Draft – Do Not Quote or Cite December 11, 2012

II-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 comments on the proposed primary PM2.5 

standards, as requested yesterday. Please let me know if you have any questions. Thanks.
Draft – Do Not Quote or Cite December 11, 2012

II-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 PM2.5 exposure studies 

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

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

relationship between long-term PM2.5 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; TCEQTexas 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) PM2.5 exposure and mortality. The 

commenters interpreted the results of the analysisthese analyses as evidence of unmeasured 

confounding in the long-term PM2.5 exposure-mortality relationship. These commenters 

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

a causal relationship exists between long-term PM2.5 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 evaluated 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 studies 
Draft – Do Not Quote or Cite December 11, 2012

II-3

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

PM2.5 concentrations over the preceding 12 months and monthly mortality rates in 113 U.S. 

counties. and examined whether community-specific trends in monthly PM2.5 concentrations and 

mortality declined at the same rate as the national rate. The investigators decomposedexamined 

this by decomposing the association between PM2.5 and mortality into two components: (1) 

“national trends”national trends, defined as the association between the national average trend in 

monthly PM2.5 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 PM2.5 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 Greven et al. (2011). These analyses demonstrated associations similar in 

magnitude and precision to other studies of long-term PM2.5 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.1The authors provided no references to support their assumptions that 

associations between PM2.5 and mortality should be similar across temporal 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 PM2.5 and mortality in their national analyses. 

 

1 Unmeasured confounders need to be factors that are associated with both the exposure and 

outcome of interest, but in the case of the Janes and Greven studies 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 Integrated Science Assessment, 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 

supported the determination that there is a causal relationship between long-term PM2.5 exposure 

and mortality.
Draft – Do Not Quote or Cite December 11, 2012

II-4

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

pollution and mortality in their 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) was

attributable to spatial variability, which the authors chose to discard. As noted above, the 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 PM2.5 concentrations averaged over the previous 

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

component, i.e.,“local” trends analysis, which examined county-specific deviations in monthly 

PM2.5 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 PM2.5 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 PM2.5 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 PM2.5 concentrations between cities, while Janes et al. (2007) and Greven et al. 

(2011) focus primarily on temporal differences in PM2.5 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 PM2.5 levels and average age-adjusted mortality rates 

across cities (purely spatial or cross-sectional association).”
Draft – Do Not Quote or Cite December 11, 2012

II-5

information is not accounted for in [Janes 2007], it is not as surprising that... vastly different 

estimates of the PM2.5/mortality relationship [were observed] than in other studies that do exploit 

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

ConsistentThe 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 consistent with comments on the Janes et al. (2007) study articulated in 

Pope and Burnett (2007), the EPA notes4 which noted that an important limitation of the local 

scale analysis conducted by Janes et al. (2007) and subsequently by Greven et al. (2011) iswas

the subchronic exposure window considered in these analyses. Both studies used annual average 

PM2.5 concentrations to characterize long-term national trends which iswas consistent with 

exposure windows considered in other studies of long-term exposure to PM2.5 and mortality

studies..

5 However, the local scale analyses used monthly average PM2.5 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 temporal 

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 years) measures of PM2.5.

As discussed by Pope and Burnett (2007) and highlighted in the Integrated Science 

Assessment, 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

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 Comments document.

5 As noted above, however, Janes et al. (2007) and Greven et al. (2011) focused on temporal 

variability and other studies of long-term exposure to PM2.5 and mortality focus on spatial 

variability.
Draft – Do Not Quote or Cite December 11, 2012

II-6

long-term exposure to PM2.5 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 those used in other studies of long-term exposure to PM2.5 and 

mortality, including the American Cancer Society (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 PM2.5 on mortality risk, 

and did not conduct any analyses relying on the temporal variation in PM2.5. The opposite is true 

of the Janes et al. (2007) and Greven et al. (2011) studies which first removed the spatial 

variability in PM2.5 and then examined the temporal variation at both the national and local scale 

to measure the effects of temporal differences in PM2.5 on mortality risk. Janes et al. (2007) and 

Greven et al. (2011) focus on changes in PM2.5 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 PM2.5-mortality 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 

PM2.5 concentrations.

As detailed in the Integrated Science Assessment (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 PM2.5 exposure and mortality “have 

developed 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 in 
Draft – Do Not Quote or Cite December 11, 2012

II-7

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 national or local scale as time-varying 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 covariates 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 PM2.5 over time and not space, the results from these two studies do not 

provide any indication that other studies of long-term exposure to PM2.5 and mortality exhibit 

spatial confounding, or that PM2.5 does not cause mortality.6The 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 highlighted 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 

variability.” 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 Comments 

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 Greven et al. (2011) provide no information 

relevant to examining confounding in studies of short-term exposure to PM2.5.
Draft – Do Not Quote or Cite December 11, 2012

II-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 supported the determination that there is a 

causal relationship between long-term PM2.5 exposure and mortality

In conclusion, the EPA believesinterprets the results of the analyses conducted by Janes 

et al. (2007) and Greven et al. (2011) areas being consistent with prior knowledge of examining 

associations with long-term exposure to PM2.5 at the national scale using long-term average 

PM2.5 concentrations. However, forFor 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 

PM2.5 and mortality. Therefore, the EPA concludes that these studies do not bring into 

questioninvalidate the large body of epidemiological evidence indicatingthat supports the EPA’s 

determination that a causal associationrelationship exists between long-term PM2.5 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 epidemiological studies” (Dominici, 2012, p. 1 (emphasis 

original)).
Draft – Do Not Quote or Cite December 11, 2012

II-9

II. RESPONSES TO SIGNIFICANT COMMENTS ON PROPOSED PRIMARY PM2.5

STANDARDS

A. General Comments on Proposed Primary PM2.5 Standards

A large number of comments on the proposed primary standards for PM2.5 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 PM2.5 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 proposed 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 PM2.5

standards are addressed in the preamble to the final rule and/or in this document. In particular, 

significant public comments related to whether or not the current PM2.5 standards should be 

revised are addressed in section III.D.2 of the preamble. Sections III.E.1, III.E.2, III.E.3, and 

III.E.4.c of the preamble 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 PM2.5 are discussed in section V of the preamble. Significant 

comments on the data handling conventions for PM2.5 are discussed in section VII.A of the 

preamble. Below, the EPA provides more specific responses to the full range of significant issues 

raised in the public comments on these issues.

B. Specific Comments on Proposed Primary PM2.5 Standards

A large number of commenters provided more detailed comments regarding the proposal 

to revise the level and form of the primary annual PM2.5 standard in conjunction with 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 support or oppose any 

revision to the current PM2.5 primary standards. The responses to these comments are generally 

discussed in section III.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 PM2.5 standards are addressed in 

sections III.E.4.c.i and III.E.4.c.ii in the preamble to the final rule and discussed more fully 

below in sections II.B.5.a and II.B.5.b respectively. Incorporating responses contained in 

sections III.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.
Draft – Do Not Quote or Cite December 11, 2012

II-10

a. Support for Revising the Current Standards

Many public comments asserted that the current PM2.5 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 American 

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, academic 

researchers, health professionals, and many private citizens.

All of these medical and public health commenters stated that the current PM2.5 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 also expressed such views.

The National Association of Clean Air Agencies (NACAA), the Northeast States for 

Coordinated Air Use Management (NESCAUM), and many state and local air agencies and 

health departments who commented on the PM2.5 standards supported revision of the suite of 

current PM2.5 standards, as did five state attorneys general (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 large 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 PM2.5 standards as articulated in section 

III.D of the preamble to proposal. Many of these commenters, however, generally

expressed views differing from the EPA’s proposed judgments about the extent to which 

the standards should be revised based on this evidence, specifically for providing 

protection for 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 Advisory Committee’s (CASAC) interpretation of the body of available 

evidence and CASAC’s recommendation to revise the PM2.5 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 developmental 

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 – Do Not Quote or Cite December 11, 2012

II-11

o Extended analyses of seminal long-term exposure studies - the American 

Cancer Society (ACS) (Krewski et al., 2009), Harvard Six Cities (Laden et al., 

2006), and Southern California Children’s Health (Gauderman et al., 2004) 

studies.

o Additional long-term exposure studies available in this review, specifically a 

study of premature mortality in older adults (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 PM2.5 exposures at 

lower concentrations than had previously been observed, including studies of 

effects in at-risk populations.

o A number of short-term PM2.5 exposure studies providing evidence of 

mortality and morbidity effects at concentrations below the level of the 

current 24-hour PM2.5 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).

Single-city short-term PM2.5 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).

Progress has been made in reducing many of the uncertainties identified in the last 

review, in better understanding mechanisms by which PM2.5 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.

PM2.5-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 based on 2005 air quality data. In this study, the EPA staff published 

estimates that “peg the annual toll from PM2.5 at 130,000 premature 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 another 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 of population-level data (i.e., health event 

data and study population data) provide important information beyond a single 

 

8

Fann et al., 2012
Draft – Do Not Quote or Cite December 11, 2012

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 PM2.5 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 this evidence provides a strong basis for concluding that the current PM2.5

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 

discussed 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 better understand mechanisms by which 

PM2.5 may be causing the observed health effects and to improve our understanding of atrisk populations, the EPA notes that CASAC found that the ISA clearly presented and 

discussed the current scientific information related 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 PM2.5-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 significant associations between PM2.5

and lung cancer.” Id.

Response: The 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 section 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 focused on 

understanding 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 

concentrations” (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 – Do Not Quote or Cite December 11, 2012

II-13

The EPA fully 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 PM2.5 exposures. 

In developing the second draft ISA, the EPA reexamined the controlled human 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 determinations 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, pp. 2 and 10).

With regard to traffic studies, the EPA disagrees with 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 specific air pollutants, including PM2.5, 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 collective body of evidence on the relationship between 

long- or short-term exposure to ambient concentrations of PM2.5 and health effects.

(3) Comment: A number of commenters argued that by making the standards more 

protective, the PM2.5 NAAQS would be more consistent with other existing standards 

(e.g., California's annual average standard of 12 μg/m3) (CARB, 2012; CA OEHHA, 

2012). Some commenters argued that “in the intervening decade since the California 

standard was established, substantial new information regarding 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 PM2.5 standards would be more 

consistent with the recommendations of the World Health Organization (WHO) and/or 

Canada (e.g., ALA et al., 2012, pp. 22 and 62; ISEE, 2012, p. 2; MOE-Ontario, 2012, p. 

1).

Response: In considering these comments, the EPA notes that 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 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 State of 

California or Canada or the guidelines established by a working group of scientists within 

the WHO. 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 requirements that must be met.
Draft – Do Not Quote or Cite December 11, 2012

II-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 

proposal in reaching her conclusions regarding final decision on the appropriate primary 

annual PM2.5 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 PM2.5

standards.

Response: In the proposal, the EPA recognized that there 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). As discussed in section II.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 was fully aware of the “new” science that has developed since 

2009 before making final decisions on whether to retain or revise the current PM 

NAAQS. 

Specifically, the EPA screened and surveyed the recent health literature, including but not 

limited to studies submitted during 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 assessment, 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 ISA and provide important insights on the relationship 

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 strongest 

causality determination possible under the EPA framework). Although some of the “new” 

epidemiological studies report effects in areas with lower PM2.5 concentrations than those 

in earlier studies considered in the ISA, and “new” toxicological and epidemiological 

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 regarding 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 development of the ISA. The rigor of that review makes these studies, and 
Draft – Do Not Quote or Cite December 11, 2012

II-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 subjected

as well to the public review 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 criteria. 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 its 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 (October 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 governing 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 – Do Not Quote or Cite December 11, 2012

II-16

(5) Comment: Some commenters 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 strengthen 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) and 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 reviews (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 PM2.5 standards. These views 

were most extensively presented in comments from the Utility Air Regulatory Group (UARG), 

representing a group of electric generating companies and organizations 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 progress 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 significantly 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 inconsistent 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 studies do not provide supportive 

evidence that the health effects observed in epidemiological studies are biologically 

plausible
Draft – Do Not Quote or Cite December 11, 2012

II-17

uncertainties in the underlying health science are as great or greater than in the PM 

NAAQS review completed in2006

there is no evidence of greater risk since the last review to justify tightening the 

current annual PM2.5 standard

“new” studies not included in the ISA continue to increase uncertainty about possible 

health risks associated with exposure to PM2.5

These comments and other 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 These commenters further contended that the EPA relied on a 

selective group of long- and short-term PM2.5 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., 2012, pp. 22 to 25; Texas CEQ, 2012, 

pp 2 to 3; UARG, Attachment 1, p. 17 to 23). These allegations included: “cherry-picking 

studies” and ignoring a number of studies that reported no association with PM2.5. 

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 by 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 review 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 recommend 

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 causality determinations reached in the 

ISA. The commenters’ specifically focused on counting the number of epidemiological

studies that reported 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 ISAs (e.g., UARG, 2009; 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 – Do Not Quote or Cite December 11, 2012

II-18

determinations and in determining the form and level of the PM2.5 and PM10 standards. 

The more detailed characterizations of individual studies included an assessment of the 

quality of the study, which was based on specific criteria as described in the ISA (U.S.

EPA, 2009a, section 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 statistical model specifications. Statistical 

significance is just one of the means of evaluating the validity of the relationships 

determined with epidemiological studies. The EPA can reasonably 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 epidemiological studies, 

even if individual studies may lack statistical significance. American Trucking 

Association 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 consistency, and has not focused solely on statistical significance as a criterion of 

study reliability. 

It has been clearly articulated throughout the epidemiological and causal inference 

literature that it is important not to focus on results of statistical tests to the exclusion 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 values, 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 health effects on PM2.5 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 overreliance on statistical significance in evaluating the overall evidence for an exposureresponse 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 nothing 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). The 
Draft – Do Not Quote or Cite December 11, 2012

II-19

dominant approach to statistical inference today, which employs 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 mathematical 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 testing 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 study 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 long- and short-term 

exposure studies considered “key” multi-city studies for consideration for informing the 

decisions on the appropriate standard levels and included those studies observing effects 

for which the evidence supported a causal or likely causal association. Figure 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 PM2.5 concentrations than had previously been considered in the last review. 

The EPA notes that many of these studies evaluated multiple health endpoints, and 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 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, and 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 

and 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 epidemiological studies, 

and subsequently during the process of forming causality determinations, the EPA has 

emphasized the pattern of results across epidemiological studies for drawing conclusions 

on the relationship between PM2.5 and health outcomes, and whether the effects observed 

are coherent across the scientific 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 preamble 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 the 
Draft – Do Not Quote or Cite December 11, 2012

II-20

EPA’s changes (in the second versus first draft ISA) from “likely causal” to “causal” for 

long-term exposure to PM2.5 and cardiovascular effects and for cancer and PM2.5 (from 

“inadequate” to “suggestive”). Id. Furthermore, CASAC recommended “upgrading” the 

causal classification for PM2.5 and total mortality to “causal” for both the short- and longterm timeframes. Id. With 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 PM2.5 and mortality, consistent with the CASAC comments” (Jackson, 2012). With 

respect to ultrafine particles, in developing the second draft ISA, the EPA reexamined the 

controlled human 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 

determinations 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 

reflect 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 null or 

inconsistent findings in numerous long-term mortality studies with reported PM2.5

concentrations above and below the level of the current annual standard.

Response: As discussed in section 1.5.3 of the ISA, the EPA thoroughly considered the 

uncertainties 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 PM2.5 exposure and cardiovascular effects”; 

however, in reaching this conclusion, the Agency recognized and considered limitations 

of the current evidence that still requires further examination (U.S. EPA, 2009a, section 

6.2.12.1). Therefore, the 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, section 1.5.4).

10 The 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 – Do Not Quote or Cite December 11, 2012

II-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 supports 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, Figures 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 PM2.5 is considerable, 

including large subgroups of the U.S. population that have been identified as at-risk 

populations (e.g., children, older adults, persons 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 PM2.5 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 risk. Taken together, this information indicates that exposure to 

ambient PM2.5 concentrations has substantial public health impacts.

Additionally, the EPA disagrees with the commenter that long-term PM2.5 exposure 

studies with null or inconsistent findings were not accurately presented in the ISA. For 

example, as discussed throughout section 7.6 and depicted in Figures 7-6 and 7-7, the 

EPA presented the collective evidence from all studies that examined the association 

between long-term PM2.5 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 sections 7.1 and 7.2 of the ISA supported that a causal relationship exists between 

long-term PM2.5 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 was a causal association between 

mortality and multiple criteria pollutants. These commenters contended, “[i]n doing so, 

the EPA attributes the cause of the mortality 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 reviewing 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 gaseous criteria pollutants. Epidemiological 

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 most strongly associated with mortality. It is 
Draft – Do Not Quote or Cite December 11, 2012

II-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 pollutants. 

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 PM2.5, the EPA has carefully evaluated the 

potential for confounding, effect measure modification and the role of PM as a 

component of a complex mixture of air pollutants (U.S. EPA, 2009a, pp. 1 to 9). The 

EPA used a rigorous weight of evidence approach to inform its causality determinations

that evaluated consistency across studies within a discipline, evidence for coherence 

across disciplines, and biological plausibility. Additionally, during this process, the EPA 

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

was the collective evidence, not one individual study that ultimately determined whether 

a causal relationship exists between PM2.5 and specific health outcomes. 

In the ISA, the combination of epidemiological, toxicological, and controlled human 

exposure studies formed the basis for the Agency concluding that a causal relationship 

exists between short- or long-term PM2.5 exposures and total mortality (U.S. EPA, 2009a, 

sections 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 PM2.5 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 that a causal relationship exists between long-term PM2.5 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 

PM2.5 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) publications, (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 
Draft – Do Not Quote or Cite December 11, 2012

II-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, 

2009a, 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, 2012b). In the EPA’s evaluation of the relationship 

between long-term exposure to PM2.5 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, section 7.6.5.1). For the reasons discussed below, 

the 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 PM2.5 over the preceding 12 months and monthly mortality 

rates in 113 U.S. counties and examined whether community-specific trends in monthly 

PM2.5 concentrations and mortality declined at the same rate as the national rate. The 

investigators examined this by decomposing the association between PM2.5 and mortality 

into two components: (1) “national” trends, defined as the association between the 

national average trend in monthly PM2.5 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 PM2.5 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 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 

PM2.5 and mortality in their national analyses. However, Janes et al. (2007) and Greven et 

al. (2011) eliminated all of the spatial variation in air pollution and mortality in their 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) was

attributable to spatial variability, which the authors chose to discard. The 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 PM2.5 concentrations averaged 

over the previous 12 months and the national average trend in monthly mortality rates

and (2) a space-by-time component, i.e., the “local” trends analysis, which examined 

county-specific deviations in monthly PM2.5 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 supported the determination that there is a causal relationship between long-term PM2.5

exposure and mortality.
Draft – Do Not Quote or Cite December 11, 2012

II-24

an attempt to identify, absent confounding, if PM2.5 was 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 longterm exposure to PM2.5 and mortality, which make 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 different estimates of the PM2.5/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) observed

associations between exposure to PM2.5 and mortality that are near the null value, often 

negative, and not statistically significant. The fact that the authors did not observe an 

association in the local analyses is not surprising. As stated in Janes et al. (2007), they 

were estimating “associations between temporal changes in exposure and outcomes

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 commentary by Pope and Burnett (2007), is the use of monthly average 

PM2.5 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 (2007) “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 using 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 PM2.5 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 those used in other studies of long-term exposure to PM2.5 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 PM2.5 on mortality risk, and did not conduct any 

analyses relying on the temporal variation in PM2.5. The opposite is true of the Janes et al. 

(2007) and Greven et al. (2011) studies which first removed the spatial variability in 

PM2.5 and then examined the temporal variation at both the national and local scale to 

measure the effects of temporal differences in PM2.5 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 PM2.5 concentrations 

between cities, while Janes et al. (2007) and Greven et al. (2011) primarily focused on temporal differences in PM2.5

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 PM2.5 levels and average age-adjusted mortality 

rates across cities (purely spatial or cross-sectional association).”
Draft – Do Not Quote or Cite December 11, 2012

II-25

and Greven et al. (2011) focus on changes in PM2.5 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 

PM2.5-mortality 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 PM2.5 concentrations.

As detailed in the ISA (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 PM2.5 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 unmeasured 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 national 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 covariates 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 PM2.5 over time and not space, the results from these two studies 

do not provide any indication that other studies of long-term exposure to PM2.5 and 

mortality exhibit spatial confounding, or that PM2.5 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) stated that 

there are flaws in the criticisms offered by Pope and Burnett (2007) on the paper by Janes 

et al. (2007). First, the commenters did not agree with Pope and Burnett (2007) that data 

used by Janes et al. (2007) was too aggregate (i.e., using deaths and PM2.5 concentrations 

averaged over months rather than days does not provide adequate temporal variability) to 

detect short-term variation. The commenters stated that most of the long-term cohort 

studies of mortality 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) did in their “local” analysis, there was 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 PM2.5.
Draft – Do Not Quote or Cite December 11, 2012

II-26

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

level. 

Second, the commenters took issue with the critique by Pope and Burnett (2007) that the 

use of county-level fixed effects eliminated 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 variation 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) only 5 percent

of the variance in the data set used in these analyses is attributable to the space by time 

component.

Third, the commenters identified the critique by Pope and Burnett (2007) that the analysis 

by Janes et al. (2007) was limited by the scale of the study (i.e., three years), which did

not allow for consideration of longer-term variability in mortality and air pollution data. 

The commenters stated 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 

mortality 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 stated that 

Greven et al. (2011) used “station-level” data instead of county level data, added three 

additional years of data to the study period, incorporated controls for socio-economic 

confounders, and investigated 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 

PM2.5 and mortality (Dominici et al. 2012). 

One commenter suggested that the epidemiological results from studies of long-term 

exposure to PM2.5 and mortality characterized 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 PM2.5 and mortality 

that generally reports consistent, positive relative risks (U.S. EPA 2009a, 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 PM2.5 and mortality” ((API, 2012, 
Draft – Do Not Quote or Cite December 11, 2012

II-27

Attachment 7, p. 5). For example, the commenter claimed that Greven et al. (2011) used 

data from more locations 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 

resolution 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 data 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 monthlevel 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 PM2.5 and mortality. 

In summary, the EPA does not question the quantitative results presented by Janes 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 

PM2.5 and mortality, or that the results presented in these two studies invalidate either the 

results themselves, or the consistency of the results observed across other cohort studies 

of long-term exposure to PM2.5 and mortality. Janes et al. (2007) and Greven et al. (2011) 

eliminated the spatial variability in the air pollution and mortality data. Thus, the results 

of these studies cannot be directly compared to time-series studies of short-term exposure 

to PM2.5 and mortality (which rely on day-to-day changes in PM2.5 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 analyses 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 included 

in the ISA and contributed to the body of evidence for an association between long-term 

PM2.5 exposures and mortality, but are not directly comparable to other cohort studies 

that rely on a different timescale and focus on spatial variability. 

As demonstrated in the ISA, there is a large body of evidence supporting the association 

between long-term exposure to PM2.5 and mortality that generally reports consistent 

relative risks between 1.0 and 1.5 (U.S. EPA 2009a, Figures 7.6 and 7.7). Based on this 

large body of evidence, the EPA concluded that a causal relationship exists between longterm exposure to PM2.5 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 these 
Draft – Do Not Quote or Cite December 11, 2012

II-28

studies of long-term exposure to PM2.5 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 causal relationship exists between long-term PM2.5 exposure and mortality. 14

(5) Comment: Some commenters questioned the use of epidemiological studies in assessing the adequacy of 

the current PM NAAQS because “of the untestable assumptions on which much of air pollution 

epidemiology, along with EPA’s proposed NAAQS revisions, are built” (ACC, 2012, pp. 20 to 21). These 

commenters made this claim based on a recent publication by Moore et al. (2012), which they asserted

demonstrates that “most, if not all, results from 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 epidemiological evidence 

used to inform whether or not the PM NAAQS should be revised. First, the Moore et al. 

(2012) study focused on evaluating effects associated with ozone (O3) exposures, which 

brings into question its relevance in the context of considering the available scientific 

evidence for the PM NAAQS review. This study was not included in the ISA or 

considered in the Provisional Science Assessment as this study did not include 

consideration of measured ambient PM2.5 concentrations. Second, Moore et al. (2012) 

examined heat as a potential confounder of the O3-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 

confounding 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, 2009a). Therefore, the study by 

Moore et al. (2012) does not inform the relationship between PM2.5 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 epidemiological 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 potential mechanisms and plausible 

biological pathways, the evidence provided by toxicological and controlled human 

exposure studies still does not resolve all questions about how PM2.5 at ambient 

concentrations could produce the mortality and morbidity effects observed 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 

epidemiology 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 epidemiologic 

studies” (Dominici (2012) p. 1 (emphasis original)).
Draft – Do Not Quote or Cite December 11, 2012

II-29

admissions and mortality). 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 experimental 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 biological 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, the 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 biological mechanisms. While this research has not 

resolved all questions, and further research 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, toxicological studies provide evidence to support the biological

plausibility of cardiovascular and respiratory effects associated with long- and short-term 

PM2.5 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 cardiovascularrelated 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 PM2.5 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 that a 

causal relationship exists between long- and short-term exposure to PM2.5 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 PM2.5 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 epidemiological studies. Ethical considerations regarding the types of 

studies that can be performed with human subjects limit the 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 status and risk factors than occurring in the 
Draft – Do Not Quote or Cite December 11, 2012

II-30

general population. 15 Consequently, the severity of health effects observed in controlled 

human exposure studies evaluating the effects of PM2.5 should be expected to be less than 

observed in epidemiological studies. Nonetheless, that effects are observed in healthy 

individuals participating in controlled exposure studies serves as an indication that PM2.5

is initiating adverse health responses and that more severe responses may reasonably be 

expected in a more diverse 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 PM2.5, but these 

are not the 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 exposed to PM2.5 (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. 

Epidemiological studies have observed associations between PM2.5 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 PM2.5

(potentially over many years) in a laboratory setting to induce enough lethalities to 

distinguish between natural deaths and those attributable to PM2.5. Furthermore, the 

heterogeneous human populations sampled in epidemiological studies are comprised of 

individuals with different 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, PM2.5-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 PM2.5 exposure and mortality studies (e.g., ACC, 2012, pp. 6 to 14; AAM, 

2012, pp. 6 to 18) and contended that the EPA’s evaluation of the scientific evidence fails 

to accurately reflect the latest scientific knowledge. Common points raised by these 

commenters were that the results from long-term exposure studies were limited because 

they: (a) found biologically implausible risk estimates; (b) estimated PM2.5 concentrations 

for years in which data were not available; and (c) did not account for exposure 

misclassification. 

 

15 For example, the EPA excludes from its controlled human exposure studies involving exposure to PM2.5 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 

Review 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.
Draft – Do Not Quote or Cite December 11, 2012

II-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 PM2.5 and mortality, consistent with 

CASAC comments” (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 commenters 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). 

The comparison of smoking and ambient PM-related effect estimates was not considered 

relevant for the PM NAAQS review and, thus, was not considered in the ISA. This issue 

was not raised during the CASAC and public review of the draft ISAs. In order to address 

the comments submitted, the EPA conducted a provisional review of 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 ambient particulate 

matter and 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 PM2.5 and both lung cancer mortality (Pope et al. 2011) and 

cardiovascular disease (CVD) mortality (Pope et al. 2009; Pope et al. 2011). In these 

studies, the authors evaluated three sources of exposure to PM2.5: 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” across 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 with 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 – Do Not Quote or Cite December 11, 2012

II-32

Figure 1. Adjusted RRs [with 95% confidence intervals (CIs)] of lung cancer mortality (A) and IHD, cardiovascular, and 

cardiopulmonary mortality (B) plotted over estimated daily exposure of PM2.5 (milligrams) and increments of cigarette 

smoking relative to never smokers (cigarettes/day). Diamonds represent comparative mortality risk estimates (with 95% CIs) 

for PM2.5 from air pollution from the comparative studies (Dockery 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 Services 2006). The dotted lines represent the 

nonlinear power function fit through the origin and the estimates (including active smoking, SHS, ambient PM2.5). Estimated 

doses from different increments of active smoking are dramatically larger than estimated 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.
Draft – Do Not Quote or Cite December 11, 2012

33

Because of the much steeper exposure-response relationship for long-term 

exposure to PM2.5 and CVD mortality at low PM2.5 concentrations, which flattens 

out at higher PM2.5 concentrations (i.e., those associated with passive and active 

cigarette smoking), it is biologically plausible that the risk estimates for CVD 

mortality due to exposure to ambient concentrations of PM2.5 would be similar to 

risk estimates for CVD mortality due to active cigarette smoking. These results 

are consistent with the results observed in epidemiological studies of long-term 

exposure to PM2.5 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 PM2.5 concentrations and active cigarette 

smoking in an area with relatively high levels of ambient PM2.5 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 ambient PM.

(b) With regard to estimating PM2.5 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 longterm 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 

review, the ISA discussed studies available since the last review that have

assessed the relationship between long-term exposure to PM2.5 and mortality to 

explore the issue of the latency period between exposure to PM2.5 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 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 exposure to PM2.5 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 with long-term exposure to PM10 reported 

cumulative effects that extended over the years that deaths 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 PM2.5

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) found, in a comparison of exposure periods ranging from 1 month to 48 

months prior to death that exposure to PM10 24 months prior to death exhibited 

the strongest association, and the weakest association was reported for exposure 

in the time period of 1 month prior to death. 

Formatted: Left: 1.5"
Draft – Do Not Quote or Cite December 11, 2012

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 

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.

(U.S. EPA, 2009a, section 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 PM2.5-related 

deaths in such studies. To explore how much higher the long-term mean PM2.5

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 

long-term mean PM2.5 concentrations (Schmidt, 2012a), 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 the 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 calculated the extended 

long-term mean PM2.5 concentration for each study. As discussed in Schmidt 

(2012a), in each case the long-term mean PM2.5 concentration averaged over the 

extended exposure period was less than 0.4 μg/m3higher than the long-term mean 

PM2.5 concentration averaged over the follow-up period. The EPA finds it 

reasonable to conclude that such a relatively small difference in long-term mean 

PM2.5 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 data 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/m3). 

Moreover, as discussed in section III.E.4.c.i of the preamble to the final rule and 

in section 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 uncertainties 
Draft – Do Not Quote or Cite December 11, 2012

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 epidemiological studies and that assessment of air pollution 

exposure using community average concentrations may lead to exposure 

misclassification or exposure measurement error. To investigate 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, 

section 7.6.3). These analyses used spatial interpolation and land use regression 

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 PM2.5 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 exposure error can result in stronger associations between 

PM2.5 and mortality than generally observed in studies having less wellcharacterized exposure.

(8) Comment: Some commenters contended that the associations observed in longterm exposure studies were due to exposures that occurred many years earlier 

when PM2.5 concentrations were much higher and therefore are “misattributing 

those risks to more recent, lower PM2.5 levels” (UARG, Attachment 1, pp. 14 to 

15; Southern Company, 2012 p. 2; AAM, 2012, pp. 14 to 15). Additionally, these 

commenters asserted 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 matter, the EPA has recognized the challenge in 

distinguishing between PM2.5-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; 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 inform 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, 

Section 8.2.3.5; U.S. EPA 2009a, section 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 PM2.5 and mortality in exploring the issue of the latency 

period between exposure to PM2.5 and death (U.S. EPA, 2009a, Section 7.6.4).
Draft – Do Not Quote or Cite December 11, 2012

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 PM2.5

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 with long-term exposure to PM10 reported 

cumulative 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 PM2.5

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). 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 PM10 24 months prior to death 

exhibited the strongest association, and the weakest 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, such that health effects may occur over the full range of 

concentrations observed in epidemiological 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 acknowledges that 

exposure windows that extend up to a few years prior to the follow-up period in 

which health event data were collected would likely more fully capture the PMrelated deaths in such studies. 

To explore how much higher the long-term mean PM2.5 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 PM2.5 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. 
Draft – Do Not Quote or Cite December 11, 2012

37

(2008). The analysis then calculated the extended long-term mean PM2.5

concentration for each study. As discussed in Schmidt (2012), in each case the 

long-term mean PM2.5 concentration averaged over the extended exposure period 

was less than 0.3 μg/m3higher than the long-term mean PM2.5 concentration 

averaged over the follow-up period. The EPA finds it reasonable to conclude that 

such a relatively small difference in long-term mean PM2.5 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 long-term 

exposure period when weighing the information from the long-term exposure 

studies in the context of the broader array of epidemiological studies that inform 

the EPA’s consideration of the level of the annual PM2.5 standard. Furthermore, as 

noted in 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

concentrations evaluated in key short-term studies in revising the level of the 

annual standard. These comments are addressed 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 commenters (NAM et 

al., 2012, pp. 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 did

not account for increasing age of the cohort, and that there were discrepancies in 

the results of the study. Another commenter (EPRI, 2012, p. 3) asserted that the 

EPA mischaracterized the results of the Veterans Cohort Study (Lipfert et al. 

2006). 

Response: The EPA disagrees with the commenters’ assertion that the increasing 

age of the study subjects from the Harvard Six Cities Study was not accounted for 

when estimating the association between decreased PM2.5 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 personyears 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, including age. The authors stratified study subjects “by sex 
Draft – Do Not Quote or Cite December 11, 2012

38

and 1-yr age groups, such that each sex/age group had its own baseline hazard.”

Id. The authors found that the associations between PM2.5 and mortality were 

comparable for both follow-up periods (Laden et al. 2006, p. 669). Additionally, 

NAM asserted that there were discrepancies in results among the six cities in the 

study that lead to considerable uncertainty. The EPA acknowledges that there was 

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 

PM2.5 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 response to Comment (4), above). Laden et al. (2006) 

recognized that there is variability in the association between the cities, but noted

that “the drop in the adjusted mortality rate was largest in the cities with the 

largest reductions in PM2.5 after controlling for such a period effect.”Id.

With regard to the Veteran’s Cohort Study, the EPA acknowledges that the air 

quality data in Figures 1 and 4 (77 FR 38929) of the proposal were 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 proposal (77 FR 38929) and the final rule. This effect estimate was 

positive and statistically significant in a single pollutant model, and remained

positive (though no longer statistically significant) in a two-pollutant model that 

included traffic density, and a three-pollutant model that included traffic density 

and PM10-2.5. The EPA also acknowledges that this effect estimate represents an 

association for which the deaths occurred before PM2.5 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 relatively small differences in longterm mean PM2.5 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: Some 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 limitations 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 PM2.5 concentration for this study as 14.3 

μg/m3, which was the long-term mean PM2.5 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 PM2.5 are based on one year of air quality data 

(1999). However, this study does not report the long-term mean PM2.5 concentration for 1999. Rather, in 

Table 1 of Lipfert et al. (2006a), the study authors reported long-term mean PM2.5 concentrations of 14.3 

μg/m3for the years 1989 to 1996 and 14.6 μg/m3for the years 1997 to 2001. 
Draft – Do Not Quote or Cite December 11, 2012

39

al., 1996; and Goss et al., 2004) and argued that this evidence provides only a 

“weak association” with PM2.5 exposures. Additionally, some commenters stated

the results from long-term PM2.5 exposure and morbidity studies that focused 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 considered at the time the EPA reaffirmed the current annual 

standard level of 15.0 μg/m3in 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 standard in this review (UARG, 2012, 

Attachment 1, p. 14).

More specifically, some commenters asserted that the McConnell et al. (2003) 

and Gauderman et al. (2004) studies reported mixed results for associations with 

PM2.5 and stronger associations with NO2 (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 associations with acidity than with fine 

particles (measured as PM2.1). Id. pp. 15 to 16. With regard to Goss et al. (2004) 

study, this commenter noted that the association between pulmonary 

exacerbations and PM2.5 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. 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 supporting 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). 

Specifically, the extended analyses of the Southern California Children’s Health 

Study provided evidence that clinically important deficits in lung function17

associated with long-term exposure to PM2.5 persist into early adulthood (U.S. 

EPA, 2009a, p. 7-27; Gauderman et al., 2004). Additional analyses of the 

 

17 Clinical significance was defined as an FEV1 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 NAAQS for sulfur dioxide (SO2) also included this 

interpretation for FEV1 (75 FR 35525, June 22, 2010).
Draft – Do Not Quote or Cite December 11, 2012

40

Southern California Children’s Health Study cohort reported an association 

between long-term PM2.5 exposure and bronchitic symptoms (U.S. EPA, 2009a, 

pp. 7-23 to 7-24; McConnell et al., 2003, long-term mean concentration of 13.8 

μg/m3) that remained positive in copollutant models, with the PM2.5 effect 

estimates increasing in magnitude in some models and decreasing in others, and a 

strong modifying effect of PM2.5 on the association between lung function and 

asthma incidence (U.S. EPA, 2009a, 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, section 7.3.9.1). The ISA thoroughly evaluated both the McConnell et al. 

(2003) and Gauderman et al. (2004) studies (U.S. EPA, 2009a, sections 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) 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” (Gauderman et al., 2004, pp. 1061 to 

1062). The commenters claimed that the authors emphasized NO2 as the 

“apparent culprit” of the lung function decrements, which they claimed was

further supported by the NO2 results “hav[ing] a much higher significance level” 

compared to PM2.5 (UARG, 2012, p. 15). The EPA disagrees with the 

commenters’ views because Gauderman et al. (2004) clearly stated throughout the 

analysis that NO2 was one component of a highly correlated mixture that 

contained PM2.5 (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 inappropriate 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 the 

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 PM2.5 exposure and respiratory effects. 

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

association between long-term PM2.5 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/m3). The commenters noted that the association between pulmonary 

exacerbations and PM2.5 was attenuated when the statistical models were adjusted 
Draft – Do Not Quote or Cite December 11, 2012

41

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. However, 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 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 FEV1 and PM levels” (Goss et al., 2004, p. 819). Moreover, 

adjusting 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 focusing 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/m3) 

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 PM10 and PM2.1 were similar to those for particle strong 

acidity and sulfate particles, though the confidence intervals for the PM10 and 

PM2.1 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 PM2.1 (r=0.82), make it difficult 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, PM10 and PM2.1 concentrations. The 

commenters 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 were 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 epidemiological studies conducted in the U.S. and abroad provided 

stronger evidence of respiratory-related morbidity associated with long-term 

PM2.5 exposure (77 FR 38918). The strongest evidence for respiratory-related 

effects available in this review was from epidemiologic studies that evaluated 

decrements in lung function growth in children and increased respiratory 
Draft – Do Not Quote or Cite December 11, 2012

42

symptoms and disease incidence in adults (U.S. EPA, 2009a, Sections 2.3.1.2, 

7.3.1.1, and 7.3.2.1). 

In considering the collective evidence from epidemiologic and experimental 

studies, the Integrated Science Assessment concluded that a causal relationship is 

likely to exist between long-term PM2.5 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 studies 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 PM2.5 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 Health Study (Gauderman et al., 

2000, long-term mean PM2.5 concentration approximately 15 μg/m3) and the 24-

Cities Study (Raizenne et al., 1996, long-term mean concentrations approximately 

14.5 μg/m3) did not warrant a more stringent annual PM2.5 standard when the 

long-term mean PM2.5 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. (2000) 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 commenters contended that PM2.5 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 provided evidence of no effect of short-term PM exposure on 

mortality and morbidity because the “overall pattern [of effects] is not what one 

would expect if PM health effects associations have a real physiological basis” 

(AAM, 2012, pp. 6 to 10). AAM stated that this conclusion was supported by the 

lack of consistent statistically significant associations across all models examined. 

Additionally, API contended that the sensitivity of PM2.5 risk estimates to the 

selection of degrees of freedom to control for temporal trends was 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 PM2.5 risk estimates to the method used to control 

for temporal trends and bring into question the association between short-term 

PM2.5 exposures and mortality and hospital admissions. Additionally, these 
Draft – Do Not Quote or Cite December 11, 2012

43

commenters have focused solely on the statistical significance of risk estimates 

and not on the pattern of associations across studies as is discussed more 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 Canada 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 trends 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 consistent 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 PM2.5-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, 

disagrees with the commenters 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 control for temporal trends..Additionally, the EPA 

disagrees with these commenters sole reliance on statistical significance when 

evaluating the results of these studies. As stated in the response to Comment (1) 

above, focusing solely on statistically significance is inappropriate when 
Draft – Do Not Quote or Cite December 11, 2012

44

evaluating studies.

(12) Comment: Multiple commenters (ACC, 2012, pp. 14 to 18; AAM, 2012, pp. 6 to 

10) questioned the EPA’s interpretation of results from specific short-term PM2.5

exposure studies that examined associations with morbidity and mortality 

outcomes. Specifically, these commenters questioned: (a) interpretation of results 

from copollutant models; (b) lag selection; (c) the derivation of national risk 

estimates from multicity 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 subsections:

(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’ interpretation of the results 

from Burnett et al. (2004). The main copollutant analyses conducted over the 

entire study duration used PM2.5 data that were not collected every day. As a 

result, when including PM2.5 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 daily PM2.5 concentrations were available, the PM2.5 association 

remained robust after adjustment for NO2, while the NO2 association was 

attenuated. Overall, this result brings into question the results from copollutants

analyses including PM2.5 that is collected every-3

rd or 6th

-day. 

Finally, the EPA disagrees with the commenters’ interpretation of the quote from 

Ito et al. (2007) that they relied on to discredit the results from copollutant 

analyses. Ito et al. (2007) cautioned against including all pollutants in one model, 

which, as they demonstrated can result in “the pollutant that varies least like all 

the rest of the pollutants, and is least affected by concurvity in such a multipollutant 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 included multiple pollutants are difficult to interpret due to 

the potential multicollinearity between pollutants. (e.g., U.S. EPA, 2004, sections

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 questioned the selection of lag days a priori and not through 
Draft – Do Not Quote or Cite December 11, 2012

45

the use of model fit criteria (ACC, 2012, pp. 14 to 18). As demonstrated in the 

ISA, studies that examined the association between short-term PM2.5 exposure 

and mortality “were consistently observed at lag 1 and lag 0-1, which have been 

confirmed through extensive analysis of PM10-mortality studies” (U.S. EPA, 

2009a, 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 estimates from multicity studies

Some commenters questioned the derivation of national risk estimates from multicity studies. Specifically, these commenters questioned the approach employed by 

study investigators to calculate a national estimate, claiming that it did not use the 

entirety of the community-level data (ACC, 2012, pp. 14 to 18). The EPA 

disagrees with these commenters understanding of the approach used to calculate 

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 cityspecific risk estimates and then utilizing either a meta-regression or a 2nd stage 

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 information that is needed to calculate a national risk estimate. 

(d) Ignoring evidence of a reduction in PM-mortality risk over time

Some commenters also questioned the EPA’s interpretation of evidence indicating 

a reduction in PM-mortality risk estimates over time, and pointed to the results of 

Dominici et al. (2007) to support their argument (ACC, 2012, pp. 14 to 18). At 

first glance, the results of Dominici et al. (2007) would seem to indicate that PMmortality risk estimates have declined over time due to the 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 impact 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 PM10” (U.S. 

EPA, 2009a, 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, 2009a, 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 revision to 

the standards at this time, multiple commenters (API, 2012, pp. 1, 17 to 20, and 

Attachment 1, pp. 9 to 24, Attachment 7, p. 9, Attachment 9; ACC, 2012, pp. 2 to 

7, 14 to 18; NAM, 2012, pp. 9, 23; AAM, 2012, pp. 5 to 15; AFPM, 2012, p. 3;
Draft – Do Not Quote or Cite December 11, 2012

46

Southern Company, 2012, pp. 2 to 3; EPRI, 2012, pp. 1 to 4; Texas CEQ, 2012, 

pp. 1 to 4) discussed a number of issues related to: (a) copollutant confounding;

(b) ecological/contextual confounding; (c) heterogeneity in risk estimates, (d) 

exposure measurement 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 PM2.5 exposure has diminished 

since the last review. The EPA disagrees with commenters’ views that the 

remaining uncertainties in the scientific evidence are too great to support revising 

the current PM2.5 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 confounding

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 PM2.5 exposures and mortality and morbidity outcomes (e.g., 

NAM 2012, p. 23, ACC 2012, pp. 14 to 18). These commenters contended that 

the EPA has inappropriately concluded that PM2.5-related mortality and morbidity 

associations are generally robust to confounding. The commenters stated that 

statistically significant PM2.5 associations in single-pollutant models in 

epidemiological studies do not remain statistically significant in copollutant 

models.

The EPA recognizes where PM2.5 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 existence 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 estimates in 

epidemiological studies conducted by a number of research groups using singleand co-pollutant models (U.S. EPA, 2009a, sections 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 

epidemiological studies, there was little change in effect estimates based on 

single- and copollutant models, although the ISA recognized that in some cases, 

the PM2.5 effect estimates were markedly reduced in size and lost statistical 

significance. 

In questioning the influence of co-pollutants on associations observed in shortterm PM exposure and mortality studies, commenters highlighted the lack of 

control for copollutants in Dominici et al. (2003, 2007) and Franklin et al. (2007). 

The EPA recognized that a limitation of the multi-city studies that examined the 
Draft – Do Not Quote or Cite December 11, 2012

47

association between short-term PM2.5 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 the causality determination for 

mortality. In Chapter 2 of the ISA (U.S. EPA, 2009a, p. 2-11), the EPA stated,

“Although recently evaluated U.S.-based multi-city studies did not analyze 

potential confounding of PM2.5 risk estimates by gaseous pollutants, evidence 

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 PM2.5-

mortality association. This is further supported by studies that examined the 

PM10-mortality relationship”, which were discussed in section 6.5.2.1 of the ISA 

(U.S. EPA, 2009a). 

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 investigating the association between long-term exposure to PM2.5 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 incorporated CO, NO2, and ozone, and were reduced 

only for models that incorporated SO2 (Krewski et al. 2000). The 2004 AQCD 

recognized, however, that SO2 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 O3 “did not confound the relationship between particles and 

mortality.” Similarly, analysis of the AHSMOG cohort (Chen et al. 2005) found 

that the association between mortality and long-term exposure to PM2.5 became 

stronger when O3 and SO2 were included in copollutants models, and the 

association for PM2.5 did not change when NO2 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 PM2.5. 

The EPA notes that these public comments do not adequately reflect the 

complexities inherent in assessing the issue of copollutant confounding. As 

discussed in the proposal (77 FR 38907, 38909, and 38910) and more fully in the 

ISA (USEPA, 2009a, sections 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 long-term exposures to PM2.5 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 complicated by correlations that often exist 

among air pollutants, by the fact that some pollutants play a role in the 

atmospheric reactions that form other pollutants such as secondary fine particles, 

and by the statistical power of the studies in question inherent in the study 

methodology. For example, the every-third or sixth-day sampling schedule often 

employed for PM2.5 compared to daily measurements of gaseous copollutants 
Draft – Do Not Quote or Cite December 11, 2012

48

drastically reduces the overall sample size to assess the effect of copollutants on 

the PM2.5-morbidity or mortality relationship, such that the reduced sample size 

can lead to less precise effect estimates (e.g., wider confidence intervals).

The EPA recognizes that when PM2.5 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 evidence, the EPA concludes 

epidemiological studies continue to support the conclusion that PM2.5 associations 

with mortality and morbidity outcomes are robust to the inclusion of gaseous 

copollutants in statistical models. The EPA evaluated the potential confounding 

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 contended that both short- and long-term PM2.5 exposure 

studies of mortality did not appropriately control for ecological or contextual 

confounders (ACC, 2012, p. 3; API, 2012, Attachment 1, p. 14; NAM 2012, p. 

23). 

In the case of short-term exposure studies, an ecological confounder would need 

to vary on a day-to-day basis with both air pollution and with the specific health 

outcome being evaluated (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 studies, 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 

individual differences in health outcomes 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 effects often operate independently from (or 

interactively with) the individual-level variables such as smoking.” These studies 

found that the inclusion of contextual variables tended to attenuate the risk 

estimates for the association between long-term exposure to PM2.5 and mortality, 

but that an independent effect of PM2.5 on mortality remains. For example, Jerrett

et al. (2005) found that for PM2.5 (controlling for age, sex, and race), the relative 

risk was 1.24 (95% CI 1.11, 1.37) for a 10 μg/m3exposure contrast. In a 

parsimonious model that controlled for 44 different individual covariates and 

ecological confounder variables that both reduced the pollution coefficient and 
Draft – Do Not Quote or Cite December 11, 2012

49

had 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 PM2.5.

Additionally commenters contended that non-traditional confounders have not 

been accounted for in epidemiological 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 would 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 epidemiological studies and the lack of statistical significance in many 

regional or seasonal estimates highlights a potential bias associated with 

combined multi-city epidemiological study results (e.g., API, 2012, Attachment 1, 

pp. 15 to 19). Additionally, these commenters contended that the wide range of 

individual city results in these multicity studies, specifically NMMAPS, 

demonstrated a biologically implausible wide range of associations (AAM, 2012, 

pp. 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 

PM2.5 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 PM2.5-related risks, the 

EPA agrees that epidemiological studies evaluating health effects associated with 

long- and short-term PM2.5 exposures have reported heterogeneity in responses 

between cities and effect estimates across geographic regions of the U.S. (U.S. 

EPA, 2009a, sections 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 PM2.5 exposure, the ISA found 
Draft – Do Not Quote or Cite December 11, 2012

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 western 

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 that 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 PM2.5 across the country and that the county-level air 

quality data used in epidemiological studies may result in exposure error, which 

could in part account for variability in city-specific risk estimates (U.S. EPA, 

2009a, section 2.3.2). 

There are a limited number of studies that evaluated regional heterogeneity in the 

association between long-term exposure to PM2.5 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 relative 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 heterogeneity in PM2.5

concentrations observed in Los Angeles, and the overall spatial homogeneity of 

PM2.5 concentrations in New York City. 

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

long-term exposure to PM2.5 and mortality 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 PM2.5

risk estimates, specifically in the northeast. The ISA found evidence indicating 

that individuals may be at greater risk of dying from higher exposures to PM2.5 in 

the warmer months, and at greater risk of PM2.5 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 various 

factors that contribute to heterogeneity observed in epidemiological studies (77 

FR 38909/3). Nonetheless, the EPA recognizes that this heterogeneity could be 

attributed, at least in part, to differences in PM2.5 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 PM2.5
Draft – Do Not Quote or Cite December 11, 2012

51

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

As recognized in the PA, the current epidemiological evidence and the limited 

amount of city-specific speciated PM2.5 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 

PM2.5 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 related 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 PM2.5 effect estimates in epidemiological studies and concurred 

with the overall conclusions presented in the ISA.

(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 in 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 addresses issues of exposure 

measurement error (U.S. EPA, 2009a, sections 2.3.2 and 3.8.6). Exposure 

measurement error may lead to bias in effect estimates in epidemiological studies. 

A number of studies evaluated in the last review (U.S. EPA, 2004, section 8.4.5) 

and in the current review (U.S. EPA, 2009a, section 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, sections 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 epidemiological 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 major 
Draft – Do Not Quote or Cite December 11, 2012

52

component of PM2.5 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).

The EPA disagrees with the interpretation of Sarnat et al. (2009) by the 

commenter. Sarnat et al. (2009) describes variability in the use of home 

ventilation (i.e., air conditioning) as a key factor contributing to both the bias and 

the variability in personal exposure. Air conditioning usage varies by individuals 

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 epidemiological 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 expected to bias the effect 

estimate away from the null. Moreover, Sarnat et al. (2009) did not assert that the 

bias can go in either direction.

(e) Model specification 

Commenters contended that the EPA did not account for the fact that “selecting 

an appropriate statistical 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 short-term exposure 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 ascribed to the pollution 

variable. Conversely, if an overly aggressive approach 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 to 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 

considered in the study. As demonstrated in section 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 PM2.5 exposure and 

mortality. Regardless of the model 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 2009a, Figure 6-

27, with additional details found in Appendix E, section E.3, Table E-16,). The 

EPA also considered the influence of model specification in the examination of 
Draft – Do Not Quote or Cite December 11, 2012

53

long-term PM2.5 exposure studies. For example, in section 7.6, Figures 7-6 and 7-

7, the ISA summarized the collective evidence that evaluated the association 

between long-term PM2.5 exposure and mortality. Regardless of the model used, 

these studies collectively found evidence of consistent positive associations 

between long-term PM2.5 exposure and mortality. 

The 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 epidemiologic studies includes 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, 2009a, 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 PM2.5

exposures and mortality and morbidity effects, alone and in combination with 

other pollutants.

(f) Shape of the concentration-response relationship

With regard to the C-R relationship, commenters questioned the interpretation of 

the shape of the C-R relationship, specifically stating that multiple studies have 

demonstrated that there is a threshold in the PM-health effect relationship and that 

the log-linear model is not biologically 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, section 2.4.3). While 

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 

recognizes that there likely are individual biologic thresholds for specific health 

responses, the ISA concluded the overall evidence from existing epidemiological

studies does 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 

epidemiological analyses have not identified a population threshold in the range 

of air quality concentrations evaluated in these studies, the EPA recognizes that it 

is possible that such thresholds exist towards the lower end of these ranges (or 

below these ranges). This would be a concentration far lower than the level of the 
Draft – Do Not Quote or Cite December 11, 2012

54

revised annual standard. The ISA concluded 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 lower 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 of 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, log-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-responserelationship 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 within 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 PM2.5 components may be more closely 

related to specific health outcomes (e.g., elemental carbon (EC) and organic 

carbon (OC)) (EPRI, 2012, p. 2). 

With regard to questions about the role of individual constituents within the mix 

of fine particles, as a general matter, the EPA recognizes that although new 

research directed toward this question has 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 fine 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 

epidemiological evidence of health effects using various indicators of fine 

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 concentrations 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 epidemiological studies continue to 

be indexed by PM2.5 mass, several recent epidemiological studies included in the 

ISA have used PM2.5 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 PM2.5 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 chemical 
Draft – Do Not Quote or Cite December 11, 2012

55

components of fine particles and a variety of different types of source categories 

are all associated with, and probably contribute to, effects associated with PM2.5. 

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 

sufficient to support eliminating any component or group of components 

associated with any specific source categories from the mix of fine particles 

included in the PM2.5 indicator (U.S. EPA, 2009a, p. 2-56). CASAC agreed that it 

was reasonable to retain PM2.5 as 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 PM2.5 as the 

indicator 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 PM2.5 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 constituent of PM2.5 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 interpreted in light of these remaining uncertainties does provide 

increased confidence relative to the last review in the reported associations 

between long- and short- term PM2.5 exposures and mortality and morbidity 

effects, alone and in combination with other pollutants, 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 epidemiological studies 

of associations observed in areas meeting the current primary PM2.5 standards, 

specifically in areas meeting the current primary annual PM2.5 standard, adds 

support to its conclusion that the current suite of PM2.5 standards needs to be 

revised to provide increased public health protection from exposure to all types of 

PM2.5.

(14) Comment: In asserting that there is no evidence of greater risk since the 2006 

review to justify lowering the current annual PM2.5 standard, some commenters 

argued that, “if the current primary PM2.5 annual standard of 15 μg/m3 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 surely still be 
Draft – Do Not Quote or Cite December 11, 2012

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, Attachment 1, p. 24). These commenters used this conclusion as the basis 

for a claim that there is no reason to revise the current annual PM2.5 standard.

Response: The EPA believes that this claim is fundamentally flawed as it fails to 

take into account that exposure to a pollutant causally associated at a populationlevel 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. Moreover, in comparing the scientific 

understanding of the risk presented by exposure to PM2.5 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 increased hospital 

admissions at various concentrations), but also the degree of confidence that the 

Agency has that the observed health effects are causally linked to PM2.5 exposure 

at those concentrations. As documented in the ISA and in the recommendations 

and conclusions of CASAC, the EPA recognizes significant advances in our 

understanding of the health effects of PM2.5, based on evidence that is stronger 

than in the last review because of its breadth and because it substantiates

previously observed health effects. 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 PM2.5 standards. From this more comprehensive perspective, since the 

risks presented by PM2.5 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 PM2.5 standards is “requisite” to protect public health with an adequate 

margin of safety. The 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 PM2.5

and mortality 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 2006 decision to retain the primary annual PM2.5

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 populations. 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). The judgment of the then-Administrator that the 2006 primary annual 

PM2.5 standard was requisite to protect public health with an adequate margin of 

safety is thus not precedential and is an inappropriate benchmark for the 

comparison drawn in the comments.
Draft – Do Not Quote or Cite December 11, 2012

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 the 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 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 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 uncertainties, the advice of CASAC, and 

the extensive public comments on the proposal in reaching her conclusions 

regarding final decision on the appropriate primary PM2.5 standard levels, 

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 literature, further supporting their view that revision of the PM2.5

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 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, in 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 PM2.5 as the indicator for fine particles. In addition to the responses contained in 
Draft – Do Not Quote or Cite December 11, 2012

58

section III.E.1 of the preamble to the final rule, the EPA provides the following 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 PM2.5 components and/or sources 

on public health. These 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 for 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 PM2.5. For example, the PSR 

encouraged more research and monitoring related to PM2.5 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 organic 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 PM2.5

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 forward 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 information 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 concentrations 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, and related emissions 
Draft – Do Not Quote or Cite December 11, 2012

59

characteristics of particles” (Samet, 2010d, p. iii). More specifically, CASAC 

asserted that “PM2.5 has been a useful surrogate index since it was adopted in the 

1997 PM NAAQS promulgation, but may become an increasingly inadequate 

index 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 cycles and reinvigorate 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 characteristics of particles. There is an inherent feedback in the 

cycle from research 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 more 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 II.B.1.b above.

3. Averaging Time

The EPA received few comments on the issue of averaging time for the PM2.5

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 PM2.5 primary standards. However, one 

group representing several States (i.e., NESCAUM, 2012) suggested 

consideration of a rolling 24-hour average, rather than a midnight-to-midnight 24-

hour average, for the 24-hour PM2.5 standard. In justifying this recommendation, 

NESCAUM noted that using a rolling 24-hour average, rather than the current 

midnight-to-midnight average, “would be particularly helpful in providing better 

public health protection in areas where there is the potential for seasonal 

overnight PM2.5 events (e.g., from woodsmoke).” 

Response: The EPA agrees with NESCAUM that it is appropriate in this review 

to increase public health protection against exposures to PM2.5. 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 PM2.5 standard and retaining the current 24-hour PM2.5

standard. These judgments reflect in large part the Administrator’s consideration 

of ambient PM2.5 concentrations in the locations where long-term and short-term 

PM2.5 health studies have been conducted. The PM2.5 concentrations reported in 

these study locations are based on midnight-to-midnight sampling. 
Draft – Do Not Quote or Cite December 11, 2012

60

Altering the sampling time period for the 24-hour PM2.5 standard, as suggested by 

these commenters, would alter the PM2.5 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. In reaching her proposed decisions on the PM2.5 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 overstated nor understated 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 alterations in the 

sampling time period. 

4. Form

The EPA received a number of public comments on the appropriate forms for the 

PM2.5 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 III.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 PM2.5 standard and (ii) the 24-hour PM2.5

standard.

a. Annual Standard

(1) Comment: Of the commenters 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 PM2.5

standard, those who commented on the form of the annual PM2.5 standard 

supported the EPA’s proposal to eliminate the spatial averaging provisions. These 

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 disproportionate 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 meeting 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 justice concern because poor people are 

more likely to live near roads, depots, factories, ports, and other pollution 
Draft – Do Not Quote or Cite December 11, 2012

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 dictating 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 atrisk populations” and to maximize “the benefits to public health of reducing the 

annual PM2.5 standard.” However, these groups expressed concern that the 

elimination of spatial averaging, in combination with the requirement for 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 PM2.5

standard. 

This concern was also shared by other commenters who disagreed with the 

elimination of 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-road 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 monitors, the proposed 

NAAQS will become more stringent without targeting the PM2.5 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 

difference 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 maintained that because 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 PM2.5

epidemiological 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 

PM2.5 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. 24 to 25). Thus, this commenter 

asserted that elimination of spatial averaging 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, these commenters argued that 
Draft – Do Not Quote or Cite December 11, 2012

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 agreed 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 Agency notes that these commenters did not challenge 

the analyses or considerations that provided the fundamental basis for the 

Administrator’s proposed decision. These unchallenged analyses indicate that 

public health would not be protected with an adequate margin of safety in all 

locations, as required 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 PM2.5-related health impacts in at-risk populations extends to 

populations living near important sources of PM2.5, including the large 

populations that live near major roadways. 

Rather than addressing 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 eliminate 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 recommends 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 

epidemiological 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 likely 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 elements 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 populations. 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 notes 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’s 
Draft – Do Not Quote or Cite December 11, 2012

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 only 10

such areas in the country in which the maximum monitor mean concentration was 

between 2 to 6 μg/m3higher than the composite monitor concentration (Frank, 

2012a, Table 4) Thus, the EPA does not agree that there is a significant difference 

between composite monitor mean PM2.5 concentrations and maximum monitor 

mean PM2.5 concentrations in the large majority of areas across the country such 

that implementation of the standard on a maximum monitor basis, or without the 

option of spatial averaging, provides more protection than is requisite due to some 

inconsistency with key underlying epidemiologic studies. 

Based on the analyses done to inform consideration of the form of the standard 

(Schmidt, 2011, Analysis A), as well as the nationwide analysis of composite 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 atrisk populations that live around the monitor measuring the highest concentration, 

such 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 question 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 health 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, pp. 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 susceptibility 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 – Do Not Quote or Cite December 11, 2012

64

used to support changes to the form of the annual PM2.5 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 epidemiological and toxicological 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 generally 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 conclusions 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 lower 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 EPA 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 final 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, averaging 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 considered 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 – Do Not Quote or Cite December 11, 2012

65

b. 24-Hour Standard

(1) Comment: Many of the individuals and groups who supported a more stringent 

24-hour PM2.5 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 99th percentile form. The 

limited number of these commenters who provided a specific rationale for this 

recommendation generally expressed their concern that the 98th 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 state and local air agencies and industry groups 

generally supported retaining the current 98th percentile form. In most cases, these 

groups expressed the overall view that the current 24-hour PM2.5 standard, 

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 run.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 PM2.5 concentrations. This analysis provided 

evidence that the 98th percentile value was a more stable metric than the 99th

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 Association v. EPA, 283 F. 3d at 374-75. In retaining the 98th percentile 

form, the Administrator focused on the relative stability of the 98th 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 proposed levels for the primary PM2.5

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 any change to the current primary PM2.5

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 requisite to protect the public health. The context for the 

court’s discussion in ATA III is identical to that here; whether to adopt a 98th percentile form for a 24-hour 

standard intended to provide supplemental protection for a generally controlling annual standard.
Draft – Do Not Quote or Cite December 11, 2012

66

suite of primary PM2.5 standards to provide 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 standard 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 rationale presented in the proposal notice as a basis for the Agency’s 

proposed decision regarding the levels of the primary PM2.5 standards. A number of 

commenters, including many environmental and public health organizations as well as 

state and local air agencies and health departments and tribes, who supported the revising 

the standard levels generally placed great weight on the recommendations of CASAC. 

Sections III.D.2 and III.E.4.c of the preamble to the final rule present the Agency’s 

response to these very general views. In addition to the discussion contained in those

sections, the EPA provides the following responses to specific issues related to the levels 

for the primary PM2.5 standards. This includes comments on the general approach used by 

the EPA to translate the available scientific information into standard levels and how 

specific PM2.5 exposure studies should be considered as a basis for the standard levels.

a. Annual Standard

i. Support for Retaining the Current Level

The group of commenters opposed to any change to the current suite of primary 

PM2.5 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 PM2.5 standards. That is, they asserted that the EPA’s causal 

determinations were not adequately supported by the underlying scientific information; 

the biological plausibility of health effects observed in epidemiological studies has not 

been demonstrated in controlled human exposure and toxicological studies; uncertainties 

in the underlying 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 PM2.5

standard; and “new” studies not included in the Integrated Science Assessment continue 

to increase uncertainty about possible health risks associated with exposure to PM2.5.

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/m3and argued that the current standard level of 15 μg/m3should 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 

evidence to support revising the annual standard level. These commenters raised specific 
Draft – Do Not Quote or Cite December 11, 2012

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 

measurements 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 distributions of underlying 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/m3is that the air 

quality 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 longterm mean PM2.5 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 

PM2.5 concentrations that will be compared 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, Attachment 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 PM2.5 concentrations in selecting a standard level, and then 

comparing the maximum monitor mean PM2.5 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 commenter 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 a 
Draft – Do Not Quote or Cite December 11, 2012

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 

PM2.5 concentrations and maximum monitor mean PM2.5 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 PM2.5 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 composite monitor PM2.5 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 PM2.5

concentrations using monitoring data20 from 2006 to 2008 and presented results 

averaged across areas within two groups (i.e., those with design values21 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 

PM2.5 concentrations from the subset of the epidemiological studies shown in 

Figure 4 (of the proposal and 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/m3is retained and attained. The commenter considered 

the subset of epidemiological studies that included 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 PM2.5 standard would 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 PM2.5 concentrations from the epidemiological studies, 

considered as a basis for selecting an annual standard level, and maximum 

monitor long-term mean PM2.5 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.
Draft – Do Not Quote or Cite December 11, 2012

69

monitors within an area when implementing the standard22), 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 to 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 composite 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 PM2.5 data are available, as 

discussed in Frank (2012a, Table 5), there were 208 such areas (with design 

values ranging up to about 15 μg/m3). Frank (2012a) also observed that other 

areas have multiple monitors with composite and maximum monitor mean PM2.5

concentrations that were the same or relatively close, with 57 areas in which the 

maximum monitor mean concentration was no more than 0.5 μg/m3higher than 

the composite monitor mean concentration and 56 areas in which the difference 

was between 0.6 and 2 μg/m3. 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/m3higher than the composite monitor concentration (Frank, 2012a, Table 

4).23 Thus, the EPA does not agree that there is a significant difference between 

composite monitor mean PM2.5 concentrations and maximum monitor mean PM2.5

concentrations in the large majority of areas across the country.

In proposing to revise the form of the annual PM2.5 standard, as discussed in 

section III.E.3.a of the preamble to the final rule, the EPA noted that when an 

annual PM2.5 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 the 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 

living in locations around the monitors recording the highest PM2.5 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/m3and the median difference is 0.6 μg/m3. The 25th and 75th percentiles are 

0.3 and 1.0 μg/m3, respectively (Frank, 2012a, p. 4).
Draft – Do Not Quote or Cite December 11, 2012

70

of the annual PM2.5 standard by eliminating the option for spatial averaging, the 

EPA continues to conclude that a standard level based on consideration of longterm 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 based 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 which the maximum monitor concentration is appreciably higher than the 

composite monitor concentration. Rather, this approach properly treats those atrisk 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 atrisk 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 margin 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 of 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 selection of an appropriate standard level and 

form based on the health effects evidence.
Draft – Do Not Quote or Cite December 11, 2012

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 consistent approach would be to decide on a mean composite 

monitor PM2.5 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 that 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 PM2.5 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 monitor 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 atrisk, 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 PM2.5 concentrations that have 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 the 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 demonstrably 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 PM2.5

concentrations using monitoring data from 2006 to 2008 which they assert 

supports retaining the current standard level of 15 μg/m3, the EPA finds flaws 

with the numerical results and the scope of the analysis, 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 mean PM2.5

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/m3) and (2) areas with design values that are just attaining the current annual 

standard (i.e., between 14.5 and 15.0 μg/m3).24 The commenter indicated that they 

 

24For the first group of areas (which included 33 areas), this analysis calculated an average across the areas 

of maximum monitor annual mean PM2.5 concentrations, averaged over 3 years, of 17.2 μg/m3compared to 

an average of composite monitor concentrations of 14.3 μg/m3. For the second group of areas (which 

included 11 areas), this analysis calculated an average across the areas of maximum monitor annual mean 

concentrations, averaged over 3 years, of 14.8 μg/m3compared to an average of composite monitor 
Draft – Do Not Quote or Cite December 11, 2012

72

used the full body of PM2.5 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 monitor 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 Notably, 

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 group) is approximately 0.5 μg/m3, not 1.2 μg/m3as 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 finds 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/m3, the analysis ignores the large 

number of areas across the country with lower design values that are relevant to 

consider in light of the epidemiological evidence of serious health effects at 

concentrations lower than 15 μg/m3, well below the level of the current standard.

In translating its analysis results into the basis for selecting an annual standard 

level, the commenter’s translation is premised on the view that the “natural focal 

point” for setting an annual PM2.5 standard level should be somewhere within the 

range of the long-term mean PM2.5 concentrations from the subset of 

epidemiological studies that included 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/m3(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 PM2.5 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/m3compared to an average of composite monitor concentrations of 14.8 μg/m3. For 

the 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/m3compared to an average of composite monitor concentrations of 14.2 μg/m3(Frank, 2012a, Table 3).
Draft – Do Not Quote or Cite December 11, 2012

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 public 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 PM2.5 standard, or with the limited set of studies considered by the 

commenter as a basis for selecting the level of the annual PM2.5 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 

PM2.5 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, then one or more of the studies would have a 

long-term mean concentration below the selected 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 PM2.5-related mortality and/or

morbidity effects to continue. Selecting a standard level that would explicitly 

allow such projected PM2.5-related mortality and morbidity effects to continue 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 PM2.5 concentrations in the key 

epidemiological studies – even the lowest long-term mean concentration from the 

set of key studies -- is not appropriate. Concentrations at and around the long-term 

mean concentrations 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 association in such study is strongest.

However, the evidence of an association with adverse health effects in the studies 

is not limited to the PM2.5 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 PM2.5 concentrations 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 concentration 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 PM2.5 standard, the EPA finds that limiting consideration only to the 
Draft – Do Not Quote or Cite December 11, 2012

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 epidemiological studies. Thus, selecting an 

annual standard level 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 commenter’s concerns with 

the EPA’s approach to considering composite and maximum monitor PM2.5

concentrations in selecting the level of the annual PM2.5 standard to be without 

merit. Further, the EPA finds no support in the commenter’s analysis for their 

suggested 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 PM2.5 levels and 

misattributing those risks to more recent, lower PM2.5 levels” (UARG, 2012, 

Attachment 1, p 7). Further, this commenter asserted that “there is no knowledge 

or evidence indicating whether premature deaths are the result of PM2.5 exposures 

in the most recent year; or due to physical damages incurred from PM2.5

exposures much earlier in life (with the impact on lifespan only emerging later in 

life); or due to total accumulated PM2.5 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 PM2.5 standard 

are based on reductions in mortality related to long-term exposures to PM2.5.

Response: As an initial matter, the EPA has recognized the challenge in 

distinguishing between PM2.5-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 

average of PM2.5 to develop their associations; they used the daily 24‐hour averages of PM2.5. 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 – Do Not Quote or Cite December 11, 2012

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 review, the Integrated 

Science Assessment discussed studies available since the last review that have 

assessed the relationship between long-term exposure to PM2.5 and mortality to 

explore the issue of the latency period between exposure to PM2.5 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 (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 exposure to PM2.5 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 

PM10 reported cumulative 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 PM2.5

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) found, in a comparison of exposure periods ranging from 1 month to 48 

months prior to death, that exposure to PM10 24 months prior to death exhibited 

the strongest association, and the weakest 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 exposure 

period that is causally related to the mortality effects of long-term PM2.5

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 

appropriate 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 long-term exposure study. This would include long-term 

mean PM2.5 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 PM2.5 concentrations ranging from 13.6 μg/m3to 14.3 
Draft – Do Not Quote or Cite December 11, 2012

76

μg/m3. 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 morbidity 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 PM2.5

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 PM2.5 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 PM2.5 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 PM2.5 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 long-term mean PM2.5

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 calculated the extended long-term mean PM2.5

concentration for each study. As discussed in Schmidt (2012), in each case the 

long-term mean PM2.5 concentration averaged over the extended exposure period 

was less than 0.3 μg/m3higher than the long-term mean PM2.5 concentration 

averaged over the follow-up period. The EPA finds it reasonable to conclude that 

such a relatively small difference in long-term mean PM2.5 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 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-term PM2.5 exposures to 

inform causality determinations reached in the ISA (U.S. EPA, 2009a, sections 7.2.11 and 7.6).
Draft – Do Not Quote or Cite December 11, 2012

77

of long-term exposure studies discussed above in the context of the broader array 

of epidemiological studies that inform the EPA’s consideration of the level of the 

annual PM2.5 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 longterm mean PM2.5 concentrations are the lowest. As discussed in the proposal, the 

EPA also considers the long-term mean PM2.5 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 midrange of the concentrations observed in the studies. Thus, setting the level of the 

annual 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 PM2.5-related risk from the 

broad array of mortality 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 period is not subject to the uncertainties 

discussed above related to the long-term exposure studies. Recognizing that the 

long-term mean PM2.5 concentrations from several of the multi-city short-term 

exposure studies shown in Figure 4 of the preamble to the final rule are below the 

long-term mean PM2.5 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 information 

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 not 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 PM2.5-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 PM2.5 standard.
Draft – Do Not Quote or Cite December 11, 2012

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 

the 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 the mean PM2.5 concentrations in key multi-city 

studies to help inform selection of the level of the annual PM2.5 standard. As both 

the EPA and CASAC recognize, in the absence of a discernible threshold, health 

effects may occur over the full range of concentrations 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 longterm mean PM2.5 concentrations reported in the studies. Following CASAC’s 

advice (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 significance of observed associations across the range of 

long-term mean PM2.5 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 population-level data across the study areas and the corresponding 

annual mean PM2.5 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 studies 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 studies, 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 such uncertainties are an 

 

30 Health event data and study population data were 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., 2007).
Draft – Do Not Quote or Cite December 11, 2012

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 on 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 PM2.5 standard. Such 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 studies, 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. (112 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 PM2.5 concentrations in key multi-city long- and short-term 

exposure studies the annual PM2.5 standard level should be set. While the EPA 

acknowledges that having 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 information.

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 events in each study area and the corresponding long-term mean PM2.5

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 

PM2.5 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 distribution 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 lower, the EPA 

considers PM2.5 concentrations between the 25th and 10th 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 appreciably lower. As highlighted in Figure 5, the long-term mean PM2.5

concentrations corresponding with study areas contributing to the 25th and 10th

percentiles of the distribution of deaths and cardiovascular-related hospitalizations 

in the two short-term exposure studies were 12.5 μg/m3and 10.3 μg/m3, 

respectively, for Zanobetti and Schwartz (2009), and 11.5 μg/m3and 9.8 μg/m3, 

respectively, for Bell et al. (2008). The EPA also recognizes, however, that there 
Draft – Do Not Quote or Cite December 11, 2012

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 appropriate 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 III.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 CASAC, as discussed 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 

presented 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 had 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 the 
Draft – Do Not Quote or Cite December 11, 2012

81

product of the peer review conducted by CASAC 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 peer review committee established pursuant to the CAA, on the 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 conclude that its 

analysis of distributions of health event and air quality data from two key multicity epidemiological studies provides important information related to 

understanding the associations between health events observed in each city (e.g., 

deaths, hospitalizations) and the corresponding long-term mean PM2.5

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 

PM2.5.

(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 longterm 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 provides only a “weak association” with PM2.5 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/m3in 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 standard 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) studies reported mixed results for associations with 

PM2.5 and stronger associations with NO2 (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 associations with acidity than with fine 

particles (measured as PM2.1). Id. pp. 15 to 16. With regard to the cystic fibrosis 

study, this commenter noted that the association between pulmonary 
Draft – Do Not Quote or Cite December 11, 2012

82

exacerbations and PM2.5 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, 

the EPA disagrees with the commenters’ interpretation of these studies.

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 the initial studies 

from the Southern California Children’s Health Study (Peters et al., 1999; 

McConnell et al., 1999’ Gauderman et al., 2000, 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 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). 

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 function31 associated with long-term exposure to PM2.5 persist into early 

adulthood (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 longterm PM2.5 exposure and bronchitic symptoms (U.S. EPA, 2009a, p. 7-23 to 7-24; 

McConnell et al., 2003, long-term mean concentration of 13.8 μg/m3) that 

remained positive in co-pollutant models, with the PM2.5 effect estimates 

increasing in magnitude in some models and decreasing in others, and a strong 

modifying effect of PM2.5 on the association between lung function and asthma 

incidence (U.S. EPA, 2009a, 7-24; Islam et al., 2007). The 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 other researchers in varying locations using different 

 

31 Clinical significance was defined as an FEV1 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 NAAQS for sulfur dioxide (SO2) also included this 

interpretation for FEV1 (75 FR 35525, June 22, 2010).

32 Gauderman et al. (2004) clearly stated throughout their analysis that NO2 was one component of a highly 

correlated mixture that contains PM2.5. Gauderman 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 – Do Not Quote or Cite December 11, 2012

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 study33 by Dockery et al. (1996) (long-term mean concentration of 

14.5 μg/m3) 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 PM10 and 

PM2.1 were similar to those for acidic aerosols and sulfate particles, though the 

confidence intervals for the PM10 and PM2.1 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 acidity with sulfate (r=0.90) and PM2.1 (r=0.82), 

make it difficult to distinguish 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 respiratory health effects and acid aerosols, 

sulfate, PM10 and PM2.1 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 aerosols 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 statements 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 association between long-term PM2.5 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/m3). The commenters noted that the association between 

pulmonary exacerbations and PM2.5 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. The EPA 

 

33 The 24-City study 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 – Do Not Quote or Cite December 11, 2012

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 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 FEV1 and 

PM levels” (Goss et al., 2004, p. 819). The EPA notes that adjusting 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 appropriate 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 from 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 

evaluation 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 toxicological 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 PM2.5 and different health outcomes. The EPA notes 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 epidemiological

studies, even if individual studies may lack statistical significance. American 

Trucking Association 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 evidence of respiratory-related morbidity 

associated with long-term PM2.5 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 growth in children and 

increased respiratory symptoms and disease incidence in adults (U.S. EPA, 2009a, 
Draft – Do Not Quote or Cite December 11, 2012

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 PM2.5 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 final decision in the last review was held to be deficient by 

the D.C. Circuit in remanding the 2006 primary annual PM2.5 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 Health Study (Gauderman et al., 2000, long-term mean PM2.5

concentration approximately 15 μg/m3) and the 24-Cities Study (Raizenne et al., 

1996, long-term mean concentrations approximately 14.5 μg/m3) did not warrant 

a more stringent annual PM2.5 standard when the long-term mean PM2.5

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. (2000) 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.

In this review, the EPA recognizes a significant amount of evidence beyond these 

two studies that expands our understanding of respiratory effects associated with 

long-term PM2.5 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 PM2.5 exposures at 

concentrations 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 studies 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 comes from studies “that observed associations between long-term exposure to 

PM10 and an increase in respiratory symptoms and reductions in lung function growth in areas where PM10

is dominated by PM2.5” (U.S. EPA, 2009a, p. 2-12). 
Draft – Do Not Quote or Cite December 11, 2012

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 weight 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-risk 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 does 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 PM2.5 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 originally reported a longterm mean PM2.5 concentration of 13.5 μg/m3

(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 

additional 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 PM2.5

concentration provided by the study authors was 12.9 μg/m3(personal

communication from Cynthia Curl, 2009; Stanek et al., 2010). The final PA noted

that this updated long-term mean concentration matched the composite monitor 

approach annual mean calculated by the EPA (Hassett-Sipple et al., 2010, 

Attachment 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 staff concluded it 

was most appropriate to include the updated air quality data in the final PA (Id.). 

Thus, the long-term mean PM2.5 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/m3. The PA noted 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 at the time of standard setting. It 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 relationship.
Draft – Do Not Quote or Cite December 11, 2012

87

quality data (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 longterm 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 translating the epidemiological information from the 

long-term exposure studies into a basis for selecting the level of the annual PM2.5

standard. Nonetheless, the EPA notes that the Miller et al. (2007) study provides 

strong evidence of cardiovascular-related effects associated with long-term PM2.5

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 

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, in 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).

ii. Support for Revising the Current Level

A second group of commenters supported revising the suite of primary PM2.5

standards to provide increased public health protection. These commenters found the 

available 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 supporting 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/m3) was adequately protective and supported a level of 11 μg/m3or below.

In general, these commenters expressed the view that given the strength of the 

available scientific evidence, the serious nature of the health effects associated with PM2.5

exposures, the large size of the at-risk populations, the risks associated with long- and 

short-term PM2.5 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 specifically, these commenters offered a range of comments related to the 
Draft – Do Not Quote or Cite December 11, 2012

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) the significance of the PM2.5-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 discussed 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 peakto-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 CAA 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 PM2.5 have serious and sometimes irreversible health 

impacts. 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 the 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 goal 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 PM2.5

exposures. It does so by lowering the overall air quality distributions across an 

area, recognizing that changes in PM2.5 air quality designed to meet an annual 

standard would likely result not only in lower annual mean PM2.5 concentrations 

but also in fewer and lower peak 24-hour PM2.5 concentrations. 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 PM2.5

standards to achieve an appropriate degree of public health protection. 

Furthermore, 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 designed to meet a given suite of standards are likely to be of a more 

regional or more localized nature.

In focusing on an approach of setting a generally controlling annual standard, the 

EPA’s intent is in fact to avoid the potential “regional inequities” that are of 
Draft – Do Not Quote or Cite December 11, 2012

89

concern to these 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 

upon 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 shortterm exposure studies primarily evaluated daily variations in health effects with 

monitor(s) that measured the variation in daily PM2.5 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 peak 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 PM2.5 exposures results from the large number of 

days during which the 24-hour average concentrations are in the low-to midrange, 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 Association

v. EPA, 283 F. 3d at 373 (rejecting arguments to lower the level of the daily PM2.5

standard when there is persuasive evidence that the main risk from exposure 

comes from 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 focused primarily on 

reducing peak days were less likely to achieve reductions in the PM2.5

concentrations that were most strongly associated with the observed health 

effects. Furthermore, the PA concluded that an approach that focused on reducing 

peak exposures 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 an approach that focuses on a generally controlling 

annual standard would likely reduce aggregate risks associated with both longand short-term exposures more consistently than a generally controlling 24-hour 

standard and, therefore, would be the most effective and efficient way to reduce 

total PM2-5-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 standards 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). The EPA thus disagrees 

with the comments that this approach will result in 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 – Do Not Quote or Cite December 11, 2012

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 compared to the last 

review. Some of these commenters highlighted the availability of multiple, multicity long- and short-term exposure studies providing “repeated, consistent 

evidence of effects below the current annual standard level” (ALA et al., 2012, 

pp. 39 to 49) and, more specifically, “significant evidence of harm with strong 

confidence well below EPA’s proposed annual standard range of 12-13 μg/m3” 

(AHA et al., 2012, pp. 10 to 12).

Response: The EPA recognizes that in setting standards that are requisite 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 of 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 within 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 rule, 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 provides 

support for considering an annual standard level below the proposed range (i.e., 

below 12 to 13 μg/m3). In particular, the EPA disagrees with the degree to which 

these commenters place more weight on the relatively more uncertain evidence 

that is suggestive 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 evidence 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 inform 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 different analytic measures -- either 

concentrations one standard deviation below the long-term means reported in the 
Draft – Do Not Quote or Cite December 11, 2012

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 PM2.5 air quality at 

which associations have been observed, some of these commenters highlighted 

CASAC’s recommendation that “[f]urther consideration should be given to using 

the 10th 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 urged 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 using 

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 public 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 that 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 25th to 10th 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 the 

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 information 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 additional 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 selected because they considered multiple locations representing 
Draft – Do Not Quote or Cite December 11, 2012

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 PM2.5 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-level data for four of the six 

studies (Rajan et al., 2011). Three 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 PM2.5-related impacts on 

at-risk populations, including potential impacts on children, older adults, persons 

with pre-existing heart and lung disease, and low-income populations, to support 

their views that the annual standard should be revised to a level of 11 μg/m3or 

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, pp. 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 does 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 approach 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/m3, 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/m3 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 PM2.5 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 PM2.5

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 effects 
Draft – Do Not Quote or Cite December 11, 2012

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 focused on considering PM2.5 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 first 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 disregard 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 information 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 determinations 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 provides 

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. As 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 PM2.5 annual 

standard level as high as 13 μg/m3. (Assuming 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 substantive 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/m3, 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/m3 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 – Do Not Quote or Cite December 11, 2012

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 

μg/m3(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] PM2.5 NAAQS” (API, 2012, p. 9).

Response: The commenter suggested (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 proposal 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 scientific evidence and 

technical information supports consideration for retaining the annual standard 

level at 15 μg/m3. 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 PM2.5 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-term exposure to PM2.5 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 the Agency’s increased confidence in the association 

between exposure to PM2.5 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 PM2.5 

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 PM2.5 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. 

Furthermore, as discussed in section III.E.4.e of the proposal, the Administrator 

provisionally concluded that the available scientific information supported 
Draft – Do Not Quote or Cite December 11, 2012

95

consideration of an annual standard level no higher that 13 μg/m3. 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/m3

(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, in 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).

b. 24-Hour Standard

With respect to the level of the 24-hour standard, the EPA received comments on 

the proposal from two distinct groups 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 PM2.5 standard. 

The other group of commenters included many medical groups, numerous physicians and 

academic researchers, many public health organizations, some State and local agencies, 

five state attorneys general, and a large number of individual commenters. These 

commenters disagreed with the Agency’s proposed decision and argued that EPA should 

lower the level of the 24-hour standard to 30 or 25 μg/m3. Comments from these groups 

on the level of the 24-hour PM2.5 standard are addressed in section III.E.4.c.ii in the 

preamble for the final rule and below.

i. Support for Retaining the Current Level

Of the public commenters who addressed the level of the 24-hour PM2.5 standard, 

all industry commenters and most State and local commenters supported the proposed 

decision to retain the current level of 35 g/m3. In many cases, these groups agreed with 

the rationale supporting the Administrator’s proposed decision to retain the current 24-

hour PM2.5 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 Administrator’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), making 
Draft – Do Not Quote or Cite December 11, 2012

96

them an unsuitable basis 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 PM2.5 standard, some did not agree with the EPA’s 

approach to considering the evidence from short-term multi-city studies. For 

example, a commenter representing UARG pointed out that the 98th percentile 

concentrations reported in the proposal for multi-city studies reflect the averages 

of 98th percentile concentrations across the cities included in those studies 

(UARG, 2012; Attachment 1; p. 25). This commenter contended that such 

averaged 98th percentile PM2.5 concentrations do not provide information that can 

appropriately inform a decision on the adequacy of the public health protection 

provided by the current 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 98th percentile PM2.5 concentrations to 

inform a decision on the appropriateness of the protection provided by the 24-

hour PM2.5 standard. In particular, the EPA notes that averaged 98th 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 PM2.5 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 98th percentile 24-hour PM2.5 concentrations below 35 g/m3

(Dominici et al., 2006; Bell et al., 2008; Zanobetti and Schwartz, 2009). Based on 

the 98th percentiles of 24-hour PM2.5 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 (HassettSipple et al., 2010). Therefore, regardless of whether the averaged 98th percentile 

concentrations or the 98th percentile concentrations in each city are considered, 

these studies provide evidence for associations between short-term PM2.5 and 

mortality or morbidity across a large number of U.S. cities, the majority of which 

would likely have met the current 24-hour PM2.5 standard during study periods. In 

their review of the PA, CASAC endorsed the conclusions drawn from analyses of 

averaged 98th percentile 24-hour PM2.5 concentrations (Samet, 2010d) and the 

EPA continues to conclude that this type of information can appropriately inform 

the Administrator’s decision on the current 24-hour PM2.5 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 

 

37This is not to say that the EPA’s decision on whether to revise the 24-hour PM2.5 standard should be 

based on or only be informed by considerations of whether studies reported associations with mortality or

morbidity in areas with averaged 98th percentile PM2.5 concentrations less than 35 mg/m3. As discussed in 

section III.E.4.d of the preamble to the final rule, in reaching a decision in the final notice on the most 

appropriate approach to strengthen the suite of PM2.5 standards, the Administrator considers the degree of 

public health protection provided by the combination of the annual and 24-hour standards together. 
Draft – Do Not Quote or Cite December 11, 2012

97

standard is necessary to protect 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 PM2.5 health 

impacts 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 observed 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. The EPA has 

carefully considered the degree of public health protection provided by the annual 

and 24-hour PM2.5 standards working together. As highlighted by commenters 

and as 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 μg/m3to provide 

protection from both long- and short-term PM2.5 exposures. In conjunction with 

the revised annual standard, the EPA concludes it is also appropriate to retain the 

current 24-hour standard in order to provide supplemental protection in areas with 

high peak-to-mean ratios of PM2.5 concentrations, possibly associated with strong 

local or seasonal sources, and against PM2.5-related effects that may be associated 

with shorter-than daily exposure periods. 

As 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 

PM2.5 concentrations in locations with averaged (i.e., averaged across study cities) 

98th percentile 24-hour concentrations from 45.8 to 34.2 μg/m3(Burnett et al., 

2004; Zanobetti and Schwartz, 2009; Bell et al., 2008; Dominici et al., 2006a, 

Burnett and Goldberg, 2003; Franklin et al., 2008). In many locations, the revised 

annual PM2.5 standard is expected to protect against the effects reported in these 

studies. However, some areas of the United States, particularly in the northwest, 

could experience 98th percentile 24-hour PM2.5 concentrations above 35 mg/m3

while annual PM2.5 concentrations remain below 12 g/m3 (U.S. EPA, 2011, 

Figure 2-10). In such locations, the current 24-hour standard is necessary to 

provide protection against effects that have been associated with short-term PM2.5

exposures. Without the 24-hour standard in place, short-term PM2.5 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-hour 
Draft – Do Not Quote or Cite December 11, 2012

98

standard provides appropriate supplementary protection against effects that have 

been associated with fine particle exposures. 

ii. Support for Revising the Current Level

Another group of commenters argued that the 24-hour standard level should be 

lowered. Many of these commenters supported setting the level of the 24-hour PM2.5

standard at either 25 or 30 g/m3. 

(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 98th percentile 

PM2.5 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) as providing evidence for associations with mortality and 

morbidity in study locations with averaged (i.e., averaged across cities) 98th

percentile 24-hour PM2.5 concentrations below 35 g/m3. These commenters also 

pointed to several single-city and panel studies reporting associations between 

short-term PM2.5 and mortality or morbidity in locations with relatively low 24-

hour PM2.5 concentrations. Because some of these multi- and single-city studies 

have reported associations with health effects in locations with 98th percentile 

PM2.5 concentrations below 35 g/m3, commenters maintained that the current 24-

hour PM2.5 standard (i.e., with its level of 35 g/m3) does not provide an 

appropriate degree of protection in all areas.

In further support of their position 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 PM2.5 concentrations. They noted that some locations, 

including parts of the northwestern U.S., experience relatively low annual PM2.5

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 PM2.5 exposures, especially in locations with high ratios of 24-

hour to annual PM2.5 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 PM2.5 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 PM2.5 concentrations. However, in highlighting 98th

percentile PM2.5 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 PM2.5 concentrations in response to a revised 

annual standard. See American Trucking Association v. EPA, 283 F. 3d at 373 

(rejecting argument to lower the level of the 24-hour PM2.5 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 – Do Not Quote or Cite December 11, 2012

99

In considering the specific multi-city studies highlighted by public commenters 

who advocated a more stringent 24-hour standard, the EPA notes that such 

studies have reported consistently positive and statistically significant associations 

with short-term PM2.5 exposures in locations with averaged 98th percentile PM2.5

concentrations ranging from 45.8 to 34.2 μg/m3and long-term mean PM2.5

concentrations ranging from 13.4 to 12.9 (Burnett and Goldberg, 2003; Burnett et 

al., 2004; Dominici et al., 2006a; Bell et al., 2008; Franklin et al., 2008; Zanobetti 

and Schwartz, 2009).38 The EPA notes that to the extent air quality distributions 

are reduced to meet the current 24-hour standard with its level of 35 g/m3and/or 

the revised annual standard with its level of 12 g/m3, 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 majority of study cities will 

necessarily be reduced, resulting in lower daily PM2.5 ambient concentrations. We 

therefore expect that the revised annual standard will result in 98th percentile 

PM2.5 concentrations in these cities that are lower than those measured in the 

studies, and that the overall distributions of PM2.5 concentrations will be lower 

than those reported to be associated with health effects. Thus, even for effects 

reported in multi-city studies with averaged 98th percentile concentrations below 

35 μg/m3, 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 PM2.5 concentrations in multi-city study 

locations were above the level of the revised annual standard (i.e., 12 μg/m3).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 Association, 283 F. 3d at 372 (endorsing this reasoning).

In considering the single-city studies highlighted by public commenters who 

advocated a more stringent 24-hour standard, the EPA first notes that, overall, 

these single-city studies reported mixed results. Specifically, some studies 

 

38Commenters also highlighted associations with short-term PM2.5 concentrations reported in sub-analyses 

restricted to days with 24-

3

(Dominici, 2006b). These subanalyses 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-term average PM2.5 concentrations, it is not clear whether they reflected PM2.5 air quality that 

would have been allowed by the revised annual PM2.5 standard being established in this notice. 

39It is also the case that additional protection is anticipated in locations with 98th percentile 24-hour PM2.5

concentrations above 35 μg/m3, even if long-term concentrations are below 12 μg/m3. 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 11, 2012

100

reported positive and statistically significant associations with PM2.5, some studies 

reported positive but non-significant associations, and several studies reported 

negative associations or a mix of positive and negative associations with PM2.5. In 

light of these inconsistent results, the proposal noted that the overall body of 

evidence from single-city studies is mixed, particularly in locations with 98th

percentiles of 24-hour concentrations below 35 μg/m3. Therefore, although some 

single-city studies reported effects at appreciably lower PM2.5 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 

confidence 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 evidence to inform decisions on the level of the 24-hour standard. 

Further, 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 the 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 PM2.5 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 EPA to 

reconsider its decision to emphasize multi-city studies over single-city studies 

when identifying the appropriate level of the 24-hour PM2.5 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 

PM2.5 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 assessed 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 reliable 

source of scientific information on which to base decisions on the NAAQS. 

(2) Comment: Some public health, medical, and environmental commenters also 

criticized the EPA’s interpretation of PM2.5 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 commenters 
Draft – Do Not Quote or Cite December 11, 2012

101

contended that public health benefits could continue to increase as annual and 24-

hour standard levels decrease below 13 g/m3and 35 g/m3, 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/m3, as is done in the final rule, rather than 13 g/m3. The Agency also 

acknowledges that estimated PM2.5-associated health risks continue to decrease 

with annual standard levels below 12 g/m3and/or with 24-hour standard levels 

below 35 g/m3. However, the EPA disagrees with the commenters’ views 

regarding the extent to which risk estimates support setting standard levels below 

12 μg/m3(annual standard) and 35 g/m3(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 adequate 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 PM2.5 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 

overstated nor understated the strengths and limitations of that evidence and 

information. In contrast, as discussed more fully above, public health, medical, 

and environmental commenters who recommended levels below 35 g/m3for the 

24-hour PM2.5 standard have not provided new information or analyses 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 98th percentile 24-hour PM2.5 concentrations below 35 g/m

3

and 

long-term average concentrations below 12 g/m3. 

 

40This 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 

PM2.5 standard.