Chapter 6 of the BCA for the final rule for 

details.

For more information on how EPA estimated the changes in the quantity of CCR managed in 

impoundments see memorandum titled “Avoided Impoundment Failures Capacity Reduction 

Analysis” (DCN SE05825) in the record for the final steam electric ELG.

For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 

6.e).

EPA also disagrees with the commenter’s characterization of natural resource damages and 

transaction costs as “indirect costs,” or that values used by EPA are significantly overstated. 

Again, the commenter does not provide data to support the assertion. For a response to the 

commenter’s assertion that the failure probability is overstated by a factor of 10, see response to 

DCN EPA-HQ-OW-2009-0819-4655-A2 (excerpt 38).

EPA recognizes that there is a difference between the release rates associated with catastrophic 

failures (i.e., wall breaches) and other types of generally more minor releases that are more 

prevalent in the historical release data. For the analysis of the proposed rule, EPA had calculated 

one overall release rate based on all release events, large or small. For the benefit analysis of the 

final rule, EPA revised the analysis of release rates by distinguishing between wall breaches and 

other types of events that are likely to release a smaller share of impoundment capacity. The 

analysis differentiates between the types of releases both on the basis of the probability of a 
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release, and the capacity factor (i.e., quantity of CCR released in the event of a release as a share 

of impoundment capacity). For further description of this revised approach, see Section 6.1 of 

the BCA for the final rule.

Finally, EPA disagrees with the commenter that the documentation that accompanied the 

proposed rule provided insufficient details about the analysis to allow external review and 

comments on the analysis. The BCA described the methodology and data extensively, including 

by providing a listing of individual observations used to derive the capacity factor and the release 

rate. The BCA also describes the basis for these parameters.

For more information on how EPA estimated the changes in the quantity of CCR managed in 

impoundments see memorandum titled “Avoided Impoundment Failures Capacity Reduction 

Analysis” (DCN SE05825) in the record for the final steam electric ELG.

Commenter Name: Jerry Schwartz

Commenter Affiliation: American Forest & Paper Association (AF&PA)

Document Control Number: EPA-HQ-OW-2009-0819-4656-A2

Comment Excerpt Number: 4

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

the agency overestimated the benefits resulting from reduced coal combustion residuals (CCR) 

that will be placed in impoundments by using questionable methods and assumptions.

Comment Response: 

EPA disagrees that it has overestimated the impoundment benefits. The commenter did not 

provide examples of data or methods that the commenter deemed “questionable” and as such 

EPA cannot provide a more detailed response.

However, see EPA’s answer to other, more detailed, comments on this analysis (e.g. response to 

DCN EPA-HQ-OW-2009-0819-4655-A2, Excerpt Number 38) for a discussion of methods and 

assumptions.

For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number Number 3 (in Comment 

Code 6.e).

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.
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Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 36

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Reduced risk of impoundment failures due to changes in the use of impoundments: Benefits to 

the proposed steam electric ELGs are dominated by the benefit for reduced impoundment 

failures—this single benefit accounts for nearly half of the value of benefits monetized for 

Option 4. EPA’s estimate of the value of avoided failures is based on a national average 

probability of impoundment failures (a 0.58 percent chance of failure in each year) applied to all 

impoundments. EPA also presents, but does not include in its final valuation, an alternative 

methodology that takes account of specific differences in impoundment characteristics. 

(The Benefit‐Cost Analysis notes that, “because of the limited data available to develop and 

validate the statistical model, EPA did not use the model in the primary benefit estimates 

presented in this chapter but instead relied on historical failure rates.”76) This method raises the 

benefit of avoided impoundment failures by a factor of 2.7 to 3.2 depending on the regulatory 

option, such that for Options 4 and 5 this benefit rises from $295 million to $918 

million.77 Using this alternative method, total Option 4 benefits rise to $1,228 million, and EPA’s 

benefit‐cost ratio for this Option rises from 0.44 to 0.89.

EPA’s method also fails to account for two other important, closely related categories of 

benefits associated with the rule. First, EPA expressly notes in the Benefit‐Cost Analysis that its 

analysis “does not account for the effect of best management practices (BMPs)—including 

integrity inspections and preventive maintenance—that would help reduce the probability of 

impoundment failures.”78 Second, EPA’s method does not account for the costs of any litigation 

that may occur around the cleanup of an impoundment failure that would be avoided as a result 

of the rule. EPA does not attempt to quantify, let alone monetize, either of these two categories 

of benefits, both of which would also result from the rule’s reduction in impoundment failures.

76 Benefit‐Cost Analysis, p.7‐2.

77 Benefit‐Cost Analysis, Appendix G.

78 Id. at 7‐2.

Comment Response: 

As noted by the commenter and discussed in the proposed rule BCA (Appendix G), the 

simplified approach may result in an underestimate of benefits and EPA also agrees that the use 

of a single release rate across all impoundments does not account for all variables that may affect 

the risk of impoundment releases or their consequences. However, data limitations limit EPA’s 

ability to develop a more sophisticated modeling of the risk of impoundment failure at this time.
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For the final rule, EPA modified the approach to incorporate consideration of the impoundment 

characteristic and type of release, following the approach the Agency used for the final CCR rule 

analysis (U.S. EPA, 2014). EPA distinguished between “big” impoundments which may be 

subject to both large-scale structural failures and other releases, and “small” impoundments 

which may have smaller non-wall breach (i.e., other) releases. The Agency calculated separate 

release rates for each impoundment category and release type. For further description of this 

revised approach, see Section 6.1 of the BCA. Note that the release rates used for the ELG 

analysis reflect compliance with inspections and management practices required under the final 

CCR rule.

The commenter states that EPA does not account for the costs of litigation that may occur around 

the cleanup of an impoundment failure; however, this is an incorrect characterization of the 

analysis. EPA includes litigation costs (or “transaction costs”) in the costs associated with 

impoundment failures, together with cleanup costs and natural resource damages. These 

transaction costs include the costs associated with negotiating NRD, determining responsibility 

among potentially responsible parties, and litigating details regarding settlements and 

remediation. The costs do not include fines, cleanup costs, damages, or other costs that constitute 

transfers or are already accounted for in the other categories analyzed separately.

For additional information on consideration of benefits in the development of the final ELGs, see 

response to DCN EPA-HQ-OW-2009-0819-4464-A1, Excerpt Number 3 (in Comment Code 

6.e).

References:

United States Environmental Protection Agency (U.S. EPA). 2014. Regulatory Impact Analysis 

for EPA’s 2015 RCRA Final Rule Regulating Coal Combustion Residue (CCR) Landfills and 

Surface Impoundments at Coal-Fired Electric Utility Power Plants.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 37

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Reduced risk of impoundment failures due to changes in the use of impoundments: Benefits to 

the proposed steam electric ELGs are dominated by the benefit for reduced impoundment 

failures—this single benefit accounts for nearly half of the value of benefits monetized for 

Option 4. EPA’s estimate of the value of avoided failures is based on a national average 

probability of impoundment failures (a 0.58 percent chance of failure in each year) applied to all 

impoundments. EPA also presents, but does not include in its final valuation, an alternative 
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methodology that takes account of specific differences in impoundment characteristics. 

(The Benefit‐Cost Analysis notes that, “because of the limited data available to develop and 

validate the statistical model, EPA did not use the model in the primary benefit estimates 

presented in this chapter but instead relied on historical failure rates.”76) This method raises the 

benefit of avoided impoundment failures by a factor of 2.7 to 3.2 depending on the regulatory 

option, such that for Options 4 and 5 this benefit rises from $295 million to $918 

million.77 Using this alternative method, total Option 4 benefits rise to $1,228 million, and EPA’s 

benefit‐cost ratio for this Option rises from 0.44 to 0.89.

EPA’s method also fails to account for two other important, closely related categories of 

benefits associated with the rule. First, EPA expressly notes in the Benefit‐Cost Analysis that its 

analysis “does not account for the effect of best management practices (BMPs)—including 

integrity inspections and preventive maintenance—that would help reduce the probability of 

impoundment failures.”78 Second, EPA’s method does not account for the costs of any litigation 

that may occur around the cleanup of an impoundment failure that would be avoided as a result 

of the rule. EPA does not attempt to quantify, let alone monetize, either of these two categories 

of benefits, both of which would also result from the rule’s reduction in impoundment failures.

76 Benefit‐Cost Analysis, p.7‐2.

77 Benefit‐Cost Analysis, Appendix G.

78 Id. at 7‐2.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4686-A1, Excerpt Number 36.
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29.h. Benefits – Air-related benefits 

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 201

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

By internalizing the externality costs of the power plants' wastewater, a fraction of 1 percent of 

electricity generation will switch to cleaner energy sources. Under Option 3 in the plan, this will 

reduce CO2 emissions by as much as taking roughly 300,000 cars off the road, as many as 

Washington, D.C., or Boston has.

Option 4 would reduce about double that amount of CO2 emissions, which is equivalent to all 

the registered cars in both cities combined.

It should be noted also that the benefit and cost analysis uses the Interagency Working Group on 

Social Cost of Carbon’s 2010 estimates, which were also updated a month after that analysis 

came out. So the new Social Cost of Carbon estimates are about 60 percent higher than before, 

and when this is taken into account, the total monetized benefits will be about 5 or 10 percent 

higher. And I think that's worth noting, if someone hasn't already.

Comment Response: 

EPA thanks the commenter for putting the emission changes in perspective and for noting the 

changes in the Social Cost of Carbon estimates.

For the final rule, EPA again estimated reductions in air emissions associated with changes in 

generation profile, auxiliary power, and transportation. The final rule will reduce annual CO2

emissions by approximately 1.8 to 4.8 million metric tons, or the equivalent of emissions from 

roughly 380,000 to 1 million cars (at 4.75 metric tons CO2e per vehicle per year).

EPA noted the 2013 revisions to the Social Cost of Carbon estimates and used these new values 

to estimate the benefits of CO2 emission reductions associated with ELG implementation 

(IWGSCC, 2013). See Chapter 7 of the BCA for details.

References:

Interagency Working Group on Social Cost of Carbon (IWGSCC), United States Government. 

2013. Technical Update of the Social Cost for Regulatory Impact Analysis under Executive 

Order 12866. Revised November 2013.
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Commenter Name: Daniel Simmons

Commenter Affiliation: Institute for Energy Research

Document Control Number: EPA-HQ-OW-2009-0819-4473-A1

Comment Excerpt Number: 1

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The Environmental Protection Agency (EPA) is proposing a regulation on discharges from 

certain steam electric power plants.1 EPA believes the rule will result in carbon dioxide 

reductions. Carbon dioxide emissions matter because carbon dioxide is an important greenhouse 

gas. But instead of examining the impact on global temperature or sea level—as EPA had done 

in similar analyses in the past—for the present rule EPA quantifies the alleged benefits of 

emissions reduction by using a metric called the “social cost of carbon.” EPA’s omission of the 

actual impacts on climate, such as the impact on temperature and sea level rise, is arbitrary and 

inappropriate. Furthermore, EPA’s use of the social cost of carbon is also inappropriate, because 

the three models EPA uses—according to a recent peer-reviewed paper by an MIT economist in 

a prestigious journal—are themselves “close to useless,” because they generate estimates of the 

social cost of carbon using “damage functions” that are “arbitrary” and not calibrated to 

observations or even based on any underlying economic theory.2

IMPACT OF CARBON DIOXIDE EMISSIONS

According to EPA, carbon dioxide is an important greenhouse gas. EPA states in the benefit and 

cost analysis that:

CO2 is an important greenhouse gas that is linked to climate changes effects, including: an 

increase in temperature; sea level rise; changes in weather patterns toward an intensified water 

cycle with stronger floods and droughts; and stress on ecosystems, especially in the Arctic, 

mountain and tropical areas, resulting in the shift of species habitat range.3

Despite EPA’s explanation that carbon dioxide is linked to climate change effects such as “an 

increase in temperature” and “sea level rise,” EPA’s analysis omits any analysis of the actual 

changes the proposed rule would have on these specific factors. This is an arbitrary and 

inappropriate omission, inconsistent with past analyses conducted by EPA.

For example, EPA and the National Highway Traffic Safety Administration’s (NHTSA) 2017 

and Later Model Year Light-Duty Vehicle Greenhouse Gas Emissions and Corporate Average 

Fuel Economy Standards, analyzed these climate change factors. As EPA explained:

EPA examined the reductions in CO2 and other GHGs associated with this rulemaking and 

analyzed the projected effects on atmospheric CO2 concentrations, global mean surface 

temperature, sea level rise, and ocean pH which are common variables used as indicators of 

climate change. The analysis projects that the final rule will reduce atmospheric concentrations 

of CO2, global climate warming, ocean acidification, and sea level rise relative to the reference 
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case. Although the projected reductions and improvements are small in comparison to the total 

projected climate change, they are quantifiable, directionally consistent, and will contribute to 

reducing the risks associated with climate change.

...

EPA determines that the projected reductions in atmospheric 

CO2, global mean temperature, sea level rise, and ocean acidification are meaningful in the 

context of this action. The results of the analysis demonstrate that relative to the reference case, 

by 2100 projected atmospheric CO2 concentrations are estimated to be reduced by 3.21 to 3.58 

part per million by volume (ppmv), global mean temperature is estimated to be reduced by 

0.0074 to 0.0176°C, and sea- level rise is projected to be reduced by approximately 0.071-0.159 

cm, based on a range of climate sensitivities (described below). The analysis also demonstrates 

that ocean pH will increase by 0.0017 pH units by 2100 relative to the reference case (ie, reduced 

acidification).

This was not the only rule that looked at actual climate change impact on temperature and sea 

level rise. EPA also conducted this analysis in the Greenhouse Gas Emissions Standards and 

Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles rule, the LightDuty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy 

Standard rule, and the Regulation of Fuels and Fuel Additives: Changes to Renewable Fuel 

Standard Program rule.

In the past, EPA has acknowledged that its estimated impact of a rule on temperature change is 

“small,” but EPA nevertheless quantified these climate change indicators that it claimed were 

(part of) the justification for the rule. EPA should quantify these same climate change indicators 

for this rule.

1Environmental Protection Agency, Effluent Limitations Guidelines and Standards for the Steam 

Electric Power Generating Point Source Category, 78 Fed. Reg. 34432, June 7, 2013.

2See Robert S. Pindyck, “Climate Change Policy: What Do the Models Tell Us?” Journal of 

Economic Literature, September 2013.

3Environmental Protection Agency, Benefit and Cost Analysis for the Proposed Effluent 

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

Category, Apr. 2013.

Comment Response: 

The commenter suggests that EPA has omitted the actual impacts on climate, including 

temperature changes and sea level rise, of the final rule. While EPA has not explicitly reported 

changes in temperature or sea level rise, these impacts were not excluded. In fact, these changes 

are implicitly incorporated into the social cost of carbon values used by EPA in estimating the
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impact of changes in CO2 emissions under the final rule (IWGSCC, 2010; IWGSCC, 2013). EPA 

recognizes that other analyses have directly reported changes in climate change indicators but for 

this analysis EPA followed the findings of the Interagency Working Group on Social Cost of 

Carbon (IWGSCC) and reported the impact of the final rule on climate change using the social 

cost of carbon values. The goal of the IWGSCC was to determine a transparent and defensible 

method for estimating values, designed for the rulemaking process, that would lead to consistent 

benefits estimations across agencies (IWGSCC, 2010; GAO, 2014a). EPA’s use of the Social 

Cost of Carbon for the steam electric ELG analysis is consistent with that in other regulatory 

impact analyses (GAO, 2014b). EPA maintains that the approach is appropriate and provides 

reasoned benefit estimates to inform policy decisions.

Regarding the critiques leveled against the basis and development of the SCC, including those in 

the Pindyck (2013) paper cited by the commenter, refer to detailed discussion in Response to 

Comments: Social Cost of Carbon for Regulatory Impact Analysis under Executive Order 12866 

(IWGSCC, 2015)

For information on the role of benefits analysis in establishing effluent limitations based on Best 

Available Technology Economically Achievable (“BAT”), see response to DCN EPA-HQ-OW2009-0819-4464-A1, Excerpt Number 3.

References:

Interagency Working Group on Social Cost of Carbon (IWGSCC), United States Government. 

2010. Technical Support Document: Social Cost of Carbon for Regulatory Impact Analysis 

under Executive Order 12866. February 2010.

Interagency Working Group on Social Cost of Carbon (IWGSCC), United States Government. 

2013. Technical Update of the Social Cost for Regulatory Impact Analysis under Executive 

Order 12866. Revised November 2013.

Interagency Working Group on Social Cost of Carbon (IWGSCC), United States Government. 

2013. Response to Comments: Social Cost for Regulatory Impact Analysis under Executive 

Order 12866. July 2015.

Government Accountability Office (GAO). 2014a. Development of Social Cost of Carbon 

Estimates, GAO-14-663, July 24, 2014.

Commenter Name: Daniel Simmons

Commenter Affiliation: Institute for Energy Research

Document Control Number: EPA-HQ-OW-2009-0819-4473-A1

Comment Excerpt Number: 3

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

THE USE OF THE SOCIAL COST OF CARBON TO ASSESS REDUCTIONS 

IN CARBON DIOXIDE EMISSIONS IS NOT APPROPRIATE

Instead of providing the public with valuable information concerning actual climate change 

indicators, EPA estimated the benefits of carbon dioxide reduction using the social cost of 

carbon (SCC).

According to EPA:

The SCC is an estimate of the monetized damages associated with an incremental increase in 

carbon emissions in a given year. It is intended to include (but is not limited to) changes in net 

agricultural productivity, human health, property damages from increased flood risk, and the 

value of ecosystem services due to climate change.4

The SCC, however, it not an appropriate measure of climate change impacts. It is an arbitrary 

calculation that is not based in actual economic theory according to the peer reviewed literature.

According to a recent peer-reviewed paper by MIT economist Robert Pindyck, the so-called 

Integrated Assessment Models (IAMs), three of which the Interagency Working Group on Social 

Cost of Carbon used to estimate the SCC, are literally made up and not based on theory.

According to Professor Pindyck, the “developers of IAMs can do little more than make 

up functional forms and corresponding parameter values. And that is pretty much what they have 

done.”5

Pindyck further explains:

Most IAMs (including the three that were used by the Interagency Working Group to estimate 

the SCC) relate the temperature increase T to GDP through a “loss function” L(T), with L(0) = 1 

and L’(T ) < 0. For example, the Nordhaus (2008) DICE model uses [an] inverse-quadratic loss 

function...

Weitzman (2009) suggested the exponential-quadratic loss function...which allows for greater 

losses when T is large. But remember that neither of these loss functions is based on any 

economic (or other) theory. Nor are the loss functions that appear in other IAMs. They 

are just arbitrary functions, made up to describe how GDP goes down when T goes up.

The loss functions in PAGE and FUND, the other two models used by the Interagency Working 

Group, are more complex but equally arbitrary...[T]here is no pretense that the equations are 

based on any theory. [Pindyck p. 11, bold added.]

Finally, in Professor Pindyck’s conclusion he writes:
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I have argued that IAMs are of little or no value for evaluating alternative climate change 

policies and estimating the SCC. On the contrary, an IAM-based analysis suggests a level of 

knowledge and precision that is nonexistent, and allows the modeler to obtain almost any 

desired result because key inputs can be chosen arbitrarily.

Professor Pindyck demonstrates the arbitrary nature of the SCC, rendering it unfit for use by 

agencies in assessing the value of regulation.

It should be noted that just because the individual IAMs have been cited in the peer-reviewed 

literature, does not justify their use for regulation. According to the OMB’s Information Quality 

Bulletin for Peer Review, “prior peer review and publication is not by itself sufficient grounds for 

determination that no further review is necessary.”6

4Environmental Protection Agency, Benefit and Cost Analysis for the Proposed Effluent 

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

Category, p. 8-6, Apr. 2013.

5Robert S. Pindyck, “Climate Change Policy: What Do the Models Tell Us?”, Journal of Econo

mic Literature, September 2013, available at: http://web.mit.edu/rpindyck/www/Papers/ClimateChange-Policy-What-Do-the-Models- Tell-Us.pdf.

6Office of Management and Budget, Information Quality Bulletin for Peer Review, http://www.w

hitehouse.gov/sites/default/files/omb/memoranda/fy2005/m05-03.pdf.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4473-A1, Excerpt Number 1 on use of the social 

cost of carbon to provide appropriate and reasoned benefit estimates to inform policy decisions.

EPA’s analysis of the CO2-related benefits of the steam electric ELG regulation is consistent 

with consensus guidance from the Interagency Working Group on Social Cost of Carbon 

(IWGSCC, 2010; 2013). The IWGSCC had its own review and comment process (GAO, 2014) 

and comments on the development of SCC values are outside the scope of this rule.

References:

Interagency Working Group on Social Cost of Carbon (IWGSCC), United States Government. 

2010. Technical Support Document: Social Cost of Carbon for Regulatory Impact Analysis 

under Executive Order 12866. February 2010.

Interagency Working Group on Social Cost of Carbon (IWGSCC), United States Government. 

2013. Technical Update of the Social Cost for Regulatory Impact Analysis under Executive 

Order 12866. Revised November 2013.
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Government Accountability Office (GAO). 2014. Development of Social Cost of Carbon 

Estimates, GAO-14-663, July 24, 2014.

Commenter Name: Daniel Simmons

Commenter Affiliation: Institute for Energy Research

Document Control Number: EPA-HQ-OW-2009-0819-4473-A1

Comment Excerpt Number: 4

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

THE USE OF THE SOCIAL COST OF CARBON TO ASSESS REDUCTIONS 

IN CARBON DIOXIDE EMISSIONS IS NOT APPROPRIATE

Instead of providing the public with valuable information concerning actual climate change 

indicators, EPA estimated the benefits of carbon dioxide reduction using the social cost of 

carbon (SCC).

According to EPA:

The SCC is an estimate of the monetized damages associated with an incremental increase in 

carbon emissions in a given year. It is intended to include (but is not limited to) changes in net 

agricultural productivity, human health, property damages from increased flood risk, and the 

value of ecosystem services due to climate change.4

The SCC, however, it not an appropriate measure of climate change impacts. It is an arbitrary 

calculation that is not based in actual economic theory according to the peer reviewed literature.

According to a recent peer-reviewed paper by MIT economist Robert Pindyck, the so-called 

Integrated Assessment Models (IAMs), three of which the Interagency Working Group on Social 

Cost of Carbon used to estimate the SCC, are literally made up and not based on theory.

According to Professor Pindyck, the “developers of IAMs can do little more than make 

up functional forms and corresponding parameter values. And that is pretty much what they have 

done.”5

Pindyck further explains:

Most IAMs (including the three that were used by the Interagency Working Group to estimate 

the SCC) relate the temperature increase T to GDP through a “loss function” L(T), with L(0) = 1 

and L’(T ) < 0. For example, the Nordhaus (2008) DICE model uses [an] inverse-quadratic loss 

function...
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Weitzman (2009) suggested the exponential-quadratic loss function...which allows for greater 

losses when T is large. But remember that neither of these loss functions is based on any 

economic (or other) theory. Nor are the loss functions that appear in other IAMs. They 

are just arbitrary functions, made up to describe how GDP goes down when T goes up.

The loss functions in PAGE and FUND, the other two models used by the Interagency Working 

Group, are more complex but equally arbitrary...[T]here is no pretense that the equations are 

based on any theory. [Pindyck p. 11, bold added.]

Finally, in Professor Pindyck’s conclusion he writes:

I have argued that IAMs are of little or no value for evaluating alternative climate change 

policies and estimating the SCC. On the contrary, an IAM-based analysis suggests a level of 

knowledge and precision that is nonexistent, and allows the modeler to obtain almost any 

desired result because key inputs can be chosen arbitrarily.

Professor Pindyck demonstrates the arbitrary nature of the SCC, rendering it unfit for use by 

agencies in assessing the value of regulation.

It should be noted that just because the individual IAMs have been cited in the peer-reviewed 

literature, does not justify their use for regulation. According to the OMB’s Information Quality 

Bulletin for Peer Review, “prior peer review and publication is not by itself sufficient grounds for 

determination that no further review is necessary.”6

4Environmental Protection Agency, Benefit and Cost Analysis for the Proposed Effluent 

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

Category, p. 8-6, Apr. 2013.

5Robert S. Pindyck, “Climate Change Policy: What Do the Models Tell Us?”, Journal of Econo

mic Literature, September 2013, available at: http://web.mit.edu/rpindyck/www/Papers/ClimateChange-Policy-What-Do-the-Models- Tell-Us.pdf.

6Office of Management and Budget, Information Quality Bulletin for Peer Review, http://www.w

hitehouse.gov/sites/default/files/omb/memoranda/fy2005/m05-03.pdf.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4473-A1, Excerpt Number 3.

Commenter Name: Daniel Simmons

Commenter Affiliation: Institute for Energy Research

Document Control Number: EPA-HQ-OW-2009-0819-4473-A1
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Comment Excerpt Number: 6

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA FAILS TO FOLLOW OMB’S CIRCULAR A-4 ON THE PRESENTATION OF 

COST/BENEFIT ANALYSES

OMB Circular A-47 (relying in turn on Circular A-94) states that “a real discount rate of 7 

percent should be used as a base-case for regulatory analysis,” as this is the average before-tax 

rate of return to private capital investment. However, Circular A-4 acknowledges that in some 

cases, the displacement of consumption is more relevant, in which case a real discount rate of 3 

percent should be used. Thus it states: “For regulatory analysis, you should provide estimates of 

net benefits using both 3 percent and 7 percent.” Note that Circular A-4 does not say that a 

discount rate should be chosen based on the impacts; instead it says quite clearly that estimates 

should be made using both rates.

In the economics of climate change academic literature, there are disputes over the proper 

discount rate, with some economists arguing that very low rates should be used in order to place 

future generations on a nearly equal footing with the present generation in policy analysis. 

Circular A-4 and the White House’s primer on Circular A-4,8explicitly cited the work of 

Martin Weitzman, one of the leading scholars in the field on this issue, who argues for a low 

discount rate in climate change analysis.9 Nonetheless, after this discussion the 2011 primer still 

concluded:

If the regulatory action will have important intergenerational benefits or costs, the agency might 

consider a sensitivity analysis using a lower but positive discount rate, ranging from 1 to 3 

percent, in addition to calculating net benefits using discount rates of 3 percent and 7 

percent. [“Regulatory Impact Analysis: A Primer,” p. 12, bold added.]

But instead of following OMB’s guidance and calculating the social cost of carbon at a 7 percent 

discount rate, EPA refuses and only uses a 5 percent discount rate. EPA states:

Because SCC values are not available for the 7 percent discount rate, EPA used the SCC based 

on a 5 percent discount rate to estimate values presented for the 7 percent discount rate. EPA 

uses 5 percent to discount CO2-related benefits and 7 percent to discount benefits from changes 

in NOX and SO2 emissions.10

This is an arbitrary and capricious deviation from OMB’s guidance on the use of discount rates. 

EPA could have run the social cost of carbon models at a 7 percent discount rate, but it failed to 

do so.

It certainly is possible to run social costs of carbon models at a 7 percent discount rate. Recently, 

the Heritage Foundation ran the DICE model,11 one of the three models that the administration 

used to estimate the social cost of carbon. Here are the results from the DICE mode at a 2.5 
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percent, 3 percent, 5 percent, and 7 percent discount rate, according to the Heritage Foundation 

analysis.

It is easy to see why EPA would be reticent to include the 7 percent discount rate as required by 

OMB—the SCC at the 7 percent discount rate is substantially lower, at roughly only 50 percent 

of the 5 percent discount rate. This demonstrates why EPA’s exclusion of the SCC at the 7 

percent discount rate is arbitrary and capricious. Furthermore, although the Heritage Foundation 

only tested the effect of including a 7 percent discount rate using the DICE model, the results 

would presumably be even more striking had they done the same procedure with the FUND 

model. This is because the DICE projects immediate (and rising) net damages from global 

warming. In contrast, the FUND model projects decades of global benefits from global warming, 

which only switches over to net damages after the year 2050.12 Therefore, applying a 7 percent 

discount rate (rather than the highest rate of 5 percent as the Working Group chose to do) to the 

stream of benefits and damages in the FUND model, would yield a present-value SCC very close 

to $0/ton, if not negative.

7OMB Circular A-4 available at: http://www.whitehouse.gov/omb/circulars_a004_a-4.

8

“Regulatory Impact Analysis: A Primer,” available 

at: http://www.whitehouse.gov/sites/default/files/omb/inforeg/regpol/circular-a4_regulatory- impact-analysis-a-primer.pdf.

9See: http://www.whitehouse.gov/sites/default/files/omb/inforeg/regpol/circular-a- 4_regulatoryimpact-analysis-a-primer.pdf.
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10Environmental Protection Agency, Effluent Limitations Guidelines and Standards for the 

Steam Electric Power Generating Point Source Category, 78 Fed. Reg. 34432, 34517, June 7, 

2013.

11Kevin Dayaratna & David Kreutzer, Re: Social Cost of 

Carbon, http://www.scribd.com/doc/168715712/Comment-to-EPA-on-the-Social-Cost-ofCarbon-Sept-16-2013.

12See Figure 1B (page 10) from the 2010 report of the Working Group on Social Cost of 

Carbon.

Comment Response: 

See response to this question in 29.b, DCN EPA-HQ-OW-2009-0819-4473-A1, Excerpt Number 

5.

Commenter Name: Daniel Simmons

Commenter Affiliation: Institute for Energy Research

Document Control Number: EPA-HQ-OW-2009-0819-4473-A1

Comment Excerpt Number: 7

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

CONCLUSION

To assess the value of carbon dioxide reductions, the EPA should examine the impact of the rule 

on climate change indicators such as temperature and sea level rise. These factors are why 

climate change matters.

EPA should not use the social cost of carbon to value carbon dioxide reductions. The social cost 

of carbon is the result of “arbitrary functions” because it is not based on economic theory and the 

developers of the models “can do little more than make up functional forms.”13 This type of 

arbitrary modeling should not be used for cost-benefit analyses.

Furthermore, EPA’s implementation of the social cost of carbon is arbitrary and capricious. 

OMB has clearly stated that a number of discount rates could be used “in addition to calculating 

net benefits using discount rates of 3 percent and 7 percent.”14 But EPA failed to follow OMB’s 

guidance and instead omitted the calculation of the social cost of carbon at 7 percent. Because 

the social cost of carbon is much lower at a 7 percent discount rate, this omission could have the 

appearance that EPA was intentionally omitting this information from the public in an effort to 

more easily justify the regulation.
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EPA should revise this regulation to omit the use of the social cost of carbon and instead use the 

impacts on climate change indicators such as temperature and sea level rise.

13Robert S. Pindyck, “Climate Change Policy: What do the Models Tell Us?”, Journal of Econo

mic Literature,September 2013, available at: http://web.mit.edu/rpindyck/www/Papers/ClimateChange-Policy-What-Do-the-Models- Tell-Us.pdf.

14Office of Management and Budget, Regulatory Impact Analysis: A Primer.

Comment Response: 

Concerns over the use of the SCC rather than climate change indicators are addressed in the 

response to DCN EPA-HQ-OW-2009-0819-4473-A1, Excerpt Number 1.

The concern over the use of alternate discount rates is addressed in Section 29.b in response to 

DCN EPA-HQ-OW-2009-0819-4473-A1, Excerpt Number 5.

Commenter Name: Quinlan J. Shea III

Commenter Affiliation: Edison Electric Institute (EEI)

Document Control Number: EPA-HQ-OW-2009-0819-4487-A1

Comment Excerpt Number: 129

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

For example, several aspects of the air quality benefits analysis are highly uncertain. As detailed 

in UWAG’s Comments, these uncertainties are mainly related to oversimplifications in the 

modeling, assumptions regarding association of air impacts with health effects, and a highly 

uncertain interpretation of the social costs of increased CO2. This uncertainty is particularly 

significant given relatively high estimates of associated benefits, which account for 18-40% 

(depending on the option and discount rate applied) of the overall benefits associated with EPA’s 

proposal.

As another example, based on a model prediction, EPA claimed that nationally SO2 emissions 

would decrease by -0.1% and -0.2% for the ELG rule options 3 and 4, respectively, compared to 

baseline emissions. Given these small decreases and the uncertainty surrounding these estimates, 

it is likely that a sensitivity analysis that explored a large range of possible assumptions could 

show that the benefits from reduced air emissions under the ELG regulatory options as low as 

zero.
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In yet another example, EPA claimed benefits based on a social cost of carbon estimate, 

developed by an outside agency working group, without the opportunity for notice and public 

comment. This estimate has significant flaws, identified in the Gradient report attached to the 

UWAG Comments. EPA assumed benefits related to the social cost of carbon by assuming that 

the rule will result in a reduction in CO2 emissions. Like SO2, the CO2 analysis was largely 

driven by projected changes to the energy-generating profile as a result of the estimated ELG 

cost burden.

As explored further in the UWAG Comments, it is likely that plausible benefits of the various 

options, or even the basic support for the need for additional regulation, could be significantly 

lower and would be insufficient to support particular regulatory options.

Comment Response: 

The commenter argues that, because the relative changes in emissions are small, a sensitivity 

analysis exploring a large range of possible assumptions might result in air emissions benefits as 

low as zero. EPA notes that such an analysis could also show greater emission reductions and 

higher benefits. As stated in previous analyses that have relied on IPM, EPA determined the 

outputs of the model to provide reasonable estimates of changes in emissions.

Modeled emissions may increase or decrease depending on the generation mix IPM uses to meet 

demand and other constraints. Thus, for the final rule analysis, EPA estimated an increase in 

2030 of 0.1% in SO2 nationally relative to baseline emissions for Option B and a decrease of 

0.1% nationally for Option D. (See Chapter 7 in BCA for details, including discussion of the 

uncertainties). However, for pollutants for which there are systematic differences in emission 

factors between units incurring incremental costs under the ELGs (i.e., coal-fired generators) and 

other electricity generating units, any shift in generation away from the units incurring 

incremental costs will have results of a predictable direction. Thus, coal-fired generating units 

have consistently higher CO2 emission factors and changes in the generation profile away from 

coal-fired units will predictably result in lower CO2 emissions overall.

Regarding SCC values, see response to DCN EPA-HQ-OW-2009-0819-4473-A1, Excerpt 

Number 3.

Finally, for information on the role of benefits analysis in establishing effluent limitations based 

on Best Available Technology Economically Achievable (“BAT”), see response to DCN EPAHQ-OW-2009-0819-4464-A1, Excerpt Number 3.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 204

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

E. Air Quality Modeling and Impacts to Humans

Several aspects of the air quality benefits analysis are highly uncertain. This is particularly 

important because the air-related impacts account for 18-40% of the overall benefits depending 

on the option and discount rate that is applied. These uncertainties are mainly related to 

oversimplifications in the modeling, assumptions regarding association of air impacts with health 

effects, and a highly uncertain interpretation of the social costs of increased carbon dioxide 

(CO2).

EPA’s Integrated Planning Model (IPM), which was used to estimate the change in emissions of 

NOx, SO2, and CO2 for two of the eight proposed ELG options, relied on several simplifying 

assumptions regarding energy use, price points, plant characteristics, and the effect of other air 

regulations on energy generation to calculate baseline and predicted changes in conditions under 

the different regulatory options. Additionally, the IPM modeling was run for only two years 

(2020 and 2030). EPA does not specify how it extrapolated between these time points to derive 

an overall benefit over the period of interest. The impact of all of these assumptions is unclear, 

but all assumptions introduce significant uncertainty into the benefit calculations.

EPA conducted regional modeling to evaluate how modeled emissions would vary across the 

U.S. In its analysis, however, EPA evaluated benefits based on an average national 

estimate. This is misleading, because based on the model estimates, some areas of the country 

would see benefits, but others would not, leading to a disproportionate burden to some areas 

compared to others from this rule. EPA should present a range of possible benefits that would 

reflect this variability.

In the assessment of reduced mortality from changes in SO2 emissions, EPA disregarded the 

variability in regional estimates, and used linear regression to interpolate between years for 

which benefits per ton estimates were not available. Both of these assumptions decrease the 

reliability of the assessment for estimating air quality benefits. By conducting sensitivity 

analyses, if only to a limited extent (e.g., using different model inputs to gauge the impact on 

benefits calculations), EPA could have presented a range of estimates that better represent these 

uncertainties.

Additional uncertainty lies in the calculations related to the development of the benefits per ton 

estimates. One of the key sources of uncertainty is the concentration-response function (CRF) 

used to determine benefits from reduced mortality. The assumption that the CRF is linear at low 

doses (i.e., that any increase or decrease in exposure will affect risk) will misrepresent the 

benefits from low-level reductions. That is, a small reduction in PM2.5 is unlikely to confer any 

added health benefit for populations currently exposed at levels that do not pose a health 

risk. The low-dose linearity assumption is not consistent with toxicity, occupational, and human 

exposure evidence, which by and large support a threshold (i.e., the exposure level below which 

no health effects occur).
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Overall, the national results indicate that SO2 emissions would change by -0.1% and -0.2% for 

the ELG rule Options 3 and 4, respectively, compared to baseline emissions. Given these small 

decreases and the uncertainty surrounding these estimates, it is likely that a sensitivity analysis 

that explored a range of alternative plausible assumptions could show that the benefits from 

reduced air emissions under the ELG regulatory options could be as low as zero. That is, EPA 

only presents a point estimate that does not reflect the uncertainty associated with all the model 

assumptions. A range of possible benefits that reflects this uncertainty would likely include a 

zero benefit.

Also, the social cost of carbon estimates, developed by an interagency working group, accounted 

for global impacts of carbon emissions. Given the national (not international) nature of the ELG 

assessment, it would have been more appropriate to also consider national costs only, which 

would have led to a 93 to 77% reduction in estimated benefits from carbon emissions 

savings. Given the complexity of making global environmental and socioeconomic projections 

over multiple centuries, the predicted international social cost of carbon estimates are highly 

uncertain, but contribute a large portion of the estimated air-related benefit of the proposed rule.

Comment Response: 

The commenter raises issues in four principal areas, addressed in turn below:

1. Integrated Planning Model 

The commenter expresses a general concern about “several simplifying assumptions” of the 

Integrated Planning Model (IPM) without being specific about the exact nature of the concerns. 

Without more detail, EPA cannot provide a direct response to the comment. However, EPA 

notes that it has used IPM extensively over the past two decades to forecast the costs, emission 

changes, and power sector impacts of numerous regulations including the Clean Air Interstate 

Rule, Cross-State Air Pollution Rule, the Mercury and Air Toxics Standards, the proposed 

Carbon Pollution Standards for New and Existing Power Plants, the Cooling Water Intake 

Structures regulation, and the Coal Combustion Residuals regulation. As EPA noted in the RIA 

for the Clean Power Plan rule (U.S. EPA, 2014), the model and EPA's assumptions input into the 

model undergo periodic formal peer review. The rulemaking process also provides opportunity 

for expert review and comment by a variety of stakeholders, including owners and operators of 

capacity in the electricity sector that is represented by the model, public interest groups, and 

other developers of U.S. electricity sector models. The feedback that the Agency receives 

provides a highly detailed review of key input assumptions, model representation, and modeling 

results. IPM has received extensive review by energy and environmental modeling experts in a 

variety of contexts. For example, in the late 1990’s, the Science Advisory Board reviewed IPM 

as part of the CAA Amendments Section 812 prospective studies that are periodically conducted. 

The model has also undergone considerable interagency scrutiny when it has been used to 

conduct over a dozen legislative analyses (performed at Congressional request) over the past 

decade. The Agency has also used the model in a number of comparative modeling exercises 

sponsored by Stanford University’s Energy Modeling Forum over the past 15 years. Finally, IPM 

has also been employed by states (e.g., for RGGI, the Western Regional Air Partnership, Ozone 

Transport Assessment Group), other Federal and state agencies, environmental groups, and 
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industry, all of whom subject the model to their own review procedures. Given this extensive 

history, EPA determined that IPM is an appropriate tool for estimating the electricity market and 

emissions impacts of the ELGs.

Regarding the IPM run years, the commenter asserts that IPM was only run for two years, 2020 

and 2030, and that EPA does not explain how it extrapolated data from those years to other years 

in order to estimate total benefits over the analysis period. In fact, as EPA explains in Chapter 7 

of the BCA for the final rule, it used IPM outputs data for 2020, 2025, 2030, and 2040 to 

represent each of the periods 2019-2022, 2023-2027, 2028-2033, and 2034-2042, respectively. 

This is similar to the approach EPA used for the proposed rule, as was explained in the BCA.

References:

U.S. EPA. 2014. Regulatory Impact Analysis for the Proposed Carbon Pollution Guidelines for 

Existing Power Plants and Emission Standards for Modified and Reconstructed Power Plants

2. Use of national benefit-per-ton values 

The commenter expresses concerns over the application of average national estimates to estimate 

benefits. EPA notes that the commenter’s statements oversimplify EPA’s approach. As described 

in Chapter 7 of the BCA, EPA used the total national emissions, not an average across the 

regions, as the basis for estimating the benefits. For monetization, it is true that EPA used a 

uniform benefit-per-ton value but this value was derived from detailed modeling of the 

electricity generation units (EGUs) responsible for emissions in the baseline and the value 

therefore reflects the underlying spatial distribution of both the emissions sources and 

populations. To the extent that there are differences between the spatial distribution of the 

emissions changes due to the final rule and spatial distribution of the sources in the baseline, 

EPA recognizes that the benefit values may be over/understated, but the direction of the 

uncertainty is more likely to result in an underestimate of the benefits.

EPA used a benefit-per-ton value that lies at the lower end of the range of regional benefit-perton values. Table 4A-2 in the Clean Power Plan rule analysis (U.S. EPA, 2014), presents benefitper-ton values for SO2 in 2020 ranging from $38,000 to $86,000 at the national level (2011 

dollars, at 3%), and ranges of $7,800-$18,000 in the West region and $40,000-$90,000 in the 

East region (the analysis also shows the range for California of $160,000 to $360,000). By 

comparison, EPA uses a national SO2 value of $38,209 (2011 dollars) for the ELG analysis. For 

NOx, the Clean Power Plan rule analysis shows a range of $5,600 to $13,000 at the national 

level, with ranges in the West and East regions of $6,700-$15,000 and $1,200-$2,600, 

respectively. By comparison, EPA used a national NOx value of $5,576 (2011 dollars) for the 

ELG analysis. The relative comparisons hold for other years and for the 7 percent discount rates. 

In 2020, 99.7 percent of SO2 reductions and 68 percent of NOx reductions projected in IPM for 

the ELG rule occur in the East region, which has higher benefit-per-ton values for both 

pollutants. Using the lower end of the national benefit-per-ton values therefore underestimates 

the benefits.
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Thus, following the commenter’s request that EPA use a range of regional values to reflect the 

uncertainty in the estimates, EPA also calculated the benefits of changes in SO2 and NOX

emissions using emissions changes projected for each region and the corresponding low and high 

benefit-per-ton estimates. Results are shown in the table below for 2020. The table also includes 

values calculated using the national totals for comparison. As apparent by these results, not only 

are the benefit estimates EPA presented based on the national totals for the final rule reasonable, 

they are actually similar to the lower end of the range of benefits EPA would obtain using the 

approach suggested by the commenters.

Pollutant

Benefits in 2020 based 

on National Benefit-perton Values (Million, 

2013$)

Benefits in 2020 based on Regional Range 

Benefit-per-ton Values (Million, 2013$)

Low High

SO2 $217.0 $229.5 $516.4

NOX $82.7 $74.0 $165.4

TOTAL SO2+NOx $300.0 $303.5 $681.8

a. The benefits are as of 2020 and not discounted to 2015.

b. Benefit per ton estimates restated in 2013 dollars using the GDP deflator

c. Emissions changes for the East region calculated by summing changes for NERC regions 

FRCC, MRO, NPCC, RFC, SERC, SPP, and TRE; emissions changes for the West based on the 

WECC region.

d. EPA did not adjust the method used to estimate (dis)benefits from changes in air emissions 

from auxiliary power and transportation; these changes reduce the total benefits by 

approximately $4.1 million.

The commenter also expressed concerns regarding EPA’s use of a linear regression to interpolate 

data for the years when direct estimates were not available. EPA considered various possible 

functional forms and found that a linear form offered the best fit, with regression coefficients 

ranging between 0.99 and 1.0. Given small differences in values between the years, any 

uncertainty introduced by linearly interpolating between years is expected to be small.

3. Concentration-response function at low doses.

For EPA’s response to the concerns regarding the concentration-response function for low doses, 

see comment EPA-HQ-OW-2009-0819-4655-A2, Excerpt Number 37.

4. Use of global impacts of carbon emissions to support decisions on national policies.

EPA recognizes that the final rule is a matter of domestic policy, not international; however, as 

stated by the Interagency Working Group on Social Cost of Carbon (IWGSCC), the issue of 

climate change is unusual in that it involves a global externality and cannot be solved solely by 
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the United States. The IWGSCC acknowledges the OMB guidance in Circular A-4 which 

requires a domestic perspective for analyses, while making an international perspective optional, 

but after taking these and other issues into consideration IWGSCC concludes that relying on the 

global measure of benefits from reducing U.S. emissions is preferable (IWGSCC, 2013). 

Therefore, EPA relied on the guidance of the IWGSCC and used social cost of carbon values that 

incorporate a global measure of benefits for estimation of CO2 emissions impacts for the final 

rule.

Interagency Working Group on Social Cost of Carbon (IWGSCC), United States Government. 

2013. Technical Update of the Social Cost for Regulatory Impact Analysis under Executive 

Order 12866. Revised November 2013.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A2

Comment Excerpt Number: 7

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Air Quality Modeling and Impacts to Humans

Several aspects of the air quality benefits analysis are highly uncertain. This is particularly 

important because the air-related impacts account for 18-40% of the overall benefits depending 

on the option and discount rate that is applied. These uncertainties are mainly related to 

oversimplifications in the modeling, assumptions regarding association of air impacts with health 

effects, and a highly uncertain interpretation of the social costs of increased CO2. More 

specifically:

 US EPA's Integrated Planning Model (IPM), which was used to estimate the change in 

emissions of NOx, SO2, and CO2 for two of the eight proposed ELG options, relied on 

several simplifying assumptions regarding energy use, price points, plant characteristics, 

and the effect of other air regulations on energy generation to calculate baseline and 

predicted changes in conditions under the different regulatory options. Additionally, the 

IPM modeling was run for only two years (2020 and 2030). US EPA does not specify 

how it extrapolated between these time points to derive an overall benefit over the period 

of interest. The impact of all of these assumptions are unclear, but all assumptions 

introduce significant uncertainty into the benefit calculations.

 US EPA conducted regional modeling to evaluate how modeled emissions would vary 

across the US. In their analysis, however, they evaluate benefits based on an average 

national estimate. This is misleading, because based on the model estimates, some areas 

of the country would see benefits, but others would not, leading to a disproportionate 

burden to some areas compared to others from this rule. US EPA should present a range 

of possible benefits that would reflect this variability.
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 In the assessment of reduced mortality from changes in SO2 emissions, US EPA 

disregarded the variability in regional estimates, and used linear regression to interpolate 

between years for which benefits per ton estimates were not available. Both of these 

assumptions decrease the reliability of the assessment for estimating air quality benefits. 

By conducting sensitivity analyses, if only to a limited extent (e.g., using different model 

inputs to gauge the impact on benefits calculations), US EPA could have presented a 

range of estimates that better represent these uncertainties.

 Additional uncertainty lies in the calculations related to the development of the benefits 

per ton estimates. One of the key sources of uncertainty is the concentration-response 

function (CRF) used to determine benefits from reduced mortality. The assumption that 

the CRF is linear at low doses (i.e., that any increase or decrease in exposure will affect 

risk) will misrepresent the benefits from low-level reductions. That is, a small reduction 

in PM2.5 is unlikely to confer any added health benefit for populations currently exposed 

at levels that do not pose a health risk. The low-dose linearity assumption is not 

consistent with toxicity, occupational, and human exposure evidence, which by and large 

support a threshold (i.e., the exposure level below which no health effects occur).

 Overall, the national results indicate that SO2 emissions would change by -0.1% and -

0.2% for the ELG rule Options 3 and 4, respectively, compared to baseline emissions. 

Given these small decreases and the uncertainty surrounding these estimates, it is likely 

that a sensitivity analysis that explored a range of alternative plausible assumptions could 

show that the benefits from reduced air emissions under the ELG regulatory options 

could be as low as zero. That is, US EPA only presents a point estimate that does not 

reflect the uncertainty associated with all the model assumptions. A range of possible 

benefits that reflects this uncertainty would likely include a zero benefit.

 The social cost of carbon (SCC) estimates, developed by an interagency working group, 

accounted for global impacts of carbon emissions. Given the national (not international) 

nature of the ELG assessment, it would have been more appropriate to also consider 

national costs only, which would have led to a 93 to 77% reduction in estimated benefits 

from carbon emissions savings. Given the complexity of making global environmental 

and socioeconomic projections over multiple centuries, the predicted international SCC 

estimates are highly uncertain, but contribute a large portion of the estimated air-related 

benefit of the proposed rule.

Comment Response: 

See responses to comments EPA-HQ-OW-2009-0819-4655, Excerpt Number 204 and EPA-HQOW-2009-0819-4487-A1, Excerpt Number 204.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A2

Comment Excerpt Number: 37

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

In Section XIV of the proposed ELG rule, benefits related to air quality (NOx, SO2, and CO2) are 

estimated for regulatory Options 3 and 4 (see Table XIV-6). In our comments, we have not 

addressed whether it is appropriate or not to include air-related benefits in the cost-benefit 

associated with ELGs as air emissions and impacts on air quality are covered by other regulatory 

actions that specifically address these impacts. Instead, we have focused on the scientific merit of 

US EPA's analysis and some of the technical issues associated with the development of the airrelated impacts. Under the proposed regulatory options, US EPA has determined that the benefits 

related to air quality improvements are substantial. Depending on the option and applied discount 

rate, air quality improvements are projected to account for 36-40% of the total benefit for Option 

3 and 18-28% for Option 4. For both of these options, most of the air quality benefits stem from 

the assumption of increased operating costs associated with implementation of the ELG rule that 

would result in an overall shift in the electricity generating profile in the US, resulting in reduced 

SO2 and CO2 emissions.6 These estimated improvements to air quality are based on a number 

oversimplified analyses conducted for baseline (current) conditions and purported improvements 

to air quality as a result of the ELG rule. As acknowledged by US EPA, reduction in emissions 

are very small, both compared to baseline emissions and relative to overall industry-wide 

emissions (e.g., less than 0.1%). These small air quality improvements, however, are then 

translated to large estimates of improved health, generating large benefits because of the use of 

conservative modeling assumptions. Specifically, these analyses, are subject to a high degree of 

conservatism and uncertainty (e.g., use of a linear CRF) which likely overestimated the total 

benefits. The uncertainty in the benefit is not reflected in the point estimates presented by US 

EPA for the two options considered in this analysis. That is, in the face of these uncertainties and 

conservatisms, US EPA conducts no sensitivity analyses to determine how using different model 

inputs would impact the benefits estimates. Without such an analysis, the air-benefits analysis is 

highly uncertain and an ineffective metric for use in the ELG rule making.

The sections below focus on the air-related benefits from reduced SO2 and CO2 emissions from 

the assumed change in electricity generation profiles. We focus on SO2 (although US EPA also 

included NO2) because the net SO2 emission reductions account for the large majority of the airrelated benefits for Option 3, and 50% or more of the benefits for Option 4, depending on the 

discount rate. The rest of the benefits are from reductions in CO2 emissions (US EPA, 2013d, 

Table 8-8). For example, for Option 3 and a discount rate of 3%, SO2 benefits are 75% of the 

total benefits and CO2 benefits make up the other 25% (small negative benefits were calculated 

for NOx increases). For Option 4 and a 3% discount, SO2 benefits are 47% of the total, and CO2

benefits are 53% of the total estimated benefits. Air-related benefit calculations were not 

performed for the other proposed alternatives, but US EPA expected these benefits to be relevant 

for understanding the preferred Options 3a, 3b, and 4a as well.

Section XIV(B)(5). Air-Related Benefits (Reduced Mortality)

The overall methodology used by US EPA to calculate the benefits from reduced SO2 emissions 

involved both an estimate of reduction in nationwide emissions from the changed electricity 

generation profile and an analysis of how these emissions translated into health benefits. More 

specially, as described in Section 8 of the Benefit and Cost Analysis for Proposed ELGs (US 
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EPA, 2013d), in the initial step, US EPA estimated SO2 reductions using the IPM. Although, 

typically more extensive analyses are conducted to estimate benefits from reduced emissions, US 

EPA instead used a simplified or "reduced-form" approach to estimate benefits. Specifically, it 

obtained "benefits per ton" estimates for electricity generating units (EGUs) reported by Fann et 

al. (2012). Benefit per ton estimates relate the reductions in air emissions (in this case, SO2) to 

reduced mortality from PM2.5 exposure. That is, SO2 emissions are converted to PM2.5 and it is 

the reduction in PM2.5, as a result of reduced SO2, and its relationship to mortality that forms the 

basis for the estimated air-benefits). The final benefits calculation simply involved multiplying 

the benefits per ton estimates for EGUs by the tons of SO2 reduced (generated from the IPM 

model) to obtain the overall benefits associated with SO2. The key assumptions associated with 

this simplified methodology and implications of these methodologies are discussed in more 

detail below.

[...]

Although the results generated by the IPM model reflect rough projections, it is noteworthy that 

when compared to actual 2009 industry-wide emissions, the model predicted that net reductions 

in SO2 were a very small fraction of overall EGU emissions. For example, under Options 3 and 

4, SO2 emissions are estimated to represent only 0.045% and 0.055% of overall industry-wide 

emissions, respectively (US EPA, 2013b). Such small net contributions to overall emissions 

suggest that the impact of ELG is minimal and raises questions regarding the validity of the large 

air-related benefits (i.e., whether such a small incremental change in air emissions would have a 

true public health benefit).

Moreover, regional analyses conducted by US EPA demonstrated significant variability across 

regions. For SO2 the emissions ranged from -1.9 to 0.3% for Option 3, and from -2.2 to 1.2% for 

Option 4. This indicates that in different regions of the US, net SO2 emissions actually can vary 

from a net reduction in emissions to a net increase in emissions. Similar results were obtained for 

the "transition" 2020 year analysis. Because of regional heterogeneity (showing both increases in 

emissions or decreases), it is not appropriate for US EPA to quantify the health associated 

benefits based on average national emissions. At the very least, US EPA should provide a range 

of benefits that would reflect the heterogeneity observed across different regions of the US, and 

even account for the reduced benefit that would be experienced by certain segments of the 

population.

Uncertainty in the Benefits per Ton Estimates

US EPA's "benefit per ton" estimate for the proposed ELG rule is largely based on a publication 

by Fann et al. (2012). Fann et al. (2012) estimated benefit per ton estimates from point and 

mobile sources, including electric utilities, with special consideration of the dynamic conversion 

of various air contaminants (including SO2) to PM2.5, which is the air fraction that ultimately 

links SO2 to health effects.

There are several key uncertainties related to how US EPA applied the estimates from Fann et al. 

(2012) to estimate benefits per ton under the ELG options. Importantly, US EPA's analysis rests 

on two key assumptions that introduce substantial uncertainty into the analysis:
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 A significant uncertainty in the reduced-form approach that US EPA used, is that the 

assumptions that went into key model attributes such as population distributions, 

meteorology, and source parameters (e.g., plant stack heights) between the ELG 

calculated emissions reductions and the emissions reductions estimated by Fann et al.

(2012). This assumption is not necessarily valid. For example, Fann et al. (2009) 

demonstrated significant variability in the estimated benefits per ton across different 

urban areas to show how these assumptions could impact the benefits per ton estimates. 

For SO2 emissions (reported as sulfur oxides or SOx) from EGUs, the benefits ranged 

from $6,300/ton in Seattle to $350,000/ton in San Joaquin (2006$, 3% discount rate and 

based on the mortality estimate from Laden et al., 2006). Therefore, if the assumptions 

used in the US EPA analysis are not the same as those in the Fann et al. (2012) analysis, 

the calculated estimates could be significantly under or overestimated. Without any 

sensitivity analyses to show how this might impact the benefits calculations there is no 

way to know the magnitude or direction of this source of uncertainty. The second source 

of uncertainty is related to the use of linear regression to interpolate between years for 

which benefits per ton estimates were not available [because estimates were obtained 

from Fann et al. (2012) only for the years 2020, 2025, and 2030]. As 

discussed by US EPA, this introduces additional uncertainty because the benefits p

er ton estimates do not account for air quality changes that vary from year to year (US 

EPA, 2013d). Also, the assumption that changes in air emissions is linear between years 

may not be valid. US EPA indicated that the impact of this is uncertain and that annual 

estimates should be considered "rough estimates" (US EPA, 2013d, pg. 8-11).

US EPA did not attempt to quantify these sources of uncertainty in the aforementioned 

assumptions nor fully discuss their impact on benefits calculations. By conducting sensitivity 

analyses, if only to a limited extent (e.g., using different model inputs to gauge the impact on 

benefits calculation), US EPA could have presented a range of estimates that better reflect 

uncertainties in the adaption of estimates of Fann et al. (2012) to the analysis in the supporting 

documentation for the ELG rule.

In addition to issues with the application of the model from Fann et al., uncertainty lies in model 

itself. Specifically, the model relies on an air quality model inputs that tends to overestimate the 

benefits of reduced air emissions, as well as the unsupported assumption that the function 

between reduced PM2.5 emissions and morality is linear, such that any reduction PM2.5 will also 

have a health benefit. These issues are discussed below.

Air Quality Model

 Fann et al. (2012) developed benefits per ton estimates using the Comprehensive Air 

Quality Model with Extensions (CAMx) air quality model together with a 

particulate source apportionment technology (PSAT) module within CAMx to estimate 

emissions from different sources. This model approach estimates the contributions from 

precursor emissions (e.g., NOx and SO2) to modeled concentrations of PM2.5. As 

discussed by Fann et al. (2012), the selection of air quality model can have a significant 

impact on benefits per ton estimates. There is no consensus air quality model to estimate 

changes in PM2.5 concentrations from changes in precursor emissions such 
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as SO2. Researchers have attempted to validate these models by comparing multiple 

estimated concentrations to field measured air concentrations. For example, Koo et al. 

(2009) compared the emissions reductions predicted by different air quality models, 

including the PSAT approach used by Fann et al. (2012), and reported that for SO2-

related PM2.5 (PM2.5–sulfate) the PSAT approach showed higher source contributions 

than those estimated by other more reliable models. In another study, Baker and Scheff 

(2007) showed a regional over- prediction by the CAMx air quality model compared to 

measured concentrations. Therefore, based both on comparisons across different air 

quality modeling approaches as well as comparisons with measured air concentrations, 

the air quality modeling approach used by Fann et al. (2012) likely over-predicted PM2.5-

sulfate emissions associated with EGUs. This in turn, resulted in overestimated benefits 

per ton values that US EPA used in its benefits calculations.

Concentration-Response Function

 One of the largest sources of uncertainty in the benefits estimation is the choice of health 

impact function or CRF that relates the reduction in air concentrations to reductions in 

adverse health outcomes. Fann et al. (2012) used BenMAP to estimate the health impacts 

and associated monetary values. BenMAP applies CRFs that are derived from 

epidemiology studies. In this case, Fann et al. (2012) selected the study by Krewski et al. 

(2009) as the source of this CRF. Krewski et al. (2009) reported a weak but statistically 

significant association between PM2.5 concentrations and all-cause mortality. However, 

this study has several methodological limitations that affect the interpretation of results. 

These include issues with the proper control 

for confounders, exposure measurement error, model selection error, and assumptio

ns of 

linearity. By effectively ignoring these limitations, benefits estimates are likely to b

e overestimated.

 One important issue is confounding. PM mortality studies are subject to confounding 

bias. There is evidence that co-pollutants can confound the PM mortality association, 

especially because many of the pollutants are strongly correlated, and disentangling the 

effects of any single pollutant (if any) is difficult (e.g., Krewski et al., 2000; Burnett et 

al., 2004). The issue of confounding is important because it relates both to the assumption 

of causality, where another factor may actually be the causal agent, and to the magnitude 

of the association, where a co-factor may account for some of the observed risk. In either 

case, ignoring the effects of confounding caused by co-pollutant results in overstated 

benefits estimates. US EPA should discuss the potential role that confounding effects 

could affect the estimated benefits.

 Exposure measurement error is another important limitation. The study by Krewski et al. 

(2009) also relies on data from central-site monitors to estimate personal exposures, 

which can results in exposure measurement error. The direction and magnitude of the 

bias depends on the type of measurement error. For PM2.5, however, because of the 

spatial variability of air pollutant concentrations the bias is likely to result in effects being 

overestimated (Goldman et al., 2011; Rhomberg et al., 2011). Because the estimated 

mortality risk is so small, it is possible that exposure measurement error accounts for 

some or all of the observed risks.
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 An additional source of uncertainty that is not discussed by US EPA involves how 

different statistical models impact epidemiology findings. To address this question, 

Krewski et al. (2009) conducted extensive sensitivity analyses, including tests of the 

effects of various model assumptions (e.g., lags and smoothing functions for time trends), 

to assess the impacts on health estimates. Krewski et al. (2009) showed that statistical 

model assumptions impact the mortality risks. US EPA should provide some discussion 

on the appropriateness of the selected model in the context of the proposed ELG rule, and 

explore how different models may have produced different outcomes.

Lastly, another important assumption is that CRFs are linear at low PM2.5 concentrations, 

meaning that health outcome is directly proportional to the ambient air pollutant concentration. 

This is not consistent with toxicity, occupational, and human exposure evidence, which by and 

large support a threshold (i.e., the exposure level below which no health effects occur). For 

example, toxicity studies demonstrate that the physiological impact of inhaled air pollutants 

results from overwhelming the lung's natural defense mechanisms (e.g., Oberdorster, 1996, 

2002; Pauluhn, 2012; Valberg et al., 2009). In actuality, a small reduction in SO2, as has been 

estimated by US EPA (less than 0.1%, on average), and the resulting reduction in PM2.5 will 

likely not confer any added health benefit for most individuals, and particularly those individuals 

currently exposed below levels of public health significance. Traditionally, estimating the 

benefits associated with reductions in air pollution levels involves complex air models and 

benefits analyses software. Instead of relying on these more complex models, US EPA used a 

reduced-form approach to estimate air-related benefits from the ELG rule. In doing so, US EPA 

made a number of assumptions that may not be valid and provided no scientific support for these 

assumptions. Importantly, US EPA did not discuss or consider numerous sources of uncertainty 

at each stage of the benefits calculation, including the choice of air quality model, CRF, and 

valuation methods (not discussed in these comments). As acknowledged by US EPA, net 

changes in the emissions of SO2 were estimated to be very small as a result of the ELG rule, and 

represent much less than 0.1% of industry-wide emissions. Given this small increase (which has 

a significant effect on the overall benefits calculation) and large amount of uncertainty 

surrounding this value, US EPA should include a sensitivity analyses into the proposed rule to 

determine uncertainty bounds for the estimated benefits.

Section XIV(B)(5). Air-Related Benefits (Avoided Climate Change Impacts)

Using the IPM model (discussed above) US EPA also calculated the expected reduction in CO2

emissions (in metric tons CO2 per year through the year 2040). Like SO2, the CO2 analysis was 

largely driven by projected changes to the energy-generating profile as a result of the estimated 

ELG cost burden. This estimate was then multiplied by the SCC [as estimated by the Interagency 

Working Group on Social Cost of Carbon (IWGSCC) (IWGSCC, 2010)]. The Social Cost of 

Carbon (SCC) comprises a net cost/benefit analysis for incremental CO2 emissions that 

considers, among other impacts:

 Changes to net agricultural productivity

 Human health

 Property damages from increased flood risk

 Value of ecosystem services due to climate change
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The values established by the IWGSCC were developed to support rule-making activities related 

to CO2 emissions across the agency (i.e., the derived values were not developed for the ELG 

analysis, specifically). Thus our analysis below remarks on general limitations of the SCC values 

developed by IWGSCC. Where applicable we note the implications of these uncertainties for the 

proposed ELG rule.

 To calculate the SCC, the underlying models "translate emissions into changes in 

atmospheric greenhouse concentrations, atmospheric concentrations into changes in 

temperature, and changes in temperature into economic damages" (IWGSCC, 2010, pg. 

5). US EPA's estimate of the social cost of carbon deviates from the guidelines of OMB 

Circular A-4 by incorporating global rather than domestic cost. Accounting for estimated 

global costs, though appropriate given the global nature of climate change concerns, is 

also a conservative choice for domestic decision making, and adds to uncertainty in the 

overall estimate by requiring socioeconomic projections in unpredictable economies. The 

working group proposed that the domestic SCC would be approximately 7-23% of the 

global SCC. Given that the proposed ELG rule is national, rather than international in 

scope, it would have been appropriate for the US EPA to adjust the SCC values to reflect 

national benefits only—effectively that would reduce CO2 related savings estimated for 

the proposed rule by 93 to 77%.

 The SCC values developed by the working group reflect the average results from three 

underlying integrated assessment models. Several important points should be noted here. 

First, the 3 models differ in their underlying assumptions (e.g., how regional damages are 

calculated as a function of GDP, whether the rate of temperature change is taken into 

account, or whether temperature affects consumption and investment). As a result, the 

three models differ strikingly in their predicted SCC, particularly at low to intermediate 

levels of temperature change (< 3 °C). For context, an increase of 3 °C is the most likely 

value predicted by Solomon et al. (2007) for a doubling of atmospheric CO2, which is 

clearly much higher than the range of carbon emissions being considered as a result of 

the proposed ELGs. Solomon et al. (2007) predicts that warming over the next several 

decades will be 0.1 to 0.2 °C per decade; this means that predicted temperature increases 

over the next several hundred years are well within the range of substantial disagreement 

between SCC models. In fact, one of the three models predicts a net economic benefit 

from additional carbon emissions in this range, attributed to beneficial impacts such as 

CO2 fertilization of agricultural productivity.

 In addition to model selection, the choice of a discount rate has a significant impact on 

the ELG benefits calculation. The appropriate choice of discount rate for climate 

impacts is highly disputed among economists, particularly in light of the 

intergenerational nature of potential future costs of climate change (IWGSCC, 2010) and 

leads to a factor of 3-7 difference in estimated benefits due to CO2 reduction from the 

proposed ELGs. Variability between and within each model depends on the discount rate 

chosen; at higher discount rates, a greater proportion of the present value cost is related to 

costs incurred in the near term when the cumulative temperature change is low (and when 

other socioeconomic parameters are more predictable). This means that a lower discount 

rate leads to higher predicted costs and creates more emphasis on predictions further in 

the future, about which there is greater uncertainty. US EPA considered a 3% discount 

rate and a 7% discount rate (which was calculated based on the 5% discounted SCC) in 
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their final cost benefit assessment. US EPA should provide further justification for their 

choices of discount rates for this issue and discuss the implications of their choice, 

particularly considering the higher uncertainty associated with air-related benefit 

estimates at the lower discount rate.

6 The calculation of air benefits involved the evaluation of three mechanism that US EPA 

(2013c) assumed would affect air emissions: "1) additional auxiliary electricity use by steam 

electric plants to operate wastewater treatment, ash handling, and other systems needed to 

comply with the new effluent limits and standards; 2) additional transportation-related emissions 

due to the increased trucking of coal combustion residue (CCR) waste to on-site or off-site 

landfills; and 3) the change in the profile of electricity generation due to relatively higher cost to 

generate electricity at plants incurring compliance costs for the proposed ELGs." Because most 

of the air quality benefits are driven by changes in SO2 and CO2 from mechanism #3 (the change 

in energy profile), we have focused our analysis on these issues. Changes in NO2 emissions from 

all three mechanisms, and changes in SO2 emissions from mechanisms #1 and #2 did not 

contribute significantly to the benefits analysis or were associated with net cost.

Comment Response: 

Regarding the concern that EPA did not conduct sensitivity analyses, see response to DCN EPAHQ-OW-2009-0819-4655-A2, Excerpt Number 42 (in comment code 28.c) which discusses 

related comments on sensitivity analyses for Integrated Planning Model (IPM) runs. Also see 

response to DCN EPA-HQ-OW-2009-0819-4655, Excerpt Number 204 (in comment code 29.h) 

for additional discussion of the use of the Integrated Planning Model to support the air-related 

benefit analyses, use of national benefit-per-ton values, and use of values that reflect global 

impacts of carbon emissions.

The commenter raises several concerns regarding the methodology used to quantify and 

monetize air-related human health benefits, which the commenter suggests results benefits being 

overstated. The three concerns raised by the commenters are addressed below:

1. Uncertainty in the Benefits per Ton Estimates. The commenter points to two specific sources 

of uncertainty in the application of benefit-per-ton estimates from Fann et al., notably the 

variability of benefit-per-ton values across areas of the country and use of linear interpolation of 

the benefit-per-ton estimates between years. Regarding the first source of uncertainty, EPA notes 

that the national value used for the steam electric ELG analysis actually falls toward the low end 

of the range and using regional values would likely yield higher benefit estimates. See response 

to DCN EPA-HQ-OW-2009-0819-4655, Excerpt Number 204 for more details on differences 

between national and regional benefit per ton estimates. Regarding the second source of 

uncertainty, which relates to the assumption of linearity in benefit per ton values over time, EPA 

recognizes that the values projected for any given future year do not account for potential 

changes in atmospheric conditions over time, but maintains that the analysis provides a 

reasonable basis for estimating the general magnitude of benefits resulting from the regulation 

where those changes represent marginal increases or decreases as is the case for the final ELGs.
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2. Uncertainty inherited from the air quality model. Fann et al 2012 includes supporting 

information that presents model performance for sulfate and nitrate. EPA notes the greater 

confidence in the level and distribution of EGU emissions of NOX and SO2, since these sources 

are stationary and monitored, in turn making the Agency more confident in the magnitude of the 

benefit per ton estimates for this sector.

3. Uncertainty associated with the choice of a response function. After reviewing the entire body 

of hundreds of peer-reviewed clinical, toxicological and epidemiological studies on PM2.5-related 

health effects, EPA concluded that PM2.5 is causally associated with a variety of health effects, 

including premature mortality. EPA’s independent Science Advisory Board agreed with this 

conclusion. For benefits analysis, EPA use mortality risk estimates from the American Cancer 

Society cohort (Pope et al. 2002) and the Harvard Six Cities cohort (Laden et al, 2006), which 

are seminal long-term multi-city cohort studies that have been extensively validated and reanalyzed by other investigators. EPA’s choice of two epidemiology studies for assessing 

mortality benefits was supported by separate panels of EPA’s independent Science Advisory 

Board (CASAC, reviewing the PM Risk and Exposure Assessment, and Council, reviewing the 

Costs and Benefits of the CAA).

Based on our review of the current body of scientific literature, EPA estimated PM-related 

mortality without applying an assumed concentration threshold. The PM Integrated Science 

Assessment, which was reviewed by EPA’s Clean Air Scientific Advisory Committee, 

concluded that the scientific literature consistently finds that a no-threshold log-linear model 

most adequately portrays the PM-mortality concentration-response relationship while also 

recognizing potential uncertainty about the exact shape of the concentration-response function.

For response to concerns regarding the use of SCC to value reductions in CO2 emissions, see 

response to comments EPA-HQ-OW-2009-0819-4473-A1, Excepts 1 and 5 (in Section 29.b).

Cited Literature:

Pope, CA III, Burnett RT, Thun MT, Calle EE, Krewski DD, Ito K, and Thurston GD 2002. 

Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. 

Journal of the American Medical Association 287:1132-1141.

Laden, F, Schwartz J, Speizer FE, and Dockery DW 2006. Reduction in fine particulate air 

pollution and mortality. American Journal of Respiratory and Critical Care Medicine 173:667-

672.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 38

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

Reduced mortality from exposure to NOx, SO2 and particulate matter and reduced CO2 

emissions resulting in avoided climate change impacts: EPA also underestimates the benefits 

associated with reduced mortality from exposure to NOx, SO2 and particulate matter (PM2.5) as 

well as from avoided climate‐change‐related impacts. EPA uses IPM modeling to determine air 

emissions reductions from the steam electric ELGs. The IPM analysis includes emission factors 

known to be highly variable and sometimes incomplete.79 In addition, EPA assumes a linear 

relationship between CO2 emissions and benefits, which may underestimate the value of large 

changes in emissions.80 EPA also uses the 2010— now outdated—per ton estimates of the social 

cost of carbon. In the latest estimates released by the Interagency Working Group, the 2020 

social cost of carbon at the 3‐percent discount rate has risen from $27 to $45 (by 65 

percent);81 benefits of reduced CO2 emissions due to the proposed ELGs would, therefore, be 65 

percent higher.

EPA points to several other deficiencies in their air quality analysis: “This analysis does not 

include all of the human health benefits associated with air pollution reductions because the 

benefits per ton estimates that were used are based only on mortality, and not morbidity 

endpoints. Thus the quantified human health benefits included in this analysis represent only a 

subset of the total potential health benefits expected to result from the proposed 

ELGs.”82 Correction of these assumptions would increase the expected benefits from reduced air 

emissions associated with this rulemaking. Assuming that Option 5 would have, at a minimum, 

the same air‐benefits as Option 4, raises the Option 5 benefits by 39 percent to $605 million. 

This single change raises the Option 5 benefit‐cost ratio from 0.19 to 0.26.

79 EPA Office of Inspector General Report No. 2006‐P‐00017, ”EPA Can Improve Emissions 

Factors Development and Management.” March 22, 2006. And EPA Office of Inspector General 

Report No. 13‐P‐0161, “EPA Needs to Improve Air Emissions Data for Oil and Natural Gas 

Production Sector.” February 20, 2013.

80 Benefit‐Cost Analysis, p.8‐9, Table 8‐9.

81 2010 Interagency Working Group 2020 social cost of carbon (in 2010$) is $28 (see Benefit‐

Cost Analysis, p.8‐7, Table 8‐6. 2013 Interagency Working Group 2020 social cost of carbon (in 

2011$) is $46 (see 

http://www.epa.gov/climatechange/EPAactivities/economics/scc.html); converted to 2010$ using 

the CPI‐U (see ftp://ftp.bls.gov/pub/special.requests/cpi/cpiai.txt).

82 Benefit‐Cost Analysis, p.8‐9, Table 8‐9.

Comment Response: 

The commenter raises three key concerns regarding EPA’s analysis of the human health benefits 

resulting from air quality improvements.
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First, the commenter expresses concerns that the emission factors used in IPM are variable and 

incomplete. IPM does not use “emissions factors” per se for those pollutants that are direct 

output of the model, namely SO2, NOX, Hg, CO2, and HCl. For NOx and for the overwhelming 

majority of the fossil fleet (e.g., Electricity Generating Units (EGUs) larger than 25 MW), 

reported emissions are available through Continuous Emissions Monitoring and those historical 

emissions form the basis of EGU emissions projections. For SO2, projected unit level emissions 

are also based on permits. Only in those cases where historical reported emissions are not 

available (usually smaller oil and gas units) does IPM use available emission factors and EPA 

strives to update and improve those emission factors with each IPM platform update based on the 

most current information and comments received. Therefore, for SO2 and NOX (as well as for 

CO2, HG and HCl which are the direct outputs of the IPM model), uncertainty in emission rates 

is very low, especially for the large coal and natural gas units which makes up the overwhelming 

portion of the total emissions. For all EGUs, primary PM emissions are post-calculated and the 

uncertainty associated with those primary PM emissions maybe somewhat higher than the direct 

model outputs of SO2 and NOX. However, primary PM emissions from power sector are small 

compared to secondary PM formation in the atmosphere through photochemical processes. 

Detailed information on IPM inputs, outputs and documentation can be found at: 

http://www.epa.gov/powersectormodeling/

The referenced report by the Office of Inspector General (footnote 79) relates to oil and gas 

production, not emissions resulting from the combustion of oil and gas in the electric power 

sector for which IPM is used. Further, the referenced OIG report covers inventories up through 

2008. There have been many improvements since the referenced report was written.

Second, the commenter notes that EPA used outdated values of the Social Cost of Carbon (SCC). 

These values were revised after EPA completed its analysis of the proposed rule. For the final 

rule, EPA used the revised SCC estimates to estimate the benefits of CO2 emission reductions 

associated with ELG implementation (IWGSCC, 2013). See Chapter 7 of the BCA for details.

Third, the commenter notes that focusing strictly on mortality understates the benefits of air 

quality improvements. This would be true if it were the case. In fact, the benefit-per-ton 

estimates EPA used to estimate benefits reflect not only mortality but also morbidity endpoints 

(e.g., asthma); this limitation was erroneously left in Table 8‐9 from a draft version, even though 

EPA had subsequently updated the benefit-per-ton values to provide a more comprehensive 

measure of the benefits. EPA apologizes for its oversight and any resulting misinterpretation. 

The final rule analysis uses benefit-per-ton estimates that reflect mortality and a variety of 

morbidity endpoints (see Chapter 7 of the BCA).
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29.i. Benefits – Benefits from reduced water withdrawals

Commenter Name: Becky Hayat

Commenter Affiliation: Natural Resources Defense Council (NRDC)

Document Control Number: EPA-HQ-OW-2009-0819-4490-A1

Comment Excerpt Number: 18

External Review Flag: Economics/Benefits

External Review Incorporated into Response: No

Comment Excerpt: 

Potential water savings under Options 4 and 5 will have an especially constructive impact on 

water-scarce regions of the U.S. 

In the southeastern and southwestern U.S., where the water-energy nexus problem is most 

visible, the benefit of reduced water withdrawals will be especially useful. In the past decade, the 

southeast has experienced particularly acute drought conditions and continues to suffer problems 

of decreasing water availability. In the southwest, where surface water resources are stretched 

thin, there is little available to meet growing demand, including new power sector needs. Even 

without factoring in the exacerbating role of climate change, water supply conflicts involving 

several major Southwest cities –including Denver, Albuquerque, Las Vegas, and Salt Lake City–

are considered highly likely by 2015.35 Thus, if EPA selected Option 5, or at a minimum Option 

4, as the final rule, the resulting water savings will be especially helpful for those states facing 

deepening challenges posed by the water dependency of steam electric power plants.

35 Union of Concerned Scientists, The Energy-Water Collision: Power and Water at Risk (June 

2011).

Comment Response: 

The commenter discusses issues of water scarcity in certain regions of the U.S. and argues that a 

final rule that reduces water withdrawals will help states facing such water issues. EPA agrees 

that reducing plant dependence on water can help improve water scarcity issues or mitigate their 

effects. Reducing the quantity of intake water also benefit power plants directly by making the 

plants less susceptible to drought-induced reduction in generation or unit closures and by 

reducing the cost associated with finding replacement water sources. For more details on these 

impacts, see paper titled “Water Withdrawals in Water Stressed Areas: Impacts of the Steam 

Electric Effluent Limitations Guidelines” (DCN SE05943) in the record for the final steam 

electric ELG rule.

Benefits would be highly location specific. EPA estimated that the final rule will reduce water 

withdrawals by 155 million gallons per day; relative to total surface water withdrawals for 

thermoelectric plants of 116 billion gallons per day in 2010 (Maupin et al, 2014) (which are 

primarily for cooling purposes), or a reduction of 0.1 percent.
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These changes are small, but will nonetheless marginally reduce the water dependency of steam 

electric power plants in water scarce regions.

Maupin, M.A., Kenny, J.F., Hutson, S.S., Lovelace, J.K., Barber, N.L., and Linsey, K.S., 2014, 

Estimated use of water in the United States in 2010: U.S. Geological Survey Circular 1405, 56 

p., http://pubs.usgs.gov/circ/1405/.

Commenter Name: Becky Hayat

Commenter Affiliation: Natural Resources Defense Council (NRDC)

Document Control Number: EPA-HQ-OW-2009-0819-4490-A1

Comment Excerpt Number: 19

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Based on responses from the technical questionnaire of the Electric Steam industry survey, the 

Allen Steam Station, located in Belmont, NC and employing a wet fly ash handling system, 

reported that it generates approximately 9.61 MGD of fly ash transport water. The plant also 

indicated that 100% of its source for fly ash transport water is intake water, none of which is 

recycled back to the plant process. If the Allen plant were to comply with the effluent limitations 

standard pursuant to Options 4 or 5, it would most likely convert its existing fly ash wet handling 

system to a dry handling method and potentially reduce its water use by 9.61 MGD. In addition, 

the Marshall Steam Station, located in Terrell, NC reported that it, too, uses wet fly ash handling 

methods and generates approximately 10.56 MGD of fly ash transport water. The Marshall plant 

also draws its fly ash sluice water from nearby surface waters, and does not engage in recycling. 

Thus, if this plant were to comply with Option 5, it too would be likely to convert to dry fly ash 

handling and reduce its water consumption by 10.56 MGD. Both these plants in North Carolina 

draw water from the Catawba River; hence, if Options 4 or 5 were selected as the final rule, it 

could potentially result in a combined water savings of 20 MGD for the Catawba River Basin, 

augmenting the reliability of cooling water supplies for power generation as well as enhancing 

public water supplies and recreation uses downstream in North and South Carolina.

Further responses from the technical questionnaire reveal that the Four Corners Generating 

Station, located near Fruitland, NM, uses a wet bottom ash handling system and generates 7.27 

MGD of bottom ash transport water. The plant also indicated that 100% of the source for the 

bottom ash transport water is intake water, none of which are recycled back to the plant process. 

Hence, if Options 4 or 5 were selected as the final rule, this New Mexico plant would be 

expected to switch to a dry bottom ash handling system, and consequently, the plant would 

reduce its water use by 7.27 MGD. In an arid state like New Mexico, where access to water can 

be highly contentious, 7.27 MGD is a significant amount of water to be saved.

Comment Response: 
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The commenter discusses water withdrawals for pollution control technologies for specific plants 

and suggests that if each plant were to switch to a dry system there would be corresponding 

water savings.

EPA has accounted for reductions in intake water volumes associated with the conversions to dry 

fly ash and/or dry bottom ash handling technologies and with plants recycling FGD wastewater 

as part of their treatment system (see Section 12.4 of the TDD for details). Chapter 8 of the BCA 

for the final rule discusses benefits of reducing water withdrawals.

Commenter Name: Becky Hayat

Commenter Affiliation: Natural Resources Defense Council (NRDC)

Document Control Number: EPA-HQ-OW-2009-0819-4490-A1

Comment Excerpt Number: 21

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The potential water savings resulting from the proposed guidelines may be particularly important 

for those regions of the U.S. where water is already in short supply. Given the enormous threat 

that steam electric power plants pose to the availability and quality of our water resources, any 

reductions in a plant’s dependency on water will yield significant environmental and economic 

benefits. Yet, EPA identified only one type of benefit associated with reduced surface water 

withdrawals, which the agency limited to a very minimal qualitative discussion. Moreover, EPA 

failed to even mention –let alone quantify or monetize– other associated benefits to reduced 

surface water withdrawals. EPA must provide an accurate analysis of the full environmental and 

economic benefits to be gained as a result of the proposed guidelines– this is to ensure that in the 

end, the most environmentally protective regulatory option, which satisfies the BAT standard, 

will be chosen as the final rule.

Comment Response: 

EPA estimates that the final rule will reduce the use of water by 155 million gallons per day, 

relative to total surface water withdrawals for thermoelectric plants of 116 billion gallons per day 

in 2010 (Maupin et al, 2014), or a reduction in the order of 0.1 percent. Reductions in water 

withdrawals are relatively small, and the implied water savings are even smaller when 

considering net consumption of water by the plants.

EPA has accounted for reductions in intake water volumes associated with the conversions to dry 

fly ash and/or dry bottom ash handling technologies (see Section 12.4 of the TDD for details).

Small changes in withdrawals are expected to provide marginal benefits, particularly in regions 

that are prone to drought, as well as marginally reduce the impingement and entrainment 

mortality from intakes. Reducing withdrawals is also expected to provide direct benefits to the 
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power plants by reducing impacts of drought on their operations. For more details on these 

impacts, see paper titled “Water Withdrawals in Water Stressed Areas: Impacts of the Steam 

Electric Effluent Limitations Guidelines” (DCN SE05943) in the record for the final steam 

electric ELG rule. Because of the data limitations, EPA did not monetize the benefits. EPA 

discusses these benefits qualitatively in Chapter 8 of the BCA.

The commenter argues that all benefits associated with this change in surface water withdrawals 

should be quantified and monetized and then says that EPA must provide an accurate analysis of 

all benefits in order to determine the regulatory option which satisfies the BAT standard. EPA 

notes that ELG determinations are based on the specific factors in the CWA (see preamble for 

details), but notes that when looking at the benefits of a regulation, EPA looks at all benefits, 

whether quantified and monetized or analyzed qualitatively.

Maupin, M.A., Kenny, J.F., Hutson, S.S., Lovelace, J.K., Barber, N.L., and Linsey, K.S., 2014, 

Estimated use of water in the United States in 2010: U.S. Geological Survey Circular 1405, 56 

p., http://pubs.usgs.gov/circ/1405/.

Commenter Name: Becky Hayat

Commenter Affiliation: Natural Resources Defense Council (NRDC)

Document Control Number: EPA-HQ-OW-2009-0819-4490-A1

Comment Excerpt Number: 22

External Review Flag: Economics/Benefits

External Review Incorporated into Response: No

Comment Excerpt: 

In EPA’s Benefit and Cost Analysis37 for the proposed guidelines, the agency identified “reduced 

impingement and entrainment mortality” as a type of benefit associated with reduced surface 

water withdrawals. However, EPA went on to state, “Due to data limitations, EPA did not 

quantify and monetize these benefits as part of this analysis.”38 While we would like further 

explanation regarding why EPA could not quantify or monetize such benefits, we are more 

concerned with EPA’s failure to take into account other associated benefits to reduced surface 

water withdrawals in addition to reduced impingement and entrainment mortality. It is wellestablished that large water withdrawals have many adverse impacts, including but not limited 

to, lowering groundwater recharge or natural stream flow levels (thus impacting instream 

flow39), and affecting fish, wildlife, or other living resources and their habitat.40 Changes in 

instream flows in turn affect surrounding property values and recreational use (discussed further 

below). Said another way, reducing withdrawals can restore natural flows (in particular for water 

bodies with low flow conditions) and thereby impact aquatic life, property prices, and recreation.
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37 U.S. EPA, Benefit and Cost Analysis for the Proposed Effluent Limitations Guidelines and 

Standards for the Steam Electric Power Generating Point Source Category (April 2013) 

(“BCA”).

38 BCA at 9-1.

39 Instream flow refers to the state in which water remains in its natural course as opposed to 

water that has been diverted artificially for other purposes.

40 U.S. Geological Survey, Simulation of the Effects of Water Withdrawals, Wastewater Return 

Flows, and Land-Use Change on Streamflow in the Blackstone River Basin, Massachusetts and 

Rhode Island (2007); Susquehanna River Basin Commission, Low Flow Protection Policy 

Related to Withdrawal Approvals (Dec. 14, 2012).

Comment Response: 

EPA discussed potential reductions in impingement mortality and entrainment (IM&E) in its 

qualitative assessment of the benefits of the ELGs. Impingement mortality occurs when fish and 

other aquatic life are trapped against the entrance of an intake structure and entrainment occurs 

when aquatic life is pulled into the cooling system, so it is possible that even a small reduction in 

surface water withdrawals by regulated plants may lead to a reduction in IM&E. However, the 

reductions in surface water withdrawals associated with the final rule are small, relative to total 

plant withdrawals. EPA estimates that the final rule will reduce the use of water by 155 million 

gallons per day; this represents a reduction in the order of 0.1 percent of the total surface water 

withdrawals for thermoelectric plants of 116 billion gallons per day in 2010 (Maupin et al, 

2014). Furthermore, many of the plants with cooling water intake systems will be complying 

with the CWIS regulation which is expected to reduce impingement mortality and potentially 

reduce entrainment. To avoid double counting benefits already associated with the CWIS 

regulation, because of data limitations, and because IM&E benefits would be relatively small, 

EPA chose not to quantify and monetize IM&E reductions from the final rule.

The commenter also takes issue with the fact that benefits from reduced water withdrawals other 

than IM&E were not considered. As mentioned above, the reduction in water withdrawals is 

relatively small, and the implied water savings would be even smaller. EPA notes that the ash 

handling technologies are generally not “consumptive” processes, meaning that most of the 

water that is withdrawn from the receiving water is returned in the form of impoundment effluent 

discharges. Because of the data limitations, EPA did not monetize the benefits. EPA discusses 

these benefits qualitatively in Chapter 8 of the BCA.

Maupin, M.A., Kenny, J.F., Hutson, S.S., Lovelace, J.K., Barber, N.L., and Linsey, K.S., 2014, 

Estimated use of water in the United States in 2010: U.S. Geological Survey Circular 1405, 56 

p., http://pubs.usgs.gov/circ/1405/.
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Commenter Name: Becky Hayat

Commenter Affiliation: Natural Resources Defense Council (NRDC)

Document Control Number: EPA-HQ-OW-2009-0819-4490-A1

Comment Excerpt Number: 24

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Streamflow levels can also influence recreation benefits through a variety of mechanisms. Flow 

levels directly influence of quality of whitewater boating experiences as well as stream aesthetics 

for general shoreline use. Streamflow at any given time affects fishing via influences on the 

locations, distribution, and behavior of fish and aquatic insects. Flow levels also directly affect 

recreation carrying capacity–for example, the number of anglers that can use the same stretch of 

river at any one time without congestion problems may increase with flow. Over time, 

streamflows affect fish stock levels and associated angler catch rates, as well as general

recreation and aesthetics via effects on streamside vegetation.42 There exists a vast amount of 

literature examining the recreation benefits of instream flows. Most, if not all, of the studies have 

confirmed that recreation value is directly correlated with protecting instream flows and/or 

increasing natural flows.43 Furthermore, in these studies, the recreation value of instream flow 

has been monetized using a WTP methodology, measuring the maximum a person would be 

willing to pay in excess of actual trip costs rather than to forego the experience.44

42 Brown, T.C., J.G. Taylor, and B. Shelby, Assessing the direct effects of streamflow on 

recreation: A literature review, Water Resource Bulletin, 27(6), 979-989 (1991).

43 Duffield, J.W., C. J. Neiler, and T.C. Brown, Recreation Benefits of Instream Flow: 

Application to Montana’s Big Hole and Bitterrot Rivers, Water Resources Research, Vol. 28, 

No. 9, pgs. 2169-2181 (Sept. 1992); U.S. Dept. of the Interior Bureau of Reclamation, Economic 

Nonmarket Valuation of Instream Flows (April 2001).

44 Id.

Comment Response: 

As discussed in responses to other comments (DCN EPA-HQ-OW-2009-0819-4490-A1, Excerpt 

Number 18), EPA expects that changes in the amount of water withdrawn by steam electric 

power plants will be small. Further, the vast majority of steam electric power plants withdraw 

and discharge to the same surface waters. Accordingly impacts on streamflow are expected to be 

marginal.
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Commenter Name: Becky Hayat

Commenter Affiliation: Natural Resources Defense Council (NRDC)

Document Control Number: EPA-HQ-OW-2009-0819-4490-A1

Comment Excerpt Number: 26

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

There are various benefits to be gained from reductions in surface water withdrawals, and hence 

an improvement in water quality, for agriculture purposes.48 Furthermore, there is ample 

evidence to show a significant direct correlation between water quality and surrounding property 

values.49 Thus, if we operate under the assumption that large amounts of withdrawals negatively 

affect water quality, then we can draw the logical conclusion that reducing water withdrawals 

may also yield the additional benefits of increasing agricultural productivity and property prices.

48 Such agricultural benefits gained from a water quality improvement have been measured in 

two ways: through changes in price to consumers, and through changes in the incomes received 

by owners of inputs used in the production of the good. See id.

49 Steinnes, D.N., Measuring the Economic Value of Water Quality: The Case of Lakeshore 

Land.” Annals of Regional Science 26: 171-176 (1992) (concluding that water quality measures 

significantly impact property values and each additional unit of change in Secchi disk readings 

(SDR) –used as a measure of objective water quality– resulted in a $206 change in average lot 

price near the lake).

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4490-A1, Excerpt Number 28.

Commenter Name: Becky Hayat

Commenter Affiliation: Natural Resources Defense Council (NRDC)

Document Control Number: EPA-HQ-OW-2009-0819-4490-A1

Comment Excerpt Number: 27

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

We urge EPA to provide a more detailed explanation regarding why it failed to monetize and 

quantify the benefits of reduced impingement and entrainment mortality associated with 

reductions in surface water withdrawals.
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Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4490-A1, Excerpt Number 22.

Commenter Name: Becky Hayat

Commenter Affiliation: Natural Resources Defense Council (NRDC)

Document Control Number: EPA-HQ-OW-2009-0819-4490-A1

Comment Excerpt Number: 28

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA must take into account other benefits associated with reduced surface water withdrawals, 

including but not limited to, healthier aquatic ecosystems, higher recreational value, agricultural 

benefits, and increase in property values. EPA’s failure to quantify/monetize the one type of 

benefit it identified in relation to reduced surface water withdrawals, along with its 

undercounting of other associated benefits, results in an unfair balancing act where the agency 

weighs complete costs against incomplete benefits. This biased cost-benefit analysis is especially 

troublesome for the most stringent regulatory options (e.g. Options 4 and 5) where EPA 

overestimated compliance costs and blatantly underestimated the benefits.

Comment Response: 

As discussed further in responses to other comments (e.g., DCN EPA-HQ-OW-2009-0819-4490-

A1, Excerpt Number 18), EPA expects that changes in the amount of water withdrawn by steam 

electric power plants will be small; accordingly quantity impacts on water availability for 

downstream water users or property owners are expected to be marginal. Given the magnitude of 

the changes, EPA analyzed the benefits of reductions in surface water withdrawals qualitatively 

(see Chapter 8 of the BCA for the final rule and paper titled “Water Withdrawals in Water 

Stressed Areas: Impacts of the Steam Electric Effluent Limitations Guidelines” (DCN SE05943) 

in the record for the final steam electric ELG rule).

Commenter Name: Cathy S. Woollums

Commenter Affiliation: MidAmerican Energy Holdings Company

Document Control Number: EPA-HQ-OW-2009-0819-4495-A1

Comment Excerpt Number: 45

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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 When assessing benefits for reduced groundwater withdrawals, EPA relied on statespecific water prices in Florida and Nebraska to estimate the monetary value of reduced 

groundwater withdrawal. But according to EPA, these states are potentially or currently 

water-stressed, resulting in above-average water prices in comparison to the national 

average, and thereby an inflated benefit estimate.

Comment Response: 

EPA disagrees with the commenter’s assertion that benefits are inflated because EPA used statespecific water prices. Only certain plants withdraw groundwater for their processes. Therefore, it 

is appropriate to use the water prices for the states in which each plant is located to estimate the 

monetary value of reduced groundwater withdrawal for these plants.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 225

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Additionally, the attached analysis from NRDC explains that EPA did not account for the 

significant benefits from Options 4 and 5 of reduced surface water withdrawals.696 EPA 

calculated that power plants would reduce water use by 153 billion gallons per year, or about 419 

million gallons per day, under Options 4 and 5, due to reductions in water use for handling ash 

transport and for the recycling of FGD wastewater.697 Although power plant withdrawals of 

cooling water are substantially greater than this amount, the amount of process water that can be 

saved by the proposed rule’s two most stringent options is about as much water as is used by all 

the homes in North Carolina,698 and thus a significant amount of water to save with any single 

regulatory measure. The water savings resulting from the rule will be especially helpful for those 

states facing deepening water-scarcity challenges caused by climate change. Yet EPA did not 

describe any of these benefits of the rule, let alone attempt to quantify or monetize 

them. Significant water withdrawals such as those from power plants have many adverse 

impacts, including lowering groundwater recharge or natural stream flow levels (thus impacting 

instream flow699), and affecting fish, wildlife, or other living resources and their habitat.700 Any 

measure that reduces surface water withdrawals, thereby restoring natural flows, provides both 

environmental and economic benefits.701 Reduced withdrawals will either restore instream flows 

in areas with low flow conditions, or increase natural stream flows, both of which improve 

aquatic ecosystems and enhance recreational opportunities, such as by increasing fish stocks.702

In addition, reducing surface water withdrawals may directly improve water quality, such as by 

increasing dilution of pollutants or decreasing temperature.703 This increased water quality has 

the added benefit of increasing agricultural productivity and property values.704
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696 NRDC, Associated Water Savings and Benefits to Reduced Surface Water Withdrawals.

697 TDD at 12-13 – 12-14; Becky Hayat & Ed Osann, Natural Resources Defense Council, 

“Steam Electric Effluent Guidelines: Associated Water Savings and Benefits to Reduced Surface 

Water Withdrawals” (Sept. 20, 2013) [hereinafter “NRDC Memo”]. Option 4a would reduce 

water use by 103 billion gallons per year. TDD at 12-14. Options 3, 3a, and 3b would reduce 

water use by 52.7 billion, 49.9 billion, and 52.1 billion gallons per 

year, respectively. Id. Options 1 and 2 would only reduce water use by 2.82 billion gallons per 

year each. Id.

698 NRDC Memo at 1 (citing Kenny, J.F., Barber, N.L., Hutson, S.S., Linsey, K.S., Lovelace, 

J.K., and Maupin, M.A., 2009, Estimated use of water in the United States in 2005: U.S. 

Geological Survey Circular 1344).

699 Instream flow refers to the state in which water remains in its natural course as opposed to 

water that has been diverted artificially for other purposes.

700 NRDC Memo at 1 (citing U.S. Geological Survey, Simulation of the Effects of Water 

Withdrawals, Wastewater Return Flows, and Land-Use Change on Streamflow in the Blackstone 

River Basin, Massachusetts and Rhode Island (2007); Susquehanna River Basin Commission, 

Low Flow Protection Policy Related to Withdrawal Approvals (Dec. 14, 2012)).

701 Id. at 9-11.

702 Id. at 10.

703 Id. at 10-11.

704 Id. at 11.

Comment Response: 

EPA agrees with the commenter’s points that there are a number of potential benefits associated 

with a reduction in surface water withdrawals.

However, these benefits, such as improved water quality from dilution, instream flows, and 

groundwater recharge are mostly a function of net changes in water volume. EPA estimates that 

the final rule will reduce the use of water by 155 million gallons per day (see Section 12.4 of the 

TDD for details), relative to total surface water withdrawals for thermoelectric plants of 116 

billion gallons per day in 2010 (Maupin et al, 2014), or a reduction in the order of 0.1 percent. 

Reductions in water withdrawals are relatively small, and in-stream effects are even smaller 

when considering net consumption of water by the plants.
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Small changes in withdrawals may provide marginal benefits, particularly in regions that are 

prone to drought, as well as marginally reduce the impingement and entrainment mortality from 

intakes. Reducing withdrawals is also expected to provide direct benefits to the power plants by 

reducing impacts of drought on their operations. For more details on these impacts, see paper 

titled “Water Withdrawals in Water Stressed Areas: Impacts of the Steam Electric Effluent 

Limitations Guidelines” (DCN XX) in the record for the final steam electric ELG rule. Because 

of the data limitations, EPA did not monetize these benefits, but describes them qualitatively in 

Chapter 8 of the BCA.

The commenter compares water withdrawal reductions to North Carolina residential water use. 

EPA offers that the metrics are not equivalent in their effect and the comparison is therefore not 

appropriate. In 2010, domestic water withdrawals and deliveries for North Carolina totaled 

668 million gallons per day, which exceeds the water withdrawal reductions estimated for the 

final rule. The water withdrawal reductions for the final rule will occur at plants distributed 

across the United States with impacts spread across a number of waterbodies and watersheds.

Maupin, M.A., Kenny, J.F., Hutson, S.S., Lovelace, J.K., Barber, N.L., and Linsey, K.S., 2014, 

Estimated use of water in the United States in 2010: U.S. Geological Survey Circular 1405, 56 

p., http://pubs.usgs.gov/circ/1405/.
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29.j. Benefits – Total benefits 

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 6

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The benefits of cleaning up this pollution far outweigh the costs. EPA's own cost benefit 

analysis, which we believe undercount or do not monetize many of the benefits of cleaning up 

this harmful pollution, demonstrates the benefits of a strong rule. These benefits include the 

health benefits of restoring hundreds of miles of our rivers so that their fish are safe to eat and 

pregnant women and children are exposed to less harmful mercury and lead, not to mention 

benefits to wildlife, drinking water quality, recreation and tourism, and property values.

Comment Response: 

EPA thanks the commenter for the support for the regulations to reduce the discharge of harmful 

pollution to surface waters.

The Agency has been as comprehensive as possible in its analysis given limitations in data and 

information and tools for estimating benefits. EPA estimated annualized benefits of the final rule

ranging between $450.6 million and $565.6 million (using a 3 percent discount rate), as 

compared to annualized costs of $479.5 million. Using a 7 percent discount rate, the annualized 

benefits range between $387.3 million to $478.4 million, as compared to costs of $471.2 million. 

The Agency provided detailed discussion on additional, non-monetized benefit categories. The 

BCA provides detail on the health, ecological, and economic benefits associated with the final 

regulation, including additional benefit categories not presented at proposal.

Commenter Name: Public Hearing Transcript

Commenter Affiliation: Public Hearing Transcript

Document Control Number: EPA-HQ-OW-2009-0819-3920-A1

Comment Excerpt Number: 19

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Stringent limitations on power plant effluent could pass many benefits onto Virginians, including 

cleaner water, improved public health, reduced environmental degradation, and job creation with 

minimal cost to ratepayers.
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Comment Response: 

EPA agrees that reducing power plant pollutant discharges will confer many benefits in Virginia 

and elsewhere. For more detail on the health, ecological, and economic benefits associated with 

the final regulation, see the BCA for the final rule.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A2

Comment Excerpt Number: 1

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

we have found that substantial portions of both the monetized and non- monetized benefits 

asserted by the US EPA are overstated or not adequately detailed, calling into question whether 

the proposed rule is adequately supported.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4655-A2, Excerpt Number 13 (Section 29.b) 

regarding the concern that EPA substantially overstated expected cost reductions quantified as 

benefits of the final rule, and details provided in supporting documents.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A2

Comment Excerpt Number: 12

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Air-related benefits, which are tangential to an analysis of utility related effluent discharge, are a 

significant driver in the benefits analysis, accounting for 18-40% of the total benefits under the 

evaluated regulatory options. Furthermore, these estimates are highly uncertain because of the 

numerous model assumptions that are needed to calculate these benefits.

Comment Response: 
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EPA disagrees that air-related benefits are tangential to the analysis, but acknowledges that these 

benefits are indirect (i.e., a large share of these benefits arise from changes in the emissions 

profile of the industry as a result of anticipated actions by the industry in response to the 

regulation).

The Agency notes that including benefits of reduced air emissions in the total benefit estimate is 

consistent with the Office of Management and Budget’s (OMB) guidance to Federal agencies on 

the development of regulatory analysis (Circular A-4). The OMB guidance specifically states 

that benefit cost analysis should identify and account for “ancillary benefits of the proposed 

regulatory action and the alternatives.”

For a more detailed response on the uncertainty, see response to DCN EPA-HQ-OW-2009-0819-

4655, Excerpt Number 204 (section 29.h).

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 12

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Valuation of the benefits of regulation involves a sequence of stages, each of which can be the 

locus of uncertainty. Three main stages can be distinguished:

 An event, such as release of a pollutant, occurs.

 The event has a health or environmental impact on a human or natural receptor.

 A monetary valuation is assigned to the impact.

For example, there could be uncertainty about whether and to what extent a coal ash 

impoundment or landfill failure, or other unplanned release of polluted wastewater, will occur 

(and more particularly, uncertainty about whether a proposed ELG standard affects the 

likelihood of such a release); subsequent uncertainty about the health or environmental impact of 

any toxic chemicals released in that event; and finally, uncertainty about appropriate monetary 

valuation of those impacts, once they have occurred.

Monetization: Are uncertain values always zero?

Another problem with benefits calculations is perhaps even more serious than the uncertainty 

in physical risks. In order to enter a benefit‐cost calculation, benefits must be not only 

quantified, but also monetized. EPA maintains relatively strict and demanding standards for 

monetization; the default for benefit categories that cannot meet the standard is a qualitative 

discussion with a zero value. While often informative, EPA’s qualitative discussions of such 
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benefits do not result in numerical valuations, and are therefore treated as equivalent to a finding 

of zero in any simple summary of benefits and costs. This imparts an asymmetric bias to the 

overall calculations: There is no comparable category of costs that default to zero for lack of 

data; there are no offsetting categories of benefits where there is a structural bias toward 

overestimation.

The difficulty in monetization results from the artificial, synthetic nature of benefits valuations. 

One of the widely discussed virtues of a market economy is that up‐to‐date prices for marketed 

goods are continually available to all, at little or no cost; it is difficult to imagine another system 

that provides equally timely, inexpensive information on prices. It is unfortunately clear that 

environmental economics has not come close to matching that performance in pricing non‐

marketed health and environmental benefits. Research standards for monetizing benefits are 

sufficiently demanding that EPA frequently relies on “benefit transfers” – that is, making the 

best available approximations based on the published literature on valuation of similar benefits 

experienced elsewhere.

Even with extensive use of benefit transfer calculations, there are large gaps remaining in the 

valuation of benefits, due to inherent limitations of quantification and/or monetization. In the 

benefit‐cost analysis conducted for the proposed steam electric ELGs, numerous benefits are 

effectively valued at zero dollars due to lack of data, including the following examples:

EPA expects that there would also be material health benefits via the fish consumption pathway 

arising from reduced discharges of other steam electric pollutants, such as cadmium, selenium, 

and zinc. Analyses of these health benefits are not possible due to lack of data...49

EPA quantified but did not monetize the expected reduction of pollutant concentrations in excess 

of human health‐based aquatic water quality criteria (AWQC) limits.50

By reducing discharges of pollutants to receiving reaches, the proposed ELGs would reduce the 

future contamination of waterbody sediments, thereby mitigating impacts to benthic organisms 

and reducing the probability that the pollutants would later be released into the water column and 

affect surface water quality and the waterbody food chain. Due to data limitations, EPA did not 

quantify or monetize this benefit.51

EPA did not quantify or monetize benefits from enhanced quality of drinking and agricultural 

water sources arising from the proposed ELGs due to data limitations.52

Reduced surface water intake would reduce impingement and entrainment mortality. Due to data

limitations, EPA did not quantify and monetize these benefits as part of this analysis.53

The last of these example omissions is particularly striking, since in other proceedings EPA has 

devoted extensive effort to quantification and monetization of changes in impingement and 

entrainment mortality, due to changes in cooling water intake systems. It should have been 

possible to arrange a “benefits transfer” between different parts of EPA itself.
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The asymmetric bias in benefits monetization, with substantial benefit categories omitted from 

monetization (implicitly valued at zero) but no comparable offsetting bias in the other direction, 

causes a fundamental distortion in bottom‐line benefit‐cost estimates. The virtue of benefit‐cost 

analysis, in theory, is that it provides objective, transparent comparison of costs and benefits, 

calculated on an equal footing. This requires comparably complete estimates on both sides. 

There is no theoretical argument for the use of an “overestimated cost—incomplete benefit” 

estimate; no useful conclusion can be drawn from the finding that relatively complete estimates 

of costs exceed substantially incomplete estimates of benefits.54

As the above quotes from EPA confirm, the benefit‐cost calculations for the proposed steam 

electric ELGs are indeed comparisons of complete and often over‐estimated costs with 

incomplete benefits. The bottom‐line estimates presented in this case are the estimates that would 

apply if all the un‐monetized benefits were known to be worth precisely zero—which is a very 

different state of knowledge from genuine uncertainty about the magnitude of these important 

but hard‐to‐measure (and sometimes impossible‐to‐measure) categories. EPA presents no 

argument that the un‐monetized benefits are all worthless; nor could it, as many of them are of 

obvious value. As a result, the conclusion is inescapable that EPA’s bottom‐line comparisons of 

costs and benefits are fundamentally wrong, albeit by uncertain amounts.

49 U.S. Environmental Protection Agency, Benefit and Cost Analysis for the Proposed Effluent 

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

Category, EPA‐821‐R‐13‐004, April 2013; hereafter, Benefit‐ Cost Analysis; p.2‐4.

50 Benefit‐Cost Analysis, p.2‐5.

51 Benefit‐Cost Analysis, p.2‐8. Receiving reaches are areas into which effluents are discharged.

52 Benefit‐Cost Analysis, p.2‐10.

53 Benefit‐Cost Analysis, p.2‐11.

54 Ackerman, F. and L. Heinzerling, Priceless: On Knowing the Price of Everything and the 

Value of Nothing (New York: New Press, 2004).

Comment Response: 

EPA disagrees with the commenter that its comparison of costs and benefits in the final rule are 

“fundamentally wrong.” The commenter notes several categories of benefits that EPA was not 

able to monetize in the benefit analysis, and EPA agrees with the commenter that the listed 

benefits are real and of critical ecological, social, and economic importance. EPA notes that the 

Agency has expanded its benefits analysis for the final rule to include additional categories not 

monetized in the proposed rule, including reduced incidence of cardiovascular disease from 

exposure to lead and arsenic, avoided cost of maintenance dredging of reservoirs and 

navigational waterways, and increased marketing of coal combustion residuals for beneficial 
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reuse (see Chapters 3, 9 and 10 in the BCA). However, the Agency was not able to quantify and 

monetize several of the categories listed by the commenter due to data and methodological 

limitations. Chapter 2 of the final BCA provides detailed qualitative discussion and, in some 

cases, screening level analyses for non-monetized benefit categories. The Agency has been as 

comprehensive as possible in its analysis given limitations in data and information and tools for 

estimating benefits, and appropriately documented the associated uncertainties.

Regarding impingement and entrainment mortality benefits specifically, EPA agrees with the 

commenter that benefit transfer from the 316b benefits analysis is possible in principle to 

estimate benefits of reduced water withdrawal. However, as discussed in Chapter 8 of the BCA, 

given the intake volume affected by the ELG (i.e., 147 million gallons per day for the final rule, 

which is approximately 0.1% of the total intake volume affected by the 316b rule) the expected 

benefits to aquatic life are likely to be minimal. The Agency however, evaluated potential 

benefits of reducing water use in power plant operations to the regulated facilities located in 

water stressed zones (see DCN SE05943).

EPA disagrees with the commenter that benefits that cannot be quantified or monetized imply 

that these benefits have no value, EPA fully documents limitations of cost-benefit analysis in the 

record for the rule.

For information on the role of benefits analysis in establishing effluent limitations based on Best 

Available Technology Economically Achievable (“BAT”), see response to DCN EPA-HQ-OW2009-0819-4464-A1, Excerpt Number 3.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 16

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Benefits assigned monetary values by EPA

EPA enumerates 23 benefits from water pollution reductions due to the proposed steam electric 

ELGs, fifteen of which are monetized (see Table 7 below). Of these, thirteen benefits have 

been—by EPA’s own account—underestimated in the total monetary benefits of the regulatory 

options; just one is overestimated. The dollar values attributed to each benefit are summed to the 

total monetized value of each option (see Table 8 for a summary by each benefit category). EPA 

provides a summary description of its benefits in Table 2‐1 of the Benefit‐Cost Analysis.

75

Under Option 4, 49 percent of all monetized benefits (including air‐related benefits) are derived 

from reduced impoundment failures, 28 percent from reduced air pollution, and 19 percent from 
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improved ecological conditions. The remaining benefits—human health, groundwater quality, 

and reduced water withdrawals—are assigned just 4 percent of the total monetized benefits of the 

proposed ELGs. EPA calculated the benefit of reduced air pollution due to the proposed steam 

electric ELGs only for Options 3 and 4, and, from this, imputed this benefit for Options 3a, 3b, 

and 4a.

Here we review the benefits for the proposed steam electric ELGs that EPA identifies as 

underestimates.

Table 7. Proposed steam electric ELG benefits (as discussed in EPA Benefit‐Cost 

Analysis) 

Benefit InclusionQuantification Monetization

Reduced incidence of cancer from reduced 

exposure to arsenic from fish consumption Included Quantified (Low) Montized (Low)

Reduced IQ losses to infants from reduced in‐

utero mercury exposure from maternal fish 

consumption

Included Quantified 

(Low) Monetized (Low)

Reduced IQ losses to children ages 0 to 7 from 

reduced childhood exposure to lead from fish 

consumption

Included Quantified 

(Low) Monetized (Low)

Reduced need for specialized education from 

reduced childhood exposure to lead from fi h 

consumption

Included Quantified 

(Low) Monetized (Low)

Reduced mortality from exposure to NOx, SO2 

and particulate matter (PM2.5) Included Quantified (Low) Monetized (Low)

Improved aquatic and wildlife habitat from 

improved ambient water quality in receiving 

reaches

Included Quantified 

(Low) Monetized (Low)

Enhanced swimming, fishing, boating, and near‐

water activities from improved water quality Included Quantified 

(Low) Monetized (Low)

Increased aesthetics from improved water 

clarity, color, odor, including nea by site 

amenities (residing, working, traveling)

Included Quantified 

(Low) Monetized (Low)

Enhanced existence, option, and bequest values 

from improved ecosystem health. Included Quantified (Low) Monetized (Low)

Reduced risks to aquatic life from exposure to 

steam electric pollutants Included Quantified (Low) Monetized (Low)

Improved T&E habitat and thus potential 

increase in T&E population Included Quantified (Low) Monetized (Low)

Reduced air emissions of CO2 

resulting in avoided climate change/global 

warming impacts

Included Quantified 

(Low) Monetized (Low)
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Increased availability of groundwater resources 

from reduced groundwater withdrawals Included Quantified (Low)

Monetization 

(Uncertain)

Reduced groundwater contamination Included Quantified 

(Low) Monetized (High)

Reduced risk of impoundment failures due to 

changes in the use of impoundments Included Quantified (Low)

Monetization 

(Uncertain)

Source: Benefit‐Cost Analysis, pp.2‐12 and 2‐13, Table 2‐1; authors’ analysis

Table 8. Annualized monetized benefits of steam electric ELGs (millions of 2010$)

Monitized Value of Benefits in Million 2010$, all Values at Mean Benefit Estimates and 3 

Percent Discount Rate

Benefit Category Option 1 Option 2 Option 3 Option 4 Option 5

Reduced Impoundment Failures $62.1 $62.1 $114.8 $295.1 $295.1

Reduced Air Pollution omitted omitted $127.6 $170.5 omitted

Improved Ecological Conditions and 

Recreational Uses $15.3 $45.0 $59.9 $116.1 $115.2

Human Health Benefits $3.9 $4.0 $7.7 $17.2 $17.2

Groundwater Quality Benefits $0.7 $0.7 $1.6 $6.5 $6.5

Reduced Water Withdrawals $0.0 $0.0 <0.1 $0.1 $0.1

Total benefits, Excluding Air‐Related 

Benefits $82.0 $111.7 $184.1 $435.0 $434.1

Total Benefits (Including Air‐related 

Benefits) n/a n/a $311.7 $605.5 n/a

Note: All values at mean benefit estimates and 3‐percent discount rate Source: 78 Fed. Reg. at 

34,518, Table XIV‐8

75 Benefit‐Cost Analysis, p.2‐13.

Comment Response: 

The commenter provides a summary of the benefit categories monetized in the BCA for the 

proposed rule, and notes that several of them are underestimated. As was the case for the 

proposed rule, EPA acknowledges that it made several conservative assumptions in the benefits 

analyses for the final rule, as discussed in the BCA. The Agency has been as comprehensive as 

possible in its analysis given limitations in data and information and tools for estimating benefits, 

and appropriately documented the associated uncertainties.

In addition, EPA has expanded the categories of benefits that are quantified and monetized and 

updated its analyses for the final rule, including the analysis of human health, surface water 

quality, and economic productivity benefits. Appendix A of the BCA highlights the additions. 
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For more details on changes EPA made to the benefit analysis of the final rule to address 

comments, also see response to related comment DCN EPA-HQ-OW-2009-0819-4686-A1, 

Excerpt Number 13.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 35

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Reduced surface water withdrawals and consumptive use: EPA calculated that power plants 

would reduce water use by 153 billion gallons per year, or about 419 million gallons per day, 

under Options 4 and 5, due to reductions in water use for ash transport and recycling of FGD 

wastewater.73 Although power plant withdrawals of cooling water are substantially greater than 

this amount, the amount of process water that can be saved by these effluent guidelines is about 

as much water as is used by all the homes in South Carolina,74and thus a significant amount of 

water to save with any single regulatory measure. The water savings resulting from the rule will 

be especially helpful for those states facing deepening water‐scarcity challenges caused by 

climate change. Yet EPA did not describe any of these benefits of the rule, let alone attempt to 

quantify or monetize them.

73 TDD at 12‐13 – 12‐14.

74 Kenny, J.F., Barber, N.L., Hutson, S.S., Linsey, K.S., Lovelace, J.K., and Maupin, M.A., 

2009, Estimated use of water in the United States in 2005: U.S. Geological Survey Circular 

1344.

Comment Response: 

EPA agrees with the commenters that reduced surface water withdrawals may result in 

ecological and economic productivity benefits. For the final rule analysis, EPA quantified the 

reduced water intake as part of its analysis of the non-water quality impacts of the rule. EPA also 

expanded on its discussion of the potential benefits arising from reduced water withdrawals 

associated with ash transport and FGD wastewater. The assessment included discussion of the 

potential benefits to regulated facilities located in water stressed areas (see DCN SE05943 in the 

docket for the final rule).
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Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4686-A1

Comment Excerpt Number: 42

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Of sixteen benefits quantified by EPA, fifteen are assigned monetary values and included in the 

total monetized benefits of the regulatory options. While the benefit from “reduced other adverse 

health effects (cancer and non‐cancer) from reduced exposure to other pollutants (arsenic, lead, 

etc.) via fish consumption” is quantified (albeit a low estimation), EPA was unable to complete 

the monetization step; as a result, this benefit is effectively assigned a zero dollar value in the 

total monetized benefit of the regulatory options.

It is important to note that for all of the benefits, the monetization step extends any 

underestimation from the quantification step. As a result, a low estimation during quantification 

results in an undervaluation of the final monetized benefit even when the monetization method is 

based on the most accurate assumptions and techniques possible.

Comment Response: 

EPA agrees with the commenter that some human health benefits were omitted from the 

proposed rule analysis and, as a result, health benefits of the proposed rule were likely 

understated. For the final rule, EPA quantified and monetized additional non-cancer health 

benefits; specifically, the Agency estimated the benefits to adults of reduced cardiovascular 

mortality from exposure to lead and arsenic via fish consumption. These analyses are described 

in greater detail in Sections 3.4 and 3.7, respectively, of the BCA for the final rule. Although 

EPA has been as comprehensive as possible in its analysis of benefits, some human health 

benefits could not be estimated given limitations in available data and methods. Chapters 2 and 3 

in the BCA discuss the remaining limitations of the human health benefits analysis.
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31. Numeric Limits

Commenter Name: Doris Cooksey

Commenter Affiliation: City Public Service of San Antonio (CPS Energy)

Document Control Number: EPA-HQ-OW-2009-0819-4283-A1

Comment Excerpt Number: 17

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The limits proposed for mercury and selenium will be very difficult to achieve on a daily basis 

and difficult for labs to analyze accurately. EPA states that while the limits are stringent, a well 

operated plant should be capable of complying with the effluent limitations at all times, which is 

not accurate. If the daily maximum limitation is set at the 991h percentile of daily 

measurements and the monthly average limitation is set at the 951h percentile of the distribution 

of monthly averages, the statistical result is one exceedance every twenty months.

Comment Response: 

EPA disagrees with the comment’s assertion that the limitations will be difficult to achieve. 

EPA’s analysis concluded that plants would be able to meet the effluent limitations at all 

times. The statistical analysis is designed to identify the long term average which is what plants 

should design for to meet the limitations. EPA also does not agree that the limitations based on 

99th and 95th percentiles mean that plants would be expected to exceed the effluent limitations at 

times. See Appendix A, Essay Section 5 and the Statistical Support Document for Effluent 

Limitations. In addition, EPA does not agree that laboratories will have difficulty analyzing the 

wastewater and quantifying the analytical result at the level needed to demonstrate compliance.

For example, EPA Method 1631E can measure mercury at very low concentrations with a 

quantitation limit of 0.5 nanogram/liter (ng/L), orders of magnitude lower than the effluent 

limitation. Plants have not had difficulty obtaining quantified results at very low levels in FGD 

wastewater. See, e.g., the EPA sampling data, CWA 308 sampling data, and self-monitoring data 

submitted by industry and used for calculating the effluent limits. These data are compiled in 

DCN SE06277 and summarized in DCN SE05733. Also see the wastewater treatment system 

data submitted by AEP for the Mountaineer Plant (data submittal dated March 2104).

The quantitation limit for selenium is also sufficiently below the effluent limitations that plants 

will be able to obtain laboratory results that demonstrate compliance. The monthly average 

limitation is 12 ug/L month; 23 ug/L daily maximum. EPA Method 200.8 is a sensitive analytical 

method capable of quantifying selenium at low concentrations. A study EPA conducted prior to 

collecting data for the purpose of establishing effluent limitations, which was done to develop 

laboratory standard operating procedures, demonstrated that the method can be used to quantify 

selenium in the FGD wastewater matrix and that typical well-operated laboratories would be able 

to quantify concentrations of selenium down to at least 5 ug/L. In practice, based on the data 

EPA has compiled for this rulemaking, laboratories are often able to quantify the concentration 
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of selenium at levels much lower than 5 ug/L (see, e.g., self-monitoring data submitted by Duke 

Energy and AEP).

Commenter Name: Chris M. Hobson

Commenter Affiliation: Southern Company

Document Control Number: EPA-HQ-OW-2009-0819-4379-A1

Comment Excerpt Number: 170

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Proposed Limits Are Not Supported By the Record

EPA proposes the following limits for FGD wastewater at existing power plants.

Pollutant Units of 

Measure

Daily Maximum 

Limit

Monthly Average 

Limit

Total Arsenic μg/L 8 242

Total Mercury ng/L 242 119

Total Selenium μg/L 16 10

Nitrate/Nitrite as 

N

mg/L 0.17 0.13

As discussed below, an exceedance frequency analysis of these limits indicates that the 

limits cannot consistently be met even by Allen and Belews Creek, the two proposed BAT 

plants.

Comment Response: 

EPA disagrees with the comment’s interpretation of exceedance analyses, as discussed in 

Appendix A, Essay Section 4.1.3 and Section 5. EPA also disagrees that “limits cannot 

consistently be met even by Allen and Belews Creek.” EPA expects well operated and designed 

facilities to be capable of complying with the final limitations, as described in Essay Section 5. 

EPA notes that commenters submitted additional effluent data for FGD wastewater in comments 

on the proposed rule and EPA used this expanded dataset to calculate effluent limits for the final 

rule. EPA’s engineering review of the effluent limits for the final rule, the effluent data, and 

other wastewater characterization data and treatment system process information, concluded that 

plants would be able to meet the effluent limitations. See DCN SE05733.

Commenter Name: Chris M. Hobson

Commenter Affiliation: Southern Company
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Document Control Number: EPA-HQ-OW-2009-0819-4379-A1

Comment Excerpt Number: 172

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA’s selection of datasets omitted years of relevant data from the model plants. EPA removed 

valid data pointsrepresenting elevated concentrations that would be expected in the tails of the 

distributions. EPA substituted baseline values for reported measurements which had the effect of 

reducing estimated variability factors. EPA used inappropriate statistical methods for estimating

under lying parameters of the Delta LogNormal distribution which resulted in underestimates of 

variability factors. For selenium and nitrate/nitrite, EPA abandoned the Delta LogNormal 

distribution and treated all reported values as if they were above the detection limit causing 

variability factors to be biased low. As implemented, EPA’s series of procedures systematically 

reduced estimates of long term averages and variability factors, and consequently reduced 

calculated limits.

Comment Response: 

EPA disagrees with the comment’s assertions that it omitted “years of relevant data from the 

model plants” and that EPA has removed valid data points. EPA notes that the dataset used to 

calculate the BAT effluent limitations for FGD wastewater is expanded from the dataset used at 

proposal, as a result of comments and data submitted on the proposed rule. Both the data 

submitted after proposal and the data EPA used at proposal were carefully evaluated to ensure 

they were valid analytical results and were representative of the BAT technology that is the basis 

for the effluent limitations. In some cases, EPA determined that the data were not appropriate for 

use in calculating the limitations. See Appendix A, Essay Section 3.4 and DCN 05733.

EPA disagrees that it applied inappropriate statistical methods. EPA’s statistical methodology 

and the basis for that methodology are explained in Essay Section 4 and Section 13 and 

Appendix B of the TDD. EPA also does not agree that, when calculating the effluent limitations, 

it inappropriately substituted baseline values for reported results that were below a specified 

value. EPA’s methodology and rationale for incorporating baseline substitution was clearly 

explained at proposal. However, in response to comments, EPA reevaluated baseline substitution 

and determined that certain adjustments were warranted; the effluent limitations for the final rule 

reflect these adjustments. See DCN SE05733 and Essay Section 3.5. Based on comments, EPA 

also made a correction to the autocorrelation procedure (see Essay 4.1.1 for a discussion of 

autocorrelation).

EPA disagrees that the procedures used systematically reduced estimates of long term averages 

and variability factors, and consequently reduced the calculated limits. For example, where for 

those instances where commenters argue that baseline substitution resulted in reducing the 

variability of the dataset, they fail to also mention that the substitution actually increased the 

long-term average. Regardless, the final rule addresses the commenter’s concern in this regard. 

EPA notes that the effluent limitations for the final rule are higher than the proposed limitations.
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Commenter Name: Jared Morrison

Commenter Affiliation: Westar Energy

Document Control Number: EPA-HQ-OW-2009-0819-4469-A1

Comment Excerpt Number: 7

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The numeric limits within the guidelines will be difficult to consistently and accurately measure 

for regulatory purposes.

Comment Response: 

EPA does not agree. See the response to DCN EPA-HQ-OW-2009-0819-4283-A1, Excerpt 

Number 17. In addition to the information regarding mercury and selenium in the referenced 

response, EPA notes that the quantitation levels for arsenic and nitrate-nitrite as N are also 

substantially lower than the effluent limitations. EPA’s study to develop laboratory standard 

operating procedures for EPA Method 200.8 demonstrated that the method can be used to 

quantify selenium in the FGD wastewater matrix, and that typical well-operated laboratories 

would be able to quantify concentrations of arsenic down to at least 2 ug/L. Nitrate-nitrite as N 

can be measured as low as 0.05 mg/L using EPA Method 353.2.

EPA notes that the comment doesn’t identify any specific barriers that would create difficulties 

for facilities to “consistently and accurately measure for regulatory purposes.”

Commenter Name: Quinlan J. Shea III

Commenter Affiliation: Edison Electric Institute (EEI)

Document Control Number: EPA-HQ-OW-2009-0819-4487-A1

Comment Excerpt Number: 39

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

E. EPA’s Proposed Limits for FGD Wastewater are Not Supported by the Data and Result 

from Flawed Statistical Approaches

Similarly, and as further detailed in the UWAG Comments, flaws in the data relied upon in 

limitation development are compounded by inappropriate EPA statistical analysis. For example, 

EPA proposes the following limits for FGD wastewater at existing power plants.
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Pollutant Units of 

Measure

Daily Maximum 

Limit

Monthly Average 

Limit

Total Arsenic μg/L 8 6

Total Mercury ng/L 242 119

Total Selenium μg/L 16 10

Nitrate/Nitrite as 

N

mg/L 0.17 0.13

An exceedance frequency analysis of these limits undertaken by UWAG consultant, AKRF, Inc., 

as described in more detail in the UWAG Comments, indicates that the limits cannot consistently 

be met even by Allen and Belews Creek, the two model plants that EPA used to set the proposed 

limits.

Comment Response: 

See the response to DCN EPA-HQ-OW-2009-0819-4283-A1, Excerpt Number 17.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 15

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Key Comments on Statistical Approach Used to Determine Proposed Numeric Limits

EPA underestimated the standard deviations in its statistical approach to determine long-term 

averages, variability factors, and effluent limitations and standards. The underestimated 

standard deviations further propagate and impact the variability factors and ultimately, the 

regulatory limits and standards.

 Use of small data sets leads to underestimation of standard deviations, and hence, 

underestimation of regulatory limits.

 The same data used to compute limits in the rulemaking were also used to determine 

what percent exceeded limits.

 Since the option long-term average is defined as the median of the plant-specific longterm averages, 50% of the current plants will have an average that is above the median, 

leading to a limitation that will also be exceeded more frequently by existing data.

 Additional information is needed to use the correlation coefficient to adjust the variability 

factor.
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 The modified delta-lognormal distribution used by EPA to compute the percentiles for 

censored data does not give accurate results when non-detects are present.

 Averaging a 4-day event to obtain a single number incorrectly decreases variability, as 

compared to using a single monthly sample.

 Treating all data that are less than the quantitation limit as one-half of the sample-specific 

quantitation limit for all analytes decreases the variability of the resulting estimates, 

leading to a standard deviation of the fitted distribution that is too low.

 Averaging duplicates reduces variability compared to what is actually measured.

Comment Response: 

EPA addresses each of the comment’s bulleted items in the Essay as follows:

 Use of small data sets leads to underestimation of standard deviations, and hence, 

underestimation of regulatory limits. 

o See the response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 

65.

 The same data used to compute limits in the rulemaking were also used to determine 

what percent exceeded limits. 

o See the response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 

132.

 Since the option long-term average is defined as the median of the plant-specific longterm averages, 50% of the current plants will have an average that is above the median, 

leading to a limitation that will also be exceeded more frequently by existing data. 

o See the response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 

133

 Additional information is needed to use the correlation coefficient to adjust the variability 

factor. 

o See the response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 

134.

 The modified delta-lognormal distribution used by EPA to compute the percentiles for 

censored data does not give accurate results when non-detects are present. 

o See the response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 

66.

 Averaging a 4-day event to obtain a single number incorrectly decreases variability, as 

compared to using a single monthly sample. 

o See the response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 

135
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 Treating all data that are less than the quantitation limit as one-half of the sample-specific 

quantitation limit for all analytes decreases the variability of the resulting estimates, 

leading to a standard deviation of the fitted distribution that is too low. 

o The comment is incorrect in stating that EPA has substituted 1⁄2 of the samplespecific quantitation limit in developing the limitations. For non-detected 

observations, EPA’s methodology used either the sample-specific reporting limit 

for that observation, or substituted a baseline value. See Essay Section 3.5 and 

DCN SE05733.

 Averaging duplicates reduces variability compared to what is actually measured. 

o See Essay Section 3.3.

Commenter Name: S. Dear Schramm-Satayathum

Commenter Affiliation: Wabash Valley Power Association, Inc. (WVPA)

Document Control Number: EPA-HQ-OW-2009-0819-4534-A2

Comment Excerpt Number: 7

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Further, the limit for arsenic of 4 μg/L is equivalent to the quantitation limit – this is very low. 

The quantitation limit allows for bias and imprecision in the test method. The Technical 

Development Document also states that for arsenic, ‘...the limitations for gasification 

wastewater based on vapor-compression are each based on data from one plant. As such, the 

option long-term averages and variability factors for these options are the same as the plantspecific long-term averages and variability factors. Also, in special cases where there are too few 

detected results, the statistical models are not appropriate for calculating limitations since 

reliable estimates could not be obtained from the models. In such instances, EPA has established 

the daily maximum limitations based on the detection limit (i.e., “minimum level”). Also, 

monthly average limitations are not established when the daily maximum limitation is based on 

the detection limit.’6 For all effective purposes, it is possible for a gasification plant to not meet 

the proposed standard if arsenic is detected at all in the wastestream.

6

Id at Section 13.8.2, Page 13‐21 to 13‐22.

Comment Response: 

EPA does not agree that the effluent limitations for gasification wastewater are too stringent, nor 

with the commenter’s implication that bias and imprecision in the test method may contribute to 

a gasification plant not meeting the effluent limitation for arsenic. The data used to establish the 

effluent limitations reflect multiple sources of variability, including sampling and analytical 
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variability. Because of this, the effluent limitations similarly reflect the sampling and analytical 

variability inherent in the data, as well as other sources of variability. See Appendix A, Essay 

Section 3.1.

EPA also does not agree that establishing the daily maximum effluent limitation for arsenic equal 

to the quantitation limit would result in gasification plants not meeting the arsenic limitation. 

EPA has established similar effluent limitations in previous ELGs (see, e.g., BAT effluent 

limitations at 40 CFR 430.24 for the Pulp, Paper, and Paperboard Point Source Category, where 

EPA established “<ML” daily maximum limitations for certain pollutants). EPA notes that 

although the commenter, who has ownership interest in a petroleum coke gasification plant (in 

fact, one of the plants for which EPA obtained data for establishing these effluent limitations), 

asserts that additional data are needed, they did not provide any such effluent data with their 

comments on the proposed rule. See Essay Section 2.5 and the response to DCN EPA-HQ-OW2009-0819-4499-A1, Excerpt Number 15.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 121

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

A. Proposed Limits Are Not Supported By the Record

EPA proposes the following limits for FGD wastewater at existing power plants.

Pollutant Units of 

Measure

Daily 

Maximum 

Limit

Monthly 

Average Limit

Total Arsenic μg/L 8 6

Total Mercury ng/L 242 119

Total Selenium μg/L 16 10

Nitrate/Nitrite as N mg/L 0.17 0.13

As discussed below, an exceedance frequency analysis of these limits indicates that the limits 

cannot consistently be met even by Allen and Belews Creek, the two model plants.

Comment Response: 

See the response to DCN EPA-HQ-OW-2009-0819-4283-A1, Excerpt Number 17.
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Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 234

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA’s selection of datasets omitted years of relevant data from the model plants. EPA removed 

valid data points representing elevated concentrations that would be expected in the tails of the 

distributions. EPA substituted baseline values for reported measurements which had the effect of 

reducing estimated variability factors. EPA used inappropriate statistical methods for estimating 

underlying parameters of the Delta LogNormal distribution which resulted in underestimates of 

variability factors. For selenium and nitrate/nitrite, EPA abandoned the Delta LogNormal 

distribution and treated all reported values as if they were above the detection limit causing 

variability factors to be biased low. As implemented, EPA’s series of procedures systematically 

reduced estimates of long term averages and variability factors, and consequently reduced 

calculated limits.

Comment Response: 

See the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 172.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 1

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

To calculate ELGs for FGD effluent, EPA implemented a series of procedures that included 

selection of datasets, removal of data points from the datasets, substitution of data, and 

estimation of underlying parameters of the Delta LogNormal distribution. As implemented, 

EPA’s series of procedures systematically reduced estimates of long term averages and 

variability factors, and consequently reduced calculated ELGs.

EPA’s selection of datasets omitted years of relevant data from the model facilities. EPA 

identified as outliers and removed valid data points representing elevated concentrations (that 

would be expected in the tails of the distributions). EPA substituted baseline values for reported 

measurements which had the effect of reducing estimated variability factors. EPA used 

inappropriate statistical methods for estimating underlying parameters of the Delta LogNormal 
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distribution which resulted in underestimates of variability factors. For selenium and nitratenitrite, EPA abandoned the Delta LogNormal distribution and treated all reported values as if 

they were above the detection limit causing variability factors to be biased low.

Comment Response: 

See the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 172.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 14

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA’s selection of datasets omitted years of relevant data from the model facilities. EPA 

identified as outliers and removed valid data points representing elevated concentrations (that 

would be expected in the tails of the distributions). EPA substituted baseline values for reported 

measurements which had the effect of reducing estimated variability factors. EPA used 

inappropriate statistical methods for estimating underlying parameters of the Delta LogNormal 

distribution which resulted in underestimates of variability factors. For selenium and nitratenitrite, EPA abandoned the Delta LogNormal distribution and treated all reported values as if 

they were above the detection limit causing variability factors to be biased low. The resulting 

magnitude of bias in EPA’s calculated ELGs for FGD effluent is so large that the proposed ELGs 

are invalid for their intended purpose.

Comment Response: 

See the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 172.
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31.a. Engr NL – Selection of Facilities for FGD Wastewater

Commenter Name: Bruce W. Ramme

Commenter Affiliation: We Energies

Document Control Number: EPA-HQ-OW-2009-0819-4475-A1

Comment Excerpt Number: 8

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The proposed rule establishes BAT effluent limitations based on data collected at steam electric 

generating units operating the candidate technologies. We Energies is concerned, however, that 

effluent limitations derived for FGD wastewater cannot be met by all coal-fueled facilities, even 

those facilities that have already installed chemical precipitation treatment systems. This is 

especially the case for plants burning subbituminous coal. EPA sampled discharges at We 

Energies Pleasant Prairie Power Plant, a site that burns subbituminous coal, but excluded the data 

because its chemical precipitation system consists of a two-stage treatment system, which EPA 

considered to be more advanced than the one-stage system it is using as the basis for the 

chemical precipitation technology option. Yet actual operating data reveal that Pleasant Prairie 

cannot consistently meet the proposed arsenic and mercury limitations associated with EPA’s 

proposed chemical precipitation technology option. Further, nothing in the rulemaking record 

demonstrates that facilities burning subbituminous coal can meet the proposed selenium and 

nitrate/nitrite limitations. We encourage EPA to recalculate effluent limitations for FGD 

wastewater using a more robust set of data that represents the variability of FGD wastewater 

across the industry. We believe EPA needs to include data from at least one site (preferably 

more) solely burning subbituminous coal in its effluent limitations derivation, and we are 

providing self-monitoring data from Pleasant Prairie to use in this calculation.

Comment Response: 

EPA used data from Pleasant Prairie to calculate effluent limitations for arsenic and mercury for 

the final rule. See response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 59.

Also see response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 53 (in Comment 

Code 9.a) regarding the inclusion of data from the Pleasant Prairie plant in the development of 

the final effluent limitations. EPA based the limits for arsenic and mercury on treatment system 

effluent data from four plants, with 183 observations for arsenic and 670 observations for 

mercury. These data represent approximately 41⁄2 years of operation for these plants. The 

selenium and nitrate-nitrite limits are based on treatment system effluent data for two plants, 

with 398 observations for selenium and 70 observations for nitrate-nitrite. These data represent 

more than 5 years of data for one plant and more than 4 years of data for the other. See response 

to DCN EPA-HQ-OW-2009-0819-4655, Excerpt Number 124 in Comment Code 4.b regarding 

the representativeness of EPA’s FGD wastewater dataset. Also see the response to DCN EPAHQ-OW-2009-0819-5552-A2, Excerpt Number 2. In addition, see the Statistical Support 
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Document for Effluent Limitations (DCN SE05733) for the results of EPA’s engineering 

evaluation of the data used to calculate the effluent limitations for the final rule.

By including Pleasant Prairie in the dataset, the effluent limitations are based on data that include 

plants burning bituminous coal, subbituminous coal, and blends of bituminous and 

subbituminous coals. The record demonstrates that the chemical precipitation plus biological 

treatment BAT basis is effective at removing the pollutants present in FGD wastewater 

regardless of the type of coal that is burned, and in particular those pollutants for which EPA is 

establishing effluent limitations. See, e.g., the pollutant removal performance for arsenic and 

mercury. The data in the record also shows that the biological treatment technology is effective 

at removing nitrate-nitrite and the different forms of selenium present in FGD wastewater; that is 

proven true for every type of coal that has been tested with the technology. There is nothing 

unique about the form of selenium or nitrate-nitrite that is present in FGD wastewater at plants 

burning subbituminous (or any other type of coal), therefore there is no theoretical reason why 

the technology would not also be equally effective at treating the wastewater from such plants, 

nor does the commenter provide any reason why that would be so. EPA also considered whether 

there were other pollutants or wastewater characteristics unique to subbituminous coal that 

would potentially interfere with operation of the biological treatment technology. EPA did not 

identify any such potential interferences and notes that the characteristics of wastewater from 

subbituminous plants (as evidenced by the data for Pleasant Prairie, as well as Hatfield’s Ferry 

burning a coal blend that includes subbituminous) are similar to the characteristics of wastewater 

from plants burning bituminous coal (i.e., Allen, Belews Creek, Miami Fort, Keystone). Also 

see response to DCN EPA-HQ-OW-2009-0819-4655, Excerpt Number 107 in Comment Code 

10.a.

Commenter Name: Bruce W. Ramme

Commenter Affiliation: We Energies

Document Control Number: EPA-HQ-OW-2009-0819-4475-A1

Comment Excerpt Number: 12

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA should include data from plants exclusively burning subbituminous coal to develop 

technology-based limits. EPA derived technology-based limits for arsenic and mercury using 

data from only three plants using chemical precipitation technology. Two of the plants burn 

Eastern Bituminous coal, while the third plant burns a blend of Eastern Bituminous and 

subbituminous coal. FGD wastewaters from sites solely burning subbituminous coal have 

different wastewater characteristics than sites burning Eastern Bituminous coal. Data from our 

Pleasant Prairie Power Plant, which burns subbituminous coal and operates a state-of-the-art 

chemical precipitation FGD wastewater treatment system with organosulfide addition, 

demonstrates that plants burning subbituminous coal may not be able to consistently meet the 

proposed technology-based limitations for arsenic or mercury. This is particularly important 
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because the limits derived for arsenic and mercury from the chemical precipitation technology 

option are carried over and used as the limits for chemical precipitation plus biological 

treatment. EPA should recalculate the proposed limitations including data from a plant solely 

burning subbituminous coal.

Comment Response: 

EPA used data from Pleasant Prairie to calculate effluent limitations for arsenic and mercury for 

the final rule. See response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 59.

Commenter Name: Bruce W. Ramme

Commenter Affiliation: We Energies

Document Control Number: EPA-HQ-OW-2009-0819-4475-A1

Comment Excerpt Number: 39

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Chemical Precipitation BAT Evaluation Did Not Include Data from Plants Exclusively 

Burning Subbituminous Coals; Subsequently, EPA Should Recalculate BAT FGD 

Wastewater Limits to Account for Different Coal Types. 

In the preamble, EPA described what sites were chosen for the field sampling program 

(emphasis added):

EPA evaluated 10 FGD wastewater treatment systems. EPA selected these FGD systems 

because at the time it believed all were among the better performing FGD wastewater treatment 

systems in the industry, based on information obtained during the site visits and discussions with 

industry representatives about the design/operation of the treatment system and optimization 

efforts performed at the plant. In addition, these plants represent geographical variability, 

different coal types (i.e., bituminous, subbituminous, coal blends), and different operating 

practices (e.g., baseload vs. cycling). 78 Fed. Reg. at 34,444 col. 3.

Furthermore, the Technical Development Document (“2013 TDD”) described how EPA 

considered the type of coal burned when selecting plants for sampling (emphasis added):

EPA considered the type of coal that the plant burns and selected plants burning different types 

of coal because the types and concentration of metals present in the FGD wastewater could 

differ based on the fuel source. Most of the plants sampled burn bituminous coal because the 

majority of plants with wet FGD systems burn bituminous coal; however, EPA also sampled 

wastewater at plants that burn subbituminous coal. 2013 TDD at 3-10.
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Yet, when EPA calculated the limits for FGD wastewater based on chemical precipitation as 

BAT under Regulatory Option 1, no steam electric generating units exclusively burning 

subbituminous coal were included in the evaluation. (EPA then transferred the BAT FGD 

wastewater effluent limitations for arsenic and mercury calculated for the chemical precipitation 

technology option to the biological treatment technology option. Therefore, the arsenic and 

mercury effluent limitations derived for Regulatory Option 1 are the same as the effluent 

limitations proposed for Regulatory Options 2, 3b, 3, 4a, and 4.) This is especially troublesome 

because 15-20 of the plants discharging FGD Wastewater burn subbituminous coal, and another 

23-28 plants burn a blend of coals. Id. at 6-5, Table 6-2.

Data used to derive the chemical precipitation BAT effluent limitations were from Duke 

Energy’s Miami Fort Station (“Miami Fort”), RPI Energy’s Keystone Generating Station 

(“Keystone”), and Allegheny Energy’s Hatfield’s Ferry Power Generating Station (“Hatfield’s 

Ferry”). 78 Fed. Reg. at 34,488 col. 1. Miami Fort and Keystone both burn Eastern Bituminous 

coal and Hatfield’s Ferry burns a blend of bituminous and subbituminous (Powder River Basin 

or “PRB”) coal. 2013 TDD at 3-11, Table 3-3.

EPA sampled one plant which solely burns subbituminous coal: We Energies Pleasant Prairie 

Power Plant. However, data from PPPP was not used to derive the chemical precipitation BAT 

effluent limitations. EPA described their rationale for not including PPPP data as follows 

(emphasis added):

Based on data EPA has evaluated for the steam electric industry and other industry sectors, twostage chemical precipitation systems generally achieve better pollutant removals than one-stage 

systems. Since the technology basis for chemical precipitation treatment of FGD wastewater in 

the proposed rule is a one-stage system and that is the configuration used to estimate compliance 

costs, EPA concluded that effluent data for the two-stage system (Pleasant Prairie) should not 

be used when calculating effluent limits for the technology option. 78 Fed. Reg. at 34,487, fn. 

62.

According to EPA’s justification, one could rationally derive that plants with two-stage systems, 

such as Pleasant Prairie, should have no problem meeting the proposed arsenic and mercury 

effluent limitations. Yet, this is not the case for Pleasant Prairie Power Plant.

Pleasant Prairie’s dedicated wastewater treatment plant (“WWTP”) to treat FGD blowdown 

employs current state-of-the-art technology for mercury removal: lime desaturation and primary 

clarification, addition of organosulfide, ferric chloride addition for iron co-precipitation, and the 

addition of a polymer, followed by a parallel plate clarifier. The wastewater treatment plant 

currently removes over 99.9 percent of mercury. The WWTP also removes a portion of arsenic 

and selenium. (Removal efficiencies have been calculated at 95% and 78%, respectively.)

Pleasant Prairie has acquired an extensive database of mercury samples collected at the FGD 

WWTP effluent as required by Wisconsin Department of Natural Resources (“WDNR”), the 

permitting authority, to demonstrate compliance with a 1.5 ug/L (or 1500 ng/L) best professional 

judgment (“BPJ”) limit. The proposed monthly average limit of 119 ng/L is about 13 times 

lower than the BPJ limit. PPPP mercury sample results at the FGD WWTP Effluent (Sampling 
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Point 102) are presented on a logarithmic scale on Figure 1 below. (Note, data greater than the 

method detection limit, but less than the quantification limit, are shown as half the quantification 

limit, consistent with the methodology EPA used to treat non-detect and flagged data. 2013 

TDD at 10-5. Fourteen samples meet this criterion. All of the substituted values are less than 

the laboratory measured values.) Data is also available in tabular format in Appendix I.

Reviewing the results of the 441 samples collected from November 2007 – July 2013, one fifth 

of the samples are below the proposed monthly average limit of 119 ng/L. One third of the 

samples are greater than the proposed monthly limit, but less than the proposed daily maximum 

limit of 242 ng/L. About half of the samples are greater than the proposed daily maximum 

limitation. The average concentration of all of the data is 334 ng/L.

We Energies collected samples from November 2007 through May 2010 to determine the 

mercury removal efficiency of the Pleasant Prairie FGD WWTS. A comparison of the total and 

dissolved mercury in the FGD WWTS influent (Reaction Tank #1 Influent) compared to the total 

mercury in the FGD WWTS effluent (Sampling Point 102) is presented on a logarithmic scale on 

Figure 2 below. While the “dissolved” mercury data accurately portrays the concentration of the 

samples passing through a 0.45 um filter, some or all of this mercury is believed to be present in 

very fine or colloidal particles that are not truly dissolved. The data demonstrates that Pleasant 

Prairie’s chemical precipitation wastewater treatment system achieves a 99.9% mercury removal 

efficiency. Data is also available in tabular format in Appendix I.
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We Energies also collected samples to determine the mercury concentration at various stages of 

the PPPP FGD WWTS. A comparison of the total mercury concentration at the FGD WWTS 

influent (Reaction Tank #1 Influent), Primary Clarifier Effluent, Secondary Clarifier Effluent, 

and FGD WWTS effluent (Sampling Point 102) is presented on a logarithmic scale on Figure 3 

below. The mercury concentration in the FGD wastewater is significantly reduced (by about 

99.5%) after the first clarification stage. The organosulfide and ferric chloride additions occur 

after the primary clarifier. The mercury concentration in the FGD wastewater is further reduced 

(by about 85% of the primary clarifier effluent concentration) leading to an ultimate removal 

efficiency of 99.9% for the FGD WWTS. Data is also available in tabular format in Appendix I.
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Pleasant Prairie has also sampled its FGD WWTP effluent for arsenic. Sample results can be 

viewed in Figure 4 below. (Note, non-detect data and data greater than the method detection 

limit, but less than the quantification limit, are shown as half the quantification limit, consistent 

with the methodology EPA used to treat non-detect and flagged data. 2013 TDD at 10-5. Five 

samples meet this criterion.) Data is also available in tabular format in Appendix I.

Only a quarter of the samples had arsenic concentrations less than the proposed monthly average 

limit of 6 ug/L.13 A third of the samples had arsenic concentrations greater than the proposed 

monthly limit, but less than the proposed daily maximum limit of 8 ug/L.14 The balance of the 

samples had arsenic concentrations greater than the proposed daily maximum limitation. The 

average arsenic concentration of all of the data is 7.8 ug/L.
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In 2008, We Energies collected samples at various points within its Pleasant Prairie FGD 

WWTS. A comparison of the arsenic concentrations in the FGD WWTS influent (reaction tank 

#1 influent), primary clarifier effluent, and secondary clarifier effluent is presented on a 

logarithmic scale on Figure 5 below. The data demonstrates that Pleasant Prairie’s chemical 

precipitation wastewater treatment system achieves a 95% arsenic removal efficiency and 

illustrates that the second stage of clarification accomplishes additional removal beyond the first 

stage. Arsenic is typically removed from water by iron addition and the ferric chloride addition at 

Pleasant Prairie occurs after the primary clarifier. Despite the iron addition and two stages of 

clarification, the effluent concentrations still appear to be higher than the concentrations of the 

single stage systems at the Eastern Bituminous coal fueled plants sampled by EPA. Data is also 

available in tabular format in Appendix I.
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The only other site EPA sampled that burns a portion of subbituminous coal is Hatfield’s Ferry. 

At Hatfield’s Ferry, during the 4-day EPA Sampling, coal blends ranged from 16% PRB and 

84% Eastern Bituminous to 42% PRB and 58% Eastern Bituminous.15 The footnote in Table 3-

10 (of the Sampling Episode Report) indicates that the 42% blend of PRB is very atypical for 

Hatfield’s Ferry as the normal fuel blends typically run around 20% PRB/80% Eastern 

Bituminous. Data obtained from sampling at Hatfield’s Ferry was used to derive the chemical 

precipitation BAT effluent limitations; however, the data collected shows that Hatfield’s Ferry 

cannot meet the proposed monthly arsenic and mercury limitations at all times. In fact, the 

Hatfield’s Ferry plant specific Long-Term Average for Total Arsenic, as calculated by EPA, is 

6.682 ug/L, and the plant-specific monthly variability factor is 1.373. Two Total Mercury 

samples were higher than the proposed monthly mercury limitation.

As described in an attachment to UWAG’s comments, AKRF conducted a technical review of 

the statistical methods and data used by EPA to estimate limitations for FGD effluent. Their 

review indicated that self-monitoring data from Hatfield’s Ferry (over 120 days) was not used by 

EPA to derive arsenic or mercury limitations for the chemical precipitation technology option. 

As AKRF described, “EPA provided no explanation of why it excluded the self-monitoring data 

from Hatfield’s Ferry...from its final selection of data to use in its calculation of ELGs.” The 

Long-Term Average for Total Arsenic, as calculated by AKRF (using a combined dataset of the 
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EPA 4-day sampling, CWA 308 Sampling, and self-monitoring data), is 9.084 ug/L, the plantspecific daily variability factor is 2.095, and the monthly variability factor is 1.316. Based on the 

combined dataset, AKRF calculated that Hatfield’s Ferry exceeded the proposed Total Arsenic 

daily maximum limitation of 8 ug/L over half of the time (52%) and exceeded the proposed 

monthly average limit of 6 ug/L most of the time (96.4%). Evaluating Hatfield’s Ferry for Total 

Mercury, AKRF calculated the Long-Term Average to be 117.575 ng/L, with a daily variability 

factor of 6.690 and a monthly variability factor of 2.344. Hatfield’s Ferry exceeded the 

proposed Total Mercury daily maximum limitation of 242 ug/L a little over one tenth of the time 

(11.7%) and exceeded the proposed monthly average limit of 119 ug/L a little less than a third of 

the time (29.2%).

In both EPA and AKRF’s evaluations, Hatfield’s Ferry’s Total Arsenic Long Term Average 

exceeds the proposed monthly average limitation. In fact, when considering Hatfield’s Ferry’s 

self-monitoring data, the Total Arsenic Long-Term Average exceeds the proposed daily 

maximum limitation most of the time. Hatfield’s Ferry, which burns a blend of Eastern 

Bituminous and PRB coals, cannot consistently meet the proposed Total Arsenic and Total 

Mercury limits derived by EPA.

While a majority of the plants with wet FGDs in the country burn bituminous coal, EPA should 

consider and evaluate whether all of the coal plants with existing chemical precipitation systems 

can meet the proposed BAT effluent limitations for FGD effluent. According to EPA, out of the 

117 plants discharging FGD wastewater, 15-20 plants burn subbituminous coal and 23-28 burn a 

blend of coals. 2013 TDD at 6-5, Table 6-2. Therefore, upwards of 48 plants (or 41% of the 

coal plants discharging FGD wastewater) may have difficulties meeting the proposed limits 

simply because they burn subbituminous coal. Nothing in the record demonstrates that plants 

burning PRB coal with existing chemical precipitation systems (including a more advanced twostage clarification system at Pleasant Prairie) can comply with the limits for FGD wastewater 

that EPA is proposing. In fact, the record demonstrates that the proposed mercury and arsenic 

limits cannot be consistently met by the only two sites EPA sampled that burn subbituminous 

coal.

EPA should include a dataset from at least one plant (preferably more) solely burning 

subbituminous coal to derive the BAT effluent limitations for the chemical precipitation 

technology option (which were subsequently transferred as the effluent limitations for the 

biological treatment technology option). Without including data from a site which exclusively 

burns subbituminous coal, EPA is biasing the dataset used to calculate the BAT limitations 

because, as EPA correctly pointed out in the TDD, “the types and concentrations of metals 

present in the FGD wastewater could differ based on the fuel source.” Id. at 3-10. Thus, We 

Energies urges EPA to recalculate the arsenic and mercury limitations derived for FGD 

wastewater using chemical precipitation as BAT (and subsequently transferred as the effluent 

limitations for the biological treatment technology option) by including a facility (or facilities) 

that exclusively burns subbituminous coal. The full Pleasant Prairie dataset has been provided to 

EPA in Appendix I and we encourage EPA to use this data in recalculating the BAT limitations 

for FGD wastewater.
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13 Three of the eight samples below the proposed monthly average limitation were taken during 

the four- day EPA sampling.

14 One of the eleven samples above the proposed monthly average limitation and below the 

proposed daily maximum limitation was taken during the four-day EPA sampling. All four of the 

monthly CWA 308 samples were above the proposed monthly average limitation and below (or 

at) the proposed daily maximum limitation.

15 Sampling Episode Report, Allegheny Energy’s Hatfield’s Ferry Power Station, EPA-HQ-OW2009-0819-0813, p. 3-22, Table 3-10.

Comment Response: 

In response to comments, EPA used data from Pleasant Prairie to develop effluent limitations for 

arsenic and mercury for the final rule. See response to DCN EPA-HQ-OW-2009-0819-4499-A1, 

Excerpt Number 59.

Regarding the representativeness of the FGD wastewater data used to characterize the effluent 

from the treatment technologies, see response to DCN EPA-HQ-OW-2009-0819-4655-A2, 

Excerpt Number 20 in Comment Code 8.c and EPA-HQ-OW-2009-0819-4655, Excerpt 

Numbers 107 in Comment Code 10.a and 124 in Comment Code 4.b. For the final rule, EPA 

updated its loadings analysis and development of the effluent limitations and standards to include 

available self-monitoring data from Pleasant Prairie, Hatfield’s Ferry, Miami Fort, and 

Keystone. EPA also included additional self-monitoring data from Allen and Belews Creek for 

its biological treatment evaluation. Based on the additional data, the effluent limitations were 

revised for the final rule. See DCN SE05733 for more information about the effluent limitations 

and the data used.

EPA notes that the commenter neglects to mention the chemical addition rate of organosulfide or 

ferric chloride that was added to the chemical precipitation system at the plants that are 

mentioned. The chemical addition rate is a key parameter that plants can adjust to improve the 

performance of chemical precipitation systems. The injection point within the chemical 

precipitation system can also affect the degree of pollutant removal. A plant that needs to take 

steps to optimize pollutant removals may need to adjust the dosage for chemical additives, the 

pH of the wastewater within the reaction tanks, clarifier flows to reduce turbulence that would 

interfere with settling, clarifier sludge wasting protocols, and a number of other factors. 

EPA notes that the commenter is incorrect in stating that, for non-detect data and data greater 

than the method detection limit, but less than the quantification limit, EPA’s methodology for 

calculating effluent limitations substitutes those observations with one-half the quantification 

limit. For all observations lower than the quantitation limit, EPA replaced the observation with 

the sample-specific quantitation limit (or the analyte-specific baseline substitution value). See 

TDD Section 13 and DCN SE05733.
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EPA also notes that, although the dataset used to calculate the effluent limitations was 

supplemented since proposal in response to comments, certain data summarized by the 

commenter were excluded from the dataset for reasons articulated in DCN SE05733.

Commenter Name: Bruce W. Ramme

Commenter Affiliation: We Energies

Document Control Number: EPA-HQ-OW-2009-0819-4475-A1

Comment Excerpt Number: 79

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

When calculating the chemical precipitation BAT effluent limitations for FGD wastewater, EPA 

must include data from sites burning subbituminous coal.

 The types and concentrations of metals present in FGD wastewater varies dependent 

upon the fuel source.

 EPA’s arsenic and mercury effluent limitations calculations only include three plants –

two that burn bituminous coal and one that burns a blend of bituminous and

subbituminous coal.

 Nothing in the rulemaking record demonstrates that plants burning subbituminous coal 

with existing chemical precipitation systems (including a more advanced two-stage 

clarification system at Pleasant Prairie) can comply with the proposed arsenic and 

mercury effluent limitations.

 Nothing in the rulemaking record demonstrates that plants burning subbituminous coal 

can achieve the proposed selenium and nitrate/nitrite effluent limitations.

 Upwards of 48 plants (or 41% of the coal plants discharging FGD wastewater) may have 

difficulties meeting the proposed limits simply because they burn subbituminous coal.

 We Energies Pleasant Prairie data has been provided to EPA through these comments and 

we encourage EPA to use this data in recalculating the BAT effluent limitations for FGD 

wastewater.

Comment Response: 

In response to comments, EPA used data from Pleasant Prairie to calculate effluent limitations 

for arsenic and mercury for the final rule. See response to DCN EPA-HQ-OW-2009-0819-4499-

A1, Excerpt Number 59.

Regarding the representativeness of the FGD wastewater data used to characterize the effluent 

from the treatment technologies, see response to DCN EPA-HQ-OW-2009-0819-4655-A2, 

Excerpt Number 20 in Comment Code 8.c, DCN EPA-HQ-OW-2009-0819-4655, Excerpt 

Number 107 in Comment Code 10.a, EPA-HQ-OW-2009-0819-4655, Excerpt Number 124 in 
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Comment Code 4.b, and EPA-HQ-OW-2009-0819-4475-A1, Excerpt Number 8 in Comment 

Code 31.a.

Regarding whether the record demonstrates that facilities burning subbituminous coal can meet 

the selenium and nitrate/nitrite-N limitations, see response to DCN EPA-HQ-OW-2009-0819-

4655, Excerpt Number 107 in Comment Code 10.a and EPA-HQ-OW-2009-0819-4475-A1, 

Excerpt Number 8 in Comment Code 31.a.

Regarding the use of the Pleasant Prairie data provided in the comments, see response to DCN 

EPA-HQ-OW-2009-0819-4475-A1, Excerpt Number 39.

Commenter Name: John W. Myers

Commenter Affiliation: Tennessee Valley Authority (TVA)

Document Control Number: EPA-HQ-OW-2009-0819-4607-A1

Comment Excerpt Number: 8

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

a. Proposed Biological Treatment-Based FGD ELGs are Inappropriate and Their 

Compliance Reliability Unproven for the Industry

TVA believes the ELGs for FGD wastewaters being proposed have not been demonstrated by 

EPA to be achievable and therefore do not represent BAT for the coal-fired industry as a whole. 

Each of the four preferred EPA FGD options in the proposal requires a combination of chemical 

precipitation and biological treatment. The proposed FGD ELG numerical limits for arsenic and 

mercury are calculated from three plants with chemical precipitation treatment systems 

(Hatfield’s Ferry, Keystone, and Miami Fort). BAT limits for selenium and nitrate/nitrite are 

based on selected performance data of advanced wastewater treatment systems at two sites: Duke 

Energy’s Allen and Belews Creek facilities. TVA has several concerns with the development and 

applicability of the proposed FGD BAT limits based on these few sites.

Comment Response: 

EPA disagrees with the commenter that “the ELGs for FGD wastewaters being proposed have 

not been demonstrated by EPA to be achievable and therefore do not represent BAT for the coalfired industry as a whole.” See response to DCN EPA-HQ-OW-2009-0819-4655, Excerpt 

Number 107 in Comment Code 10.a.

Regarding the representativeness of the FGD wastewater data used to characterize the effluent 

from the treatment technologies, see response to DCN EPA-HQ-OW-2009-0819-4655-A2, 

Excerpt Number 20 in Comment Code 8.c and EPA-HQ-OW-2009-0819-4655, Excerpt 

Numbers 107 in Comment Code 10.a and 124 in Comment Code 4.b. EPA disagrees with the 
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commenter that “[e]ach of the four preferred EPA FGD options in the proposal requires a 

combination of chemical precipitation and biological treatment.” EPA notes that the regulations 

do not require facilities to implement the specific technologies that form the bases of the final 

limitations and standards, but only that the appropriate facility effluent limitations and standards 

be achieved. There are a number of other treatment technologies and processes available to 

plants for meeting the effluent limitations. See the preamble for information on the extent to 

which plants that generate FGD wastewater will have processes or equipment in place to meet 

the effluent limitations by the time they will need to meet the final ELGs.
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31.a.i. Engr NL Select Facs for FGD – Chemical Precipitation Treatment

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 59

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

5.8 It is unclear why EPA based its BAT determination only on sites that employ 

organosulfide addition, which is not typically used for arsenic removal. Data 

from Pleasant Prairie (a 2-stage clarification system) and Dickerson (an iron 

addition system) should also be included.

Arsenic is typically removed from water by iron addition; adding organosulfide does not remove 

significant amounts of iron. Therefore, data from sites using iron addition should be included in 

the BAT determination, even if organosulfide is not added. Data from 2-stage clarification 

systems should also be included in the BAT determination. According to EPA, Pleasant Prairie 

data were not included because the facility has 2-stage clarification. While Pleasant Prairie 

employs lime desaturation in the first stage and iron and organosulfide precipitation in the 

second stage, this approach should be comparable in performance to a one-stage clarification 

system. Dickerson’s chemical precipitation system includes iron addition. Thus, data sets from 

both of these plants should be included in evaluating limits for arsenic. The EPA sampling data 

at Pleasant Prairie chemical precipitation effluent are generally below the daily limit of 8 μg/L 

but above the monthly average limit of 6 μg/L. Dickerson chemical precipitation effluent data 

are below the limit.

5.9 The Pleasant Prairie data should also be included in the evaluation of limits 

for mercury.

As discussed in Section 5.8, the Pleasant Prairie data were excluded because the plant employed 

a 2-stage clarification treatment approach. However, this approach should have no impact on 

mercury capture and, if anything, may slightly improve mercury removal performance. Thus, 

these data should be included in the various evaluations of mercury, as well as arsenic, limits.

Comment Response: 

EPA disagrees with the commenter that “[i]t is unclear why EPA based its BAT determination 

only on sites that employ organosulfide addition, which is not typically used for arsenic 

removal.” It is clear in the record that EPA identified chemical precipitation including hydroxide 

and sulfide precipitation, as well as iron coprecipitation, as the basis for the chemical 

precipitation technology option for FGD wastewater treatment to optimize removals of both 

arsenic and mercury. The organosulfide addition primarily targets the removal of mercury, but 

can also be helpful in removing other metals. Because Dickerson does not use organosulfide in 
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its FGD wastewater treatment system, it was not identified as operating a treatment system 

consistent with the BAT basis and was, therefore, excluded from EPA’s analyses. EPA also 

notes that during the EPA sampling episode, the plant experienced an upset in the operation of its 

clarifier:

“In the afternoon of day 3 of the sampling episode, the clarifier sludge bed overturned. The 

condition was identified by turbidity measurements and wastewater treatment operators added 

polymer to counteract the situation. At 1630 on August 25, the wastewater treatment operator 

stated that turbidity levels were still elevated, although the polymer addition had reduced the 

turbidity. The operator said that SP-2 day 1 and 2 samples should be unaffected, but day 3 and 4 

samples would be affected. The sampling team monitored sample color and turbidity of the 

samples during the remainder of the sampling episode.” [DCN SE01308]

This type of upset in the FGD wastewater treatment system is not indicative of a well-operated 

system. Therefore, in addition to the plant not adding organosulfide to optimize the removal of 

mercury and other metals, EPA also determined that the data collected from the FGD wastewater 

treatment system during the EPA sampling episode at the Dickerson plant is not representative of 

a BAT system because the system was not well operated at the time the samples were collected. 

Even if EPA were to determine that the data obtained by the CWA 308 sampling were sufficient, 

it still would not represent the BAT level of control for arsenic and mercury in FGD wastewater 

because Dickerson was not adding organosulfide and therefore was not operating one of the key 

components of the BAT basis.

In response to this and other comments about the plants included in the dataset used to develop 

the effluent limitations, EPA reassessed the characteristics of plants for which it had sampling 

data to characterize chemical precipitation treatment of FGD wastewater over a period of time, in 

order to determine whether any additional data should be used in the limitations development. As 

it did for the proposed rule, for the final rule, EPA rejected using data collected during the 

detailed study because these data represent time periods that were too short to adequately 

characterize treatment system performance (either one or two days only) and because the data 

were later found to be subject to analytical interferences. In addition, as it did for the proposed 

rule, for the final rule, EPA determined that data from Dickerson are not consistent with the BAT 

level of control, for the reasons described above in this response. Similarly, as it did for the 

proposed rule, for the final rule, EPA determined that the Allen and Belews Creek data for 

arsenic and mercury at the bioreactor influent are not consistent with the BAT level of control 

because the plants were not adding organosulfide, a critical component of the BAT basis to 

optimize removals of mercury and other metals.

For the final rule, EPA also determined that it would be appropriate to use data from Pleasant 

Prairie in the dataset as representing performance of the chemical precipitation portion of the 

BAT basis, and to establish the arsenic and mercury effluent limitations in the final rule. 

Although Pleasant Prairie operates a two-stage chemical precipitation treatment system, with 

each stage including clarification, EPA determined that the Pleasant Prairie treatment system was 

in large measure operated in a manner consistent with the one-stage chemical precipitation 

treatment systems operated at Keystone, Miami Fort, and Hatfield’s Ferry. EPA concluded that it 

is the fact of addition of certain components of the chemical precipitation system that makes it 
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consistent with the BAT basis, not how many stages a plant breaks its chemical addition into. In 

other words, it does not matter how many steps a plant uses to achieve chemical precipitation, so 

long as it makes use of the components that EPA has identified as part of the BAT basis, it can 

achieve the final limitations.

In the chemical precipitation system, plants add lime (calcium hydroxide), ferric (or ferrous) 

chloride, and/or organosulfide to precipitate some metals. EPA’s BAT basis of chemical 

precipitation plus biological treatment includes all three of these chemical additions. Lime is 

added to elevate the pH of the wastewater to a designated set point, helping precipitate metals 

into insoluble metal hydroxides that can be removed by settling and filtration. Ferric (or 

ferrous) chloride is used to coprecipitate additional metals and organic matter. The ferric chloride 

also acts as a coagulant, forming a dense floc that enhances settling of the precipitated metals in 

the downstream clarification step. Sulfide precipitation improves the removal of some metals, 

such as mercury, by creating metal sulfide compounds that are less soluble than metal hydroxide 

compounds. Chemical precipitation can be designed to add all three chemicals to the same 

reaction tank or to add each chemical in separate tanks.

Thus, although a two-stage chemical precipitation treatment system can provide the operator 

with additional flexibility and capability to more precisely target differing pH setpoints, as well 

as the sequencing of adding other treatment chemicals, a two-stage system can also be operated 

such that it is generally equivalent to a one-stage treatment system. The same would be true of 

the degree of suspended solids removal accomplished by the two clarifiers in the two-stage 

treatment system, whereby the effluent TSS concentrations for a one-stage and two-stage system 

would be comparable depending on how the treatment system is operated.

Although EPA received comments suggesting certain plants, including Pleasant Prairie, should 

be included in the BAT limitations development dataset, EPA did not receive any comments 

during the 106-day public comment period suggesting that certain plants operate treatment 

systems that are not consistent with the chemical precipitation technology basis described and 

costed for treatment of FGD wastewater, and thus should not be included in the final limitations 

development. In light of comments stating that Pleasant Prairie should be included in the BAT 

limitations development dataset even though it operates two-stage precipitation, including a 

second stage of clarification, EPA looked closely at the model BAT plants (for the chemical 

precipitation portion of the BAT basis), as well as other BAT-candidate plants for which EPA 

collected samples, to determine if their treatment systems included additional equipment or 

treatment steps that were not specified at proposal as part of the chemical precipitation 

technology basis.

During EPA’s evaluation of the model BAT plants, it became apparent that Keystone, one of the 

model BAT plants, may be viewed by some as having more advanced technology than specified 

by EPA as the chemical precipitation technology basis for treatment of FGD 

wastewater. However, a close review of the Keystone treatment system design and the data for 

the model BAT plants show that the Keystone technology is not “beyond BAT.” In essence, the 

additional equipment at Keystone is a “distinction without a difference,” as is the case for the 

additional equipment and treatment stage at Pleasant Prairie.
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As EPA noted above for Pleasant Prairie, the effluent TSS concentrations for a one-stage and 

two-stage treatment system may be comparable depending on how the treatment system is 

operated. As described below, EPA determined that the additional equipment included in the 

Keystone treatment system is operated in such a manner that the effluent concentration of TSS

(and as a result, arsenic, mercury and other pollutants) at the plant is comparable to the removal 

of TSS (and arsenic, mercury and other pollutants) at the other model BAT plants.

The treatment system at Keystone includes polishing filters (“sock filters”), in addition to sand 

filters, to remove TSS following one-stage chemical precipitation and a single clarifier. Both the 

polishing filters and sand filters are designed to remove suspended solids from the FGD 

wastewater. As EPA noted in the Sampling Episode Report for Keystone:

“The FGD wastewater treatment system was originally designed such that the plant could bypass 

the polishing filters if the TSS level after the sand filters met the plant’s permit limit. However, 

Keystone has found that using the polishing filters full time is necessary to keep the TSS 

concentration below their permit limit, which is 10 mg/L (monthly average) and 20 mg/L (daily 

maximum).“1 See DCN EPA-HQ-OW-2009-0819-0808.

During its reassessment of the characteristics for the model BAT plants, EPA carefully reviewed 

the information in the record for the treatment system at Keystone, and in particular the use of 

polishing filters, to evaluate whether it represents a level of treatment beyond that included in 

EPA’s BAT basis. Based on the information in the record, EPA determined that the design 

performance capability of the polishing filter at Keystone is equivalent to the design performance 

capability of the sand filters at the other model BAT plants. A technical report prepared by the 

Electric Power Research Institute (EPRI) explains the capability of sand filtration as applied to 

FGD wastewater:

Filtration is used to remove TSS and heavy metals in particulate form. Filtration will typically 

not be used in process wastewater applications unless metals limits cannot be met with chemical 

precipitation and clarification. Sand filters can typically reduce FGD wastewater TSS to below 

10 ppm and remove solids that are 5 micrometers or larger. Membrane technologies, such as 

microfiltration, ultrafiltration, nanofiltration, or reverse osmosis could be used to remove 

smaller solids particles from process wastewater. However, these technologies have not been 

commercially applied to FGD wastewater and there are concerns with potential membrane 

scaling. [Emphasis added]

Flue Gas Desulphurization (FGD) Wastewater Chemical Precipitation Bench-Scale Treatability 

Study. EPRI, Palo Alto, CA, 2015. EPRI Report Number 3002004893.

The EPRI characterization of filtration capabilities (in terms of particle size) is generally 

consistent with the figure below, showing that particle filtration (e.g., sand filters) will remove 

 

1 The ELGs at 40 CFR 423 include BPT effluent limitations applicable to FGD wastewater, with the limitations set 

at 30 mg/L monthly average and 100 mg/L daily maximum. Keystone’s NPDES permit limits for TSS (10 mg/L 

monthly average; 20 mg/L daily maximum) are more stringent than the ELG effluent limitations. As noted in EPA’s 

notes for a February 1, 2010 site visit, “The permit authority lowered Keystone’s limit on TSS in exchange for 

allowing the plant to discharge a higher concentration of selenium.” See DCN EPA-HQ-OW-2009-0819-1839.
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particles as small as approximately one micron, and that microfiltration technology is used to 

remove particles smaller than 2 micron and can remove particles as small as 0.04 micron. (The 

figure below is from the Good Water Company website, 

http://goodwatercompany.com/Products/Green_Options/. It was included in a section on well 

water treatment for drinking water. The filtration principles, however, are the same for 

wastewater treatment systems.) 

EPA’s notes from a February 1, 2010, site visit to Keystone include a diagram for the treatment 

system showing that the polishing filters were designed to have a filter pore size of 3 micron 

(Attachment 5 to DCN EPA-HQ-OW-2009-0819-1839). As part of EPA’s reassessment of the 

model BAT plants, EPA contacted Keystone staff and confirmed that the pore size of the sock 

filters actually being used at Keystone is 10 micron (see 8/25/2015 email documenting phone 

call confirming 10 micron rating for filters; DCN SE06290). This information demonstrates that 

the polishing filters at Keystone do not meet EPRI’s definition of microfiltration, ultrafiltration, 

nanofiltration, or reverse osmosis, nor the similar definitions used by the equipment vendor cited 

above.

EPA also reviewed the TSS effluent data collected during EPA-collected sampling and CWA 

308 sampling at the four model BAT plants and found that the plants all demonstrate TSS 

removal consistent with particle filtration, such as sand filtration and comparable techniques.

TSS (mg/L)

EPA-collected sampling Summary Results for 

CWA 308 sampling
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Keystone 13.4 <4, <4, <4, <4

Hatfield’s Ferry <2.5 4.4, <4, <4, <4

Miami Fort 14.1 8.4, 4.8, 8.8, 8.8

Pleasant Prairie <4.0 <4, <4, <4, <4

MDL = 1.1 mg/L

QL = 4 mg/L

Detailed TSS results for CWA 308 sampling

Keystone 3.2 J 2 J ND 3.2 J

Hatfield’s Ferry 4.4 2.8 J 2.8 J 1.6 J

Miami Fort 8.4 4.8 8.8 8.8

Pleasant Prairie 2.8 J 2 J ND 1.2 J

ND: Reported result is less than the MDL of 1.1 mg/L

J: Reported result is above the MDL, but below the QL of 4 mg/L

Based on the information in the record regarding the treatment system design, theoretical 

filtration capability, and the TSS concentrations achieved by the model BAT plants, as shown by 

the sampling data, EPA concluded that the combination of the clarification, sand filter and 

polishing filter at Keystone results in a treatment level that is comparable to the level of 

treatment achieved by the clarification and sand filtration at the other model BAT plants of 

Miami Fort, Hatfield’s Ferry, and Pleasant Prairie. And, as noted above, EPA determined that the 

Pleasant Prairie treatment system is in large measure operated in a manner consistent with the 

one-stage chemical precipitation treatment systems operated at Keystone, Miami Fort, and 

Hatfield’s Ferry. Therefore, EPA determined that the data from all four plants are consistent with 

the BAT level of control for arsenic and mercury in FGD wastewater discharges, and thus EPA 

used data from all four plants in developing the final arsenic and mercury limits.

EPA determined that the level of TSS removal (i.e., filtration) at Keystone is comparable to the 

other BAT plants, and thus there should be no need for the other model BAT plants or any other 

plants to install similar polishing filters to treat their FGD wastewater. Keystone uses the 

polishing filters to ensure compliance with their NPDES permit limits for TSS, which are more 

stringent than the previously established BPT limitations on TSS in the ELGs. See 40 CFR 

423.12. However, although use of these polishing filters provides Keystone with added assurance 

that the effluent will not exceed its NPDES limits, the sampling data for the four model BAT 

plants show that they all achieve comparable TSS removal. Therefore, EPA has no reason to 

conclude that other plants would also need to employ polishing filters in addition to clarification 

and sand filtration to achieve the TSS removals that Keystone achieves. In other words, the use 

of polishing filters at Keystone does not result in treated effluent that is markedly different than 

the levels that the other model BAT plants achieve with their particular combination of solidliquid separation technologies. In fact, the data from the other model plants demonstrate that, in 

some cases, they are achieving lower or equivalent TSS effluent values than Keystone.

EPA nonetheless estimated what it would cost plants to install and operate polishing filters 

similar to those used at Keystone. EPA contacted a filtration system vendor and obtained cost 

information for the filtration units and associated equipment, as well as replacement filter 
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cartridges. EPA used these data to estimate total installed cost and annual operating costs for the 

polishing filters. EPA evaluated these costs for both 10 micron and 1 micron filters and found the 

costs would be the same (see DCN SE06334 for more information about the cost for polishing 

filters). EPA’s analysis demonstrates that the additional cost to install and operate polishing 

filters similar to Keystone’s would be negligible. When compared to the industry-level costs for 

the BAT technology (i.e., treating FGD wastewater with chemical precipitation plus biological 

treatment), polishing filter costs represent 0.1% of total capital costs and 0.6% of annual O&M 

costs. EPA notes that the Clean Water Act does not require EPA to make a precise calculation of 

costs. See, e.g., CMA v. EPA, 870 F.2d 177, 237-38 (5th Cir. 1989) (“The Act requires the EPA 

to ‘take into account’ the costs of BAT; it does not require a precise calculation. The EPA ‘need 

make only a reasonable cost estimate in setting BAT’; it is sufficient if the EPA develops ‘a 

rough idea of the costs the industry would incur’” (citation omitted).); Kennecott Copper v. EPA,

612 F.2d 1232, 1238 (10th Cir. 1979) (EPA has “wide leeway in its analysis of costs”); BP 

Exploration & Oil Inc. v. EPA, 66 F.3d 784, 799-800 (6th Cir. 1995) (“The CWA does not 

require a precise calculation of BAT and NSPS costs” (citation omitted).); NRDC v. EPA, 863 

F.2d 1420, 1426 (9th Cir. 1988) (“[T]he Act does not require a precise calculation of BAT 

costs.”); Weyerhaeuser v. Costle, 590 F.2d 1011, 1045 (D.C. Cir. 1978) (“[Congress] left EPA 

with discretion to decide how to account for the consideration factors, and how much weight to 

give each factor.”); BASF Wyandotte Corp. v. Costle, 598 F.2d 637, 662 (1st Cir. 1979).

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 82

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Although it had data from seven plants with chemical precipitation systems, EPA chose only 

three to characterize chemical precipitation treatment levels: Miami Fort, Keystone, and 

Hatfield’s Ferry. See 2013 TDD at 10-9 to 10-10, Table 10-4 at 10-10. The three plants that 

EPA selected have the highest pollutant loadings of the plants sampled by EPA. Therefore, they 

have the highest annual TWPE removals. EPA should have sampled more plants to calculate 

more representative pollutant reductions.

EPA did not use Belews Creek’s and Allen’s chemical precipitation effluent because those plants 

do not use organosulfide in their chemical precipitation systems. But for all parameters except 

mercury, Belews Creek and Allen chemical precipitation effluent is likely an accurate 

representation of treatment levels for chemical precipitation. EPA excluded data from Dickerson 

Generating Station because it “was not adding organosulfide chemicals to the wastewater 

treatment system at the time of sampling. The plant also experienced frequent shutdowns, 

wastewater treatment upsets, and the treatment system is not designed to remove 

selenium.” 2013 TDD at 10-6.32
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EPA excluded Pleasant Prairie because of its two-stage treatment system, which EPA noted “is 

more advanced than the one-stage chemical precipitation system used as the bases [sic] for the 

chemical precipitation technology option.” Id. Based on EPA’s justification, one could 

conclude that plants with two-stage systems, such as Pleasant Prairie, should have no problem 

meeting the proposed arsenic and mercury effluent limitations. Yet this is not the case for 

Pleasant Prairie. Including Pleasant Prairie in EPA’s dataset would have produced less stringent 

proposed limits even though it has a two-stage system. UWAG believes EPA should have used 

the Pleasant Prairie data when developing the proposed effluent limits for chemical precipitation 

systems.

32 EPA’s decision not to use Dickerson’s data is not justified by its status as a peaking 

plant. That Dickerson is a peaking plant with “frequent shutdowns” is not a reason to exclude its 

data; to the contrary, it is a good reason for including its data so that the operations of peaking 

units are reflected in the data.

Comment Response: 

Regarding the plants with the “highest pollutant loadings,” see response to DCN EPA-HQ-OW2009-0819-4470-A1, Excerpt Number 3.

Regarding the representativeness of the FGD wastewater data used to characterize the effluent 

from the treatment technologies, see response to DCN EPA-HQ-OW-2009-0819-4655-A2, 

Excerpt Number 20 in Comment Code 8.c and EPA-HQ-OW-2009-0819-4655, Excerpt 

Numbers 107 in Comment Code 10.a and 124 in Comment Code 4.b.

EPA disagrees with the comment that “for all parameters except mercury, Belews Creek and 

Allen chemical precipitation effluent is likely an accurate representation of treatment levels for 

chemical precipitation.” EPA notes that sulfide precipitation is capable of achieving removals for 

more than just mercury and, as such, EPA expects that some pollutants would show greater 

removals in a sulfide precipitation system compared to a system without sulfide precipitation. 

Therefore, the Allen and Belews Creek data were excluded because they do not operate their 

chemical precipitation system consistent with the BAT level of control. Regarding the exclusion 

of the Dickerson plant, as well as Allen and Belews Creek, from the dataset of plants that EPA 

used to calculate effluent limitations for arsenic and mercury, see response to DCN EPA-HQOW-2009-0819-4499-A1, Excerpt Number 59.

Regarding the inclusion of data from Pleasant Prairie in the development of the effluent 

limitations and standards, see response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt 

Number 59 and DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 53 (in Comment 

Code 9.a).
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Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 3

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Although EPA collected data from Pleasant Prairie and Dickerson facilities, it did not include 

data from those facilities in its ELG calculations. EPA did not explain why it excluded data from 

Pleasant Prairie or Dickerson from its ELG calculations.

Comment Response: 

EPA used data from Pleasant Prairie to calculate effluent limitations for arsenic and mercury for 

the final rule. Data for Dickerson were not used to calculate effluent limitations for the ELGs 

because the plant does not operate its treatment system consistent with the BAT level of control. 

See response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 59.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 18

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA provided no explanation of why it excluded the self-monitoring data from Hatfield’s Ferry 

and Miami Fort from its final selection of data to use in its calculation of ELGs.

Comment Response: 

For the final rule, in response to public comments, EPA updated its loadings analysis and 

development of the effluent limitations and standards to include available self-monitoring data 

from Hatfield’s Ferry and Miami Fort. EPA also included additional self-monitoring data from 

Keystone, Pleasant Prairie, Allen, and Belews Creek. See the Statistical Support Document for 

Effluent Limitations (DCN SE05733).

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG
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Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 27

External Review Flag: Statistics

External Review Incorporated into Response: No

Comment Excerpt: 

EPA identified Pleasant Prairie as having a treatment system that would have better pollutant 

removals than facilities with the BAT treatment system:

“Based on data EPA has evaluated for the steam electric industry and other industry sectors, twostage chemical precipitation systems generally achieve better pollutant removals than one-stage 

systems. Since the technology basis for chemical precipitation treatment of FGD wastewater in 

the proposed rule is a one-stage system and that is the configuration used to estimate compliance 

costs, EPA concluded that effluent data for the two-stage system (Pleasant Prairie) should not be 

used when calculating effluent limits for the technology option.” (page 13-4, EPA 2013)

Therefore, results of this assessment, including Pleasant Prairie, should be conservative (i.e., 

have lower frequencies of exceedance than expected).

Comment Response: 

EPA used data from Pleasant Prairie to calculate effluent limitations for arsenic and mercury for 

the final rule. See response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 59. See 

the Statistical Support Document for Effluent Limitations (DCN SE05733) for the results of 

EPA’s engineering evaluation of the data used to calculate the effluent limitations for the final 

rule.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 89

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA’s effluent limits based on chemical precipitation also do not reflect even the bestperforming precipitation systems. EPA chose to base its limits on a one-stage system, rather 

than a two-stage precipitation system, despite acknowledging that “two-stage chemical 

precipitation systems generally achieve better pollutant removals than one-stage systems.”346 The 

two-stage system allows the pH and other conditions to be optimized for each precipitation 

step.347 The Wisconsin Energy Pleasant Prairie plant uses a two-stage system, and EPA collected 

effluent data from that plant as part of this rulemaking.348 Because the BAT limits for arsenic 
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and mercury based on chemical precipitation are transferred to the chemical precipitation plus 

biological treatment option, EPA’s decision not to use the most effective precipitation systems as 

the basis for these BAT limits is means that the mercury and arsenic limits for the combined 

chemical and biological treatment option are also much weaker than they should be. EPA must 

base the mercury and arsenic limits for options involving chemical precipitation on the 

performance of two-stage chemical precipitation.

346 78 Fed. Reg. at 34,487 n.62.

347 TDD at 7-5 to 7-6.

348 78 Fed. Reg. at 34,487 n.62.

Comment Response: 

EPA used data from Pleasant Prairie to calculate effluent limitations for arsenic and mercury for 

the final rule. See response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 59. 

Therefore, a two-stage chemical precipitation system is reflected in its analyses.
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31.a.ii. Engr NL Select Facs for FGD – Chemical Precipitation followed by Biological 

Treatment

Commenter Name: John W. Myers

Commenter Affiliation: Tennessee Valley Authority (TVA)

Document Control Number: EPA-HQ-OW-2009-0819-4607-A1

Comment Excerpt Number: 10

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

3. The sampling and analysis program employed by EPA to characterize pollutant removals was 

inadequate to conduct an appropriate and defensible analysis of wastewater treatment 

performance and variability over time. As detailed in comments submitted by the Utility Water 

Act Group (UWAG), the limited number of samples evaluated, the failure to collect 

representative intake composite samples, an inappropriate selection of sampling locations, and 

neglecting the need for paired influent and effluent samples are of significant concern. As noted 

by UWAG the projected exceedance rates based on the limited operational history for the 

proposed model plants average greater than 20% for the proposed daily maximum limits and 

greater than 40% for the proposed monthly average limits.

Comment Response: 

EPA does not agree that the data used to characterize pollutant reductions was inadequate to 

assess performance and variability over time. The effluent limitations are not based on a “limited 

number of samples.” EPA based the limits for arsenic and mercury on treatment system effluent 

data for four plants, with 183 observations for arsenic and 670 observations for mercury. These 

data represent approximately 41⁄2 years of operation for these plants. The selenium and nitratenitrite limits are based on treatment system effluent data for two plants, with 398 observations 

for selenium and 70 observations for nitrate-nitrite. These data represent more than 5 years of 

data for one plant and more than 4 years of data for the other. See response to DCN EPA-HQOW-2009-0819-4655, Excerpt Number 124 in Comment Code 4.b regarding the 

representativeness of EPA’s FGD wastewater dataset. Also see the response to DCN EPA-HQOW-2009-0819-5552-A2, Excerpt Number 2.

Regarding the comment about “failure to collect representative intake composite samples,” 

during the detailed study of the steam electric industry, EPA determined that it was unnecessary 

to collect intake water samples for the FGD wastewater analyses because the concentrations of 

the pollutants present in the untreated FGD wastewater are at such high levels that it was obvious 

that the pollutants are generated as part of the FGD process and are not due to intake water 

contributions. Neither this commenter, nor any other commenter, provided data to EPA to 

demonstrate that the pollutant concentrations present in the untreated FGD wastewater are due to 

intake water contributions. Additionally, EPA notes that the commenter (or UWAG on behalf of 

the commenter) collected intake samples during the detailed study sampling episode at TVA’s 

Widows Creek plant; however, those intake sample results have never been shared with EPA.
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The pollutant concentrations in the influent are sufficiently high, relative to the effluent 

concentrations, to demonstrate that pollutants in FGD wastewater are effectively removed by the 

BAT treatment technology. The influent pollutant concentrations in the untreated wastewater are 

variable, yet consistently remain substantially above the effluent concentrations. The data are 

sufficiently representative of influent and effluent concentrations that comparing the mean 

effluent concentrations to the mean influent concentrations provides a reasonable estimate of 

pollutant reductions. In addition, the effluent limitations are based on statistical analysis of the 

effluent data (see the TDD Appendix B) and are not based on percent removal across the 

treatment system. For these reasons, it is not necessary to collect paired influent and effluent 

samples.

Regarding the EPA’s engineering review of the data and the effluent limitations, see DCN 

SE05733.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 83

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

4. EPA’s proposed effluent limits for the biological treatment BAT option can be reliably 

achieved across the industry

EPA gathered extensive monitoring data about the performance of the systems at two plants: 

Belews Creek and Allen, because these were the two plants that had been operating at least six 

months and achieved steady state, according to their operators. Based on these data, EPA has 

proposed limits for arsenic, mercury, selenium, and nitrates/nitrites. EPA’s limits for mercury 

and arsenic are based on the performance of a chemical precipitation system employing 

both hydroxide and polysulfide treatment, while the selenium and nitrate/nitrite limits are based 

on the biological treatment system.

All of these effluent limits proposed by EPA are supported by the record. In fact, the record 

would support setting mercury and arsenic limits even lower based on the additional reductions 

that occur in the biological treatment system.

On behalf of the Sierra Club, Dr. David Jenkins reviewed the data used by EPA to set these 

proposed standards. Dr. Jenkins was also able to obtain influent and effluent data for selenium 

and mercury for a third plant operating the ABMet system, which the vendor identified simply as 

the “NE USA” plant. According to the vendor, the plant uses both hydroxide and polysulfide 

chemical precipitation prior to the biological treatment system, which means that this system 
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represents more completely the treatment technology proposed as BAT than the Allen 

and Belews plants.

We believe that the data obtained from the vendor is for the American Electric Power 

Mountaineer plant in West Virginia. The vendor identifies that plant as a single-boiler 1300 MW 

facility, and the system became operational in late 2011.325 Both of these relatively unique facts 

match the Mountaineer plant in the record.326 Another critical fact is that the vendor reports that 

the ABMet system handles combustion waste landfill leachate, which is true of the Mountaineer 

system as well.327 This fact is highly relevant for EPA’s BAT determination regarding leachate, 

as is discussed in detail further below.

As discussed in the report of Dr. David Jenkins, Appendix C, the effluent data from Belews and

Allen plants, as well as those from a third plant, show that the ABMet system can reliably meet 

the selenium and mercury limits set by EPA, and that the ABMet system can achieve mercury 

reductions even greater than those achieved by the two-stage chemical precipitation system.

325 Jay Harwood, Making the Change: Meeting EPA Effluent Limitation Guidelines, May 23, 

2013, at slides 23-24.

326 See Email to TJ Finseth from AEP, Docket No. EPA-HQ-OW-2009-0819-0577, stating that 

the ABMet system at Mountaineer started up on Nov. 11, 2011, and achieved steady state on 

February 11, 2012.

327 See HDR, Inc., Biological Treatment for Power Generation, June 11, 2013, at Slide 16; see 

also ERG Memo, Status of Biological Treatment Systems to Remove Selenium (April 19, 2013), 

EPA-HQ-OW-2009-0819-2127.

Comment Response: 

EPA agrees with the commenter that the “effluent limits for the biological treatment BAT option 

can be reliably achieved across the industry.” See responses to DCN EPA-HQ-OW-2009-0819-

4702-A7, Excerpt Number 5 in Comment Code 10.a and DCN EPA-HQ-OW-2009-0819-4655, 

Excerpt Number 107 also in Comment Code 10.a. Also see DCN 05733.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 85

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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c. The biological treatment option can meet EPA’s proposed effluent limits across a range 

of operating conditions.

Industry has expressed concerns that EPA has based its limits for the biological treatment option 

only on plants burning eastern bituminous coal, and that these results may not be achievable at 

plants burning other types of coal. This concern overlooks is that wet FGD systems are most 

likely to be used at plants burning bituminous coal. According to EPA and EIA data, over 

70% of the nation’s wet-scrubbed generating capacity is at plants that burn bituminous 

coal.337 This is because bituminous coal has high sulfur levels, and therefore requires the greater 

sulfur dioxide removal rates of a wet scrubber, as compared to a dry scrubber. Plants burning 

sub-bituminous coals are more likely to control SO2 using a dry scrubber or dry sorbent 

injection, if any SO2 emission controls are needed at all.338

337 See EPA 2009 Final Detailed Study Report, EPA-HQ-OW-2009-0819-0387, at Table 4-2. To 

the extent that plants switch to PRB coal, they would be able to use dry scrubbers and eliminate 

the FGD wastewater stream entirely.

338 Lindsay Morris, The Ins and Outs of SO2 Control, Power Engineering, June 1, 2012, 

available at http://www.power-eng.com/articles/print/volume-116/issue-6/features/the-ins-andouts-of-so2-control.html.

Comment Response: 

EPA agrees with the commenter that “wet FGD systems are most likely to be used at plants 

burning bituminous coal [sic] because bituminous coal has high sulfur levels.” Additionally, 

EPA has determined that its dataset used to characterize the effluent from the treatment 

technologies is representative of the industry as a whole. See response to DCN EPA-HQ-OW2009-0819-4655-A2, Excerpt Number 20 and EPA-HQ-OW-2009-0819-4655, Excerpt Numbers 

107 in Comment Code 10.a and 124 in Comment Code 4.b. Also see DCN SE05846 (Variability 

in Flue Gas Desulfurization Wastewater: Monitoring and Response).
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31.a.iii. Engr NL Select Facs for FGD – Chemical Precipitation followed by VaporCompression Evaporation Treatment

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 68

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Other than having a much more advanced wastewater treatment system, the Brindisi plant is 

similar to many coal plants in the United States. The plant was built in 1993 and has four units 

that are scrubbed by a limestone forced oxidation system.262 The plant burns a blend of low 

sulfur and bituminous coal, has SCR installed for NOx control on all four units, a fabric filter on 

Unit 3, and ESPs on the other units.263 Therefore, the record supports EPA’s conclusion that 

these limits could be achieved by plants in the United States operating a similar system, 

comprising pre-treatment, vapor compression, and crystallization.

262 Id. At 3-13, 13-5; ENEL Site Visit Notes, EPA-HQ-OW-2009-0819-1795.

263 EPA-HQ-OW-2009-0819-1791, at 2-1.

Comment Response: 

EPA agrees with the commenter that the “Brindisi plant is similar to many coal plants in the 

United States.” As the commenter describes, the operations at the Brindisi plant are generally 

comparable to the types of operations at most coal-fired plants in the United 

States. Additionally, EPA determined that the concentrations of untreated FGD wastewater at 

the Brindisi plant are within the range of the untreated FGD wastewater concentrations for the 

plants in the United States.
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31.b. Engr NL – Selection of Facilities for Gasification Wastewater

Commenter Name: Paul Carpmone

Commenter Affiliation: Tampa Electric Company (TEC)

Document Control Number: EPA-HQ-OW-2009-0819-4520-A2

Comment Excerpt Number: 10

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Insufficient Data Available for Gasification Wastewater Rulemaking

Polk PS is one of three coal gasification power plants currently operating in the US, and one of 

only two operating during the sampling period associated with this proposed rulemaking. Even 

though these plants employ the same basic process, there are differences in operation just as 

there are variations within traditional coal burning power plants. At a minimum, these plants 

differ according to coal type and in the byproducts which result from the gasification process.

In 2007, EPA visited Polk PS for the purpose of obtaining samples of wastewater associated with 

the gasification process. The sampling protocol included sampling throughout the process water 

recycle system and was conducted over four days in the fall. Similarly, the Wabash Valley plant 

was visited for a four-day sampling event. The third plant, Edwardsport IGCC, was not yet 

operational. In essence, EPA has used the data obtained from two power plants over a mere total 

of eight days to establish a federal effluent limitation guideline.

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4655, Excerpt Number 167 in Comment Code 

23.

EPA notes that the commenter operates the Polk Power Station and the gasification process at 

that plant (in fact, as the commenter noted, one of the plants for which EPA obtained data for 

establishing these effluent limitations). Thus, it is particularly noteworthy that, although the 

commenter asserts that insufficient data were available for gasification wastewater, they did not 

provide any such effluent data with their comments on the proposed rule. In its proposed rule, 

EPA clearly identified the data that it had collected and used to calculate the proposed 

limitations. EPA solicited comment on the proposed rule, providing stakeholders with the 

opportunity to submit additional data if they chose to do so. In some cases, such as for the 

chemical precipitation and biological treatment technologies for FGD wastewater, commenters 

submitted large amounts of data representing years of treatment system operation. EPA 

evaluated these effluent data and, as appropriate, used these data in establishing the effluent 

limitations for the final rule. However, in other cases, such as for gasification wastewater and for 

the vapor-compression evaporation technology for FGD wastewater, EPA received no additional 

data. Thus, in establishing the ELGs, EPA has used all of the appropriate data available. Had 
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industry or other stakeholders come forward and provided EPA with more data, EPA likely 

would have used it, if it were valid and representative of the BAT basis, as appropriate.

See Appendix A, Essay Section 3.2.1.1.

Commenter Name: S. Dear Schramm-Satayathum

Commenter Affiliation: Wabash Valley Power Association, Inc. (WVPA)

Document Control Number: EPA-HQ-OW-2009-0819-4534-A2

Comment Excerpt Number: 4

External Review Flag: Statistics

External Review Incorporated into Response: No

Comment Excerpt: 

Proposed Limits are Based on Results from a Limited Type of Wastestream

It appears that USEPA based these proposed limits from a single effluent stream - condensate 

from vapor compression evaporator – which is inappropriate. Each gasification facility is unique 

and so are the gasification effluent streams. Condensate from vapor compression evaporator at 

the gasification plant associated with the Wabash River Combined Cycle Plant (herein, ‘Wabash 

River’) is distillate water, which is a very clean effluent stream. In Wabash River’s case, the 

gasification facility is capable of discharging gasification wastewaters from up to 6 locations 

‘prior to use of the gasification wastewater with water or any other process wastewater’ and not 

all wastewater from each of these streams has the same characteristics as the condensate from the 

vapor compression evaporator.

In the Technical Development Document accompanying this proposed rulemaking, USEPA 

acknowledges that the Polk Power Station does produce two effluent streams, but ‘determined 

that the data collected at forced circulation evaporator condensate did not demonstrate typical 

removal rates for pollutants generally well treated by evaporation and therefore were not 

adequate to form the basis of the limitations. Based on its review of the treatment system, EPA 

believes that the evaporator (or at a minimum the forced circulation evaporation stage) was 

operating abnormally and allowing carryover of pollutant to the condensate effluent stream. For 

this reason, EPA based the limitations for this technology option on the limitations calculated 

from the vapor compression evaporator effluent data.’3It is unclear how USEPA determined that 

this was not ‘typical removal rates for pollutants generally well treated by evaporation’ at a 

gasification plant.

3

Id at Section 13.8.1, Page 13‐20.

Comment Response: 
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Regarding establishing the limitations and standards based on the distillate/condensate stream 

and the six effluent streams from the Wabash River plant, see responses to DCN EPA-HQ-OW2009-0819-4655, Excerpt Number 171 in Comment Code 23.a.

Regarding the exclusion of the Polk Power Station forced circulation evaporator condensate, see 

response to DCN EPA-HQ-OW-2009-0819-4655, Excerpt Number 6. As discussed at proposal, 

EPA determined that the data collected at forced circulation evaporator condensate do not 

demonstrate typical removal rates for pollutants generally well-treated by evaporation and 

therefore are not adequate to form the basis of the limits. See, e.g., the concentrations for TDS 

and chlorides in the forced circulation evaporator condensate. Based on EPA’s review of the 

treatment system, the data indicate that the evaporator (or at a minimum the forced circulation 

evaporation stage) at Polk was operating abnormally and allowing carryover of pollutants to the 

condensate effluent stream. Comments on the proposed effluent guidelines from Tampa Electric 

Company (the owner/operator of Polk Power Station) did not dispute EPA’s conclusion about 

abnormal operation of the evaporator, nor EPA’s decision not to use data for the forced 

circulation evaporation condensate for calculating the effluent limits for gasification wastewater.
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31.c. Stats NL – Selection of Data Within Facilities for FGD Wastewater

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 28

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

To accurately characterize the tails of distributions, as much data as is available should be used. 

For example it would require at least 100 days of sampling over the course of a year to 

empirically characterize the 99th percentile of daily concentrations. As the number of samples 

decreases, the extent to which the characterization is based on assumption, rather than fact, 

increases.

Over 120 days of self-monitoring data for arsenic and mercury were available from Hatfield’s 

Ferry. Over 20 days of self-monitoring data for mercury were available form Miami Fort. Almost 

100 days of self-monitoring data for nitrate-nitrite were available from Belews Creek, and 7 days 

of self-monitoring data for nitrate-nitrite were available from Allen. In addition, almost 200 days 

of self-monitoring data for selenium were available from Belews Creek, and almost 70 available 

from Allen.

Of these data, EPA chose to use only 78 days of self-monitoring data for selenium from Belews 

Creek and 63 days of self-monitoring data from Allen. For arsenic, mercury and nitrate-nitrite, 

EPA relied exclusively on only 8 samples per facility. Four of those 8 samples were collected on 

successive days and an additional 1 sample per month was collected in each of 4 other months.

Comment Response: 

In response to comments, EPA supplemented the data used to calculate the final effluent 

limitations, including self-monitoring data for the plants identified by the comment. EPA based 

the limits for arsenic and mercury on treatment system effluent data for four plants, with 183 

observations for arsenic and 670 observations for mercury. These data represent approximately 

41⁄2 years of operation for these plants. The selenium and nitrate-nitrite limits are based on 

treatment system effluent data for two plants, with 398 observations for selenium and 70 

observations for nitrate-nitrite. These data represent approximately more than 5 years of data for 

one plant and more than 4 years of data for the other. See the Statistical Support Document for 

Effluent Limitations (DCN SE05733).

EPA’s experience has shown that daily pollutant concentrations in effluent discharges generally 

follow a lognormal distribution. That has been true in past effluent guidelines for other industry 

sectors, and that is also the case here for effluent data from steam electric power plants. As has 

been the case for effluent guidelines for other industry sectors, the effluent data for steam electric 

power plants includes a mixture of samples with quantifiable (i.e., measurable) concentrations 
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and samples having no quantifiable measure of the pollutant (i.e., non-detects). To properly 

handle mixtures of detected and non-detected data generated in such situations, EPA has adopted 

a modification of the delta-lognormal distribution to model pollutant effluent concentrations 

when developing effluent limitations. The modified delta-lognormal distribution is appropriate in 

that it models effluent data as a mixture of detected measurements that follow a lognormal 

distribution and non-detected measurements that occur with a certain probability. The modified 

delta lognormal model has been upheld on several occasions in court challenges and has support 

in peer reviewed literature. Using this well-tested statistical model, EPA is able to estimate key 

parameters that define the distribution of the data, including the long-term average, standard 

deviations, variability, and percentiles (e.g., 99th percentile). This model thus provides a 

reasonable basis with which to calculate values that are used to establish the effluent limitations. 

EPA’s statistical approach for establish effluent limitations has been upheld in court on 

numerous occasions. See Chem. Mfrs. Ass’n v. EPA, 870 F.2d 177, 230 (5th Cir. 1989); Nat’l 

Wildlife Fed’n v. EPA, 286 F.3d 554, 573 (D.C. Cir. 2002); Am. Coke & Coal Chems. Inst. v. 

EPA, 452 F.3d 930, 945 (D.C. Cir. 2006). Furthermore, it provides a statistical approach for 

doing so without the need to collect the large amounts of data that otherwise may be needed to 

empirically establish the effluent limitations. See Appendix A, Essay Sections 2 and 4.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 29

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Furthermore, EPA chose to censor what little data it retained. Remarkably, EPA removed 1 of 8 

samples for mercury from the Hatfield’s Ferry dataset, and removed 1 of the 78 samples for 

selenium from Belews Creek. The Hatfield’s Ferry censored data point was within the range of 

historical effluent concentrations. The operators of Belews Creek specifically addressed the 

censored selenium observation, refuting EPA’s conjecture that the recorded value may have been 

due to a system upset. Neither point should have been censored. By removing those data points, 

EPA eliminated the very information it was intending to characterize – i.e., the tails of the 

distributions.

EPA chose to ignore the most relevant facts (i.e., available self-monitoring data from model 

facilities), and instead to base their calculated ELGs primarily on assumption.

Comment Response: 

In response to comments, EPA supplemented the data used to calculate effluent limitations for 

the final rule, including self-monitoring data for the plants identified by the comment. See the 

response to DCN EPA-HQ-OW-2009-0819-5552-A2, Excerpt Number 2 (Comment Code 10.a). 
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EPA does not agree that the data referred to by the commenter for Hatfield’s Ferry and Belews 

Creek should have been used to calculate the effluent limitations. See the response to DCN EPAHQ-OW-2009-0819-46558, Excerpt Number 5 (Comment Code 31.c.i) and DCN EPA-HQ-OW2009-0819-4655-A18, Excerpt Number 19 (Comment Code 31.c.ii).

Also see the response to DCN EPA-HQ-OW-2009-0819-46558, Excerpt Number 28.
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31.c.i. Stats NL Select Data for FGD – Chemical Precipitation Treatment 

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 2

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

In addition to the data EPA collected and required facilities to collect, some facilities had 

historical self-monitoring data on pollutant concentrations in FGD effluent: “For this rulemaking, 

data for most of the plants came from multiple sources such as EPA sampling, CWA 308, or 

plant self-monitoring. For three plants (Allen, Belews Creek, and Hatfield’s Ferry), the multiple 

sources of the data were collected during overlapping time periods, thus, EPA combined these 

data into a single dataset for the plant. For two plants (Keystone and Miami Fort), the multiple 

sources of the data were collected during non-overlapping time periods. However, in these 

instances the time period between the non-overlapping data collection periods was relatively 

small (two months). Furthermore, EPA has no information to indicate that the data represent 

different operating conditions. Thus, EPA also combined the multiple sources of data for each of 

these plants into a single dataset for the plant. This approach is consistent with EPA’s traditional 

approach for other effluent guidelines rulemakings.” (page 13-6, EPA 2013)

Here, EPA acknowledged having self-monitoring data from the Hatfield’s Ferry facility, as well 

as from Allen and Belews Creek. In addition, self-monitoring data were available from the 

Miami Fort facility.

Comment Response: 

In response to comments, EPA supplemented the data used to calculate effluent limitations for 

the final rule, including self-monitoring data for the plants identified by the comment. EPA 

based the limits for arsenic and mercury on treatment system effluent data for four plants, with 

183 observations for arsenic and 670 observations for mercury. These data represent 

approximately 41⁄2 years of operation for these plants. The selenium and nitrate-nitrite limits are 

based on treatment system effluent data for two plants, with 398 observations for selenium and 

70 observations for nitrate-nitrite. These data represent approximately more than 5 years of data 

for one plant and more than 4 years of data for the other. See the Statistical Support Document 

for Effluent Limitations (DCN SE05733).

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 5
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External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA identified and excluded a high measured concentration (978 ng/l) of mercury at Hatfield’s 

Ferry, claiming the measurement was invalid:

“EPA excluded mercury data collected on 10/5/10 at the chemical precipitation effluent at 

Hatfield’s Ferry. This exclusion was due to an unusually high analytical result inconsistent with 

proper operation of the BAT/NSPS chemical precipitation treatment technology.” (page 20, EPA 

2012)

The effluent data collected at the model facilities are the only objective bases for characterizing 

the “proper operation of the BAT NSPS chemical precipitation treatment technology”. Absent 

additional independent data on the performance of the BAT chemical precipitation technology, 

EPA has no objective standard against which to compare the results from the CWA 308 

sampling. Therefore, absent additional supporting data, EPA would have no way to determine 

that the Hatfield’s Ferry measurement was “inconsistent” with proper operation.

Furthermore, the self-monitoring data from Hatfield’s Ferry, which EPA chose to exclude from 

its analyses, provides clear evidence that the 978 ng/l mercury reading is well within the 

historical range of measured values. The maximum recorded mercury concentration after 

chemical precipitation treatment at Hatfield’s Ferry was 3310 ng/l (see Table 2, below). Also, 

based on 121 historical measurements 978 ng/l would fall between the 97th and 98th percentiles 

of all measurements. Because EPA’s ELG method attempts to estimate the 99th percentile of 

daily measurements, the 10/5/10 mercury measurement at Hatfield’s Ferry is completely 

relevant.

Comment Response: 

EPA does not agree that EPA lacks sufficient information to determine the mercury observation 

for 10/5/2010 (978 ng/L) is inconsistent with proper operation of the treatment system at 

Hatfield’s Ferry. Based on the information in the record, EPA determined that the data should be 

excluded because it reflected sampling or analytical error, and thus did not reflect the 

BAT/NSPS level of control for mercury, for the reasons described below.

EPA excluded mercury data collected on 10/5/10 at the chemical precipitation effluent at 

Hatfield’s Ferry. This exclusion was due to an unusually high analytical result inconsistent with 

proper operation of the BAT/NSPS chemical precipitation treatment technology. Specifically, 

based on information in the record, the sampling result indicates that the sample may have been 

contaminated during sample collection or was adversely affected by treatment system upset. The 

decision to exclude the analytical result (978 ng/L) is supported by the plant’s NPDES 

compliance monitoring data for that time period. The maximum daily value reported for FGD 

wastewater treatment system effluent for the month of October 2010 was 127 ng/L. If the 

excluded value accurately represented the mercury concentration in the plant’s FGD treatment 
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system effluent, due to the hydraulic residence times and mixing that occurs in the FGD absorber 

and the wastewater treatment system, similarly high concentrations of mercury should have been 

reflected in the plant’s NPDES compliance monitoring samples. Furthermore, the maximum 

daily values reported by the plant for each monthly reporting period for August 2010 through 

February 2011 were also substantially lower than the excluded value, ranging from 108 ng/L to 

268 ng/L.

The excluded value may be the result of sample contamination occurring during sample 

collection. EPA used “clean sampling” techniques for its field sampling program, including 

requiring plant staff to also use such procedures when collecting the CWA 308 samples. These 

clean sampling procedures are intended to minimize the potential for contaminating samples, 

particularly in environments where dust and other contaminants are present. For all plants in the 

field sampling program, except Hatfield’s Ferry, the CWA 308 sampling was conducted after 

EPA had first conducted its on-site field sampling program. This approach enabled plant staff to 

become familiar with the specialized sampling collection protocols used for “clean sampling” 

prior to initiating their CWA 308 sampling. However, in the case of Hatfield’s Ferry, the plant 

initiated the CWA 308 sampling prior to the EPA field sampling and unfamiliarity with the clean 

sampling protocols may have allowed the October 2010 sample to become contaminated.

If the excluded result is not associated with sample contamination, then it indicates that the plant 

did not exercise good control of the treatment system during startup following a shutdown 

period. All three generating units had been shutdown for at least a week preceding the December 

2010 sampling event. Unit 3 then started up on October 3, generating electricity at approximately 

one-third capacity for the unit. Unit 3 then operated at nearly full load on October 4 and 

approximately two-thirds load on October 5, but then shutdown again on October 6. Based on 

the information in the record, the FGD wastewater treatment system likely was not operating in a 

stable manner during this period. In their comments on the proposed effluent guidelines, 

FirstEnergy (operator for Hatfield’s Ferry) did not dispute EPA’s determination that the 978 

ng/L observation should be excluded, nor EPA’s reasons for doing so.

With respect to the comment about other observations at Hatfield’s Ferry (e.g., 3310 ng/L), EPA 

identified other data from Hatfield’s Ferry that warranted exclusion and were not used to 

calculate the effluent limitations. See the Statistical Support Document for Effluent Limitations 

(DCN SE05733).
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31.c.ii. Stats NL Select Data for FGD – Chemical Precipitation followed by Biological 

Treatment

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 9

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The proposed limits for nitrate/nitrite are based on very limited data.

Comment Response: 

See the response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 54.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 54

External Review Flag: Engineering

External Review Incorporated into Response: No

Comment Excerpt: 

5.3 The biological treatment systems that EPA evaluated as BAT provide very 

limited data for setting a nitrate/nitrite limit.

The biological treatment systems that EPA evaluated as BAT (Belews Creek, Allen) have very 

limited data to support the nitrate/nitrite criterion. Therefore, it is very challenging to assess the 

long-term ability of these plants—as well as all facilities—to consistently achieve the 

nitrate/nitrite limit by anaerobic biological treatment. Normal changes in plant operations, such 

as coal switching and load swings, could result in a violation for a facility, as FGD water 

chemistry changes and because the limit is potentially challengingly to achieve.

Of the available data collected by EPA or by the plants during Clean Water Act (CWA) 308 

sampling (shown in Figure 5-8), two of the data points are above the monthly limit of 0.13 mg/L. 

Nitrate/nitrite data were not collected by facilities past the timeframe EPA designated as startup 

for each facility. During this startup timeframe, both Belews Creek and Allen facilities had 

measured data points that were higher than the proposed nitrate/nitrite limits. In addition, the 

detection limits for some samples collected at the Allen and Belews Creek facilities were 

sometimes higher than the nitrate/nitrite limit.
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A review of the self-monitoring data provided by the Belews Creek and Allen facilities [EPA, 

2009a,b] shows that there are no long-term data available to determine the ability of these 

facilities to achieve the nitrate/nitrite limits over time. EPA used “autocorrelation values” in 

developing limits where there was consistency in data over time for selenium. EPA 

acknowledges that not enough data are available to develop an autocorrelation value for 

nitrate/nitrite and instead “transferred the autocorrelation from selenium since these two 

chemicals behave similarly in the biological system.” [EPA, 2013, pages 13–14 and 13–15; 

Westat, 2013] This is a significant assumption, especially to promulgate new numeric standards. 

While both nitrate/nitrite and selenium are reduced in biological treatment systems, their 

chemistries are likely different. Nitrate/nitrite removal occurs first and often at a slightly negative 

oxidation-reduction (ORP) level. After nitrate/nitrite are removed, selenium reduction may then 

occur and generally at a more negative ORP level. EPA did not have enough data to develop 

variability factors and had to use arithmetic (rather than average) for the “plant-specific longterm average.” The nitrate limit is almost completely based on the data from one plant, Belews 

Creek, and a selenium autocorrelation value [EPA, 2013, pages 13–19.] Additional nitrate/nitrite 

data would greatly improve the robustness of EPA’s proposed numeric limits.

Biological treatment systems are designed for selenium removal and will result in incidental 

nitrogen reductions. There is significant uncertainty in the proposed numeric standards for 

nitrate/nitrite because of the limited data available, as well as the assumption that the 

nitrate/nitrite and selenium chemistries are similar and that the nitrate/nitrate will have the same 

auto-correlation as selenium.
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Comment Response: 

EPA does not agree that there is very limited data to support the proposed nitrate-nitrite limits, 

nor that there is insufficient long-term data to determine the effectiveness of nitrate removal. The 

effluent limitations for nitrate-nitrite, which have been revised since proposal in response to 

comments, are based on 70 observations collected over several years of operation. These data are 

more than adequate for establishing the effluent limitations and they provide long-term 

demonstration of the effectiveness of nitrate removal. See the Statistical Support Document for 

Effluent Limitations and Section 3 of the TDD.

The commenter mentions that the biological treatment systems were designed for selenium 

removal and suggests that the nitrogen reductions are merely incidental. EPA does not agree. 

Comments on the proposed rule acknowledge that “Thermodynamically, the nitrate/nitrite must 

be removed prior to initiation of selenium removal (selenate and selenite).” Therefore although 

the plants installing the biological systems did so to for the express purpose of removing 

selenium, the biological treatment systems are de facto designed to remove nitrate/nitrite because 

they would not meet their designed selenium effluent concentration without also removing 

nitrate/nitrite. As shown by the data used to calculate the effluent limitations, there is not 

significant uncertainty about whether plants will be able to meet the effluent limitations for 

nitrate-nitrite in the final rule.

EPA evaluated the effect that coal switching and load swings may have on treatment system 

performance and effluent quality, and determined that plants would be able to manage any 

effects such operational changes may have on wastewater characteristics such that they would be 

able to meet the final effluent limitations.

See the response to DCN EPA-HQ-OW-2009-0819-4655, Excerpt Number 107 and DCN 

SE05846 (memorandum Variability in Flue Gas Desulfurization Wastewater: Monitoring and 

Response).

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 235

External Review Flag: Engineering

External Review Incorporated into Response: No

Comment Excerpt: 

C. The Proposed Nitrate/Nitrite Limit is Not Appropriate

The biological treatment systems that EPA evaluated – Belews Creek and Allen Stations – were 

designed for selenium removal. Nitrate removal is a precursor reaction which occurs prior to 

selenium removal in biological systems. Thus, some nitrate removal will occur within the 
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bioreactor, but it is not understood how much will be removed and how that removal will be 

impacted by higher nitrate levels going into the bioreactors.

Also, there are very limited data to support EPA’s proposed nitrate-nitrite limits. As we have 

demonstrated, the nitrate/nitrite levels in FGD wastewater at Belews Creek and Allen are much 

lower than the levels in other FGD wastewaters. In addition, Belews Creek and Allen did not 

collect nitrate/nitrite data after the facilities completed the start-up modes of their treatment 

systems. Therefore, there are insufficient data from these two plants for EPA to develop national 

effluent limitations guidelines for nitrate/nitrite.

In addition, rainwater generally contains higher nitrate/nitrite level than the limits that EPA 

proposes. According to an online report,67 43 of 51 samples over 31 states in the United States 

contained nitrate, ranging from 0.13 mg/L to 8.16 mg/L nitrate-N.

Given that similar background concentrations of nitrate/nitrite are likely ubiquitous, it is going to 

prove very difficult to meet the proposed limits, based only on likely intake water concentrations.

63 ERG Memorandum to Steam Electric Rulemaking Record, Pollutants of Concern 

Methodology Memorandum, April 19, 2013, EPA-HQ-OW-2009-0819-2151.

64 The seven plants referred to are Belews Creek, Allen, Miami Fort, Pleasant Prairie, Hatfield’s 

Ferry, Keystone, and Dickerson.

65 Computer Sciences Corporation (CSC). 2013. Results of the ICP/MS Collision Cell Method 

Detection Limit Studies in the Synthetic Flue Gas Desulfurization Matrix. (16 January. EPAHQ-OW-2009-0819-2116.

66 ERG Memorandum to Steam Electric Rulemaking Record, Pollutants of Concern 

Methodology Memorandum, April 19, 2013, EPA-HQ-OW-2009-0819-2151.

67 Root, E., W. Jones, B. Schwarz, and J. Gibbons. November 22, 2004. Rainwater Chemistry 

Across the United States.

Comment Response: 

EPA does not agree. See the response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt 

Number 54. Also see the Statistical Support Document for Effluent Limitations (DCN SE05733).

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 4
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External Review Flag: Engineering

External Review Incorporated into Response: No

Comment Excerpt: 

EPA chose 8/26/2009 as the end of the commissioning period at Allen, and 7/31/2008 as the end 

of the commissioning period at Belews Creek for selenium treatment. However, the longitudinal

plots for selenium at Allen and Belews Creek in Appendix 2 of EPA 2012 are completely noninformative regarding changes in the pattern of selenium concentrations in bioreactor effluent.

Examination of the actual bioreactor effluent data for selenium show that the range of values 

from 7/13/2009 (the date operators of Allen identified as the end of the start-up period) to 

8/26/2009 fall within the range of values from 8/26/2009 until the end of the data series 

(5/23/2011). Similarly, the range of values from 6/11/2008 (the date operators of Belews 

identified as the end of the start-up period) to 7/31/2008 fall within the range of values from 

8/26/2009 until the end of the data series (5/25/2011).

Comment Response: 

In response to comment, EPA supplemented the dataset used to develop effluent limitations for 

the final rule to reflect the dates that Duke Energy’s treatment system operators identified as the 

end of the initial commissioning period for the FGD wastewater treatment system. Thus, the data 

used to calculate effluent limitations for the final rule include data that were obtained after the 

dates specified by the commenter (i.e., 7/13/2009 for Allen; 6/11/2008 for Belews Creek). The 

data used to calculate the effluent limitations also include additional data for Allen and Belews 

Creek that Duke Energy submitted following proposal. See the Statistical Support Document for 

Effluent Limitations (DCN SE05733) for information about the data that were used to calculate 

effluent limitations, as well as the data that were excluded.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 19

External Review Flag: Engineering

External Review Incorporated into Response: No

Comment Excerpt: 

EPA also identified and excluded a high measured concentration of selenium at Belews Creek:

“EPA also excluded questionable selenium data collected on 7/14/10 at the bioreactor effluent at 

Belews Creek. This exclusion was made since this observation (299 ug/L) is much higher than 

any other observed in the remainder of dataset.
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Since no plausible explanation validating the extreme observation could be determined, EPA 

excluded the bioreactor effluent selenium observation for July 14, 2010.” (page 21, EPA 2012)

EPA’s justification for excluding the 7/14/10 measurement, that “no plausible explanation 

validating the extreme observation could be determined” is simply false. In fact, Duke Energy, in 

a letter to EPA dated 2/27/2010, did provide an explanation documenting the validity of the 

selenium measurement at Belews Creek on July 14, 2010:

“EPA also excluded the selenium result of 299 ppb from July 14, 2010 as an extreme 

observation. But this July 14 result is valid. The increase in selenium on this day can be directly 

attributed to the increased selenate (Se VI) concentration, 2,360 ppb, in the FGD influent.

The increase in dissolved selenium and selenate (VI) species in the FGD influent and bioreactor 

influent during this period of time is more than likely due to a change in the FGD chemistry of 

the system and not an upset condition. Just as the mercury results in section II.A.2 above were 

affected by high oxidizing conditions, it is very likely that the increase in dissolved selenium and 

selenate (VI) is also due to high oxidizing conditions in the scrubber. This is particularly likely 

since both the mercury and selenium results show the same pattern of increases dissolved phases 

at about the same time.“ (Duke Energy, 2012)

Comment Response: 

EPA does not agree that the 7/14/2010 observation for selenium is acceptable for use in 

calculating the effluent limitations. The reported value of 299 ug/L selenium is much higher than 

any other observation in the remainder of dataset for Belews Creek. EPA evaluated the selenium 

contributions in the FGD purge and bioreactor influent (total and dissolved selenium, as well as 

concentrations of selenate and selenite), and the values for total selenium, selenite, and selenate 

in the bioreactor effluent (there are no dissolved selenium results for the bioreactor effluent on 

that date). In addition, EPA evaluated the concentrations for total selenium, dissolved selenium, 

selenite, and selenate at all three sampling locations for the months preceding and following the 

July 14 sampling event. EPA also evaluated electricity generation, absorber and wastewater pH 

data, bioreactor influent ORP, and bioreactor influent and effluent nitrate concentrations for 

7/14/2010 and the months preceding and following that date for indications of changes or 

abnormalities.

There were no significant changes in ORP to suggest the wastewater characteristics reflected the 

effects of high oxidizing conditions in the scrubber, so the commenter’s suggestion in that regard 

is unlikely. EPA noted that the bioreactor influent nitrate concentrations rose somewhat in the 

days preceding the observation; however, the increase was not large and the bioreactor effluent 

nitrate concentrations were non-detect at <2.3 mg/L, showing that the bioreactor was effectively 

denitrifying the wastewater.

The high effluent selenium observation also coincided with elevated selenate in the effluent (217 

ug/L). There were also substantial increases in total selenium and selenate in the bioreactor 

influent and the FGD purge, showing that the bioreactor did experience an increased pollutant 

load. However, even taking into account the concentration of selenate present in the FGD purge 
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and bioreactor influent samples, the bioreactor effluent is substantially higher than would be 

expected based on the demonstrated performance of the Belews Creek biological treatment 

system, as well as the performance observed for the biological treatment system at Allen. For 

example, the selenium in the bioreactor influent on 7/14/2010 was less than 3 times higher than 

the influent concentration for the previous observation on 6/23/2010; yet when the bioreactor 

influent selenium load increased by 10 times in May 2011 there was little effect on effluent 

concentrations (rising from <5 ug/L to 7/7 ug/L). Similar examples can be found at Belews 

Creek for selenate, where a large change in selenate (relative to the change observed for 

7/14/2010) was not accompanied by increased effluent selenium or selenate. See, e.g., data for 

October 2011 and December 2012.

These observations for Belews Creek are supported by the data for the biological treatment 

system at Allen. There were multiple occasions at Allen when the bioreactor influent selenium 

and selenate increased sharply, with the concentrations rising 10-15 times higher in a short 

period of time, yet with little if any observable effect on the bioreactor effluent concentrations. 

See, e.g., Allen data for August 2010, March 2011, December 2011, September 2012, and March 

2013. In addition, the influent selenium concentrations at Allen in September 2012 and March 

2013 were even higher than observed at Belews Creek on 7/14/2010.

The 299 ug/L observation is 10 times higher than any of the other 398 observations for the 

treatment systems at Belews Creek and Allen, which represent more than 5 years of operation at 

Belews Creek and more than 4 years of operation at Allen. Excluding the 7/14/2010 observation, 

there are 216 observations for selenium in the bioreactor effluent; the maximum value is 29.4 

ug/L and the median is 6.2 ug/L (i.e., half of all data are lower than 6.2 ug/L). There are 182 

observations for selenium in the bioreactor effluent at Allen; the maximum value is 27.6 ug/L 

and the median is 5.0 ug/L.

Based upon a thorough review of the bioreactor performance data for Allen and Belews Creek, 

EPA concluded that the 7/14/2010 observation should be excluded when calculating the effluent 

limitations for the final rule because the unusually high value is the result of a treatment system 

upset condition or other abnormal operation, such as would result from inadequate operator 

control of the biological process, and thus does not reflect the BAT level of control. This is 

consistent with information EPA obtained during a site visit to Allen Station on October 22, 

2009:

“Allen stated that the major improvement of the Allen biological treatment system over the 

Belews Creek system is the inclusion of oxidation-reduction potential (ORP) and pH probes on 

each individual cell (the Belews Creek system has one ORP probe for each stage). Additionally, 

the Allen system has sampling points on the effluent from the second stage (Belews Creek has 

sampling points on the effluent from the second stage recycle). These improvements have 

resulted in greater ease of operations for the biological treatment system at Allen.” DCN EPAHQ-OW-2009-0819-0598"

A properly operated treatment system includes close operator attention to influent wastewater 

characteristics, key process control parameters and effluent quality. See the response to DCN 

EPA-HQ-OW-2009-0819-4655, Excerpt Number 107 and DCN SE05846 (memorandum 
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Variability in Flue Gas Desulfurization Wastewater: Monitoring and Response). Also see Duke 

Energy’s March 2014 submittal of data for Allen and Belews Creek Stations.
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31.c.iii. Stats NL Select Data for FGD – Chemical Precipitation followed by VaporCompression Evaporation Treatment

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 62

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Furthermore, EPA’s sample data collection for distillate limit setting resulted in a small data set 

comprising only three samples of the Brindisi brine concentrator distillate (that is, evaporator 

distillate) and three samples of the crystallizer condensate. These data were collected from one 

plant (Brindisi) over a period of 3 consecutive days in 2011 [EPA, 2012]. To set appropriate 

limits for VCE distillate, additional data with wider plant and operational characteristics would 

be useful.

Comment Response: 

EPA does not agree that additional data are needed to establish effluent limitations for FGD 

wastewater based on vapor-compression evaporation treatment technology.

EPA has used all available valid data in developing the final effluent limitations and standards. 

Furthermore, in its proposed rule, EPA clearly identified the data that it had collected and used to 

calculate the proposed limitations, along with its data selection criteria. EPA solicited comment 

on the proposed rule, providing stakeholders with the opportunity to submit additional data if 

they chose to do so. In some cases, such as for the chemical precipitation and biological 

treatment technologies for FGD wastewater, commenters submitted large amounts of data 

representing years of treatment system operation. EPA evaluated the new effluent data and, as 

appropriate, included these data in establishing the effluent limitations for the final rule. 

However, in other cases, such as treatment of gasification wastewater using evaporation and 

treatment of FGD wastewater using vapor-compression evaporation technology, EPA received 

no additional data over the course of the 106-day public comment period. EPA also notes that a 

pre-publication version of the proposed rule was posted on EPA’s website in April 2013, five 

months before the September 20, 2013 end of the public comment period. As a result, industry 

and other stakeholder had ample opportunity to collect and provide additional data for the vapor 

compression evaporation treatment technology to EPA, but did not do so. Thus, in establishing 

the ELGs, EPA has used all available and relevant data that fit its data selection criteria. Had 

industry or other stakeholders come forward during the comment period and provided EPA with 

more data, EPA likely would have used it, provided it was valid and representative of the 

BAT/NSPS technology basis, as appropriate. See Appendix A, Essay Section 3.2.1.1.
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Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 67

External Review Flag: Engineering

External Review Incorporated into Response: No

Comment Excerpt: 

5. The effluent limits based on mechanical evaporation are reasonable.

EPA’s effluent standards for mechanical evaporation are based on data from the Enel’s Federico 

II plant in Brindisi, Italy.259 These limits are based on a rigorous and well-documented sampling 

analysis at that plant.260 The system at Brindisi produces two separate wastewater streams: a 

distillate from the brine concentrator and a condensate from the crystallizer. EPA based its 

effluent limits on the more concentrated of the two waste streams—the crystallizer condensate. 

Because most plants operating these systems will combine these waste streams prior to discharge 

or reuse in the plant, EPA’s decision to base the limits on the more concentrated waste 

stream provide an extra margin for compliance.261 Therefore, these limits should be readily 

achievable at plants operating a well-managed mechanical evaporation system.

259 TDD at 13-19.

260 See EPA-HQ-OW-2009-0819-1792.

261 TDD at 13-19 to 13-20.

Comment Response: 

EPA agrees that plants operating the vapor-compression evaporation technology basis are 

capable of meeting the final effluent limitations and standards. In addition, there are other 

technologies and process that are technologically available and are capable of meeting the final 

effluent limitations and standards. See the response to DCN EPA-HQ-OW-2009-0819-5552-A2, 

Excerpt Number 7.
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31.d. Stats NL – Selection of Data Within Facilities for Gasification Wastewater

Commenter Name: Cari Boyce

Commenter Affiliation: Duke Energy

Document Control Number: EPA-HQ-OW-2009-0819-4305-A3

Comment Excerpt Number: 94

External Review Flag: Engineering

External Review Incorporated into Response: No

Comment Excerpt: 

The very limited data set does not provide a comprehensive evaluation of the performance of 

wastewater treatment technologies for coal gasification (IGCC) systems and is inadequate to 

support the proposed effluent guidelines for this subcategory. The proposed guidelines are based 

on very sparse data on the performance of the only two IGCC systems (Wabash River Combined 

Cycle Plant (Wabash River) and Polk Power Station (Polk)) in operation within the U.S. at the 

time of the proposed rule’s development.46 The data set comprised only 4 samples from each of 

the two plants for each of the four pollutants being considered for limitation. Moreover, for each 

of the two plants, the 4 samples were taken from 4 days within a single calendar month.47 From 

this already limited data set, EPA discarded the arsenic and mercury data from the Wabash River 

facility48 for use in the statistical analysis and limitation development. 49 As a result, the effluent 

sample results for arsenic and mercury are limited to a single calendar month (and actually a 

single 4-consecutive-day period) from a single plant.

46 TDD Section 4.2.3, page 4-10 [EPA-921-R-13-002]. Duke Energy’s Edwardsport facility, 

which went operational in June 2013, was not in service when data for the proposed rule was 

collected and therefore, data from this unit was not available for EPA’s evaluation in developing 

the proposed rule.

47 See, “Sampling Data Used as the Basis for Effluent Limitations for the Steam Electric 

Rulemaking,” (10/31/2012) [DCN SE02002] (referred to in these comments as “Sampling 

Data”).

48 TDD, at Section 13.8.1, page 13-21

49 The data was discarded as failing EPA’s data editing criteria since more than 50% of the 

influent concentrations for arsenic and mercury were either below detection limits or were less 

than 10 times EPA’s baseline value. TDD, at Section 13.4, page 13-“Memorandum to Ronald 

Jordan: Effluent Limitations for FGD Wastewater, Gasification Wastewater, and Combustion 

Residue Leachate for the Proposed Effluent Limitation Guidelines and Standards for the Steam 

Electric Rulemaking,” (Jordan Memorandum”) (10/20/2012) [DCN SE01999], page 54.

Comment Response: 
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EPA does not agree that the effluent data for gasification wastewater are inadequate for 

establishing effluent limitations, and EPA also does not agree that the data in the record 

(including both influent and effluent data) are insufficient for evaluating the performance of the 

vapor-compression evaporation technology for treating gasification wastewater.

EPA has used all available valid data in calculating the effluent limitations established by the 

ELGs. Furthermore, in its proposed rule, EPA clearly identified the data that it had collected and 

used to calculate the proposed limitations. EPA solicited comment on the proposed rule, 

providing stakeholders with the opportunity to submit additional data if they chose to do so. In 

some cases, such as for the chemical precipitation and biological treatment technologies for FGD 

wastewater, commenters submitted large amounts of data representing years of treatment system 

operation. EPA evaluated the new effluent data and, as appropriate, included these data in 

establishing the effluent limitations for the final rule. However, in other cases, such as here for 

gasification wastewater and for the vapor-compression evaporation technology for FGD 

wastewater, EPA received no additional data. EPA notes that the commenter operates an IGCC 

plant that began commercial operation in June 2013, months before the end of the 106-day 

comment period for the proposed rule ended on September 20, 2013. Thus at the same time that 

the commenter was asserting in comments that EPA should use more data, and was in a position 

to provide such data to EPA for its own plant, it failed to do so. The commenter claims that data

for their Edwardsport IGCC facility “was not available for EPA’s evaluation in developing the 

proposed rule,” but that in no way justifies a failure on the part of the commenter to provide such 

data during the comment period for the proposed rule, at the very same time that they were 

asserting that EPA’s data were inadequate. Thus, in establishing the ELGs, EPA has used all of 

the data it could accumulate. Had industry or other stakeholders come forward during the 

comment period and provided EPA with more data, EPA likely would have used it if the data 

were valid and representative of the BAT technology, as appropriate. See Appendix A, Essay 

Section 3.2.1.1.

As explained in the TDD at proposal, EPA excluded certain data from Wabash River for 

calculating the arsenic and mercury limits because they failed to pass the criteria for the LTA 

test. See TDD Section 13 and the Statistical Support Document for Effluent Limitations (DCN 

05733).

Commenter Name: Cari Boyce

Commenter Affiliation: Duke Energy

Document Control Number: EPA-HQ-OW-2009-0819-4305-A3

Comment Excerpt Number: 95

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The Data Set Is Inadequate to Support the Effluent Limit Development Process
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Duke believes the data set for the gasification sector should be considered insufficient to support 

effluent limitation development. This is especially true given that the development of a long-term 

average to characterize the baseline performance of a model technology is the critical foundation 

of the limitation development process, as described by EPA in the above section. There are only 

eight daily samples confined to two calendar months for selenium and Total Dissolved Solids 

(TDS) and merely four daily samples arising from a single month and a single IGCC plant for 

arsenic and mercury. Although it is recognized that “long-term” is not a defined term, it seems 

intuitive that a single calendar month comprising only 4 daily samples cannot be considered 

“long-term.” While a long-term average is intended to level out the operational variability of 

facility processes and treatment system, it is equally true that the LTA will reflect the process 

variability indirectly. To be meaningful, “long-term” will need to encompass a sufficiently long 

period to reflect variations in coal,54 other process ingredients, process equipment wear, 

calibrations, operational settings and climatic conditions. Samples taken from a very limited time 

frame (all Wabash River samples were taken from within a 9-day period in October 2011 and all 

Polk samples were taken from a 4-consecutive-day period in February 2011) will be expected to 

be relatively uniform as it is much more likely to reflect the same fuel, similar process and 

treatment facility conditions. This estimate cannot be considered as a reliable or definitive 

characterization of long-term average performance. Lacking a meaningful LTA, which is a 

critical component of the limitation development process, the limitations proposed for 

gasification wastewater are clearly flawed.

The same deficiency applies to the development of variability factors for daily and monthly 

performance. A 4-sample or 8-sample data set from such a brief period cannot be considered a 

representative view of variability. This deficiency is particularly apparent when monthly average 

limits are considered. For arsenic and mercury, the data set covers only a single calendar month 

(actually less than a single week). Since no distribution of monthly averages exists, a 95% 

variability factor could not be calculated. Absolutely no information on variability of monthly 

averages can be inferred from this data. Even for selenium and TDS, there are only two monthly 

averages available (and only a single monthly average from each plant). This methodology 

cannot be considered an adequate basis for setting limits that would be in effect for many years 

or even decades of operation (given the associated variability in effluent quality that may be 

anticipated over such periods).

Consequently, Duke believes it is statistically and technically inappropriate to use this data set in 

determining a continuous compliance limit. In a hypothetical scenario, if a permittee were to 

apply for an NPDES permit modification in order to change a discharge limitation, and that 

permit modification was supported by only four data points gathered over only four days’ time, 

then the permitting agency would be very likely to deny that request on the basis that the limited 

data set does not appropriately characterize the wastestream. Duke Energy believes that EPA 

needs more data to appropriately characterize IGCC gasification wastewater.

Data Set Too Sparse to Develop Autocorrelation Factor

Within the Technical Development Document, EPA acknowledges that it “was unable to 

perform an evaluation and obtain a reliable estimate of the autocorrelation factor because there 

were too few observations available at the plants. Thus, for these plants, EPA set the 
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autocorrelation to zero in the calculation of the limits. EPA did so because there were not 

sufficient data to reliably evaluate the autocorrelation, nor did EPA have a valid correlation 

estimate available that could be transferred from a similar technology and wastestream.”55

The autocorrelation is important since “the autocorrelated data affect the true variability of 

treatment performance, [and] EPA typically adjusts the variance estimates for the autocorrelated 

data.”56 For the gasification subcategory there was no adjustment to the EPA calculated limits to 

account for possible variation. 57

In summary, Duke Energy believes that it is inappropriate to set national effluent limitations and 

standards using only two brief sampling periods from two facilities for selenium and TDS. Duke 

Energy strongly objects and thinks it is highly inappropriate to set limits for arsenic and mercury 

since the data only comes from one facility over a period of a few days. A meaningful LTA 

cannot be developed from this sparse data set and similarly no meaningful performance 

variability information can be inferred.

54 Trace contaminant levels can vary substantially with the type and origin of the coal being 

used and these variations can affect process wastewater quality. Variations can and do occur 

even when the coal comes from a single mine over extended periods.

55 TDD, at Section 13.6.3, page 13-15

56 Id. at Section 13.6.3, page 13-14

57 Final Detailed Study Report Chapter 3 – Steam Electric Industry Profile p. 3-17

Comment Response: 

EPA does not agree that the effluent data for gasification wastewater are inadequate for 

establishing effluent limitations, and EPA also does not agree that the data in the record 

(including both influent and effluent data) are insufficient for evaluating the performance of the 

vapor-compression evaporation technology for treating gasification wastewater. See the response 

to DCN EPA-HQ-OW-2009-0819-4305-A3, Excerpt Number 94.

The commenter misconstrues the meaning of the term “long-term average,” as it applies to the 

statistical calculation of the effluent limitations. As stated in the Statistical Support Document for 

Effluent Limitations (DCN 05733), the “long-term average (LTA) is the mean of the underlying 

statistical distribution of the daily effluent values.” Thus, while the LTA represents the average 

concentration that is achieved over a period of time, it is based on the statistical distribution of 

the data. Given the known or assumed distribution that is applicable for the effluent data, the 

methodology presented in TDD Section 13 can be used to estimate the long-term average. In the 

case where all observations are non-detected, the LTA is the arithmetic mean of the reported 

values.
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As the commenter states, in cases where there are not sufficient data to determine that the 

effluent data are autocorrelated and to calculate that value, EPA assumed the data are not 

autocorrelated. This is a reasonable assumption in the absence of data showing that 

autocorrelation is present. The commenter did not provide any data showing that the data are 

autocorrelated, nor for use in calculating autocorrelation.

Commenter Name: Quinlan J. Shea III

Commenter Affiliation: Edison Electric Institute (EEI)

Document Control Number: EPA-HQ-OW-2009-0819-4487-A1

Comment Excerpt Number: 71

External Review Flag: Engineering

External Review Incorporated into Response: No

Comment Excerpt: 

The proposed gasification wastewater limits on arsenic, mercury, selenium, and TDS are based 

on data from two facilities for arsenic and mercury and one facility for selenium and TDS – eight 

data points total, four samples from each of the two facilities (Polk and Wabash River). As EPA 

says, there are “little characterization data” (TDD at 1-8). EPA had too few data to analyze for 

autocorrelation, and so it simply assumed there was no autocorrelation (id. 13-15).

Apparently EPA based the limits on condensate from a vapor compression evaporator, probably 

the cleanest wastestream that could be found among several internal to the Wabash River station. 

For the Polk Power Station, EPA assumed that the evaporation (or at least the forced circulation 

evaporation stage) was acting abnormally (id. at 13-20).

There are six locations at Wabash River from which wastewater could be discharged and two 

effluent streams at Polk. Although Wabash River reuses most of the waters in the process, there 

are times when the wastewaters need to be discharged from the facility.

Comment Response: 

See the response to DCN EPA-HQ-OW-2009-0819-4305-A3, Excerpt Number 94 and EPA-HQOW-2009-0819-4305-A3, Excerpt Number 95.

Regarding the EPA’s conclusion that the forced circulation evaporation stage of the treatment 

system at Polk was not operating properly, see the response to DCN EPA-HQ-OW-2009-0819-

4534-A2, Excerpt Number 4.

The commenter states that there are six locations at Wabash River from which wastewater could 

be discharged; however, the commenter neglect to also note that only one of these wastewater 

streams is gasification wastewater. The final rule defines gasification wastewater as follows:
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“The term gasification wastewater means any wastewater generated at an integrated gasification 

combined cycle operation from the gasifier or the syngas cleaning, combustion, and cooling 

processes. Gasification wastewater includes, but is not limited to the following: sour/grey water; 

CO2/steam stripper wastewater; sulfur recovery unit blowdown, and wastewater resulting from 

slag handling or fly ash handling, particulate removal, halogen removal, or trace organic 

removal. Air separation unit blowdown, noncontact cooling water, and runoff from fuel and/or 

byproduct piles are not considered gasification wastewater. Wastewater that is collected 

intermittently in floor drains in the gasification process area from leaks, spills, and cleaning 

occurring during normal operation of the gasification operation is not considered gasification 

wastewater.”

In response to the comment, EPA contacted WVPA and obtained additional information to better 

understand the nature of the various wastewater streams mentioned by the comment (see DCN 

SE04337 and SE04337A1). The diagram provided by the WVPA (DCN SE04337A1) identifies 

the following wastestreams: RCC distillate; S-260 (sump pump); Cooling tower blowdown; ASU 

blowdown; Slag pile runoff; Petcoke pile runoff & Adjacent roadway; and Stormwater 

runoff. Only the first wastestream, RCC distillate, is wastewater from the gasification process 

and included within the ELG definition. The other wastestreams (other than stormwater runoff 

which also is not gasification wastewater) are actually specifically identified within the definition 

as not being gasification wastewater. 

Commenter Name: S. Dear Schramm-Satayathum

Commenter Affiliation: Wabash Valley Power Association, Inc. (WVPA)

Document Control Number: EPA-HQ-OW-2009-0819-4534-A2

Comment Excerpt Number: 2

External Review Flag: Engineering

External Review Incorporated into Response: No

Comment Excerpt: 

Additional Data is Needed

The basis for the proposed effluent limitations on gasification wastewater is inadequate and 

additional data is needed. USEPA proposes to limit gasification wastewater from all new and 

existing sources based on sample results collected from one facility for arsenic and mercury 

limits and two facilities for selenium and total dissolved solids limits.

To be more specific, the proposed limit for arsenic and mercury are based on four data points 

from a single existing facility (Tampa Electric’s Polk Power Station); selenium and total 

dissolved solids are based on eight data points – four sample results from each of the two 

sampled facilities. We understand that USEPA requested data from all gasification facilities with 

an NPDES permit in the United States that were in existence in 2010 – which happens to be two 

facilities (Polk Power Station and Wabash River Combined Cycle Plant). At the time of 
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USEPA’s 2010 wastewater sampling program letter, several gasification plants were in the 

process of being permitted or already commenced construction.

Proposing limits based on so few data points on all existing and future gasification wastewaters 

is premature, especially for arsenic and mercury. USEPA acknowledges in the Technical 

Development Document accompanying this proposed rulemaking that gasification wastewater 

has been identified by USEPA as one of several wastestreams for which there is ‘little 

characterization data.’1 USEPA also states ‘...for the vapor- compression evaporation treatment 

technology option for gasification wastewater (represented by Polk and Wabash River), EPA 

was unable to perform an evaluation and obtain a reliable estimate of the autocorrelation because 

there were too few observations available at the plants. Thus, for these plants, EPA set the 

autocorrelation to zero in the calculation of the limits. EPA did so because there were not 

sufficient data to reliably evaluate the autocorrelation, nor did EPA have a valid correlation 

estimate available that could be transferred from a similar technology and wastestream.’

2

1 Section 1.3.2, Page 1‐8. EPA. 2013. Technical Development Document for the Proposed 

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

Source Category, EPA‐821‐R‐13‐002, EPA‐HQ‐ OW‐2009‐0819‐2257. April 2013.

2

Id at Section 13.6.3, Page 13-15.

Comment Response: 

See the response to DCN EPA-HQ-OW-2009-0819-4305-A3, Excerpt Number 94 and EPA-HQOW-2009-0819-4305-A3, Excerpt Number 95.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 170

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

C. The Record Does Not Have Adequate Data for IGCC Wastestreams

The proposed limits on arsenic, mercury, selenium, and TDS are based on data from two 

facilities for arsenic and mercury and one facility for selenium and TDS – eight data points total, 

four samples from each of the two facilities (Polk and Wabash River). At both plants the four 

samples were taken in a single calendar month. And since EPA discarded arsenic and mercury 

data from Wabash River, the arsenic and mercury data are from four consecutive days at a single 
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plant. As EPA says, there is “little characterization data” (2013 TDD at 1-8). EPA had too few 

data to analyze for autocorrelation, and so it simply assumed there was none (id. 13-15). In 

particular, four daily samples from a single plant in a single month cannot characterize a “longterm average” for the industry.

Comment Response: 

See the response to DCN EPA-HQ-OW-2009-0819-4305-A3, Excerpt Number 94 and EPA-HQOW-2009-0819-4305-A3, Excerpt Number 95.
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31.e. Stats NL – Baseline Substitutions

Commenter Name: Steve Jackson

Commenter Affiliation: Alliant Energy Corporate Services, Inc.

Document Control Number: EPA-HQ-OW-2009-0819-4516-A2

Comment Excerpt Number: 7

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Data substitution methods used to evaluate impacts and benefits are flawed

Comment Response:

See the response to DCN EPA-HQ-OW-2009-0819-4516-A2, Excerpt Number 17.

Commenter Name: Steve Jackson

Commenter Affiliation: Alliant Energy Corporate Services, Inc.

Document Control Number: EPA-HQ-OW-2009-0819-4516-A2

Comment Excerpt Number: 17

External Review Flag: Engineering

External Review Incorporated into Response: No

Comment Excerpt: 

Data substitution methods used to evaluate impacts and benefits are flawed.

EPA states that data substitution methods were utilized when developing the proposed ELG 

limits. At section 13.2.2 of the TDD, EPA describes how it utilized a baseline value for certain 

pollutants in place of a detected value or sample-specific detection limit "to account for the 

possibility that certain detected results may be at a lower concentration than can be reliably 

achieved by well-operated laboratories". This methodology is flawed for three reasons. First, 

what does this methodology say about the validity of compliance data? To illustrate, one of our 

facilities recently received its new NPDES permit with an arsenic limit of 0.2 microgram per liter 

(ug/l). If data representing compliance with such a low limit were included in the ELG data set, 

EPA would .have substituted the data- but the facility is nevertheless expected to defend the 

laboratory 's results and demonstrate compliance. Secondly, this methodology overestimates the 

amount of pollutant in a facility's discharge, thereby misrepresenting the rule impact and 

possibly resulting in the development of flawed limits. Finally, what does this methodology say 

about the capability of laboratories? Is the data generated by a certified, accredited laboratory 

invalid? Should a facility be using this data to demonstrate compliance? Alliant Energy requests 

that EPA re-evaluate this methodology, considering instead the cost and regulatory attributes of 

using actual available data compared to data substitution .
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Comment Response: 

EPA disagrees that its limitations methodology that considers the use of baseline substitution is 

flawed. In response to comments such as these, EPA reevaluated the baseline substitution 

approach and made adjustments for the final rule. For the final rule, EPA has used a reasonable 

approach that considers the effect of using baseline substitution, in essence calculating what the 

limitations would be with and without the substitution. The approach that produces the higher 

value was selected as the effluent limitation. See Appendix A, Essay Section 3.5 for the effluent 

limitations.

The commenter has confused limitations development and compliance requirements. The 

limitations methodology is a statistical approach to establishing limitations which are 

incorporated into facility permits. The permit regulations in 40 CFR part 122, not today’s 

limitations methodology, establish the requirements that are applicable for monitoring 

compliance with effluent limits included in NPDES permits.

The commenter has also confused limitations development with EPA’s pollutant removal 

estimates for the rule and the environmental assessment of the baseline impacts of the pollutant 

discharges to the environment and how those impacts would be mitigated by the ELGs 

established by this rule. EPA does not use the effluent limitations values in the environmental 

assessments. For details on how EPA included non-detect values in developing effluent 

limitations, see TDD Section 13 and DCN SE05733. For details on how EPA included nondetect values for estimating pollutant reductions and related analyses, see TDD Section 10 and 

the Costs & Loads Report.

Commenter Name: Kim Mireles

Commenter Affiliation: Luminant

Document Control Number: EPA-HQ-OW-2009-0819-4614-A1

Comment Excerpt Number: 16

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA's proposed steam electric limits for FGD wastewater are too low because EPA 

substituted "baseline" values and did not use the correct statistical method for the 

sampling design used.

When a reported concentration or a detection limit was below an EPA "baseline" value, EPA 

used the baseline number instead. EPA should provide explanation of their use of the term 

"baseline." It appears that the term is used to devise a value for data substitution, but EPA 

provides no explanation or justification for this data technique.

Comment Response: 
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EPA disagrees with the comment that EPA has not explained the baseline value. TDD Section 13 

and DCN SE05733 define EPA’s use of the term “baseline value,” explains how those values 

were derived, and explain the methodology used to substitute baseline values in the data 

processing and limitations calculations. (This information was similarly provided in the 

documentation for the proposed rule – see the TDD Section for the proposed ELGs and DCN 

SE01999 and DCN SE02000.) See DCN SE05733 and the response to DCN EPA-HQ-OW2009-0819-4379-A1, Excerpt Number 172.

EPA disagrees with the comment’s assertion that EPA “did not use the correct statistical method 

for the sampling design used.” EPA used all of the available data that demonstrated the 

performance of the model technology (including its proper operating and designed conditions). 

The data used for EPA’s limitations calculations were not selected or collected by a statistical 

sampling design. See Essay Section 4.2.3.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 6

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

For Arsenic, the baseline substitutions caused a reduction in the mean and the standard deviation 

of the data from Miami Fort. For Selenium, the baseline substitutions caused reductions in the 

standard deviations of the data from Allen and Belews Creek.

Comment Response: 

In response to comments on the proposed rule, EPA has calculated the limitations using two 

approaches to baseline substitutions as described in Appendix A, Essay Section 3.5. Because the 

data entering into the calculations differ, it is expected that different assumptions for nondetected values would affect the means and standard deviations. For the final rule, EPA selected 

the higher value from the two approaches for the effluent limitations. See the response to DCN 

EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number: 172
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31.f. Stats NL – Data Aggregation

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 68

External Review Flag: Engineering

External Review Incorporated into Response: No

Comment Excerpt: 

6.9 Averaging duplicates also reduces variability compared to what is actually 

measured.

On page 10-5, the TDD [EPA, 2013] states

“... where duplicate sample results were obtained, the duplicates were averaged to represent that 

time of sampling.”

Alternative recommendation: When estimating standard deviation, randomly choose one of the 

two duplicate results. If a non-detect is the result selected, the standard deviation of the entire set 

can be computed by using a censored-data method such as Kaplan-Meier, rather than by using 

substitution.

Comment Response: 

TDD section 13 describes the statistical derivation of standard deviations used in calculating the 

limitations.

EPA disagrees with the comment’s alternative recommendation to randomly choose one of the 

two duplicate results in calculating limitations. As explained in Appendix A, Essay Section 3.3, 

the approach suggested by the commenter would not be consistent with NPDES regulations and 

would introduce potential sources of variation that are not generally appropriate for inclusion in 

effluent limitations. EPA’s approach in averaging duplicates is consistent with reporting of 

compliance data required by NPDES permits.

EPA disagrees that censored methods, including the Kaplan-Meier approach, are more 

appropriate than the modified delta-lognormal distribution for the limitations data. See Essay 

Section 4.2.2 for EPA’s consideration of censored methods.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 128
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External Review Flag: Engineering

External Review Incorporated into Response: No

Comment Excerpt: 

8. Some remaining observations on procedures in the TDD.

a) On page 10-10 of the TDD, EPA computes an average effluent concentration by averaging the 

4 values of EPA’s 4-day sampling event, and then using the average to represent that month,

averaging it with 4 individual CWA monthly samples. This method is acceptable only to 

estimate the overall average. Averaging the 4-day event to obtain a single number incorrectly 

decreases the variability as compared to a single monthly sample. The TDD’s method will tend 

to underestimate the standard deviation, a percentile, and the variability factor.

Alternative Recommendation: one of the four samples in the 4-day set should be randomly 

selected instead to represent that month. In this way equivalent data are used for each month, 

preserving the characteristic of standard deviation. This more accurately describes the variability 

used to compute effluent limitations.

Comment Response: 

The comment has confused EPA’s limitations development (TDD Section 13) with EPA’s 

procedure for estimating pollutant loadings and removals (TDD Section 10). The arithmetic 

means described in TDD Section 10 were used solely to simplify the calculation of estimated 

effluent pollutant loadings and pollutant removals, while still providing a reasonable estimate of 

these values. That approach was not used when calculating the effluent limitations. See TDD 

Section 13 and TDD Appendix B for the statistical procedures EPA used to derive the monthly 

average limitation. EPA disagrees that it would be appropriate to randomly select one value from 

each month in developing monthly averages. See Appendix A, Essay Section 3.3 on use of 

averaged duplicates. Additionally, in developing effluent limitations, EPA uses as much data as 

are available that meet the data acceptance criteria, including that the data are valid results and 

reflect performance of the BAT technology. See Essay Section 3.2.1.1.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 129

External Review Flag: Engineering

External Review Incorporated into Response: No

Comment Excerpt: 
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c) On page 10-5 the TDD states that where duplicate sample results were obtained, the duplicates 

were averaged to represent that time of sampling. Averaging again reduces variability from what 

is actually measured.

Alternative Recommendation: when estimating standard deviation, randomly choose one of the 

two duplicate results. If a nondetect is the one selected, the standard deviation of the entire set 

can be computed using a censored data method such as Kaplan-Meier rather than using 

substitution.

Comment Response: 

See the response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number #68 and DCN 

EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 128.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 135

External Review Flag: Engineering

External Review Incorporated into Response: No

Comment Excerpt: 

6.7 Averaging a 4-day event to obtain a single number incorrectly decreases 

variability, as compared to using a single monthly sample.

EPA computes an average effluent concentration by averaging the four values from EPA’s 4-day 

sampling event to represent that month, and then averaging it with four individual Clean Water 

Act monthly samples [EPA, 2013, page 10-10]. EPA’s procedure will tend to underestimate the 

standard deviation, the percentile, and the variability factor.

Alternative recommendation: Instead, one of the four samples in the 4-day set could be 

randomly selected to represent that month. In this way, equivalent data are used for each month, 

preserving the characteristic of standard deviation. This choice more accurately describes the 

variability used to compute effluent limitations.

Comment Response: 

The comment is incorrect in stating that EPA has averaged data to obtain single monthly values 

to use in developing the limitations. See TDD Section 13 Appendix B for EPA’s methodology in 

developing monthly average limitations. See the response to DCN EPA-HQ-OW-2009-0819-

4499-A1, Excerpt Number 68 and DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 

128.
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31.h. Stats NL – Statistical Method used to Calculate the Limits

Commenter Name: Cari Boyce

Commenter Affiliation: Duke Energy

Document Control Number: EPA-HQ-OW-2009-0819-4305-A3

Comment Excerpt Number: 97

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Detection Limit Issues for the Proposed Limits for Arsenic and Mercury

In addition to the deficiencies discussed in the preceding section, other problems adding to the 

inappropriateness of the proposed effluent limitations for arsenic and mercury for gasification 

wastewater are presented here. In Section X.E of the preamble to the Proposed Rule, EPA states 

“Due to routine variability in treated effluent, a power plant that discharges consistently at a level 

near the values of the daily maximum limitation or the monthly average limitation may 

experience frequent values exceeding the limitations. For this reason, EPA recommends that 

power plants design and operate the treatment system to achieve the option long-term average for 

the model technology. Thus, a system that is designed to represent the BAT level of control will 

be capable of complying with the limitations.”59 With this prelude, Duke Energy states the 

following additional concerns with the proposed limitations for arsenic and mercury for 

gasification wastewater.

Arsenic

The arsenic daily limitation in the proposed rule is 4 ug/L, which is the detection limit for arsenic 

as well.60 The option LTA from Table X.1 of the preamble to the proposed rule is also 4.0 ug/L. 

The limit for arsenic was set at the detection limit for arsenic, based on only the limited data set 

of 4 daily samples gathered from Polk Power Station, each of which showed arsenic to be nondetectible in the effluent. An effluent limit set at a detection limit is objectionable under the 

limited data set available here. The problem presented by such circumstances is that there is no 

information on variability of the effluent concentration. EPA concedes as much in Table 13-7 of

the TDD, where footnote “c” states, with respect to the arsenic data, that “variability factors 

could not be calculated” since “[a]ll observations were non-detected.” A facility confronted with 

such a limit would have no assurance that its discharge could consistently meet an effluent limit 

equal to the detection limit when only 4 samples have been taken, even if they all have been nondetectible. Considerably more data showing only non-detected results would be needed before a 

discharger could have some confidence that the range of variability is confined beneath the 

detection limit.

Ironically, this situation opens the very real possibility EPA warned of concerning frequent 

exceedances due to routine treated effluent variability. The Polk Station’s non- detect arsenic 

discharges could be running close to the detection limit but Polk will have no way of knowing 

that – at least not until sufficient time passes for routine variability to express itself with an 
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exceedance. Duke Energy believes that, due to routine variability in discharge, a technologybased effluent limitation set at a detection limit will not be consistently attainable. Consequently, 

Duke Energy respectfully urges that the proposed arsenic limit at the detection limit should be 

deleted.

Mercury

The mercury daily maximum and monthly average limitations from the proposed rule are 1.76 

ng/L and 1.29 ng/L, respectively. Duke Energy questions whether EPA sampling and analytical 

method 1631E or other available analytical methods are sufficiently sensitive to consistently 

measure mercury to this low level. The proposed option LTA in Table X-1

61 is 1.075 ng/L. EPA 

itself recommended that power plants design and operate treatment systems to meet the option 

LTA. Duke Energy doubts that analytical methods are sensitive enough to consistently 

differentiate between the option LTA of 1.075 ng/L and the proposed daily maximum and 

monthly average limitations of 1.76 ng/l and 1.29 ng/L. Even if a state-of–the-art vaporcompression evaporation treatment system is built to meet the option LTA, Duke Energy has 

serious reservations that sufficiently sensitive analytical methods will consistently measure and 

report accurately to within 0.685 ng/L (i.e., 1.76 ng/L daily limitation minus 1.075 ng/L option 

LTA = 0.685 ng/L). Duke Energy believes this limit should be deleted.

59 78 Fed. Reg. at 34490, in Section X.E, EPA described its methodology for accounting for 

operational variability in treated effluent values in the setting of daily maximum and monthly 

average effluent limitations.

60 See Table X.1, Section X.E of the preamble to the proposed rule. See also TDD, Table 13-7, 

Section 13.8.2, and the Jordan Memorandum, Section 5.6 and Tables 34 and 47.

61 78 Fed. Reg. at 34490

Comment Response: 

EPA disagrees with the comment’s assertion that the arsenic daily maximum limitation does not 

allow for sufficient variability, nor does EPA agree that an effluent limitation set equal to a 

detection limit may not be consistently attainable. (Here, the term “detection limit” is referring to 

the quantitation limit). Such an approach has been used in previous ELG rulemaking; see, e.g., 

the ELGs for the Pulp, Paper, and Paperboard Point Source Category. As explained in Appendix 

A, Essay 3.1, the data EPA used to establish effluent limitations reflect many sources of 

variability, including variability associated with sampling and laboratory analysis. This holds 

true for the non-detect data used to establish the effluent limitations for arsenic in gasification 

wastewater and for FGD wastewater based on evaporation technology. See Essay Section 

2.5. Also see the response to DCN EPA-HQ-OW-2009-0819-4534-A2, Excerpt Number 7.

EPA disagrees with the commenter’s assertion that more effluent data for arsenic are needed. 

EPA has used all available valid data in calculating the effluent limitations established by the 
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ELGs. Furthermore, in its proposed rule, EPA clearly identified the data that it had collected and 

used to calculate the proposed limitations. EPA solicited comment on the proposed rule, 

providing stakeholders with the opportunity to submit additional data if they chose to do so. In 

some cases, such as for the chemical precipitation and biological treatment technologies for FGD 

wastewater, commenters submitted large amounts of data representing years of treatment system 

operation. EPA evaluated all of these new effluent data and, as appropriate, included these data 

in establishing the effluent limitations for the final rule. However, in other cases, such as for 

gasification wastewater and for the vapor-compression evaporation technology for FGD 

wastewater, EPA received no additional data. EPA notes that the commenter operates an IGCC 

plant that began commercial operation in June 2013, months before the end of the comment 

period for the proposed rule. Thus at the same time that the commenter was asserting in 

comments that EPA should use more data, and was in a position to provide such data to EPA for 

its own plant, it failed to do so. Thus, in establishing the ELGs, EPA has used all of the data it 

could accumulate. Had industry or other stakeholders come forward during the comment period 

and provided EPA with more data, EPA likely would have used it if the data were valid and 

representative of the BAT technology, as appropriate. See Appendix A, Essay Section 4.1.2.

EPA disagrees with the commenter’s assertion that available analytical methods may not be able 

to consistently measure low enough for plants to demonstrate compliance with the mercury 

limitation. EPA Method 1631E can measure mercury at very low concentrations with a 

quantitation limit of 0.5 nanogram/liter (ng/L), orders of magnitude lower than the effluent 

limitation.. As explained in Essay Section 5, EPA considers facilities that are well-operated and 

designed can meet the limitations which are based upon data from facilities with the model 

technology.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 60

External Review Flag: Analytical

External Review Incorporated into Response: No

Comment Excerpt: 

5.10 The daily effluent limitations for arsenic are calculated incorrectly for two 

wastewaters: chemical precipitation/evaporation for FGD water and vaporcompression/evaporation for gasification.

The limits for arsenic in Table X-1 of the proposed Rule should be 5 μg/L, not 4 μg/L; per 

EPA’s description, the limit is set at the ML of the lab with the highest MDL [EPA, 2013]:

“The maximum ML is derived from that maximum MDL value by multiplying standard 

deviation of the results from that laboratory by 10 and rounding the result to the nearest value of 

1, 2, or 5 times 10n, where n is a positive or negative integer.”
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The standard deviation of arsenic analyses for the lab with the highest MDL (Test America) was 

0.252 [Test America, 2012]. Multiplying by 10 (2.52) and rounding to the “nearest value of 1, 2, 

or 5 times 10n, where n is a positive or negative integer” produces an ML of 5 μg/L. In addition, 

the statement in footnote (e) that the 4 μg/L limit is based on the detection limit is not correct—

per EPA’s stated procedure, the limit is intended to be equal to the ML. Due to the rounding 

procedure described above, there is not a linear relationship between the MDL and the ML.

Comment Response: 

EPA disagrees with the commenter’s assertion that the ML for arsenic should be 5 μg/L. The 

rounding step was included in the procedure to simplify the preparation of analytical standards 

for instrument calibration by making the ML a whole number. In the specific example cited by 

the commenter, preparing a standard for arsenic at an ML of 2.52 μg/L would be considerably 

more difficult that preparing a standard at 1, 2, or 5 μg/L. It appears that the commenter has 

misunderstood the implementation of the rounding step in the ML determination. As described 

in the ML procedure, a value of 2.52 would round down to 2, since it is less than half way 

between 2 and 5, which are two of the three incremental values mentioned in the procedure (1, 2, 

or 5). For example, had the standard deviation been 0.152 instead (as compared to the standard 

deviation of 0.252 noted in the comment), ten times that value would be 1.52, which would 

round up to 2. On the other hand, had the standard deviation been 0.352 instead (as compared to 

the standard deviation of 0.252 noted in the comment), ten times that value would be 3.52, which 

would round up to 5, since 3.52 is greater than half the distance between 2 and 5 (e.g., 3.5). EPA 

recognizes that the rounding procedure affects the relationship between the MDL and the ML 

such that it is not strictly linear in every case, but notes that the intent of the rounding is to aid in 

the preparation of standards, as described above.

EPA removed the footnote (e) from the table because it is not needed and led to confusion.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 121

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

For many regulations, including the proposed Effluent Limitations Guidelines and Standards 

(hereafter abbreviated “TDD”), the mean is an important statistic. However in this effort an 

accurate measure of standard deviation is equally important. The standard deviation is used to 

compute percentiles and variability factors, both of which determine regulatory limits. Current 

methods in several places within the TDD will lead to underestimating the standard deviation, 

and therefore underestimating the regulatory limits themselves. I have recommended some 

possible solutions to improve estimates of the standard deviation.
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A recurring theme is that methods for dealing with nondetects in the TDD are inadequate, not 

availing themselves of knowledge gained over the last 30 years. Substitution of values for 

nondetects, declaring all nondetects to be detects at the quantitation limit, and similar procedures 

will produce estimates of mean and standard deviation that are off the mark. References to 

methods papers on this topic in the TDD stop after Owen and DeRouen (1980). Methods in 

Helsel (2012) and references therein would improve consistency in TDD methods and the 

resulting estimates.

Comment Response: 

EPA agrees that the standard deviation, along with the mean, is an important statistical parameter 

in calculating the limitations. As explained in Appendix A, Essay Section 4.1.1, EPA has 

corrected its calculation of the autocorrelation adjustment which had underestimated the standard 

deviations used to calculate the proposed limitations. In response to comments on the proposed 

rule, EPA also modified its use of the baseline value as explained in Essay Section 3.5. Also see 

Essay Section 3.5 (baseline discussion).

EPA disagrees that its selection of the modified delta-lognormal distribution is inadequate. See 

Essay Section 4.1. Contrary to the comment’s assertion, EPA has considered other statistical 

procedures that can be used to model mixtures of detected and non-detected measurements. See 

Essay Section 4.2.

Commenter Name: Erik Silvola

Commenter Affiliation: Great River Energy (GRE)

Document Control Number: EPA-HQ-OW-2009-0819-4572-A1

Comment Excerpt Number: 2

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Proposed Numeric Limits 

GRE believes the approach taken to derive the proposed numeric limits results in the calculation 

of limits that are too low due to an underestimation of the standard deviation of real life 

discharges. This is an artifact of small data sets collected over a short timeframe. We reference 

EPRI and UWAG comments.

Comment Response: 

As explained in Essay Section 4.1.1, EPA has corrected its calculation of the autocorrelation 

adjustment which had underestimated the standard deviations used to calculate the proposed 

limitations.
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EPA disagrees that the comment’s assertion that the “limits are too low” for any reason, 

including the amount of data used as a basis for the limitations development. As explained in 

Appendix A, Essay Section 3.2.1.1, EPA has used all of the relevant data made available to it. 

Essay Section 2.3 and Section 5 describe EPA’s rationale for the percentile basis of its 

limitations and achievability of its limitations.

Commenter Name: John W. Myers

Commenter Affiliation: Tennessee Valley Authority (TVA)

Document Control Number: EPA-HQ-OW-2009-0819-4607-A1

Comment Excerpt Number: 12

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

b. FGD Limits Established are Too Stringent and Facilities Will Not Be Able to Achieve 

Consistent Compliance

EPA’s data analysis to derive the proposed numerical limits is statistically unsound. As pointed 

out in EPRI comments, EPA elected to utilize a small data set which distorts the proposed limits 

to the low, more stringent side. In addition, EPA’s use of the median values of plant-specific 

long-term averages will result in 50% of facilities exceeding the proposed ELG with potentially 

serious enforcement and shutdown consequences. As recommended by EPRI, TVA supports a 

95th percentile upper confidence level (UCL) statistical approach in deriving numerical limits 

upon which the performance of alternative treatment methodologies can be evaluated.

Comment Response: 

EPA disagrees with the comment’s assertion that its derivation of the limitations is statistically 

unsound. See Appendix A, Essay Section 4 for EPA’s response to comments related to the 

modified delta-lognormal distribution.

EPA disagrees with the comment’s assertion that its data set distorts the limitations to the “low, 

more stringent side.” As explained in Essay Section 3.2.1.1, EPA has used all of the relevant data

made available to it. Essay Section 2.3 and Section 5 describe EPA’s rationale for the percentile 

basis of its limitations and achievability of its limitations.

EPA disagrees that a tolerance limit, or upper confidence level, is appropriate as explained in 

Essay Section 4.2.1.

EPA disagrees with the comment’s interpretation of the use of the median in deriving the option 

long-term average. See Essay Section 2.4.
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Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 10

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Effects of EPA’s Data Selection, Data Manipulation and Flawed Statistical Methods on 

Calculated ELGs

EPA’s data censoring, data manipulation, and use of inappropriate statistical methods 

systematically reduced the magnitude of calculated ELGs. The effect was generally consistent 

across the BAT facilities EPA selected and for the four pollutants (Arsenic, Mercury, Selenium 

and Nitrate-Nitrite). In some cases EPA’s data handling and statistical methods reduced 

variability factors (“VF”), in other cases long-term averages (“LTA”) were reduced, and in some 

cases variability factors and long-term averages were reduced.

Calculated Facility-Specific ELGs

To examine the combined effects of EPA’s data analysis steps on the ELG calculations, a 

separate ELG, in addition to the LTA and VFs, was calculated for each pollutant and BAT 

facility (Tables 9 – 12). Calculations were performed according to the methods described in the 

TDD (EPA 2013). For arsenic and mercury, separate ELGs were calculated for Hatfield’s Ferry, 

Keystone and Miami Fort. For nitrate-nitrite and selenium, separate ELGs were calculated for 

Allen and Belews Creek. Figures 1 – 4 (below) summarize these results. Results for Monthly 

Average Limits follow the same pattern as results for Daily Maximum Limits and therefore are 

not presented graphically.

Figure 1. For arsenic, EPA’s analysis steps systematically reduced the LTA for all three facilities 

and systematically reduced the VF for Miami Fort (Table 9). Those reductions propagated into 

reductions of calculated ELGs for Hatfield’s Ferry and Miami Fort. Data were inadequate for 

calculating Arsenic VFs for Keystone.
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Figure 2. For mercury, EPA’s analysis steps systematically reduced the VFs for all three 

facilities and systematically reduced the LTAs for Hatfield’s Ferry and Miami Fort (Table 

10). Those reductions propagated into systematic reductions of calculated ELGs for all three 

facilities.
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Figure 3. For nitrate-nitrite, EPA’s analysis steps systematically reduced the LTA for both 

facilities and systematically reduced the VF for Belews Creek (Table 11). Those reductions 

propagated into reductions of calculated ELGs for Belews Creek. Except for the LogNormal 

case, data were inadequate for calculating Nitrate-Nitrite VFs for Allen. Data from Belews 

Creek were inadequate for calculating VFs using the 2-Stage statistical method.
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Figure 4. For selenium, EPA’s analysis steps systematically reduced the VFs for both facilities 

and systematically reduced the LTA for Belews Creek (Table 12). Those reductions propagated 

into systematic reductions of calculated ELGs for both facilities. Data from Allen were 

inadequate for calculating VFs using the 2- Stage statistical method.
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Comment Response: 

In producing the table estimates, the comment has used different assumptions than EPA about 

the effluent data and statistical methodology. As explained in Appendix A, Essay Section 4.2.3, 

it is inappropriate to apply survey estimation techniques to effluent data because they were not 

collected using 2-stage sampling designs.
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As explained in Essay Section 4.1.1, EPA has corrected its calculation of the autocorrelation 

adjustment which had underestimated the standard deviations used to calculate the proposed 

limitations.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 11

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

For arsenic, EPA’s data analysis steps had little effect on the calculated Option ELG (Figure 

5). This is because the median LTA was the LTA from Miami Fort, and with only 8 samples, the 

LTA for Miami Fort was not materially affected by EPA’s data handling steps.

For mercury, each of EPA’s selections of data and statistical methods resulted in reductions in 

the Option ELGs (Figure 6).

For nitrate-nitrate, EPA’s selection of data from the EPA Sampling and CWA 308 Sampling 

only, while ignoring over 100 self-monitoring samples had an enormous effect on the calculated 

Option ELGs (Figure 7). The LTA for the 15 available samples from Allen was 1.642 mg/l, and 

the LTA for the 106 available samples from Belews Creek was 6.006 mg/l (Table 11). In 

contrast, the LTA for the 8 EPA selected samples from Allen was 0.104 mg/l and the LTA for 

the 8 EPA selected samples from Belews Creek was 0.115 mg/l. Because the biological 

treatment Option only included two facilities, the sample median LTA used to calculate the 

Option ELGs was equivalent to the sample mean LTA.

For selenium, each of EPA’s selections of data and statistical methods resulted in reductions in 

the Option ELGs (Figure 8). The reduction in ELGs going from the Delta LogNormal method to 

the LogNormal method is particularly notable. This is because that change was intended to 

address the issue of autocorrelation, and the result of that manipulation should have been to 

increase the ELGs. Instead, EPA accomplished the opposite.

Figure 5. Effect of EPA’s selections of data and statistical methods on calculated Option ELGs 

for arsenic.
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Figure 6. Effect of EPA’s selections of data and statistical methods on calculated Option ELGs 

for mercury.
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Figure 7. Effect of EPA’s selection of data and statistical methods on calculated Option ELGs 

for nitrate-nitrite.
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Figure 8. Effect of EPA’s selections of data and statistical methods on calculated Option ELGs 

for selenium.
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Comment Response: 
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See the response to DCN EPA-HQ-OW-2009-0819-46558, Excerpt Number 10.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 25

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Although the sample median is an appropriate statistic for characterizing the central tendency of 

a distribution, with a small sample size the sample median contains considerable uncertainty. For 

the single-stage chemical precipitation Option (with 3 facilities), there is only a 1-in-4 chance 

that the sample minimum and maximum LTAs bracket the true median LTA. For the biological 

treatment Option (with 2 facilities), there is only a 1-in-2 chance that the two sample LTAs 

bracket the true median LTA. For the biological treatment Option, those are the same odds as 

flipping a coin.

Comment Response: 

EPA disagrees with the comment’s interpretation for the long-term average. As explained in 

Appendix A, Essay Section 2.2, EPA applies statistical methods as a framework for the 

development of limitations using all of the relevant data made available to it (see Essay Section 

3.2.1.1). Also see Essay Section 2.4 for EPA’s use of the median for the LTA.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 30

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The statistical method EPA used to calculate underlying parameters of the Delta LogNormal 

distribution assumed that samples were collected according to a simple random sampling design. 

In fact, that clearly was not the case. For arsenic, mercury and nitrate-nitrate, the data EPA relied 

on was collected according to a two-stage sampling design. By treating those data as if they 

came from simple random sampling, EPA under-estimated the underlying variance. By underestimating the variance, EPA caused the corresponding variability factors to be biased low.
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Comment Response: 

The comment is incorrect in stating that EPA assumes that the data were collected by a simple 

random sampling design. In addition, the comment is incorrect in stating that the data EPA used 

were collected according to a two-stage sampling design. The comment confuses the statistical 

methods that are appropriate for survey data with those appropriate for effluent data. See 

Appendix A, Essay Section 4.2.3. EPA describes its statistical methodology in TDD section 13.
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31.h.i. Stats NL Stat Method Used – Comments on Appendix B

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 64

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

6.1 EPA underestimated the standard deviations in its statistical approach to 

determine long-term averages, variability factors, and effluent limitations and 

standards. The underestimated standard deviations further propagate and 

impact the variability factors and ultimately, the regulatory limits and standards.

Comment Response: 

For its calculations of the final limitations, EPA corrected its autocorrelation adjustment which 

had underestimated the standard deviations used to calculate the proposed limitation. See Essay 

Section 4.1.1. See the response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 15.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 65

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

6.2 Use of small data sets leads to underestimation of standard deviation, and 

hence, underestimation of regulatory limits.

EPA has relied on small data sets (< 20, and sometimes as few as 4, data points) to compute 

regulatory limits. The standard deviation, percentiles, and variability factors calculated from 

small data sets will be lower and less accurate than those calculated from larger, more complete 

data sets (population). Much environmental data, including data collected for ELG standard 

setting, is skewed and follows a log normal distribution.

Alternative recommendation: Derive a “sample size factor” from simulations of a random 

selection of small samples from the population log normal distribution and multiply the standard 

deviation of the small sample set by the appropriate sample size factor to obtain a better estimate 
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of the population standard deviation. Use this population standard deviation to calculate longterm averages, variability factors, and regulatory limits.

As an example: If one considers a log normal distribution with mean of the logs = 0 and standard 

deviation of the logs = 1, the true standard deviation in original units is 2.16. If one randomly 

selects 100 sets of a small sample size, say 4, from this distribution, a large majority (more than 

75%) of the sets will have a standard deviation below the true value of 2.16. The median 

standard deviation of the small data set from the simulation is 1.456 and the sample size factor is 

2.16/1.456 = 1.48. Similarly, for a log normal distribution with mean of the logs = 1 and standard 

deviation of the logs = 1, the true standard deviation in original units is 5.87. A simulation of a 

random selection of 100 data sets of sample size 4 from this population yields a median standard 

deviation of the small data set of 3.486, resulting in a sample size factor of 5.87/3.486 = 1.68. 

Please see Appendix C for details of these calculations.

As the sample size increases, the sample size factor decreases, trending towards 1.0. Details of 

the suggested procedure and the simulation runs are presented in Appendix C. The Appendix 

also presents computation of sample size factors using the data set (23 data points) for mercury 

concentrations in FGD wastewater chemical precipitation effluent as an approximation to a 

“large data set.”

Comment Response: 

See response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 113.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 66

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

6.6 The modified delta-lognormal (DLOG) distribution used by EPA to compute 

percentiles for censored data does not give accurate results when non- detects are 

present.

The modified delta-lognormal (DLOG) distribution substitutes detection limits for non-detects, 

thus tending to underestimate standard deviations. Using underestimated standard deviations 

leads, in turn, to underestimating variability factors and regulatory limits.

Alternative recommendation: Consider using alternative procedures employed in the survival 

analysis field for computing percentiles of censored data (some values excluded), especially for 

small data sets. Kaplan-Meier is one such procedure.
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Comment Response: 

EPA disagrees with the commenter’s assertion that the statistical approach used by EPA (i.e., the 

modified delta-lognormal) does not produce accurate results when non-detects are present, or 

that it underestimates the standard deviation and variability, and results in overly stringent 

regulatory limits. In addition, the commenter fails to describe how EPA should have employed 

survival analysis to calculate effluent limits, and does not justify why a statistical approach using 

survival analysis would be appropriate for setting effluent limits using the data for this rule. The 

record for this rule demonstrates that EPA’s selection of the modified delta-lognormal statistical 

approach is reasonable and appropriate; nothing in the commenter’s submission proves to the 

contrary.

EPA disagrees with the commenter’s claims in the above excerpt regarding the modified deltalognormal approach. The commenter provides little explanation for the assertion, but it appears 

to be based on the commenter’s incorrect assertion regarding how the non-detects are used in the 

modified delta-lognormal to estimate standard deviations. The modified delta-lognormal models 

the detected values and the non-detected values separately and differently. Specifically, the 

detected values are modeled using a lognormal distribution and the non-detected values are 

modeled using the delta distribution. Contrary to the commenter’s statement, in estimating the 

standard deviations, the modified delta- lognormal uses the number of non-detects to estimate the 

proportion of non-detects at each detection limit in the discrete part of the distribution, and the 

detected values are used to estimate the parameters (including standard deviations) based on the 

continuous lognormal part of the distribution (see Appendix B of the Technical Development 

Document for the final rulemaking). Because of the separate modeling of the discrete and 

continuous parts of the modified delta-lognormal distribution, the presence of non-detects does 

not result in an underestimation of the standard deviation as claimed by the commenter. When 

all observations are detected, the modified delta-lognormal is equivalent to the lognormal 

distribution, which is the distribution generally considered to be appropriate for environmental 

data.1

Furthermore, the commenter contradicted the claims made in the excerpt above with a comment 

made in Appendix C of the letter (page C-2). In Appendix C (page C-2), the commenter stated 

that “...the maximum likelihood procedure used by DLOG to estimate standard deviation is 

overall unbiased...”. EPA believes that the modified delta lognormal procedure is the most 

appropriate method for use with the type of data observed in this rulemaking (i.e., a mixture of 

detected values assumed to follow a lognormal distribution and non-detected values occurring at 

various fixed detection limits). Since the non-detects are unquantified observations, it is 

impossible to test the assumption of how the data are truly distributed. The modified deltalognormal approach allows for these non-detect observations to be used without having to make 

presumptions (and possibly introduce bias) about their distribution. Precedents for the valid use 

of the modified delta lognormal procedure can be found in the rulemakings for Organic 

Chemicals, Plastics, and Synthetic Fibers (1987) and Pesticides Chemical Manufacturing (1993). 

The commenter fails to provide sufficient justification for their “alternative recommendation,” 

namely that EPA “consider using alternative procedures employed in the survival analysis field 

(with some values excluded),...”. First, the commenter’s suggestion is vague and fails describe 

how EPA should have employed survival analysis to calculate the effluent limits or identify 
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which specific statistical methods from the survival field should be used for these data. The field 

of survival analysis is broad and contains many competing procedures. Moreover, the 

commenter fails to demonstrate that, presuming a method based on survival analysis were to be 

used, it would be superior to the modified delta-lognormal method used to calculate effluent 

limits, or that it would even be appropriate for this purpose. In addition, the commenter does not 

explain what is meant by the phrase “some values excluded”. EPA uses all available data that 

represent normal operating conditions when calculating the effluent limits. The commenter’s 

suggestion of using a method with “some values excluded” is not reasonable since data should 

not be excluded without reason, and this comment is inconsistent with EPA’s policy using all 

available data representative of normal operating conditions. Finally, the commenter was 

specific in the suggestion to use Kaplan-Meier, which is a non-parametric method (i.e., does not 

assume any particular data distribution) that can be used to estimate percentiles. EPA disagrees 

with this suggestion because the commenter does not provide any basis for why Kaplan-Meier 

should be preferred over the modified delta-lognormal. Also, EPA believes that the data for this 

industry follow a modified delta-lognormal distribution, so the use of a non-parametric 

procedure, such as Kaplan-Meier, would be inefficient. EPA selected the modified deltalognormal method because it provides a reasonably good fit to the wastewater effluent data for 

this industry. In addition, the use of modified delta-lognormal with data such as that available 

for this industry has been supported by the statistical community and EPA for decades (e.g., 

Owen and DeRouen (1980)2, Crow and Shimizu (1988)3, Aitchison (1955)4, Kahn and Rubin 

(1989)5). Also see Appendix A, Essay Section 4.2.2.

1 Richard O. Gilbert, Statistical Methods for Environmental Pollutant Monitoring, Van Nostrand 

Reinhold, New York, 1987.

2 W.J. Owen and T.A. DeRouen (1980), “Estimation of the Mean for Lognormal Data 

Containing Zeroes and Left-Censored Values, with Applications to the Measurement of Worker 

Exposure to Air Contaminants,” Biometrics 36: 707-719.

3 Edwin L. Crow and Kunio Shimizu (1988), Lognormal Distributions: Theory and 

Applications Marcel Dekker, New York.

4

J. Aitchison (1955). “On the distribution of a positive random variable having a discrete 

probability mass at the origin.” Journal of the American Statistical Association 50: 901-908.

5 H.D.Kahn and M.B. Rubin, “Use of Statistical Methods in Industrial Water Pollutant Control 

Regulations in the United States, “Environmental Monitoring and Assessment, 12: 129-148.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 113
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External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

1. EPA has used several small data sets (n<20, sometimes even n=4) for computing regulatory 

limits. The range and variability of small subsets will often be lower than a more representative 

sampling of a skewed population. With skewed data, high infrequent observations are often not 

included when only a few values are measured. Resulting estimates of standard deviation, 

percentiles and variability factors from these small data sets will be lower and less accurate than 

if computed from larger, more complete data sets from the same sources. Even though the 

maximum likelihood procedure used by DLOG to estimate standard deviations is overall 

unbiased, the distribution of those estimates will still be skewed. This means that more of them 

will be lower than the true standard deviation, with fewer higher than the true value, though 

sometimes much higher. When data from only a few plants are collected, the estimate of 

standard deviation is more likely to be closer to the median of the true distribution of standard 

deviations than an unbiased mean value. To make this more clear, I simulated data using 

lognormal distributions with mean of the logs = 0 and 1, within the range of skewed 

distributions typical for environmental science. The standard deviation of the logs equals 1 for 

both distributions. For lognormal distributions, the standard deviation in original units changes 

with the mean logarithm. With mean log=0 the standard deviation of the distribution, the ‘true 

standard deviation’ in original units is 2.16. With mean log=1 the true standard deviation in 

original units is 5.87. These values for standard deviation are the correct targets for estimates. 

For 100 sets of sample size 4 from these two distributions, a plot of the estimated standard 

deviations using maximum likelihood (the method used by DLOG) is shown in the histograms 

below. More than 50% of the estimates in each case are below the true standard deviation.
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When small samples are taken from skewed data as the TDD data are, the single estimate of 

standard deviation will more often than not underestimate the standard deviation of the data as a 

whole.
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The primary impact of underestimating the standard deviation in the TDD is that the variability 

factor will likely be too low, and so the regulatory limit will be too low as compared to what 

would be calculated with a sample size that was more representative of the population of daily 

values.

Alternative recommendation: collect or find additional data. I realize this is always the 

statistician’s mantra, but is the best remedy. The median will be much closer to the true value as 

sample sizes get larger. A second possible solution is to use a larger data set from one of the 

categories of measured data. Compute the mean and standard deviation of the logarithms for this 

data set as a guide. Simulate 100 sets of differing sample sizes from a lognormal distribution 

with this mean and standard deviation. Compute the median standard deviation of the resulting 

small data sets, and divide it into the standard deviation of the original distribution, 

original/median, to form a ‘sample size factor’. The standard deviation as currently computed 

should be multiplied by the appropriate sample size factor before computing percentiles and 

variability factors. This will be an attempt with existing data to overcome the difficulty of 

estimating a true standard deviation with small data sets.
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I’ll illustrate the process with the above two distributions. If the ‘large’ data set of measurements 

had a mean logarithm of 0, the sample size factor for an n=4 data set (the true mean of 2.16 

divided by the median of the simulated standard deviations) is 2.16/1.456 = 1.48. For a mean 

logarithm=1 distribution in Figure 2, the sample size factor equals 5.87/3.486 = 1.68. From this it 

appears that if the actual monitoring data have distributions in this range of shapes, the standard 

deviations estimated from a sample size of 4 should be multiplied by approximately 1.5 before 

being used in further calculations. As sample sizes increase, the sample size factor will decrease 

towards 1. For data that are less skewed, the sample size factors will be smaller. I’ve provided 

an additional example computation using the mercury data for FGD chemical precipitation 

effluent as the ‘large data set’ in the appendix to this memo.

Appendix

Computing the Sample Size Factor from existing data – an example

Included in the data set “ELG data EPA-HQ-OW-2009-0819-1965.xlsx” are 23 mercury 

concentrations for FGD chemical precipitation effluent. Using these as the ‘large data set’ 

representing the population of mercury concentrations for this sample type, the method to 

compute a sample size factor described in comment 1 in the September 6, 2013 memo from 

Practical Stats is illustrated below.

a. The chemical precipitation effluent concentrations of mercury (in ng/L) have the following 

descriptive statistics:

Mean Standard Deviation Median

Final concentration 103.2 75.4 82.5

logarithms 4.385 - -

These values are lower than for the two distributions used in the main body of the memo, which 

means that the Sample Size Factor will be lower as well for a given sample size. Twenty-three 

observations is near the minimum to be called a ‘large’ data set.

b. Using a population of data with meanlog = 4.385 and sdlog = 0.737, Minitab statistical 

software was used to randomly select 100 sets of samples of size 4, 8, and 20 from this 

population. Figure A1 below shows the histogram of 100 standard deviations produced for the 

sample size of 8. The ‘true’ standard deviation in units of concentration for a lognormal 

distribution with the above parameters in natural log units is found using the formula

sdtrue=exp(meanlog+(0.5*sdlog**2))*sqrt(exp(sdlog**2)-1)

which here equals 89.42. Note that for a lognormal distribution the standard deviation in original 

concentration units is a function of both the mean and standard deviation of the logarithms. The 

median standard deviation of sampled data for the 100 replicates of each sample size is given 

below:
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Sample size median of estimated standard deviations

n=4 51.67

n=8 70.88

n=20 72.26

c. The population (true) standard deviation is divided by the median estimated standard deviation 

for each sample size. The ratio is given below as the Sample Size Factor, to be multiplied by the 

estimated standard deviation for data sets of the specified sample size prior to computing 

percentiles and variability factors.

Sample size Sample Size Factor

n=4 89.42/51.67 = 1.73

n=8 89.42/70.88 = 1.26

n=20 89.42/72.26 = 1.24
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For computing percentiles and variability factors for FGD chemical precipitation effluent 

mercury data of sample size 8, say for other plants or times, the standard deviation computed 

from those 8 observations should first be multiplied by 1.26 (to come closer to what the true 

standard deviation is expected to be if there were a larger sample size) and the result used as the 

standard deviation to estimate a 99th percentile and other statistics of the distribution.

Comment Response: 

EPA does not agree that the use of a small dataset would necessarily lead to an underestimation 

of regulatory limits. In addition, it is important to note that EPA has used all available valid data 

in calculating the effluent limitations established by the ELGs. Furthermore, in its proposed rule, 

EPA clearly identified the data that it had collected and used to calculate the proposed 

limitations. EPA solicited comment on the proposed rule, providing stakeholders with the 

opportunity to submit additional data if they chose to do so. In some cases, such as for the 

chemical precipitation and biological treatment technologies for FGD wastewater, commenters 

submitted large amounts of data representing years of treatment system operation. EPA 

evaluated all of these effluent data submitted in comments and, as appropriate, included these 

data in establishing the effluent limitations for the final rule. However, in other cases, such as for 

gasification wastewater and for the vapor-compression evaporation technology for FGD 

wastewater, EPA received no additional data. Thus, in establishing the ELGs, EPA has used all 

of the data it could accumulate. Had industry or other stakeholders come forward and provided 

EPA with more data, EPA would have used it if it were valid and representative of the BAT 

technology, as appropriate.

EPA has historical precedence of employing limited data sets when larger data sets are not 

available; a precedence that has been upheld in previous court cases as referenced in the essay 

section. See Appendix A, Essay Section 3.2.1.1 and Essay Section 4.1.2. EPA disagrees with the 

suggestion of using a “sample size factor.” A sample size factor is not necessary because EPA 

has adequate data and any sample size adjustment would introduce uncertainty into the 

calculation of the effluent limitations. There is no indication that the suggested sample size 

factor will perform consistently for all estimated parameters. The alternative method considers 

ONLY the standard deviation, while EPA’s approach to calculating limits estimates of many 

parameters. The comment attributes skewness as one of the motivating factors requiring sample 

size adjustment, but there is no analysis of how skewed the data must be or if the adjustment 

again performs consistently over a wide variety of possible skewed data. The alternative method 

simulates data as a means of analysis; however, the analysis is incomplete, the results are 

questionable, and the comment certainly does not provide enough evidence to support 

abandoning EPA’s current and longstanding methodology. See Essay Section 4.1.2.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 126
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External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

6. The method for adjustment of the variability factor using a serial correlation coefficient is not 

given in either the TDD, its Appendices, nor the April 15, 2012 memorandum “Serial 

correlations for Steam Electric with and without adjustment for baseline values [EP-C-10-023 

WA 2-6 (Steam Electric)]”. Data were available to compute a correction for serial correlation of 

daily data for only two chemicals. For selenium and nitrate-N, the lag-1 serial correlation of 

rho=0.291 means from my calculation [see below] that the uncorrected standard deviation should 

have been multiplied by approx. 1.35. The April 15 memo on serial correlation goes into detail 

on how the correlation coefficient rho was calculated, but nowhere states how rho was used to 

adjust the computation for percentiles and variability factors.

While the computation of the autocorrelation coefficient used a censored data procedure such as 

those cited in Helsel (2012) to incorporate detects and nondetects into the calculation, Appendix 

B, Section B.6 states that when computing long-term averages and variability factors, all 

nondetects are simply set to the quantitation limit and called detected values. This is very 

inappropriate. No explanation is given as to why this was done here at this point, while much 

better methods are used when computing the correlation coefficients themselves. The ‘declaring 

nondetects to be detects’ method will underestimate the variability in the data, therefore biasing 

low the variability factor used to set limitations. A sure indication that something is wrong would 

be if the estimate of variability after correction for autocorrelation were found to be lower than 

before. Correction for autocorrelation will increase estimates of variability, recognizing that the 

numbers of independent observations are fewer than the numbers of samples taken. The issue is 

not that autocorrelation should not be corrected for, but that the process used for handling 

nondetects is improper and biased.

Alternative Recommendation: 1) provide more detail in a memo available to all interested parties 

on how this correction was actually accomplished. 2) consistently use reliable, industry-standard 

methods for handling nondetects, rather than either substitution of an arbitrary number, or 

declaring nondetects to be detects at the quantitation limit.

An adjustment for lag-1 serial correlation was provided by Matalas and Langbein in 1962:

StdDev_corrected = sqrt(FACTOR)*StdDev

FACTOR = { (1 + r)/(1 - r) - (2/N)*r*(1-rN)/(1-r)2}

where r is the lag-1 serial correlation coefficient. Often the Factor equation is simplified and 

truncated as the latter portion is close to 0 for reasonable sample sizes, resulting in:

FACTOR = (1 + r)/(1 - r)

For an r of 0.291, the sqrt[FACTOR] using the simpler formula = 1.35
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This 35% increase for the only two chemicals with sufficient data so far to calculate this effect 

indicates that this correction may also be important for other chemicals. A return to this issue in 

the not-distant future, after more monitoring data becomes available for the other chemicals, is

important to determine if a serial-correlation correction factor can be computed for chemicals in 

addition to the two now being utilized.

Comment Response: 

As explained in Appendix A, Essay Section 4.1.1, EPA corrected its autocorrelation equations 

used to calculate the final limitations. Given this change, EPA does not agree that any other 

changes need to be made to the calculation procedures.

The comment is incorrect in stating that the procedures were not documented for the proposed 

rule. The method for adjustment of the variability factor using a serial correlation coefficient is 

given in Appendix B of the proposed and final TDD.

The adjustment factor suggested in the comment applies to random data. As explained in Essay 

Section 4.2.3, the effluent data are not randomly selected, and thus, the adjustments does not 

apply to the calculations of the limitations.

EPA has used “industry-standard methods for handling nondetects” as recommended by the 

comment. See Essay Section 4.1 that describes EPA’s reasons for selecting the modified deltalognormal distribution.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 127

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

7. The modified delta-lognormal (DLOG) distribution is being used to compute percentiles for 

censored data. Developed in 1955, DLOG has been abandoned in scientific studies in favor of 

others over the last 30 years. Hinton (1993) showed that the modified DLOG mean is strongly 

biased upward, more so than several other alternate methods, when nondetects are present. 

Gilliom and Helsel (1986) found that the standard deviation estimated by DLOG is less accurate 

than alternate methods. Helsel and Cohn [1988] demonstrated that substituting the detection limit 

for nondetects, as done by the modified DLOG procedure used in the TDD, underestimates the 

standard deviation. This is not surprising, as the same number is substituted for all nondetects, 

reducing variability. The results are 95th and 99th percentiles that are too low, and so a 

variability factor that is too low. Since the direction of bias of the mean is the opposite of the

direction of bias in the standard deviation, it is impossible to predict whether using a better 
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alternative to DLOG will increase or decrease the eventual effluent limitation as compared to the 

correct method. However, it is clear that better computation methods than DLOG are available.

Alternative Recommendation: WESTAT cited better methods from survival analysis in 

computing serial correlation estimates for data that include nondetects. Their April 15 memo on 

serial correlation (EPA-HQ-OW-2009-0819-1963.pdf) states that using survival analysis 

procedures “provides better estimates of the serial correlation for the concentration series than 

when using the ARIMA model with substitute values for the non-detects.” DLOG as used in the 

TDD similarly substitutes the detection limit value for all nondetects. Percentiles and so 

variability factors can be computed using the better methods cited by WESTAT, rather than 

using DLOG, resulting in estimates that are less controversial whether that be lower and higher 

than computed now. Examples of survival analysis procedures for computing percentiles of 

censored data include the Kaplan-Meier estimator and Maximum Likelihood. See Helsel (2012) 

for details.

Comment Response: 

EPA disagrees with the commenter’s assertion that the modified delta-lognormal has been 

abandoned in scientific studies in favor of others in the last 30 years since EPA finds that this 

assertion is unfounded. EPA has found that a number of researchers have used or investigated 

the delta-lognormal distribution over the last 20 years, even as recently as 2013. Further, the 

commenter stated that the modified delta-lognormal produces biased estimates of the mean and 

standard deviation, low limits and variability factors, and the commenter references several 

articles and books to support the criticisms. EPA has reviewed all the commenter’s references 

and found that none of these references support the commenter’s assertions. Moreover, the 

commenter suggests an “Alternative Recommendation” to calculate the effluent limits; however, 

the commenter fails to provide sufficient justification for why the alternative method is better 

than the modified delta-lognormal. The record for this rule demonstrates that EPA’s selection of 

the modified delta-lognormal statistical approach is reasonable and appropriate; nothing in the 

commenter’s submission proves to the contrary.

First, EPA disagrees with the commenter’s claim in the excerpt above that the modified deltalognormal has been abandoned in scientific studies in favor of others over the last 30 years. The 

modified delta- lognormal is a minor, direct extension of the delta-lognormal method to 

incorporate multiple detection limits rather than a single detection limit. A literature search has 

revealed that a number of researchers have used or investigated the delta-lognormal distribution 

over the last 20 years, for example, see the articles by Lo, Jacobson, and Squire (1992), Buntao 

and Niwitpong (2013), Fletcher (2008), and Walter and Ortiz (2012), along with the references 

therein. Based on this, it is clear that the delta-lognormal has not been abandoned and is still 

found to be useful for modeling in applications that involve data exhibiting both discrete and 

continuous parts. Thus, the commenter’s statement is unfounded.

Second, the commenter stated that the modified delta-lognormal procedure produces biased 

estimates of the mean and standard deviation, low limits and variability factors, and the 

commenter references several articles to support the criticisms (Hinton (1993), Gilliom and 

Helsel (1986), and Helsel and Cohn (1988)). EPA has reviewed each of the references above 
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and disagrees that these references support the assertions for the reasons described below. The 

commenter states that Hinton (1993) shows that the modified delta-lognormal method gives 

estimates of the mean that are biased upward (i.e., estimates that tend to be too large). Hinton 

(1993) is a journal article that compares the performance of three statistical methods used in 

estimating the mean: modified delta-lognormal model, Cohen’s method, and regression of 

normal order scores. The author’s simulation is based on sample sizes between 10 and 20, and 

censoring levels between 5% and 80%. In these simulation studies, data were generated from 

lognormal distributions. These simulation studies showed that modified delta-lognormal 

performed well when the percent of censoring was less than 40%, but the competing methods 

had better performance when the percent of censoring was greater than 40%. This reference, 

however, does not properly evaluate the performance of the modified delta-lognormal in setting 

limits for this rulemaking for the following two reasons: (i) The simulated data was based on 

lognormal with a mean of 2 and coefficients of variation (CV) with values of 0.3 and 1. The 

commenter fails to explain the relevance of using these values for the mean and CVs to the data 

used to develop the effluent limitations for the ELGs; and (ii) The commenter fails to justify the 

logic in using data generated by a lognormal distribution to criticize limitations that were derived 

from data generated from a different distribution (i.e., modified delta-lognormal). In other 

words, the simulated data was drawn from a lognormal distribution, which is different from the 

EPA’s assumption that the data were generated from the modified delta-lognormal. This 

difference in the essential nature of the underlying data in the comment is critical because it 

inappropriately tips the results in favor of the position advocated in the comment. Further, it has 

been shown that the delta-lognormal procedure (a simplified version of the modified delta 

lognormal) produced a better estimator than censored lognormal (e.g., Cohen’s method) when 

the underlying distribution of the data is delta-lognormal, rather than lognormal (see Owen and 

DeRouen (1980)). When all observations are detected, the modified delta-lognormal distribution 

is equivalent to Cohen’s maximum likelihood estimation presented in the paper and both 

methods are equivalent to the lognormal distribution.

The commenter stated that simulation studies reported in Gilliom and Helsel (1986) and Helsel 

and Cohn (1988) show that the modified delta-lognormal based on substituting detection limits 

for non-detects result in underestimated standard deviations, leading to percentiles and variability 

factors that are too low. However, the commenter also states that it is not clear whether the 

modified delta-lognormal procedure results in limits that are higher or lower than competing 

methods. EPA has reviewed the simulation studies of Gilliom and Helsel (1986) and Helsel and 

Cohn (1988) and finds that neither article actually evaluated the modified delta-lognormal 

procedure. Instead, both articles considered simplistic substitution approaches that replace a 

non-detect with zero, half the detection limit, or the detection limit. Thus, the commenter 

assertion is unfounded and the commenter has no basis in concluding that the modified deltalognormal underestimated standard deviations resulting in low limits and variability factors. The 

modified delta-lognormal procedure is a sophisticated and appropriate method for dealing with 

non-detects, and it has been shown to work well when the data come from a delta lognormal 

distribution (see Owen and DeRouen (1980)).

The commenter also briefly suggests that EPA should consult “Helsel (2012) for details”. Helsel 

(2012) is a book that covers many aspects of the analysis of censored environmental 

data. However, the commenter’s reference to Helsel’s book is not specific and does not point to 
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exactly which of the methods discussed in the book that the commenter would recommend. The 

commenter’s suggestion is too vague and too broad for EPA to interpret.

Finally, the commenter fails to provide sufficient justification for their “Alternative 

Recommendation”, in which the commenter cited a memo from Westat in which an approach 

was developed specifically for the estimation of serial correlations. The serial correlations 

needed to be estimated in order to investigate the effect that the correlation may have on the 

calculated limits. The commenter states that the Westat memo “cited better methods from 

survival analysis in computing serial correlation estimates for data that include 

nondetects”. However, the Westat approach was not simply an application of a standard survival 

analysis procedure. Instead, the Westat approach is a complicated ad hoc procedure that 

combines survival analysis with a Bayesian approach, simulations, and an ARIMA model. The 

commenter states that the “better methods cited by Westat” should also be used by EPA to 

compute percentiles and variability factors. The commenter further states that such an approach 

would result in “estimates that are less controversial” than estimates produced using the modified 

delta-lognormal procedure. EPA disagrees with this assertion. The approach used by Westat 

was developed specifically for the estimation of serial correlations and was not intended for the 

estimation of other quantities, such as percentiles or variability factors. The commenter does not 

explain how Westat’s method could be further adapted for the estimation of percentiles and 

variability factors or whether such an adaptation would produce estimates of sufficient quality 

for use in the setting of effluent limits for this rule. The commenter has not presented any 

evidence that the method used by Westat would result in estimates of percentiles or variability 

factors that are uniformly better or superior to the estimates obtained from the modified deltalognormal procedure.

Also, as part of the commenter’s “Alternative Recommendation”, the commenter further stated 

that EPA should consider using survival analysis procedures, such as Kaplan-Meier and 

Maximum Likelihood, for computing percentiles of censored data. The commenter fails to 

demonstrate why these survival analysis methods should be preferred over the modified deltalognormal. EPA found that the data for this industry follow a modified delta-lognormal 

distribution, so the use of a non-parametric procedure such as Kaplan-Meier, would be 

inefficient, especially in data sets with a small sample size. Regarding the suggestion of the use 

of maximum likelihood, in a peer reviewed journal, Owen and DeRouen compared the 

estimators obtained using the delta distribution and a censored lognormal approach (based on 

maximum likelihood) and found that the estimator for the delta-lognormal “generally has a 

smaller mean squared error than the censored lognormal estimator...”. Since the modified deltalognormal is a minor direct extension of the delta lognormal, EPA believes that it is evidence 

that the modified delta-lognormal method is to be preferred over a maximum likelihood 

approach for the type of data available for this rulemaking. Thus, EPA maintains that the 

modified delta-lognormal is the most appropriate method for calculating the limits in this 

rulemaking. See Appendix A, Essay Section 4.1 and 4.2.2.
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Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 15

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA’s Statistical Methods for Calculating ELGs

A. Flawed Estimation of Underlying Parameters

where xi is the reported concentration and nc is the number of samples above the reporting limits.

These equations are appropriate for estimating the mean and variance when samples are 

collected according to a simple random sampling design in which each day of the year has an 

equal probability of being selected for sampling (Cochran 1977). The paper by Kahn and Rubin 

(1989) appropriately used these equations with three examples of census-like data. In the Kahn 

and Rubin paper, each example (Table 2 and Figures 2- 4 in Kahn and Rubin 1989) was for 

almost a full year of data with a measurement taken on almost every day of the year (i.e., n=363, 

n=353, n=336).

The sampling designs used to collect FGD effluent data at the six facilities were not simple 

random sampling designs. The EPA sampling design included four samples collected in one 

month, and one sample collected in each of four other months. For several facilities, the selfmonitoring data were also collected in manner not consistent with simple random sampling. A 

disproportionate number of self-monitoring samples from Belews Creek were collected in the 
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first year of operation of the bioreactor treatment system. For Allen, most samples were collected 

during winter months.

EPA’s method for estimating the mean and variance give equal weight to each sample. If a 

disproportionate number of samples were collected in a single month or season, the mean and 

average computed using EPA’s method will be biased towards the conditions of that month or 

season and will not be representative of the entire year, as required by the theory underlying the 

method. Statistical methods referred to as design- based methods have been developed to address 

this type of situation (e.g., Cochran 1977) and can be applied here.

The pattern of sampling of effluent samples resembles two-stage sampling with the primary 

sampling unit being month and the secondary sampling unit being day within month. For twostage sampling, a subset of months would be selected by simple random sampling, and within 

each selected month several days would be selected by simple random sampling. Although the 

dates of effluent sampling likely were not selected in strictly this manner, the pattern of effluent 

sampling more closely resembles two-stage sampling than simple random sampling of all days 

within the year. Accordingly, design-based statistical methods for estimating means and 

variances from two-stage sampling are more appropriate for analyzing the effluent data from the 

seven facilities. Formulae for estimation with two-stage sampling are presented in Appendix A.

Appendix B, page 44.

The 2-stage estimates for the daily mean and variance were calculated using the following 

equations (Cochran 1977). The annual mean was estimated as:

The annual variance was estimated as:
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Comment Response: 

In producing the table estimates, the comment has used different assumptions than EPA about 

the effluent data and statistical methodology. As explained in Appendix A, Essay Section 4.2.3, 

it is inappropriate to apply survey estimation techniques to effluent data because they were not 

collected using random and 2-stage designs, as even the commenter noted.

EPA disagrees with the comment’s assertion that EPA’s method will be biased towards the 

conditions of the months or seasons when the data were collected. See Essay Section 3.2.1.2.
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31.h.ii. Calculation of the Serial Correlation (Autocorrelation)

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 134

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

6.5 Additional information is needed to use the correlation coefficient to adjust 

the variability factor.

It is good to note that EPA considered the impact of serial correlation in adjusting the variability 

factors. However, the steps EPA appears to have taken to address this are inappropriate. Also, 

while the April 15, 2013, memorandum [EPA, 2013] goes into great detail about how the lag-1 

serial correlation coefficient (rho) was calculated, there is no indication in that memo or 

elsewhere in the TDD of how to use the correlation coefficient to adjust the variability factor.

Based on the lag-1 serial correlation coefficient of 0.291 provided for two chemicals (selenium 

and nitrate-N), we calculate an adjustment factor of 1.35. The uncorrected standard deviation

should be multiplied by this factor to account for serial correlation. Details of our calculations 

are in Appendix C. It appears that EPA’s correction for serial correlation may go in the wrong 

direction due to its treatment of non-detects. Appendix C suggests an alternative approach for 

incorporating non-detects, using survival analysis procedures, which will alleviate this problem.

Given the magnitude of the adjustment factor for the two chemicals, the impact of serial 

correlation on variability factors for other chemicals could be significant. It would be useful if 

EPA could provide more details on how the serial correlation correction was applied.

Comment Response: 

EPA’s calculation of correlation and how it is used in calculating effluent limitations are 

described in TDD Section 13 Appendix B and DCN SE06279. As explained in Essay Section 

4.1.1, EPA has corrected its calculation of the correlation adjustment which had underestimated 

the standard deviations used to calculate the proposed limitations. EPA does not agree that any 

other changes need to be made to the calculation procedures.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 8
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External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

As noted by EPA, if a positive autocorrelation is present in the data then estimates of the 

variance computed using standard methods will be biased low. Therefore, EPA’s method, as 

described in the 2013 TDD and supporting documents (e.g., EPA 2012), includes a correction 

factor (also referred to as a variance inflation factor) for correcting biased variance estimates. 

EPA’s correction factor assumes sample observations follow the pattern of a first order 

autoregressive process. The application of EPA’s variance inflation factor is appropriate when: 

1) observations are positively autocorrelated, and 2) samples were collected over sequential days 

(e.g., 40 CFR Ch 1, Subpart C, Part 75, Subpart E, section 75.41).

Comment Response: 

EPA’s methodology for autocorrelation is appropriate when samples whether or not they are 

from sequential days, regardless of the sign of the correlation. Unlike the equations used by EPA 

for the limitations, the equations referenced in the comment (i.e., 40 CFR Ch 1, Subpart C, Part 

75, Subpart E, section 75.41) are appropriate only when the samples are collected over sequential 

days but not when there are gaps in the sample collection days. Contrary to what is stated in the 

comment, the equations referenced in the comment are appropriate for data if the correlation is 

less than zero.

EPA has corrected its autocorrelation adjustment for the final rule. See Appendix A, Essay 

Section 4.1.1.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 16

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The second requirement for applying a variance inflation factor (i.e., data from of sampling on 

successive days) was not met by the Selenium datasets for biological treatment. In fact, the 63 

observations from Allen were collected over 20 months and the 77 observations from Belews 

Creek were collected over 33 months. Furthermore, the magnitude of the correction factor 

(which is a multiplicative factor) quickly approaches 1 as the number of days sampled increases 

(see Appendix B).

Appendix B page 46
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When observations are autocorrelated, the estimated variance from a sample of sequential 

observations can be biased low. This is because the effective sample size in a sequential sample 

of autocorrelated observations is lower than the number of samples

collected. In this case, a correction factor can be used to eliminate the bias (Zieba, 2010).

The correction factor is derived by recognizing that the sample (method of moments) estimate of 

the variance has two components – the underlying variance of individual observations and the 

variance of the mean of observations (Zieba, 2010):

In general, the variance of a mean is defined in terms of the elements of the variance- covariance 

(dispersion) matrix (Kendall and Stuart, 1977):

For uncorrelated observations, the all covariance terms are equal to zero and variance of the 

mean is:

which leads to the standard unbiased estimator for the variance (Cochran, 1977):

However, for autocorrelated observations, the covariance terms are non-zero and must be 

included in the variance of the mean:
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is the effective sample size.

The correction factor is the ratio of the expected value of the sample variance with uncorrelated 

observations to the expected value of the sample variance with autocorrelated observations:

To correct for bias due to serial autocorrelation, the unbiased estimator for the variance is 

multiplied by the adjustment factor (Zieba, 2010):

From equations (6) and (8), it follows that in a sequential sample of autocorrelated observations 

the effective sample size is:
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Comment Response: 

EPA has corrected its autocorrelation adjustment for the final rule. See Appendix A, Essay 

Section 4.1.1.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 20

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA attempted to estimate autocorrelation coefficients for selenium data collected at Allen and 

Belews Creek facilities (Westat 2013). For use in calculating the ELG for selenium, EPA 

calculated the autocorrelation coefficients using baseline substitutions (i.e., 5 ug/l for selenium). 

The data from Allen included 63 observations, of which 59 were either below detection or set to 
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the baseline value of 5 ug/l leaving only 4 actual measurements. The data from Belews Creek 

included 77 observations, of which 51 were either below detection or set to the baseline value. 

With only 4 actual measurements from Allen, EPA calculated an autocorrelation coefficient of 

0.6815. For Belews Creek, EPA calculated a negative autocorrelation coefficient (-0.0997).

Comment Response: 

EPA has corrected its autocorrelation adjustment for the final rule. See Appendix A, Essay 

Section 4.1.1.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 21

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA did not discuss what types of underlying processes would have generated a negative 

autocorrelation for one facility and a positive autocorrelation for the other facility. However, 

EPA accepted both estimates as valid and then averaged the two, claiming an autocorrelation 

coefficient of 0.291 for all facilities with chemical precipitation followed by biological treatment. 

Furthermore, EPA used that same autocorrelation coefficient for nitrate-nitrite.

Comment Response: 

EPA has corrected its calculation of the autocorrelation adjustment for the final rule. See 

Appendix A, Essay Section 4.1.1.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 23

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Because the estimated autocorrelation coefficient is unreliable, the data were not collected on 

successive days, and the number of days sampled is large, application of an autocorrelation 

correction factor is not warranted for calculating the ELGs for selenium and nitrate-nitrite.
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Comment Response: 

EPA disagrees with the comment’s assertion that the autocorrelation adjustment is not warranted 

for the selenium and nitrate-nitrite data for the biological treatment technology for FGD 

wastewater. See Appendix A, Essay Section 4.1.1.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 24

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Remarkably, EPA’s variability factors and ELGs for selenium, which EPA claims include its 

autocorrelation correction factor, are lower than the corresponding variability factors and ELGs 

without the correction factor. The reason is two-fold. First, for calculating the ELGs for 

selenium, EPA abandoned the use of the Delta LogNormal distribution and treated all 

observations (the vast majority of which were below detection or artificially set to the baseline 

value) as if they were from a LogNormal distribution (i.e., all above the detection limit). With 

110 of 140 observations set to constant values and treated as if above the detection limit, the 

calculated variability factors were reduced (see Table 12). Second, due to the number of days 

included in the dataset the (multiplicative) correction factor would have been very close to 1.
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Comment Response: 

EPA has corrected its autocorrelation calculations for the final rule. See Appendix A, Essay 

Section 4.1.1.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 31

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA’s application of a correction for autocorrelated data was not statistically warranted and used 

a highly uncertain estimate of the autocorrelation coefficient. However, the magnitude of the 

correction was relatively small and did not increase the estimated ELGs materially.
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What is notable is that EPA used its claim that an autocorrelation correction was needed as an 

excuse to change its ELG statistical methodology. EPA abandoned the Delta LogNormal model 

and treated the selenium and nitrate-nitrate data using a LogNormal model. In doing so EPA 

assumed all observations - including those below detection and those EPA set to baseline values 

– as if they were above the detection limit. This change in methodology caused the ELGs for 

selenium to decrease.

The purpose of applying a correction for positive autocorrelation is to correct a negative bias in 

the estimated variance. Therefore, the correction factor is intended to increase the variance 

estimate which would cause the ELG to increase. EPA’s concocted method had just the opposite 

effect.

Comment Response: 

EPA has corrected its calculation of the autocorrelation for the final rule. See Appendix A, Essay 

Section 4.1.1.
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31.k. Stats NL – Engineering Review of Limitations for FGD Wastewater

Commenter Name: Chris M. Hobson

Commenter Affiliation: Southern Company

Document Control Number: EPA-HQ-OW-2009-0819-4379-A1

Comment Excerpt Number: 84

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The resulting magnitude of the bias in EPA’s calculated limits for FGD effluent is so large that 

the proposed limits are invalid for their intended purpose. The daily maximum limit is intended 

to be the 99th percentile of daily concentrations from a plant operating with a BAT treatment 

system, and the monthly average limit is intended to be the 95th percentile of monthly average 

concentrations. Accordingly, 1% of daily concentrations would be expected to exceed the daily 

maximum limit and 5% of monthly average concentrations would be expected to exceed the 

monthly average limit. Historical data from the plants EPA identified as operating BAT 

treatment systems (or systems that exceed BAT treatment) demonstrate that EPA’s proposed 

ELGs are invalid.

Table 19 provides a summary of the historical frequency of exceedances analysis for the plants 

EPA identified as operating with BAT or better treatment systems. Historical frequencies of 

exceedance of EPA’s proposed daily maximum limits (DML) range from 0% to 52% and 

average 20.1% (20 times higher than intended). Historical frequencies of exceedance of EPA’s 

proposed monthly average limits (MAL) range from 0% to 100% and average 41.5% (over 8 

times higher than intended). With the exception of selenium at Allen, all cases of 0% exceedance 

were based on data from less than one year.

Table 19: Historical Exceedance Rates At Proposed Model Plants for EPA’s Proposed 

ELGs

Analyte Plant Daily Average 

Concentration 

DML 

Percentage of 

Exceedances 

Monthly 

Average 

Concentration 

MAL 

Percentage of 

Exceedances 

Arsenic (μg/L) Hatfield’s 9.129 52.0% 9.081 96.4%

Arsenic (μg/L) Keystone 4.013 0% 4.025 0%

Arsenic (μg/L) Miami Fort 4.575 0% 4.800 0%

Arsenic (μg/L) Pleasant 

Prairie 6.150 0% 5.350 0%

Mercury (ng/L) Hatfield’s 158.333 11.7% 160.669 29.2%

Mercury (ng/L) Keystone 63.150 0% 84.700 0%

Mercury (ng/L) Miami Fort 196.923 36.7% 121.960 100.0%
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Mercury (ng/L) Pleasant 

Prairie 279.361 41.2% 299.661 88.9%

Nitrate/nitrite-N Allen 4.722 46.7% 5.054 50.0%

Nitrate/nitrite-N Belews Creek 4.361 39.6% 11.931 62.5%

Selenium (μg/L) Allen 5.530 0% 6.147 0%

Selenium (μg/L) Belews Creek 12.701 13.3% 12.136 71.4%

Average: 20.1% 41.5% 

The exceedance rate for the proposed arsenic limit at Hatfield’s Ferry is 96.4%. The exceedance 

rates for the proposed mercury limit at Hatfield’s Ferry and Miami Fort are 29.2% and 100%, 

respectively. Pleasant Prairie, which has a two-staged chemical precipitation treatment system, 

has an exceedance rate of 88.9%. According to EPA, Pleasant Prairie was not used to set ELG 

limits because its treatment system is more advanced than one-stage chemical precipitation 

treatment system proposed as BAT.

The exceedance rates for the proposed nitrate/nitrite-N limits at Allen and Belews Creek are 50% 

and 62.5%, respectively. The exceedance rate for selenium at Belews Creek is 71.4% at Belews 

Creek. But these plants are the same plants and same data that EPA used to set the proposed 

limits. The exceedance frequency analysis demonstrates that EPA’s proposed limits for 

chemical precipitation treatment and for biological treatment are flawed.

Comment Response: 

EPA disagrees with the comment’s interpretation of the percentile basis for limitations as 

explained in Essay Section 2. EPA disagrees with the assertion that the “historical” frequencies 

of exceedance then can be compared to the “intended” probabilities of exceedance. Facilities 

were not required to comply with the limitations prior to the rule, and thus, comparing historical 

to post-rule performance is not appropriate. EPA has promulgated limitations that well-operated, 

maintained and designed facilities are capable of achieving. See Essay Section 4.1.3 and Essay 

Section 5.2. EPA revised the BAT effluent limitations for FGD wastewater subsequent to 

proposal, based on an expanded dataset that includes data EPA obtained following proposal. See 

DCN SE05733 for EPA’s evaluation of the effluent limitations and the data used to calculate the 

limitations.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 7

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

A number of the selenium and mercury measurements in the EPA data sets used for determining 

BAT are above both the daily and monthly numeric limits.

Comment Response: 

See the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 84.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 52

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

5.1 The proposed limits for selenium, arsenic, and mercury in FGD wastewater may not 

be achievable for all power plants employing the proposed BAT.

A review of Belews Creek long-term effluent data for selenium (Figure 5-1) shows instances 

where effluent concentrations exceeded proposed limitations [EPA, 2009]. In its memo dated 

October 12, 2012 entitled Effluent Limitations for FGD Wastewater, Gasification Wastewater, 

and Combustion Residual Leachate for the Proposed Effluent Limitations Guidelines and 

Standards for the Steam Electric Rulemaking [EPA, 2012a], EPA states that selenium results 

from August through October, 2008, reflected less than optimal treatment performance due to 

lack of experience on the part of operating staff or because the sampling period occurred shortly 

after commissioning. However, the system started up in February, 2008, and had been operating 

for a six-month commissioning period [EPA, 2012a] before sampling began. Also, EPA 

excluded the data point of 299 μg/L obtained on 7/4/10, although the Agency stated that Duke 

Energy reported no indication of abnormal events within that sampling time period.

As illustrated in Figure 5-1, some facilities have much higher inlet selenium levels exceeding 

8000 parts-per-billion) than the measured selenium levels at Allen and Belews Creek, upon 

which the proposed selenium limits were based. Thus, these facilities may have even greater 

challenges in meeting the proposed selenium limits.

Comparison of the data collected by EPA during EPA sampling and CWA 308 sampling 

performed by the facilities for the ELG effort [EPA, 2012b–f] shows that there are several 

instances of exceedances of the arsenic limit within this limited data set (Figure 5-2).
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Figure 5-3 presents the data collected by EPA, either as part of their own sampling or as part of 

the CWA 308 sampling performed by the facilities for the ELG effort [EPA, 2012b–f]. EPA 

evaluated the data from Hatfield‘s Ferry, Keystone, and Miami Fort. A review of results from all 
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sites that employ ferric chloride and organosulfide addition shows instances where 

concentrations of mercury exceed the proposed limits.

 

Comment Response: 

EPA disagrees with the comment’s interpretation of the percentile basis of the limitations. See 

the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 84.

EPA disagrees that it has improperly selected or excluded certain data. See Appendix A, Essay 

Section 3.2 and DCN SE05733 for the engineering evaluation of plant conditions and data 

selection. 

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 69

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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6.10 In the context of daily maximum limitation, EPA’s statement that “a welloperated plant should be capable of complying with the effluent limitations at all 

times” is not accurate.

EPA’s statement in Section 13.5.2 of the TDD [EPA, 2013] is inaccurate because the daily 

maximum limitation is set at the 99th percentile of daily measurements. Thus, by definition, the 

effluent level can be expected to exceed the limit 1 in 100 times. For 365 days of once-per-day 

measurements, there will be 3 to 4 exceedances per year just by chance when a plant is in 

control.

Comment Response: 

EPA disagrees with the comment’s interpretation of the percentile basis of the limitations. See 

the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 84.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 70

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

6.11 In the context of monthly average limitation, a well-operated plant will 

exceed the effluent limit in 1 out of every 20 months, on average.

The monthly average limitation is set at the 95th percentile of the distribution of monthly 

averages. Thus, by definition, the effluent level can be expected to exceed the limit in 1 out of 

every 20 months, on average, just by chance when a plant is in control.

Comment Response: 

EPA disagrees with the comment’s interpretation of the percentile basis of the limitations. See 

the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 84.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 122

External Review Flag: No External Review

External Review Incorporated into Response: No
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Comment Excerpt: 

2. The evaluation of success of the limits in the Steam Electric Rulemaking used the same data to 

compute the limits and also to see how well those limits performed (what percent of data 

exceeded limits). This underestimates the proportion of new data (not used to compute limits) 

that exceeds the limits, as new data will be somewhat different than the same data used to 

develop the limits. The impact: more exceedances can be expected than noted here when new 

data are collected at the same plants at other times, and even more so when collected from other 

plants. The limits are less ‘reasonable’ than acknowledged here, due to the method used to 

validate the limits’ performance.

Alternative recommendation: a cross-validation method (where limits are compared to data not 

used to develop the limits) is the standard statistical procedure to give a more accurate picture of 

how often computed limits might be exceeded. There are several ways to perform crossvalidation in the statistical literature, such as a jackknife procedure, and one of them should be 

employed here.

The jacknife or “drop one out” procedure works as follows. If there were 12 measurements, to 

determine how often they would be expected to exceed a limit, one measurement would be set 

aside and the limit computed using the other 11. It would be noted whether or not the set-aside

measurement exceeded the limit just computed. The set-aside measurement is returned to the 12, 

and a different observation set aside. A different limit is then computed with the remaining 11, 

noting whether the newly set-aside observation exceeds the limit or not. This continues as each 

individual measurement is set aside and is compared to the limit computed from the remaining 

11. In this way, the percent of measurements exceeding a limit that they were not used to 

compute can be reported. This provides a more accurate estimate of what percent of 

measurements not yet taken might exceed the limit computed from the original 12.

Comment Response: 

EPA disagrees with the comment’s interpretation of the percentile basis of the limitations See the 

response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 84.

EPA disagrees that the jackknife is an appropriate statistical approach in developing and 

evaluating limitations. See Appendix A, Essay Section 4.1.4.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 123

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 
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3. The daily maximum limitation is an estimate of the 99th percentile of the distribution of daily 

measurements. The 99th percentile is by definition the level that is exceeded 1 in 100 times. For 

365 days of once per day measurements, 3 to 4 exceedances can be expected just by chance each 

year when a process is in control. If 3 measurements are made each day, 9 to 12 of these can be 

expected to exceed the daily maximum limitation. EPA states that “a well-operated plant should 

be capable of complying with the effluent limitations at all times“(Section 13.5.2). Based on the 

definition of the percentile used, this is not the case.

Alternative Recommendation: a plant could be considered out of control if more than 1% of 

daily measurements over a year’s time exceed the 99th percentile, rather than if any one 

measurement during the year exceeds that level. If 3 out of 365 once per day measurements 

exceeded the daily limitation, no action is warranted. It is simply what is expected based on the 

method used to compute the daily maximum limitation. If more than this 1% exceed, the plant is 

not operating as expected and can be considered out of compliance.

Comment Response: 

EPA disagrees with the comment’s interpretation of the percentile basis of the limitations. See 

the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 84.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 124

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

4. The monthly average limitation is an estimate of the 95th percentile of the distribution of the 

monthly averages of the daily measurements. That percentile will be exceeded by definition once 

out of every 20 monthly averages for a plant that is in control. If a single exceedance indicates a 

plant is out of control, by definition all plants will be considered out of control after monitoring 

for about 20 months, or 1.75 years, on average.

Alternative Recommendation: a plant could be considered out of control if a monthly average 

exceeds the limitation more often than an average of once in 20 months, rather than immediately 

when a monthly average exceeds the limit. So if after monitoring for three years, 3 monthly 

averages exceeded the limitation, the plant is out of control. If only 1 or 2 monthly averages 

(fewer than 5%) exceed the limitation, the plant would not be out of control as this the expected 

rate of exceedance resulting from using a 95th percentile.

Comment Response: 
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EPA disagrees with the comment’s interpretation of the percentile basis of the limitations. See 

the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 84.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 125

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

5. The option long-term average is defined as the median of the plant specific long- term 

averages. It is used as the “average performance level ... that a plant with well- designed and 

well-operated model technologies is capable of achieving. “ (page 13- 13 of the Technical 

Development Document). The option long-term average is multiplied by the option variability 

factor to set an effluent limitation. Referring to this limitation, EPA states in the first paragraph 

of page 13-13 “EPA expects that plants will comply with promulgated limitations at all times.” 

Using a median to represent expected plant performance level is inappropriate -- by definition, 

50% of current plants will have an average that is above the median. The option long-term 

average is set at a level that 50% of plants are not now currently achieving.

Alternative Recommendation: in other situations EPA uses the UCL95 to characterize a level 

below which the true population mean likely occurs. If a value is above the UCL95 it does not 

represent an average performance level. Consistent with other EPA regulations estimating an 

average performance level, the UCL95 of the plant specific long-term averages could be used. 

This statistic (the UCL95) is computed by EPA’s freely-available ProUCL software, so is easily 

computed by all. One of the recommended methods for computing the UCL95, one that requires 

little in the way of assumptions, is the BCA bootstrap method. Bootstrapping does not require an 

assumption of a normal distribution, for example. Software is readily available -- ProUCL 

computes the BCA bootstrap.

Comment Response: 

EPA disagrees that the UCL95 is appropriate for setting limitations. The UCL95 is the same as 

the tolerance limitation addressed in Appendix A, Essay Section 4.2.1.

EPA disagrees with the comment’s interpretation of the median. EPA’s use of the median in 

calculating the LTA is addressed in Essay Section 2.4.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)
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Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 132

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

6.3 The same data used to compute limits in the rulemaking were also used to 

determine performance (what percent exceeded limits).

Using the same data to compute limits and to determine performance underestimates the 

proportion of new data (not used to compute limits) that exceeds the limits. Underestimation 

occurs because the new data will be somewhat different than the data used to develop the new 

limits. Thus, more exceedances can be expected than noted in the proposed rule—both when new 

data are collected at the same plants and especially when new data are collected at other plants.

Alternative recommendation: Use a cross-validation method, where limits are compared to data 

not used to develop the limits. There are several ways to perform cross-validation, such as using 

a jackknife procedure (see Appendix C).

Comment Response: 

EPA describes its purpose for comparing the data used as the basis for the limitations to the 

values of the limitations in Appendix A, Essay Section 4.1.3. Also see DCN SE05733.

EPA disagrees with the comment’s interpretation of the percentile basis of the limitations. See 

the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 84 (in Comment 

Code #31.k).

EPA disagrees that cross-validation is necessary in evaluating limitations. See Essay Section 

4.1.4.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 133

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

6.4 Since the option long-term average is defined as the median of the plantspecific long-term averages, 50% of the current plants will have an average that 
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is above the median, leading to a limitation that will also be exceeded more 

frequently by existing data.

Alternative recommendation: Consider using the UCL95 (95th percentile upper confidence 

limit) of the plant-specific average performance levels to set the option long-term average. The 

statistic, UCL95, is easily computed by EPA’s freely available ProUCL software (see Appendix 

C).

Comment Response: 

EPA disagrees that the UCL95 is appropriate for setting limitations. The UCL95 is the same as 

the tolerance limitation addressed in Essay Section 4.2.1.

EPA disagrees with the comment’s interpretation of the long-term average. Using the median of 

the plant-specific long-term averages does not mean that those plants whose long-term average is 

above the median are more likely to exceed the effluent limitation. See Essay Section 2.4, TDD 

Section 13, and DCN SE05733.

Commenter Name: Kim Mireles

Commenter Affiliation: Luminant

Document Control Number: EPA-HQ-OW-2009-0819-4614-A1

Comment Excerpt Number: 21

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Because of the errors noted above, EPA calculated effluent limitations for FGD wastewater are 

overly stringent and not justified. Using EPA's traditional methods of calculating effluent limits, 

a daily maximum limit is typically the 99th percentile of daily concentrations and a monthly 

average limit is typically the 95th percentile of monthly average concentrations. Therefore 1% of 

daily concentrations would be expected to exceed the daily maximum limit, and 5% of monthly 

average concentrations would be expected to exceed the monthly average limit. Instead, with 

EPA's proposed steam electric limits for FGD wastewater, the average frequency of exceeding 

the proposed daily max would be 19.7%, almost 20 times higher than intended. The average 

frequency of exceeding EPA's proposed monthly limits is 40.3%, over eight times higher than 

intended.

Comment Response: 

EPA disagrees with the comment’s interpretation of the percentile basis of the limitations. See 

the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 84.
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Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 123

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The resulting magnitude of the bias in EPA’s calculated limits for FGD effluent is so large that 

the proposed limits are invalid for their intended purpose. The daily maximum limit is intended 

to be the 99th percentile of daily concentrations from a plant operating with a BAT treatment 

system, and the monthly average limit is intended to be the 95th percentile of monthly average 

concentrations. Accordingly, 1% of daily concentrations would be expected to exceed the daily 

maximum limit and 5% of monthly average concentrations would be expected to exceed the 

monthly average limit. Historical data from the model plants EPA identified as operating BAT 

treatment systems (or treatment systems that exceed BAT) demonstrate that EPA’s proposed 

limits are invalid.

Table 18 provides a summary of the historical frequency of exceedances analysis for the plants 

EPA identified as operating with BAT or better treatment systems. Historical frequencies of 

exceedance of EPA’s proposed daily maximum limits (DML) range from 0% to 52% and 

average 20.1% (20 times higher than intended). Historical frequencies of exceedance of EPA’s 

proposed monthly average limits (MAL) range from 0% to 100% and average 41.5% (over 8 

times higher than intended). With the exception of selenium at Allen, all cases of 0% 

exceedance were based on data from less than one year.

Table 18: Historical Exceedance Rates At Proposed Model Plants for EPA’s Proposed 

ELGs

Analyte Plant Daily Average 

Concentration

DML

Percentage of 

Exceedances

Monthly 

Average 

Concentration

MAL 

Percentage of 

Exceedances

Arsenic (μg/L) Hatfield’s Ferry 9.129 52.0% 9.081 96.4%

Arsenic (μg/L) Keystone 4.013 0% 4.025 0%

Arsenic (μg/L) Miami Fort 4.575 0% 4.800 0%

Arsenic (μg/L) Pleasant Prairie 6.150 0% 5.350 0%

Mercury (ng/L) Hatfield’s Ferry 158.333 11.7% 160.669 29.2%

Mercury (ng/L) Keystone 63.150 0% 84.700 0%

Mercury (ng/L) Miami Fort 196.923 36.7% 121.960 100.0%

Mercury (ng/L) Pleasant Prairie 279.361 41.2% 299.661 88.9%
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Analyte Plant Daily Average 

Concentration

DML

Percentage of 

Exceedances

Monthly 

Average 

Concentration

MAL 

Percentage of 

Exceedances

Nitrate/nitrite-N 

(mg/L) Allen 4.722 46.7% 5.054 50.0%

Nitrate/nitrite-N 

(mg/L) Belews Creek 4.361 39.6% 11.931 62.5%

Selenium (μg/L) Allen 5.530 0% 6.147 0%

Selenium (μg/L) Belews Creek 12.701 13.3% 12.136 71.4%

Average: 20.1% 41.5%

The exceedance rate for the proposed arsenic monthly average limitation at Hatfield’s Ferry is 

96.4%. According to EPA, Pleasant Prairie was not used to set ELGs because its treatment 

system is more advanced than the one-stage chemical precipitation treatment system proposed as 

BAT. Yet Pleasant Prairie cannot even meet the proposed BAT limitations derived by 

EPA. The figure below graphs Pleasant Prairie’s arsenic self-monitoring data and EPA’s 

sampling data and shows that Pleasant Prairie cannot consistently meet either the daily maximum 

limitation or the monthly average limitation. The details of the Pleasant Prairie analysis are 

included in WE Energies’ comments on the proposed rule.
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The exceedance rates for the proposed monthly average mercury limitation at Hatfield’s Ferry 

and Miami Fort are 29.2% and 100%, respectively. Pleasant Prairie, which has a two-stage 

chemical precipitation treatment system, has a mercury monthly average limitation exceedance 

rate of 88.9%, based on the EPA sampling data and a portion of Pleasant Prairie’s selfmonitoring data.

WE Energies has evaluated the proposed mercury limitations in light of its full set of Pleasant 

Prairie self-monitoring data and has concluded that Pleasant Prairie cannot consistently meet 

either proposed monthly average or daily maximum limitations, as illustrated in the figure 

below. This analysis is described in further detail in WE Energies’ comments on the proposal.

The exceedance rates for the proposed nitrate/nitrite-N monthly average limitations at Allen and 

Belews Creek are 50% and 62.5%, respectively. The exceedance rate for selenium monthly 

average limitation at Belews Creek is 71.4%. These exceedance rates were calculated using the 

same plants and same data that EPA used to set the proposed limits. The exceedance frequency 

analysis thus demonstrates that EPA’s proposed limits for chemical precipitation treatment and 

for biological treatment are flawed.

Comment Response: 

EPA disagrees with the comment’s interpretation of the percentile basis of the limitations. See 

the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 84.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG
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Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 12

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Combined available data (i.e., EPA sampling, CWA 308 sampling and self- monitoring data) 

from Allen and Belews Creek were used to assess the performance of EPA’s proposed ELGs for 

biological treatment of nitrate-nitrite and selenium.

Historical frequencies of exceedance of EPA’s proposed daily maximum limits range from 0% to 

52% and average 20.1% (see Table 13). With the exception of selenium at the Allen facility, all 

cases of 0% exceedance were based on data from less than a year.

Historical frequencies of exceedance of EPA’s proposed monthly average limits range from 0% 

to 100% and average 41.5% (see Table 14). Again, with the exception of selenium at the Allen 

facility, all cases of 0% exceedance were based on data from less than a year. Only months with 

at least 4 days of sampling were included in the assessment of monthly average limitations.
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Comment Response: 

EPA disagrees with the comment’s interpretation of the percentile basis of the limitations. See 

the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 84.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 13

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

For EPA’s proposed daily maximum limit, the average historical exceedance rate for model 

facilities (plus one facility with a treatment system that exceeds BAT) is over 20%, although the 

intended exceedance rate is only 1%. Similarly for EPA’s proposed monthly average limit, the 

historical exceedance rate for model facilities is over 40%, although the intended exceedance rate 

is only 5%. These facts demonstrate that EPA’s proposed limits do not satisfy the fundamental 

requirements of ELGs.

Reasons for the discrepancies between the intended exceedance rates and the historical 

exceedance rates can be found in the EPA’s selection and censoring of data, and in EPA’s 

selection of statistical methods. EPA’s selections for implementing its general ELG methodology 
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systematically reduced the calculated ELGs. The calculated ELGs were reduced to the point that 

they are not valid for their intended purpose.

Comment Response: 

EPA disagrees with the comment’s interpretation of the percentile basis of the limitations. See 

the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 84.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 17

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The resulting magnitude of bias in EPA’s calculated ELGs for FGD effluent is so large that the 

proposed ELGs are invalid for their intended purpose. The daily maximum limit is intended to be 

the 99th percentile of daily concentrations from a facility operating with a BAT treatment 

system, and the monthly average limit is intended to be the 95th percentile of monthly average 

concentrations. Accordingly, 1% of daily concentrations would be expected to exceed the daily 

maximum limit and 5% of monthly average concentrations would be expected to exceed the 

monthly average limit. Historical data from the facilities EPA identified as operating with BAT 

treatment systems (or systems that exceed BAT treatment) demonstrate that EPA’s proposed 

ELGs are invalid.

For facilities EPA identified as operating with BAT or better treatment systems, the average 

(over facilities and pollutants) frequency of exceedance of EPA’s proposed daily maximum 

limits is 20.1% - 20 times higher than intended. The average (over facilities and pollutants) 

frequency of exceedance of EPA’s proposed monthly limits is 41.5% - over 8 times higher than 

intended.

Comment Response: 

EPA disagrees with the comment’s interpretation of the percentile basis of the limitations. See 

the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 84.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655-A18

Comment Excerpt Number: 26
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External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The available historical data from EPA’s selected facilities operating BAT treatment systems can 

be used to assess the performance of EPA’s calculated ELGs. Specifically, historical daily 

concentrations and monthly average concentrations can be compared to EPA’s proposed limits to 

characterize the historical frequency of exceedances. The historical frequencies of exceedance 

then can be compared to the intended probabilities of exceedance.

The daily maximum limit is intended to be the 99th percentile of daily concentrations from a 

facility operating with a BAT treatment system, and the monthly average limit is intended to be 

the 95th percentile of monthly average concentrations. Accordingly, 1% of daily concentrations 

would be expected to exceed the daily maximum limit and 5% of monthly average 

concentrations would be expected to exceed the monthly average limit.

Comment Response: 

EPA disagrees with the comment’s interpretation of the percentile basis of the limitations. See 

the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 84.

Commenter Name: Thomas Cmar

Commenter Affiliation: Earthjustice, et al.

Document Control Number: EPA-HQ-OW-2009-0819-4684-A1

Comment Excerpt Number: 84

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

a. EPA’s proposed selenium limits can be met by the biological treatment system under a 

range of influent conditions.

Based on Dr. Jenkins’ analysis of the data from the Mountaineer plant, “the ABMet® unit 

consistently produced an effluent with a total Se level below 7.2 ppb and with many values in 

the 1-2 ppb range (Figures 5 and 6) making it fully compliant with the EPA’s proposed daily 

maximum and monthly average total Se limitations.”328 As Dr. Jenkins concludes, once the 

ABMet system at the Allen plant was fully acclimated, it was able to handle significant 

fluctuations in the influent total selenium levels, and still meet the proposed selenium effluent 

limits.329

Data from all three plants show that meeting the selenium limits set by EPA can be achieved, 

after an adequate start up and commissioning period, so long as tight process control is 
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maintained, there is adequate sensing and control capabilities, and the system “provide[s] 

adequate equalization capacity within and/or between the first-stage chemical precipitation 

process and the biological treatment stage.”330 Monitoring of the selenium levels at the effluent 

from the chemical precipitation stage is also critical.331

b. EPA’s mercury limits can be met by the biological system following only hydroxide 

precipitation.

EPA’s mercury limits for the biological treatment option are well supported by the record. 

Because those limits are based on the performance of the chemical precipitation system, and do 

not account for additional removals of mercury in the biological system, even lower mercury 

limits could be established.

EPA acknowledged this additional metals removal in the biological treatment system,332 finding 

that “the biological treatment stage provides pollutant removals for arsenic and mercury (and 

other pollutants of concern with similar removal mechanisms) in addition to the pollutant 

removals that occur in the chemical precipitation stage of the biological treatment technology 

option . . . . Thus, plants employing and optimally operating all components of the biological 

treatment technology option (including adding organosulfide to achieve sulfide precipitation) 

should achieve pollutant removals for arsenic and mercury (and other pollutants with 

similar removal mechanisms) that are equal to or even greater than the removals based on 

chemical precipitation technology."333

Dr. Jenkins’ analysis confirms EPA’s findings for mercury:334 “in all of the ABMet® plants 

evaluated the biological stage of the “Chemical Precipitation and Biological Treatment” 

provided additional Hg removal over that obtained by the chemical precipitation step 

(Figures 12-14) both when the precipitation step employed hydroxide only and when it employed 

hydroxide plus polysulfide.”335

Dr. Jenkins concludes that the “anaerobic biological system effluent total Hg concentration 

seems to be proportional to the biological system influent total Hg over an influent total Hg 

range from approximately 1000 ppt to approximately 20 ppt.”336 Thus, if the effluent from the 

chemical treatment system is compliant with the limits EPA set for mercury based on that 

technology (242 ppt daily maximum and 119 ppt monthly average), then even lower levels 

would be expected in the effluent.

328 Jenkins FGD Report, Appendix C, at 9.

329 Id. at 8.

330 Id. at 10. EPA’s exclusion of data during start-up, commissioning, and upsets for the Allen 

plant was justified. Dr. Jenkins concludes that based on the Allen system’s ability to handle 

subsequent spikes in influent selenium, it was justified for EPA to omit earlier selenium 
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exceedences that corresponded to influent selenium spikes, on the basis that the system was still 

in a start-up or commissioning phase. Id. at 8

331 Id.

332 78 Fed. Reg. at 34,473.

333 TDD at 13-26.

334 Dr. Jenkins found that the presence of non-detects in both the influent to and effluent from the 

biological treatment system prevented a similar analysis regarding arsenic.

335 Jenkins FGD Report, Appendix C, at 11.

336 Id. at 12.

Comment Response: 

EPA agrees with the comment that properly operated, maintained, and designed facilities are 

capable of complying with the limitations. See Appendix A, Essay Section 5.2.
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32. Analytical Methods

Commenter Name: Doris Cooksey

Commenter Affiliation: City Public Service of San Antonio (CPS Energy)

Document Control Number: EPA-HQ-OW-2009-0819-4283-A1

Comment Excerpt Number: 18

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Several of the FGD 

limits are set at laboratory detection limits and if there is any matrix interference from 

the FGD wastewater, labs will not be able to produce viable results. Per EPRI, EPA used 'a 

synthetic FGD water at about the 50th percentile of TDS (17,000 mg/L), and labs typically 

diluted the sample by 20 times to avoid analytical issues'. Dilutions raise the method 

detection limit therefore the expected result is that labs may not be able to meet the extremely 

low detection limits proposed. FGD systems that run at higher percentiles or concentrations 

ofTDS will have even more difficulty finding a lab that can meet the analytical standards 

proposed.

Comment Response: 

EPA disagrees with the commenter’s assertion that laboratories “will not be able to produce 

viable results” and that they “may not be able to meet the extremely low detection limits” needed 

for plants to demonstrate compliance with the effluent limitations for FGD wastewater that are 

set equal to the detection limit. The limits at issue are the limits for new sources (and the 

voluntary incentives program (both of which are based on chemical precipitation and 

evaporation.) The commenter states that the reason laboratories may not be able to do so is 

because FGD wastewater contains high concentrations of TDS and that laboratories may need to 

dilute the wastewater sample to avoid analytical issues. As support for that position the 

commenter states in certain analyses and a laboratory participating in an EPA study diluted FGD 

wastewater containing 17,000 mg/L TDS, and also asserted that FGD systems that operate at 

even higher concentrations of TDS “will have even more difficulty finding a lab that can meet 

the analytical standards proposed.” However, the commenter overlooks the fact that plants 

subject to these new source performance standards or effluent limitations under the voluntary 

program (which are based on the detection limit2) will have very clean wastewater because the 

other effluent limitations that would apply to their discharge include TDS limitations of 50 mg/L 

daily maximum and 24 mg/L monthly average; and as a result, the laboratories will not 

experience analytical issues that would prevent them from measuring pollutant concentrations at 

 

2 More precisely, the effluent limitations were developed based on the sample-specific quantitation limits for the 

data. The “detection limit” effluent limitations the commenter refers to are the FGD wastewater NSPS/PSNS daily 

maximum limitations for arsenic (4 up/L) and selenium (5 up/L). The discharge is also subject to effluent limitations 

for mercury (39 ng/L daily maximum; 24 ng/L monthly average) and TDS (50 mg/L daily maximum; 24 mg/L 

monthly average). These effluent limitations also apply to plants that adopt the limitations under the BAT voluntary 

incentives program for existing sources.
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the levels needed for plants to demonstrate compliance. The new source performance standards 

and effluent limitations under the voluntary incentives program are based on plants employing 

advanced treatment technologies to treat their FGD wastewater, including chemical precipitation, 

softening, and,vapor-compression evaporation. As part of this treatment process, the wastewater 

is evaporated, leaving behind dissolved constituents that comprise the majority of the TDS 

present in untreated FGD wastewater. It is the condensed vapor from the evaporation process 

that is the treated FGD wastewater which plants discharge and that the laboratories will be 

analyzing, and the pollutants that remain in the wastewater following treatment will not be 

present at concentrations that would interfere with the laboratory being able to measure to the 

levels needed. Wastewater samples collected by EPA for this treatment technology showed that 

the TDS concentrations in the treated FGD wastewater averaged approximately 15 mg/L (see the 

long-term average in DCN SE05733). Although plants are not required to use the technologies 

that serve as the basis for the effluent limitations, they would still be required to demonstrate 

compliance with the TDS effluent limitations, thus the laboratory analyses for arsenic and 

selenium would not be affected by the TDS concentrations in the sample.

Also see responses to EPA-HQ-OW-2009-0819-4305-A3, Excerpt Number 67, and EPA-HQOW-2009-0819-4499-A1, Excerpt Number 89.

Commenter Name: Cari Boyce

Commenter Affiliation: Duke Energy

Document Control Number: EPA-HQ-OW-2009-0819-4305-A3

Comment Excerpt Number: 67

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Dilution of Samples are Needed to Protect Sensitive Lab Equipment and Address Matrix 

Interferences

The limits proposed are set at 8 ug/L (daily maximum) and 6 ug/L (monthly average) for arsenic 

and 16 ug/L (daily maximum) and 10 ug/L (monthly average) for selenium. However, due to the 

higher levels of Total Dissolved Solids (TDS) found in FGD wastewater, analytical methods 

would normally require higher dilution ratios to protect sensitive laboratory equipment. Increases 

in the dilution ratio result in increased reporting limits, most likely higher than the proposed 

effluent guideline limits for these constituents.

There is not a typical sample composition for wastewater from FGD systems. Two treatment 

systems run side by side can have completely different characteristics and TDS in FGD waters 

has been as high as 80,000 ppm. Dilution is necessary to prevent physical interferences from 

ionization suppression, nebulizer clogging, and reduction of ion transmission due to deposits on 

the extraction and/or skimmer cones. Target TDS in samples is between 1,500 to 2,000 ppm. The 

use of aerosol dilution systems extends the amount of TDS that can be in the sample by about 
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10%, but this method does not remove the need to still physically dilute the sample in order to 

bring the TDS into a reasonable concentration range. High concentrations of matrix elements 

(Ca, Mg, Cl, B, SO4, etc.) or other interfering components can also require more dilution in 

order to meet the method quality control requirements. This is particularly applicable for 

MS/MSD (matrix spike / matrix spike duplicate) recoveries and the requirement that the internal 

standards recovery be between 60 and 125%.

Without sufficient dilution to protect the analytical equipment and to dilute potential matrix 

interferences, even with the use of a modified method 200.8, repeatable and reliable achievement 

of sample recoveries within specified limits is uncertain. Most commercial laboratories do not 

have the economic flexibility to run multiple dilution ratios on a single sample to ensure an 

optimum analysis.

Additionally, the flow minimization requirement included in the Proposed Rule results in an 

increase in the FGD absorber chloride concentrations, TDS concentrations and recycle rate. This 

provision not only increases the need for additional dilution to protect instrumentation, but also 

increases the reporting limit for the sample.

It should also be noted that the Inductively Coupled Plasma – Mass Spectrometry (ICP-MS) 

vendor manuals and Method 200.8 (Rev 5.4, 1994, Section 4.1.4) recommend keeping the 

sample TDS concentration to less than 2,000 mg/l, which results in a greater than 13 to 1 dilution 

ratio for the average FGD wastewater sample of 28,600 mg/l TDS20. This dilution ratio would 

result in a reporting limit of greater than the proposed monthly average concentrations for 

selenium and arsenic. The same table in the TDD references an average chloride concentration of 

7,740 mg/l, which is less than 20% of the design chloride operating level for some of our units. 

In fact, some of our units burning Illinois Basin coal have FGD wastewater TDS concentrations 

in excess of 80,000 mg/l, which would result in a potential dilution ratio of 40 to 1, with a 

corresponding increase in the reporting limits, well above those proposed for selenium and 

arsenic. Higher TDS concentrations also tend to have greater interferences, making matrix 

spike/recovery percentages consistently outside of the allowable range for EPA Method 200.8.

In the summer of 2012, EPA commissioned a method detection limit (MDL) study for synthetic 

FGD wastewater and the results were published in October, 201221. The study used a synthetic 

matrix that was originally 12,000 ppm TDS, which is on the very low end of TDS seen in actual 

FGD samples. The participating laboratories were instructed to spike the solution and then dilute 

by a factor of 2. It appears that EPA’s intent was for the participants to use a solution of 6,000 

ppm TDS. The participants in the study diluted the matrix anywhere from 4 to 10 times prior to 

analysis, which means that the lab instrument saw an effective TDS of 1,200 to 6,000 ppm. One 

of the reports, from Test America, specifically states that the matrix was diluted according to 

routine procedure to keep the matrix from overwhelming the instrument. Southwest Research 

also diluted the sample to avoid interference from the FGD matrix on selenium. The final ML 

(minimum level) values recommended by the report are 2 ppb for arsenic and 5 ppb for 

selenium. However, actual FDG wastewater would normally require higher dilution ratios than 

those listed in EPA’s MDL study which would result in raising the reporting limits, most likely 

higher than the proposed effluent guideline limits for these constituents.
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EPRI also conducted a similar MDL study in 2012. In this study, EPRI used a synthetic FGD 

matrix with 17,000 ppm TDS, which is a closer representation of the mean TDS concentration 

for FDG wastewater (around the 50% percentile). The labs in EPRI’s study typically had to 

dilute the sample up to 20 times to avoid analytical issues. Whether a laboratory uses normal 

dilution or gas dilution, or some combination of both, the effective detection limit for the sample 

is raised. Additionally, of five laboratories commissioned by the EPA that participated in their 

MDL/ML study, only two of these laboratories are known to routinely analyze FGD wastewater. 

In comparison to EPRI’s results, it does not appear that EPA’s MDL study is appropriate and it 

should not be used for any purpose related to this rulemaking.

Commercial labs, also, do not typically have equipment dedicated to analyze FGD wastewater. 

The equipment they use could necessitate using dilution ratios as high as 500 to 1 to prevent 

fouling and scaling of the ICP plasma disks, which results in equipment contamination. Labs 

have reported having to disassemble their equipment and replace components prior to returning 

the lab equipment back to service due to this type of contamination. So, these high dilution ratios 

are critical to maintaining their reliability and sample integrity.

Results from Duke Energy’s Round Robin Testing

Duke Energy recently conducted a round robin analysis of FGD wastewater to determine the 

repeatability and reporting limits for arsenic, mercury, selenium and nitrate/nitrite among four 

different commercial laboratories. Samples were pulled from the FGD wastewater treatment 

system effluent of five different Duke Energy stations. The sampling included effluent from a 

chemical precipitation system, a chemical precipitation plus biological treatment system and 

settling basin plus biological treatment systems. The bulk samples were sent to the Duke Energy 

Environmental Lab where they were split into four individual samples. Three of these samples 

were sent to commercial labs for analysis, while the fourth sample was analyzed internally at 

Duke Energy’s Environmental Lab. The results of the round robin sampling event are shown in 

Tables 1-13 to 1-16 below.

As is demonstrated from this exercise, various labs do not all follow the exact same procedures. 

Some labs need to dilute the samples more than other labs, which results in higher dilution 

factors. As mentioned earlier, higher dilution factors subsequently result in overall higher 

reporting limits. The tables below show that the reporting limits among these four laboratories 

ranged from 1 ppb to 500 ppb for arsenic and 1 ppb to 500 ppb for selenium. While all of the 

differences in procedures between these four labs is unknown, for at least two of the laboratories, 

the reporting limits were determined in Milli-Q water following the 40 CFR 136 MDL/ML 

procedure, whereas, the Standard Operating Procedures (SOPs) published by EPA recommend 

that MDLs and RLs be determined using a synthetic FGD mixture.

Each of the labs selected for this evaluation are experienced with the analysis of FGD 

wastewater, and yet there was still a significant disparity in not only the reported results, but also 

the reporting limits. Given the lack of agreement between labs on the results from FGD 

wastewater analysis, it is critical that any BAT limits promulgated account for these disparities.

Table 1-13. Laboratory Comparison for Arsenic in FGD Matrix
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Arsenic (ug/L) - EPA 200.8

Lab A Dilution 

Factor Lab B Dilution Factor Lab C Dilution Factor Lab D Dilution Factor

Station 1 < 5.0 5 < 5.0 5 14 5 < 500 100

Station 2 < 5.0 5 < 5.0 5 20 2 < 250 50

Station 3 < 5.0 5 3.7 1 18 2 < 100 100

Station 4 < 5.0 5 1.6 1 27 2 < 250 50

Station 5 < 5.0 5 < 5.0 5 46 2 < 500 100

Table 1-14. Laboratory Comparison for Selenium in FGD Matrix

Selenium (ug/L) - EPA 200.8

Lab A Dilution 

Factor Lab B Dilution Factor Lab C Dilution Factor Lab D Dilution Factor

Station 1 397 5 357 5 460 2 < 500 100

Station 2 < 5.0 5 < 5.0 5 2.9 2 < 250 50

Station 3 38.8 5 28.2 2 37 2 < 100 100

Station 4 < 5.0 5 2.2 1 2.9 2 < 250 50

Station 5 1014 5 881 5 1300 2 980 100

Table 1-15. Laboratory Comparison for Mercury in FGD Matrix

Mercury (ng/L) – EPA 1631

Lab A Dilution 

Factor Lab B Dilution Factor Lab C Dilution Factor Lab D Dilution Factor

Station 1 161 5 140 1 95.2 10 110 10

Station 2 0.76 5 1.73 1 0.85 1 0.56 1

Station 3 4,590 99 4,240 100 3,880 500 2,800 1,000

Station 4 14.3 5 13.2 1 8.56 1 8 1

Station 5 113 5 10.4 1 93.3 10 93 10

Table 1-16. Laboratory Comparison for Nitrate/Nitrite-N in FGD Matrix

Nitrate/Nitrite-N (mg-N/L) - EPA 353.2

Lab A Dilution 

Factor Lab B Dilution Factor Lab C Dilution Factor Lab D Dilution Factor

Station 1 176 200 176 200 160 200 180 25

Station 2 < 0.01 1 < 0.02 1 0.43 1 < 0.10 1

Station 3 < 0.01 1 0.02 1 0.085 1 < 0.10 1

Station 4 < 0.01 1 <0.02 1 0.042 1 < 0.10 1
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Station 5 36 50 35.8 15 28 100 38 10

20 TDD Section 6.1, Table 6-3, pages 6-5 and 6-6 [EPA-921-R-13-002].

21 USEPA. Results of the ICP/MS Collision Cell Method Detection Limit Studies in the Synthetic 

Flue Gas Desulfuriztion Matrix. EPA-HQ-OW-2009-0819-2116. October 18, 2012.

Comment Response: 

EPA recognizes that, in some cases, samples with high total dissolved solids (TDS) may require 

some level of dilution in order to be successfully analyzed by ICP/MS procedures, including 

those that utilize the collision cell or dynamic reaction cell instrumentation. However, EPA 

notes that the “target TDS” of 1,500 to 2,000 ppm cited by the commenter and the reference to 

information in EPA Method 200.8 are based on much older ICP/MS instrumentation (Method 

200.8, Revision 5.4 from 1994 cites a figure of 0.2% v/v, from a 1986 reference and which 

equates to 2,000 ppm TDS). More modern ICP/MS instruments do not have the same physical 

limitations with regard to TDS as were noted in 1986 and many instrument manufacturers 

provide “high solids” interface equipment that is expressly designed to address the TDS 

concern. EPA’s record includes information about analyses by commercial laboratories that 

routinely use such interfaces. Furthermore, the analytical results for EPA’s sampling data, the 

CWA 308 sampling data, and self-monitoring data submitted by power companies demonstrate 

that analytical laboratories, both commercial and company-owned certified laboratories, are able 

to measure the regulated pollutants in FGD wastewater at the levels needed to show compliance 

with the effluent limitations. 3(The same is true for gasification wastewater, where EPA’s data 

show that laboratories results are low enough to demonstrate compliance with the effluent 

limitations.)

In addition to asserting generally that laboratories will need to dilute samples to protect 

laboratory equipment (which EPA addresses in the preceding paragraph), the commenter states 

that TDS in FGD waters has been as high as 80,000 ppm, and specifically points to their own 

plants stating that “some of our units burning Illinois Basin coal have FGD wastewater TDS 

concentrations in excess of 80,000 mg/l.” However, the commenter fails to also mention that 

plants that do not discharge their FGD wastewater will not need to send the wastewater to 

laboratories for analysis. This is because the effluent limitations are applicable to discharges of 

FGD wastewater; those wet-scrubbed plants that generate but do not discharge their FGD 

wastewater would not have to do such compliance monitoring for these effluent limitations. 

EPA’s record indicates that many facilities already do not discharge their FGD wastewater. EPA 

reviewed Steam Electric Survey data, which was includes data from a census of every coal-fired 

and petroleum coke-fired power plant in the U.S., and found that the highest reported chloride 

concentration for plants that actually discharge the FGD wastewater is 25,000 ppm. The ICR 

includes data for only two wet-scrubbed plants with chlorides higher than 25,000 ppm and 

 

3 EPA notes that the BAT effluent limitations in the final rule are higher than at proposal. See the preamble and 

regulation for the final rule. Even if the effluent limitations had remained at the proposed level, the data in the record 

show that laboratories are able to measure pollutants at concentrations necessary for plants to show they are in 

compliance.
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neither of these plants discharge the FGD wastewater. The data in the record for FGD 

wastewater shows that, in general, TDS concentrations in FGD wastewater are typically double 

the chloride concentration. Using that rule of thumb, the TDS at the discharging plants would be 

no higher than approximately 50,000 ppm. The data used to calculate the effluent limitations 

includes data from plants with concentrations of approximately 30,000 ppm TDS, which the 

laboratories were able to analyze without difficulty. Given the data in the record showing 

laboratories have been able to analyze the regulated pollutants at low levels in FGD wastewater 

containing high concentrations of TDS, EPA has no reason to expect that laboratories would not 

be able to measure the pollutants at the necessary level even for FGD discharges with higher 

concentrations of TDS. See the comment response elsewhere in Code 32, showing that 

laboratories could measure arsenic concentrations as low as 0.2 ug/L and selenium at 0.5 

ug/L. These values are 10 times lower than the ML calculated for the MDL study, which was 

based on the maximum ML for the participating laboratories. Even if TDS levels of 50,000 were 

higher than the laboratory instrumentation could accommodate, a 2X dilution would bring the 

TDS down to 25,000 mg/L, lower than the approximately 30,000 mg/L TDS wastewater and 

industry have demonstrated they can analyze and still achieve quantitation limits of at least as 

low as 2 ug/L arsenic and 5 ug/L selenium. This demonstrates that plants will be able to find 

laboratories that can measure pollutant concentrations for them to show compliance with their 

effluent limitations.

EPA disagrees with the statement that most commercial laboratories lack economic flexibility to 

run multiple sample dilutions. Rather, as in any compliance monitoring scenario, it is incumbent 

upon the discharger that is contracting out the analyses to develop a contractual mechanism that 

generates the required data, even if that means explicitly addressing the need for multiple 

dilutions and developing an equitable approach to paying for such results. In short, most 

commercial laboratories will do what they are paid to do when asked in an appropriate 

manner. The fact that FGD wastewater analyses are not as simple as analyses of samples from 

some other industries is not an impediment to the provision of useful compliance monitoring 

results. The commenter states that laboratories do not have equipment dedicated to analyze FGD 

wastewater; however, there is no need for laboratories to dedicate instrumentation for the sole 

purpose of analyzing FGD wastewater. EPA included costs for laboratory analyses of the 

compliance monitoring samples and these costs reflect the use of collision cell or dynamic 

reaction cell equipment when performing ICP/MS analyses of FGD wastewater samples. Should 

a laboratory find that there is sufficient demand for its analytical services that it chooses to 

dedicate certain equipment at the facility for the sole purpose of analyzing FGD wastewater it 

could do so, but it is not necessary and laboratories routinely analyze wastewaters generated 

from a variety of industrial processes on a daily basis because they have many clients that are 

required to report pollutant concentration data for NPDES compliance monitoring purposes. In 

fact, a number of power plants already have either effluent limitations or monitoring 

requirements for FGD wastewater included in their NPDES permits; thus, many commercial 

laboratories already have experience analyzing FGD wastewater samples with their existing 

instrumentation.

EPA does not support as fact the proposition that commercial laboratories may not be able to 

dedicate ICP/MS equipment to FGD wastewater analyses, nor should that be necessary. At the 

same time, however, the ELGs establish numeric effluent limitations and standards for FGD 
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wastewater and gasification wastewater (and combustion residual leachate from new sources). 

These effluent limits apply to discharges from approximately 70 power plants (accounting for the 

effects of the CCR rule and CPP; approximately 90 plants if not taking the CPP into account). In 

addition, a number of power plants, such as many of those discharging to the Ohio River and 

Great Lakes, or located in states such as North Carolina, Maryland, and Pennsylvania, already 

have monitoring requirements for FGD wastewater included in their NPDES permits. Because of 

this, there is already a substantial market for analyzing FGD wastewater and that market will 

grow as the ELGs are implemented. EPA anticipates that commercial laboratories will respond

accordingly, not only in terms of equipping their facilities with sufficient numbers of ICP/MS 

instruments capable of performing such analyses, but also in terms of establishing dilution 

schemes and pricing options that are capable of generating data of the appropriate quality to meet 

the monitoring requirements. Since the new ELG requirements do not begin to apply November 

1, 2018 at the earliest, labs will have ample time to prepare for this growing demand for analysis 

of FGD wastewater.

With regard to flow minimization, as described elsewhere in the Comment Response Document, 

EPA notes that although EPA anticipates that some plants may implement some degree of flow 

minimization to reduce the cost of FGD wastewater treatment to meet the ELGs, the rule does 

not require them to do so. For those plants that EPA’s analyses assume would implement flow 

minimization, the resulting TDS concentrations in their wastewater are not at levels that would 

result in analytical interferences that prevent laboratories from measuring pollutant 

concentrations at the levels necessary to demonstrate compliance with the effluent limitations. 

For the plants where EPA included flow minimization in the cost estimates for the ELG, the 

highest chloride concentration that would result from flow minimization at these three plants is 

10,000 ppm. The data in the record for FGD wastewater shows that, in general, TDS 

concentrations in FGD wastewater are typically double the chloride concentration. Using that 

rule of thumb, the TDS at these plants would be no higher than approximately 20,000 ppm. The 

data used to calculate the effluent limitations includes data from plants with much higher 

concentrations of TDS, which the laboratories were able to analyze without difficulty.

EPA disagrees with the commenter’s contention that the results of EPA’s MDL study “should 

not be used for any purpose related to this rulemaking.” The fact that only two of the five 

laboratories tasked by EPA to participate in the MDL study had routine experience with FGD

wastewater analyses does not make EPA’s MDL study invalid. because EPA did not design the 

study to involve only laboratories with FGD experience. Instead, EPA used laboratories that had 

experience analyzing industrial wastewater samples using ICP/MS analytical methods in 

conjunction with collision cell instrumentation. Had EPA used only laboratories with FGD 

experience, EPA anticipates that the results of the study may well have demonstrated even better 

method sensitivity.

The results of the commenter’s round robin study are difficult to interpret, given the lack of 

specific information provided. The commenter describes the participants as “four different 

commercial laboratories” and then states that “[t]hree of these samples were sent to commercial 

labs for analysis, while the fourth sample was analyzed internally ...” indicating that the fourth 

participant was not a commercial laboratory, but in fact the laboratory responsible for splitting 

the original bulk samples for distribution.
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The fact that “various labs do not all follow the exact same procedures” may be as much a 

function of poor study design and poor contracting processes as it is of the alleged shortcomings 

of EPA’s studies. That “all of the differences in procedures between these four labs is unknown” 

coupled with the commenter’s observation that two of the laboratories determined their MDLs in 

reagent (e.g., Milli-Q) water and two used the synthetic FGD matrix further erodes the credibility 

of the results because it indicates the laboratories did not receive clear guidance about how to 

conduct the study. Conducting a study without a clearly defined structure and protocols, and then 

using the results from what appears to be a mix of independent efforts to draw conclusions about 

the labs’ inability to reach what should be a clearly defined objective, is not indicative of sound 

scientific procedures. What the results for arsenic and selenium do demonstrate is that absent 

any clear instructions or guidance, different laboratories will respond to analysis requests 

differently. The tables do not provide any clear indication of either the MDLs or minimum 

levels (MLs) employed by each laboratory, and EPA can only infer that values preceded by the 

“less than” symbol (<) may be one or the other type of limit, and since they are all round 

numbers, probably MLs rather than MDLs. For example, the differences between the arsenic 

results from Labs A and B are minimal, in that all of the arsenic results are below 5 μg/L, with 

two results from Lab B provided as specific values of 3.7 and 1.6, which are below 5.0. Without 

any other information, including the associated quality control results from these analyses, EPA 

cannot adequately judge the arsenic results from Lab C. However, EPA notes that one purpose of 

the use of the collision cell procedure is to avoid polyatomic spectral interferences that can result 

in high bias or false positives in the determination of arsenic by ICP/MS. The results from Lab 

D suggest that they were given limited instructions as to the intent of the study and therefore, 

their results are of limited use.

Commenter Name: Chris M. Hobson

Commenter Affiliation: Southern Company

Document Control Number: EPA-HQ-OW-2009-0819-4379-A1

Comment Excerpt Number: 66

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Second, EPA should not have used cyanide data for any purpose, including calculating TWPEs 

and TWPE removals because the data are invalid due to potential analytical interferences with 

the analytical method(s) as well as the chemical (sodium hydroxide) used to preserve the 

samples.

Comment Response: 

EPA is not establishing effluent limitations for cyanide in the final rule. Although cyanide 

analyses can be challenging, upon review of the laboratory reports EPA concluded that the data 

were acceptable for the purposes the data were used for in the steam electric rulemaking; namely 

to estimate the baseline pollutant loadings and removals associated with the ELGs. EPA notes 
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that cyanide removals represent a small portion of the total pounds of pollutants removed by the 

ELGs (see DCN SE05847). Since EPA estimated the pollutant removals for cyanide they were 

included in the total pollutant removal estimates for the rulemaking. As a result, cyanide removal 

are included in the TWPE calculation. EPA notes that its loadings analysis and pollutant 

reduction estimates, which in turn feed into cost-effectiveness analyses, technically are not 

required for BAT. See response to DCN EPA-HQ-OW-2009-0819-4499-A1, Excerpt Number 

72. For the role of cost-effectiveness in EPA's decisions for the final rule, see response to DCN 

EPA-HQ-OW-2009-0819-4655, Excerpt Number 27 in Comment Code 6.h.

Commenter Name: Chris M. Hobson

Commenter Affiliation: Southern Company

Document Control Number: EPA-HQ-OW-2009-0819-4379-A1

Comment Excerpt Number: 69

External Review Flag: Analytical

External Review Incorporated into Response: No

Comment Excerpt: 

EPA Used Invalid Cyanide Data in Calculating TWPEs

All of EPA’s cyanide data are invalid because of the potential interferences with the analytical 

method as well as the chemical (sodium hydroxide) used to preserve the samples. EPA should 

not use these data for any purpose, including calculating TWPEs and TWPE removals.

EPA used Standard Methods, Method 4500 CN E, a colorimetric pyridine-barbituric acid 

procedure. This method has numerous interferences, especially in complex sample matrices. This 

method, as well as other cyanide methods, was originally designed for use with discharges from 

metal plating facilities where cyanide was known to be present. Most of the interferences result 

in false positives, and many of these interferences are caused by sulfide and other reduced sulfur 

compounds that may be present in FGD wastewater. Other compounds that can cause false 

positives under the right conditions are organosulfides, thiosulfates, nitrates, and other nitrogen 

compounds. Some of these compounds can actually cause cyanide to be produced during the acid 

distillation procedure of the method. The procedures for removing interferences, as provided in 

the methods, are often not effective, and complex samples, such as FGD wastewater, may also 

contain unknown interferences. It is entirely possible that most – if not all – of the reported 

cyanide detections could be sample matrix interferences.

The laboratory analyzing the samples for cyanide reported interferences that are discussed in the 

data narratives to the SERs. The laboratory, in fact, diluted most of the FGD wastewater samples 

1 to 10 before even proceeding with the cyanide distillation. In doing so, this raised the reporting 

limit for cyanide from 0.01 mg/L up to 0.1 mg/L. Most of the FGD wastewaters analyzed had 

slight detections of cyanide very close to the reporting limit of 0.1 mg/L; these most likely were 

the result of positive interferences. The laboratory reported poor to no recovery of cyanide in 

matrix spikes; reported detections in laboratory reagent blanks that, when multiplied by the 10 
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dilution factor, represented a substantial portion of the reported concentration in the samples; and 

also reported poor reproducibility in the field duplicates. In one instance, a very high detection of 

cyanide in a Miami Fort sample could not be confirmed; a field duplicate of that sample was less 

than the reporting limit. These issues were likely due to the difficult FGD matrix and likely 

interferences in the tests. EPA had the data narrative reviews indicating these problems, but 

inappropriately did nothing to act on them or modify the cyanide results obtained.

The table below provides the cyanide data EPA used to calculate TWPE removals for chemical 

precipitation and for chemical precipitation plus biological treatment. All of the cyanide data are 

qualified by the laboratory due to one or more of the following reasons:

(1) Cyanide samples were not preserved immediately upon collection as required by the method 

and were not analyzed within the holding time as required by the method,

(2) Cyanide measurements were less than the MDL,

(3) Cyanide measurements were less than the RL or quantification limit,

(4) MS (matrix spike) and/or MSD (matrix spike duplicate) were not within laboratorycontrol 

limits, or

(5) Cyanide was found in the blank.

Summary of EPA’s Cyanide Data Included in EPA’s TWPE Removal Calculations

Plant Sampling Point 

Average 

Concentration, 

mg/L (with 

qualifying 

flags) 

EPA’s Qualifications of 

Analytical Results 

Allen SP-1, Days 1-4 0.26 B CN was found in the blank for one 

day.

Allen SP-3, Days 1-4 and 

Monthly 1-4

0.12 B, F, J

2 < RL; 2 found CN in the blank; 1 

MS and/or MSD not within 

laboratory control limits.

Belews Creek SP-1, Days 1-4 0.042 U, F, J 1 < MDL; 3 < RL

Belews Creek SP-3, Days 1-4 and 

Monthly 1-4

0.044 U, J, F

1 < MDL; 7 < RL; 5 MS and/or 

MSD not within laboratory control 

limits.

Dickerson SP-1, Days 1-4 0.95 B CN was found in the blank for two 

days.

Hatfield’s Ferry

SP-1, Days 1-4 

(liquid and solid 

phases separated 

44 H, P

Samples not preserved directly 

following collection. Analyzed 23-

25 days past the holding time 

required by the method.
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and analyzed 

separately)

Hatfield’s Ferry SP-2, Days 1-4 and 

Monthly 1-4

0.18 J, F MS and/or MSD not within 

laboratory control limits.

Keystone

SP-1, Days 1-4 

(liquid and solid 

phases separated 

and analyzed 

separately)

109 H, P

Samples not preserved directly 

following collection. Analyzed 7-10 

days past the holding time required 

by the method.

Keystone SP-2, Days 1-4 and 

Monthly 1-4

0.16 B, J, U 1 < MDL; 3 < RL; 1 found CN in 

the blank.

Miami Fort

SP-1, Days 1-4 

(liquid and solid 

phases separated 

and analyzed 

separately)

107 H, B, P

Samples not preserved directly 

following collection. Analyzed 13-

16 days past the holding time 

required by the method.

Miami Fort SP-2, Days 1-4 and 

Monthly 1-4

3.3 B, C, J, F

2 < RL; 5 found CN in the blank; 1 

MS and/or MSD not within 

laboratory control limits.

Pleasant Prairie SP-1, Days 1-4 0.24 CN was found in the blank for all 4 

days.

Roxboro Settling Pond 

Effluent None No CN data measured.

EPA should not have used these cyanide data for any purpose, given these analytical issues. The 

detected results are highly suspect.

EPA has encountered problems with this cyanide test in other ELG rulemakings. In the proposed 

metal products & machinery ELG rule, EPA proposed to use all reported cyanide results 

including those for non-cyanide processes, which inappropriately predicted and exaggerated 

high TWPE removal for the treatment options. EPA corrected this error in the final rule by 

eliminating use of cyanide detection from industrial wastewaters not associated with cyanide 

plating or other cyanide operations. Development Document for the Final Metal Products and 

Machinery Category at 12-5. Similarly, FGD scrubber systems do not use any materials or 

chemicals having cyanide constituents, and any measured results show all the symptoms of 

known interferences for this test.

In addition, it is highly unlikely that cyanide exists in FGD wastewater purge from limestone 

forced oxidation systems. Cyanide compounds are generated in reducing environments and 

destroyed in oxidizing environments (i.e., an LSFO absorber, especially one operated to produce 

saleable gypsum). Cyanide compounds are volatile in an acidic environment such as an FGD 

absorber. Therefore, from a theoretical chemistry standpoint, cyanide should not be present in 

FGD wastewater.

Comment Response: 
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See the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 66.

Commenter Name: Chris M. Hobson

Commenter Affiliation: Southern Company

Document Control Number: EPA-HQ-OW-2009-0819-4379-A1

Comment Excerpt Number: 95

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA’s Method Detection Limit Study for FGD Wastewater Analysis is Flawed

EPA conducted a MDL study on FGD wastewater using EPA Method 200.8 by inductivelycoupled plasma mass spectrometry (ICP-MS) equipped with collision cell interference reduction 

equipment. The study involved the determination of MDLs in two matrices: reagent water and 

FGD wastewater. EPA’s FGD wastewater sample was a synthetic FGD water containing 12,000 

mg/L of TDS.

ICP-MS instruments are limited in the amount of TDS than can be introduced into the ICP 

plasma. EPA Method 200.8 states that the upper limit if 0.2% or 2,000 mg/L TDS39. Higher TDS 

levels will cause physical interferences and inaccurate results. To analyze samples with higher 

TDS, the sample can be diluted prior to injection, or the instrument can be equipped with a high 

solids introduction system that uses gas to reduce the amount of sample entering the plasma. In 

either case, sample dilution reduces the electronic signal for the target analytes and internal 

standards, raising the effective detection limit for the sample.

The laboratories in EPA’s MDL study had to dilute samples more than specified by EPA to 

avoid problems with plasma suppression and matrix interference, which did not conform to the 

EPA’s Study Plan. Because sample dilution varied from lab to lab (TDS ranged from 1,200 to 

6,000 mg/L), the results are not comparable across laboratories. In calculating MDLs for the 

synthetic FGD water, the dilution factors should have been accounted for by normalizing the 

results to TDS.

EPA’s synthetic FGD water used in their study was much more dilute than actual treated FGD 

effluent samples analyzed during their MDL study. In fact, actual FGD treated wastewaters for 

most plant will require higher dilution, raising the MDLs and RLs of the analytical method. In 

addition, higher FGD wastewater recycle rates will result in higher TDS levels, which in turn 

will require even higher dilution to analyze the target metals accurately. Therefore the MDLs and 

RLs (QLs) for certain FGD wastewaters may be higher than the proposed limits for arsenic, 

selenium and mercury. EPA should adjust the effluent limitations guidelines for FGD wastewater 

to account for the impact of sample dilution on MDLs and RLs.
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39 EPA. 2004. Method 200.8, Determination of Trace Elements I Waters and Wastes by 

Inductively Coupled Plasma – Mass Spectrometry, Revision 5.4.

Comment Response: 

As noted in response to DCN EPA-HQ-OW-2009-0819-4305-A3, Excerpt Number 67, Method 

200.8 contains text regarding the effects of high TDS levels and potential 

interferences. However, EPA notes that this text has appeared in the method since its earliest 

versions (circa 1994), is based on the 1986 reference cited in the method, and reflects the 

capabilities of ICP-MS instrumentation at that time, without the use of collision cell or dynamic 

reaction accessories. More modern ICP/MS instruments do not have the same physical 

limitations with regard to TDS as were noted in 1986 and many instrument manufacturers 

provide “high solids” interface equipment that is expressly designed to address the TDS 

concern. EPA’s data gathering efforts for this rule involved analyses by commercial laboratories 

that routinely use such interfaces.

Some of the laboratories in EPA’s MDL study diluted the synthetic FGD matrix more than other 

laboratories. Other laboratories did dilute the EPA-provided solution by the factor of 2 described 

in EPA’s study plan. EPA did not “normalize” any of the MDL study sample results to TDS in 

its evaluation or use of those results because such normalization is not a routine aspect of the 

published MDL procedure. However, laboratories do take into account the dilution of the 

sample in reporting results from actual field samples, including raising the detection limit to 

account for the dilution factor.

EPA notes that the monthly limit for arsenic of 8 μg/L (based on chemical precipitation 

treatment of FGD wastewater) is 4 times the highest minimum level (ML) for arsenic from any 

of the laboratories in the EPA MDL study (2 μg/L). The MDL values from the other laboratories 

in the EPA MDL study were considerably lower. For example, the ML resulting from the pooled 

laboratory results yields a ML of 1 ug/L; at least one laboratory participating in the MDL Study 

obtained a ML of 0.2 ug/L which is an order of magnitude lower than the maximum value from 

the study. Similar results were obtained for selenium. The highest ML for selenium from any of 

the laboratories in the EPA MDL study was 5 μg/L. The pooled pooled laboratory results yields 

a ML of 2 ug/L, and the lowest ML was 0.5 ug/L – again, an order of magnitude lower than the 

maximum value from the study. These ML results demonstrate that focusing on the maximum 

ML is a very conservative approach that fails to acknowledge that most other labs actually can 

measure pollutant concentrations at lower levels, in some cases substantially lower. This means 

that even if a sample needed to be diluted further because of particularly high TDS 

concentrations, laboratories would be able to measure pollutant concentrations at the levels 

necessary to demonstrate compliance with the effluent limitations. The ability of laboratories to 

measure pollutant concentrations at low levels, despite the TDS present in FGD wastewater 

samples, is illustrated by the effluent data showing arsenic and selenium (as well as other 

pollutants) quantified at low levels for the EPA sampling, CWA 308 sampling, and industry selfmonitoring data presented in DCN SE05733 and SE06277. Also see the data for the Mountaineer 

Plant, submitted by AEP in March 2014. EPA also notes that in pilot study of an FGD 

wastewater treatment system at IPL’s Petersburg plant, where TDS ranged as high as 27,000 
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ppm, the laboratory was able to quantify the low effluent concentrations of arsenic (averaging 

1.4 ug/L).

MDL and ML values are laboratory-specific, thus facilities with high TDS levels should to 

contract with laboratories with appropriate instrumentation and relevant experience in the 

analysis of FGD wastewaters. As noted in response to other comments, dischargers can and 

should provide appropriate guidance to any internal or external laboratories performing 

analyses. In this instance, such guidance would include any existing data on TDS in the FGD 

matrix, as well as limits on the extent of dilution that would be acceptable for demonstrating 

compliance with the ELG.

Commenter Name: Lisa Carty

Commenter Affiliation: Xcel Energy

Document Control Number: EPA-HQ-OW-2009-0819-4458-A1

Comment Excerpt Number: 36

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

The ELG is based on improper analytical methods and fails to take into account detection limits.

The analysis of arsenic (As) and selenium (Se) by inductively coupled plasma (ICP) and ICP/MS 

(mass spec) are known to be biased in the waste streams being addressed in the proposed ELG 

rules, especially at the proposed microgram (μg/l) and nanogram per liter (ng/l) levels. The bias 

is noted in a paper prepared for the World of Coal Ash (WOCA) Conference held in May of 

2011 that all methods developed for analytical determinations of trace contaminants in 

environmental samples are subject to physical, chemical, and /or spectral interferences. This 

2011 paper also references the EPA documented estimates that ICP and ICP/MS trace metal 

analysis from just the basic spectral interferences are and can impact a potential false positive or 

false negative bias on the reported results. Arsenic data is estimated by the EPA to encounter a 

25 to 50 percent false positive rate even when the method quality control (QC) is acceptable.

A review of the two Standard Operating Procedures (SOPs) drafted by the EPA in conjunction 

with two instrument manufacturers have been designed to specifically address the trace element 

analysis in FGD wastewaters; which are known to contain high levels of dissolved salts. The 

preparations of synthetic FGD solutions are used to conduct the study. The SOPs are written to 

be used with specialized instrument configurations/accessories that are designed to mitigate but 

cannot eliminate the effects of these and other potential sample interferences. The SOP being 

referenced for comment is employing the instrument or a similar model being used by some 

laboratories; however additional costs will be incurred for instrumentation upgrades and training; 

not including the expected rise in costs related to actual instrument maintenance, due to the 

effects of the sample matrices. Further costs will be incurred in the sampling processes; to 
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include the addition of sampling containers, preservatives, collection of additional QC samples, 

and potential shipping costs of the samples to the laboratory.

A review of the method detection limit (MDL) study shows the MDL for arsenic from a 2 μg/l 

spike into the FGD solution of 0.61μg/l; it is not general practice for laboratories to report to the 

MDL without qualifying the data due to the uncertainty when approaching the MDL. Many 

laboratories use reporting limits (RLs) to report results as opposed to the MDL. The EPA allows 

the statistically determined MDL to be multiplied by a factor as high as 10 times which in this 

case will result in a reporting limit of 6 μg/l for arsenic and 3 μg/l for selenium. The calculation 

of the MDL for the study indicates that the spiked amount is too high to provide a realistic view

of the actual instrument performance as it relates to the proposed limits in the ELG rule; hence 

providing misleading information as to the effectiveness of the actual instrument performance 

when dealing with the difficult matrix. This has been addressed in the SOP by stating that the 

values are examples, and not method requirements. Comparing the MDL studies for the two 

manufactures shows the decrease in the MDL with the use of a 40 μg/l spike amount resulting in 

a 3 μg/l for the RL.

In conclusion the ability of the proposed analytical techniques and instrumentation to provide 

data that is of known quality is not possible given the difficulty of the matrices, the known 

background issues, and the admission by the EPA that the results for arsenic can have a 25 – 50 

percent false positive rate with acceptable method quality control.

Comment Response: 

EPA recognized the risks of interferences from FGD matrices, and this was the main reason for 

development of the FGD collision cell procedure. The procedure contains substantial additional 

quality control measures that are designed to ensure accurate determination of arsenic, selenium 

and other elements in FGD wastewaters. The commenter cites a 2011 presentation from the 

World of Coal Ash conference. Despite the lack of other relevant information, including the 

name of the author, EPA identifies the intended citation as Rago and Breland, “Evaluation of 

Inductively Couple Plasma (ICP) False Positives for Arsenic and Trace Metals Analysis in Coal 

Ash and Coal Ash Media.” After reviewing that presentation, we note that the authors never 

present any data on false positive or false negative rates at all. Rather, they cite two other 

documents as containing statements from “EPA” that purportedly list such rates. The Rago and 

Breland presentation actually presents data that indicates that ICP results (without an MS 

detector) are “statistically higher” than the corresponding ICP/MS results on the same 

samples. They conclude that the interelement correction factors used in ICP instruments “may 

not adequately compensate for very high native aluminum concentrations” in the coal ash 

samples analyzed. These findings are not surprising and are one of the reasons that EPA did not 

pursue ICP analyses of the FGD wastewaters, in favor of the use of ICP/MS with collision cell 

instead.

The statements that the commenter attributes to “EPA” regarding false positive and negative 

rates appear to be drawn from two 2001 sources at EPA Region 4. EPA has not been able to 

confirm the statements cited by Rago and Breland from those 2001 sources. However, EPA 

notes that one of the statements clearly had nothing to do with either coal ash or FGD wastewater 
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analyses, as these matrices are not analyzed by laboratories with EPA contracts as part of the 

Superfund Contract Laboratory Program. Lacking more specifics from the commenter, EPA 

surmises that the claimed false positive and negative rates quoted are simply more general 

assessments of the effects of spectral interferences on ICP and ICP/MS without the use of 

collision cell equipment. As noted elsewhere, these known types of interferences were what lead 

EPA to pursue the use of collision cell ICP/MS in the first place. To characterize any of those 

statements as “an admission” by EPA suggests that the commenter is taking information 

completely out of context from a secondary source that they have not actually examined.

As noted in response to other comments, EPA agrees that Method 200.8 does discuss the effects 

of high TDS levels and potential interferences. However, EPA notes that this text has appeared 

in the method since its earliest versions (circa 1990) and reflects the capabilities of ICP-MS 

instrumentation at that time, and without the use of collision cell or dynamic reaction 

accessories. Since the time of those early versions of Method 200.8, instrument manufacturers 

have developed and sold various “high solids” accessories that are designed to address this 

issue. Combined with the capabilities of the collision cell or dynamic reaction accessories, 

modern instrumentation is capable of monitoring the regulated analytes at the levels needed to 

demonstrate compliance with the effluent limits.

In estimating the cost of compliance with the rule, EPA factored in costs for the use of collision 

cell or dynamic reaction cell equipment when performing ICP/MS analyses of FGD wastewater 

samples. However, EPA disagrees that any additional costs are involved for “sampling 

containers, preservatives, collection of additional QC samples, and potential shipping costs of the 

samples to the laboratory” beyond those associated with any compliance monitoring 

effort. Based on its own sampling activities in preparation of the rule, EPA is not aware of any 

characteristics of FGD wastewaters that require additional costs beyond the fact that the FGD 

wastewater must be sampled.

Regarding the commenter’s citation of an MDL for arsenic of 0.61 μg/L, EPA suspects that the 

commenter is actually referring to the arsenic MDL result provided in the draft collision cell 

procedure, and not to the a multi-laboratory MDL study that EPA conducted in 2012. That MDL 

study generally yielded much lower single-laboratory MDL values, and a pooled (across 

laboratories) MDL for arsenic of 0.35 μg/L.

Contrary to the commenter’s assertion, EPA does not “allow” the MDL to be multiplied by a 

factor as high as 10 in deriving the reporting limit termed the “minimum level of quantitation” or 

“ML.” Rather, it is the standard deviation underlying the calculated MDL that is multiplied by a 

factor of 10. As noted in the 2012 MDL study, the pooled MDL value for arsenic was 0.35 μg/L, 

which yields a pooled ML of 1.0 μg/L after appropriate rounding. The maximum MDL for 

arsenic determined in that study was 0.80 μg/L, which yields a maximum ML of 2.0 μg/L after 

appropriate rounding. The spiking concentrations used by the laboratories in the 2012 study 

were within the expected range of the results for the single-laboratory MDL values as well.

EPA stands by its conclusions about the ability of the collision cell or dynamic reaction cell 

procedures to produce valid results for arsenic and selenium in FGD wastewaters relative to the 

final ELGs.
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Commenter Name: Raven Power Holdings, LLC

Commenter Affiliation: Raven Power Holdings, LLC

Document Control Number: EPA-HQ-OW-2009-0819-4467-A1

Comment Excerpt Number: 28

External Review Flag: Engineering, Statistics

External Review Incorporated into Response: No

Comment Excerpt: 

EPA proposed daily average limits of 6 μg/l for arsenic and 10 μg/l for selenium. EPA has also 

recognized the matrix interferences resulting in positive bias in FGD wastewaters when 

analyzing for low-level compounds4and in the June 7, 2010 Hanlon memo (excerpt below) to 

EPA Region Water Division Directors, recognized that FGD sampling may require labs to alter 

analytical methods and the need for experienced labs and analysts.

It is essential that the Director make permitting decisions based on sufficiently sensitive data 

and, thus, sound science. The use of insufficiently sensitive analytical methods could lead the 

Director to make an incorrect determination about the presence or absence of a pollutant in an 

applicant’s discharge. These assumptions, in turn, could result in the Director making an 

incorrect permitting decision. Additionally, requiring insufficiently sensitive analytical methods 

in permits for compliance monitoring purposes could result in an undetected exceedance of 

permit limits.

Due to advances in instrumentation since a method was developed and the benefit of experienced 

analysts, an analyst may achieve detection limits (MDLs) and minimum levels (MLs) lower than 

the published values. Thus, the Director should not rely solely on sensitivity measures, such as 

MDLs or MLs, in published methods. These measures only give an upper, not a lower, bound on 

capabilities. In addition, EPA provides analysts the flexibility to modify an approved method 

without EPA review. This flexibility allows a laboratory to demonstrate performance better than 

the published MDL or ML.

The lack of a sufficiently detailed and approved method to accurately and reliably analyze FGD 

wastewaters is problematic in light of the proposed low- level limits proposed. In addition, the 

proposed limits are below the reporting limits laboratories are typically able to achieve with the 

FGD matrix. High levels of TDS found in FGD wastewaters require sample dilution to protect 

sensitive laboratory equipment and to prevent both analytical and physical interferences. Dilution 

of the sample increases the reporting limit of the analysis. Instrumentation vendors for 

inductively coupled plasma – mass spectrophotometry (ICP-MS) recommend sample TDS not to 

exceed 2,000 ppm. Without sample dilution and the resulting increase in reporting limits, 

repeatable and reliable results, along with achievement of matrix spike/matrix spike 

duplicate recoveries within specified method limits is questionable. Given an elevated TDS of 

60,000 ppm, which is by far not the maximum TDS seen within the industry, and utilizing the 

necessary dilution to achieve a 2,000 ppm maximum TDS entering the instrument, the minimum 

reporting limit that can be achieved is 30 ppb for arsenic and selenium.
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Raven Power recommends that because there is not a sufficiently detailed and approved method 

to accurately and reliable analyze FGD wastewaters and that due to the elevated reporting limits 

caused by elevated TDS concentrations, EPA should revise the proposed FGD wastewater 

effluent limits and method 200.8 Standard Operating Procedures (SOPs) for analyzing FGD 

waters.

4 USEPA, Steam Electric Generating Point Source Category: Final Detailed Study Report, [EPA821-R-09-008] October 29, 2009 

Comment Response: 

EPA notes that the monthly average limitation in the final rule for arsenic is 8 ug/L and the 

monthly average limitation for selenium is 12 ug/L.

EPA notes that the concerns raised by the commenter with regard to method sensitivity are the 

very reasons that lead EPA to work with industry representatives to develop the collision cell and 

dynamic reaction cell procedures. As noted in response to other comments, The record 

indicates that laboratories using modern instrumentation and the collision cell or dynamic 

reaction cell procedure can achieve detection and reporting limits suitable for demonstrating 

compliance with the proposed ELG limits for arsenic or selenium.

The analytical methods already provide laboratories with certain flexibility options, as detailed in 

40 CFR 136.6. In keeping with generally accepted laboratory practices, each laboratory 

undertaking FGD wastewater analyses should develop standard operating procedures specific to 

their laboratory setting and instrumentation and that they may base those procedures on 

information provided in the collision cell procedure developed by EPA, the dynamic reaction cell 

procedure developed by one of the instrument vendors, as well as information from other sources 

(e.g., industry and other instrument vendors), so long as the resulting laboratory procedure falls 

within the flexibility outlined at 40 CFR 136.6.

Commenter Name: Jay Hudson

Commenter Affiliation: Santee Cooper

Document Control Number: EPA-HQ-OW-2009-0819-4476-A1

Comment Excerpt Number: 29

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Analyti cal Methods
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Regarding EPA's mandated analysis requirements, we note that the complexity of these waste 

streams makes analysis very difficult, that necessary analytical equipment is very expensive, and 

that staffing will have to increase to account for increased laboratory volume due to ELG 

mandated sampling.

For metals analysis, traditional ICP-OES analyses (Method 6010) is often impractical given 

interferences which necessitate dilutions that negatively impact the reporting limit. An 

alternative technique is analysis by ICP-MS (Method 6020). However, this technique is subject 

to polyatomic interferences for some elements (e.g., arsenic and selenium). These interferences 

must be dealt with in order to achieve the desired detection limits, necessitating use 

of an advanced ICP-MS (e.g. collision cell technology). The cost of this instrument is 

approximately $200,000, and the method requires substantial analyst time for proper 

filtration,digestion and analysis of samples. This cost must be borne by the utility and its 

customers either in implementing these expensive methods internally or by using one of the few 

qualified contract laboratories with this capability.

Other analysis mandates would require similarly high laboratory and analysis costs. Regarding 

nutrient analysis, use of ion chromatography (Method 9056A) for nitrate/nitrite is very challengi 

ng due to interferences . The superior alternative is the cadmium reduction method (Method 

353.2). However, this would require a $10,000 modification to an existing instrument. Given the 

increased number of oil and grease samples which may result from this regulation, it would be 

necessary to use EPA Method 1664 for this analysis which would necessitate purchase of 

additional instrumentation costing approximately $60,000.

The additional costs described above only address instrumentation for the analytes that will be 

newly controlled. However, additional testing will also be required to properly operate additional 

treatment processes mandated by the rule. These additional testing costs cannot be predicted at 

this time.

Substantial additional costs will also be incurred due to requiring a significant increase of 

analyst time. Additional staffing would be necessary to handle the influx of steam effluent 

samples generated.

Comment Response: 

As noted in the proposed rulemaking and elsewhere in the responses to comments, EPA has 

always recognized that the waste streams subject to this rulemaking pose analytical 

challenges. However, wastewater matrices from other regulated industries also present 

analytical challenges. Moreover, FGD wastewaters have been analyzed for non-regulatory 

purposes for many years. EPA developed the collision cell and dynamic reaction cell procedures 

after extensive consultations with industry representatives, and effectively ruled out the use of 

ICP/OES for the analysis of metals, in favor of the combination of ICP/MS with the addition of 

the collision cell or dynamic reaction cell procedures.

As noted elsewhere in these comment responses, in estimating the cost of compliance with the 

rule, EPA included costs for laboratory analyses of the compliance monitoring samples and these 
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costs reflect the use of collision cell or dynamic reaction cell equipment when performing 

ICP/MS analyses of FGD wastewater samples. The commenter makes reference to the need to 

acquire additional laboratory equipment due to this rule; however, EPA’s cost estimates are 

based on plants sending their samples to commercial laboratories for analysis. Commercial 

laboratories already analyze FGD wastewater samples from a number of plants so the analytical 

capability exists at such laboratories.

EPA notes that the majority of the analytical methods cited by the commenter are from the SW846 methods manual (e.g., 6010, 6020, and 9056a), and EPA notes that none of those methods 

were either proposed for use in this rulemaking, nor are any of those methods approved at 40 

CFR part 136 for use in monitoring compliance with effluent guideline limitations under the 

NPDES program. Thus, while the cited methods may bear some similarity to the actual 

approved method for wastewater compliance monitoring, their capabilities are immaterial to the 

rulemaking because they are not approved for use for CWA purposes.

The one method cited by the commenter that is approved at 40 CFR part 136 is Method 1664, 

where the actual approved versions are 1664A and 1664B. The commenter states that the 

increased number of samples to be analyzed for oil and grease as a result of the rulemaking 

would necessitate the use of “EPA Method 1664” and therefore require purchase of additional 

instrumentation. EPA disputes this contention because the rule does not include any new 

effluent limits on oil and grease, and therefore, the rule cannot result in an increase in monitoring 

of oil and grease. Thus, EPA finds the commenters concerns about such costs unfounded.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 18

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA’s Method Detection Limits (MDLs) and Minimum Levels (MLs) for arsenic and selenium 

may overestimate method sensitivity. The MDLs do not account for required dilution of highsolids FGD wastewater.

Comment Response: 

See responses to EPA-HQ-OW-2009-0819-4305-A3, Excerpt Number 67.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)
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Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 76

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

Additionally, there are analytical interferences associated with measuring sulfides in wastewaters 

when using the two most common methods for sulfide anlaysis (the colormetric method and the 

Iodometric Titration method). The potential interferences are provided in Standard Methods for 

the Examination of Water and Wastewater [Standard Methods, 2013]. False positives can occur 

in the wastewater and in the source water if the interferences are not corrected. Therefore, the 

data EPA used may be biased high.

In the Iodometric Titration Method (Standard Methods 4500-S2-F), the color change that the lab 

staff must note is subtle, and would be difficult to observe in a wastewater. In essence, the 

method is not useful below 1.0 mg/L. Furthermore, this method has a high bias (interference) 

when other reducing substances are present, including thiosulfate, sulfite, and various organic 

compounds, both solid and dissolved.

The colorimetric method is biased high if the sample had turbidity or color. Interferences can be 

confirmed using the method of standard additions, which establishes a linear response factor for 

spiked aliquots of sample, or by including matrix spike samples as part of normal quality control.

Comment Response: 

EPA is not establishing effluent limitations for sulfide in the ELGs.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 89

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

9.1 EPA’s Method Detection Limit (MDL) study does not accurately represent 

the capability of EPA Method 200.8 with collision/reaction cell for analysis of 

FGD wastewater.

 Laboratories had to dilute samples more than specified by EPA, to avoid problems with 

plasma supression and matrix interference

 Actual FGD waters would require higher dilution, raising detection limits
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The impact of sample dilution should be accounted for in developing effluent limits that are 

based on MDLs/MLs. EPA determined the sensitivity of EPA Method 200.8 by inductivelycoupled plasma mass spectrometry (ICP-MS) equipped with collision cell interference reduction 

from the results of a five-laboratory method detection limit (MDL) study [EPA, 2012]. The study 

involved determination of MDLs in two matrices: reagent water and FGD water; EPRI’s 

comments relate to the FGD water results only.

ICP-MS instruments are limited in the amount of total dissolved solids (TDS) that can be 

introduced into the ICP plasma. Method 200.8 states that the upper limit is 0.2% (2,000 mg/L) 

[EPA, 2004]; higher TDS will cause physical interferences and inaccurate results. To analyze 

samples with higher TDS, the sample can be diluted prior to injection, or the instrument can be 

equipped with a high solids introduction system that uses gas dilution to reduce the amount of 

sample entering the plasma chamber. In either case, sample dilution reduces the electronic signal 

for the target analytes and internal standards, raising the effective detection limit for the sample.

EPA’s sample matrix was a synthetic FGD water containing 12,000 mg/L of TDS. Labs were 

instructed to first spike the EPA solution with the target analytes and then dilute the solution by 

two times, to a TDS of 6,000 mg/L. The diluted solution was considered the reference matrix for 

the study [EPA, 2012].

The laboratories in EPA’s MDL study used various approaches to analyze the synthetic FGD 

solution, which did not all conform to the EPA’s Study Plan.

 Test America first diluted the EPA solution by two times, then spiked with 1 ug/L of each 

element (except As and Pb, which were present as contaminants in the sample). They 

then diluted the spiked solution by an additional two times to avoid plasma suppression 

(to 3,000 mg/L TDS and an element concentration of 0.5 ug/L) [Test America, 2012]. It 

appears that this lab did not use a high solids introduction system (dilution gas = 0).

 Southwest Research Institute first diluted the EPA FGD solution by five times, then 

spiked at 1 ug/L, then diluted the spiked solution by a further two times (to 1,200 mg/L 

TDS and 0.5 ug/L of each target element), to avoid interference from the FGD 

water matrix on selenium. It appears that this lab did not use a high solids introduction 

system [Southwest Research Institute, 2012].

 Several other laboratories injected the reference matrix directly into instruments equipped 

with high solids introduction systems; Perkin-Elmer reported a gas dilution factor of 3 

[Perkin-Elmer, 2012]. The dilution factors for the other labs were not stated.

Because sample dilution varied from lab to lab (TDS to the plasma ranged from 1,200 mg/L to 

6,000 mg/L), the results are not comparable across labs. In calculating MDLs for the synthetic 

FGD solution, the dilution factors should have been accounted for by normalizing the results to 

TDS.

EPA’s synthetic FGD solution is much more dilute than most treated FGD effluent samples 

analyzed by EPA or EPRI. Figure 9-1 illustrates this point: EPA’s synthetic FGD water reference 

matrix is shown on a cumulative distribution plot of mean TDS concentrations in 25 actual FGD 

water treatment system effluents—19 from a recent EPRI study [EPRI, 2012] and 6 from EPA’s 
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site visits. The EPA synthetic FGD water (6,000 mg/L) is at the 10th percentile of the 

distribution. In EPRI’s study, which used a synthetic FGD water at about the 50th percentile of 

TDS (17,000 mg/L), labs typically diluted the sample by 20 times to avoid analytical issues.

Due to the TDS discrepancy between actual samples and EPA’s matrix, laboratories will see 

higher reporting limits for many FGD samples than the Minimum Levels (MLs) calculated from 

EPA’s MDL study. This will be true even for laboratories using high solids introduction systems. 

The high reporting limits will impact power plant owners’ ability to monitor accurately at the 

proposed numerical effluent limits for arsenic and selenium in high-TDS waters. The impact of 

the required sample dilution should be taken into account in developing effluent limits that are 

based on MDLs/MLs.

Comment Response: 

As noted in response to other comments, EPA disagrees that the proposed FGD limits are based 

on MDLs/MLs. The data used to establish the effluent limitations are described in DCN 
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SE05733, as were the statistical procedures used to develop those numerical limits. Also see 

TDD Appendix B.

While EPA agrees that dilution will affect the sensitivity of any method for a given sample, EPA 

notes that the limitations imposed by TDS that are described in EPA Method 200.8 date to the 

early 1990s and do not reflect the capabilities of newer instrumentation.

EPA acknowledges that the laboratories in the 2012 MDL study utilized various approaches to 

analyze the synthetic FGD solution, however, the EPA study plan did not preclude the use of 

those approaches, and none were outside of the realm of typical approaches to addressing 

challenging matrices. As noted by the commenters, several laboratories used instruments 

equipped with high-solids introduction systems and successfully analyzed the samples. EPA 

does not agree that the resulting MDLs need to be adjusted to include the “dilution” inherent in 

the use of such devices.

As noted in response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 95, the 

results from the MDL Study and the effluent data in the record demonstrate that plants will be 

able to measure pollutant concentrations at the levels needed to show compliance with the 

effluent limitations.

MDL and ML values are laboratory-specific, thus facilities with high TDS levels need to 

contract with laboratories with appropriate instrumentation and relevant experience in the 

analysis of FGD wastewaters. As noted in response to other comments, dischargers can and 

should provide appropriate guidance to any internal or external laboratories performing 

analyses. In this instance, such guidance would include any existing data on TDS in the FGD 

matrix, as well as limits on the extent of dilution that would be acceptable for demonstrating 

compliance with the ELG.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 90

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

9.2 EPRI concurs with EPA’s recommendation to use ICP-MS with interference 

reduction technology to measure non-mercury metals in FGD treatment system 

effluents, but more detailed guidance is needed for laboratories to successfully 

analyze FGD waters.

Multilaboratory studies conducted by EPRI have determined that the target metals can be 

accurately analyzed in FGD waters using either collision/reaction cell or dynamic reaction cell 
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ICP-MS [EPRI, 2009; EPRI, 2012]. Analysis with instruments not equipped with interference 

reduction will lead to extremely high biased results for some metals. EPA’s Standard Operating 

Procedure (SOP) for collision cell ICP-MS is a helpful start to provide guidance to laboratories 

in the use of interference reduction techniques with FGD water samples. However, there are 

details of the sample preparation and instrument operation that are critical to obtaining accurate 

results on FGD waters but are not addressed in EPA’s SOP. EPRI has prepared two guidance 

documents to supplement EPA’s SOP and Method 200.8, which are attached to these comments 

as Appendix F. We recommend that the information in EPRI’s guidance be incorporated into 

future EPA SOP revisions.

Comment Response: 

EPA appreciates the commenter’s general support of the use of either the collision cell or 

dynamic reaction cell procedures. EPA has reviewed the additional guidance prepared by EPRI 

and agrees that it may be useful to laboratories, but does not agree that the information needs to 

be included in the SOP developed by EPA. The SOP was prepared as guidance to laboratory 

analysts, with the expectation that the laboratory would use the SOP along with their protocols to 

develop their own laboratory-specific SOP. To the extent that the EPRI guidance is useful to the 

laboratories, they may also incorporate that information into their lab-specific SOPs.

Commenter Name: Paul Chu

Commenter Affiliation: Electric Power Research Institute (EPRI)

Document Control Number: EPA-HQ-OW-2009-0819-4499-A1

Comment Excerpt Number: 91

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

9.3 The MDL and ML are poor indicators of method performance. Alternate 

measures of detection and quantitation are needed.

In 2007, EPA completed an extensive study of alternatives to the MDL procedure, under the 

auspices of a Federal Advisory Committee on Detection and Quantitation (FACDQ). After 

extensive pilot testing and issuance of the final report [FACDQ, 2007], EPA decided not to move 

ahead with the recommendations of the Committee. Nevertheless, the shortcomings of the 

current Part 136, Appendix B procedure remain—such as the failure to take long-term instrument 

and operator variability into account, lack of a requirement that MDLs be determined in the 

matrix under consideration, and statistical issues related to the relationship between spiking level 

and standard deviation. EPRI encourages EPA to reingage with the laboratory community and 

other interested parties to address these issues.

Comment Response: 
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EPA notes that independent of the steam electric rulemaking, EPA has continued to work with 

representative laboratory trade groups and others to refine the method detection limit 

procedure. Effort such as those revisions are outside of the scope of this rulemaking.

Commenter Name: Tom DeLawrence

Commenter Affiliation: Public Service Company of New Hampshire(PSNH)

Document Control Number: EPA-HQ-OW-2009-0819-4633-A1

Comment Excerpt Number: 65

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

EPA proposes to require that compliance with effluent limitations must reflect results obtained 

from “sufficiently sensitive” analytical methods. 78 Fed. Reg. at 34524. A “sufficiently 

sensitive” method is defined as “a method that ensures the sample-specific quantitation level for 

the wastewater being analyzed is at or below the level of the effluent limitation.” Id. This 

Proposed Rule would require the use of methods with quantitation levels low enough to measure 

the pollutant level in a facility’s discharge, the effluent limit in an NPDES permit, or water 

quality criteria. However, where there are methods approved in 40 C.F.R. Part 136, the rule 

encourages monitoring by some unapproved “sufficiently sensitive” method. This provision 

might allow permitting agencies to use unapproved methods outside EPA’s Alternative Test 

Procedure (ATP), which would not account for precision, accuracy or any of the procedural 

safeguards in the ATP program.

Measurements of water pollutants must be based on reliable and well-defined analytical 

methods. EPA’s present method for calculating detection and quantitation levels is 

unsatisfactory. As EPA is well aware, laboratories have struggled for decades to meet detection 

limits specified by EPA even under approved methods. See, e.g., 75 Fed. Reg. 15500, 15516 

(Mar. 29, 2010). In response to numerous complaints regarding the shortcomings of EPA’s 

method detection limits (MDL), EPA convened a Federal Advisory Committee in 2007, which 

found that the current MDL procedure had deficiencies that should be corrected. However, to 

date, none of the Committee’s recommendations for correcting the MDL deficiencies have been 

accomplished. If EPA is going to require the use of “sufficiently sensitive” methods, EPA should 

also require that only EPA-approved methods, if available, should be used. Stated differently, the 

“sufficiently sensitive” rule should apply only to choosing from among methods in 40 C.F.R. 

Part 136. We request that EPA state this in the actual rule and not just in the Preamble.

Nevertheless, use of sufficiently sensitive monitoring methods should not be required. Many of 

these methods are unnecessarily complicated and would not only increase lab costs, but they 

could also require long waiting times for the results, which could create problems with filing 

DMRs on time. For instance, for flow minimization techniques for FGD waste water (i.e., 

recycling to maximum chloride level), the TDS levels are sometimes so high (due to recycling) 

that the laboratory would have to dilute the sample to 0.02% in order to be able to analyze it 
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using the most sensitive method for metals determination, Method 200.8, due to instrumentation 

constraints.

EPA erroneously concluded that the Proposed Rule will cause little increased burden to 

applicants or permittees. Any rule that requires the use of more sensitive methods, particularly 

experimental and unapproved test methods will increase the cost of analyses required by the 

permits. Such cost increases include the research and development required to run a nonapproved method and the cost to purchase the advanced equipment needed to run more sensitive 

methods. For example, the cost of Method 1668C for PCBs is estimated to cost $1,000 per 

sample.

In sum, before EPA makes any “sufficiently sensitive” rule final, the Office of Management and 

Budget should conduct a full review of the potential impacts of the rule and EPA should address 

the recommendations of the Federal Advisory Committee it created. EPA should also set 

measurement quality performance objectives to ensure the objectivity of scientific information 

and processes. Moreover, EPA should only require the use of sufficiently sensitive methods if 

EPA eliminates the internal effluent limitations and continues to allow commingling of waste 

streams. If internal effluent limitations are implemented, then there is no need for extra sensitive 

and more expensive monitoring methods.

Comment Response: 

The final rule does not require permittees to use EPA-approved analytical methods that are 

sufficiently sensitive to provide reliable, quantified results at levels necessary to demonstrate 

compliance with the final effluent limitations and standards because another recently 

promulgated rule already accomplishes this. As public commenters pointed out, EPA was 

conducting a rulemaking on that topic; and, in August 2014, EPA published a rule requiring the 

use of sufficiently sensitive analytical test methods when completing any NPDES permit 

application. Moreover, the NPDES permit authority must prescribe that only sufficiently 

sensitive methods be used for analyses of pollutants or pollutant parameters under an NPDES 

permit where EPA has promulgated a CWA method for analysis of that pollutant. That rule 

clarifies that NPDES applicants and permittees must use EPA-approved analytical methods that 

are capable of detecting and measuring the pollutants at, or below, the applicable water quality 

criteria or permit limits.

Regarding the method detection limit comments and the need for “unnecessarily complicated” 

methods and the need to dilute samples, see the responses to DCN EPA-HQ-OW-2009-0819-

4499-A1, Excerpt Number 89; EPA-HQ-OW-2009-0819-4305-A3, Excerpt Number 67; 

and EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 95. However, EPA disputes that the 

fact that samples must be diluted will “require long waiting times for results.” In fact, as noted 

in response to DCN EPA-HQ-OW-2009-0819-4305-A3, using knowledge of the effluent 

composition, the permittee may need to adjust their contracting strategy to ensure that 

appropriate dilutions are analyzed and that multiple dilutions may be necessary. However, once 

that fact is known to a well-run laboratory, the “waiting times” for results should not exceed 

those encountered for other existing regulatory analyses, nor affect timely filing of discharge 

monitoring reports (DMRs).
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EPA is not promulgating revisions to the effluent limitations for PCBs in this rule.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 44

External Review Flag: Analytical

External Review Incorporated into Response: No

Comment Excerpt: 

a. Sulfides Issues with the Titrimetric Procedure

There are several methods for analyzing sulfide. The two most commonly used EPA-approved 

methods are the titrimetric procedure (EPA 376.1 or the more detailed Standard Methods 20th

Edition SM-4500-S2-F) and the methylene blue colorimetric procedure (EPA 376.2 or the more 

detailed Standard Methods 20th Edition SM-4500-S2-D). For either method, the Standard 

Methods reference highly recommends performing the interference removal procedures 

described in Standard Methods 20th Edition SM-4500-S2-C, because both methods are highly 

susceptible to interferences.

Judging from the very high detection limits for most of the EPA sulfide data (1 mg/L or higher), 

it is likely that many facilities used EPA Method 376.1 for the Form 2C data. Method 376.1 

measures any material that will react with and be oxidized by iodine. In Standard Methods (SM4500-S2- F), it is recommended that this method be used only if sulfide is known to be present 

above 1 mg/L and interferences are either absent or can be effectively removed by SM-4500-S2-

C.

Iodine demand (the reaction of iodine with water constituents) is similar to chlorine demand, as 

iodine and chlorine are similar oxidants in water. Even deionized water has iodine 

demand. Iodine reacts with any organic material and also with any reducing material such as 

sulfites, particularly metals with varying oxidation states like iron and manganese, both of which 

are found in ash pond discharges. All will register as positive sulfide interferences. The EPA 

version of the iodine titration method, 376.1, while acknowledging high detection limits (and 

recommending Method 376.2, the colorimetric method, for values <1 mg/L), is an abridged 

extraction from the Standard Methods method, with only a limited description of potential 

interferences.

The sample preservation and interference removal process for both the colorimetric and 

iodometric methods is to precipitate the sulfide using zinc acetate and sodium hydroxide.13 The 

sample is then filtered to remove the precipitate. If using the iodine titration method, the 

material on the filter is then re-solubilized in an acid-iodine solution, at which time the iodine 

reacts with any acid soluble reducing agents (including sulfide). The remaining iodine is then 
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back-titrated with sodium thiosulfate. The iodine missing from the back-titration is assumed to 

have reacted with sulfide.

However, in the case of ash pond discharge, significant particulate metals (EPA has estimated 30 

mg/L TSS) will be caught on the filter to react with the acid/iodine. Also, dissolved Mn+2 and 

ferrous iron (the most common forms) are present. These metal interferents would not be 

removed by the described process. Instead, both would precipitate as hydroxide by the sodium 

hydroxide and be caught on the filter. Therefore, they would be available to react with the 

acid/iodine and would be misidentified as sulfide.

b. Sulfides Methods Issues: Method 376.2 and SM4500-S2-C and –D

The colorimetric methods 376.2 and the 20th Ed. SM-4500-S2-D method from which it is 

adapted have much lower detection limits, but they also have other types of interferences (most 

notably sample turbidity) and are considerably more difficult to run. The colorimetric sulfide 

test is generally superior to the iodometric titration method, which is largely useful only to 

standardize the sulfide standard so that the colorimetric method can be performed. The 

colorimetric method has a much lower reporting limit (0.05 mg/L) and is far more specific for 

sulfide.

It is not without its problems, however. The titration method is relatively easy to use in the 

field. Ease of use in the field is critical because, unless preserved, sulfides must be measured 

immediately. Even with preservatives, the holding time is relatively short. In fact, EPA Method 

376.2 does not discuss preservation and simply states that analysis must begin 

immediately. (Standard Methods says samples may be preserved with zinc acetate and sodium 

hydroxide but does not specify a holding time.) Essentially the laboratory must be set up to run 

Method 376.1 (the iodometric titration) as well as the colorimetric procedure, since the titration 

is needed to standardize the stock sulfide standard solution. A fresh standardization and 

calibration curve must be generated each day.

There are several types of possible interferences with the colorimetric method. The TSS content 

causes high readings, since TSS cannot be removed without also losing the sulfide preserved as 

precipitated zinc sulfide. Reducing agents such as thiosulfate can interfere with color 

development. Sulfide itself, when present in concentrations higher than 20 mg/L, may inhibit 

color development or prevent it altogether at higher concentrations. Sometimes the color reagent 

forms a precipitate in some samples, which also would be read as color if not 

detected. Obviously, if a sample forms a precipitate, this must be observed by the technician 

(automated color measurement will not detect this), or else a positive interference will occur. A 

sample with precipitate might be used if filtered or centrifuged to measure the characteristic blue 

color, but the results could be questionable, depending on color absorption onto the filter (low) 

or else fine particulate passing through the filter (high).

For the reasons stated above, UWAG recommends that EPA remove all of the sulfide data from 

its analytical database. Given the flawed sulfide data and the lack of information on test methods 

for most of these data points, the Form 2C data are not appropriate as a basis for regulation. In 
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the presence of dissolved oxygen (DO), sulfide generally will not be generated and, if generated, 

will not persist for long.

13 Samples not preserved can be measured in the field within 15 minutes, but the interference 

removal step must be skipped. In this case, the sampler must know sulfide is present while 

interferences are relatively absent, such as in a sulfur well.

Comment Response: 

EPA is not establishing ELGs for sulfide in this rule.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 96

External Review Flag: Analytical

External Review Incorporated into Response: No

Comment Excerpt: 

6. Issues with EPA’s Use of Cyanide Data

a. EPA Used Invalid Cyanide Data in Calculating TWPEs

All of EPA’s cyanide data are invalid because of the potential interferences with the analytical 

method as well as the chemical (sodium hydroxide) used to preserve the samples. EPA should 

not use these data for any purpose, including calculating TWPEs and TWPE removals.

EPA used Standard Methods, Method 4500 CN E, a colorimetric pyridine-barbituric acid 

procedure. This method has numerous interferences, especially in complex sample 

matrices. This method, as well as other cyanide methods, were originally designed for use with 

discharges from metal plating facilities where cyanide was known to be present. Most of the 

interferences result in false positives, and many of these interferences are caused by sulfide and 

other reduced sulfur compounds that may be present in FGD wastewater. Other compounds that 

can cause false positives under the right conditions are organosulfides, thiosulfates, nitrates, and 

other nitrogen compounds. Some of these compounds can actually cause cyanide to be produced 

during the acid distillation procedure of the method. The procedures for removing interferences, 

as provided in the methods, are often not effective, and complex samples, such as FGD 

wastewater, may also contain unknown interferences. It is entirely possible that most – if not all 

– of the reported cyanide detections could be sample matrix interferences.
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The laboratory analyzing EPA’s samples for cyanide reported interferences that are discussed in 

the data narratives to the SERs. See, e.g., EPA-HQ-OW-2009-0819-0885.03. The laboratory 

diluted most of the FGD wastewater samples 1 to 10 before even proceeding with the cyanide 

distillation. In doing so, this raised the reporting limit for cyanide from 0.01 mg/L to 0.1 

mg/L. Most of the FGD wastewaters analyzed had slight detections of cyanide very close to the 

reporting limit of 0.1 mg/L; these most likely were the result of positive interferences. The 

laboratory reported:

 poor to no recovery of cyanide in matrix spikes;

 detections in laboratory reagent blanks that, when multiplied by the 10 dilution factor, 

represented a substantial portion of the reported concentration in the samples; and

 poor reproducibility in the field duplicates.

In one instance, a very high detection of cyanide in a Miami Fort sample could not be confirmed; 

a field duplicate of that sample was less than the reporting limit. These issues were likely due to 

the difficult FGD matrix and likely interferences in the tests.

The table below provides the cyanide data EPA used to calculate TWPE removals for chemical 

precipitation and for chemical precipitation plus biological treatment. All of the cyanide data are 

qualified by the laboratory due to one or more of the following reasons:

1. Cyanide samples were not preserved immediately upon collection as required by the 

method and were not analyzed within the holding time as required by the method,

2. Cyanide measurements were less than the MDL,

3. Cyanide measurements were less than the RL or quantification limit,

4. MS (matrix spike) and/or MSD (matrix spike duplicate) were not within laboratory 

control limits, or

5. Cyanide was found in the blank.

Summary of EPA’s Cyanide Data Included in EPA’s TWPE Removal Calculations 

Plant Sampling Point

Average 

Concentration, 

mg/L (with 

qualifying 

flags)

EPA’s Qualifications of 

Analytical Results

Allen SP-1, Days 1-4 0.26 B CN was found in the blank for one 

day.

Allen SP-3, Days 1-4 

and Monthly 1-4

0.12 B, F, J 2

Belews Creek SP-1, Days 1-4 0.042 U, F, J 1

Belews Creek SP-3, Days 1-4 

and Monthly 1-4

0.044 U, J, F 1

Dickerson SP-1, Days 1-4 0.95 B CN was found in the blank for two 

days.
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Plant Sampling Point

Average 

Concentration, 

mg/L (with 

qualifying 

flags)

EPA’s Qualifications of 

Analytical Results

Hatfield’s Ferry

SP-1, Days 1-4 

(liquid and solid 

phases separated 

and analyzed 

separately)

44 H, P

Samples not preserved directly 

following collection. Analyzed 23-

25 days past the holding time 

required by the method.

Hatfield’s Ferry SP-2, Days 1-4 

and Monthly 1-4

0.18 J, F MS and/or MSD not within 

laboratory control limits.

Keystone

SP-1, Days 1-4 

(liquid and solid 

phases separated 

and analyzed 

separately)

109 H, P

Samples not preserved directly 

following collection. Analyzed 7-

10 days past the holding time 

required by the method.

Keystone SP-2, Days 1-4 

and Monthly 1-4

0.16 B, J, U 1

Miami Fort

SP-1, Days 1-4 

(liquid and solid 

phases separated 

and analyzed 

separately)

107 H, B, P

Samples not preserved directly 

following collection. Analyzed 13-

16 days past the holding time 

required by the method.

Miami Fort SP-2, Days 1-4 

and Monthly 1-4

3.3 B, C, J, F 2

Pleasant Prairie SP-1, Days 1-4 0.24 CN was found in the blank for all 4 

days.

Roxboro Settling Pond 

Effluent None No CN data measured.

EPA should not have used these cyanide data for any purpose, given these analytical issues.

EPA has encountered problems with this cyanide test in other ELG rulemakings. In the proposed 

MP&M ELG rule, EPA proposed to use all reported cyanide results including those for noncyanide processes, which inappropriately predicted and exaggerated high TWPE removal for the 

treatment options. EPA corrected this error in the final rule by eliminating use of cyanide 

detection from industrial wastewaters not associated with cyanide plating or other cyanide 

operations. MP&M Development Document at 12-5. Similarly, FGD scrubber systems do not 

use any materials or chemicals having cyanide constituents, and any measured results show all 

the symptoms of known interferences for this test.

In addition, it is highly unlikely that cyanide exists in FGD wastewater purge from limestone 

forced oxidation systems. Cyanide compounds are generated in reducing environments and 

destroyed in oxidizing environments (e.g., an LSFO absorber, especially one operated to produce 
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saleable gypsum). Cyanide compounds are volatile in an acidic environment such as an FGD 

absorber. Therefore, from a theoretical chemistry standpoint, cyanide should not be present in 

FGD wastewater.

Comment Response: 

See the response to DCN EPA-HQ-OW-2009-0819-4379-A1, Excerpt Number 66.

Commenter Name: Elizabeth E. Aldridge, Hunton & Williams

Commenter Affiliation: UWAG

Document Control Number: EPA-HQ-OW-2009-0819-4655

Comment Excerpt Number: 134

External Review Flag: No External Review

External Review Incorporated into Response: No

Comment Excerpt: 

A. Collision Cell Analysis of FGD Wastewater

EPA has done a study to develop MDL data for the collision cell procedure (i.e., analysis by 

EPA Method 200.8 by inductively-coupled plasma mass spectrometry (ICP-MS) equipped with 

collision cell interference reduction equipment. Multiple laboratories participated in the study, 

with the purpose of deriving corresponding Minimum Levels, or quantitation limits, to support 

EPA’s efforts to regulate discharges from FGD systems. EPA derived the Minimum Levels 

using procedures published in the Federal Register on March 12, 2003 (68 Fed. Reg. 

11,770). See Study Plan for Developing Method Detection Limits and Minimum Levels of 

Quantitation for Selected Analytes Using EAD’s Draft Collision Cell ICP/MS Procedure (July 

24, 2012), EPA-HQ-OW-2009-0819-0575.

EPA’s contractor CSC recommended using the maximum MDL and ML as regulatory limits:

For the purpose of developing effluent limitations guidelines and standards for discharges of 

FGD wastewater, CSC recommends that EAD use the maximum MDL and maximum ML values 

for the FGD matrix. The maximum values are the “worst-case” results for each of the target 

analytes from the MDL study, meaning that the other laboratories in the study were able to 

achieve better sensitivity. The data from this study illustrates that all of the laboratories in this 

study (which were all identified as well-operated laboratories with experienced staff and 

operating the appropriate analytical instrumentation) could achieve MDL values at least that low, 

and the maximum ML values represent the corresponding quantitation limits from the study.

CSC, Results of the ICP/MS Collision Cell Method Detection Limit Studies in the Synthetic Flue 

Gas Desulfurization Matrix (Jan. 16, 2013), EPA-HQ-OW-2009-0819-2116 at 5.
Effluent Limitations Guidelines and Standards for the Steam Electric Power Generating Point Source Category:

EPA’s Response to Public Comments

9-532

UWAG agrees with EPRI’s comments on EPA’s MDL study. EPA used a synthetic FGD 

wastewater for the study containing 12,000 mg/L TDS. Selecting just a single TDS level is not 

at all representative of FGD wastewaters within the industry. EPRI’s analysis shows that EPA’s 

synthetic FGD wastewater is much more dilute than most treated FGD effluent samples analyzed 

by EPA or EPRI. EPRI compared EPA’s synthetic FGD wastewater to mean concentrations of 

19 treated FGD effluent samples from a recent EPRI study and six samples from EPA’s 

sampling program. The EPA synthetic FGD wastewater (6,000 mg/L, after dilution according to 

EPA’s instructions) is at the 10th percentile of the distribution. In comparison, in EPRI’s earlier 

study, which used a synthetic FGD wastewater at about the 50th percentile of TDS (17,000 

mg/L), labs typically diluted the sample by 20 times to avoid analytical issues. Id.

For this reason and others detailed by EPRI, UWAG does not believe EPA’s MDL study is 

valid.68 EPA should not use the MDL study for any purpose related to the rulemaking.

Also, because EPA’s synthetic FGD wastewater was much more dilute than actual treated FGD 

effluent samples, actual FGD treated wastewaters for most plant will require higher dilution, 

raising the MDLs and RLs of the analytical method. In addition, higher FGD wastewater recycle 

rates will result in higher TDS levels, which in turn will require even higher dilution to analyze 

the target metals accurately. Therefore the MDLs and RLs (QLs) for certain FGD wastewaters 

may be higher than the proposed limits for arsenic, selenium and mercury. EPA should adjust its 

proposed limits for FGD wastewater to account for the impact of sample dilution on MDLs and 

RLs.

68 In 2010, UWAG provided detailed comments to EPA on its Standard Operating Procedure for 

ICP-MS for Trace Element Analyses in Flue Gas Desulfurization Wastewaters (SOP). See

letters to Ronald P. Jordan and Richard W. Reding, from Donna B. Hill, UWAG Effluent 

Guidelines Chair, dated March 19, 2010 and April 6, 2010 (Attachments 19 and 20 to these 

comments).

Comment Response: 

Regarding the method detection limit comments, see the response to DCN EPA-HQ-OW-2009-

0819-4499-A1.

Further, EPA disagrees with the commenter’s characterization of the recommendation of EPA’s 

contractor CSC with regard to the results of the MDL study. Contrary to the commenter’s 

assertion, the quote from the January 16, 2013 report on the MDL study is not a recommendation 

that EPA use “the maximum MDL and ML as regulatory limits” (emphasis added). Rather, the 

quoted text is a recommendation that EPA compare whatever discharge limits it derives from the 

data on actual FGD wastewaters to those maximum MDL and ML values as part of EPA’s 

deliberations. In fact, this is exactly how EPA used those values, and as noted elsewhere in these 

responses, the daily and monthly discharge limits for arsenic and selenium are higher than the 

maximum MLs from that study.