Chapter 1. Introduction 

This Integrated Science Assessment (ISA) is a review, synthesis, and evaluation of the most 

policy-relevant evidence, and communicates critical science judgments relevant to the National 

Ambient Air Quality Standards (NAAQS) review. As such, the ISA forms the scientific foundation 

for the review of the primary (health-based) and secondary (welfare-based) NAAQS for particulate 

matter (PM). The ISA accurately reflects “the latest scientific knowledge useful in indicating the 

kind and extent of identifiable effects on public health which may be expected from the presence of 

[a] pollutant in ambient air” (42 U.S.C. 7408). Key information and judgments formerly contained in 

an Air Quality Criteria Document (AQCD) for PM are incorporated in this assessment. Additional 

details of the pertinent literature published since the last review, as well as selected older studies of 

particular interest, are included in a series of annexes. This ISA thus serves to update and revise the 

evaluation of the scientific evidence available at the time of the previous review of the NAAQS for 

PM that was concluded in 2006. 

The Integrated Review Plan for the National Ambient Air Quality Standards for Particulate 

Matter identifies a series of policy-relevant questions that provide a framework for this assessment 

of the scientific evidence (U.S. EPA, 2008, 157072). These questions frame the entire review of the 

NAAQS for PM, and thus are informed by both science and policy considerations. The ISA 

organizes and presents the scientific evidence such that, when considered along with findings from 

risk analyses and policy considerations, will help the EPA address these questions during the 

NAAQS review for PM. In evaluating the health evidence, the focus of this assessment will be on 

scientific evidence that is most relevant to the following questions that have been taken directly from 

the Integrated Review Plan: 

 Has new information altered the body of scientific support for the occurrence of health 

effects following short- and/or long-term exposure to levels of fine and thoracic coarse 

particles found in the ambient air? 

 Has new information altered conclusions from previous reviews regarding the 

plausibility of adverse health effects associated with exposures to PM2.5, PM10, PM10-2.5, 

or alternative PM indicators that might be considered? 

 What evidence is available from recent studies focused on specific size fractions, 

chemical components, sources, or environments (e.g., urban and non-urban areas) of PM 

to inform our understanding of the nature of PM exposures that are linked to various 

health outcomes? 

 To what extent is key scientific evidence becoming available to improve our 

understanding of the health effects associated with various time periods of PM 

exposures, including not only short-term (daily or multi-day) and chronic (months to 

years) exposures, but also peak PM exposures (<24 hours)? To what extent is critical 

research becoming available that could improve our understanding of the relationship 

between various health endpoints and different lag periods (e.g., <1 day, single day, 

multi-day distributed lags)? 

 What data are available to improve our understanding of spatial and/or temporal 

heterogeneity of PM exposures considering different size fractions and/or components? 

 At what levels of PM exposure do health effects of concern occur? Is there evidence for 

the occurrence of adverse health effects at levels of PM lower than those observed 

previously? If so, at what levels and what are the important uncertainties associated with 

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database (Health and 

Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used by U.S. EPA in the process of 

developing science assessments such as the Integrated Science Assessments (ISA) and the Integrated Risk Information System (IRIS). 

December 2009 1-1 
that evidence? What is the nature of the dose-response relationships of PM for the 

various health effects evaluated? 

 What evidence is available linking particle number concentration with adverse health 

effects of UF particles? 

 Do risk/exposure estimates suggest that exposures of concern for PM-induced health 

effects will occur with current ambient levels of PM or with levels that just meet the 

current standards? If so, are these risks/exposures of sufficient magnitude such that the 

health effects might reasonably be judged to be important from a public health 

perspective? What are the important uncertainties associated with these risk/exposure 

estimates? 

 To what extent is key evidence becoming available that could inform our understanding 

of subpopulations that are particularly sensitive or vulnerable to PM exposures? In the 

last review, sensitive or vulnerable subpopulations that appeared to be at greater risk for 

PM-related effects included individuals with pre-existing heart and lung diseases, older 

adults, and children. Has new evidence become available to suggest additional sensitive 

subpopulations should be given increased focus in this review (e.g., fetuses, neonates, 

genetically susceptible subpopulations)? 

 To what extent is key evidence becoming available to inform our understanding of 

populations that are particularly vulnerable to PM exposures? Specifically, is there new 

or emerging evidence to inform our understanding of geographical, spatial, SES, and 

environmental justice considerations? 

 To what extent have important uncertainties identified in the last review been reduced 

and/or have new uncertainties emerged? 

 To what extent is new information available to inform our understanding of non-PMexposure factors that might influence the associations between PM levels and health 

effects being considered (e.g., weather-related factors; behavioral factors such as 

heating/air conditioning use; driving patterns; and time-activity patterns)? 

In evaluating evidence on welfare effects of PM, the focus will be on evidence that can help 

inform these questions from the Integrated Review Plan: 

 What new evidence is available on the relationship between PM mass/size fraction 

and/or specific PM components and visibility impairment and climate-related and other 

welfare effects? 

 To what extent has key scientific evidence now become available to improve our 

understanding of the nature and magnitude of visibility, climate, and ecosystem 

responses to PM and the variability associated with those responses (including ecosystem 

type, climatic conditions, environmental effects and interactions with other 

environmental factors and pollutants)? 

 Do the evidence, the air quality assessment, and the risk/exposure assessment provide 

support for considering alternative averaging times? 

 At what levels of ambient PM do visibility impairment and/or environmental effects of 

concern occur? Is there evidence for the occurrence of adverse visibility and other 

welfare-related effects at levels of PM lower than those observed previously? If so, at 

what levels and what are the important uncertainties associated with the evidence? 

 Do the analyses suggest that PM-induced visibility impairment and/or other welfareeffects will occur with current ambient levels of PM or with levels that just meet the 

current standards? If so, are these effects of sufficient magnitude and/or frequency such 

December 2009 1-2 
that these effects might reasonably be judged to be important from a public welfare 

perspective? What are the uncertainties associated with these estimates? 

 What new evidence and/or techniques are available to quantify the benefits of improved 

visibility and/or other welfare-related effects? 

 To what extent have important uncertainties identified in the last review been reduced 

and/or have new uncertainties emerged? 

1.1. Legislative Requirements 

Two sections of the United States (U.S.) Clean Air Act (CAA, the Act) govern the 

establishment and revision of the NAAQS. Section 108 of the Act (42 U.S.C. 7408) directs the 

Administrator to identify and list “air pollutants” that “in his judgment, may reasonably be 

anticipated to endanger public health and welfare” and whose “presence... in the ambient air results 

from numerous or diverse mobile or stationary sources” and to issue air quality criteria for those that 

are listed (42 U.S.C. 7408). Air quality criteria are intended to “accurately reflect the latest scientific 

knowledge useful in indicating the kind and extent of identifiable effects on public health or welfare 

which may be expected from the presence of [a] pollutant in ambient air...” 42 U.S.C. 7408(b). 

Section 109 of the Act (42 U.S.C. 7409) directs the Administrator to propose and promulgate 

“primary” and “secondary” NAAQS for pollutants listed under Section 108. 42 U.S.C. 7409(a). 

Section 109(b)(1) defines a primary standard as one “the attainment and maintenance of which in the 

judgment of the Administrator, based on such criteria and allowing an adequate margin of safety, are 

requisite to protect the public health.”1 42 U.S.C. 7409(b)(1). A secondary standard, as defined in 

Section 109(b)(2), must “specify a level of air quality the attainment and maintenance of which, in 

the judgment of the Administrator, based on such criteria, is required to protect the public welfare 

from any known or anticipated adverse effects associated with the presence of [the] pollutant in the 

ambient air.”2 42 U.S.C. 7409(b)(2). 

The requirement that primary standards include 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. See Lead Industries Association v. EPA, 647 F.2d 1130, 

1154 (D.C. Cir 1980), cert. denied, 449 U.S. 1042 (1980); American Petroleum Institute v. Costle, 

665 F.2d 1176, 1186 (D.C. Cir. 1981), cert. denied, 455 U.S. 1034 (1982); American Farm Bureau 

Federation v. EPA, 559 F. 3d 512, 533 (D.C. Cir. 2009). Both kinds of uncertainties are components 

of the risk associated with pollution at levels below those at which human health effects can be said 

to occur with reasonable scientific certainty. Thus, in selecting primary standards that include an 

adequate margin of safety, the Administrator is seeking not only to prevent pollution levels that have 

been demonstrated to be harmful, but also to prevent lower pollutant levels that may pose an 

unacceptable risk of harm, even if the risk is not precisely identified as to nature or degree. 

In selecting a margin of safety, the EPA considers such factors as the nature and severity of the 

health effects involved, the size of the sensitive population(s) at risk, and the kind and degree of the 

uncertainties that must be addressed. The selection of any particular approach to providing an 

adequate margin of safety is a policy choice left specifically to the Administrator’s judgment. See 

Lead Industries Association v. EPA, supra, 647 F.2d 1161-62. 

In setting standards that are “requisite” to protect public health and welfare, as provided in 

Section 109(b), the Administrator’s task is to establish standards that are neither more nor less 

 

1

 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)]. 

2

 Welfare effects as defined in Section 302(h) [42 U.S.C. 7602(h)] include, but are not limited to, “effects on soils, water, crops, vegetation, 

man-made materials, animals, wildlife, weather, visibility and climate, damage to and deterioration of property, and hazards to

transportation, as well as effects on economic values and on personal comfort and well-being.” 

December 2009 1-3 
stringent than necessary. In so doing, EPA may not consider the costs of implementing the standards. 

See generally Whitman v. American Trucking Associations, 531 U.S. 457, 465-472, 475-76 (2001). 

Section 109(d)(1) requires that “not later than December 31, 1980, and at 5-yr 

intervals thereafter, the Administrator shall complete a thorough review of the criteria 

published under Section 108 and the national ambient air quality standards...and shall make such 

revisions in such criteria and standards and promulgate such new standards as may be 

appropriate...” 42 U.S.C. 7409(d)(1). Section 109(d)(2) requires that an independent scientific 

review...committee “shall complete a review of the criteria and the national primary and secondary 

ambient air quality standards...and shall recommend to the Administrator any new standards and 

revisions of existing criteria and standards as may be appropriate...” 42 U.S.C. 7409(d)(2). Since the 

early 1980s, this independent review function has been performed by the Clean Air Scientific 

Advisory Committee (CASAC). 

1.2. History of Reviews of the NAAQS for PM 

PM is the generic term for a broad class of chemically and physically diverse substances that 

exist as discrete particles (liquid droplets or solids) over a wide range of sizes. Particles originate 

from a variety of anthropogenic stationary and mobile sources, as well as from natural sources. 

Particles may be emitted directly or formed in the atmosphere by transformations of gaseous 

emissions such as sulfur oxides (SOX), nitrogen oxides (NOX), and volatile organic compounds 

(VOC). The chemical and physical properties of PM vary greatly with time, region, meteorology, 

and source category, thus complicating the assessment of health and welfare effects. Table 1-1

summarizes the NAAQS that have been promulgated for PM to date. These reviews are briefly 

described below, and further details are provided in the Integrated Review Plan (U.S. EPA, 2008, 

157072). 

EPA first established NAAQS for PM in 1971 (36 FR 8186, April 30, 1971), based on the 

original criteria document (NAPCA, 1969, 014684). The reference method specified for determining 

attainment of the original standards was the high-volume sampler, which collects PM up to a 

nominal size of 25-45 micrometers (μm) (referred to as total suspended particulates [TSP]). The 

primary standards (measured by the indicator TSP) were 260 μg/m3

, 24-h avg, not to be exceeded 

more than once per year, and 75 μg/m3

, annual geometric mean. The secondary standard was 

150 μg/m3

, 24-h avg, not to be exceeded more than once per year. In October 1979 (44 FR 56730, 

October 2, 1979), EPA announced the first periodic review of the air quality criteria and NAAQS for 

PM, and significant revisions to the original standards were promulgated in 1987 (52 FR 24634, 

July 1, 1987). In that decision, EPA changed the indicator for particles from TSP to PM10, the latter 

including particles with a mean aerodynamic diameter1 ≤ 10 μm, which delineated that subset of 

inhalable particles small enough to penetrate to the thoracic region (including the tracheobronchial 

and alveolar regions) of the respiratory tract (referred to as thoracic particles). EPA also revised the 

level and form of the primary standards by (1) replacing the 24-h TSP standard with a 24-h PM10

standard of 150 μg/m3

 with no more than one expected exceedence per year; and (2) replacing the 

annual TSP standard with a PM10 standard of 50 μg/m3

, annual arithmetic mean, averaged over 3 yr. 

 

1

 The more precise term is 50% cut point or 50% diameter (d50). This is the aerodynamic particle diameter for which the efficiency of 

particle collection is 50%. Larger particles are not excluded altogether, but are collected with substantially decreasing efficiency and 

smaller particles are collected with increasing (up to 100%) efficiency. 

December 2009 1-4 
Table 1-1. Summary of NAAQS promulgated for PM, 1971-2006. 

Year (Final Rule) Indicator Avg Time Level Form

24 h 260 μg/m3

 (primary) 

150 μg/ m3

 (secondary) Not to be exceeded more than once per yr 1971 (36 FR 8186)

TSP (Total 

Suspended 

Particulates) Annual 75 μg/m3

 (primary) Annual geometric mean

24 h 150 μg/m3 Not to be exceeded more than once per yr on average over a 3-yr period 1987 (52 FR 24634) PM10

Annual 50 μg/m3 Annual arithmetic mean, averaged over 3 yr

24 h 65 μg/m3 98th percentile, averaged over 3 yr PM2.5 Annual 15 μg/m3 Annual arithmetic mean, averaged over 3 yr1

24 h 150 μg/m3 Initially promulgated 99th percentile, averaged over 3 yr; when 1997 standards 

were vacated in 1999, the form of 1987 standards remained in place (not to be 

exceeded more than once per yr on average over a 3-yr period)

1997 (62 FR 38652)

PM10

Annual 50 μg/m3 Annual arithmetic mean, averaged over 3 yr

24 h 35 μg/m3 98th percentile, averaged over 3 yr PM2.5 Annual 15 μg/m3 Annual arithmetic mean, averaged over 3 yr2 2006 (71 FR 61144)

PM10 24 h 150 μg/m3 Not to be exceeded more than once per yr on average over a 3-yr period

Note: When not specified, primary and secondary standards are identical. 

The secondary standard was revised by replacing it with 24-h and annual standards identical in 

all respects to the primary standards. The revisions also included a new reference method for the 

measurement of PM10 in the ambient air and rules for determining attainment of the new standards. 

On judicial review, the revised standards were upheld in all respects. See Natural Resources Defense 

Council v. Administrator, 902 F. 2d 962 (D.C. Cir. 1990), cert. denied, 498 U.S. 1082 (1991). 

In April 1994, EPA announced its plans for the second periodic review of the air quality 

criteria and NAAQS for PM, and promulgated significant revisions to the NAAQS in 1997 (62 FR 

38652, July 18, 1997). In that decision, EPA revised the PM NAAQS in several respects. Most 

significantly, EPA determined that the fine and coarse3

 fractions of PM10 should be considered 

separately. The Administrator’s decision to modify the standards was based on evidence that serious 

health effects were associated with short- and long-term exposure to fine particles in areas that met 

the existing PM10 standards. EPA accordingly added new standards, using PM2.5 as the indicator for 

fine particles (with PM2.5 referring to particles with a nominal mean aerodynamic diameter 

≤ 2.5 μm), and PM10 as the indicator for thoracic coarse particles or coarse-fraction particles 

(generally including particles with a nominal mean aerodynamic diameter >2.5 μm and ≤ 10 μm, or 

PM10-2.5). The EPA established two new PM2.5 standards: an annual standard of 15 μg/m3

, based on 

the 3-yr avg of annual arithmetic mean PM2.5 concentrations from single or multiple 

community-oriented monitors; and a 24-h standard of 65 μg/m3

, based on the 3-yr avg of the 98th 

percentile of 24-h PM2.5 concentrations at each population-oriented monitor within an area. Also, 

EPA established a new reference method for measuring PM2.5 in the ambient air and adopted 

protocols for determining attainment of the new standards. To continue to address thoracic coarse 

particles, EPA retained the annual PM10 standard, while revising the form, but not the level, of the 

 

1

 The level of the 1997 annual PM2.5 standard was to be compared to measurements made at the community-oriented monitoring site 

recording the highest level, or, if specific constraints were met, measurements from multiple community-oriented monitoring sites could 

be averaged (“spatial averaging”). This approach was judged to be consistent with the short-term epidemiologic studies on which the 

annual PM2.5 standard was primarily based, in which air quality data were generally averaged across multiple monitors in an area or were 

taken from a single monitor that was selected to represent community-wide exposures, not localized “hot spots” (62 FR 38672). These 

criteria and constraints were intended to ensure that spatial averaging would not result in inequities in the level of protection afforded by 

the PM2.5 standards. Community-oriented monitoring sites were specified to be consistent with the intent that a spatially averaged annual 

standard provide protection for persons living in smaller communities, as well as those in larger population centers. 

2

 In the revisions to the PM NAAQS finalized in 2006, EPA tightened the constraints on the spatial averaging criteria by further limiting 

the conditions under which some areas may average measurements from multiple community-oriented monitors to determine compliance 

(71 FR 61165-61167, October 17, 2006). 

3

 See definitions of “fine” and “coarse” particles in Section 3.2. 

December 2009 1-5 
24-h PM10 standard to be based on the 99th percentile of 24-h PM10 concentrations at each monitor 

in an area. The EPA revised the secondary standards by making them identical in all respects to the 

primary standards. 

Following promulgation of the 1997 PM NAAQS, petitions for review were filed by a large 

number of parties, addressing a broad range of issues. In May 1999, a three-judge panel of the U.S. 

Court of Appeals for the District of Columbia Circuit issued an initial decision that upheld EPA’s 

decision to establish fine particle standards, holding that “the growing empirical evidence 

demonstrating a relationship between fine particle pollution and adverse health effects amply 

justifies establishment of new fine particle standards.” American Trucking Associations v. EPA (175 

F. 3d 1027, 1055-56 (D.C. Cir. 1999); rehearing granted in part and denied in part, 195 F. 3d 4 (D.C. 

Cir. 1999), affirmed in part and reversed in part, Whitman v. American Trucking Associations 531 

U.S. 457 (2001). The panel also found “ample support” for EPA’s decision to regulate coarse particle 

pollution, but vacated the 1997 PM10 standards, concluding that EPA had not provided a reasonable 

explanation justifying use of PM10 as an indicator for coarse particles (175 F. 3d at 1054-55). 

Pursuant to the court’s decision, EPA removed the vacated 1997 PM10 standards from the Code of 

Federal Regulations. The pre-existing 1987 PM10 standards remained in place (65 FR 80776, 

December 22, 2000). The Court also upheld EPA’s determination not to establish more stringent 

secondary standards for fine particles to address effects on visibility (175 F. 3d at 1027). 

More generally, the panel held (over one judge’s dissent) that EPA’s approach to establishing 

the level of the standards in 1997, both for the PM and ozone (O3) NAAQS promulgated on the 

same day, effected “an unconstitutional delegation of legislative authority” (Id. at 1034-40). 

Although the panel stated that “the factors EPA uses in determining the degree of public health 

concern associated with different levels of ozone and PM are reasonable,” it remanded the rule to 

EPA, stating that when EPA considers these factors for potential non-threshold pollutants “

lacks is any determinate criterion for drawing lines” to determine where the standards should be set.

Consistent with EPA’s long-standing interpretation and D.C. Circuit precedent, the panel also 

reaffirmed its prior holdings that in setting NAAQS EPA is “not permitted to consider the cost of 

implementing those standards” (Id

what EPA 

. at 1040-41). 

On EPA’s petition for rehearing, the panel adhered to its position on these points. American 

Trucking Associations v. EPA, 195 F. 3d 4 (D.C. Cir. 1999). The full Court of Appeals denied EPA’s 

suggestion for rehearing en banc, with five judges dissenting (Id. at 13). 

Both sides filed cross appeals on these issues to the U.S. Supreme Court, and the Court 

granted certiorari. In February 2001, the Supreme Court issued a unanimous decision upholding 

EPA’s position on both the constitutional and cost issues. Whitman v. American Trucking 

Associations, 531 U.S. 457, 464, 475-76. On the constitutional issue, the Court held that the statutory 

requirement that NAAQS be “requisite” to protect public health with an adequate margin of safety 

sufficiently guided EPA’s discretion, affirming EPA’s approach of setting standards that are neither 

more nor less stringent than necessary. The Supreme Court remanded the case to the Court of 

Appeals for resolution of any remaining issues that had not been addressed in that court’s earlier 

rulings (Id. at 475-76). In March 2002, the Court of Appeals rejected all remaining challenges to the 

standards, holding under the traditional standard of judicial review that PM2.5 standards were 

reasonably supported by the administrative record and were not “arbitrary and capricious” American 

Trucking Associations v. EPA, 283 F. 3d 355, 369-72 (D.C. Cir. 2002). 

In October 1997, EPA published its plans for the third periodic review of the air quality criteria 

and NAAQS for PM (62 FR 55201). After CASAC and public review, EPA finalized the 2004 PM 

AQCD (U.S. EPA, 2004, 056905) and 2005 Staff Paper (U.S. EPA, 2005, 090209). For the primary 

fine particle standards, most CASAC PM Panel members favored the option of revising the level of 

the 24-h PM2.5 standard in the range of 35 to 30 μg/m3

 with a 98th percentile form, in concert with 

revising the level of the annual PM2.5 standard in the range of 14 to 13 μg/m3 (Henderson, 2005, 

188316). Most of the members of the CASAC PM Panel also strongly supported establishing a new, 

secondary PM2.5 standard to protect urban visibility and recommended establishing a sub-daily (4- to 

8-h averaging time) PM2.5 standard within the range of 20 to 30 μg/m3

 with a form within the range 

of the 92nd to 98th percentile (Henderson, 2005, 188316). For thoracic coarse particles, there was 

general concurrence among CASAC PM Panel members to revise the PM10 standards by 

establishing a primary standard specifically targeted to address particles in the size range of 2

μm (PM

.5 to 10 

10-2.5). The CASAC PM Panel was also in general agreement “that coarse particles in urban

or industrial areas are likely to be enriched by anthropogenic pollutants that tend to be inherently 

more toxic than the windblown crustal material which typically dominates coarse particle mass in

December 2009 1-6 
arid rural areas.” Based on its review of the Staff Paper, there was general agreement among the 

CASAC PM Panel members that a 24-h PM10-2.5 standard with a level in the range of 50 to 70 μg/m3

with a 98th percentile form, was reasonably justified and that a PM

, 

10-2.5 standard with an annual 

averaging time was not warranted (Henderson, 2005, 156537). On January 17, 2006, EPA proposed

to revise the NAAQS for PM (71 FR 2620). For fine particles, EPA proposed to retain PM

. 

e 

d PM 

x 

h 

the 

h 

ing 

 for 

2.5 as the 

indicator, to retain standards for 24-h and annual exposures, and to revise the form of the annual 

standard to tighten conditions for demonstrating compliance using spatially averaged monitoring

EPA also proposed to revise the level of the 24-h PM2.5 standard to 35 μg/m3

 to provide increased 

protection against health effects associated with short-term PM2.5 exposures, including premature 

mortality and increased hospital admission and emergency room visits, but proposed to retain th

level of the annual PM2.5 standard at 15 μg/m3, continuing protection against health effects 

associated with long-term exposure including premature mortality and development of chronic 

respiratory disease. With regard to the primary standards for thoracic coarse particles, EPA proposed

to revise the 24-h PM10 standard in part by establishing a new indicator for thoracic coarse particles 

(particles generally between 2.5 and 10 μm in diameter), qualified so as to include any ambient mix 

of PM10-2.5 that was dominated by resuspended dust from high density traffic on paved roads an

generated by industrial sources and construction sources, and proposed to exclude any ambient mi

of PM10-2.5 that was dominated by rural windblown dust and soils and PM10-2.5 generated by 

agricultural and mining sources. EPA also proposed a detailed monitoring regime in conjunction wit

this proposed indicator (71 FR 2710, 2731-42). The EPA proposed to set a 24-h standard (using 

proposed indicator) at a level of 70 μg/m3

 to continue to provide a level of protection against healt

effects associated with short-term exposure (including hospital admissions for cardiopulmonary 

diseases, increased respiratory symptoms and possibly premature mortality) in those areas where the 

proposed indicator was found, generally equivalent to the level of protection provided by the exist

24-h PM10 standard. Also, EPA proposed to revoke, upon finalization of a primary 24-h standard

thoracic coarse particles, the 24-h PM10 standard as well as the annual PM10 standard. 

EPA proposed to revise the secondary standards by making them identical to the suite of 

proposed primary standards for fine and coarse particles, providing protection against PM-related 

public welfare effects including visibility impairment, effects on vegetation and ecosystems, and 

materials damage and soiling. EPA also solicited comment on adding a new sub-daily PM2.5

secondary standard to address visibility impairment in urban areas. 

CASAC provided additional advice to EPA in a letter to the Administrator requesting 

reconsideration of CASAC’s recommendations for both the primary and secondary PM2.5 standards, 

as well as standards for thoracic coarse particles (Henderson, 2006, 156538). 

On September 21, 2006, EPA announced its final decisions to revise the primary and 

secondary NAAQS for PM to provide increased protection of public health and welfare, respectively 

(71 FR 61144). With regard to the primary and secondary standards for fine particles, EPA revised 

the level of the 24-h PM2.5 standard to 35 μg/m3

, retained the level of the annual PM2.5 standard at 

15 μg/m3

, and revised the form of the annual PM2.5 standard by narrowing the constraints on the 

optional use of spatial averaging. EPA established the secondary standard for fine particles identical 

to the primary standards. With regard to the primary and secondary standards for thoracic coarse 

particles, EPA retained PM10 as the indicator for coarse particles, retained the level and form of the 

24-h PM10 standard (so the standard remains 150 μg/m3

 with a one expected exceedence form) and 

revoked the annual standard because available evidence generally did not support a link between 

long-term exposure to current ambient levels of coarse particles and health or welfare effects. 

Following promulgation of the revised PM NAAQS in 2006, several parties filed petitions for 

review with respect to: (1) selecting the level of the annual primary PM2.5 standard; (2) setting the 

secondary PM2.5 standards identical to the primary standards; (3) retaining PM10 as the indicator for 

coarse particles and retaining the level and form of the PM10 24-h standard; and (4) revoking the 

PM10 annual standard. On judicial review, the D.C. Circuit remanded the annual standard for fine 

particles to EPA because EPA failed to adequately explain why the annual PM2.5 standard provided 

the requisite protection from both short- and long-term exposures to fine particles including 

protection for vulnerable subpopulations. With respect to protection from short-term exposures, in 

1997 EPA determined that the annual standard was the generally controlling standard for lowering 

both short- and long-term PM2.5 concentrations and the 24-h standard was set to “provide an 

adequate margin of safety against infrequent or isolated peak concentrations that could occur in areas 

that attain the annual standard” (62 FR 38676-77, July 18, 1997). In the 2006 decision, the 

Administrator considered it appropriate to use a somewhat different evidence-based approach from 

December 2009 1-7 
that used in 1997 to set the level of the 24-h and annual PM2.5 standards. In that decision, the 

Administrator relied upon evidence from the short-term exposure PM2.5 studies as the principal basis 

for selecting the proposed level of the 24-h standard and relied upon evidence from the long-term 

exposure PM2.5 studies as the principal basis for selecting the level of the annual standard. The court 

found EPA failed to adequately explain this change in approach in light of CASAC and staff’s 

recommendations to do otherwise. The court also found that EPA had failed to adequately explain 

why a short-term 24-h standard by itself would provide the protection needed from short-term 

exposures. American Farm Bureau Federation v. EPA, 559 F. 3d 512, 520-24 (D.C. Cir. 2009). With 

respect to protection from long-term exposure, the court found that EPA failed to adequately explain 

how the current standard provided “an adequate margin of safety for vulnerable subpopulations, such 

as children, the elderly, or those with conditions that exposure them to greater risk from fine 

particles”. Specifically, EPA did not provide a reasonable explanation of why certain studies, 

including a study of children in Southern California showing lung damage from long-term exposure, 

did not call for a more stringent annual standard (Id. at 522-23). 

The court also remanded the secondary standard for fine particles, based on EPA’s failure to 

adequately explain why setting the secondary NAAQS equivalent to the primary standards provided 

the required protection for public welfare including protection from visibility impairment. The court 

found that EPA failed to identify a target level of visibility impairment that would be requisite to 

protect public welfare. This was contrary to the statute and resulted in a lack of a reasoned basis for 

the final decision. In addition, EPA’s near exclusive reliance on a comparison of numbers of counties 

that would be in nonattainment under various types of standards was an inadequate basis for making 

a decision. It did not take into account the relative visibility protection of different standards, as well 

as the failure of a 24-h standard to address regional differences in humidity and its effect on visibility 

(Id. at 528-31). 

The court upheld EPA’s decision to retain the 24-h PM10 standard to provide protection for 

coarse particle exposures and to revoke the annual PM10 standard. The court found that EPA 

reasonably included all coarse PM within the standard, both urban and non-urban, to provide 

nationwide protection for exposure to coarse PM. It rejected arguments that the evidence showed 

there are no risks from exposure to non-urban coarse PM (Id. at 531-33). The court further found that 

EPA had a reasonable basis to not set separate standards for urban and non-urban coarse PM, namely 

the inability to reasonably define what ambient mixes would be included under either “urban” or 

“non-urban.” In addition, the court found that record evidence supported EPA’s cautious decision to 

provide “some protection from exposure to thoracic coarse particles... in all areas.” The court also 

upheld EPA’s decision to use PM10 as the indicator for coarse particles and to retain the level of the 

standard at 150 μg/m3

. EPA’s final rule acknowledged that evidence of harm from urban-type coarse 

PM is stronger than for other types, and targeted protection at areas where urban-type coarse PM is 

most likely present. The targeting is done by using the indicator PM10 for coarse particles. PM10

includes both coarse PM and fine PM. Urban and industrial areas tend to have higher levels of fine 

PM than rural areas, so that in those areas less coarse PM is allowed – the desired targeting. 

Conversely, fine PM levels tend to be lower in rural areas, so more coarse particles are allowed in 

those areas – again the desired targeting. Likewise, the court concluded that the EPA’s choice of the 

level for the PM10 standard was reasonable for many of the same reasons (Id. at 533-36). The court 

also upheld EPA’s decision to revoke the annual PM10 standard (Id. at 537-38). 

1.3. ISA Development 

EPA initiated the current formal review of the NAAQS for PM on June 28, 2007 with a call for 

information from the public (72 FR 35462). In addition to the call for information, publications were 

identified through an ongoing literature search process that includes extensive computer database 

mining on specific topics. Literature searches were conducted routinely to identify studies published 

since the last review, focusing on publications from 2002 to May 2009. Search strategies were 

iteratively modified in an effort to optimize the identification of pertinent publications. Additional 

papers were identified for inclusion in several ways: review of pre-publication tables of contents for 

journals in which relevant papers may be published; independent identification of relevant literature 

by expert authors; and identification by the public and CASAC during the external review process. 

Generally, only information that had undergone scientific peer review and had been published or 

December 2009 1-8 
accepted for publication was considered. All relevant epidemiologic, controlled human exposure, 

animal toxicological, and welfare effects studies published since the last review were considered, 

including those related to exposure-response relationships, mode(s) of action (MOA), or susceptible 

populations. 

In general, in assessing the scientific quality and relevance of health and environmental effects 

studies, the following considerations have been taken into account when selecting studies for 

inclusion in the ISA or its annexes. The selection process for studies included in this ISA is shown in 

Figure 1-1. 

 Are the study populations, subjects, or animal models adequately selected and are they 

sufficiently well defined to allow for meaningful comparisons between study or exposure 

groups? 

 Are the statistical analyses appropriate, properly performed, and properly interpreted? 

Are likely covariates adequately controlled or taken into account in the study design and 

statistical analysis? 

 Are the PM aerometric data, exposure, or dose metrics of adequate quality and 

sufficiently representative of information regarding ambient PM? 

 Are the health or welfare effect measurements meaningful and reliable? 

In selecting epidemiologic studies, EPA considered whether a given study contained 

information on associations with short- or long-term PM exposures at or near ambient levels of PM; 

evaluated health effects of PM size fractions, components or source-related indicators; considered 

approaches to evaluate issues related to potential confounding by other pollutants; assessed potential 

effect modifiers; and evaluated 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. Among the epidemiologic studies selected, particular emphasis 

was placed on those studies most relevant to the review of the NAAQS. Specifically, studies 

conducted in the U.S. or Canada were discussed in more detail than those from other geographical 

regions. Particular emphasis was placed on: (1) recent multicity studies that employ standardized 

analysis methods for evaluating effects of PM and that provide overall estimates for effects based on 

combined analyses of information pooled across multiple cities; (2) studies that help understand 

quantitative relationships between exposure concentrations and effects; (3) recent studies (published 

since the last PM NAAQS review) that provide evidence on effects in susceptible populations; and 

(4) studies that consider and report PM as a component of a complex mixture of air pollutants. 

December 2009 1-9 
Figure 1-1. Identification of studies for inclusion in the ISA. 

December 2009 1-10 
Criteria for the selection of research evaluating controlled human exposure or animal 

toxicological studies included a focus on studies conducted using relevant pollutant exposures. For 

both types of studies, relevant pollutant exposures are considered to be those generally within one or 

two orders of magnitude of ambient PM concentrations. Studies in which higher doses were used 

may also be considered if they provide information relevant to understanding MOAs or mechanisms, 

as noted below. 

Evaluation of controlled human exposure studies focused on those that approximated expected 

human exposure conditions in terms of concentration and duration. In the selection of controlled 

human exposure studies, emphasis is placed on studies that: (1) investigate potentially susceptible 

populations such as people with cardiovascular diseases or asthmatics, particularly studies that 

compare responses in susceptible individuals with those in age-matched healthy controls; (2) address 

issues such as concentration-response or time-course of responses; (3) investigate exposure to PM 

separately and in combination with other pollutants such as O3; (4) include control exposures to 

filtered air; and (5) have sufficient statistical power to assess findings. 

For selecting toxicological studies for highlighting in the text, emphasis is placed on inhalation 

studies conducted at concentrations <2 mg/m3

 and those studies that approximate expected human 

dose conditions in terms of concentration, size distributions, and duration, which will depend on the 

toxicokinetics and biological sensitivity of the particular laboratory animals examined. Studies that 

elucidated MOAs and/or susceptibility, particularly if the studies were conducted under 

atmospherically relevant conditions, were emphasized whenever possible. A limited number of 

toxicological studies were included that employed intratracheal (IT) instillation techniques, mainly 

for PM10-2.5 studies in rodents, that explored new emerging areas of investigation (e.g., vasomotor 

function), or that evaluated specific potential MOA or mechanisms of response. The sources, 

transport, and fate of fibers and unique nano-materials (viz., dots, hollow spheres, rods, fibers, tubes) 

are not reviewed herein because the in vivo disposition of these unique nanomaterials is not 

necessarily relevant to the behavior of ultrafine (UF) aerosols in the urban environment that are 

created by combustion sources and photochemical formation of secondary organic aerosols. In 

considering the potential effects of different components of PM, EPA has focused on studies that 

have assessed effects for a range of PM sources or components, including those using source 

apportionment methods or comparing effects for numerous PM components, and not on studies of 

individual constituents or species. Studies of ubiquitous PM sources as part of a mixture (i.e., diesel 

exhaust, gasoline exhaust, wood smoke) are included, provided they meet the other remaining 

selection criteria. Those studies of mixtures that are not a significant source of ambient PM, such as 

environmental tobacco smoke (ETS), are not included. 

These criteria provide benchmarks for evaluating various studies and for focusing on the 

policy relevant studies in assessing the body of health and welfare effects evidence. Detailed critical 

analysis of all PM health and welfare effects studies, especially in relation to the above 

considerations, is beyond the scope of this document. Of most relevance for evaluation of studies is 

whether they provide useful qualitative or quantitative information on exposure-effect or 

exposure-response relationships for effects associated with current ambient air concentrations of PM 

that can inform decisions on whether to retain or revise the standards. 

In developing the PM ISA, EPA began by reviewing and summarizing the evidence on (1) 

atmospheric sciences and exposure; (2) the health effects evidence from in vivo and in vitro animal 

toxicological, controlled human exposure, and epidemiologic studies; and (3) the welfare effects of 

PM, including visibility, climate, and ecological effects. In June 2008, EPA held a workshop to 

obtain review of the scientific content of initial draft materials or sections for the draft ISA and its 

annexes, that primarily contain summary information. The purpose of the initial peer review 

workshop was to ensure that the ISA is up to date and focused on the most policy-relevant findings, 

and to assist EPA with integration of evidence within and across disciplines. Following the peer 

review workshop, EPA addressed comments from the peer review workshop and completed the 

initial integration and synthesis of the evidence. 

The integration of evidence on health or welfare effects involves collaboration between 

scientists from various disciplines. As described in the section below, the ISA organization is based 

on health or welfare effect categories. As an example, an evaluation of health effects evidence would 

include summaries of findings from epidemiologic, controlled human exposure, and toxicological 

studies, and integration of the results to draw conclusions based on the causal framework described 

below. Using the causal framework described in Section 1.5, EPA scientists consider aspects such as 

strength, consistency, coherence and biological plausibility of the evidence, and develop draft 

December 2009 1-11 
causality judgments on the nature of the relationships. The draft integrative synthesis sections and 

conclusions are reviewed by EPA internal experts and, as appropriate, by outside expert authors. In 

practice, causality determinations often entail an iterative process of review and evaluation of the 

evidence. The draft ISA is released for review by the CASAC and the public. Comments on the 

characterization of the science as well as the implementation of the causal framework are carefully 

considered in revising and completing the ISA. 

PM10 health studies are included in this assessment because they provide important evidence 

regarding the health effects of PM in general. However, the ISA draws no conclusions regarding 

causality for short- or long-term exposure to PM10, as PM10 is comprised of both fine and thoracic 

coarse particles. As a result, causality determinations are limited to PM2.5, PM10-2.5, and UF particle 

(UFP) size fractions. In the cases where it was determined that PM10 is dominated by fine or thoracic 

coarse PM in specific study locations, these health studies are used in supporting the causality 

determinations for PM2.5 or PM10-2.5. Epidemiologic studies of short-term exposure to PM10 are also 

relied upon to examine potential effect modifiers, potential confounding by copollutants, and the 

influence of different modeling approaches on PM-mortality risk estimates, as well as the 

concentration-response relationship between PM and mortality. Therefore, to the extent possible, the 

findings of PM10 studies are considered insofar as they provide information relevant to the review of 

the NAAQS for fine and thoracic coarse particles. 

1.4. Document Organization 

This ISA is composed of nine chapters. This introductory chapter presents background 

information, and provides an overview of EPA’s framework for making causal judgments. Key 

findings and conclusions for consideration in the review of the NAAQS for PM from the 

atmospheric sciences, ambient air data analyses, exposure assessment, dosimetry, health and welfare 

effects, including judgments on causality for the health and welfare effects of PM exposure, are 

presented in Chapter 2. More detailed summaries, evaluations and integration of the evidence are 

included in Chapters 3 through 9. 

Chapter 3 highlights key concepts or issues relevant to understanding the atmospheric 

chemistry, sources, and exposure of and to PM following a “source-to-exposure” paradigm. 

Chapter 4 summarizes key concepts and recent findings on the dosimetry of PM, and Chapter 5 

discusses possible pathways and MOA for the effects of PM. Chapters 6 and 7 evaluate and integrate 

epidemiologic, controlled human exposure, and animal toxicological information relevant to the 

review of the primary NAAQS for PM. Health effects related to short-term exposures (hours to days) 

to PM are the focus of Chapter 6. Chapter 7 evaluates health evidence related to long-term exposures 

(months to years) to PM. Chapters 6 and 7 are organized by health outcome categories, such as 

cardiovascular or respiratory effects, and each section includes effects of the various types of PM 

studied. For each health outcome category, summary sections then integrate the findings to draw 

conclusions on the evidence for the main size classes of PM (i.e., PM2.5, PM10-2.5, and UFP). 

Chapter 6 also includes a summary and synthesis of the recent health evidence that uses systematic 

approaches to assess health effects of sources and constituents of ambient PM; most such studies 

have evaluated effects of short-term exposure. Chapter 8 evaluates evidence related to populations 

potentially susceptible to PM-related effects. 

Chapter 9 evaluates welfare effects evidence that is relevant to the review of the secondary 

NAAQS for PM. This chapter includes consideration of effects of PM on visibility impairment, 

materials damage, effects of PM on climate, and ecological effects of PM that were not addressed in 

the Integrated Science Assessment for Oxides of Nitrogen and Sulfur―Ecological Criteria 

(NOXSOX ISA) (U.S. EPA, 2008, 157074). The chapter also presents key conclusions and scientific 

judgments regarding causality for welfare effects of PM. In 2008, EPA completed the NOXSOX ISA 

(U.S. EPA, 2008, 157074), that focused on ecological effects related to the deposition of nitrogen 

(N)- and sulfur (S)-containing compounds. The 2008 NOXSOX ISA included ecological effects from

particle-phase compounds (e.g., nitrates and sulfates), primarily effects from acidification a

N-nutrient enrichment and eutrophication. In this ISA, the focus is on recent data for direct welfare

effects of particle-phase NO

nd 

amage 

o 

X and SOX in the ambient air – primarily visibility impairment, d

to materials, and positive and negative climate interactions – not the welfare effects related t

deposition of particle-phase NOX and SOX. 

December 2009 1-12 
A series of annexes supplement this ISA. The annexes provide additional details of the 

pertinent literature published since the last review, as well as selected older studies of particular 

interest. These annexes contain information on: 

 atmospheric chemistry of PM, sampling and analytic methods for measurement of PM, 

concentrations, emissions, sources and human exposure to PM (Annex A); 

 studies on the dosimetry of PM (Annex B); 

 controlled human exposure studies of health effects related to exposure to PM (Annex 

C); 

 toxicological studies of health effects related to exposure to PM in laboratory animals 

and cell cultures (Annex D); 

 epidemiologic studies of health effects from short- and long-term exposure to PM 

(Annex E); and 

 studies that evaluate PM-induced health effects attributable to specific constituents or 

sources (Annex F). 

Within Annexes B through F, detailed information about methods and results of health studies 

is summarized in tabular format, and generally includes information about: concentrations of PM 

and averaging times; study methods employed; results; and quantitative results for relationships 

between effects and exposure to PM. As noted in the section above, the most pertinent results of this 

body of studies are brought into the ISA. 

1.5. EPA Framework for Causal Determination 

The EPA has developed a consistent and transparent basis to evaluate the causal nature of air 

pollution-induced health or environmental effects. The framework described below establishes 

uniform language concerning causality and brings more specificity to the findings. It drew 

standardized language from across the federal government and wider scientific community, 

especially from the recent National Academy of Sciences (NAS) Institute of Medicine (IOM) 

document, Improving the Presumptive Disability Decision-Making Process for Veterans (IOM, 2008, 

156586), the most recent comprehensive work on evaluating causality. 

This introductory section focuses on the evaluation of health effects evidence; while focusing 

on human health outcomes, the concepts are also generally relevant to causality determination for 

welfare effects. This section: 

 describes the kinds of scientific evidence used in establishing a general causal 

relationship between exposure and health effects; 

 defines cause, in contrast to statistical association; 

 discusses the sources of evidence necessary to reach a conclusion about the existence of 

a causal relationship; 

 highlights the issue of multifactorial causation; 

 identifies issues and approaches related to uncertainty; and 

 provides a framework for classifying and characterizing the weight of evidence in 

support of a general causal relationship. 

Approaches to assessing the separate and combined lines of evidence (e.g., epidemiologic, 

controlled human exposure, and animal toxicological studies) have been formulated by a number of 

December 2009 1-13 
regulatory and science agencies, including the IOM of the NAS (IOM, 2008, 156586), International 

Agency for Research on Cancer (IARC, 2006, 093206), EPA Guidelines for Carcinogen Risk 

Assessment (U.S. EPA, 2005, 086237), Centers for Disease Control and Prevention (CDC, 2004, 

056384), and National Acid Precipitation Assessment Program (NAPAP, 1991, 095894). These 

formalized approaches offer guidance for assessing causality. The frameworks are similar in nature, 

although adapted to different purposes, and have proven effective in providing a uniform structure 

and language for causal determinations. Moreover, these frameworks have supported 

decision-making under conditions of uncertainty. 

1.5.1. 

1.5.2. 

Scientific Evidence Used in Establishing Causality 

Causality determinations are based on the evaluation and synthesis of evidence from across 

scientific disciplines; the type of evidence that is most important for such determinations will vary 

by assessment. The most direct evidence of a causal relationship between pollutant exposures and 

human health effects comes from controlled human exposure studies. This type of study 

experimentally evaluates the health effects of administered exposures in human volunteers under 

highly-controlled laboratory conditions. 

In most epidemiologic or observational studies of humans, the investigator does not control 

exposures or intervene with the study population. Broadly, observational studies can describe 

associations between exposures and effects. These studies fall into several categories: 

cross-sectional, prospective cohort, and time-series studies. “Natural experiments” offer the 

opportunity to investigate changes in health with a change in exposure; these include comparisons of 

health effects before and after a change in population exposures, such as the closure of a pollution 

source. 

Experimental animal data can help characterize effects of concern, exposure-response 

relationships, susceptible populations, MOAs and enhance understanding of biological plausibility of 

observed effects. In the absence of controlled human exposure or epidemiologic data, animal data 

alone may be sufficient to support a likely causal determination, assuming that similar responses are 

expected in humans. 

Association and Causation 

“Cause” is a significant, effectual relationship between an agent and an effect on health or 

public welfare. “Association” is the statistical dependence among events, characteristics, or other 

variables. An association is prima facie evidence for causation; alone, however, it is insufficient 

proof of a causal relationship between exposure and disease or health effect. Determining whether an 

observed association is causal rather than spurious involves consideration of a number of factors, as 

described below. Much of the newly available health information evaluated in this ISA comes from 

epidemiologic studies that report a statistical association between ambient exposure and health 

outcomes. 

Many of the health and environmental outcomes reported in these studies have complex 

etiologies. Diseases such as asthma, coronary artery disease or cancer are typically initiated by a web 

of multiple agents. Outcomes depend on a variety of factors, such as age, genetic susceptibility, 

nutritional status, immune competence, and social factors (Gee and Payne-Sturges, 2004, 093070; 

IOM, 2008, 156586). Effects on ecosystems are also multifactorial with a complex web of causation. 

Further, exposure to a combination of agents could cause synergistic or antagonistic effects. Thus, 

the observed risk represents the net effect of many actions and counteractions. 

1.5.3. Evaluating Evidence for Inferring Causation 

Moving from association to causation involves elimination of alternative explanations for the 

association. In estimating the causal influence of an exposure on health or environmental effects, it is 

recognized that scientific findings include uncertainty. Uncertainty can be defined as a state of 

having limited knowledge where it is impossible to exactly describe an existing state or future 

outcome; the lack of knowledge about the correct value for a specific measure or estimate. 

Uncertainty characterization and uncertainty assessment are two activities that lead to different 

degrees of sophistication in describing uncertainty. Uncertainty characterization generally involves a 

December 2009 1-14 
qualitative discussion of the thought processes that lead to the selection and rejection of specific 

data, estimates, scenarios, etc. Uncertainty assessment is more quantitative. The process begins with 

simpler measures (e.g., ranges) and simpler analytical techniques and progresses, to the extent 

needed to support the decision for which the assessment is conducted, to more complex measures 

and techniques. Data will not be available for all aspects of an assessment, and those data that are 

available may be of questionable or unknown quality. In these situations, evaluation of uncertainty 

can include professional judgment or inferences based on analogy with similar situations. The net 

result is that the assessments will be based on a number of assumptions with varying degrees of 

uncertainty. Uncertainties commonly encountered in evaluating health evidence for the criteria air 

pollutants are outlined below for epidemiologic and experimental studies. Various approaches to 

characterizing uncertainty include classical statistical methods, sensitivity analysis, or probabilistic 

uncertainty analysis, in order of increasing complexity and data requirements. The ISA generally 

evaluates uncertainties qualitatively in assessing the evidence from across studies; in some situations 

quantitative analysis approaches, such as meta-regression may be used. 

It is important to note here that, although the following discussion refers primarily to health 

effect studies, many parallels exist with welfare effects studies. Controlled exposure studies have 

been conducted in which plant species have been directly exposed to air pollutants, and the strengths 

and limitations of that body of studies mirror those of the controlled human exposure studies 

discussed below. Ecological field or natural gradient studies are similar to epidemiologic studies, for 

example, in the study of free-living populations and in the challenges faced in distinguishing effects 

of pollutants within a mixture. 

Controlled human exposure studies evaluate the effects of exposures to a variety of pollutants 

in a highly-controlled laboratory setting. Also referred to as human clinical studies, these 

experiments allow investigators to expose subjects to fixed concentrations of air pollutants under 

carefully regulated environmental conditions and activity levels. Controlled human exposures to PM 

typically involve exposing subjects either at rest or while engaged in intermittent exercise in a 

whole-body exposure chamber, although mouthpiece and facemask systems can also be used. A 

variety of different types of particles are used in these studies including ambient outdoor particles, 

concentrated ambient particles (CAPs), diesel exhaust (DE) from a diesel engine, wood smoke 

generated in a wood stove, laboratory generated model particles (e.g., elemental carbon [EC] or zinc 

oxide [ZnO]), or particles collected on a filter, resuspended in saline, and administered either 

through IT instillation or inhalation. The recovery of particles on filters is variable and some 

components, such as organics, may be too volatile to be collected. Exposures to artificially generated 

particles may provide important information on the health effects of PM, but are not truly 

representative of ambient air pollution particles. The direct exposure of humans to ambient air 

pollution particles may be complicated by factors that cannot be controlled such as coexposures to 

other air pollutants (e.g., O3, SO2, and NO2). In concentrating ambient particles, gaseous 

copollutants are not proportionately concentrated and interactions between PM and the copollutant

cannot be investigated unless the latter are re-introduced. These limitations as well as daily 

variability in concentration and composition can make it difficult to compare the results from 

controlled human exposure studies employing particles from 

s 

different sources. 

In some instances, controlled human exposure studies can also be used to characterize 

concentration-response relationships at pollutant concentrations relevant to ambient conditions. 

Controlled human exposures are typically conducted using a randomized crossover design with 

subjects exposed both to PM and a clean air control. In this way, subjects serve as their own controls, 

effectively controlling for many potential confounders. However, controlled human exposure studies 

are limited by a number of factors including a small sample size and short exposure times. These 

laboratory studies are often conducted at PM concentrations much higher than those typically 

observed under ambient conditions, which may result in an overestimate of the acute response to 

exposure in the general population. Although the repetitive nature of ambient PM exposures may 

lead to cumulative health effects, this type of exposure is not practical to replicate in a laboratory 

setting. In addition, while subjects do serve as their own controls, personal exposure to pollutants in 

the hours and days preceding the controlled exposures may vary significantly between and within 

individuals. Finally, controlled human exposure studies require investigators to adhere to stringent 

health criteria for a subject to be included in the study, and therefore the results cannot necessarily be 

generalized to an entire population. Although some controlled human exposure studies have included 

health comprised individuals such as asthmatics or individuals with chronic obstructive pulmonary 

disease (COPD) or coronary artery disease, these individuals must also be relatively healthy and do 

December 2009 1-15 
not represent the most sensitive individuals in the population. Thus, a lack of observation of effects 

from controlled human exposure studies does not necessarily mean that a causal relationship does 

not exist. While controlled human exposure studies provide important information on the biological 

plausibility of associations observed between air pollutant exposure and health outcomes in 

epidemiologic studies, observed effects in these studies may underestimate the response in certain 

subpopulations. 

Epidemiologic studies provide important information on the associations between health 

effects and exposure of human populations to ambient air pollution. In the evaluation of 

epidemiologic evidence, one important consideration is potential confounding. Confounding is “...a 

confusion of effects. Specifically, the apparent effect of the exposure of interest is distorted because 

the effect of an extraneous factor is mistaken for or mixed with the actual exposure effect (which 

may be null)” (Rothman and Greenland, 1998, 086599). One approach to remove spurious 

associations from possible confounders is to control for characteristics that may differ between 

exposed and unexposed persons; this is frequently termed “adjustment.” Appropriate statistical 

adjustment for confounders requires identifying and measuring all reasonably expected confounders. 

Deciding which variables to control for in a statistical analysis of the association between exposure 

and disease or health outcome depends on knowledge about possible mechanisms and the 

distributions of these factors in the population under study. In addition, scientific judgment is needed 

regarding likely sources and magnitude of confounding, together with consideration of how well the 

existing constellation of study designs, results, and analyses address this potential threat to 

inferential validity. One key consideration in this review is evaluation of the potential contribution of 

PM to health effects when it is a component of a complex air pollutant mixture. Reported PM effect 

estimates in epidemiologic studies may reflect independent PM effects on respiratory and 

cardiovascular health. Ambient PM may also be serving as an indicator of complex ambient air 

pollution mixtures that share the same source as PM (i.e., combustion of S-containing fuels or motor 

vehicle emissions). Alternatively, copollutants may mediate the effects of PM or PM may influence 

the toxicity of copollutants. 

Another important consideration in the evaluation of epidemiologic evidence is effect 

modification. “Effect-measure modification differs from confounding in several ways. The main 

difference is that, whereas confounding is a bias that the investigator hopes to prevent or remove 

from the effect estimate, effect-measure modification is a property of the effect under study . . . In 

epidemiologic analysis one tries to eliminate confounding but one tries to detect and estimate effectmeasure modification” (Rothman and Greenland, 1998, 086599). Examples of effect modifiers in 

some of the studies evaluated in this ISA include environmental variables (e.g., temperature or 

humidity), individual risk factors (e.g., education, cigarette smoking status, age), and community 

factors (e.g., percent of population > 65 years old). It is often possible to stratify the relationship 

between health outcome and exposure by one or more of these risk factor variables. Effect modifiers 

may be encountered (a) within single-city time-series studies; or (b) across cities in a two-stage 

hierarchical model or meta-analysis. 

Several statistical methods are available to detect and control for potential confounders, with 

none of them being completely satisfactory. Multivariable regression models constitute one tool for 

estimating the association between exposure and outcome after adjusting for characteristics of 

participants that might confound the results. The use of multipollutant regression models has been 

the prevailing approach for controlling potential confounding by copollutants in air pollution health 

effects studies. Finding the pollutant likely responsible for the health outcome from multipollutant 

regression models is made difficult by the possibility that one or more air pollutants may be acting as 

a surrogate for an unmeasured or poorly-measured pollutant or for a particular mixture of pollutants. 

In addition, more than one pollutant may exert similar health effects, resulting in independently 

observed associations for multiple pollutants. Further, the correlation between the air pollutant of 

interest and various copollutants may make it difficult to discern associations between different 

pollutant exposures and health effects. Thus, results of models that attempt to distinguish gaseous 

and particle effects must be interpreted with caution. The number and degree of diversity of 

covariates, as well as their relevance to the potential confounders, remain matters of scientific 

judgment. Despite these limitations, the use of multipollutant models is still the prevailing approach 

employed in most air pollution epidemiologic studies, and provides some insight into the potential 

for confounding or interaction among pollutants. 

Adjustment for potential confounders can be influenced by differential exposure measurement 

error. There are several components that contribute to exposure measurement error in epidemiologic 

December 2009 1-16 
studies, including the difference between true and measured ambient concentrations, the difference 

between average personal exposure to ambient pollutants and ambient concentrations at central 

monitoring sites, and the use of average population exposure rather than individual exposure 

estimates. Previous AQCDs have examined the role of measurement error in time-series 

epidemiologic studies using simulated data and mathematical analyses and suggested that “transfer 

of effects” would only occur under unusual circumstances (i.e., “true” predictors having high 

positive or negative correlation; substantial measurement error; or extremely negatively correlated 

measurement errors) (U.S. EPA, 2004, 056905). 

Confidence that unmeasured confounders are not producing the findings is increased when 

multiple studies are conducted in various settings using different subjects or exposures; each of 

which might eliminate another source of confounding from consideration. Thus, multicity studies 

which use a consistent method to analyze data from across locations with different levels of 

covariates can provide insight on potential confounding in associations. Intervention studies, because 

of their quasi-experimental nature, can be particularly useful in characterizing causation. 

In addition to controlled human exposure and epidemiologic studies, the tools of experimental 

biology have been valuable for developing insights into human physiology and pathology. Animal 

toxicological studies explore the effects of pollutants on human health, especially through the study 

of model systems in other species. These studies evaluate the effects of exposures to a variety of 

pollutants in a highly controlled laboratory setting, and allow exploration of MOAs or mechanisms 

by which a pollutant may cause effects. Background knowledge of the biological mechanisms by 

which an exposure might or might not cause disease can prove crucial in establishing, or negating, a 

causal claim. There are, however, uncertainties associated with quantitative extrapolations between 

laboratory animals and humans on the pathophysiological effects of any pollutant. Animal species 

can differ from each other in fundamental aspects of physiology and anatomy (e.g., metabolism, 

airway branching, hormonal regulation) that may limit extrapolation. The differences between 

humans and rodents with regard to pollutant absorption and distribution profiles based on breathing 

pattern, exposure dose, and differences in lung structure and anatomy all have to be taken into 

consideration. 

A relatively new tool available for experimental studies of PM exposure is the particle 

concentrator. Particle concentrators enable human subjects, animals, or cell culture systems to be 

exposed to atmospheric PM at concentrations greater than that observed under ambient conditions. 

As ambient PM is just one component of a complex mixture that interacts with gases and other 

aerosols, CAPs systems provide a method of exposing subjects to the particle phase. There are 

several instrument systems used to concentrate ambient PM in controlled human or animal exposure 

studies (Gordon et al., 1999, 001176; Maciejczyk and Chen, 2005, 087456; Sioutas et al., 1995, 

001629; Sioutas et al., 1999, 001633). Gases (such as O3 and SO2) are not concentrated nor is 

PM10-2.5 (except for the coarse particle concentrator) and only certain systems are capable of 

concentrating UFPs. In UF CAPs systems, increased number fraction of organic carbon and PAHs, 

along with decreased relative percentage of EC particles have been reported in concentrated PM 

compared to ambient PM (Su et al., 2006, 157021). These data suggest that for UF concentrators, the 

CAPs do not accurately reflect atmospheric UFP composition. 

The ability to extrapolate between species has not generally changed since the 2004 PM 

AQCD but some considerations related to coarse particles merit attention. The inhalability of 

particles >2.5 μm in diameter is considerably lower in rats than in humans; however, once inhaled, 

deposition in the extrathoracic region is near 100% percent for particles >5 μm for most laboratory 

animal species (rat, mouse, hamster, guinea pig, and dogs). By contrast, penetration of thoracic 

coarse particles into the lower respiratory tract is greater in humans than rodents due to the 

moderately less efficient nasal deposition of humans and oronasal breathing (especially during 

exercise). The extent to which coarse particle deposition in the lower respiratory tract differs 

between the species is highly dependent on the activity level of the human exposure scenario in 

contrast with the resting exposure conditions common to rodent exposures. Endotracheal exposures 

of rodents may be needed to achieve coarse particle tissue doses in the lower respiratory tract of 

rodents similar to those experienced by humans. For particles <1 μm, including UFPs, deposition is 

expected to be relatively similar between the species. 

There are also differences between species in both the rates of particle clearance from and 

retention in the lung. The clearance rate of particles from the ciliated airways of rats is considerably 

greater than humans. There is also evidence of prolonged particle retention in the smaller 

bronchioles of humans that does not appear to exist or has not been observed in rats. Under most 

December 2009 1-17 
circumstances, clearance from the alveolar region of rats is also more rapid than observed in humans. 

Thus, these combined effects contribute to a greater particle burden in the lower respiratory tract of 

humans relative to rats. An important consideration in studies where are rats chronically exposed to 

high concentrations of insoluble particles, is the potential for “overload conditions.” Rats, unlike 

other laboratory animals or humans, may experience a reduction in their alveolar clearance rates and 

an accumulation of interstitial particle burden and under these conditions, the relevance of tissue 

burdens and responses to humans is questionable. Considering interspecies differences in both 

deposition and clearance, greater exposure concentrations are required to achieve coarse particle 

tissue doses in the lower respiratory tract of rodents similar to those experienced by humans. 

1.5.4. Application of Framework for Causal Determination 

EPA uses a two-step approach to evaluate the scientific evidence on health or environmental 

effects of criteria pollutants. The first step determines the weight of evidence in support of causation 

and characterizes the strength of any resulting causal classification. The second step includes further 

evaluation of the quantitative evidence regarding the concentration-response relationships and the 

loads or levels, duration and pattern of exposures at which effects are observed. 

To aid judgment, various “aspects”1

 of causality have been discussed by many philosophers 

and scientists. The most widely cited aspects of causality in epidemiology, and public health, in 

general, were articulated by Sir Austin Bradford Hill (1965, 071664) and have been widely used 

(CDC, 2004, 056384; IARC, 2006, 093206; IOM, 2008, 156586; NRC, 2004, 156814; U.S. EPA, 

2005, 086237). Several adaptations of the Hill aspects have been used in aiding causality judgments 

in the ecological sciences (Adams, 2003, 156192; Collier, 2003, 155736; Fox, 1991, 156444; 

Gerritsen et al., 1998, 156465). 

These aspects (Hill, 1965, 071664) have been modified (Table 1-2) for use in causal 

determinations specific to health and welfare effects or pollutant exposures.2 Some aspects are more 

likely than others to be relevant for evaluating evidence on the health or environmental effects of 

criteria air pollutants. For example, the analogy aspect does not always apply and specificity would 

not be expected for multi-etiologic health outcomes such as asthma or cardiovascular disease, or 

ecological effects related to acidification. Aspects that usually play a larger role in determination of 

causality are consistency of results across studies, coherence of effects observed in different study 

types or disciplines, biological plausibility, exposure-response relationship, and evidence from 

“natural” experiments. 

Although these aspects provide a framework for assessing the evidence, they do not lend 

themselves to being considered in terms of simple formulas or fixed rules of evidence leading to 

conclusions about causality (Hill, 1965, 071664). For example, one cannot simply count the number 

of studies reporting statistically significant results or statistically nonsignificant results and reach 

credible conclusions about the relative weight of the evidence and the likelihood of causality. In 

addition, it is important to note that the aspects in Table 1-2 cannot be used as a strict checklist, but 

rather to determine the weight of the evidence for inferring causality. While these aspects are 

particularly salient in this assessment, it is also important to recognize that no one aspect is either 

necessary or sufficient for drawing inferences of causality. 

 

1

 The “aspects” described by Hill (1965, 071664) have become, in the subsequent literature, more commonly described as “criteria.” The 

original term “aspects” is used here to avoid confusion with ‘criteria’ as it is used, with different meaning, in the Clean Air Act. 

2

 The Hill aspects were developed for interpretation of epidemiologic results. They have been modified here for use with a broader array of 

data, i.e., epidemiologic, controlled human exposure, and animal toxicological studies, as well as in vitro data, and to be more consistent 

with EPA’s Guidelines for Carcinogen Risk Assessment. 

December 2009 1-18 
Table 1-2. Aspects to aid in judging causality. 

Aspect Description 

CONSISTENCY OF THE 

OBSERVED ASSOCIATION 

An inference of causality is strengthened when a pattern of elevated risks is observed across 

several independent studies, conducted in multiple locations by multiple investigators. The 

reproducibility of findings constitutes one of the strongest arguments for causality. If there are 

discordant results among investigations, possible reasons such as differences in exposure, 

confounding factors, and the power of the study are considered.

COHERENCE An inference of causality from epidemiologic associations may be strengthened by other lines of 

evidence (e.g., controlled human exposure and animal toxicological studies) that support a 

cause-and-effect interpretation of the association. Causality is also supported when epidemiologic 

associations are reported across study designs and across related health outcomes. Evidence on 

ecological or welfare effects may be drawn from a variety of experimental approaches (e.g., 

greenhouse, laboratory, and field) and subdisciplines of ecology (e.g., community ecology, 

biogeochemistry and paleological/ historical reconstructions). The coherence of evidence from 

various fields greatly adds to the strength of an inference of causality. The absence of other lines of 

evidence, however, is not a reason to reject causality 

BIOLOGICAL PLAUSIBILITY An inference of causality tends to be strengthened by consistency with data from experimental 

studies or other sources demonstrating plausible biological mechanisms. A proposed mechanistic 

linking between an effect, and exposure to the agent, is an important source of support for causality, 

especially when data establishing the existence and functioning of those mechanistic links are 

available. A lack of biological understanding, however, is not a reason to reject causality. 

BIOLOGICAL GRADIENT 

(EXPOSURE-RESPONSE 

RELATIONSHIP) 

A well characterized exposure-response relationship (e.g., increasing effects associated with greater 

exposure) strongly suggests cause and effect, especially when such relationships are also observed 

for duration of exposure (e.g., increasing effects observed following longer exposure times). There 

are, however, many possible reasons that a study may fail to detect an exposure-response 

relationship. Thus, although the presence of a biological gradient may support causality, the 

absence of an exposure-response relationship does not exclude a causal relationship. 

STRENGTH OF THE 

OBSERVED ASSOCIATION 

The finding of large, precise risks increases confidence that the association is not likely due to 

chance, bias, or other factors. However, given a truly causal agent, a small magnitude in the effect 

could follow from a lower level of exposure, a lower potency, or the prevalence of other agents 

causing similar effects. While large effects support causality, modest effects therefore do not 

preclude it. 

EXPERIMENTAL EVIDENCE The strongest evidence for causality can be provided when a change in exposure brings about a 

change in occurrence or frequency of health or welfare effects. 

TEMPORAL RELATIONSHIP OF 

THE OBSERVED ASSOCIATION 

Evidence of a temporal sequence between the introduction of an agent and appearance of the effect 

constitutes another argument in favor of causality. 

SPECIFICITY OF THE 

OBSERVED ASSOCIATION 

As originally intended, this refers to increased inference of causality if one cause is associated with 

a single effect or disease (Hill, 1965, 071664). Based on the current understanding this is now 

considered one of the weaker guidelines for causality; for example, many agents cause respiratory 

disease and respiratory disease has multiple causes. At the scale of ecosystems, as in 

epidemiology, complexity is such that single agents causing single effects, and single effects 

following single causes, are extremely unlikely. The ability to demonstrate specificity under certain 

conditions remains, however, a powerful attribute of experimental studies. Thus, although the 

presence of specificity may support causality, its absence does not exclude it.

ANALOGY Structure activity relationships and information on the agent’s structural analogs can provide insight 

into whether an association is causal. Similarly, information on mode of action for a chemical, as one 

of many structural analogs, can inform decisions regarding likely causality.

1.5.5. First Step—Determination of Causality 

In the ISA, EPA assesses the results of recent relevant publications, building upon evidence 

available during the previous NAAQS review, to draw conclusions on the causal relationships 

between relevant pollutant exposures and health or environmental effects. This ISA uses a five-level 

December 2009 1-19 
hierarchy that classifies the weight of evidence for causation, not just association1

. In developing this 

hierarchy, EPA has drawn on the work of previous evaluations, most prominently the IOM’s 

Improving the Presumptive Disability Decision-Making Process for Veterans (IOM, 2008, 156586), EPA’s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005, 086237) and the U.S. Surgeon 

General’s smoking reports (CDC, 2004, 056384). This weight of evidence evaluation is based on 

various lines of evidence from across the health and environmental effects disciplines. These 

separate judgments are integrated into a qualitative statement about the overall weight of the 

evidence and causality. The five descriptors for causal determination are described in Table 1-3. 

For PM, this determination of causality step involved a rather complex evaluation of evidence 

for different PM indices, different types of health or environmental effects, and for short- and longterm exposure periods. There were insufficient data on peak (i.e., <24 h) exposures for any PM size 

fraction with health effects to make causality determinations for this exposure category. Causality 

determinations were made for the PM measure (PM2.5, PM10-2.5, and UFPs, to the extent evidence 

was available for each measure), the overall effect category, and the exposure duration. As noted 

above, to the extent possible, results of PM10 studies are considered in causality determinations for

PM ) 

to 

ht of 

 

2.5 and PM10-2.5. In the evaluation of health effects findings in Chapter 6 (for short-term exposure

and Chapter 7 (for long-term exposure), evidence was evaluated for health outcome categories, such

as cardiovascular effects, and then conclusions were drawn based upon the integration of evidence 

from across disciplines (e.g., epidemiology, controlled human exposure, and toxicology) and also 

across the suite of related individual health outcomes. Chapters 6 and 7 initially summarize and 

evaluate findings for individual health outcomes, then integrate the results in summary sections 

draw conclusions on causality for each PM indicator. The causality narratives present the weig

evidence that highlights the quality and breadth of the data, including any limitations or 

uncertainties. In the integrative synthesis and conclusions in Chapter 2, the ISA presents causality 

determinations and a summary of the underlying basis for those determinations for the PM indicator 

(e.g., PM2.5), for the exposure time period (e.g., short- and long-term exposure) and for the major 

health effect categories. 

1

 It should be noted that the CDC and IOM frameworks use a four-category hierarchy for the strength of the evidence. A five-level 

hierarchy is used here to be consistent with the EPA Guidelines for Carcinogen Risk Assessment and to provide a more nuanced set of 

categories. 

December 2009 1-20 
Table 1-3. Weight of evidence for causal determination. 

Determination Health Effects Ecological and Welfare Effects 

CAUSAL 

RELATIONSHIP

Evidence is sufficient to conclude that there is a causal 

relationship with relevant pollutant exposures. That is, the 

pollutant has been shown to result in health effects in 

studies in which chance, bias, and confounding could be 

ruled out with reasonable confidence. For example: a) 

controlled human exposure studies that demonstrate 

consistent effects; or b) observational studies that cannot 

be explained by plausible alternatives or are supported by 

other lines of evidence (e.g., animal studies or mode of 

action information). Evidence includes replicated and 

consistent high-quality studies by multiple investigators. 

Evidence is sufficient to conclude that there is a causal 

relationship with relevant pollutant exposures. That is, the 

pollutant has been shown to result in effects in studies in 

which chance, bias, and confounding could be ruled out 

with reasonable confidence. Controlled exposure studies 

(laboratory or small- to medium-scale field studies) 

provide the strongest evidence for causality, but the scope 

of inference may be limited. Generally, determination is 

based on multiple studies conducted by multiple research 

groups, and evidence that is considered sufficient to infer 

a causal relationship is usually obtained from the joint 

consideration of many lines of evidence that reinforce 

each other. 

LIKELY TO BE A 

CAUSAL 

RELATIONSHIP

Evidence is sufficient to conclude that a causal 

relationship is likely to exist with relevant pollutant 

exposures, but important uncertainties remain. That is, 

the pollutant has been shown to result in health effects in 

studies in which chance and bias can be ruled out with 

reasonable confidence but potential issues remain. For 

example: a) observational studies show an association, 

but copollutant exposures are difficult to address and/or 

other lines of evidence (controlled human exposure, 

animal, or mode of action information) are limited or 

inconsistent; or b) animal toxicological evidence from 

multiple studies from different laboratories that 

demonstrate effects, but limited or no human data are 

available. Evidence generally includes replicated and 

high-quality studies by multiple investigators. 

Evidence is sufficient to conclude that there is a likely 

causal association with relevant pollutant exposures. That 

is, an association has been observed between the 

pollutant and the outcome in studies in which chance, bias 

and confounding are minimized, but uncertainties remain. 

For example, field studies show a relationship, but 

suspected interacting factors cannot be controlled, and 

other lines of evidence are limited or inconsistent. 

Generally, determination is based on multiple studies in 

multiple research groups. 

SUGGESTIVE OF 

A CAUSAL 

RELATIONSHIP

Evidence is suggestive of a causal relationship with 

relevant pollutant exposures, but is limited because 

chance, bias and confounding cannot be ruled out. For 

example, at least one high-quality epidemiologic study 

shows an association with a given health outcome but the 

results of other studies are inconsistent. 

Evidence is suggestive of a causal relationship with 

relevant pollutant exposures, but chance, bias and 

confounding cannot be ruled out. For example, at least 

one high-quality study shows an effect, but the results of 

other studies are inconsistent. 

INADEQUATE TO 

INFER A CAUSAL 

RELATIONSHIP

Evidence is inadequate to determine that a causal 

relationship exists with relevant pollutant exposures. The 

available studies are of insufficient quantity, quality, 

consistency or statistical power to permit a conclusion 

regarding the presence or absence of an effect. 

The available studies are of insufficient quality, 

consistency or statistical power to permit a conclusion 

regarding the presence or absence of an effect. 

NOT LIKELY TO 

BE A CAUSAL 

RELATIONSHIP

Evidence is suggestive of no causal relationship with 

relevant pollutant exposures. Several adequate studies, 

covering the full range of levels of exposure that human 

beings are known to encounter and considering 

susceptible populations, are mutually consistent in not 

showing an effect at any level of exposure. 

Several adequate studies, examining relationships with 

relevant exposures, are consistent in failing to show an 

effect at any level of exposure. 

1.5.6. 

1.5.

Second Step—Evaluation of Response 

Beyond judgments regarding causality are questions relevant to quantifying health or 

environmental risks based on our understanding of the quantitative relationships between pollutant 

exposures and health or welfare effects. 

6.1. Effects on Human Populations 

Once a determination is made regarding the causal relationship between the pollutant and 

outcome category, important questions regarding quantitative relationships include: 

December 2009 1-21 
 What is the concentration-response or dose-response relationship in the human 

population? 

 What exposure conditions (dose or exposure, duration and pattern) are important? 

 What subpopulations appear to be differentially affected (i.e., more susceptible to 

effects)? 

To address these questions, in the second step of the EPA framework, the entirety of 

quantitative evidence is evaluated to best quantify those concentration-response relationships that 

exist. This requires evaluation of pollutant concentrations and exposure durations at which effects 

were observed for exposed populations including potentially susceptible populations. This 

integration of evidence results in identification of a study or set of studies that best approximates the 

concentration-response relationships between health outcomes and PM indicators for the U.S. 

population or subpopulations, given the current state of knowledge and the uncertainties that 

surrounded these estimates. 

To accomplish this, evidence from multiple and diverse types of studies is considered. To the 

extent available, the ISA evaluates results from across epidemiologic studies that use various 

methods to evaluate the form of relationships between PM and health outcomes, and draws 

conclusions on the most well-supported shape of these relationships. Controlled human exposure 

studies can also provide data on the concentration-response relationship. Animal data may inform 

evaluation of concentration-response relationships, particularly relative to MOAs, and characteristics 

of susceptible populations. For some health outcomes, the probability and severity of health effects 

and associated uncertainties can be characterized. Chapter 2 presents the integrated findings 

informative for evaluation of population risks. 

An important consideration in characterizing the public health impacts associated with 

exposure to a pollutant is whether the concentration-response relationship is linear across the full 

concentration range encountered, or if nonlinear relationships exist along any part of this range. Of 

particular interest is the shape of the concentration-response curve at and below the level of the 

current standards. The shape of the concentration-response curve varies, depending on the type of 

health outcome, underlying biological mechanisms and dose. At the human population level, 

however, various sources of variability and uncertainty tend to smooth and “linearize” the 

concentration-response function (such as the low data density in the lower concentration range, 

possible influence of measurement error, and individual differences in susceptibility to air pollution 

health effects). In addition, many chemicals and agents may act by perturbing naturally occurring 

background processes that lead to disease, which also linearizes population concentration-response 

relationships (Clewell and Crump, 2005, 156359; Crump et al., 1976, 003192; Hoel, 1980, 156555). 

These attributes of population dose-response may explain why the available human data at ambient 

concentrations for some environmental pollutants (e.g., PM, O3, lead [Pb], ETS, radiation) do not 

exhibit evident thresholds for health effects, even though likely mechanisms include nonlinear 

processes for some key events. These attributes of human population dose-response relationships 

have been extensively discussed in the broader epidemiologic literature (Rothman and Greenland, 

1998, 086599). 

Publication bias is a source of uncertainty regarding the magnitude of health risk estimates. It 

is well understood that studies reporting non-null findings are more likely to be published than 

reports of null findings, and publication bias can also result in overestimation of effect estimate sizes 

(Ioannidis, 2008, 188317). For example, effect estimates from single-city epidemiologic studies have 

been found to be generally larger than those from multicity studies (Anderson et al., 2005, 087916). 

Finally, identification of the susceptible population groups contributes to an understanding of 

the public health impact of pollutant exposures. Epidemiologic studies can help identify susceptible 

populations by evaluating health responses in the study population. Examples include stratified 

analyses for subsets of the population under study, or testing for interactions or effect modification 

by factors such as gender, age group, or health status. Experimental studies using animal models of 

susceptibility or disease can also inform the extent to which health risks are likely greater in specific 

population subgroups. Further discussion of these groups is in Chapter 8. 

December 2009 1-22 
1.5.

1.5.7. 

6.2. Effects on Public Welfare 

Key questions for understanding the quantitative relationships between exposure (or 

concentration or deposition) to a pollutant and risk to the public welfare (e.g., ecosystems, visibility, 

materials, climate): 

 What elements of the ecosystem (e.g., types, regions, taxonomic groups, populations, 

functions, etc.) appear to be affected, or are more sensitive to effects? 

 Under what exposure conditions (amount deposited or concentration, duration and 

pattern) are effects seen? 

 What is the shape of the concentration-response or exposure-response relationship? 

Evaluations of causality typically consider the probability of welfare effects changing in 

response to exposure. A challenge to the quantification of exposure-response relationships for 

ecological effects is the variability across ecosystems. Ecological responses are evaluated within the 

range of observations, so a quantitative relationship may be determined for a given ecological system 

and scale. However, there is great regional and local variability in ecosystems. Thus, exposureresponse relationships are often available site by site, rather than at the national or even regional 

scale. For example, an ecological response to deposition of a given pollutant can differ greatly 

between ecosystems. Where results from greenhouse or animal ecotoxicological studies are 

available, they may be used to aid in characterizing exposure-response relationships, particularly 

relative to mechanisms of action, and characteristics of sensitive biota. 

Concepts in Evaluating Adversity of Health Effects 

In evaluating the health evidence, a number of factors can be considered in determining the 

extent to which health effects are “adverse” for health outcomes such as changes in lung function. 

What constitutes an adverse health effect may vary between populations. Some changes in healthy 

individuals may not be considered adverse while those of a similar type and magnitude are 

potentially adverse in more susceptible individuals. 

The American Thoracic Society (ATS) published an official statement titled What Constitutes 

an Adverse Health Effect of Air Pollution? (ATS, 2000, 011738). This statement updated the 

guidance for defining adverse respiratory health effects that had been published 15 years earlier 

(ATS, 1985, 006522), taking into account new investigative approaches used to identify the effects 

of air pollution and reflecting concern for impacts of air pollution on specific susceptible groups. In 

the 2000 update, there was an increased focus on quality of life measures as indicators of adversity 

and a more specific consideration of population risk. Exposure to air pollution that increases the risk 

of an adverse effect to the entire population is viewed as adverse, even though it may not increase 

the risk of any identifiable individual to an unacceptable level; estimated mean population effects do 

not reflect more severe effects in individuals. For example, a population of asthmatics could have a 

distribution of lung function such that no identifiable individual has a level associated with 

significant impairment. Exposure to air pollution could shift the distribution such that no identifiable 

individual experiences clinically-relevant effects; this shift toward decreased lung function, however, 

would be considered adverse because individuals within the population would have diminished 

reserve function and, therefore, would be at increased risk to further environmental insult. 

1.6. Summary 

This ISA is a review, synthesis, and evaluation of the most policy-relevant science, and 

communicates critical science judgments relevant to the NAAQS review. It reviews the most 

policy-relevant evidence from environmental effects studies and includes information on 

atmospheric chemistry, PM sources and emissions, exposure, and dosimetry. This ISA incorporates 

clarification and revisions based on advice and comments provided by EPA’s CASAC (Samet, 2009, 

190992; Samet, 2009, 199522). Annexes to the ISA provide additional details of the literature 

published since the last review. A framework for making critical judgments concerning causality 

December 2009 1-23 
appears in this chapter. It relies on a widely accepted set of principles and standardized language to 

express evaluation of the evidence. This approach can bring rigor and clarity to current and future 

assessments. This ISA should assist EPA and others, now and in the future, to accurately represent 

what is presently known—and what remains unknown—concerning the effects of PM on human 

health and public welfare. 

December 2009 1-24 
Chapter 1 References 

Adams SM (2003). Establishing causality between environmental stressors and effects on aquatic ecosystems. Hum Ecol 

Risk Assess, 9: 17-35. 156192

Anderson HR; Atkinson RW; Peacock JL; Sweeting MJ; Marston L (2005). Ambient particulate matter and health effects: 

Publication bias in studies of short-term associations. Epidemiology, 16: 155-163. 087916

ATS (1985). American Thoracic Society: Guidelines as to what constitutes an adverse respiratory health effect, with special 

reference to epidemiologic studies of air pollution. Am Rev Respir Dis, 131: 666-668. 006522

ATS (2000). What constitutes an adverse health effect of air pollution? Official statement of the American Thoracic 

Society. Am J Respir Crit Care Med, 161: 665-673. 011738

CDC (2004). The health consequences of smoking: A report of the Surgeon General. Centers for Disease Control and 

Prevention, U.S. Department of Health and Human Services. Washington, DC. 056384

Clewell HJ; Crump KS (2005). Quantitative estimates of risk for noncancer endpoints. Risk Anal, 25: 285-289. 156359

Collier TK (2003). Forensic ecotoxicology: Establishing causality between contaminants and biological effects in field 

studies. Hum Ecol Risk Assess, 9: 259 - 266. 155736

Crump KS; Hoel DG; Langley CH; Peto R (1976). Fundamental carcinogenic processes and their implications for low dose 

risk assessment. Cancer Res, 36: 2973-2979. 003192

Fox GA (1991). Practical causal inference for ecoepidemiologists. J Toxicol Environ Health, 33: 359-373. 156444

Gee GC; Payne-Sturges DC (2004). Environmental health disparities: A framework integrating psychosocial and 

environmental concepts. Environ Health Perspect, 112: 1645-1653. 093070

Gerritsen J; Carlson RE; Dycus DL; Faulkner C; Gibson GR (1998). Lake and reservoir bioassessment and biocriteria: 

Technical guidance document. US Environmental Protection Agency, Office of Water. Washington, DC. EPA 841-

B-98-007. http://www.epa.gov/owow/monitoring/tech/lakes.html. 156465

Gordon T; Gerber H; Fang CP; Chen LC (1999). A centrifugal particle concentrator for use in inhalation toxicology. Inhal 

Toxicol, 11: 71-87. 001176

Henderson R (2005). Clean Air Scientific Advisory Committee (CASAC) review of the EPA staff recommendations 

concerning a Potential Thoracic Coarse PM standard in the Review of the National Ambient Air Quality Standards 

for Particulate Matter: Policy Assessment of Scientific and Technical Information. U.S. Environmental Protection 

Agency. Washington, DC. 156537

Henderson R (2005). EPA's Review of the National Ambient Air Quality Standards for Particulate Matter (Second Draft 

PM Staff Paper, January 2005): A review by the Particulate Matter Review Panel of the EPA Clean Air Scientific 

Advisory Committee. U.S. Environmental Protection Agency. Washington D.C.. 188316

Henderson R (2006). Clean Air Scientific Advisory Committee recommendations concerning the proposed National 

Ambient Air Quality Standards for particulate matter. U.S. Environmental Protection Agency. Washington, DC. 

156538

Hill AB (1965). The environment and disease: Association or causation. J R Soc Med, 58: 295-300. 071664

Hoel DG (1980). Incorporation of background in dose-response models. Fed Proc, 39: 73-75. 156555

IARC (2006). IARC monographs on the evaluation of carcinogenic risks to humans: Preamble. International Agency for 

Research on Cancer, World Health Organization. Lyon,France . 

http://monographs.iarc.fr/ENG/Preamble/CurrentPreamble.pdf . 093206

Ioannidis JPA (2008). Why most discovered true associations are inflated. Epidemiology, 19: 640-648. 188317

 

Note: Hyperlinks to the reference citations throughout this document will take you to the NCEA HERO database (Health and 

Environmental Research Online) at http://epa.gov/hero. HERO is a database of scientific literature used by U.S. EPA in the process of 

developing science assessments such as the Integrated Science Assessments (ISA) and the Integrated Risk Information System (IRIS). 

December 2009 1-25 
IOM (2008). Improving the Presumptive Disability Decision-Making Process for Veterans; Committee on Evaluation of the 

Presumptive Disability Decision-Making Process for Veterans, Board on Military and Veterans Health. Washington, 

DC: Institue of Medicine of the National Academies, National Academies Press. 156586

Maciejczyk P; Chen LC (2005). Effects of subchronic exposures to concentrated ambient particles (CAPs) in mice: VIII 

source-related daily variations in in vitro responses to CAPs. Inhal Toxicol, 17: 243-253. 087456

NAPAP (1991). The experience and legacy of NAPAP report of the Oversight Review Board. National Acid Precipitation 

Assessment Program. Washington, DC. 095894

NAPCA (1969). Air quality criteria for particulate matter. National Air Pollution Control Administration. Washington, DC. 

014684

NRC (2004). Research priorities for airborne particulate matter: IV Continuing research progress. National Academies 

Press. Washington, DC. 156814

Rothman KJ; Greenland S (1998). Modern epidemiology. Philadelphia, PA: Lippincott-Raven Publishers. 086599

Samet JM (2009). CASAC Review of integrated science assessment for particulate matter (second external review draft, 

July 2009). U.S. Environmental Protection Agency. Washington, D.C.. EPA-CASAC-10-001. 199522

Samet JM (2009). Review of EPA's Integrated Science Assessment for Particulate Matter (First External Review Draft, 

December 2008). Clean Air Scientific Advisory Committee (CASAC) and members of the CASAC Particulate 

Matter (PM) Review Panel, Science Advisory Board, U.S. Environmental Protection Agency. Washington, D.C.. 

EPA-CASAC-09-008. 190992

Sioutas C; Kim S; Chang M (1999). Development and evaluation of a prototype ultrafine particle concentrator. J Aerosol 

Sci, 30: 1001-1017. 001633

Sioutas D; Koutrakis P; Ferguson ST; Burton RM (1995). Development and evaluation of a prototype ambient particle 

concentrator for inhalation exposure studies. Inhal Toxicol, 7: 633-644. 001629

Su Y; Sipin MF; Spencer MT; Qin X; Moffet RC; Shields LG; Prather KA; Venkatachari P; Jeong C-H; Kim E; Hopke PK; 

Gelein RM; Utell MJ; Oberdörster G; Berntsen J; Devlin RB; Chen LC (2006). Real-time characterization of the 

composition of individual particles emitted from ultrafine particle concentrators. Aerosol Sci Technol, 40: 437-455. 

157021

U.S. EPA (2004). Air quality criteria for particulate matter. U.S. Environmental Protection Agency. Research Triangle Park, 

NC. EPA/600/P-99/002aF-bF. 056905

U.S. EPA (2005). Guidelines for carcinogen risk assessment, Final Report. Risk Assessment Forum, U.S. Environmental 

Protection Agency. Washington, DC. EPA/630/P-03/001F. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=116283. 086237

U.S. EPA (2005). Review of the national ambient air quality standards for particulate matter: Policy assessment of 

scientific and technical information OAQPS staff paper. U.S. Environmental Protection Agency. Washington, DC. 

EPA/452/R-05-005a. http://www.epa.gov/ttn/naaqs/standards/pm/data/pmstaffpaper_20051221.pdf . 090209

U.S. EPA (2008). Integrated review plan for the national ambient air quality standards for particulate matter. U.S. 

Environmental Protection Agency, Office of Research and Development, National Center for Environmental 

Assessment. Research Triangle Park, NC. 157072

U.S. EPA (2008). Integrated science assessment for oxides of nitrogen and sulfur: Ecological criteria. U.S. Environmental 

Protection Agency. Research Triangle Park, NC. EPA/600/R-08/082F. 157074

December 2009 1-26