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**Subject:** MATS RIA OMB Submission **Date:** December 9 , 2011 This version of the Mercury and Air Toxics Standards (MATS) Regulatory Impact Analysis (RIA) incorporates edits made since the since the version delivered on 11/23. These include small changes based on post

- processed PM emission changes from the final policy case modeled in IPM that were not available in time for the 11/23 version and revisions b ased on comments received during the interagency review process. Below is a summary of EPA’s responses to the RIA

- related comments received during the interagency process. **Preamble Comments Pertaining to the RIA Impacts of the Rule on Ratepayers** 
 It does not appear as though EPA took into adequate consideration the real potential utilities will close and the surrounding communities experience economic hardship due to these regulations. **EPA analyzes the impact of the rule and assesses potential closures, includes any**  **electricity rate impact or other power sector changes resulting from those closures in its analysis, estimates the potential employment changes from those closures (and**  **changes in fuel use as well), and conducted an analysis of the impacts on small**  **businesses as required by SBREFA. Fully detailed information on the economic costs of the rule, as well as its benefits, are presented in the RIA.** 

 The coal units affected by this regulation would be faced with a large investment of funds that wil l result in no added production from the plants. On the contrary, the parasitic load (electricity necessary to run the equipment in the plant itself) that each plant normally requires would increase substantially due to the installation of emission contro ls devices that require power to operate. So, in essence, the power plants will ultimately produce fewer megawatts due to the increased parasitic load and associated revenues would be decreased. Has this effect been accounted for in the costs of the rule and effect on ratepayers? **Parasitic load is fully accounted for in EPA modeling.**

 Page 555: We refer to a statement on this page: ““The EPA’s estimates of increase in the retail electricity price range from 1.3 percent to 5.9 percent regionally in 2015... Low

income households will thus see some increase in electricity price, but this increase should be modest.” This percent price increase does not take into account the cumulative effect of numerous EPA rules that could place upward pressure on electricity prices. Additionally, it is unclear why a price increase as high as 5.9 percent would not be considered a major increase to a low

- income consumer.2

**Electricity prices are not anticipated to be much different from historical levels, even after the rule. So**  **me regions will experience greater rate impacts than others, but EPA estimates that the average household impact will be less than $3 per month.** 

 We strongly recommend that EPA consider providing context for the projected change in electricity prices by comparing either the projected prices or the magnitude of the projected increase to recent historical data. For example, based on a quick look at EIA data( http://38.96.246.204/electricity/monthly/excel/epmxlfile5_3.xls ), it appears that EPA could explain its projected average price of electricity with the EGU MACT rule would still be less than average electricity prices for 2008

- 2010 (EPA should confirm that those numbers are comparable). Alternatively, EPA could say that the 3% increase is on par (or even less) than typical year

-to
- year price variability (again, after verifying that is in fact the case). **EPA plans to include this information in communicati ons materials, and presents a**  **chart illustrating historical electricity prices**  **Chapter 2 of the RIA.**

 In response to retirement projections and reliability concerns cited by a commenter, EPA responds that most studies projecting over 10 GW of retirements do not hold up to scrutiny and that many tools exist to maintain reliability (including new generation, demand response, energy efficiency, transmission upgrades, and energy storage). First, EPA’s retirement analysis relied heavily on the installation of DS I for compliance, which few of the many studies disparaged by the EPA did. More detail on EPA’s sensitivity case where “less DSI systems and more scrubber systems were installed” is required. In this case, DSI was limited to 35GW on installation and only one more GW is retired as compared to the base analysis. However, in modeling frameworks, it is likely that the most optimal units for DSI will get the technology, then other units will install FGD. Where the real sensitivity would become apparent is lim iting DSI by size and coal type, which would show the limitations of the technology. In addition, the retirement projections rely heavily on low natural gas prices

– a higher gas price sensitivity analysis is required. In addition, many of the reliabilit y measures cited by the EPA are still in the developmental stages or potentially very costly

– EPA should have also factored the costs of maintaining reliability into their analysis. **Using higher natural gas prices would almost certainly result in lower le vels of coal**  **retirements and is unlikely to result in major differences with the primary policy scenario. With regards to DSI, EPA believes that is has appropriately modeled DSI and**  **has provided a sensitivity that is also informative. In EPA’s analysis, certain limitations**  **are included when modeling DSI. For example, it can only be used in conjunction with lower sulfur fuels, it is not allowed at units with fluidized bed or an existing scrubber,**  **units must have a fabric filter or ESP (or retrofit with FF or ESP). In addition, the costs**  **of DSI vary by unit size and rank of coal that is burned. In the 35 GW sensitivity, we allow the model to most cost** 
**- effectively determine which units will install the**  **technology subject to the aforementioned constraints. There is no evidence that** 3

**larger units are unable to install the technology, and several large units over 500 MW have tested and are currently installing DSI.**  **In addition, arguments have consistently been made that the technologies to reduce emissions are**  **not ready for wider adoption when new requirements are set forth (Acid Rain Program and scrubbers,**  **NOx SIP Call and SCRs, mercury control, etc). History has shown in every instance that technology in fact, ends up performing much better in practice than**  **originally thought and that industry is adept at handling particular challenges to widespread technology**  **adoption. Employment Effects** 
 Page 549: We refer to a statement on this page: “The Agency found that the impact on employment nationally should be small on net...” EPA should also note that there would be a decrease in labor productivity (i.e., more labor required to produce the same amount of electricity), which would cause the short

- run aggregate supply curve to shift to the left, resulting in highe r prices and businesses producing less (i.e., lower GDP). **Note added.**

 Pages 569 and 550, Last Paragraph: Please confirm if any of the commenters has referenced a study or provided any data to back up their claims on the adequacy of labor availability. We would also appreciate receiving a copy of the TSD referenced in EPA’s response. **Some commenters have said labor availability will be an issue (primarily utilities) and other commenters (including boilermakers and the pollution control industry) argued**  **tha t there will be more than adequate labor availability to support MATS compliance**  **activities. Historically, the pollution control sector has effectively responded to the increased demand for pollution controls/labor, and there is substantial evidence that**  **labor availability will not be an issue.**

 Page 603: We refer to the statement on this page: ““...each additional $1 million spending on pollution abatement results in an small net increase of 1.6 jobs; the estimated effect is not statistically significant different from zero.” It seems better to simply state the study finds spending on pollution abatement does not have a statistically significant effect on jobs. EPA’s a nalysis should also point out that there would be a decrease in labor productivity (i.e., more labor required to produce the same amount of electricity), which would cause the short

- run aggregate supply curve to shift to the left, resulting in higher price s and businesses producing less (i.e., lower GDP). **Because of the interest in employment EPA has used this study for a number of regulations to estimate the mean net employment and provided the 95% confidence**  **interval results to reflect the high degree of uncertainty (the interval includes zero so**  **we are showing we don’t know the sign of the effect but the interval itself is helpful when others give exaggerated claims of huge job changes well outside our 95%**  **confidence interval).**4

**The impact of a decrease in productivity has been noted in this section.** 

**Cumulative Effects of EPA Rules**
 Page 557: We refer to a statement on this page: “...the direct benefits from the 1990 Clean Air Act Amendments reach almost $2 trillion for the year 2020...” What was the effect on real GDP? This is a more relevant measure for decision makers than social costs, as changes to GDP growth are what determine whether the economy is experiencing a recession. We suggest EPA delete the discussion of this report, since it is not re levant to the rulemaking at hand. **The Agency disagrees with the assertion that the effects of a program on GDP would be “more relevant” information for decision makers than an understanding of the net**  **benefits of a program (or collection of related program s) obtained through rigorous**  **benefit**
**- cost analysis based on standard principles and practices of welfare economics.**  **In fact, prevailing OMB guidance issued pursuant to relevant Executive Orders (esp**  **ecially Circular A** 
**- 4 issued in response to EO 12866) expl**  **icitly provides for assessing a program’s net benefits through benefit** 
**- cost analysis but does not explicitly**  **call for an assessment of a program’s effect on GDP growth to be a routine part of major rule Regulatory Impact Analyses. This is because most ec**  **onomists recognize that the projected net benefits of program is more salient information for**  **policymaking than the effects of that program on GDP, which is not a reliable measure of utility, or economic welfare. Furthermore, the public comments to which**  **the draft preamble text responds pertain to expressed concern about cumulative effects of**  **multiple regulations. The most comprehensive assessment available of the overall effect of air pollution regulatory programs implemented pursuant to the Clean Air Ac** **t as a whole is provided by the March 2011 Second Prospective Study of the benefits**  **and costs of the 1990 Clean Air Act Amendments. This study clearly demonstrates the substantial positive net benefits of cumulative clean air programs from 1990 to 2020.**  **These analytical results are both relevant and useful for responding to the comments regarding cumulative effects of air pollution rules. Therefore the Agency disagrees**  **with the suggestion to delete references to a study which provides useful perspective in response to the submitted public comments.**  **Benefits**
 For the final rule, the only mercury benefit that can be quantified either in economic terms or by a widely understood measure

– the total nationwide increase in IQ which results from a 90% reduction in utility mercury emissions

– are removed from the main body and are put in an appendix. These findings are replaced by a “hazard quotient.” People understand what IQ points mean: if the MATS rule were to have caused children born of mothers who ate fre sh caught fish (whose mercury levels were influenced by power plant emissions) to gain an average IQ of 5 points when power plant mercury5

emissions were sharply reduced, we would all have understood what an important public health gain had been achieved. No explanation would have been needed. However, EPA has now found that of the 240,000 children born of mothers who eat fish influenced by power plant emissions, the total IQ gain nationwide from the 90% reduction in power plant emissions is 510 IQ points, also expressed in the documents as 2/1,000 of an IQ point per child. EPA calculates the monetized benefit of this increase of 510 IQ points nationwide to be between $500,000 and $6 million, depending on assumptions such as discount rates. The benefit is based upon total lower lifetime wages due to the reduction of 510 IQ points, and contrasts with costs of the regulation of about $11 billion. This finding is good news. It means that pregnant women can now be told that US mercury emissions will not harm t he intelligence of their unborn child. Wouldn’t it be a good idea to make sure that readers of this document now know that they are safer than they might have previously thought? Public health findings aren’t always about harm we have found, but also abo ut harm we suspected but later found not to be of concern. In contrast, the use of a “hazard quotient” has no intuitive meaning to people. Further, it isn’t clear what actual harm exists if the hazard quotient is above 1.5 (the level at which a hazard is said to exist). There is suggestion of risk, but is the risk of a similar magnitude of the IQ risks, now quantified? Of less risk of harm to health than the IQ risks? Therefore the suggestion is to also include, in the body of the Final Rule (instead o f in an Appendix), the quantifiable (and positive) findings that virtually no adverse effect on IQs have occurred from US mercury emissions (because virtually no benefit occurs from a 90% reduction in such emissions). This appears to be news which anyone interested in health effects of mercury would want to know. **The commenter conflates the National**
**- Scale Mercury Risk Assessment (Hg Risk TSD)**  **supporting the Appropriate and Necessary finding with the mercury benefits analysis in the RIA. Each analysis u**  **ses somewhat different methods because each document serves a different purpose. For the Hg Risk TSD, we moved the IQ analysis to an**  **appendix in response to a clear recommendation from the SAB peer review, but we retained the IQ analysis for the Hg benefi**  **ts analysis in the main body of the RIA. The decision to focus on the (reference dose) RfD** 
**- based hazard quotient (HQ)**  **estimates, rather than IQ loss, in the Hg Risk TSD reflects concerns that the IQ loss metric may not capture the full range of neurodev** **elopmental effects associated with mercury exposure. Therefore, while we acknowledge that IQ loss provides a readily**  **interpretable health effect endpoint, the HQ metric captures other neurological**
  ** related health effects that could occur at lower levels of** **exposure. The decision to focus on IQ decrements for the benefits assessment in the RIA was**  **driven by data and methodology availability for IQ analysis. Data and methodology of sufficient quality and quantity were not available for any of the other neuro**  **logical**6

**endpoints considered. In addition, we disagree with the commenter regarding the use of the central** 
**** **tendency measure (e.g., 2/1000 of an IQ point) for the recreational angler because it does not capture the skewed distribution of mercury** 
**- related im**  **pacts. Relative to the freshwater recreational angler cited by the commenter, freshwater subsistence fisher**  **populations are likely to have substantially elevated mercury risk due to their higher self** 
**- caught fish consumption rates. The Hg Risk TSD shows tha**  **t IQ loss estimates for freshwater subsistence fishers can be orders of magnitude higher than the central**  **tendency numbers cited by the commenter for recreational anglers.**

 Page 619: Table 9: Since some studies have found no significant effect of PM2.5 on mortality, perhaps zero should be included in the range of PM2.5 benefits, as Electric Power Research Institute has suggested. EPRI indicated: “Since some models in some studies do not find a statistically significant effect of PM2.5 on mortality, the effects range could even include zero...” (Source: EPRI PM2.5 Reductions and Impact on Premature Death: An EPRI perspective; Issue Brief 1018632.) Also, the same EPRI briefing states the EPRI

- Washington University Veterans Study did not find any statistically significant mortality associations with PM2.5, but found some PM components that were significantly associated with mortality. The EPRI briefing goes on to say: “Of great significance for CAIR, this study did not find a significant association between th e sulfate component of PM and mortality...if this study were used to derive estimates of health benefits attributable to reductions in SO2 emissions, the numbers would differ from those derived from the Pope et al...some studies have shown that estimated imp acts of PM diminish when other co

- pollutants are considered in the analyses. If the co

pollutants are indeed associated with increased mortality and are correlated with PM levels, then the PM effects estimated from this single pollutant model approach can be biased upwards.” **EPA disagrees with this recommendation. The Integrated Science Assessment (ISA) for Particulate Matter (U.S. EPA, 2009), which was twice reviewed by the Science Advisory**  **Board, concluded that there is a causal relationship between exposure to PM2.5 and**  **premature mortality after reviewing the entire body of scientific evidence. In addition, the ISA also concluded that the scientific evidence is not yet sufficient to**  **allow differentiation of effect estimates by particle type. This me ans that while some**  **PM mixtures may be more toxic than other mixtures, the scientific literature does not support the commenter’s assertion that some particles are not toxic. Although we**  **note this uncertainty in the RIA, we assume that all particles are eq ually toxic for the**  **purpose of calculating benefits. This assumption was supported by the National Academies of Science and the Health Effects Subcommittee of the Advisory Council on**  **Clean Air Compliance Analysis.**

 Page 628: We refer to the statement on this page: “The fourth value is the 95 th percentile of the SCC from all three models at a 3 percent discount rate.” Why not7

include a fifth value at the 5 th percentile in order to represent lower

- than

- expected impacts from temperature change **The Social C ost of Carbon (SCC) values used to estimate climate benefits for the MATS**  **final rule are consistent with the recommendations of the Interagency Working Group on the SCC discussed extensively in the Technical Support Document available on**  **OMB’s website at: http://www.whitehouse.gov/sites/default/files/omb/inforeg/for** 
**** **agencies/Social**
**- Cost** **- of** 
**- Carbon** 
**- for** 
**- RIA.pdf. The main purpose of this exercise was to**  **develop a schedule of SCC values that can be applied consistently across regulatory analyses and Agencies.**  **The TSD clearly states that: The interagency group selected four SCC values for use in regulatory**  **analyses. Three values are based on the average SCC across models and socio**  **- economic and emissions scenarios at the 2.5, 3, and 5 percent discount**  **rates. The fourth value is included to represent the higher** 
**- than** 
**- expected**  **economic impacts from climate change further out in the tails of the SCC distribution. For this purpose, we use the SCC value for the 95**  **th percentile at a**  **3 percent discount rate. (The full se t of distributions by model and scenario**  **combination is included in the Appendix.) As noted above, the 3 percent discount rate is the central value, and so the central value that emerges is the**  **average SCC across models at the 3 percent discount rate. For purposes of**  **capturing the uncertainties involved in regulatory impact analysis, we emphasize the importance and value of considering the full range.**  **In keeping with the interagency directive, EPA used this approach for the Light Duty Vehicle Rule to esti**  **mate benefits from CO2 emission reductions and in all subsequent EPA regulatory actions to date for this purpose.**  **OMB led and several other interagency reviewers for the MATS final rule actively participated in the SCC**  **Interagency Working Group to develop this approach. It is our understanding that any**  **deviation from the approach outlined in the TSD would have to be reviewed and considered by the interagency group before it could be implemented by the EPA or**  **other agencies. On page 30 of the SCC TSD,**  **limitations of the current SCC estimates are discussed. A key question remaining from the interagency process is the relevant assumption to be**  **made about relative risk aversion with regard to high**
**- impact climate outcomes. The**  **current SCC values do not co nsider the possibility that individuals may have a higher**  **willingness to pay to reduce the likelihood of low**
**- probability, high impact outcomes**  **than they do to reduce the likelihood of higher**
**- probability but lower impact damages**  **with the same expected costs . “The inclusion of the 95**  **th percentile estimate in the**  **final set of SCC values was largely motivated by this concern.” The interagency group also noted that estimates of climate damages are far more uncertain under more**  **extreme climate change scenarios**

.8

 We strongly recommend that EPA provide a much clearer explanation regarding the mercury benefits of this rule. The mercury benefits quantified in the cost/benefit sections include only a small portion of the total benefits of the mercury reductions projected from the rule

– only the IQ loss from children exposed to recreationally

caught freshwater fish. It is entirely unclear from the preamble to the rule, the executive summary in the RIA and other summaries of the costs/benefits of the rule that the “Hg

- related benefits” represent such a small subset of the Hg benefits. We strongly suggest clarification of these benefits by, for example, changing tables to read “Partial Hg

- related benefits (recreational freshwater fish IQ effects only)” or some other sim ilarly explicit language. **Text has been added to the Executive Summary, the Cost/Benefits Comparison Chapter and in appropriate areas of the Preamble to address this recommendation.** 
**RIA -**  **Specific Comments**

 Industry does not make retirement decisions based upon one regulation, but on the entire group of regulations. Therefore, a more accurate and comprehensive RIA would look at the aggregate effect of proposed and recently promulgated EPA rules. EPA should include these aggregate costs for all proposed and recently promulgated rules. Executive Order 13563 directs each agency to tailor its regulations to take into account the costs of cumulative regulations. **The Agency did not prepare a cumulative impact analysis to accompany the rule for the following reas**  **ons: 1) the various EO requirements that the Agency must comply with require us to estimate impacts specific to this rule; 2) decision makers and the**  **public need to know the impacts specific to a particular rule in order to judge the merits of the regulati**  **on; 3) estimates specific to a particular rule are more transparent than those from a cumulative impact analysis. A cumulative impact analysis lumps**  **several regulations together and can potentially mask a high**
**- cost/low benefit**  **regulation among other rules that may have large net benefits. By analyzing each**  **regulation separately, EPA makes clear statements about what impacts, costs, and benefits will be generated as a result of this particular regulation.**  **This does not, however, mean EPA has failed to consider cumulative impacts of the**  **regulation. The inclusion of CSAPR and other regulatory actions (including federal, state, and local actions) in the IPM base case is necessary in order to reflect the level**  **of controls that are likely to be in place in r esponse to other requirements apart from**  **MATS. This base case provides meaningful projections of how the power sector will respond to the cumulative regulatory requirements for air emissions, while isolating**  **the incremental impacts of MATS. These results a re presented in Chapter 3 of the RIA.**  **Additionally, the Agency does reflect on the broader cumulative impacts of our regulations. In March 2011, EPA issued the Second Clean Air Act Prospective Report** 9

**which assessed at the benefits and costs of regulations pursuant to the 1990 Clean Air**  **Act Amendments. The study examines the cumulative impact of these regulations (found at http://www.epa.gov/air/sect812/feb11/summaryreport.pdf). As shown in**  **the report, the direct benefits from the 1990 Clean Air Act Amendmen ts reach almost**  **$2 trillion for the year 2020, a figure that dwarfs the direct costs of implementation ($65 billion). The full report is at http://www.epa.gov/air/sect812/prospective2.html.**  **The direct benefits of the 1990 Clean Air Act Amendments and asso ciated programs**  **significantly exceed their direct costs, which means economic welfare and quality of life for Americans were improved by passage of the 1990 Amendments. The wide**  **margin by which benefits exceed costs combined with extensive uncertainty anal ysis**  **suggest it is very unlikely this result would be reversed using any reasonable alternative assumptions or methods. This conclusion is likely to also be attributable to**  **this rule as shown in the RIA.**

 EPA may want to include in the RIA an analysis of the effect of the regulation on U.S. Gross Domestic Product (GDP). Such an analysis would be a useful measure of whether the policy is cost

- effective. Similarly, it would also be useful to estimate the economic effect of the rule at the state level (e.g. , state GDP). This would serve to satisfy Executive Order 13563, which states that the regulatory system should promote economic growth. **Prevailing OMB guidance issued pursuant to relevant Executive Orders (especially Circular A** 
**- 4 issued in response to**  **EO 12866) explicitly provides for assessing a program’s net benefits through benefit** 
**- cost analysis but does not explicitly call for an**  **assessment of a program’s effect on GDP growth to be a routine part of major rule Regulatory Impact Analyses. This is be**  **cause most economists recognize that the projected net benefits of program is more salient information for policymaking than**  **the effects of that program on GDP, which is not a reliable measure of utility, or economic welfare.** 

 Employment Impacts Due to I ncreases in Electricity Prices Are Not Accounted For The Executive Summary (ES) of the RIA (and ensuing portions of subsequent chapters of the RIA) discuss two types of employment impacts stemming from these regulations

– see pg. 14 of the ES. The first t ype is changes in employment over time in the effected industry, in this case the electric utility industry. The second type is short term increases in employment for construction of pollution control equipment prior to compliance dates. These impacts a re summarized in Table ES

- 6. Long term employment changes in the electric utility industry are estimated to be about 8,000 jobs, but the estimate is said to be not statistically different than zero. Short term employment gains are estimated to be about 4 7,000 jobs. Both these estimates are for increased employment. The comment is that by far the largest employment effect due to the MATS regulation is likely to be a substantial increase in unemployment because of increased electricity10

prices. Regulations which increase electricity prices result in lost jobs because of reduced purchasing power across the economy because of these higher electricity prices. Many firms across the US will do marginally less business because households and businesses will have less disposable income, as a result of paying more for electricity. And when these firms do less business, they need fewer workers. Thus fewer workers will be hired in expanding businesses and more workers will be let go in contracting ones; some such fi rms will close down. Deschenes (2010) finds that every 1% increase in electricity prices causes a nationwide reduction in employment of between 0.1% and 0.16%. The total US civilian labor force as of Oct. 2011 is 154.2 million. In his preface, Deschene s thanks Michael Greenstone, the Obama Administration’s first Research Director of the Council of Economic Advisors for helpful advice. The RIA ES states (pg. 14): “Retail electricity prices are projected to increase in the contiguous US by an average of 3 .0% in 2015 with the final MATS Rule.” It also states that natural gas prices will be higher than they would otherwise be, but we do not try to estimate unemployment impacts of higher natural gas prices. Multiplying 154 million US workers by 0.3% and by 0.48% (three times 0.1% to 0.16% to reflect the estimated 3% increase in electricity prices) gives a total unemployment increase of from 462,000 (low end) to 739,000 workers (high end). These would be the dominant estimated unemployment effects caused by the MATS regulations. If instead of total number of employed people, the 154 million person civilian work force, we used Full Time Equivalent (FTE), as in Deschenes (2010), the unemployment estimates would be lower by about 43%; however, FTE would not in clude self employed workers (Deschenes, 2010), so FTE estimates of unemployment would be biased low. Thus the estimate of the number of unemployed workers as a result of the higher electricity prices stemming from MATS would be between the FTE and Civilia n Work Force estimates. Presumably there are other estimates of the cross elasticity of unemployment with respect to energy prices, so these estimates using cross elasticities from Deschenes (2010) may be low or high. The important point is that the unemp loyment created by higher electricity prices should be included in the RIA. Reference: Deshenes, O. 2010. Climate Policy and Labor Markets. Working Paper 16111. National Bureau of Economic Research. **The recommended study is too preliminary for regul atory use. The NBER website**  **where the study can be found ( http://www.nber.org/books/full10** 
**- 1**  **) notes that "The following chapters are**  **preliminary drafts**  **unless otherwise noted. They have not yet been subjecte**  **d to the formal review process of the NBER." Add**  **i tionally, EPA has identified a number of issues with the application of this paper**  **for the purpose of estimating employment impacts in the RIA. There i**  **s not enough discussion of control variables for the re**  **ader to evaluate how well the model is controlling for other influences on employment. As mentioned in section C of the**  **paper, omitted factors might bias the estimates.**11

**The author's choice of methods ignores longer term economic adjustments that are ma**  **de in response to a shock. EPA believes that an employment impact analysis needs consider short term impacts as well as longer term adjustment paths.**  **Deschenes himself, as well as his conference discussant Matt Kahn, both emphasize quite clearly in the t**  **ext of the paper (and Kahn’s comments) that the methodology used in this study does not identify a causal relationship between electricity prices and**  **employment. That is, the econometric approach that Deschenes uses (OLS with fixed effects) cannot isolate**  **whether either increases in electricity prices lead to declines in employment or if changes in employment lead to changes in electricity prices. At best**  **the Deschenes approach can estimate the correlation between the two; not causation.**

 Electricity Price Increases (and thus Increased Unemployment) from MATS May Be Understated When Interaction with Other Electricity Rate Impacts from Other Regulations are Taken Into Account According to the ES, only 5.5 MW of coal units are expected to retire as a result of the MATS rule (pg. 14). Does this estimate include retirements which might occur when a unit which must comply with the new MATS rule must also comply with other new air quality and water quality rules, including (for air quality) rules regarding (1 thro ugh 3) NO 2 , SO 2 , and PM National Ambient Air Quality Standards, (4) Visibility Rule, and (5) Cross State Air Pollution Rule? Some EGUs which might be able to continue to operate economically while installing technology to meet MATS may no longer be able to operate economically if they also have to add additional technologies to meet other rules noted above. If each rule analyze s coal unit retirements based upon the impact of each rule only by itself, e.g., if the MATS rule does not take into account costs that will occur due to other regulations, then plant retirements due to the combination of new regulations, and thus electric ity price increases, may both be greater than impacts analyzed for MATS alone, or on a rule by rule basis. It would therefore be crucial for EPA to estimate the number of coal units retired based upon the combined rules, and the resulting electricity pri ce increases. Further, the increase in unemployment as a result of the combined rules should also be calculated. Pg. 14 (not a typo) of the RIA for the Cross State Air Pollution Rule states: “Retail electricity prices are projected to increase nationally by an average of 2.5 % in 2012 and 1.5 % in 2014 with the proposed Transport Rule.” This appears to be an additional 4% increase in electricity costs, relative to the MATS rule. Would these costs increase, and added coal plants (other than those assumed to be retired in the Cross State [Transport] rule) retire, when MATS requirements are added to those of the Cross State rule on a plant by plant basis? The same argument pertains when other air quality rules (such as the upcoming PM rule) are promulgated

. Thus the actual electricity price increases, and the actual unemployment estimates due to higher electricity prices, may be understated when interactive effects are considered.12

We would like to ask EPA to clarify whether costs impacts on individual EGU s from rules other than MATS are considered when determinations are made as to whether MATS will cause such units to retire. If the answer is affirmative, which of the new rules are considered in this context? If the answer is negative, would EPA be will ing to consider joint effects, in order to re

- estimate the number of coal units retired, and the resulting additional electricity price increases? **The MATS analysis includes existing and enforceable environmental requirements for the power sector (both st**  **ate and Federal), including the finalized Cross**
**- State Air**  **Pollution Rule. The IPM documentation has an extensive list of all the power sector rules and regulations that are included in the modeling. EPA has not included in this**  **analysis any speculative c onstraints regarding rules which have not yet been finalized.**  **The MATS regulatory impact analysis looks at the impact of the MATS regulation as it is implemented on top of a base case which accounts for all other existing and**  **enforceable air pollution cont rol requirements, including the final Cross** 
**- State Air**  **Pollution Rule. As a result, the projections of the MATS policy case are a valid reflection of the outcome in the power sector of complying with MATS, CSAPR, and**  **other existing regulations. As noted a bove, the projected electricity prices under the**  **MATS policy scenario, which also incorporates CSAPR, are well within historic norms. The MATS impact analysis is explicitly designed to determine “whether MATS will**  **cause such units to retire” and its resul ts are a valid reflection of the economic**  **impacts of this final rule. Finally, it appears as though the above interagency comment may have derived the estimate of a 4% increase in retail electricity price by**  **adding the CSAPR RIA’s 2012 estimate of 2.5% an d 2014 estimate of 1.5%** 
**- however, it**  **is improper to add those impacts together, as they are each a proportional measure of conditions with and without CSAPR**  **in the year analyzed , and rather than showing a**  **4% increase, they show an initial 2.5% increase in 2012 that declined to only 1.5% by**  **2014. Also, there are different years of analysis for the two rules.** 

 Estimated Benefits in MATS Include Reduction in Mortality from PM 2.5 at Levels Below the National Ambient Air Quality Standard (NAAQS) for PM 2.5 The c urrent NAAQS as well as the new NAAQS that is under consideration both set levels for daily and annual PM 2.5 concentrations which are said to be protective of public health. If PM 2.5 concentrations are above either the daily or annual level in a given loc ality, states must create a plan to reduce concentrations down to that regulatory permissible level. If PM 2.5 concentrations are below these legal concentrations, then nothing more need be done to protect the public health. NAAQS standards are subject to public review. In estimating benefits from MATS, EPA assumes that PM 2.5 concentrations at levels well below the NAAQS standards, down to nearly background levels, cause premature mortality. In making this assumption, EPA essentially changes the level of harm in the PM 2.5 NAAQS to levels far below those in the NAAQS. Two questions thus arise:
 Should the assumption of a linear dose

- response function down to roughly background levels be subject to public review before being used in a RIA?13  What would be the benefits (and cost to benefit ratios) in the RIA if only mortality above, but not below, the NAAQS were included? **In implementing these rules, emission controls may lead to reductions in ambient PM2.5 below the PM NAAQS in some areas. It is important to e**  **mphasize that NAAQS are not set at a level of zero risk.**  **Instead, the NAAQS reflect the level determined by the Administrator to be protective of public health within an adequate margin of**  **safety, taking into consideration effects on susceptible populatio ns based on the**  **scientific literature available at the time the standard is set. While benefits occurring**  **below the standard may be less certain than those occurring above the standard, EPA considers them to be legitimate components of the total benefits**  **estimate. Additionally, in this RIA we binned the estimated population exposed to projected**  **future baseline PM 2.5**  **air quality levels for comparison against the “Lowest Measured Level” (LML) of PM**  **2.5 air quality in the mortality studies. The purpose of thi**  **s analysis is to show whether the estimated premature deaths associated with reduced PM**  **2.5 exposure occur at or above the range of ambient PM**  **2.5 observations studied in Pope et**  **al. (2002) and Laden et al. (2006)**  **, which are the two epidemiological studies that EPA uses to estimate PM**  **2.5 -**  **related premature mortality co** 
**- benefits. We found that a**  **significant proportion of the avoided PM**
**- related premature deaths we estimated in**  **this analysis occurred among populations exposed at or above the LML of each study in**  **the baseline, increasing our confidence in our estimate of the magnitude of the PM**
  ** related premature deaths avoided. Approximately 11% of the avoided premature** **deaths occur at or abov e an annual mean PM**  **2.5 level of 10 μg/m**  **3 (the LML of the Laden**  **et al. 2006 study), and about 73% occur at or above an annual mean PM 2.5**  **level of 7.5 μg/m**  **3 (the LML of the Pope et al. 2002 study). As we model avoided premature deaths**  **among populations expos ed to levels of PM**  **2.5 that are successively lower than the LML**  **of each study our confidence in the results diminishes.**

 Determining Toxicity of Individual PM 2.5 Species, Relevance to MATS RIA
 Since 1996, scientific advisory bodies to EPA (such as the Nati onal Research Council of the National Academy of Sciences) have suggested that different PM 2.5 species are likely to have different toxicity, and that EPA should use toxicology and other means to determine which PM 2.5 species are most, or least harmful. In March, 2009, on

- the

- record public comments were submitted to EPA by DOE/FE staff suggesting a means by which toxicity of specific PM 2.5 species could be determined. In the 2009 Integrated Science Assessment (ISA) for PM, EPA has established several excel lent criteria for judging the degree to which PM 2.5 may be causally related to various health endpoints. The comments suggested that EPA could take advantage of the large number of new studies available, then and especially now, and use the criteria in th e ISA to estimate the degree to which individual PM 2.5 species may be causally related to the health endpoints considered (such as cardiovascular mortality). To be clear, the suggestion was not that EPA create “speciated standards” for particularly toxic PM 2.5 species (e.g., black carbon). To do so might take several years. Rather, the14

suggestion was that EPA use its excellent criteria to determine the strength of evidence for the toxicity of important PM 2.5 species. To do so would enable states, in de veloping plans to reduce PM 2.5 concentrations, to preferentially reduce the most toxic species. The suggestions made in March 2009 are relevant to the MATS RIA, because only particular PM 2.5 species are reduced using the technologies needed to reduce mercu ry emissions by 90%. These species are largely inorganic salts. Should an EPA analysis of the degree to which individual PM 2.5 species may be related to mortality be undertaken, the results could have relevance to the benefits estimates in the MATS RIA. **The Integrated Science Assessment for Particulate Matter (U.S. EPA, 2009), which underwent two rounds of peer review by EPA’s independent Science Advisory Board**  **and public comment, already evaluated the body of scientific evidence regarding the strength of**  **the evidence on particle component toxicity, as recommended by the commenter. This assessment concluded that “many constituents of PM2.5 can be**  **linked with multiple health effects, and the evidence is not yet sufficient to allow differentiation of those c**  **onstituents or sources that are more closely related to specific health outcomes”.**  **The assumption that all particles are equally toxic for the purpose of calculating benefits was supported by the National Academies of Science (NRC, 2002) and the**  **Health Effects Subcommittee of the Advisory Council on Clean Air Compliance Analysis**  **(U.S. EPA**
**- SAB, 2010). We specifically note this uncertainty in the RIA: “This is an**  **important assumption, because PM 2.5**  **produced via transported precursors emitted from EGUs may**  **differ significantly from direct PM 2.5**  **released from diesel engines and other industrial sources, but the scientific evidence is not yet sufficient to allow**  **differential effect estimates by particle type.”**

 We will not repeat in detail here why it is cru cial to utilize studies which include many PM 2.5 species (if an important PM 2.5 species is not included in a study, different PM 2.5 species might rise to the level of a statistically significant risk only in the absence of such species). Nor will we repea t in detail why it is important to use pollution data that reflects subject exposure reasonably accurately (without good subject exposure, the significance and levels of health risks for pollutants whose concentrations are variable across a city will likel y be understated, and risks might be “transferred” to pollutants with less spatial variability). We merely note the importance of these issues for reference. **No response needed.**

 **Section ES.2, Page ES -**  **8:** “EPA believes these unquantified benefits are subs tantial...” It is not clear what value signifies a cutoff between what is substantial and what is insubstantial.15

**Revised to indicate the unquantified benefits “could be substantial.” Since the**  **monetized benefits of this rule are so large, if the unquantif ied benefits were only 1%**  **of the total, they would be worth hundreds of millions of dollars.** 

 **Page ES -**  **3: “**We also include in our monetized benefits estimates the effect from the reduction in CO 2 emissions resulting from this rule.” EPA repeatedly makes a point of not analyzing the impacts of other emission rules on coal retirements, but does not seem to have a problem assigning the benefits to other emissions from this rule. **This is both inaccurate and a non sequitur. The inclusion of CSAPR and other**  **regu latory actions (including federal, state, and local actions) in the IPM base case**  **reflects the industry behavior that will likely occur in response to other requirements apart from MATS. This base case provides meaningful projections of how the power**  **secto r will respond to the cumulative regulatory requirements for air emissions, while**  **isolating the incremental impacts of MATS. Additionally, while the rule targets mercury and other HAP emissions, the technology used to control these pollutants**  **also results in reductions of PM and SO**  **2 . These reductions are expected to result in**  **significant health co**
**- benefits and**  **are an important category to quantify . A**  **nalysis of only one pollutant misrepresents the total impacts of rule.** 

 **Table ES**
**- 3:**  there appears to be disc repancies in the calculated monetary value of avoided IQ loss that should be reconciled. Table ES

- 3 states that, at the 7% discount rate, the estimated monetary value of avoided IQ loss associated with methylmercury exposure from self

- caught fish consumpti on among recreational anglers is reported between $0.000005

–$0.000009 (in billions of 2007$). The Table also states that, at the 3% discount rate, the value is reported between $0.004

–$0.006. The values at 3% and 7% appear to be inconsistent with each oth er. **Revised in 11/23 version.**

 **Section ES.4, Page ES -**  **15:** “Of the 83 small entities affected, 49 are projected to have costs greater than 1 percent of their revenues.” Perhaps EPA should implement a policy to help protect these 49 small entities from propo rtionally large cost increases. **As described in the FRFA in the preamble and Chapter 7 of the RIA, EPA has taken steps to minimize the significant economic impact on small entities. Because this rule**  **does not affect units with a generating capacity of les s than 25 MW, small entities that**  **do not own at least one generating unit with a capacity greater than 25 MW are not subject to the rule. According to the EPA's analysis, among the coal** 
**- and oil** 
**- fired EGUs**  **(i.e., excluding combined cycle gas turbines and g as combustion turbines) about 26**  **potentially small entities only own EGUs with a capacity less than or equal to 25 MW, and none of those entities are subject to the final rule based on the statutory**  **definition of potentially regulated units. For those unit s the commenter references** 16

**that are affected by the proposed rule, the EPA considered a number of comments received, both during the Small Business Advocacy Review (SBAR) Panel and the public**  **comment period. While none of the alternatives adopted in the fi nal rule are**  **specifically applied to small entities, the EPA believes these modifications will make compliance less onerous for all regulated units, including those owned by small**  **entities. Chapter 3:** 
 **Page 3 -**  **5: “** Mercury emissions are modeled as a function of mercury content of the fuel type(s) consumed at each plant in concert with that plant’s pollutant control configuration.” Assuming that EPA uses the USGS’ COALQUAL database, there a some issues that could arise from the use of this data. First , COALQUAL is over 10 years old (1998) and second, it does not account for Hg reductions that could occur from coal washing, and only has the Hg content of coal as it is in the ground. **EPA does not use the USGS COALQUAL database for its IPM modeling assum ptions.**  **Instead, EPA has developed its own assumptions for mercury content in coals through ICRs, independent studies, and industry experts. See IPM documentation for more**  **detail.**

 **Page 3 -**  **5:** “Total PM emissions are calculated exogenously to IPM, using EPA’s Source Classification Code (SCC) and control

- based emissions factors.” Combined with ES

- 1
“The great majority of the estimates are attributable to co

- benefits from 4,300 to 11,000 fewer PM 2.5 - related premature mortalities.” There seems to be a large di sconnect between the fact that PM emissions are exogenously calculated and the fact that they show the largest portion of the benefits. **While PM is exogenously calculated, it is based upon the types of fuel used, emissions control types and costs, and emi**  **ssion modification factors in EPA modeling (all endogenous to the model). In effect, emission estimates are all determined in a**  **similar fashion (reflecting modeled fuel choice and pollution control retrofitting) with certain emissions reported as a direct**  **model output and other emissions (including PM) generated through post** 
**- processing calculations. The process EPA uses to project**  **EGU PM emissions is fully described in the IPM documentation.**

 **Page 3 -**  **7: “**As noted above, IPM has been used for evaluating the economic and emission impacts of environmental policies for over two decades.” Has any retrospective analysis been done comparing IPM projections and actual reality? There is no indication that even though the model has been used for decades that is does a good job predicting what will really happen. **The Agency’s use of IPM is intended to provide accurate estimates of the incremental impact of regulations or policy (e.g., X% increase in electricity prices, X GW of** 17

**additional retirements, $X/ton allowance prices), and is not used as an absolute**  **forecast for the power sector. IPM results are generally consistent with other Agencies’ power sector forecasts (e.g., EIA). Analyses from other researchers**  **(Resources for the Future, MIT) have generally concluded that EPA tends to overstate**  **the costs of regulations.**

 **Page 3 -**  **12, Figure 3 -**  **6:** Based on information presented during the discussions on the proposed rule, EPA was showing a substantial number of existing FGD upgrades resulting from this rule. These upgra des have not been mentioned in the preamble or in the RIA. If the number of these upgrades is substantial, they should be shown in Figure 3

- 6 and their impact should be discussed in detail. In the IPM manual documents, a cost of a scrubber upgrade is sho wn as an allowance of $100/kW. However, this cost is shown only as a fixed O&M cost. We do not agree with this, since a scrubber upgrade would involve expenditure of capital. Such an upgrade would normally require modifications to the scrubber vessel, r eplacement of auxiliary equipment, etc. If a substantial number of such upgrades are required under this rule, these capital costs cannot be ignored. In addition, the fixed O&M costs will go up as well as there would be additional variable O&M costs, sin ce sorbent injection rates would generally have to be increased and/or injection of additives may be required. **EPA agrees and also assumes that there is a capital cost associated with the scrubber upgrade. However, EPA implements this cost assumption in**  **the current IPM environment through the use of an annualized cost adder equivalent to capital**  **expense amortization but is included in the model’s “accounting category” of FOM. The appearance of this cost as FOM is an artifact of current IPM design, even t**  **hough the scrubber upgrade capital expenditure is accurately accounted for in the modeling**  **results. In addition, EPA acknowledges your observation about displaying the magnitude of scrubber upgrading and has added that information to the updated RIA.** 

 Pag e 3

- 12, Figure 3

- 6: Since ESP upgrade was not an option used in the analyses for the proposed rule, we recommend that additional information be provided on this option, either here or in the IPM manual document. We would like a confirmation that only tho se ESP upgrade techniques have been used that do not require extended plant outages to install. For example, a project involving extension of ESP surface area may require an outage lasting more than two years. Such long outages may become another factor c ontributing to the grid reliability issue. **The approach for ESP upgrades will be fully described in the IPM documentation. The supplemental documentation for final MATS explains the procedure used to**  **determine the type and extent of ESP upgrades used. I ncluded is a table that defines**  **each of the three levels of ESP upgrade that were considered (including characteristics, trigger points, associated costs, and performance improvements). A**  **detailed spreadsheet is included indicating the type of upgrade sel ected for each**  **evaluated coal unit. About 34 GW of capacity is projected to receive ESP upgrades, of**18

**which 87% is projected receive upgrades that involve no internal flow or area adjustments. EPA believes that these upgrades will require only very short**  **outages that will have no impact on grid reliability. The remaining 13% is projected to incur**  **ESP upgrade costs that could possibly involve internal adjustments. However, these adjustments (assumed to occur at only about 4 GW of capacity total nationwide** **, about 1% of total existing coal capacity) are unlikely to necessitate an outage of a**  **length that it cannot be scheduled appropriately such that the grid operator can accommodate the absence of a particular unit by drawing on other sources of**  **generation t o meet load during the outage period. Furthermore, EPA believes even**  **this projection is conservative because as explained in the IPM documentation, EPA assumed a filterable PM limit for this ESP upgrade analysis that is roughly ten percent**  **below (i.e., mo re stringent than) the filterable PM limit in the final MATS rule.** 

 **Page 3 -**  **12, Figure 3 -**  **6** : Please provide the updated IPM manual document that shows how the costs of ESP upgrade were estimated. **IPM documentation will be transmitted.**

 **Page 3 -**  **25: “**The direct private compliance cost includes, but is not limited to, capital investments in pollution controls, operating expenses of the pollution controls, investments in new generating sources, and additional fuel expenditures.” No accounting for reliability measures in the compliance costs. **IPM represents the cost of reliability measures through the requirement to maintain adequate reserves in each region. A higher level of retirements may cause capacity**  **costs to rise as a result of increased costs of buil ding new capacity needed to satisfy**  **the reserve requirement, or from additional costs for transferring reserves from neighboring regions. IPM modeling captures these costs as increases in capacity prices**  **when the reserve margin constraint is binding, and these costs are reflected in all EPA**  **modeling outputs (e.g., electricity prices or annualized costs).**

 **Section 4.1, Page 4 -**  **1, Paragraph 2** : “It is not expected that mercury benefits would be substantially changed, and given the small magnitude of the benefi ts...” It seems odd that the majority of the benefits of the rule do not come from Mercury, since a major goal of the rule is to reduce mercury. Since the vast majority of benefits come from reducing PM 2.5, is there a more cost

- effective approach to reduci ng PM 2.5 than the Mercury and Air Toxics Standard? This would serve to satisfy Executive Order 13563, which indicates regulations should be chosen that maximize net benefits. **The MACT standard is a technology**
**- based standard that, under the Clean Air Act**  **Amendments of 1990, must not be less than the average emission level achieved by controls on the best performing 12 percent**  **of existing sources by category. While EPA cannot consider cost when setting the MACT floor,**  **EPA has appropriately incorporated**  **provisions in the proposed rule to provide regulated units**  **with flexibility**19

**to reduce emissions in the most cost**
**- effective and efficient manner for that particular**  **unit.**

 **Section 5.2.2, Page 5 -**  **11: “The appropriate economic measure is therefore ex ante Will**  **ingness to Pay (WTP) for changes in a risk.”** In general, willingness to pay (WTP) is problematic because there are an infinite number of areas individuals could be asked to place a value on, yet individuals have a finite budget; thus, it seems likely that WTP would likely overstate what an individual would actually be willing and able to pay. Therefore, WTP should be constrained to not exceed a typical individual's budget. **While we agree that budget constraints are important considerations for well**
  ** design** **ed WTP studies, we disagree that budget constraints disqualify the use of all WTP studies. . EPA’s use of WTP estimates to quantify the economic value of avoided**  **deaths and certain illnesses is consistent with advice received from the EPA Science Advisory**  **Board (SAB). In particular, the SAB noted that “conventional benefit**
**- cost**  **analysis is based on the identification of potential Pareto improvements (i.e., the "Kaldor** 
**- Hicks criterion" or "compensation test"). Straightforward application of the**  **Kaldor**
**- Hicks**  **criterion implies EPA should account for any and all individual characteristics that influence an individual's (or household's) willingness to pay for**  **reduced health risk.” The SAB also noted that, “[ c]oncerning morbidity, the Agency**  **should continue to us e Willingness** 
**- to**  **- Pay (WTP) estimates for morbidity values** **, rather than cost** 
**- of** 
**- illness (COI) estimates, should these be available. Where WTP is**  **unavailable, COI estimates can be used as placeholders, awaiting further research, provided suitable caveats are**  **included in the analysis.” Finally, the SAB recommended that t**  **he Agency should “continue to use WTP estimates when these are available ,**  **rather than COI estimates... [and] it is important to recognize that the COI estimates are not appropriate alternative es** **timates to be substituted for WTP estimates because they do not reflect the preferred concept of valuation” (U.S. EPA** 
**- SAB 2004a**  **and U.S. EPA**
**- SAB 2004b). In addition, each of the WTP estimates that EPA uses have**  **been peer reviewed and supported by the SAB.**

 **Section 5.3, Pages 5 -**  **19 and 5**
**- 20:**  The assumption that all fine particles are equally potent in causing premature mortality is important, as changes to premature mortalities make up the vast majority of total benefits. Since some studies have found no si gnificant effect of PM2.5 on mortality, perhaps zero should be included in the range of PM2.5 benefits, as Electric Power Research Institute has suggested. EPRI indicated: “Since some models in some studies do not find a statistically significant effect of PM2.5 on mortality, the effects range could even include zero...” (Source: EPRI PM2.5 Reductions and Impact on Premature Death: An EPRI perspective; Issue Brief 1018632.) Also, the same EPRI briefing states the EPRI

- Washington University Veterans Study di d not find any statistically significant mortality associations with PM2.5, but found some PM components that were significantly associated with mortality. The EPRI briefing goes on to say: “Of great significance for CAIR, this study did not find a signif icant association between the sulfate component of PM and mortality...if this study were20

used to derive estimates of health benefits attributable to reductions in SO2 emissions, the numbers would differ from those derived from the Pope et al...some studies h ave shown that estimated impacts of PM diminish when other co

- pollutants are considered in the analyses. If the co

- pollutants are indeed associated with increased mortality and are correlated with PM levels, then the PM effects estimated from this single p ollutant model approach can be biased upwards.” **EPA disagrees with this recommendation. As described in the RIA, EPA estimates avoided PM** 
**- related premature mortality based on risk estimates from the American**  **Cancer Society cohort (Pope et al., 2002) and the Harvard Six Cities cohort (Laden et**  **al., 2006) as well as providing mortalities estimates based on the results of an expert elicitation (Roman et al,2008) as a characterization of uncertainty. The choice of these**  **studies was supported by the Health Ef fects Subcommittee of the Advisory Council on**  **Clean Air Compliance Analysis. In addition, when EPA conducted an expert elicitation on the relationship between PM2.5 exposure and premature mortality in 2006, the**  **experts placed most weight on the results of these two studies.**  **The Integrated Science Assessment (ISA) for Particulate Matter (U.S. EPA, 2009), which was twice reviewed by the Science Advisory Board, concluded that there is a causal**  **relationship between exposure to PM2.5 and premature mortality af ter reviewing the**  **entire body of scientific evidence. In addition, the ISA also concluded that the scientific evidence is not yet sufficient to allow differentiation of effect estimates by**  **particle type. This means that while some PM mixtures may be more toxic than other**  **mixtures, the scientific literature does not support the commenter’s assertion that some particles are not toxic. Although we note this uncertainty in the RIA, we assume**  **that all particles are equally toxic for the purpose of calculating b enefits. This**  **assumption was supported by the National Academies of Science and the Health Effects Subcommittee of the Advisory Council on Clean Air Compliance Analysis.** 

 **Section 5.4.2.5, Page 5 -**  **35:** “Although the association was not statistically signif icant for cough, the results were still positive and close to significance; consequently, we decided to include this endpoint...” It does not make sense to use a statistically insignificant result in deriving estimates. If the sign had been negative, would it have been included? **The health endpoints included in this RIA are consistent with previous RIAs. The Science Advisory Board Health Effects Subcommittee recommends the addition of**  **asthma**
**- related symptoms (i.e., asthma exacerbations) to the primary anal**  **ysis, provided that the studies use the panel study approach and that they have**  **comparable design and baseline frequencies in both asthma prevalence and exacerbation rates (SAB** 
**- HES, 2004). Note that the SAB** 
**- HES, while supporting the**  **incorporation of asthma exacerbation estimates, does not believe that the association**  **between ambient air pollution, including ozone and PM, and the new onset of asthma is sufficiently strong to support inclusion of this asthma** 
**- related endpoint in the**  **primary estimate. The Ostr o et al. (2001) study was included since it was close to** 21

**statistical significance, not because it showed a positive result. Note that a negative relationship between PM and cough would not be biologically plausible.** 

 **Section 5.4.4.1, Page 5 -** **42:** “Given the mixed theoretical finding and empirical evidence regarding adjustments to VSL for risk and population characteristics, we use a single VSL for all reductions in mortality risk.” It seems more logical to use a range of value of statistical life (VSL) estimates, rather than a single value, in order to account for the uncertainty in the measure. **As described in the RIA, EPA determined that a single, peer**
**- reviewed estimate applied**  **consistently best reflects the advice it has received from the EPA’s independent**  **Science Advisory Board until updated guidance on mortality valuation is available. The Agency continues its efforts to update its guidance on this issue.** 

 **Section 5.4.4.1, Page 5 -** **43** : “An ideal benefits estimate of mortality risk reduction would reflect these human characteristics, in addition to an individual’s WTP to improve one’s own chances of survival plus WTP to improve other individuals’ survival rates.” Capturing the WTP to improve other individuals’ survival rates would be an example of a non - use value, thus creating a bias. Individuals likely also place a value on non

- use things such as less government regulation; for instance, Executive Order 13563 directs Agencies to “identify and consider regulatory approaches that reduce burdens and maintain flexibility and freedom of choice for the public.” **This issue does not impact the benefit estimates presented in the RIA because the specific VSL value applied by EPA is not based on studies that include WTP for the**  **reduction in mortality risk of other individuals.** 

 **Section 5.4.4.2, Page: 5 -** **46** : WTP for avoiding chronic bronchitis ($340,000) likely exceeds an average individual’s budget, especially after considering essentials such as food, clothing, housing, etc. $340,000 is greater than six y ears of income for an individual earning $50,000 per year. **We believe this comment reflects a misunderstanding of how the WTP value for avoided cases of chronic bronchitis was calculated in the economics literature that**  **provides the basis of this estimate . In each of the two studies used to quantify the**  **WTP (Krupnick and Cropper 1992; Viscusi et al. 1991), the researchers elicit the value that survey participants are willing to pay to reduce their risk of contracting chronic**  **bronchitis by a small amount. T he value of this small change in risk may then be**  **aggregated to produce an implied value of a single case of chronic bronchitis. This is similar to EPA’s approach to mortality valuation.** 

 **Section 5.4.4.1, Pages 5 -** **40, 5 -** **42:** “The VSL approach is a summary m easure for the value of small changes in mortality risk experienced by a large number of people.” On22

page 5

- 42, EPA indicates it uses a VSL of $6.3 million. This seems to be an unreasonably large value. A more practical measure of the value attributed to an increase in expected life for the affected individuals would be the amount of income these individuals could expect from living longer due to the rule. This would have the effect of preventing the number from exceeding an individual’s remaining lifetime income, since one cannot pay more than that amount. So, if the average affected individual could be expected to earn $250,000 more during his or lifetime, multiplying $250,000 by 11,000 (number of premature deaths), would result in an upward bound of tot al benefits of the rule due to premature deaths of $2.75 billion. **We disagree with this comment. EPA’s use of WTP estimates to quantify the economic value of avoided deaths is consistent with advice received from the EPA Science**  **Advisory Board. In particu lar, the SAB noted that “VSL is the conceptually appropriate**  **method for assessing the benefits of avoided premature mortality.” (U.S. EPA**
**- SAB**  **2004a and U.S. EPA**
**- SAB 2004b). Similar to our response on the comment regarding**  **chronic bronchitis valuation, the valuation estimate is simply an aggregation of WTP**  **for small changes in risk. As described in the RIA, EPA determined that a single, peer**
  ** reviewed estimate applied consistently best reflects the advice it has received from** **the SAB until updated guidance o n mortality valuation is available. The Agency**  **continues its efforts to update its guidance on this issue.**

 **Section 5.4.5.2, Page 5 -**  **50, Table 5**
**- 12:**  Willingness to pay (WTP) is problematic because there are an infinite number of areas individuals could be asked to place a value on, yet individuals have a finite budget; thus, it seems likely that WTP would likely overstate what an individual would actually be willing and able to pay. Therefore, WTP should be constrained to not exceed a typical individual's budget. **While we agree that budget constraints are important considerations for well**
  ** designed WTP studies, we disagree that budget constraints disqualify the use of all** **WTP studies. We disagree with this comment. EPA’s use of WTP estimates to quantify t**  **he economic value of avoided deaths and certain illnesses is consistent with advice received from the EPA Science Advisory Board. In particular, the SAB noted that**  **“conventional benefit**
**- cost analysis is based on the identification of potential Pareto**  **impro vements (i.e., the "Kaldor** 
**- Hicks criterion" or "compensation test").**  **Straightforward application of the Kaldor**
**- Hicks criterion implies EPA should account**  **for any and all individual characteristics that influence an individual's (or household's) willingness**  **to pay for reduced health risk.” The SAB also noted that, “[ c]oncerning**  **morbidity, the Agency should continue to use Willingness**
**- to**  **- Pay (WTP) estimates for**  **morbidity values , rather than cost** 
**- of** 
**- illness (COI) estimates, should these be**  **available. Where WTP is unavailable, COI estimates can be used as placeholders,**  **awaiting further research, provided suitable caveats are included in the analysis.” Finally, the SAB recommended that t**  **he Agency should “continue to use WTP estimates when these are available** **, rat her than COI estimates... [and] it is important**  **to recognize that the COI estimates are not appropriate alternative estimates to be**23

**substituted for WTP estimates because they do not reflect the preferred concept of valuation” (U.S. EPA** 
**- SAB 2004a and U.S. EPA** 
**- SAB 2004b). In addition, each of the WTP**  **estimates that EPA uses have been peer reviewed and supported by the SAB. Section 5.6, Page 5**  **- 88, middle paragraph**  : “The fourth value is the 95 th percentile of the SCC from all three models at a 3% discount rate. It is included to represent higher

-than

expected impacts from temperature change further out in the tails of the SCC distribution.” Why not include a fifth value at the 5 th percentile in order to represent lower

- than

- expected impacts from temperature chan ge? **The Social Cost of Carbon (SCC) values used to estimate climate benefits for the MATS final rule are consistent with the recommendations of the Interagency Working Group**  **on the SCC discussed extensively in the Technical Support Document (SCC TSD)**  **avai lable on OMB’s website at:**  **http://www.whitehouse.gov/sites/default/files/omb/inforeg/for**
**- agencies/Social** 
**** **Cost -**  **of**
**- Carbon** 
**- for** 
**- RIA.pdf. The main purpose of this exercise was to develop a**  **schedule of SCC values that can be applied consistently across regulato ry analyses and**  **Agencies. The TSD clearly states that: The interagency group selected four SCC values for use in regulatory analyses. Three**  **values are based on the average SCC across models and socio**
**- economic and emissions**  **scenarios at the 2.5, 3, and 5 percent discount rates. The fourth value is included to**  **represent the higher**
**- than** 
**- expected economic impacts from climate change further out**  **in the tails of the SCC distribution. For this purpose, we use the SCC value for the 95 th**  **percentile at a 3 percent discount rate. (The full set of distributions by model and**  **scenario combination is included in the Appendix.) As noted above, the 3 percent discount rate is the central value, and so the central value that emerges is the average**  **SCC across models at the 3 percent discount rate. For purposes of capturing the**  **uncertainties involved in regulatory impact analysis, we emphasize the importance and value of considering the full range.**  **The SCC modeling exercise, which included 3 models, 3 discount rates, and 5 socioeconomic scenarios, produced 45 separate distributions of SCC for a given year.**  **Prior to seeing the results of the exercise, the interagency group agreed to combine the distributions for the models and scenarios at each discount rate and selected the**  **statistics to present for each distribution in RIAs. In particular, the interagency group found it necessary to limit the number of estimates presented to four to maintain**  **coherence while also reflecting the uncertainty of the estimation exercise. In sh ort,**  **the group concluded that presenting more than four estimates in the summary tables, which typically provide estimates for non** 
**- GHG benefits and for multiple years, would**  **overwhelm the reader. It is also worth noting that the shape of the distributions —**  **skewed to the right with a long tail —**  **supports the decision to present the 95 th**  **percentile estimate.**24

**In keeping with the interagency directive, EPA used this approach for the Light Duty Vehicle Rule to estimate benefits from CO**  **2 emission reductions and**  **thi s approach has**  **been used in all subsequent EPA regulatory actions to date. OMB led**  **the SCC Interagency Working Group to develop this approach**  **and several other interagency reviewers for the MATS final rule actively participated. It is our understanding tha**  **t any deviation from the approach outlined in the**  **SCC TSD would have to be reviewed**  **and considered by the interagency group before it could be implemented by the EPA or other agencies.**  **Moreover, key questions about the relevant assumptions to use regardin g risk**  **aversion motivated the interagency group to present the 95 th**  **percentile estimate in addition to the average estimates. The SCC TSD elaborates on limitations of the**  **analysis and remaining questions about risk aversion (page 30). Specifically, a key question is the relevant assumption to be made about relative risk aversion with**  **regard to high**
**- impact climate outcomes. The current SCC values do not consider the**  **possibility that individuals may have a higher willingness to pay to reduce the likelihood o** **f low**
**- probability, high impact outcomes than they do to reduce the**  **likelihood of higher**
**- probability but lower impact damages with the same expected**  **costs. “The inclusion of the 95 th**  **percentile estimate in the final set of SCC values was largely motivated b** **y this concern.” The interagency group also noted that estimates of climate damages are far more uncertain under more extreme climate change**  **scenarios. Based upon the foregoing, EPA recommends that the SCC estimates remain as presented in the MATS final RI**  **A submitted to OMB and the interagency review group.** 

 **Section 5.8, Page 5 -**  **99, first paragraph: We estimate that by 2016 the rule will have reduced the number of PM2.5** 
**- related premature deaths by between 4,300 and**  **11,000...”** It would be useful for EPA to pro vide an estimate of the average amount of time these 4,300 to 11,000 individuals would live beyond what would otherwise be a premature death without implementation of the rule. **EPA does not have the necessary data to estimate avoided life years lost for this rule.**  **However, in the 2006 PM NAAQS RIA, EPA estimated that the discounted average gain in life years is 10 years. In Hubbell (2006), the estimate of average undiscounted life**  **years gained was 15.26 years.**

 **Section 6.1, Page 6 -**  **1:** “From an economic perspective, labor is an input into producing goods and services. If regulation requires that more labor be used to produce a given amount of output, the additional labor is reflected by an increase in the cost of production.” It should be noted that the decrease in labor productivity would cause the short

- run aggregate supply curve to shift to the left, with the result being that businesses produce less (i.e., lower GDP).25

**Noted in RIA in a footnote**  **.**

 **Section 6.1, Page 6 -**  **2:** “With significant numbers of workers unemployed, the opportunity costs associated with displacing jobs in other sectors are likely to be much smaller.” It seems that even at unemployment levels of 9 percent, 91 percent of the labor force is still working and thus the opportunity costs associated with displacing jobs in other sectors is not likely to be much smaller. **Revised to say “smaller.”**

 **Section 6.3, Page 6 -**  **7, first paragraph** : “When a regulation is promulgated, the first response of industry is to order pollution control equipmen t and services in order to comply with the regulation when it becomes effective.” It should be noted that an alternative first response is for individual plants to shut down in order to avoid the higher costs associated with the pollution control equipment and services. **EPA acknowledges that there will be some retirements and has included estimates in Chapter 3, along with potential employment losses associated with those retirements**  **(in additional to estimates for the pollution control sector). In additio**  **n, EPA has revised the language in this paragraph to indicate that this type of industry response is**  **one possible, but not the only, response to the promulgation of regulation that will affect them.** 

 **Section 6.3, Page 6 -**  **7, first paragraph: “Revenue and employment in the environmental technology industry...”**  A clear definition of what industries (e.g., NAICS codes) are included in the environmental technology industry is needed. **The following is now note d in the RIA: The definition of the environmental technology**  **industry from the Department of Commerce’s ITA FY 2010 environmental technologies industries assessment is not according to NAICS code but instead is “all goods and**  **services that generate revenue associated with environmental protection,**  **assessment, compliance with environmental regulations, pollution control and prevention, waste management, renewable energy, remediation of contaminated**  **property, design and operation of environmental infrastructu re, and the provision and**  **delivery of environmental resources.”**

 **Section 6.2.1, Page 6 -**  **6, Table 6**
**- 2:**  Since the overall results of the Morgenstern et al. study are statistically insignificant, it seems more practical to not provide corresponding job estimat es, but to simply indicate the overall employment impacts were found to be statistically insignificant. Additionally, a summary of other studies that have estimated the effects of regulation on the economy would be useful. **Because of the interest in empl oyment EPA has used this study for a number of**  **regulations to estimate the mean net employment and provided the 95% confidence**26

**interval results to reflect the high degree of uncertainty (the interval includes zero so we are showing we don’t know the sign o** **f the effect but the interval itself is helpful when others give exaggerated claims of huge job changes well outside our 95%**  **confidence interval). There is now a footnote in the RIA that expresses this point.**  **Additional studies are being explored at thi s time. If needed, the 2011 OMB Report to**  **Congress on the Costs and Benefits of the Federal Regulations has a short summary of the literature which we could cite.** 

 **Section 8.1, Page 2, Table 8**
**- 1**  : It may be more clear to the reader to change “+B” to “+NB,” (Net Benefits) because the reader has to search through the various footnotes in order to find that “B is the sum of all unquantified benefits and disbenefits.” **EPA disagrees with this suggesti on. Readers would still have to reference the**  **footnotes to find the meaning of “NB”.**