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Chapter 1. Introduction
 

1 The Integrated Science Assessment (ISA) is a concise evaluation and synthesis of the most 

2 policy-relevant science for reviewing the national ambient air quality standards (NAAQS). Because 

3 the ISA communicates critical science judgments relevant to the NAAQS review, it forms the 

4 scientific foundation for the review of the NAAQS for ozone (O3). The existing primary O3 standard 

includes an 8-hour (h) average (avg) standard set at 75 parts per billion (ppb) and not to be exceeded 

6 more than once per year. The secondary standard for O3 is set equal to the primary standard. 

7 The ISA accurately reflects “the latest scientific knowledge useful in indicating the kind and 

8 extent of identifiable effects on public health which may be expected from the presence of [a] 

9 pollutant in ambient air” (1990, 080701). Key information and judgments formerly contained in the 

Air Quality Criteria Document (AQCD) for O3 are incorporated in this assessment. Additional 

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

12 studies of particular interest, are included. This ISA thus serves to update and revise the evaluation of 

13 the scientific evidence available at the time of the completion of the 2006 O3 AQCD (U.S. EPA, 

14 2006, 088089). 

The draft Integrated Review Plan for the Ozone National Ambient Air Quality Standards (IRP) 

16 (U.S. EPA, 2009, 684024) identified key policy-relevant questions that provided a framework for 

17 this assessment of the scientific evidence. These questions frame the entire review of the NAAQS for 

18 O3 and thus are informed by both science and policy considerations. The ISA organizes, presents, 

19 and integrates the scientific evidence which is considered along with findings from risk analyses and 

policy considerations to help the U.S. Environmental Protection Agency (EPA) address these 

21 questions during the NAAQS review. In evaluating the health evidence, the focus of this assessment 

22 is on scientific evidence that is most relevant to the following questions taken directly from the 

23 Integrated Review Plan: 

24  To what extent has new scientific information become available that alters or 

substantiates our understanding of the health effects associated with various time periods 

26 of exposure to ambient O3, including short-term (1-3 hours), prolonged (6-8 hours), and 

27 chronic (months to years) exposures? 

28  To what extent has new scientific information become available that alters or 

29 substantiates our understanding of the health effects of O3 on at-risk populations, 

including those with potentially increased susceptibility such as children and 

31 disadvantaged populations? 

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). 

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1  To what extent has new scientific information become available that alters or
 

2 substantiates conclusions from previous reviews regarding the plausibility of adverse
 

3 health effects caused by O3 exposure?
 

4  At what levels of O3 exposure are health effects observed? Is there evidence of effects at 

exposure levels lower than those previously observed, and what are the important 

6 uncertainties associated with that evidence? What is the nature of the exposure-response 

7 relationships of O3 for the various health effects evaluated? 

8  To what extent has new scientific information become available that alters or 

9 substantiates our understanding of non-O3-exposure factors that might influence the 

associations between O3 levels and health effects being considered (e.g., weather-related 

11 factors; behavioral factors such as heating/air conditioning use; driving patterns; and 

12 time-activity patterns)? 

13  To what extent do risk and/or exposure analyses suggest that exposures of concern for 

14 O3-related health effects are likely to occur with current ambient levels of O3 or with 

levels that just meet the O3 standard? Are these risks/exposures of sufficient magnitude 

16 such that the health effects might reasonably be judged to be important from a public 

17 health perspective? What are the important uncertainties associated with these 

18 risk/exposure estimates? 

19  To what extent have important uncertainties identified in the last rulemaking been 

addressed and/or have new uncertainties emerged? 

1.1. Legis lative Requirements 

21 Two sections of the Clean Air Act (CAA) (2011, 013410) govern the establishment and 

22 revision of the NAAQS. Section 108 (42 USC §7408) directs the Administrator to identify and list 

23 certain air pollutants and then to issue air quality criteria for those pollutants. The Administrator is to 

24 list those air pollutants that in her “judgement; cause or contribute to air pollution which may 

reasonably be anticipated to endanger public health or welfare” and whose “presence...in the 

26 ambient air results from numerous or diverse moble or stationary sources.”(1990, 080701). Air 

27 quality criteria are intended to “accurately reflect the latest scientific knowledge useful in indicating 

28 the kind and extent of identifiable effects on public health or welfare which may be expected from 

29 the presence of [a] pollutant in ambient air . . . (42 USC §7408(b)). 

Section 109 (1990, 037658) directs the Administrator to propose and promulgate “primary” 

31 and “secondary” NAAQS for pollutants for which air quality criteria have been issued. Section 

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

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

3 requisite to protect the public health.”.1 A secondary standard, as defined in section 109(b)(2), must 

4 “specify a level of air quality the attainment and maintenance of which, in the judgment of the 

5 Administrator, based on such criteria, is required to protect the public welfare from any known or 

6 anticipated adverse effects associated with the presence of [the] pollutant in the ambient air.”.2 

7 The requirement that primary standards include an adequate margin of safety was intended to 

8 address uncertainties associated with inconclusive scientific and technical information available at 

9 the time of standard setting. It was also intended to provide a reasonable degree of protection against 

10 hazards that research has not yet identified. See Lead Industries Association v. EPA, 647 F.2d 1130, 

11 1154 (D.C. Cir 1980) (1980, 090977), cert. denied, 449 U.S. 1042 (1980); American Petroleum 

12 Institute v. Costle, 665 F.2d 1176, 1186 (D.C. Cir. 1981) (1981, 090978), cert. denied, 455 U.S. 1034 

13 (1982). Both kinds of uncertainties are components of the risk associated with pollution at levels 

14 below those at which human health effects can be said to occur with reasonable scientific certainty. 

15 Thus, in selecting primary standards that include an adequate margin of safety, the Administrator is 

16 seeking not only to prevent pollution levels that have been demonstrated to be harmful but also to 

17 prevent lower pollutant levels that may pose an unacceptable risk of harm, even if the risk is not 

18 precisely identified as to nature or degree. 

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

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

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

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

23 Lead Industries Association v. EPA, supra, 647 F.2d at 1161-1162 (1980, 090977). 

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

25 Section 109(b), EPA’s task is to establish standards that are neither more nor less stringent than 

26 necessary. In so doing, EPA may not consider the costs of implementing the standards. See generally 

27 Whitman v. American Trucking Associations, 531 U.S. 457, 465-472, 475-76 (2001, 043004). 

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

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

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

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

32 appropriate...”. Section 109(d)(2) requires that an independent scientific review committee “shall 

33 complete a review of the criteria ... and the national primary and secondary ambient air quality 

34 standards ... and shall recommend to the Administrator any new . . . standards and revisions of 

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) 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.” (2005, 090976). 

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1 existing criteria and standards as may be appropriate ...”. Since the early 1980's, this independent 

2 review function has been performed by CASAC. 

1.2. His tory of the NAAQS for Ozone 

3 Tropospheric (ground-level) O3 is the indicator for the mix of photochemical oxidants (e.g., 

4 peroxyacetyl nitrate, hydrogen peroxide) formed from biogenic and anthropogenic precursor 

5 emissions. Naturally occurring O3 in the troposphere can result from biogenic organic precursors 

6 reacting with naturally occurring nitrogen oxides (NOX) and by stratospheric O3 intrusion into the 

7 troposphere. Anthropogenic precursors of O3, especially NOX, and volatile organic compounds 

8 (VOCs), originate from a wide variety of stationary and mobile sources. Ambient O3 concentrations 

9 produced by these emissions are directly affected by temperature, solar radiation, wind speed, and 

10 other meteorological factors. 

11 NAAQS are comprised of four basic elements: indicator, averaging time, level, and form. The 

12 indicator defines the pollutant to be measured in the ambient air for the purpose of determining 

13 compliance with the standard. The averaging time defines the time period over which air quality 

14 measurements are to be obtained and averaged or cumulated, considering evidence of effects 

15 associated with various time periods of exposure. The level of a standard defines the air quality 

16 concentration used (i.e., an ambient concentration of the indicator pollutant) in determining whether 

17 the standard is achieved. The form of the standard specifies the air quality measurements that are to 

18 be used for compliance purposes (e.g., the annual fourth-highest daily maximum 8-hour 

19 concentration, averaged over 3 years), and whether the statistic is to be averaged across multiple 

20 years. These four elements taken together determine the degree of public health and welfare 

21 protection afforded by the NAAQS. 

Table 1-1. Summary of primary and secondary NAAQS promulgated for ozone during the period 

1971-2008 

Final Rule Indicator Avg Time Level (ppm) Form 

Total 1971 (36 FR 8186) photochemical 1-h 0.08 Not to be exceeded more than 1 hour per year (1971, 039176) oxidants 

Attainment is defined when the expected number of 1979 (44 FR 8202) O3 1-h 0.12 days per calendar year, with maximum hourly average (1979, 039177) concentration greater than 0.12 ppm, is ≤ 1 

1993 (58 FR 13008) EPA decided that revisions to the standards were not warranted at the time. (1993, 043977) 

1997 (62 FR 38856) Annual fourth-highest daily maximum 8-h concentration O3 8-h 0.08 (1997, 083356) averaged over 3 years 

2008 (73 FR 16483) Form of the standards remained unchanged relative to O3 8-h 0.075 (2008, 684051) the 1997 standard 

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Table 1-1 summarizes the O3 NAAQS that have been promulgated to date. In each review, the 

secondary standard has been set to be identical to the primary standard. These reviews are briefly 

described below. 

EPA first established primary and secondary NAAQS for photochemical oxidants in 1971 

(U.S. EPA, 1971, 039176). Both primary and secondary standards were set at a level of 0.08 parts 

per million (ppm), 1-h avg, total photochemical oxidants, not to be exceeded more than 1 hour per 

year. The standards were based on scientific information contained in the 1970 AQCD (U.S. EPA, 

1970, 014681). 

In 1977, EPA announced the first periodic review of the 1970 AQCD (U.S. EPA, 1970, 

014681) in accordance with Section 109(d)(1) of the Clean Air Act. In 1978, EPA published an 

AQCD (U.S. EPA, 1978, 040586). Based on the 1978 AQCD, EPA published proposed revisions to 

the original NAAQS in (1978, 684050) and final revisions in 1979 (1979, 039177). The level of the 

primary and secondary standards was revised from 0.08 to 0.12 ppm; the indicator was revised from 

photochemical oxidants to O3; and the form of the standards was revised from a deterministic to a 

statistical form, which defined attainment of the standards as occurring when the expected number of 

days per calendar year with maximum hourly average concentration greater than 0.12 ppm is equal 

to or less than one. 

In 1982 (Air quality criteria document for ozone and other photochemical oxidants, 1982, 

043971), EPA announced plans to revise the 1978 AQCD (U.S. EPA, 1978, 040586). In 1983, EPA 

announced that the second periodic review of the primary and secondary standards for O3 had been 

initiated (Review of the national ambient air quality standards for ozone, 1983, 043972). EPA 

subsequently published the 1986 O3 AQCD (U.S. EPA, 1986, 017607) and 1989 Staff Paper 

(U.S. EPA, 1989, 041919). Following publication of the 1986 O3 AQCD, a number of scientific 

abstracts and articles were published that appeared to be of sufficient importance concerning 

potential health and welfare effects of O3 to warrant preparation of a Supplement to the 1986 O3 

AQCD (U.S. EPA, 1992, 042599). Under the terms of a court order, on August 10, 1992, EPA 

published a proposed decision (1992, 043976) stating that revisions to the existing primary and 

secondary standards were not appropriate at the time (1992, 043976). This notice explained that the 

proposed decision would complete EPA’s review of information on health and welfare effects of O3 

assembled over a 7-year period and contained in the 1986 O3 AQCD (U.S. EPA, 1986, 017607) and 

its Supplement to the 1986 O3 AQCD (U.S. EPA, 1992, 042599). The proposal also announced 

EPA’s intention to proceed as rapidly as possible with the next review of the air quality criteria and 

standards for O3 in light of emerging evidence of health effects related to 6- to 8-hour O3 exposures. 

On March 9, 1993, EPA concluded the review by deciding that revisions to the standards were not 

warranted at that time (1993, 043977). 

In August 1992, EPA announced plans to initiate the third periodic review of the air quality 

criteria and O3 NAAQS (1992, 043976). On the basis of the scientific evidence contained in the 

1996 O3 AQCD (U.S. EPA, 1996, 017831) and the 1996 Staff Paper (U.S. EPA, 1996, 039046), and 

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effects at levels allowed by the then existing standards, EPA proposed to revise the primary and 

secondary O3 standards on December 13, 1996 (U.S. EPA, 1996, 031951). The EPA proposed to 

replace the then existing 1-hour primary and secondary standards with 8-h avg O3 standards set at a 

level of 0.08 ppm (equivalent to 0.084 ppm using standard rounding conventions). The EPA also 

proposed, in the alternative, to establish a new distinct secondary standard using a biologically based 

cumulative seasonal form. The EPA completed the review on July 18, 1997 by setting the primary 

standard at a level of 0.08 ppm, based on the annual fourth-highest daily maximum 8-h avg 

concentration, averaged over 3 years, and setting the secondary standard identical to the revised 

primary standard (U.S. EPA, 1997, 083356). 

On May 14, 1999, in response to challenges to EPA’s 1997 decision by industry and others, the 

U.S. Court of Appeals for the District of Columbia Circuit (D.C. Circuit Court) remanded the O3 

NAAQS to EPA, finding that Section 109 of the CAA, as interpreted by EPA, effected an 

unconstitutional delegation of legislative authority. In addition, the D.C. Circuit Court directed that, 

in responding to the remand, EPA should consider the potential beneficial health effects of O3 

pollution in shielding the public from the effects of solar ultraviolet (UV) radiation, as well as 

adverse health effects. On January 27, 2000, EPA petitioned the U.S. Supreme Court for certiorari on 

the constitutional issue (and two other issues) but did not request review of the D.C. Circuit Court 

ruling regarding the potential beneficial health effects of O3. On February 27, 2001, the U.S. 

Supreme Court unanimously reversed the judgment of the D.C. Circuit Court on the constitutional 

issue, holding that Section 109 of the CAA does not delegate legislative power to the EPA in 

contravention of the Constitution, and remanded the case to the D.C. Circuit Court to consider 

challenges to the O3 NAAQS that had not been addressed by that Court’s earlier decisions. On 

March 26, 2002, the D.C. Circuit Court issued its final decision, finding the 1997 O3 NAAQS to be 

“neither arbitrary nor capricious,” and denied the remaining petitions for review. In response to the 

D.C. Circuit Court remand to consider the potential beneficial health effects of O3 pollution in 

shielding the public from effects of solar (UV) radiation, on November 14, 2001, EPA proposed to 

leave the 1997 8-h O3 NAAQS unchanged (2001, 684026). After considering public comment on the 

proposed decision, EPA published its final response to this remand on January 6, 2003, reaffirming 

the 8-h O3 NAAQS set in 1997 (National ambient air quality standards for ozone: Final response to 

remand; final rule, 2003, 015702). Finally, on April 30, 2004, EPA announced the decision to make 

the 1-h O3 NAAQS no longer applicable to areas 1 year after the effective date of the designation of 

those areas for the 8-h NAAQS (2004, 684054). For most areas, the date that the 1-h NAAQS no 

longer applied was June 15, 2005. 

EPA initiated the next periodic review if the air quality criteria and O3 standards in September 

2000 with a call for information (2000, 080678). The schedule for completion of that rulemaking 

later became governed by a consent decree resolving a lawsuit filed in March 2003 by a group of 

plaintiffs representing national environmental and public health organizations. Based on the 2006 O3 

AQCD (U.S. EPA, 2006, 088089) published in March 2006, and the Staff Paper (U.S. EPA, 2007, 

090207) and related technical support documents, the proposed decision was published in the 

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1 Federal Register on July 11, 2007 (2007, 684055). The EPA proposed to revise the level of the 

2 primary standard to a level within the range of 0.075 to 0.070 ppm. Two options were proposed for 

3 the secondary standard: (1) replacing the current standard with a cumulative, seasonal standard, 

4 expressed as an index of the annual sum of weighted hourly concentrations cumulated over 

12 daylight hours during the consecutive 3-month period within the O3 season with the maximum 

6 index value, set at a level within the range of 7 to 21 ppm-h; and (2) setting the secondary standard 

7 identical to the revised primary standard. The EPA completed the rulemaking with publication of a 

8 final decision on March 27, 2008 (2008, 684051), revising the level of the 8-hour primary O3 

9 standard from 0.08 ppm to 0.075 ppm and revising the secondary standard to be identical to the 

primary standard. 

11 On September 16, 2009, the EPA Administrator announced her decision to reconsider the 

12 March 2008 decisions on revisions to the primary and secondary O3 NAAQS. 

1.3. ISA Development 

13 EPA initiated the current review of the NAAQS for O3 on September 29, 2008, with a call for 

14 information from the public (2008, 684057). In addition to the call for information, publications 

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

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

17 published since the last review, focusing on publications since 2005. Search strategies were 

18 iteratively modified to optimize identification of pertinent publications. Additional papers are 

19 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 

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

22 Publications considered for inclusion in the ISA were added to the Health and Environmental 

23 Research Online (HERO) database recently developed by EPA (http://hero.epa.gov/); note that the 

24 references in the ISA include a HERO ID that provides a link to the database. All references that are 

considered for inclusion in each chapter, organized by discipline, will be found through the HERO 

26 links provided at the beginning of the individual chapter reference sections. The HERO link provides 

27 the list of references that are included, as well as those that are considered and not included in the 

28 ISA, with bibliographic information and abstracts. 

29 Typically, only information that had undergone scientific peer review and had been published 

or accepted for publication was considered for inclusion, along with analyses conducted by EPA 

31 using publicly available data. This review has attempted to evaluate all relevant data published since 

32 the last review pertaining to the atmospheric science of O3, human exposure to ambient O3, and 

33 epidemiologic, controlled human exposure, and animal toxicological studies on O3, including those 

34 related to exposure-response relationships, mode(s) of action (MOA), or susceptible populations, and 

literature on the ecological or welfare effects of ambient O3. Added to the body of research on O3 

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1 effects were EPA’s analyses of air quality and emissions data, studies on atmospheric chemistry, 

2 transport, and fate of these emissions, as well as issues related to exposure to O3. 

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

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

inclusion in the ISA. The selection process for studies included in this ISA is shown in Figure 1-1. 

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

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

8 groups? 

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

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

11 statistical analysis? 

12  Are the air quality data, exposure, or dose metrics of adequate quality and sufficiently 

13 representative of information regarding ambient O3? 

14  Are the health, ecological or welfare effect measurements meaningful and reliable? 

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

16 information on associations with short- or long-term O3 exposures at or near ambient levels of O3; 

17 considered approaches to evaluate issues related to potential confounding by other pollutants; 

18 assessed potential effect modifiers; addressed health endpoints and populations not previously 

19 extensively researched; and evaluated important methodological issues (e.g., lag or time period 

between exposure and effects, model specifications, thresholds, mortality displacement) related to 

21 interpretation of the health evidence. Among the epidemiologic studies selected, particular emphasis 

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

23 conducted in the United States (U.S.) or Canada were discussed in more detail than those from other 

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

standardized analysis methods for evaluating effects of O3 and that provide overall estimates for 

26 effects, based on combined analyses of information pooled across multiple cities; (2) studies that 

27 help understand quantitative relationships between exposure concentrations and effects; (3) new 

28 studies that provide evidence on effects in susceptible populations; and (4) studies that consider and 

29 report O3 as a component of a complex mixture of air pollutants. 

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

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 O3 concentrations. Studies in which higher doses were used may 

also be considered if they provide information relevant to understanding modes of action 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 

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populations such as people with cardiovascular diseases; (2) address issues such as concentrationresponse or time-course of responses; (3) include control exposures to filtered air; and (4) have 

sufficient statistical power to assess findings. 

Review of the animal toxicological evidence focused on studies that approximate expected 

human dose conditions, which will vary depending on the toxicokinetics and biological sensitivity of 

the particular laboratory animal species or strains studied. Due to resource constraints on exposure 

duration and numbers of animals tested, animal studies typically utilize high-concentration 

exposures to acquire data relating to mechanisms and assure a measurable response. Such studies 

were considered to the extent that they provided useful information to inform our understanding of 

interspecies differences and potential sensitivity differences between healthy and susceptible human 

populations. 

Evaluation of the ecological impact of O3 focused on studies of vegetation and effects on 

ecosystems that occur in the U.S. and report endpoints or processes most relevant to the review of 

the secondary standard. Many studies have been published about vegetation and ecosystems outside 

of U.S. and North America, largely in Europe and Asia. This document includes discussion of studies 

of vegetation and ecosystems outside of North America if those studies contribute to the 

understanding of O3 effects across species and ecosystems. For example, studies outside North 

America that deal with physiological and biochemical processes that contribute to the effects of O3 

across species are discussed. Also, ecosystem studies outside of North America that contribute to the 

understanding of O3 effects on ecosystem processes are discussed. In addition, the specific role that 

tropospheric O3 plays in the earth's radiation budget and how perturbations in tropospheric O3 might 

affect (1) climate through its role as a greenhouse gas and (2) health, ecology and welfare through its 

role in shielding ultraviolet radiation are assessed. 

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 O3 health, ecological 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 O3 

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

In developing the O3 ISA, EPA began by reviewing and summarizing the evidence on 

atmospheric sciences and exposure and the health effects evidence from in vivo and in vitro 

toxicological studies, controlled human exposure studies, and epidemiologic studies. In August 2010, 

EPA held a public workshop, in which EPA experts and several non-EPA experts were asked to 

review the scientific content of preliminary draft materials for the draft ISA. The purpose of the 

initial review workshop was to ensure that the ISA is up to date and focused on the most policyrelevant findings, and to assist EPA with integration of evidence within and across disciplines. 

Subsequently, EPA addressed comments and completed the initial integration and synthesis of the 

evidence. 

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1 The integration of evidence on health, and ecological or welfare effects, involves collaboration 

2 between scientists from various disciplines. As described in the section below, the ISA organization 

3 is based on health and ecological effect categories. As an example, an evaluation of health effects 

4 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 

6 framework described below. Using the causal framework described in Section 1.6, EPA scientists 

7 consider aspects such as strength, consistency, coherence, and biological plausibility of the evidence, 

8 and develop draft causality judgments on the nature of the relationships. The draft integrative 

9 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 

11 review and evaluation of the evidence. The draft ISA is released for review by the CASAC and the 

12 public, and comments received on the characterization of the science as well as the implementation 

13 of the causal framework are carefully considered in revising and completing the ISA. 

1.4. Document Organization 

14 The ISA is composed of 10 chapters. This introductory chapter presents background 

information and provides an overview of EPA’s framework for making causal judgments. Chapter 2 

16 is an integrated summary of key findings and conclusions regarding the source to dose paradigm, 

17 MOA, important health effects of O3, including respiratory, cardiovascular, nervous system, 

18 perinatal/developmental, and mortality outcomes, and ecological or welfare effects. Chapter 3 

19 highlights key concepts and evidence relevant to understanding the sources, ambient concentrations, 

and atmospheric behavior of ambient O3. Chapter 4 evaluates the evidence on human exposure to 

21 ambient O3. Chapter 5 describes the dosimetry of O3 as well as a discussion of the MOA of O3. 

22 Chapter 6 reviews, evaluates and integrates epidemiologic, human clinical, and animal toxicological 

23 information on health effects related to short-term exposures (i.e., hours, days, or weeks) to O3, 

24 including respiratory effects, cardiovascular and systemic effects, central nervous system (CNS) 

effects, effects on the liver and cutaneous/ocular tissues, and mortality. Chapter 7 is similar to 

26 Chapter 6, but focuses on health effects related to long-term exposures (i.e., months or years) to O3. 

27 Chapter 8 summarizes the evidence on potentially susceptible populations for health effects of O3 

28 exposure. Chapter 9 reviews, evaluates and integrates evidence on the ecological effects of ambient 

29 O3, including crop and forest productivity, visible foliar injury, and ecosystem processes. Chapter 10 

presents relevant evidence on the welfare effects of O3, focusing primarily on the effects on climate 

31 and UV exposure. As noted above, these discussions focus on the most policy-relevant studies, and 

32 the broader body of literature considered is included in HERO; and additional HERO links are 

33 provided at the beginning of the individual chapter reference sections. 

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1.5. Document Scope 

1 For the current review of the primary O3 standard, relevant scientific information on human 

2 exposures and health effects associated with exposure to ambient O3 has been assessed. Previous 

3 reviews have included an extensive body of evidence from all three major health disciplines – 

4 toxicology, controlled human exposure studies and epidemiology – on the health effects of O3 

exposure (U.S. EPA, 2006, 088089). In this ISA, the conclusions from previous reviews are 

6 summarized at the beginning of each health outcome discussion to provide the foundation for 

7 consideration of evidence from recent studies. Results of key studies from previous reviews are 

8 included in discussions or tables and figures, as appropriate, and conclusions are drawn based on the 

9 synthesis of evidence from recent studies with the extensive literature summarized in previous 

reviews. 

11 The ISA also includes the assessment of scientific information associated with known or 

12 anticipated ecological and public welfare effects that is relevant to the review of the secondary O3 

13 standard. Research on the ecological effects of O3, including impacts on vegetation, have been 

14 discussed extensively in previous AQCDs (U.S. EPA, 2006, 088089). The welfare effects of O3, 

particularly focusing on climate forcing effects and shielding of UV light, are discussed. The current 

16 document incorporates findings of recent studies, building upon previous evaluations and 

17 conclusions. 

1.6. EPA Framework for Caus al Determination 

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

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

uniform language concerning causality and brings more specificity to the findings. This standardized 

21 language was drawn from across the federal government and wider scientific community, especially 

22 from the recent National Academy of Sciences (NAS) Institute of Medicine (IOM) document, 

23 Improving the Presumptive Disability Decision-Making Process for Veterans, (2008, 156586) the 

24 most recent comprehensive work on evaluating causality. 

The introductory portion of this section focuses on the evaluation of health effects evidence. 

26 While focusing on human health outcomes, the concepts are also generally relevant to causality 

27 determination for welfare effects. This section: 

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

29 relationship between exposure and health effects; 

 defines cause, in contrast to statistical association; 

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

32 a causal relationship; 

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1  highlights the issue of multifactorial causation; 

2  identifies issues and approaches related to uncertainty; and 

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

4 support of a general causal relationship.
 

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

6 human clinical, and animal toxicological studies) have been formulated by a number of regulatory 

7 and science agencies, including the IOM of the NAS (2008, 156586), International Agency for 

8 Research on Cancer (2006, 093206), EPA Guidelines for Carcinogen Risk Assessment (2005, 

9 086237), and Centers for Disease Control and Prevention (2004, 056384). These formalized 

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

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

12 language for causal determinations. Moreover, these frameworks have supported decision-making 

13 under conditions of uncertainty. 

1.6.1. Scien tific Evide n ce Us ed in Es tablis hin g Cau s ality 

14 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 

16 by pollutant or assessment. The most compelling evidence of a causal relationship between pollutant 

17 exposures and human health effects comes from human clinical studies. This type of study 

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

19 highly controlled laboratory conditions. 

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

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

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

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

24 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 closure of a pollution 

26 source. 

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

28 relationships, susceptible populations and MOAs. In the absence of controlled human exposure or 

29 epidemiologic data, animal data alone may be sufficient to support a likely causal determination, 

assuming that humans respond similarly to the experimental species. 

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1.6.2. As s o ciation an d Ca us a tio n 

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

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

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

4 proof of a causal relationship between exposure and disease. Unlike an association, a causal claim 

supports the creation of counterfactual claims; that is, a claim about what the world would have been 

6 like under different or changed circumstances (IOM, 2008, 156586). Much of the newly available 

7 health information evaluated in this ISA comes from epidemiologic studies that report a statistical 

8 association between ambient exposure and health outcome. 

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

etiologies. Diseases such as asthma, coronary heart disease (CHD) or cancer are typically initiated 

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

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

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

14 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. 

1.6.3. Evalu a tin g Evid en c e fo r In fe rrin g Cau s a tio n 

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

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

18 it is recognized that scientific findings incorporate uncertainty. “Uncertainty” can be defined as a 

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

future outcome, e.g., the lack of knowledge about the correct value for a specific measure or 

21 estimate. Uncertainty characterization and uncertainty assessment are two activities that lead to 

22 different degrees of sophistication in describing uncertainty. Uncertainty characterization generally 

23 involves a qualitative discussion of the thought processes that lead to the selection and rejection of 

24 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 

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

27 measures and techniques. Data may not be available for all aspects of an assessment and those data 

28 that are available may be of questionable or unknown quality. In these situations, evaluation of 

29 uncertainty can include professional judgment or inferences based on analogy with similar situations. 

The net result is that the assessment will be based on a number of assumptions with varying degrees 

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

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

33 evaluating uncertainty include classical statistical methods, sensitivity analysis, or probabilistic 

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

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

quantitative analysis approaches, such as metaregression, may be used. 

Meta-analysis may be a valuable tool for evaluating evidence by combining results from a 

body of studies. Blair et al. (1995, 079190) observed that meta-analysis can enhance understanding 

of associations between exposures and effects that are not readily apparent in examination of 

individual study results and can be particularly useful for formally examining sources of 

heterogeneity. However, these authors noted that meta-analysis may not be useful when the 

relationship between the exposure and outcome is obvious, when only a few studies are available for 

a particular exposure-outcome relationship, where there is limited access to data of sufficient quality, 

or where there is substantial variation in study design or population. In addition, important 

differences in effect estimates, exposure metrics, or other factors may limit or even preclude 

quantitative statistical combination of multiple studies. 

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 known concentrations of air pollutants under 

carefully regulated environmental conditions and activity levels. 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 O3 and a clean air 

control. In this way, subjects serve as their own controls, effectively controlling for many potential 

confounders. However, human clinical studies are limited by a number of factors, including a small 

sample size and short exposure times. The repetitive nature of ambient O3 exposures at levels that 

can vary widely may lead to cumulative health effects, but this type of exposure is not practical to 

replicate in a laboratory setting. In addition, although 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, human clinical 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 human clinical studies 

have included health-compromised individuals such as those with respiratory or cardiovascular 

disease, these individuals must also be relatively healthy and do not represent the most sensitive 

individuals in the population. Thus, a lack of observation of effects from human clinical studies does 

not necessarily mean that a causal relationship does not exist. While human clinical 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 populations. 

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 

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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 due to possible confounders is to control for characteristics that may differ between 

exposed and unexposed persons; this is frequently termed “adjustment.” 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 O3 to health 

effects when it is a component of a complex air pollutant mixture. Reported O3 effect estimates in 

epidemiologic studies may reflect independent O3 effects on health outcomes. Ambient O3 may also 

be serving as an indicator of complex ambient air pollution mixtures, particularly the photochemical 

oxidant mixture. Alternatively, co-pollutants may mediate the effects of O3, or O3 may influence the 

toxicity of co-pollutants. 

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). When a risk factor is a confounder, 

it is the true cause of the association observed between the exposure and the outcome; when a risk 

factor is an effect modifier, it changes the magnitude of the association between the exposure and the 

outcome in stratified analyses. Examples of potential effect modifiers in some of the studies 

evaluated in this ISA may include environmental variables, such as temperature or humidity, 

individual risk factors, such as education, cigarette smoking status, age in a prospective cohort study, 

and community factors, such as 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 potential effect 

modifiers. For variables that modify the association, effect estimates in each stratum will be different 

from one another and different from the overall estimate, indicating a different exposure-response 

relationship may exist in populations represented by these variables. Effect modifiers may be 

encountered (1) within single-city time-series studies; or (2) 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 multi-pollutant regression models has been 

the prevailing approach for controlling potential confounding by co-pollutants in air pollution health 

effects studies. Finding the likely causal pollutant from multi-pollutant 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 

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than one pollutant may exert similar health effects, resulting in independently observed associations 

for multiple pollutants. For example, O3, NO2 and SO2 have each been linked to respiratory effects in 

epidemiologic studies. Correlation between O3 concentrations and various co-pollutants makes it 

difficult to quantitatively interpret associations between different pollutant exposures and health 

effects. Thus, results of models that attempt to distinguish O3 effects from those of co-pollutants 

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 multi-pollutant 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. 

Another way to adjust for potential confounding is through stratified analysis, i.e., examining 

the association within homogeneous groups with respect to the confounding variable. The use of 

stratified analyses has an additional benefit: it allows examination of effect modification through 

comparison of the effect estimates across different groups. If investigators successfully measured 

characteristics that distort the results, adjustment of these factors help separate a spurious from a true 

causal association. 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. Identifying these mechanisms makes it possible to control for potential sources that may result 

in a spurious association. 

Adjustment for potential confounders can be influenced by differential exposure measurement 

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

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. Consideration of issues important for evaluation of exposure to ambient O3 include the 

relationship between O3 measured at central site monitors with exposure to ambient O3 in indoor 

environments, since penetration of O3 into buildings may be limited. Previous AQCDs have 

examined the role of measurement error for non-reactive pollutants in time-series epidemiologic 

studies using simulated data and mathematical analyses and suggested that transfer of effects from 

the “causal” variable to the confounder 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 

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

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

3 In addition to clinical and epidemiologic studies, the tools of experimental biology have been 

4 valuable for developing insights into human physiology and pathology. Laboratory tools have been 

extended to explore the effects of putative toxicants on human health, especially through the study of 

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

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

8 by which a pollutant may cause effects. Understanding the biological mechanisms underlying 

9 various health outcomes can prove crucial in establishing or negating causality. There are, however, 

uncertainties associated with quantitative extrapolations between laboratory animals and humans on 

11 the pathophysiological effects of any pollutant. Animal species can differ from each other in 

12 fundamental aspects of physiology and anatomy (e.g., metabolism, airway branching, hormonal 

13 regulation) that may limit extrapolation. 

14 Interpretations of experimental studies of air pollution effects in laboratory animals, as in the 

case of environmental comparative toxicology studies, are affected by limitations associated with 

16 extrapolation models. The differences between humans and other species with regard to pollutant 

17 absorption and distribution profiles based on metabolism, hormonal regulation, breathing pattern, 

18 exposure dose, and differences in lung structure and anatomy, all have to be taken into consideration. 

19 Also, in spite of a high degree of homology and the existence of a high percentage of orthologous 

genes across humans and rodents (particularly mice), extrapolation of molecular alterations at the 

21 gene level is complicated by species-specific differences in transcriptional regulation. Given these 

22 molecular differences, at this time there are uncertainties associated with quantitative extrapolations 

23 between laboratory animals and humans of observed pollutant-induced pathophysiological 

24 alterations under the control of widely varying biochemical, endocrine, and neuronal factors. 

1.6.4. Ap plic ation o f Fra me work fo r Ca us al De te rmin ation 

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

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

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

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

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

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Table 1-2. Aspects to aid in judging causality 

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

Consistency of the independent studies. The reproducibility of findings constitutes one of the strongest arguments for

observed association 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. 

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

evidence (e.g., clinical and animal studies) that support a cause-and-effect interpretation of the 

association. Evidence on ecological or welfare effects may be drawn from a variety of experimental

Coherence	 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. 

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 

Biological plausibility.	 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 biologic

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 biologic gradient may support causality, the absence of an 

exposure-response relationship does not exclude a causal relationship. 

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

Strength of the observed bias, or other factors. However, given a truly causal agent, a small magnitude in the effect could follow

association 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. 

The strongest evidence for causality can be provided when a change in exposure brings about a change Experimental evidence in occurrence or frequency of health or welfare effects. 

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

the observed association 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 our 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. 

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

Analogy 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 To aid judgment, various “aspects”1 of causality have been discussed by many philosophers 

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

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

4 (CDC, 2004, 056384; IARC, 2006, 093206; IOM, 2008, 156586; U.S. EPA, 2005, 086237).These 

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

6 specific to health and welfare effects or pollutant exposures (U.S. EPA, 2009, 179916).2 Some 

7 aspects are more likely than others to be relevant for evaluating evidence on the health or ecological 

8 effects of criteria air pollutants. For example, the "analogy" aspect does not always apply, especially 

9 for the gaseous criteria pollutants, and specificity would not be expected for multi-etiologic health 

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, ecological, and animal toxicological studies, as well as in vitro data, and to be more 

consistent with EPA’s Guidelines for Carcinogen Risk Assessment. 

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1 outcomes, such as asthma or cardiovascular disease, or ecological effects related to acidification. 

2 Aspects that usually play a larger role in determination of causality are consistency of results across 

3 studies, coherence of effects observed in different study types or disciplines, biological plausibility, 

4 exposure-response relationship, and evidence from “natural” experiments. 

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

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

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

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

9 credible conclusions about the relative weight of the evidence and the likelihood of causality. Rather, 

10 these important considerations are taken into account with the goal of producing an objective 

11 appraisal of the evidence, informed by peer and public comment and advice, which includes 

12 weighing alternative views on controversial issues. In addition, it is important to note that the aspects 

13 in Table 1-2 cannot be used as a strict checklist, but rather to determine the weight of the evidence 

14 for inferring causality. In particular, not meeting one or more of the principles does not automatically 

15 preclude a determination of causality (See discussion in CDC, 2004, 056384). 

1.6.5. De termin a tio n o f Cau s ality 

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

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

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

19 hierarchy that classifies the weight of evidence for causation, not just association1; that is, whether 

20 the weight of scientific evidence makes causation at least as likely as not, in the judgment of the 

21 reviewing group. In developing this hierarchy, EPA has drawn on the work of previous evaluations, 

22 most prominently the IOM’s Improving the Presumptive Disability Decision-Making Process for 

23 Veterans (2008, 156586), EPA’s Guidelines for Carcinogen Risk Assessment (2005, 086237), and the 

24 U.S. Surgeon General’s smoking report (CDC, 2004, 056384). In the ISA, EPA uses a series of five 

25 descriptors to characterize the weight of evidence for causality. This weight of evidence evaluation is 

26 based on various lines of evidence from across the health and environmental effects disciplines. 

27 These separate judgments are integrated into a qualitative statement about the overall weight of the 

28 evidence and causality. The five descriptors for causal determination are described in Table 1-3. 

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. 

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Table 1-3. Weight of evidence for causal determination 

Health Effects Ecological and Welfare Effects 

Evidence is sufficient to conclude that there is a causal 

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. 

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 co-pollutant 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. 

Evidence is inadequate to determine that a causal

Inadequate to relationship exists with relevant pollutant exposures. The The available studies are of insufficient quality,

infer a causal available studies are of insufficient quantity, quality, consistency or statistical power to permit a conclusion 

relationship consistency or statistical power to permit a conclusion regarding the presence or absence of an effect. 

regarding the presence or absence of an effect. 

Evidence is suggestive of no causal relationship with

relevant pollutant exposures. Several adequate studies, Not likely to Several adequate studies, examining relationships with covering the full range of levels of exposure that human be a causal relevant exposures, are consistent in failing to show an beings are known to encounter and considering relationship effect at any level of exposure. susceptible populations, are mutually consistent in not

showing an effect at any level of exposure.
 

1 For the O3 ISA, determination of causality involved the evaluation of evidence for different 

2 types of health effects associated with short- and long-term exposure periods. In making 

3 determinations of causality, evidence was evaluated for health outcome categories, such as 

4 respiratory effects, and then conclusions were drawn based upon the integration of evidence from 

5 across disciplines (e.g., epidemiology, clinical studies and toxicology) and also across the suite of 

6 related individual health outcomes. To accomplish this integration, evidence from multiple and 

7 various types of studies was considered. Response was evaluated over a range of observations which 

8 was determined by the type of study, methods of exposure or dose, and response measurements. 

9 Results from different protocols were compared and contrasted. EPA focuses on health outcome 

10 categories, rather than very specific endpoints, since the coherence of evidence across a spectrum of 

11 related endpoints (e.g., effects ranging from inflammatory effects to respiratory mortality) is an 

12 important aspect for drawing conclusions regarding causality. 

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1 In drawing judgments regarding causality for the criteria air pollutants, EPA focuses on 

2 evidence of effects at relevant pollutant exposures. To best inform reviews of the NAAQS, these 

3 evaluations go beyond a determination of causality at any dose or concentration to emphasize the 

4 relationship apparent at relevant pollutant exposures. Concentrations generally within an order of 

5 magnitude or two of ambient pollutant measurements are considered to be relevant for this 

6 determination. Building upon the determination of causality are questions relevant to quantifying 

7 health or environmental risks based on our understanding of the quantitative relationships between 

8 pollutant exposures and health or welfare effects. While the causality determination is based 

9 primarily on evaluation of health or environmental effects evidence, EPA also evaluates evidence 

10 related to the doses or levels at which effects are observed. Considerations relevant to evaluation of 

11 quantitative relationships for health and environmental effects are summarized below. 

1.6.5.1. Effe c ts o n Huma n P op ula tio ns 

12 Once a determination is made regarding the causal relationship between the pollutant and 

13 outcome category, important questions regarding quantitative relationships include: 

14  What is the concentration-response, exposure-response, or dose-response relationship in 

15 the human population? 

16  What is the interrelationship between incidence and severity of effect? 

17  What exposure conditions (dose or exposure, duration and pattern) are important? 

18  What populations appear to be differentially affected (i.e., more susceptible to effects)? 

19 To address these questions, the entirety of policy-relevant quantitative evidence is evaluated to 

20 best quantify those concentration-response relationships that exist. This requires evaluation of 

21 pollutant concentrations and exposure durations at which effects were observed for exposed 

22 populations, including potentially susceptible populations. This integration of evidence resulted in 

23 identification of a study or set of studies that best approximated the concentration-response 

24 relationships between health outcomes and O3, given the current state of knowledge and the 

25 uncertainties that surrounded these estimates. To accomplish this, evidence is considered from 

26 multiple and diverse types of studies. To the extent available, the ISA evaluates results from across 

27 epidemiologic studies that use various methods to evaluate the form of relationships between O3 and 

28 health outcomes and draws conclusions on the most well-supported shape of these relationships. 

29 Animal data may also inform evaluation of concentration-response relationships, particularly relative 

30 to MOAs and characteristics of susceptible populations. Controlled human exposure studies have 

31 provided the strongest and most quantifiable exposure-response data on the human health effects of 

32 O3. Chapter 2 presents the integrated findings informative for evaluation of population risks. 

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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, such as the low data density in the lower 

concentration range, possible influence of exposure measurement error, and individual differences in 

susceptibility to air pollution health effects, tend to smooth and “linearize” the concentrationresponse function. 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], environmental tobacco 

smoke [ETS], radiation) do not exhibit evident thresholds for cancer or noncancer 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) 

Although publication bias commonly exists for many research areas, it may be present to a lesser 

degree for epidemiologic studies on O3. Many epidemiologic studies have focused on the effects of 

PM, and O3 was largely considered as a potentially confounding co-pollutant of PM. Thus, O3-effect 

estimates may have been presented in these studies regardless of the statistical significance of the 

results. 

Finally, identification of the susceptible population groups contributes to an understanding of 

the public health impact of pollutant exposures. In this ISA, the term “susceptible population” will 

be used as an overarching concept to encompass populations variously described as susceptible, 

vulnerable, or sensitive. “Susceptible populations” is defined here as those populations that have a 

greater likelihood of experiencing health effects related to exposure to an air pollutant (e.g., O3) due 

to a variety of factors including but not limited to: genetic or developmental factors, race, gender, 

lifestage, lifestyle (e.g., smoking status and nutrition) or preexisting disease; as well as populationlevel factors that can increase an individual's exposure to an air pollutant (e.g., O3) such as 

socioeconomic status [SES], which encompasses reduced access to health care, low educational 

attainment, residential location, and other factors. Epidemiologic studies can help identify 

susceptible populations by evaluating health responses in the study population. Examples include 

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1 stratified analyses for subsets of the population under study or testing for interactions or effect 

2 modification by factors such as gender, age group, or health status. Experimental studies using 

3 animal models of susceptibility or disease can also inform the extent to which health risks are likely 

4 greater in specific population groups. Further discussion of these groups is presented in Section 5.7. 

1.6.5.2. Effe c ts o n Ec os ys te ms or Pu blic We lfa re 

Key questions for understanding the quantitative relationships between exposure (or
 

6 concentration or deposition) to a pollutant and risk to ecosystems or the public welfare include: 

7  What elements of the ecosystem (e.g., types, regions, taxonomic groups, populations,
 

8 functions, etc.) appear to be affected, or are more sensitive to effects?
 

9  Under what exposure conditions (amount deposited or concentration, duration and 

pattern) are effects seen?
 

11  What is the shape of the concentration-response or exposure-response relationship? 

12 Evaluations of causality generally consider the probability of quantitative changes in 

13 ecological and welfare effects in response to exposure. A challenge to the quantification of exposure14 response relationships for ecological effects is the great regional and local variability in ecosystems. 

Thus, exposure-response relationships are often determined for a specific ecological system and 

16 scale, rather than at the national or even regional scale. Quantitative relationships therefore are 

17 available site by site. For example, an ecological response to deposition of a given pollutant can 

18 differ greatly between ecosystems. Where results from greenhouse or animal ecotoxicological 

19 studies are available, they may be used to aid in characterizing exposure-response relations, 

particularly relative to mechanisms of action, and characteristics of sensitive biota. 

1.6.6. Concepts in Evaluating Ad vers ity of He a lth Effec ts 

21 In evaluating the health evidence, a number of factors can be considered in determining the 

22 extent to which health effects are “adverse” for health outcomes such as changes in lung function or 

23 in cardiovascular health measures. Some health outcome events, such as hospitalization for 

24 respiratory or cardiovascular diseases, are clearly considered adverse; what is more difficult is 

determining the extent of change in the more subtle health measures that is adverse. What constitutes 

26 an adverse health effect may vary between populations. Some changes in healthy individuals may 

27 not be considered adverse; while those of a similar type and magnitude are potentially adverse in 

28 more susceptible individuals. 

29 For example, the extent to which changes in lung function are adverse has been discussed by 

the American Thoracic Society (ATS) in an official statement titled What Constitutes an Adverse 

31 Health Effect of Air Pollution? (2000, 011738). This statement updated the guidance for defining 

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1 adverse respiratory health effects that had been published 15 years earlier (ATS, 1985, 006522), 

2 taking into account new investigative approaches used to identify the effects of air pollution and 

3 reflecting concern for impacts of air pollution on specific susceptible groups. In the 2000 update, 

4 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 

6 adverse effect to the entire population is viewed as adverse, even though it may not increase the risk 

7 of any identifiable individual to an unacceptable level. For example, a population of asthmatics 

8 could have a distribution of lung function such that no identifiable individual has a level associated 

9 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 

11 function, however, would be considered adverse because individuals within the population would 

12 have diminished reserve function and therefore would be at increased risk to further environmental 

13 insult. 

14 It is important to recognize that the more subtle health outcomes may be linked to health 

events that are clearly adverse. For example, air pollution has been shown to affect markers of 

16 transient myocardial ischemia such as ST-segment abnormalities and onset of exertional angina. In 

17 some cases, these effects are silent yet may still increase the risk of a number of cardiac events, 

18 including MI and sudden death. 

1.7. Summary 

19 This draft ISA is a concise evaluation and synthesis of the most policy-relevant science for 

reviewing the NAAQS for O3, and it is the chief means for communicating the critical science 

21 judgments relevant to that NAAQS review. It reviews the most policy-relevant evidence from 

22 atmospheric science, exposure, health, and ecological and welfare effects studies; and includes 

23 mechanistic evidence from basic biological science. A framework for making critical judgments 

24 concerning causality was presented 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 

26 clarity to current and future assessments. Once complete, the ISA should assist EPA and others, now 

27 and in the future, to accurately represent what is presently known and what remains unknown 

28 concerning the effects of O3 on human health and public welfare. 

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