## ORAL ARGUMENT NOT YET SCHEDULED UNITED STATES COURT OF APPEALS FOR THE DISTRICT OF COLUMBIA CIRCUIT

NATIONAL ASSOCIATION OF ) CLEAN WATER AGENCIES, ) ) 

## Petitioner, ) ) v. ) No. 11 - 1131 (consolidated ) with 11 - 1167 and 11 - 1185) ENVIRONMENTAL PROTECTION ) AGENCY and LISA PEREZ JACKSON, ) ADMINISTRATOR, EPA, ) ) Respondents. )

___________________________________ )

EPA’S OPPOSITION TO EMERGENCY JOINT MOTION FOR STAY OF THE SEWAGE SLUDGE INCINERATION RULE USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 1 of 23

(Page 1 of Total)1 

## Respondents, the Environmental Protection Agency and Lisa Perez Jackson (“EPA” or “Agency”) submit this Opposition to the “Emergency Joint Motion for Stay of the SSI Rule” filed by Petitioners , the National Association of Clean Water Agencies and Hatfield Township Municipal Authority (collectively “NACWA”). See Doc. #1330427 (“NACWA Mot

.”). For the reasons stated below, NACWA’s Motion must be denied

. BACKGROUND Petitioners seek to stay EPA’s final rule entitled “Standards of Performance for New Stationary Sources and Emission Guidelines for Existing Sources: Sewage Sludge Incineration Units,” 76 Fed. Reg. 15 ,372 (Mar. 21, 2011) (“SSI Rule” or “Rule”). That Rule sets New Source Performance Standards and Emission Guidelines under Clean Air Act (“CAA” or “the Act”) Section 129, 42 U.S.C. § 7429, to reduce emissions of nine air pollutants from new and existing sewage sludge incinerators. 1 

## CAA Section 129, entitled “Solid Waste Combustion,” requires EPA to establish emissions standards for certain categories of “solid waste incineration units.” Id. A “solid waste incineration unit” is “a distinct operating unit of any

1 

## The nine pollutants are: cadmium, carbon monoxide, hydrogen chloride, lead, mercury, nitrogen oxides, particulate matter, polycholorinated dibenzo

-p-dioxins and polychlorinated dibenzofurans, and sulfur dioxide. 42 U.S.C. § 7429(a)(4). USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 2 of 23

(Page 2 of Total)2 

## facility which combusts any solid waste material from commercial or industrial establishments or the general public (including single and multiple residences, hotels, and motels).” Id. § 7429(g)(1)

. Section 129 specifies categories of solid waste incineration units for which EPA must establish standards: those combusting municipal solid waste, hospital and medical waste, industrial or commercial waste, and “other categories of solid waste incineration units” that combust waste not specifically identified. Id. § 7429(a)(1)(A)

-(E); see Davis County v. Solid Waste Mgmt. v. EPA , 101 F.3d 1395, 1403 (D.C. Cir. 1996) ; NRDC v. EPA , 489 F.3d 1250, 1255 (D.C. Cir. 2007). Sewage sludge incinerators are one of the “other categories of solid waste incineration units” that EPA is required to regulate under Section 129. A sewage sludge incinerator is a device at a wastewater treatment facility that combusts domestic sewage sludge to reduce the volume of sludge. 76 Fed. Reg. at 15 ,374. This combustion releases various air pollutants. Id. at 15 ,375. EPA’s SSI Rule regulates two subcategories of new and existing sewage sludge incinerators: multiple hearth incinerators and fluidized bed incinerators. 2 

## Section 129 directs EPA to set emissions standards that “reflect the Id. at 15 ,376.

2 

## Section 129 gives EPA discretion to “distinguish among classes, types . . . and sizes of units within a category” to establish the standards. 42 U.S.C

. § 7429(a)(2). USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 3 of 23

(Page 3 of Total)3 

## maximum degree of reduction in emissions” of air pollutants, “taking into consideration the cost of achieving such emission reduction, and any non

-air quality health and environmental impacts and energy requirements [that EPA] determines is achievable for new or existing units in each category.” 42 U.S.C. § 7429(a)(2). This is referred to as the “maximum achievable control technology” level of control, or “MACT.” See Ne. Md. Waste Disposal Auth. v. EPA Maryland, 358 F.3d 936, 940 (D.C. Cir. 2004) ; NRDC, 489 F.3d at 1254. EPA develops MACT standards through a two

-step process. First, EPA determines the minimum level of stringency that the Act requires

– the “MACT floor.” For new units, the MACT floor is “the emissions control . . . achieved in practice by the best controlled similar unit . . . .” 42 U.S.C. § 7429(a)(2). For existing units, the MACT floor is “the average emissions limitation achieved by the best performing 12 percent of units in the category.” Id. Second, EPA determines whether more stringent beyond

-the

-floor standards are achievable based on costs, non

-air quality health and environmental impacts, and energy requirements. Id

. Here, EPA determined that beyond

-the

-floor MACT standards were not warranted and adopted MACT floor standards for each of the nine pollutants emitted from the multiple hearth and fluidized bed sewage sludge incinerators. 76 Fed. Reg. at 15,394. USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 4 of 23

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## STANDARD OF REVIEW A stay is a disfavored remedy and “it is the movant’s obligation to justify the court’s exercise of such an extraordinary remedy.” Cuomo v. U .S. Nuclear Regulatory Comm’n, 772 F.2d 972, 978 (D.C. Cir. 1985). To determine whether a stay is warranted, the Court stringently applies four factors: (1) whether the movant has demonstrated a substantial likelihood that it will prevail on the merits; (2) the prospect of irreparable injury to the movant if relief is withheld; (3) the possibility of harm to other parties if relief is granted; and (4) the public interest. Nken v. Holder, 129 S. Ct. 1749, 1761 (2009) . “A stay is not a matter of right, even if irreparable injury might otherwise result.” Id. at 1760 (citation omitted). Demonstrating a substantial likelihood of success on the merits requires a showing that NACWA is likely to persuade this Court that EPA’s SSI Rule is “arbitrary, capricious, an abuse of discretion, or otherwise not in accordance with law.” 42 U.S.C. § 7607 (d)(9)(A). This narrow, deferential standard presumes the validity of agency actions and prohibits the Court from substituting its judgment for that of the Agency

. Motor Vehicle Mfrs. Ass’n v. State Farm Mut. Auto. Ins. Co. , 463 U.S. 29, 43

-44 (1983). Judicial deference also typically extends to any agency’s interpretation of a statute it administers

. United States v. Mead Corp. , 533 U.S. 218, 227

-31 (2001); Chevron, U.S.A., Inc. v. Natural Res. Def. Council, Inc. , 467 U.S.. 837, 842

-45 (1984)

. USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 5 of 23

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## Irreparable harm requires injury that is “both certain and great, it must be actual and not theoretical.” Wis
. Gas C o. v. FERC, 758 F.2d 669, 674 (D.C. Cir. 1985). The injury must be “of such imminence that there is a clear and present need for equitable relief to prevent irreparable harm.” Id. (citation omitted); see also Nken, 129 S. Ct. at 1761 (more than a “mere possibility” of success on the merits is required, and the standard for irreparable harm requires more than showing the “possibility” of harm). ARGUMENT I. INDUSTRY PETITIONERS CANNOT DEMONSTRATE A SUBSTANTIAL LIKELIHOOD OF SUCCESS ON THE MERITS A. EPA Reasonably Regulated Sewage Sludge Incinerators Under CAA Section 129. Chevron guides review of NACWA’s claim that the SSI Rule conflicts with the Clean Air Act. The Court “must decide (1) whether the statute unambiguously forbids the Agency’s interpretation, and if not, (2) whether the interpretation, for other reasons exceeds the bounds of the permissible.” Barnhart v. Walton, 535 U.S. 212, 218 (2002). Here, under Chevron step one, EPA’s regulation of sewage sludge incinerators under Section 129 is reasonable

. First, this Court in Natural Resources Defense Council v. EPA , 489 F.3d 1250 (D.C. Cir. 2007), specifically determined that Section 129 “plainly and broadly” defines “solid waste incineration unit” “to include ‘a distinct operating USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 6 of 23

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## unit of any facility which combusts any solid waste material from commercial or industrial establishments or the general public . . . .’” Id. at 1257 (quoting 42 U.S.C. § 7429(g)(1)). “The word ‘any’ is usually understood to be all inclusive.” Id. (citation and internal quotation marks omitted). Consistent with that unambiguously broad language, EPA determined that Section 129 covers incineration units that combust sewage sludge

– a type of solid waste

– and established emission standards for such units. NACWA’s attempt to distinguish NRDC on the ground that it involved a different type of incinerator is irrelevant. NACWA Mot

. at 10. The Court’ s opinion regarding the definition of “solid waste incineration unit” is directly on-point and NACWA should not be allowed to constrict “the scope of this plain, broad language

.” 489 F.3d at 1258. Second, Section 129(a)(1)(E) requires EPA to establish standards for “other categories of solid waste incineration units,” in addition to the specific categories of solid waste incineration units listed in subsections (a)(1)(B) through (D). 42 U.S.C

. § 7429(a)(1)(B)

-(E). As this Court has found, that broad language specifically allows EPA the “discretion to identify ‘ other categories of solid waste incineration units.’” Davis County, 101 F.3d at 1405 (emphasis in original). Here, EPA reasonably interpreted that phrase to include sewage sludge incinerators

– which are solid waste incinerators

– as one of the “other categories” under Section 129. USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 7 of 23

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## NACWA disagrees, arguing that sewage sludge incinerators do not fall under “other categories” because sewage sludge comes from within the publicly owned treatment works (“POTW”) rather than “ ’ from commercial or industrial establishments or the general public’ under § 129(g)(1).” NACWA Mot

. at 9. This is a distinction without difference. Sewage sludge is “a solid, semi

- solid, or liquid residue generated during the treatment of domestic sewage in a [POTW] .

. . .” EPA

-HQ

-OAR

-2009

-0559

-0028 at 1 (Exh. 1 relevant pages attached hereto)

. “Domestic sewage is generated by residences, businesses, etc. . . .” Id. Sewage sludge therefore originates from the general public and residential and commercial facilities. The POTW’s treatment of that domestic waste to separate out from the waste stream the sewage sludge that will be combusted does not change the original source of the sewage sludge. 76 Fed. Reg. at 15 ,383. 3

3 

## Under Clean Air Act Section 7429(g)(6), the term “solid waste” has the definition established by EPA under the Resource Conservation and Recovery Act (“RCRA”). NACWA argues that EPA “concluded that these [sewage] sludges are not solid waste” in a 1990 rulemaking. NACWA Mot

. at 9 (citing 55 Fed. Reg. 46,354, 46364 (Nov. 2, 1990)). On March 21, 2011, however, EPA finalized a rule under RCRA, which included sewage sludge in the definition of non

-hazardous solid waste. See 76 Fed. Reg. 15 ,456, 15 ,513 (Mar

. 21, 2011). NACWA filed a petition for review of that RCRA solid waste definition in this court. Plus , the 1990 Federal Register notice to which NACWA refers addresses only hazardous waste, for which EPA has established a separate regulatory definition under RCRA. See 40 C.F.R. Pt. 261. USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 8 of 23

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## Finally, Section 129 explicitly excludes certain incinerators f rom the definition of solid waste incineration units , 42 U.S.C. § 7429(g)(1); see Davis County, 101 F.3d at 1398 , and sewage sludge incinerators are not among those exclusions . “Where Congress explicitly enumerates certain exceptions to a general prohibition, additional exceptions are not to be implied, in the absence of a contrary legislative intent.” Sierra Club v. EPA , 551 F.3d 1019, 1028 (D.C. Cir. 2008) , cert denied, 130 S. Ct. 1735 (2010) (citation omitted). NACWA argues that EPA must regulate sewage sludge incinerators under Section 112, which requires EPA to establish emissions standards for sources of hazardous air pollutants . NACWA Mot

. at 5

-8

. To support its view, NACWA isolates a single provision of Section 112

– subsection (e)(5)

– which is contained in the section entitled “Schedule for standards and review.” 42 U.S.C. § 7412(e). That provision, however, merely provides a deadline for EPA to establish emissions standards for hazardous air pollutants from POTWs. 42 U.S.C. § 7412(e)(5); see 76 Fed. Reg. at 15,383. Subsection (e)(5) does not require EPA to regulate sewage sludge incinerators under Section 112. Reading Section 112 in conjunction with Section 129 dispels NACWA’s argument. Read together, it is clear that Congress did not intend for Section 112 to trump regulation of solid waste incinerators under Section 129. Section 112 is a more general provision that applies to hazardous air pollutants from all listed USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 9 of 23

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## source categories , whereas Section 129 is more specific and applies to certain pollutants (some of which are not hazardous air pollutants) from a particular type of source

– solid waste incineration units. See NRDC, 489 F.3d at 1256. “The principle that a specific statutory provision prevails over a more general provision is established beyond question.” F.T.C. v. Manager, Retail Credit Co., Miami Beach Branch Of fice, 515 F.2d 988, 993 (D.C. Cir. 1975) (citations omitted). “However inclusive may be the general language of a statute, it will not be held to apply to a matter specifically dealt with in another part of the same enactment . . . .” Id. at 994, n.10 (citations and internal quotation marks omitted). Here, EPA’s interpretation is a reasonable one that gives meaning and effect to both Sections: Section 129 requires (and EPA has established) emissions standards for certain pollutants from sewage sludge incinerators at POTWs , whereas Section 112 requires emissions standards for hazardous air pollutants from other parts of the POTW that do not combust solid waste and, thus, are not solid waste incineration units

. 4

## NACWA prefers to focus on the interplay between Section 112(e)(5) and the Clean Water Act, rather than the structural relationship in the Clean Air Act

4 

## As noted below, EPA set POTW standards years ago under Section 112 and did not include sewage sludge incinerators. USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 10 of 23

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## between Sections 112 and 129

. NACWA is correct that Section 112(e)(5) incorporates the Clean Water Act’s definition of POTW or “treatment works .” The relationship between Section 112(e)(5) and the Clean Water Act, however, has no bearing on which emissions standards

– Section 112 or Section 129

– should apply
to sewage sludge incinerators. 5



## To buttress its view that EPA must regulate sewage sludge incinerators under Section 1 12, NACWA resorts to prior EPA “regulatory pronouncements.” NACWA Mot

. at 6, 7. Such statements are irrelevant to whether the plain language of Section 129 allows EPA to regulate sewage sludge incinerators. Moreover, the regulatory statements on which NACWA relies pre-date this Court’s opinion in NRDC

. The salient point is that Section 112(e)(5) says nothing that requires regulation of emissions from solid waste incinerators,

whereas Section 129 does.

6

5 

## EPA’s regulation of sewage sludge incinerators under Section 129 does not undermine its regulation of the final use and disposal of sewage sludge under the Clean Water Act regulations at 40 C.F.R. Pt. 503. See 76 Fed. Reg. at 15,375. Importantly, Clean Water Action Section 405 specifically states that nothing is intended to waive more stringent requirements of the Clean Water Act or any other federal law. 33 U.S.C. § 1345

. Even if prior EPA pronouncements were relevant, however, NACWA dismisses EPA’s 1999 emissions standards for POTWs under

6 

## Additionally, NACWA’s reliance on these notices is misplaced as EPA explained in the final rule. 76 Fed. Reg. at 15 ,383. USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 11 of 23

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## Section 112(d), which specifically excluded sewage sludge incinerators

. See 64 Fed. Reg. 57 ,572 (Oct. 26, 1999). In fact, in the proposal for those standards, EPA stated that “[s]ewage sludge incineration will be regulated under section 129 of the CAA, and will be included in the source category Other Solid Waste Incinerators [.]” 63 Fed. Reg. 66,084, 66,087 (Dec

. 1, 1998). For these reasons, EPA’ s interpretation of Section 129 is reasonable. B. EPA Reasonably Used A Statistical Methodology To Determine The MACT Floor for Existing Units Under Section 129. NACWA’s challenge to EPA’s use of a statistical methodology to help determine the MACT floors for existing units also is subject to a Chevron analysis. 7

7 

## NACWA does not challenge EPA’s methodology for determining the MACT

floor for new units. Section 129 provides that the MACT floor for existing units “shall not be less stringent than the average emissions limitation achieved by the best performing 12 percent of units in the category[.]” 42 U.S.C. § 7429(a)(2). There are 204 sewage sludge incinerators in operation, and out of those, 144 are multiple hearth units and 60 are fluidized bed units. See EPA

-HQ

-OAR

-2009

-0559

-0157 at 3 (Exh. 2 attached hereto) . Thus, 12 percent of each of those units (rounding up to the nearest whole integer) is 18 multiple hearth units and 8 fluidized bed units. Id. at 6. EPA was able to collect actual data for 20 multiple hearth units and 6 USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 12 of 23

(Page 12 of Total)12 

## fluidized bed units, but not all of these units had data for every pollutant. 8 

## For those pollutants where EPA did not have enough data, EPA used all of the quality

-assured data it did have to determine the MACT floor, and then verified this data using a statistical methodology to determine the minimum number of observations (or actual data) needed to reflect the performance of the best 12 percent of units. Here, the number of observations or data that EPA collected actually equaled or exceeded the minim um number of observations that were

necessary according to this statistical methodology. EPA therefore was able to determine that the collected data mirrored the data of the best performing 12 percent of units in the source category. Thus, the MACT floor calculation from the collected data is consistent with what it would have been if EPA had collected actual data from the best performing 12 percent of units. Exh 2 at 6

- 10

. Id.

The issue at hand is whether EPA must, in all cases, use only actual data from the best performing 12 percent or units, or if EPA can use other approaches (such as the statistical methodology used here) in conjunction with actual data to determine the MACT floors. In Sierra Club v. EPA , 167 F.3d 658 (D.C. Cir. 1999), this Court answered that question and determined that the phrase “average

8 

## EPA collected actual data for mercury and particulate matter for 12 percent of the multiple hearth units and, thus, was able to base the MACT floor for those units and pollutants on that data. USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 13 of 23

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## emissions limitation achieved by the best performing 12 percent of units” “does not by its plain meaning exclude estimation, either by sampling or some other reliable means.” Id. at 66 1

-62

. Under Chevron, the Court determined that Section 129 says “nothing about how the performance of the best units is to be calculated.” Id. at 66 1. Also, “EPA typically has wide latitude in determining the extent of data

-gathering necessary to solve a problem” and the Court “generally defer[s] to an agency’s decision to proceed on the basis of imperfect scientific information, rather than to invest the resources to conduct the perfect study.” Id. at 662 (citation and internal quotation marks omitted). As long as EPA’s approach for making the estimation bears a “rational relationship to the reality it purports to represent,” EPA’s methodology will be upheld. Id. Here, EPA’s statistical methodology is permissible because it allowed a “reasonable inference” based on actual data “as to the performance of the top 12 percent of units.” Sierra Club, 167 F.3d at 663. EPA also explained “why its methodology yields the required estimate.” Cement Kiln Recycling Ass’n v. EPA , 255 F.3d 855, 862 (D.C. Cir. 2001); see Exh. 2 at 6

- 10

. As EPA explained, this statistical methodology assures that the data EPA collected adequately represent data from the best performing 12 percent of units in each subcategory. Exh. 2 at 9. The methodology also accounts for various factors to ensure that the minimum number of observations necessary to make that determination is not an arbitrary USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 14 of 23

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## number. The fact that EPA’s collected data equaled or exceeded the minimum number of observations determined under the methodology assures that the MACT floor calculations are what they would have been if EPA had been able to collect a complete dataset from the best performing 12 percent of units

. 9 

## C. EPA Reasonably Accounted For Variability In Sewage Sludge Emissions. This Court has recognized EPA’s authority to account for varia bility in setting MACT floors, Cement Kiln, 255 F.3d at 863 (quoting Sierra Club, 167 F.3d at 665) , which reflects the fact that even the performance of the best units will not always be the same. Here, EPA collected emissions data from nine different facilities in nine different states across the country. 76 Fed. Reg. at 15,391. The facilities represent residential and commercial populations as well as varying winter and early spring climates

– the seasons during which the majority of the air

9 

## Section 129’s MACT floor provision for existing sources stands in contrast to the corresponding MACT floor provision in Section 112. Section 112 requires the MACT floor to reflect the average emissions limitation achieved by the best performing 12 percent of sources “for which the Administrator has emissions information.” 42 U.S.C § 7412(d)(3) (A) . Section 129 does not contain this qualifier. Because Congress envisioned that Section 129 standards would be based on the average of all sources in the top 12 percent of the source category, the ability to reasonably estimate the sources’ emissions, rather than rely only on actual emissions testing data for each source, is appropriate to ensure that MACT floor standards are established in a timely manner, and do in fact reflect the emissions performance of the top 12 percent of sources. USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 15 of 23

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## emissions testing were conducted. Id. Taken together, these data

– from a variety of facilities

– adequately incorporate variability in air emissions from wastewater treatment systems across the country. Id. NACWA wants EPA to account for variability in a different way

– by looking at the variability of the sludge feed in addition to looking at the variability of the air emissions. NACWA Mot. at 12

- 14. EPA, however, already appropriately accounted for geographic variability by gathering emissions data from facilities that are spread across the country in different climates. 76 Fed. Reg. at 15,391. Additionally, EPA applied a statistical methodology (the Upper Predictive Limit) that analyzed variability of air emissions tests within a unit over time based on various factors to account for future variability. Exh. 2 at 10

- 14, 11

- 12. Thus, the MACT

-floors reflect the potential variations in the air emissions that may result from variations in the sludge content. 10 

## II. INDUSTRY PETITIONERS CANNOT DEMONSTRATE AN IMMINENT THREAT OF IRREPARABLE HARM None of NACWA’s alleged economic injuries is sufficient to warrant a stay.

10 

## NACWA does not dispute the reasonableness of EPA’s use of the UPL to account for variability and, instead, argues that EPA should have used inadequate sampling data under the Clean Water Act and incomplete stack test data to account for variability. NACWA Mot

. at 13

- 14. It is not for this Court, however, to substitute its judgment for that of the Agency concerning how to best account for variability. Motor Vehicle Mfrs. Ass’n, 463 U.S. at 43

-44. USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 16 of 23

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## First, NACWA relies on a request by New York State asking POTWs either to certify, by June 30, 2011, that they will comply with the SSI Rule, or to shut down their sewage sludge incinerator by March 21, 2012. See NACWA Mot

. at 15

. NACWA also argues that the Commonwealth of Virginia is “planning to ‘move quickly’ to implement the SSI Rule.” NACWA Mot

. at 15, Ex. 3, ¶ 8. Both of these State actions or representations

– which neither EPA nor the SSI Rule requires

– come at least two and a half years before the Rule’s compliance date for existing units. 11



## Second, NACWA claims its members will suffer unrecoverable economic losses because the installation of new pollution control devices is time

-consuming and costly. NACWA Mot

. at 17

- 18. Allegations of mere economic injuries, Moreover, NACWA’s purported harm from independent actions by States

– not EPA

– to require early compliance commitments or shutdowns, or to fast

-track implementation of the SSI Rule, does not “directly result from the action which the movant seeks to enjoin, ” i.e. , the SSI Rule. See Wis

. Gas, 758 F.2d at 674 (emphasis added).

11 

## Under the SSI Rule, the compliance date for new sources is the earlier of 60 days af ter the unit reaches the feed rate at which it will operate or within 180 days after initial startup. 76 Fed. Reg. at 15,373. Existing sources must come into compliance either three years after EPA approves a state plan implementing the emissions guidelines, or five years after promulgation of the Rule, whichever is earlier. USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 17 of 23

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## “however substantial, in terms of money, time, and energy” simply are not enough to support granting a stay. Wis
. Gas, 758 F.2d at 674. NACWA’s expenditures for pollution control equipment represent the costs of compliance with government regulation, which “ordinarily is not irreparable harm.” Am. Hosp. Ass’n v. Harris, 625 F. 2d 1328, 133 1 (7 th 

## Cir. 1980). As the Third Circuit has explained, “[a]ny time a corporation complies with a government regulation that requires corporation action, it spends money and loses profits; yet it could hardly be contended that proof of such an injury, alone, would satisfy the requisite for a preliminary injunction,” i.e. , an irreparable injury. A.O. Smith Corp. v. FTC, 530 F.2d 515, 527 (3 rd 

## Cir. 1976). Compliance costs would be sufficient only if the “very existence” of the POTW itself is threatened, see Wis
. Gas, 758 F.2d at 674, which none of NACWA’s declarations alleges . 12

12 

## None of NACWA’s declarants state that their POTWs actually will decide to shut down their sewage sludge incinerators or that doing so would threaten the existence of the entire facility as opposed to just the use of the sewage sludge incinerator within the facility. Moreover, out of the 204 operating sewage sludge incinerators, EPA estimates that 155 of them currently are meeting the emissions limitations in the SSI Rule. 76 Fed. Reg. at 15,386. The fact that approximately 75% of sewage sludge incinerators already meet the SSI Rule USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 18 of 23

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## standards belies NACWA’s notion that compliance costs are so harmful as to warrant a stay, or that installation of pollution control measures is impracticable. Third, NACWA claims that the SSI Rule will cause environmental harm because some facilities will be “forced” to switch to landfilling, and some may stop conducting environmentally beneficial projects such as incineration. See NACWA Mot. at 15

- 16. 13 

## As EPA explained, the method chosen to treat sewage sludge is a local choice

– not a choice “forced” upon these facilities by EPA or the SSI Rule

– which depends on “environmental protection concerns, community needs, geographic constraints, and economic conditions.” 76 Fed. Reg. at 15 ,395. 14



## Finally, NACWA argues that if POTWs install new control equipment to comply with the SSI Rule and the Court invalidates the SSI Rule, EPA will be able Thus, a municipality’s choice to pursue a potentially more costly landfilling option rather than the less costly incineration option is not a harm that directly results from the SSI Rule

– it results from the municipality’s choice.

13 

## NACWA also argues that there will be “environmental impacts” if municipalities are “forced” to switch to landfilling, such as increased methane emissions from the landfill and increased emissions from trucking the sewage sludge to the landfills. NACWA Mot

. at 27. Although EPA disagrees with NACWA ’s increased greenhouse gas argument, such an impact, even if true, is not an irreparable harm to NACWA

. 14 

## Some municipalities may find landfilling to be a more cost

-effective and environmentally

-friendly alternative. 76 Fed. Reg

. at 15 ,395. USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 19 of 23

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## to use the lower emissions from the new control equipment to set future MACT floors . NACWA Mot

. at 17. This alleged harm, however, is too speculative, i.e. , if a unit installs pollution control equipment, if the Rule is vacated, and if EPA subsequently uses those new controls to set MACT floors, NACWA may be harmed. Such conjectural harm is insufficient. See Nken, 129 S. Ct. at 1761. III. A STAY WOULD HARM THE ENVIRONMENT AND THIRD PARTIES AND BE CONTRARY TO THE PUBLIC INTEREST We address the last two stay factors together because the harm to each is similar. As to the harm to third parties, the Court must consider whether “despite showings of probable success and irreparable injury on the part of petitioner, the issuance of a stay would have a serious adverse effect on other interested persons.” V

a. Petroleum Jobbers Ass’n v. Fed

. Power Comm ’n, 259 F.2d 921, 925 (D.C. Cir. 1958). As for where the public interest lies, “[i]n litigation involving the administration of regulatory statutes designed to promote the public interest, this factor necessarily becomes crucial. ” Id. Here, the interests of NACWA “must give way to the realization of public purposes .” Id. The Clean Air Act “protect[s] and enhance [s] the quality of the Nation’s air resources so as to promote the public health and welfare and the productive capacity of its population.” 42 U.S.C. § 7401(b)(1). To that end, the SSI Rule reduces the emission of nine air pollutants that are known or suspected of causing USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 20 of 23

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## cancer and other serious health effects. Specifically, EPA estimates that the Rule will reduce nationwide emissions from sewage sludge incinerators by:

**•** 19

-30 tons per year of hydrogen chloride **•** 430

-700 tons per year of acid gases **•** 58

-70 tons per year of particulate matter, and **•** 1 .7 tons per year of lead 76 Fed. Reg. at 15 ,398 ; see id. 15,400 (charts summarizing monetized benefits) ; EPA

-HQ

-OAR

-2009

-0559

-0159 (Exh. 3 attached hereto) (summarizing predicted health incidences for particulate matter) ; EPA

-HQ

-OAR

-2009

-0559

-0042 at Section 5 (Exh. 4 relevant pages attached hereto) . Also, EPA expects that the SSI Rule will result in annual health benefits that will decrease premature death, certain illnesses, incidences of emergency room visits, days when people miss work, and days when people must restrict their activities. Exh. 4 at Section 5. Finally, as compared to the compliance costs about which NACWA complains, EPA estimates the net benefits from the SSI Rule to be $26 million to $220 million, depending on the type of discount rate applied. Id. p. 1

-2 and Section 5. A stay of this Rule will only further delay these important environmental and health benefits. CONCLUSION For the foregoing reasons, EPA respectfully requests that the Court deny the Emergency Joint Motion for Stay of the SSI Rule. USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 21 of 23

(Page 21 of Total)21 

## Respectfully Submitted, IGNACIA S. MORENO Assistant Attorney General /s/ Michele L. Walter Michele Walter, DC Bar # 487329 United States Department of Justice Environmental & Natural Resources Division P.O. Box 23986 Washington, D.C. 20026

-3986 Michele.Walter@ usdoj.gov Tel: 202

-514

-2795 Attorney for Respondents Dated: October 11, 2011 USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 22 of 23

(Page 22 of Total)22 

## CERTIFICATE OF SERVICE The undersigned hereby certifies that, on October 11, 2011, a true and correct copy of the foregoing EPA’S OPPOSITION TO EMERGENCY JOINT MOTION FOR STAY OF THE SEWAGE SLUDGE INCINERATION RULE, was served electronically through the ECF system on all registered counsel.

_

/s/ Michele L. Walter

__________ MICHELE L. WALTER USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 23 of 23

(Page 23 of Total)

# Exhibit 1

USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 1 of 2

(Page 24 of Total)

### Differences between Sewage Sludge, Medical Wastes, Hazardous Wastes and Municipal Solid Wastes and the Incinerators Used to Combust these Materials

X X X X X X X Y X X Y X ?C X X X X X X X Y X X Y X X X X X X X X X X X X X X X X X X X X X X X Y X X X Y X X X ~C X X X Y X


### A. Sewage Sludge Sewage sludge (biosolids) is defined as a solid, semi

-solid, or liquid residue generated during the treatment ofdomestic sewage in a publicly owned treatment works (POTV~, and consists ofsolids removed in primary, secondary, or advanced wastewater treatment processes and any material derived from sewage sludge (e.g., blended sewage sludge/fertilizer product). Domestic sewage is generated by residences, businesses, etc., located in the POTWs services area, along with Stormwater runoff, and is transported to the POTWs via sewers. All ofthe sewage is treated at POTWs which are owned by municipalities or other governmental agencies, as a service to its rate payers. The land application, surface disposal and incineration ofsewage sludge is regulated under 40 CFR Part 503 (Use or Disposal of Sewage Sludge). Sewage sludge incinerators are regulated under Subpart E ofthe Part 503 Regulation, which established pollutant limits, operational standards and recording, monitoring & reporting requirement that ensure protection ofhuman health and the environment. This includes, but is not limited to:

- Site specific emission limits for arsenic, cadmium, chromium, lead and nickel

- Compliance with the NESHAP limits for beryllium and mercury
- Compliance with an operational standard for total hydrocarbon or an alternative standard for carbon monoxide Sewage sludge incinerators are also regulated under 40 CFR Part 60, Subpart O (New Source Performance Standards for Sewage Sludge Treatment Plants) and Section 112 of the Clean Air Act (Hazardous Air Pollutants). There are two types of incinerators that are used to combust sewage sludge (i.e., multiple hearths and fluidized beds). 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 2 of 2

(Page 25 of Total)

# Exhibit 2

USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 1 of 28

(Page 26 of Total)vyu~rw.~r~.~t~fn

MEMORANDUM To: Amy Hambrick, U.S. EPA, Sector Policies and Programs Division/Natural

Resources and Commerce Group From: Eastern Research Group, Inc.
Date: January 2011 Subject: Revised MACT Floor Analysis for the Sewage Sludge Incinerator Source

Category
1.0 INTRODUCTION AND SUMMARY OF RESULTS The U.S. Environmental Protection Agency (EPA), under section 129 of the Clean Air Act (CAA),is required to regulate emissions of nine pollutants from sewage sludge incineration (SSI) units. The nine pollutants are: hydrogen chloride (HCI), carbon monoxide (CO), lead (Pb), cadmium (Cd), mercury (Hg), particulate matter (PM), total mass basis dioxins /furans (TMB PCDD/PCDF)and toxic equivalency basis dioxin/furans (TEQ PCDD/PCDF),nitrogen oxides (NOX), and sulfur dioxide (SOZ). The purpose of this memorandum is to present the methodology used to determine the ma~mum achievable control technology (MACT) floor limits for SSI units. The MALT floor analysis was conducted using emissions data obtained from responses to an Information Collection Request (ICR). Emissions test information for each of the Section 129 pollutants was analyzed, MACT floor averages were calculated, and then a data variability analysis was conducted. The MACT floor emissions limits were determined based on the results of these analyses. Table 1 -1 summarizes the MACT floor limits for existing sources regulated by the SSI emission guidelines (EG)and the MALT floor limits for new sources regulated by the SSI new source performance standards (NSPS). The table presents limits for two subcategories under the EG and the NSPS: multiple hearth incineration units (MH) and fluidized bed incineration units (FB). For both the MH and FB new source subcategories, the best performing FB unit was used as the best performing similar source. The discussion of the SSI subcategories is presented in section 3.0. Table 1-1. Summary of MALT Floor Limits for Sewage Sludge Incinerators
Pollutant Units EG NSPS FB MH FB MH Cd m /dscm 0.0016 0.095 0.0011 0.0024 Pb m /dscm 0.0074 0.30 0.00062 0.0035 H m /dscm 0.037 0.28 0.0010 0.15 PM m /dscm 18 80 9.6 60 HCl mvd 0.51 1.2 0.24 1.2 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 2 of 28

(Page 27 of Total)Table 1-1. Summary of MACT Floor Limits for Sewage Sludge Incinerators (Continued)
Pollutant Units EG NSPS FB MH FB MH SOZ mvd 15 26 5.3 26 NOX mvd 150 220 30 210 CO mvd 64 3,800 27 52 PCDD/PCDF TMB ng/dscm 1.2 5.0 0.013 0.045 PCDD/PCDF TEQ ng/dscm 0.10 0.32 0.0044 0.0022

The memorandum is organized as follows: 2.0 Background of MALT Floor Methodology 3.0 Development of Subcategories for SSI Source Category 4.0 MALT Floor Determination Methodology 5.0 Summary of Results 6.0 References 2.0 BACKGROUND OF MACT FLOOR METHODOLOGY All standards established pursuant to CAA Section 129(a)(2) must reflect MALT,the maximum degree ofreduction in emissions of certain listed air pollutants that the Administrator, taking into consideration the cost of achieving such emission reduction, and any non-air quality health and environmental impacts and energy requirements, determines is achievable for each category. This level of control is referred to as a MALT standard. The minimum level of stringency is called the MALT "floor," and CAA Section 129(a)(2) sets forth differing levels of minimum stringency that EPA's standards must achieve, depending on whether they regulate new or existing sources. For new units, the MACT floor cannot be less stringent than the emission control that is achieved in practice by the best controlled similar unit. Emission standards for existing units may be less stringent than standards for new units, but cannot be less stringent than the average emission limitation achieved by the best performing 12 percent of units in the category. These requirements constitute the MALT floor for new and existing sources; however, EPA may not consider costs or other impacts in determining the MALT floors. EPA must consider cost, non-air quality health and environmental impacts, and energy requirements in connection with any standards that are more stringent than the MACT floor (beyond

-the-floor controls).
MALT analyses involve an assessment of the emissions from the best performing units in a source category. The assessment can be based on actual emissions data, on knowledge of the air pollution control in place in combination with actual emissions data, or on state regulatory 2 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 3 of 28

(Page 28 of Total)requirements that may enable EPA to estimate the actual performance of the regulated units and

other relevant emissions information. For each source category, the assessment involves a review of actual emissions data with an appropriate accounting for emissions variability. Other methods of estimating emissions can be used provided that the methods can be shown to provide reasonable estimates of the actual emissions performance of a source or sources. In a March 2007 court decision (Sierra Club v. EPA, 479 F. 3d 875 [DC Cir. 2007]) (Brick MAC7~ EPA was directed to set MALT floors with the following guidance:

• Floors for e~sting sources must reflect the average emission limitation achieved by the best

-performing 12 percent of existing sources, not levels EPA considers to be achievable by all sources (479 F. 3d at 880 -81).

• EPA cannot set floors of "no control." The court reiterated its prior holdings, including National Lime Association, confirming that EPA must set floor standards for all HAP emitted by the major source, including those HAP that are not controlled by at-the-stack control devices (479 F. 3d at 883).

• EPA cannot ignore non-technology factors that reduce HAP emissions. Specifically, the court held that "EPA's decision to base floors exclusively on technology even though nontechnology factors affect emissions violates the Act" (479 F. 3d at 883).

• EPA may not use emission levels of the worst performers to estimate variability of the best performers without a demonstrated relationship between the two (479 F. 3d at 882). These decisions were incorporated into the MALT floor analysis for SSI units. 3.0 DEVELOPMENT OF SUBCATEGORIES FOR SSI SOURCE CATEGORY The Clean Air Act allows EPA to subcategorize a source category based on differences in class, type, or size. There are two types of incinerators currently used to combust sewage sludge (or biosolids): MH units and FB units. Of the 204 sewage sludge incineration units in operation, 60 use the FB design, while 144 use the MH design. The two types are significantly different combustor designs. A MH unit consists of a vertical cylinder containing from 6 to 12 horizontal hearths and a rotating center shaft with rabble arms. Biosolids enter the top hearth and flows downward while combustion air flows from the bottom to the top. The MH is divided into three zones. The upper hearths comprise the drying zone in which biosolids, water, and some organic compounds are evaporated. The middle hearths comprise the combustion zone. The exposure to the combustion gas and biosolids to high temperature is only in this section and residence time of the gas is short. The lower hearths form the cooling zone, where ash is cooled as its heat is transferred to the incoming combustion air. Multiple hearth units are sensitive to any change in the feed, such as feed moisture and feed rate. Since the emissions of CO and organic compounds are dependent on the temperature of the top hearth, any changes occurring in the biosolids input can cause operational upset with momentary drop in top hearth temperature and increase in emissions.' 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 4 of 28

(Page 29 of Total)In an FB unit, the reactor is a vertical steel shell comprised offour sections. The lower

section is called the windbox and acts as a plenum in which combustion air is received. Above the windbox is a refractory arch. The section above the refractory arch is filled with sand and is called the bed area or combustion zone. Hot air is distributed homogeneously throughout the fluidized bed. The intensive mixing of the solid and gas in the fluidized state results in a high heat transfer resulting in rapid combustion of the biosolids. The section above the bed is the freeboard or disengagement zone. The freeboard provides six to seven seconds of gas residence time which complete the combustion of any volatile hydrocarbons escaping from the bed. ~ The differences between the two combustor designs result in significant differences in emissions, size of the flue gas stream, ability to handle variability in the feeds, control of temperature and other process variables, auxiliary fuel use, and other characteristics. Generally, FB units have lower emissions of organic compounds, PCDD/PCDF, and CO than MH units due to the combustion temperature, mv~ing, and residence time differences.''2 This comparison is demonstrated in EPA's Compilation of Emission Factors (also referred to as AP-42)2, and in the emissions information gathered to support developing these proposed standards.3 Intermittent operations, involving frequent shutdown and startup, are generally easier and more rapid for FB units than MH units. Additionally, FB units have better capability of handling feeds with varying moisture and volatile contents. Lower excess air and auxiliary fuel is required to operate FB units resulting in smaller flue gas flow rates and consequently smaller sized downstream control devices. To reflect the differences in their combustion mechanisms, two subcategories, FB and MH,were developed for existing and new SSI sources. 4.0 MACT FLOOR DETERMINATION METHODOLOGY Section 129(a)(2) of the CAA requires that EPA determine the emission control that is achieved in practice by the best controlled similar unit when establishing the MALT floor for new units, and the average emission limitation achieved by the best performing 12 percent of units when establishing the MALT floor for existing units. EPA must exercise its judgment, based on an evaluation of the relevant factors and available data, to determine the level of emission control that has been achieved by the best performing SSI units under variable conditions. The Court has recognized that EPA may consider variability in estimating the degree of emissions reduction achieved by best

-performing sources and in setting MALT floors. (See Mossville Envt'1 Action Now v. EPA,(370 F.3d 1232, 1241 -42 D.C. Cir 2004), holding EPA may consider emission variability in estimating performance achieved by best

-performing sources and may set the floor at a level that best

-performing sources can expect to meet "every day and under all operating conditions"). Maximum Achievable Control Technology and other technology -based standards are necessarily derived from short-term emissions test data, but such data are not representative of the range of operating conditions that the best performing facilities face on a day -to -day basis. In statistical terms, each test produces a limited data sample, not a complete enumeration of the available data for performance of the unit over a long period of time.4 EPA,therefore, often needs to adjust the short-term data to account for these varying conditions. The types of

4 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 5 of 28

(Page 30 of Total)variability that EPA attempts to account for include operational distinctions between and within

tests at the same unit. "Between-test variability" can occur even where conditions appear to be the same when two or more tests are conducted. Variations in emissions may be caused by different settings for emissions testing equipment, different field teams conducting the testing, differences in sample handling or different laboratories analyzing the results. Identifying an achieved emission level for best performing sources needs to account for these differences between tests, in order for "a uniform standard [to] be capable of being met under most adverse conditions which can reasonably be expected to recur[.]" (See NLA I, 627 F.2d at 431, n. 46.) (See also Portland Cement Assn,486 F.2d at 396 noting industry point that "a single test offered a weak basis" for inferring that plants could meet the standards.) The same types of differences leading to between-test variability also cause variations in results between various runs comprising a single test, or "within-test variability." A single test at a unit usually includes at least three separate test runs. (See 40 CFR 63.7(e)(3) for MALT standards under CAA Section 112 and 40 CFR 60.80 for NSPS under CAA Section 111.) Each data point should be viewed as a snapshot of actual performance. Along with an understanding of the factors that may affect performance, each of these snapshots gives information about the normal, and unavoidable, variation in emissions that would be expected to recur over time. Variability can be accounted for using different statistical methods. For example, recent rules have used the upper limit (UL)or the Upper Prediction Limit (UPL)to determine the MALT floor emission limits. A UL is based on the distribution of the available emission observations (e.g., test runs), and does not embody a predictive aspect that a UPL does. A prediction interval (e.g., a UPL)for a future observation is an interval that will, with a specified degree of confidence, contain .the next (or some other pre-specified) randomly selected observation from a population. In other words, the prediction interval estimates what future values will be, based on present or past background samples taken. Given this defuution, the UPL represents the value the mean of three future test run observations (three-run average) can be expected to fall below, based on the results of the independent sample of size (n)from the same population. Therefore, should a future test condition be selected randomly from any of these sources (i.e., average of three runs), we can be 99 percent confident that the reported level will fall below a MACT floor emission limit calculated using a UPL. Since a source must demonstrate compliance with the MALT floor using the average of a three-run test, the appropriate test condition to use to assess variability is three. If a source had to demonstrate compliance by showing that each individual test run was below the MALT floor emission limit, it would be appropriate to use a future test condition of one. The UPL is an appropriate statistical tool to use in determinuig variability in the SSI data. For this source category, where there is a limited sampling of the source category and we do not have test data from all of the SSI units in the best performing 12% for each subcategory, the predictive aspect of the UPL calculation is especially important. (See sections 4.1 through 4.3 for further discussion of the dataset and the statistical approach.) 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 6 of 28

(Page 31 of Total)4.1 MACT Floor Analvses Dataset As stated earlier, the CAA requires that MALT for new sources be no less stringent than the emission control achieved in practice by the best controlled similar unit. For existing sources, the CAA requires that MALT be no less stringent than the average emission limitation achieved by the best performing 12 percent of units in a source category. Because the number of units in different subcategories maybe different, the number of units that represent the best performing 12 percent of sources in different subcategories may be different. Also, mathematically, the number of units that represent the best performing 12 percent of the units in a subcategory will not always be an integer. To ensure that each MALT standard is based on at least 12 percent of the units in a subcategory, EPA has determined that it is appropriate to always round up to the nearest integer when 12 percent of a given subcategory is not an integer. For example, if 12 percent of a subcategory is 4.1, the standards will be based on the best performing five units even though rounding conventions would normally lead to rounding down to four units. As discussed earlier, there are 204 SSI units, composed of 144 multiple hearth units and 60 fluidized bed units. This procedure results in a top 12 percent comprising 18 MH units and eight FB units. Information collection request surveys were sent to nine municipalities operating SSI units to collect emissions information. To select the surveyed owners, EPA reviewed the inventory of SSI units for the control devices being operated, and identified a subset of units expected to have the lowest emissions based on the type of unit and the installed air pollution controls. EPA believes these controls achieve the most reductions possible for the CAA Section 129 pollutants, and thereby allow EPA to identify for each pollutant the units with the lowest emissions. For example, units were selected that operated more than one of the following technologies: activated carbon injection to reduce Hg and PCCD/PCDF;regenerative thermal oxidizers or afterburners to reduce CO and organics; wet electrostatic precipitators to reduce fine particulate; high efficiency scrubbers such as packed bed scrubbers and impingement tray scrubbers to reduce PM,Cd,Pb, particulate Hg, and acid gases such as HCl and SO2i and units with multiple control devices that could reduce PM,Cd,Pb, particulate Hg, such as venturi scrubber in combination with impingement scrubbers and wet ESPs or with another particulate control device. EPA considered whether non-technology factors, such as the characteristics of the waste combusted, would influence which sources are the best performing. In contrast to regulated MWC units or CISWI units, SSI units receive a more homogenous type of waste to burn. There are variations in the amount of each of the CAA Section 129 pollutants present depending on the regions, climates, and sources of wastewater (commercial or residential). The variations are not as significant as variations that would occur if different types of materials were combusted, e.g., sewage sludge, coal, gas, oil, wood, municipal waste, etc. All SSI units are required to meet the EPA's Office of Water SSI discharge and emission requirements (40 CFR part 503). Part 503 establishes daily average concentration limits for Pb, Cd, and other metals in sewage sludge that is disposed of by incineration. Part 503 also requires that 5SI units meet the National Emission Standards for Beryllium and Hg in subparts C and E,respectively, of 40 CFR part 61. In order to meet the 40 CFR part 503 standards, facilities are already incorporating management practices and measures to reduce waste and limit the concentration of pollutants in the sludge sent to SSI units, such as segregating contaminated and uncontaminated wastes and establishing discharge limits or pre-treatment standards for non-domestic users discharging wastewater to publicly owned treatment works (POTWs). Thus, non-technology measures to reduce emission are 6 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 7 of 28

(Page 32 of Total)already being taken. As a result, the data used to develop the MALT emission limits reflects the

control technologies used at each facility, and the other HAP emission reduction approaches, such as management practices each facility is following to comply with the part 503 standards. The nine companies selected to receive the ICR operate 20 SSI units with the most efficient pollution controls that would reduce emissions of CAA section 129 pollutants of interest. Therefore, the sources identified for testing and the resulting emission information received from the surveyed SSI units represent the best performing SSI units. Six of the nine operate MH units, resulting in 13 MH units surveyed. Three of the nine operate FB units, resulting in seven FB units surveyed. Some owners of multiple units at a facility provided information for less than the total number they operated, e.g. 1 unit instead of 2, because not all units were in operation during the test period. Ofthose 20 units from the nine surveyed municipalities, EPA collected data from 17 units that were in operation (11 MH units and six FB units). The surveyed information was supplemented with test information for nine MH SSI units collected from state environmental agencies public databases. In total, emissions information were collected from FB units and 20 MH units from facilities responding to the ICR and additional test reports provided by state environmental agencies. Attachment H identifies the control devices used at FB and MH units with advanced controls and identifies the nine companies that were sent ICR surveys. Although emissions information was collected from six FB units and 20 MH units, not every test report contained information on all pollutants. Except for PCDD/PCDF and SO2, test information for most of the nine CAA 129 pollutants was available from FB units. PCDD/PCDF data was provided for five FB units, and SOZ data were only available for four units. One facility (operating two FB units) provided "zero" values for SOZ emissions, without providing detection limits. Depending on the pollutant, the number of MH units with emissions information ranges from five to 19. Table 4-1 presents the distribution of emissions information for the CAA section 129 pollutants. The floor analysis was then conducted using all the quality assured emissions information for each pollutant in each subcategory (e.g, all FB units for Cd, and all 14 MH units for Cd), as this information includes emissions data from the population of best performing units. For Hg,data from the top 18 MH units (or 12% of the 144 MH units in the total inventory) were used.

Table 4-1. Summary of the Number of Units with Test Information nn the Section 129 Pollutants Subcategory Pb Cd Hg PM HCl SOS NOS CO PCDD/PCDF FB 6 6 6 6 6 4 6 6 5 MH 14 14 19 18 7 11 8 9 5 Test results from each of these units are based on the results of at least three individual runs per test, meaning that one would expect MACT floor calculations based on a population of 21 FB runs (7 FB units * 3 runs per FB unit) and on a population of 60 MH runs (20 MH unit * 3 runs per MH unit). While EPA does not have actual emissions test data for the population of units that represent the best performing 12 percent, the statistical technique described below is the approach 7 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 8 of 28

(Page 33 of Total)used to establish the existing source MALT floor. The MACT floor calculations are based on all

of the actual quality assured data received (for example, a population of 15 MH runs from five MH incinerators for PCDD/PCDF~. Because the emission data are normally distributed, or can be transformed to be normally distributed (using the log

-normal transformation of the data as described in Section 4.3), a statistical technique can be employed to determine the minimum number of observations needed to accurately characterize the distribution of the best performing 12 percent of units in each subcategory. EPA used this statistical technique because of the lack of data from the full set of the best performing 12 percent of sources. While Congress adopted identical language describing the MALT floor calculation in section 129(a)(2) as it did in section 112(d)(3), the latter section includes a provision stating that the floor for existing sources cannot be less stringent than "the average emission limitation achieved by the best performing 12 percent of the existing sources (for which the Administrator has emissions information)[.]" Section 129, however, simply states that the existing source floor cannot be less stringent than the average emission limitation achieved by the best performing 12 percent of the e~sting sources in the category. Therefore, while EPA believes Congress intended for the MACT floor calculation under each section of the Act to be the same, this difference in the text of the two provisions requires us to establish the MACT floor for section 129 source categories based on the best performing 12 percent of sources in the category. Because EPA does not have that data at this time, the statistical technique described below is the only manner in which we can establish the existing source floor on that basis. This technique (shown in Equation 1)is necessary to provide the assurance that the characteristics of the sampled data set mirror those of the best performing 12 percent of units in the source category. Equation 1 shows that the number of observations is a function of the total population size (in each subcategory), the level of confidence, the level of precision, and degree of the variability (expressed as probability of occurrence).5 Equation 1:

where: n= N* Z *Z *p~q /[(E *E *(N- 1)) +(Z *Z'~p *q)]

n = minimum number of observations or sample size, N = population sizes, Z =the Z-score associated with a specific confidence level, E =level of precision or error tolerance, p = degree of variability of the observations, and q =1 —p.
The number of runs test associated with the total population is N, since EPA set the confidence level at 90°Io for this source category, the Z-score is 1.645); as EPA's level of precision for this case is 20%,E = 0.2; and the degree of variability of the observations is 0.5

a For this calculation, the population size is the number of test runs that correspond to 12% of units in each subcategory (the MACT floor population). Performance tests consist of 3 individual test runs. For the FB subcategory, 12% of 60 units is 8 units, so the population size is 24 observations (8 FB * 3 runs per FB). For the MH subcategory, the population size is 54 observations (18 MH * 3 runs per MH). 8 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 9 of 28

(Page 34 of Total)(which means p and q are both 0.5). Note that a variability of 0.5 maximizes the number of

observations required for collection. Therefore, using a variability of 0.5 is a conservative approach in that its use overestimates the minimum number of observations which may actually overestimate the minunum sample size. In order to assess whether or not the number of observations collected adequately characterizes the population, Equation 1 was applied to each subcategory for each pollutant. If the number of observations collected equaled or exceeded the minimum number of observations calculated using Equation 1, then the MALT floor calculations of the sampled data set are consistent with what the MACT floor calculations would have been had they been performed on the complete data set from the best performing 12% of the population. Table 4-2 demonstrates (for the pollutants with the lowest number of observations) the data utilized by EPA meets or exceeds the number of observations necessary to provide an accurate representation of that data distributed from the best performing 12% of the source population as determined using Equation 1. Table 4-2. Minimum Size Sample Calculation
Number of observations Minimum number of collected and used (for observations (calculated pollutants with lowest Subcategory Population size, N using Equation 1) number of test data) FB 24 11 12 MH 58 14 15

For units whose emissions testing results were below detection levels and who provided numerical detection levels, EPA used the detection levels in the MALT floor analysis. If a source reported a "zero" or a negative value, that run was not used to calculate the average of the test. Each data set used to calculate the MALT floor limits were reviewed for outliers. If emission levels appeared to be three standard deviations from the mean, the test reports containing the emissions information were reviewed to determine if there were any irregularities during the operation of the SSI unit, or during the testing or analysis. Information from three sources was removed from the MALT floor calculations during the review. The HCl emissions for test run 1 conducted by Columbia Metro were two orders of magnitude greater than the other two test runs. Calls to the facility indicated that a data entry error was made for test run 1. The SOZ emissions from Ypsilanti were two orders of magnitude greater than all the other SOZ test information. A review of the source test report indicated a different test method was used than used at all the other facilities providing SOz data. Additionally, the reported emissions in the report could not be replicated using the raw data. The CO emissions reported from one run from tests conducted at one of The Metropolitan Council's St. Paul units was 3 standard deviations greater than the other two test runs in the test. The high value was also 3 standard deviations greater than other tests conducted at the unit. A review of the source test report did not indicate any irregularities during the test run. However, because the value was not consistent with the other tests conducted at the facility and also greater than 3 standard deviations from the other tests, this data point was removed from the MACT floor analysis. 9 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 10 of 28

(Page 35 of Total)The MALT floor analysis for PM was conducted on emissions measured using only EPA

Test Method 5, or equivalent State test methods. Although PM emissions were reported to be collected using other test methods, such as OTM 27, the results from the different test methods were not combined because they do not measure equivalent PM fractions or species. 4.2 MALT Floor Calculation For each unit providing emissions information for a pollutant, the average (mean) of the test runs for all the tests conducted on the unit was calculated. If one test were conducted consisting of three test runs, the emissions from the unit would be the average of the three test runs. If two tests were conducted each consisting of three test runs, the average of all 6 test. runs would be calculated. To conduct the existing source MALT floor analysis for each pollutant, individual SSI units in each subcategory for which EPA had emissions test data were ranked based on their average emissions levels of the pollutant from lowest to highest. The MALT floor was calculated as the average of the test runs from the best performing (i.e., lowest emitting) 12 percent of sources. For the SSI source category, all the quality assured emissions information from the ICR responses and additional test reports collected were used in the MALT floor calculation. That is, for each pollutant the MACT floor emissions level was calculated as the average emission limit for all the test runs from the quality assured emissions data collected. As discussed in section 3.0, two subcategories were developed for new sources. For the FB new source subcategory, the best performing FB unit was used as the best performing similar source. For the MH new source subcategory, the best performing MH unit was used as the best performing similar source. To conduct the new source MACT floor analysis for each pollutant, the SSI unit in each subcategory with the lowest emission test average (mean)from 3 test runs for the pollutant was identified. The MALT floor was calculated as the average emission level of the test runs from the best performing single unit (i.e., lowest emitting). If the lowest emitting source provided emissions information from less than 3 test runs, then the MALT floor was calculated from the next lowest emitting source with at least 3 test runs. This procedure was followed because compliance is based on the average of 3 test runs. 4.3 Incorporating Data Variability The first step in the statistical analysis includes a determination of whether the data used for each MALT floor calculation were normally or log-normally distributed. If the data were normally distributed (e.g., similar to a typical bell curve), then furthervariability analyses could be conducted on the data set. If the data were not normally distributed (for example if the data were asymmetric or skewed to the right or left), then the type of distribution (e.g., log

-normal) was determined and a data transformation was performed (e.g., taking the natural log of the data) to normalize the data prior to conducting the variability analysis. Two statistical measures, skewness and kurtosis, were examined to determine if the data were normally or log-normally distributed. The skewness statistic (S)characterizes the degree of asymmetry of a given data distribution. Normally distributed data have a skewness of zero. A skewness statistic that is 10 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 11 of 28

(Page 36 of Total)greater (less) than zero indicates that the data are asymmetrically distributed with a right (left) tail

extending toward positive (negative) values. Further, the standard error of the skewness statistic (SES)is given by SES = SQRT(6/N) where N is the sample size. According to the small sample skewness hypothesis test, if the skewness statistic (S)is greater than two times the SES, the data distribution can be considered non-normal. The kurtosis statistic (K)characterizes the degree of peakedness or flatness of a given data distribution in comparison to a normal distribution. Normally distributed data have a kurtosis of zero. A kurtosis statistic that is greater (less) than zero indicates a relatively peaked (flat) distribution. Further, the standard error of the kurtosis statistic (SEK)is given by SEK = SQRT(24/N) where N is the sample size. According to the small sample kurtosis hypothesis test, if K is greater than two times the SEK,the data distribution is typically considered to be nonnormal.The skewness and kurtosis hypothesis tests were applied to both the reported test values and the lognormal values of the reported test values. If the S and K statistics of the reported dataset were both less than twice the SES and SEK,respectively, the dataset was classified as normally distributed. An EPA guidance document shows that environmental data are more likely to be log

-normally distributed than normally distributed.6 If neither of the S and K statistics or only one of these statistics was less than twice the SES or SEK,respectively, then the skewness and kurtosis hypothesis tests were conducted for the natural log-transformed data. If both the reported values and the natural-log transformed reported values had S and K statistics that were greater than twice the SES or SEK,respectively, the log-normally distributed dataset was selected as the basis of the floor. If the results of the skewness and kurtosis hypothesis tests were mixed for the reported values and the natural log-transformed reported values, the log

-normal distribution was chosen. After determining the distribution of each dataset, a student's t-test statistic was used. The t-test was used in the promulgated hospital and medical waste incineration (HMWI) rulemaking and proposed Portland Cement rulemaking, and it is more appropriate for smaller sample sizes. The t-statistic is calculated using the following Excel equation: Equation 2:

Where: t-statistic = TINV(2*(1-0.99),n-1)

n =the number of test runs from units in the top 12 percent Next, the average (or sample mean)and sample .standard deviation of the test runs were calculated. For the existing source variability analysis, all the quality assured emission test runs reported for the best performing 12 percent of units in each subcategory were identified. By including multiple emission tests from units with a test average in the top 12 percent, EPA can evaluate intra-unit variability of emission tests over time, considering variability in control device 11 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 12 of 28

(Page 37 of Total)performance, unit operations, and fuels fired during the test. As discussed previously, the UPL

was used for the SSI MALT floor variability analysis. For the e~cisting source analysis, the 99% UPL values was calculated for each pollutant and for each subcategory using the test run data for those units in the best

-performing 12 percent. Since the compliance with the MALT floor emission limit is based on the average of a three-run test, the UPL is calculated by: Equation 3:

Where: ~~L= x +t~0.9~,n -1~x sax~1+ 1~ n era

n =the number of test runs (i.e., sample size) m =the number of test runs in the compliance average s = standard deviation of the emission test data x =mean,i.e., average of the emission test data t(0.99, n-1) = t-statistic for 99% significance and a sample size of n. This calculation was performed using the following two Excel functions: Normal distribution: 99°~o UPL = AVERAGE (Test Runs in Top 12°Io) + [STDEV(Test Runs in Top 12%)

x TINV(2 * 0.99, n-1 degrees of freedom)*SQRT((1 /n)+(1/3))], for aone-tailed tvalue (with 2 x probability), probability of 0.01, and sample size of n Lognormal distribution: 99% UPL = EXP {AVERAGE(Natural Log Values of Test Runs in Top 12%) + [STDEV(Natural Log Values of Test Runs in Top 12%) x TINV(2 * 0.99, n-1 degrees of freedom) * SQRT((1 /n)+(1/3))]}, for aone-tailed t-value (with 2 x probability), probability of 0.01, and sample size of n The 99 percent UPL represents the value which one can expect the mean of future 3-run performance tests from the best

-performing 12 percent of sources to fall below with 99 percent confidence, based upon the results of the independent sample of observations from the same best performing sources. In establishing the limits, the UPL values were rounded up to two significant figures. For example, a value of 1.42 would be rounded to 1.5 (as has been done for other CAA section 129 rules) because a limit of 1.4 would be lower than the calculated MALT floor value. The SSI emissions database for FB units contains data from six units at four facilities. The entities surveyed were requested to provide recent (within the previous five years) emissions test reports. Most survey recipients provided only the most recent report. One facility, with three units, provided results of emissions test conducted for compliance reports spanning a 10 year period. This facility also uses the most advanced pollution controls on their FB units in the subcategory. The one facility comprises 70 percent of the Cd and Pb data, 90 percent of the CO and Hg data, and 75 percent of the HCl data and PM data. As a result, the existing source MALT floors calculated using the UPL methodology, and all the test run data from the one facility, effectively results in calculating more stringent limits more akin to a new source MALT 12 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 13 of 28

(Page 38 of Total)floor than an e~sting source MACT floor. In order to adequately incorporate the emissions from

all the SSI units in the FB subcategory, a weighted UPL was used for calculating the existing source MALT floors for the final rule. The weighted UPL is calculated from a weighted mean and weighted variance as described below. There are many different types of weighting procedures. The most straightforward methodology is to base it on the number of data points (i.e., test runs)from each SSI unit. This weighting scheme ensures that no facility in the MACT best performers pool is over-represented in the computation of the MACT floor. The first step in weighting procedure is to assign a weighting factor to each test run by multiplying each observation for source i and run jwith a weight term, w,;, as shown in equation 4: Equation 4:

Where: w~~ = x —

1 1~ M; N

M~ =the number of observations (i.e., runs)for source i and N =the number of best performing sources in the MACT pool.

The second step is to calculate the mean and total variance for the weighted data from the weight terms using equations 5 and 6: Equation 5:
N M; ~~W~ixii Weighted Mean: xweighted

_ ~ =1 j =1 N Mr w!% i =1 j=1

Equation 6:

Where: N M; r , weighted 12 w~'~xi' — XU 1 Weighted Variance: v'Ne`g'"ed = `_' ;=1 N M. ~K– l~~~w~~

t=1 ) =1

13 K 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 14 of 28

(Page 39 of Total)N =the total number of observations in the MACT best performers pool. K =~M~ Whei~lthe weights are equal to one, the above equations reduce to those for un-weighted data, as expected. As shown in equation 7, the weighted mean and weighted variance are then used in the UPL calculation instead of the simple (i.e., un-weighted) mean and variance.
Equation 7:

UPL = x weighted + t(~.99~ n~ — 1) X ~ weighted lx 1 + 1

1 i2~ YYI~

For MH units, there are more emissions data from a larger number of facilities /units. For example, we have data on Cd and Pb from 11 facilities with 14 units, Hg from 11 facilities with 18 units. The MACT floor calculations are not skewed by 1 or 2 units or facilities. Consequently, the MACT floor for e~sting MH units does not need to be calculated using a weighted UPL. To determine the MACT floor for new sources, a UPL calculation similar to that for existing sources was conducted, except the best performing unit's data within a subcategory was used to calculate the MALT floor emission limit for each pollutant instead of the average of the best performing 12 percent of units. The best performing unit was identified as the lowest emitting source with at least 3 test runs. In summary, the approach ranks individual SSI units based on actual performance and establishes MACT floors based on the best performing source for each pollutant and subcategory, with an appropriate accounting of emissions variability. In other words, the UPL was determined for the data set of individual test runs for the single best performing source for each regulated pollutant from each subcategory. 4.4 Use of Non

-Detect Values Non

-detect values comprise more than 50 percent of the emission data for HCl from FB units and PCDD/PCDF from both MH and FB units and may influence the MACT floor analysis for other pollutants. EPA developed a methodology to account for the imprecision introduced by incorporating non-detect data into the MACT floor calculation. At very low emission levels where emission tests result in non-detect values, the inherent imprecision in the pollutant measurement method has a large influence on the reliability of the data underlying the regulatory floor emission limit. Because of sample and emission matrix effects, laboratory techniques, sample size and other factors, method detection levels normally vary from test to test for any specific test method and pollutant measurement. The confidence level that a value measured at the detection level is greater than zero is about 99 percent. The expected measurement imprecision for an emission value occurring at ar near the method detection level is about 40 to 50 percent. Pollutant measurement imprecision decreases to a consistent level of 10 to 15 percent for values measured at a level about three times the method detection level.

14 

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(Page 40 of Total)One approach that can be applied to account for measurement variability in this situation

starts with defining a method detection level that is representative of the data used in the data pool. The first step in this approach would be identify the highest test

-specific method detection level reported in a data set that is also equal to or less than the average emission calculated for the data set. This approach has the advantage of relying on the data collected to develop the floor emission limit, while to some degree, minimizing the effect of a tests) with an inordinately high method detection level (e.g., the sample volume was too small, the laboratory technique was insufficiently sensitive or the procedure for deternuning the detection level was other than that specified). The second step is to determine the value equal to three times the representative method detection level and compare it to the calculated floor emission limit. If three times the representative method detection level were less than the calculated floor emission limit, we would conclude that measurement variability is adequately addressed and we would not adjust the calculated floor emission limit. If, on the other hand, the value equal to three times the representative method detection level were greater than the calculated floor emission limit, we would conclude that the calculated floor emission limit does not account entirely for measurement variability. Therefore, the use the value equal to three times the method detection level in place of the calculated floor emission limit ensures that the floor emission limit accounts for measurement variability and imprecision. The approach discussed above was used to calculate the proposed MALT floor limit for HCl from FB units, and Hg from MH units. The following additional procedures were followed for PCDD/PCDF total mass basis (TMB)and to~c equivalency (TEQ)basis limits. To calculate a TMB limit, all the 17 congeners of interest were identified and non-detect values that are associated with each were indicated. The mean of the non -detect values was calculated and multiplied by 17 (for the total number of congeners of interest). The mean value was then used as the detection limit of the run. Then, each data set was reviewed to identify the highest testspecific method detection level reported that was also equal to or less than the average emission level (i.e., unadjusted for probability confidence level) calculated for the data set. The second step discussed above and also used for HCl was used to set the limit. To calculate a limit on a TEQ basis, first, the mean of the non-detect values was calculated. Then the tonic equivalency factor (TES for each congener was multiplied by the mean to determine the TEQ for each congener. TEQs for each congener were summed to calculate a TEQ sum value. The TEQ sum was then used as the detection limit for the test run. The second step discussed above and also used for HCl was used to set the limit.
4.4 CO Span Adjustments Carbon monoxide values obtained from emission test reports were reviewed to determine whether the span of the test used was capable of accurately reading the reported value. If the span was inconsistent with the reported value, the CO levels were adjusted to provide a value that was more consistent with the span. EPA Method 10 is structured such that measurement data quality relative to the calibration span of the instrument can be assessed. For example, the allowable calibration error, 15 

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(Page 41 of Total)

### system bias, and drift requirements are directly proportional to the site

-specific instrument

calibration span (i.e., ± 2.0 percent of the calibration span value). For instrument calibration span values of 25 ppmv and less, the allowable calibration error, bias, or drift values are each ± 0.5 ppmv. For a measurement made using an instrumental test method, the equivalent of the method detection level can be assessed using: a square root formula, the reported calibration span value, and the allowable data quality criteria (i.e. the allowable calibration error, bias, and drift values). The estimated CO measurement error resulting from the square root formula was adjusted by a factor of three to be consistent with the methodology EPA applied for non-detect data (where limits no less than three times the method detection level were established). The calculations used to estimate the measurement error are shown in Equations 8 and 9: Equation 8:

Where: For tests where calibration span is greater than 25 ppm:

0.02*calibration span = Method 10 allowable calibration error, system bias, and drift requirement for calibration spans greater than 25 ppm Equation 9:

Where: For tests where calibration span is 25 ppm or less:

0.5 = Method 10 allowable calibration error, system bias, and drift requirement for calibration spans less than or equal to 25 ppm

In order to develop a basis for measurement error, instrument calibration spans in available test reports were reviewed. In most cases, a calibration span was specified in the report. If no span value was reported, the maximum concentration from a protocol gas certificate was used in lieu of the span. In several cases a test report with the exact test date in question was not available to the Agency to extract the calibration span or protocol gas certificates. In order to fill these data gaps, test reports from the same units on alternate dates or test reports from similar units at the same facility were reviewed to identify a likely calibration span for the units in question. If alternate reports were available, the report with the date closest to the test date associated with the CO runs in question was used. Where no span values could be found, it was assumed that if the test was conducted on or before May, 2008, the associated CO span would be 1000 ppm, and tests conducted after May 2008 would have a CO span of 100 ppm. This 16 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 17 of 28

(Page 42 of Total)assumption was made because, before revisions were made to Method 10 in May of 2008, it was

common that units were using the prescriptive span guidance that was listed in the old method.' The current version of EPA Method 10 does not include these span requirements but instead requires the tester to choose calibration ranges that reflect the range of expected emission concentrations at the unit.$ Span values were input into Equations 8 and 9 in order to estimate the measurement error for each run. In cases where the reported emission concentrations were lower than their corresponding measurement errors, the default measurement errors were used in lieu of the reported concentration. Attachment H shows a detailed list of each of the test reports reviewed. The attachment indicates whether a substitution was made to fill data gaps for CO. Additional background on CO measurement imprecision and the basis for this CO span adjustment methodology can be found in separate memoranda.9,'o

5.0 RESULTS Table 5-1 summarizes the MACT floor variability analysis results for existing units. Table 5-2 summarizes the MACT floor variability analysis results for new units. Attachments A-1 through A -8 contain the data and detailed calculation of the UPL for Cd, Pb, Hg,filterable PM,HCI, 502,NOX,and CO at existing FB units. Attachments B-1 through B-8 contain the data and detailed calculation of the UPL for Cd, Pb, Hg,filterable PM,HCI, SO2, NOX,and CO at existing MH units. Attachments C-1 through C-8 contain the data and detailed calculation of the UPL for Cd, Pb, Hg,filterable PM,HCI, SO2, NOX, and CO at all new FB units. Attachments D-1 through D-8 contain the data and detailed calculation of the UPL for Cd, Pb, Hg,filterable PM,HCI, SOZ,NOX,and CO at all new MH units. Attachments E-1 through E-5 summarize the MACT floor variability analysis for PCDD/PCDF at existing and new FB units. Attachments F

-1 through F

-5 summarize the MACT floor variability analysis for PCDD/PCDF at existing and new MH units. Attachment G identifies the control devices used at FB and MH units with advanced controls and identifies the nine companies that were sent ICR surveys. Attachment H lists CO data extracted from test reports and shows the calculations made to determine the appropriate span adjusted values to use in determining the MACT floors for CO.

17 

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(Page 43 of Total)6.0 REFERENCES
A Comparison ofFluid Bed and Multiple Hearth Biosolids Incineration. Ky Dangtran, John Mullen, and Dale Mayrose. Paper presented at the 14`h Annual Residuals and Sludge Management Conference. February 27-March 1, 2000, Boston MA. 2. Compilation of Air Pollutant Emission Factors, Volume I: Stationary Point and Area Sources. Fifth Edition. U.S. Environmental Protection Agency. January 1995. 3. Facility, Unit, and Emissions Test Database for the Sewage Sludge Incineration Source Category. Memorandum from ERG to Amy Hambrick, U.S. EPA. June 2010. 4. Natrella, Experimental Statistics, National Bureau of Standards Handbook 91, chapter 1 revised ed., 1966. 5. Sample Size Requirements for Studying Small Populations in Gerontology Research; Robert B. Noble, A. John Bailer, Suzanne R. Kunkel &Jane K. Straker; Health Services Outcomes Research Methodologies (2006)6:59-67
6. Guidance for Data Quality Assessment: Practical Methods for Data Analysis" EPA/600/R-96/084, July 2000. 7. USEPA,Emissions Measurement Center. Old Version of EPA Method 10. [Online] http://www.epa.gov

/ttn/emc/promgate

/m-l0.pdf. 8. USEPA,Emissions Measurement Center. US EPA Method 10 (Revised). [Online] 2008 May. http://

www. epa. gov/ttn/emc

/promgate/method10r06.pdf. 9. Westlin, Peter. 

### Measurement Imprecisionfor Carbon Monoxide. s.l.: EPA Emissions Measurement Center, January 2011. 10. Incorporating Measurement Error in Reported Carbon Monoxide (CO)and Total Hydrocarbon (THC)Data. Memorandum from ERG to Brian Shrager, U.S. EPA. January 2011.

18 

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(Page 44 of Total)Table 5-1. Summary of MACT Floor Results for Existing Units

Pollutant Units FB Units MH Units Avg of top 12% (wei hted) 99% of

UPL (wei hted) Limits Avg of top 12% 99% of

UPL Limits Cd m /dscm 0.00049 0.00151 0.0016 0.030 0.0947 0.095 Pb m /dscm 0.0026 0.00736 0.0074 0.082 0.295 0.30 H m /dscm 0.010 0.0367 0.037 0.095 0.2722 0.28 PM m dscm 43 17.4 18 41.3 79.1 80 HCl mvd 0.19 0.5072 0.51 0.53 1.14 1.2 SOz mvd 2.8 14.04 15 9.4 25.7 26 NOX mvd 56 143 150 130 217 220 CO mvd 27 63.2 64 1,015 3,775 3,800 PCDD/PCDF n /dscm 0.199 1.15 1.2 0.69 4.95 5.0 PCDD/PCDF TEQ ng/dscm 0.016 0.0998 0.10 0.047 0.314 0.32

~ Proposed limits were rounded up to 2 significant figures. 2 The value shown is the result of the non-detect analysis, which results in using the limit that is based on 3 times the highest detection limit that is less than the average.

Table 5-2. Summary of MALT Floor Results for New Units

Pollutant Units FB Units MH Units Avg of top unit 99% of

UPL Limits Avg of top unit 99°l0 of

UPL Limit' Cd m /dscm 0.00017 0.001098 0.0011 0.00033 0.00231 0.0024 Pb m /dscm 0.00031 0.000618 0.00062 0.00084 0.00343 0.0035 H m /dscm 0.00036 0.000992 0.0010 0.051 0.1502 0.15 PM m /dscm 1.41 9.53 9.6 1.2 59.9 60 HCl mvd 0.044 0.2301 0.24 0.201 0.512 1.23 SO2 mvd 0.62 5.26 5.3 1.2 265 263 NOX mvd 14.9 29.6 30 68.5 206 210 CO mvd 8.21 26.93 27 27.6 51.4 52 PCDD/PCDF n /dscm 0.0109 0.0128 0.013 0.0095 0.0447 0.045 PCDD/PCDF TEQ ng

/dscm 0.0025 0.00431 0.0044 0.00095 0.00212 0.0022
' Proposed limits were rounded up to 2 significant figures. z The value shown is the result of the non-detect analysis, which results in using the limit that is based on 3 times the highest detection limit that is less than the average. 3 Limit calculated for NSPS was higher than for EG. NSPS limits cannot be less stringent than EG limits. Therefore, the EG lunits were used.



### 19 

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### Attachment A Detailed MACT Floor Analysis for Existing FB Sources Cd,Pb,Hg,PM,

HCI,SO2,NOX,and CO
See MACTFIoor_AttachA_F'BVariability.xlsx USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 21 of 28

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### Attachment B Detailed MALT Floor Analysis for Existing MH Units 

### Cd,Pb,Hg,PM,

HCI,S02,NOX,and CO See MACTFIoor_AttachB_MHVariability.~sx USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 22 of 28

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### Attachment C Detailed MACT Floor Analysis for New FB Units Cd,Pb,Hg,PM,HCI,SO2,NOX,and CO
See MACTFIoor_AttachC_FBVariability_NSPS.~sx USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 23 of 28

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### Attachment D Detailed MACT Floor Analysis for New MH Units Cd,Pb,Hg,PM,

HCI,S02,NOX,and CO
See MACTFIoor_AttachD_MHVariability_NSPS.~sx USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 24 of 28

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### Attachment E Detailed MACT Floor Analysis for New and Existing FB and MH Sources PCDD/PCDF
See MACTFIoor_AttachE_FBVariability_DF.~sx USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 25 of 28

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### Attachment F Detailed MACT Floor Analysis for New and

Existing MH Sources PCDD/PCDF
See MACTFIoor_AttachF_MHVariability_DF.~sx USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 26 of 28

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### Attachment G

List of SSI Units with Advanced Control Devices and Companies that Received the ICR Survey
See MACTFIoor Attache Units w advanced controls.xls USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 27 of 28

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### Attachment H Attachment H. CO Spans and Estimated Measurement Error See MACTFIoor_AttachH_CO_SpanAdjustments.xlsx USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 28 of 28

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# Exhibit 3

USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 1 of 2

(Page 54 of Total)MEMORANDUM

TO: SSI NSPSAND EG DOCKET FROM: AMY LAMSON,RISK AND BENEFITS GROUP SUBJECT: HEALTH INCIDENCES FOR SSI FINAL RULE DATE: 2/18/2011

Due to time limitations under the court

-ordered schedule, we were unable to fully update the RIAs for the SSI NSPS and EG for the final rule. We provide this memo to the docket as documentation of the estimated health incidences to support the information in the communication materials. These health incidences were calculated using the methodology described in the proposal RIA using the emission reductions estimated for the final rule, which is available at http://www.epa.~ov/ttn/ecas/ria.html
. Summary of Reductions in Health Incidences from PM2,5 for the Final SSI NSPS and EG in 2015* Final MALT Floor Avoided Premature Mortality Pope et al. 2 Laden et al. 6 Avoided Morbidity Chronic Bronchitis 2 Acute Myocardial Infarction 4 Hospital Admissions, Respiratory 1 Hospital Admissions, Cardiovascular 1 Emergency Room Visits, Respiratory 2 Acute Bronchitis 4 Work Loss Days 320 Asthma Exacerbation 42 M RAD 1,900 Lower Respiratory Symptoms 46 Upper Respiratory Symptoms 35 *These health incidences are 81% lower than those shown in the proposal RIA for this rule. 

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# EX~llblt 4

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### September 2010



# Regulatory Impact Analysis: Standards of Performance for New Stationary Sources and Emission Guidelines for Existing Sources: Sewage Sludge Incineration Units

Prepared for Tom Walton U.S. Environmental Protection Agency Office of Air Quality Planning and Standards (OAQPS) Air Benefit and Cost Group

(MD-C439-02) Research Triangle Park, NC 27711 Prepared by
RTI International 3040 Cornwallis Road Research Triangle Park, NC 27709

RTI Project Number 0209897.004.074 

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### RTI Project Number 0209897.004.074 

# Regulatory Impact Analysis: Standards of Performance for New Stationary Sources and Emission Guidelines for Existing Sources: Sewage Sludge Incineration Units

September 2010 Prepared for U.S. Environmental Protection Agency Office of Air Quality Planning and Standards (OAQPS) Air Benefit and Cost Group

(MD-C439-02) Research Triangle Park, NC 27711 Prepared by
RTI International 3040 Cornwallis Road Research Triangle Park, NC 27709

RTI International is a trade name of Research Triangle Institute. 

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### SECTION 1 INTRODUCTION Section 129 ofthe Clean Air Act (CAA)requires that performance standards for new units and emission guidelines (EG)for existing units be established for each category ofsolid waste incineration units. In previous actions, the U.S. Environmental Protection Agency (EPA) has promulgated rules and EG for hospital medical and infectious waste incinerators (HMIWI), commercial and industrial solid waste incinerators (CISWI), and other solid waste incineration (OSWI)units. These actions did not apply to sewage sludge incinerators (SSI). EPA is proposing new source performance standards (NSPS)and EG for SSI units. As part ofthe regulatory process, EPA is required to develop a regulatory impact analysis (RIA). The RIA includes an economic impact analysis (EIA)and a small entity impacts analysis and documents the RIA methods and results. 1.1 Executive Summary The key results ofthe RIA are as follows:

• Options Analyzed: EPA analyzed the following options and selected Option 2:

— Option 1 is the MACT floor level ofcontrol for the two subcategories developed for existing sewage sludge incineration (SSI) units, multiple hearth (MH) units, and fluidized bed (FB)units.

— Option 2 is the same as Option 1, with the addition ofactivated carbon injection for additional mercury (Hg)emissions reduction from MH units.

— Option 3 is the same as Option 2, with the addition ofan afterburner on all MH units for additional carbon monoxide (CO)emissions reduction. ■ Engineering Cost Analysis: EPA estimates the proposed rule's total annualized costs will be $92 million (2008$). ■ Social Cost Analysis: Because the proposed regulatory option affects governmental entities (96 ofthe 97 owners are governmental entities) providing services not provided in a market, the Office ofAir Quality Planning and Standards (OAQPS)has used the direct compliance cost method as a measure ofsocial costs. The social cost is approximately $92 million (2008$). ■ Small Entity Analyses: EPA performed a screening analysis for impacts for 18 small government entities by comparing compliance costs to revenues (e.g., revenue tests). EPA's analysis found the tests were below 1 %for small entities. ■ Benefits Analysis: In the year offull implementation (2015), EPA estimates the monetized PM2.5 benefits ofthe proposed NSPS and EG are $130 million to $320 million and $120 million to $290 million, at 3%and 7% discount rates, respectively.

1 -1 

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### All estimates are in 2008$ for the year 2015. Using alternate relationships between PM2.5 and premature mortality supplied by experts, higher and lower benefits estimates are plausible, but most ofthe expert-based estimates fall between these estimates. The benefits from reducing other air pollutants have not been monetized in this analysis, including reducing 2,900 tons ofCO, 96 tons ofHC1, 3.0 tons ofPb, 1.6 tons ofCd, 5,500 pounds ofmercury (Hg), and 90 grams oftotal dioxins/furans (CDD/CDF)each year. In addition, ecosystem benefits and visibility benefits have not been monetized in this analysis.

• Net Benefits: The net benefits for the NSPS and EG are $37 million to $220 million and $26 million to $190 million, at 3%and 7% discount rates, respectively (Table 1- 1). All estimates are in 2008$ for the year 2015. 1.2 Organization of this Report

EIA: The remainder ofthis report supports and details the methodology and the results ofthe

• Section 2 describes the SSI process, alternative disposal methods, and affected entities.
• Section 3 describes the engineering cost analysis. ■ Section 4 describes the economic impact and small entity analyses.
• Section 5 presents the benefits estimates.

1 -2 

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(Page 60 of Total)Table 1 -1. Summary of the Monetized Benefits, Social Costs, and Net Benefits for the SSI NSPS and EG in 2015 (millions of 2008$)a3% Discount Rate 7% Discount Rate Proposed: Option 2 Total Monetized Benefits" $130 to $320 $120 to $290 Total Social Costs` $92 $92 Net Benefits $37 to $220 $26 to $190 26,000 tons ofcarbon monoxide 96 tons ofHCl 5,500 pounds ofmercury 1.6 tons ofcadmium Non

- monetized Benefits 3.0 tons oflead 90 grams ofdioxins

/furans Health effects from NOZ and SOZ exposure Ecosystem effects Visibility impairment Option 1 Total Monetized Benefitsb $130 to $320 $120 to $290 Total Social Costs` $63 $63 Net Benefits $66 to $250 $55 to $220 2,900 tons ofcarbon monoxide 96tons ofHCl 820 pounds ofmercury 1.6 tons of cadmium Non

- monetized Benefits 3.0 tons of lead 74 grams ofdioxins/furans Health effects from NOZ and SOZ exposure Ecosystem effects Visibility impairment Option 3 Total Monetized Benefits° $130 to $310 $120 to $290 Total Social Costs` $132 $132 Net Benefits -$5.4 to $180 -$14 to $150 26,000 tons of carbon monoxide 96 tons ofHCl 5,500 pounds ofmercury 1.6 tons ofcadmium Non

- monetized Benefits 3.0 tons of lead 90 grams of dioxins/furans Health effects from NOZ and SOZ exposure Ecosystem effects Visibility impairment All estimates aze for the implementation year (2015),and are rounded to two significant figures. These results include 2 new FB incinerators anticipated to come online by 2015 and the large entities comply and small entities landfill assumption. b The total monetized benefits reflect the human health benefits associated with reducing exposure to PM2.5 through reductions of directly emitted PM2.5 and PMZ,S precursors such as NOX and SOZ. It is important to note that the monetized benefits include many but not all health effects associated with PMZ,S exposure. Benefits aze shown as a range from Pope et al. (2002)to Laden et al. (200.These models assume that all fine particles, regardless oftheir chemical composition, aze equally potent in causing premature mortality because there is no clear scientific evidence that would support the development ofdifferential effects estimates by particle type.l'hese estimates include energy disbenefits valued at $0.5 million at a 3 %discount rate from COZ emissions. `The annual compliances costs serve as a proxy for the annual social costs ofthis rule given the lack ofdifference between the two.

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(Page 61 of Total)SECTION 5 HUMAN HEALTH BENEFITS OF EMISSIONS REDUCTIONS 5.1 Synopsis In this section, we provide an estimate ofthe monetized benefits associated with reducing particulate matter (P1V~ for the proposed Sewage Sludge Incinerator (SSI)New Source Performance Standard (NSPS)and Emissions Guidelines (EG). For this rule, the PM reductions are the result ofemission limits on PM,emission limits on PM2.5 precursors such as NOX and SO2, as well as emission limits on other pollutants. The total PM2_5reductions are the consequence ofthe technologies installed or waste diversion to meet these multiple limits. These estimates reflect the monetized human health benefits ofreducing cases ofmorbidity and premature mortality among populations exposed to the PM2.5 precursors reduced by this rulemaking. Using a 3%discount rate, we estimate the total monetized benefits including energy disbenefits ofthe proposed SSI NSPS and EG to be $130 million to $320 million in the implementation year (2015). Using a 7% discount rate, we estimate the total monetized benefits including energy disbenefits ofthe proposed SSI NSPS and EG to be $120 million to $290 million in the implementation year. All estimates are in 2008$.
These estimates reflect EPA's most current interpretation ofthe scientific literature. Higher or lower estimates ofbenefits are possible using other assumptions; examples ofthis are provided in Figure 5-2. Data,resource, and methodological limitations prevented EPA from monetizing the benefits from several important benefit categories, including benefits from reducing hazardous air pollutants, ecosystem effects, and visibility impairment. The benefits from reducing other air pollutants have not been monetized in this analysis, including reducing 2,900 tons ofCO, 96 tons ofHCI, 3.0 tons ofPb, 1.6 tons ofCd, 5,500 pounds ofmercury (Hg), and 90 grams oftotal dioxins/furans (CDD/CDF)each year. 5.2 Calculation ofPM2,5 Human Health Benefits This rulemaking would reduce emissions ofPM2.5, 502, and NO2. Because SOX and NOZ are also precursors to PM2_5,reducing these emissions would also reduce PM2.5 formation, human exposure, and the incidence ofPM2.5-related health effects. For this rule, the PM reductions are the result ofemission limits on PM,emission limits on PM2.5 precursors such as NOX and SO2, as well as emission limits on other pollutants. The total PM2.5 reductions are the consequence ofthe technologies installed or waste diversion to meet these multiple limits. Due to analytical limitations, it was not possible to provide a comprehensive estimate ofPM2.5-related benefits. Instead, we used the "benefit-per-ton" approach to estimate these benefits based. on the

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(Page 62 of Total)methodology described in Fann, Fulcher, and Hubbell (2009). The key assumptions are

described in detail below. These PM2.5benefit-per-ton estimates provide the total monetized human health benefits (the sum ofpremature mortality and premature morbidity) ofreducing one ton ofPMz.s from a specified source. EPA has used the benefit per-ton technique in several previous RIAs, including the recent NOZ NAAQS RIA (U.S. EPA, 2010b). Table 5-1 shows the quantified and unquantified benefits captured in those benefit-per-ton estimates. Table 5-1. Human Health and Welfare Effects ofPM2.5
Pollutant Quantified and Monetized Unquantified Effects Effect in Primary Estimates Changes in: PM2.5 Adult premature mortality Subchronic bronchitis cases

Bronchitis: chronic and acute Low birth weight Hospital admissions: respiratory and Pulmonary function cardiovascular Chronic respiratory diseases other than chronic Emergency room visits for asthma bronchitis Nonfatal heart attacks (myocardial infarction) Non

-asthma respiratory emergency room visits Lower and upper respiratory illness Visibility Minor restricted

-activity days Household soiling Work loss days Asthma exacerbations (asthmatic population) Infant mortality

Consistent with the Portland Cement NESHAP (U.S. EPA, 2009a),the PM2.5 benefits estimates utilize the concentration

-response functions as reported in the epidemiology literature, as well as the 12 functions obtained in EPA's expert elicitation study as a sensitivity analysis.

One estimate is based on the concentration

-response (C-R)function developed from the extended analysis ofAmerican Cancer Society (ACS)cohort, as reported in Pope et al. (2002), a study that EPA has previously used to generate its primary benefits estimate. When calculating the estimate, EPA applied the effect coefficient as reported in the study without an adjustment for assumed concentration threshold of 10 μg /m3 as was done in recent (2006-2009)Office ofAir and Radiation RIAs. One estimate is based on the C-R function developed from the extended analysis of the Harvard Six Cities cohort, as reported by Laden et al. (2006). This study, published after the completion ofthe StaffPaper for the 2006 PM2.5NAAQS,has been used as an alternative estimate in the PMz.S NAAQS RIA and PM2.5 benefits estimates in RIAs completed since the PM2.5NAAQS. When calculating the estimate, EPA applied the effect coefficient as reported in the study without an adjustment for assumed concentration threshold of 10 μg/m3 as was done in recent (2006-2009) RIAs.

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### Twelve estimates are based on the C-R functions from EPA's expert elicitation study (IEc, 2006;Roman et al., 2008)on the 

### PM2.5

-mortality relationship and interpreted for benefits analysis in EPA's final RIA for the 

### PM2.5 NAAQS.For that study, twelve experts (labeled A through L)provided independent estimates ofthe 

### PM2.5

-mortality concentration

-response function. EPA practice has been to develop independent estimates of

### PM2.5

-mortality estimates corresponding to the concentration

-response function provided by each ofthe twelve experts, to better characterize the degree of variability in the expert responses. The effect coefficients are drawn from epidemiology studies examining two large population cohorts: the American Cancer Society cohort (Pope et al., 2002)and the Harvard Six Cities cohort (Laden et al., 2006).' These are logical choices for anchor points in our presentation because, while both studies are well designed and peer reviewed, there are strengths and weaknesses inherent in each, which we believe argues for using both studies to generate benefits estimates. Previously, EPA had calculated benefits based on these two empirical studies, but derived the range ofbenefits, including the minimum and maximum results, from an expert elicitation ofthe relationship between exposure to 

### PM2.5 and premature mortality (Roman et al., 2008).2 Within this assessment, we include the benefits estimates derived from the concentrationresponse function provided by each ofthe twelve experts to better characterize the uncertainty in the concentration

-response function for mortality and the degree ofvariability in the expert responses. Because the experts used these cohort studies to inform their concentration

-response functions, benefits estimates using these functions generally fall between results using these epidemiology studies (see Figure 5-2). In general, the expert elicitation results support the conclusion that the benefits of

### PM2,5 control are very likely to be substantial. Readers interested in reviewing the general methodology for creating the benefit-per-ton estimates used in this analysis should consult Fann, Fulcher, and Hubbell (2009). As described in Fann, Fulcher, and Hubbell (2009), benefit

-per-ton estimates are developed for selected pollutant /source category combinations. The per-ton values calculated therefore apply only to tons reduced from those specific pollutant /source combinations (e.g., 

### S02emitted from electric generating units; NO2emitted from mobile sources). In this analysis, we apply the national average benefit

-per-ton estimate fora 2015 analysis year and multiply it by the corresponding emission reductions ofdirectly emitted 

### PM2,5, SO2,and NOx to quantify the benefits ofthis rule. The benefit

-per-ton estimates found in Fann, Fulcher, and Hubbell (2009)reflect a specifc set of key assumptions and input data. As we update these underlying assumptions to reflect the

'These two studies specify multi

-pollutant models that control for SOZ,among other pollutants. ZPlease see the Section 5.2 ofthe Portland Cement proposal RIA in Appendix SA for more information regarding the change in the presentation ofbenefits estimates.


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### scientific literature, we re-estimate the benefit-per-ton estimates and post the updated estimates

at http://www.epa.gov

/air/benmap

/bpt.html. In addition, we adjust these estimates to match the currency year for the costs in this analysis. These models assume that all fine particles, regardless oftheir chemical composition, are equally potent in causing premature mortality because there is no clear scientific evidence that would support the development ofdifferential effects estimates by particle type. Directly emitted PM,SO2, and NOx are the primary PM2.5 precursors affected by this rule. Even though we assume that all fine particles have equivalent health effects, the benefit-per-ton estimates vary between precursors because each ton ofprecursor reduced has a different propensity to form PM2.5. For example,NOX has a lower benefit-per-ton estimate than direct PM2.5 because it does not form as much PM2.5, thus the exposure would be lower, and the monetized health co-benefits would be lower. The benefit-per-ton coefficients in this analysis were derived using modified versions of the health impact functions used in the PM NAAQS Regulatory Impact Analysis. Specifically, this analysis uses the benefit

-per-ton method first applied in the Portland Cement NESHAP RIA (U.S. EPA, 2009a), which incorporated three updates: a new population dataset, an expanded geographic scope ofthe benefit

-per-ton calculation, and the functions directly from the epidemiology studies without an adjustment for an assumed threshold.3 Removing the threshold assumption is a key difference between the method used in this analysis ofPM benefits and the methods used in RIAs prior to Portland Cement, and we now calculate incremental benefits down to the lowest modeled PM2.5 air quality levels.
EPA strives to use the best available science to support our benefits analyses, and we recognize that interpretation ofthe science regarding air pollution and health is dynamic and evolving. Based on our review ofthe current body ofscientific literature, EPA now estimates PM-related mortality without applying an assumed concentration threshold. EPA's Integrated Science Assessment for Particulate Matter (U.S. EPA, 2009b), which was recently reviewed by EPA's Clean Air Scientific Advisory Committee (U.S. EPA-SAB, 2009a; U.S. EPA-SAB, 2009b), concluded that the scientific literature consistently finds that a no- threshold log

-linear model most adequately portrays the PM-mortality concentration

-response relationship while recognizing potential uncertainty about the exact shape ofthe concentration

-response function. Since then, the Health Effects Subcommittee (U.S.EPA-SAB, 2010)ofEPA's Council

3The benefit

-per-ton estimates have also been updated since the Cement RIA to incorporate a revised VSL,as discussed on the next page.

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### concluded, "The HES fully supports EPA's decision to use a no- threshold model to estimate mortality reductions. This decision is supported by the data, which are quite consistent in showing effects down to the lowest measured levels. Analyses ofcohorts using data from more recent years, during which time PM concentrations have fallen, continue to report strong associations with mortality. Therefore, there is no evidence to support a truncation ofthe CRF." In conjunction with the underlying scientific literature, this document provided a basis for reconsidering the application ofthresholds in PM2.5 concentration

-response functions used in EPA's RIAs. For a summary ofthese scientific review statements and the panel members commenting on thresholds since 2002, please consult the Technical Support Document (TSD) Summary ofExpert Opinions on the Existence ofa Threshold (U.S. EPA, 2010c), which is provided as an appendix to this RIA. Consistent with this recent scientific advice, we are replacing the previous threshold sensitivity analysis with a new "Lowest Measured Level" (LML)assessment. This information allows readers to determine the portion ofpopulation exposed to annual mean PM2.5 levels at or above the LML ofeach study; in general, our confidence in the estimated PM mortality decreases as we consider air quality levels further below the LML in major cohort studies that estimate PM-related mortality. While an LML assessment provides some insight into the level of uncertainty in the estimated PM mortality benefits, EPA does not view the LML as a threshold and continues to quantify PM-related mortality impacts using a full range ofmodeled air quality concentrations. It is important to emphasize that we have high confidence in PM2,5-related effects down to the lowest LML ofthe major cohort studies. Just because we have greater confidence in the benefits above the LML,this does not mean that we have no confidence that benefits occur below the LML.
For this analysis, policy-specific air quality data is not available due to time or resource limitations. For these rules, we are unable to estimate the percentage ofpremature mortality associated with this specific rule's emission reductions at each PMz.51eve1. However, we believe that it is still important to characterize the distribution ofexposure to baseline air quality levels. As a surrogate measure ofmortality impacts, we provide the percentage ofthe population exposed at each PM2.5 level using the most recent modeling available from the recently proposed Transport Rule (U.S. EPA,2010e). It is important to note that baseline exposure is only one parameter in the health impact function, along with baseline incidence rates population, and change in air quality. In other words,the percentage ofthe population exposed to air pollution below the LML is not the same as the percentage ofthe population experiencing health impacts as a result ofa specific emission reduction policy. The most important aspect, which we are

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### unable to quantify for rules without air quality modeling, is the shift in exposure associated with

this specific rule. Therefore, caution is warranted when interpreting the LML assessment. For more information on the data and conclusions in the LMI,assessment for rules without policyspecific air quality modeling, please consult the LML TSD (U.S. EPA, 2010d), which is provided as an appendix to this RIA. The results ofthis analysis are provided in Section 5.4.
As is the nature ofRegulatory Impact Analyses (RIAs),the assumptions and methods used to estimate air quality benefits evolve over time to reflect the Agency's most current interpretation ofthe scientific and economic literature. For a period oftime (2004-2008),the Office ofAir and Radiation (OAR)valued mortality risk reductions using a value ofstatistical life (VSL)estimate derived from a limited analysis ofsome ofthe available studies. OAR arrived at a VSL using a range of$1 million to $10 million (2000$)consistent with two meta

-analyses of the wage-risk literature. The $1 million value represented the lower end ofthe interquartile range from the Mrozek and Taylor (2002)meta

-analysis of 33 studies. The $10 million value represented the upper end ofthe interquartile range from the Viscusi and Aldy (2003) metaanalysis of43 studies. The mean estimate of$5.5 million (2000$)4 was also consistent with the mean VSL of$5.4 million estimated in the Kochi et al. (2006)meta

-analysis. However,the Agency neither changed its official guidance on the use ofVSL in rule

-makings nor subjected the interim estimate to a scientific peer-review process through the Science Advisory Board (SAB)or other peer-review group. During this time, the Agency continued work to update its guidance on valuing mortality risk reductions, including commissioning a report from mete-analytic experts to evaluate methodological questions raised by EPA and the SAB on combining estimates from the various data sources. In addition, the Agency consulted several times with the Science Advisory Board Environmental Economics Advisory Committee (SAB-EEAC)on the issue. With input from the meta

-analytic experts, the SAB-EEAC advised the Agency to update its guidance using specific, appropriate meta

-analytic techniques to combine estimates from unique data sources and different studies, including those using different methodologies (i.e., wage-risk and stated preference)(U.S. EPA-SAB, 2007). Until updated guidance is available, the Agency determined that a single, peer-reviewed estimate applied consistently best reflects the SAB-EEAC advice it has received. Therefore, the Agency has decided to apply the VSL that was vetted and endorsed by the SAB in the Guidelines

4 After adjusting the VSL to account for a different currency year (2008$)and to account for income growth to 2015,the $5.5 million VSL is $7.9 million. 

### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 12 of 40

(Page 67 of Total)for Preparing Economic Analyses (U.S. EPA, 2000)5 while the Agency continues its efforts to

update its guidance on this issue. This approach calculates a mean value across VSL estimates derived from 261abor market and contingent valuation studies published between 1974 and 1991. The mean VSL across these studies is $6.3 million (2000$).6 The Agency is committed to using scientifically sound, appropriately reviewed evidence in valuing mortality risk reductions and has made significant progress in responding to the SAB-EEAC's specific recommendations. Figure 5-1 illustrates the relative breakdown ofthe monetized PM2,5 health benefits.

Resp
0.01% '/o
v NNci ncaN.~yiiiN v.v~~ Lower Resp Symp 0.00' ERVisits, Resp0.00% Figure 5-1. Breakdown of Monetized PM2,5 Health Benefits using Mortality Function from

Pope et al. (2002)a
a This pie chart breakdown is illustrative, using the results based on Pope et al. (2002)as an example. Using the Laden et al. (2006)fiznction for premature mortality, the percentage oftotal monerized benefits due to adult mortality would be 97%.This chart shows the breakdown using a 3%discount rate, and the results would be similar ifa 7% discount rate was used. Tables 5-2 and 5-3 provide a general summary ofthe all units comply assumption and large entities comply and small entities landfill assumption results by pollutant, including the

SIn the (draft) update ofthe Economic Guidelines (U.S. EPA,2008),EPA retained the VSL endorsed by the SAB with the understanding that further updates to the mortality risk valuation guidance would be forthcoming in the near future. Therefore, this report does not represent final agency policy. 6In this analysis, we adjust the VSL to account for a different currency year (2008$)and to account for income growth to 2015. After applying these adjustments to the $63 million value, the VSL is $9.1 million.
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### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 13 of 40

(Page 68 of Total)emission reductions and monetized benefits-per-ton at discount rates of 3%and 7%.'Table 5 -4

provides a summary ofthe reductions in health incidences as a result ofthe pollution reductions for the large entities comply and small entities landfill results. In Table 5-5, we provide the benefits using our anchor points ofPope et al. and Laden et al. as well as the results from the expert Table 5-2. Summary of Monetized Benefits Estimates for Proposed SSI NSPS and EG in

2015 (2008$)

(large entities comply and small entities landfill)a

Emissions Benefit per Benefit per Benefit Benefit per Total Monetized Total

Monetized Pollutant Reductions ton (Pope, ton (Laden, Per ton Pope, ton

(Laden, Benefits Benefits (tons) 3%) 3%) 7 %) 7

%) millions (millions 2008$ at 3%) 2008$ at 7 %) Direct PMZ.S 254 $230,000 $560,000 $210,000 $500,000 $58 to $140 $52 to $130

.. PMZ.S Precursors 0 SOZ 2,298 $29,000 $72,000 $27,000 $65,000 $68 to $170 $61 to $150 a ~ NOZ 824 $4,900 $12,000 $4,400 $11,000 $4.0 to $9.8 $3.6 to $8.8 Total $130 to $320 $120 to $290

~'' DirectPM,; 254 $230,000 $560,000 $210,000 $500,000 $58 to $140 $52 to $130 c 0 PM, 5 Precursors O .~ SOZ 2,298 $29,000 $72,000 $27,000 $65,000 $68 to $170 $61 to $150 NOz 824 $4,900 $12,000 $4,400 $11,000 $4.0 to $9.8 $3.6 to $8.8 0 a Total $130 to $320 $120 to $290 Direct PM2.5 254 $230,000 $560,000 $210,000 $500,000 $58 to $140 $52 to $130 M PM2.5 Precursors e •,°; SOz 2,298 $29,000 $72,000 $27,000 $65,000 $68 to $170 $61 to $150 cL
~ NOZ 824 $4,900 $12,000 $4,400 $11,000 $4.0 to $9.8 $3.6 to $8.8 Total $130 to $320 $120 to $290

'To comply with Circular A-4, EPA provides monetized benefits using discount rates of 3%and 7% (OMB,2003). These benefits are estimated for a specific analysis year (i.e., 2015), and most ofthe PM benefits occur within that year with two exceptions: acute myocardial infarctions (AMIs)and premature mortality. For AMIs,we assume 5 years offollow-up medical costs and lost wages. For premature mortality, we assume that there is a "cessation" lag between PM exposures and the total realization ofchanges in health effects. Although the structure ofthe lag is uncertain, EPA follows the advice ofthe SAB-HES to assume a segmented lag structure chazacterized by 30% ofmortality reductions in the first year, 50%over years 2to 5,and 20%over the years 6 to 20 after the reduction in PM2.5 (U.S. EPA-SAB, 2004). Changes in the lag assumptions do not change the total number ofestimated deaths but rather the timing ofthose deaths. Therefore, discounting only affects the AMI costs after the analysis year and the valuation ofpremature mortalities that occur after the analysis year. As such, the monetized benefits using a 7%discount rate are only approximately 10%less than the monetized benefits using a 3%discount rate.
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(Page 69 of Total)All estimates are for the implementation year (2015), and are rounded to two significant figures so numbers may

not sum across columns. All fine particles are assumed to have equivalent health effects, but the benefit per ton estimates vary because each ton ofprecursor reduced has a different propensity to form PM2,5. The monetized benefits incorporate the conversion from precursor emissions to ambient fine particles. These results include 2 new FB incinerators anticipated to come online by 2015. These estimates do not include energy disbenefits valued at $0.5 million at a 3%discount rate for COZ emissions. 

### elicitation on PM mortality. Figures 5-2 through 5-4 provide a visual representation ofthe range ofbenefits estimates and the pollutant breakdown ofthe monetized benefits.

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(Page 70 of Total)Table 5-3. Summary of Monetized Benefits Estimates for Proposed SSI NSPS and EG in 2015 (2008$)(all units comply)e
Total Total

Benefit Benefit per Benefit Benefit Monetized Monetized Emissions per ton ton per ton per ton Benefits Benefits Reductions (Pope, (Laden, (Pope, (Laden, (millions 2008$ (millions 2008$ Pollutant (tons) 3%) 3%) 7 %) 7

%) at 3%) at 7 %) Direct PMz.s

.. PM2,5 Precursors a SOZ a ~ NOZ

~ Direct PM2.5 0 a, PM2,5 Precursors O ,fl SOz 0 a NOZ 0 ~, a 209 $230,000 $560,000 $210,000 $500,000 $48.0 to $120.0 $43.0 to $110.0

2,193 $29,000 $72,000 $27,000 $65,000 $65 to $160 $59 to $140 5 $4,900 $12,000 $4,400 $11,000 $.02 to $.06 $.02 to $.OS Total $110 to $270 $100 to $250 209 $230,000 $560,000 $210,000 $500,000 $48.0 to $120.0 $43.0 to $110.0

2,193 $29,000 $72,000 $27,000 $65,000 $65 to $160 $59 to $140 5 $4,900 $12,000 $4,400 $11,000 $.02 to $.06 $.02 to $.OS Total $110 to $270 $100 to $250 Direct PMZ.S 209 $230,000 $560,000 $210,000 $500,000 $48 to $120 $43 to $110
c•, PM2,5 Precursors C SOZ 2,193 $29,000 $72,000 $27,000 $65,000 $65 to $160 $59 to $140 a ~ NOZ 5 $4,900 $12,000 $4,400 $11,000 $.02 to $.06 $.02 to $.OS Total $110 to $270 $100 to $250

a All estimates are for the implementation year (2015), and are rounded to two significant figures so numbers may not sum across columns. All fine particles are assumed to have equivalent health effects, but the benefit per ton estimates vary because each ton ofprecursor reduced has a different propensity to form PM2.5. The monetized benefits incorporate the conversion from precursor emissions to ambient fine particles. These results include 2 new FB incinerators anticipated to come online by 2015. These estimates do not include energy disbenefits valued at $0.5 million at a 3%discount rate for COZ emissions.



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(Page 71 of Total)Table 5-4. Summary ofReductions in Health Incidences from PM2,;Benefits for the Proposed SSI NSPS and EG in 2015a Option 1 Proposed: Option 2 Option 3 Avoided Premature Mortality Pope et al. 14 14 14 Laden et al. 36 36 36 Avoided Morbidity Chronic Bronchitis 10 10 10 Acute Myocardial Infarction 23 23 23 Hospital Admissions, Respiratory 3 3 3 Hospital Admissions, Cardiovascular 7 7 7 Emergency Room Visits, Respiratory 14 l4 14 Acute Bronchitis 23 23 23 Work Loss Days 1,900 1,900 1,900 Asthma Exacerbation 250 250 250 Minor Respiratory Symptoms 11,000 11,000 11,000 Lower Respiratory Symptoms 270 270 270 Upper Respiratory Symptoms 210 210 210

a All estimates are for the analysis year (2015)and are rounded to whole numbers with two significant figures. All fine particles are assumed to have equivalent health effects, but each PMZ.S precursor pollutant has a different propensity to form PM2,5. Confidence intervals are unavailable for this analysis because ofthe benefit

-per-ton methodology. These results include 2new FB incinerators anticipated to come online by 2015 and the large " entities comply and small entities landfill assumption.

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(Page 72 of Total)Table 5-5. All PM2,5 Benefits Estimates for the Proposed SSI NSPS and EG at Discount Rates of 3% and 7% in 2015 (in millions of 2008$)a Proposed: Option 1 Option 3

Option 2 3% 7% 3% 7% 3% 7% Benefit-per-ton Coefficients derived from Epidemiology Literature Pope et al. $130 $120 $130 $120 $130 $120 Laden et al. $320 $290 $320 $290 $320 $290 Benefit-per-ton Coefficients Derived from Expert Elicitation ExpertA $340 $300 $340 $300 $340 $300 ExpertB $260 $230 $260 $230 $260 $230 ExpertC $260 $230 $260 $230 $260 $230 ExpertD $180 $160 $180 $160 $180 $160 Expert E $420 $380 $420 $380 $420 $380 ExpertF $230 $210 $230 $210 $230 $210 ExpertG $150 $140 $150 $140 $153 $139 ExpertH $190 $170 $190 $170 $190 $170 ExpertI $250 $230 $250 $230 $250 $230 Expert) $210 $190 $210 $190 $210 $190 ExpertK $51 $46 $51 $46 $51 $46 ExpertL $190 $170 $190 $170 $190 $170 All estimates are rounded to two significant figures. Estimates do not include confidence intervals because they were derived through the benefit-per-ton technique described above. The benefits estimates from the Expert Elicitation are provided as a reasonable characterization ofthe uncertainty in the mortality estimates associated with the concentration

-response function. These results include 2 new FB incinerators anticipated to come online by 2015 and the large entities comply and small entities landfill assumption. These estimates do not include energy disbenefits valued at $0.5 million at a 3%discount rate for COZ emissions.

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(Page 73 of Total)S400

$350
$300
$250 0 0 `. $200 c 0

~ $150
$100
$50
$0 Benefits estimates derived from 2 epidemiology functions and 12 expert functions Figure 5-2. Total Monetized PMZ,S Benefits for the Proposed SSI NSPS and EG in 2015
a This graph shows the estimated benefits at discount rates of 3% and 7% using effect coefficients derived from the Pope et al. study and the Laden et al study, as well as 12 effect coefficients derived from EPA's expert elicitation on PM mortality. The results shown are not the direct results from the studies or expert elicitation; rather, the estimates are based in part on the concentration

-response function provided in those studies. These results include 2 new FB incinerators anticipated to come online by 2015 and the large entities comply and small entities landfill assumption. These estimates do not include energy disbenefits valued at $0.5 million at a 3% discount rate for COz emissions.

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(Page 74 of Total)Figure 5-3. Breakdown of Monetized Benefits for the Proposed SSI NSPS and EG by PMZ,S Precursor Pollutant and Source

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(Page 75 of Total)iearth

Fluidized Bed 10%



### Figure 5-4. Breakdown of Monetized Benefits for the Proposed SSI NSPS and EG by

Subcategory

5.3 Energy Disbenefits Electricity usage associated with the operation ofcontrol devices is anticipated to increase emissions ofpollutants from utility boilers that supply electricity to the sewage sludge incinerators. For example, increased scrubber pump horsepower and sorbent injection controls may cause slight increases in electricity consumption. We estimate that the increased electricity consumption associated with the proposed option would be 12 million kWh ifall entities comply, and 12 million kWh ifthe small entities landfill. Using national emission factors from eGRID for electrical generating units (EGUs), we estimate the increased emissions to be 19,000 tpy ofCO2 for the proposed option assuming that small entities landfill.8 Since NOx and SOZ are covered by capped emissions trading programs, we are only estimating the COZ emission increases from the increased electricity demand. The methodology used to calculate these

g Option 3 has additional energy disbenefits associated with the supplemental fuel required to run the afterburners, which results in additional emissions ofCO2i CO,and NOx. The COZ energy disbenefits for Option 3 are shown in Tables 5-7 and 5-8. The additional NOx disbenefits (as a precursor to PMz.s using the methodolology described in Section 5.2) for Option 3 are $0.4 million to $0.9 million, which do not affect the rounded benefits results.

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### emission increases is described "Secondary Impacts ofControl Options for the Sewage Sludge

Incineration Source Category ", which is available in the docket. 5.3.I Social Cost 

## ofCarbon and Greenhouse Gas Disbenefits 

### EPA has assigned a dollar value to reductions in carbon dioxide (CO2)emissions using recent estimates ofthe "social cost ofcarbon" (SCC). The SCC is an estimate ofthe 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 ofecosystem services due to climate change. The SCC estimates used in this analysis were developed through an 

### interagency process that included EPA and other executive branch entities, and concluded in February 2010. EPA first used these SCC estimates in the benefits analysis for the final joint EPA/DOT Rulemaking to establish Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards; see the rule's preamble for discussion about application ofSCC (75 FR 25324; 5/7/10). The SCC Technical Support Document (SCC TSD)provides a complete discussion ofthe methods used to develop these SCC estimates.9 The interagency group selected four SCC values for use in regulatory analyses, which we have applied in this analysis: $5, $21, $35, and $65 per metric ton ofCO2 emissions10 in 2010, in 2007 dollars. The first three values are based on the average SCC from three integrated assessment models, at discount rates of2.5, 3, and 5 percent, respectively. SCCs at several discount rates are included because the literature shows that the SCC is quite sensitive to assumptions about the discount rate, and because no consensus exists on the appropriate rate to use in an intergenerational context. The fourth value is the 95th percentile ofthe SCC from all three models at a 3 percent discount rate. It is included to represent higher

-than

-expected impacts from temperature change further out in the tails ofthe SCC distribution. Low probability, high impact events are incorporated into all ofthe SCC values through explicit consideration oftheir effects in two ofthe three models as well as the use ofa probability density function for

9 Docket ID EPA-HQ-OAR

-2009-0472- 114577, Technical Support Document: Social Cost ofCarbonfor Regulatory ImpactAnalysis Under Executive Order 12866, Interagency Working Group on Social Cost of Carbon,with participation by Council ofEconomic Advisers, Council on Environmental Quality, Department of Agriculture, Department ofCommerce,Department ofEnergy,Deparhnent ofTransportation,Environmental Protection Agency,National Economic Council, Office ofEnergy and Climate Change,Office ofManagement and Budget, Office of Science and Technology Policy, and Department ofTreasury (February 2010). Also available at http:/

/www.ena.eov

/otaq/climate

/reeulations.htm 10 The interagency group decided that these estimates apply only to COZ emissions. Given that warming profiles and impacts other than temperature change (e.g. ocean acidification) vary across GHGs,the group concluded "transforming gases into COZ-equivalents using GWP,and then multiplying the carbon

-equivalents by the SCC, would not result in accurate estimates ofthe social costs ofnon-COZ gases" (SCC TSD,pg 13).


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(Page 77 of Total)equilibrium climate sensitivity. Treating climate sensitivity probabilistically results in more high

temperature outcomes, which in turn lead to higher projections ofdamages.
The SCC increases over time because future emissions are expected to produce larger incremental damages as physical and economic systems become more stressed in response to greater climatic change. Note that the interagency group estimated the growth rate ofthe SCC directly using the three integrated assessment models rather than assuming a constant annual growth rate. This helps to ensure that the estimates are internally consistent with other modeling assumptions. The SCC estimates for the analysis years of2015, in 2008$ are provided in Table 5-6. When attempting to assess the incremental economic impacts ofcarbon dioxide emissions, the analyst faces a number ofserious challenges. A recent report from the National Academies of Science (NRC, 2008) points out that any assessment will suffer from uncertainty, speculation, and lack of information about (1)future emissions ofgreenhouse gases, (2)the effects ofpast and future emissions on the climate system, (3)the impact ofchanges in climate on the physical and biological environment, and (4)the translation ofthese environmental impacts into economic damages. As a result, any effort to quantify and monetize the harms associated with climate change will raise serious questions ofscience, economics, and ethics and should be viewed as provisional. The interagency group noted a number of limitations to the SCC analysis, including the incomplete way in which the integrated assessment models capture catastrophic and noncatastrophic impacts, their incomplete treatment ofadaptation and technological change, uncertainty in the extrapolation ofdamages to high temperatures, and assumptions regarding risk aversion. The limited amount ofresearch linking climate impacts to economic damages makes the interagency modeling exercise even more difficult. The interagency group hopes that over time researchers and modelers will work to fill these gaps and that the SCC estimates used for regulatory analysis by the Federal government will continue to evolve with improvements in modeling. Additional details on these limitations are discussed in the SCC TSD.
In light ofthese limitations, the interagency group has committed to updating the current estimates as the science and economic understanding ofclimate change and its impacts on society improves over time. Specifically, the interagency group has set a preliminary goal of revisiting the SCC values within two years or at such time as substantially updated models become available, and to continue to support research in this area.

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(Page 78 of Total)Applying the global SCC estimates to the estimated increases in COz emissions for the

range ofpolicy scenarios, we estimate the dollar value ofthe climate

-related disbenefits captured by the models for each analysis year. For internal consistency, the annual disbenefits are discounted back to NPV terms using the same discount rate as each SCC estimate (i.e. 5%,3%, and 2.5%)

rather than 3%and 7%.I ~ These estimates are provided in Tables 5 -7 and 5-8. Table 5-6. Social Cost of Carbon (SCC)Estimates (per tonne of CO2)for 2015 a
Discount Rate and Statistic SCC estimate (2008$) 5% Average $5.9 3% Average $24•~ 2.5%Average $39.9 3% 95 %ile $75.6

a The SCC values are dollar-year and emissions-year specific. SCC values represent only a partial accounting of climate impacts. Table 5-7. Monetized SCC-derived Disbenefits of COz Emission Increases in 2015

(all units comply, millions of 2008$)a Proposed: Discount Rate and Statistic Option 1 Option 2 Option 3 24,900 tpy COZ 24,900 tpy COZ 126,000 tpy COz 5% Average $0.1 $0.1 $0.7 3% Average $0.6 $0.6 $3.1 2.5%Average $1.0 $1.0 $5.0 3% 95° /vile $1.9 $1.9 $9.5

a The SCC values are dollar-year and emissions-year specific. SCC values represent only a partial accounting of climate impacts. These results include 2 new FB incinerators anticipated to come online by 2015. Table 5-8. Monetized SCC-derived Disbenefits of COZ Emission Increases in 2015

(large entities comply and small entities landfill, millions of 2008$)a Proposed: Discount Rate and Statistic Option 1 Option 2 Option 3 21,782 tpy COZ 21,782 tpy COZ 114,784tpy COZ 5% Average $0.1 $0.1 $0.7 3% Average $0.5 $0.5 $2.8 2.5 %Average $0.9 $0.9 $4.6

" It is possible that other benefits or costs ofproposed regulations unrelated to COZ emissions will be discounted at rates that differ from those used to develop the SCC estimates.
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(Page 79 of Total)3% 95 %ile $1.6 $1.6 $8.7

The SCC values are dollar-year and emissions-year specific. SCC values represent only a partial accounting of climate impacts. These results include 2 new FB incinerators anticipated to come online by 2015. 5.4 Unquantified Benefits The monetized benefits estimated in this RIA only reflect the portion of benefits attributable to the health effect reductions associated with ambient fine particles. Data, resource, and methodological limitations prevented EPA from quantifying or monetizing the benefits from several important benefit categories, including benefits from reducing toxic emissions, ecosystem effects, and visibility impairment. The health benefits from reducing hazardous air pollutants (HAPs)and carbon monoxide have not been monetized in this analysis. In addition to being a PM2.5 precursor, SOZ emissions also contribute to adverse effects from acidic deposition in aquatic and terrestrial ecosystems, increased mercury methylation, as well as visibility impairment. The benefits from reducing other air pollutants that have not been monetized in this analysis including 2,900 tons ofcarbon monoxide, 96 tons ofHCI, 3.0 tons of lead, 1.6 tons of cadmium, 5,500 pounds ofmercury, and 90 grams oftotal dioxins/furans each year. 5.4.1 Carbon Monoxide Benefits Carbon monoxide (CO)exposure is associated with a variety of health effects. Without knowing the location ofthe emission reductions and the resulting ambient concentrations using fine-scale air quality modeling, we were unable to estimate the exposure to CO for nearby populations. Due to data, resource, and methodological limitations, we were unable to estimate the benefits associated with the reductions ofCO emissions that would occur as a result ofthis rule. Carbon monoxide in ambient air is formed primarily by the incomplete combustion of carbon

-containing fuels and photochemical reactions in the atmosphere. The amount ofCO emitted from these reactions, relative to carbon dioxide (COz), is sensitive to conditions in the combustion zone, such as fuel oxygen content, burn temperature, or mixing time. Upon inhalation, CO diffuses through the respiratory system to the blood, which can cause hypoxia (reduced oxygen availability). Carbon monoxide can elicit a broad range ofeffects in multiple tissues and organ systems that are dependent upon concentration and duration ofexposure. The Integrated Science Assessment for Carbon Monoxide (U.S. EPA, 2010a)concluded that short-term exposure to CO is "likely to have a causal relationship" with cardiovascular morbidity, particularly in individuals with coronary heart disease. Epidemiologic studies associate short-term CO exposure with increased risk ofemergency department visits and

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### hospital admissions. Coronary heart disease includes those who have angina pectoris (cardiac

chest pain), as well as those who have experienced a heart attack. Other subpopulations potentially at risk include individuals with diseases such as chronic obstructive pulmonary disease (COPD),anemia, or diabetes, and individuals in very early or late life stages, such as older adults or the developing young. The evidence is suggestive ofa causal relationship between short-term exposure to CO and respiratory morbidity and mortality. The evidence is also suggestive ofa causal relationship for birth outcomes and developmental effects following longterm exposure to CO,and for central nervous system effects linked to short- and long-term exposure to CO. 5.4.2 Other S02Benefits In addition to being a precursor to PM2.5, S02 emissions are also associated with a variety ofrespiratory health effects. Unfortunately, we were unable to estimate the health benefits associated with reduced SOz exposure in this analysis because we do not have air quality modeling data available. Without knowing the location ofthe emission reductions and the resulting ambient concentrations, we were unable to estimate the exposure to SOZ for nearby populations. Therefore, this analysis only quantifies and monetizes the PM2.5 benefits associated with the reductions in SOZ emissions. Following an extensive evaluation ofhealth evidence from epidemiologic and laboratory studies, the U.S. EPA has concluded that there is a causal relationship between respiratory health effects and short-term exposure to SOz(U.S. EPA,2008). According to summary ofthe ISA in EPA's risk and exposure assessment (REA)for the SOZ NAAQS,"the immediate effect ofSOz on the respiratory system in humans is bronchoconstriction" (U.S. EPA, 2009c). In addition, the REA summarized from the ISA that "asthmatics are more sensitive to the effects ofSOZ likely resulting from preexisting inflammation associated with this disease." A clear concentrationresponse relationship has been demonstrated in laboratory studies following exposures to S02 at concentrations between 20 and 100 ppb, both in terms ofincreasing severity ofeffect and percentage ofasthmatics adversely affected (U.S. EPA, 2009c). Based on our review ofthis information, we identified four short-term morbidity endpoints that the SOZ ISA identified as a "causal relationship": asthma exacerbation, respiratory

-related emergency department visits, and respiratory

-related hospitalizations. The differing evidence and associated strength ofthe evidence for these different effects is described in detail in the S02 ISA. The SOZ ISA also concluded that the relationship between short-term SOZ exposure and premature mortality was "suggestive ofa causal relationship" because it is difficult to attribute the mortality risk effects to S02alone. Although the SOz ISA stated that studies are generally consistent in reporting a

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### relationship between SOZ exposure and mortality, there was a lack ofrobustness ofthe observed

associations to adjustment for pollutants. S02 emissions also contribute to adverse welfare effects from acidic deposition, visibility impairment, and enhanced mercury methylation. Deposition ofsulfur causes acidification, which can cause a loss ofbiodiversity offishes, zooplankton, and macro invertebrates in aquatic ecosystems, as 

### well as a decline in sensitive tree species, such as red spruce (Picea rubens)

### and sugar maple (Ater saccharum) 

### in terrestrial ecosystems. In the northeastern United States, the surface waters affected by acidification are a source offood for some recreational and subsistence fishermen and for other consumers and support several cultural services, including aesthetic and educational services and recreational fishing. Biological effects ofacidification in terrestrial ecosystems are generally linked to aluminum toxicity, which can cause reduced root growth, which restricts the ability ofthe plant to take up water and nutrients. These direct effects can, in turn, increase the sensitivity ofthese plants to stresses, such as droughts, cold temperatures, insect pests, and disease leading to increased mortality ofcanopy trees. Terrestrial acidification affects several important ecological services, including declines in habitat for threatened and endangered species (cultural), declines in forest aesthetics (cultural), declines in forest productivity (provisioning), and increases in forest soil erosion and reductions in water retention (cultural and regulating) (U.S. EPA, 2008d). Reducing SOz emissions and the secondary formation ofPM2.5 would improve the level ofvisibility throughout the United States. Fine particles with significant light-extinction efficiencies include sulfates, nitrates, organic carbon, elemental carbon, and soil (Sider, 1996). These suspended particles and gases degrade visibility by scattering and absorbing light. Higher visibility impairment levels in the East are due to generally higher concentrations offine particles, particularly sulfates, and higher average relative humidity levels. In fact, particulate sulfate is the largest contributor to regional haze in the eastern U.S. (i.e., 40% or more annually and 75%during summer). In the western U.S., particulate sulfate contributes to 20-50% of regional haze (U.S. EPA, 2009c). Visibility has direct significance to people's enjoyment of daily activities and their overall sense ofwellbeing. Good visibility increases the quality oflife where individuals live and work,and where they engage in recreational activities. 5.4.3 HAP Benefits 

### Due to data, resource, and methodology limitations, we were unable to estimate the benefits associated with the hazardous air pollutants that would be reduced as a result ofthis rule. Available emissions data show that several different HAPs are emitted from SSI. This rule

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### is anticipated to reduce 96 tons ofHCI, 3.0 tons oflead, 1.6 tons ofcadmium, 5,500 pounds of

mercury, and 90 grams oftotal dioxins /furans each year. In the absence ofair quality modeling and/or concentration

-response functions, we are unable to quantify the magnitude ofthe reduction in human exposure to these pollutants associated with the emission reductions from this rule. 5.4.3.1 Mercury 

### Mercury is a highly neurotoxic contaminant that enters the food web as a methylated compound, methylmercury (U.S. EPA, 2008d). The contaminant is concentrated in higher trophic levels, including fish eaten by humans. Experimental evidence has established that only inconsequential amounts ofmethylmercury can be produced in the absence ofsulfate (U.S. EPA, 2008d). Current evidence indicates that in watersheds where mercury is present, increased sulfate deposition very likely results in methylmercury accumulation in fish (Drevnick et al., 2007; Munthe et al, 2007). The SOZ ISA concluded that evidence is sufficient to infer a casual relationship between sulfur deposition and increased mercury methylation in wetlands and aquatic environments (U.S. EPA,2008d).
In addition to the role ofsulfate deposition on methylation, this proposed rule would also reduce mercury emissions. Mercury is emitted to the air from various man-made and natural sources. These emissions transport through the atmosphere and eventually deposit to land or water bodies. This deposition can occur locally, regionally, or globally, depending on the form of mercury emitted and other factors such as the weather. The form ofmercury emitted varies depending on the source type and other factors. Available data indicate that the mercury emissions from these sources are a mixture ofgaseous elemental mercury, inorganic ionic mercury, and particulate bound mercury. Gaseous elemental mercury can be transported very long distances, even globally, to regions far from the emissions source (becoming part ofthe global "pool

")before deposition occurs. Inorganic ionic and particulate bound mercury have a shorter atmospheric lifetime and can deposit to land or water bodies closer to the emissions source. Furthermore, elemental mercury in the atmosphere can undergo transformation into ionic mercury, providing a significant pathway for deposition ofemitted elemental mercury. This source category emitted about 3.1 tons ofmercury in the air in 2008 in the U.S. Based on the EPA's National Emission Inventory, about 103 tons ofmercury were emitted from all anthropogenic sources in the U.S. in 2005. Moreover,the United Nations has estimated that about 2,100 tons ofmercury were emitted worldwide by anthropogenic sources in 2005. We believe that total mercury emissions in the U.S. and globally in 2008 were about the same

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### magnitude in 2005. Therefore, we estimate that in 2008,these sources emitted about 3% ofthe

total anthropogenic mercury emissions in the U.S. and about 0.15% ofthe global emissions. Overall, this rule would reduce mercury emissions by about 5,500 pounds per year from current levels, and therefore, contribute to reductions in mercury exposures and health effects. Due to time and resource limitations, we were unable to model mercury dispersion, deposition, methylation, bioaccumulation in fish tissue, and human consumption ofinercury

-contaminated fish that would be needed in order to estimate the human health benefits from reducing mercury emissions. Potential exposure routes to mercury emissions include both direct inhalation and consumption offish containing methylmercury. In the U.S.,the primary route ofhuman exposure to mercury emissions from industrial sources is generally indirectly through the consumption offish containing methylmercury. As described above, mercury that has been emitted to the air eventually settles into water bodies or onto land where it can either move directly or be leached into waterbodies. Once deposited, certain microorganisms can change it into methylmercury, a highly toxic form that builds up in fish, shellfish and animals that eat fish. Consumption offish and shellfish are the main sources ofmethylmercury exposure to humans. Methylmercury builds up more in some types offish and shellfish than in others. The levels of methylmercury in fish and shellfish vary widely depending on what they eat, how long they live, and how high they are in the food chain. Most fish, including ocean species and local freshwater fish, contain some methylmercury. For example, in recent studies by EPA and the U.S. Geological Survey (USGS)offish tissues, every fish sampled from 291 streams across the country contained some methylmercury (Scudder, 2009). The majority offish consumed in the U.S. are ocean species. The methylmercury concentrations in ocean fish species are primarily influenced by the global mercury pool. However,the methylmercury found in local fish can be due, at least partly, to mercury emissions from local sources. Research shows that most people's fish consumption does not cause a mercury -related health concern. However, certain people may be at higher risk because oftheir routinely high consumption offish (e.g., tribal and other subsistence fishers and their families who rely heavily on fish for a substantial part oftheir diet). It has been demonstrated that high levels ofmethylmercury in the bloodstream ofunborn babies and young children may harm the developing nervous system, making the child less able to think and learn. Moreover, mercury exposure at high levels can harm the brain, heart, kidneys, lungs, and immune system ofpeople ofall ages.

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### Several studies suggest that the methylmercury content offish may reduce these cardioprotective effects offish consumption. Some ofthese studies also suggest that methylmercury may cause adverse effects to the cardiovascular system. For example, the NRC (2000)review of the literature concerning methylmercury health effects took note oftwo epidemiological studies that found an association between dietary exposure to methylmercury and adverse cardiovascular effects.'Z Moreover, in a study of 1,833 males in Finland aged 42 to 60 years, Solonen et al. (1995)observed a relationship between methylmercury exposure via fish consumption and acute myocardial infarction (AMI or heart attacks), coronary heart disease, cardiovascular disease, and all-cause mortality.13 The NRC also noted a study of917 seven year old children in the Faroe Islands, whose initial exposure to methylmercury was in utero although post natal exposures may have occurred as well. At seven years ofage, these children exhibited an increase in blood pressure and a decrease in heart rate variability.14 Based on these and other studies, NRC concluded in 2000 that, while "the data base is not as extensive for cardiovascular effects as it is for other end points (i.e. neurologic effects) the cardiovascular system appears to be a target for methylmercury toxicity. "15 

### Since publication ofthe NRC report there have been some 30 published papers presenting the findings ofstudies that have examined the possible cardiovascular effects of methylmercury exposure. These studies include epidemiological, toxicological, and toxicokinetic investigations. Over a dozen review papers have also been published. Ifthere is a causal relationship between methylmercury exposure and adverse cardiovascular effects, then reducing exposure to methylmercury would result in public health benefits from reduced cardiovascular effects.
In early 2010, EPA sponsored a workshop in which a group ofexperts were.asked to assess the plausibility ofa causal relationship between methylmercury exposure and cardiovascular health effects and to advise EPA on methodologies for estimating population

'Z National Research Council (NRC). 2000. Toxicological Effects ofMethylmercury. Committee on the Toxicological Effects ofMethylmercury, Board on Environmental Studies and Toxicology. National Academies Press. Washington,DC.pp. 168-173. 13Salonen, J.T., Seppanen,K.Nyyssonen et al. 1995. "Intake ofmercury from fish lipid peroxidarion, and the risk of myocardial infarction and coronary, cardiovascular and any death in Eastern Finnish men." Circulation, 91 (3):645-655. 14Sorensen, N,K. Murata, E. Budtz-Jorgensen, P. Weihe,and Grandjean,P., 1999. "Prenatal Methylmercury Exposure As A Cardiovascular Risk Factor At Seven Years ofAge",Epidemiology, pp370-375. 'sNational Research Council (NRC). 2000. Toxicological Effects ofMethylmercury. Committee on the Toxicological Effects ofMethylmercury, Board on Environmental Studies and Toxicology. National Academies Press. Washington,DC.p. 229.


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### level cardiovascular health impacts ofreduced methylmercury exposure. The report from that

workshop is in preparation. 5.4.3.2 Cadmium Breathing air with very high levels ofcadmium can severely damage the lungs and may cause death. In the United States, where proper industrial hygiene is generally practiced, inhaling very high levels ofcadmium at work is expected to be rare and accidental. Breathing air with lower levels ofcadmium over long periods oftime (for years) results in a build-up ofcadmium in the kidney, and if sufficiently high, may result in kidney disease. Lung cancer has been found in some studies ofworkers exposed to cadmium in the air and studies ofrats that breathed in cadmium. The U.S. Department ofHealth and Human Services (DHHS)has determined that cadmium and cadmium compounds are known human carcinogens. The International Agency for Research on Cancer (IARC)has determined that cadmium is carcinogenic to humans. The EPA has determined that cadmium is a probable human carcinogen.16 5.4.3.3 Lead The main target for lead toxicity is the nervous system, both in adults and children. Longterm exposure ofadults to lead at work has resulted in decreased performance in some tests that measure functions ofthe nervous system. Lead exposure may also cause weakness in fingers, wrists, or ankles. Lead exposure also causes small increases in blood pressure, particularly in middle-aged and older people. Lead exposure may also cause anemia. At high levels of exposure, lead can severely damage the brain and kidneys in adults or children and ultimately cause death. In pregnant women,high levels ofexposure to lead may cause miscarriage. Highlevel exposure in men can damage the organs responsible for sperm production.
We have no conclusive proofthat lead causes cancer (is carcinogenic) in humans. Kidney tumors have developed in rats and mice that had been given large doses ofsome kind oflead compounds. The Department ofHealth and Human Services (DHHS)has determined that lead and lead compounds are reasonably anticipated to be human carcinogens based on limited evidence from studies in humans and sufficient evidence from animal studies, and the EPA has determined that lead is a probable human carcinogen. The International Agency for Research on Cancer (IARC)has determined that inorganic lead is probably carcinogenic to humans. IARC determined that organic lead compounds are not classifiable as to their carcinogenicity in humans based on inadequate evidence from studies in humans and in animals.

16 Agency for Toxic Substances and Disease Registry (ATSDR). 2008. Public Health Statement for Cadmium. CAS# 1306-19-0. Atlanta, GA:U.S. Department ofHealth and Human Services, Public Health Service. Available on the Internet at <httn://www.atsdr.cdc.gov/PHS/PHS.asp?id=46&tid=15>.

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(Page 86 of Total)Children are more sensitive to the health effects oflead than adults. No safe blood lead

level in children has been determined. Lead affects children in different ways depending on how much lead a child swallows. A child who swallows large amounts oflead may develop anemia, kidney damage, colic (severe "stomach ache"), muscle weakness, and brain damage, which ultimately can kill the child. In some cases, the amount oflead in the child's body can be lowered by giving the child certain drugs that help eliminate lead from the body. Ifa child swallows smaller amounts oflead, such as dust containing lead from paint, much less severe but still important effects on blood, development, and behavior may occur. In this case, recovery is likely once the child is removed from the source oflead exposure, but there is no guarantee that the child will completely avoid all long-term consequences oflead exposure. At still lower levels ofexposure, lead can affect a child's mental and physical growth. Fetuses exposed to lead in the womb,because their mothers had a lot oflead in their bodies, may be born prematurely and have lower weights at birth. Exposure in the womb, in infancy, or in early childhood also may slow mental development and cause lower intelligence later in childhood. There is evidence that these effects may persist beyond childhood." 5.4.3.4 Hydrogen Chloride (HCl) Hydrogen chloride gas is intensely irritating to the mucous membranes ofthe nose, throat, and respiratory tract. Briefexposure to 35 ppm causes throat irritation, and levels of50 to 100 ppm are barely tolerable for 1 hour. The greatest impact is on the upper respiratory tract; exposure to high concentrations can rapidly lead to swelling and spasm ofthe throat and suffocation. Most seriously exposed persons have immediate onset ofrapid breathing, blue coloring ofthe skin, and narrowing ofthe bronchioles. Patients who have massive exposures may develop an accumulation offluid in the lungs. Exposure to hydrogen chloride can lead to Reactive Airway Dysfunction Syndrome (BADS),a chemically- or irritant-induced type of asthma. Children may be more vulnerable to corrosive agents than adults because ofthe relatively smaller diameter oftheir airways. Children may also be more vulnerable to gas exposure because ofincreased minute ventilation per kg and failure to evacuate an area promptly when exposed. Hydrogen chloride has not been classified for carcinogenic effects.18

"Agency for Toxic Substances and Disease Registry (ATSDR). 2007. Public Health Statement for Lead. CAS#: 7439-92-1. Atlanta, GA:U.S. Department ofHealth and Human Services, Public Health Service. Available on the Internet at < http://www.atsdr. cdc.gov /ToxProfiles/phsl3.htm1>. '$ Agency for Toxic Substances and Disease Registry (ATSDR). Medical Management Guidelines for Hydrogen Chloride (HCl). CAS#: 7647-01 -0. Atlanta, GA:U.S. Department ofHealth and Human Services, Public Health Service. Available on the Internet at < htt~//www.atsdr.cdc.gov/Mhmi/mmg173.html>.



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(Page 87 of Total)5.4.3.5 Dioxins (Chlorinated dibenzodioxins (CDDs) A number ofeffects have been observed in people exposed to 2,3,7,8-TCDD levels that
are at least 10 times higher than background levels. The most obvious health effect in people exposure to relatively large amounts of2,3,7,8-TODD is chloracne. Chloracne is a severe skin disease with acne-like lesions that occur mainly on the face and upper body. Other skin effects noted in people exposed to high doses of2,3,7,8-TCDD include skin rashes, discoloration, and excessive body hair. Changes in blood and urine that may indicate liver damage also are seen in people. Alterations in the ability ofthe liver to metabolize (or breakdown) hemoglobin, lipids, sugar, and protein have been reported in people exposed to relatively high concentrations of 2,3,7,8-TCDD. Most ofthe effects are considered mild and were reversible. However, in some people these effects may last for many years. Slight increases in the risk ofdiabetes and abnormal glucose tolerance have been observed in some studies ofpeople exposed to 2,3,7,8- TCDD. We do not have enough information to know if exposure to 2,3,7,8-TCDD would result in reproductive or developmental effects in people, but animal studies suggest that this is a potential health concern.
In certain animal species, 2,3,7,8-TCDD is especially harmful and can cause death after a single exposure. Exposure to lower levels can cause a variety ofeffects in animals, such as weight loss, liver damage, and disruption ofthe endocrine system. In many species ofanimals, 2,3,7,8-TCDD weakens the immune system and causes a decrease in the system's ability to fight bacteria and viruses at relatively low levels (approximately 10 times higher than human background body burdens). In other animal studies, exposure to 2,3,7,8-TCDD has caused reproductive damage and birth defects. Some animal species exposed to CDDs during pregnancy had miscarriages and the offspring ofanimals exposed to 2,3,7,8-TCDD during pregnancy often had severe birth defects including skeletal deformities, kidney defects, and weakened immune responses. In some studies, effects were observed at body burdens 10 times higher than human background levels.19 5.4.3.6 Furans (Chlorinated dibenzofurans (CDFs)) Most ofthe information on the adverse health effects comes from studies in people who were accidentally exposed to food contaminated with CDFs. The amounts that these people were exposed to were much higher than are likely from environmental exposures or from a normal diet. Skin and eye irritations, especially severe acne, darkened skin color, and swollen eyelids

19 Agency for Toxic Substances and Disease Registry (ATSDR). 1999. ToxFAQs for Chlorinated Dibenzo-p-dioxins (CDDs) (CAS#: 2,3,7,8-TCDD 1746-01 -6). Atlanta, GA:U.S. Department ofHealth and Human Services, Public Health Service. Available on the Internet at http:// www.atsdr.cdc.~ov

/tfacts104.html.
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### with discharge, were the most obvious health effects ofthe CDF poisoning. CDF poisoning also

caused vomiting and diarrhea, anemia, more frequent lung infections, numbness, effects on the nervous system, and mild changes in the liver. Children born to exposed mothers had skin irritation and more difficulty learning, but it is unknown ifthis effect was permanent or caused by CDFs alone or CDFs and polychlorinated biphenyls in combination. Many ofthe same effects that occurred in people accidentally exposed also occurred in laboratory animals that ate CDFs. Animals also had severe weight loss, and their stomachs, livers, kidneys, and immune systems were seriously injured. Some animals had birth defects and testicular damage, and in severe cases, some animals died. These effects in animals were seen when they were fed large amounts ofCDFs over a short time, or small amounts over several weeks or months. Nothing is known about the possible health effects in animals from eating CDFs over a lifetime.20 5.5 Characterization ofUncertainty in the Monetized PM2.5Benefits In any complex analysis, there are likely to be many sources ofuncertainty. Many inputs are used to derive the final estimate ofeconomic benefits, including emission inventories, air quality models (with their associated parameters and inputs), epidemiological estimates of concentration

-response (C-R)functions, estimates ofvalues, population estimates, income estimates, and estimates ofthe future state ofthe world (i.e., regulations, technology, and human behavior). For some parameters or inputs it may be possible to provide a statistical representation ofthe underlying uncertainty distribution. For other parameters or inputs, the necessary information is not available. The annual benefit estimates presented in this analysis are also inherently variable due to the processes that govern pollutant emissions and ambient air quality in a given year. Factors such as hours ofequipment use and weather are constantly variable, regardless ofour ability to measure them accurately. As discussed in the PM2,5 NAAQS RIA (Table 5-5) (U.S. EPA,2006), there are a variety ofuncertainties associated with these PM benefits. Therefore, the estimates of annual benefits should be viewed as representative ofthe magnitude ofbenefits expected, rather than the actual benefits that would occur every year.
It is important to note that the monetized benefit-per-ton estimates used here reflect specific geographic patterns ofemissions reductions and specific air quality and benefits

20 Agency for Toxic Substances and Disease Regishy (ATSDR). 1995. ToxFAQsiM for Chlorodibenzofurans (CDFs). Atlanta, GA: U.S. Department ofHealth and Human Services, Public Health Service. Available on the Internet at <

httn://www.atsdr.cdc.EOV /tfacts32.htm1>.


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### modeling assumptions. For example, these estimates do not reflect local variability in population

density, meteorology, exposure, baseline health incidence rates, or other local factors. Use of these $/ton values to estimate benefits associated with different emission control programs (e.g., for reducing emissions from large stationary sources like EGUs)may lead to higher or lower benefit estimates than if benefits were calculated based on direct air quality modeling. Great care should be taken in applying these estimates to emission reductions occurring in any specific location, as these are all based on national or broad regional emission reduction programs and therefore represent average benefits-per-ton over the entire United States. The benefits-per-ton for emission reductions in specific locations may be very different than the estimates presented here. PM2.5 mortality benefits are the largest benefit category that we monetized in this analysis. To better characterize the uncertainty associated with mortality impacts that are estimated to occur in areas with low baseline levels ofPM2.5, we included the LML assessment. Without policy-specific air quality modeling, we are unable to quantify the shift in exposure associated with this specific rule. For this rule, as a surrogate measure ofmortality impacts, we provide the percentage ofthe population exposed at each PMZ.S level using the most recent modeling available from the recently proposed Transport Rule (U.S. EPA,2010e). A very large proportion ofthe population is exposed at or above the lowest LML ofthe cohort studies (Figures 5-5 and 5-6), increasing our confidence in the PM mortality analysis. Figure 5-5 shows a bar chart ofthe percentage ofthe population exposed to various air quality levels in the preand post
-policy policy. Figure 5-6 shows a cumulative distribution function ofthe same data. Both figures identify the LML for each ofthe major cohort studies. As the policy shifts the distribution ofair quality levels, fewer people are exposed to PMZ.S levels at or above the LML. Using the Pope et al. (2002)study, the 85% ofthe population is exposed to annual mean PM2.5 levels at or above the LML of7.5 μg/m3. Using the Laden et al. (2006)study, 40% ofthe population is exposed above the LML of 10 μg/m3.As we model mortality impacts among populations exposed to levels ofPM2.5 that are successively lower than the LML ofthe lowest cohort study, our confidence in the results diminishes. However, the analysis above confirms that the great majority ofthe impacts occur at or above the lowest cohort study's LMI.,. It is important to emphasize that we have high confidence in PM2.5-related effects down to the lowest LML of the major cohort studies. Just because we have greater confidence in the benefits above the LML, this does not mean that we have no confidence that benefits occur below the LML.

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### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 35 of 40

(Page 90 of Total)zsr Pope ex al. 2002 Laden et al. 2006

20%

15/

10%

5%

0% The control svategy lowers PMZ.S levels substantially, parcicularly among highly exposed populations. In the baseline, 85% of the population lived in areas where PM2,5 levels above the lowest measured levels of the Pope study, increasing our confidence in the estimated mortality reductions for this rule.

1 2 3 4 5 5.8 6 7 7.5 8 9 10 11 12 13 14 15 16 17 18 19 20
■ Post

-control ■Baseline Figure 5-5. Percentage of Adult Population by Annual Mean PM2,5 Exposure

(pre- and post

-policy policy)

iouss

- Pope etal, 2002 Laden et al, 2006 y0°'o

SO°o

7096
~~~;
50%

4o°n

30°0

24'n

10?6

0°' The control strategy lowers PM25 levels substantially, particularly am ong h igh ly exposed populations, In the baseline, 89% of the population lived in areas where PM25 levels above the lowest measured levels of the Pope study, increasing our confidence in the estimated mortality reductions forthis rule. - ---- -- -

1 2 3 4 5 5.~ 6 7 7.5 ~ 9 1Q 11 12 13 14 15 1r, 1' 1S 15 20

— Port

- control

— Baselin? Figure 5-6. Cumulative Distribution of Adult Population at Annual Mean PMZ,S levels

(pre- and post

-policy policy)

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### Above we present the estimates ofthe total monetized benefits, based on our

interpretation ofthe best available scientific literature and methods and supported by the SABHES and the NAS (NRC,2002). The benefits estimates are subject to a number ofassumptions and uncertainties. For example, for key assumptions underlying the estimates for premature mortality, which typically account for at least 90% ofthe total monetized benefits, we were able to quantify include the following: 1. PM2.5 benefits were derived through benefit per-ton estimates, which do not reflect local variability in population density, meteorology, exposure, baseline health incidence rates, or other local factors that might lead to an over-estimate or underestimate ofthe actual benefits ofcontrolling directly emitted fine particulates. 2. We assume that all fine particles, regardless oftheir chemical composition, are equally potent in causing premature mortality. This is an important assumption, because PM2.5 produced via transported precursors emitted from EGUs may differ significantly from direct PM2,5 released from diesel engines and other industrial sources, but no clear scientific grounds exist for supporting differential effects estimates by particle type. 3. We assume that the health impact function for fine particles is linear down to the lowest air quality levels modeled in this analysis. Thus, the estimates include health benefits from reducing fine particles in areas with varied concentrations ofPM2.5, including both regions that are in attainment with fine particle standard and those that do not meet the standard down to the lowest modeled concentrations. 4. To characterize the uncertainty in the relationship between PM2.5 and premature mortality (which typically accounts for 85% to 95% oftotal monetized benefits), we include a set oftwelve estimates based on results ofthe expert elicitation study in addition to our core estimates. Even these multiple characterizations omit the uncertainty in air quality estimates, baseline incidence rates, populations exposed and transferability ofthe effect estimate to diverse locations. As a result, the reported confidence intervals and range ofestimates give an incomplete picture about the overall uncertainty in the PM2.5 estimates. This information should be interpreted within the context ofthe larger uncertainty surrounding the entire analysis. For more information on the uncertainties associated with PM2.5 benefits, please consult the PM2.5NAAQS RIA (Table 5-5). This RIA does not include the type ofdetailed uncertainty assessment found in the PM NAAQS RIA because we lack the necessary air quality input and monitoring data to run the benefits model. In addition, we have not conducted any air quality modeling for this rule. Moreover, it was not possible to develop benefit-per-ton metrics and associated estimates of uncertainty using the benefits estimates from the PM RIA because ofthe significant differences between the sources affected in that rule and those regulated here. However,the results ofthe

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### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 37 of 40

(Page 92 of Total)Monte Carlo analyses ofthe health and welfare benefits presented in Chapter 5 ofthe PM RIA

can provide some evidence ofthe uncertainty surrounding the benefits results presented in this analysis. 5.6 Comparison of Benefits and Costs Using a 3%discount rate, we estimate the total monetized benefits ofthe proposed SSI NSPS and EG including energy disbenefits to be $130 million to $320 million in the implementation year (2015). Using a 7% discount rate, we estimate the total monetized benefits ofthe SSI NSPS and EG including energy disbenefits to be $120 million to $290 million. The annualized costs are $92 million at a 7% interest rate.21 Thus, net benefits are $37 million to $220 million at a 3%discount rate for the benefits and $26 million to $190 million at a 7% discount rate. All estimates are in 2008$. Table 5 -9 shows a summary ofthe monetized co-benefits, social costs, and net benefits for the SSI NSPS and EG,respectively. Figures 5-7 and 5-8 show the full range ofnet benefits estimates (i.e., annual co-benefits minus annualized costs) utilizing the 14 different PM2,5 mortality functions at discount rates of 3%and 7%. In addition, the benefits from reducing 2,900 tons ofcarbon monoxide, 96 tons ofHCI, 3.0 tons of lead, 1.6 tons ofcadmium, 5,500 pounds of mercury, and 90 grams oftotal dioxins/furans each year have not been included in these estimates.

21 For more information on the annualized costs, please refer to Section 4 ofthis RIA. There are no estimates of costs available at a 3%discount rate.
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### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 38 of 40

(Page 93 of Total)S3so
S3oo
Szso

~. Szoo 0 0 Slso 0

~ $100
$50
$0
-$50 Cost estimate combined with total monetized benefits estimates derived from 2 epidemiology functions and 12 expert functions Figure 5-7. Net Benefits for the Proposed SSI NSPS and EG at 3% Discount Rate a a Net Benefits are quantified in terms ofPM2.5 benefits for implementation year (2015). This graph shows 14 benefits estimates combined with the cost estimate. All combinations are treated as independent and equally probable. All fine particles are assumed to have equivalent health effects, but the benefit per ton estimates vary because each ton ofprecursor reduced has a different propensity to become PM25. The monetized benefits incorporate the conversion from precursor emissions to ambient fine particles. These estimates include energy disbenefits valued at $0.5 million at a 3% discount rate for COz emissions.

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### USCA Case #11-1131 Document #1334650 Filed: 10/11/2011 Page 39 of 40

(Page 94 of Total)$300

$250

$200

o $150 0 N
C O ~1~~
Sso P
So _...

-Sso

-- Cost estimate combined with total monetized benefits estimates derived from 2 epidemiology functions and 12 expert functions Figure 5-8. Net Benefits for the Proposed SSI NSPS and EG at 7% Discount Rate a
aNet Benefits are quantified in terms ofPM2.5 benefits for implementation year (2015). This gaph shows 14 benefits estimates combined with the cost estimate. All combinations are treated as independent and equally probable. All fine particles are assumed to have equivalent health effects, but the benefit per ton estimates vary because each ton ofprecursor reduced has a different propensity to become PM2 5. The monetized benefits incorporate the conversion from precursor emissions to ambient fine particles. These estimates include energy disbenefits valued at $0.5 million at a 3°/o discount rate for COZ emissions.

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