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- 1 From: Lydia Wegman/RTP/USEPA/US To: "Frey, Nathan J." <Nathan_J._Frey@omb.eop.gov> Cc: Beth Hassett

- Sipple/RTP/USEPA/US@EPA, Karen Martin/RTP/USEPA/US@EPA, John

Hannon/DC/USEPA/US@EPA, Joseph

- J Dougherty/DC/USEPA/US@EPA, Steven Silverman/DC/USEPA/US@EPA Date: 12/11/2012 03:58 PM Subject: PM NAAQS FRN: Updated preamble language and draft RTC on the primary PM2.5 stds

Nathan,

Attached is a compare version to the interagency review draft final rule preamble, pages 114

- 117, reflecting our expanded response to specific public comments and the portion of the draft Response to Comments document responding to general and specific com ments on the proposed primary PM2.5 standards, as requested yesterday. Please let me know if you have any questions. Thanks.Draft

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- 2 Revisions to section III of PM NAAQS FRN Preamble EO12866_PM_NAAQS_2060AO47_FRN_Preamble_and_Reg_Text_20121120.docx Pgs: 114

- 117

Several commenters offered detailed comments on the long

- term PM 2.5 exposure studies

arguing that associations from mortality studies are subjected to unmeasured confounding and as

a result are not appropriately characterized as being cau s al ( providing evidence of a causal

relationship between long

- term PM 2.5 exposure and mortality ( e.g., UARG, 2012, pp. 10 to 11,

Attachment A, pp. 17 to 23; API, 2012, pp. 13 to 14, Attachment 1, pp. 11 to 14 , Attachment 7,

pp. 2

- 10 ; ACC, 2012, p. 18 to 21; AFPM, 2012, p. 8; TCEQ T exas CEQ , 2012, p. 4).

Specifically, these commenters cited two studies (i.e., Janes et al.

, 2007 and Greven et al.

, 2011)

that used a new type of statistical analysis , in which the study authors to examine associations

between annual (long

- term) and monthly (sub

- chronic) PM 2.5 exposure and mortality . The

commenters interpreted the results of the analysis the se analys e s as evidence of unmeasured

confounding in the long

- term PM 2.5 exposure

- mortality relationship. These commenters

interpreted these studies as raising fundamental questions regarding the EPA’s d etermination that

a causal relationship exists between long

- term PM 2.5 exposure and mortality. In addition to the

commenters mentioned above, all of the authors of the publications by Janes et al. (2007) and

Greven et al. (2011 ) (i.e., Francesca Dominici, Scott Zeger, Holly Janes, and Sonja Greven)

submitted a joint comment to the public docket in order to clarify specific points regarding these

two studies (Dominici et al

., 2012).

The first study, Janes et al.

, ( 2007 ) , was evalu ated in the Integrated Science Assessment

(U.S. EPA, 2009a, p. 7

- 88). The second study, Greven et al

., . ( 2011

, )

, an extension of the Janes

et al. (2007) study adding three more years of data, is a “new” study discussed in the Provisional

Science Assessment (U.S. EPA, 2012 ) and the Response to Comments document. ). Both studiesDraft

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- 3 used nationwide Medicare mortality data to examine the association between monthly average

PM 2.5 concentrations over the preceding 12 months and monthly mortality rates in 11 3 U.S.

counties

. and examined whether community

- specific trends in monthly PM 2.5 concentrations and

mortality declined at the same rate as the national rate

. The investigators decomposed examined

this by decompos ing the association between PM 2.5 and mortali ty into two components: (1)

“national trends” national trends

, defined as the association between the national average trend in

monthly PM 2.5 concentrations averaged over the previous 12 months and the national average

trend in monthly mortality rates

, and (2) “ local trends

, ,”

, defined as county

- specific deviations in

monthly PM 2.5 concentrations and monthly mortality rates from national trends.

The EPA does not question the results of the national trends analyses conducted by Janes

et al. (2007) and Gr even et al. (2011). These analyses demonstrated associations similar in

magnitude and precision to other studies of long

- term PM 2.5 exposure and mortality. However,

the authors hypothesized that the results from the “local” and “national” analyses should be

similar in magnitude, and that any difference between the two results would be due to

unmeasured confounding. 1 The authors provide d no references to support their assumptions that

associations between PM 2.5 and mortality should be similar across tempora l and spatial scales

nor why any differences in effect estimate size would be due to unmeasured confounding. 2 Both

Janes et al. (2007) and Greven et al. (2011) observed positive and statistically significant

associations between long

- term exposure to PM 2.5 and mortality in their national analyses.

1 Unmeasured confound ers need to be factors that are associated with both the exposure and outcome of interest, but in the case of the Janes and Greven stud ies this would also need to hold true over multiple dimensions of time and space as stated by Pope and Burnett , 2007

. 2 In its evaluation of Janes et al . (2007) in the I ntegrated S cience A ssessment , the EPA did not identify limitations in the statistical methods used per se (U.S. EPA, 2009a, p. 7

- 88) and included the results of the national

- scale analyses in that study in the body of evidence that support ed the determination that there is a causal relationship between long

- term PM 2.5 exposure and mortality

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- 4 However, Janes et al. (2007) and Greven et al. (2011) eliminated all of the spatial variation in air

pollution and mortality in thei r data set when estimating the national effect , focusing instead on

both chronic (yearly) and sub

- chronic (monthly) temporal differences in the data (Domin i ci et al.

2012)

. Janes et al. (2007) (Table 1) highlight ed that over 90 percent of the variance in the data

set used for the analyses conducted by both Janes et al. (20 07) and Greven et al. (2011) was
attributable to spatial variability, which the authors chose to discard. As noted above, t he focus

of the analyses by Janes et al. (2007) and Greven et al. (2011) was on two components: (1) a

temporal or time component, i.e., the “national” trends analysis, which examined the association

between the national average trend in monthly PM 2.5 concentrations averaged over the previous

12 months and the national average trend in monthly mortality rates and (2) a space

- by

- time

c omponent, i.e., “local” trends analysis, which examined county

- specific deviations in monthly

PM 2.5 concentrations and monthly mortality rates from national trends. These two components

combined comprised less than 10 percent of the variance in the data set

. The authors included a

focus on the space

- by

- time component , which represented approximately 5 percent of the

variance in the data set, in an attempt to identify, absent confounding, if PM 2.5 was associated

with mortality at this unique exposure window. Thus, these studies are not directly comparable to

other cohort studies investigating the relationship between long

- term exposure to PM 2.5 and

mortality, which make use of spatial variability in air pollution and mortality data

. 3 This point

was highlighted by the study authors who stated that “ when one considers that this wealth of

3 Though not directly comparable, the national effect estimates for mortality reported by Janes et al. (2007) and Greven et al. (2011) are coincidentally similar in magnitude to those previously reported. It is important to note that previous cohort studies have focused on identifying spatial differences in PM 2.5 concentrations between cities, while Janes et al. (2007) and Greven et al. (2011 ) focus primarily on temporal differences in PM 2.5 concentrations. In fact, Greven et al. (2011) state “We do not focus here on a third type [of statistical approach] used in cohort studies, measuring the association between average PM 2.5 levels and averag e age

- adjusted mortality rates across cities (purely spatial or cross

- sectional association).”Draft

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- 5 information is not accounted for in [ Janes 2007 ], it is not as surprising that

... vastly different

estimates of the PM 2.5 /mortality relationship [were observed] than in other studies that do exploit

that variability ” ( Dominici et al., 2012, p. 2 ).

Consistent The EPA notes that the results of the local trends analyses conducted by Janes

et al. (2007) and Greven et al. (2011) are limited by the monthly timescale used in these

analyses. This view is c onsistent with comments on the Janes et al. (2007) study articulated in

Pope and Burnett (2007 ), the EPA notes 4 which noted that an important limitation of the local

scale analysis conducted by Janes et al. (2007) and subsequently by Greven et al. (2011) is was
the subchronic exposure window considered in these analyses. Both studi es used annual average

PM 2.5 concentrations to characterize long

- term national trends which is was consistent with

exposure windows considered in other studies of long

- term exposure to PM 2.5 and mortality

studies.

. 5 However, the local scale analyses used monthly average PM 2.5 concentrations to

characterize county

- specific deviations from national trends (the “ local ” scale). The use of

monthly average data likely does not provide enough exposure contrast to observe te mporal

changes in mortality at the local scale. It also represents a different exposure window than

considered in the large body of evidence of health effects related to short

- term (from less than

one day to up to several days) and chronic (one or more yea rs) measures of PM 2.5
.

As discussed by Pope and Burnett (2007) and highlighted in the I ntegrated S cience

A ssessment , the conclusions of Janes et al

. Furthermore, the EPA disagrees with commenters that

studies by Janes et al. (2007) and Greven et al. (2011) provide evidence that other studies of

4 S ome commenters argued that there were flaws in the criticisms offered by Pope and Burnett (2007) on the paper by Janes et al. (2007) (UARG, 2012, Attachment A , pp. 19 to 23). The EPA responds to each of these specific comments in the Response to Comments document.
5 As noted above, however, Janes et al. (2007) and Greven et al. (2011) focus ed on temporal variability and other studies of long

- term exposure to PM 2.5 and mortality focus on spatial variability

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- 6 long

- term exposure to PM 2.5 and mortality are affected by unmeasured confounding. As noted

above, the design of the studies conducted by Janes et al (2007) and Greven et al (2011) are

fundamentally different than tho se used in other studies of long

- term exposure to PM 2.5 and

mortality , including the Amer i can Cancer Society (ACS) cohort and the Harvard Six Cities

study. S tudies , such as the ACS and Harvard Six Cities studies, used the spatial variation

between cities t o measure the effect of long

- term (annual) exposures to PM 2.5 on mortality risk,

and did not conduct any analyses relying on the temporal variation in PM 2.5
. The opposite is true

of the Janes et al

. (2007) and Greven et al

. (2011) studies which first removed the spatial

variability in PM 2.5 and then examined the temporal variation at both the national and local scale

to measure the effects of temporal differences in PM 2.5 on mortality risk. Janes et al. (2007) and

Greven et al. (2011) focus on changes in PM 2.5 concentrations over time and

, therefore

, control

for confounders would be based on including variables that vary over time rather than over

space. As a result, any evidence of potential confounding of the PM 2.5 - mortalit y risk relationship

derived from Janes et al. (2007) and Greven et al. (2011) cannot be extrapolated to draw

conclusions related to potential spatial confounding in studies based on the spatial variation in

PM 2.5 concentrations.

As detailed in the I ntegrated S cience A ssessment (U.S. EPA, 2009a, section 7.6)

, and

recognized by the authors of Janes et al. (2007) and Greven et al. (2011), the cohort studies that

informed the causality determination for long

- term PM 2.5 exposure and mortality “have

develo ped approaches to adjust for measured and unmeasured confounders” (Dominici et al

.,

2012 , p. 2 ). These approaches were specifically designed to adjust for spatial confounding. The

hypothesis that the authors of Janes et al. (2007) and Greven et al. (2011) chose to examine was

that differences in the local and national effects indicated unmeasured temporal confounding inDraft

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- 7 either the local or national effect estimate . This hypothesis was specific to these two studies that

examined temporal variability in expos ure to air pollution and did not include known potential

confounders at either the national or local scale as time

- varying covariates in the statistical

model. The authors acknowledge d that the interpretation of either the national or local estimates

needs to occur with an appreciation of the potential confounding effects of national and local

scale covariates that were omitted from the model ( Dominic i et al.

, 2012 ).

It is important to recognize that because Janes et al. (2007) and Greven et al. (2011)

focus ed on variations in PM 2.5 over time and not space, the results from these two studies do not

provide any indication that other studies of long

- term exposure to PM 2.5 and mortality exhibit

spatial confound ing , or that PM 2.5 does not cause mortality. 6 The authors of Janes et al. (2007)

and Greven et al. (2011) recognized that “it is entirely possible that these papers are looking for

an association at a timescale for which no association truly exists” (Dominici et al

., . 2012 , p. 3 ).

Furthermore, as high lighted in the Integrated Science Assessment and discussed by Pope and

Burnett (2007)

, the conclusions of Janes et al. (2007) “are overstated. . . [T]heir analysis tells us

little or nothing about unmeasured confounding in those and related studies because the

methodology of Janes et al

. largely excludes the sources of variability that are exploited in those

other studies. By using monthly mortality counts and lagged 12

- month average pollution

concentrations, the authors eliminate the opportunity to exploit short

- term or day

- to

- day

variab ility.” Some commenters argued that there were flaws in the criticisms offered by Pope

and Burnett (2007) on the paper by Janes et al. (2007) (UARG, 2012, Attachment A, pp. 19 to

23). The EPA responds to each of these specific comments in the Response to C omments

document. In its evaluation of Janes et al. (2007), the EPA did not identify limitations in the

6 Further, the EPA notes that Janes et al. (2007) and Greve n et al. (2011) provide no information relevant to examining confounding in studies of short

- term exposure to PM 2.5
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- 8 statistical methods used per se ( U.S. EPA, 2009a, p. 7

- 88) and the results of the national

- scale

analyses were included in the body of evidence that sup ported the determination that there is a

causal relationship between long

- term PM 2.5 exposure and mortality

In conclusion, the EPA believes interprets the results of the analyses conducted by Janes

et al. (2007) and Greven et al. (2011) are as being consiste nt with prior knowledge of examining

associations with long

- term exposure to PM 2.5 at the national scale using long

- term average

PM 2.5 concentrations. However, for For the reasons presented above and discussed in more detail

in the Response to Comments document, the Agency disagrees with the commenters’ assumption

that their “national” and “local” scale analyses should produce similar the results and their

conclusion that differing results is evidence of Janes et al. (2007) and Greven et al. (2011)

indicate unmeasured confounding

. in the results of other cohort studies of long

- term exposure to

PM 2.5 and mortality

. Therefore, the EPA concludes that these studies do not bring into

question invalidate the large body of epidemiological evidence indicating that supports the EPA’s

determination that a causal association relationship exists between long

- term PM 2.5 exposure and

mortality.

7

7 The EPA notes that the EPA’s conclusion with regard to interpretation of the results from Janes et al. (2007) and Greven et al. (2012) is supported by the study authors ’ conclusion that “[ o]ur results do not invalidate previous epidemiologic al studies ” (Dominici, 2012, p. 1 (emphasis original)).Draft

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- 9 II. RESPONSES TO SIGNIFICANT COMMENTS ON PROPOSED PRIMARY PM 2.5 STANDARDS

A. General Comments on Proposed Primary PM 2.5 Standards

A large number of comments on the proposed primary standards for PM 2.5 were very general in nature, basically expressing one of two substantively different views: (1) support for revisions to the primary standards to be more public health

- protective or (2) opposition to any revision of the current PM 2.5 standards. Many of these commenters simply expressed their views without stating any rationale, while others gave general reasons for their views but without reference to the factual evidence or rationale presented in the proposal notice as a basis for the Agency’s propos ed decision. The preamble to the final rule in its entirety presents the Agency’s response to these very general views.

Specific public comments on a range of issues related to the proposed primary PM 2.5 standards are addressed in the preamble to the fin al rule and/or in this document. In particular, significant public comments related to whether or not the current PM 2.5 standards should be revised are addressed in section II I

. D.2 of the preamble. Sections I II. E.1, III.E.2, III.E.3, and III.E.4.c of the p reamble discuss significant comments addressing the four basic elements of the standard: indicator, averaging time, form, and level, respectively. Significant comments on the revised Air Quality Index (AQI) for PM 2.5 are discussed in section V of the preamble. Significant comments on the data handling conventions for PM 2.5 are discussed in section V I I .A of the preamble. Below, the E PA provides more specific responses to the full range of significant issues raised in t he public comments on these issues.

B. Specific Comments on Proposed Primary PM 2.5 Standards

A large number of commenters provided more detailed comments regarding the proposal
to revise the level and form of the primary annual PM 2.5 standard in conjunction w ith retaining the current 24

- hour standard. Below, the EPA provides more detailed responses to the full range of significant issues raised in these comments.

1. Need to Revise Current Standards

This section responds to more detailed comments that either supp ort or oppose any revision to the current PM 2.5 primary standards

. The responses to these comments are generally discussed in section II I

. D.2 of the preamble to the final rule and discussed more fully below. Significant comments on specific long

- and short

- term exposure studies that relate to consideration of the appropriate level of the annual and 24

- hour PM 2.5 standards are addressed in sections I I I. E

. 4. c. i and I II. E

. 4. c. ii in the preamble to the final rule and discussed more fully below in sect ions II. B

. 5

. a and II. B

. 5

. b respectively. Incorporating responses contained in sections I I I. E.4.c of the preamble to the final rule

, the EPA provides the following responses to specific issues related to the need to revise the fine particle standards

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- 10 a. Suppo rt for Revising the Current Standards

Many public comments asserted that the current PM 2.5 standards are insufficient to protect public health with an adequate margin of safety and that revisions to the standards are therefore appropriate within the meaning of section 109 (d) of the Act , indeed necessitated. Among those calling for revisions to the current standards were the Children’s Health Protection Advisory Committee (CHPAC); major medical and public health groups including the Americ an Heart Association (AHA), American Lung Association (ALA), American Public Health Association (APHA), American Thoracic Society (ATS); the Physicians for Social Responsibility (PSR); the International Society for Environmental Epidemiology (ISEE); major environmental groups such as the Clean Air Council, Clean Air Task Force, Earthjustice, Environmental Defense Fund (EDF), National Resources Defense Council (NRDC), and Sierra Club; many environmental justice organizations as well as medical doctors, acade mic researchers, health professionals, and many private citizens.

All of these medical and public health commenters stated that the current PM 2.5 standards need to be revised, and that even more protective standards than those proposed by the EPA are needed to adequately protect public health, particularly for at

- risk populations. Many environmental justice organizations and individual commenters a lso expressed such views.

The National Association of Clean Air Agencies (NACAA), the Northeast States for Coordinated Air Use Management (NESCAUM), and many s tate and local air agencies and health departments who commented on the PM 2.5 standards supported revision of the suite of current PM 2.5 standards, as did five s tate a ttorneys g eneral (Schneiderman et al., 2012) and the National Tribal Air Association (NTAA).

(1) Comment: In general, all of these commenters agreed on the importance of results from the lar ge body of scientific studies and technical analyses presented and discussed in the Integrated Science Assessment (ISA), the Risk Assessment (RA), and the Policy Assessment (PA) and on the need to revise the PM 2.5 standards as articulated in section III.D of the preamble to proposal . Many of these commenters, however, generally expressed views differ ing from the EPA’s proposed judgments about the extent to which the standards should be revised based on this evidence, specifically for providing protection fo r at

- risk populations. These commenters generally concluded that the body of evidence assessed in the ISA was stronger and more compelling than in the last review. In addition, these commenters generally placed much weight on the Clean Air Scientific Advis ory Committee’s ( CASAC ) interpretation of the body of available evidence and CASAC’s recommendation to revise the PM 2.5 standards to provide increased public health protection

. In arguing for more health protective standards, these commenters expressed the following specific views:

Multiple, multi

- city studies show clear evidence of premature mortality, cardiovascular and respiratory harm, as well as reproductive and development al effects at ambient concentrations “far below the level of the current standard” (ALA, et al., 2012, p. 39). Specific studies cited by commenters included:Draft

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- 11 o E xtended analyses of seminal long

- term exposure studies

- the A merican C ancer S ociety (ACS) (Krews ki et al., 2009), Harvard Six Cities (Laden et al., 2006), and Southern California Children’s Health (Gauderman et al., 2004) studies.

o A dditional long

- term exposure studies available in this review, specifically a study of premature mortality in older adul ts (Eftim et al., 2008) and the Women’s Health Initiative (WHI) study of cardiovascular morbidity and mortality effects in women (Miller et al., 2007) providing stronger evidence of mortality and morbidity effects associated with long

- term PM 2.5 exposures at lower concentrations than had previously been observed, including studies of effects in at

- risk populations.

o A number of short

- term PM 2.5 exposure studies providing evidence of mortality and morbidity effects at concentrations below the level of the

cur rent 24

- hour PM 2.5 standard. Specifically, these commenters made note of multi

- city studies of premature mortality (Zanobetti and Schwartz, 2009) and increased hospitalizations for cardiovascular and respiratory

- related effects in older adults (Bell et al. , 2008).

S ingle

- city short

- term PM 2.5 studies “provide valuable information regarding impacts on susceptible populations and on health risk in areas with high peak to mean concentration ratios” (ALA, et al., 2012, p. 65).

P rogress ha s been made in reducing many of the uncertainties identified in the last review, in better understanding mechanisms by which PM 2.5 may be causing the observed health effects, and in improving our understanding of at

- risk populations.

The EPA’s quantitative risk assessment concluded that the risks estimated to remain when the current standards are met are large and important from a public health perspective and warrant increased protection.

PM 2.5 - related risks are likely larger than those estimated in the RA , in part because the EPA focused on limited study areas and health endpoints

. Some commenters cited
to a recent study ba sed on 2005 air quality data . In this study, the EPA staff publi shed estimates that “ peg the annual toll from PM 2.5 at 130,000 prematur e deaths each year” 8 (ALA et al., p. 5). Furthermore, “this analysis estimated a staggering 1.1 million life years lost among people over age 65, accounting for 7 percent of life years lost in 2005 in this population of elderly Americans. Looking at it ano ther way, this translates into an average shortened lifespan of 8.5 months per individual affected. Further, the analysis estimated 1,800 deaths among babies and infants attributable to PM air pollution.” Id.

The EPA’s distributional statistical analysis o f population

- level data (i.e., health event data and study population data) provide important information beyond a single

8 Fann et al., 2012Draft

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II

- 12 statistical metric (e.g., mean) to consider in reaching decisions on the appropriate annual standard level

. Response: The EPA generally agrees with these commenters’ conclusion regarding the need to revise the current suite of PM 2.5 standards. The scientific evidence noted by these commenters was generally the same as that assessed in the ISA and the PA , and the EPA agrees that t

his evidence provides a strong basis for concluding that the current PM 2.5 standards, taken together, are not requisite to protect public health with an adequate margin of safety, and they need to be revised to provide increased protection. For reasons dis cussed in section III.E.4.c of the preamble to the final rule and in section II.B.5 below

, however, the EPA disagrees with aspects of these commenters’ views on the level of protection that is appropriate

. In addition, with regard to progress made to bette r understand mechanisms by which PM 2.5 may be caus ing the observed health effects and to improv e our understanding of at

risk populations

, the EPA notes that CASAC found that the ISA clearly presented and discussed the current scientific information relate d to potential modes of action (Chapter 5) and at

- risk populations (Chapter 8) (Samet, 2009e, pp. 7 to 8; Samet, 2009f, pp. 2 and 11 to 12).

(2) Comment: With regard to the scope of the literature reviewed for PM 2.5 - related health effects, some commenters asserted that the EPA inappropriately narrowed the scope of the review by excluding a number of categories of relevant studies, specifically related to studies of diesel pollution and traffic

- related pollution (ALA, et al., 2012, p. 17). These commenters argued that, based upon the exclusion of these types of studies, the ISA “came to the erroneous conclusion that the causal relationship between PM and cancer is merely suggestive. This conclusion does not square with the International Agency Research on Cancer (IARC) finding that diesel emissions are a known human carcinogen nor with the conclusions of the extended analyses of the [Harvard] Six Cities and ACS cohort studies that report positive and statistically signi ficant associations between PM 2.5 and lung cancer.” Id.

Response: T he EPA disagrees with these commenters’ views that diesel exhaust studies were excluded from the ISA and were not considered when making the causality determination for cancer, mutagenicity, and genotoxicity. As discussed in s ection 7.5 of the ISA, diesel exhaust studies were integrated within the broader body of scientific evidence that was considered in reaching the causality determination for these health endpoints. Additionally, as discussed in section 1.5.3 of the ISA, the evidence from diesel exhaust studies was also considered as part of the collective evidence evaluated when making determinations for other, noncancer health outcomes (e.g., cardiovascular and respiratory effects). Specifically, when evaluating this evidence

, the ISA focus ed on underst anding the effects of diesel exhaust particles. It is important to recognize that the ISA focused on diesel exhaust studies that evaluated exposures that were relevant to ambient concentrations, i.e., “within one or two orders of magnitude of ambient PM

co ncentrations” (U.S. EPA, 2009a, section 1.3). The causal determination for cancer, mutagenicity, and genotoxicity presented in the ISA represents an integration of experimental and observational evidence of exposures to ambient PM concentrations.Draft

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- 13 The EPA f

ully considered the findings of studies that assessed these and other health effects associated with exposure to diesel particles in reaching causality determinations regarding health outcomes associated with PM 2.5 exposures.
In developing the second draf t ISA, the EPA reexamined the controlled human exposure and toxicological studies of fresh diesel and gasoline exhaust

. T his information, in addition to other considerations

, supported a change in the causal determinations for ultrafine particles. Specifically, in reevaluating the causal determinations for short

- term ultrafine particle exposures and cardiovascular and respiratory effects, the EPA changed the classification fro m “inadequate” to “suggestive ” for both categories of health outcomes (Vandenberg, 2009, p. 3). CASAC agreed with the EPA’s rationale for revising these causal determinations (Samet, 2009f, p p

. 2 and 10).

With regard to traffic studies, the EPA disagrees w ith the commenters’ views that traffic studies that focused on exposure indicators such as distance to roadways should have been included in the ISA. These studies were excluded from consideration because they did not measure ambient concentrations of spec ific air pollutants, including PM 2.5 , but instead were studies evaluating exposure to the undifferentiated “traffic related air pollution” mixture (ALA et al., 2012, p.17) (U.S. EPA, 2009a, section 1.3). As a result, these studies do not add to the collect ive body of evidence on the relationship between long

- or short

- term exposure to ambient concentrations of PM 2.5 and health effects.

(3) Comment : A number of commenters argued that by making the standards more protective, the PM 2.5 NAAQS would be more consiste nt with other existing standards (e.g., California's annual average standard of 12 μg/m 3 ) (CARB, 2012; CA OEHHA, 2012). Some commenters argued that “in the intervening decade since the California standard was established, substantial new information regard ing adverse health effects at lower concentrations supports setting a more protective standard (ALA et al, 2012, p. 23). Other commenters argued that revising the primary PM 2.5 standards would be more consistent with the recommendations of the World Health Organization (WHO) and/or Canada (e.g., ALA et al., 2012, p p

. 22 and 62; ISEE, 2012, p. 2 ; MOE

- Ontario, 2012, p. 1)

. Response : In considering these comments, the EPA notes tha t the Administrator’s decision on setting an appropriate annual standard level is constrained by the provision of the CAA that requires that the primary NAAQS be requisite to protect public health with an adequate margin of safety. This requires that her j udgment is to be based on an interpretation of the evidence that neither overstates nor understates the strength and limitations of the evidence, or the appropriate inferences to be drawn from the evidence. This is not the same legal framework that governs the standards set by the State of California or Canada or the guidelines established by a working group of scientists within the WH O

. For example, the California statute does not refer to setting a standard that is ‘‘requisite’’ to protect, as that term is used in the CAA, and California, unlike EPA, may take economic impacts into consideration in setting air quality standards. In addition, as with the WHO guidelines, the standards appear to be more in the nature of goals as compared to binding requiremen ts that must be met.Draft

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- 14 As discussed in section III.E.4.d of the preamble for the final rule, the Administrator has considered the epidemiological and other scientific evidence, estimates of risk reductions associated with just meeting alternative standards, air quality analyses, related limitations and uncertainties, the advice of CASAC, and the extensive public comments on the
propo sal in reaching her conclusions regarding final decision on the appropriate primary annual PM 2.5 standard level , consistent with the requirements of the CAA.

(4) Comment: Some of these commenters also identified “new” studies that were not included in the ISA as providing further support for the need to revise the PM 2.5 standards.

Response : In the proposal, the EPA recognized that th ere were a number of new scientific studies on the health effects of PM that had been published since the mid

- 2009 cutoff date for inclusion in the ISA (77 FR 38899). A s discussed in section I I. B.3 of the preamble to the final rule, the EPA conducted a provisional assessment of “new” science published since the close of the ISA including studies submitted to the EPA during the public comment period. The purpose of the provisional science assessment was to ensure that the Administrator wa s fully aware of the “ new ” science that has developed since 200 9 before making final decisions on whether to retain or revise the current PM NAAQS.

Specifically, t he EPA screened and surveyed the recent health literature, including but not limited to studies submitted dur ing the public comment period, and conducted a provisional assessment (U.S. EPA, 2012b) that places the results of those studies of potentially greatest policy relevance in the context of the findings of the ISA (U.S. EPA, 2009a). This provisional assessme nt, including a summary of the key conclusions is included in Appendix A to this RTC document

. The provisional assessment found that the “new” studies expand the scientific information considered in the I SA and provide important insights on the relationshi p between PM exposure and health effects. The provisional assessment also found that “new” studies generally strengthen the evidence that long

- and short

- term exposures to fine particles are associated with a wide range of health effects (i.e. the stronges t causality determination possible under the EPA framework)

. Although s ome of the “new” epidemiological studies report effects in areas with lower PM 2.5 concentrations than those in earlier studies considered in the ISA , and “new” toxicological and epidemi ological studies continue to link various health effects with a range of fine particle sources and components , the provisional assessment found that the results reported in “new” studies do not materially change any of the broad scientific conclusions rega rding the health effects of PM exposure made in the ISA.

As further noted in section II.B.3 of the preamble to the final rule, as in prior NAAQS reviews, the EPA is basing its decision in this review on studies and related information included in the ISA, RA, and PA, which have undergone CASAC and public review. The studies assessed in the ISA , and the integration of the scientific evidence presented in that document, have undergone extensive critical review by the EPA, CASAC, and the public during the dev elopment of the ISA. The rigor of that review makes these studies, andDraft

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- 15 their integrative assessment, the most reliable source of scientific information on which to base decisions on the NAAQS. NAAQS decisions can have profound impacts on public health and welfare, and NAAQS decisions are based on studies that have been rigorously assessed in an integrative manner not only by the EPA but also by the statutorily

- mandated independent advisory committee, CASAC, and have been subject ed as well to the public revi ew that accompanies this process. As described above, the provisional assessment did not and could not provide that kind of in

- depth critical review.

This decision is consistent with the EPA’s practice in prior NAAQS reviews. Since the 1970 amendments, the EPA has taken the view that NAAQS decisions are to be based on scientific studies and related information that have been assessed as a part of the pertinent air quality criteria. See e.g., 36 FR 8186 (April 30, 1971) (the EPA based original NAAQS for six pollutants on scientific studies discussed in air quality criteria documents and limited consideration of comments to those concerning validity of scientific basis); 38 FR 25678, 25679 to 25680 (September 14, 1973) (the EPA revised air quality criteria for sulfur oxides to provide basis for reevaluation of secondary NAAQS). This longstanding interpretation was strengthened by new legislative requirements enacted in 1977, which added section 109(d)(2) of the CAA concerning CASAC review of air quality criteri a. The EPA has consistently followed this approach. 52 FR 24634, 24637 (July 1, 1987) (after review by CASAC, the EPA issued a post

- proposal addendum to the PM Air Quality Criteria Document (AQCD) , to address certain new scientific studies not included in the 1982 AQCD); 61 FR 25566, 25568 (May 22, 1996) (after review by CASAC, the EPA issued a post

- proposal supplement to the 1982 AQCD to address certain new health studies not included in the 1982AQCD or 1986 Addendum). The EPA reaffirmed this approach in i ts decision not to revise the ozone NAAQS in 1993, as well as in its final decision on the PM NAAQS in the 1997 and 2006 reviews. 58 FR 13008, 13013

- 13014 (March 9, 1993) (ozone review); 62 FR 38652, 38662 (July 18, 1997) and 71 FR 61141, 61148

- 61149 (O ctober 17, 2006) (PM reviews) (The EPA conducted a provisional assessment but based the final PM decisions on studies and related information included in the air quality criteria that had been reviewed by CASAC).

As discussed in the EPA's 1993 decision not to revise the NAAQS for ozone, “ new ” studies may sometimes be of such significance that it is appropriate to delay a decision on revision of NAAQS and to supplement the pertinent air quality criteria so the “new” studies can be taken into account (58 FR at 13013 to 13014, March 9, 1993). In this 2012 review of the PM NAAQS , the provisional assessment of recent studies concludes that, taken in context, the “new” information and findings do not materially change any of the broad scientific conclusions regarding the health effects of PM exposure made in the ISA (U.S. EPA, 2012b). For this reason, reopening the air quality criteria review would not be warranted even if there were time to do so under the court order gov erning the schedule for this rulemaking. Accordingly, the EPA is basing the final decisions in this review on the studies and related information included in the PM air quality criteria that have undergone CASAC and public review. The EPA will consider the “new” published studies for purposes of decision making in the next periodic review of the PM NAAQS, which will provide the opportunity to fully assess them through a more rigorous review process involving the EPA, CASAC, and the public.Draft

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- 16 (5) Comment: Some com menters encouraged the EPA to consider emerging evidence for a broader range of health outcomes. For example, one commenter urged the EPA “to exercise a high level of vigilance in order to identify and act on additional peer

- reviewed studies that may stren gthen a putative link between PM and diabetes and neurodegenerative diseases” (PSR, 2012, p. 7).

Response: The EPA agrees that additional research could expand our understanding of a broader range of health outcomes (e.g., central nervous system effects) a nd potential additional at

- risk populations (e.g., diabetics). The PA highlighted a number of areas for future health

- related research, model development, and data collection activities that could provide important evidence for informing future PM NAAQS re views (U.S. EPA, 2011a, section 2.5). The EPA will consider all policy

- relevant studies published in the
peer

- review literature, including “new” studies published since the close of the ISA in its next PM NAAQS review.

b. Support for Retaining the Current Standards

Another group of commenters opposed revising the current PM 2.5 standards. These views were most extensively presented in comments from the Utility Air Regulatory Group (UARG), representing a group of electric generating companies and organization s and several national trade associations; the American Petroleum Institute (API) representing more than 500 oil and natural gas companies; the National Association of Manufacturers (NAM), the American Chemistry Council (ACC), the American Fuel & Petroleum Manufacturers (AFPM), the Alliance of Automobile Manufacturers, and other manufacturing associations; the Electric Power Research Institute (EPRI); and the Texas Commission on Environmental Quality (TCEQ). These commenters generally mentioned many of the same studies that were cited by the commenters who supported revising the standards, as well as other studies, but highlighted different aspects of these studies in reaching substantially different conclusions about their strength and the extent to which p rogress has been made in reducing uncertainties in the evidence since the last review. Furthermore, they asserted that the evidence that has become available since the last review does not establish a more certain risk or a risk of effects that are signifi cantly different in character to those that provided a basis for the current standards, nor does the evidence demonstrate that the risk to public health upon attainment of the current standards would be greater than was understood when the EPA established the current standards in 2006.

These commenters generally expressed the view that the current standards provide the requisite degree of public health protection. In supporting their view, these commenters generally argued that the EPA’s conclusions are in consistent with the current state of the science and questioned the underlying scientific evidence including the causal determinations reached in the ISA. More specifically, this group of commenters argued that:

the EPA did not apply its framework for causal determination consistently across studies or health outcomes and, in the process, the EPA relied on a selective group of long

- and short

- term exposure studies to reach conclusions regarding causality toxicological and controlled human exposure studi es do not provide supportive evidence that the health effects observed in epidemiological studies are biologically plausibleDraft

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- 17 uncertainties in the underlying health science are as great or greater than in the PM NAAQS review completed in 2006 there is no evi dence of greater risk since the last review to justify tightening the current annual PM 2.5 standard “new” studies not included in the ISA continue to increase uncertainty about possible health risks associated with exposure to PM 2.5

These comments and oth er similar comments are addressed below.

(1) Comment: Multiple commenters asserted that the EPA did not apply its framework for causal determinations consistently across studies or health outcomes ( API, 2012, Attachment 1, p. 30 ). 9 T hese commenters further contend ed that the EPA relied on a selective group of long

- and short

- term PM 2.5 exposure studies when making causality determinations in the ISA ( ACC, 2012, Attachment A, pp. 1 to 2; API, 2012, pp. 18 to 20; API, 2012, Attachment 1, p. 30; NAM et al., 201 2, pp. 22 to 25; Texas CEQ, 2012, pp 2 to 3; UARG

, Attachment 1, p. 17 to 23) . Th ese allegations include d: “cherry

- picking studies” and ignoring a number of studies that rep orted no association with PM 2.5
. Response: The EPA disagrees with these commenters ’ assertion that the EPA did not consistently apply the causality framework. The EPA’s evaluation of the scientific evidence and its application of the causal framework used in the current PM NAAQS review was the subject of exhaustive and detailed review b y CASAC and the public. Prior to finalizing the ISA, two drafts were released for CASAC and public review to evaluate the scientific integrity of the documents. Evidence related to the substantive issues raised by CASAC and public commenters with regard to the content of the first and second draft ISAs were discussed at length during these public CASAC meetings and considered in developing the final ISA. CASAC supported the development of the EPA’s causality framework and its use in the current PM NAAQS rev iew and concluded :

The five

- level classification of strength of evidence for causal inference has been systematically applied; this approach has provided transparency and a clear statement of the level of confidence with regard to causation, and we recomme nd its continued use in future Integrated Science Assessments (Samet 2009f, p. 1).
The EPA disagrees with these commenters’ views on assessing the health effects evidence and on their conclusions regarding the causal ity determinations reached in the ISA . T he commenters’ specifically focus ed on counting the number of epidemiologic al studies that report ed results with statistical significance without regard to other considerations that are important in a comprehensive evaluation of the evidence. Specifically, the EPA recognizes the distinction between evaluation of the relative scientific quality of individual study results , and the evaluation of the pattern of results within the broader body of scientific evidence and considered both in reaching causality

9 The EPA notes that the same concerns about the causal determinations presented in the ISA were raised in comments to CASAC on the first and second draft ISA s (e.g., UARG, 20 09; API, 2009; ACC, 2012, Appendix B). CASAC, therefore, had the opportunity to consider these comments as it reached consensus conclusions that the EPA had consistently and appropriately applied the causality framework, as well as its consensus agreement on the causality determinations themselves.Draft

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- 18 determinations and in determining the form and level of the PM 2.5 and PM 10 standards

. The more detailed characterizations of individual studies include d an assessment of the quality of the study, which wa s based on specific criteria as described in the ISA (U

. S

. EPA, 2009a, s ection 1.5.3).
Statistical significance is an indicator of the precision of a study’s results, which is influenced by a variety of factors including, but not limited to, the size of the study, exposure and measurement error, and statis tical model specifications. Statistical significance is just one of the means of evaluating the validity of the relationships determined with epidemiologic al st udies

. The EPA can reasonably look to other indicia of reliability such as the consistency and c oherence of a body of studies as well as other confirming data to justify reliance on the results of a body of epidemiologic al studies, even if individual studies may lack statistical significance. American Trucking Ass ociation v. EPA , 283 F. 3d 355, 371 ( D.C. Cir. 2002)

. As a result, in developing an integrated assessment of the health effects evidence for PM, the EPA has emphasized the importance of examining the pattern of results across various studies and their coherence and consis t ency , and has not focus ed solely on statistical significance as a criterion of study reliability

. It has been clearly articulated throughout the epidemiologic al and causal inference literature that it is important not to focus on results of statistical tests to the e xclusi on of other information. For example, Rothman (1998) stated: “Many data analysts appear to remain oblivious to the qualitative nature of significance testing [and that]... statistical significance is itself only a dichotomous indicator. As it has only two va lues, significant or not significant .” As a result

, Rothman recommended that P

- values be omitted as long as point and interval estimates are available.
The concepts underlying the EPA’s approach to evaluating statistical associations reported for the heal th effects on PM 2.5 have been discussed in numerous publications, including a report by the U.S. Surgeon General on the health consequences of smoking (Centers for Disease Control and Prevention, 2004). This report cautions against over

reliance on statist ical significance in evaluating the overall evidence for an exposure

response relationship:

Hill made a point of commenting on the value, or lack thereof, of statistical testing in the determination of cause: “ No formal tests of significance can answer those [causal] questions. Such tests can, and should, remind us of the effects the play of chance can create, and they will instruct us in the likely magnitude of those effects. Beyond that, they contribute nothin g to the ‘proof’ of our hypothesis ” (Hill 1965, p. 299).
Hill’s warning was in some ways prescient, as the reliance on statistically significant testing as a substitute for judgment in a causal inference remains today (Savitz et al., 1994; Holman et al., 2001; Poole 2001). To understand the basis for this warning, it is critical to recognize the difference between inductive inferences about the truth of underlying hypotheses, and deductive statistical calculations that are relevant to those inferences, but that are not inductive statements themselves. The latter include p values, confidence intervals, and hypothesis tests (Greenland 1998; Goodman 1999). TheDraft

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- 19 dominant approach to statistical inference today, which em ploys those statistical measures, obscures this important distinction between deductive and inductive inferences (Royall 1997), and has produced the mistaken view that inferences flow directly and inevitably from data. There is no mathematic al formula that can transform data into a probabilistic statement about the truth of an association without introducing some formal quantification of external knowledge, such as in Bayesian approaches to inference (Goodman 1993; Howson and Urbach

, 1993). Significance tes ting and the complementary estimation of confidence intervals remain useful for characterizing the role of chance in producing the association in hand (CDC, 2003, pp. 23 to 24).

Accordingly, the statistical significance of findings from an individual stud y has played an important role in the EPA’s evaluation of the study’s results and overall the EPA has placed greater emphasis on studies reporting statistically significant results in making determinations as to the elements of the standard

. In particular

, as noted in section III.E.4.b.i of the preamble to the final rule, the EPA identified l ong

- and short

- term exposure studies considered “key” multi

- city studies for consideration for informing the decisions on the appropriate standard levels and include d those studies observing effects for which the evidence supported a causal or likely causal association. F igure 4 in the preamble to the final rule (also Figure 4 in the proposal, 77 FR 38933) represents the subset of multi

- city studies included in Figures 1 through 3 of the preamble to the final rule (also Figures 1 through 3 in the proposal, 77 FR 38929 to 38931) that provided evidence of positive and generally statistically significant effects associated in whole

, or in part

, with more recent air quality data, generally representing health effects associated with lower PM 2.5 concentrations than had previously been considered in the last review. The EPA notes that many of these studies evaluated multiple health endpoints, a nd not all of the effects evaluate d provided evidence of positive and statistically significant effects. For purposes of informing the Administrator’s decision on the appropriate standard levels, the Agency considers the full body of scientific evidence and focuses on those aspects of the key studies that provided evidence of positive and generally statistically significant effects. The EPA notes that many of these studies evaluated multiple health endpoints, a nd not all of the effects evaluated provided evidence of positive and statistically significant effects. For purposes of informing the Administrator’s decision on the appropriate standard levels, the Agency considers the full body of scientific evidence

an d focuses on those aspects of the key studies that provided evidence of positive and generally statistically significant effects.

However, in the broader evaluation of the evidence from many epidemiologic al studies, and subsequently during the process of forming causality determinations, the EPA has emphasized the pattern of results across epidemiologic al studies for drawing conclusions on the relationship between PM 2.5 and health outcomes, and whether the effects observed are coherent across the scientifi c disciplines. Thus, in making causality determinations, the EPA did not limit its focus or consideration to just studies that reported positive associations or where the results were statistically significant.

As discussed in section III.D.2 of the pream ble to the final rule, the EPA notes that the final causality determinations presented in the ISA reflected CASAC’s recommendations on the second draft ISA (Samet, 2009f, pp. 2 to 3). Specifically, CASAC supported theDraft

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- 20 EPA’s changes (in the second versus fi rst draft ISA) from “likely causal” to “causal” for long

- term exposure to PM 2.5 and cardiovascular effects and for cancer and PM 2.5 (from “inadequate” to “suggestive”)

. Id . Furthermore, CASAC recommended “upgrading” the causal classification for PM 2.5 and total mortality to “causal” for both the short

- and long

term timeframes. Id. W i th regard to mortality, the “EPA carefully reevaluated the body of evidence, including the collective evidence for biological plausibility for mortality effects, and determined that a causal relationship exists for short

- and long

- term exposure to PM 2.5 and mortality, consistent with the CASAC comments” (Jackson, 2012). With respect to ultrafine particles, i n developing the second draft ISA, the EPA reexamined the controlled hum an exposure and toxicological studies of fresh diesel and gasoline exhaust This information, in addition to other considerations, supported a change in the causal determinations for ultrafine particles. Specifically, in reevaluating the causal determinatio ns for short

- term ultrafine particle exposures and cardiovascular and respiratory effects, the EPA changed the classification from “inadequate” to “suggestive ” for both categories of health outcomes (Vandenberg, 2009, p. 3). CASAC agreed with the EPA’s rationale for revising these causal determinations (Samet, 2009f, p. 10).

(2) Comment: Some commenters asserted that the EPA inappropriately used the Hill criteria by failing to consider the limitations of studies with weak associations, thereby overstating the consistency of the observed associations (API, 2012, Attachment 1, pp 30 to 35). Specifically, these commenters argued that risk estimates greater than 3 to 4

r eflect strong associations supportive of a causal link, while smaller risk estimates (i.e., 1.5 to 3) are considered to be weak and require other lines of evidence to demonstrate causality. Additionally, these commenters believed that the EPA downplayed nu ll or inconsistent findings in numerous long

- term mortality studies with reported PM 2.5 concentrations above and below the level of the current annual standard.

Response: As discussed in s ection 1.5.3 of the ISA, the EPA thoroughly considered the uncertain ties and limitations of all studies during its evaluation of the scientific literature (U.S. EPA, 2009a, pp. 1 to 14). This collective body of evidence, including known uncertainties and limitations of the studies evaluated

, were considered by the EPA (and reviewed by the CASAC) during the process of forming causality determinations as discussed in Chapters 6 and 7 of the ISA. For example, the EPA concluded that “a causal relationship exists between short

- term PM 2.5 exposure and cardiovascular effects”; how ever, in reaching this conclusion, the Agency recognized and considered limitations of the current evidence that still requires further examination ( U.S. EPA, 2009a, s ection 6.2.12.1) . Therefore, t

he commenters have mischaracterized the EPA’s process. The limitations of the studies , and their uncertainties, were noted and considered by the EPA.

The EPA also disagrees with the commenters ’ assertion that the magnitude of the association must be large to support a determination of causality. As discussed in the ISA , the strength of the observed association is an important aspect to aid in judging causality and “while large effects support causality, modest effects therefore do not preclude it” ( U.S. EPA, 2009a, Table 1

- 2, s ection 1.5.4)

. 10 T he weight of evidence

10 For example, environmental tobacco smoke (second

- hand smoke) causes lung cancer in humans, even though the magnitude of the association is small (U.S. EPA, 1992).Draft

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- 21 approach used by the EPA encompasses a multitude of factors of which the magnitude of the association is only one component ( U.S. EPA, 2009a, Table 1

- 3) . An evaluation of the association across multiple investigators and locations suppo rts the “reproducibility of findings [which] constitutes one of the strongest arguments for causality” ( U.S. EPA, 2009a, Table 1

- 2) . Even though the risk estimates for air pollution studies may be modest

, the associations are consistent across hundreds of studies as demonstrated throughout the ISA (U.S. EPA, 2009a, Figure s 2

- 1, 6

- 27, and 7

- 7) . Furthermore, the causality determinations rely on different lines of evidence, by integrating evidence across disciplines, including animal toxicological studies and controlled human exposure studies.

The EPA recognizes that the population potentially affected by PM 2.5 is considerable, including large subgroups of the U.S. population that have been identified as at

- risk populations (e.g., children, older adults, perso ns with underlying cardiovascular or respiratory disease). While individual effect estimates from epidemiological studies may be modest in size, the public health impact of the mortality and morbidity associations can be quite large given that exposure to airborne PM 2.5 is ubiquitous. Indeed, with the large population exposed, exposure to a pollutant causally associated at a population level with mortality and serious illness has significant public health consequences, virtually regardless of the relative r isk. Taken together, this information indicates that exposure to ambient PM 2.5 concentrations has substantial public health impacts.

Additionally, t

he EPA disagrees with the commenter that long

- term PM 2.5 exposure studies with null or inconsistent findings were not accurately presented in the ISA. For example, as discussed throughout s ection 7.6 and depicted in Figures 7

- 6 and 7

- 7, the EPA presented the collective evidence from all studies that examined th e association between long

- term PM 2.5 exposure and mortality. Overall, across these studies there was evidence of consistent positive associations in different cohorts. That evidence in combination with the biological plausibility provided by experimental studies evaluated in s ections 7.1 and 7.2 of the ISA supported that a causal relationship exists between long

- term PM 2.5 exposure and mortality, which is consistent with CASAC advice (Samet, 2009f, pp. 2 to 3).

(3) Comment: Some commenters argued that in some cases, the EPA used the same study and the same underlying database to conclude that there wa s a causal association between mortality and multiple criteria pollutants. These commenters contend ed , “[i]n doing so, the EPA attributes the cause of the mortalit y effects observed to whichever criteria pollutant it is reviewing at the time” (API, 2012, pp. 14 to 16).

Response: The EPA strongly disagrees that the Agency “attributes the cause of mortality effects observed to whichever criteria pollutant it is review ing at the time.” The EPA consistently recognizes that other pollutants are also associated with health outcomes, as is reflected in the fact that the EPA has established NAAQS to limit emissions of the particulate criteria pollutants as well as other gase ous criteria pollutants. Epidemiologic al studies often examine the association between short

- and long

- term exposures to multiple air pollutants and mortality within a common dataset in an attempt to identify the air pollutant(s) of the complex mixture mos t strongly associated with mortality. It isDraft

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- 22 important to recognize that more than one pollutant can have effects on the same system; in fact, it is not reasonable to assume that effects can be attributed to only one pollutant and to exclude effects of all other pollutant s.
The EPA carefully considers evidence from experimental studies providing information

on mode (s) of action in evaluating the overall weight of the scientific evidence to develop causal judgments. In evaluating these studies

, the EPA employs specific study selection criteria to identify those studies most relevant to the review of the NAAQS. In its assessment of the health evidence regarding PM 2.5 , the EPA has carefully evaluated the potential for confounding, effect measure m odification and the role of PM as a component of a complex mixture of air pollutants (U

. S

. EPA, 2009 a , p p . 1 to 9). The EPA use d a rigorous weight of evidence approach to inform its causality determinations that evaluate d consistency across studies within a discipline, evidence for coherence across disciplines, and biological plausibility. Additionally, during this process, the EPA

assesse d the limitations of each study in the context of the collective body of evidence. It

was the collective evidence, not o ne individual study that ultimately determine d whether a causal relationship exists between PM 2.5 and specific health outcome s

.
In the ISA , the combination of epidemiologic al, toxicological, and controlled human exposure studies formed the basis for the A gency concluding that a causal relationship exists between short

- or long

- term PM 2.5 exposure s and total mortality (U

. S

. EPA, 2009 a , s ection s 2.3.1.1 and 2.3.1.2). This was the first time that the Agency concluded that a causal relationship exists between short

- or long

- term exposure to a criteria pollutant and mortality.

Additionally, while the EPA has evaluated the studies used to inform the causality determination for PM 2.5 in ISAs for other criteria air pollutants, the Agency has done so in the context of examining the collective body of evidence for each of the respective criteria air pollutants. Therefore , the EPA disagrees with the commenter that the underlying database used in the PM ISA was also used in concluding a causal relationship exists between mortality and other criteria pollutants. As discussed in the recently

- completed ISAs for nitrogen oxides, sulfur oxides and carbon monoxide, the EPA did not conclude that a causal relationship exists with mortality and these criteria pollutants due to either short

- or long

- term exposures (U.S. EPA, 2008e, 2008f, 2010k).

(4) Comment: A number of commenters questioned the underlying scientific basis used in the ISA to conclude th at a causal relationship exists between long

- term PM 2.5 exposure and mortality. Specifically, commenters asserted that evidence from two studies, Janes et al. (2007) and Greven et al. (2011), indicated that the association between long

- term PM 2.5 exposures and mortality is subject to unmeasured confounding. The commenters further asserted that these studies therefore indicated that unmeasured confounding is inherent in all long

- term exposure studies of mortality (UARG, 2012, pp. 10 to 11, Attachment A, pp. 17 to 23; API, 2012, pp. 13 to 14, Attachment 1, pp. 11 to 14, Attachment 7, pp 3 to 10; ACC, 2012, p. 18 to 21; AFPM, 2012, p. 8; TCEQ, 2012, p. 4; EPRI, 2012, p. 3). In addition, all of the authors of the Janes et al. (2007) and Greven et al. (2011) publ ications, (i.e., Francesca Dominici, Scott Zeger, Holly Janes, and Sonja Greven) submitted a joint comment to the public docket in order to clarify specific pointsDraft

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- 23 regarding these two studies (Dominici et al. 2012).

Response: The EPA evaluated the study by Janes et al. (2007) in the ISA ( U.S. EPA

, 2009 a , p. 7

- 88) and evaluated the study by Greven et al. (2011) (an extension of the study by Janes et al. (2007) incorporating three additional years of data) in the Provisional Science Assessment ( U.S. EPA, 2012 b ). In the EPA’s evaluation of the relationship between long

- term exposure to PM 2.5 and mortality, the Janes et al. (2007) study was included in the body of evidence that supported the determination that a causal relationship existed (U.S. EPA, 2009a, sect ion 7.6.5.1)

. For the reasons discussed below,
t he EPA does not agree with the commenters’ views that these two studies call into question the scientific merit or the consistency of the results of long

- term exposure studies of mortality that contribute to this body of evidence

. Both studies used nationwide Medicare mortality data to examine the association between monthly averages of PM 2.5 over the preceding 12 months and monthly mortality rates in 113 U.S. counties and examined whether community

- specific trends in monthly PM 2.5 concentrations and mortality declined at the same rate as the national rate. The investigators examined this by decompos ing the association between PM 2.5 and mortality into two components : (1) “ national ” trends , defined as the assoc iation between the national average trend in monthly PM 2.5 concentrations averaged over the previous 12 months and the national average trend in monthly mortality rates and (2) “ local ” trends

, defined as county

- specific deviations in monthly PM 2.5 concentr ations and monthly mortality rates from national trends.

The EPA does not question the results of the national trends analyses conducted by Janes et al. (2007) and Greven et al. (2011). 11 Both Janes et al. (2007) and Greven et al. (2011) observed positive and statistically significant associations between long

- term exposure to PM 2.5 and mortality in their national analyses. However, Janes et al. (2007) and Greven et al. (2011) eliminate d all of the spatial variation in air pollution and mortality in thei r data set when estimating the national effect , focusing instead on both chronic (yearly) and sub

- chronic (monthly) temporal differences in the data (Dominici et al. 2012). Janes et al. (2007) (Table 1) highlighted that over 90 percent of the variance in the data set used for the analyses conducted by both Janes et al. (2007) and Greven et al. (2011) wa s attributable to spatial variability, which the authors chose to discard. T he focus of the analyses by Janes et al. (2007) and Greven et al. (2011) was on two components: (1) a temporal or time component, i.e., the “national” trends analysis, which examined the association between the national average trend in monthly PM 2.5 concentrations averaged over the previous 12 months and the national average trend in mo nthly mortality rates and (2) a space

- by

- time component, i.e., the “local” trends analysis , which examined county

- specific deviations in monthly PM 2.5 concentrations and monthly mortality rates from national trends. These two components combined comprised less than 10 percent of the variance in the data set

. The authors included a focus on the space

- by

- time component, which represented approximately 5 percent of the variance in the data set, in

11 In its evaluation of Janes et al. (2007) in the ISA, the EPA did not identify limitations in the statistical methods used per se (U.S. EPA, 2009a, p. 7

- 88) and included the results of the national

- scale analyses in that study in the body of evidence that s upported the determination that there is a causal relationship between long

- term PM 2.5 exposure and mortality.Draft

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- 24 an attempt to identify, absent confounding, if PM 2.5 wa s associated with mortality at this unique exposure window. Thus, the national effects reported in these studies are not directly comparable to other cohort studies investigating the relationship between long

term exposure to PM 2.5 and mortality, which ma ke use of spatial variability in air pollution and mortality data. 12 Indeed, the study authors noted expressly that “when one considers that this wealth of [spatial] information is not accounted for in that study, it is not as surprising that we see vastly d ifferent estimates of the PM 2.5 /mortality relationship than in other studies that do exploit that variability” (Dominici et al. 2012 , p. 2 )

. For the local analyses, both Janes et al. (2007) and Greven et al. (2011) observe d associations between exposure t o PM 2.5 and mortality that are near the null value, often negative, and not statistically significant. The fact that the authors d id not observe an association in the local analyses is not surprising. As stated in Janes et al. (2007), they

we re estimating “associations between temporal changes in exposure and outcome s within counties relative to the national trend. ” However, a limitation of the analysis conducted by Janes et al. (2007) [and subsequently by Greven et al. (2011)], and recognized in a commenta ry by Pope and Burnett (2007), is the use of monthly average PM 2.5 concentrations to examine associations at the local scale. This is a limitation because such an exposure assignment approach does not provide enough exposure contrast to observe temporal changes in mortality. The ISA (U.S. EPA, 2009a, p. 7

- 88) recognized comments made by Pope and Burnett (2007) that pointed out that the conclusions of Janes et al (2 007) “are overstated. . . their analysis tells us little or nothing about unmeasured confounding in those and related studies because the methodology of Janes et al largely excludes the sources of variability that are exploited in those other studies. By u sing monthly mortality counts and lagged 12

- month average pollution concentrations, the authors eliminate the opportunity to exploit short

- term or day

- to

- day variability.”

Furthermore, the EPA disagrees with commenters that Janes et al. (2007) and Greven et al. (2011) provide evidence that other studies of long

- term exposure to PM 2.5 and mortality are affected by unmeasured confounding. As noted above, the design of the studies conducted by Janes et al (2007) and Greven et al (2011) are fundamentally diffe rent than those used in other studies of long

- term exposure to PM 2.5 and mortality, including the ACS cohort and the Harvard Six Cities study. Studies, such as the ACS and Harvard Six Cities studies, used the spatial variation between cities to measure the effect of long

- term (annual) exposures to PM 2.5 on mortality risk, and did not conduct any analyses relying on the temporal variation in PM 2.5 . The opposite is true of the Janes et al. (2007) and Greven et al. (2011) studies which first removed the spatia l variability in PM 2.5 and then examined the temporal variation at both the national and local scale to measure the effects of temporal differences in PM 2.5 on mortality risk. Janes et al. (2007)

12 Though not directly comparable, the effect estimates for mortality reported by Janes et al. (2007) and Greven et al. (2011) were coincidentally similar in magnitude to those previously reported in other long

- term cohort studies. It is important to note that previous cohort studies focused on identifying spatial differences in PM 2.5 concentrations between cities, while Janes et al. (2007) and Grev en et al. (2011) primarily focused on temporal differences in PM 2.5 concentrations. In fact, Greven et al. (2011) stated, “We do not focus here on a third type [of statistical approach] used in cohort studies, measuring the association between average PM 2. 5 levels and average age

- adjusted mortality rates across cities (purely spatial or cross

- sectional association).”Draft

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- 25 and Greven et al. (2011) focus on changes in PM 2.5 concentra tions over time and therefore control for confounders would be based on including variables that vary over time rather than over space. As a result, any evidence of potential confounding of the PM 2.5 - mortality risk relationship derived from Janes et al. (2 007) and Greven et al. (2011) cannot be extrapolated to draw conclusions related to potential spatial confounding in studies based on the spatial variation in PM 2.5 concentrations.

As detailed in the ISA (U.S. EPA, 2009a, section 7.6), and recognized by th e authors of Janes et al. (2007) and Greven et al. (2011), the cohort studies that informed the causality determination for long

- term PM 2.5 exposure and mortality “have developed approaches to adjust for measured and unmeasured confounders” (Dominici et al . 2012). These approaches were specifically designed to adjust for spatial confounding. The hypothesis that the authors of Janes et al. (2007) and Greven et al. (2011) chose to examine was that differences in the local and national effects indicate unmeasu red temporal confounding in either the local or national effect estimate. This hypothesis was specific to these two studies that examined temporal variability in exposure to air pollution and did not include known potential confounders at either the nation al or local scale as covariates in the statistical model. The authors acknowledged that the interpretation of either the national or local estimates needs to occur with an appreciation of the potential confounding effects of national and local scale covari ates that were omitted from the model (Dominici et al., 2012).

It is important to recognize that because Janes et al. (2007) and Greven et al. (2011) focused on variations in PM 2.5 over time and not space, the results from these two studies do not provide any indication that other studies of long

- term exposure to PM 2.5 and mortality exhibit spatial confounding, or that PM 2.5 does not cause mortality. 13 The authors of Janes et al. (2007) and Greven et al. (2011) recognized “it is entirely possible that these papers are looking for an association at a timescale for which no association truly exists” (Dominici et al. 2012, p.3).

Specific comments by UARG (UARG, 2012, Attachment A, pp. 19 to 23) state d that there are flaws in the criticisms offered by Pope and Burnett (2007) on the paper by Janes et al. (2007). First, the commenters d id not agree with Pope and Burnett (2007) that data used by Janes et al. ( 2007) wa s too aggregate (i.e., using deaths and PM 2.5 concentrations averaged over months rather than days does not provide adequate temporal variability) to detect short

- term variation. The commenters state d that most of the long

- term cohort studies of mo rtality rely on even more aggregate timescales that are multi

- year averages.
The EPA agrees that many of the long

- term cohort studies rely on timescales that are aggregated beyond monthly averages (as was done by Janes et al.

, 2007) in multi

- city studies where spatial variability in exposure is being examined. However , Janes et al. (2007) discounted all of the spatial variability in their analyses. Thus , the EPA agrees with the criticism by Pope and Burnett (2007) that when looking within a single city or geographic area, as Janes et al. (2007) d id in their “local” analysis, there wa s not enough

13 Further, the EPA notes that Janes et al. (2007) and Greven et al. (2011) provide no information relevant to examining confounding in studies of short

- term exposure to PM 2.5 .Draft

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- 26 variability in exposure to aggregate exposure at the monthly level instead of the daily level.

Second, the commenters t ook issue with the critique by Pope and Burn ett (2007) that the use of county

- level fixed effects eliminate d the source of long

- term average spatial variability. As stated by the commenters, “To estimate the new model developed by Janes et al. (2007a), they must use other sources of variation: they must use temporal and spatial

- temporal variation” (UARG, 2012, Attachment A, p. 21). While this may be true, as mentioned above, the Medicare mortality dataset used by the authors does not have adequate temporal resolution to look at spatial

- temporal varia tion in the “local” analyses conducted by Janes et al (2007) and reanalyzed by Greven et al. (2011). As noted by Janes et al. (2007) (See Table 1), and discussed by Dominci et al. (2012) o nly 5 percent of the variance in the data set used in these analyses is attributable to the space by time component

. Third, the commenters identif ied the critique by Pope and Burnett (2007) that the analysis by Janes et al. (2007) wa s limited by the scale of the study (i.e., three years), which d id not allow for considerat

ion of longer

- term variability in mortality and air pollution data. The commenters state d that “ [a] ll researchers are limited by the data available to them, and Janes et al. (2007a) used only three years in their analysis because that is all the data they had available” (UARG, 2012, Attachment A, p. 21). While researchers may be limited by the data available to them, scientists must decide whether those limitations enable them to answer the scientific question that they are posing. Because the Medicare
mort ality was aggregated at the monthly level, it could take decades and decades of data to provide the appropriate exposure contrast to conduct these analyses.

There were also specific comments suggesting that the study by Greven et al. (2011) substantiated the results of Janes et al. (2007). Specifically, the commenters state d that Greven et al. (2011) use d “station

- level” data instead of county level data, add ed three additional years of data to the study period, incorporate d controls for socio

- economic

con founders, and investigate d trends at the regional level (UARG, 2012, Attachment A, p. 22). While these may be improvements upon the original study by Janes et al. (2007), the results in Greven et al. (2011) are not comparable to, nor would they invalidate, the results of cohort studies investigating the relationship between long

- term exposure to PM 2.5 and mortality (Dominici et al. 2012)

. One commenter suggested that the epidemiological results from studies of long

- term exposure to PM 2.5 and mortality char acterized in the ISA are inconsistent and discordant, indicating significant confounding (API, 2012, Attachment 7, pp. 2 to 10). This commenter pointed to the study by Greven et al. (2011) as an example of a study that avoids such potential confounding. As demonstrated in the ISA , there is a large body of evidence supporting the association between long

- term exposure to PM 2.5 and mortality that generally reports consistent , positive relative risks (U

. S

. EPA 2009 a, Figures 7.6 and 7.7).

This commenter also suggested that the data used by Greven et al. (2011) were “superior or comparable to data used in other studies of PM 2.5 and mortality” ((API, 2012,Draft

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- 27 Attachment 7, p. 5). For example, the commenter claimed that Greven et al. (2011) used data from more locat ions than other researchers. Specifically, this commenter pointed out that Greven et al. (2011) included data from 814 ZIP code areas while Pope et al. (2009) focused on 211 county units. The EPA acknowledges that Greven et al. (2011) used a more spatially resolved data set (i.e., ZIP codes instead of counties), but points out that the study by Greven et al. (2011) includes data from just 113 counties, compared to the 211 counties included in Pope et al. (2009). Furthermore, while this enhanced spatial

reso lution may help to reduce exposure measurement error, the focus on the study by Greven et al. (2011) was on temporal variability in exposure, and in this case does not provide additional exposure contrast. Additionally, the commenter also cited the use of monthly average mortality data as a strength of the study by Geven et al. (2011), when, in fact, for a study focusing on temporal variability in exposure, daily average mortality would be preferable. The EPA considers the use of monthly

- average mortality d ata as a limitation. Finally, the commenter acknowledged that the study by Greven et al. (2011) did not include any individual

- level covariates, but had to rely on county

- and month

level information for potential confounders, including smoking. For these reasons, the EPA disagrees with the commenters’ views that the study by Greven et al. (2011) is superior to other cohort studies of long

- term exposure to PM 2.5 and mortality.

In summary, t

he EPA does not question the quantitative results presented by Jane s et al. (2007) and Greven et al. (2011) ; however, the EPA disagrees that the results of these studies are comparable to the results of other cohort studies of long

- term exposure to PM 2.5 and mortality, or that the results presented in these two studies in validate either the results themselves, or the consistency of the results observed across other cohort studies of long

- term exposure to PM 2.5 and mortality

. Janes et al. (2007) and Greven et al. (2011) eliminated the spatial variability in the air pollutio n and mortality data. Thus, the results of these studies cannot be directly compared to time

- series studies of short

- term exposure to PM 2.5 and mortality (which rely on day

- to

- day changes in PM 2.5 concentrations and mortality) because the authors only use temporal variability measured on a monthly scale. Nor can the results of these studies be directly compared to cohort studies of long

- term exposure to PM 2.5 and mortality (which rely on the spatial variability of air pollution concentrations and mortality ) because their analyses include a fixed effect for county in the regression model which eliminates spatial variability when estimating the national effect. Additionally, Janes et al. (2007) and Greven et al. (2011) use a different time scale in their anal yses compared to the timescales used in other cohort studies. Janes et al. (2007) and Greven et al. (2011) examined whether an association exists at a sub

- chronic (i.e., monthly) time scale. Thus, the results of the study by Janes et al. (2007) are include d in the ISA and contributed to the body of evidence for an association between long

- term PM 2.5 exposures and mortality, but are not directly comparable to other cohort studies that rely on a different timescale and focus on spatial variability.

As demon strated in the ISA , there is a large body of evidence supporting the association between long

- term exposure to PM 2.5 and mortality that generally reports consistent relative risks between 1.0 and 1.5 (U

. S

. EPA 2009 a, Figures 7.6 and 7.7). Based on this lar ge body of evidence, the EPA concluded that a causal relationship exists between long

term exposure to PM 2.5 and mortality (U.S. EPA, section 7.6.5.1)

. The results presented by Janes et al. (2007) and Greven et al. (2011) are not comparable to the results of theseDraft

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- 28 studies of long

- term exposure to PM 2.5 and mortality. Therefore, the EPA concludes that these studies do not invalidate the large body of epidemiological evidence that supports the EPA’s determination that a causa l relationship exists between long

- term PM 2.5 exposure and mortality. 14

(5) Comment: Some commenters questioned the use of epidemiologic al studies in assessing the adequacy of the current PM NAAQS because “of the untestable assumptions on which much of air pol lution epidemiology, along with EPA’s proposed NAAQS revisions, are built” (ACC, 2012, p p. 20 to 21). These
commenters ma de this claim based on a recent publication by Moore et al. (2012), which they asserted demonstrates that “most, if not all, results fr om epidemiologic studies of air pollution

– requires reliance on untestable and possible invalid assumptions, and that the alternative analyses designed to meet such assumptions can produce different (e.g., null instead of positive) results” (ACC, 2012, p. 20).

Response : The EPA disagrees with the commenters ’ views that the results of the recently published Moore et al. (2012) study bring into question the epidemiologic al evidence used to inform whether or not the PM NAAQS should be revised. First, the Moore et al. (2012) study focuse d on evaluating effects associated with ozone ( O 3 ) exposure s , which brings into question its relevance in the context of considering the avai lable scientific evidence for the PM NAAQS review. This study w as not included in the ISA or consider ed in the Provisional Science Assessment as th is study did not include consideration of measure d ambient PM 2.5 concentrations . Second, Moore et al. (2012) examine d heat as a potential confounder of the O 3 - asthma hospital admission relationship. For PM, temperature is also a known potential confounder, but a number of studies have demonstrated that alternative approaches to controlling for the potential confo unding effects of weather do not influence PM risk estimates (e.g., Welty and Zeger (2005), as discussed on p. 6

- 163 and 6

- 164, U.S. EPA , 2009 a ). Therefore, the study by Moore et al. (2012) does not inform the relationship between PM 2.5 exposure and health effects.

(6) Comment: With regard to toxicological and controlled human exposure studies, some commenters argued that the available evidence does not provide coherence or biological plausibility for health effects observed in epidemiologic al studies (API, 2012, pp. 21 to 22, Attachment 1, pp. 25 to 29; AAM, 2012, pp. 15 to 16; Texas CEQ, 2012, p. 3). With regard to the issue of mechanisms, these commenters noted that although the EPA recognizes that new evidence is now available on potentia l mechanisms and plausible biological pathways, the evidence provided by toxicological and controlled human exposure studies still does not resolve all questions about how PM 2.5 at ambient concentrations could produce the mortality and morbidity effects ob served in epidemiological studies. More specifically, for example, some of these commenters stated that:

A review of the Integrated Science Assessment, however, suggests that the experimental evidence is inconsistent and not coherent with findings in epide miology studies. Specifically, the findings of mild and reversible effects in most experimental studies conducted at elevated exposures are not consistent with the more serious associations described in epidemiology studies (e.g., hospital

14 We note that the EPA’s conclusion with regard to interpretation of the results from Janes (2007) and Greven (2012) is supported by the study authors’ conclusion that “[ o]ur results do not invalidate previous epidemiologi c studies ” (Dominici (2012) p. 1 (emphasis original)).Draft

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- 29 admissions and m ortality). Also, both animal studies and controlled human exposure studies have identified no effect levels for acute and chronic exposure to PM and PM constituents at concentrations considerably above ambient levels. The EPA should consider the experiment al findings in light of these higher exposure levels and what the relevance may be for ambient exposures (API, 2012, Attachment 1, p. 25).

Response: The EPA notes that in the review completed in 1997, the Agency considered the lack of demonstrated biologic al mechanisms for the varying effects observed in epidemiological studies to be an important caution in its integrated assessment of the health evidence upon which the standards were based (71 FR 61157, October 17, 2006). In the review completed in 2006, t he EPA recognized the findings from additional research that indicated that different health responses were linked with different particle characteristics and that both individual components and complex particle mixtures appeared to be responsible for many biologic responses relevant to fine particle
exposures. Id . Since that review, there has been a great deal of research directed toward advancing our understanding of biologic al mechanisms. While this research has not resolved all questions, and further re search is warranted (U.S. EPA, 2011a, section 2.5), it has provided important insights as discussed in section III.B.1 of the proposal (77 FR at 38906 to 38909) and discussed more fully in the ISA (U.S. EPA, 2009a, chapter 5).

As noted in the proposal, to xicological studies provide evidence to support the biologic al plausibility of cardiovascular and respiratory effects associated with long

- and short

- term PM 2.5 exposures observed in epidemiological studies (77 FR 38906) and provide supportive mechanistic evidence that the cardiovascular morbidity effects observed in long

- term exposure epidemiological studies are coherent with studies of cardiovascular

related mortality (77 FR 38907). The ISA concluded that the new evidence available in this review “greatly expands” upon the evidence available in the last review “particularly in providing greater understanding of the underlying mechanisms for PM 2.5 induced cardiovascular and respiratory effects for both short

- and long

- term exposures” (U.S. EPA, 2009a, p. 2

- 17). The mechanistic evidence now available, taken together with newly available epidemiological evidence, increases the Agency’s confidence tha t a causal relationship exists between long

- and short

- term exposure to PM 2.5 and cardiovascular effects and mortality. In addition, CASAC supported the ISA approach and characterization of potential mechanisms or modes of action (Samet, 2009e, pp. 7 to 8; Samet, 2009f, p. 11), as well as the findings of a causal relationship at the population level between exposure to PM 2.5 and mortality and cardiovascular effects (Samet, 2009f, pp. 2 to 3).

Additionally, the EPA disagrees with commenters that the mild and reversible effects observed in controlled human exposure studies are inconsistent with the more serious effects observed in epidemiologic al studies. Ethical considerations regarding the types of studies that can be performed with human subjects limit t he effects that can be evaluated to those that are transient, reversible, and of limited short

- term consequence. The relatively small number of subjects recruited for controlled exposure studies should also be expected to have less variability in health st atus and risk factors than occurring in theDraft

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- 30 general population. 15 Consequently, the severity of health effects observed in controlled human exposure studies evaluating the effects of PM 2.5 should be expected to be less than observed in epidemiologic al stud ies. Nonetheless, that effects are observed in healthy individuals participating in controlled exposure studies serves as an indicat ion that PM 2.5 is initiating adverse health responses and that more severe responses may reasonably be expected in a more di verse population

, specifically , in at

- risk populations. Put another way, there are serious public health risks from exposure of large populations of people including those with pre

- existing illnesses, to ambient concentrations of PM 2.5 , b ut these
are not t he same as the very small risks that individuals who do not have such conditions face when participating in a controlled human exposure study.

It should also be noted that there is a small body of toxicological evidence demonstrating mortality in rodents e xposed to PM 2.5 (e.g., Killingsworth et al. 1997; Godleski et al. 1996). Overall

, it is not surprising that lethality is not induced in more toxicological research, as these types of studies do not readily lend themselves to this endpoint. Epidemiologic al studies have observed associations between PM 2.5 and mortality in communities with populations in the range of many thousands to millions of people. Clearly, it is not feasible to expose hundreds (if not thousands) of animals to PM 2.5 (potentially over ma ny years) in a laboratory setting to induce enough lethalities to distinguish between natural deaths and those attributable to PM 2.5 . Furthermore, the heterogeneous human populations sampled in epidemiological studies are comprised of individuals with diff

erent physical, genetic, health, and socioeconomic backgrounds which may impact the outcome. However, in toxicological studies, the rodent groups most frequently evaluated are typically inbred, such that inter

- individual variability is minimized. Thus, if the rodent strain used is quite robust, PM 2.5 - induced effects may not be observed at low exposure concentrations.

(7) Comment: A number of commenters disagreed with the EPA’s evaluation of specific long

- term PM 2.5 exposure and mortality studies ( e.g., ACC , 201 2, p p. 6 to 14; AAM

, 2012, p p. 6 to 18) and contend ed that the EPA’s evaluation of the scientific evidence fails to accurately reflect the latest scientific knowledge. Common points raised by these
commenters we re that the results from long

- term exposure s tudies we re limited because they: (a) f ou nd biologically implausible risk estimates; (b) estimate d PM 2.5 concentrations for years in which data w ere not available; and (c) d id not account for exposure misclassification.

15 For example, the EPA excludes from its controlled human exposure studies involving exposure to PM 2.5 any individual with a significant risk factor for experiencing adverse effects from such exposure. Thus, the EPA excludes a priori the following categories of persons: those with a history of angina, cardiac arrhythmias, and ischemic myocardial infarction or coronary bypass surgery; those with a cardiac pacemaker; those with uncontrolled hypertension (greater than 150 systolic and 90 diastolic); those with neurogenetive diseases; those with a history of bleeding diathesis; those taking beta

- blockers; those using oral anticoagulants; those who are pregnant, attempting to become pregnant, or breastfeeding; those who have experienced a respiratory infection within four weeks of exposure; those experiencing eye or abdominal surgery within six weeks of exposure; those with active allergies; those with a history of chronic illnesses such as diabetes, cancer, rheumatologic diseases, immunodeficiency state, known cardiovascular disease, or chronic respiratory diseases; smokers. The EPA “Application for Independent Re view Board Approval of Human Subjects Research: Cardiopulmonary Effects of healthy Older GSTM1 Null and Sufficient individuals to Concentrated Ambient Air Particles (CAPTAIN)

, ” Nov. 9, 2011, p. 9

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- 31 Response: The EPA carefully evaluated “the body of evidence, including the collective evidence for biological plausibility for mortality effects, and determined that a causal relationship exists for ...long

- term exposure to PM 2.5 and mortality, consistent with CASAC comm ents” (Jackson, 2012). This evaluation of the evidence included review of the potential limitations mentioned by commenters. Furthermore, CASAC supported the EPA’s evaluation of the scientific evidence and the application of the causal framework in making a causal determination for mortality attributed to long

- term PM exposures (Samet, 2009f, pp. 2 to 3). Below, the EPA responds to each of the specific limitations noted by commenters:

(a) With respect to biological plausibility, some commenter s argued that the estimated associations between ambient PM and mortality are stronger than those for long

- term heavy cigarette smoking, thereby defying biological plausibility (ACC, 2012, pp

. 6 to 7). T he comparison of smoking and ambient PM

- related effect estimates wa s n o t considered relevant for the PM NAAQS review and

, thus

, was n o t consider ed in the ISA. This issue

was n o t raised during the CASAC and public review of the draft ISA s. In order to address the comments submitted, the EPA conducted a provisional review o f the “new” literature published since the close of the ISA including studies cited by commenters, and identified several relevant studies that compared and evaluated effect estimates determined for relationships between specific health outcomes and ambien t particulate
matter a nd active smoking (Pope et al. 2009; Pope et al. 2011). These authors analyzed data from the ACS cohort in order to evaluate the shape of the exposure

- response relationship for PM 2.5 and both lung cancer mortality (Pope et al. 2011) a nd cardiovascular disease ( CVD ) mortality (Pope et al. 2009; Pope et al. 2011). In these studies, the authors evaluated three sources of exposure to PM 2.5 : active smoking, passive smoking, and ambient air pollution.
For lung cancer mortality, the authors observed “a monotonic, nearly linear exposure response relationship with fairly constant marginal increases in RR [relative risk] with increasing exposure” a cross the full range of observed exposures (Pope et al. 2011). When the authors evaluated CVD mortality, they observed “an exposure

- response relationship that is substantially non

- linear, that is, much steeper at the very low levels of exposure compared wi th higher levels of exposure” (Pope et al. 2011). In fact, the authors noted that “For lung cancer mortality, the RRs steadily increase to nearly 40 at the highest increment of cigarette smoking (>42 cigarettes per day), whereas for CVD mortality, the RRs level off at approximately 2.0

- 2.5” (Pope et al. 2011) (Figure 1).

### Draft

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- 32 

### Figure 1. Adjusted RRs [with 95% confidence intervals (CIs)] of lung cancer mortality (A) and IHD, cardiovascular, and cardiopulmonary mortality (B) plotted over estimat ed daily exposure of PM 2.5 

### (milligrams) and increments of cigarette smoking relative to never smokers (cigarettes/day). Diamonds represent comparative mortality risk estimates (with 95% CIs) for PM 2.5 

### from air pollution from the comparative studies (Docker y et al. 1993; Laden et al. 2006; Miller et al. 2007; Pope et al. 1995, 2002, 2004). Stars represent comparable pooled RR estimates (with 95% CIs) associated with SHS exposure from comparative studies (Teo et al. 2006; U.S. Department of Health and Human S ervices 2006). The dotted lines represent the nonlinear power function fit through the origin and the estimates (including active smoking, SHS, ambient PM 2.5 

### ). Estimated doses from different increments of active smoking are dramatically larger than estimat ed doses from ambient pollution or SHS; therefore, associations at lower exposure levels (due to ambient air pollution and SHS) are shown as insets with a magnified scale. Source: Pope et al. 2011

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33 Because of the much steeper exposure

- response relationship for long

- term exposure to PM 2.5 and CVD mortality at low PM 2.5 concentrations , which flattens out at higher PM 2.5 concentrations (i.e., those associated with passive and active cigarette smoking), it is biologically plausible that the risk estimates for C VD mortality due to exposure to ambient concentrations of PM 2.5 would be similar to risk estimates for CVD mortality due to active cigarette smoking. These results are consistent with the results observed in epidemiologic al studies of long

- term exposure to PM 2.5 and mortality, and with the conclusions drawn in the ISA

. For example, Dockery et al. (1993) found essentially the same risk estimates for CVD mortality associated with both ambient PM 2.5 concentrations and active cigarette smoking in an area with r elatively high levels of ambient PM 2.5 concentration. Thus , contrary to views expressed by commenters, the EPA concludes that the scientific evidence provides biologically plausibility for the mortality effects observed in epidemiological studies of ambien t PM.

(b) With regard to estimating PM 2.5 exposure for periods when data are not available, as discussed in section III.E.4.c.i of the preamble to the final rule and in section II.B.5.a.i below, both in the last review and the current review, the EPA has assessed studies that used different air quality periods for estimating long

term exposure and tested associations with mortality for the different exposure periods ( U.S. EPA , 2004, s ection 8.2.3.5; U.S. EPA 2009a, s ection 7.6.4 ). In this review, the ISA d iscussed studies available since the last review that have assessed the relationship between long

- term exposure to PM 2.5 and mortality to explore the issue of the latency period between exposure to PM 2.5 and death ( U.S. EPA , 2009a, section 7.6.4).

Notably, in a recent analysis of the extended Harvard Six Cities Study, Schwartz et al. (2008) used model averaging (i.e., multiple models were averaged and weighted by probability of accuracy) to assess exposure periods prospectively. The exposure periods were es timated across a range of unconstrained distributed lag models (i.e., same year, one year prior, two years prior to death). In comparing lags, the authors reported that the effects of changes in exposure to PM 2.5 on mortality were strongest within a two

- ye ar period prior to death ( U.S. EPA

, 2009a, p. 7

- 92, Figure 7

- 9). Similarly, a large multi

- city study of the elderly found that the mortality risk associated with long

- term exposure to PM 10 reported cumulative effects that extended over the years that death s were observed in the study population (i.e., the follow

- up period) and for the three

- year period prior to death (Zanobetti et al., 2008).

Further, in a study of two locations that experienced an abrupt decline in PM 2.5 concentrations (i.e., Utah Steel Strike, coal ban in Ireland), Röösli et al. (2005) reported that approximately 75 percent of health benefits were observed in the first 5 years ( U.S. EPA , 2009a, Table 7

- 9). Schwartz et al. (2008) and Puett et al. (2008) f ound, in a comparison of exposure periods ranging from 1 month to 48 months prior to death that exposure to PM 10 24 months prior to death exhibited the strongest association, and the weakest association was reported for exposure in the time period of 1 mon th prior to death. Formatted: Left: 1.5"Draft

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34 Collectively, the EPA notes that the available evidence for determining the window over which the mortality effects of long

- term PM exposures occur, as discussed above and in section III.E.4.c.i of the preamble to the final rule and in section II.B.5.a.i below , suggests that a latency period of up to five years would account for the majority of deaths, with the strongest association observed in the two years prior to death. Further, the EPA recognizes that there is no discernible populat ion

- level threshold below which effects would not occur, such that health effects may occur over the full range of concentrations observed in the epidemiologic al studies , including the lower concentrations in the latter years. ( U.S. EPA , 2009 a , s ection 2.4 .2.3). In light of this evidence and these considerations, the EPA concludes that it is appropriate to consider air quality concentrations that are contemporaneous with the collection of health event data (i.e., collected over the same time period ) as being causally associated with at least some proportion of the deaths assessed in a long

- term exposure study.

In addition, the EPA acknowledges that the appropriate exposure period for mortality effects observed in long

- term exposure studies may extend up to a few years prior to the years in which health event data were collected. Such an extended exposure window would likely more fully capture the PM 2.5 - related deaths in such studies. To explore how much higher the long

- term mean PM 2.5 concentrations w ould likely have been had air quality data prior to the follow

- up years of the studies been included, the EPA conducted a sensitivity analysis of long

- term mean PM 2.5 concentrations (Schmidt, 2012 a ), particularly

, considering studies that only included dea ths from a relatively recent follow

- up period. As examples of such studies, this analysis considered the Eftim et al. (2008) study of mortality in the ACS sites and the Harvard Six Cities sites, as well as sites in the eastern region in the Zeger et al. (2 008) study. Using data from the EPA’s AQS database, the analysis added the two years of air quality data just prior to the follow

- up period in each study, which was 2000 to 2002 in Eftim et al. (2008) and 2000 to 2005 in Zeger et al. (2008). The analysis t hen calculated the extended long

- term mean PM 2.5 concentration for each study. As discussed in Schmidt (2012 a ), in each case the long

- term mean PM 2.5 concentration averaged over the extended exposure period was less than 0. 4 μg/m 3 higher than the long

- term mean PM 2.5 concentration averaged over the follow

- up period. The EPA finds it reasonable to conclude that such a relatively small difference in long

- term mean PM 2.5 concentrations would likely apply for other long

- term exposure studies that used similarly recent follow

- up periods as well (e.g., Goss et al., 2004; Lipfert et al., 2006). Furthermore, the EPA finds that this sensitivity analysis illustrates that, even when considering a somewhat longer exposure window, including the years the health event dat a were collected plus the two previous years, health effects are occurring at concentrations below the current level of the annual standard (i.e., below 15 μg/m 3 ).

Moreover, as discussed in section III.E.4.c.i of the preamble to the final rule and in sect ion II.5.a.i below, the EPA notes that the relevant exposure period for the short

- term exposure studies is the period contemporaneous with the collection of health event data, and that this exposure period is not subject to the uncertaintiesDraft

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35 related to the long

- term exposure studies. This is one of the reasons that the EPA gave special consideration to the long

- term mean concentrations evaluated in key short

- term exposure studies in revising the level of the annual standard.

(c) The EPA has long recognized that exposure error is an important issue for interpretation of epidemiologic al studies and that assessment of air pollution exposure using community average concentrations may lead to exposure misclassification or exposure measurement error. To investiga te this issue, several analyses using ACS data focused on neighborhood

- to

- neighborhood differences in urban air pollutants (Jerrett et al. 2005; Krewski et al. 2009) ( U.S. EPA, 2009a,

s ection 7.6.3). These analyses used spatial interpolation and land use r egression methods to assign exposure to study subjects living in Los Angeles, CA, resulting in improved exposure assessment compared to the full cohort of the ACS study. Statistically significant associations between PM 2.5 and mortality from all causes and cardiopulmonary diseases were reported with the magnitude of the relative risks being greater in the analyses with the improved exposure assessment compared to the relative risks reported for the full ACS cohort. This provides evidence that reducing expos ure error can result in stronger associations between PM 2.5 and mortality than generally observed in studies having less well

characterized exposure.

(8) Comment: Some commenters contend ed that the associations observed in long

term exposure studies we re due to exposures that occurred many years earlier when PM 2.5 concentrations were much higher and therefore are “misattributing those risks to more recent, lower PM 2.5 levels” (UARG, Attachment 1, p p

. 14 to 15; Southern Co mpany, 2012 p. 2; AAM , 2012, p p . 14 to 15). Additionally, these
commenters assert ed that mortality due to long

- term exposure is the result of cumulative exposure over a lifetime, which led to the development of chronic conditions that ultimately contributed to death.

Response: As an initial ma tter, the EPA has recognized the challenge in distinguishing between PM 2.5 - associated effects due to past and recent long

- term exposures, and in identifying the relevant latency period for long

- term exposure to PM and resultant health effects ( U.S. EPA, 20 09a ; 77 FR 38941/1). While the EPA acknowledges that there remain important uncertainties related to characterizing the most relevant exposure periods in long

- term exposure studies, the assertion that there is “no knowledge or evidence” that helps to infor m this issues is not correct.

Both in the last review and the current review, the EPA has assessed studies that used different air quality periods for estimating long

- term exposure and tested associations with mortality for the different exposure periods ( U.S. EPA , 2004, S ection 8.2.3.5; U.S. EPA 2009a, s ection 7.6.4). In this review, the ISA discussed studies available since the last review that have assessed the relationship between long

- term exposure to PM 2.5 and mortality in exploring the issue of the l atency period between exposure to PM 2.5 and death ( U.S. EPA , 2009a, S ection 7.6.4).Draft

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36 Notably, in a recent analyses of the Harvard Six Cities Study, Schwartz et al. (2008) used model averaging (i.e., multiple models were averaged and weighted by probability of accuracy) to assess exposure periods prospectively (77 FR 38907/1

- 2) . The exposure periods were estimated across a range of unconstrained distributed lag models (i.e., same year, one year prior, two years prior to death). In comparing lags, the authors reported the effects of changes in exposure to PM 2.5 on mortality were strongest within a two year period prior to death ( U.S. EPA

, 2009a, p. 7

- 92, Figure 7

- 9). Similarly, a large multi

- city study of the elderly found that the mortality risk associated wit h long

- term exposure to PM 10 reported cumulative effects that extended over the year s that deaths were observed in the study population (i.e., the follow

- up period) and for the 3

- year period prior to death (Zanobetti et al., 2008).

Further, in a study of two locations that experienced an abrupt decline in PM 2.5 concentrations (i.e., Utah Steel Strike, coal ban in Ireland), Röösli et al. (2005) reported that approximately 75 percent of health benefits were observed in the first 5 years ( U.S. EPA , 2009a, Tab le 7

- 9). Furthermore, Schwartz et al. (2008) and Puett et al. (2008) found, in a comparison of exposure periods ranging from 1 month to 48 months prior to death that exposure to PM 10 24 months prior to death exhibited the strongest association, and the wea kest association was reported for exposure in the time period of 1 month prior to death.

Overall, the EPA notes that the available evidence for determining the window over which the mortality effects of long

- term pollution exposures occur suggests that a latency period of up to five years would account for the majority of deaths, with the strongest association observed in the two years prior to death. Further, the EPA recognizes that there is no discernible threshold below which effects would not occur, su ch that health effects may occur over the full range of concentrations observed in epidemiologic al studies , including the lower concentrations in the latter years . In light of this evidence and these considerations, the EPA concludes that it is appropriate to consider air quality concentrations that are contemporaneous with the collection of health event data

as evidence to be used in determining causality. The EPA acknowledg es that exposure windows that extend up to a few years prior to the follow

- up perio d in which health event data were collected would likely more fully capture the PM

related deaths in such studies.

To explore how much higher the long

- term mean PM 2.5 concentrations would likely have been had air quality data prior to the follow

- up years of the studies been included, the EPA conducted a sensitivity analysis of PM 2.5 concentrations (Schmidt, 2012), particularly

, considering studies that only included deaths from a relatively recent follow

- up period. As examples of such studies, this analysis considered the Eftim et al. (2008) study of mortality in 51 ACS sites and the Harvard Six Cities sites, as well as sites in the eastern region in the Zeger et al. (2008) study. Using data from the EPA’s AQS databa se, the analysis added the two years of air quality data just prior to the follow

- up period in each study, which was 2000 to 2002 in Eftim et al. (2008) and 2000 to 2005 in Zeger et al.Draft

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37 (2008). The analysis then calculated the extended long

- term mean PM 2.5 concentration for each study. As discussed in Schmidt (2012), in each case the long

- term mean PM 2.5 concentration averaged over the extended exposure period

was less than 0. 3 μg/m 3 higher than the long

- term mean PM 2.5 concentration averaged over the follo w

- up period. The EPA finds it reasonable to conclude that such a relatively small difference in long

- term mean PM 2.5 concentrations would likely apply for other long

- term exposure studies that used similarly recent follow

- up periods as well (e.g., Goss et al., 2004; Lipfert et al., 2006).

Based on the above considerations, the EPA concludes that it is appropriate to consider the available air quality information from the long

- term exposure studies, while taking into account the uncertainty in the relevant l ong

- term exposure period when weighing the information from the long

- term exposure studies in the context of the broader array of epidemiologic al studies that inform the EPA’s consideration of the level of the annual PM 2.5 standard

. Furthermore, as noted i n the preamble and in the response to the previous comment (Comment ( 7 ) ) , the relevant exposure period for the short

- term exposure studies is the period contemporaneous with the collection of health event data, and that this exposure period is not subject to the uncertainties related to the long

- term exposure studies. The EPA accordingly gave special consideration to the long

- term mean concentration s evaluated in key short

- term studies in revising the level of the annual standard. These comments are address ed further in section III.E.4.c.i of the preamble to the final rule and in section II.B.5.a.i below.

(9) Comment: Some commenters asserted there were limitations in specific long

- term exposure studies of mortality . For example, one group of commenter s ( NAM et al. , 2012, p p. 23 to 24 ) asserted there were serious weaknesses in the long

- term exposure studies considered by the EPA ( e.g., Harvard Six Cities Study , Laden et al., 2006 ). Specifically, NAM et al. asserted that the Harvard Six Cities Study d id
not ac count for increasing age of the cohort, and that there we re discrepancies in the results of the study. Another commenter ( EPRI , 2012, p . 3 ) assert ed that the EPA mischaracterized the results of the Veterans Cohort Study (Lipfert et al. 2006).

Response: Th e EPA disagrees with the commenters’ assertion that the increasing age of the study subjects from the Harvard Six Cities Study w as not accounted for when estimating the association between decreased PM 2.5 concentrations and decreased mortality observed by Laden et al. (2006). The average age of the cohort at enrollment was 50 years (range 25 to

- 74 years) and the first follow

- up period consisted of the 15 years following enrollment (including 104,243 pers on

years of follow up and 1,364 deaths ) . An additional follow

- up period (16 to 24
years after enrollment) included an additional 54,735 person

- years of follow

- up and 1,368 deaths. The overall death rate for the first follow

- up period was 13.1 deaths per 1, 000 years of follow

- up; it was 25.0 in the second follow

- up period “reflecting the aging of this cohort” (Laden et al. 2006 , p. 668 ). To account for this, Laden et al. (2006) controlled for baseline individual risk factors and potential confounders, includ ing age. The authors stratified study subjects “by sexDraft

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38 and 1

- yr age groups, such that each sex/age group had its own baseline hazard

. ” Id

. The authors found that the association s between PM 2.5 and mortality were comparable for both follow

- up periods (Laden et al. 2006, p. 669)

. Additionally, NAM assert ed that there we re discrepancies in results among the six cities in the study that lead to considerable uncertainty. The EPA acknowledges that there wa s variability in the results for the individual cities in the Harvard Six Cities Study (in fact the objective of the study was to look at the variability between cities) , but disagrees that such variability contributes to uncertainty. In fact, variability in the PM 2.5 concentrations among the cities is necessary in long

- term cohort studies, such as the Harvard Six Cities Study, which rely on spatial variability for exposure contrast (See also r esponse to Comment ( 4 ) , above). Laden et al. (2006) recognize d that there is variability in the association between the ci ties, but note d that “the drop in the adjusted mortality rate was largest in the cities with the largest reductions in PM 2.5 after controlling for such a period effect.” Id.
With regard to the Veteran’s Cohort Study, t he EPA acknowledges that the air quality data in Figure s 1 and 4 ( 77 FR 38929) of the propos al w ere attributed to the wrong Lipfert et al. (2006) study

. 16 The EPA included Lipfert et al., (2006a) in Table 4 in the preamble for the final rule and in the preamble for the proposal (77 FR 38933) of Lipfert et al. (2006a) based on the effect estimated presented in Figure 1 of the propos al (77 FR 38929) and the final rule . This effect estimate wa s positive and statistically significant in a single pollutant model, and remain ed positive (thoug h no longer statistically significant) in a two

- pollutant model that include d traffic density, and a three

- pollutant model that include d traffic density and PM 10

- 2.5
. The EPA also acknowledges that this effect estimate represents an association for which t

he deaths occurred before PM 2.5 measurements were collected, but disagrees with comments from EPRI that it is inappropriate to use such effect estimates. As discussed in the response to Comment ( 8 ) above , the EPA finds it reasonable to conclude that only r elatively small differences in long

term mean PM 2.5 concentrations would likely be observed in long

- term exposure studies in which the exposure is measured during periods after the follow

- up periods during which the health effects were measured.

(10) Comment: S ome commenters asserted there were limitations in the long

- term exposure studies of morbidity, including studies evaluating respiratory effects in children. For example, one commenter (UARG, 2012, Attachment 1, pp. 14 to 16) asserted there were serious lim itations in the long

- term exposure studies of respiratory morbidity in that each of the studies considered by the EPA (including McConnell et al., 2003; Gauderman et al., 2004; Dockery et al., 1996; Raizenne et

16 As noted in a footnote to Figure 1 in the preamble to the final rule, the air quality data reported in Figure 1 of the proposal incorrectly identified the long

- term mean PM 2.5 concentration for this study as 14.3 μg/m 3 , which was the long

- term mean PM 2.5 concentration for Lipfert et al. (2006b). This mistake was also made in the Figure 2

- 2 of the ISA (U.S. EPA, 2009a, p. 2

- 15. The EPA notes that footnote a for Figure 4 of Lipfert et al. (2006a) identifies that the mortality risks for PM 2.5 are based on one year of air quality data (1999). However, this study does not report the long

- term mean PM 2.5 concentration for 1999. Rather, in Table 1 of Lipfert et al. (2006a), the study authors reported long

- term mean PM 2 .5 concentrations of 14.3 μg/m 3 f or the years 1989 to 1996 and 14.6 μg/m 3 for the years 1997 to 2001.Draft

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39 al., 1996; and Goss et al., 2004) and argued that this evidence provides only a “weak association” with PM 2.5 exposures. Additionally, some commenters state d the results from long

- term PM 2.5 exposure and morbidity studies that focus ed on lung function are confounded by copollutants as demonstrated by McConnell et al. (2003) and Gauderman et al. (2004) (UARG , 2012, p. 12, Attachment 1 p. 14
to 16; API , 2012 Attachment 1, p. 45 to 46). UARG also asserted that these studies were all consi dered at the time the EPA reaffirmed the current annual standard level of 15.0 μg/m 3 in 2006, that the Administrator in the last review determined that the information they provided “was too limited to serve as the basis for setting a level of a national s tandard,” and that they should be given little weight in setting the level of the annual standard in this review (UARG, 2012, Attachment 1, p. 14).

More specifically, some commenter s asserted that the McConnell et al. (2003) and Gauderman et al. (2004) stu dies reported mixed results for associations with PM 2.5 and stronger associations with NO 2 (API, 2012, Attachment 1, pp. 14 to 15). Similarly, this commenter argued that the Dockery et al. (1996) and Raizenne et al. (1996) studies showed stronger associati ons with acidity than with fine particles (measured as PM 2.1 ). Id. pp. 15 to 16. With regard to Goss et al. (2004) study, this commenter noted that the association between pulmonary exacerbations and PM 2.5 in this study was no longer statistically signifi cant when the model adjusted for each individual’s baseline lung function. The commenters referred to the data on lung function as an “important explanatory variable,” and suggested that the EPA should rely on results from the model that included individua l baseline lung function information. Id . p. 16. For the reasons discussed in section III.E.4.c.i in the preamble to the final rule and below, the EPA disagrees with the commenters’ interpretation of these studies.

Response: As discussed in section III.E.4.c.i of the preamble for the final rule and in a further response at section II.B.5.a.i below, as an initial matter, the EPA notes that three of these studies (McConnell et al., 2003; Dockery et al., 1996; Raizenne et al., 1996 ) as well as earlier studies from the Southern California Children’s Health Study (Gauderman et al., 2000, 20002) were discussed and considered in the 2004 Air Quality Criteria Document ( U.S. EPA , 2004) and considered within the air quality criteria suppor ting the EPA’s final decisions in the review completed in 2006. Two additional studies (Gauderman et al., 2004; Goss et al., 2004) were discussed and considered in the provisional science assessment conducted for the last review ( U.S. EPA , 2006a).

Specifi cally, the extended analyses of the Southern California Children’s Health Study provided evidence that clinically important deficits in lung function 17 associated with long

- term exposure to PM 2.5 persist into early adulthood (U.S. EPA, 2009a, p. 7

- 27; Gaude rman et al., 2004). Additional analyses of the

17 Clinical significance was defined as an FEV 1 below 80 percent of the predicted value, a criterion commonly used in clinical settings to identify persons at increased risk for adverse respiratory conditions (U.S. EPA, 2009a, p. 7

- 29 to 7

- 30). The primary N AAQS for sulfur dioxide (SO 2 ) also included this interpretation for FEV 1 (75 FR 35525, June 22, 2010).Draft

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40 Southern California Children’s Health Study cohort reported an association between long

- term PM 2.5 exposure and bronchitic symptoms ( U.S. EPA , 2009a,
p p. 7

- 23 to 7

- 24; McConnell et al., 2003, long

- term mean co ncentration of 13.8 μg/m 3 ) that remained positive in co pollutant models, with the PM 2.5 effect estimates increasing in magnitude in some models and decreasing in others, and a strong modifying effect of PM 2.5 on the association between lung function and

as thma incidence ( U.S. EPA , 2009 a , p. 7

- 24; Islam et al., 2007). The outcomes observed in these more recent reports from the Southern California Children’s Health Study, including evaluation of a broader range of endpoints and longer follow

- up periods, were larger in magnitude and more precise than previously reported. Supporting these results were new longitudinal cohort studies conducted by other researchers in varying locations using different methods ( U.S. EPA

, 2009a, s ection 7.3.9.1). The ISA thoroughly evaluated both the McConnell et al. (2003) and Gauderman et al. (2004) studies (U.S. EPA, 2009a, s ections 7.3.1 and 7.3.2 )

. In an additional study occurring in the same 12 Southern California communities, Gauderman et al. (2004) found evidence of decrements in lung function growth in children and adolescents , which persisted with adjustment for copollutants. Similar to the criticism of the McConnell et al. (2003) study, commenters focused on the statistical significance of results. Gauderman et al. (2004) d id not present the results from copollutants models but state d “two

- pollutant models for any pair of pollutants did not provide a significantly better fit to the data than the corresponding single

- pollutant models” (Gauderman et al., 2004, p p. 106 1 to 1062). The commenters claim ed that the authors emphasize d NO 2 as the “apparent culprit” of the lung function decrements, which they claim ed was further supported by the NO 2 results “hav[ing] a much higher significance level” compared to PM 2.5 (UARG, 2 012, p. 15) . The EPA disagrees with the
commenters ’ views because Gauderman et al. (2004) clearly state d throughout the analysis that NO 2 wa s one component of a highly correlated mixture that contain ed PM 2.5 (Gauderman et al., 2004, p. 1064) . Moreover, the commenters are incorrect that statistical significance is the sole, or determinative, measure of epidemiologic study reliability. As stated in response to Comment ( 1 ) above , the reliance of the commenters on statistical significance is inap propriate when evaluating individual study results and the collective evidence across studies. The EPA, therefore, disagrees with the commenters that the studies by McConnell et al. (2003) and Gauderman et al. (2004) are flawed and should not be used in th e PM NAAQS review process. Overall, the evidence from these two studies contributed to the overall evidence used to conclude that a “likely to be causal relationship” exists between long

- term PM 2.5 exposure and respiratory effects.

New evidence from a U.S . cohort of cystic fibrosis patients provided evidence of association between long

- term PM 2.5 exposures and exacerbations of respiratory symptoms resulting in hospital admissions or use of home intravenous antibiotics ( U.S. EPA , 2009a, p. 7

- 25; Goss et al. , 2004, long

- term mean concentration of 13.7 μg/m 3 ). The commenters note d that the association between pulmonary exacerbations and PM 2.5 w as attenuated when the statistical models were adjustedDraft

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41 for each individual’s baseline lung function. The commenters refer red to the data on lung function as an “important explanatory variable

, ” and suggest ed that the EPA should rely on results from the model that include d individual baseline lung function information . However, it is unlike ly that lung function is a potential confounder or an important explanatory variable in this study. In fact, the authors
note d that “it is more likely that lung function decline may be intimately associated with chronic exposure to air pollutants and may b e part of the causal pathway in worsening prognosis in CF [cystic fibrosis]; in support of this explanation, we found both cross

- sectional and longitudinal strong inverse relationships between FEV 1 and PM levels” (Goss et al., 2004, p. 819). Moreover, ad ju sting for a variable that is on the causal pathway can lead to overadjustment bias, which is likely to attenuate the association (Schisterman et al. 2009); this is likely what was observed by the authors. Thus, the EPA is reasonable (and
correct ) in focusi ng on the results that do not include lung function in the model.

The study by Dockery et al. (1996) (long

- term mean concentration of 14.5 μg/m 3 ) was included in the 1996 PM AQCD, and reviewed again in both the 2004 PM AQCD and the 2009 PM ISA. Particulate air pollution, specifically particle strong acidity and sulfate particles (indicators of fine PM), were associated with reports of bronchitis in the past year. Similarly, the magnitude of the associations between bronchitis and PM 10 and PM 2.1 were simila r to those for particle strong acidity and sulfate particles, though the confidence intervals for the PM 10 and PM 2.1 associations were slightly wider and the associations were not statistically significant. Particle strong acidity, sulfate, and fine PM are formed in secondary reactions of the emissions from incomplete combustion. As noted by the authors, “the strong correlations of several pollutants in this study, especially particle strong acidity with sulfate (r=0.90) and PM 2.1 (r=0.82), make it difficul t to distinguish the agent of interest

. ” Overall, Dockery et al. (1996) (and, similarly, Raizenne et al. 1996) observed similar associations between respiratory health effects and particle strong acidity, sulfate, PM 10 and PM 2.1 concentrations. The
comment ers also note that these associations were sensitive to the inclusion of the 6 Canadian sites. None of the Canadian cities were in the “sulfate belt” where particle strong acidity was highest. Thus, the change in effect estimate when the Canadian cities we re excluded from the analysis is likely due to the lower prevalence of bronchitis and the lower particle strong acidity in these cities, and not due to some susceptibility factor, as suggested by the commenters. In fact, contrary to the statements made by the commenters, the authors did not observe any subgroups that appeared to be markedly more susceptible to the risk of bronchitis.

As noted in section III.B.1.a of the proposal, with regard to respiratory effects, the ISA concluded that extended analyses of studies available in the last review as well as new epidemiologic al studies conducted in the U.S. and abroad provided stronger evidence of respiratory

- related morbidity associated with long

- term PM 2.5 exposure (77 FR 38918). The strongest evidence for respiratory

- related effects available in this review was from epidemiologic studies that evaluated decrements in lung f

unction growth in children and increased respiratoryDraft

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42 symptoms and disease incidence i n adults (U.S. EPA, 2009a, S ections 2.3.1.2, 7.3.1.1, and 7.3.2.1).

In considering the collective evidence from epidemiologic and experimental

s tudies, the Integrated Science Assessment concluded that a causal relationship is likely to exist between long

- term PM 2.5 exposures and respiratory effects ( U.S. EPA , 2009a, p. 2

- 12, pp. 7

- 42 to 7

- 43). CASAC concurred with this causality determination (Samet, 2009f, p.9).

The commenter’s assertion that the EPA should adhere to its assessment of the long

- term studie s of respiratory morbidity as it did in the review completed in 2006 is significantly mistaken. Most obviously, the EPA’s final decision in the last review was held to be deficient by the D.C. Circuit in remanding the 2006 primary annual PM 2.5 standard. As discussed in section III.A.2 of the preamble to the final rule , the D.C. Circuit specifically held that the EPA did not provide a reasonable explanation of why certain morbidity studies, including an earlier study from the Southern California Children’s H ealth Study (Gauderman et al., 2000 , long

- term mean PM 2.5 concentration approximately 15 μg/m 3 ) and the 24

- Cities Study (Raizenne et al., 1996 , long

- term mean concentrations approximately 14.5 μg/m 3 ) did not warrant a more stringent annual PM 2.5 standard w hen the long

- term mean PM 2.5 concentrations reported in those studies were at or lower than the level of the annual standard. American Farm Bureau Federation v. EPA

. 559 F. 3d at 525. Indeed, the court found that, viewed together, the Gauderman et al. (200 0) and Raizenne et al., (1996) studies “are related and together indicate a significant public health risk...On this record, therefore, it appears the EPA too hastily discounted the Gauderman and 24

- Cities studies as lacking in significance.” Id. The EPA knows of no reasonable explanation to perpetuate that disregard in this review.

(11) Comment: Some c ommenters contend ed that PM 2.5 risk estimates are highly sensitive to the approach used to control for temporal trends (API, 2012, Attachment 1pp. 11 to 12; AAM, 2012, pp. 6 to 10). Specifically, the results of the Air Pollution and Health: A European and North American Approach (APHENA) study provide d evidence of no effect of short

- term PM exposure on mortality and morbidity because the “overall pattern [of effec ts] is not what one would expect if PM health effects associations have a real physiological basis” (AAM , 2012, p p. 6 to 10)

. AAM state d that this conclusion wa s supported by the lack of consistent statistically significant associations across all models e xamined. Additionally, API contend ed that the sensitivity of PM 2.5 risk estimates to the selection of degrees of freedom to control for temporal trends wa s further demonstrated in Dominici et al. (2007) and Ostro et al. (2006).

Response: The EPA disagrees with the commenters’ view that the results from Katsouyanni et al. (2009), Dominici et al. (2007), and Ostro et al. (2006) demonstrate the sensitivity of PM 2.5 risk estimates to the method used to control for temporal trends and bring into question the as sociation between short

- term PM 2.5 exposures and mortality and hospital admissions. Additionally, theseDraft

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43 commenters have focused solely on the statistical significance of risk estimates and not on the pattern of associations across studies as is discussed m ore fully in Comment (1).

The APHENA study combined data from existing multi

- city study databases from the U.S. (the National Morbidity, Mortality, and Air Pollution Study [NMMAPS]), Europe (Air Pollution and Health: A European Approach [APHEA]), and Cana da to “develop more reliable estimates of the potential acute effects of air pollution on human health [and] provide a common basis for [the] comparison of risks across geographic areas” (Katsouyanni et al., 2009) . In an attempt to address both of these issues the investigators conducted extensive sensitivity analyses to evaluate the robustness of the results to different model specifications (e.g., penalized splines vs. natural splines) and the extent of smoothing to control for temporal trends. In models where an appropriate number of degrees of freedom (df) to control for temporal t rends were employed risk estimates were robust across the different model specifications. The trend analyses consisted of subjecting the models to varying extent of smoothing selected either a priori (i.e., 3 df/year, 8 df/year, and 12 df/year), which was selected through exploratory analyses using between 2 and 20 df, or by using the absolute sum of the residuals of the partial autocorrelation function (PACF). Although the investigators did not identify the model they deemed to be the most appropriate for comparing the results across study locations, they did specify that “overall effect estimates (i.e., estimates pooled over several cities) tended to stabilize at high degrees of freedom” (Katsouyanni et al., 2009).

The results of the APHENA study are cons istent with those reported by both Dominici et al. (2007) and Ostro et al. (2006), which as part of their studies conducted sensitivity analyses to examine the influence of increasing the degrees of freedom per year to control for temporal trends on the PM 2.5 - mortality association. In both cases the authors found evidence that as the degrees of freedom per year increases a point is reached where risk estimates tend to stabilize, which for both of these studies was approximately 7 degrees of freedom

or more per year.
It should be noted that the commenters even state “[i]n most cases, the results and conclusions from these updated analyses were not significantly altered, but effect estimates were lower” (API, 2012, Attachment 1, p 12). The EPA, therefore, dis agrees with the commenter s that the lack of consistent statistically significant results across all models supports the lack of an association between short

- term PM exposure on hospital admissions and mortality. The inconsistency in the results across some of the models (i.e., for APHENA those that controlled for temporal trends using 3 df/year or PACF compared to those that employed 8 or 12 df/year , while for Dominici et al. (2007) and Ostro et al. (2006) those less than 7 df/year ) is due to inadequate con trol for temporal trends

. . Additionally, the EPA disagrees with th ese commenters sole reliance on statistical significance when evaluating the results of th ese stud ies . As stated in the response to Comment ( 1 ) above , focusing solely on statistical ly signifi cance is inappropriate whenDraft

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44 evaluating studies

. (12) Comment: Multiple commenters (ACC, 2012, p p. 14 to 18; AAM, 2012, p p. 6 to 10) questioned the EPA’s interpretation of results from specific short

- term PM 2.5 exposure studies that examined associations with morbidity and mortality outcomes. Specifically, these commenters question ed : (a) interpretation of results from copollutant models; ( b ) lag selection; ( c) the derivation of national risk estimates fr om mult i city studies; and ( d ) the ignoring of evidence indicating a reduction in PM

- mortality risk over time.

Response: Overall, the EPA disagrees with each of the points raised by the commenters and provides detailed responses to each in the following subsecti ons:
(a) Interpretation of results from copollutants models

The commenters questioned the EPA’s interpretation of results from the copollutants models examined in Burnett et al. (2004) as well as all studies that examined copollutants models based on Ito et al. (2007), which stated that the use of multipollutant models “are a cautionary exercise, and throw into question the now commonplace practice of using multipollutant models in health effects analysis.” The EPA disagrees with the commenters’ interpretatio n of the results from Burnett et al. (2004). The main copollutant analyses conducted over the entire study duration used PM 2.5 data tha t w ere not collected every day. As a result, when including PM 2.5 in copollutant analyses with other pollutants that are measured on a daily basis

, the overall sample size is reduced, which reduces the precision of resulting effect estimates. Burnett et al. (2004) performed a sensitivity analysis that further depicts this point. When limiting the dataset to days in which dai ly PM 2.5 concentrations were available

, the PM 2.5 association remained robust after adjustment for NO 2 , while the NO 2 association was attenuated. Overall, this result brings into question the results from copollutants analyses including PM 2.5 that is colle cted every

- 3 rd or 6 th

- day

. Finally , the EPA disagrees with the commenters’ interpretation of the quote from Ito et al. (2007) that they rel ied on to discredit the results from copollutant analyses . Ito et al. (2007) caution ed against including all polluta nts in one model, which

, as they demonstrate d can result in “ the pollutant that varies least like all the rest of the pollutants, and is least affected by concurvity in such a multi

pollutant model” being the pollutant that looks to be causing the effect. The EPA has emphasized evaluation of models including no more than two pollutants because models that include d multiple pollutants are difficult to interpret due to the potential multicollinearity between pollutants. ( e.g. , U.S. EPA

, 2004

, section s 8.4.3.2 and 8.4.3.3 )

. (b) Lag selection

With regard to the lags selected in certain mortality studies (i.e., Franklin et al. 2007), commenters question ed the selection of lag days a priori and not throughDraft

– Do Not Quote or Cite December 1 1 , 2012

45 the use of model fit criteria (ACC, 2012, p p. 14 to 18). As de monstrated in the ISA , studies that examined the association between short

- term PM 2.5 exposure and mortality “were consistently observed at lag 1 and lag 0

- 1, which have been confirmed through extensive analysis of PM 10 - mortality studies” (U

. S

. EPA, 2009 a , p. 6

- 200). Therefore, the lag days selected by Franklin et al. (2007) a priori (i.e., lag 0

- 1) were consistent with the large body of evidence that has demonstrated associations between short

- term PM exposure and mortality.

(c) Derivation of national risk es timates from multicity studies

Some commenters questioned the derivation of national risk estimates from multi

city studies. Specifically, these commenters question ed the approach employed by study investigators to calculate a national estimate, claiming that it d id not use the entirety of the community

- level data (ACC, 2012, p p . 14 to 18). The EPA disagrees with these commenters understanding of the approach used to c alculate national risk estimates in multicity studies. Multi

- city studies

, in fact

, do use the entirety of the dataset to calculate national risk estimates. By calculating city

specific risk estimates and then utilizing either a meta

- regression or a 2 nd st age Bayesian Hierarchical model, investigators use the city

- specific estimates to calculate the national risk estimate. Investigators of multi

- city studies are not excluding any community

- level data, but instead are using the totality of data to provide in formation that is needed to calculate a national risk estimate.

(d) Ignoring evidence of a reduction in PM

- mortality risk over time

Some commenters also question ed the EPA’s interpretation of evidence indicating a reduction in PM

- mortality risk estimates over time, and point ed to the results of Dominici et al. (2007) to support their argument (ACC, 2012, p p . 14 to 18). At first glance, the results of Dominici et al. (2007) would seem to indicate that PM

mortality risk estimates have declined over time due to t he observed decline in the slope for all

- cause and cardiorespiratory mortality. However, this analysis was motivated by accountability research and instead of measuring the impact of a sudden change in air quality, this study attempted to measure the impac t of policy interventions. As such, “a flaw in the use of the time

- series study design for this type of analysis is that it adjusts for long

- term trends, and, therefore, does not estimate the change in mortality in response to the gradual change in PM 10 ” ( U.S. EPA , 2009 a , p. 6

- 163). Therefore, the EPA disagrees with the commenters

. Although this analysis may indicate a slight reduction in PM

- mortality risk estimates over time “the analytic approach used in the study does not allow for a systematic analysis of the effect of air pollution policies on the risk of mortality” ( U.S. EPA , 2009 a , p. 6

- 163).

(13) Comment: In asserting that the uncertainties in the underlying health science are as great or greater than in the last review and therefore do not support revi sion to the standards at this time, multiple commenters (API, 2012, p p . 1, 17 to 20, and Attachment 1, p p . 9 to 24, Attachment 7 , p. 9 , Attachment 9; ACC, 2012, p p . 2 to 7 , 14 to 18 ; NAM, 2012, p p . 9 , 23 ; AAM, 2012, p p

. 5 to 15; AFPM, 2012, p. 3;Draft

– Do Not Quote or Cite December 1 1 , 2012

46 Southern Company, 2012, p p . 2 to 3; EPRI, 2012, p p

. 1 to 4; T exas CEQ, 2012,
p p

. 1 to 4 ) discussed a number of issues related to : (a) copollutant confounding ; (b) ecological/contextual confounding ; ( c ) heterogeneity in risk estimates, ( d )
exposure measure ment error ; ( e ) model specification ; (f) the shape of the concentration

- response (C

- R) function ; and ( g ) understanding the relative toxicity of components within the mixture of fine particles.

Response: The EPA believes that the overall uncertainty about possible health risks associated with both long

- and short

- term PM 2.5 exposure has diminished since the last review. T he EPA disagrees with commenters’ views that the remaining uncertainties in the scientific evidence are too great to support revising the current PM 2.5 NAAQS. The EPA has carefully considered the uncertainties highlighted by commenters in its evaluation of the scientific evidence as discussed in section III. D.2 of the preamble to the final rule and below :
(a) Copollutant c onfoundin g

Some commenters asserted that the EPA has not adequately interpreted the results from studies that examined the effect of copollutants on the relationship between long

- and short

- term PM 2.5 exposures and mortality and morbidity outcomes ( e.g., NAM 2012, p. 23

, ACC 2012, p p. 14 to 18 ) . These commenters contend ed that the EPA has inappropriately concluded that PM 2.5 - related mortality and morbidity associations are generally robust to confounding. The commenters stated that statistically significant PM 2.5 associat ions in single

- pollutant models in epidemiologic al studies do not remain statistically significant in copollutant models.

The EPA recognizes where PM 2.5 and other pollutants are highly correlated, it can be difficult to distinguish effects of the various pollutants in copollutant models. The loss of statistical significance or the reduction in the magnitude of the effect estimate when a copollutant model is used may be the result of factors other than confounding. These changes do not prove either the exis tence or absence of confounding. These impacts must be evaluated in a broader context that considers the entire body of evidence. The broader examination of this issue in the ISA included a focus on evaluating the stability of the size of the effect estima tes in epidemiologic al studies conducted by a number of research groups using single

and co

- pollutant models ( U.S. EPA , 2009a, s ections 6.2.10.9, 6.3.8.5, and 6.5, Figures 6

- 5, 6

- 9, and 6

- 15). This examination found that, for most epidemiologic al studies, there was little change in effect estimates based on single

- and copollutant models, although the ISA recognized that in some cases, the PM 2.5 effect estimates were markedly reduced in size and lost statistical significance.

In questioning the i nfluence of co

- pollutants on associations observed in short

term PM exposure and mortality studies, commenters highlight ed the lack of control for copollutants in Dominici et al. (2003, 2007) and Franklin e t al. (2007). The EPA recognized that a limitation of the multi

- city studies that examined theDraft

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4 7 association between short

- term PM 2.5 exposure and mortality evaluated in the ISA was the relative lack of copollutant analyses. This limitation was mentioned when evaluating the collective evidence and forming t he causality determination for mortality. In Chapter 2 of the ISA ( U.S. EPA, 2009a, p. 2

- 11), the EPA state d, “Although recently evaluated U.S.

- based multi

- city studies did not analyze potential confounding of PM 2.5 risk estimates by gaseous pollutants, ev idence from the limited number of single

- city studies evaluated in the 2004 PM AQCD ( U.S. EPA , 2004) suggest that gaseous copollutants do not confound the PM 2.5 - mortality association. This is further supported by studies that examined the PM 10 - mortality re lationship”, which were discussed in s ection 6.5.2.1 of the ISA ( U.S. EPA , 2009 a ).

These commenters also questioned the lack of copollutant analyses in long

- term exposure and mortality studies. The EPA recognizes that a limited number of studies investiga ting the association between long

- term exposure to PM 2.5 and mortality have included copollutant models. As discussed in the previous review, the analysis of multiple pollutants from the ACS cohort observed increases in
two

- pollutant models that incorporat ed CO, NO 2 , and ozone, and were reduced only for models that incorporated SO 2 ( Krewski et al. 2000 )

. The 2004 AQCD recognized, however, that SO 2 is a precursor for fine particle sulfates, which complicates the interpretation of copollutant model results

. In a follow

- up study of the ACS cohort restricted to just Los Angeles, CA (Jerrett et al. 2005), the authors observed that O 3 “did not confound the relationship between particles and mortality

. ” Similarly, analysis of the AHSMOG cohort (Chen et al. 2005) fou nd that the association between mortality and long

- term exposure to PM 2.5 became stronger when O 3 and SO 2 were included in copollutants models, and the association for PM 2.5 did not change when NO 2 was included in co

- pollutants models. The results of these studies provide confidence that more recent reports with updated datasets are showing independent effects of PM 2.5
. The EPA notes that these public comments do not adequately reflect the complexities inherent in assessing the issue of copollutant confoun ding. As discussed in the proposal (77 FR 38907, 38909, and 38910) and more fully in the ISA (USEPA, 2009a, s ections 6.2, 6.3, and 6.5), although copollutant models may be useful tools for assessing whether gaseous copollutants may be potential confounders , such models alone cannot determine whether copollutants are in fact confounders. The EPA believes that observing robust effect estimates after examination of copollutant models provides greater confidence in the observed associations between short

- and l ong

- term exposures to PM 2.5 and mortality and morbidity, while recognizing that potential confounding by copollutants remains a very challenging issue to address, even with well

- designed studies. Interpretation of the results of copollutant models is compl icated by correlations that often exist among air pollutants, by the fact that some pollutants play a role in the atmospheric reactions that fo rm other pollutants such as secondary fine particles, and by the statistical power of the studies in question inh erent in the study methodology. For example

, the every

- third or sixth

- day sampling schedule often employed for PM 2.5 compared to daily measurements of gaseous copollutantsDraft

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48 drastically reduces the overall sample size to assess the effect of copollutants on the PM 2.5 - morbidity or mortality relationship, such that the reduced sample size can lead to less precise effect est imates (e.g., wider confidence intervals).

The EPA recognizes that when PM 2.5 is correlated with gaseous pollutants it can be difficult to identify the effect of individual pollutants in the ambient mixture (77 FR 38910). However, based on the available ev idence, the EPA concludes epidemiologic al studies continue to support the conclusion that PM 2.5 associations with mortality and morbidity outcomes are robust to the inclusion of gaseous copollutants in statistical models. The EPA evaluated the potential co nfounding effects of gaseous copollutants and, although it is recognized that uncertainties and limitations still remain, the Agency concluded the collective body of scientific evidence is “stronger and more consistent than in previous reviews providing a strong basis for decision making in this review" (77 FR 38910/1).

(b) Ecological/contextual confounding

Some commenters contend ed that both short

- and long

- term PM 2.5 exposure studies of mortality did not appropriately control for ecological or contextual conf ounders ( ACC, 2012, p. 3; API, 2012, Attachment 1, p. 14; NAM 2012, p. 23 )

.
In the case of short

- term exposure studies

, an ecologic al confounder would need to vary on a day

- to

- day basis with both air pollution and with the specific health outcome being ev aluated (e.g., mortality or hospital admissions or emergency department visits ) . The confounders that fit these criteria for short

- term exposure studies are related to weather (e.g., temperature, dew point, relative humidity). The short

- term exposure studi es , specifically time

- series studies, evaluated in the ISA all included weather covariates in their models to account for their potential confounding effects (U.S. EPA, 2009a, Chapter 6 )

. With regard to long

- term exposure studies, a number of multilevel cohort studies (Naess et al. 2007; Jerrett et al. 2003; Jerrett et al. 2005) have evaluated individual

- level and contextual, or ecologic

- level variables as potential confounders. As reported in Jerrett et al. (2005), “Contextual effects occur when individu al differences in health outcome s are associated with the grouped variables that represent the social, economic, and environmental settings where the individuals live, work, or spend time (e

. g

. , poverty or crime rate in a neighborhood). These contextual ef fects often operate independently from (or interactively with) the individual

- level variables such as smoking

. ” These studies found that the inclusion of contextual variables tend ed to attenuate the risk estimate s for the association between long

- term expo sure to PM 2.5 and mortality, but that an independent effect of PM 2.5 on mortality remains. For example, Jerret t et al. (2005) found that for PM 2.5 (controlling for age, sex, and race), the relative risk was 1.24 (95% CI 1.11, 1.37) for a 10 μg/m 3 exposure contrast. In a parsimonious model that controlled for 44 different individual covariates and ecologic al confounder variables that both reduce d the pollution coefficient andDraft

– Do Not Quote or Cite December 1 1 , 2012

49 ha d associations with mortality, the relative risk was 1.11 (95% CI 0.99, 1.25) for the same exposure contrast. The EPA believes that the results of these studies provide confidence that more recent reports with updated datasets are showing independent effects of PM 2.5
. Additionally commenters contend ed that non

- traditional confounders h ave not been accounted for in epidemiologic al studies of short

- and long

- term exposure to air pollution, which could confound the associations observed (API, 2012, Attachment 1, p. 14). These confounders include physical and psychological population stress factors. The EPA disagrees with these commenters because : (1) there is very limited evidence of stress affecting the air pollution

- health effect relationship upon which to base the commenters assertion ; (2) in order for stress to be a true confounder it w ould need to vary temporally (for short

- term exposure studies) and spatially (for long

- term exposure studies) with both air pollution concentrations and the health effect of interest, which has not been demonstrated ; and (3) rather than stress acting as a true confounder, more than likely stress is on the causal pathway to the health effects that have been observed to be associated with air pollution. The EPA acknowledges that stress may contribute bias to epidemiological studies; however, stress more than likely would influence the magnitude of individual effect estimates in a single

- city or multi

- city study and not the trends of positive associations observed across studies conducted in multiple locations.

(c) Heterogeneity in risk estimates

Some commenters argued that the heterogeneity in risk estimates observed in multi

- city epidemiologic al studies and the lack of statistical significance in many regional or seasonal estimates highlights a potential bias associated with combined multi

- city epidemiologic al s tudy results (e.g., API, 2012, Attachment 1, pp. 15 to 19). Additionally, these commenters contend ed that the wide range of individual city results in these multicity studies, specifically NMMAPS, demonstrate d a biologically implausible wide range of assoc iations (AAM, 2012,
p p . 6 to 10). These commenters further argued that more refined intra

- urban exposure estimates conducted for two of the largest cities included in the ACS study, Los Angeles and New York City, based on land

- use regression models and/or kriging methods (Krewski et al., 2009) “underscore the importance of considering city

- specific health estimates, which may account for heterogeneity in PM 2.5 concentrations or other differences among cities, rather than relying on pooled nationwide results from multi

- city studies” (API, 2012, Attachment 1, p. 17).

With respect to understanding the nature and magnitude of PM 2.5 - related risks, the EPA agrees that epidemiologic al studies evaluating health effects associated with long

- and short

- term PM 2.5 expo sures have reported heterogeneity in responses between cities and effect estimates across geographic regions of the U.S. ( U.S. EPA , 2009a, s ections 6.2.12.1, 6.3.8.1, 6.5.2, and 7.6.1; U.S. EPA , 2011a, p. 2

- 25). For example, when focusing on short

- term PM 2 .5 exposure, the ISA foundDraft

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50 that multi

- city studies that examined associations with mortality and cardiovascular and respiratory hospital admissions and emergency department visits demonstrated greater cardiovascular effects in the eastern versus the wester n U.S. (Dominici, et al., 2006; Bell et al., 2008; Franklin et al. (2007, 2008)). However, the rationale that heterogeneity in risk estimates presents a potential bias as posed by the commenters is simplistic and does not account for a number of factors th at have been shown to influence city

- specific risk estimates in epidemiologic studies. As discussed in the ISA , the EPA recognizes that there are compositional differences in PM 2.5 across the country and that the county

- level air quality data used in epidemiologic al studies may result in exposure error, which could in part account for variability in city

- specific risk estimates (U.S. EPA, 2009a, s ection 2.3.2)

.
There are a limited number of studies that evaluate d regional heterogeneity in the association between long

- term exposure to PM 2.5 and mortality. Krewski et al. (2009) conducted subset analyses of the ACS cohort in Los Angeles, CA and New York City, NY, and observed a relativ e risk in Los Angeles that was greater in magnitude than what was observed in the full ACS cohort, while the relative risk in New York City was less than what was observed in the full ACS cohort. These observations are likely due to the greater spatial het erogeneity in PM 2.5 concentrations observed in Los Angeles, and the overall spatial homogeneity of PM 2.5 concentrations in New York City.

In another retrospective cohort, Zeger et al. (2008) observed associations between long

- term exposure to PM 2.5 and mo rtality for the eastern and central ZIP codes that were similar to those reported in the ACS and Harvard Six Cities studies, though no association was observed in the western region. The lack of the association in the western region is “largely because the Los Angeles basin counties (California) have higher PM levels than other West Coast urban centers, but not higher adjusted mortality rates” (Zeger et al. 2008). The ISA also evaluated studies that provided some evidence for seasonal differences in PM 2.5
r isk estimates, specifically in the northeast. The ISA found evidence indicating that individuals may be at greater risk of dying fro m higher exposures to PM 2.5 in the warmer months, and at greater risk of PM 2.5 associated hospitalization for cardiovascular and respiratory diseases during colder months of the year. The limited influence of seasonality on PM risk estimates in other regions of the U.S. may be due to a number of factors including varying PM composition by season, exposure misclassification due to regional tendencies to spend more or less time outdoors and air conditioning usage, and the prevalence of infectious diseases during the winter months ( U.S. EPA , 2009a, p. 3

- 182).

Overall, the EPA recognizes that uncertainties still remain regarding va rious factors that contribute to heterogeneity observed in epidemiologic al studies (77 FR 38909/3). Nonetheless, the EPA recognizes that this heterogeneity could be attributed, at least in part, to differences in PM 2.5 composition across the U.S., as well as to exposure differences that vary regionally such as personal activity patterns, microenvironmental characteristics, and the spatial variability of PM 2.5Draft

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51 concentrations in urban areas ( U.S. EPA , 2009a, section 2.3.2; 77 FR 38910).

As recognized in the PA , the current epidemiologic al evidence and the limited amount of city

- specific speciated PM 2.5 data does not allow conclusions to be drawn that specifically differentiate effects of PM in different locations ( U.S. EPA, 2011a, p. 2

- 25). Furthermore, the ISA concluded “that many constituents of PM 2.5 can be linked with multiple health effects, and the evidence is not yet sufficient to allow differentiation of those constituents or sources that are more closely relate d to specific health outcomes ” ( U.S. EPA, 2009a, p. 2

- 17). CASAC thoroughly reviewed the EPA’s presentation of the scientific evidence indicating heterogeneity in PM 2.5 effect estimates in epidemiological studies and concurred with the overall conclusions presented in the IS A.

(d) Exposure measurement error

Industry commenters argued that the EPA did not adequately consider exposure measurement error, which they asserted is an important source of bias in epidemiological studies that can bias effect estimates i n either direction (e.g., API, 2012, Attachment 1, pp. 19 to 20).

The EPA agrees that exposure measurement error is an important source of uncertainty, and that the variability in risk estimates observed in multi

- city studies could be attributed, in part, to exposure error due to measurement

- related issues (77 FR 38910). However, the Agency disagrees with the commenters’ assertion that exposure measurement error was not adequately considered in this review. The ISA included an extensive discussion that addr esses issues of exposure measurement error ( U.S. EPA , 2009a, s ections 2.3.2 and 3.8.6). Exposure measurement error may lead to bias in effect estimates in epidemiologic al studies. A number of studies evaluated in the last review ( U.S. EPA , 2004, s ection 8. 4.5) and in the current review ( U.S. EPA , 2009a, s ection 3.8.6) have discussed the direction and magnitude of bias resulting from specified patterns of exposure measurement error (Armstrong 1998; Thomas et al. 1993; Carroll et al. 1995) and have generally concluded “classical” (i.e., random, within

- person) exposure measurement error can bias effect estimates towards the null. Therefore, consistent with conclusions reached in the last review, the ISA concluded “in most circumstances, exposure error tends to bias a health effect estimate downward ” ( U.S. EPA , 2009a, s ections 2.3.2 and 3.8.6). Thus, the EPA has both considered and accounted for the possibility of exposure measurement error, and the possible bias would make it more difficult to detect true associations, not less difficult.

Additionally a commenter specifically questioned the influence of exposure measurement error on the results from epidemiologic al analyses by referencing a study conducted by Sarnat et al. (2009) ( API, 2012, Attachment 1 , p . 19 ) . This commenter stated:

Sarnat et al . (2009) found that personal exposures to sulfate (a majorDraft

– Do Not Quote or Cite December 1 1 , 2012

52 component of PM 2.5 in certain parts of the country), averaged over time, varied by individual, city and season, and this variability can lead to CRFs that do not represent the true relationship between exposure and outcome. These factors may bias the results of an epidemiology analysis in either direction and are particularly relevant for long

- term studies (for which these factors likely vary over time).

T he EPA disagrees with the interpretation of Sarnat et al. (2009) by the
commenter. Sarnat et al. (2009) describe s variability in the use of home ventilation (i.e., air conditioning) as a key factor contributing to both the bias and the variability in perso nal exposure. Air conditioning usage varies by i ndividuals and between cities. Use of air conditioning results in the introduction of less outdoor air to the indoors, resulting in the central

- site monitoring value overestimating exposure. In an epidemiolog ic al analysis, this condition causes the effect estimate to be biased towards the null, with some variability. Given the limiting condition that the maximum indoor concentration of ambient PM is that of the outdoors, the exposure error would not be expecte d to bias the effec t estimate away from the null. Moreover, Sarnat et al. (2009) d id not assert that the bias can go in either direction

. (e) Model specification

Commenters contend ed that the EPA did not account for the fact that “selecting an appropriate sta tistical model for epidemiologic studies of air pollution involves several choices that involve much ambiguity, scant biological evidence, and a profound impact on analytic results, given that many estimated associations are weak” (ACC, 2012, p. 5 ) For sho rt

- term ex posure studies

, the EPA recognizes, as summarized in the HEI review panel commentary that selecting a level of control to adjust for time

- varying factors, such as temperature, in time

- series epidemiologic studies involves a trade

- off (HEI, 2003). For example, if the model does not sufficiently adjust for the relationship between the health outcome and temperature, some effects of temperature could be falsely ascri bed to the pollution variable. Conversely, if an overly aggressive appro ach is used to control for temperature, the result would possibly underestimate the pollution

- related effect and compromise the ability to detect a small but true pollution effect ( U.S. EPA, 2004, p. 8

- 236; HEI, 2003, p. 266). The selection of approaches t o address such variables depends in part on prior knowledge and judgments made by the investigators, for example, about weather patterns in the study area and expected relationships between weather and other time

- varying factors and health outcomes conside red in the study. As demonstrated in s ection 6.5 of the ISA, the EPA thoroughly considered each of these issues and the overall effect of different model specifications on the association between short

- term PM 2.5 exposure and

mor tal ity. Regardless of the m odel employed, consistent positive associations were observed across studies that controlled for the potential confounding effects of time and weather using different approaches ( e.g., U.S. EPA 2009 a, Figure 6

- 27

, with additional details found in Appendix E, s ection E.3, T able E

- 16, ). The EPA also considered the influence of model specification in the examination ofDraft

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53 long

- term PM 2.5 exposure studies. For example, in s ection 7.6, Figures 7

- 6 and 7

- 7 , the ISA summarize d the collective evidence that evaluated t he association between long

- term PM 2.5 exposure and mortality. Regardless of the model used, these studies collectively found evidence of consistent positive associations between long

- term PM 2.5 exposure and mortality.

T he EPA , therefore, disagrees with commenters that model specification was not considered when evaluating the epidemiologic evidence used to form causality determinations. The EPA specifically points out that the process of assessing the scientific quality and relevance of e pidemiologic studies includ es examining “important methodological issues (e.g., lag or time period between exposure and effects, model specifications, thresholds, mortality displacement) related to interpretation of the health evidence ( U.S. EPA , 2009 a , p. 1

- 9).” Consistent with the conclusions of the 2004 PM AQCD, the EPA recognizes that there is still no clear consensus at this time as to what constitutes appropriate control of weather and temporal trends in short

- term exposure studies, and that no single statistical modeling approach is likely to be most appropriate in all cases ( U.S. EPA, 2004, p. 8

- 238). However, the EPA believes that the available evidence interpreted in light of these remaining uncertainties does provide increased confidence relative to the last review in the reported associations between short

- and long

- term PM 2.5 exposures and mortality and morbidity effects, alone and in combination with other pollutants.

(f) Shape of the concentration

- response r elationship

With regard to the C

- R relat ionship, commenters questioned the interpretation of the shape of the C

- R relationship, specifically stat ing that multiple studies have demonstrated that there is a threshold in the PM

- health effect relationship and that the log

- linear model is not biologi cally plausible ( API, 2012 pp. 17 to 20; API, 2012, Attachment 9; ACC, 2012, Appendix A, pp. 7 to 8) . The EPA disagrees with this assertion due to the number of studies evaluated in the ISA that continue to demonstrate a no

- threshold log

- linear model most adequately represents the PM concentration

- response relationship ( U.S. EPA, 2009a, s ection 2.4.3). W hile recognizing that uncertainties remain, the EPA believes that our understanding of this issue for both long

- and short

- term exposure studies has advanced since the last review. As discussed in the ISA , both long

- and short

- term exposure studies have employed a variety of statistical approaches to examine the shape of the concentration

- response function and whether a threshold exists

. While the EPA recogniz es that there likely are individual biologic thresholds for specific health responses, the ISA concluded the overall evidence from existing epidemiologic al studies do es not support the existence of thresholds at the population level, for effects associated with either long

- or short

- term PM exposures within the ranges of air quality observed in these studies (U.S. EPA, 2009a, section 2.4.3)

. While epidemiologic al analyses have not identified a population threshold in the range of air quality concentrations evaluated in the se studies, the EPA recognizes that it is possible that such thresholds exist toward s the lower end of these ranges (or below these ranges). This would be a concentration far lower than the level of theDraft

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54 revised annual standard. The ISA conc luded that this evidence collectively supported the conclusion that a no

- threshold, log

- linear model is most appropriate ( U.S. EPA, 2009a, sections 6.2.10.10, 6.5.2.7, and 7.6.4). CASAC likewise advised that “[a]lthough there is increasing uncertainty at l ower levels, there is no evidence of a threshold (Samet, 2010d, p. ii).

The EPA recognizes that some short

- term exposure studies have examined the PM C

- R relationship in individual cities or on a city

- to

- city basis and observed heterogeneity in the shape o f the C

- R curve across cities. As discussed in (b) above, these findings are a source of uncertainty that the EPA agrees requires further investigation. Nonetheless, the ISA concluded that “the studies evaluated further support the use of a no

- threshold, l og

- linear model, but additional issues such as the influence of heterogeneity in estimates between cities and the effects of seasonal and regional differences in PM on the concentration

- response

relationship still require further investigation” ( U.S. EPA, 2009a, p. 2

- 25).

(g) Relative toxicity of components

Some commenters highlighted uncertainties in understanding the role of individual constituents with in the mix of fine particles. These commenters asserted that a mass

- based standard may not be appropriate due to the growing body of evidence indicating that certain PM 2.5 components may be more closely related to specific health outcomes (e.g., elemental ca rbon ( EC ) and organic carbon ( OC ) ) (EPRI, 2012, p. 2).

With regard to questions about the role of individual constituents within the mix of fine particle s , as a general matter, the EPA recognizes that although new research directed toward this question ha s been conducted since the last review, important questions remain and the issue remains an important element in the Agency’s ongoing research program. At the time of the last review, the Agency determined that it was appropriate to continue to control fin e particles as a group, as opposed to singling out any particular component or class of fine particles (71 FR 61162 to 61164, October 17, 2006). This distinction was based largely on epidemiologic al evidence of health effects using various indicators of fi ne particles in a large number of areas that had significant contributions of differing components or sources of fine particles, together with some limited experimental studies that provided some evidence suggestive of health effects associated with high c oncentrations of numerous fine particle components.

In this review, as discussed in the proposal (77 FR 38922 to 38923) and in section III.E.1 preamble to the final rule , while most epidemiologic al studies continue to be indexed by PM 2.5 mass, several recent epidemiologic al studies included in the ISA have used PM 2.5 speciation data to evaluate health effects associated with fine particle exposures. In the ISA, the EPA thoroughly evaluated the scientific evidence that examined the effect of different PM 2.5 components and sources on a variety of health outcomes ( U.S. EPA , 2009a, section 6.6) and observed that the available information continues to suggest that many different chemicalDraft

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55 components of fine particles and a variety of different t ypes of source categories are all associated with, and probably contribute to, effects associated with PM 2.5
. The ISA concluded that the current body of scientific evidence indicated that “many constituents of PM can be linked with differing health effects and the evidence is not yet sufficient to allow differentiation of those constituents or sources that are more closely related to specific health outcomes” (U

. S

. EPA, 2009a, p. 2

- 26 and 6

- 212). Furthermore, the PA concluded that the evidence is not suffic ient to support eliminating any component or group of components associated with any specific source categories from the mix of fine particles included in the PM 2.5 indicator (U

. S

. EPA, 2009a, p. 2

- 56). CASAC agreed that it was reasonable to retain PM 2.5 a s an indicator for fine particles in this review as “[t]here was insufficient peer

- reviewed literature to support any other indicator at this time” (Samet, 2010c, p. 12).

This information is relevant to the Agency’s decision to retain PM 2.5 as the indicato r for fine particles as discussed in section III.E.1 of the preamble for the final rule . The EPA also believes that it is relevant to the Agency’s conclusion as to whether revision of the suite of primary PM 2.5 standards is appropriate. While there remain uncertainties about the role and relative toxicity of various components of fine PM, the current evidence continues to support the view that fine particles should be addressed as a group for purposes of public health protection and that “many constituents of PM can be linked with differencing health effects and the evidence is not yet sufficient to allow differentiation of those constituents or sources that are more closely related to specific health outcomes” such that it is inappropriate to remove any con stituent of PM 2.5 from the standard ( U.S. EPA

, 2009a, 2

- 17 ; U.S. EPA, 2011a, p. 2

- 25)

. In summary, in considering the above issues related to uncertainties in the underlying health science, on balance, the EPA believes that the available evidence interpret ed in light of these remaining uncertainties does provide increased confidence relative to the last review in the reported associations between long

- and short

- term PM 2.5 exposures and mortality and morbidity effects, alone and in combination with other p ollutants, and supports stronger inferences as to the causal nature of the associations. The EPA also believes that this increased confidence, when taken in context of the entire body of available health effects evidence and in light of the evidence from e pidemiologic al studies of associations observed in areas meeting the current primary PM 2.5 standards, specifically in areas meeting the current primary annual PM 2.5 standard, adds support to its conclusion that the current suite of PM 2.5 standards needs to be revised to provide increased public health protection from exposure to all types of PM 2.5
. (14) Comment : In asserting that there is no evidence of greater risk since the 2006 review to justify lowering the current annual PM 2.5 standard, some commenters argued that, “if the current primary PM 2.5 annual standard of 15 μg/m 3 was considered to be adequately protective of public health in 2006, given relative risk estimates that EPA was using at that time, then that standard would s urely still beDraft

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56 adequately protective of the public health if relative risk estimates remain at the same level (or lower)” (UARG, 2012, Attachment 1, p. 24). These commenters compared risk coefficients used for mortality in the EPA’s risk assessment done in the last review with those from the Agency’s core risk assessment done as part of this review, and they concluded that “the entire range of the core relative risk for long

- term mortality is lower now than it was in the prior review” (UARG, 2012, Attachmen t 1, p. 24). These commenters used this conclusion as the basis for a claim that there is no reason to revise the current annual PM 2.5 standard.

Response : The EPA believes that this claim is fundamentally flawed as it fails to take into account that exposu re to a pollutant causally associated at a population

level with premature mortality and serious illness has significant public health consequences, virtually regardless of the relative risk since exposure is, for all practical purposes, ubiquitous

. Moreov er, i n comparing the scientific understanding of the risk presented by exposure to PM 2.5 between the last and current reviews, one must examine not only the quantitative estimate of risk from those exposures (e.g., the numbers of premature deaths or increa sed hospital admissions at various concentrations), but also the degree of confidence that the Agency has that the observed health effects are causally linked to PM 2.5 exposure at those concentrations. As documented in the ISA and in the recommendations

an d conclusions of CASAC, the EPA recognizes significant advances in our understanding of the health effects of PM 2.5 , based on evidence that is stronger than in the last review because of its breadth and because it substantiates previously observed health e ffects. As a result of these advances, the EPA is now more certain that fine particles, alone or in combination with other pollutants, present a significant risk to public health at concentrations allowed by the current primary PM 2.5 standards. From this m ore comprehensive perspective, since the risks presented by PM 2.5 are more certain, similar or even somewhat lower relative risk estimates would not be a basis to conclude that no revision to the suite of PM 2.5 standards is “requisite” to protect public he alth with an adequate margin of safety. Th e comment also ignores that the relative risk estimate is only one factor considered by the Administrator . Most obviously, it ignores that epidemiological studies since the last review indicate associations between PM 2.5 and mor t ality and morbidity in areas meeting the current annual standard.
In any case, the commenters’ reliance on the flawed 2006 review is badly misplaced. As discussed in section III.A.2 above, the D.C. Circuit remanded Administrator Johnson’s 20 06 decision to retain the primary annual PM 2.5 standard because the Agency failed to adequately explain why the annual standard provided the requisite protection from both short

- and long

- term exposure to fine particles including protection for at

- risk pop ulations. The EPA

, in fact

, knows of no legitimate explanation. The 2006 standard was also at sharp odds with CASAC advice and recommendations as to the requisite level of protection (Henderson, 2006a,b). T he judgment of the then

- Administrator that the 200 6 primary annual PM 2.5 standard was requisite to protect public health with an adequate margin of safety is thus not precedential and is an in appropriate benchmark for the comparison drawn in the comments

.Draft

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57 (15) Comment: One group of commenters who argued that a revised annual standard was not necessary to protect the public health asserted that the proposed standard was “far more stringent that the standards in other industrialized countries” (NAM et al. , 2012, p.5). These commenters cited to standards set by th e European Union and Japan Ministry of the Environment . Id.

Response: In considering these comments, as discussed in Comment (3) in section II.B.1.a above, the EPA notes that the Administrator’s decision on setting an appropriate annual standard level is c onstrained by the provision of the CAA that requires that the primary NAAQS be requisite to protect public health with an adequate margin of safety. This requires that her judgment is to be based on an interpretation of the evidence that neither overstates nor understates the strength and limitations of the evidence, or the appropriate inferences to be drawn from the evidence. This is not the same legal framework that governs the standards set by the European Union or Japan.

As discussed in section III.E.4 .d of the preamble for the final rule, the Administrator has considered the epidemiological and other scientific evidence, estimates of risk reductions associated with just meeting alternative standards, air quality analyses, related limitations and uncert ainties, the advice of CASAC, and the extensive public comments on the proposal in reaching her conclusions regarding final decision on the appropriate primary PM 2.5 standard level s, consistent with the requirements of the CAA.

(16) Comment : Some of these commenters also identified “new” as well as older studies that had been included in prior reviews as providing additional evidence that the causality determinations presented in the ISA did not consider the totality of the scientific literatu re , further supporting the ir view that revision of the PM 2.5 NAAQS is inappropriate

. Response : As discussed in section II.B.3 of the preamble to the final rule and in section II.B.1.a above, the EPA notes that, as in past NAAQS reviews, the Agency is bas ing the final decisions in this review on the studies and related information included in the PM ISA that have undergone CASAC and public review, and will consider newly published studies for purposes of decision making in the next PM NAAQS review. Nonethe less, i n provisionally evaluating commenters’ arguments, the EPA notes that its provisional assessment of “new” science found that such studies did not materially change the conclusions reached in the ISA (U.S. EPA, 2012b).

2. Indicator

The EPA received comparatively few public comments on issues related to the indicator for fine particles. No public comments were submitted regarding the use of a different size cut for fine particles. Public comments from all major public and private sector groups received on the proposal were generally in favor of the EPA’s proposal to retain PM 2.5 as the indicator for fine particles. In addition to the responses contained inDraft

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58 s ection I II. E.1 of the preamble to the final rule, the EPA provides the foll owing responses to specific issues related to the indicator for fine particles.

(1) Comment: Some commenters emphasized the need to conduct additional research to more fully understand the effect of specific PM 2.5 components and/or sources on public health. Th ese commenters expressed views about the importance of evaluating health effect associations with various fine particle components and types of source categories as a basis for focusing ongoing and future research to reduce uncertainties in this area and f or considering whether alternative indicator(s) may be appropriate to consider in future PM NAAQS reviews for standards intended to protect against the array of health effects that have been associated with fine particles as indexed by PM 2.5 . For example, the PSR encouraged more research and monitoring related to PM 2.5 components and noted the importance of components associated with coal combustion (PSR, 2012, pp. 5 to 6). EPRI asserted that “new” studies support focusing on elemental carbon ( EC ) and organ ic carbon ( OC ) and encouraged the EPA to seriously consider the

mass

- based approach (EPRI, 2012, p. 2). Likewise, Georgia Mining Association (GMA) supported additional monitoring and research efforts related to PM 2.5 composition and specifically encouraged the evaluation of using particle number (e.g., particle count) (GMA, 2012, pp. 2 to 3). ALA et al. argued that causal conclusions of an European expert elicitation workshop (Knol et al., 2009) are stronger than the causal determinations reached in the ISA for ultrafine particles. These commenters suggested that “action is needed to establish ambient air quality standards for ultrafines in the next review cycle” (ALA et al., 2012, p. 21). One group of commenter stated “Further delay in moving the process fo rward of acquiring the necessary data and beginning the long process of establishing and implementing a standard for ultrafine particles/nano particles represents an unacceptable health risk to the nation” (Sammons, et al., 2012, p. 6).

Response: The Administrator agrees with these commenters that the results of additional research and monitoring efforts will be helpful for informing future PM NAAQS reviews. Section 2.5 of the PA highlighted areas for future health

- related research, model development, and data collection activities and recognized that “these efforts, if undertaken, could provide important evidence for information future PM NAAQS reviews, and, in particular, consideration of possible alternative indicators, averaging times, and/or levels ” (U.S. EPA, 2011a, p. 2

- 106). The EPA recognizes that i nformation from such studies could also help inform the development of strategies that emphasize control of specific types of emission sources so as to address particles of greatest concern to public health.

These views are consistent with comments offered by CASAC. In general, “CASAC urges the Agency to reinvigorate research that might lead to new indicators that my be more directly linked to the health ad welfare effects associated with ambient conc entrations of PM. CASAC also suggests the ongoing collection of more comprehensive PM monitoring data, including expanding the range of sizes to provide information in the ultrafine particle range, and adding measurements of numbers, chemistry, species, an d related emissionsDraft

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59 characteristics of particles” (Samet, 2010d, p. iii). More specifically, CASAC asserted that “PM 2.5 has been a useful surrogate index since it was adopted in the 1997 PM NAAQS promulgation, but may become an increasingly inadequate inde x of health risk as the mass concentration limits are reduced...While research evidence on PM and health has evolved, we urge the Agency to undertake additional efforts to leverage the gains made thus far. Now is the time to look ahead to future review cycle s and reinvig orate support for the development of evidence that might lead to newer indicators that may correlate better with the health effects associated with ambient air concentrations of particulate matter (PM) and for more comprehensive PM monitoring data, including expanding the range of sizes, and adding measurements of numbers, chemistry, species, and related emissions characteristic s of particles. There is an inherent feedback in the cycle from res e arch to policy formulation whereby researchers use the monitoring data that are gathered primarily for regulatory purposes with available indicators, and, in turn, expand the scientific basis for regulation. If EPA initiates efforts with air pollution research and monitoring communities now to create a mo re robust monitoring platform for research, the Agency will be better positioned to make an evidence

- based transition to the ‘next generation’ of indicators of PM

- related health risks ” (Samet, 2010c, p. 2).

See also response to comment (13)(g) in section I I.B.1.b above.

3. Averaging Time

The EPA received few comments on the issue of averaging time for the PM 2.5 primary standards. One specific significant comment is addressed below.

(1) Comment: As discussed in section III.E.2 of the preamble to the final rule, the EPA received no significant comments on the appropriateness of either the 24

- hour or annual averaging times for the PM 2.5 primary standards. However, one group representing several States (i.e., NESCAUM, 2012) suggested consideration of a rolling 24

- ho ur average, rather than a midnight

- to

- midnight 24

- hour average, for the 24

- hour PM 2.5 standard. In justifying this recommendation, NESCAUM noted that using a rolling 24

- hour average, rather than the current midnight

- to

- midnight average, “would be particula rly helpful in providing better public health protection in areas where there is the potential for seasonal overnight PM 2.5 events (e.g., from woodsmoke).”

Response: The EPA agrees with NESCAUM that it is appropriate in this review to increase public heal th protection against exposures to PM 2.5 . As discussed in the preamble to the final rule (section III.E.4.c.ii), the Administrator has judged it appropriate to achieve such an increase in public health protection by lowering the level of the annual PM 2.5 s tandard and retaining the current 24

- hour PM 2.5 standard. These judgments reflect in large part the Administrator’s consideration of ambient PM 2.5 concentrations in the locations where long

- term and short

- term PM 2.5 health studies have been conducted. The PM 2.5 concentrations reported in these study locations are based on midnight

- to

- midnight sampling.Draft

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60 Altering the sampling time period for the 24

- hour PM 2.5 standard, as suggested by these commenters, would alter the PM 2.5 concentrations reported and, thus, would alter the degree of health protection provided by the 24

- hour standard. As discussed in section II.A of the preamble to the final rule, the CAA charges the Administrator with setting NAAQS that are “requisite” (i.e., neither more nor less stringent than necessary) to protect public health with an adequate margin of safety . In setting such standards, the Administrator must weigh the available scientific evidence and information, including associated uncertainties and limitations

. I n reaching her propo sed decisions on the PM 2.5 standards that would provide “requisite” protection , the Administrator carefully considered the available scientific evidence and risk information , making public health policy judgments that , in her view, neither overstate d nor u nderstate d the strengths and limitations of that evidence and information. Commenters have not provided new information or analyses to support the appropriateness of the changes in public health protection that could result from their recommended alteratio ns in the sampling time period.

4. Form

The EPA received a number of public comments on the appropriate forms for the PM 2.5 standards , primarily related to the spatial averaging provisions within the form of the annual standard

. Few public commenters commented specifically on the form of the 24

- hour standard. None of the public commenters raised objections to continuing the use of a concentration

- based form for the 24

- hour standard

. Incorporating responses contained in sections II I

. E.3.a and III.E.3.b of the preamble to the final rule, the EPA provides the following responses to specific comments related to the form of (i) the annual PM 2.5 standard and (ii) the 24

- hour PM 2.5 standard.

a. Annual Standard

(1) Comment: Of the comme nters noted in section III.D.2 of the preamble to the final rule and in section II.B.1.a above who supported a more stringent annual PM 2.5 standard, those who commented on the form of the annual PM 2.5 standard supported the EPA’s proposal to eliminate the spatial averaging provisions. T hese commenters contended that the EPA’s analyses of the potential impacts of spatial averaging, discussed in section III.E.3.a of the preamble to the final rule

, demonstrated that the current form results in uneven public health protection leading to disp roportionate impacts on at

- risk populations. Specifically, the ALA and other environmental and public health commenters contended that “spatial averaging allows exposure of people to unhealthy levels of pollution at specific locales even within an area mee ting the standard” (ALA et al., 2012, p. 23). These commenters particularly focused on the importance for low

- income and minority populations of eliminating the spatial averaging provisions. They concluded that spatial averaging “is an environmental justic e concern because poor people are more likely to live near roads, depots, factories, ports, and other pollutionDraft

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61 sources.” Id. p. 24. ALA et al. further asserted that “in order for EPA to meet its Environmental Justice and Clean Air Act requirements dictati ng that all Americans be protected from environmental health concerns, spatial averaging must be removed” Id . p. 25.

Other commenters (e.g., AAM, 2012; Dow, 2012) also supported the elimination of spatial averaging in order to “avoid potential disproportionate impacts on at

risk populations” and to maximize “the benefits to public health of reducing the annual PM 2.5 standard.” However, these groups expressed concern that the elimination of spatial averaging, in combination with the requirement f or near road monitors (as discussed in section VIII.B.3.b.i of the proposal), would effectively and inappropriately increase the stringency of the annual PM 2.5 standard.

This concern was also shared by other commenters who disagreed with the elimination o f spatial averaging. For example, the Class of ’85 RRG emphasized concerns about increasing the stringency of the standard while providing few health benefits if spatial averaging is eliminated, particularly in combination with the requirement for near

- roa d monitors. These commenters contended that “[b]ecause EPA proposes to use the readings from the highest single worst case monitor (rather than the average of all community area monitors), and since roadway monitoring locations will likely be worst case mo nitors, the proposed NAAQS will become more stringent without targeting the PM 2.5 species most harmful to human health” (Class of ’85 RRG, 2012, p. 6). Other commenters argued that “unless the Agency adjusts the level of the NAAQS to account for the differ ence in concentrations at the community

- based monitors used to set the standard and those at near

- roach monitors, use of the latter to judge compliance with the NAAQS would be unreasonable” (API, 2012, p. 58).

Several commenters also ma intained that becau se spatial averaging is consistent with how air quality data are considered in the underlying epidemiological studies, such averaging should not be eliminated. Specifically, commenters including NAM et al. , AFPM, API, and ACC pointed out that PM 2.5 epidemi ological studies use spatially averaged multi

- monitor concentrations, rather than the single highest monitor, when evaluating health effects. Therefore, these commenters contended that allowing spatial averaging would make the PM 2.5 standard more consistent with the approaches used in the epidemiological studies upon which the standard is based. One commenter argued that averaging measurements across multiple monitors in an area “would almost certainly also have included monitors in areas in which minorities and low

- income individuals reside. Therefore, their potentially higher exposures would have been addressed in the epidemiological studies” (API, 2012

, pp. 2 4 to 25). Thus, this commenter asserted that elimination of spatial averag ing is not warranted.

In addition, some commenters contended that the EPA failed to consider whether modifying, rather than eliminating, the constraints on spatial averaging would have been sufficient to protect public health. If so, th ese commenter s argue d thatDraft

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62 “elimination of spatial averaging would go beyond what is requisite to protect the public health” (NAM et al., 2012, p. 20)

. Response: In considering the public comments on the form of the annual standard, the EPA recognizes a number of commenters a greed with the basis for the EPA’s proposal to eliminate spatial averaging. While other commenters expressed disagreement or concern with the proposed decision to eliminate the spatial averaging provisions, the A gency notes that these comment er s did not ch allenge the analyses or considerations that provided the fundamental basis for the Administrator’s propos ed decision

. These unchallenged analyses indicate that public health would not be protected with an adequate margin of safety in all locations , as requ ired by law, if disproportionately higher exposure concentrations in at

- risk populations such as low income communities as well as minority communities were averaged together with lower concentrations measured at other sites in a large urban area. Moreover, the Agency’s concern over possible disproportionate PM 2.5 - related health impacts in at

- risk populations extends to populations living near important sources of PM 2.5 , including the large populations that live near major roadways.

Rather than ad dressing these analyses specifically , these commenters generally raised concerns that eliminating the option for spatial averaging would increase the stringency of the standard

. The EPA notes that CASAC agreed that it was “reasonable” for the EPA to elimin ate the spatial averaging provisions (Samet, 2010d, p. 2). Further, in CASAC’s comments on the first draft PA, it noted, “Given mounting evidence showing that persons with lower SES levels are a susceptible group for PM

- related health risks, CASAC recommen ds that the provisions that allow for spatial averaging across monitors be eliminated for the reasons cited in the (first draft) Policy Assessment” (Samet, 2010c, p. 13). In its review of the second draft PA, CASAC recognized that “although much of the epi demiological research has been conducted using community

- wide averages, several key studies reference the nearest measurement site, so that some risk estimates are not necessarily biased by the averaging process. Further, the number of such studies is like ly to expand in the future” (Samet, 2010d, pp. 1 to 2).

In considering CASAC advice and public comments, the EPA notes that the stringency or level of protection provided by each NAAQS is not based solely on the form of the standard; rather, the four eleme nts of the standard that together serve to define each standard (i.e., indicator, averaging time, form, and level) must be considered collectively in evaluating the protection afforded by each standard

. , including the protection afforded to at

- risk populat ions . Therefore, the EPA considers these comments are appropriate to discuss collectively with other issues related to the appropriate level for the annual standard as discussed in section III.E.4.c

- d of the preamble and in section II.B.5.c below.

The EPA note s further that this issue is similar to the issue of whether to base compliance with the standard on use of a maximum monitor or composite monitors. As explained in responses addressing that parallel issue

, the EPA’sDraft

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63 analysis of nationwide air quality patterns indicates that in many instances there is no difference at all, or minor difference, between maximum monitor results and those from composite monitors ( Frank

, 2012a

. )

. Further, there were only a few other areas in which the maximum monitor mean concentration was appreciably higher than the composite monitor mean concentration, such as areas in which some monitors may be separately impacted by local sources. There were on ly 10 such areas in the country in which the maximum monitor mean concentration was between 2 to 6 μg/m 3 higher than the composite monitor concentration (Frank, 2012a, Table 4 ) Thus, the EPA does not agree that there is a significant difference between com

posite monitor mean PM 2.5 concentrations and maximum monitor mean PM 2.5 concentrations in the large major ity of areas across the country such that implementation of the standard on a maximum monitor basis , or without the option of spatial averaging, provid es more protection than is requisite due to some inconsistency with key underlying epidemiologic studies.

B ased on the analyses done to inform consideration of the form of the standard (Schmidt, 2011, Analysis A), as well as the nationwide analysis of com posite and maximum monitor values just discussed, the EPA concludes that spatial averaging (or a composite monitor approach) does not provide a margin of safety for the at

risk populations that live around the monitor measuring the highest concentration,

s uch as in those few areas in which the maximum monitor concentration is appreciably higher than the composite monitor concentration. Thus, the comment that eliminating spatial averaging makes the standard more stringent misstates the issue. The proper ques tion is what level of protection is requisite with an adequate margin of safety. If the standard needs to be made more stringent to provide such protection, then such stringency is not only permissible but required (or “appropriate” in the words of section 109 (d)). Diluting the needed protection by averaging monitoring results can result in potentially disproportionate impacts on
at

- risk populations and so would fail to carry out the core statutory requirement to provide requisite protection to public heal th with an adequate margin of safety

. 18

(2) Comment: One commenter argued that the rationale to support elimination of spatial averaging to potentially avoid disproportionate impacts on at

- risk populations is flawed because the “ evidence for greater susceptibility from PM
exposures in these populations is weak” (API, 2012, Attachment 1, p p. ES

- 2 ). Furthermore, this commenter asserted that the “evidence presented in the ISA and summarized in the PA and Proposed Rule in support of increased susceptibili ty to PM among children, older adults, those with pre

- existing heart and lung diseases, and those of lower SES is limited and inconsistent. This evidence does not add to the understanding or identification of susceptible populations, and it should not be

18 As noted in section II.A of the preamble to the final rule, The legislative history of section 109 indicates that a primary standard is to be set at “the maximum permissible ambient air level . . . which will protect the health of any [sensitive] group of the population,” and that for this purpose “reference should be made to a representative sample of persons comprising the sensitive group rather than to a single person in such a group.” S. Rep. No. 91

- 1196, 91st Cong., 2d Sess. 10 (1970).Draft

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64 u sed to support changes to the form of the annual PM 2.5 standard” (API, 2012, Attachment 1, p. 47).

Response: The EPA strongly disagrees with the commenter ’ s conclusion regarding the evidence for populations at increased risk for PM

- related health effects. Chapter 8 of the ISA discusses the available evidence regarding at

- risk populations

. and why children, older adults, those with pre

- existing heat and lung diseases, and those of lower SES are legitimately regarded as at

- risk

. For example, “[o]lder adults represent a potentially susceptible population due to the higher prevalence of pre

- existing cardiovascular and respiratory diseases found in this age range compared to younger age groups.” (U.S. EPA

, 2009 a , p. 8

- 3 )

. Results of epidemiologic al and toxicolo gical studies support this conclusion, and indicate as well increased susceptibility of older adults to all

- cause mortality from short

- term exposure, and increased susceptibility to respiratory morbidity and mortality. Id. at pp. 8

- 4 to 5. Children have g enerally been considered more susceptible to PM exposure due to factors such as more time spent outdoors, greater activity levels, exposures resulting in higher doses per body weight and long surface area, and the possibility of irreversible effects on the developing respiratory system. Id. p. 8

- 5.

Two drafts of the ISA drawing these conclusion s with regard to at

- risk populations were reviewed by CASAC and by the public , and these same comments were before CASAC as part of that public comment process . CASAC found the “organization and presentation” of the evidence for at

- risk populations presented in the ISA to be “complete, clear, and well

- organized” (Samet, 2009f, p. 12). Furthermore, CASAC found that the “data presented fully justifies consideration of lo wer socioeconomic status (SES) people as a susceptible group” (Samet, 2010c. p. 11).

(3) Comment: Some commenters asserted that elimination of spatial averaging from the form of the annual standard “does not excuse EPA’s obligation under the CAA to set standards that explicitly incorporate a margin of safety” (ALA et al., 2012, p. 25).

Response: The E PA agrees with the commenters that setting a standard that provides protection with an adequate margin of safety is not limited to considering the protection afforded by the form of the standard alone. As noted in section III.E.3. i of the preamble to the f inal rule, the EPA notes that the stringency or level of protection provided by each NAAQS is not based solely on the form of the standard, rather, the four elements of the of the standard that together serve to define each standard (i.e., indicator, avera ging time, form, and level) must be considered collectively in evaluating the protection afforded by each standard. As discussed in section III.E.4, the EPA Administrator’s conclusions on the appropriate indicator, averaging time, form, and level are consi dered together in reaching her final decision on the appropriate annual standard that will provide requisite public health protection with an adequate margin of safety.Draft

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65 b. 24

- Hour Standard

(1) Comment: Many of the individuals and groups who supported a more strin gent 24

- hour PM 2.5 standard noted in section III.D.2 of the preamble to the final rule and in section II.B.1.a above , however, recommended a more restrictive concentration

- based percentile form, specifically a 99 th percentile form. The limited number of th ese commenters who provided a specific rationale for this recommendation generally expressed their concern that the 98 th percentile form could allow too many days where concentrations exceeded the level of the standard, and thus fail to adequately protect public health. Other public commenters representing s tate and local air agencies and industry groups generally supported retaining the current 98 th percentile form. In most cases, these groups expressed the overall view that the current 24

- hour PM 2.5 stand ard, including the form of the current standard, should be retained.

Response: The EPA notes that the viewpoints represented in this review are similar to comments submitted in the last review and through various NAAQS reviews. The EPA recognizes that the selection of the appropriate form includes maintaining adequate protection against peak 24

- hour values while also providing a stable target for risk management programs, which serves to provide for the most effective public health protection in the long ru n. 19

As discussed in section III.E.3.b of the preamble to the final rule, the PA considered air quality data reported in 2000 to 2008 to update our understanding of the ratio between peak

- to

- mean PM 2.5 concentrations. This analysis provided evidence that th e 98 th percentile value was a more stable metric than the 99 th percentile ( U.S. EPA, 2011a, Figure 2

- 2, p. 2

- 62). The EPA may legitimately consider such stability in considering the form of a NAAQS. See American Trucking Ass ociation v. EPA , 283 F. 3d at 37 4

- 75. In retaining the 98 th percentile form, the Administrator focused on the relative stability of the 98 th percentile form as a basis for her decision, while recognizing that the degree of public health protection likely to be afforded by a standard is a result of the combination of the form and level of the standard.

5. Level

A large number of comments on the pr oposed levels for the primary PM 2.5 standards basically expressed one of two substantively different views

. As explained in section III.D.2 of the preamble to the final rule and in sections II.A and II.B.1 above, one group of commenters generally opposed a ny change to the current primary PM 2.5 standards and more specifically disagreed with the basis for the EPA’s proposal to revise the annual standard level. Another group of commenters supported revising the current

19 As noted in section III.E.3.b of the preamble to the final rule, it is legitimate for the EPA to consider promotion of overall effectiveness of risk management programs designed to attain the NAAQS, including their overall stability, in setting a standard that is requ isite to protect the public health. The context for the court’s discussion in ATA III is identical to that here; whether to adopt a 98 th percentile form for a 24

- hour standard intended to provide supplemental protection for a generally controlling annual s tandard.Draft

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66 suite of primary PM 2.5 standards to provi de increased public health protection. Some commenters in this second group argued that both the annual and 24

- hour standard levels should be lowered while other commenters in this group agreed with the EPA’s proposal to retain the level of the 24

- hour sta ndard in conjunction with revising the level of the annual standard.

Many of these commenters simply expressed their views without stating any rationale, while others gave general reasons for their views but without reference to the factual evidence or ra tionale presented in the proposal notice as a basis for the Agency’s proposed decision regarding the levels of the primary PM 2.5 standards. A number of commenters, including many environmental and public health organizations as well as

s tate and local air agencie s and health departments and t ribes, who supported the revising the standard level s generally placed great weight on the recommendation s of CASAC. Section s III.D.2 and I I I. E.4.c of the preamble to the final rule present the Agency’s response to thes e very general views. In addition to the discussion contained in th ose section s , the EPA provides the following responses to specific issues related to the levels for the primary PM 2.5 standards. This includes comments on the general approach used by the E PA to translate the available scientific information into standard levels and how specific PM 2.5 exposure studies should be considered as a basis for the standard level s.

a. Annual Standard

i. Support for Retaining the Current Level

The group of commenters opposed to any change to the current suite of primary PM 2.5 standards generally raised questions regarding the underlying scientific evidence, including the causal determinations reached in the ISA, and focused strongly on the uncertainties they saw in the scientific evidence as a basis for their conclusion that no changes to the current standard levels were warranted. In commenting on the proposed standard levels, these commenters typically relied on the arguments summarized and addressed in section III.D. 2 of the preamble to the final rule and in section II.B.1.b above as to why they believed it was inappropriate for the EPA to make any revisions to the suite of primary PM 2.5 standards. That is, they asserted that the EPA’s causal determinations were not a dequately supported by the underlying scientific information; the biological plausibility of health effects observed in epidemiologic al studi es has not been demonstrated in controlled human exposure and toxicological studies ; uncertainties in the underlyin g health science are as great or greater than in 2006; there is no evidence of greater risk since the last review to justify tightening the current annual PM 2.5 standard; and “new” studies not included in the Integrated Science Assessment continue to incre ase uncertainty about possible health risks associated with exposure to PM 2.5
. With regard to the level of the annual standard, these commenters strongly disagreed with the Agency’s proposed decision to revise the level to within a range of 12 to 13 μg/m 3 and argued that the current standard level of 15 μg/m 3 should be retained

. For example, UARG, API, and other commenters in this group raised a number of issues that they asserted called into question the EPA’s interpretation of the epidemiological evidenc e to support revising the annual standard level. These commenters raised specificDraft

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67 questions related to the general approach used by the EPA to translate the air quality and other information from specific epidemiological studies into standard levels which are discussed in section III.E.4.c.i of the preamble to the final rule , including:

the EPA’s approach for using composite monitor air quality distributions reported in epidemiological studies to select a standard level that would be compared to
measurement s at the monitor recording the highest value in an area to determine compliance with the standard; the appropriate exposure period for effects observed in long

- term exposure mortality studies; and

the use of the EPA’s analysis of distribution s of underlyi ng population

- level data (i.e., health event and study population data) for those epidemiological studies for which such information was available.
These commenters also raised questions regarding the EPA’s consideration of specific scientific evidence as a basis for setting a standard level, including :
evidence of respiratory morbidity effects in long

- term exposure studies and more limited evidence of health effects which have been categorized in the ISA as suggestive of a causal relationship (i.e., developmental and reproductive outcomes )

These comments and other comments are discussed below

. (1) Comment: Some commenters in this group argued that one reason why they believe there is no basis for setting a standard level below 15 μg/m 3 is that the air
qua lity metric from epidemiological studies that the EPA relied on in the proposal is not the same metric that will be compared to the level of the standard to determine compliance with the standard. That is, commenters noted that the long

term mean PM 2.5 concentrations that the EPA considered, shown in Figure 4 above, are composite monitor mean concentrations (i.e., concentrations averaged across multiple monitors within areas with more than one monitor), whereas the PM 2.5 concentrations that will be comp ared to the level of the standard are maximum monitor concentrations (i.e., the concentration measured by the monitor within an area reporting the highest concentration). This comment was presented most specifically in UARG’s comments (UARG, 2012, Attachme nt 1, pp. 2 to 6), which raised two overarching issues as discussed below.
First, the commenter noted that the EPA’s approach of considering composite monitor mean PM 2.5 concentrations in selecting a standard level, and then comparing the maximum monitor m ean PM 2.5 concentration in each area to the standard level when the standard is implemented, was characterized in the proposal as inherently having the potential to build in a margin of safety (UARG, 2012, Attachment 1, p. 4, citing 77 FR 38905). The comme nter asserted that the Administrator is ignoring this distinction between composite and maximum monitor concentrations, and that this approach creates an unwarranted case for lowering the standard level, since in the commenter’s view, it would result in aDraft

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68 margin of safety that would be arbitrary, not based on evidence, and unquantified (UARG, 2012, Attachment 1, p. 4). In support of this view, the commenter asserted that there is a significant difference between composite monitor mean PM 2.5 concentrations a

nd maximum monitor mean PM 2.5 concentrations. The commenter asserted that the maximum monitor value will always be higher than the composite monitor value (except in areas that contain only a single monitor), such that when an area just attains the NAAQS, that area’s composite monitor long

- term mean PM 2.5 concentration will be lower than the level of the standard (UARG, 2012, Attachment 1, p. 3).
Second, the commenter asserted that a more “reasoned and consistent approach would be to decide on a mean compos ite monitor PM 2.5 level that should be achieved and then identify the maximum monitor level that would result in that composite value” (UARG, 2012, Attachment 1, p. 4). The commenter conducted an analysis of maximum monitor versus composite monitor annual mean PM 2.5 concentrations using monitoring data 20 from 2006 to 2008 and presented results averaged across areas within two groups (i.e., those with design values 21 above the current standard level and those with design values just below the current standard level) to illustrate their suggested alternative approach. The commenter interpreted this analysis as showing that the composite monitor long

- term mean PM 2.5 concentrations from the subset of the epidemiological studies shown in Figure 4 (of the proposal a nd above) that the commenter considered to be an appropriate focus for this analysis would be achieved across the U.S. if the current annual NAAQS of 15 μg/m 3 is retained and attained

. The commenter considered the subset of epidemiological studies that inc luded only long

- term exposures studies of effects for which the evidence is categorized as causal or likely causal, but did not consider short

- term exposure studies. On this basis, the commenter asserted that attaining the current annual PM 2.5 standard wou ld result in composite monitor long

- term mean concentrations in all areas that would be generally within or below the range of the composite monitor long

- term mean concentrations from such studies and, as a result, there is no reason to lower the level of the current annual NAAQS.

Response: In considering the first issue related to the EPA’s approach, the EPA notes that in proposing to revise both the form and level of the annual standard, the Administrator clearly took into account the distinction between the composite monitor long

- term mean PM 2.5 concentrations from the epidemiological studies, considered as a basis for selecting an annual standard level, and maximum monitor long

- term mean PM 2.5 concentrations. In deciding to focus on the composite monitor long

- term mean concentrations in selecting the standard level, and on the maximum monitor concentrations in selecting the form of the standard (i.e., consistent with proposing to eliminate the option for spatial averaging across

20 The commenter indicated that this analysis was based on monitoring data for every core based statistical area (CBSA) in the EPA’s Air Quality System (AQS) database.
21 The design value is the air quality statistic that is compared to the level of the NAAQS to determine the attainment status of a given area

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69 monitors within an area when implementing the standard 22 ), the Administrator reasonably considered the distinction between these metrics in a manner that was consistent with advice from CASAC (Samet et al., 2010d, pp. 2 t o 3).

As noted in section III.A.3 of the preamble to the final rule , the EPA recognizes that a statistical metric (e.g., the mean of a distribution) based on maximum monitor concentrations may be identical to or above the same statistical metric based on c omposite monitor concentrations. More specifically, many areas have only one monitor, in which case the composite and maximum monitor concentrations are identical. Based on the most recent data from the EPA’s AQS from 2009 to 2011 in the 331 CBSAs in which valid PM 2.5 data are available, as discussed in Frank (2012a, Table 5), there were 20 8 such areas (with design values ranging up to about 15 μg/m 3 ). Frank (2012a) also observed that other areas have multiple monitors with composite and maximum monitor mea n PM 2.5 concentrations that were the same or relatively close, with 5 7 areas in which the maximum monitor mean concentration was no more than 0.5 μg/m 3 higher than the composite monitor mean concentration and 56 areas in which the difference was between 0. 6 and 2 μg/m 3 . Further, there were only a few other areas in which the maximum monitor mean concentration was appreciably higher than the composite monitor mean concentration, such as areas in which some monitors may be separately impacted by local sources . There were only 10 such areas in the country in which the maximum monitor mean concentration was between 2 to 6 μg/m 3 higher than the composite monitor concentration (Frank, 2012a, Table 4). 23 Thus, the EPA does not agree that there is a significant diffe rence between composite monitor mean PM 2.5 concentrations and maximum monitor mean PM 2.5 concentrations in the large majority of areas across the country.

In proposing to revise the form of the annual PM 2.5 standard, as discussed in section III.E.3.a of th e preamble to the final rule, the EPA noted that when an annual PM 2.5 standard was first set in 1997, the form of the standard included the option for averaging across measurements at appropriate monitoring sites within an area, generally consistent with t he composite monitor approach used in epidemiological studies, with some constraints intended to ensure that spatial averaging would not result in inequities in the level of protection for communities within large metropolitan areas. In the last review the EPA tightened the constraints on spatial averaging, and in this review has eliminated the option altogether, on the basis of analyses in each review that showed that such constraints may be inadequate to avoid substantially greater exposures for people li ving in locations around the monitors recording the highest PM 2.5 concentrations in some areas, potentially resulting in disproportionate impacts on at

- risk populations of persons with lower SES levels as well as minorities . In light of these analyses, and consistent with the Administrator’s decision to revise the form

22 As discussed in section III.E.3.a of the preamble to the final rule and in response to comment (1) in section II.B.4.a above.
23 The average difference between the maximum and composite design value among the 123 CBSAs with two or more monitors is 0.8 μg/m 3 and the median difference is 0.6 μg/m 3 . The 25 th and 75 th percentiles are 0.3 and 1.0 μg/m 3 , respectively (Frank, 2012a, p. 4).Draft

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70 of the annual PM 2.5 standard by eliminating the option for spatial averaging, the EPA continues to conclude that a standard level based on consideration of long

term mean concentrations from composite monitors, and applied at each monitor within an area including the monitor measuring the highest concentration, is the appropriate approach to use in setting a standard that will protect public health, including the health of at

- risk populations, with an adequate margin of safety, as required by the CAA.

The EPA acknowledges that at proposal, the Agency characterized the approach of using maximum monitor concentrations to determine compliance with the standard, while selecting the standard level b ased on consideration of composite monitor concentrations, as one that inherently had the potential to build in a margin of safety (77 FR 38905), and CASAC reiterated that view in supporting the EPA’s approach (Samet, 2010d, p. 3). Nonetheless, in light of the analysis discussed above, the EPA more specifically recognizes that this approach does not build in any margin of safety in the large number of areas across the country with only one monitor. Further, based on the analyses done to inform consideration of the form of the standard (Schmidt, 2011, Analysis A), the EPA concludes that this approach does not provide a margin of safety for the at

- risk populations that live around the monitor measuring the highest concentration, such as in those few areas in w hich the maximum monitor concentration is appreciably higher than the composite monitor concentration. Rather, this approach properly treats those at

risk populations the same way it does the broader populations that live in areas with only one monitor, by providing the same degree of protection for those at

risk populations that would otherwise be disproportionately impacted as it does for the broader populations in other areas, While the EPA recognizes that this approach can result in some additional marg in of safety for the subset of areas with multiple monitors in which at

- risk populations may not be disproportionately represented in areas around the maximum monitor, which may be the case in areas with relatively small differences between the maximum and composite monitor concentrations, the EPA notes that this margin would be relatively small in such areas.
Based on the above considerations, the EPA does not agree that the Agency’s approach of using maximum monitor concentrations to determine compliance with the standard, while selecting the standard level based on consideration of composite monitor concentrations creates an unwarranted case for lowering the standard level based on a margin of safety that would be arbitrary, not based on evidence, or lack quantification. The EPA recognizes that setting a standard to protect public health, including the health of at

- risk populations, with an adequate margin of safety, depends upon selecting a standard level sufficiently below where there is clear evidence o f health effects so as to provide such protection, and that the EPA’s approach regarding consideration of composite and maximum monitor concentrations is intended to, and does, serve to address this requirement as part of and not separate from the selectio n of an appropriate standard level and form based on the health effects evidence.Draft

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71 In considering the second issue related to the commenter’s suggested alternative approach, the EPA strongly disagrees with the commenter’s view that a more “reasoned and cons istent approach would be to decide on a mean composite monitor PM 2.5 level that should be achieved and then identify the maximum monitor level that would result in that composite value” (UARG, 2012, Attachment 1, p. 4). As discussed above, the EPA notes th at for areas with only one monitor, or with multiple monitors that measure concentrations that are very close in magnitude, the maximum monitor level that would limit the composite monitor PM 2.5 level to be no greater than the level that should be achieved to protect public health with an adequate margin of safety, would essentially be the same as that composite monitor level. Further, as discussed above, even for areas in which the maximum monit or concentration is appreciably higher than other monitor concentrations within the same area, public health would not be protected with an adequate margin of safety if the disproportionately higher exposures of at

risk, susceptible populations around the monitor measuring the highest concentration were in essence averaged away with measurements from monitors in other locations within large urban areas. Further, the commenter’s suggested approach would be based on annual average PM 2.5 concentrations that ha ve been measured over some past time period. Such an approach would reflect the air quality that existed in the past, but it would not necessarily provide appropriate constraints on the range of concentrations that would be allowed by such a standard in th e future, when relationships between maximum and composite monitor concentrations in areas across the country may be different. For these reasons, the EPA fundamentally rejects the commenter’s suggested approach because it results in a standard that demons trably would not protect public health, including providing protection for at

- risk populations, with an adequate margin of safety in areas across the country.
More specifically, in further considering the commenter’s analysis of design values based on maximum versus composite monitor annual mean PM 2.5 concentrations using monitoring data from 2006 to 2008 which they assert supports retaining the current standard level of 15 μg/m 3 , the EPA finds flaws with the numerical results and the scope of the analy sis, as well as flaws in the commenter’s translation of the analysis results into the basis for selecting an annual standard level.
In considering the commenter’s analysis, the EPA notes that the analysis compared maximum versus composite monitor annual me an PM 2.5 concentrations, averaged over 3 years, for two groups of areas: (1) areas with design values that exceed the current annual standard level (i.e., greater than 15.0 μg/m 3 ) and (2) areas with design values that are just attaining the current annual standard (i.e., between 14.5 and 15.0 μg/m 3 ). 24 The commenter indicated that they

24 For the first group of areas (which included 33 areas), this analysis calculated an average across the areas of maximum monitor annual mean PM 2.5 concentrations, averaged over 3 years, of 17.2 μg/m 3 compared to an average of composite monitor concentrations of 14.3 μg/m 3 . For the second group of areas (which includ ed 11 areas), this analysis calculated an average across the areas of maximum monitor annual mean concentrations, averaged over 3 years, of 14.8 μg/m 3 compared to an average of composite monitorDraft

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72 used the full body of PM 2.5 monitoring data from the EPA’s AQS database (UARG, 2012, Attachment 1, p. 4 )

. In attempting to reproduce the commenter’s results, the EPA repeated the calculations using only valid air quality data (i.e., data that meet data completeness and monitor siting criteria) from the AQS database for the same time period (Frank, 2012a). 25 Based on this corrected analysis, the EPA finds that the composite monit or concentrations averaged across the areas within each group are somewhat higher than those calculated by the commenter, and the average differences between the maximum and composite monitor concentrations are somewhat smaller (Frank, 2012a, Table 3). 26 No tably, the difference between the maximum and composite monitor average concentrations for the second group of areas is substantially reduced in the corrected analysis, such that the difference (averaged across the 10 areas with valid data in the second gr oup) is approximately 0.5 μg/m 3 , not 1.2 μg/m 3 as in the commenter’s analysis. In addition, the commenter’s analysis compared the average of the composite monitors to the average of the maximum monitors for each subset of areas. This comparison of averages across all the areas in each subset masks the fact that the large majority of areas across the country have only one monitor, with the composite monitor and maximum monitor values the same for such areas, and many other areas have a maximum monitor value that is close to the composite monitor value. As discussed above, these circumstances have a major impact on the protection that would be achieved by the approach suggested by the commenter.
With regard to the scope of the commenter’s analysis, the EPA fin ds that by limiting the scope to a small subset of areas with design values above or just below the current annual standard level of 15 μg/m 3 , the analysis ignores the large number of areas across the country with lower design values that are relevant to

c onsider in light of the epidemiological evidence of serious health effects at concentrations lower than 15 μ g/m 3 , well below the level of the current standard.

In translating its analysis results into the basis for selecting an annual standard level, the c ommenter’s translation is premised on the view that the “natural focal point” for setting an annual PM 2.5 standard level should be somewhere within the range of the long

- term mean PM 2.5 concentrations from the subset of epidemiological studies that include d only long

- term exposure studies of effects for which the evidence is categorized as causal or likely causal, but not for effects

concentrations of 13.6 μg/m 3 (UARG, 2012, Attachment 1, Table 1).
25 The EPA notes that the Frank (2012a) analysis is similar to an earlier EPA staff analysis (Hassett

- Sipple et al., 2010), which used air quality data from the EPA’s AQS database to compare maximum versus composite monitor long

- term mean PM 2.5 concentrations across the study areas in six selected multi

- city epidemiological studies.
26 The EPA’s analysis was intended to repeat the commenter’s analysis, but using only valid air quality data (from 2006 to 2008). For the first group of areas (which included 21 areas with valid data), the EPA’s analysis calculated an average across the areas of maximum monitor annual mean concentrations, averaged of 3 years, of 16.8 μg/m 3 compared to an average of composite monitor concentrations of 14.8 μg/m 3 . For th e second group of areas (which included 10 areas with valid data), the EPA’s analysis calculated an average across the areas of maximum monitor annual mean concentrations, averaged over 3 years, of 14.8 μg/m 3 compared to an average of composite monitor con centrations of 14.2 μg/m 3 (Frank, 2012a, Table 3).Draft

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73 categorized as suggestive of causality, nor did it include short

- term exposure studies (which are included in Figure 4 of the proposal notice and above). Such a view is not consistent with setting a standard that would provide sufficient protection from the serious health effects reported even in the limited subset of studies considered by the commenter

. much less protecting pub lic health with an adequate margin of safety . As discussed below, the EPA does not agree with the commenter’s view as to the appropriate focal point for selecting the level of an annual PM 2.5 standard, or with the limited set of studies considered by the

c ommenter as a basis for selecting the level of the annual PM 2.5 standard.

Regarding an appropriate focal point for selecting the level of the annual standard, as discussed in the proposal and as advised by CASAC, the EPA has focused on PM 2.5 concentrations somewhat below the lowest long

- term mean concentrations from each of the key studies of both long

- and short

- term exposures of effects for which the evidence is causal or likely causal, as considered by the EPA (i.e., the first two sets of studies shown in Figure 4 of the preamble to the final rule and in the proposal, 77 FR 38933 ). If the level of the annual standard was set just somewhere within the range of the long

- term mean concentrations from the various long

- term exposure studies, the n one or more of the stud ie s would have a long

- term mean concentration below the selec ted level of the standard. Absent some reason to ignore or discount these studies, which the commenter does not provide (and of which the EPA is unaware) , setting such a standard would allow that level of air quality and its associated risk of PM 2.5 - related mortality and /or morbidity effects to continue. Selecting a standard level that would explicitly allow such projected PM 2.5 - related mortality and morbidity effects to c ontinue to occur could not be considered sufficient to protect the public health with an adequate margin of safety.

Further, focusing on just the long

- term mean PM 2.5 concentrations in the key epidemiological studies

– even the lowest long

- term mean conce ntration from the set of key studies

-- is not appropriate. Concentrations at and around the long

- term

mean concentration s represent the part of the air quality distribution where the data in any given study are most concentrated and, thus, where the confidence in the magnitude and significance of an associati on in such study is strongest. However
, the evidence of an association with adverse health effects in the studies is not limited to the PM 2.5 concentrations just at and around the long

- term mean, but rather extends more broadly to a lower part of the distribution, recognizing that no discernible population

- level threshold for any such effects can be identified based on the available evidence . This broader region of the distribution of PM 2.5 concent

rations should be considered to the extent relevant information is available , recognizing that the degree of confidence in the association identified in a study would change as one moves away from concentrations at and around the long

- term mean concentrati on in any given study. The commenter’s approach ignores this fundamental consideration.

Regarding the set of studies that is appropriate to inform the selection of the level of the annual PM 2.5 standard, the EPA finds that limiting consideration only to th eDraft

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74 long

- term exposure studies, as this commenter suggests, would be tantamount to ignoring the short

- term exposure studies

, 27 which provide some of the strongest evidence from the entire body of ep idemiological studies. Thus, s e lecting a n annual standard lev el using the limited set of studies suggested by the commenter would fail to provide a degree of protection that would be sufficient to protect public health with an adequate margin of safety.

For all the reasons discussed above, the EPA finds the commente r’s concerns with the EPA’s approach to considering composite and maximum monitor PM 2.5 concentrations in selecting the level of the annual PM 2.5 standard to be without merit. Further, the EPA finds no support in the commenter’s analysis for their suggeste d alternative approach.

(2) Comment: With respect to the appropriate exposure period for mortality effects observed in long

- term exposure studies, some commenters in this group generally expressed views consistent with comments from UARG that argued that these studies “are most likely detecting health risk from earlier, higher PM 2.5 levels and misattributing those risks to more recent, lower PM 2.5 levels” (UARG, 2012, Attachment 1, p 7). Further, this commenter asserted that “there is no knowledge or evidence i ndicating whether premature deaths are the result of PM 2.5 exposures in the most recent year; or due to physical damages incurred from PM 2.5 exposures much earlier in life (with the impact on lifespan only emerging later in life); or due to total accumulat ed PM 2.5 exposure over many years.” Id

. In addition , the commenter asserted that the long

- term exposure studies of mortality are central to the EPA’s basis for proposing to set a lower annual standard level, since most of the estimated benefits associated with a lower annual PM 2.5 standard are based on reductions in mortality related to long

- term exposures to PM 2.5
. Response: As an initial matter, the EPA has recognized the challenge in distinguishing between PM 2.5 - associated effects due to past and recent long

- term exposures, and in identifying the relevant latency period for long

- term exposure to PM and resultant health effects (U.S. EPA, 2009a, section 7.6.4; 77 FR 38941/1). While the EPA has acknowledged that there remain important uncertainties related to characterizing the most relevant exposure periods in long

- term exposure studies, the assertion that there is “no knowledge or evidence” that helps to inform this issue is not correct, as discussed below.

27 The commenter suggests that the EPA should not place significant reliance on the long

- term mean concentrations from short

- term exposure studies because “[T]he short

‐ term studies did not use the annual

av erage of PM 2.5 to develop their associations; they used the daily 24

‐ hour averages of PM 2.5 . Thus, short

‐ term studies do not provide a natural indicator for the appropriate level of an annual standard....” (UARG, 2012, Attachment 1, p. 3). The EPA finds this argument unpersuasive. Quite simply, effects were observed in these studies with an air quality distribution that can meaningfully be characterized by these long

- term mean concentrations. Indeed, in remanding the 2006 standard, the D.C. Circuit discussed at length the interrelationship of the long

- and short

- term standards and studies, and remanded the 2006 standard to the EPA, in part, because the EPA had either ignored these relationships or had failed to provide an adequate explanation for disregarding them

. American Farm Bureau Federation v. EPA. 559 F. 3d at 522

- 24.Draft

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75 Both in the last review and in the current review , the EPA has assessed studies that used different air quality periods for estimating long

- term exposure and tested associations with mortality for the different exposure periods (U.S. EPA, 2004, section 8.2.3.5; U.S. EPA 2009a, section 7.6.4). In this rev iew, the Integrated Science Assessment discussed studies available since the last review that have assessed the relationship between long

- term exposure to PM 2.5 and mortality to explore the issue of the latency period between exposure to PM 2.5 and death (U .S. EPA, 2009a, section 7.6.4).

Notably, in a recent analysis of the extended Harvard Six Cities Study, Schwartz et al. (2008) used model averaging (i.e., multiple models were averaged and weighted by probability of accuracy) to assess exposure periods pro spectively (77 FR 38907/1

- 2). The exposure periods were estimated across a range of unconstrained distributed lag models (i.e., same year, one year prior, two years prior to death). In comparing lags, the authors reported that the effects of changes in exp osure to PM 2.5 on mortality were strongest within a 2

- year period prior to death (U.S. EPA, 2009a, p. 7

- 92, Figure 7

- 9). Similarly, a large multi

- city study of the elderly found that the mortality risk associated with long

- term exposure to PM 10 reported cu mulative effects that extended over the years that deaths were observed in the study population (i.e., the follow

- up period) and for the 3

- year period prior to death (Zanobetti et al., 2008).

Further, in a study of two locations that experienced an abrupt decline in PM 2.5 concentrations (i.e., Utah Steel Strike, coal ban in Ireland), Röösli et al. (2005) reported that approximately 75 percent of health benefits were observed in the first 5 years (U.S. EPA, 2009a, Table 7

- 9). Schwartz et al. (2008) and Puet t et al. (2008) found, in a comparison of exposure periods ranging from 1 month to 48 months prior to death, that exposure to PM 10 24 months prior to death exhibited the strongest association, and the weakest association was reported for exposure in the ti me period of 1 month prior to death.

Overall, the EPA notes that the available evidence for determining the exposure period that is causally related to the mortality effects of long

- term PM 2.5 exposures , as discussed above, suggests that a latency period of up to five years would account for the majority of deaths , with the strongest association observed in the two years prior to death. Further, the EPA recognizes that there is no discernible population

- level threshold below which effects would not occur, such that health effects may occur over the full range of concentrations observed in the epidemiological studies, including the lower concentrations in the latter years. In light of this evidence and these considerations, the EPA concludes that it is
appro priate to consider air quality concentrations that are generally contemporaneous with the collection of health event data (i.e., collected over the same time period) as being causally associated with at least some proportion of the deaths assessed in a lon g

- term exposure study. This would include long

- term mean PM 2.5 concentrations from most of the key long

- term exposure studies of effects with causal or likely causal evidence shown in Figure 4 above, which reported long

- term mean PM 2.5 concentrations ranging from 13.6 μg/m 3 to 14.3Draft

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76 μg/m 3

. These studies include studies of mortality by Eftim et al. (2008), which separately analyzed the ACS and Harvard Six City sites, Zeger et al. (2008), and Lipfert et al. (2006), as well as studies of mor bidity endpoints by Goss et al. (2004), McConnell et al. (2003) and Gauderman et al. (2004), and Dockery et al. (1996) and Razienne et al. (1996). The EPA acknowledges that uncertainty in the relevant exposure period is most notable in two other long

- term exposure studies of mortality. The Miller et al. (2007) reported a long

- term mean PM 2.5 concentration for a 1

- year exposure period that post

- dated the follow

- up period in which health event data were collected by two years. Also, the Krewski et al. (2009) study reported a long

- term mean PM 2.5 concentration for an exposure period that included only the last two years of the 18

- year follow

- up period. Based on these considerations, the EPA does not now consider it appropriate to put weight on the reported long

- term mean concentrations from these two studies for the purpose of translating the information from the long

- term mortality studies into a basis for selecting the level of the annual PM 2.5 standard. 28

In addition, the EPA acknowledges that exposure periods that extend at least a couple years prior to the follow

- up period in which health event data were collected would likely more fully capture the PM

- related deaths in such studies. To explore how much higher the long

- term mean PM 2.5 concentrations would lik ely have been had air quality data prior to the follow

- up years of the studies been included, the EPA conducted a sensitivity analysis of long

- term mean PM 2.5 concentrations (Schmidt, 2012) particularly considering studies that only included deaths from a relatively recent follow

- up period. As examples of such studies, this analysis considered the Eftim et al. (2008) study of mortality in 51 ACS sites and the Harvard Six Cities sites, as well as sites in the eastern region in the Zeger et al. (2008) study. Using data from the EPA’s AQS database, the analysis added the two years of air quality data just prior to the follow

- up period in each study, which was 2000 to 2002 in Eftim et al. (2008) and 2000 to 2005 in Zeger et al. (2008). The analysis then calculat ed the extended long

- term mean PM 2.5 concentration for each study. As discussed in Schmidt (2012), in each case the long

- term mean PM 2.5 concentration averaged over the extended exposure period

was less than 0. 3 μg/m 3 higher than the long

- term mean PM 2.5 c oncentration averaged over the follow

- up period. The EPA finds it reasonable to conclude that such a relatively small difference in long

- term mean PM 2.5 concentrations would likely apply for other long

- term exposure studies that used similarly recent follo w

- up periods as well (e.g., Goss et al., 2004; Lipfert et al., 2006).

Based on the above considerations, the EPA concludes that it is appropriate to consider the available air quality information from the long

- term exposure studies, while taking into accou nt the uncertainties in the relevant long

- term exposure periods in weighing the information from these studies. The EPA further concludes that it is appropriate to consider the air quality information from the set

28 Nonetheless, the EPA notes that the Krewski et al. (2009) and Miller et al. (2007) studies provide strong evidence of mortality and cardiovascular

- related effects associated with long

- te rm PM 2.5 exposures to inform causality determinations reached in the ISA (U.S. EPA, 2009a, sections 7.2.11 and 7.6).Draft

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77 of long

- term exposure studies discussed ab ove in the context of the broader array of epidemiological studies that inform the EPA’s consideration of the level of the annual PM 2.5 standard.

The EPA also notes that while the long

- term exposure studies are an important component of the epidemiological evidence that informs the Agency’s consideration of the level of the annual standard, they do not provide the only relevant information, nor are they the set of studies for which the relevant long

term mean PM 2.5 concentrations are the lowest. As discusse d in the proposal, the EPA also considers the long

- term mean PM 2.5 concentrations from the short

- term mortality and morbidity studies as providing important information in considering the level of the annual standard. As discussed above, a large proportion of the aggregate risk associated with short

- term exposures results from the large number of days during which the 24

- hour average concentrations are in the low

- to mid

range of the concentrations observed in the studies. Thus, setting the level of the

ann ual standard based on long

- term mean concentrations, as well as the distribution of concentrations below the mean, in the short

- term exposure studies is the most effective and efficient way to reduce total PM 2.5 - related risk from the broad array of mortali ty and morbidity effects associated with short

- term exposures.
Further, the EPA notes that the relevant exposure period for the short

- term exposure studies is the period contemporaneous with the collection of health event data, and that this exposure perio d is not subject to the uncertainties discussed above related to the long

- term exposure studies. Recognizing that the long

- term mean PM 2.5 concentrations from several of the multi

- city short

- term exposure studies shown in Figure 4 of the preamble to the fi nal rule are below the long

- term mean PM 2.5 concentrations from the long

- term exposure studies (with the exception of Miller et al., 2007). 29 It is reasonable that in selecting the level of the annual standard primary consideration should be given to the in formation from this set of short

- term exposure studies. There is no reasonable basis to discount the long

- term mean concentrations of the short

- term exposure studies for purposes of setting the level of the annual standard. Thus, the commenter is incorrect in asserting that the long

- term exposure studies, not the short

- term exposure studies, would be central in the Administrator’s decision on the level of the annual standard. The standard is ultimately intended to protect no t just against the single type of effect that contributes the most to quantitative estimates of risk to public health, but rather to the broad array of effects, including mortality and morbidity effects from long

- and short

- term exposures across the range of at

- risk populations impacted by PM 2.5 - related effects.

29 As noted in sections III.E.4.c.i and III.E.4.d of the preamble to the final rule , the EPA is not placing weight on the reported long

- term mean concentrations from the Miller et al. (2007) study for the purpose of translating the information from the long

- term mortality studies into a basis for selecting the level of the annual PM 2.5 standard.Draft

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78 (3) Comment : With regard to the EPA’s analysis of distributions of underlying population

- level data (i.e., health event and study population data) and corresponding air quality data from each study area in certain key multi

- city epidemiological studies (Rajan et al., 2011), some commenters in this group raised a number of issues related to this analysis ( e.g., McClellan, 2012; API, 2012, Attachment 1, pp. 5 to 6 ). Some commenters noted the limited number of studies for which health event and study population data were available, and questioned whether these distributions would apply to other studies. Commenters expressed concerns that this analysis had not been formally reviewed by CASAC and was not published in the peer

- review literature. One commenter asserted that th e data sets the EPA used in the distributional analysis were “not available to other scientists for critical independent analysis and interpretation” (McClellan, 2012, p. 2). Based on such concerns, some commenters asserted that the EPA should not consider this information as a basis for selecting a standard level.

Response : As an initial matter, as discussed in section III.E.4.b of the preamble to the final rule , the EPA agrees with CASAC’s advice that it is appropriate to consider additional data beyond t he mean PM 2.5 concentrations in key multi

- city studies to help inform selection of the level of the annual PM 2.5 standard. As both the EPA and CASAC recognize, in the absence of a discernible threshold, health effects may occur over the full range of conce ntrations observed in the epidemiological studies, and there is a high degree of confidence that the observed effects are associated with concentrations that extend below the long

term mean PM 2.5 concentrations reported in the studies. Following CASAC’s ad vice (Samet, 2010d, p.2), the EPA used additional population

- level and air quality data made available by study authors to conduct an analysis of the distributions of such data, to help provide information on the degree of confidence in the magnitude and s ignificance of observed associations across the range of long

- term mean PM 2.5 concentrations in study areas within key multi

- city epidemiological studies.

With regard to the number of multi

- city studies for which an analysis of the distributions of popula

tion

- level data across the study areas and the corresponding annual mean PM 2.5 concentrations was done, the EPA noted at proposal that data for such an analysis were made available from study authors for four studies, including two long

- term exposure studi es and two short

- term exposure studies. 30 The EPA recognized that access to health event data can be restricted due to confidentiality issues, such that it is not reasonable to expect that such information could be made available from all studies. In considering the information from these four st udies, the EPA has further taken into consideration uncertainties discussed in response to the above comment related to the appropriate exposure period for long

- term exposure studies. Based on these considerations, as noted above, the EPA concludes that su ch uncertainties are an

30 Health event data and study population data w ere available from two short

- term exposure studies (Bell et al. 2008; Zanobetti and Schwartz, 2009) and one long

- term exposure study (Krewski et al., 2009). Only study population data were available from another long

- term exposure study (Miller et al., 200 7).Draft

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79 important factor in evaluating the usefulness of the air quality information from the two long

- term exposure studies in this analysis (Krewski et al., 2009; Miller et al., 2007) and that it would not be appropriate to place weight o n the distributional analysis of health event and air quality data from these two studies specifically for the purpose of translating the information from the long

- term mortality studies into a basis for selecting the level of the annual PM 2.5 standard. Su ch uncertainties are not relevant to the short

- term exposure studies, and thus, the Agency focuses on the two short

- term exposure studies in this analysis (Bell et al., 2008; Zanobetti and Schwartz, (2009).

In focusing on these two short

- term exposure stud ies, the EPA first notes that these studies are key multi

- city studies that reported positive and statistically significant associations between mortality and cardiovascular

- related hospital admissions across a large number of areas throughout the U.S. (11 2 U.S. cities in Zanobetti and Schwartz, 2009; 202 U.S. counties in Bell et al., 2008) using relatively recent air quality and health event data (i.e., 1999 through 2005 in both studies). The EPA considers this to be a modest but important data set to use for this distributional analysis to help inform consideration of how much below the long

- term mean PM 2.5 concentrations in key multi

- city long

- and short

- term exposure studies the annual PM 2.5 standard level should be set. While the EPA acknowledges that h aving such data available from more studies would have been useful, the Agency finds the information from this limited set of studies to be an important consideration in selecting an annual standard level, consistent with CASAC advice to consider such info rmation.

The results of this distributional analysis are shown below in Figure 5 of the preamble to the final rule and below (adapted from Figure 3 in Rajan et al., 2011). For each study, this figure shows the cumulative frequency of the number of health e vents in each study area and the corresponding long

- term mean PM 2.5 concentrations in each area. Consistent with CASAC advice (Samet, 2010d, p.2), such an analysis helps to inform the EPA’s understanding of the long

- term mean PM 2.5 concentrations that were most influential in generating the health effect estimates in individual studies. In particular, the EPA recognizes that there is significantly greater confidence in the magnitude and significance of observed associations in that part of the air quality d istribution corresponding to where the bulk of the health events evaluated in each study have been observed. With regard to the part of the distribution in which confidence in the magnitude and significance of associations observed may become appreciably l ower, the EPA considers PM 2.5 concentrations between the 25 th and 10 th percentiles of the distribution of health events to be a reasonable range for providing a general frame of reference for that part of the distribution in which confidence may become app reciably lower. As highlighted in Figure 5, t he long

- term mean PM 2.5 concentrations corresponding with study areas contributing to the 25 th and 10 th percentiles of the distribution of deaths and cardiovascular

- related hospitalizations in the two short

- term exposure studies were 12.5 μg/m 3 and 10.3 μg/m 3

, respectively, for Zanobetti and Schwartz (2009), and 11.5 μg/m 3 and 9.8 μg/m 3

, respectively, for Bell et al. (2008) . The EPA also recognizes, however, that thereDraft

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80 is no clear dividing line or single percentile within a given distribution provided by the scientific evidence that is most appropriate or ‘correct’ to use to characterize where the degree of confidence in the associations warrants setting the annual standard level. The decision as to the ap propriate standard level below the long

- term mean concentrations of the key studies is largely a public health policy judgment to be made by the Administrator, taking into account all of the evidence and its related uncertainties, as discussed in section I II.E.4.d of the preamble to the final rule.

In response to concerns that this analysis was not reviewed by CASAC nor published in the peer

- reviewed literature, the EPA notes that this analysis was conducted to directly respond to advice from CASA C

, as di scussed in section III.E.4.b.1 of the preamble to the final rule , in conjunction with their review of the PA. The EPA notes that the same type of distributional analysis was presented in the second draft PA based on air quality data, as well as population

- weighted air quality data, rather than health event or study population data. In considering that distributional information, CASAC urged that the EPA redo the analysis using health event or study population data, which is exactly what the EPA did and
pres ented in the final PA. The EPA provided CASAC with the final PA and communicated how the final staff conclusions reflected consideration of its advice and that those staff conclusions were based in part on the specific distributional analysis that CASAC ha d urged the EPA to conduct (Wegman, 2011, Attachment p. 2). CASAC did not choose to provide any additional comments or advice after receiving the final PA. The EPA considers this distributional analysis to be theDraft

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81 product of the peer review conducted by CAS AC of the PA, and thus does not agree with commenters’ characterization that the analysis lacked appropriate peer review. The EPA’s final analysis was based on the comments provided by CASAC, the pe e r review committee established pursuant to the CAA , on th e draft analysis, such that the final analysis stems directly from CASAC’s advice and the EPA’s response to its comments.

With regard to the availability of the underlying data sets, the EPA disagrees with the commenters’ assertion that these data are not publically available. As noted in the EPA staff technical memorandum, the underlying data sets provided by study authors are available in the rulemaking docket (Rajan et al., 2011, pp. 2 to 3).

Based on the above considerations, the EPA continues to conclu de that its analysis of distributions of health event and air quality data from two key multi

city epidemiological studies provides important information related to understanding the associations between health events observed in each city (e.g., deaths, h ospitalizations) and the corresponding long

- term mean PM 2.5 concentrations observed in the studies. While recognizing that this is a relatively modest data set, the EPA further concludes that such information can appropriately help to inform the selection of the level of an annual standard that will protect public health with an adequate margin of safety from these types of health effects which are causally related to long

- and short

- term exposures to PM 2.5
. (4) Comment : Some commenters in this group asserted there were limitations in the long

- term exposure studies of morbidity, including studies evaluating respiratory effects in children. For example, one commenter (UARG, 2012, p. 12, Attachment 1, pp. 14 to 16) asserted there were serious limitations in the l ong

term exposure studies of respiratory morbidity in each of the studies considered by the EPA (including McConnell et al., 2003; Gauderman et al., 2004; Dockery et al., 1996; Raizenne et al., 1996; and Goss et al., 2004) and argued that this evidence pro vides only a “weak association” with PM 2.5 exposures. This commenter asserted that many of these long

- term exposure studies evaluating respiratory effects were considered at the time the EPA reaffirmed the current annual standard level of 15 μg/m 3 in 2006, that the Administrator in the last review determined that the information they provided “was too limited to serve as the basis for setting a level of a national standard,” and that they should be given little weight in setting the level of the annual stan dard in this review (UARG, 2012, Attachment 1, p. 14).

More specifically, this commenter asserted that the McConnell et al. (2003) and Gauderman et al. (2004) stud ies reported mixed results for associations with PM 2.5 and stronger associations with NO 2 (API, 2012, Attachment 1, pp. 14 to 15). Similarly, this commenter argued that the Dockery et al. (1 996) and Raizenne et al. (1996) studies show ed stronger associations with acidity than with fine particles (measured as PM 2.1 ). Id. pp. 15 to 16. With reg ard to the cystic fibrosis study, this commenter noted that the association between pulmonaryDraft

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82 exacerbations and PM 2.5 in this study was no longer statistically significant when the model adjusted for each individual’s baseline lung function. The commenters referred to the data on lung function as an “important explanatory variable,” and suggested that the EPA should rely on results from the model that included individual baseline lung function information. Id . p. 16.

Response : For the reasons discussed in section III.E.4.c.i of the preamble for the final rule, the response in section II.B.1.b above, and the further response below,
t he EPA disagrees with the commenters’ interpretation of these studies

. As an initial matter, the E PA notes that three of these studies (McConnell et al., 2003; Dockery et al., 1996; Raizenne et al., 1996) as well as the initial studies from the Southern California Children’s Health Study ( Peters et al., 1999; McConnell et al., 1999’ Gauderman et al., 2 000, 2002 ; Avol et al., 2001 ) were discussed and considered in the 2004 Air Quality Criteria Document ( U.S. EPA, 2004) and , thus, considered within the air quality criteria supporting the EPA’s final decisions in the review completed in 2006. Two additiona l studies (Gauderman et al., 2004; Goss et al., 2004) were discussed and considered in the provisional science assessment conducted for the last review ( U.S. EPA, 2006a). All of these studies were considered in the ISA that informs the current review ( U.S. EPA, 2009a).
With regard to the Southern California Children’s Health Study, extended analyses considered in the ISA provided evidence that clinically important deficits in lung function 31 associated with long

- term exposure to PM 2.5 persist into early adu lthood (U.S. EPA, 2009a, p. 7

- 27; Gauderman et al., 2004). These effects remained positive in copollutant models. 32 Additional analyses of the Southern California Children’s Health Study cohort reported an association between long

term PM 2.5 exposure and br onchitic symptoms ( U.S. EPA, 2009a, p. 7

- 23 to 7

- 24; McConnell et al., 2003, long

- term mean concentration of 13.8 μg/m 3 ) that remained positive in co

- pollutant models, with the PM 2.5 effect estimates increasing in magnitude in some models and decreasing in others, and a strong modifying effect of PM 2.5 on the association between lung function and asthma incidence ( U.S. EPA, 2009 a , 7

- 24; Islam et al., 2007). T he outcomes observed in the more recent reports from the Southern California Children’s Health Study

, including evaluation of a broader range of endpoints and longer follow

- up periods, were larger in magnitude and more precise than reported in the initial version of the study . Supporting these results were new longitudinal cohort studies conducted by oth er researchers in varying locations using different

31 Clinical significance was defined as an FEV 1 below 80 percent of the predicted value, a criterion commonly used in clinical settings to identify persons at increased risk for adverse respiratory conditions (U.S. EPA, 2009a, p. 7

- 29 to 7

- 30). The prim ary NAAQS for sulfur dioxide (SO 2 ) also included this interpretation for FEV 1 (75 FR 35525, June 22, 2010).
32 Gauderman et al. (2004) clearly stated throughout their analysis that NO 2 was one component of a highly correlated mixture that contains PM 2.5 . Ga uderman et al. (2004) did not present the results from copollutants models but stated “two

- pollutant models for any pair of pollutants did not provide a significantly better fit to the data than the corresponding single

- pollutant models.”Draft

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83 methods ( U.S. EPA, 2009a, section 7.3.9.1). The EPA, therefore, disagrees with the commenters that the studies by McConnell et al. (2003) and Gauderman et al. (2004) are flawed and should not be used in the PM NAAQS review process.

The 24

- City study 33 by Dockery et al. (1996) (long

- term mean concentration of 14.5 μg/m 3 ) was considered in the current as well as two previous reviews ( U.S. EPA, 2009a; U.S. EPA, 2004; U.S. EPA, 1996). This study observed that PM, specifically “particle strong acidity” and sulfate particles (indicators of fine particles), were associated with reports of bronchitis in the previous year. Similarly, the magnitude of the associations between bronchitis and PM 10 and PM 2.1 were simila r to those for acidi c aerosols and sulfate particles, though the confidence intervals for the PM 10 and PM 2.1 associations were slightly wider and the associations were not statistically significant. Acid aerosols , sulfate, and fine particles are formed in secondary reactions of the emissions from incomplete combustion and these pollutants have similar regional and temporal distributions

. As noted by the study authors, “the strong correlations of several pollutants in this study, especially particle strong a cidity with sulfate (r=0.90) and PM 2.1 (r=0.82), make it difficult to di stinguish the agent of interest ” (Dockery et al., 1996, p. 505). Overall, Dockery et al. (1996) (and, similarly, Raizenne et al., 1996) observed similar associations between respirator y health effects and acid aerosols

, sulfate, PM 10 and PM 2.1 concentrations. The commenters noted that the associations with particle acidity were sensitive to the inclusion of the six Canadian sites. The EPA notes that none of these Canadian cities were in the “sulfate belt” where particle strong acidity was highest. Thus, the change in the effect estimate when the six Canadian cities were excluded from the analysis is likely due to the lower prevalence of bronchitis and the lower concentrations of acid aer osols in these cities, and not due to some difference in susceptibility to bronchitis between the U.S. and Canadian populations that is not due to air pollution, as suggested by the commenters (UARG, 2012, Attachment 1, p. 15). In fact, contrary to the sta tements made by the commenters, the authors did not observe any subgroups that appeared to be markedly more susceptible to the risk of bronchitis.

The Goss et al. (2004) study considered a U.S. cohort of cystic fibrosis patients and provided evidence of a ssociation between long

- term PM 2.5 exposures and exacerbations of respiratory symptoms resulting in hospital admissions or use of home intravenous antibiotics ( U.S. EPA, 2009a, p. 7

- 25; long

- term mean concentration of 13.7 μg/m 3 ). The commenters noted that the association between pulmonary exacerbations and PM 2.5 in this study was no longer statistically significant when the model adjusted for each individual’s baseline lung function. The commenters referred to the data on lung function as an “important
exp lanatory variable,” and suggested that the EPA should rely on results from the model that included individual baseline lung function information. The EPA

33 The 24

- City stu dy conducted by Dockery et al. (1996) included 18 sites in the U.S. and 6 sites in Canada. The Raizenne et al. (1996) study considered 22 of these 24 study areas. Athens, OH and South Brunswick, NJ were not included in this study.Draft

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84 disagrees with the commenters’ interpretation of this study. The Agency concludes it is unlikely that lung function is a potential confounder or an important explanatory variable in this study. In fact, the authors noted that “it is more likely that lung function decline may be intimately associated with chronic exposure to air pollutants and may be part o f the causal pathway in worsening prognosis in CF [cystic fibrosis]; in support of this explanation, we found both

cross

- sectional and longitudinal strong inverse relationships between FEV 1 and PM levels” (Goss et al., 2004, p. 819). The EPA notes that adj usting for a variable that is on the causal pathway can lead to overadjustment bias, which is likely to attenuate the association (Schisterman et al. 2009); this is likely what was observed by the authors. Thus, the EPA continues to believe it is appropria te to focus on the results reported in Goss et al. (2004) that did not include individual baseline lung function in the model.
In addition, the EPA disagrees with commenters’ reliance solely on statistical significance when interpreting the study results f rom individual study results and the collective evidence across studies. As discussed in section III.D.2 of the preamble to the final rule and in the response in section II.B.1.b above , statistical significance of individual study findings has played an important role in the EPA’s evaluation of the study’s results and the EPA has placed greater emphasis on studies reporting statistically significant results. However, in the broader eval uation of the evidence from many epidemiological studies, and subsequently during the process of forming causality determinations in the Integrated Science Assessment by integrating evidence from across epidemiological, controlled human exposure, and toxic ological studies, the EPA has emphasized the pattern of results across epidemiological studies and whether the effects observed were coherent across the scientific disciplines for drawing conclusions on the relationship between PM 2.5 and different health o utcomes. The EPA note s further that the D.C. Circuit has held that the EPA can look to other indicia of reliability such as the consistency and coherence of a body of studies as well as other confirming data to justify reliance on the results of a body of epidemiologic al studies, even if individual studies may lack statistical significance. American Trucking Ass ociation v. EPA , 283 F. 3d at 371 (in the context of discussing whether study results were confounded by co

- pollutants).

As noted in section III.B.1 .a of the proposal, with regard to respiratory effects, the Integrated Science Assessment concluded that extended analyses of studies available in the last review as well as new epidemiological studies conducted in the U.S. and abroad provided stronger evi dence of respiratory

- related morbidity associated with long

- term PM 2.5 exposure (77 FR 38918). The strongest evidence for respiratory

- related effects available in this review was from epidemiological studies that evaluated decrements in lung function growt h in children and increased respiratory symptoms and disease incidence in adults (U.S. EPA, 2009a,Draft

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85 sections 2.3.1.2, 7.3.1.1, and 7.3.2.1). 34

In considering the collective evidence from epidemiological, toxicological, and controlled human exposure studies, including the studies discussed above, the EPA recognizes that the Integrated Science Assessment concluded that a causal relationship is likely to exist between long

- term PM 2.5 exposures and respiratory effects ( U.S. EPA, 2009a, p. 2

- 12, pp. 7

- 42 to 7

- 43). CASAC concurred with this causality determination (Samet, 2009f, p.9).

The commenter’s assertion that the EPA should adhere to its assessment of these studies as it did in the review completed in 2006 is significantly mistaken. Most obviously, the EPA’s f

inal decision in the last review was held to be deficient by the D.C. Circuit in remanding the 2006 primary annual PM 2.5 standard. As discussed in section III.A.2 of the preamble to the final rule , the D.C. Circuit specifically held that the EPA did not pr ovide a reasonable explanation of why certain morbidity studies, including an earlier study from the Southern California Children’s Health Study (Gauderman et al., 2000 , long

- term mean PM 2.5 concentration approximately 15 μg/m 3 ) and the 24

- Cities Study (Raizenne et al., 1996 , long

- term mean concentrations approximately 14.5 μg/m 3 ) did not warrant a more stringent annual PM 2.5 standard when the long

- term mean PM 2.5 concentrations reported in those studies were at or lower than the level of the annual stan dard. American Farm Bureau Federation v. EPA . 559 F. 3d at 525. Indeed, the court found that, viewed together, the Gauderman et al. (2000) and Raizenne et al., (1996) studies “are related and together indicate a significant public health risk...On this recor d, therefore, it appears the EPA too hastily discounted the Gauderman and 24

- Cities studies as lacking in significance.” Id.

In this review, the EPA recognizes a significant amount of evidence beyond these two studies that expands our understanding of res piratory effects associated with long

- term PM 2.5 exposures. This body of scientific evidence includes an extended and new analyses from the Southern California Children’s Health Study (Gauderman et al., 2004; Islam et al., 2007; Stanojevic et al., 2008) as well as additional studies that examined these health effects (Kim et al., 2004; Goss et al., 2004). Thus, even more so than in the last review, the evidence indicates a “significant public health risk” to children from long

- term PM 2.5 exposures at

concen trations below the level of the current annual standard. A standard that does not reflect appropriate consideration of this evidence would not be requisite to protect public health with an adequate margin of safety.

(5) Comment : With regard to the use of studi es of health effects for which the EPA finds the evidence to be “suggestive” of a causal relationship, some commenters argued that such studies “do not merit any weight in the setting of the annual NAAQS” (e.g., UARG, 2012, Appendix 1, p. 3).

34 Supporting evidence co mes from studies “that observed associations between long

- term exposure to PM 10 and an increase in respiratory symptoms and reductions in lung function growth in areas where PM 10 is dominated by PM 2.5 ” (U.S. EPA, 2009a, p. 2

- 12).Draft

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86 Response : The EPA disagrees with the commenter’s view that studies of health effects for which the evidence is suggestive of a causal relationship, rather than studies of health effects for which the evidence supports a causal or likely causal relationship, merit no we ight at all in setting the NAAQS. To place no weight at all on such evidence would in essence treat such evidence as though it had been categorized as “not likely to be a causal relationship.” To do so would ignore the important distinctions in the nature of the evidence supporting these different causality determinations in the ISA. It would also ignore the CAA requirement that primary standards are to be set to provide protection with an adequate margin of safety, including providing protection for at

- ris k populations. Thus, ignoring this information in making decisions on the appropriate standard level would not be appropriate. 35 Nonetheless, in considering studies of health effects for which the evidence is suggestive of a causal relationship, the EPA doe s believe that it is appropriate to place less weight on such studies than on studies of health effects for which there is evidence of a causal or likely causal relationship.

(6) Comment: Some commenters questioned the long

- term mean PM 2.5 concentration reported in the final PA and used in Figure 4 of the proposal for the Miller et al. (2007) study (API, 2012, Attachment 1, p. 8; UARG, 2012, Attachment 1, pp. 2 to 3, fn 3 , p. 12 ).

Response: The EPA recognizes that the study authors origina lly reported a long

term mean PM 2.5 concentration of 13.5 μg/m 3 (Miller et al., 2007, Table 2). This concentration was presented in the ISA (US EPA, 2009a) and discussed in the second draft PA (US EPA, 2010f). In response to a request from the EPA for addi tional information on the air quality data used in selected epidemiological studies (Hassett

- Sipple and Stanek, 2009), study investigators provided updated air quality data for the study period. The updated long

- term mean PM 2.5 concentration provided by th e study authors was 12.9 μg/m 3 (personal communication from Cynthia Curl, 2009; Stanek e t al., 2010). T he final PA note d that this updated long

- term mean concentration matche d the composite monitor approach annual mean calculated by the EPA ( Hassett

- Sipple et al., 2010, Atta chment A, p. 6) for the year of air quality data (i.e., 2000) considered by the study investigators ( U.S. EPA, 2011a, p. 2

- 32, fn 24 ). The EPA s taff conclude d it

wa s most appropriate to include the updated air quality data in th e final PA ( Id .)

. Thus, the long

- term mean PM 2.5 concentration for Miller et al. (2007) discussed in the proposal and presented in Figures 1 and 4 of the proposal was reported as 12.9 μg/m 3

. The PA note d that in comparison to other long

- term exposure studies, the Miller et al. (2007) study was more limited in that it was based on only one year of air quality data ( U.S. EPA, 2011a, p. 2

- 82 ). The proposal further noted that the air quality data considered were extrapolated from that one single year of air

35 As discussed in section II.A of the preamble to the final rule, the requirement that primary standards provide an adequate margin of safety was intended to address uncertainties associated with inconclusive scientific and technical information available a t the time of standard setting. I t was also intended to provide a reasonable degree of protection against hazards that research has not yet identified. This certainly encompasses consideration of effects for which there is evidence suggestive of a causal r elationship.Draft

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87 quality dat a (2000) to the whole study, and that the air quality data post

- dated the years of health events considered ( i.e., 1994 to 1998) (77 FR 38918, fn 62).

For the reasons discussed in section III.E.4.c.i of the preamble to the final rule, the EPA does not now consider it appropriate to put weight on the reported long

term mean concentration from the Miller et al. (2007) study (either the original value reported in the published study nor the updated value provided by the study authors) for the purpose of transl ating the epidemiological information from the long

- term exposure studies into a basis for selecting the level of the annual PM 2.5 standard. Nonetheless, the EPA notes that the Miller et al. (2007) study provides strong evidence of cardiovascular

- related effects associated with long

- term PM 2.5 exposures to inform causality determinations reached in the ISA (U.S. EPA, 2009a, sections 7.2.11 and 7.6).

(7) Comment : Some of these commenters also identified “new” studies as providing additional evidence to support their views that the annual standard level does not need to be revised

. Response: As discussed in section II.B.3 of the preamble to the final rule and in

se ction II.B.1.a above, the EPA notes that, as in past NAAQS reviews, the Agency is basing the final decisions in this review on the studies and related information included in the PM ISA that have undergone CASAC and public review, and will consider newly p ublished studies for purposes of decision making in the next PM NAAQS review. Nonetheless, i n provisionally evaluating commenters’ arguments, the EPA notes that its provisional assessment of “new” science found that such studies did not materially change t he conclusions reached in the ISA (U.S. EPA, 2012b).

ii. Support for Revising the Current Leve l

A second group of commenters supported revising the suite of primary PM 2.5 standards to provide increased public health protection. These commenters found the avail able scientific information and technical analyses to be stronger and more compelling than in the last review. These commenters generally placed substantial weight on CASAC advice and on the EPA staff analyses presented in the final PA

. While generally sup porting the EPA’s proposal to lower the level of the annual standard, many commenters in this group disagreed that a level within the EPA’s proposed range (i.e., 12 to 13 μg/m 3 ) was adequately protective and supported a level of 11 μg/m 3 or below.

In gener al, these commenters expressed the view that given the strength of the available scientific evidence, the serious nature of the health effects associated with PM 2.5 exposures, the large size of the at

- risk populations, the risks associated with long

- and short

- term PM 2.5 exposures, and the important uncertainties inherently present in the evidence, the EPA should follow a highly precautionary policy response by selecting an annual standard level that incorporates a large margin of safety.

More specificall y, these commenters offered a range of comments related to theDraft

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88 general approach used by the EPA to select standard levels, including: (1) the EPA’s approach for setting a generally controlling annual standard; (2) the importance of the greatly expanded and stronger overall scientific data base; (3) consideration of the distributional statistical analysis conducted by the EPA and other approaches for translating the air quality information from specific epidemiological studies into standard levels; and (4) t

he significance of the PM 2.5 - related public health impacts, especially potential impacts on at

- risk populations, including children, in reaching judgments on setting standards that provide protection with an adequate margin of safety. These comments are di scussed in turn below.

(1) Comment: Some of these commenters disagreed with the EPA’s approach for setting a “generally controlling” annual standard in conjunction with a 24

- hour standard providing supplemental protection particularly for areas with high peak

to

- mean ratios. These commenters argued this approach would lead to “regional inequities” as demonstrated in the EPA’s analyses contained in Appendix C of the PA (ALA et al., pp. 26 to 27). Specifically, these commenters argued:

There is no basis in the CA A for such a determination. The CAA requires only that the NAAQS achieve public health protection with an adequate margin of safety. It is well

- documented that both long

- and short

- term exposures to PM 2.5 have serious and sometimes irreversible health impa cts. There is no health protection reason to argue that one standard should be “controlling” as a matter of policy without regard to the health consequences of such a policy. To adopt such a policy ignores the obligation to provide equal protection under t he law to all Americans because it would result in uneven protection from air pollution in different localities and regions of the country (ALA et al., 2012, p. 26).

Response: The EPA believes these commenters misunderstood the basis for the EPA’s policy g oal of setting a “generally controlling” annual standard. This approach relates exclusively to setting standards that will provide requisite protection against effects associated with both long

- and short

- term PM 2.5 exposures. It does so by lowering the ov erall air quality distributions across an area, recognizing that changes in PM 2.5 air quality designed to meet an annual standard would likely result not only in lower annual mean PM 2.5 concentrations but also in fewer and lower peak 24

- hour PM 2.5 concentr ations. As discussed in section III.A.3 in the proposal and in the preamble to the final rule , the EPA recognizes that there are various ways to combine the two primary PM 2.5 standards to achieve an appropriate degree of public health protection. Furthermo re, the extent to which these two standards are interrelated in any given area depends in large part on the relative levels of the standards, the peak

- to

- mean ratios that characterize air quality patterns in an area, and whether changes in air quality desi gned to meet a given suite of standards are likely to be of a more regional or more localized nature.

In focusing on a

n approach of setting a generally controlling annual standard, the EPA’s intent is in fact to avoid the potential “regional inequities” that are ofDraft

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89 concern to the se commenters. The EPA judges that the most appropriate way to set standards that provide more consistent public health protection is by using the approach of setting a generally controlling annual standard. This judgment builds

u pon information presented in the PA as discussed in section III.A.3 of the preamble to the final rule . More specifically, the PA recognized that the short

term exposure studies primarily evaluated daily variations in health effects with monitor(s) that mea sured the variation in daily PM 2.5 concentrations over the course of several years. The strength of the associations observed in these epidemiological studies was demonstrably in the numerous “typical” days within the air quality distribution, not in the p eak days ( U.S. EPA, 2011a, p. 2

- 9). In addition, the quantitative risk assessments conducted for this and previous reviews demonstrated the same point : that is, much, if not most

, of the aggregate risk associated with short

- term PM 2.5 exposures results fro m the large number of days during which the 24

- hour average concentrations are in the low

- to mid

range, below the peak 24

- hour concentrations ( U.S. EPA, 2011a, section 2.2.2; U.S. EPA, 2010a, section 3.1.2.2). In addition, there was no evidence suggesting that risks associated with long

- term exposures were likely to be disproportionately driven by peak 24

- hour concentrations. 36 See also American Trucking Ass ociation v. EPA , 283 F. 3d at 373 (rejecting arguments to lower the level of the daily PM 2.5 standard when there is persuasive evidence that the main risk from exposure comes fro m the entire air quality distribution rather than from peak days, and the annual standard will lower that distribution). For these reasons, the PA concluded that strategies that fo cused primarily on reducing peak days were less likely to achieve reductions in the PM 2.5 concentrations that were most strongly associated with the observed health effects. Furthermore, the PA concluded that a n approach that focused on reducing peak expos ures would most likely result in more uneven public health protection across the U.S. by either providing inadequate protection in some areas or overprotecting in other areas ( U.S. EPA, 2011a, p. 2

- 9; U.S. EPA, 2010a, section 5.2.3). This is because reductions based on control of peak days are less likely to control the bulk of the air quality distribution. As noted above, this would create the very inequity of results the commenters seek to avoid.

As a result, the EPA believes a n approach that focuses on a generally controlling annual standard would likely reduce aggregate risks associated with both long

and short

- term exposures more consistently than a generally controlling 24

- hour standard and, theref

ore, would be the most effective and efficient way to reduce total PM 2

- 5 - related population risk. The CASAC agreed with this approach and considered it was “appropriate to return to the strategy used in 1997 that considers the annual and the short

- term sta ndards together, with the annual standard as the controlling standard, and the short

- term standard supplementing the protection afforded by the annual standard” (Samet, 2010d, p. 1). T he EPA thus disagrees with the comments that this approach will result i n the concerns raised by the

36 In confirmation, a number of studies have presented analyses excluding higher PM concentration days and reported a limited effect on the magnitude of the effect estimates or statistical significance of the association (e.g., Dominici, 2006b; Schwartz et al., 1996; Pope and Dockery, 1992).Draft

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90 commenters; rather the EPA concludes that this approach will help to address these concerns.

(2) Comment: Many of these commenters asserted that the currently available scientific information is greatly expanded and stronger compar ed to the last review. Some of these commenters highlighted the availability of multiple, multi

city long

- and short

- term exposure studies providing “repeated, consistent evidence of effects below the current annual standard level” (ALA et al., 2012, pp. 3 9 to 49) and, more specifically, “significant evidence of harm with strong confidence well below EPA’s proposed annual standard range of 12

- 13 μg/m 3 ” (AHA et al., 2012, pp. 10 to 12).

Response: The EPA recognizes that in setting standards that are requisit e to protect public health with an adequate margin of safety, the Administrator must weigh the various types of available scientific information in reaching public health policy judgments that neither overstate nor understate the strength and limitations o f this information or the appropriate inferences to be drawn from the available science.
In general, the EPA agrees with these commenters’ views that the currently available scientific evidence is stronger “because of its breadth and the substantiation of previously observed health effects” (77 FR 38906/2) and provides “greater confidence in the reported associations than in the last review” (77 FR 38940/1). The EPA also agrees with the commenters’ position that it is appropriate to consider the regions wi thin the broader air quality distributions where we have the strongest confidence in the associations reported in epidemiological studies in setting the level of the annual standard. However, as discussed in section III.E.4.d of the preamble to the final r ule , in weighing the available evidence and technical analyses, as well as the associated uncertainties and limitations in that information, the EPA disagrees with the commenters’ views regarding the extent to which the available scientific information pro vides support for considering an annual standard level below the proposed range (i.e., below 12 to 13 μg/m 3 ). In particular, the EPA disagrees with the degree to which these commenters place more weight on the relatively more uncertain evidence that is sug gestive of a causal relationship (e.g., low birth weight). Consistent with CASAC advice (Samet, 2010d, p. 1), the Agency concludes it is appropriate and reasonable to place the greatest emphasis on health effects for which the ISA concluded there is eviden ce of a causal or likely causal relationship and to place less weight on the health effects that provide evidence that is only suggestive of a causal relationship.

(3) Comment : With regard to using the air quality information from epidemiological studies to in form decisions on standard levels, commenters in this group generally supported the EPA’s efforts to explore different statistical metrics from epidemiological studies to inform the Administrator’s decisions. These commenters argued that by considering dif ferent analytic measures

-- either concentrations one standard deviation below the long

- term means reported in theDraft

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91 epidemiological studies or the EPA’s distributional statistical analysis of population

- level data that extends the approach used in previous PM NAAQS reviews to consider information beyond a single statistical metric

-- “the annual standard must be significantly lower than EPA has proposed” (ALA et al., 2012, pp. 50 to 61). Furthermore, with regard to characterizing the PM 2.5 air quality at whi ch associations have been observed, some of these commenters highlighted CASAC’s recommendation that “[f]urther consideration should be given to using the 10 th percentile as a level for assessing various scenarios of levels for the PM NAAQS” (Samet, 2010c, p. 11) (ALA et al., 2012, p. 55). Other commenters urged that the EPA extend the distributional analysis to include additional studies. For example, CHPAC urg ed the EPA to also conduct distributional analysis for children’s health studies to better inform standards that would protect both children and adults from adverse health outcomes (CHPAC, 2012, p. 3)

. Response : The EPA agrees with these commenters’ views that it is appropriate to take into account different statistical metrics from epidemiological studies to inform the decisions on standard levels that are appropriate to consider. In the development of the PA, the EPA staff explored various approaches for us ing information from epidemiological studies in setting the standards. The general approach used in the final PA, discussed in sections III.A.3 and III.E.4.a of the preamble to the final rule , reflects consideration of CASAC advice (Samet, 2010c,d) and p ublic comments on multiple drafts of the PA

. With regard to using the distributional statistical analysis to characterize the confidence in the associations

, the EPA emphasizes that there is no clear dividing line provided by the scientific evidence, and t hat choosing how far below the long

- term mean concentrations from the epidemiological studies is appropriate to identify a standard level that will provide protection for the public health with an adequate margin of safety is largely a public health policy judgment. The EPA considers the region from approximately the 25 th to 10 th percentiles to be a reasonable range for providing a general frame of reference as to the part of the distribution over which our confidence in the magnitude and significance of th e associations observed in epidemiological studies becomes appreciably lower. However, the EPA disagrees with the commenters’ views that the available information compels placing more emphasis on the lower part of this range. The EPA recognizes that this i nformation comes primarily from two short

- term exposure studies, a relatively modest data set. In light of the limited nature of this information, and in recognition of more general uncertainties inherent in the epidemiological evidence, the Administrator deems it reasonable not to place more emphasis on concentrations in the lower part of this range, as discussed in section III.E.4.d of the preamble to the final rule.

With regard to the scope of the distributional statistical analysis, the EPA requested ad ditional population

- level data from the study authors for a group of six multi

- city studies for which previous air quality analyses had been conducted (Hassett

- Sipple et al., 2010; Schmidt et al., 2010, Analysis 2). These six studies were originally select ed because they considered multiple locations representingDraft

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92 varying geographic regions across multiple years. Thus, these studies provided evidence on the influence of different particle mixtures on health effects associated with long

- and short

- term PM 2.5 exposures. In addition, these multi

- city studies considered relatively more recent health events and air quality conditions (1999 to 2005). As discussed in section III.E.4.b.i of the preamble to the final rule , the EPA received and analyzed population

- leve l data for four of the six studies (Rajan et al., 2011). T hree of these four studies (Krewski et al., 2009; Bell et al., 2008; Zanobetti and Schwartz, 2009) served as the basis for the C

- R functions used to develop the core risk estimates ( U.S. EPA, 2010a, section 3.3.3). While the EPA agrees that it would be useful to have such data from more studies, the Agency believes that the additional data that was requested and received from study authors provide useful information to help inform the Administrator’s selection of the annual standard level.

(4) Comment: Many commenters in this group highlighted PM 2.5 - related impacts on
at

- risk populations, including potential impacts on children, older adults, persons with pre

- existing heart and lung disease, and low

- inco me populations, to support their views that the annual standard should be revised to a level of 11 μg/m 3 or lower (CHPAC, 2012; AHA et al., 2012; ALA, 2012, pp. 29 to 38; Rom et al., 2012; Air Alliance Houston, et al

. , 2012 , p. 1 ; PSR, p p. 2 and 4 ). These commenters urged the EPA to adopt a policy approach that placed less weight on the remaining uncertainties and limitations in the evidence and placed more emphasis on margin of safety considerations, including providing protection against effects for which there is more limited scientific evidence. For example, CHPAC urged the EPA “to place the same weight on studies examining impacts on children’s health as that of adult studies. ... The fact that there may be stronger evidence from adult studies do es not mean that standards based on adult studies will be protective for children and consequently will meet the standard requisite to protect public health with an adequate margin of safety” (CHPAC, 2012 p. 3). Furthermore, with regard to the EPA’s approa ch for weighing uncertainties, some of these commenters stated that “we find no justification in the preamble for an annual standard level as high as 13 μg/m 3 , other than the vague assertion that uncertainties increase at lower concentrations. Further, the final proposal completely failed to address the Policy Assessment recommendations that if 13 μg/m 3 was proposed, the 24

- hour standard should be strengthened as well” (ALA et al., p. 7).

Response: The EPA has carefully evaluated and considered evidence of effects in
at

- risk populations. With regard to effects classified as having evidence of a causal or likely causal relationship with long

- or short

- term PM 2.5 exposures (i.e., premature mortality, cardiovascular effects, and respiratory effects), the Agency takes note that it considered the full range of studies evaluating these effects, including studies of at

- risk populations, to inform its review of the primary PM 2.5 standards. Specific multi

- city studies summarized in Figures 1, 2, and 3 in the preamble for the final rule highlight evidence of effects observed in two different lifestages

– children and older adults

– that have been identified as at

- risk populations. Thus, the EPA places as much weight on studies that explored effectsDraft

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93 in children for which the evidence is causal or likely causal in nature as on studies of such effects in adults, including older adults . As discussed above in responses to commenters supporting the retention of the current standards, in setting the standard, the EPA has focuse d on considering PM 2.5 concentrations somewhat below the lowest long

- term mean concentrations from each of the key studies of both long

- and short

- term exposures of effects for which the evidence supports a causal or likely causal relationship (i.e., the f irst two sets of studies shown in Figure 4 of the preamble to the final rule). The EPA has thus considered the available evidence of effects in children as well as other at

- risk populations, given that those commenters urging the EPA to discount or disrega rd those studies provided no legitimate reason to do so. With respect to the EPA’s consideration of more limited studies providing evidence suggestive of a causal relationship (e.g., developmental and reproductive effects), as noted above in responding to comments from the first group of commenters, the Agency is placing some weight on this body of evidence in setting standards that provide protection for at

- risk populations,. However, the Agency does not agree that the same weight must be placed on this in formation as on the body of scientific information for which there is evidence of a causal or likely causal relationship. To do so here would ignore the difference in the breadth and strength of the evidence supporting the different causality determination s reached in the ISA.

With regard to weighing the uncertainties and limitations remaining in the evidence and technical analyses, as discussed in section II.A of the preamble to the final rule, the EPA recognizes that in setting a primary NAAQS that provi des an adequate margin of safety, the Administrator must consider a number of factors including the nature and severity of the health effects involved, the size of sensitive population(s) at risk, and the kind and degree of the uncertainties that remain. A s discussed in section III.E.4.d of the preamble to the final rule, the Agency agrees with these commenters that, in weighing the available evidence and technical analyses including the uncertainties and limitations in this scientific information, there is no legitimate justification for setting a primary PM 2.5 annual standard level as high as 13 μg/m 3

. ( A ssuming retention of a 24

- hour standard either at or close to the current level).

(5) Comment: Some commenters urged the EPA “to select a standard based on science, not politics” (ALA et al., 2012, p. 6). More specficially, these commenters asserted “last minute changes to the proposed level (following interagency review) were not accompanied by su bstantive changes in the text to the proposal. In fact, we find no justification in the preamble for an annual standard as high as 13 μg/m 3 , other than the vague assertion that uncertainties increase at lower concentrations. Further the final proposal comp letely failed to address the Policy Assessment recommendations that if 13 μg/m 3 was proposed, then the 24

- hour standard should be strengthened as well. The apparent last minute and unsupported insertion of a less protective annual standard to the proposal appears to be political interference, not scientific consideration” (ALA et al., 2012, p. 7).Draft

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94 Response: As stated in the previous response, the EPA agrees that the evidence in the record of this review does not support an annual standard at the level of 13
μ g/m 3 (unless the 24

- hour standard level were to be lowered substantially ).

(6) Comment: Some commenters argued that the EPA “committed a serious procedural error in not explicitly soliciting comment on retaining the current [annual] PM 2.5 NAAQS” (API, 2012, p. 9).

Response: The commenter suggest ed (without providing any specific argument) that the EPA somehow prejudged the outcome of the rulemaking , or otherwise committed procedural error, by not proposing to retain the 2006 NAAQS. This is incorrect . First, the EPA provided far more process through this review than the amount required by law. Commenters had multiple opportunities to review and comment on all of the critical documents underlying the review (notably the ISA, the RA, and the PA), as well as on all of the critical scientific and policy issues, assumptions, and factual data informing the review as discussed in the proposal (77 FR 38890). Given that the basic question being addressed throughout this proceeding is whether or not it is appropriate to revise the 2006 standard (CAA section 109 (d)), that issue was necessarily before the public for comment (as evidenced by all the comments urging retention of the standard, among other indicia of proper notice). Nor does the EPA’s prop osal indicate a pre

- judgment of the outcome of the review. Rather, the proposal reflected the EPA’s consideration of the body of scientific data and analysis comprising the record for this review.

The EPA strongly disagrees that the currently available sci entific evidence and technical information supports consideration for retaining the annual standard level at 15 μg/m 3

. and consequently did not propose to do so

. As discussed in section III.D.3. of the preamble for the final rule, having carefully considered CASAC advice and the public comments on the proposal as discussed in section III.D.2 preamble to the final rule and in section II.B.1 above, the EPA believes the fundamental scientific conclusions on the effects of PM 2.5 reached in the ISA, and discussed in the PA, are valid. The Agency believes that since the last review the overall uncertainty about the public health risks associated with both long

- and short

- ter m exposure to PM 2.5 has been diminished to an important degree. The remaining uncertainties in the available evidence do not diminish confidence in the associations between exposure to fine particles and mortality and serious morbidity effects. Based on th e Agency’s increased confidence in the association between exposure to PM 2.5 and serious public health effects, combined with evidence of such an association in areas that would meet the current standards , the Administrator agrees with CASAC that revision of the current suite of PM 2.5 standards to provide increased public health protection is necessary. Based on these considerations discussed in section III.D.3 of the preamble to the final rule, the Administrator concludes that the current suite of primary PM 2.5 standards is not sufficient, and thus not requisite, to protect public health with an adequate margin of safety, and that revision is needed to increase public health protection. Furt hermore, as discussed in section III.E.4.e of the proposal, the Ad ministrator provisionally concluded that the available scientific information supportedDraft

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95 consideration of an annual standard level no higher that 13 μg/m 3 . In considering public comments on the proposal as discussed in sections III.E.4.c.i and III.E.4.d of the preamble for the final rule and above, the Agency concludes there is no scientific basis for considering retaining the annual standard level at 15 μg/m 3 (absent a substantially lower level of the daily standard)

. (7) Comment: Some of these commenters also identified “new” studies as providing additional evidence to support their views that the annual standard level needs to be lowered

. Response: As discussed in section II.B.3 of the preamble to the final rule and in section II.B.1.a above, the EPA notes that, as in past NAAQS reviews, the Agency is basing the final decisions in this review on the studies and related information included in the PM ISA that have undergone CASAC and public review, and will consider newly published studies for purposes of decision making in the next PM NAAQS review. Nonetheless, i n provisionally evaluating commenters’ arguments, the EPA notes that its provisional asses sment of “new” science found that such studies did not materially change the conclusions reached in the ISA (U.S. EPA, 2012b).

b. 24

- Hour Standard

With respect to the level of the 24

- hour standard, the EPA received comments on the proposal from two distinct g roups of commenters. One group that included virtually all commenters representing industry associations

, businesses

, and many States agreed with the Agency’s proposed decision to retain the level of the 24

- hour PM 2.5 standard. The other group of commenter s included many medical groups, numerous physicians and academic researchers, many public health organizations, some State and local agencies, five s tate a ttorneys g eneral, and a large number of individual commenters. These commenters disagreed with the Ag ency’s proposed decision and argued that EPA should lower the level of the 24

- hour standard to 30 or 25 μg/m 3 . Comments from these groups

on the level of the 24

- hour PM 2.5 standard are a ddressed in section III.E.4.c.ii in the preamble for the final rule an d below

.

i. Support for Retaining the Current Level

O f the public commenters who addressed the level of the 24

- hour PM 2.5 standard, all industry commenters and most State and l ocal commenters supported the proposed decision to retain the current level of 35 g/m 3 . In many cases, these groups agreed with the rationale supporting the Administrator’s proposed decision to retain the current 24

- hour PM 2.5 standard, including her emphasis on the annual standard as the generally controlling standard with the 24

- hour standard providing supplementary protection, and her conclusion that multi

- city, short

- term exposure studies provide the strongest data set for informing decisions on the appropriate 24

- hour standard level. Many of these commenters agreed with the Administ rator’s view that the single

- city, short

- term studies provided a much more limited data set (e.g., limited statistical power, limited exposure data) and more equivocal results (e.g., mixed results within the same study area), makingDraft

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96 them an unsuitable basi s for setting the level of the 24

- hour standard.

(1) Comment: While these commenters agreed with the EPA’s proposed decision to retain the current 24

- hour PM 2.5 standard, some did not agree with the EPA’s approach to considering the evidence from short

- term m ulti

- city studies. For example, a commenter representing UARG pointed out that the 98 th percentile concentrations reported in the proposal for multi

- city studies reflect the averages of 98 th percentile concentrations across the cities included in those stu dies (UARG, 2012; Attachment 1; p. 25). This commenter contended that such averaged 98 th percentile PM 2.5 concentrations do not provide information that can appropriately inform a decision on the adequacy of the public health protection provided by the cur rent or alternative 24

- hour standards

. Response: While the EPA agrees that there is uncertainty in linking effects reported in multi

- city studies to specific air quality concentrations (U.S. EPA, 2011, section 2.3.4.1), the EPA disagrees with this commenter’s view that such uncertainty precludes the use of averaged 98 th percentile PM 2.5 concentrations to inform a decision on the appropriateness of the protection provided by the 24

- hour PM 2.5 standard. In particular, the EPA notes that averaged 98 th percentile concentrations do provide information on the extent to which study cities contributing to reported associations would likely have met or violated the current 24

- hour PM 2.5 standard during the study period. As evidence of this, the EPA notes the three multi

- city studies specifically highlighted by this commenter as having averaged 98 th percentile 24

- hour PM 2.5 concentrations below 35 g/m 3 (Dominici et al., 2006; Bell et al., 2008; Zanobetti and Schwartz, 2009). Based on the 98 th percentiles of 2 4

- hour PM 2.5 concentrations in the individual cities evaluated in these studies, the EPA notes that the majority of these study cities would likely have met the current standard during the study periods (Hassett

Sipple et al., 2010). Therefore, regardless of whether the averaged 98 th percentile concentrations or the 98 th percentile concentrations in each city are considered, these studies provide evidence for associations between short

- term PM 2.5 and mortality or morbidity across a large number of U.S. citi es, the majority of which would likely have met the current 24

- hour PM 2.5 standard during study periods. In their review of the PA, CASAC endorsed the conclusions drawn from analyses of averaged 98 th percentile 24

- hour PM 2.5 concentrations ( Samet, 2010d ) a nd the EPA continues to conclude that this type of information can appropriately inform the Administrator’s decision on the current 24

- hour PM 2.5 standard. 37

(2) Comment: One commenter questioned whether the 24

- hour standard would offer any additional protection beyond the protection provided by the annual standard

. This commenter argued that EPA has not provided any evidence that the 24

- hour

37 This is not to say that the EPA’s decision on whether to revise the 24

- hour PM 2.5 standard should be based on or only be informed by considerations of whether studies reported associations with mortality or morbidity in areas with averaged 98 th percentile PM 2.5 concentrations less than 35 mg/m 3 . As discussed in section III.E.4.d of the preamble to the final rule , in reaching a decision in th e final notice on the most appropriate approach to strengthen the su ite of PM 2.5 standards, the Administrator considers the degree of public health protection provided by the combination of t he annual and 24

- hour standards together.Draft

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97 standard is necessary to protec t public health and asserted that the EPA should better explain why the existing 24

- hour standard is not more stringent than
necessary (API, 2012, p. 9). More specifically, based on statements in the PA (quoting “there is no evidence suggesting that risks associated with long

- term exposures are likely to be disproportionately driven by peak 24

- hour concentrations” and citing to several studies that evaluated the effect on the magnitude and statistical significance of the association between PM 2.5 health imp acts with and without high PM concentrations days, finding very little difference, U.S. EPA, 2011a, p. 2

- 9 ) , this commenter asserted “If the annual standard is protective of effects from both short

- and long

- term exposures, and no additional effects are ob served with peak events, this indicates that there is likely no additional benefit to having the 24

- hour standard. Retaining the 24

- hour standard, therefore, would be an additional level of protection, or ‘margin of safety’” (API, 2012, Attachment 1, p.2).

Response: The EPA disagrees with the commenter’s contention that evidence has not been provided to support the appropriateness of the retaining the current 24

- hour standard in conjunction with revising the annual standard. T he EPA has carefully consider ed the degree of public health protection provided by the annual and 24

- hour PM 2.5 standards working together

. As highlighted by commenters and a s discussed in section III.E.4.d of the preamble to the final rule , based on the evidence and quantitative risk assessment, the EPA concludes that it is appropriate to set an annual standard with a level of 12 μ g/m 3 to provide protection from both long

- and short

- term PM 2.5 exposures. In conjunction with the revised annual standard, the EPA concludes it is also app ropriate to retain the current 24

- hour standard in order to provide supplemental protection in areas with high peak

- to

- mean ratios of PM 2.5 concentrations, possibly associated with strong local or seasonal sources, and against PM 2.5 - related effects that ma y be associated with shorter

- than daily exposure periods.

A s discussed in more detail in section III.E.4.a of the preamble to the final rule

, in reaching this conclusion the EPA notes that multi

- city studies provide clear evidence for positive and statistically significant associations with short

- term PM 2.5 concentrations in locations with averaged (i.e., averaged across study cities) 98 th percentile 24

- hour concentrations from 45.8 to 34.2 μg/m 3 (Burnett et al., 2004; Zanobetti and Schwartz, 2009; Bell et al., 2008; Dominici et al., 2006a, Burnett and Goldberg, 2003; Franklin et al., 2008). I n many locations, the revised annual P M 2.5 standard is expected to protect against the effects reported in these studies. However , some areas of the United Stat es, particularly in the northwest, could experience 98 th percentile 24

- hour PM 2.5 concentrations above 35 mg/m 3
while annual PM 2.5 concentrations remain below 12 g/m 3 (U.S. EPA, 2011, Figure 2

- 10). In such locations, the current 24

- hour standard is necess ary to provide protection against effects that have been associated with short

- term PM 2.5 exposures. Without the 24

- hour standard in place, short

- term PM 2.5 concentrations in some locations could be allowed to exceed those that have clearly been associated with mortality and morbidity. Therefore , the EPA disagrees with
commenters who call into question support for the conclusion that the 24

- hourDraft

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98 standard provides appropriate supplementary protection against effects that have been associated with fine particle exposures.

ii. Support for Revising the Current Level

A nother group of commenters argued that the 24

- hour standard level should be lowered . Many of thes e commenters supported setting the level of the 24

- hour PM 2.5 standard at either 25 or 30 g/m 3

. (1) Comment: In support of their position, the ALA et al., AHA et al., five state Attorneys General, and a number of additional groups pointed to 98 th percentile PM 2.5 concentrations in locations of multi

- city and single

- city epidemiological studies. For example, the ALA and others pointed to multi

- city studies by Dominici et al. (2006), Zanobetti and Schwartz (2009), Burnett et al. (2000), and Bell et al. (2008) a s providing evidence for associations with mortality and morbidity in study locations with averaged (i.e., averaged across cities) 98 th percentile 24

- hour PM 2.5 concentrations below 35 g/m 3 . These commenters also pointed to several single

- city and panel studies reporting associations between short

- term PM 2.5 and mortality or morbidity in locations with relatively low 24

- hour PM 2.5 concentrations. Because some of these multi

- and single

- city studies have reported associations with health effects in locatio ns with 98 th percentile PM 2.5 concentrations below 35 g/m 3 , commenters maintained that the current 24

- hour PM 2.5 standard (i.e., with its level of 35 g/m 3 ) does not provide an appropriate degree of protection in all areas.

In further support of their pos ition that the level of the current 24

- hour standard should be lowered , these commenters pointed out the variability across the U.S. in ratios of 24

- hour to annual PM 2.5 concentrations. They noted that some locations, including parts of the northwestern U. S., experience relatively low annual PM 2.5 concentrations but can experience relatively high 24

- hour concentrations at certain times of the year. In order to provide protection against effects associated with short

- term PM 2.5 exposures, especially in locat ions with high ratios of 24

- hour to annual PM 2.5 concentrations, these commenters advocated setting a lower level for the 24

- hour standard.

Response: The EPA agrees with these commenters that it is appropriate to maintain a 24

- hour PM 2.5 standard in order to supplement the protection provided by the revised annual standard, particularly in locations with relatively high ratios of 24

- hour to annual PM 2.5 concentrations. However, in highlighting 98 th percentile PM 2.5 concentrations in study locations without also considering the impact of a revised annual standard on short

- term concentrations, these commenters ignore the fact that many areas would be expected to experience decreasing short

- and long

- term PM 2.5 concentrations in response to a revised annual st andard. See American Trucking Ass ociation v. EPA , 283 F. 3d at 373 (rejecting argument to lower the level of the 24

- hour PM 2.5 standard since the argument had failed to account for the reductions in the entire air quality distribution resulting from the implementation of the annual standard).Draft

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99 In considering the specific multi

- city studies highlighted by public commenters who advo cated a more stringen t 24

- hour standard, the EPA notes that such studies have reported consistently positive and statistically significant associations with short

- term PM 2.5 exposures in locations with averaged 98 th percentile PM 2.5 concentrations ranging from 45.8 to 34.2 μg/m 3 and long

- term mean PM 2.5 concentrations rang ing from 13.4 to 12.9 (Burnett and Goldberg, 2003; Burnett et al., 2004; Dominici et al., 2006 a ; Bell et al., 2008; Franklin et al., 2008; Zanobetti and Schwartz, 2009). 38 The EPA notes th at to the extent air quality distributions are reduced to meet the current 24

- hour standard with its level of 35 g/m 3 and/or the revised annual standard with its level of 12 g/m 3 , additional protection would be anticipated against the effects reported in these short

- term , multi

- city studies. Put another way, to attain an annual standard with a level below the long

- term means in the locations of these short

- term studies (as EPA is adopting in the final rule), the overall air quality distributions in the ma jority of study cities will necessarily be reduced, resulting in lower daily PM 2.5 ambient concentrations. We therefore expect that the revised annual standard will result in 98 th percentile PM 2.5 concentrations in these cities that are lower than those me asured in the studies, and that the overall distributions of PM 2.5 concentrations will be lower than those reported to be associated with health effects. Thus, even for effects reported in multi

- city studies with averaged 98 th percentile concentrations bel ow 35 μ g/m 3 , additional protection from the risks associated with short

- term exposures is anticipated from the revised annual standard, without revising the 24

- hour standard, because long

- term average PM 2.5 concentrations in multi

- city study locations were above the level of the revised annual standard (i.e., 12 μ g/m 3 ). 39 As discussed above, reducing the annual standard is the most efficient way to reduce the risks from short

- term exposures identified in these studies, as the bulk of the risk comes from the large number of days across the bulk of the air quality distribution, not the relatively small number of days with peak concentrations. See American Trucking Ass ociation , 283 F. 3d at 372 (endorsing this reasoning).

In considering the single

- city studies h ighlighted by public commenters who advocated a more stringen t 24

- hour standard, the EPA first notes that, overall, these single

- city studies reported mixed results. Specifically, some studies

38 Commenters also highlighted associations with short

- term PM 2.5 concentrations reported in sub

- analyses restricted to days with 24

- 3 (Dominici, 2006b). These sub

analyses were not included in the original publication by Dominici et al. (2006a). Authors provided results of sub

- analyses for the Administrator ’s consideration in a letter to the docket following publication of the proposed rule in January 2006 (personal communication with Dr. Francesca Dominici, 2006b). As noted in section III.A.3 of the preamble to the final rule and to the proposal , these sub

- analyses are part of the basis for the conclusion that there is no evidence suggesting that risks associated with long

- term exposures are likely to be disproportionately driven by peak 24

- hour concentrations. Because the sub

- analyses did not present long

- t erm average PM 2.5 concentrations, it is not clear whether they reflected PM 2.5 air quality that would have been allowed by the revised annual PM 2.5 standard being established in this notice.
39 It is also the case that additional protection is anticipated i n locations with 98 th percentile 24

- hour PM 2.5 concentrations above 35 μg/m 3 , even if long

- term concentrations are below 12 μg/m 3 . As noted in the proposal (77 FR 38938) and in the PA (U.S. EPA, 2011, Figure 2

- 10), as well as by a number of the commenters (e.g., ALA et al., 2012, p. 26), parts of the northwestern U.S. are more likely than other parts of the country to violate the 24

- hour standard and meet the revised annual standard.Draft

– Do Not Quote or Cite December 1 1 , 2012

100 reported positive and statistically significant associations wi th PM 2.5 , some studies reported positive but non

- significant associations, and several studies reported negative associations or a mix of positive and negative associations with PM 2.5 . In light of these inconsistent results, the proposal noted that the ove rall body of evidence from single

- city studies is mixed, particularly in locations with 98 th percentile s of 24

- hour concentrations below 35 μg/m 3 . Therefore, a lthough some single

- city studies report ed effects at appreciably lower PM 2.5 concentrations than short

- term multi

- city studies, the uncertainties and limitations associated with the single

- city studies were noted to be greater . In light of these greater uncertainties and limitations, the Administrator concluded in the proposal that she had less confid ence in using these studies as a basis for setting the level of the standard (77 FR 38943).

Given the considerations and conclusions noted above, in the proposal the Administrator concluded that the short

- term multi

- city studies provide the strongest evid ence to inform decisions on the level of the 24

- hour stan dard. F urther , she viewed single

- city, short

- term exposure studies as a much more limited data set providing mixed results, and she had less confidence in using these studies as a basis for setting t he level of a 24

- hour standard (77 FR 38942)

. In highlighting specific single

- city studies, public health, environmental, and State and local commenters appear to have selectively focused on studies reporting associations with PM 2.5 and to have overlooked studies that reported more equivocal results (e.g., Ostro et al., 2003; Rabinovitch et al., 2004; Slaughter et al., 2005; Villeneuve et al., 2006) (U.S. EPA, 2011, Figure 2

- 9). As such, these commenters have not presented new information that causes the EP A to reconsider its decision to emphasize multi

- city studies over single

- city studies when identifying the appropriate level of the 24

- hour PM 2.5 standard.

In further considering the single

- city studies highlighted by public commenters, the EPA notes that some commenters advocating for a lower level for the 24

- hour PM 2.5 standard also discussed short

- term studies that have been published since the close of the ISA. These recent studies were conducted in single cities or in small panels of volunteers. As in prior NAAQS reviews and as discussed in more detail in section II.B.3 of the preamble to the final rule and in section II.B.1.a above , the EPA is basing its decisions in this review on studies and related information assessed in the ISA. The studies assess ed in the ISA, and the conclusions based on those studies, have undergone extensive critical review by the EPA, CASAC, and the public. The rigor of that review makes the studies assessed in the ISA, and the conclusions based on those studies, the most reli able source of scientific information on which to base decisions on the NAAQS.

(2) Comment: Some p ublic health, medical, and environmental commenters also criticized the EPA’s interpretation of PM 2.5 risk results. These commenters presented risk estimates for combinations of annual and 24

- hour standards using more recent air quality data than that used in the EPA’s RA (U.S. EPA, 2010a). Based on these additional risk analyses, the ALA and other commentersDraft

– Do Not Quote or Cite December 1 1 , 2012

101 contended that public health benefits could continue to increase as annual and 24

- hour standard levels decrease below 13 g/m 3 and 35 g/m 3 , respectively.

Response: The EPA agrees with these commenters that important public health benefits are expected as a result of revising the level of the annual standard to 12 g/m 3 , as is done in the final rule, rather than 13 g/m 3 . The Agency also acknowledges that estimated PM 2.5 - associated health risks continue to decrease with annual standard levels below 12 g/m 3 and/or with 24

- hour standard levels below 35 g/m 3 . However, the EPA disagrees with the commenters’ views regarding the extent to which risk estimates support setti ng standard levels below 12 μg/m 3 (annual standard) and 35 g/m 3 (24

- hour standard). 40

The CAA charges the Administrator with setting NAAQS that are “requisite” (i.e., neither more nor less stringent than necessary) to protect public health with an adequat e margin of safety . In setting such standards the Administrator must weigh the available scientific evidence and information, including associated uncertainties and limitations . As described above, in reaching her proposed decisions on the PM 2.5 standards that would provide “requisite” protection , the Administrator carefully considered the available scientific evidence and risk information , making public health policy judgments that , in her view, neither
overstate d nor understate d the strengths a nd limitations of that evidence and information. In contrast, a s discussed more fully above

, public health, medical, and environmental commenters who recommended levels below 35 g/m 3 for the 24

- hour PM 2.5 standard have not provided new information or anal yses to suggest that such standard levels are appropriate, given the uncertainties and limitations in the available health evidence , particularly uncertainties in studies conducted in locations with 98 th percentile 24

- hour PM 2.5 concentrations below 35 g/ m 3 and long

- term average concentrations below 12 g/m 3

.

40 This section focuses on the 24

- hour standard. Section III.E.4.c.i of the preamble to the final rule and section II.B.5.a.i above also discuss these commenters’ recommendations within the context of the annual PM 2.5 standard.